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458 results on '"Johnson SC"'

1. Smart Scattering Scanning Near-Field Optical Microscopy

Author

Labouesse, S, Johnson, SC, Bechtel, HA, Raschke, MB, and Piestun, R

Subjects
Optical Physics, Quantum Physics, Electrical and Electronic Engineering
Abstract

Scattering scanning near-field optical microscopy (s-SNOM) provides spectroscopic imaging from molecular to quantum materials with few nanometer deep subdiffraction limited spatial resolution. However, in its conventional implementation s-SNOM is slow to effectively acquire a series of spatio-spectral images, especially with large fields of view. This problem is further exacerbated for weak resonance contrast or when using light sources with limited spectral irradiance. Indeed, the generally limited signal-to-noise ratio prevents sampling a weak signal at the Nyquist sampling rate. Here, we demonstrate how acquisition time and sampling rate can be significantly reduced by using compressed sampling, matrix completion, and adaptive random sampling, while maintaining or even enhancing the physical or chemical image content. We use fully sampled real data sets of molecular, biological, and quantum materials as ground-truth physical data and show how deep under-sampling with a corresponding reduction of acquisition time by 1 order of magnitude or more retains the core s-SNOM image information. We demonstrate that a sampling rate of up to 6× smaller than the Nyquist criterion can be applied, which would provide a 30-fold reduction in the data required under typical experimental conditions. Our smart s-SNOM approach is generally applicable and provides systematic full spatio-spectral s-SNOM imaging with a large field of view at high spectral resolution and reduced acquisition time.

Published
2020

2. Synchrotron infrared nano-spectroscopy and -imaging

Author

Bechtel, HA, Johnson, SC, Khatib, O, Muller, EA, and Raschke, MB

Subjects
Chemical Physics, Condensed Matter Physics, Physical Chemistry, Physical Chemistry (incl. Structural)
Abstract

Infrared (IR) spectroscopy has evolved into a powerful analytical technique to probe molecular and lattice vibrations, low-energy electronic excitations and correlations, and related collective surface plasmon, phonon, or other polaritonic resonances. In combination with scanning probe microscopy, near-field infrared nano-spectroscopy and -imaging techniques have recently emerged as a frontier in imaging science, enabling the study of complex heterogeneous materials with simultaneous nanoscale spatial resolution and chemical and quantum state spectroscopic specificity. Here, we describe synchrotron infrared nano-spectroscopy (SINS), which takes advantage of the low-noise, broadband, high spectral irradiance, and coherence of synchrotron infrared radiation for near-field infrared measurements across the mid- to far-infrared with nanometer spatial resolution. This powerful combination provides a qualitatively new form of broadband spatio-spectral analysis of nanoscale, mesoscale, and surface phenomena that were previously difficult to study with IR techniques, or even any form of micro-spectroscopy in general. We review the development of SINS, describe its technical implementations, and highlight selected examples representative of the rapidly growing range of applications in physics, chemistry, biology, materials science, geology, and atmospheric and space sciences.

Published
2020

4. The geochemistry of metalliferous black shales : understanding primary enrichments, metamorphic processes, and the role of metal-rich black shales in archiving earth evolution

Author

Johnson, SC

Abstract

Black shales offer an important context to study the evolution of the oceans and atmosphere. As an archive of past climatic, evolutionary and geodynamic events in Earth history they offer the opportunity to further understand the nature of such events. Various redox sensitive and bio-essential trace metals can become enriched in black shales as a function of the nature of the environment in which they were deposited. Of particular interest are shales with high metal enrichment, as they may represent an important geochemical flux. In addition to archiving paleo-ocean and climatic conditions, metal-rich black shales offer important economic targets for hydrocarbon and mineral exploration. Previous work has shown that many important trace metals in black shales are hosted by diagenetic pyrite. Furthermore, metal-rich pyrite has been argued as a potential source for orogenic gold deposits where the metamorphic breakdown of pyrite to pyrrhotite releases gold and other trace metals. This thesis presents a series of studies on aspects of black shale enrichment and mineralogy and offers greater insight as to the evolution of our oceans and atmosphere and how this may relate to secular metal enrichments. Each adopts a multi-proxy, geochemical approach, augmenting pyrite trace element chemistry with isotopic, and whole-rock geochemical or mineralogical data. In addition to addressing the nature of the depositional environment of black shales, mechanisms of ore genesis via the metamorphism of metal-rich shale sequences are also presented and evaluated. Four main aspects of the geochemistry of black shales are investigated in this thesis: 1) primary metal enrichment as a result of the changing nature of the water column during climatic perturbation, 2) the application of pyrite trace element chemistry along with other geochemical techniques to understand, and differentiate, primary metal enrichments and metamorphic overprint, 3) mechanisms by which pyrite may convert to pyrrhotite in black shale and what implications this may have for metal mobility, and 4) understanding of metal enrichments in black shale through geological time in the context of geodynamic and geochemical evolution. The understanding of primary metal enrichments in black shales is critical in order to interpret the nature of the depositional environment. Chapters 2, 3 and 4 offer reviews of metal enrichment in sediments through time, as well as whole rock and pyrite trace element chemistry, as a means to record the chemical nature of the water column at the time of deposition. This is then applied in Chapter 5 to a metalliferous black shale section in NW Estonia of Cambrian to Ordovician age. This work contains a new detailed sedimentological study of the section to establish a depositional context. This is augmented by a high-resolution multi-proxy data and isotope geochemistry suggests that the section archives a major carbon isotope excursion (the Steptoean Positive Isotope Excursion; SPICE), not previously reported in these rocks, and allows the section to be placed in a global context. The high phosphorous content of the biograinstones deposited prior to the carbon isotope excursion suggests that phosphogenesis may have led to increased bio-productivity, affecting the carbon cycle. The high pyrite content and the geochemistry of this mineral in the lower portion of the black shale, which sits above the isotope excursion, suggests that the SPICE event may have led to the onset of low-oxygen conditions across the Baltica shallow shelf, and the deposition of metal-rich black shales. In Chapter 6, the geodynamic and biochemical processes associated with metal enrichments in the formation metal-rich shales are reviewed and discussed together with a geochemical and mineralogical study of the Talvivaara deposit in Finland. As the world's largest black-shale poly-metallic deposit it offers a context to evaluate the economic aspects of black shale enrichment. The Paleoproterozoic age of this deposit and the fact that there are no known analogues that match its size, suggests that there may have been unique environmental factors that played a role in its metal enrichment. Much like the Estonian example, Talvivaara was deposited in the immediate wake of a large, global carbon isotope excursion. The excursion (the Lomagundi- Jatuli event, ~2.1 Ga) is the largest carbon isotope excursion preserved in the rock record and is followed by the first, and largest, mass burial of organic carbon in Earth history. This suggests that there may be analogous processes operating, but on different scales, in order to facilitate such enrichments. The deposit has been metamorphosed to amphibolite facies with only some primary pyrite, zircon and bituminous organic matter preserved. In-situ ˜í¬•\\(^{34}\\)S-isotopic values of the sulfide phases and LA-ICP-MS analyses of iron sulfide phases, shows that the earliest pyrite (interpreted to be of syn-sedimentary to early-diagenetic in origin) is trace metal rich. The ˜í¬•\\(^{34}\\)S values in these pyrites suggest bacterial sulfate reduction from an open sulfate reservoir. The earliest pyrite is the most metal-rich, suggesting that the original depositional environment facilitated high metal concentrations. The shale package was then metamorphosed releasing trace elements and sulfur that then went on to form their own phases. Chapter 7 presents new data and insights as to the nature of metamorphic reduction of pyrite to pyrrhotite in black shales. Often this transformation is only considered as proceeding at greenschist facies metamorphism (~300¬¨‚àûC, and above). An experimental study, focusing on the magnetic character of pyrite, suggests that the transformation begins at ~177¬¨‚àûC. The lower temperature proposed is supported by LA-ICP-MS studies of pyrite and pyrrhotite in Estonian oil shale and diagenetic to catagenetic sulfide concretions in sub-greenschist facies black shales from NW Russia. A model is presented suggesting that the degradation of organic matter during catagenesis is sufficient in producing enough reducing potential to facilitate the initial stages of the transformation to pyrrhotite. Chapter 8 presents a synthesis of the geochemistry of metal-rich black shales. Some of the most metal-rich black shales worldwide are classified and compared to 'normal' black shales from throughout Earth history. In doing so, a new model is presented which suggests that during the Phanerozoic, plate collisional events led to increased detrital material into basins, leading to increased bio-productivity and atmospheric O\\(_2\\). With increasing O\\(_2\\) in the atmosphere, the processes of weathering and erosion became more vigorous leading to further influx of detritus and blooms of bio-productivity promoting the development of water column anoxia. Eventually, the cycle breaks when uptake by organisms exceeds input from the continents, leading to the return of 'normal' black shales and increasing carbon release to the atmosphere. This process is likely to have been the dominant process during the Phanerozoic, where supercontinent cycles are more dynamic and cover greater surface area. However, the Proterozoic also has some of the largest metalliferous, and organic-rich, sediments in the rock record and do not directly correlate to periods of supercontinent amalgamation. Instead, a discussion is presented that addresses the influence of widespread glaciations as a process to effectively erode, whilst simultaneously release oxygen, leading to increased oxidative weather and bio-productivity in their aftermath.

Published
2023
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5. The Structured Distance to the Nearest System Without Property P

Author

Johnson, SC, Wicks, M, Žefran, M, and DeCarlo, RA

Subjects
Mechanical Engineering, FOS: Mechanical engineering
Abstract

For a system matrix M, this paper explores the smallest (Frobenius) norm additive structured perturbation δM for which a system property P (e.g., controllability, observability, stability, etc.) fails to hold, i.e., δM is the structured perturbation with smallest Frobenius norm such that there exists a property matrix R ∈ P for which M-δM-R drops rank. The Frobenius norm is used because of its direct dependence on the magnitude of each entry in the perturbation matrix. Necessary conditions on a locally minimum norm structured rank-reducing perturbation δM and associated property matrix R are set forth and proven. An iterative algorithm is also set forth that computes a locally minimum norm structured perturbation and associated property matrix satisfying the necessary conditions. Algorithm convergence is proven using a discrete Lyapunov function.

Published
2021
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7. Relationship of amyloid beta and neurofibrillary tau deposition in Neurodegeneration in Aging Down Syndrome (NiAD) study at baseline

Author

Tudorascu, DL, primary, Laymon, CM, additional, Zammit, M, additional, Minhas, DS, additional, Anderson, SJ, additional, Ellison, PA, additional, Zaman, S, additional, Ances, BM, additional, Sabbagh, M, additional, Johnson, SC, additional, Mathis, CA, additional, Klunk, WE, additional, Handen, BL, additional, Christian, BT, additional, and Cohen, AD, additional

Published
2020
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12. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Author

Lozano, Rafael, Fullman, Nancy, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshari, Mahdi, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Akalu, Temesgen Yihunie, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Albujeer, Ammar, Alebel, Animut, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Almasi, Ali, Al-Maskari, Fatma, Al-Mekhlafi, Hesham M, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Amini, Erfan, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Appiah, Lambert Tetteh, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Monika, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Assadi, Reza, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Azarpazhooh, Mahmoud Reza, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banerjee, Amitava, Banoub, Joseph Adel Mattar, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Barthelemy, Celine M, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Battista, Robert J, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Benzian, Habib, Berhane, Adugnaw, Berhe, Abadi Kidanemariam, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhansali, Anil, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Biehl, Molly H, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Bisanzio, Donal, Biswas, Tuhin, Bitew, Helen, Bizuneh, Hailemichael, Bjertness, Espen, Bobasa, Eshetu Mulisa, Boufous, Soufiane, Bourne, Rupert, Bozorgmehr, Kayvan, Bragazzi, Nicola Luigi, Brainin, Michael, Brant, Luisa C, Brauer, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Bukhman, Gene, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Callender, Charlton SKH, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Josip, Car, Mate, Cárdenas, Rosario, Carrero, Juan J, Carter, Austin, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Causey, Kate, Çavlin, Alanur, Cercy, Kelly M, Cerin, Ester, Chaiah, Yazan, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chattu, Vijay Kumar, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J, Chung, Sheng-Chia, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Claßen, Thomas Khaled Dwayne, Cohen, Aaron J, Collado-Mateo, Daniel, Cooper, Cyrus, Cooper, Leslie Trumbull, Cornaby, Leslie, Cortinovis, Monica, Costa, Megan, Cousin, Ewerton, Cromwell, Elizabeth A, Crowe, Christopher Stephen, Cunningham, Matthew, Daba, Alemneh Kabeta, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I, Daryani, Ahmad, Das, Siddharth K, Das Gupta, Rajat, das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davis, Adrian C, Davitoiu, Dragos Virgil, Davletov, Kairat, Dayama, Anand, de Courten, Barbora, De Leo, Diego, De Neve, Jan-Walter, De Steur, Hans, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta Tilahun, Deiparine, Selina, Dellavalle, Robert P, Demoz, Gebre Teklemariam, Demtsu, Balem, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Dessie, Getenet Ayalew, Dey, Subhojit, Dharmaratne, Samath D, Dhimal, Meghnath, Dicker, Daniel, Dinberu, Mesfin Tadese, Ding, Eric L, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Douwes-Schultz, Dirk, Driscoll, Tim Robert, Duan, Leilei, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B, Duraes, Andre R, Ebrahimpour, Soheil, Edvardsson, David, El Bcheraoui, Charbel, Eldrenkamp, Erika, El-Khatib, Ziad, Elyazar, Iqbal RF, Enayati, Ahmadali, Endries, Aman Yesuf, Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Esteghamati, Sadaf, Estep, Kara, Fakhar, Mahdi, Fakhim, Hamed, Fanzo, Jessica, Faramarzi, Mahbobeh, Fareed, Mohammad, Farhadi, Farzaneh, Farid, Talha A, Farinha, Carla Sofia e Sá, Farioli, Andrea, Faro, Andre, Farvid, Maryam S, Farzadfar, Farshad, Farzaei, Mohammad Hosein, Farzam, Hossein, Fazaeli, Ali Akbar, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Fekadu, Wubalem, Feldman, Rachel, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C, Feyissa, Garumma Tolu, Fijabi, Daniel Obadare, Filip, Irina, Finegold, Samuel, Finger, Jonas David, Fischer, Florian, Fitzmaurice, Christina, Flor, Luisa Sorio, Foigt, Nataliya A, Foreman, Kyle J, Frank, Tahvi D, Franklin, Richard Charles, Fukumoto, Takeshi, Fukutaki, Kai, Fuller, John E, Fürst, Thomas, Furtado, João M, Gakidou, Emmanuela, Gallus, Silvano, Gankpe, Fortune Gbetoho, Gansevoort, Ron T, Garcia, Ana Cristina, Garcia-Basteiro, Alberto L, Garcia-Gordillo, Miguel A, Gardner, William M, Gebre, Abadi Kahsu, Gebre, Teshome, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gebremichael, Bereket, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijnse, Johanna M, Geramo, Yilma Chisha Dea, Getachew, Sefonias, Gething, Peter W, Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Ghadiri, Keyghobad, Ghasemi-Kasman, Maryam, Ghiasvand, Hesam, Ghimire, Mamata, Ghoshal, Aloke Gopal, Giampaoli, Simona, Gill, Paramjit Singh, Gill, Tiffany K, Giussani, Giorgia, Gnedovskaya, Elena V, Goldberg, Ellen M, Goli, Srinivas, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Gorman, Taren M, Goto, Atsushi, Goulart, Alessandra C, Goulart, Bárbara Niegia Garcia, Grada, Ayman, Griswold, Max G, Grosso, Giuseppe, Gugnani, Harish Chander C, Guillemin, Francis, Guimaraes, Andre Luiz Sena, Guo, Yuming, Gupta, Prakash C, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Ha, Giang Hai, Haagsma, Juanita A, Hachinski, Vladimir, Hafezi-Nejad, Nima, Haghparast Bidgoli, Hassan, Hagos, Tekleberhan B, Haile, Michael Tamene, Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randah R, Hamidi, Samer, Hankey, Graeme J, Harb, Hilda L, Harikrishnan, Sivadasanpillai, Haririan, Hamidreza, Haro, Josep Maria, Hasan, Mehedi, Hassankhani, Hadi, Hassen, Hamid Yimam, Havmoeller, Rasmus, Hawley, Caitlin N, Hay, Simon I, He, Yihua, Hedayatizadeh-Omran, Akbar, Hegazy, Mohamed I, Heibati, Behzad, Heidari, Behnam, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Heredia-Pi, Ileana, Herteliu, Claudiu, Heydarpour, Behzad, Heydarpour, Fatemeh, Heydarpour, Sousan, Hibstu, Desalegn T, Híjar, Martha, Hoek, Hans W, Hoffman, Daniel J, Hole, Michael K, Homaie Rad, Enayatollah, Hoogar, Praveen, Horita, Nobuyuki, Hosgood, H Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hotez, Peter J, Hoy, Damian G, Hsairi, Mohamed, Hsiao, Thomas, Hu, Guoqing, Huang, John J, Hughes, Caitlyn, Huynh, Chantal K, Igumbor, Ehimario U, Ikeda, Chad Thomas, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Ivers, Rebecca Q, Izadi, Neda, Jacobsen, Kathryn H, Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovljevic, Mihajlo, Jalu, Moti Tolera, Jamal, Amr A, James, Spencer L, Jassal, Simerjot K, Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S, Johnson, Catherine O, Johnson, Sarah C, Jonas, Jost B, Jonnagaddala, Jitendra, Jorjoran Shushtari, Zahra, Joshi, Ankur, Jozwiak, Jacek Jerzy, Jungari, Suresh Banayya, Jürisson, Mikk, K, Madhanraj, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kahssay, Molla, Kalani, Rizwan, Kapil, Umesh, Karami, Manoochehr, Karami Matin, Behzad, Karanikolos, Marina, Karimi, Narges, Karimi, Seyed M, Karimi-Sari, Hamidreza, Kasaeian, Amir, Kassa, Dessalegn H, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassa, Zemenu Yohannes, Kassebaum, Nicholas J, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazemi, Zhila, Karyani, Ali Kazemi, Kazi, Dhruv Satish, KC, Prakash, Kebede, Seifu, Keiyoro, Peter Njenga, Kemmer, Laura, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khafaei, Behzad, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A, Khan, Ejaz Ahmad, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young-Ho, Khanna, Tripti, Khater, Mona M, Khatony, Alireza, Khazaeipour, Zahra, Khazaie, Habibolah, Khoja, Abdullah T, Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Khubchandani, Jagdish, Kiadaliri, Aliasghar A, Kiarie, Helen W, Kibret, Getiye D, Kiirithio, Daniel N, Kim, Daniel, Kim, Jun Y, Kim, Young-Eun, Kim, Yun Jin, Kimokoti, Ruth W, Kinfu, Yohannes, Kinra, Sanjay, Kisa, Adnan, Kissimova-Skarbek, Katarzyna, Kissoon, Niranjan, Kivimäki, Mika, Kocarnik, Jonathan M, Kochhar, Sonali, Kokubo, Yoshihiro, Kolola, Tufa, Kopec, Jacek A, Kosek, Margaret N, Kosen, Soewarta, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael A, Krishan, Kewal, Krohn, Kristopher J, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kudom, Andreas A, Kulikoff, Xie Rachel, Kumar, G Anil, Kumar, Manasi, Kumar, Pushpendra, Kutz, Michael J, Kyu, Hmwe Hmwe, Lachat, Carl, Lad, Deepesh P, Lad, Sheetal D, Lafranconi, Alessandra, Lagat, Abraham K, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lami, Faris Hasan, Lamichhane, Prabhat, Lan, Qing, Lang, Justin J, Lansingh, Van C, Lansky, Sonia, Larson, Heidi J, Larsson, Anders O, Laryea, Dennis Odai, Lassi, Zohra S, Latifi, Arman, Lau, Kathryn Mei-Ming, Laxmaiah, Avula, Lazarus, Jeffrey V, Leasher, Janet L, Lebedev, Georgy, Ledesma, Jorge R, Lee, James B, Lee, Paul H, Leever, Andrew T, Leigh, James, Leinsalu, Mall, Leshargie, Cheru Tesema, Leung, Janni, Lewycka, Sonia, Li, Shanshan, Li, Xiaohong, Li, Yichong, Liang, Juan, Liang, Xiaofeng, Liben, Misgan Legesse, Lim, Lee-Ling, Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Logroscino, Giancarlo, Lopez, Alan D, Lorkowski, Stefan, Lotufo, Paulo A, Lucchesi, Lydia R, Lyons, Ronan A, Macarayan, Erlyn Rachelle King, Mackay, Mark T, Maddison, Emilie R, Madotto, Fabiana, Maghavani, Dhaval P, Magis-Rodriguez, Carlos, Mahotra, Narayan Bahadur, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Mamun, Abdullah A, Manda, Ana-Laura, Mandarano-Filho, Luiz Garcia, Mangalam, Srikanth, Manguerra, Helena, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Maravilla, Joemer C, Marcenes, Wagner, Marks, Ashley, Martin, Randall V, Martins, Sheila C O, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, Mashamba-Thompson, Tivani Phosa, 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Subjects
GENDER-DIFFERENCES, SUICIDE, Medicine (all), Burden of Disease Study 2017, SDG, CONSUMPTION, 11 Medical And Health Sciences, GBD, Sustainable Development Goals, PREVENTION, ALCOHOL-USE, CARDIOVASCULAR-DISEASE, SMOKING PREVALENCE, General & Internal Medicine, factors risk, Medicine and Health Sciences, Human medicine, CESSATION, PERSPECTIVE, TRANSITION
Abstract

Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health -related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related S DG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2.5th percentile and 100 as the 97.5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings The global median health-related SDG index in 2017 was 59.4 (IQR 35.4-67.3), ranging from a low of 11.6 (95% uncertainty interval 9.6-14.0) to a high of 84.9 (83.1-86.7). SDG index values in countries assessed at the subnational level varied substantially particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attaimnent by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation The GBD study offers a unique, robust platform for monitoring the health -related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health -related SDG indicators, NCDs, NCD-related risks, and violence -related indicators will require a concerted shift away from what might have driven past gains curative interventions in the case of NCDs towards multisectoral, prevention -oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the S DGs. What is clear is that our actions or inaction today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

Published
2018

13. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017

Author

Roth, Gregory A., Collaborotors, G. B. D.Causes Death, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M., Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Load, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Adamu, Abdu A., Adebayo, Oladimeji, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adookunboh, Olatunii, Adhena, Beyene Meressa, Adib, Mina G., Admasie, Aniha, Afshin, Ashkan, Agarwal, Gina, Agesa, Karelia M., Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Melidi, Ahmed, Muktar Beshir, Ahmed, Sayent, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Fddine, Akbari, Mohammad Esmaeil, Akinyeniti, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Raddadi, Rajaa M., Alandab, Fares, Alam, Khurshid, Alam, Tahiya, Alebel, Animut, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, Francois, Allebeck, Peter, Alonso, Jordi, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T., Aminde, Leopold N., Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampern, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Aniha, Mustafa Geleto, Antonio, Carl Abelardo T., Anwari, Palwasha, Aremu, Olatunde, Arnlov, Johan, Arora, Amit, Arora, Monika, Artaman, Al, Aryal, Krishna K., Asayesh, Hamid, Asfaw, Ephremi Tsegay, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R., Ausloos, Marcel, Avokpaho, Euripide F. G. A., Awasthi, Ashish, Quintattilla, Beatriz Paulina Ayala, Ayele, Yohanes, Ayer, Rakesh, Azzopardi, Peter S., Babazadeh, Arefeh, Bacha, Umar, Badali, Hamid, Badawi, Alaa, Bali, Ayele Geleto, Ballesteros, Katherine E., Banach, Maciej, Banerjee, Kajori, Bannick, Marlena S., Banoub, Joseph Adel Mattar, Barboza, Miguel A., Barker-Collo, Suzanne Lyu, Barnighausen, Till Winfried, Barquera, Simon, Barrero, Lope, Bassat, Quique, Base, Sanjay, Baune, Bernhard T., Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Beth, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Mcysam, Bejot, Yannick, Bekele, Bayu Begashaw, Belacliew, Abate Bekele, Belay, Ezra, Belay, Yihalem Abebe, Bell, Michelle L., Bello, Aminu K., Bennett, Derrick A., Bensenor, Isabela M., Berman, Adam F., Bernabe, Eduardo, Bernstein, Robert S., Bertolacci, Gregory J., Beuran, Mircea, Beyranvand, Tina, Bhalla, Ashish, Bhattarai, Suraj, Bhaumik, Sounayadeeep, Bhutta, Zulfiqar A., Biadgo, Belete, Biehl, Molly H., Bijani, Ali, Bikbov, Boris, Bilano, Ver, Bililign, Nigus, Bin Sayeed, Muhammad Shandaat, Bisanzio, Donal, Biswas, Tuhin, Blacker, Brigitte F., Basara, Berrak Bora, Borschmann, Rohan, Bosetti, Cristina, Bozorgmehr, Kayvan, Brady, Oliver J., Brant, Luisa C., Brayne, Carol, Brazinova, Alexandra, Breitborde, Nicholas J. K., Brenner, Hermann, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Busse, Reinhard, Butt, Zahid A., Callender, Charlton S. K. 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Sa, Faro, Andre, Farvid, Maryam S., Farzadfar, Farshad, Farzaei, Mohammad Hosein, Feign, Valery L., Feigl, Andrea B., Fentahun, Netsanet, Eereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C., Ferrari, Alice J., Feyissa, Garumma Tolu, Filip, Irina, Finegold, Samuel, Fischer, Florian, Eitzmaurice, Christina, Foigt, Nataliya A., Foreman, Kyle J., Fornari, Carla, Frank, Tahvi D., Fukumoto, Takeshi, Fuller, John E., Fullman, Nancy, Furst, Thomas, Furtado, Joao M., Futran, Neal D., Gallus, Silvano, Garcia-Basteiro, Alberto L., Garcia-Gordillo, Miguel A., Gardner, William M., Gebre, Abadi Kahsu, Gebrehiwol, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gebremichael, Bereket, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijinse, Johanna M., Genova-Maleras, Ricard, Geramo, Yilma Chisha Dea, Gething, Peter W., Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Falavarjani, Khalil Ghasemi, Ghasemi-Kasman, Maryam, Ghimire, Mamata, Gibney, Katherine B., Gill, Paramjit Singh, Gill, Tiffany K., Gillum, Richard F., Ginawi, Ibrahim Abdelmageed, Giroud, Maurice, Giussani, Giorgia, Goenka, Shifalika, Goldberg, Ellen M., Goli, Srinivas, Gomez-Dantes, Hector, Gona, Philimon N., Gopalani, Sameer Vali, Gorman, Taren M., Goto, Atsushi, Goulart, Alessandra C., Gnedovskaya, Elena V., Grada, Aymara, Grosso, Giuseppe, Gugnani, Hanish Chander, Guimaraes, Andre Luiz Sena, Gun, Nailing, Gupta, Prakash C., Gupta, Rahid, Gupta, Rajenv, Gupta, Tanush, Gutierrez, Reyna Alma, Gyawali, Bishal, Haagsma, Juanita A., Hafezi-Nejad, Nima, Hagos, Tekleberhan B., Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randall R., Hamidi, Sinner, Handal, Meads J., Hankey, Graeme J., Harb, Hilda L., Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hasan, Mehedi, Hassankhani, Hadi, Hassen, Hamid, Havmoeller, Rasmus, Hay, Roderick J., Hay, Simon I., He, Yihua, Hedayatizadeh-Omran, Akbar, Hegazy, Mohamed I., Heibati, Behzad, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Henry, Nathaniel J., Herteliu, Claudiu, Heydarpour, Fatemeh, Heydarpour, Pouria, Heydarpour, Sousan, Hibstu, Desalegn Tsegaw, Hoek, Hans W., Hole, Michael K., Red, Enayatollah Homaie, Hoogar, Praveen, Hosgood, H. Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hotez, Peter J., Hoy, Damian C., Hsiao, Thomas, Hu, Guoqing, Huang, John J., Husseini, Abdullatif, Hussen, Mohammedaman Mama, Hutfless, Susan, Idrisov, Bulat, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Nazrul, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Jacobsen, Kathryn H., Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovlievic, Mihajlo, Jalu, Moti Tolera, James, Spencer L., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jenkins, Kathy J., Jha, Ravi Prakash, Jha, Vivekanand, Johnson, Catherine O., Johnson, Sarah C., Jonas, Jost B., Joshi, Ankur, Jozwiak, Jacek Jerzy, Jungari, Suresh Banayya, Jurisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalani, Rizwan, Karami, Manoochehr, Matin, Behzad Karami, Karch, Andre, Karema, Corine, Karimi-Sari, Hamidreza, Kasaeian, Amir, Kassa, Dessalegn H., Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kaul, Anil, Kazemi, Zhila, Karyani, Ali Kazemi, Kazi, Dhruv Satish, Kefale, Adane Teshome, Keiyoro, Peter Njenga, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khafaei, Behzad, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young-Ho, Khater, Mona M., Khoja, Abdullah T., Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Khubchandani, Jagdish, Kiadaliri, Aliasghar A., Kibret, Getiye D., Kidanemariam, Zelalem Teklemariam, Kiirithio, Daniel N., Kim, Daniel, Kim, Young-Eun, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohannes, Kisa, Adnan, Kissimova-Skarbek, Katarzyna, Kivimaki, Mika, Knudsen, Ann Kristin Skrindo, Kocarnik, Jonathan M., Kochhar, Sonali, Kokubo, Yoshihiro, Kolola, Tufa, Kopec, Jacek A., Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael A., Krishan, Kewal, Defo, Barthelemy Kuate, Bicer, Burcu Kinuk, Kumar, G. Anil, Kumar, Manasi, Kumar, Pushpendra, Kutz, Michael J., Kuzin, Igor, Kyu, Hmwe Hmwe, Lad, Deepesh P., Lad, Sheetal D., Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lallukka, Tea, Lam, Jennifer O., Lami, Faris Hasan, Van Lansingh, C., Lansky, Sonia, Larson, Heidi J., Latifi, Amman, Lau, Kathryn Mei-Ming, Lazarus, Jeffrey V., Lebedev, Georgy, Lee, Paul H., Leigh, James, Leili, Mostafa, Leshargie, Cheru Tesema, Li, Shanshan, Li, Yichong, Liang, Juan, Lim, Lee-Ling, Lim, Stephen S., Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Lansdale, Chris, Lopez, Alan D., Lorkowski, Stefan, Lotufo, Paulo A., Lozano, Rafael, Lunevicius, Raimundas, Ma, Stefan, Macarayan, Erlyn Rachelle King, Mackay, Mark T., MacLachlan, Jennifer H., Maddison, Emilie R., Nadotto, Fabiana, Abd El Razek, Hassan Magdy, Abd El Razek, Muhammed Magdy, Maghavani, Dhaval P., Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Manda, Ana-Laura, Mandarano-Filho, Luiz Garcia, Manguerra, Helena, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Marami, Dadi, Maravilla, Joemer C., Marcenes, Wagner, Marczak, Laurie, Marks, Ashley, Marks, Guy B., Martinez, Gabriel, Martins-Melo, Francisco Rogerlandio, Martopullo, Ira, Marz, Winfried, Marron, Melvin B., Masci, Joseph R., Lylassenburg, Benjamin Ballard, Mathur, Manu Raj, Mathur, Prashant, Matzopoulos, Richard, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Cohn, McGrath, John J., McKee, Martin, McMahon, Brian J., Mehata, Suiiesh, Mehndiratta, Man Mohan, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Mekonnen, Tefera C., Melese, Addisu, Melku, Mulugeta, Memiah, Peter T. N., Memish, Ziad A., Mendoza, Walter, Mengistu, Desalegn Tadese, Mengistu, Getnet, Mensah, George A., Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J., Meshovic, Tbmislav, Mezgebe, Haftay Berhane, Miazgowski, Bartosz, Miazgowski, Tomasz, Millear, Anoushka I., Miller, Ted R., Katherine, Molly, Petrie, Miller, Mini, G. K., Mirabi, Parvaneh, Mirarefin, Mojde, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke Temesgen, Mitiku, Habtamu, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammad, Moslem, Mohammadifard, Noushin, Mohammed, A. 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Subjects
Adult, Male, Adolescent, national age-sex-specific mortality, UNITED-STATES, Global Health, Socioeconomic Factor, Global Burden of Disease, GBD, causes of death, Young Adult, Age Distribution, Life Expectancy, General & Internal Medicine, Cause of Death, PUBLIC-HEALTH PROBLEM, mortality, 282 causes global burden of disease, Sex Distribution, Child, Aged, Aged, 80 and over, BARRIERS, DEMENTIA, Medicine (all), Infant, Newborn, Infant, 11 Medical And Health Sciences, Middle Aged, TRENDS, PREVENTION, PREVALENCE, ALZHEIMERS-DISEASE, INDIVIDUALS, 3121 General medicine, internal medicine and other clinical medicine, Child, Preschool, REGISTRATION, Female, Human medicine, Human
Abstract

Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.

Published
2018

14. Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016

Author

Nancy, Fullman, Jamal, Yearwood, Solomon, M, Abay, Cristiana, Abbafati, Foad, Abd-Allah, Jemal, Abdela, Ahmed, Abdelalim, Zegeye, Abebe, Teshome, Abuka, Abebo, Victor, Aboyans, Haftom, Niguse, Abraha, Daisy, M, X, Abreu, Laith, Abu-Raddad, J, Akilew, Awoke, Adane, Rufus, Adesoji, Adedoyin, Olatunji, Adetokunboh, Tara, Ballav, Adhikari, Mohsen, Afarideh, Ashkan, Afshin, Gina, Agarwal, Dominic, Agius, Anurag, Agrawal, Sutapa, Agrawal, Aliasghar, Ahmad, Kiadaliri, Miloud, Taki, Eddine, Aichour, Mohammed, Akibu, Rufus, Olusola, Akinyemi, Tomi, Akinyemiju, F, Nadia, Akseer, Faris, Hasan, Lami, Al, Fares, Alahdab, Ziyad, Al-Aly, Khurshid, Alam, Tahiya, Alam, Deena, Alasfoor, Mohammed, I, Albittar, Kefyalew, Addis, Alene, Ayman, Al-Eyadhy, Syed, Danish, Ali, Mehran, Alijanzadeh, Syed, M, Aljunid, Ala’A, Alkerwi, François, Alla, Peter, Allebeck, Christine, Allen, Mahmoud, A, Alomari, Rajaa, Al-Raddadi, Ubai, Alsharif, Khalid, A, Altirkawi, Nelson, Alvis-Guzman, Azmeraw, T, Amare, Kebede, 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Dean, Hosseini, Mostafa, Hosseini, Seyed Reza, Hostiuc, Mihaela, Hostiuc, Sorin, Hoy, Damian G., Hsairi, Mohamed, Htet, Aung Soe, Hu, Guoqing, Huang, John J., Iburg, Kim Moesgaard, Idris, Fachmi, Igumbor, Ehimario Uche, Ikeda, Chad, Ileanu, Bogdan Vasile, Ilesanmi, Olayinka S., Innos, Kaire, Irvani, Seyed Sina Naghibi, Irvine, Caleb M.S., Islami, Farhad, Jacobs, Troy A., Jacobsen, Kathryn H., Jahanmehr, Nader, Jain, Rajesh, Jain, Sudhir Kumar, Jakovljevic, Mihajlo M., Jalu, Moti Tolera, Jamal, Amr A., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Józwiak, Jacek, John, Oommen, Johnson, Sarah Charlotte, Jonas, Jost B., Joshua, Vasna, Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalani, Rizwan, Kar, Chittaranjan, Karanikolos, Marina, Karch, André, Karema, Corine Kakizi, Karimi, Seyed M., Kasaeian, Amir, Kassa, Dessalegn Haile, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazanjan, Konstantin, Kebede, Seifu, Keiyoro, Peter Njenga, Kemp, Grant Rodger, Kengne, Andre Pascal, Kereselidze, Maia, Ketema, Ezra Belay, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Md Nuruzzaman, Khan, Muhammad Ali, Khanal, Mukti Nath, Khang, Young-Ho, Khater, Mona M., Khoja, Abdullah Tawfih Abdullah, Khosravi, Ardeshir, Khubchandani, Jagdish, Kibret, Getiye Dejenu, Kiirithio, Daniel Ngari, Kim, Daniel, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohanne, Kinra, Sanjay, Kisa, Adnan, Kissoon, Niranjan, Kochhar, Sonali, Kokubo, Yoshihiro, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael, Krishan, Kewal, Krohn, Kristopher J., Kuate Defo, Barthelemy, Kumar, G. Anil, Kumar, Pushpendra, Kutz, Michael, Kuzin, Igor, Kyu, Hmwe H., Lad, Deepesh Pravinkumar, Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lan, Qing, Lang, Justin J., Lansingh, Van C., Lansky, Sonia, Larsson, Ander, Latifi, Arman, Lazarus, Jeffrey Victor, Leasher, Janet L., Lee, Paul H., Legesse, Yirga, Leigh, Jame, Leshargie, Cheru Tesema, Leta, Samson, Leung, Janni, Leung, Ricky, Levi, Miriam, Li, Yongmei, Liang, Juan, Liben, Misgan Legesse, Lim, Lee-Ling, Lim, Stephen S., Lind, Margaret, Linn, Shai, Listl, Stefan, Liu, Patrick Y., Liu, Shiwei, Lodha, Rakesh, Lopez, Alan D., Lorch, Scott A., Lorkowski, Stefan, Lotufo, Paulo A., Lucas, Timothy C.D., Lunevicius, Raimunda, Lurton, Grégoire, Lyons, Ronan A., Maalouf, Fadi, Macarayan, Erlyn Rachelle King, Mackay, Mark T., Maddison, Emilie R., Madotto, Fabiana, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Mohammed, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malhotra, Rajesh, Malta, Deborah Carvalho, Mamun, Abdullah A., Manguerra, Helena, Manhertz, Treh, Mansournia, Mohammad Ali, Mantovani, Lorenzo G., Manyazewal, Tsegahun, Mapoma, Chabila C., Margono, Christopher, Martinez-Raga, Jose, Martins, Sheila Cristina Ourique, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, März, Winfried, Massenburg, Benjamin Ballard, Mathur, Manu Raj, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Colm, McGrath, John J., McKee, Martin, Mehata, Suresh, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Meier, Toni, Mejia-Rodriguez, Fabiola, Meles, Kidanu Gebremariam, Melku, Mulugeta, Memiah, Peter, Memish, Ziad A., Mendoza, Walter, Mengiste, Degu Abate, Mengistu, Desalegn Tadese, Menota, Bereket Gebremichael, Mensah, George A., Meretoja, Atte, Meretoja, Tuomo J., Mezgebe, Haftay Berhane, Miazgowski, Tomasz, Micha, Renata, Milam, Robert, Millear, Anoushka, Miller, Ted R., Mini, G.K., Minnig, Shawn, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke, Mitchell, Philip B., Mlashu, Fitsum Weldegebreal, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammadibakhsh, Roghayeh, Mohammed, Ebrahim, Mohammed, Mohammed A., Mohammed, Shafiu, Mokdad, Ali H., Mola, Glen Liddell D., Molokhia, Mariam, Momeniha, Fatemeh, Monasta, Lorenzo, Montañez Hernandez, Julio Cesar, Moosazadeh, Mahmood, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Moreno Velasquez, Ilai, Mori, Rintaro, Morrison, Shane D., Moses, Mark, Mousavi, Seyyed Meysam, Mueller, Ulrich O., Murhekar, Manoj, Murthy, Gudlavalleti Venkata Satyanarayana, Murthy, Sriniva, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nagata, Chie, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Naik, Gurudatta A., Naik, Nitish, Najafi, Farid, Naldi, Luigi, Nangia, Vinay, Nansseu, Jobert Richie Njingang, Narayan, K.M. Venkat, Nascimento, Bruno Ramo, Negoi, Ionut, Negoi, Ruxandra Irina, Newton, Charles R., Ngunjiri, Josephine Wanjiku, Nguyen, Grant, Nguyen, Long, Nguyen, Trang Huyen, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nolte, Ellen, Nong, Vuong Minh, Norheim, Ole F., Norrving, Bo, Noubiap, Jean Jacques N., Nyandwi, Alypio, Obermeyer, Carla Makhlouf, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew Toyin, Olagunju, Tinuke Oluwasefunmi, Olivares, Pedro R., De Oliveira, Patricia Pereira Vasconcelo, Olsen, Helen E., Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin, Opio, John Nelson, Oren, Eyal, Ortega-Altamirano, Doris V., Ortiz, Alberto, Ozdemir, Raziye, Pa, Mahesh, Pain, Amanda W., Palone, Marcos Roberto Tovani, Pana, Adrian, Panda-Jonas, Songhomitra, Pandian, Jeyaraj D., Park, Eun-Kee, Parsian, Hadi, Patel, Teja, Pati, Sanghamitra, Patil, Snehal T., Patle, Ajay, Patton, George C., Paturi, Vishnupriya Rao, Paudel, Deepak, De Moares Pedroso, Marcel, Pedroza, Sandra P., Pereira, David M., Perico, Norberto, Peterson, Hannah, Petzold, Max, Peykari, Niloofar, Phillips, Michael Robert, Piel, Frédéric B., Pigott, David M., Pillay, Julian David, Piradov, Michael A., Polinder, Suzanne, Pond, Constance D., Postma, Maarten J., Pourmalek, Farshad, Prakash, Swayam, Prakash, V., Prasad, Narayan, Prasad, Noela Marie, Purcell, Caroline, Qorbani, Mostafa, Quintana, Hedley Knewjen, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Muhammad Aziz, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Raju, Sree Bhushan, Ram, Usha, Rana, Saleem M., Rankin, Zane, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E., Razo-García, Christian Aspacia, Reddy, Priscilla, Reiner, Robert C., Reis, Cesar, Reitsma, Marissa B., Remuzzi, Giuseppe, Renzaho, Andre M.N., Resnikoff, Serge, Rezaei, Satar, Rezai, Mohammad Sadegh, Ribeiro, Antonio L., Rios Blancas, Maria Jesu, Rivera, Juan A., Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A., Rothenbacher, Dietrich, Roy, Ambuj, Roy, Nobhojit, Ruhago, George Mugambage, Sabde, Yogesh Damodar, Sachdev, Perminder S., Sadat, Nafi, Safdarian, Mahdi, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salama, Joseph, Salamati, Payman, De Freitas Saldanha, Raphael, Salimzadeh, Hamideh, Salomon, Joshua A., Samy, Abdallah M., Sanabria, Juan Ramon, Sancheti, Parag K., Sanchez-Niño, Maria Dolore, Santomauro, Damian, Santos, Itamar S., Santric Milicevic, Milena M., Sarker, Abdur Razzaque, Sarrafzadegan, Nizal, Sartorius, Benn, Satpathy, Maheswar, Savic, Miloje, Sawhney, Monika, Saxena, Sonia, Saylan, Mete I., Schaeffner, Elke, Schmidhuber, Josef, Schmidt, Maria Inê, Schneider, Ione J.C., Schumacher, Austin E., Schutte, Aletta E., Schwebel, David C., Schwendicke, Falk, Sekerija, Mario, Sepanlou, Sadaf G., Servan-Mori, Edson E., Shafieesabet, Azadeh, Shaikh, Masood Ali, Shakh-Nazarova, Marina, Shams-Beyranvand, Mehran, Sharafi, Heidar, Sharif-Alhoseini, Mahdi, Shariful Islam, Sheikh Mohammed, Sharma, Meenakshi, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shfare, Mebrahtu Teweldemedhin, Shi, Peilin, Shields, Chloe, Shigematsu, Mika, Shinohara, Yukito, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shrime, Mark G., Shukla, Sharvari Rahul, Siabani, Soraya, Sigfusdottir, Inga Dora, Silberberg, Donald H., Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singh, Jasvinder A., Singh, Lavanya, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Sinke, Abiy Hiruye, Sisay, Mekonnen, Skirbekk, Vegard, Sliwa, Karen, Smith, Alison, Soares Filho, Adauto Martin, Sobaih, Badr H.A., Somai, Melek, Soneji, Samir, Soofi, Moslem, Sorensen, Reed J.D., Soriano, Joan B., Soyiri, Ireneous N., Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Srinivasan, Vinay, Stanaway, Jeffrey D., 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Updike, Rachel, Uthman, Olalekan A., Uzochukwu, Benjamin S. Chudi, Valdez, Pascual Rubén, Van Boven, Job F.M., Varughese, Santosh, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Violante, Francesco S., Vladimirov, Sergey K., Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Vos, Theo, Wagnew, Fasil, Waheed, Yasir, Wallin, Mitchell T., Walson, Judd L., Wang, Yafeng, Wang, Yuan-Pang, Wassie, Molla Mesele, Weaver, Marcia R., Weiderpass, Elisabete, Weintraub, Robert G., Weiss, Jordan, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T. Eoin, Westerman, Ronny, White, Richard G., Whiteford, Harvey A., Widecka, Justyna, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D.A., Wondimkun, Yohanes Ayele, Workicho, Abdulhalik, Wyper, Grant M.A., Xavier, Deni, Xu, Gelin, Yan, Lijing L., Yano, Yuichiro, Yaseri, Mehdi, Yimer, Nigus Bililign, Yin, Peng, Yip, Paul, Yirsaw, Biruck Desalegn, Yonemoto, Naohiro, Yonga, Gerald, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z., Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, El Sayed Zaki, Maysaa, Zaman, Sojib Bin, Zamani, Mohammad, Zenebe, Zerihun Menlkalew, Zhou, Maigeng, Zhu, Jun, Zimsen, Stephanie R.M., Zipkin, Ben, Zodpey, Sanjay, Zuhlke, Liesl Joanna, Murray, Christopher J.L., Lozano, Rafael, Viðskiptadeild (HR), School of Business (RU), Háskólinn í Reykjavík, Reykjavik University, Abay, Sm, Abebo, Ta, Abraha, Hn, Abreu, Dmx, Abu-Raddad, Lj, Adane, Aa, Adedoyin, Ra, Adhikari, Tb, Aichour, Mte, Akinyemi, Ro, Akinyemiju, Tf, Al Lami, Fh, Albittar, Mi, Alene, Ka, Ali, Sd, Aljunid, Sm, Alomari, Ma, Altirkawi, Ka, Amare, At, Amoako, Ya, Andrei, Cl, Antonio, Cat, Araújo, Vem, Aryal, Kk, Asfaw, Et, Asgedom, Sw, Asghar, Rj, Ashebir, Mm, Asseffa, Na, Atey, Tm, Atre, Sr, Avokpaho, Efga, Ayala Quintanilla, Bp, Ayalew, Aa, Ayele, Ht, Ayuk, Tb, Babalola, Tk, Barber, Rm, Barboza, Ma, Barker-Collo, Sl, Barrero, Lh, Baune, Bt, Bekele, Bb, Belachew, Ab, Belay, Sa, Belay, Ya, Bell, Ml, Bello, Ak, Bennett, Da, Bennett, Jr, Bensenor, Im, Berhe, Df, Bhutta, Za, Bolliger, Iw, Bou-Orm, Ir, Brady, Oj, Breitborde, Njk, Butt, Za, Campos-Nonato, Ir, Campuzano, Jc, Carrero, Jj, Castañeda-Orjuela, Ca, Chang, Hy, Chang, Jc, Chiang, Pp, Chisumpa, Vh, Choi, Jj, Christopher, Dj, Chung, Sc, Ciobanu, Lg, Cortesi, Pa, Criqui, Mh, Cromwell, Ea, Crump, Ja, Daba, Ak, Dachew, Ba, Dadi, Af, Dargan, Pi, Das, Sk, De Neve, Jw, Dellavalle, Rp, Des Jarlais, Dc, Dharmaratne, Sd, Doku, Dt, Dorsey, Er, Dos Santos, Kpb, Doyle, Ke, Driscoll, Tr, Duncan, Bb, Ehrlich, Jr, El-Khatib, Zz, Endries, Ay, Faraon, Eja, Feigin, Vl, Feigl, Ab, Fereshtehnejad, Sm, Fernandes, Jc, Fijabi, Do, Flaxman, Ad, Foreman, Kj, Frostad, Jj, Futran, Nd, Gebre, Ak, Gebrehiwot, Tt, Gebremedhin, At, Gelaw, Ya, Geleijnse, Jm, Gething, Pw, Giref, Az, Gishu, Md, Godwin, Ww, Gona, Pn, Gopalani, Sv, Goulart, Ac, Gugnani, Hc, Haagsma, Ja, Hailu, Gb, Hamadeh, Rr, Hankey, Gj, Harb, Hl, Harewood, Hc, Haro, Jm, Hassen, Hy, Hay, Si, Hearps, Sjc, Hegazy, Mi, Henry, Nj, Herrera Ballesteros, Vh, Hibstu, Dt, Hiluf, Mk, Hoek, Hw, Hosgood, Hd, Hosseini, Sr, Hoy, Dg, Huang, Jj, Iburg, Km, Igumbor, Eu, Ileanu, Bv, Irvani, Ssn, Irvine, Cm, Jacobs, Ta, Jacobsen, Kh, Jain, Sk, Jakovljevic, Mb, Jalu, Mt, Jamal, Aa, Jayatilleke, Au, Jha, Rp, Johnson, Sc, Jonas, Jb, Karema, Ck, Karimi, Sm, Kassa, Dh, Kassa, Gm, Kassa, Td, Kassebaum, Nj, Katikireddi, Sv, Keiyoro, Pn, Kemp, Gr, Kengne, Ap, Ketema, Eb, Khafaie, Ma, Khalil, Ia, Khan, Ea, Khan, Mn, Khan, Ma, Khanal, Mn, Khang, Yh, Khater, Mm, Khoja, Ata, Kibret, Gd, Kiirithio, Dn, Kim, Yj, Kimokoti, Rw, Kopec, Ja, Koul, Pa, Krohn, Kj, Kumar, Ga, Kyu, Hh, Lad, Dp, Lal, Dk, Lang, Jj, Lansingh, Vc, Lazarus, Jv, Leasher, Jl, Lee, Ph, Leshargie, Ct, Liben, Ml, Lim, Ll, Lopez, Ad, Lorch, Sa, Lotufo, Pa, Lucas, Tcd, Lyons, Ra, Macarayan, Erk, Mackay, Mt, Maddison, Er, Malta, Dc, Mamun, Aa, Mansournia, Ma, Mantovani, Lg, Mapoma, Cc, Martins, Sco, Martins-Melo, Fr, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mcgrath, Jj, Mehta, Km, Meles, Kg, Memish, Za, Mengiste, Da, Mengistu, Dt, Menota, Bg, Mensah, Ga, Meretoja, Tj, Mezgebe, Hb, Miller, Tr, Mini, Gk, Mirrakhimov, Em, Mitchell, Pb, Mlashu, Fw, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Mola, Gl, Montañez Hernandez, Jc, Morrison, Sd, Mousavi, Sm, Mueller, Uo, Murthy, Gv, Musa, Ki, Naik, Ga, Nansseu, Jrn, Narayan, Kv, Nascimento, Br, Negoi, Ri, Newton, Cr, Ngunjiri, Jw, Nguyen, Th, Ningrum, Dna, Nong, Vm, Norheim, Of, Noubiap, Jjn, Obermeyer, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olagunju, To, Olivares, Pr, Oliveira, Ppv, Olsen, He, Olusanya, Bo, Olusanya, Jo, Opio, Jn, Ortega-Altamirano, Dv, Pain, Aw, Palone, Mrt, Pandian, Jd, Park, Ek, Patil, St, Patton, Gc, Paturi, Vr, Pedroso, Mm, Pedroza, Sp, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Piradov, Ma, Pond, Cd, Postma, Mj, Prasad, Nm, Quintana, Hk, Rahman, Ma, Rahman, Su, Rai, Rk, Raju, Sb, Rana, Sm, Rawaf, Dl, Ray, Se, Razo-García, Ca, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Ribeiro, Al, Rios Blancas, Mj, Rivera, Ja, Roth, Ga, Ruhago, Gm, Sabde, Yd, Sahraian, Ma, Saldanha, Rf, Salomon, Ja, Samy, Am, Sanabria, Jr, Sancheti, Pk, Sanchez-Niño, Md, Santric Milicevic, Mm, Sarker, Ar, Saylan, Mi, Schmidt, Mi, Schneider, Ijc, Schumacher, Ae, Schutte, Ae, Schwebel, Dc, Sepanlou, Sg, Servan-Mori, Ee, Shaikh, Ma, Shariful Islam, Sm, Shfare, Mt, Shrime, Mg, Shukla, Sr, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silveira, Dga, Singh, Ja, Singh, Np, Sinha, Dn, Sinke, Ah, Soares Filho, Am, Sobaih, Bha, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Stein, Dj, Stokes, Ma, Sufiyan, Mb, Suliankatchi, Ra, Sunguya, Bf, Sur, Pj, Sykes, Bl, Sylaja, Pn, Tadakamadla, Sk, Tadesse, Ah, Taffere, Gr, Tariku, At, Temsah, Mh, Tesema, Ag, Tesfaye, Dj, Thompson, Mj, To, Qg, Tran, Bx, Tran, Kb, Tripathy, Sp, Tuem, Kb, Ukwaja, Kn, Uthman, Oa, Uzochukwu, Bsc, Valdez, Pr, van Boven, Jfm, Vladimirov, Sk, Vlassov, Vv, Vollset, Se, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weaver, Mr, Weintraub, Rg, Weldegwergs, Kg, West, Te, White, Rg, Whiteford, Ha, Wolfe, Cd, Wondimkun, Ya, Wyper, Gma, Yan, Ll, Yimer, Nb, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaki, Me, Zaman, Sb, Zenebe, Zm, Zimsen, Srm, Zuhlke, Lj, Murray, Cjl, and Lozano, R.

Subjects
Peformance, Coverage, Dánartíðni, Lífslíkur, Life expectancy, GBD, Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best), universal health coverage, Article, access quality health care, health care access and quality index, Nations, Healthcare Acce, Cause-specific mortality, Psychology, Healthcare Access and Quality Index, Mælitæki, States, Medicine (all), Health care, Þjóðir, Public Health, Global Health, Social Medicine and Epidemiology, Quality, Heilbrigðisþjónusta, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Sálfræði, Indicator, Amenable mortality, Transition, we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8–98·1) in Iceland, followed by 96·6 (94·9–97·9) in Norway and 96·1 (94·5–97·3) in the Netherlands, to values as low as 18·6 (13·1–24·4) in the Central African Republic, 19·0 (14·3–23·7) in Somalia, and 23·4 (20·2–26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1–93·6) in Beijing to 48·0 (43·4–53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6–68·8) in Goa to 34·0 (30·3–38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view—and subsequent provision—of quality health care for all populations, Trends, Inequalities
Abstract

Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97.1 (95% UI 95.8-98.1) in Iceland, followed by 96.6 (94.9-97.9) in Norway and 96.1 (94.5-97.3) in the Netherlands, to values as low as 18.6 (13.1-24.4) in the Central African Republic, 19.0 (14.3-23.7) in Somalia, and 23.4 (20.2-26.8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91.5 (89.1-936) in Beijing to 48.0 (43.4-53.2) in Tibet (a 43.5-point difference), while India saw a 30.8-point disparity, from 64.8 (59.6-68.8) in Goa to 34.0 (30.3-38.1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4.8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20.9-point to 17.0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17.2-point to 20.4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view and subsequent provision of quality health care for all populations., Bill & Melinda Gates Foundation. Barbora de Courten is supported by a National Heart Foundation Future Leader Fellowship (100864). Ai Koyanagi’s work is supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R + D + I and funded by the ISCIII —General Branch Evaluation and Promotion of Health Research—and the European Regional Development Fund (ERDF-FEDER). Alberto Ortiz was supported by Spanish Government (Instituto de Salud Carlos III RETIC REDINREN RD16/0019 FEDER funds). Ashish Awasthi acknowledges funding support from Department of Science and Technology, Government of India through INSPIRE Faculty scheme Boris Bikbov has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 703226. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Panniyammakal Jeemon acknowledges support from the clinical and public health intermediate fellowship from the Wellcome Trust and Department of Biotechnology, India Alliance (2015–20). Job F M van Boven was supported by the Department of Clinical Pharmacy & Pharmacology of the University Medical Center Groningen, University of Groningen, Netherlands. Olanrewaju Oladimeji is an African Research Fellow hosted by Human Sciences Research Council (HSRC), South Africa and he also has honorary affiliations with Walter Sisulu University (WSU), Eastern Cape, South Africa and School of Public Health, University of Namibia (UNAM), Namibia. He is indeed grateful for support from HSRC, WSU and UNAM. EUI is supported in part by the South African National Research Foundation (NRF UID: 86003). Ulrich Mueller acknowledges funding by the German National Cohort Study grant No 01ER1511/D, Gabrielle B Britton is supported by Secretaría Nacional de Ciencia, Tecnología e Innovación and Sistema Nacional de Investigación de Panamá. Giuseppe Remuzzi acknowledges that the work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Behzad Heibati would like to acknowledge Air pollution Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran. Syed Aljunid acknowledges the National University of Malaysia for providing the approval to participate in this GBD Project. Azeem Majeed and Imperial College London are grateful for support from the Northwest London National Insititute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research & Care. Tambe Ayuk acknowledges the Institute of Medical Research and Medicinal Plant Studies for office space provided. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). João Fernandes gratefully acknowledges funding from FCT–Fundação para a Ciência e a Tecnologia (grant number UID/Multi/50016/2013). Jan-Walter De Neve was supported by the Alexander von Humboldt Foundation. Kebede Deribe is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (201900). Kazem Rahimi was supported by grants from the Oxford Martin School, the NIHR Oxford BRC and the RCUK Global Challenges Research Fund. Laith J Abu-Raddad acknowledges the support of Qatar National Research Fund (NPRP 9-040-3-008) who provided the main funding for generating the data provided to the GBD-IHME effort. Liesl Zuhlke is funded by the national research foundation of South Africa and the Medical Research Council of South Africa. Monica Cortinovis acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Chuanhua Yu acknowleges support from the National Natural Science Foundation of China (grant number 81773552 and grant number 81273179) Norberto Perico acknowledges that work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Charles Shey Wiysonge’s work is supported by the South African Medical Research Council and the National Research Foundation of South Africa (grant numbers 106035 and 108571). John J McGrath is supported by grant APP1056929 from the John Cade Fellowship from the National Health and Medical Research Council and the Danish National Research Foundation (Niels Bohr Professorship). Quique Bassat is an ICREA (Catalan Institution for Research and Advanced Studies) research professor at ISGlobal. Richard G White is funded by the UK MRC and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement that is also part of the EDCTP2 programme supported by the European Union (MR/P002404/1), the Bill & Melinda Gates Foundation (TB Modelling and Analysis Consortium: OPP1084276/OPP1135288, CORTIS: OPP1137034/OPP1151915, Vaccines: OPP1160830), and UNITAID (4214-LSHTM-Sept15; PO 8477-0-600). Rafael Tabarés-Seisdedos was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. Mihajlo Jakovljevic acknowleges contribution from the Serbian Ministry of Education Science and Technological Development of the Republic of Serbia (grant OI 175 014). Shariful Islam is funded by a Senior Fellowship from Institute for Physical Activity and Nutrition, Deakin University and received career transition grants from High Blood Pressure Research Council of Australia. Sonia Saxena is funded by various grants from the NIHR. Stefanos Tyrovolas was supported by the Foundation for Education and European Culture, the Sara Borrell postdoctoral program (reference number CD15/00019 from the Instituto de Salud Carlos III (ISCIII–Spain) and the Fondos Europeo de Desarrollo Regional. Stefanos was awarded with a 6 months visiting fellowship funding at IHME from M-AES (reference no. MV16/00035 from the Instituto de Salud Carlos III). S Vittal Katikreddi was funded by a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_12017/13 & MC_ UU_12017/15) and the Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15). Traolach S Brugha has received funding from NHS Digital UK to collect data used in this study. The work of Hamid Badali was financially supported by Mazandaran University of Medical Sciences, Sari, Iran. The work of Stefan Lorkowski is funded by the German Federal Ministry of Education and Research (nutriCARD, Grant agreement number 01EA1411A). Mariam Molokhia’s research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We also thank the countless individuals who have contributed to GBD 2016 in various capacities.

Published
2018

15. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Author

Dicker, Daniel, Nguyen, Grant, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abdurahman, Ahmed Abdulahi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Agrawal, Anurag, Ahmadi, Mehdi, Ahmadi, Alireza, Ahmadieh, Hamid, Ahmed, Mohamed Lemine Cheikh brahim, Ahmed, Sayem, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Anlay, Degefaye Zelalem, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Megha, Artaman, Al, Aryal, Krishna K, Asadi-Lari, Mohsen, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Ataro, Zerihun, Atey, Tesfay Mehari Mehari, Athari, Seyyed Shamsadin, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Attia, Engi F, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Awuah, Baffour, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barquera, Simon, Barrero, Lope H, Basaleem, Huda, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Ezra, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Berhane, Adugnaw, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhatia, Eesh, Bhatt, Samir, Bhattarai, Suraj, Bhaumik, Soumyadeeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Bisanzio, Donal, Biswas, Tuhin, Bjørge, Tone, Bleyer, Archie, Basara, Berrak Bora, Bose, Dipan, Bosetti, Cristina, Boufous, Soufiane, Bourne, Rupert, Brady, Oliver J, Bragazzi, Nicola Luigi, Brant, Luisa C, Brazinova, Alexandra, Breitborde, Nicholas J K, Brenner, Hermann, Britton, Gabrielle, Brugha, Traolach, Burke, Kristin E, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Callender, Charlton S K H, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Mate, Cárdenas, Rosario, Carreras, Giulia, Carrero, Juan J, Carter, Austin, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Catalá-López, Ferrán, Çavlin, Alanur, Cerin, Ester, Chaiah, Yazan, Champs, Ana Paula, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chaturvedi, Pankaj, Chen, Wanqing, Chiang, Peggy Pei-Chia, Chimed-Ochir, Odgerel, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Christensen, Hanne, Christopher, Devasahayam J, Chung, Sheng-Chia, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Cohen, Aaron J, Collado-Mateo, Daniel, Constantin, Maria-Magdalena, Conti, Sara, Cooper, Cyrus, Cooper, Leslie Trumbull, Cortesi, Paolo Angelo, Cortinovis, Monica, Cousin, Ewerton, Criqui, Michael H, Cromwell, Elizabeth A, Crowe, Christopher Stephen, Crump, John A, Cucu, Alexandra, Cunningham, Matthew, Daba, Alemneh Kabeta, Dachew, Berihun Assefa, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I, Daryani, Ahmad, Das, Siddharth K, Das Gupta, Rajat, das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, Dayama, Anand, Courten, Barbora de, De la Hoz, Fernando Pio, De leo, Diego, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta T, Deiparine, Selina, Dellavalle, Robert P, Demoz, Gebre Teklemariam, Demtsu, Balem Betsu, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Des Jarlais, Don C, Dessie, Getenet Ayalew, Dey, Subhojit, Dharmaratne, Samath Dhamminda, Dhimal, Meghnath, Ding, Eric L, Djalalinia, Shirin, Doku, David Teye, Dolan, Kate A, Donnelly, Christl A, Dorsey, E Ray, Douwes-Schultz, Dirk, Doyle, Kerrie E, Drake, Thomas M, Driscoll, Tim Robert, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B, Duraes, Andre R, Ebrahimi, Hedyeh, Ebrahimpour, Soheil, Edessa, Dumessa, Edvardsson, David, Eggen, Anne Elise, El Bcheraoui, Charbel, El Sayed Zaki, Maysaa, Elfaramawi, Mohammed, El-Khatib, Ziad, Ellingsen, Christian Lycke, Elyazar, Iqbal R F, Enayati, Ahmadali, Endries, Aman Yesuf Yesuf, Er, Benjamin, Ermakov, Sergey Petrovich, Eshrati, Babak, Eskandarieh, Sharareh, Esmaeili, Reza, Esteghamati, Alireza, Esteghamati, Sadaf, Fakhar, Mahdi, Fakhim, Hamed, Farag, Tamer, Faramarzi, Mahbobeh, Fareed, Mohammad, Farhadi, Farzaneh, Farid, Talha A, Farinha, Carla Sofia e Sá, Farioli, Andrea, Faro, Andre, Farvid, Maryam S, Farzadfar, Farshad, Farzaei, Mohammad Hosein, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Feizy, Fariba, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C, Feyissa, Garumma Tolu, Fijabi, Daniel Obadare, Filip, Irina, Finegold, Samuel, Fischer, Florian, Flor, Luisa Sorio, Foigt, Nataliya A, Ford, John A, Foreman, Kyle J, Fornari, Carla, Frank, Tahvi D, Franklin, Richard Charles, Fukumoto, Takeshi, Fuller, John E, Fullman, Nancy, Fürst, Thomas, Furtado, João M, Futran, Neal D, Galan, Adriana, Gallus, Silvano, Gambashidze, Ketevan, Gamkrelidze, Amiran, Gankpe, Fortune Gbetoho, Garcia-Basteiro, Alberto L, Garcia-Gordillo, Miguel A, Gebre, Teshome, Gebre, Abadi Kahsu, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gelano, Tilayie Feto, Gelaw, Yalemzewod Assefa, Geleijnse, Johanna M, Genova-Maleras, Ricard, Gessner, Bradford D, Getachew, Sefonias, Gething, Peter W, Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Ghiasvand, Hesam, Ghimire, Mamata, Ghoshal, Aloke Gopal, Gill, Paramjit Singh, Gill, Tiffany K, Gillum, Richard F, Giussani, Giorgia, Goenka, Shifalika, Goli, Srinivas, Gomez, Ricardo Santiago, Gomez-Cabrera, Mari Carmen, Gómez-Dantés, Hector, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Goto, Atsushi, Goulart, Alessandra C, Goulart, Bárbara Niegia Garcia, Grada, Ayman, Grosso, Giuseppe, Gugnani, Harish Chander, Guimaraes, Andre Luiz Sena, Guo, Yuming, Gupta, 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Samuel, Ogbo, Felix Akpojene, Oh, In-Hwan, Okoro, Anselm, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olivares, Pedro R, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Sok King, Opio, John Nelson, Oren, Eyal, Ortiz, Justin R, Ortiz, Alberto, Ota, Erika, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa Ojo, Oyekale, Abayomi Samuel, P A, Mahesh, Pacella, Rosana, Pakhale, Smita, Pakhare, Abhijit P, Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Pandey, Achyut Raj, Pandian, Jeyaraj Durai, Parisi, Andrea, Park, Eun-Kee, Parry, Charles D H, Parsian, Hadi, Patel, Shanti, Patle, Ajay, Patten, Scott B, Patton, George C, Paudel, Deepak, Pearce, Neil, Peprah, Emmanuel K, Pereira, Alexandre, Pereira, David M, Perez, Krystle M, Perico, Norberto, Pervaiz, Aslam, Pesudovs, Konrad, Petri, William A, Petzold, Max, Phillips, Michael R, Pigott, David M, Pillay, Julian David, Pirsaheb, Meghdad, Pishgar, Farhad, Plass, Dietrich, Polinder, Suzanne, Pond, Constance Dimity, Popova, Svetlana, Postma, Maarten J, Pourmalek, Farshad, Pourshams, Akram, Poustchi, Hossein, Prabhakaran, Dorairaj, Prakash, V., Prakash, Swayam, Prasad, Narayan, Qorbani, Mostafa, Quistberg, D Alex, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahman, Sajjad ur, Rai, Rajesh Kumar, Rajati, Fatemeh, Rajsic, Sasa, Raju, Sree Bhushan, Ram, Usha, Ranabhat, Chhabi Lal, Ranjan, Prabhat, Ranta, Anna, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E, Razo-García, Christian, Rego, Maria Albertina Santiago, Rehm, Jürgen, Reiner, Robert C, Reinig, Nickola, Reis, Cesar, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Satar, Rezaeian, Shahab, Rezai, Mohammad Sadegh, Riahi, Seyed Mohammad, Ribeiro, Antonio Luiz P, Riojas, Horacio, Rios-Blancas, Maria Jesu, Roba, Kedir Teji, Robinson, Stephen R, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Roshchin, Denis O, Rostami, Ali, Rothenbacher, Dietrich, Rubagotti, Enrico, Ruhago, George Mugambage, Saadat, Soheil, Sabde, Yogesh Damodar, Sachdev, Perminder S, Saddik, Basema, Sadeghi, Ehsan, Moghaddam, Sahar Saeedi, Safari, Hosein, Safari, Yahya, Safari-Faramani, Roya, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salahshoor, Mohamadreza, Salam, Nasir, Salama, Joseph S, Salamati, Payman, Saldanha, Raphael de Freita, Salimi, Yahya, Salimzadeh, Hamideh, Salz, Inbal, Sambala, Evanson Zondani, Samy, Abdallah M, Sanabria, Juan, Sanchez-Niño, Maria Dolore, Santos, Itamar S, Santos, João Vasco, Santric Milicevic, Milena M, Sao Jose, Bruno Piassi, Sardana, Mayank, Sarker, Abdur Razzaque, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Savic, Miloje, Sawant, Arundhati R, Sawhney, Monika, Saxena, Sonia, Sayyah, Mehdi, Scaria, Vinod, Schaeffner, Elke, Schelonka, Kathryn, Schmidt, Maria Inê, Schneider, Ione J C, Schöttker, Ben, Schutte, Aletta Elisabeth, Schwebel, David C, Schwendicke, Falk, Scott, James G, Sekerija, Mario, Sepanlou, Sadaf G, Serván-Mori, Edson, Shabaninejad, Hosein, Shackelford, Katya Anne, Shafieesabet, Azadeh, Shaheen, Amira A, Shaikh, Masood Ali, Shakir, Raad A, Shams-Beyranvand, Mehran, Shamsi, MohammadBagher, Shamsizadeh, Morteza, Sharafi, Heidar, Sharafi, Kiomar, Sharif, Mehdi, Sharif-Alhoseini, Mahdi, Sharma, Meenakshi, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Sheth, Kevin N, Shi, Peilin, Shibuya, Kenji, Shifa, Girma Temam, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shokraneh, Farhad, Shrime, Mark G, Shukla, Sharvari Rahul, Si, Si, Siabani, Soraya, Siddiqi, Tariq J, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silpakit, Nari, Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singam, Narayana Sarma Venkata, Singh, Jasvinder A, Singh, Virendra, Sinha, Anju Pradhan, Sinha, Dhirendra Narain, Sitas, Freddy, Skirbekk, Vegard, Sliwa, Karen, Soares Filho, Adauto Martin, Sobaih, Badr Hasan, Sobhani, Soheila, Soofi, Moslem, Soriano, Joan B, Soyiri, Ireneous N, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Srivastava, Rakesh Kumar, Starodubov, Vladimir I, Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J, Steiner, Caitlyn, Stewart, Leo G, Stokes, Mark A, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Sulo, Gerhard, Sunguya, Bruno F, Sur, Patrick John, Sutradhar, Ipsita, Sykes, Bryan L, Sylaja, P.N., Sylte, Dillon O, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Tadakamadla, Santosh Kumar, Takahashi, Ken, Tandon, Nikhil, Tassew, Aberash Abay, Tassew, Segen Gebremeskel, Tavakkoli, Mohammad, Taveira, Nuno, Tawye, Nega Yimer, Tehrani-Banihashemi, Arash, Tekalign, Tigist Gashaw, Tekle, Merhawi Gebremedhin, Temesgen, Habtamu, Temsah, Mohamad-Hani, Temsah, Omar, Terkawi, Abdullah Sulieman, Teshale, Manaye Yihune, Tessema, Belay, Teweldemedhin, Mebrahtu, Thakur, Jarnail Singh, Thankappan, Kavumpurathu Raman, Thirunavukkarasu, Sathish, Thomas, Laura Anne, Thomas, Nihal, Thrift, Amanda G, Tilahun, Binyam, To, Quyen G, Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Torre, Anna E, Tortajada-Girbés, Miguel, Tovani-Palone, Marcos Roberto, Towbin, Jeffrey A, Tran, Bach Xuan, Tran, Khanh Bao, Tripathi, Suryakant, Tripathy, Srikanth Prasad, Truelsen, Thomas Clement, Truong, Nu Thi, Tsadik, Afewerki Gebremeskel, Tsilimparis, Nikolao, Tudor Car, Lorainne, Tuzcu, E Murat, Tyrovolas, Stefano, Ukwaja, Kingsley Nnanna, Ullah, Irfan, Usman, Muhammad Shariq, Uthman, Olalekan A, Uzun, Selen Begüm, Vaduganathan, Muthiah, Vaezi, Afsane, Vaidya, Gaurang, Valdez, Pascual R, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Vasconcelos, Ana Maria Nogale, Venketasubramanian, Narayanaswamy, Vidavalur, Ramesh, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vujcic, Isidora S, Wagner, Gregory R, Wagnew, Fasil Wagnew Shiferaw, Waheed, Yasir, Wang, Yanping, Wang, Yuan-Pang, Wassie, Molla Mesele, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weiss, Jordan, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Widecka, Katarzyna, Wijeratne, Tissa, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D A, Wondemagegn, Sintayehu Ambachew, Wu, Shouling, Wyper, Grant M A, Xu, Gelin, Yadav, Rajaram, Yakob, Bereket, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Ye, Pengpeng, Yearwood, Jamal A, Yentür, Gökalp Kadri, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, York, Hunter W, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zachariah, Geevar, Zadnik, Vesna, Zafar, Shamsa, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zare, Zohreh, Zeeb, Hajo, Zeleke, Mulugeta Molla, Zenebe, Zerihun Menlkalew, Zerfu, Taddese Alemu, Zhang, Kai, Zhang, Xueying, Zhou, Maigeng, Zhu, Jun, Zodpey, Sanjay, Zucker, Inbar, Zuhlke, Liesl Joanna J, Lopez, Alan D, Gakidou, Emmanuela, and Murray, Christopher J L

Subjects
Child mortality, Alnæmi, Dánartíðni, Heilsufar, GBD, Börn, Dauði, Almennar lyflækningar, Fullorðnir, General & Internal Medicine, parasitic diseases, Psychology, age-specific mortality, Estimating adult mortality, Medicine (all), HIV, 11 Medical And Health Sciences, General Medicine, All-cause mortality, humanities, Countries, Death, mortality, national, Sálfræði, Health, GBD, mortality, Human medicine, Trends
Abstract

The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence no. SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law-2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data., Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing., Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Aging of the National Institutes of Health (award P30AG047845), and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163).

Published
2018

16. Story recall performance and AT classification via positron emission tomography: A comparison of logical memory and Craft Story 21.

Author

Bruno D, Jauregi-Zinkunegi A, Betthauser T, Carlsson C, Bendlin BB, Okonkwo O, Chin NA, Asthana S, Langhough RE, Johnson SC, and Mueller KD

Subjects
Humans, Male, Female, Aged, Middle Aged, Cross-Sectional Studies, Neuropsychological Tests, tau Proteins metabolism, Brain diagnostic imaging, Alzheimer Disease diagnostic imaging, Positron-Emission Tomography methods, Mental Recall physiology
Abstract

Background: Early detection of Alzheimer's disease (AD) is one of the critical components of the global response to the growing dementia crisis. Analysis of serial position performance in story recall tests has yielded sensitive metrics for the prediction of AD at low cost. In this study, we examined whether serial position markers in two story recall tests (the logical memory test, LMT, and the Craft Story 21 test, CST) were sensitive to cross-sectional biomarker-based assessment of in vivo neuropathology., Methods: Participants were selected from the Wisconsin Registry of Alzheimer's Prevention (n = 288; WRAP) and the Alzheimer's Disease Research Center (n = 156; ADRC), both from the University of Wisconsin-Madison. Average age at PET was 68.9 (6.7) and 67.0 (8.0), respectively. Data included tau and PiB PET, and LMT for WRAP participants and CST for ADRC participants. Two sets of Bayesian analyses (logistic regressions and ANCOVAs) were conducted within each cohort, separately., Results: Results indicated that the A+T+ classification was best predicted, cross-sectionally, by the recency ratio (Rr), indexing how much of the end of the story was forgotten between initial learning and delayed assessment. Rr outperformed traditional scores and discriminated between A+T+ and A+T-/A-T-, in both cohorts., Conclusions: Overall, this study confirms that serial position analysis of LMT and CST data, and particularly Rr as an index of recency loss, is a valuable tool for the identification of in vivo tau pathology in individuals free of dementia. Diagnostic considerations are discussed., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Published
2024
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17. CSF dynamics throughout the ventricular system using 4D flow MRI: associations to arterial pulsatility, ventricular volumes, and age.

Author

Vikner T, Johnson KM, Cadman RV, Betthauser TJ, Wilson RE, Chin N, Eisenmenger LB, Johnson SC, and Rivera-Rivera LA

Subjects
Humans, Aged, Middle Aged, Male, Female, Aged, 80 and over, Adult, Aging physiology, Cerebrovascular Circulation physiology, Cerebrospinal Fluid physiology, Cerebrospinal Fluid diagnostic imaging, Magnetic Resonance Imaging methods, Pulsatile Flow physiology, Cerebral Ventricles diagnostic imaging, Cerebral Ventricles physiology
Abstract

Background: Cerebrospinal fluid (CSF) dynamics are increasingly studied in aging and neurological disorders. Models of CSF-mediated waste clearance suggest that altered CSF dynamics could play a role in the accumulation of toxic waste in the CNS, with implications for Alzheimer's disease and other proteinopathies. Therefore, approaches that enable quantitative and volumetric assessment of CSF flow velocities could be of value. In this study we demonstrate the feasibility of 4D flow MRI for simultaneous assessment of CSF dynamics throughout the ventricular system, and evaluate associations to arterial pulsatility, ventricular volumes, and age., Methods: In a cognitively unimpaired cohort (N = 43; age 41-83 years), cardiac-resolved 4D flow MRI CSF velocities were obtained in the lateral ventricles (LV), foramens of Monro, third and fourth ventricles (V3 and V4), the cerebral aqueduct (CA) and the spinal canal (SC), using a velocity encoding (venc) of 5 cm/s. Cerebral blood flow pulsatility was also assessed with 4D flow (venc = 80 cm/s), and CSF volumes were obtained from T1- and T2-weighted MRI. Multiple linear regression was used to assess effects of age, ventricular volumes, and arterial pulsatility on CSF velocities., Results: Cardiac-driven CSF dynamics were observed in all CSF spaces, with region-averaged velocity range and root-mean-square (RMS) velocity encompassing from very low in the LVs (RMS 0.25 ± 0.08; range 0.85 ± 0.28 mm/s) to relatively high in the CA (RMS 6.29 ± 2.87; range 18.6 ± 15.2 mm/s). In the regression models, CSF velocity was significantly related to age in 5/6 regions, to CSF space volume in 2/3 regions, and to arterial pulsatility in 3/6 regions. Group-averaged waveforms indicated distinct CSF flow propagation delays throughout CSF spaces, particularly between the SC and LVs., Conclusions: Our findings show that 4D flow MRI enables assessment of CSF dynamics throughout the ventricular system, and captures independent effects of age, CSF space morphology, and arterial pulsatility on CSF motion., (© 2024. The Author(s).)

Published
2024
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18. Rethinking the residual approach: Leveraging machine learning to operationalize cognitive resilience in Alzheimer's disease.

Author

Birkenbihl C, Cuppels M, Boyle RT, Klinger HM, Langford O, Coughlan GT, Properzi MJ, Chhatwal J, Price JT, Schultz AP, Rentz DM, Amariglio RE, Johnson KA, Gottesman RF, Mukherjee S, Maruff P, Lim YY, Masters CL, Beiser A, Resnick SM, Hughes TM, Burnham S, Tunali I, Landau S, Cohen AD, Johnson SC, Betthauser TJ, Seshadri S, Lockhart SN, O'Bryant SE, Vemuri P, Sperling RA, Hohman TJ, Donohue MC, and Buckley RF

Abstract

Cognitive resilience describes the phenomenon of individuals evading cognitive decline despite prominent Alzheimer's disease neuropathology. Operationalization and measurement of this latent construct is non-trivial as it cannot be directly observed. The residual approach has been widely applied to estimate CR, where the degree of resilience is estimated through a linear model's residuals. We demonstrate that this approach makes specific, uncontrollable assumptions and likely leads to biased and erroneous resilience estimates. We propose an alternative strategy which overcomes the standard approach's limitations using machine learning principles. Our proposed approach makes fewer assumptions about the data and construct to be measured and achieves better estimation accuracy on simulated ground-truth data., Competing Interests: Conflict of interest Paul Maruff is a full-time employee of Cogstate Ltd. Samuel N. Lockhart is a full time employee of Invicro LLC. SCJ has served in the past three years as a consultant to ALZPath and Enigma Biomedical.

Published
2024
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19. Brain aging patterns in a large and diverse cohort of 49,482 individuals.

Author

Yang Z, Wen J, Erus G, Govindarajan ST, Melhem R, Mamourian E, Cui Y, Srinivasan D, Abdulkadir A, Parmpi P, Wittfeld K, Grabe HJ, Bülow R, Frenzel S, Tosun D, Bilgel M, An Y, Yi D, Marcus DS, LaMontagne P, Benzinger TLS, Heckbert SR, Austin TR, Waldstein SR, Evans MK, Zonderman AB, Launer LJ, Sotiras A, Espeland MA, Masters CL, Maruff P, Fripp J, Toga AW, O'Bryant S, Chakravarty MM, Villeneuve S, Johnson SC, Morris JC, Albert MS, Yaffe K, Völzke H, Ferrucci L, Nick Bryan R, Shinohara RT, Fan Y, Habes M, Lalousis PA, Koutsouleris N, Wolk DA, Resnick SM, Shou H, Nasrallah IM, and Davatzikos C

Abstract

Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2024
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20. Alzheimer's disease genetic risk and changes in brain atrophy and white matter hyperintensities in cognitively unimpaired adults.

Author

Soldan A, Wang J, Pettigrew C, Davatzikos C, Erus G, Hohman TJ, Dumitrescu L, Bilgel M, Resnick SM, Rivera-Rivera LA, Langhough R, Johnson SC, Benzinger T, Morris JC, Laws SM, Fripp J, Masters CL, and Albert MS

Abstract

Reduced brain volumes and more prominent white matter hyperintensities on MRI scans are commonly observed among older adults without cognitive impairment. However, it remains unclear whether rates of change in these measures among cognitively normal adults differ as a function of genetic risk for late-onset Alzheimer's disease, including APOE -ɛ4, APOE -ɛ2 and Alzheimer's disease polygenic risk scores (AD-PRS), and whether these relationships are influenced by other variables. This longitudinal study examined the trajectories of regional brain volumes and white matter hyperintensities in relationship to APOE genotypes ( N = 1541) and AD-PRS ( N = 1093) in a harmonized dataset of middle-aged and older individuals with normal cognition at baseline (mean baseline age = 66 years, SD = 9.6) and an average of 5.3 years of MRI follow-up (max = 24 years). Atrophy on volumetric MRI scans was quantified in three ways: (i) a composite score of regions vulnerable to Alzheimer's disease (SPARE-AD); (ii) hippocampal volume; and (iii) a composite score of regions indexing advanced non-Alzheimer's disease-related brain aging (SPARE-BA). Global white matter hyperintensity volumes were derived from fluid attenuated inversion recovery (FLAIR) MRI. Using linear mixed effects models, there was an APOE -ɛ4 gene-dose effect on atrophy in the SPARE-AD composite and hippocampus, with greatest atrophy among ɛ4/ɛ4 carriers, followed by ɛ4 heterozygouts, and lowest among ɛ3 homozygouts and ɛ2/ɛ2 and ɛ2/ɛ3 carriers, who did not differ from one another. The negative associations of APOE - ɛ 4 with atrophy were reduced among those with higher education ( P < 0.04) and younger baseline ages ( P < 0.03). Higher AD-PRS were also associated with greater atrophy in SPARE-AD ( P = 0.035) and the hippocampus ( P = 0.014), independent of APOE -ɛ4 status. APOE -ɛ2 status (ɛ2/ɛ2 and ɛ2/ɛ3 combined) was not related to baseline levels or atrophy in SPARE-AD, SPARE-BA or the hippocampus, but was related to greater increases in white matter hyperintensities ( P = 0.014). Additionally, there was an APOE -ɛ4 × AD-PRS interaction in relation to white matter hyperintensities ( P = 0.038), with greater increases in white matter hyperintensities among APOE -ɛ4 carriers with higher AD-PRS. APOE and AD-PRS associations with MRI measures did not differ by sex. These results suggest that APOE - ɛ 4 and AD-PRS independently and additively influence longitudinal declines in brain volumes sensitive to Alzheimer's disease and synergistically increase white matter hyperintensity accumulation among cognitively normal individuals. Conversely, APOE - ɛ 2 primarily influences white matter hyperintensity accumulation, not brain atrophy. Results are consistent with the view that genetic factors for Alzheimer's disease influence atrophy in a regionally specific manner, likely reflecting preclinical neurodegeneration, and that Alzheimer's disease risk genes contribute to white matter hyperintensity formation., Competing Interests: The following authors declare that they have no competing interests: A.S., J.W., C.P., C.D., G.E., T.J.H., L.D., M.B., S.M.R., L.A.R.-R., R.L., T.B., J.C.M. and J.F. C.L.M. and M.S.A. are advisors to Eli Lilly. S.C.J. has served as an advisor to Roche Diagnostics. S.M.L. is a scientific advisor to Cytox Ltd., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Published
2024
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21. Psychosocial implications of learning amyloid PET results in an observational cohort.

Author

Clark LR, Erickson CM, Chin NA, Basche KE, Ketchum FB, Rosario HL, Peterson AJ, Eveler ML, and Johnson SC

Abstract

Introduction: Information on the psychosocial impact of Alzheimer's disease (AD) biomarker testing in adults at risk of AD is needed to inform best practices for communicating biomarker results., Methods: Ninety-nine cognitively unimpaired older adults learned amyloid positron emission tomography (PET) results (mean age = 72.0 ± 4.8, 95% White, 28% elevated amyloid). Linear mixed-effects regression models were used to test the main effects and interaction of PET result × time on psychosocial outcomes up to 6 months after learning results., Results: A significant interaction of PET result × time was observed for concern about AD (β = 0.28, p = 0.02) and intrusive thoughts and avoidance (β = -0.82, p < 0.001). A main effect of PET result was observed for AD test-related distress (β = 12.09, p < 0.001)., Discussion: Cognitively unimpaired adults learning elevated-amyloid PET results reported mildly intrusive thoughts/avoidance initially following disclosure, but these symptoms decreased over time. Concern about AD dementia and AD biomarker test-related distress remained higher in elevated-amyloid compared to non-elevated-amyloid participants., Highlights: Longitudinal assessment of psychosocial reactions after amyloid PET disclosure was conducted. Transient highly intrusive thoughts or avoidance after learning elevated amyloid results. Persistent test result-related distress after receiving elevated-amyloid results. There is increased concern about AD dementia after receiving elevated-amyloid results. Happiness and relief are experienced after receiving non-elevated-amyloid results., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

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2024
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23. Unraveling diurnal and technical variability in cerebral hemodynamics from neurovascular 4D-Flow MRI.

Author

Rivera-Rivera LA, Roberts GS, Peret A, Langhough RE, Jonaitis EM, Du L, Field A, Eisenmenger L, Johnson SC, and Johnson KM

Subjects
Humans, Male, Female, Aged, Adult, Retrospective Studies, Prospective Studies, Pulse Wave Analysis methods, Young Adult, Middle Aged, Blood Flow Velocity physiology, Aged, 80 and over, Brain diagnostic imaging, Brain blood supply, Brain physiology, Pulsatile Flow physiology, Cerebrovascular Circulation physiology, Magnetic Resonance Imaging methods, Circadian Rhythm physiology, Hemodynamics physiology
Abstract

Neurovascular 4D-Flow MRI enables non-invasive evaluation of cerebral hemodynamics including measures of cerebral blood flow (CBF), vessel pulsatility index (PI), and cerebral pulse wave velocity (PWV). 4D-Flow measures have been linked to various neurovascular disorders including small vessel disease and Alzheimer's disease; however, physiological and technical sources of variability are not well established. Here, we characterized sources of diurnal physiological and technical variability in cerebral hemodynamics using 4D-Flow in a retrospective study of cognitively unimpaired older adults (N = 750) and a prospective study of younger adults (N = 10). Younger participants underwent repeated MRI sessions at 7am, 4 pm, and 10 pm. In the older cohort, having an MRI earlier on the day was significantly associated with higher CBF and lower PI. In prospective experiments, time of day significantly explained variability in CBF and PI; however, not in PWV. Test-retest experiments showed high CBF intra-session repeatability (repeatability coefficient (RPC) =7.2%), compared to lower diurnal repeatability (RPC = 40%). PI and PWV displayed similar intra-session and diurnal variability (PI intra-session RPC = 22%, RPC = 24% 7am vs 4 pm; PWV intra-session RPC = 17%, RPC = 21% 7am vs 4 pm). Overall, CBF measures showed low technical variability, supporting diurnal variability is from physiology. PI and PWV showed higher technical variability but less diurnal variability., Competing Interests: Declaration of conflicting interestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: S.C. Johnson served on an advisory board for Roche Diagnostics in 2018 for which he received an honorarium and is principal investigator of an equipment grant from Roche. He conducts tau imaging in NIH funded studies as well as a study funded by Cerveau Technologies using radioligand precursor material supplied by Cerveau Technologies.

Published
2024
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24. KLOTHO KL-VS heterozygosity is associated with diminished age-related neuroinflammation, neurodegeneration, and synaptic dysfunction in older cognitively unimpaired adults.

Author

Driscoll IF, Lose S, Ma Y, Bendlin BB, Gallagher C, Johnson SC, Asthana S, Hermann B, Sager MA, Blennow K, Zetterberg H, Carlsson C, Kollmorgen G, Quijano-Rubio C, Dubal D, and Okonkwo OC

Subjects
Humans, Female, Male, Middle Aged, Aged, Glucuronidase genetics, Glucuronidase cerebrospinal fluid, Interleukin-6 cerebrospinal fluid, Interleukin-6 genetics, Receptors, Immunologic genetics, Neuroinflammatory Diseases genetics, Neuroinflammatory Diseases cerebrospinal fluid, S100 Calcium Binding Protein beta Subunit cerebrospinal fluid, S100 Calcium Binding Protein beta Subunit genetics, Cohort Studies, Glial Fibrillary Acidic Protein cerebrospinal fluid, Glial Fibrillary Acidic Protein genetics, Alzheimer Disease cerebrospinal fluid, Alzheimer Disease genetics, alpha-Synuclein cerebrospinal fluid, alpha-Synuclein genetics, Neurogranin cerebrospinal fluid, Neurogranin genetics, Membrane Glycoproteins, Klotho Proteins, Biomarkers cerebrospinal fluid, Aging genetics, Chitinase-3-Like Protein 1 cerebrospinal fluid, Chitinase-3-Like Protein 1 genetics, Heterozygote
Abstract

Introduction: We examined whether the aging suppressor KLOTHO gene's functionally advantageous KL-VS variant (KL-VS heterozygosity [KL-VS HET ]) confers resilience against deleterious effects of aging indexed by cerebrospinal fluid (CSF) biomarkers of neuroinflammation (interleukin-6 [IL-6], S100 calcium-binding protein B [S100B], triggering receptor expressed on myeloid cells [sTREM2], chitinase-3-like protein 1 [YKL-40], glial fibrillary acidic protein [GFAP]), neurodegeneration (total α-synuclein [α-Syn], neurofilament light chain protein), and synaptic dysfunction (neurogranin [Ng])., Methods: This Alzheimer disease risk-enriched cohort consisted of 454 cognitively unimpaired adults (M age  = 61.5 ± 7.75). Covariate-adjusted multivariate regression examined relationships between age (mean-split[age ≥ 62]) and CSF biomarkers (Roche/NeuroToolKit), and whether they differed between KL-VS HET (N = 122) and non-carriers (KL-VS NC ; N = 332)., Results: Older age was associated with a poorer biomarker profile across all analytes (Ps ≤ 0.03). In age-stratified analyses, KL-VS NC exhibited this same pattern (Ps ≤ 0.05) which was not significant for IL-6, S100B, Ng, and α-Syn (Ps ≥ 0.13) in KL-VS HET . Although age-related differences in GFAP, sTREM2, and YKL-40 were evident for both groups (Ps ≤ 0.01), the effect magnitude was markedly stronger for KL-VS NC ., Discussion: Higher levels of neuroinflammation, neurodegeneration, and synaptic dysfunction in older adults were attenuated in KL-VS HET ., Highlights: Older age was associated with poorer profiles across all cerebrospinal fluid biomarkers of neuroinflammation, neurodegeneration, and synaptic dysfunction. KLOTHO KL-VS non-carriers exhibit this same pattern, which is does not significantly differ between younger and older KL-VS heterozygotes for interleukin-6, S100 calcium-binding protein B, neurogranin, and total α-synuclein. Although age-related differences in glial fibrillary acidic protein, triggering receptor expressed on myeloid cells, and chitinase-3-like protein 1 are evident for both KL-VS groups, the magnitude of the effect is markedly stronger for KL-VS non-carriers. Higher levels of neuroinflammation, neurodegeneration, and synaptic dysfunction in older adults are attenuated in KL-VS heterozygotes., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Published
2024
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25. Konectom™ cognitive processing speed test enables reliable remote, unsupervised cognitive assessment in people with multiple sclerosis: Exploring the use of substitution time as a novel digital outcome measure.

Author

Scaramozza M, Chiesa PA, Zajac L, Sun Z, Tang M, Juraver A, Bartholomé E, Charré-Morin J, Saubusse A, Johnson SC, Brochet B, Carment L, Ruiz M, Campbell N, and Ruet A

Subjects
Humans, Adult, Male, Female, Middle Aged, Reproducibility of Results, Young Adult, Adolescent, Smartphone, Psychomotor Performance physiology, Outcome Assessment, Health Care, Cognition physiology, Processing Speed, Multiple Sclerosis physiopathology, Multiple Sclerosis complications, Multiple Sclerosis diagnosis, Neuropsychological Tests standards, Cognitive Dysfunction diagnosis, Cognitive Dysfunction etiology, Cognitive Dysfunction physiopathology
Abstract

Background: The Konectom™ smartphone-based cognitive processing speed (CPS) test is designed to assess processing speed and account for impact of visuomotor function on performance., Objective: Evaluate reliability and validity of Konectom CPS Test, performed in clinic and remotely., Methods: Data were collected from people with multiple sclerosis (PwMS) aged 18-64 years and healthy control participants (HC) matched for age, sex, and education. Remote test-retest reliability (intraclass correlation coefficients, ICC); correlation with established clinical measures (Spearman correlation coefficients); group analyses between cognitively impaired/unimpaired PwMS; and influence of age, sex, education, and upper limb motor function on CPS Test measures were assessed., Results: Eighty PwMS and 66 HC participated. CPS Test measures from remote tests had good test-retest reliability (ICC of 0.67-0.87) and correlated with symbol digit modalities test (highest |ρ| = 0.80, p < 0.0001). Remote measures were stable (change from baseline < 5%) and correlated with MS disability (highest |ρ| = 0.39, p = 0.0004) measured by Expanded Disability Status Scale. CPS Test measures displayed sensitivity to cognitive impairment (highest d = 1.47). Demographics and motor function had the lowest impact on CPS Test substitution time, a measure accounting for visuomotor function., Conclusion: Konectom CPS Test measures provide valid, reliable remote measurements of cognitive processing speed in PwMS., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: MS, MR, ZS: employees of and may hold stock in Biogen. LZ, MT, EB, NC, PAC, AJ: former employees of and may hold stock in Biogen. BB: honoraria for advisory boards for Biogen, Genzyme, Merck-Serono, Novartis, and Roche; his institution (Groupe Hospitalier Pellegrin) received support for clinical trials and research activities from Actelion, Bayer HealthCare, Biogen, Genzyme, Merck-Serono, MedDay, Novartis, Roche, and Teva. LC: study funding from Biogen. AR: scientific advisory boards of Biogen and Merck; travel or speaker honoraria from Alexion, Biogen, Merck, Novartis, Roche, and Sanofi-Genzyme; institution received research support from Biogen, Roche, and Sanofi-Genzyme. The remaining authors had nothing to disclose.

Published
2024
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26. Evaluating Life Simple Seven's influence on brain health outcomes: The intersection of lifestyle and dementia.

Author

Denier-Fields DN, Gangnon RE, Rivera-Rivera LA, Betthauser TJ, Bendlin BB, Johnson SC, and Engelman CD

Abstract

Introduction: Lifestyle factors have been studied for dementia risk, but few have comprehensively assessed both Alzheimer's disease (AD) and cerebrovascular disease (CBVD) pathologies. Our research aims to determine the relationships between lifestyle and various dementia pathologies, challenging conventional research paradigms., Methods: Analyzing 1231 Wisconsin Registry for Alzheimer's Prevention (WRAP) study participants, we focused on Life Simple Seven (LS7) score calculations from questionnaire data and clinical vitals. We assessed brain health indicators including CBVD, AD, and cognition., Results: Higher LS7 scores were associated with better CBVD outcomes, including lower percent white matter hyperintensities and higher cerebral blood flow, and higher Preclinical Alzheimer's Composite 3 and Delayed Recall scores. No significant associations were observed between LS7 scores and AD markers of amyloid and tau accumulation., Discussion: This study provides evidence that the beneficial effects of LS7 on cognition are primarily mediated through cerebrovascular pathways rather than direct influences on AD pathology.

Published
2024
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27. Harmonizing tau positron emission tomography in Alzheimer's disease: The CenTauR scale and the joint propagation model.

Author

Leuzy A, Raket LL, Villemagne VL, Klein G, Tonietto M, Olafson E, Baker S, Saad ZS, Bullich S, Lopresti B, Bohorquez SS, Boada M, Betthauser TJ, Charil A, Collins EC, Collins JA, Cullen N, Gunn RN, Higuchi M, Hostetler E, Hutchison RM, Iaccarino L, Insel PS, Irizarry MC, Jack CR Jr, Jagust WJ, Johnson KA, Johnson SC, Karten Y, Marquié M, Mathotaarachchi S, Mintun MA, Ossenkoppele R, Pappas I, Petersen RC, Rabinovici GD, Rosa-Neto P, Schwarz CG, Smith R, Stephens AW, Whittington A, Carrillo MC, Pontecorvo MJ, Haeberlein SB, Dunn B, Kolb HC, Sivakumaran S, Rowe CC, Hansson O, and Doré V

Abstract

Introduction: Tau-positron emission tomography (PET) outcome data of patients with Alzheimer's disease (AD) cannot currently be meaningfully compared or combined when different tracers are used due to differences in tracer properties, instrumentation, and methods of analysis., Methods: Using head-to-head data from five cohorts with tau PET radiotracers designed to target tau deposition in AD, we tested a joint propagation model (JPM) to harmonize quantification (units termed "CenTauR" [CTR]). JPM is a statistical model that simultaneously models the relationships between head-to-head and anchor point data. JPM was compared to a linear regression approach analogous to the one used in the amyloid PET Centiloid scale., Results: A strong linear relationship was observed between CTR values across brain regions. Using the JPM approach, CTR estimates were similar to, but more accurate than, those derived using the linear regression approach., Discussion: Preliminary findings using the JPM support the development and adoption of a universal scale for tau-PET quantification., Highlights: Tested a novel joint propagation model (JPM) to harmonize quantification of tau PET. Units of common scale are termed "CenTauRs". Tested a Centiloid-like linear regression approach. Using five cohorts with head-to-head tau PET, JPM outperformed linearregressionbased approach. Strong linear relationship was observed between CenTauRs values across brain regions., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Published
2024
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29. Longitudinal plasma phosphorylated-tau217 and other related biomarkers in a non-demented Alzheimer's risk-enhanced sample.

Author

Du L, Langhough RE, Wilson RE, Reyes RER, Hermann BP, Jonaitis EM, Betthauser TJ, Chin NA, Christian B, Chaby L, Jeromin A, Molfetta GD, Brum WS, Arslan B, Ashton N, Blennow K, Zetterberg H, and Johnson SC

Abstract

Introduction: Understanding longitudinal change in key plasma biomarkers will aid in detecting presymptomatic Alzheimer's disease (AD)., Methods: Serial plasma samples from 424 Wisconsin Registry for Alzheimer's Prevention participants were analyzed for phosphorylated-tau217 (p-tau217; ALZpath) and other AD biomarkers, to study longitudinal trajectories in relation to disease, health factors, and cognitive decline. Of the participants, 18.6% with known amyloid status were amyloid positive (A+); 97.2% were cognitively unimpaired (CU)., Results: In the CU, amyloid-negative (A-) subset, plasma p-tau217 levels increased modestly with age but were unaffected by body mass index and kidney function. In the whole sample, average p-tau217 change rates were higher in those who were A+ (e.g., simple slopes(se) for A+ and A- at age 60 were 0.232(0.028) and 0.038(0.013))). High baseline p-tau217 levels predicted faster preclinical cognitive decline., Discussion: p-tau217 stands out among markers for its strong association with disease and cognitive decline, indicating its potential for early AD detection and monitoring progression., Highlights: Phosphorylated-tau217 (p-tau217) trajectories were significantly different in people who were known to be amyloid positive. Subtle age-related trajectories were seen for all the plasma markers in amyloid-negative cognitively unimpaired. Kidney function and body mass index were not associated with plasma p-tau217 trajectories. Higher plasma p-tau217 was associated with faster preclinical cognitive decline., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Published
2024
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30. Exploring the impact of music on response to ketamine/esketamine: A scoping review.

Author

Kheirkhah M, Nugent AC, Livinski AA, Neely L, Johnson SC, Henter ID, Varnosfaderani SD, Price RB, Hejazi N, Yavi M, Jamalabadi H, Javaheripour N, Walter M, and Zarate CA Jr

Subjects
Humans, Anesthetics, Dissociative administration & dosage, Anesthetics, Dissociative therapeutic use, Depression drug therapy, Depression therapy, Pain Management, Ketamine administration & dosage, Ketamine therapeutic use, Music Therapy
Abstract

Music and ketamine are both known to affect therapeutic outcomes, but few studies have investigated their co-administration. This scoping review describes the existing literature on the joint use of music and ketamine-or esketamine (the S(+) enantiomer of ketamine)-in humans. The review considers that extant studies have explored the intersection of ketamine/esketamine and music in healthy volunteers and in patients of various age groups, at different dosages, through different treatment processes, and have varied the sequence of playing music relative to ketamine/esketamine administration. Studies investigating the use of music during ketamine anesthesia are also included in the review because anesthesia and sedation were the early drivers of ketamine use. Studies pertaining to recreational ketamine use were omitted. The review was limited to articles published in the English language but not restricted by publication year. To the best of our knowledge, this scoping review is the first comprehensive exploration of the interplay between music and ketamine/esketamine and offers valuable insights to researchers interested in designing future studies., Competing Interests: Declaration of Competing Interest Dr. Carlos A. Zarate Jr, is listed as a co-inventor on a patent for the use of ketamine in major depression and suicidal ideation; as a co-inventor on a patent for the use of (2 R,6 R)-hydroxynorketamine, (S)-dehydronorketamine, and other stereoisomeric dehydroxylated and hydroxylated metabolites of (R,S)-ketamine metabolites in the treatment of depression and neuropathic pain; and as a co-inventor on a patent application for the use of (2 R,6 R)-hydroxynorketamine and (2 S,6 S)-hydroxynorketamine in the treatment of depression, anxiety, anhedonia, suicidal ideation, and post-traumatic stress disorders. He has assigned his patent rights to the U.S. government but will share a percentage of any royalties that may be received by the government. All other authors have no conflict of interest to disclose, financial or otherwise., (Published by Elsevier Ltd.)

Published
2024
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31. Climate change can impair bacterial pathogen defences in sablefish via hypoxia-mediated effects on adaptive immunity.

Author

Leeuwis RHJ, Hall JR, Zanuzzo FS, Smith N, Clow KA, Kumar S, Vasquez I, Goetz FW, Johnson SC, Rise ML, Santander J, and Gamperl AK

Subjects
Animals, Hypoxia immunology, Immunity, Innate, Immunoglobulin M blood, Immunoglobulin M immunology, Fishes immunology, Fishes microbiology, Oxygen metabolism, Gram-Negative Bacterial Infections immunology, Antigens, Bacterial immunology, Adaptive Immunity, Climate Change, Aeromonas salmonicida immunology, Aeromonas salmonicida physiology, Fish Diseases immunology, Fish Diseases microbiology
Abstract

Low-oxygen levels (hypoxia) in aquatic habitats are becoming more common because of global warming and eutrophication. However, the effects on the health/disease status of fishes, the world's largest group of vertebrates, are unclear. Therefore, we assessed how long-term hypoxia affected the immune function of sablefish, an ecologically and economically important North Pacific species, including the response to a formalin-killed Aeromonas salmonicida bacterin. Sablefish were held at normoxia or hypoxia (100% or 40% air saturated seawater, respectively) for 6-16 weeks, while we measured a diverse array of immunological traits. Given that the sablefish is a non-model organism, this involved the development of a species-specific methodological toolbox comprised of qPCR primers for 16 key immune genes, assays for blood antibacterial defences, the assessment of blood immunoglobulin (IgM) levels with ELISA, and flow cytometry and confocal microscopy techniques. We show that innate immune parameters were typically elevated in response to the bacterial antigens, but were not substantially affected by hypoxia. In contrast, hypoxia completely prevented the ∼1.5-fold increase in blood IgM level that was observed under normoxic conditions following bacterin exposure, implying a serious impairment of adaptive immunity. Since the sablefish is naturally hypoxia tolerant, our results demonstrate that climate change-related deoxygenation may be a serious threat to the immune competency of fishes., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Published
2024
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33. Four-dimensional flow MRI for quantitative assessment of cerebrospinal fluid dynamics: Status and opportunities.

Author

Rivera-Rivera LA, Vikner T, Eisenmenger L, Johnson SC, and Johnson KM

Subjects
Humans, Animals, Hydrodynamics, Cerebrovascular Circulation physiology, Rheology, Cerebrospinal Fluid diagnostic imaging, Cerebrospinal Fluid physiology, Magnetic Resonance Imaging, Imaging, Three-Dimensional
Abstract

Neurological disorders can manifest with altered neurofluid dynamics in different compartments of the central nervous system. These include alterations in cerebral blood flow, cerebrospinal fluid (CSF) flow, and tissue biomechanics. Noninvasive quantitative assessment of neurofluid flow and tissue motion is feasible with phase contrast magnetic resonance imaging (PC MRI). While two-dimensional (2D) PC MRI is routinely utilized in research and clinical settings to assess flow dynamics through a single imaging slice, comprehensive neurofluid dynamic assessment can be limited or impractical. Recently, four-dimensional (4D) flow MRI (or time-resolved three-dimensional PC with three-directional velocity encoding) has emerged as a powerful extension of 2D PC, allowing for large volumetric coverage of fluid velocities at high spatiotemporal resolution within clinically reasonable scan times. Yet, most 4D flow studies have focused on blood flow imaging. Characterizing CSF flow dynamics with 4D flow (i.e., 4D CSF flow) is of high interest to understand normal brain and spine physiology, but also to study neurological disorders such as dysfunctional brain metabolite waste clearance, where CSF dynamics appear to play an important role. However, 4D CSF flow imaging is challenged by the long T1 time of CSF and slower velocities compared with blood flow, which can result in longer scan times from low flip angles and extended motion-sensitive gradients, hindering clinical adoption. In this work, we review the state of 4D CSF flow MRI including challenges, novel solutions from current research and ongoing needs, examples of clinical and research applications, and discuss an outlook on the future of 4D CSF flow., (© 2023 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Published
2024
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34. Post-GWAS multiomic functional investigation of the TNIP1 locus in Alzheimer's disease highlights a potential role for GPX3.

Author

Panyard DJ, Reus LM, Ali M, Liu J, Deming YK, Lu Q, Kollmorgen G, Carboni M, Wild N, Visser PJ, Bertram L, Zetterberg H, Blennow K, Gobom J, Western D, Sung YJ, Carlsson CM, Johnson SC, Asthana S, Cruchaga C, Tijms BM, Engelman CD, and Snyder MP

Subjects
Aged, Aged, 80 and over, Female, Humans, Male, Amyloid beta-Peptides cerebrospinal fluid, Biomarkers cerebrospinal fluid, DNA-Binding Proteins genetics, Polymorphism, Single Nucleotide genetics, Proteomics, Alzheimer Disease genetics, Alzheimer Disease cerebrospinal fluid, Genome-Wide Association Study, Glutathione Peroxidase genetics, Glutathione Peroxidase cerebrospinal fluid, tau Proteins cerebrospinal fluid, tau Proteins genetics
Abstract

Introduction: Recent genome-wide association studies (GWAS) have reported a genetic association with Alzheimer's disease (AD) at the TNIP1/GPX3 locus, but the mechanism is unclear., Methods: We used cerebrospinal fluid (CSF) proteomics data to test (n = 137) and replicate (n = 446) the association of glutathione peroxidase 3 (GPX3) with CSF biomarkers (including amyloid and tau) and the GWAS-implicated variants (rs34294852 and rs871269)., Results: CSF GPX3 levels decreased with amyloid and tau positivity (analysis of variance P = 1.5 × 10 -5 ) and higher CSF phosphorylated tau (p-tau) levels (P = 9.28 × 10 -7 ). The rs34294852 minor allele was associated with decreased GPX3 (P = 0.041). The replication cohort found associations of GPX3 with amyloid and tau positivity (P = 2.56 × 10 -6 ) and CSF p-tau levels (P = 4.38 × 10 -9 )., Discussion: These results suggest variants in the TNIP1 locus may affect the oxidative stress response in AD via altered GPX3 levels., Highlights: Cerebrospinal fluid (CSF) glutathione peroxidase 3 (GPX3) levels decreased with amyloid and tau positivity and higher CSF phosphorylated tau. The minor allele of rs34294852 was associated with lower CSF GPX3. levels when also controlling for amyloid and tau category. GPX3 transcript levels in the prefrontal cortex were lower in Alzheimer's disease than controls. rs34294852 is an expression quantitative trait locus for GPX3 in blood, neutrophils, and microglia., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Published
2024
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35. Association of neighborhood disadvantage with cognitive function and cortical disorganization in an unimpaired cohort.

Author

Safai A, Jonaitis E, Langhough RE, Buckingha WR, Johnson SC, Powell WR, Kind AJH, Bendlin BB, and Tiwari P

Abstract

Objective: Neighborhood disadvantage is associated with worse health and cognitive outcomes. Morphological similarity network (MSN) is a promising approach to elucidate cortical network patterns underlying complex cognitive functions. We hypothesized that MSNs could capture intricate changes in cortical patterns related to neighborhood disadvantage and cognitive function, potentially explaining some of the risk for later life cognitive impairment among individuals who live in disadvantaged contexts., Methods: This cross-sectional study included cognitively unimpaired participants (n=524, age=62.96±8.377, gender (M:F)=181:343, ADI(L:H) =450,74) from the Wisconsin Alzheimer's Disease Research Center or Wisconsin Registry for Alzheimer's Prevention. Neighborhood disadvantage status was obtained using the Area Deprivation Index (ADI). Cognitive performance was assessed through six tests evaluating memory, executive functioning, and the modified preclinical Alzheimer's cognitive composite (mPACC). Morphological Similarity Networks (MSN) were constructed for each participant based on the similarity in distribution of cortical thickness of brain regions, followed by computation of local and global network features. We used linear regression to examine ADI associations with cognitive scores and MSN features. The mediating effect of MSN features on the relationship between ADI and cognitive performance was statistically assessed., Results: Neighborhood disadvantage showed negative association with category fluency, implicit learning speed, story recall and mPACC scores, indicating worse cognitive function among those living in more disadvantaged neighborhoods. Local network features of frontal and temporal brain regions differed based on ADI status. Centrality of left lateral orbitofrontal region showed a partial mediating effect between association of neighborhood disadvantage and story recall performance., Conclusion: Our findings suggest differences in local cortical organization by neighborhood disadvantage, which also partially mediated the relationship between ADI and cognitive performance, providing a possible network-based mechanism to, in-part, explain the risk for poor cognitive functioning associated with disadvantaged neighborhoods. Future work will examine the exposure to neighborhood disadvantage on structural organization of the brain.

Published
2024

36. Prediction of future cognitive decline among cognitively unimpaired individuals using measures of soluble phosphorylated tau or tau tangle pathology.

Author

Ossenkoppele R, Salvadó G, Janelidze S, Binette AP, Bali D, Karlsson L, Palmqvist S, Mattsson-Carlgren N, Stomrud E, Therriault J, Rahmouni N, Rosa-Neto P, Coomans EM, van de Giessen E, van der Flier WM, Teunissen CE, Jonaitis EM, Johnson SC, Villeneuve S, Benzinger TLS, Schindler SE, Bateman RJ, Doecke JD, Doré V, Feizpour A, Masters CL, Rowe C, Wiste HJ, Petersen RC, Jack CR Jr, and Hansson O

Abstract

Plasma p-tau217 and Tau-PET are strong prognostic biomarkers in Alzheimer's disease (AD), but their relative performance in predicting future cognitive decline among cognitively unimpaired (CU) individuals is unclear. In this head-to-head comparison study including 9 cohorts and 1534 individuals, we found that plasma p-tau217 and medial temporal lobe Tau-PET signal showed similar associations with cognitive decline on a global cognitive composite test (R 2 PET =0.32 vs R 2 PLASMA =0.32, p difference =0.812) and with progression to mild cognitive impairment (Hazard ratio[HR] PET =1.56[1.43-1.70] vs HR PLASMA =1.63[1.50-1.77], p difference =0.627). Combined plasma and PET models were superior to the single biomarker models (R 2 =0.36, p<0.01). Furthermore, sequential selection using plasma p-tau217 and then Tau-PET reduced the number of participants required for a clinical trial by 94%, compared to a 75% reduction when using plasma p-tau217 alone. We conclude that plasma p-tau217 and Tau-PET showed similar performance for predicting future cognitive decline in CU individuals, and their sequential use (i.e., plasma p-tau217 followed by Tau-PET in a subset with high plasma p-tau217) is useful for screening in clinical trials in preclinical AD., Competing Interests: DECLARATION OF INTERESTS R.O. has received research support from Avid Radiopharmaceuticals, Janssen Research & Development, Roche, Quanterix and Optina Diagnostics. He has given lectures in symposia sponsored by GE Healthcare and serves on advisory boards for Asceneuron and Bristol Myers Squibb. SP has acquired research support (for the institution) from ki elements / ADDF and Avid. In the past 2 years, he has received consultancy/speaker fees from Bioartic, Biogen, Esai, Lilly, and Roche. Research programs of WF have been funded by ZonMW, NWO, EU-JPND, EU-IHI, Alzheimer Nederland, Hersenstichting CardioVascular Onderzoek Nederland, Health~Holland, Topsector Life Sciences & Health, stichting Dioraphte, Gieskes-Strijbis fonds, stichting Equilibrio, Edwin Bouw fonds, Pasman stichting, stichting Alzheimer & Neuropsychiatrie Foundation, Philips, Biogen MA Inc, Novartis-NL, Life-MI, AVID, Roche BV, Fujifilm, Eisai, Combinostics. WF holds the Pasman chair. WF is recipient of ABOARD, which is a public-private partnership receiving funding from ZonMW (#73305095007) and Health~Holland, Topsector Life Sciences & Health (PPP-allowance; #LSHM20106). WF is recipient of TAP-dementia (www.tap-dementia.nl), receiving funding from ZonMw (#10510032120003) in the context of Onderzoeksprogramma Dementie, part of the Dutch National Dementia Strategy. TAP-dementia receives co-financing from Avid Radiopharmaceuticals and Amprion. Gieskes-Strijbis fonds also contributes to TAP-dementia. WF has been an invited speaker at Biogen MA Inc, Danone, Eisai, WebMD Neurology (Medscape), NovoNordisk, Springer Healthcare, European Brain Council. WF is consultant to Oxford Health Policy Forum CIC, Roche, Biogen MA Inc, and Eisai. WF participated in advisory boards of Biogen MA Inc, Roche, and Eli Lilly. WF is member of the steering committee of EVOKE/EVOKE+ (NovoNordisk). All funding is paid to her institution. WF is member of the steering committee of PAVE, and Think Brain Health. WF was associate editor of Alzheimer, Research & Therapy in 2020/2021. WF is associate editor at Brain. EvdG has performed contract research for Heuron Inc. and Roche. EvdG has a consultancy agreement with IXICO and Life Molecular Imaging for reading PET scans. CET has research contracts with Acumen, ADx Neurosciences, AC-Immune, Alamar, Aribio, Axon Neurosciences, Beckman-Coulter, BioConnect, Bioorchestra, Brainstorm Therapeutics, Celgene, Cognition Therapeutics, EIP Pharma, Eisai, Eli Lilly, Fujirebio, Instant Nano Biosensors, Novo Nordisk, Olink, PeopleBio, Quanterix, Roche, Toyama, Vivoryon. She is editor in chief of Alzheimer Research and Therapy, and serves on editorial boards of Medidact Neurologie/Springer, and Neurology: Neuroimmunology & Neuroinflammation. She had consultancy/speaker contracts for Eli Lilly, Merck, Novo Nordisk, Olink and Roche. SES has served as a consultant to Eisai and Novo Nordisk and has received speaker fees from Eli Lilly and Medscape. She has analyzed biomarker data provided by C2N Diagnostics. JT has served as a consultant for the Neurotorium educational platform and for Alzheon. PR-N has served at scientific advisory boards and/or as a consultant for Roche, Novo Nordisk, Eisai, and Cerveau radiopharmaceuticals. CCR has received research grants from NHMRC, Enigma Australia, Biogen, Eisai and Abbvie. He is on the scientific advisory board for Enigma/Mellieur Technologies and has consulted for Prothena, Eisai, Roche, and Biogen Australia. RJB laboratory research funding from the National Institutes of Health, Alzheimer’s Association, BrightFocus Foundation, Rainwater Foundation, Association for Frontotemporal Degeneration FTD Biomarkers Initiative, Avid Radiopharmaceuticals, Janssen, Tau Consortium, Novartis, Centene Corporation, Association for Frontotemporal Degeneration, the Cure Alzheimer’s Fund, Coins for Alzheimer’s Research Trust Fund, The Foundation for Barnes-Jewish Hospital, Good Ventures Foundation, DIAN-TU Pharma Consortium, Tau SILK Consortium (AbbVie, Biogen, Eli Lilly, and an anonymous organization), the NfL Consortium (AbbVie, Biogen, Bristol Meyers Squibb, Hoffman La Roche), and the Tracy Family SILQ Center; having equity ownership interest in C2N Diagnostics and receiving income based on technology licensed by Washington University to C2N Diagnostics; and receiving income from C2N Diagnostics for serving on the scientific advisory board. OH has acquired research support (for the institution) from AVID Radiopharmaceuticals, Biogen, C2N Diagnostics, Eli Lilly, Eisai, Fujirebio, GE Healthcare, and Roche. In the past 2 years, he has received consultancy/speaker fees from AC Immune, Alzpath, BioArctic, Biogen, Bristol Meyer Squibb, Cerveau, Eisai, Eli Lilly, Fujirebio, Merck, Novartis, Novo Nordisk, Roche, Sanofi and Siemens. SCJ has served in the past two years on advisory boards for Enigma Biomedical and ALZPath. The other authors report no competing interests.

Published
2024
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37. Sex, racial, and APOE -ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer's disease.

Author

Peterson A, Sathe A, Zaras D, Yang Y, Durant A, Deters KD, Shashikumar N, Pechman KR, Kim ME, Gao C, Khairi NM, Li Z, Yao T, Huo Y, Dumitrescu L, Gifford KA, Wilson JE, Cambronero F, Risacher SL, Beason-Held LL, An Y, Arfanakis K, Erus G, Davatzikos C, Tosun D, Toga AW, Thompson PM, Mormino EC, Zhang P, Schilling K, Albert M, Kukull W, Biber SA, Landman BA, Johnson SC, Schneider J, Barnes LL, Bennett DA, Jefferson AL, Resnick SM, Saykin AJ, Hohman TJ, and Archer DB

Abstract

Introduction: The effects of sex, race, and Apolipoprotein E ( APOE ) - Alzheimer's disease (AD) risk factors - on white matter integrity are not well characterized., Methods: Diffusion MRI data from nine well-established longitudinal cohorts of aging were free-water (FW)-corrected and harmonized. This dataset included 4,702 participants (age=73.06 ± 9.75) with 9,671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FA FWcorr ) were used to assess differences in white matter microstructure by sex, race, and APOE -ε4 carrier status., Results: Sex differences in FA FWcorr in association and projection tracts, racial differences in FA FWcorr in projection tracts, and APOE -ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced., Discussion: There are prominent differences in white matter microstructure by sex, race, and APOE -ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted., Competing Interests: SCJ has served on advisory boards for Enigma Biomedical and ALZPath in the past two years. AJS receives support from multiple NIH grants (P30 AG010133, P30 AG072976, R01 AG019771, R01 AG057739, U19 AG024904, R01 LM013463, R01 AG068193, T32 AG071444, U01 AG068057, U01 AG072177, U19 AG074879, and U24 AG074855). He has also received support from Avid Radiopharmaceuticals, a subsidiary of Eli Lilly (in kind contribution of PET tracer precursor) and participated in Scientific Advisory Boards (Bayer Oncology, Eisai, Novo Nordisk, and Siemens Medical Solutions USA, Inc) and an Observational Study Monitoring Board (MESA, NIH NHLBI), as well as External Advisory Committees for multiple NIA grants. He also serves as Editor-in-Chief of Brain Imaging and Behavior, a Springer-Nature Journal.

Published
2024
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38. Characterizing brain tau and cognitive decline along the amyloid timeline in Alzheimer's disease.

Author

Cody KA, Langhough RE, Zammit MD, Clark L, Chin N, Christian BT, Betthauser TJ, and Johnson SC

Subjects
Humans, Aged, Male, Female, Aged, 80 and over, Neurofibrillary Tangles pathology, Neurofibrillary Tangles metabolism, Disease Progression, Aniline Compounds, Cohort Studies, Amyloid beta-Peptides metabolism, Middle Aged, Longitudinal Studies, Thiazoles, Neuropsychological Tests, Amyloid metabolism, Alzheimer Disease metabolism, Alzheimer Disease diagnostic imaging, Alzheimer Disease pathology, tau Proteins metabolism, Positron-Emission Tomography methods, Cognitive Dysfunction metabolism, Cognitive Dysfunction diagnostic imaging, Cognitive Dysfunction pathology, Brain metabolism, Brain diagnostic imaging, Brain pathology
Abstract

Recent longitudinal PET imaging studies have established methods to estimate the age at which amyloid becomes abnormal at the level of the individual. Here we recontextualized amyloid levels into the temporal domain to better understand the downstream Alzheimer's disease processes of tau neurofibrillary tangle (NFT) accumulation and cognitive decline. This cohort study included a total of 601 individuals from the Wisconsin Registry for Alzheimer's Prevention and Wisconsin Alzheimer's Disease Research Center that underwent amyloid and tau PET, longitudinal neuropsychological assessments and met clinical criteria for three clinical diagnosis groups: cognitively unimpaired (n = 537); mild cognitive impairment (n = 48); or dementia (n = 16). Cortical 11C-Pittsburgh compound B (PiB) distribution volume ratio (DVR) and sampled iterative local approximation were used to estimate amyloid positive (A+; global PiB DVR > 1.16 equivalent to 17.1 centiloids) onset age and years of A+ duration at tau PET (i.e. amyloid chronicity). Tau PET burden was quantified using 18F-MK-6240 standardized uptake value ratios (70-90 min, inferior cerebellar grey matter reference region). Whole-brain and region-specific approaches were used to examine tau PET binding along the amyloid timeline and across the Alzheimer's disease clinical continuum. Voxel-wise 18F-MK-6240 analyses revealed that with each decade of A+, the spatial extent of measurable tau spread (i.e. progressed) from regions associated with early to late NFT tau stages. Regional analyses indicated that tau burden in the entorhinal cortex was detectable, on average, within 10 years of A+ onset. Additionally, the entorhinal cortex was the region most sensitive to early amyloid pathology and clinical impairment in this predominantly preclinical sample. Among initially cognitively unimpaired (n = 472) individuals with longitudinal cognitive follow-up, mixed effects models showed significant linear and non-linear interactions of A+ duration and entorhinal tau on cognitive decline, suggesting a synergistic effect whereby greater A+ duration, together with a higher entorhinal tau burden, increases the likelihood of cognitive decline beyond their separable effects. Overall, the amyloid time framework enabled a spatiotemporal characterization of tau deposition patterns across the Alzheimer's disease continuum. This approach, which examined cross-sectional tau PET data along the amyloid timeline to make longitudinal disease course inferences, demonstrated that A+ duration explains a considerable amount of variability in the magnitude and topography of tau spread, which largely recapitulated NFT staging observed in human neuropathological studies. By anchoring disease progression to the onset of amyloid, this study provides a temporal disease context, which may help inform disease prognosis and timing windows for anti-amyloid therapies., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Published
2024
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39. Interferon-gamma contributes to disease progression in the Ndufs4(-/-) model of Leigh syndrome.

Author

Hanaford AR, Khanna A, James K, Truong V, Liao R, Chen Y, Mulholland M, Kayser EB, Watanabe K, Hsieh ES, Sedensky M, Morgan PG, Kalia V, Sarkar S, and Johnson SC

Subjects
Animals, Mice, Brain Stem pathology, Brain Stem metabolism, Disease Models, Animal, Mice, Inbred C57BL, Mice, Knockout, Disease Progression, Electron Transport Complex I genetics, Electron Transport Complex I deficiency, Interferon-gamma metabolism, Leigh Disease pathology, Leigh Disease genetics
Abstract

Aim: Leigh syndrome (LS), the most common paediatric presentation of genetic mitochondrial dysfunction, is a multi-system disorder characterised by severe neurologic and metabolic abnormalities. Symmetric, bilateral, progressive necrotizing lesions in the brainstem are defining features of the disease. Patients are often symptom free in early life but typically develop symptoms by about 2 years of age. The mechanisms underlying disease onset and progression in LS remain obscure. Recent studies have shown that the immune system causally drives disease in the Ndufs4(-/-) mouse model of LS: treatment of Ndufs4(-/-) mice with the macrophage-depleting Csf1r inhibitor pexidartinib prevents disease. While the precise mechanisms leading to immune activation and immune factors involved in disease progression have not yet been determined, interferon-gamma (IFNγ) and interferon gamma-induced protein 10 (IP10) were found to be significantly elevated in Ndufs4(-/-) brainstem, implicating these factors in disease. Here, we aimed to explore the role of IFNγ and IP10 in LS., Methods: To establish the role of IFNγ and IP10 in LS, we generated IFNγ and IP10 deficient Ndufs4(-/-)/Ifng(-/-) and Ndufs4(-/-)/IP10(-/-) double knockout animals, as well as IFNγ and IP10 heterozygous, Ndufs4(-/-)/Ifng(+/-) and Ndufs4(-/-)/IP10(+/-), animals. We monitored disease onset and progression to define the impact of heterozygous or homozygous loss of IFNγ and IP10 in LS., Results: Loss of IP10 does not significantly impact the onset or progression of disease in the Ndufs4(-/-) model. IFNγ loss significantly extends survival and delays disease progression in a gene dosage-dependent manner, though the benefits are modest compared to Csf1r inhibition., Conclusions: IFNγ contributes to disease onset and progression in LS. Our findings suggest that IFNγ targeting therapies may provide some benefits in genetic mitochondrial disease, but targeting IFNγ alone would likely yield only modest benefits in LS., (© 2024 The Authors. Neuropathology and Applied Neurobiology published by John Wiley & Sons Ltd on behalf of British Neuropathological Society.)

Published
2024
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40. Mid-to-Late Life Healthy Lifestyle Modifies Genetic Risk for Longitudinal Cognitive Aging among Asymptomatic Individuals.

Author

Xu Y, Sun Z, Jonaitis E, Deming Y, Lu Q, Johnson SC, and Engelman CD

Abstract

Importance: Genetic and lifestyle factors contribute to an individual's risk of developing Alzheimer's disease. However, it is unknown whether and how adherence to healthy lifestyles can mitigate the genetic risk of Alzheimer's., Objective: The aim of this study is to investigate whether adherence to healthy lifestyles can modify the impact of genetic predisposition to Alzheimer's disease on later-life cognitive decline., Design Setting and Participants: This prospective cohort study included 891 adults of European ancestry, aged 40 to 65, who were without dementia and had complete healthy-lifestyle and cognition data during the follow-up. Participants joined the Wisconsin Registry for Alzheimer's Prevention (WRAP) beginning in 2001. We conducted replication analyses using a subsample with similar baseline age range from the Health and Retirement Study (HRS)., Exposures: We assessed participants' exposures using a continuous non- APOE polygenic risk score for Alzheimer's, a binary indicator for APOE-ε4 carrier status, and a weighted healthy-lifestyle score, including factors such as no current smoking, regular physical activity, healthy diet, light to moderate alcohol consumption, and frequent cognitive activities., Main Outcomes and Measures: We z-standardized cognitive scores for global (Preclinical Alzheimer's Cognitive Composite score 3 - PACC3) and domain-specific assessments (delayed recall and immediate learning)., Results: We followed 891 individuals for up to 10 years (mean [SD] baseline age, 58 [6] years, 31% male, 38% APOE-ε4 carriers). After false discovery rate (FDR) correction, we found statistically significant PRS × lifestyle × age interactions on preclinical cognitive decline but the evidence is stronger among APOE-ε4 carriers. Among APOE-ε4 carriers, PRS-related differences in overall and memory-related domains between people scoring 0-1 and 4-5 regarding healthy lifestyles became evident around age 67 after FDR correction. These findings were robust across several sensitivity analyses and were replicated in the population-based HRS., Conclusion: A favorable lifestyle can mitigate the genetic risk associated with current known non- APOE genetic variants for longitudinal cognitive decline, and these protective effects are particularly pronounced among APOE-ε4 carriers., Competing Interests: Conflict of Interest Disclosures: Dr. Johnson has served as a consultant to Roche Diagnostics, Merck and Prothena and has received research funding from Cerveau Technologies. No other disclosures were reported.

Published
2024
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41. Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes.

Author

Yan D, Hu B, Darst BF, Mukherjee S, Kunkle BW, Deming Y, Dumitrescu L, Wang Y, Naj A, Kuzma A, Zhao Y, Kang H, Johnson SC, Carlos C, Hohman TJ, Crane PK, Engelman CD, and Lu Q

Subjects
Humans, Risk Factors, Male, Female, United Kingdom epidemiology, Aged, Genetic Predisposition to Disease, Multifactorial Inheritance genetics, Aged, 80 and over, Alzheimer Disease genetics, Endophenotypes, Genome-Wide Association Study, Biological Specimen Banks
Abstract

Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimer's disease (AD; n=61,212). Among 1738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Furthermore, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD., Competing Interests: DY, BH, BD, SM, BK, YD, LD, YW, AN, AK, YZ, HK, SJ, CC, TH, PC, CE, QL No competing interests declared, (© 2023, Yan, Hu et al.)

Published
2024
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42. Older adults at greater risk for Alzheimer's disease show stronger associations between sleep apnea severity in REM sleep and verbal memory.

Author

Lui KK, Dave A, Sprecher KE, Chappel-Farley MG, Riedner BA, Heston MB, Taylor CE, Carlsson CM, Okonkwo OC, Asthana S, Johnson SC, Bendlin BB, Mander BA, and Benca RM

Subjects
Humans, Female, Male, Middle Aged, Aged, Risk Factors, Verbal Learning physiology, Apolipoprotein E4 genetics, Memory physiology, Severity of Illness Index, Sleep Apnea Syndromes complications, Sleep Apnea Syndromes physiopathology, Sleep Apnea Syndromes genetics, Alzheimer Disease genetics, Alzheimer Disease physiopathology, Alzheimer Disease complications, Sleep, REM physiology, Sleep Apnea, Obstructive complications, Sleep Apnea, Obstructive physiopathology, Sleep Apnea, Obstructive genetics, Polysomnography
Abstract

Background: Obstructive sleep apnea (OSA) increases risk for cognitive decline and Alzheimer's disease (AD). While the underlying mechanisms remain unclear, hypoxemia during OSA has been implicated in cognitive impairment. OSA during rapid eye movement (REM) sleep is usually more severe than in non-rapid eye movement (NREM) sleep, but the relative effect of oxyhemoglobin desaturation during REM versus NREM sleep on memory is not completely characterized. Here, we examined the impact of OSA, as well as the moderating effects of AD risk factors, on verbal memory in a sample of middle-aged and older adults with heightened AD risk., Methods: Eighty-one adults (mean age:61.7 ± 6.0 years, 62% females, 32% apolipoprotein E ε4 allele (APOE4) carriers, and 70% with parental history of AD) underwent clinical polysomnography including assessment of OSA. OSA features were derived in total, NREM, and REM sleep. REM-NREM ratios of OSA features were also calculated. Verbal memory was assessed with the Rey Auditory Verbal Learning Test (RAVLT). Multiple regression models evaluated the relationships between OSA features and RAVLT scores while adjusting for sex, age, time between assessments, education years, body mass index (BMI), and APOE4 status or parental history of AD. The significant main effects of OSA features on RAVLT performance and the moderating effects of AD risk factors (i.e., sex, age, APOE4 status, and parental history of AD) were examined., Results: Apnea-hypopnea index (AHI), respiratory disturbance index (RDI), and oxyhemoglobin desaturation index (ODI) during REM sleep were negatively associated with RAVLT total learning and long-delay recall. Further, greater REM-NREM ratios of AHI, RDI, and ODI (i.e., more events in REM than NREM) were related to worse total learning and recall. We found specifically that the negative association between REM ODI and total learning was driven by adults 60 + years old. In addition, the negative relationships between REM-NREM ODI ratio and total learning, and REM-NREM RDI ratio and long-delay recall were driven by APOE4 carriers., Conclusion: Greater OSA severity, particularly during REM sleep, negatively affects verbal memory, especially for people with greater AD risk. These findings underscore the potential importance of proactive screening and treatment of REM OSA even if overall AHI appears low., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Published
2024
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43. Impact of dietary ketosis on volatile anesthesia toxicity in a model of Leigh syndrome.

Author

Spencer KA, Howe MN, Mulholland MT, Truong V, Liao RW, Chen Y, Setha M, Snell JC, Hanaford A, James K, Morgan PG, Sedensky MM, and Johnson SC

Subjects
Humans, Child, Child, Preschool, Mice, Animals, Diet, Seizures, Electron Transport Complex I metabolism, Leigh Disease genetics, Isoflurane, Ketosis metabolism, Mitochondrial Diseases, Anesthesia, Anesthetics
Abstract

Background: Genetic mitochondrial diseases impact over 1 in 4000 individuals, most often presenting in infancy or early childhood. Seizures are major clinical sequelae in some mitochondrial diseases including Leigh syndrome, the most common pediatric presentation of mitochondrial disease. Dietary ketosis has been used to manage seizures in mitochondrial disease patients. Mitochondrial disease patients often require surgical interventions, leading to anesthetic exposures. Anesthetics have been shown to be toxic in the setting of mitochondrial disease, but the impact of a ketogenic diet on anesthetic toxicities in this setting has not been studied., Aims: Our aim in this study was to determine whether dietary ketosis impacts volatile anesthetic toxicities in the setting of genetic mitochondrial disease., Methods: The impact of dietary ketosis on toxicities of volatile anesthetic exposure in mitochondrial disease was studied by exposing young Ndufs4(-/-) mice fed ketogenic or control diet to isoflurane anesthesia. Blood metabolites were measured before and at the end of exposures, and survival and weight were monitored., Results: Compared to a regular diet, the ketogenic diet exacerbated hyperlactatemia resulting from isoflurane exposure (control vs. ketogenic diet in anesthesia mean difference 1.96 mM, Tukey's multiple comparison adjusted p = .0271) and was associated with a significant increase in mortality during and immediately after exposures (27% vs. 87.5% mortality in the control and ketogenic diet groups, respectively, during the exposure period, Fisher's exact test p = .0121). Our data indicate that dietary ketosis and volatile anesthesia interact negatively in the setting of mitochondrial disease., Conclusions: Our findings suggest that extra caution should be taken in the anesthetic management of mitochondrial disease patients in dietary ketosis., (© 2024 The Authors. Pediatric Anesthesia published by John Wiley & Sons Ltd.)

Published
2024
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44. The New Diagnostic Radiology Oral Exam: Challenges, Opportunities, and Future Directions.

Author

Pfiffner S, Albazi E, Musa A, Altinok G, Johnson SC, and Harb A

Subjects
Humans, Educational Measurement methods, Forecasting, Diagnosis, Oral methods, United States, Radiology trends
Abstract

Competing Interests: Declaration of Competing Interest Arif Musa, M.D. is a recipient of grant funding from the Radiological Society of North American Research & Education Foundation and a contractor for WebMD/Medscape.

Published
2024
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45. Longitudinal normative standards for cognitive tests and composites using harmonized data from two Wisconsin AD-risk-enriched cohorts.

Author

Jonaitis EM, Hermann BP, Mueller KD, Clark LR, Du L, Betthauser TJ, Cody K, Gleason CE, Christian BT, Asthana S, Chappell RJ, Chin NA, Johnson SC, and Langhough RE

Subjects
Humans, Male, Aged, Female, Longitudinal Studies, Wisconsin, Cross-Sectional Studies, Cognitive Dysfunction diagnosis, Cohort Studies, Cognition physiology, Aged, 80 and over, Middle Aged, Alzheimer Disease diagnosis, Neuropsychological Tests standards, Neuropsychological Tests statistics & numerical data, Biomarkers
Abstract

Introduction: Published norms are typically cross-sectional and often are not sensitive to preclinical cognitive changes due to dementia. We developed and validated demographically adjusted cross-sectional and longitudinal normative standards using harmonized outcomes from two Alzheimer's disease (AD) risk-enriched cohorts., Methods: Data from the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center were combined. Quantile regression was used to develop unconditional (cross-sectional) and conditional (longitudinal) normative standards for 18 outcomes using data from cognitively unimpaired participants (N = 1390; mean follow-up = 9.25 years). Validity analyses (N = 2456) examined relationships between percentile scores (centiles), consensus-based cognitive statuses, and AD biomarker levels., Results: Unconditional and conditional centiles were lower in those with consensus-based impairment or biomarker positivity. Similarly, quantitative biomarker levels were higher in those whose centiles suggested decline., Discussion: This study presents normative standards for cognitive measures sensitive to pre-clinical changes. Future directions will investigate potential clinical applications of longitudinal normative standards., Highlights: Quantile regression was used to construct longitudinal norms for cognitive tests. Poorer percentile scores were related to concurrent diagnosis and Alzheimer's disease biomarkers. A ShinyApp was built to display test scores and norms and flag low performance., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Published
2024
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46. Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals.

Author

Skampardoni I, Nasrallah IM, Abdulkadir A, Wen J, Melhem R, Mamourian E, Erus G, Doshi J, Singh A, Yang Z, Cui Y, Hwang G, Ren Z, Pomponio R, Srinivasan D, Govindarajan ST, Parmpi P, Wittfeld K, Grabe HJ, Bülow R, Frenzel S, Tosun D, Bilgel M, An Y, Marcus DS, LaMontagne P, Heckbert SR, Austin TR, Launer LJ, Sotiras A, Espeland MA, Masters CL, Maruff P, Fripp J, Johnson SC, Morris JC, Albert MS, Bryan RN, Yaffe K, Völzke H, Ferrucci L, Benzinger TLS, Ezzati A, Shinohara RT, Fan Y, Resnick SM, Habes M, Wolk D, Shou H, Nikita K, and Davatzikos C

Subjects
Humans, Aged, Female, Male, Middle Aged, Aged, 80 and over, Cognitive Dysfunction genetics, Cognitive Dysfunction physiopathology, Cognitive Dysfunction diagnostic imaging, Magnetic Resonance Imaging, Cohort Studies, Deep Learning, Brain diagnostic imaging, Brain pathology, Aging genetics, Aging physiology
Abstract

Importance: Brain aging elicits complex neuroanatomical changes influenced by multiple age-related pathologies. Understanding the heterogeneity of structural brain changes in aging may provide insights into preclinical stages of neurodegenerative diseases., Objective: To derive subgroups with common patterns of variation in participants without diagnosed cognitive impairment (WODCI) in a data-driven manner and relate them to genetics, biomedical measures, and cognitive decline trajectories., Design, Setting, and Participants: Data acquisition for this cohort study was performed from 1999 to 2020. Data consolidation and harmonization were conducted from July 2017 to July 2021. Age-specific subgroups of structural brain measures were modeled in 4 decade-long intervals spanning ages 45 to 85 years using a deep learning, semisupervised clustering method leveraging generative adversarial networks. Data were analyzed from July 2021 to February 2023 and were drawn from the Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) international consortium. Individuals WODCI at baseline spanning ages 45 to 85 years were included, with greater than 50 000 data time points., Exposures: Individuals WODCI at baseline scan., Main Outcomes and Measures: Three subgroups, consistent across decades, were identified within the WODCI population. Associations with genetics, cardiovascular risk factors (CVRFs), amyloid β (Aβ), and future cognitive decline were assessed., Results: In a sample of 27 402 individuals (mean [SD] age, 63.0 [8.3] years; 15 146 female [55%]) WODCI, 3 subgroups were identified in contrast with the reference group: a typical aging subgroup, A1, with a specific pattern of modest atrophy and white matter hyperintensity (WMH) load, and 2 accelerated aging subgroups, A2 and A3, with characteristics that were more distinct at age 65 years and older. A2 was associated with hypertension, WMH, and vascular disease-related genetic variants and was enriched for Aβ positivity (ages ≥65 years) and apolipoprotein E (APOE) ε4 carriers. A3 showed severe, widespread atrophy, moderate presence of CVRFs, and greater cognitive decline. Genetic variants associated with A1 were protective for WMH (rs7209235: mean [SD] B = -0.07 [0.01]; P value = 2.31 × 10-9) and Alzheimer disease (rs72932727: mean [SD] B = 0.1 [0.02]; P value = 6.49 × 10-9), whereas the converse was observed for A2 (rs7209235: mean [SD] B = 0.1 [0.01]; P value = 1.73 × 10-15 and rs72932727: mean [SD] B = -0.09 [0.02]; P value = 4.05 × 10-7, respectively); variants in A3 were associated with regional atrophy (rs167684: mean [SD] B = 0.08 [0.01]; P value = 7.22 × 10-12) and white matter integrity measures (rs1636250: mean [SD] B = 0.06 [0.01]; P value = 4.90 × 10-7)., Conclusions and Relevance: The 3 subgroups showed distinct associations with CVRFs, genetics, and subsequent cognitive decline. These subgroups likely reflect multiple underlying neuropathologic processes and affect susceptibility to Alzheimer disease, paving pathways toward patient stratification at early asymptomatic stages and promoting precision medicine in clinical trials and health care.

Published
2024
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47. APOE4 homozygozity represents a distinct genetic form of Alzheimer's disease.

Author

Fortea J, Pegueroles J, Alcolea D, Belbin O, Dols-Icardo O, Vaqué-Alcázar L, Videla L, Gispert JD, Suárez-Calvet M, Johnson SC, Sperling R, Bejanin A, Lleó A, and Montal V

Subjects
Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Age of Onset, Amyloid metabolism, Amyloid genetics, Amyloid beta-Peptides cerebrospinal fluid, Amyloid beta-Peptides genetics, Amyloid beta-Peptides metabolism, Apolipoprotein E3 genetics, Cohort Studies, Positron-Emission Tomography, tau Proteins genetics, tau Proteins cerebrospinal fluid, Alzheimer Disease genetics, Alzheimer Disease pathology, Alzheimer Disease diagnostic imaging, Alzheimer Disease cerebrospinal fluid, Apolipoprotein E4 genetics, Biomarkers cerebrospinal fluid, Homozygote
Abstract

This study aimed to evaluate the impact of APOE4 homozygosity on Alzheimer's disease (AD) by examining its clinical, pathological and biomarker changes to see whether APOE4 homozygotes constitute a distinct, genetically determined form of AD. Data from the National Alzheimer's Coordinating Center and five large cohorts with AD biomarkers were analyzed. The analysis included 3,297 individuals for the pathological study and 10,039 for the clinical study. Findings revealed that almost all APOE4 homozygotes exhibited AD pathology and had significantly higher levels of AD biomarkers from age 55 compared to APOE3 homozygotes. By age 65, nearly all had abnormal amyloid levels in cerebrospinal fluid, and 75% had positive amyloid scans, with the prevalence of these markers increasing with age, indicating near-full penetrance of AD biology in APOE4 homozygotes. The age of symptom onset was earlier in APOE4 homozygotes at 65.1, with a narrower 95% prediction interval than APOE3 homozygotes. The predictability of symptom onset and the sequence of biomarker changes in APOE4 homozygotes mirrored those in autosomal dominant AD and Down syndrome. However, in the dementia stage, there were no differences in amyloid or tau positron emission tomography across haplotypes, despite earlier clinical and biomarker changes. The study concludes that APOE4 homozygotes represent a genetic form of AD, suggesting the need for individualized prevention strategies, clinical trials and treatments., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2024
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48. Routine and Special Vaccinations in People With HIV.

Author

Dunlevy HA and Johnson SC

Subjects
Humans, COVID-19 prevention & control, COVID-19 immunology, HIV Infections prevention & control, HIV Infections complications, HIV Infections immunology, Vaccination
Abstract

Vaccinations are an important part of primary care for people with HIV (PWH) and can protect against viral hepatitis and some sexually transmitted infections, as well as respiratory bacterial and viral infections. Vaccinations for influenza, COVID-19, herpes zoster (shingles), hepatitis B, meningococcal disease, mpox, and human papillomavirus are recommended for PWH. Additionally, the Advisory Committee on Immunization Practices has released recommendations incorporating the newer formulations of the pneumococcal pneumonia and respiratory syncytial virus vaccines. Additional considerations for the timing of vaccinations are de-scribed, including whether to delay vaccination until improvement of the immune status. Live vaccines (other than nonreplicating) are contraindicated for PWH with CD4+ counts less than 200 cells/μL or uncontrolled HIV.

Published
2024

49. The role of moonlighting in radiology residency.

Author

Musa A, Hall H, Johnson SC, Alchammas J, Badawy M, and Harb A

Subjects
Humans, United States, Education, Medical, Graduate, Radiography, Radiology, Interventional education, Internship and Residency, Radiology education
Abstract

Competing Interests: Declaration of competing interest Arif Musa is the recipient of grant funding from the Radiological Society of North America Research & Education Foundation. Arif Musa is also an independent contractor for WebMD.

Published
2024
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50. Midlife sensory and motor functions improve prediction of blood-based measures of neurodegeneration and Alzheimer's disease in late middle-age.

Author

Paulsen AJ, Pinto AA, Schubert CR, Chappell RJ, Chen Y, Engelman CD, Ferrucci L, Hancock LM, Johnson SC, and Merten N

Abstract

Introduction: We assessed whether midlife sensory and motor functions added to prediction models using the Cardiovascular Risk Factors, Aging, and Incidence of Dementia Score (CAIDE) and Framingham Risk Score (FRS) improve risk predictions of 10-year changes in biomarkers of neurodegeneration and Alzheimer's disease., Methods: Longitudinal data of N  = 1529 (mean age 49years) Beaver Dam Offspring Study participants from baseline, 5-year, and 10-year follow-up were included. We tested whether including baseline sensory (hearing, vision, olfactory) impairment and motor function measures improves CAIDE or FRS risk predictions of 10-year incidence of biomarker positivity of serum-based neurofilament light chain (NfL) and amyloid beta (Aβ) 42 /Aβ 40 using logistic regression., Results: Adding sensory and motor measures to CAIDE-only and FRS-only models significantly improved NfL and Aβ 42 /Aβ 40 positivity predictions in adults above the age of 55., Discussion: Including midlife sensory and motor function improved long-term biomarker positivity predictions. Non-invasive sensory and motor assessments could contribute to cost-effective screening tools that identify individuals at risk for neurodegeneration early to target interventions and preventions., Highlights: Sensory and motor measures improve risk prediction models of neurodegenerative biomarkersSensory and motor measures improve risk prediction models of AD biomarkersPrediction improvements were strongest in late midlife (adults >55 years of age)Sensory and motor assessments may help identify high-risk individuals early., Competing Interests: The authors have no conflicts of interest to report. Author disclosures are available in the supporting information [Link], [Link]., (© 2024 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Published
2024
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