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2. Assessing the future medical cost burden for the European health systems under alternative exposure-to-risks scenarios

Author

Goryakin, Y., Thiebaut, S. P., Cortaredona, Sébastien, Lerouge, M. A., Cecchini, M., Feigl, A. B., and Ventelou, B.

Abstract

Background Ageing populations and rising prevalence of non-communicable diseases (NCDs) increasingly contribute to the growing cost burden facing European healthcare systems. Few studies have attempted to quantify the future magnitude of this burden at the European level, and none of them consider the impact of potential changes in risk factor trajectories on future health expenditures. Methods The new microsimulation model forecasts the impact of behavioural and metabolic risk factors on NCDs, longevity and direct healthcare costs, and shows how changes in epidemiological trends can modify those impacts. Economic burden of NCDs is modelled under three scenarios based on assumed future risk factors trends: business as usual (BAU); best case and worst case predictions (BCP and WCP). Findings The direct costs of NCDs in the EU 27 countries and the UK (in constant 2014 prices) will grow under all scenarios. Between 2014 and 2050, the overall healthcare spending is expected to increase by 0.8% annually under BAU. In the all the countries, 605 billion Euros can be saved by 2050 if BCP is realized compared to the BAU, while excess spending under the WCP is forecast to be around 350 billion. Interpretation: Although the savings realised under the BCP can be substantial, population ageing is a stronger driver of rising total healthcare expenditures in Europe compared to scenario-based changes in risk factor prevalence.

Published
2020

5. Promoting sport and physical activity in Italy: a cost-effectiveness analysis of seven innovative public health policies.

Author

Goryakin, Y., Aldea, A., Lerouge, A., Spica, V. Romano, Nante, N., Vuik, S., Devaux, M., and Cecchini, M.

Subjects
PHYSICAL activity, PUBLIC health, CHRONIC diseases, MEDICAL economics, MOBILE apps
Abstract

Copyright of Annali di Igiene, Medicina Preventiva e di Comunità is the property of Societa Editrice Universo s.r.l. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2019
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6. Impact of primary care‐initiated interventions promoting physical activity on body mass index: systematic review and meta‐analysis.

Author

Goryakin, Y., Suhlrie, L., and Cecchini, M.

Subjects
*PHYSICAL activity, *BODY mass index, *PHYSICAL fitness, *MUSCLE mass, *HEALTH promotion
Abstract

Summary: Introduction: Physical inactivity is a risk factor for obesity, overweight and for a number of chronic diseases. Although primary care may be an ideal setting to encourage people to do more exercise, there are still significant gaps in the literature on the effectiveness of primary care‐initiated policies to promote physical activity. Methods: In this paper, we systematically review and meta‐analyse the evidence on the impact of primary care‐initiated interventions to promote exercise on the body mass index and on physical activity energy expenditure levels among people at an increased risk of having potentially disabling non‐communicable diseases (but healthy enough to exercise). Results: We find that such interventions reduce body mass index by about 0.21 kg m−2 (95% confidence interval: −0.41 to −0.01) and increase physical activity‐related energy expenditure (based mostly on self‐recall) by about 1.77 metabolic equivalent of task‐hours a week (95% confidence interval: 0.58 to 2.95). Discussion: This study suggests that primary care‐initiated interventions promoting physical activity can be an effective strategy to reduce weight and increase exercise levels in this population group, although the question remains about whether such interventions can be cost‐effective. [ABSTRACT FROM AUTHOR]

Published
2018
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11. The prevalence and determinants of catastrophic health expenditures attributable to non-communicable diseases in low- and middle-income countries: a methodological commentary

Author

Goryakin, Y and Suhrcke, M

Subjects
Financing, Personal, Cross-Sectional Studies, Cost of Illness, Socioeconomic Factors, Chronic Disease, 1. No poverty, Income, Prevalence, Humans, Prospective Studies, Health Expenditures, Developing Countries, 3. Good health
Abstract

BACKGROUND: Non-communicable diseases (NCDs), while traditionally considered a "rich world"-problem, have been spreading fast in low and middle income countries and by now account for a large share of mortality and ill-health in these countries, too. In addition to the disease burden, NCDs may also impose a substantial economic cost. One way in which NCDs might impact people's economic well-being may be via the out-of-pocket expenditures required to cover treatment and other costs associated with suffering from an NCD. METHODS: In this commentary, we identify and discuss the methodological challenges related to cross-country comparison of-out-of-pocket and catastrophic out-of-pocket health care expenditures, attributable to NCDs, focussing on low and middle income countries. RESULTS: There is significant evidence of substantial cost burden placed by NCDs on patients living in low and middle income countries, with most of it being heavily concentrated among low socioeconomic status groups. However, a large variation in definition of COOPE between studies prevents cross-country comparison. In addition, as most studies tend to be observational, causal inferences are often not possible. This is further complicated by the cross-sectional nature of studies, small sample sizes, and/or limited duration of follow-up of patients. Most evidence for certain conditions (e.g., cancer) tends to be collected in high-income countries only. CONCLUSIONS: The definitions for COOPEs should be standardized as much as possible, to enable comparison of COOPE prevalence between countries. Prospective study design using larger samples representative of broader sections of local population, collecting better data on both direct and indirect treatment costs is also needed.

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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E, Dorsey, Kadine, Priscila, Bender, Dos, Santos, Kerrie, E, Doyle, Tim, Driscoll, R, Manisha, Dubey, Eleonora, Dubljanin, Bruce, Bartholow, Duncan, Michelle, Echko, Dumessa, Edessa, David, Edvardsson, Joshua, R, Ehrlich, Erika, Eldrenkamp, Ziad, El-Khatib, Matthias, Endres, Aman, Yesuf, Endries, Babak, Eshrati, Sharareh, Eskandarieh, Alireza, Esteghamati, Mahdi, Fakhar, Tamer, Farag, Mahbobeh, Faramarzi, Emerito, Jose, Aquino, Faraon, André, Faro, Farshad, Farzadfar, Adesegun, Fatusi, Mir, Sohail, Fazeli, Valery, Feigin, L, Andrea, B, Feigl, Netsanet, Fentahun, Seyed-Mohammad, Fereshtehnejad, Eduarda, Fernandes, João, C, Fernandes, Daniel, Obadare, Fijabi, Irina, Filip, Florian, Fischer, Christina, Fitzmaurice, Abraham, D, Flaxman, Luisa, Sorio, Flor, Nataliya, Foigt, Kyle, J, Foreman, Joseph, Frostad, J, Thomas, Fürst, Neal, D, Futran, Emmanuela, Gakidou, Silvano, Gallus, Ketevan, Gambashidze, Amiran, Gamkrelidze, Morsaleh, Ganji, Abadi, Kahsu, Gebre, Tsegaye, Tewelde, Gebrehiwot, Amanuel, Tesfay, Gebremedhin, Yalemzewod, Assefa, Gelaw, Johanna, M, Geleijnse, Demeke, Geremew, Peter, W, Gething, Reza, Ghadimi, Khalil, Ghasemi, Falavarjani, Maryam, Ghasemi-Kasman, Paramjit, Singh, Gill, Ababi, Zergaw, Giref, Maurice, Giroud, Melkamu, Dedefo, Gishu, Giorgia, Giussani, William, W, Godwin, Srinivas, Goli, Hector, Gomez-Dantes, Philimon, N, Gona, Amador, Goodridge, Sameer, Vali, Gopalani, Yevgeniy, Goryakin, Alessandra, Carvalho, Goulart, Ayman, Grada, Max, Griswold, Giuseppe, Grosso, Harish, Chander, Gugnani, Yuming, Guo, Rahul, Gupta, Rajeev, Gupta, Tanush, Gupta, Tarun, Gupta, Vipin, Gupta, Juanita, A, Haagsma, Vladimir, Hachinski, Nima, Hafezi-Nejad, Gessessew, Bugssa, Hailu, Randah, Ribhi, Hamadeh, Samer, Hamidi, Graeme, J, Hankey, Hilda, Harb, L, Heather, C, Harewood, Sivadasanpillai, Harikrishnan, Josep, Maria, Haro, Hamid, Yimam, Hassen, Rasmus, Havmoeller, Caitlin, Hawley, Simon, I, Hay, Jiawei, He, Stephen, J, Hearps, C, Mohamed, I, Hegazy, Behzad, Heibati, Mohsen, Heidari, Delia, Hendrie, Nathaniel, J, Henry, Victor, Hugo, Herrera, Ballesteros, Claudiu, Herteliu, Desalegn, Tsegaw, Hibstu, Molla, Kahssay, Hiluf, Hans, W, Hoek, Enayatollah, Homaie, Rad, Nobuyuki, Horita, Dean, H, Hosgood, Mostafa, Hosseini, Seyed, Reza, Hosseini, Mihaela, Hostiuc, Sorin, Hostiuc, Damian, G, Hoy, Mohamed, Hsairi, Aung, Soe, Htet, Guoqing, Hu, John, J, Huang, Kim, Moesgaard, Iburg, Fachmi, Idris, Ehimario, Uche, Igumbor, Chad, Ikeda, Bogdan, Vasile, Ileanu, Olayinka, Ilesanmi, S, Kaire, Innos, Seyed, Sina, Naghibi, Irvani, Caleb, M, Irvine, S, Farhad, Islami, Troy, A, Jacobs, Kathryn, Jacobsen, H, Nader, Jahanmehr, Rajesh, Jain, Sudhir, Kumar, Jain, Mihajlo, Jakovljevic, M, Moti, Tolera, Jalu, Amr, Jamal, A, Mehdi, Javanbakht, Achala, Upendra, Jayatilleke, Panniyammakal, Jeemon, Ravi, Prakash, Jha, Vivekanand, Jha, Jacek, Józwiak, Oommen, John, Sarah, Charlotte, Johnson, Jost, Jonas, B, Vasna, Joshua, Mikk, Jürisson, Zubair, Kabir, Rajendra, Kadel, Amaha, 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Koyanagi, Ai, Michael, Kravchenko, Kewal, Krishan, Kristopher, J, Krohn, Barthelemy, Kuate, Defo, Anil, G, Kumar, Pushpendra, Kumar, Michael, Kutz, Igor, Kuzin, Hmwe, H, Kyu, Deepesh, Pravinkumar, Lad, Alessandra, Lafranconi, Dharmesh, Kumar, Lal, Ratilal, Lalloo, Hilton, Lam, Qing, Lan, Justin, J, Lang, Van, Lansingh, C, Sonia, Lansky, Anders, Larsson, Arman, Latifi, Jeffrey, Victor, Lazarus, Janet, Leasher, L, Paul, H, Lee, Yirga, Legesse, James, Leigh, Cheru, Tesema, Leshargie, Samson, Leta, Janni, Leung, Ricky, Leung, Miriam, Levi, Yongmei, Li, Juan, Liang, Misgan, Legesse, Liben, Lee-Ling, Lim, Stephen, S, Lim, Margaret, Lind, Shai, Linn, Stefan, Listl, Patrick, Y, Liu, Shiwei, Liu, Rakesh, Lodha, Alan, D, Lopez, Scott, Lorch, A, Stefan, Lorkowski, Paulo, A, Lotufo, Timothy, C, D, Lucas, Raimundas, Lunevicius, Grégoire, Lurton, Ronan, A, Lyons, Fadi, Maalouf, Erlyn, Rachelle, King, Macarayan, Mark, T, Mackay, Emilie, Maddison, R, Fabiana, Madotto, Hassan, Magdy, Abd, El, Razek, Mohammed, Magdy, Abd, Razek, El, Marek, Majdan, Reza, Majdzadeh, Azeem, Majeed, Reza, Malekzadeh, Rajesh, Malhotra, Deborah, Carvalho, Malta, Abdullah, Mamun, A, Helena, Manguerra, Treh, Manhertz, Mohammad, Ali, Mansournia, Lorenzo, Mantovani, G, Tsegahun, Manyazewal, Chabila, C, Mapoma, Christopher, Margono, Jose, Martinez-Raga, Sheila, Cristina, Ouriques, Martins, Francisco, Rogerlândio, Martins-Melo, Ira, Martopullo, Winfried, März, Benjamin, Ballard, Massenburg, Manu, Raj, Mathur, Pallab, K, Maulik, Mohsen, Mazidi, Colm, Mcalinden, Mcgrath, Martin, Mckee, Suresh, Mehata, Ravi, Mehrotra, Kala, M, Mehta, Varshil, Mehta, Toni, Meier, Fabiola, Mejia-Rodriguez, Kidanu, Gebremariam, Meles, Mulugeta, Melku, Peter, Memiah, Ziad, A, Memish, Walter, Mendoza, Degu, Abate, Mengiste, Desalegn, Tadese, Mengistu, Bereket, Gebremichael, Menota, George, Mensah, A, Atte, Meretoja, Tuomo, J, Meretoja, Haftay, Berhane, Mezgebe, Tomasz, Miazgowski, Renata, Micha, Robert, Milam, Anoushka, Millear, Ted, R, Miller, Mini, Gk, Shawn, Minnig, Andreea, Mirica, Erkin, M, Mirrakhimov, Awoke, Misganaw, Philip, B, Mitchell, Fitsum, Weldegebreal, Mlashu, Babak, Moazen, Karzan, Abdulmuhsin, Mohammad, Roghayeh, Mohammadibakhsh, Ebrahim, Mohammed, Mohammed, A, Mohammed, Shafiu, Mohammed, Ali, H, Mokdad, Glen, Liddell, D, Mola, Mariam, Molokhia, Fatemeh, Momeniha, Lorenzo, Monasta, Julio, Cesar, Montañez, Hernandez, Mahmood, Moosazadeh, Maziar, Moradi-Lakeh, Paula, Moraga, Lidia, Morawska, Ilais, Moreno, Velasquez, Rintaro, Mori, Shane, D, Morrison, Mark, Moses, Seyyed, Meysam, Mousavi, Ulrich, Mueller, O, Manoj, Murhekar, Gudlavalleti, Venkata, Satyanarayana, Murthy, Srinivas, Murthy, Jonah, Musa, Kamarul, Imran, Musa, Ghulam, Mustafa, Saravanan, Muthupandian, Chie, Nagata, Gabriele, Nagel, Mohsen, Naghavi, Aliya, Naheed, Gurudatta, A, Naik, Nitish, Naik, Farid, Najafi, Luigi, Naldi, Vinay, Nangia, Jobert, Richie, Njingang, Nansseu, K, M, Venkat, Narayan, Bruno, Ramos, Nascimento, Ionut, Negoi, Ruxandra, Irina, Negoi, Charles, Newton, R, Josephine, Wanjiku, Ngunjiri, Grant, Nguyen, Long, Nguyen, Trang, Huyen, Nguyen, Emma, Nichols, Dina, Nur, Anggraini, Ningrum, Ellen, Nolte, Vuong, Minh, Nong, Ole, Norheim, F, Norrving, Bo, Jean, Jacques, Noubiap, N, Alypio, Nyandwi, Carla, Makhlouf, Obermeyer, Richard, Ofori-Asenso, Felix, Akpojene, Ogbo, In-Hwan, Oh, Olanrewaju, Oladimeji, Andrew, Toyin, Olagunju, Tinuke, Oluwasefunmi, Olagunju, Pedro, R, Olivares, Patricia, Pereira, Vasconcelos, Oliveira, De, Helen, E, Olsen, Bolajoko, Olubukunola, Olusanya, Jacob, Olusegun, Olusanya, Kanyin, Ong, John, Nelson, Opio, Eyal, Oren, Doris, V, Ortega-Altamirano, Alberto, Ortiz, Raziye, Ozdemir, Mahesh, Pa, Amanda, W, Pain, Marcos, Roberto, Tovani, Palone, Adrian, Pana, Songhomitra, Panda-Jonas, Jeyaraj, D, Pandian, Eun-Kee, Park, Hadi, Parsian, Tejas, Patel, Sanghamitra, Pati, Snehal, T, Patil, Ajay, Patle, George, C, Patton, Vishnupriya, Rao, Paturi, Deepak, Paudel, Marcel, De, Moares, Pedroso, Sandra, P, Pedroza, David, Pereira, M, Norberto, Perico, Hannah, Peterson, Max, Petzold, Niloofar, Peykari, Michael, Robert, Phillips, Frédéric, Piel, B, David, M, Pigott, Julian, David, Pillay, Michael, A, Piradov, Suzanne, Polinder, Constance, D, Pond, Maarten, Postma, J, Farshad, Pourmalek, Swayam, Prakash, Prakash, V, Narayan, Prasad, Noela, Marie, Prasad, Caroline, Purcell, Mostafa, Qorbani, Hedley, Knewjen, Quintana, Amir, Radfar, Anwar, Rafay, Alireza, Rafiei, Kazem, Rahimi, Afarin, Rahimi-Movaghar, Vafa, Rahimi-Movaghar, Mahfuzar, Rahman, Muhammad, Aziz, Rahman, Sajjad, Rahman, Ur, Rajesh, Kumar, Rai, Sree, Bhushan, Raju, Usha, Ram, Saleem, M, Rana, Zane, Rankin, Davide, Rasella, David, Laith, Rawaf, Salman, Rawaf, Sarah, E, Ray, Christian, Aspacia, Razo-García, Priscilla, Reddy, Robert, C, Reiner, Cesar, Reis, Marissa, B, Reitsma, Giuseppe, Remuzzi, Andre, M, Renzaho, N, Serge, Resnikoff, Satar, Rezaei, Mohammad, Sadegh, Rezai, Antonio, Ribeiro, L, Maria, Jesus, Rios, Blancas, Juan, A, Rivera, Leonardo, Roever, Luca, Ronfani, Gholamreza, Roshandel, Ali, Rostami, Gregory, A, Roth, Dietrich, Rothenbacher, Ambuj, Roy, Nobhojit, Roy, George, Mugambage, Ruhago, Yogesh, Damodar, Sabde, Perminder, S, Sachdev, Nafis, Sadat, Mahdi, Safdarian, Saeid, Safiri, Rajesh, Sagar, Amirhossein, Sahebkar, Sahraian, Haniye, Sadat, Sajadi, Joseph, Salama, Payman, Salamati, Raphael, De, Freitas, Saldanha, Hamideh, Salimzadeh, Joshua, A, Salomon, Abdallah, Samy, M, Juan, Ramon, Sanabria, Parag, Sancheti, K, Maria, Dolores, Sanchez-Niño, Damian, Santomauro, Itamar, S, Santos, Milena, Santric, M, Milicevic, Abdur, Razzaque, Sarker, Nizal, Sarrafzadegan, Benn, Sartorius, Maheswar, Satpathy, Miloje, Savic, Monika, Sawhney, Sonia, Saxena, Mete, I, Saylan, Elke, Schaeffner, Josef, Schmidhuber, Maria, Inês, Schmidt, Ione, J, C, Schneider, Austin, Schumacher, E, Aletta, E, Schutte, David, Schwebel, C, Falk, Schwendicke, Mario, Sekerija, Sadaf, G, Sepanlou, Edson, Servan-Mori, E, 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Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G. 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Ray, Dos Santos, Kadine Priscila Bender, Doyle, Kerrie E., Driscoll, Tim R., Dubey, Manisha, Dubljanin, Eleonora, Duncan, Bruce Bartholow, Echko, Michelle, Edessa, Dumessa, Edvardsson, David, Ehrlich, Joshua R., Eldrenkamp, Erika, El-Khatib, Ziad, Endres, Matthia, Endries, Aman Yesuf, Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Fakhar, Mahdi, Farag, Tamer, Faramarzi, Mahbobeh, Faraon, Emerito Jose Aquino, Faro, André, Farzadfar, Farshad, Fatusi, Adesegun, Fazeli, Mir Sohail, Feigin, Valery L., Feigl, Andrea B., Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, João C., Fijabi, Daniel Obadare, Filip, Irina, Fischer, Florian, Fitzmaurice, Christina, Flaxman, Abraham D., Flor, Luisa Sorio, Foigt, Nataliya, Foreman, Kyle J., Frostad, Joseph J., Fürst, Thoma, Futran, Neal D., Gakidou, Emmanuela, Gallus, Silvano, Gambashidze, Ketevan, Gamkrelidze, Amiran, Ganji, Morsaleh, Gebre, Abadi Kahsu, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gelaw, Yalemzewod Assefa, Geleijnse, Johanna M., Geremew, Demeke, Gething, Peter W., Ghadimi, Reza, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Gill, Paramjit Singh, Giref, Ababi Zergaw, Giroud, Maurice, Gishu, Melkamu Dedefo, Giussani, Giorgia, Godwin, William W., Goli, Sriniva, Gomez-Dantes, Hector, Gona, Philimon N., Goodridge, Amador, Gopalani, Sameer Vali, Goryakin, Yevgeniy, Goulart, Alessandra Carvalho, Grada, Ayman, Griswold, Max, Grosso, Giuseppe, Gugnani, Harish Chander, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Gupta, Tarun, Gupta, Vipin, Haagsma, Juanita A., Hachinski, Vladimir, Hafezi-Nejad, Nima, Hailu, Gessessew Bugssa, Hamadeh, Randah Ribhi, Hamidi, Samer, Hankey, Graeme J., Harb, Hilda L., Harewood, Heather C., Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hassen, Hamid Yimam, Havmoeller, Rasmu, Hawley, Caitlin, Hay, Simon I., He, Jiawei, Hearps, Stephen J.C., Hegazy, Mohamed I., Heibati, Behzad, Heidari, Mohsen, Hendrie, Delia, Henry, Nathaniel J., Herrera Ballesteros, Victor Hugo, Herteliu, Claudiu, Hibstu, Desalegn Tsegaw, Hiluf, Molla Kahssay, Hoek, Hans W., Homaie Rad, Enayatollah, Horita, Nobuyuki, Hosgood, H. 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., Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J., Stokes, Mark Andrew, Sturua, Lela, Sufiyan, Muawiyyah Babale, Suliankatchi, Rizwan Abdulkader, Sunguya, Bruno F., Sur, Patrick J., Sykes, Bryan L., Sylaja, P.N., Szoeke, Cassandra E.I., Tabarés-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Tadesse, Andualem Henok, Taffere, Getachew Redae, Tandon, Nikhil, Tariku, Amare Tariku, Taveira, Nuno, Tehrani-Banihashemi, Arash, Temam Shifa, Girma, Temsah, Mohamad-Hani, Terkawi, Abdullah Sulieman, Tesema, Azeb Gebresilassie, Tesfaye, Dawit Jember, Tessema, Belay, Thakur, J.S., Thomas, Nihal, Thompson, Matthew J., Tillmann, Taavi, To, Quyen G., Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Torre, Anna, Tortajada, Miguel, Tran, Bach Xuan, Tran, Khanh Bao, Tripathi, Avnish, Tripathy, Srikanth Prasad, Troeger, Christopher, Truelsen, Thoma, Tsoi, Derrick, Tudor Car, Lorainne, Tuem, Kald Beshir, Tyrovolas, Stefano, Uchendu, Uche S., Ukwaja, Kingsley Nnanna, Ullah, Irfan, 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 comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Author

Gakidou, Emmanuela, Afshin, Ashkan, Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M., Abd-Allah, Foad, Abdulle, Abdishakur M., Abera, Semaw Ferede, Aboyans, Victor, Abu-Raddad, Laith J., Abu-Rmeileh, Niveen M. E., Abyu, Gebre Yitayih, Adedeji, Isaac Akinkunmi, Adetokunboh, Olatunji, Afarideh, Mohsen, Agrawal, Anurag, Agrawal, Sutapa, Kiadaliri, Aliasghar Ahmad, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akinyemi, Rufus Olusola, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alam, Tahiya, Alasfoor, Deena, Alene, Kefyalew Addis, Ali, Komal, Alizadeh-Navaei, Reza, Alkerwi, Ala'a, Alla, Francois, Allebeck, Peter, Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A., Alvis-Guzman, Nelson, Amare, Azmeraw T., Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Ansari, Hossein, Anto, Josep M., Antonio, Carl Abelardo T., Anwari, Palwasha, Arian, Nicholas, Arnlov, Johan, Artaman, A., Aryal, Krishna Kumar, Asayesh, Hamid, Asgedom, Solomon Weldegebreal, Atey, Tesfay Mehari, Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G. Arthur, Awasthi, Ashish, Azzopardi, Peter, Bacha, Umar, Badawi, Alaa, Balakrishnan, Kalpana, Ballew, Shoshana H., Barac, Aleksandra, Barber, Ryan M., Barker-Collo, Suzanne L., Barnighausen, Till, Barquera, Simon, Barregard, Lars, Barrero, Lope H., Batis, Carolina, Battle, Katherine E., Baune, Bernhard T., Beardsley, Justin, Bedi, Neeraj, Beghi, Ettore, Bell, Michelle L., Bennett, Derrick A., Bennett, James R., Bensenor, Isabela M., Berhane, Adugnaw, Berhe, Derbew Fikadu, Bernabe, Eduardo, Betsu, Balem Demtsu, Beuran, Mircea, Beyene, Addisu Shunu, Bhansali, Anil, Bhutta, Zulfiqar A., Bikbov, Boris, Birungi, Charles, Biryukov, Stan, Blosser, Christopher D., Boneya, Dube Jara, Bou-Orm, Ibrahim R., Brauer, Michael, Breitborde, Nicholas J. K., Brenner, Hermann, Brugha, Traolach S., Bulto, Lemma Negesa Bulto, Baumgarner, Blair R., Butt, Zahid A., Cahuana-Hurtado, Lucero, Cardenas, Rosario, Carrero, Juan Jesus, Castaneda-Orjuela, Carlos A., Catala-Lopez, Ferran, Cercy, Kelly, Chang, Hsing-Yi, Charlson, Fiona J., Chimed-Ochir, Odgerel, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal A., Christensen, Hanne, Christopher, Devasahayam Jesudas, Cirillo, Massimo, Cohen, Aaron J., Comfort, Haley, Cooper, Cyrus, Coresh, Josef, Cornaby, Leslie, Cortesi, Paolo Angelo, Criqui, Michael H., Crump, John A., Dandona, Lalit, Dandona, Rakhi, das Neves, Jose, Davey, Gail, Davitoiu, Dragos V., Davletov, Kairat, de Courten, Barbora, Degenhardt, Louisa, Deiparine, Selina, Dellavalle, Robert P., Deribe, Kebede, Deshpande, Aniruddha, Dharmaratne, Samath D., Ding, Eric L., Djalalinia, Shirin, Huyen Phuc Do, Huyen Phuc Do, Dokova, Klara, Doku, David Teye, Dorsey, E. Ray, Driscoll, Tim R., Dubey, Manisha, Duncan, Bruce Bartholow, Duncan, Sarah, Ebert, Natalie, Ebrahimi, Hedyeh, El-Khatib, Ziad Ziad, Enayati, Ahmadali, Endries, Aman Yesuf, Ermakov, Sergey Petrovich, Erskine, Holly E., Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Estep, Kara, Faraon, Emerito Jose Aquino, E Sa Farinha, Carla Sofia, Faro, Andre, Farzadfar, Farshad, Fay, Kairsten, Feigin, Valery L., Fereshtehnejad, Seyed-Mohammad, Fernandes, Joao C., Ferrari, Alize J., Feyissa, Tesfaye Regassa, Filip, Irina, Fischer, Florian, Fitzmaurice, Christina, Flaxman, Abraham D., Foigt, Nataliya, Foreman, Kyle J., Frostad, Joseph J., Fullman, Nancy, Furst, Thomas, Furtado, Joao M., Ganji, Morsaleh, Garcia-Basteiro, Alberto L., Gebrehiwot, Tsegaye Tewelde, Geleijnse, Johanna M., Geleto, Ayele, Gemechu, Bikila Lencha, Gesesew, Hailay Abrha, Gething, Peter W., Ghajar, Alireza, Gibney, Katherine B., Gill, Paramjit Singh, Gillum, Richard F., Giref, Ababi Zergaw, Gishu, Melkamu Dedefo, Giussani, Giorgia, Godwin, William W., Gona, Philimon N., Goodridge, Amador, Gopalani, Sameer Vali, Goryakin, Yevgeniy, Goulart, Alessandra Carvalho, Graetz, Nicholas, Gugnani, Harish Chander, Guo, Jingwen, Gupta, Rajeev, Gupta, Tanush, Gupta, Vipin, Gutierrez, Reyna A., Hachinski, Vladimir, Hafezi-Nejad, Nima, Hailu, Gessessew Bugssa, Hamadeh, Randah Ribhi, Hamidi, Samer, Hammami, Mouhanad, Handal, Alexis J., Hankey, Graeme J., Harb, Hilda L., Hareri, Habtamu Abera, Hassanvand, Mohammad Sadegh, Havmoeller, Rasmus, Hawley, Caitlin, Hay, Simon I., Hedayati, Mohammad T., Hendrie, Delia, Beatriz Heredia-Pi, Ileana, Hoek, Hans W., Horita, Nobuyuki, Hosgood, H. Dean, Hostiuc, Sorin, Hoy, Damian G., Hsairi, Mohamed, Hu, Guoqing, Huang, Hsiang, Huang, John J., Iburg, Kim Moesgaard, Ikeda, Chad, Inoue, Manami, Irvine, Caleb Mackay Salpeter, Jackson, Maria Delores, Jacobsen, Kathryn H., Jahanmehr, Nader, Jakovljevic, Mihajlo (Michael) B., Jauregui, Alejandra, Javanbakht, Mehdi, Jeemon, Panniyammakal, Johansson, Lars R. K., Johnson, Catherine O., Jonas, Jost B., Jurisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kamal, Ritul, Karch, Andre, Karema, Corine Kakizi, Kasaeian, Amir, Kassebaum, Nicholas J., Kastor, Anshul, Katikireddi, Srinivasa Vittal, Kawakami, Norito, Keiyoro, Peter Njenga, Kelbore, Sefonias Getachew, Kemmer, Laura, Kengne, Andre Pascal, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khang, Young-Ho, Khosravi, Ardeshir, Khubchandani, Jagdish, Kieling, Christian, Kim, Daniel, Kim, Jun Y., Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohannes, Kisa, Adnan, Kissimova-Skarbek, Katarzyna A., Kivimaki, Mika, Knibbs, Luke D., Knudsen, Ann Kristin, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael, Krohn, Kristopher J., Kromhout, Hans, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kumar, G. 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Ray, Driscoll, Tim R., Dubey, Manisha, Duncan, Bruce Bartholow, Duncan, Sarah, Ebert, Natalie, Ebrahimi, Hedyeh, El-Khatib, Ziad Ziad, Enayati, Ahmadali, Endries, Aman Yesuf, Ermakov, Sergey Petrovich, Erskine, Holly E., Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Estep, Kara, Faraon, Emerito Jose Aquino, Farinha, Carla Sofia E. 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Dean, Hostiuc, Sorin, Hoy, Damian G., Hsairi, Mohamed, Hu, Guoqing, Huang, Hsiang, Huang, John J., Iburg, Kim Moesgaard, Ikeda, Chad, Inoue, Manami, Irvine, Caleb Mackay Salpeter, Jackson, Maria Delore, Jacobsen, Kathryn H., Jahanmehr, Nader, Jakovljevic, Mihajlo B., Jauregui, Alejandra, Javanbakht, Mehdi, Jeemon, Panniyammakal, Johansson, Lars R.K., Johnson, Catherine O., Jonas, Jost B., Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kamal, Ritul, Karch, André, Karema, Corine Kakizi, Kasaeian, Amir, Kassebaum, Nicholas J., Kastor, Anshul, Katikireddi, Srinivasa Vittal, Kawakami, Norito, Keiyoro, Peter Njenga, Kelbore, Sefonias Getachew, Kemmer, Laura, Kengne, Andre Pascal, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khang, Young-Ho, Khosravi, Ardeshir, Khubchandani, Jagdish, Kieling, Christian, Kim, Daniel, Kim, Jun Y., Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohanne, Kisa, Adnan, Kissimova-Skarbek, Katarzyna A., Kivimaki, Mika, Knibbs, Luke D., Knudsen, Ann Kristin, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael, Krohn, Kristopher J., Kromhout, Han, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kumar, G. Anil, Kutz, Michael, Kyu, Hmwe H., Lal, Dharmesh Kumar, Lalloo, Ratilal, Lallukka, Tea, Lan, Qing, Lansingh, Van C., Larsson, Ander, Lee, Alexander, Lee, Paul H., Leigh, Jame, Leung, Janni, Levi, Miriam, Li, Yichong, Li, Yongmei, Liang, Xiaofeng, Liben, Misgan Legesse, Linn, Shai, Liu, Patrick, Lodha, Rakesh, Logroscino, Giancarlo, Looker, Katherine J., Lopez, Alan D., Lorkowski, Stefan, Lotufo, Paulo A., Lozano, Rafael, Lunevicius, Raimunda, Macarayan, Erlyn Rachelle King, 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, Mantovani, Lorenzo G., Mapoma, Chabila C., Martin, Randall V., Martinez-Raga, Jose, Martins-Melo, Francisco Rogerlândio, Mathur, Manu Raj, Matsushita, Kunihiro, Matzopoulos, Richard, Mazidi, Mohsen, McAlinden, Colm, McGrath, John J., Mehata, Suresh, Mehndiratta, Man Mohan, Meier, Toni, Melaku, Yohannes Adama, Memiah, Peter, Memish, Ziad A., Mendoza, Walter, Mengesha, Melkamu Merid, Mensah, George A., Mensink, Gert B.M., Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J., Mezgebe, Haftay Berhane, Micha, Renata, Millear, Anoushka, Miller, Ted R., Minnig, Shawn, Mirarefin, Mojde, Mirrakhimov, Erkin M., Misganaw, Awoke, Mishra, Shiva Raj, Mohammad, Karzan Abdulmuhsin, Mohammed, Kedir Endri, Mohammed, Shafiu, Mohamed Ibrahim, Norlinah, Mohan, Murali B.V., Mokdad, Ali H., Monasta, Lorenzo, Montañez Hernandez, Julio Cesar, Montico, Marcella, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Morrison, Shane D., Mountjoy-Venning, Cliff, Mueller, Ulrich O., Mullany, Erin C., Muller, Kate, Murthy, Gudlavalleti Venkata Satyanarayana, Musa, Kamarul Imran, Naghavi, Mohsen, Naheed, Aliya, Nangia, Vinay, Natarajan, Gopalakrishnan, Negoi, Ionut, Negoi, Ruxandra Irina, Nguyen, Cuong Tat, Nguyen, Grant, Nguyen, Minh, Nguyen, Quyen Le, Nguyen, Trang Huyen, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nomura, Marika, Nong, Vuong Minh, Norheim, Ole F., Norrving, Bo, Noubiap, Jean Jacques N., Obermeyer, Carla Makhlouf, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew Toyin, Olagunju, Tinuke Oluwasefunmi, Olivares, Pedro R., Olsen, Helen E., Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Opio, John Nelson, Oren, Eyal, Ortiz, Alberto, Ota, Erika, Owolabi, Mayowa O., Pa, Mahesh, Pacella, Rosana E., Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Pandian, Jeyaraj D., Papachristou, Christina, Park, Eun-Kee, Parry, Charles D., Patten, Scott B., Patton, George C., Pereira, David M., Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Phillips, Michael Robert, Pillay, Julian David, Piradov, Michael A., Pishgar, Farhad, Plass, Dietrich, Pletcher, Martin A., Polinder, Suzanne, Popova, Svetlana, Poulton, Richie G., Pourmalek, Farshad, Prasad, Narayan, Purcell, Carrie, Qorbani, Mostafa, Radfar, Amir, Rafay, Anwar, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rai, Rajesh Kumar, Rajsic, Sasa, Ram, Usha, Rawaf, Salman, Rehm, Colin D., Rehm, Jürgen, Reiner, Robert C., Reitsma, Marissa B., Reynales-Shigematsu, Luz Myriam, Remuzzi, Giuseppe, Renzaho, Andre M.N., Resnikoff, Serge, Rezaei, Satar, Ribeiro, Antonio L., Rivera, Juan A., Roba, Kedir Teji, Rojas-Rueda, David, Roman, Yesenia, Room, Robin, Roshandel, Gholamreza, Roth, Gregory A., Rothenbacher, Dietrich, Rubagotti, Enrico, Rushton, Lesley, Sadat, Nafi, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sahathevan, Ramesh, Salama, Joseph, Salomon, Joshua A., Samy, Abdallah M., Sanabria, Juan Ramon, Sanchez-Niño, Maria Dolore, Sánchez-Pimienta, Tania G., Santomauro, Damian, Santos, Itamar S., Santric Milicevic, Milena M., Sartorius, Benn, Satpathy, Maheswar, Sawhney, Monika, Saxena, Sonia, Schaeffner, Elke, Schmidt, Maria Inê, Schneider, Ione J.C., Schutte, Aletta E., Schwebel, David C., Schwendicke, Falk, Seedat, Soraya, Sepanlou, Sadaf G., Serdar, Berrin, Servan-Mori, Edson E., Shaddick, Gavin, Shaheen, Amira, Shahraz, Saeid, Shaikh, Masood Ali, Shamah Levy, Teresa, Shamsipour, Mansour, Shamsizadeh, Morteza, Shariful Islam, Sheikh Mohammed, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Shen, Jiabin, Shi, Peilin, Shibuya, Kenji, Shields, Chloe, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shin, Min-Jeong, Shiri, Rahman, Shirkoohi, Reza, Shishani, Kawkab, Shoman, Haitham, Shrime, Mark G., Sigfusdottir, Inga Dora, Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singh, Jasvinder A., Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Slepak, Erica Leigh, Smith, David L., Smith, Mari, Sobaih, Badr H.A., Sobngwi, Eugene, Soneji, Samir, Sorensen, Reed J.D., Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Srinivasan, Vinay, Steel, Nichola, Stein, Dan J., Steiner, Caitlyn, Steinke, Sabine, Stokes, Mark Andrew, Strub, Bryan, Subart, Michelle, Sufiyan, 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Subjects
Líkamsþyngdarstuðull, Dánarmein, Heilsufar, Dánartíðni, Birthweight, Fæðingarþyngd, Börn, HEALTH-RISKS, Pregnancy, EPIDEMIOLOGY, Psychology, Meðganga, Children, Konur, Body mass index, PRECAUTIONARY PRINCIPLE, Public health, Global burden of disease/statistics and numerical data, Medicine (all), Smoking, COST, Men, 11 Medical And Health Sciences, Health policy, Háþrýstingur, Sálfræði, World health, Hypertension, Lýðheilsa, Reykingar, Life Sciences & Biomedicine, COUNTRIES, Quality of life, DEATHS, Lífsgæði, Health risk assessment, Medicine, General & Internal, Heilbrigðisvísindi, General & Internal Medicine, Heilbrigðisstefna, Women, Mortality, Áhættugreining, CHINESE POPULATION, OBESITY PREVENTION, Science & Technology, HYPERTENSION, MORTALITY, Malnutrition, Næringarskortur, Karlar, Cause of death/trends, RA
Abstract

Correction in: LANCET Volume: 390 Issue: 10104 Pages: 1736-1736 Published: OCT 14 2017 ; LANCET Volume: 390 Issue: 10106 Pages: E38-E38 Published: OCT 28 2017., Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22 717 randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according to the GBD 2016 source counting methods. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. Finally, we explored four drivers of trends in attributable burden: population growth, population ageing, trends in risk exposure, and all other factors combined. Findings Since 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and household air pollution showed the most significant declines, while metabolic risks, such as body-mass index and high fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors in terms of attributable DALYs at the global level for men were smoking (124.1 million DALYs [95% UI 111.2 million to 137.0 million]), high systolic blood pressure (122.2 million DALYs [110.3 million to 133.3 million], and low birthweight and short gestation (83.0 million DALYs [78.3 million to 87.7 million]), and for women, were high systolic blood pressure (89.9 million DALYs [80.9 million to 98.2 million]), high body-mass index (64.8 million DALYs [44.4 million to 87.6 million]), and high fasting plasma glucose (63.8 million DALYs [53.2 million to 76.3 million]). In 2016 in 113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains an 9.3% (6.9-11.6) decline in deaths and a 10.8% (8.3-13.1) decrease in DALYs at the global level, while population ageing accounts for 14.9% (12.7-17.5) of deaths and 6.2% (3.9-8.7) of DALYs, and population growth for 12.4% (10.1-14.9) of deaths and 12.4% (10.1-14.9) of DALYs. The largest contribution of trends in risk exposure to disease burden is seen between ages 1 year and 4 years, where a decline of 27.3% (24.9-29.7) of the change in DALYs between 2006 and 2016 can be attributed to declines in exposure to risks. Interpretation Increasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to global disease burden, increasing trends, and variable patterns across countries at the same level of development. GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively small part in the past decade., The Bill & Melinda Gates Foundation, Bloomberg Philanthropies.

Published
2017

16. Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries : an analysis from the Global Burden of Disease Study 2016

Author

Fullman, Nancy, Barber, Ryan M, Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, Abdulkader, Rizwan Suliankatchi, Abdulle, Abdishakur M, Abera, Semaw Ferede, Aboyans, Victor, De Steur, Hans, Gupta, Vipin, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Nguyen, Quyen Le, Stanaway, Jeffrey D, Atre, Sachin R, Kim, Daniel, Criqui, Michael H, Aryal, Krishna Kumar, Ahmadieh, Hamid, Stein, Dan J, Steiner, Caitlyn, Steinke, Sabine, Stokes, Mark Andrew, Strub, Bryan, Aichour, Miloud Taki Eddine, Nguyen, Trang Huyen, Defo, Barthelemy Kuate, Sufiyan, Muawiyyah Babale, Dandona, Rakhi, Mantovani, Lorenzo G, Sunguya, Bruno F, Sur, Patrick J, Mazidi, Mohsen, Kimokoti, Ruth W, Swaminathan, Soumya, Sykes, Bryan L, Avila-Burgos, Leticia, Sylte, Dillon O, Nguyen, Grant, Schwebel, David C, Szoeke, Cassandra E I, Murthy, Gudlavalleti Venkata Satyanarayana, Tabarés-Seisdedos, Rafael, Hafezi-Nejad, Nima, Tadakamadla, Santosh Kumar, Degenhardt, Louisa, McAlinden, Colm, Tandon, Nikhil, Kinfu, Yohannes, Tao, Tianchan, Schwendicke, Falk, Tarekegn, Yihunie L, Giref, Ababi Zergaw, Ahmed, Muktar Beshir, Tavakkoli, Mohammad, Taveira, Nuno, Tegegne, Teketo Kassaw, Avokpaho, Euripide Frinel G Arthur, Terkawi, Abdullah Sulieman, Hailu, Gessessew Bugssa, Alla, François, Seedat, Soraya, Tessema, Gizachew Assefa, Thakur, JS, Alam, Khurshid, Rajsic, Sasa, Nguyen, Minh, Deiparine, Selina, Thankappan, Kavumpurathu Raman, Thrift, Amanda G, Tiruye, Tenaw Yimer, Tobe-Gai, Ruoyan, Martin, Randall V, Topor-Madry, Roman, Torre, Anna, McGaughey, Madeline, Tortajada, Miguel, Ram, Usha, Hamadeh, Randah Ribhi, Nichols, Emma, Awasthi, Ashish, Fürst, Thomas, Tran, Bach Xuan, Sepanlou, Sadaf G, Troeger, Christopher, Deribe, Kebede, Truelsen, Thomas, Tsoi, Derrick, Tuem, Kald Beshir, Ranabhat, Chhabi Lal, McGrath, John J, Tuzcu, Emin Murat, Majeed, Azeem, Tyrovolas, Stefanos, Servan-Mori, Edson E, Ukwaja, Kingsley N, Hammami, Mouhanad, Kisa, 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Quyen Le, Nguyen, Trang Huyen, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nomura, Marika, Nong, Vuong Minh, Norheim, Ole F., Noubiap, Jean Jacques N., Obermeyer, Carla Makhlouf, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew Toyin, Olagunju, Tinuke Oluwasefunmi, Olivares, Pedro R., Olsen, Helen E., Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin, Oren, Eyal, Ortiz, Alberto, Owolabi, Mayowa O., Mahesh, P.A., Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Papachristou, Christina, Park, Eun-Kee, Patton, George C., Paulson, Katherine, Pereira, David M., Perico, David Norberto, Pesudovs, Konrad, Petzold, Max, Phillips, Michael Robert, Pigott, David M., Pillay, Julian David, Pinho, Christine, Piradov, Michael A., Pishgar, Farhad, Poulton, Richie G., Pourmalek, Farshad, Qorbani, Mostafa, Radfar, Amir, Rafay, Anwar, Rao, Puja C., Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Ur Rahman, Mohammad Hifz, Rahman, Muhammad Aziz, Rai, Rajesh Kumar, Rajsic, Sasa, Ram, Usha, Ranabhat, Chhabi Lal, Rawaf, Salman, Reidy, Patrick, Reiner, Robert C., Reinig, Nikola, Reitsma, Marissa B., Remuzzi, Giuseppe, Renzaho, Andre M.N., Resnikoff, Serge, Rezaei, Satar, Blancas, Maria Jesus Rio, Roba, Kedir Teji, Rojas-Rueda, David, Rokni, Mohammad Bagher, Roshandel, Gholamreza, Roth, Gregory A., Roy, Ambuj, Rubagotti, Enrico, Sadat, Nafi, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Salama, Joseph, Salomon, Joshua A., Samy, Abdallah M., Sanabria, Juan Ramon, Santomauro, Damian, Santos, Itamar S., Santos, João Vasco, Santric Milicevic, Milena M., Sartorius, Benn, Satpathy, Maheswar, Sawhney, Monika, Saxena, Sonia, Saylan, Mete I., Shirude, Shreya, Schmidt, Maria Inê, Schneider, Ione J.C., Schneider, Matthew T., Schöttker, Ben, Schutte, Aletta E., Schwebel, David C., Schwendicke, Falk, Seedat, Soraya, Sepanlou, Sadaf G., Servan-Mori, Edson E., Shackelford, Katya Anne, Shaheen, Amira, Shahraz, Saeid, Shaikh, Masood Ali, Shamsipour, Mansour, Shamsizadeh, Morteza, Islam, Sheikh Mohammed Shariful, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Shi, Peilin, Shibuya, Kenji, Shields, Chloe, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shin, Min-Jeong, Shiri, Rahman, Shirkoohi, Reza, Shishani, Kawkab, Shoman, Haitham, Shrime, Mark G., Silberberg, Donald H., Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singh, Jasvinder A., Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Slepak, Erica Leigh, Sligar, Amber, Smith, Alison, Smith, David L., Smith, Mari, Sobaih, Badr H.A., Sobngwi, Eugene, Soljak, Michael, Soneji, Samir, Sorensen, Reed J.D., Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Srinivasan, Vinay, Stanaway, Jeffrey D., Stein, Dan J., Steiner, Caitlyn, Steinke, Sabine, Stokes, Mark Andrew, Strub, Bryan, Sufiyan, Muawiyyah Babale, Abdulkader, Rizwan Suliankatchi, Sunguya, Bruno F., Sur, Patrick J., Swaminathan, Soumya, Sykes, Bryan L., Sylte, Dillon O., Szoeke, Cassandra E.I., Tabarés-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Tandon, Nikhil, Tao, Tianchan, Tarekegn, Yihunie L., Tavakkoli, Mohammad, Taveira, Nuno, Tegegne, Teketo Kassaw, Shifa, Girma Temam, Terkawi, Abdullah Sulieman, Tessema, Gizachew Assefa, Thakur, J.S., Thankappan, Kavumpurathu Raman, Thrift, Amanda G., Tiruye, Tenaw Yimer, Tobe-Gai, Ruoyan, Topor-Madry, Roman, Torre, Anna, Tortajada, Miguel, Tran, Bach Xuan, Troeger, Christopher, Truelsen, Thoma, Tsoi, Derrick, Tuem, Kald Beshir, Tuzcu, Emin Murat, Tyrovolas, Stefano, Ukwaja, Kingsley N., Uneke, Chigozie Jesse, Updike, Rachel, Uthman, Olalekan A., Van Boven, Job F.M., Van Donkelaar, Aaron, Varughese, Santosh, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Vidavalur, Ramesh, Violante, Francesco S., Vladimirov, Sergey K., Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Vos, Theo, Wadilo, Fiseha, Wakayo, Tolassa, Wallin, Mitchell T., Wang, Yuan-Pang, Weichenthal, Scott, Weiderpass, Elisabete, Weintraub, Robert G., Weiss, Daniel J., Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A., Wijeratne, Tissa, Wiysonge, Charles Shey, Woldeyes, Belete Getahun, Wolfe, Charles D.A., Woodbrook, Rachel, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yakob, Bereket, Yan, Lijing L., Yano, Yuichiro, Yaseri, Mehdi, Ye, Pengpeng, Yimam, Hassen Hamid, Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z., Zaidi, Zoubida, El Sayed Zaki, Maysaa, Zavala-Arciniega, Lui, Zhang, Xueying, Zipkin, Ben, Zodpey, Sanjay, Lim, Stephen S., Murray, Christopher J.L., Fullman, N, Barber, R, Abajobir, A, Abate, K, Abbafati, C, Abbas, K, Abd-Allah, F, Abdulle, A, Abera, S, Aboyans, V, Abu-Raddad, L, Abu-Rmeileh, N, Adedeji, I, Adetokunboh, O, Afshin, A, Agrawal, A, Agrawal, S, Kiadaliri, A, Ahmadieh, H, Ahmed, M, Aichour, A, Aichour, I, Aichour, M, Aiyar, S, Akinyemi, R, Akseer, N, Al-Aly, Z, Alam, K, Alam, N, Alasfoor, D, Alene, K, Alizadeh-Navaei, R, Alkerwi, A, Alla, F, Allebeck, P, Allen, C, Al-Raddadi, R, Alsharif, U, Altirkawi, K, Alvis-Guzman, N, Amare, A, Amini, E, Ammar, W, Antonio, C, Ansari, H, Anwari, P, Arora, M, Artaman, A, Aryal, K, Asayesh, H, Asgedom, S, Assadi, R, Atey, T, Atre, S, Avila-Burgos, L, Arthur Avokpaho, E, Awasthi, A, Azzopardi, P, Bacha, U, Badawi, A, Balakrishnan, K, Bannick, M, Barac, A, Barker-Collo, S, Bärnighausen, T, Barrero, L, Basu, S, Battle, K, Baune, B, Beardsley, J, Bedi, N, Beghi, E, Béjot, Y, Bell, M, Bennett, D, Bennett, J, Bensenor, I, Berhane, A, Berhe, D, Bernabé, E, Betsu, B, Beuran, M, Beyene, A, Bhala, N, Bhansali, A, Bhatt, S, Bhutta, Z, Bikbov, B, Bilal, A, Birungi, C, Biryukov, S, Bizuayehu, H, Blosser, C, Boneya, D, Bose, D, Bou-Orm, I, Brauer, M, Breitborde, N, Brugha, T, Bulto, L, Butt, Z, Cahuana-Hurtado, L, Cameron, E, Campuzano, J, Carabin, H, Cárdenas, R, Carrero, J, Carter, A, Casey, D, Castañeda-Orjuela, C, Rivas, J, Castro, R, Catalá-López, F, Cercy, K, Chang, H, Chang, J, Charlson, F, Chew, A, Chisumpa, V, Chitheer, A, Christensen, H, Christopher, D, Cirillo, M, Cooper, C, Criqui, M, Cromwell, E, Crump, J, Dandona, L, Dandona, R, Dargan, P, Das Neves, J, Davitoiu, D, De Courten, B, De Steur, H, Degenhardt, L, Deiparine, S, Deribe, K, Deveber, G, Ding, E, Djalalinia, S, Do, H, Dokova, K, Doku, D, Dorsey, E, Driscoll, T, Dubey, M, Duncan, B, Ebel, B, Ebrahimi, H, El-Khatib, Z, Enayati, A, Endries, A, Ermakov, S, Erskine, H, Eshrati, B, Eskandarieh, S, Esteghamati, A, Estep, K, Faraon, E, Sofia E Sa Farinha, C, Faro, A, Farzadfar, F, Fazeli, M, Feigin, V, Feigl, A, Fereshtehnejad, S, Fernandes, J, Ferrari, A, Feyissa, T, Filip, I, Fischer, F, Fitzmaurice, C, Flaxman, A, Foigt, N, Foreman, K, Frank, T, Franklin, R, Friedman, J, Frostad, J, Fürst, T, Furtado, J, Gakidou, E, Garcia-Basteiro, A, Gebrehiwot, T, Geleijnse, J, Geleto, A, Gemechu, B, Gething, P, Gibney, K, Gill, P, Gillum, R, Giref, A, Gishu, M, Giussani, G, Glenn, S, Godwin, W, Goldberg, E, Gona, P, Goodridge, A, Gopalani, S, Goryakin, Y, Griswold, M, Gugnani, H, Gupta, R, Gupta, T, Gupta, V, Hafezi-Nejad, N, Bidgoli, H, Hailu, G, Hamadeh, R, Hammami, M, Hankey, G, Harb, H, Hareri, H, Hassanvand, M, Havmoeller, R, Hawley, C, Hay, S, He, J, Hendrie, D, Henry, N, Heredia-Pi, I, Hoek, H, Holmberg, M, Horita, N, Hosgood, H, Hostiuc, S, Hoy, D, Hsairi, M, Htet, A, Huang, H, Huang, J, Huynh, C, Iburg, K, Ikeda, C, Inoue, M, Irvine, C, Jacobsen, K, Jahanmehr, N, Jakovljevic, M, Jauregui, A, Javanbakht, M, Jeemon, P, Jha, V, John, D, Johnson, C, Johnson, S, Jonas, J, Jürisson, M, Kabir, Z, Kadel, R, Kahsay, A, Kamal, R, Karch, A, Karema, C, Kasaeian, A, Kassebaum, N, Kastor, A, Katikireddi, S, Kawakami, N, Keiyoro, P, Kelbore, S, Kemmer, L, Kengne, A, Kesavachandran, C, Khader, Y, Khalil, I, Khan, E, Khang, Y, Khosravi, A, Khubchandani, J, Kieling, C, Kim, D, Kim, J, Kim, Y, Kimokoti, R, Kinfu, Y, Kisa, A, Kissimova-Skarbek, K, Kivimaki, M, Kokubo, Y, Kopec, J, Kosen, S, Koul, P, Koyanagi, A, Kravchenko, M, Krohn, K, Defo, B, Bicer, B, Kulikoff, X, Kumar, G, Kutz, M, Kyu, H, Lal, D, Lalloo, R, Lansingh, V, Larsson, A, Lazarus, J, Lee, P, Leigh, J, Leung, J, Leung, R, Levi, M, Li, Y, Liben, M, Linn, S, Liu, P, Liu, S, Lodha, R, Looker, K, Lopez, A, Lorkowski, S, Lotufo, P, Lozano, R, Lucas, T, Lunevicius, R, Mackay, M, Maddison, E, El Razek, H, El Razek, M, Majdan, M, Majdzadeh, R, Majeed, A, Malekzadeh, R, Malhotra, R, Malta, D, Mamun, A, Manguerra, H, Mantovani, L, Manyazewal, T, Mapoma, C, Marks, G, Martin, R, Martinez-Raga, J, Martins-Melo, F, Martopullo, I, Mathur, M, Mazidi, M, Mcalinden, C, Mcgaughey, M, Mcgrath, J, Mckee, M, Mehata, S, Mehndiratta, M, Meier, T, Meles, K, Memish, Z, Mendoza, W, Mengesha, M, Mengistie, M, Mensah, G, Mensink, G, Mereta, S, Meretoja, A, Meretoja, T, Mezgebe, H, Micha, R, Millear, A, Miller, T, Minnig, S, Mirarefin, M, Mirrakhimov, E, Misganaw, A, Mishra, S, Mitchell, P, Mohammad, K, Mohammed, K, Mohammed, S, Mohan, M, Mokdad, A, Mollenkopf, S, Monasta, L, Hernandez, J, Montico, M, Moradi-Lakeh, M, Moraga, P, Morawska, L, Morrison, S, Moses, M, Mountjoy-Venning, C, Mueller, U, Muller, K, Murthy, G, Musa, K, Naghavi, M, Naheed, A, Naidoo, K, Nangia, V, Natarajan, G, Negoi, I, Negoi, R, Nguyen, C, Nguyen, G, Nguyen, M, Nguyen, Q, Nguyen, T, Nichols, E, Ningrum, D, Nomura, M, Nong, V, Norheim, O, Noubiap, J, Obermeyer, C, Ogbo, F, Oh, I, Oladimeji, O, Olagunju, A, Olagunju, T, Olivares, P, Olsen, H, Olusanya, B, Olusanya, J, Ong, K, Oren, E, Ortiz, A, Owolabi, M, Mahesh, P, Pana, A, Panda, B, Panda-Jonas, S, Papachristou, C, Park, E, Patton, G, Paulson, K, Pereira, D, Perico, D, Pesudovs, K, Petzold, M, Phillips, M, Pigott, D, Pillay, J, Pinho, C, Piradov, M, Pishgar, F, Poulton, R, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rao, P, Rahimi-Movaghar, V, Rahman, M, Ur Rahman, M, Rai, R, Rajsic, S, Ram, U, Ranabhat, C, Rawaf, S, Reidy, P, Reiner, R, Reinig, N, Reitsma, M, Remuzzi, G, Renzaho, A, Resnikoff, S, Rezaei, S, Blancas, M, Roba, K, Rojas-Rueda, D, Rokni, M, Roshandel, G, Roth, G, Roy, A, Rubagotti, E, Sadat, N, Safdarian, M, Safi, S, Safiri, S, Sagar, R, Salama, J, Salomon, J, Samy, A, Sanabria, J, Santomauro, D, Santos, I, Santos, J, Santric Milicevic, M, Sartorius, B, Satpathy, M, Sawhney, M, Saxena, S, Saylan, M, Shirude, S, Schmidt, M, Schneider, I, Schneider, M, Schöttker, B, Schutte, A, Schwebel, D, Schwendicke, F, Seedat, S, Sepanlou, S, Servan-Mori, E, Shackelford, K, Shaheen, A, Shahraz, S, Shaikh, M, Shamsipour, M, Shamsizadeh, M, Islam, S, Sharma, J, Sharma, R, She, J, Shi, P, Shibuya, K, Shields, C, Shiferaw, M, Shigematsu, M, Shin, M, Shiri, R, Shirkoohi, R, Shishani, K, Shoman, H, Shrime, M, Silberberg, D, Silva, D, Silva, J, Silveira, D, Singh, J, Singh, V, Sinha, D, Skiadaresi, E, Slepak, E, Sligar, A, Smith, A, Smith, D, Smith, M, Sobaih, B, Sobngwi, E, Soljak, M, Soneji, S, Sorensen, R, Sposato, L, Sreeramareddy, C, Srinivasan, V, Stanaway, J, Stein, D, Steiner, C, Steinke, S, Stokes, M, Strub, B, Sufiyan, M, Abdulkader, R, Sunguya, B, Sur, P, Swaminathan, S, Sykes, B, Sylte, D, Szoeke, C, Tabarés-Seisdedos, R, Tadakamadla, S, Tandon, N, Tao, T, Tarekegn, Y, Tavakkoli, M, Taveira, N, Tegegne, T, Shifa, G, Terkawi, A, Tessema, G, Thakur, J, Thankappan, K, Thrift, A, Tiruye, T, Tobe-Gai, R, Topor-Madry, R, Torre, A, Tortajada, M, Tran, B, Troeger, C, Truelsen, T, Tsoi, D, Tuem, K, Tuzcu, E, Tyrovolas, S, Ukwaja, K, Uneke, C, Updike, R, Uthman, O, Van Boven, J, Van Donkelaar, A, Varughese, S, Vasankari, T, Venketasubramanian, N, Vidavalur, R, Violante, F, Vladimirov, S, Vlassov, V, Vollset, S, Vos, T, Wadilo, F, Wakayo, T, Wallin, M, Wang, Y, Weichenthal, S, Weiderpass, E, Weintraub, R, Weiss, D, Werdecker, A, Westerman, R, Whiteford, H, Wijeratne, T, Wiysonge, C, Woldeyes, B, Wolfe, C, Woodbrook, R, Xavier, D, Xu, G, Yadgir, S, Yakob, B, Yan, L, Yano, Y, Yaseri, M, Ye, P, Yimam, H, Yip, P, Yonemoto, N, Yoon, S, Yotebieng, M, Younis, M, Zaidi, Z, El Sayed Zaki, M, Zavala-Arciniega, L, Zhang, X, Zipkin, B, Zodpey, S, Lim, S, and Murray, C

Subjects
Adult, Male, Adolescent, DEVELOPMENT ASSISTANCE, Global Health, projection indicators to 2030, CHINA, Global Burden of Disease, Health Statu, MEXICO, Noncommunicable Disease, Young Adult, SYSTEMS, Quality-Adjusted Life Year, General & Internal Medicine, Infant Mortality, Medicine and Health Sciences, Conservation of Natural Resource, gains and gaps for the health-related SDGs,annualized rates of change, projection indicators to 2030, Health Status Indicator, annualized rates of change, Child, Medicine (all), MORTALITY, Infant, Newborn, Infant, Child Abuse, Sexual, Middle Aged, PREPAID PRIVATE, CARE, COVERAGE, Sex Offense, Child, Preschool, Female, 40-PERCENT, GOVERNMENT, gains and gaps for the health-related SDGs, Human
Abstract

Background The UN's Sustainable Development Goals (SDGs) are grounded in the global ambition of "leaving no one behind". Understanding today's gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990-2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030. Methods We used standardised GBD 2016 methods to measure 37 health-related indicators from 1990 to 2016, an increase of four indicators since GBD 2015. We substantially revised the universal health coverage (UHC) measure, which focuses on coverage of essential health services, to also represent personal health-care access and quality for several non-communicable diseases. We transformed each indicator on a scale of 0-100, with 0 as the 2.5th percentile estimated between 1990 and 2030, and 100 as the 97.5th percentile during that time. An index representing all 37 health-related SDG indicators was constructed by taking the geometric mean of scaled indicators by target. On the basis of past trends, we produced projections of indicator values, using a weighted average of the indicator and country-specific annualised rates of change from 1990 to 2016 with weights for each annual rate of change based on out-of-sample validity. 24 of the currently measured health-related SDG indicators have defined SDG targets, against which we assessed attainment. Findings Globally, the median health-related SDG index was 56.7 (IQR 31.9-66.8) in 2016 and country-level performance markedly varied, with Singapore (86.8, 95% uncertainty interval 84.6-88.9), Iceland (86.0, 84.1-87.6), and Sweden (85.6, 81.8-87.8) having the highest levels in 2016 and Afghanistan (10.9, 9.6-11.9), the Central African Republic (11.0, 8.8-13.8), and Somalia (11.3, 9.5-13.1) recording the lowest. Between 2000 and 2016, notable improvements in the UHC index were achieved by several countries, including Cambodia, Rwanda, Equatorial Guinea, Laos, Turkey, and China; however, a number of countries, such as Lesotho and the Central African Republic, but also high-income countries, such as the USA, showed minimal gains. Based on projections of past trends, the median number of SDG targets attained in 2030 was five (IQR 2-8) of the 24 defined targets currently measured. Globally, projected target attainment considerably varied by SDG indicator, ranging from more than 60% of countries projected to reach targets for under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria, to less than 5% of countries projected to achieve targets linked to 11 indicator targets, including those for childhood overweight, tuberculosis, and road injury mortality. For several of the health-related SDGs, meeting defined targets hinges upon substantially faster progress than what most countries have achieved in the past. Interpretation GBD 2016 provides an updated and expanded evidence base on where the world currently stands in terms of the health-related SDGs. Our improved measure of UHC offers a basis to monitor the expansion of health services necessary to meet the SDGs. Based on past rates of progress, many places are facing challenges in meeting defined health-related SDG targets, particularly among countries that are the worst off. In view of the early stages of SDG implementation, however, opportunity remains to take actions to accelerate progress, as shown by the catalytic effects of adopting the Millennium Development Goals after 2000. With the SDGs' broader, bolder development agenda, multisectoral commitments and investments are vital to make the health-related SDGs within reach of all populations. Copyright The Authors. Published by Elsevier Ltd. This is an Open Access article published under the CC BY 4.0 license.

Published
2017

17. Assessing the future medical cost burden for the European health systems under alternative exposure-to-risks scenarios.

Author

Goryakin Y, Thiébaut SP, Cortaredona S, Lerouge MA, Cecchini M, Feigl AB, and Ventelou B

Subjects
Adult, Aged, Body Mass Index, Europe, Female, Health Expenditures, Humans, Male, Middle Aged, Risk Factors, Cost of Illness, Delivery of Health Care economics, Delivery of Health Care trends, Health Care Costs
Abstract

Background: Ageing populations and rising prevalence of non-communicable diseases (NCDs) increasingly contribute to the growing cost burden facing European healthcare systems. Few studies have attempted to quantify the future magnitude of this burden at the European level, and none of them consider the impact of potential changes in risk factor trajectories on future health expenditures., Methods: The new microsimulation model forecasts the impact of behavioural and metabolic risk factors on NCDs, longevity and direct healthcare costs, and shows how changes in epidemiological trends can modify those impacts. Economic burden of NCDs is modelled under three scenarios based on assumed future risk factors trends: business as usual (BAU); best case and worst case predictions (BCP and WCP)., Findings: The direct costs of NCDs in the EU 27 countries and the UK (in constant 2014 prices) will grow under all scenarios. Between 2014 and 2050, the overall healthcare spending is expected to increase by 0.8% annually under BAU. In the all the countries, 605 billion Euros can be saved by 2050 if BCP is realized compared to the BAU, while excess spending under the WCP is forecast to be around 350 billion. Interpretation: Although the savings realised under the BCP can be substantial, population ageing is a stronger driver of rising total healthcare expenditures in Europe compared to scenario-based changes in risk factor prevalence., Competing Interests: The authors have declared that no competing interests exist.

Published
2020
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18. Promoting sport and physical activity in Italy: a cost-effectiveness analysis of seven innovative public health policies.

Author

Goryakin Y, Aldea A, Lerouge A, Romano Spica V, Nante N, Vuik S, Devaux M, and Cecchini M

Subjects
Cost-Benefit Analysis, Health Expenditures statistics & numerical data, Health Promotion economics, Humans, Italy, Life Style, Models, Economic, Quality-Adjusted Life Years, Risk Factors, Sedentary Behavior, Exercise physiology, Health Policy, Health Promotion methods, Public Policy
Abstract

Background: Inactive lifestyles are a key risk factor underpinning the development of many chronic diseases, yet more than half of the Italian population does not meet WHO thresholds for at least moderate physical activity. This study aims to make the economic case to upscale investments in policy actions to promote exercise and physical activity., Study Design: Modelling-based cost-effectiveness analysis in Italy., Methods: The study assesses the impact on health and healthcare expenditure of seven public health policies to promote exercise and physical activity against a business as usual scenario. Assessed policies include: promotion of active transport, workplace sedentarily interventions, investments in sports and recreation, mass media campaigns, prescription of physical activity in primary care, school-based interventions and mobile apps., Results: Public policies to promote exercise have the potential to improve population health and produce savings in healthcare expenditure. Assessed policies can avoid hundreds of cases of cardiovascular diseases and diabetes per year and tens of cases of cancer resulting in gains in DALYs in the order of thousands per year. In the medium-term, the vast majority of policies show excellent cost-effectiveness ratio, below internationally recognized thresholds., Conclusions: Investing in policies to promote active lifestyles is a good investment for Italy.

Published
2019
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19. The short-term effect of BMI, alcohol use, and related chronic conditions on labour market outcomes: A time-lag panel analysis utilizing European SHARE dataset.

Author

Feigl AB, Goryakin Y, Devaux M, Lerouge A, Vuik S, and Cecchini M

Subjects
Absenteeism, Adult, Alcohol Drinking, Alcoholism epidemiology, Body Mass Index, Cardiovascular Diseases, Chronic Disease, Diabetes Mellitus, Employment, Ethanol, Europe, Female, Humans, Male, Middle Aged, Noncommunicable Diseases economics, Noncommunicable Diseases epidemiology, Obesity epidemiology, Overweight, Risk Factors, Alcoholism economics, Obesity economics
Abstract

Introduction: Non-communicable diseases (NCDs) like cancer, cardiovascular disease, and diabetes have spread at a remarkable pace in European countries over the past decades. Overweight/obesity and alcohol use are two leading risk factors contributing to both economic and epidemiological burden associated with NCDs. In OECD countries, the impact of indirect costs of obesity varies between 0.20% and 1.21% of GDP. Indirect costs of alcohol use range from 0.19% (Portugal) to 1.6% (Estonia) of GDP., Aim: To assess the longitudinal impact of alcohol use and high body-mass index (BMI) on labour market outcomes in the European region by modeling the direct effect of high BMI and alcohol use, and the effect via associated diseases., Methods: The impact of BMI, alcohol use, and associated diseases on employment likelihood, intent to retire early, days of absenteeism, and hours of work per week, were modelled via lagged Poisson and Zero-inflated Poisson regressions, adjusting for missingness via inverse probability weighting, as appropriate, using European SHARE data., Results: Controlling for other chronic conditions, being overweight increases employment likelihood among men, but not among women. Obesity decreased female, but not male, employment chances. All chronic conditions linked with high BMI negatively affected employment likelihood, and increased the intention to retire early significantly. Alcohol use positively affects employment likelihood in women at all drinking levels relative to lifetime abstainers, but only in moderate (not heavy) male drinkers. There is super-additionality of impact of NCDs on absenteeism and hours worked, presenting a key economic argument to tackle NCD prevention and compression of morbidity., Implications: NCD prevention is not just important for employment and hours worked, but also for employee morale, especially given increasing retirement age in Europe and globally., Competing Interests: The authors have declared that no competing interests exist.

Published
2019
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20. Physical Activity Levels and New Public Transit: A Systematic Review and Meta-analysis.

Author

Xiao C, Goryakin Y, and Cecchini M

Subjects
Bicycling, Clinical Trials as Topic, Humans, Walking, Exercise, Transportation methods
Abstract

Context: Physical inactivity is a public health concern as it contributes to the rising burden of noncommunicable diseases. Introducing new public transportation options, such as extending or building new light rail or bus rapid transit stations, could encourage commuters to walk to and from public transit stops, thus increasing their physical activity levels. Despite previous research generally finding positive associations between public transit usage and physical activity levels, few have summarized the association between introducing new public transportation options and different intensities of physical activity. This study aimed to systematically review the current evidence and perform a meta-analysis on this association., Evidence Acquisition: Ten databases were systematically searched for studies published between 1997 and 2017. To ensure comparability, study outcomes were converted to MET hours/week. A random effects meta-analysis and sensitivity analysis were then conducted., Evidence Synthesis: Nine studies were identified to be included in the systematic review, of which five were eligible for meta-analysis. Pooled results suggest that building new public transit options is associated with a statistically significant increase in light to moderate physical activity levels by 1.76 MET hours/week (95% CI=0.19, 3.32, p=0.03). This is equivalent to increasing walking and other light to moderate physical activity by about 30 minutes per week, relative to baseline. No significant effect was found for the moderate to vigorous physical activity outcome., Conclusions: Results show new public transit options can substantially contribute to increasing low- to moderate-intensity exercise levels, which has the potential to improve health on a population scale., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Published
2019
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21. Does greater individual social capital improve the management of hypertension? Cross-national analysis of 61 229 individuals in 21 countries.

Author

Palafox B, Goryakin Y, Stuckler D, Suhrcke M, Balabanova D, Alhabib KF, Avezum A, Bahonar A, Bai X, Chifamba J, Dans AL, Diaz R, Gupta R, Iqbal R, Ismail N, Kaur M, Keskinler MV, Khatib R, Kruger A, Kruger IM, Lanas F, Lear SA, Li W, Liu J, Lopez-Jaramillo P, Peer N, Poirier P, Rahman O, Pillai RK, Rangarajan S, Rosengren A, Swaminathan S, Szuba A, Teo K, Wang Y, Wielgosz A, Yeates KE, Yusufali A, Yusuf S, and McKee M

Abstract

Introduction: Social capital, characterised by trust, reciprocity and cooperation, is positively associated with a number of health outcomes. We test the hypothesis that among hypertensive individuals, those with greater social capital are more likely to have their hypertension detected, treated and controlled., Methods: Cross-sectional data from 21 countries in the Prospective Urban and Rural Epidemiology study were collected covering 61 229 hypertensive individuals aged 35-70 years, their households and the 656 communities in which they live. Outcomes include whether hypertensive participants have their condition detected, treated and/or controlled. Multivariate statistical models adjusting for community fixed effects were used to assess the associations of three social capital measures: (1) membership of any social organisation, (2) trust in other people and (3) trust in organisations, stratified into high-income and low-income country samples., Results: In low-income countries, membership of any social organisation was associated with a 3% greater likelihood of having one's hypertension detected and controlled, while greater trust in organisations significantly increased the likelihood of detection by 4%. These associations were not observed among participants in high-income countries., Conclusion: Although the observed associations are modest, some aspects of social capital are associated with better management of hypertension in low-income countries where health systems are often weak. Given that hypertension affects millions in these countries, even modest gains at all points along the treatment pathway could improve management for many, and translate into the prevention of thousands of cardiovascular events each year., Competing Interests: Competing interests: None declared.

Published
2017
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23. Soft drink prices, sales, body mass index and diabetes: Evidence from a panel of low-, middle- and high-income countries.

Author

Goryakin Y, Monsivais P, and Suhrcke M

Abstract

We take advantage of four different cross-country datasets containing data on 78 countries for the period 1999-2014, in order to assess the relationship of carbonated soft drinks' sales, as well as their prices, with body mass index (BMI), overweight, obesity and diabetes. Using an ecological study design and multivariate regression longitudinal estimation approaches, we find that carbonated soft drink sales were significantly positively related to BMI, overweight and obesity - but only in the low and lower-middle income countries. This finding was robust to a number of sensitivity and falsification checks. In this sub-sample, an increase in per capita soft drink sales by 1 litre per year was related to an increase of BMI by about 0.009 kg/m 2 (p < 0.1).. This is a small effect, implying that halving annual consumption per capita in this group of countries would result in a drop of BMI by only about 0.03 kg/m 2 . Although soft drink prices were negatively related to weight-related outcomes in the sample of higher middle income and high income countries, this finding was not robust to falsification checks. The results thus suggest that sales restrictions to steer consumers away from soft drinks could indeed have a beneficial health effects in poorer countries, although the effect magnitude appears to be very small. However, given potential limitations of using ecological research design, results from individual level studies would be required to further ascertain the role of soft drink sales and prices in obesity and diabetes.

Published
2017
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24. The contribution of urbanization to non-communicable diseases: Evidence from 173 countries from 1980 to 2008.

Author

Goryakin Y, Rocco L, and Suhrcke M

Subjects
Adolescent, Adult, Empirical Research, Female, History, 20th Century, History, 21st Century, Humans, Male, Middle Aged, Young Adult, Internationality, Noncommunicable Diseases epidemiology, Urbanization history
Abstract

It is widely believed that the expanding burden of non-communicable diseases (NCDs) is in no small part the result of major macro-level determinants. We use a large amount of new data, to explore in particular the role played by urbanization - the process of the population shifting from rural to urban areas within countries - in affecting four important drivers of NCDs world-wide: diabetes prevalence, as well as average body mass index (BMI), total cholesterol level and systolic blood pressure. Urbanization is seen by many as a double-edged sword: while its beneficial economic effects are widely acknowledged, it is commonly alleged to produce adverse side effects for NCD-related health outcomes. In this paper we submit this hypothesis to extensive empirical scrutiny, covering a global set of countries from 1980-2008, and applying a range of estimation procedures. Our results indicate that urbanization appears to have contributed to an increase in average BMI and cholesterol levels: the implied difference in average total cholesterol between the most and the least urbanized countries is 0.40mmol/L, while people living in the least urbanized countries are also expected to have an up to 2.3kg/m 2 lower BMI than in the most urbanized ones. Moreover, the least urbanized countries are expected to have an up to 3.2p.p. lower prevalence of diabetes among women. This association is also much stronger in the low and middle-income countries, and is likely to be mediated by energy intake-related variables, such as calorie and fat supply per capita., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Published
2017
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25. Is foreign direct investment good for health in low and middle income countries? An instrumental variable approach.

Author

Burns DK, Jones AP, Goryakin Y, and Suhrcke M

Subjects
Gross Domestic Product statistics & numerical data, Humans, Investments statistics & numerical data, Life Expectancy trends, Quality Indicators, Health Care statistics & numerical data, Regression Analysis, United Nations statistics & numerical data, Developing Countries statistics & numerical data, Emigrants and Immigrants statistics & numerical data, Healthcare Financing, Investments standards, Quality Indicators, Health Care economics
Abstract

There is a scarcity of quantitative research into the effect of FDI on population health in low and middle income countries (LMICs). This paper investigates the relationship using annual panel data from 85 LMICs between 1974 and 2012. When controlling for time trends, country fixed effects, correlation between repeated observations, relevant covariates, and endogeneity via a novel instrumental variable approach, we find FDI to have a beneficial effect on overall health, proxied by life expectancy. When investigating age-specific mortality rates, we find a stronger beneficial effect of FDI on adult mortality, yet no association with either infant or child mortality. Notably, FDI effects on health remain undetected in all models which do not control for endogeneity. Exploring the effect of sector-specific FDI on health in LMICs, we provide preliminary evidence of a weak inverse association between secondary (i.e. manufacturing) sector FDI and overall life expectancy. Our results thus suggest that FDI has provided an overall benefit to population health in LMICs, particularly in adults, yet investments into the secondary sector could be harmful to health., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Published
2017
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26. The impact of poor adult health on labor supply in the Russian Federation.

Author

Goryakin Y and Suhrcke M

Subjects
Adolescent, Adult, Age Distribution, Aged, Female, Humans, Male, Middle Aged, Residence Characteristics statistics & numerical data, Russia epidemiology, Self Report, Severity of Illness Index, Sex Distribution, Socioeconomic Factors, Young Adult, Chronic Disease epidemiology, Employment statistics & numerical data, Health Status
Abstract

We examine the labor supply consequences of poor health in the Russian Federation, a country with exceptionally adverse adult health outcomes. In both baseline OLS models and in models with individual fixed effects, more serious ill-health events, somewhat surprisingly, generally have only weak effects on hours worked. At the same time, their effect on the extensive margin of labor supply is substantial. Moreover, when combining the effects on both the intensive and extensive margins, the effect of illness on hours worked increases considerably for a range of conditions. In addition, for most part of the age distribution, people with poor self-assessed health living in rural areas are less likely to stop working, compared to people living in cities. While there is no conclusive explanation for this finding, it could be related to the existence of certain barriers that prevent people with poor health from withdrawing from the labor force in order to take care of their health.

Published
2017
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28. Global Health Workforce Labor Market Projections for 2030.

Author

Liu JX, Goryakin Y, Maeda A, Bruckner T, and Scheffler R

Subjects
Age Factors, Aging, Developing Countries, Economic Development, Employment, Forecasting, Health Services Accessibility, Humans, Income, Public Health, World Health Organization, Delivery of Health Care, Global Health, Health Personnel, Health Services, Health Services Needs and Demand, Health Workforce, Population Growth
Abstract

Background: In low- and middle-income countries, scaling essential health interventions to achieve health development targets is constrained by the lack of skilled health professionals to deliver services., Methods: We take a labor market approach to project future health workforce demand based on an economic model based on projected economic growth, demographics, and health coverage, and using health workforce data (1990-2013) for 165 countries from the WHO Global Health Observatory. The demand projections are compared with the projected growth in health worker supply and the health worker "needs" as estimated by WHO to achieve essential health coverage., Results: The model predicts that, by 2030, global demand for health workers will rise to 80 million workers, double the current (2013) stock of health workers, while the supply of health workers is expected to reach 65 million over the same period, resulting in a worldwide net shortage of 15 million health workers. Growth in the demand for health workers will be highest among upper middle-income countries, driven by economic and population growth and aging. This results in the largest predicted shortages which may fuel global competition for skilled health workers. Middle-income countries will face workforce shortages because their demand will exceed supply. By contrast, low-income countries will face low growth in both demand and supply, which are estimated to be far below what will be needed to achieve adequate coverage of essential health services., Conclusions: In many low-income countries, demand may stay below projected supply, leading to the paradoxical phenomenon of unemployed ("surplus") health workers in those countries facing acute "needs-based" shortages. Opportunities exist to bend the trajectory of the number and types of health workers that are available to meet public health goals and the growing demand for health workers.

Published
2017
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30. Crime and subjective well-being in the countries of the former Soviet Union.

Author

Stickley A, Koyanagi A, Roberts B, Goryakin Y, and McKee M

Subjects
Adolescent, Adult, Asia, Crime, Cross-Sectional Studies, Diagnostic Self Evaluation, Europe, Female, Humans, Male, Middle Aged, Surveys and Questionnaires, USSR, Young Adult, Crime Victims psychology, Happiness, Mental Health, Personal Satisfaction, Self Report, Theft psychology, Violence psychology
Abstract

Background: Criminal victimisation and subjective well-being have both been linked to health outcomes, although as yet, comparatively little is known about the relationship between these two phenomena. In this study we used data from nine countries of the former Soviet Union (fSU) to examine the association between different types of crime and subjective well-being., Methods: Data were obtained from 18,000 individuals aged 18 and above collected during the Health in Times of Transition (HITT) survey in 2010/11 in Armenia, Azerbaijan, Belarus, Georgia, Moldova, Kazakhstan, Kyrgyzstan, Russia and Ukraine. Information was obtained on respondents' experience of crime (violence and theft) and self-reported affective (happiness) and cognitive (life satisfaction) well-being. Ordered probit and ordinary least squares (OLS) regression analyses were undertaken to examine the associations between these variables., Results: In pooled country analyses, experiencing violence was associated with significantly lower happiness and life satisfaction. Theft victimisation was associated with significantly reduced life satisfaction but not happiness. Among the individual countries, there was a more pronounced association between violent victimisation and reduced happiness in Kazakhstan and Moldova., Conclusions: The finding that criminal victimisation is linked to lower levels of subjective well-being highlights the importance of reducing crime in the fSU, and also of having effective support services in place for victims of crime to reduce its detrimental effects on health and well-being.

Published
2015
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31. Fruit and vegetable consumption in the former Soviet Union: the role of individual- and community-level factors.

Author

Goryakin Y, Rocco L, Suhrcke M, Roberts B, and McKee M

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Diet Surveys, Female, Fruit, Humans, Male, Middle Aged, Nutrition Assessment, Restaurants, Sex Factors, Socioeconomic Factors, USSR, Vegetables, Young Adult, Commerce, Diet, Feeding Behavior, Food Supply, Residence Characteristics
Abstract

Objective: To explain patterns of fruit and vegetable consumption in nine former Soviet Union countries by exploring the influence of a range of individual- and community-level determinants., Design: Cross-sectional nationally representative surveys and area profiles were undertaken in 2010 in nine countries of the former Soviet Union as part of the Health in Times of Transition (HITT) study. Individual- and area-level determinants were analysed, taking into account potential confounding at the individual and area level., Setting: Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia and Ukraine., Subjects: Adult survey respondents (n 17 998) aged 18-95 years., Results: Being male, increasing age, lack of education and lack of financial resources were associated with lower probability of consuming adequate amounts of fruit or vegetables. Daily fruit or vegetable consumption was positively correlated with the number of shops selling fruit and vegetables (for women) and with the number of convenience stores (for men). Billboard advertising of snacks and sweet drinks was negatively related to daily fruit or vegetable consumption, although the reverse was true for billboards advertising soft drinks. Men living near a fast-food outlet had a lower probability of fruit or vegetable consumption, while the opposite was true for the number of local food restaurants., Conclusions: Overall fruit and vegetable consumption in the former Soviet Union is inadequate, particularly among lower socio-economic groups. Both individual- and community-level factors play a role in explaining inadequate nutrition and thus provide potential entry points for policy interventions, while the nuanced influence of community factors informs the agenda for future research.

Published
2015
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32. The impact of diabetes on employment in Mexico.

Author

Seuring T, Goryakin Y, and Suhrcke M

Subjects
Adolescent, Adult, Age Factors, Female, Humans, Male, Mexico epidemiology, Middle Aged, Regression Analysis, Sex Factors, Socioeconomic Factors, Young Adult, Diabetes Mellitus epidemiology, Employment statistics & numerical data
Abstract

This study explores the impact of diabetes on employment in Mexico using data from the Mexican Family Life Survey (MxFLS) (2005), taking into account the possible endogeneity of diabetes via an instrumental variable estimation strategy. We find that diabetes significantly decreases employment probabilities for men by about 10 percentage points (p<0.01) and somewhat less so for women - 4.5 percentage points (p<0.1)--without any indication of diabetes being endogenous. Further analysis shows that diabetes mainly affects the employment probabilities of men and women above the age of 44 and also has stronger effects on the poor than on the rich, particularly for men. We also find some indication for more adverse effects of diabetes on those in the large informal labour market compared to those in formal employment. Our results highlight--for the first time--the detrimental employment impact of diabetes in a developing country., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Published
2015
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33. The impact of economic, political and social globalization on overweight and obesity in the 56 low and middle income countries.

Author

Goryakin Y, Lobstein T, James WP, and Suhrcke M

Subjects
Acculturation, Developing Countries, Female, Humans, Income, Models, Statistical, Obesity, Socioeconomic Factors, Economic Development, Internationality, Overweight epidemiology, Politics
Abstract

Anecdotal and descriptive evidence has led to the claim that globalization plays a major role in inducing overweight and obesity in developing countries, but robust quantitative evidence is scarce. We undertook extensive econometric analyses of several datasets, using a series of new proxies for different dimensions of globalization potentially affecting overweight in up to 887,000 women aged 15-49 living in 56 countries between 1991 and 2009. After controlling for relevant individual and country level factors, globalization as a whole is substantially and significantly associated with an increase in the individual propensity to be overweight among women. Surprisingly, political and social globalization dominate the influence of the economic dimension. Hence, more consideration needs to be given to the forms of governance required to shape a more health-oriented globalization process., (Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Published
2015
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34. A systematic review on health resilience to economic crises.

Author

Glonti K, Gordeev VS, Goryakin Y, Reeves A, Stuckler D, McKee M, and Roberts B

Subjects
Female, Humans, Longitudinal Studies, Male, Economics, Resilience, Psychological
Abstract

Background: The health effects of recent economic crises differ markedly by population group. The objective of this systematic review is to examine evidence from longitudinal studies on factors influencing resilience for any health outcome or health behaviour among the general population living in countries exposed to financial crises., Methods: We systematically reviewed studies from six electronic databases (EMBASE, Global Health, MEDLINE, PsycINFO, Scopus, Web of Science) which used quantitative longitudinal study designs and included: (i) exposure to an economic crisis; (ii) changes in health outcomes/behaviours over time; (iii) statistical tests of associations of health risk and/or protective factors with health outcomes/behaviours. The quality of the selected studies was appraised using the Quality Assessment Tool for Quantitative Studies. PRISMA reporting guidelines were followed., Results: From 14,584 retrieved records, 22 studies met the eligibility criteria. These studies were conducted across 10 countries in Asia, Europe and North America over the past two decades. Ten socio-demographic factors that increased or protected against health risk were identified: gender, age, education, marital status, household size, employment/occupation, income/ financial constraints, personal beliefs, health status, area of residence, and social relations. These studies addressed physical health, mortality, suicide and suicide attempts, mental health, and health behaviours. Women's mental health appeared more susceptible to crises than men's. Lower income levels were associated with greater increases in cardiovascular disease, mortality and worse mental health. Employment status was associated with changes in mental health. Associations with age, marital status, and education were less consistent, although higher education was associated with healthier behaviours., Conclusions: Despite widespread rhetoric about the importance of resilience, there was a dearth of studies which operationalised resilience factors. Future conceptual and empirical research is needed to develop the epidemiology of resilience.

Published
2015
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35. Smoking status, nicotine dependence and happiness in nine countries of the former Soviet Union.

Author

Stickley A, Koyanagi A, Roberts B, Leinsalu M, Goryakin Y, and McKee M

Subjects
Adolescent, Adult, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Pleasure, Self Report, Socioeconomic Factors, USSR, Young Adult, Happiness, Nicotine adverse effects, Smoking psychology, Smoking Cessation psychology, Tobacco Use Disorder psychology
Abstract

Background: The US Food and Drug Administration has established a policy of substantially discounting the health benefits of reduced smoking in its evaluation of proposed regulations because of the cost to smokers of the supposed lost pleasure they suffer by no longer smoking. This study used data from nine countries of the former Soviet Union (fSU) to explore this association in a setting characterised by high rates of (male) smoking and smoking-related mortality., Methods: Data came from a cross-sectional population-based study undertaken in 2010/2011 in Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia and Ukraine. Information was collected from 18 000 respondents aged ≥18 on smoking status (never, ex-smoking and current smoking), cessation attempts and nicotine dependence. The association between these variables and self-reported happiness was examined using ordered probit regression analysis., Results: In a pooled country analysis, never smokers and ex-smokers were both significantly happier than current smokers. Smokers with higher levels of nicotine dependence were significantly less happy than those with a low level of dependence., Conclusions: This study contradicts the idea that smoking is associated with greater happiness. Moreover, of relevance for policy in the fSU countries, given the lack of public knowledge about the detrimental effects of smoking on health but widespread desire to quit reported in recent research, the finding that smoking is associated with lower levels of happiness should be incorporated in future public health efforts to help encourage smokers to quit by highlighting that smoking cessation may result in better physical and emotional health., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Published
2015
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36. Price elasticities of alcohol demand: evidence from Russia.

Author

Goryakin Y, Roberts B, and McKee M

Subjects
Adult, Female, Humans, Longitudinal Studies, Male, Middle Aged, Models, Econometric, Russia, Sex Factors, Socioeconomic Factors, Time Factors, Alcohol Drinking economics, Alcoholic Beverages economics, Costs and Cost Analysis statistics & numerical data
Abstract

In this paper, we estimate price elasticities of demand of several types of alcoholic drinks, using 14 rounds of data from the Russia Longitudinal Monitoring Survey-HSE, collected from 1994 until 2009. We deal with potential confounding problems by taking advantage of a large number of control variables, as well as by estimating community fixed effect models. All in all, although alcohol prices do appear to influence consumption behaviour in Russia, in most cases the size of effect is modest. The finding that two particularly problematic drinks-cheap vodka and fortified wine-are substitute goods also suggests that increasing their prices may not lead to smaller alcohol consumption. Therefore, any alcohol pricing policies in Russia must be supplemented with other measures, such as restrictions on numbers of sales outlets or their opening times.

Published
2015
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37. Mental health inequalities in 9 former Soviet Union countries: evidence from the previous decade.

Author

Goryakin Y, Suhrcke M, Roberts B, and McKee M

Subjects
Adult, Female, Humans, Longitudinal Studies, Male, Middle Aged, Socioeconomic Factors, USSR, Young Adult, Healthcare Disparities trends, Mental Health trends, Social Change
Abstract

In the previous two decades, countries of the former Soviet Union underwent substantive economic and social changes. While there has been some limited evidence on the relationship between socioeconomic well-being and mental health in the developing and transitional economies, the evidence on economic inequalities in mental health has so far been scarce. In this paper, we analyse two unique datasets collected in 2001 (N = 18,428) and in 2010 (N = 17,998) containing data on 9 countries of the former Soviet Union, exploring how mental health inequalities have changed between 2001 and 2010. Using regression analysis, as well as the indirect standardization approach, we found that mental health appears to have substantially improved in most studied countries during the past decade. Specifically, both the proportion of people with poor mental health, as well as wealth-related inequalities in poor mental health, decreased in almost all countries, except Georgia. Hence, we did not find evidence of a trade-off between changes in average and distributional mental health indicators between 2001 and 2010. Our findings give ground for optimism that at least on these measures, the most difficult times associated with the transition to a market economy in this region may be coming to an end., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Published
2015
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38. Does active commuting improve psychological wellbeing? Longitudinal evidence from eighteen waves of the British Household Panel Survey.

Author

Martin A, Goryakin Y, and Suhrcke M

Subjects
Adolescent, Adult, Aged, Female, Humans, Longitudinal Studies, Male, Middle Aged, Motor Activity, Psychological Tests, Regression Analysis, Transportation, United Kingdom, Young Adult, Automobile Driving psychology, Bicycling psychology, Emotions, Personal Satisfaction, Walking psychology
Abstract

Objective: The aim of this study is to explore the relationship between active travel and psychological wellbeing., Method: This study used data on 17,985 adult commuters in eighteen waves of the British Household Panel Survey (1991/2-2008/9). Fixed effects regression models were used to investigate how (i.) travel mode choice, (ii.) commuting time, and (iii.) switching to active travel impacted on overall psychological wellbeing and how (iv.) travel mode choice impacted on specific psychological symptoms included in the General Health Questionnaire., Results: After accounting for changes in individual-level socioeconomic characteristics and potential confounding variables relating to work, residence and health, significant associations were observed between overall psychological wellbeing (on a 36-point Likert scale) and (i.) active travel (0.185, 95% CI: 0.048 to 0.321) and public transport (0.195, 95% CI: 0.035 to 0.355) when compared to car travel, (ii.) time spent (per 10minute change) walking (0.083, 95% CI: 0.003 to 0.163) and driving (-0.033, 95% CI: -0.064 to -0.001), and (iii.) switching from car travel to active travel (0.479, 95% CI: 0.199 to 0.758). Active travel was also associated with reductions in the odds of experiencing two specific psychological symptoms when compared to car travel., Conclusion: The positive psychological wellbeing effects identified in this study should be considered in cost-benefit assessments of interventions seeking to promote active travel., (Copyright © 2014. Published by Elsevier Inc.)

Published
2014
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39. The prevalence and determinants of catastrophic health expenditures attributable to non-communicable diseases in low- and middle-income countries: a methodological commentary.

Author

Goryakin Y and Suhrcke M

Subjects
Cost of Illness, Cross-Sectional Studies, Humans, Prevalence, Prospective Studies, Socioeconomic Factors, Chronic Disease economics, Developing Countries, Financing, Personal economics, Health Expenditures statistics & numerical data, Income
Abstract

Background: Non-communicable diseases (NCDs), while traditionally considered a "rich world"-problem, have been spreading fast in low and middle income countries and by now account for a large share of mortality and ill-health in these countries, too. In addition to the disease burden, NCDs may also impose a substantial economic cost. One way in which NCDs might impact people's economic well-being may be via the out-of-pocket expenditures required to cover treatment and other costs associated with suffering from an NCD., Methods: In this commentary, we identify and discuss the methodological challenges related to cross-country comparison of-out-of-pocket and catastrophic out-of-pocket health care expenditures, attributable to NCDs, focussing on low and middle income countries., Results: There is significant evidence of substantial cost burden placed by NCDs on patients living in low and middle income countries, with most of it being heavily concentrated among low socioeconomic status groups. However, a large variation in definition of COOPE between studies prevents cross-country comparison. In addition, as most studies tend to be observational, causal inferences are often not possible. This is further complicated by the cross-sectional nature of studies, small sample sizes, and/or limited duration of follow-up of patients. Most evidence for certain conditions (e.g., cancer) tends to be collected in high-income countries only., Conclusions: The definitions for COOPEs should be standardized as much as possible, to enable comparison of COOPE prevalence between countries. Prospective study design using larger samples representative of broader sections of local population, collecting better data on both direct and indirect treatment costs is also needed.

Published
2014
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40. Economic development, urbanization, technological change and overweight: what do we learn from 244 Demographic and Health Surveys?

Author

Goryakin Y and Suhrcke M

Subjects
Adolescent, Adult, Age Factors, Body Mass Index, Developed Countries economics, Developing Countries economics, Female, Global Health, Health Surveys, Humans, Middle Aged, Models, Economic, Obesity epidemiology, Sedentary Behavior, Socioeconomic Factors, Young Adult, Developed Countries statistics & numerical data, Developing Countries statistics & numerical data, Economic Development statistics & numerical data, Overweight epidemiology, Urbanization
Abstract

Obesity and overweight are spreading fast in developing countries, and have reached world record levels in some of them. Capturing the size, patterns and trends of the problem has, however, been severely hampered by the lack of comparable data in low and middle income countries. We seek to begin to fill this gap by testing several hypotheses on the determinants/correlates of overweight among women, related to the influence of economic and technological development. We undertake econometric analysis of nationally representative data on about 878,000 women aged 15-49 from 244 Demographic and Health Surveys (DHS) for 56 countries over the years 1991-2009. Our findings support most previously expressed hypotheses of what might explain obesity patterns in developing countries, but they also reject some prior notions and add considerable nuance to the emerging pattern., (Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2014
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41. Social capital and self-reported general and mental health in nine Former Soviet Union countries.

Author

Goryakin Y, Suhrcke M, Rocco L, Roberts B, and McKee M

Subjects
Adult, Cross-Sectional Studies, Female, Health Behavior, Humans, Male, Residence Characteristics, Social Behavior, Socioeconomic Factors, USSR, Health Status, Loneliness psychology, Mental Health, Social Conditions, Social Support, Trust psychology
Abstract

Social capital has been proposed as a potentially important contributor to health, yet most of the existing research tends to ignore the challenge of assessing causality in this relationship. We deal with this issue by employing various instrumental variable estimation techniques. We apply the analysis to a set of nine former Soviet countries, using a unique multi-country household survey specifically designed for this region. Our results confirm that there appears to be a causal association running from several dimensions of individual social capital to general and mental health. Individual trust appears to be more strongly related to general health, while social isolation- to mental health. In addition, social support and trust seem to be more important determinants of health than the social capital dimensions that facilitate solidarity and collective action. Our findings are remarkably robust to a range of different specifications, including the use of instrumental variables. Certain interaction effects are also found: for instance, untrusting people who live in communities with higher aggregate level of trust are even less likely to experience good health than untrusting people living in the reference communities.

Published
2014
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42. The effect of health on labour supply in nine former Soviet Union countries.

Author

Goryakin Y, Rocco L, Suhrcke M, Roberts B, and McKee M

Subjects
Adult, Age Factors, Commonwealth of Independent States epidemiology, Cross-Sectional Studies, Environment, Health Behavior, Humans, Middle Aged, Residence Characteristics, Socioeconomic Factors, Workforce, Employment, Health Status
Abstract

This paper examines for the first time the consequences of ill health on labour supply for a sample of nine countries from the former Soviet Union (FSU), using a unique multicountry household survey specifically designed for this region. We control for a wide range of individual, household, and community factors, using both standard regression techniques and instrumental variable estimation to address potential endogeneity. Specifically, we find in our baseline ordinary least squares specification that poor health is associated with a decrease in the probability of working of about 13 %. Controlling for community-level unobserved variables slightly increases the magnitude of this effect, to about 14 %. Controlling for endogeneity with the instrumental variable approach further supports this finding, with the magnitude of the effect ranging from 12 to 35 %. Taken together, our findings confirm the cost that the still considerable adult health burden in the FSU is imposing on its population, not only in terms of the disease burden itself, but also in terms of individuals' labour market participation, as well as potentially in terms of increased poverty risk. Other things being equal, this would increase the expected "return on investment" to be had from interventions aimed at improving health in this region.

Published
2014
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43. Micro- and meso-level influences on obesity in the former Soviet Union: a multi-level analysis.

Author

Watson K, Roberts B, Chow C, Goryakin Y, Rotman D, Gasparishvili A, Haerpfer C, and McKee M

Subjects
Adolescent, Adult, Age Distribution, Aged, Body Mass Index, Female, Humans, Logistic Models, Male, Middle Aged, Multilevel Analysis, Prevalence, Self Report, Sex Distribution, Socioeconomic Factors, Surveys and Questionnaires, USSR epidemiology, Young Adult, Obesity epidemiology, Residence Characteristics, Social Environment
Abstract

Background: Limited evidence exists on obesity in the former Soviet Union (fSU), particularly its micro- and meso-level determinants. The objectives of this study were to determine age- and gender-adjusted prevalence of self-reported overweight and obesity in nine fSU countries; explore the relationship between individual and household (micro-level) factors and obesity; and explore the relationship between features of nutritional and physical environments (meso-level) and obesity., Methods: Data were collected from 18,000 adults using household surveys and from 333 communities using community profiles in Azerbaijan, Armenia, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia and Ukraine in 2010. Individual- and community-level determinants of self-reported obesity (body mass index ≥ 30 kg/m(2)) were analysed using multi-level random intercept logistic regression models., Results: A total of 13% of the males and 18% of the females were categorized as obese. Factors associated with obesity in males were older age, increasing educational achievement, declining self-reported health, alcohol consumption and automobile ownership. Males who were current smokers, not married and perceived physical activity to be important were less likely to be obese. For females, obesity was associated with older age, completion of secondary-level education, declining self-reported health and average household financial situation. Unmarried women were less likely to be obese. Multi-level analysis indicated that individuals living in communities with higher presence of garbage were more likely to be obese., Conclusions: This is the first study to examine both micro- and meso-level influences on obesity in fSU using multi-level analysis. Findings indicate a similar obesity risk profile to countries in Western Europe and North America.

Published
2013
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44. Economic evaluation of nurse staffing and nurse substitution in health care: a scoping review.

Author

Goryakin Y, Griffiths P, and Maben J

Subjects
Clinical Competence, Nurses supply & distribution, Personnel Staffing and Scheduling
Abstract

Objective: Several systematic reviews have suggested that greater nurse staffing as well as a greater proportion of registered nurses in the health workforce is associated with better patient outcomes. Others have found that nurses can substitute for doctors safely and effectively in a variety of settings. However, these reviews do not generally consider the effect of nurse staff on both patient outcomes and costs of care, and therefore say little about the cost-effectiveness of nurse-provided care. Therefore, we conducted a scoping literature review of economic evaluation studies which consider the link between nurse staffing, skill mix within the nursing team and between nurses and other medical staff to determine the nature of the available economic evidence., Design: Scoping literature review., Data Sources: English-language manuscripts, published between 1989 and 2009, focussing on the relationship between costs and effects of care and the level of registered nurse staffing or nurse-physician substitution/nursing skill mix in the clinical team, using cost-effectiveness, cost-utility, or cost-benefit analysis. Articles selected for the review were identified through Medline, CINAHL, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects and Google Scholar database searches., Review Methods: After selecting 17 articles representing 16 unique studies for review, we summarized their main findings, and assessed their methodological quality using criteria derived from recommendations from the guidelines proposed by the Panel on Cost-Effectiveness in Health Care., Results: In general, it was found that nurses can provide cost effective care, compared to other health professionals. On the other hand, more intensive nurse staffing was associated with both better outcomes and more expensive care, and therefore cost effectiveness was not easy to assess., Conclusions: Although considerable progress in economic evaluation studies has been reached in recent years, a number of methodological issues remain. In the future, nurse researchers should be more actively engaged in the design and implementation of economic evaluation studies of the services they provide., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Published
2011
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