597 results on '"Agarwal, Gina"'
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2. A comparison of self-reported chronic disease, health awareness and behaviours in social housing residents: cross-sectional study of communities in Ontario and Quebec
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Agarwal, Gina, Pirrie, Melissa, Koester, Christie, Pete, Drashti, Antolovich, Julia, Angeles, Ricardo, Marzanek, Francine, Girard, Magali, and Kaczorowski, Janusz
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- 2024
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3. Paramedic attitudes and experiences working as a community paramedic: a qualitative survey
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Paramalingam, Aarani, Ziesmann, Andrea, Pirrie, Melissa, Marzanek, Francine, Angeles, Ricardo, and Agarwal, Gina
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- 2024
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4. “You are the only other person in the world that knows that about me”: Family physician stories of proximity to patients experiencing social inequity
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Molinaro, Monica L., Shen, Katrina, Tandon, Chitrini, Agarwal, Gina, Inglis, Gabrielle, and Vanstone, Meredith
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- 2024
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5. Challenges in recruiting frequent users of ambulance services for a community paramedic home visit program
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Plishka, Mikayla, Angeles, Ricardo, Pirrie, Melissa, Marzanek, Francine, and Agarwal, Gina
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- 2023
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6. Team approach to polypharmacy evaluation and reduction: feasibility randomized trial of a structured clinical pathway to reduce polypharmacy
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Mangin, Dee, Lamarche, Larkin, Agarwal, Gina, Ali, Abbas, Cassels, Alan, Colwill, Kiska, Dolovich, Lisa, Brown, Naomi Dore, Farrell, Barbara, Freeman, Karla, Frizzle, Kristina, Garrison, Scott R., Gillett, James, Holbrook, Anne, Jurcic-Vrataric, Jane, McCormack, James, Parascandalo, Jenna, Richardson, Julie, Risdon, Cathy, Sherifali, Diana, Siu, Henry, Borhan, Sayem, Templeton, Jeffery A., Thabane, Lehana, and Trimble, Johanna
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- 2023
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7. Global, regional, and national burden of stroke and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
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Collaborators, GBD 2019 Stroke, Feigin, Valery L, Stark, Benjamin A, Johnson, Catherine Owens, Roth, Gregory A, Bisignano, Catherine, Abady, Gdiom Gebreheat, Abbasifard, Mitra, Abbasi-Kangevari, Mohsen, Abd-Allah, Foad, Abedi, Vida, Abualhasan, Ahmed, Abu-Rmeileh, Niveen ME, Abushouk, Abdelrahman I, Adebayo, Oladimeji M, Agarwal, Gina, Agasthi, Pradyumna, Ahinkorah, Bright Opoku, Ahmad, Sohail, Ahmadi, Sepideh, Salih, Yusra Ahmed, Aji, Budi, Akbarpour, Samaneh, Akinyemi, Rufus Olusola, Hamad, Hanadi Al, Alahdab, Fares, Alif, Mohammad, Alipour, Vahid, Aljunid, Syed Mohamed, Almustanyir, Sami, Al-Raddadi, Rajaa M, Salman, Rustam Al-Shahi, Alvis-Guzman, Nelson, Ancuceanu, Robert, Anderlini, Deanna, Anderson, Jason A, Ansar, Adnan, Antonazzo, Ippazio Cosimo, Arabloo, Jalal, Ärnlöv, Johan, Artanti, Kurnia Dwi, Aryan, Zahra, Asgari, Samaneh, Ashraf, Tahira, Athar, Mohammad, Atreya, Alok, Ausloos, Marcel, Baig, Atif Amin, Baltatu, Ovidiu Constantin, Banach, Maciej, Barboza, Miguel A, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barone, Mark Thomaz Ugliara, Basu, Sanjay, Bazmandegan, Gholamreza, Beghi, Ettore, Beheshti, Mahya, Béjot, Yannick, Bell, Arielle Wilder, Bennett, Derrick A, Bensenor, Isabela M, Bezabhe, Woldesellassie Mequanint, Bezabih, Yihienew Mequanint, Bhagavathula, Akshaya Srikanth, Bhardwaj, Pankaj, Bhattacharyya, Krittika, Bijani, Ali, Bikbov, Boris, Birhanu, Mulugeta M, Boloor, Archith, Bonny, Aime, Brauer, Michael, Brenner, Hermann, Bryazka, Dana, Butt, Zahid A, dos Santos, Florentino Luciano Caetano, Campos-Nonato, Ismael R, Cantu-Brito, Carlos, Carrero, Juan J, Castañeda-Orjuela, Carlos A, Catapano, Alberico L, Chakraborty, Promit Ananyo, Charan, Jaykaran, Choudhari, Sonali Gajanan, Chowdhury, Enayet Karim, Chu, Dinh-Toi, Chung, Sheng-Chia, Colozza, David, Costa, Vera Marisa, Costanzo, Simona, Criqui, Michael H, Dadras, Omid, Dagnew, Baye, Dai, Xiaochen, Dalal, Koustuv, Damasceno, Albertino Antonio Moura, D'Amico, Emanuele, Dandona, Lalit, and Dandona, Rakhi
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Brain Disorders ,Aging ,Prevention ,Stroke ,Clinical Research ,2.4 Surveillance and distribution ,Aetiology ,Good Health and Well Being ,Adult ,Aged ,Aged ,80 and over ,Body Mass Index ,Cerebral Hemorrhage ,Female ,Global Burden of Disease ,Humans ,Incidence ,Income ,Ischemic Stroke ,Male ,Middle Aged ,Prevalence ,Quality-Adjusted Life Years ,Risk Factors ,Subarachnoid Hemorrhage ,GBD 2019 Stroke Collaborators ,Clinical Sciences ,Neurosciences ,Neurology & Neurosurgery - Abstract
BackgroundRegularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels.MethodsWe applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level.FindingsIn 2019, there were 12·2 million (95% UI 11·0-13·6) incident cases of stroke, 101 million (93·2-111) prevalent cases of stroke, 143 million (133-153) DALYs due to stroke, and 6·55 million (6·00-7·02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11·6% [10·8-12·2] of total deaths) and the third-leading cause of death and disability combined (5·7% [5·1-6·2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70·0% (67·0-73·0), prevalent strokes increased by 85·0% (83·0-88·0), deaths from stroke increased by 43·0% (31·0-55·0), and DALYs due to stroke increased by 32·0% (22·0-42·0). During the same period, age-standardised rates of stroke incidence decreased by 17·0% (15·0-18·0), mortality decreased by 36·0% (31·0-42·0), prevalence decreased by 6·0% (5·0-7·0), and DALYs decreased by 36·0% (31·0-42·0). However, among people younger than 70 years, prevalence rates increased by 22·0% (21·0-24·0) and incidence rates increased by 15·0% (12·0-18·0). In 2019, the age-standardised stroke-related mortality rate was 3·6 (3·5-3·8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3·7 (3·5-3·9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62·4% of all incident strokes in 2019 (7·63 million [6·57-8·96]), while intracerebral haemorrhage constituted 27·9% (3·41 million [2·97-3·91]) and subarachnoid haemorrhage constituted 9·7% (1·18 million [1·01-1·39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79·6 million [67·7-90·8] DALYs or 55·5% [48·2-62·0] of total stroke DALYs), high body-mass index (34·9 million [22·3-48·6] DALYs or 24·3% [15·7-33·2]), high fasting plasma glucose (28·9 million [19·8-41·5] DALYs or 20·2% [13·8-29·1]), ambient particulate matter pollution (28·7 million [23·4-33·4] DALYs or 20·1% [16·6-23·0]), and smoking (25·3 million [22·6-28·2] DALYs or 17·6% [16·4-19·0]).InterpretationThe annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries.FundingBill & Melinda Gates Foundation.
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- 2021
8. A call to stop extractive health research on South Asian diaspora communities in Canada
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Agarwal, Gina, Banerjee, Ananya Tina, and Brar, Jasdeep
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Medical research -- Management -- Demographic aspects ,Medicine, Experimental -- Management -- Demographic aspects ,Asians -- Health aspects ,Company business management ,Health - Abstract
Several major funding awards have been granted to research teams led by White principal investigators to conduct research involving South Asian diaspora communities. (1-3) This extractive practice, whereby the composition [...]
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- 2024
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9. Five insights from the Global Burden of Disease Study 2019
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Collaborators, GBD 2019 Viewpoint, Murray, Christopher JL, Abbafati, Cristiana, Abbas, Kaja M, Abbasi, Mohammad, Abbasi-Kangevari, Mohsen, Abd-Allah, Foad, Abdollahi, Mohammad, Abedi, Parisa, Abedi, Aidin, Abolhassani, Hassan, Aboyans, Victor, Abreu, Lucas Guimarães, Abrigo, Michael RM, Abu-Gharbieh, Eman, Abu Haimed, Abdulaziz Khalid, Abushouk, Abdelrahman I, Acebedo, Alyssa, Ackerman, Ilana N, Adabi, Maryam, Adamu, Abdu A, Adebayo, Oladimeji M, Adelson, Jaimie D, Adetokunboh, Olatunji O, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agrawal, Anurag, Ahmad, Tauseef, Ahmadi, Keivan, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Aji, Budi, Akinyemiju, Tomi, Akombi, Blessing, Alahdab, Fares, Alam, Khurshid, Alanezi, Fahad Mashhour, Alanzi, Turki M, Albertson, Samuel B, Alemu, Biresaw Wassihun, Alemu, Yihun Mulugeta, Alhabib, Khalid F, Ali, Muhammad, Ali, Saqib, Alicandro, Gianfranco, Alipour, Vahid, Alizade, Hesam, Aljunid, Syed Mohamed, Alla, François, Allebeck, Peter, Almadi, Majid Abdulrahman Hamad, Almasi-Hashiani, Amir, Al-Mekhlafi, Hesham M, Almulhim, Abdulaziz M, Alonso, Jordi, Al-Raddadi, Rajaa M, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Bekalu, Amare, Azmeraw T, Amini, Saeed, Amit, Arianna Maever L, Amugsi, Dickson A, Anbesu, Etsay Woldu, Ancuceanu, Robert, Anderlini, Deanna, Anderson, Jason A, Andrei, Tudorel, Andrei, Catalina Liliana, Anjomshoa, Mina, Ansari, Fereshteh, Ansari-Moghaddam, Alireza, Antonio, Carl Abelardo T, Antony, Catherine M, Anvari, Davood, Appiah, Seth Christopher Yaw, Arabloo, Jalal, Arab-Zozani, Morteza, Aravkin, Aleksandr Y, Arba, Aseb Arba Kinfe, Aripov, Timur, Ärnlöv, Johan, Arowosegbe, Oluwaseyi Olalekan, Asaad, Malke, Asadi-Aliabadi, Mehran, Asadi-Pooya, Ali A, Ashbaugh, Charlie, Assmus, Michael, Atout, Maha Moh'd Wahbi, Ausloos, Marcel, Ausloos, Floriane, Quintanilla, Beatriz Paulina Ayala, Ayano, Getinet, Ayanore, Martin Amogre, Azari, Samad, Azene, Zelalem Nigussie, Darshan, BB, Babaee, Ebrahim, and Badawi, Alaa
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Prevention ,2.4 Surveillance and distribution ,Aetiology ,Good Health and Well Being ,Birth Rate ,Delivery of Health Care ,Female ,Global Burden of Disease ,Global Health ,Humans ,Male ,Noncommunicable Diseases ,Outcome Assessment ,Health Care ,Risk Factors ,Socioeconomic Factors ,Wounds and Injuries ,GBD 2019 Viewpoint Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3·5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.
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- 2020
10. Ligne directrice C-CHANGE pour l'harmonisation des lignes directrices nationales de prevention et de prise en charge des maladies cardiovasculaires en contexte de soins primaires au Canada : mise a jour 2022
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Jain, Rahul, Stone, James A., Agarwal, Gina, Andrade, Jason G., Bacon, Simon L., Bajaj, Harpreet S., Baker, Brian, Cheng, Gemma, Dannenbaum, David, Gelfer, Mark, Habert, Jeffrey, Hickey, John, Keshavjee, Karim, Kitty, Darlene, Lindsay, Patrice, LAbbe, Mary R., Lau, David C.W., Macle, Laurent, McDonald, Michael, Nerenberg, Kara, Pearson, Glen J., Pham, Thuy, Poppe, Alexandre Y., Rabi, Doreen M., Sherifali, Diana, Selby, Peter, Smith, Eric, Stern, Sol, Thanassoulis, George, Terenzi, Kristin, Tu, Karen, Udell, Jacob, Virani, Sean A., Ward, Richard A., Warburton, Darren E.R., Wharton, Sean, Zymantas, Jennifer, Hua-Stewart, Diane, Liu, Peter P., and Tobe, Sheldon W.
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Anticoagulants (Medicine) ,Hypoglycemic agents ,Cardiovascular diseases -- Care and treatment -- Management -- Prevention -- Cases ,Type 2 diabetes ,Company legal issue ,Company business management ,Health - Abstract
L'objectif du projet C-CHANGE (Canadian Cardiovascular Harmonized National Guideline Endeavour), une initiative d'harmonisation des lignes directrices nationales de prevention et de prise en charge des maladies cardiovasculaires, est de faciliter [...]
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- 2023
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11. Global, Regional, and Country-Specific Lifetime Risks of Stroke, 1990 and 2016
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Feigin, Valery L, Nguyen, Grant, Cercy, Kelly, Johnson, Catherine O, Alam, Tahiya, Parmar, Priyakumari G, Abajobir, Amanuel A, Abate, Kalkidan H, Abd-Allah, Foad, Abejie, Ayenew N, Abyu, Gebre Y, Ademi, Zanfina, Agarwal, Gina, Ahmed, Muktar B, Akinyemi, Rufus O, Al-Raddadi, Rajaa, Aminde, Leopold N, Amlie-Lefond, Catherine, Ansari, Hossein, Asayesh, Hamid, Asgedom, Solomon W, Atey, Tesfay M, Ayele, Henok T, Banach, Maciej, Banerjee, Amitava, Barac, Aleksandra, Barker-Collo, Suzanne L, Bärnighausen, Till, Barregard, Lars, Basu, Sanjay, Bedi, Neeraj, Behzadifar, Masoud, Béjot, Yannick, Bennett, Derrick A, Bensenor, Isabela M, Berhe, Derbew F, Boneya, Dube J, Brainin, Michael, Campos-Nonato, Ismael R, Caso, Valeria, Castañeda-Orjuela, Carlos A, Rivas, Jacquelin C, Catalá-López, Ferrán, Christensen, Hanne, Criqui, Michael H, Damasceno, Albertino, Dandona, Lalit, Dandona, Rakhi, Davletov, Kairat, de Courten, Barbora, deVeber, Gabrielle, Dokova, Klara, Edessa, Dumessa, Endres, Matthias, Faraon, Emerito JA, Farvid, Maryam S, Fischer, Florian, Foreman, Kyle, Forouzanfar, Mohammad H, Gall, Seana L, Gebrehiwot, Tsegaye T, Geleijnse, Johanna M, Gillum, Richard F, Giroud, Maurice, Goulart, Alessandra C, Gupta, Rahul, Gupta, Rajeev, Hachinski, Vladimir, Hamadeh, Randah R, Hankey, Graeme J, Hareri, Habtamu A, Havmoeller, Rasmus, Hay, Simon I, Hegazy, Mohamed I, Hibstu, Desalegn T, James, Spencer L, Jeemon, Panniyammakal, John, Denny, Jonas, Jost B, Jóźwiak, Jacek, Kalani, Rizwan, Kandel, Amit, Kasaeian, Amir, Kengne, Andre P, Khader, Yousef S, Khan, Abdur R, Khang, Young-Ho, Khubchandani, Jagdish, Kim, Daniel, Kim, Yun J, Kivimaki, Mika, Kokubo, Yoshihiro, Kolte, Dhaval, Kopec, Jacek A, Kosen, Soewarta, Kravchenko, Michael, Krishnamurthi, Rita, Kumar, G Anil, Lafranconi, Alessandra, and Lavados, Pablo M
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Aging ,Brain Disorders ,Stroke ,Prevention ,Aetiology ,2.4 Surveillance and distribution ,Good Health and Well Being ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Cause of Death ,Female ,Global Burden of Disease ,Global Health ,Humans ,Incidence ,Male ,Middle Aged ,Risk ,Sex Distribution ,Socioeconomic Factors ,GBD 2016 Lifetime Risk of Stroke Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundThe lifetime risk of stroke has been calculated in a limited number of selected populations. We sought to estimate the lifetime risk of stroke at the regional, country, and global level using data from a comprehensive study of the prevalence of major diseases.MethodsWe used the Global Burden of Disease (GBD) Study 2016 estimates of stroke incidence and the competing risks of death from any cause other than stroke to calculate the cumulative lifetime risks of first stroke, ischemic stroke, or hemorrhagic stroke among adults 25 years of age or older. Estimates of the lifetime risks in the years 1990 and 2016 were compared. Countries were categorized into quintiles of the sociodemographic index (SDI) used in the GBD Study, and the risks were compared across quintiles. Comparisons were made with the use of point estimates and uncertainty intervals representing the 2.5th and 97.5th percentiles around the estimate.ResultsThe estimated global lifetime risk of stroke from the age of 25 years onward was 24.9% (95% uncertainty interval, 23.5 to 26.2); the risk among men was 24.7% (95% uncertainty interval, 23.3 to 26.0), and the risk among women was 25.1% (95% uncertainty interval, 23.7 to 26.5). The risk of ischemic stroke was 18.3%, and the risk of hemorrhagic stroke was 8.2%. In high-SDI, high-middle-SDI, and low-SDI countries, the estimated lifetime risk of stroke was 23.5%, 31.1% (highest risk), and 13.2% (lowest risk), respectively; the 95% uncertainty intervals did not overlap between these categories. The highest estimated lifetime risks of stroke according to GBD region were in East Asia (38.8%), Central Europe (31.7%), and Eastern Europe (31.6%), and the lowest risk was in eastern sub-Saharan Africa (11.8%). The mean global lifetime risk of stroke increased from 22.8% in 1990 to 24.9% in 2016, a relative increase of 8.9% (95% uncertainty interval, 6.2 to 11.5); the competing risk of death from any cause other than stroke was considered in this calculation.ConclusionsIn 2016, the global lifetime risk of stroke from the age of 25 years onward was approximately 25% among both men and women. There was geographic variation in the lifetime risk of stroke, with the highest risks in East Asia, Central Europe, and Eastern Europe. (Funded by the Bill and Melinda Gates Foundation.).
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- 2018
12. Global, Regional, and Country-Specific Lifetime Risks of Stroke, 1990 and 2016.
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GBD 2016 Lifetime Risk of Stroke Collaborators, Feigin, Valery L, Nguyen, Grant, Cercy, Kelly, Johnson, Catherine O, Alam, Tahiya, Parmar, Priyakumari G, Abajobir, Amanuel A, Abate, Kalkidan H, Abd-Allah, Foad, Abejie, Ayenew N, Abyu, Gebre Y, Ademi, Zanfina, Agarwal, Gina, Ahmed, Muktar B, Akinyemi, Rufus O, Al-Raddadi, Rajaa, Aminde, Leopold N, Amlie-Lefond, Catherine, Ansari, Hossein, Asayesh, Hamid, Asgedom, Solomon W, Atey, Tesfay M, Ayele, Henok T, Banach, Maciej, Banerjee, Amitava, Barac, Aleksandra, Barker-Collo, Suzanne L, Bärnighausen, Till, Barregard, Lars, Basu, Sanjay, Bedi, Neeraj, Behzadifar, Masoud, Béjot, Yannick, Bennett, Derrick A, Bensenor, Isabela M, Berhe, Derbew F, Boneya, Dube J, Brainin, Michael, Campos-Nonato, Ismael R, Caso, Valeria, Castañeda-Orjuela, Carlos A, Rivas, Jacquelin C, Catalá-López, Ferrán, Christensen, Hanne, Criqui, Michael H, Damasceno, Albertino, Dandona, Lalit, Dandona, Rakhi, Davletov, Kairat, de Courten, Barbora, deVeber, Gabrielle, Dokova, Klara, Edessa, Dumessa, Endres, Matthias, Faraon, Emerito JA, Farvid, Maryam S, Fischer, Florian, Foreman, Kyle, Forouzanfar, Mohammad H, Gall, Seana L, Gebrehiwot, Tsegaye T, Geleijnse, Johanna M, Gillum, Richard F, Giroud, Maurice, Goulart, Alessandra C, Gupta, Rahul, Gupta, Rajeev, Hachinski, Vladimir, Hamadeh, Randah R, Hankey, Graeme J, Hareri, Habtamu A, Havmoeller, Rasmus, Hay, Simon I, Hegazy, Mohamed I, Hibstu, Desalegn T, James, Spencer L, Jeemon, Panniyammakal, John, Denny, Jonas, Jost B, Jóźwiak, Jacek, Kalani, Rizwan, Kandel, Amit, Kasaeian, Amir, Kengne, Andre P, Khader, Yousef S, Khan, Abdur R, Khang, Young-Ho, Khubchandani, Jagdish, Kim, Daniel, Kim, Yun J, Kivimaki, Mika, Kokubo, Yoshihiro, Kolte, Dhaval, Kopec, Jacek A, Kosen, Soewarta, Kravchenko, Michael, Krishnamurthi, Rita, Kumar, G Anil, and Lafranconi, Alessandra
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GBD 2016 Lifetime Risk of Stroke Collaborators ,Humans ,Incidence ,Cause of Death ,Risk ,Age Distribution ,Sex Distribution ,Socioeconomic Factors ,Adult ,Aged ,Aged ,80 and over ,Middle Aged ,Female ,Male ,Stroke ,Global Health ,Global Burden of Disease ,Brain Disorders ,Aging ,Prevention ,2.4 Surveillance and distribution ,General & Internal Medicine ,Medical and Health Sciences - Abstract
BackgroundThe lifetime risk of stroke has been calculated in a limited number of selected populations. We sought to estimate the lifetime risk of stroke at the regional, country, and global level using data from a comprehensive study of the prevalence of major diseases.MethodsWe used the Global Burden of Disease (GBD) Study 2016 estimates of stroke incidence and the competing risks of death from any cause other than stroke to calculate the cumulative lifetime risks of first stroke, ischemic stroke, or hemorrhagic stroke among adults 25 years of age or older. Estimates of the lifetime risks in the years 1990 and 2016 were compared. Countries were categorized into quintiles of the sociodemographic index (SDI) used in the GBD Study, and the risks were compared across quintiles. Comparisons were made with the use of point estimates and uncertainty intervals representing the 2.5th and 97.5th percentiles around the estimate.ResultsThe estimated global lifetime risk of stroke from the age of 25 years onward was 24.9% (95% uncertainty interval, 23.5 to 26.2); the risk among men was 24.7% (95% uncertainty interval, 23.3 to 26.0), and the risk among women was 25.1% (95% uncertainty interval, 23.7 to 26.5). The risk of ischemic stroke was 18.3%, and the risk of hemorrhagic stroke was 8.2%. In high-SDI, high-middle-SDI, and low-SDI countries, the estimated lifetime risk of stroke was 23.5%, 31.1% (highest risk), and 13.2% (lowest risk), respectively; the 95% uncertainty intervals did not overlap between these categories. The highest estimated lifetime risks of stroke according to GBD region were in East Asia (38.8%), Central Europe (31.7%), and Eastern Europe (31.6%), and the lowest risk was in eastern sub-Saharan Africa (11.8%). The mean global lifetime risk of stroke increased from 22.8% in 1990 to 24.9% in 2016, a relative increase of 8.9% (95% uncertainty interval, 6.2 to 11.5); the competing risk of death from any cause other than stroke was considered in this calculation.ConclusionsIn 2016, the global lifetime risk of stroke from the age of 25 years onward was approximately 25% among both men and women. There was geographic variation in the lifetime risk of stroke, with the highest risks in East Asia, Central Europe, and Eastern Europe. (Funded by the Bill and Melinda Gates Foundation.).
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- 2018
13. It's high time Canada started collecting race-based performance data on medical training and careers
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Menezes, Anjali, Henry, Shayna, and Agarwal, Gina
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- 2022
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14. Canadian Cardiovascular Harmonized National Guideline Endeavour (C-CHANGE) guideline for the prevention and management of cardiovascular disease in primary care: 2022 update
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Jain, Rahul, Stone, James A., Agarwal, Gina, Andrade, Jason G., Bacon, Simon L., Bajaj, Harpreet S., Baker, Brian, Cheng, Gemma, Dannenbaum, David, Gelfer, Mark, Habert, Jeffrey, Hickey, John, Keshavjee, Karim, Kitty, Darlene, Lindsay, Patrice, L'Abbe, Mary R., Lau, David C.W., Macle, Laurent, McDonald, Michael, Nerenberg, Kara, Pearson, Glen J., Pham, Thuy, Poppe, Alexandre Y., Rabi, Doreen M., Sherifali, Diana, Selby, Peter, Smith, Eric, Stern, Sol, Thanassoulis, George, Terenzi, Kristin, Tu, Karen, Udell, Jacob, Virani, Sean A., Ward, Richard A., Warburton, Darren E.R., Wharton, Sean, Zymantas, Jennifer, Hua-Stewart, Diane, Liu, Peter P., and Tobe, Sheldon W.
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Practice guidelines (Medicine) -- Evaluation ,Primary health care -- Methods ,Cardiovascular diseases -- Prevention ,Health - Abstract
The goal of the Canadian Cardiovascular Harmonized National Guideline Endeavour (C-CHANGE) process is to give all Canadian health care providers easy access to a comprehensive and practical set of harmonized [...]
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- 2022
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15. Challenges in eating disorder diagnosis and management among family physicians and trainees: a qualitative study
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Tse, Angel, Xavier, Sabatinie, Trollope-Kumar, Karen, Agarwal, Gina, and Lokker, Cynthia
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- 2022
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16. Health knowledge and self-efficacy to make health behaviour changes: a survey of older adults living in Ontario social housing
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Dzerounian, Jasmine, Pirrie, Melissa, AlShenaiber, Leena, Angeles, Ricardo, Marzanek, Francine, and Agarwal, Gina
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- 2022
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17. Workplace violence against emergency health care workers: What Strategies do Workers use?
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Spelten, Evelien, van Vuuren, Julia, O’Meara, Peter, Thomas, Brodie, Grenier, Mathieu, Ferron, Richard, Helmer, Jennie, and Agarwal, Gina
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- 2022
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18. Barriers to and strategies to address COVID-19 testing hesitancy: a rapid scoping review
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Embrett, Mark, Sim, S. Meaghan, Caldwell, Hilary A. T., Boulos, Leah, Yu, Ziwa, Agarwal, Gina, Cooper, Rhiannon, AJ, Allyson J. Gallant, Bielska, Iwona A., Chishtie, Jawad, Stone, Kathryn, Curran, Janet, and Tricco, Andrea
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- 2022
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19. Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Murray, Christopher JL, Callender, Charlton SKH, Kulikoff, Xie Rachel, Srinivasan, Vinay, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbasi, Nooshin, Abbastabar, Hedayat, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdoli, Nasrin, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Abejie, Ayenew Negesse, Aboyans, Victor, Abraha, Haftom Niguse, Abreu, Daisy Maria Xavier, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Almasi, Ali, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Arian, Nicholas, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Atey, Tesfay Mehari Mehari, and Atique, Suleman
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Health Sciences ,Behavioral and Social Science ,Contraception/Reproduction ,Basic Behavioral and Social Science ,Aging ,Aetiology ,2.4 Surveillance and distribution ,Reproductive health and childbirth ,Good Health and Well Being ,Adolescent ,Adult ,Aged ,Birth Rate ,Child ,Child ,Preschool ,Female ,Global Burden of Disease ,Global Health ,Humans ,Infant ,Infant ,Newborn ,Male ,Maternal Age ,Middle Aged ,Mortality ,Population Density ,Population Growth ,Young Adult ,GBD 2017 Population and Fertility Collaborators ,Medical and Health Sciences ,General & Internal Medicine ,Biomedical and clinical sciences ,Health sciences - Abstract
BackgroundPopulation estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods.MethodsWe estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10-54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10-14 years and 50-54 years was estimated from data on fertility in women aged 15-19 years and 45-49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories.FindingsFrom 1950 to 2017, TFRs decreased by 49·4% (95% uncertainty interval [UI] 46·4-52·0). The TFR decreased from 4·7 livebirths (4·5-4·9) to 2·4 livebirths (2·2-2·5), and the ASFR of mothers aged 10-19 years decreased from 37 livebirths (34-40) to 22 livebirths (19-24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83·8 million people per year since 1985. The global population increased by 197·2% (193·3-200·8) since 1950, from 2·6 billion (2·5-2·6) to 7·6 billion (7·4-7·9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2·0%; this rate then remained nearly constant until 1970 and then decreased to 1·1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2·5% in 1963 to 0·7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2·7%. The global average age increased from 26·6 years in 1950 to 32·1 years in 2017, and the proportion of the population that is of working age (age 15-64 years) increased from 59·9% to 65·3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1·0 livebirths (95% UI 0·9-1·2) in Cyprus to a high of 7·1 livebirths (6·8-7·4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0·08 livebirths (0·07-0·09) in South Korea to 2·4 livebirths (2·2-2·6) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0·3 livebirths (0·3-0·4) in Puerto Rico to a high of 3·1 livebirths (3·0-3·2) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2·0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger.InterpretationPopulation trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress.FundingBill & Melinda Gates Foundation.
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- 2018
20. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Collaborators, GBD 2017 Causes of Death, Roth, Gregory A, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Adamu, Abdu A, Adebayo, Oladimeji M, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adib, Mina G, Admasie, Amha, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akbari, Mohammad Esmaeil, Akinyemi, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Raddadi, Rajaa M, Alahdab, Fares, Alam, Khurshid, Alam, Tahiya, Alebel, Animut, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Alonso, Jordi, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Aminde, Leopold N, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Aremu, Olatunde, Ärnlöv, Johan, Arora, Amit, Arora, Monika, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R, Ausloos, Marcel, Avokpaho, Euripide FGA, Awasthi, Ashish, Quintanilla, Beatriz Paulina Ayala, Ayele, Yohanes, Ayer, Rakesh, Azzopardi, Peter S, Babazadeh, Arefeh, Bacha, Umar, Badali, Hamid, and Badawi, Alaa
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Brain Disorders ,Pediatric ,Prevention ,Aetiology ,2.4 Surveillance and distribution ,Infection ,Good Health and Well Being ,Adolescent ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Cause of Death ,Child ,Child ,Preschool ,Female ,Global Burden of Disease ,Global Health ,Humans ,Infant ,Infant ,Newborn ,Life Expectancy ,Male ,Middle Aged ,Sex Distribution ,Socioeconomic Factors ,Young Adult ,GBD 2017 Causes of Death Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundGlobal development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017.MethodsThe causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries-Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised.FindingsAt the broadest grouping of causes of death (Level 1), non-communicable diseases (NCDs) comprised the greatest fraction of deaths, contributing to 73·4% (95% uncertainty interval [UI] 72·5-74·1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 18·6% (17·9-19·6), and injuries 8·0% (7·7-8·2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22·7% (21·5-23·9), representing an additional 7·61 million (7·20-8·01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7·9% (7·0-8·8). The number of deaths for CMNN causes decreased by 22·2% (20·0-24·0) and the death rate by 31·8% (30·1-33·3). Total deaths from injuries increased by 2·3% (0·5-4·0) between 2007 and 2017, and the death rate from injuries decreased by 13·7% (12·2-15·1) to 57·9 deaths (55·9-59·2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118·0% (88·8-148·6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36·4% (32·2-40·6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33·6% (31·2-36·1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respiratory infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990-neonatal disorders, lower respiratory infections, and diarrhoeal diseases-were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases.InterpretationImprovements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade.FundingBill & Melinda Gates Foundation.
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- 2018
21. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
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James, Spencer L, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Zegeye, Abera, Semaw F, Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Ackerman, Ilana N, Adamu, Abdu A, Adebayo, Oladimeji M, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adib, Mina G, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M, Al-Raddadi, Rajaa M, Alahdab, Fares, Alam, Khurshid, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Alouani, Mohamed ML, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Aminde, Leopold N, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Arabloo, Jalal, Arauz, Antonio, Aremu, Olatunde, Ariani, Filippo, Armoon, Bahroom, Ärnlöv, Johan, Arora, Amit, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asghar, Rana Jawad, Ataro, Zerihun, Atre, Sachin R, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide FGA, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayer, Rakesh, Azzopardi, Peter S, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, and Bali, Ayele Geleto
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Prevention ,2.4 Surveillance and distribution ,Aetiology ,Good Health and Well Being ,Adolescent ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Child ,Child ,Preschool ,Disabled Persons ,Female ,Global Burden of Disease ,Global Health ,Humans ,Incidence ,Infant ,Infant ,Newborn ,Life Expectancy ,Male ,Middle Aged ,Morbidity ,Prevalence ,Sex Distribution ,Socioeconomic Factors ,Wounds and Injuries ,Young Adult ,GBD 2017 Disease and Injury Incidence and Prevalence Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundThe Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data.MethodsWe estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting.FindingsGlobally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs s1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]).InterpretationGlobal all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury.FundingBill & Melinda Gates Foundation.
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- 2018
22. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
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Collaborators, GBD 2017 SDG, Lozano, Rafael, Fullman, Nancy, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshari, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Akalu, Temesgen Yihunie, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Albujeer, Ammar, Alebel, Animut, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Almasi, Ali, Al-Maskari, Fatma, Al-Mekhlafi, Hesham M, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Amini, Erfan, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, and Anwari, Palwasha
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Prevention ,Pediatric ,Good Health and Well Being ,Peace ,Justice and Strong Institutions ,Female ,Global Burden of Disease ,Global Health ,Goals ,Health Status ,Health Status Indicators ,Humans ,Male ,Mortality ,Risk Factors ,Sex Offenses ,Sustainable Development ,United Nations ,GBD 2017 SDG Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundEfforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment.MethodsWe measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator.FindingsThe global median health-related SDG index in 2017 was 59·4 (IQR 35·4-67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6-14·0) to a high of 84·9 (83·1-86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030.InterpretationThe GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains-curative interventions in the case of NCDs-towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions-or inaction-today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030.FundingBill & Melinda Gates Foundation.
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- 2018
23. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Collaborators, GBD 2017 Risk Factor, Stanaway, Jeffrey D, Afshin, Ashkan, Gakidou, Emmanuela, Lim, Stephen S, Abate, Degu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abera, Semaw F, Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adane, Akilew Awoke, Adebayo, Oladimeji M, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O, Adib, Mina G, Admasie, Amha, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Agarwal, Gina, Aggarwal, Anju, Aghayan, Sargis Aghasi, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akbari, Mohammad Esmaeil, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M, Alahdab, Fares, Alam, Khurshid, Alam, Samiah, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Ali, Komal, Ali, Syed Mustafa, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antó, Josep M, Antonio, Carl Abelardo T, Anwari, Palwasha, Appiah, Lambert Tetteh, Appiah, Seth Christopher Yaw, Arabloo, Jalal, Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Ataro, Zerihun, Ausloos, Marcel, Avokpaho, Euripide FGA, Awasthi, Ashish, Quintanilla, Beatriz Paulina Ayala, Ayer, Rakesh, and Ayuk, Tambe B
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Prevention ,Aetiology ,2.2 Factors relating to the physical environment ,Good Health and Well Being ,Adolescent ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Child ,Child ,Preschool ,Disabled Persons ,Environmental Exposure ,Female ,Global Burden of Disease ,Global Health ,Health Risk Behaviors ,Humans ,Infant ,Infant ,Newborn ,Life Expectancy ,Male ,Metabolic Diseases ,Middle Aged ,Occupational Diseases ,Occupational Exposure ,Quality-Adjusted Life Years ,Risk Assessment ,Sex Distribution ,Socioeconomic Factors ,Young Adult ,GBD 2017 Risk Factor Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk-outcome associations.MethodsWe used the CRA 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 groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. 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. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017.FindingsIn 2017, 34·1 million (95% uncertainty interval [UI] 33·3-35·0) deaths and 1·21 billion (1·14-1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6-62·4) of deaths and 48·3% (46·3-50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39-11·5) deaths and 218 million (198-237) DALYs, followed by smoking (7·10 million [6·83-7·37] deaths and 182 million [173-193] DALYs), high fasting plasma glucose (6·53 million [5·23-8·23] deaths and 171 million [144-201] DALYs), high body-mass index (BMI; 4·72 million [2·99-6·70] deaths and 148 million [98·6-202] DALYs), and short gestation for birthweight (1·43 million [1·36-1·51] deaths and 139 million [131-147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3-6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low.InterpretationBy quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.FundingBill & Melinda Gates Foundation.
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- 2018
24. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Collaborators, GBD 2017 Mortality, Dicker, Daniel, Nguyen, Grant, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abdurahman, Ahmed Abdulahi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Agrawal, Anurag, Ahmadi, Mehdi, Ahmadi, Alireza, Ahmadieh, Hamid, Ahmed, Mohamed Lemine Cheikh brahim, Ahmed, Sayem, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Anlay, Degefaye Zelalem, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Megha, and Artaman, Al
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Behavioral and Social Science ,Pediatric ,Prevention ,Basic Behavioral and Social Science ,2.4 Surveillance and distribution ,Aetiology ,Good Health and Well Being ,Adolescent ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Child ,Child ,Preschool ,Female ,Global Burden of Disease ,Global Health ,Humans ,Infant ,Infant ,Newborn ,Life Expectancy ,Male ,Middle Aged ,Mortality ,Sex Distribution ,Socioeconomic Factors ,Young Adult ,GBD 2017 Mortality Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundAssessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally.MethodsThe GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950.FindingsGlobally, 18·7% (95% uncertainty interval 18·4-19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2-59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5-49·6) to 70·5 years (70·1-70·8) for men and from 52·9 years (51·7-54·0) to 75·6 years (75·3-75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5-51·7) for men in the Central African Republic to 87·6 years (86·9-88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3-238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6-42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2-5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development.InterpretationThis analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing.FundingBill & Melinda Gates Foundation.
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- 2018
25. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Kyu, Hmwe Hmwe, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abil, Olifan Zewdie, Aboyans, Victor, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Ackerman, Ilana N, Adamu, Abdu A, Adebayo, Oladimeji M, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O, Adib, Mina G, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Anurag, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M, Al-Raddadi, Rajaa M, Alahdab, Fares, Alam, Khurshid, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Alonso, Jordi, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Aminde, Leopold N, Amini, Erfan, Amiresmaili, Mohammadreza, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Arabloo, Jalal, Aremu, Olatunde, Ärnlöv, Johan, Arora, Amit, Arora, Megha, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Ataro, Zerihun, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide FGA, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayer, Rakesh, Azzopardi, Peter S, Babazadeh, Arefeh, Badali, Hamid, and Balakrishnan, Kalpana
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Prevention ,Aging ,Good Health and Well Being ,Aged ,Communicable Diseases ,Disabled Persons ,Female ,Global Burden of Disease ,Health Status ,Healthy Lifestyle ,Humans ,Life Expectancy ,Male ,Mortality ,Mortality ,Premature ,Prevalence ,Quality-Adjusted Life Years ,Risk Factors ,Socioeconomic Factors ,Wounds and Injuries ,GBD 2017 DALYs and HALE Collaborators ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundHow long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years.MethodsWe used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males.FindingsGlobally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2).InterpretationWith increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low SDI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health.FundingBill & Melinda Gates Foundation.
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- 2018
26. Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016
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Griswold, Max G, Fullman, Nancy, Hawley, Caitlin, Arian, Nicholas, Zimsen, Stephanie RM, Tymeson, Hayley D, Venkateswaran, Vidhya, Tapp, Austin Douglas, Forouzanfar, Mohammad H, Salama, Joseph S, Abate, Kalkidan Hassen, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abdulkader, Rizwan Suliankatchi, Abebe, Zegeye, Aboyans, Victor, Abrar, Mohammed Mehdi, Acharya, Pawan, Adetokunboh, Olatunji O, Adhikari, Tara Ballav, Adsuar, Jose C, Afarideh, Mohsen, Agardh, Emilie Elisabet, Agarwal, Gina, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmed, Muktar Beshir, Akibu, Mohammed, Akinyemiju, Tomi, Akseer, Nadia, Asfoor, Deena H Al, Al-Aly, Ziyad, Alahdab, Fares, Alam, Khurshid, Albujeer, Ammar, Alene, Kefyalew Addis, Ali, Raghib, Ali, Syed Danish, Alijanzadeh, Mehran, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Allebeck, Peter, Alvis-Guzman, Nelson, Amare, Azmeraw T, Aminde, Leopold N, Ammar, Walid, Amoako, Yaw Ampem, Amul, Gianna Gayle Herrera, Andrei, Catalina Liliana, Angus, Colin, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Assadi, Reza, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F, Awasthi, Ashish, Ayele, Henok Tadesse, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Badali, Hamid, Badawi, Alaa, Banach, Maciej, Barker-Collo, Suzanne Lyn, Barrero, Lope H, Basaleem, Huda, Baye, Estifanos, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Béjot, Yannick, Belachew, Abate Bekele, Belay, Saba Abraham, Bennett, Derrick A, Bensenor, Isabela M, Bernabe, Eduardo, Bernstein, Robert S, Beyene, Addisu Shunu, Beyranvand, Tina, Bhaumik, Soumyadeeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bililign, Nigus, Birlik, Sait Mentes, Birungi, Charles, Bizuneh, Hailemichael, Bjerregaard, Peter, Bjørge, Tone, Borges, Guilherme, Bosetti, Cristina, Boufous, Soufiane, Bragazzi, Nicola Luigi, Brenner, Hermann, and Butt, Zahid A
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Epidemiology ,Public Health ,Health Sciences ,Alcoholism ,Alcohol Use and Health ,Aging ,Prevention ,Behavioral and Social Science ,Substance Misuse ,Women's Health ,2.4 Surveillance and distribution ,Cancer ,Oral and gastrointestinal ,Stroke ,Good Health and Well Being ,Adolescent ,Adult ,Age Distribution ,Aged ,Aged ,80 and over ,Alcohol Drinking ,Cause of Death ,Commerce ,Female ,Global Burden of Disease ,Global Health ,Humans ,Male ,Middle Aged ,Observational Studies as Topic ,Population Surveillance ,Prevalence ,Prospective Studies ,Quality-Adjusted Life Years ,Retrospective Studies ,Risk Assessment ,Risk Factors ,Sex Distribution ,Young Adult ,GBD 2016 Alcohol Collaborators ,Medical and Health Sciences ,General & Internal Medicine ,Biomedical and clinical sciences ,Health sciences - Abstract
BackgroundAlcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older.MethodsUsing 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health.FindingsGlobally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2·2% (95% uncertainty interval [UI] 1·5-3·0) of age-standardised female deaths and 6·8% (5·8-8·0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3·8% (95% UI 3·2-4·3) of female deaths and 12·2% (10·8-13·6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2·3% (95% UI 2·0-2·6) and male attributable DALYs were 8·9% (7·8-9·9). The three leading causes of attributable deaths in this age group were tuberculosis (1·4% [95% UI 1·0-1·7] of total deaths), road injuries (1·2% [0·7-1·9]), and self-harm (1·1% [0·6-1·5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27·1% (95% UI 21·2-33·3) of total alcohol-attributable female deaths and 18·9% (15·3-22·6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0·0-0·8) standard drinks per week.InterpretationAlcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.FundingBill & Melinda Gates Foundation.
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- 2018
27. 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
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Collaborators, GBD 2016 Healthcare Access and Quality, Fullman, Nancy, Yearwood, Jamal, Abay, Solomon M, Abbafati, Cristiana, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abebe, Zegeye, Abebo, Teshome Abuka, Aboyans, Victor, Abraha, Haftom Niguse, Abreu, Daisy MX, Abu-Raddad, Laith J, Adane, Akilew Awoke, Adedoyin, Rufus Adesoji, Adetokunboh, Olatunji, Adhikari, Tara Ballav, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Kiadaliri, Aliasghar Ahmad, Aichour, Miloud Taki Eddine, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi F, Akseer, Nadia, Lami, Faris Hasan Al, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Alasfoor, Deena, Albittar, Mohammed I, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Syed Danish, Alijanzadeh, Mehran, Aljunid, Syed M, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine, Alomari, Mahmoud A, Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla, Andrei, Catalina Liliana, Androudi, Sofia, Antonio, Carl Abelardo T, Araújo, Valdelaine EM, Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Ashebir, Mengistu Mitiku, Asseffa, Netsanet Abera, Atey, Tesfay Mehari, Atre, Sachin R, Atteraya, Madhu S, Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G Arthur, Awasthi, Ashish, Quintanilla, Beatriz Paulina Ayala, Ayalew, Animut Alebel, Ayele, Henok Tadesse, Ayer, Rakesh, Ayuk, Tambe Betrand, Azzopardi, Peter, Azzopardi-Muscat, Natasha, Babalola, Tesleem Kayode, Badali, Hamid, Badawi, Alaa, Banach, Maciej, Banerjee, Amitava, Banstola, Amrit, Barber, Ryan M, Barboza, Miguel A, Barker-Collo, Suzanne L, Bärnighausen, Till, Barquera, Simon, Barrero, Lope H, Bassat, Quique, Basu, Sanjay, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, and Bedi, Neeraj
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Health Services and Systems ,Public Health ,Health Sciences ,Clinical Research ,Biodefense ,Prevention ,Vaccine Related ,Good Health and Well Being ,Communicable Diseases ,Global Burden of Disease ,Health Services Accessibility ,Humans ,Noncommunicable Diseases ,Quality of Health Care ,Wounds and Injuries ,GBD 2016 Healthcare Access and Quality Collaborators ,Medical and Health Sciences ,General & Internal Medicine ,Biomedical and clinical sciences ,Health sciences - Abstract
BackgroundA 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.MethodsDrawing 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.FindingsIn 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.InterpretationGBD 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.FundingBill & Melinda Gates Foundation.
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- 2018
28. Physician perspectives of the community paramedicine at clinic (CP@clinic) and my care plan app (myCP app) for older adults
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Sadri, Pauneez, primary, Keenan, Amelia, additional, Angeles, Ricardo, additional, Marzanek, Francine, additional, Pirrie, Melissa, additional, and Agarwal, Gina, additional
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- 2024
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29. Development of the Health Awareness and Behaviour Tool (HABiT) : reliability and suitability for a Canadian older adult population
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Agarwal, Gina, Pirrie, Melissa, Angeles, Ricardo, Marzanek, Francine, and Parascandalo, Jenna
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- 2019
30. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019: Update From the GBD 2019 Study
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Roth, Gregory A., Mensah, George A., Johnson, Catherine O., Addolorato, Giovanni, Ammirati, Enrico, Baddour, Larry M., Barengo, Noel C., Beaton, Andrea, Benjamin, Emelia J., Benziger, Catherine P., Bonny, Aime, Brauer, Michael, Brodmann, Marianne, Cahill, Thomas J., Carapetis, Jonathan R., Catapano, Alberico L., Chugh, Sumeet, Cooper, Leslie T., Coresh, Josef, Criqui, Michael H., DeCleene, Nicole K., Eagle, Kim A., Emmons-Bell, Sophia, Feigin, Valery L., Fernández-Sola, Joaquim, Fowkes, F. Gerry R., Gakidou, Emmanuela, Grundy, Scott M., He, Feng J., Howard, George, Hu, Frank, Inker, Lesley, Karthikeyan, Ganesan, Kassebaum, Nicholas J., Koroshetz, Walter J., Lavie, Carl, Lloyd-Jones, Donald, Lu, Hong S., Mirijello, Antonio, Misganaw, Awoke T., Mokdad, Ali H., Moran, Andrew E., Muntner, Paul, Narula, Jagat, Neal, Bruce, Ntsekhe, Mpiko, Oliveira, Gláucia M.M., Otto, Catherine M., Owolabi, Mayowa O., Pratt, Michael, Rajagopalan, Sanjay, Reitsma, Marissa B., Ribeiro, Antonio Luiz P., Rigotti, Nancy A., Rodgers, Anthony, Sable, Craig A., Shakil, Saate S., Sliwa, Karen, Stark, Benjamin A., Sundström, Johan, Timpel, Patrick, Tleyjeh, Imad I., Valgimigli, Marco, Vos, Theo, Whelton, Paul K., Yacoub, Magdi, Zuhlke, Liesl J., Abbasi-Kangevari, Mohsen, Abdi, Alireza, Abedi, Aidin, Aboyans, Victor, Abrha, Woldu A., Abu-Gharbieh, Eman, Abushouk, Abdelrahman I., Acharya, Dilaram, Adair, Tim, Adebayo, Oladimeji M., Ademi, Zanfina, Advani, Shailesh M., Afshari, Khashayar, Afshin, Ashkan, Agarwal, Gina, Agasthi, Pradyumna, Ahmad, Sohail, Ahmadi, Sepideh, Ahmed, Muktar B., Aji, Budi, Akalu, Yonas, Akande-Sholabi, Wuraola, Aklilu, Addis, Akunna, Chisom J., Alahdab, Fares, Al-Eyadhy, Ayman, Alhabib, Khalid F., Alif, Sheikh M., Alipour, Vahid, Aljunid, Syed M., Alla, François, Almasi-Hashiani, Amir, Almustanyir, Sami, Al-Raddadi, Rajaa M., Amegah, Adeladza K., Amini, Saeed, Aminorroaya, Arya, Amu, Hubert, Amugsi, Dickson A., Ancuceanu, Robert, Anderlini, Deanna, Andrei, Tudorel, Andrei, Catalina Liliana, Ansari-Moghaddam, Alireza, Anteneh, Zelalem A., Antonazzo, Ippazio Cosimo, Antony, Benny, Anwer, Razique, Appiah, Lambert T., Arabloo, Jalal, Ärnlöv, Johan, Artanti, Kurnia D., Ataro, Zerihun, Ausloos, Marcel, Avila-Burgos, Leticia, Awan, Asma T., Awoke, Mamaru A., Ayele, Henok T., Ayza, Muluken A., Azari, Samad, B, Darshan B., Baheiraei, Nafiseh, Baig, Atif A., Bakhtiari, Ahad, Banach, Maciej, Banik, Palash C., Baptista, Emerson A., Barboza, Miguel A., Barua, Lingkan, Basu, Sanjay, Bedi, Neeraj, Béjot, Yannick, Bennett, Derrick A., Bensenor, Isabela M., Berman, Adam E., Bezabih, Yihienew M., Bhagavathula, Akshaya S., Bhaskar, Sonu, Bhattacharyya, Krittika, Bijani, Ali, Bikbov, Boris, Birhanu, Mulugeta M., Boloor, Archith, Brant, Luisa C., Brenner, Hermann, Briko, Nikolay I., Butt, Zahid A., Caetano dos Santos, Florentino Luciano, Cahill, Leah E., Cahuana-Hurtado, Lucero, Cámera, Luis A., Campos-Nonato, Ismael R., Cantu-Brito, Carlos, Car, Josip, Carrero, Juan J., Carvalho, Felix, Castañeda-Orjuela, Carlos A., Catalá-López, Ferrán, Cerin, Ester, Charan, Jaykaran, Chattu, Vijay Kumar, Chen, Simiao, Chin, Ken L., Choi, Jee-Young J., Chu, Dinh-Toi, Chung, Sheng-Chia, Cirillo, Massimo, Coffey, Sean, Conti, Sara, Costa, Vera M., Cundiff, David K., Dadras, Omid, Dagnew, Baye, Dai, Xiaochen, Damasceno, Albertino A.M., Dandona, Lalit, Dandona, Rakhi, Davletov, Kairat, De la Cruz-Góngora, Vanessa, De la Hoz, Fernando P., De Neve, Jan-Walter, Denova-Gutiérrez, Edgar, Derbew Molla, Meseret, Derseh, Behailu T., Desai, Rupak, Deuschl, Günther, Dharmaratne, Samath D., Dhimal, Meghnath, Dhungana, Raja Ram, Dianatinasab, Mostafa, Diaz, Daniel, Djalalinia, Shirin, Dokova, Klara, Douiri, Abdel, Duncan, Bruce B., Duraes, Andre R., Eagan, Arielle W., Ebtehaj, Sanam, Eftekhari, Aziz, Eftekharzadeh, Sahar, Ekholuenetale, Michael, El Nahas, Nevine, Elgendy, Islam Y., Elhadi, Muhammed, El-Jaafary, Shaimaa I., Esteghamati, Sadaf, Etisso, Atkilt E., Eyawo, Oghenowede, Fadhil, Ibtihal, Faraon, Emerito Jose A., Faris, Pawan S., Farwati, Medhat, Farzadfar, Farshad, Fernandes, Eduarda, Fernandez Prendes, Carlota, Ferrara, Pietro, Filip, Irina, Fischer, Florian, Flood, David, Fukumoto, Takeshi, Gad, Mohamed M., Gaidhane, Shilpa, Ganji, Morsaleh, Garg, Jalaj, Gebre, Abadi K., Gebregiorgis, Birhan G., Gebregzabiher, Kidane Z., Gebremeskel, Gebreamlak G., Getacher, Lemma, Obsa, Abera Getachew, Ghajar, Alireza, Ghashghaee, Ahmad, Ghith, Nermin, Giampaoli, Simona, Gilani, Syed Amir, Gill, Paramjit S., Gillum, Richard F., Glushkova, Ekaterina V., Gnedovskaya, Elena V., Golechha, Mahaveer, Gonfa, Kebebe B., Goudarzian, Amir Hossein, Goulart, Alessandra C., Guadamuz, Jenny S., Guha, Avirup, Guo, Yuming, Gupta, Rajeev, Hachinski, Vladimir, Hafezi-Nejad, Nima, Haile, Teklehaimanot G., Hamadeh, Randah R., Hamidi, Samer, Hankey, Graeme J., Hargono, Arief, Hartono, Risky K., Hashemian, Maryam, Hashi, Abdiwahab, Hassan, Shoaib, Hassen, Hamid Y., Havmoeller, Rasmus J., Hay, Simon I., Hayat, Khezar, Heidari, Golnaz, Herteliu, Claudiu, Holla, Ramesh, Hosseini, Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Househ, Mowafa, Huang, Junjie, Humayun, Ayesha, Iavicoli, Ivo, Ibeneme, Charles U., Ibitoye, Segun E., Ilesanmi, Olayinka S., Ilic, Irena M., Ilic, Milena D., Iqbal, Usman, Irvani, Seyed Sina N., Islam, Sheikh Mohammed Shariful, Islam, Rakibul M., Iso, Hiroyasu, Iwagami, Masao, Jain, Vardhmaan, Javaheri, Tahereh, Jayapal, Sathish Kumar, Jayaram, Shubha, Jayawardena, Ranil, Jeemon, Panniyammakal, Jha, Ravi P., Jonas, Jost B., Jonnagaddala, Jitendra, Joukar, Farahnaz, Jozwiak, Jacek J., Jürisson, Mikk, Kabir, Ali, Kahlon, Tanvir, Kalani, Rizwan, Kalhor, Rohollah, Kamath, Ashwin, Kamel, Ibrahim, Kandel, Himal, Kandel, Amit, Karch, André, Kasa, Ayele Semachew, Katoto, Patrick D.M.C., Kayode, Gbenga A., Khader, Yousef S., Khammarnia, Mohammad, Khan, Muhammad S., Khan, Md Nuruzzaman, Khan, Maseer, Khan, Ejaz A., Khatab, Khaled, Kibria, Gulam M.A., Kim, Yun Jin, Kim, Gyu Ri, Kimokoti, Ruth W., Kisa, Sezer, Kisa, Adnan, Kivimäki, Mika, Kolte, Dhaval, Koolivand, Ali, Korshunov, Vladimir A., Koulmane Laxminarayana, Sindhura Lakshmi, Koyanagi, Ai, Krishan, Kewal, Krishnamoorthy, Vijay, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kulkarni, Vaman, Kumar, G. Anil, Kumar, Nithin, Kurmi, Om P., Kusuma, Dian, Kwan, Gene F., La Vecchia, Carlo, Lacey, Ben, Lallukka, Tea, Lan, Qing, Lasrado, Savita, Lassi, Zohra S., Lauriola, Paolo, Lawrence, Wayne R., Laxmaiah, Avula, LeGrand, Kate E., Li, Ming-Chieh, Li, Bingyu, Li, Shanshan, Lim, Stephen S., Lim, Lee-Ling, Lin, Hualiang, Lin, Ziqiang, Lin, Ro-Ting, Liu, Xuefeng, Lopez, Alan D., Lorkowski, Stefan, Lotufo, Paulo A., Lugo, Alessandra, M, Nirmal K., Madotto, Fabiana, Mahmoudi, Morteza, Majeed, Azeem, Malekzadeh, Reza, Malik, Ahmad A., Mamun, Abdullah A., Manafi, Navid, Mansournia, Mohammad Ali, Mantovani, Lorenzo G., Martini, Santi, Mathur, Manu R., Mazzaglia, Giampiero, Mehata, Suresh, Mehndiratta, Man Mohan, Meier, Toni, Menezes, Ritesh G., Meretoja, Atte, Mestrovic, Tomislav, Miazgowski, Bartosz, Miazgowski, Tomasz, Michalek, Irmina Maria, Miller, Ted R., Mirrakhimov, Erkin M., Mirzaei, Hamed, Moazen, Babak, Moghadaszadeh, Masoud, Mohammad, Yousef, Mohammad, Dara K., Mohammed, Shafiu, Mohammed, Mohammed A., Mokhayeri, Yaser, Molokhia, Mariam, Montasir, Ahmed A., Moradi, Ghobad, Moradzadeh, Rahmatollah, Moraga, Paula, Morawska, Lidia, Moreno Velásquez, Ilais, Morze, Jakub, Mubarik, Sumaira, Muruet, Walter, Musa, Kamarul Imran, Nagarajan, Ahamarshan J., Nalini, Mahdi, Nangia, Vinay, Naqvi, Atta Abbas, Narasimha Swamy, Sreenivas, Nascimento, Bruno R., Nayak, Vinod C., Nazari, Javad, Nazarzadeh, Milad, Negoi, Ruxandra I., Neupane Kandel, Sandhya, Nguyen, Huong L.T., Nixon, Molly R., Norrving, Bo, Noubiap, Jean Jacques, Nouthe, Brice E., Nowak, Christoph, Odukoya, Oluwakemi O., Ogbo, Felix A., Olagunju, Andrew T., Orru, Hans, Ortiz, Alberto, Ostroff, Samuel M., Padubidri, Jagadish Rao, Palladino, Raffaele, Pana, Adrian, Panda-Jonas, Songhomitra, Parekh, Utsav, Park, Eun-Cheol, Parvizi, Mojtaba, Pashazadeh Kan, Fatemeh, Patel, Urvish K., Pathak, Mona, Paudel, Rajan, Pepito, Veincent Christian F., Perianayagam, Arokiasamy, Perico, Norberto, Pham, Hai Q., Pilgrim, Thomas, Piradov, Michael A., Pishgar, Farhad, Podder, Vivek, Polibin, Roman V., Pourshams, Akram, Pribadi, Dimas R.A., Rabiee, Navid, Rabiee, Mohammad, Radfar, Amir, Rafiei, Alireza, Rahim, Fakher, Rahimi-Movaghar, Vafa, Ur Rahman, Mohammad Hifz, Rahman, Muhammad Aziz, Rahmani, Amir Masoud, Rakovac, Ivo, Ram, Pradhum, Ramalingam, Sudha, Rana, Juwel, Ranasinghe, Priyanga, Rao, Sowmya J., Rathi, Priya, Rawal, Lal, Rawasia, Wasiq F., Rawassizadeh, Reza, Remuzzi, Giuseppe, Renzaho, Andre M.N., Rezapour, Aziz, Riahi, Seyed Mohammad, Roberts-Thomson, Ross L., Roever, Leonardo, Rohloff, Peter, Romoli, Michele, Roshandel, Gholamreza, Rwegerera, Godfrey M., Saadatagah, Seyedmohammad, Saber-Ayad, Maha M., Sabour, Siamak, Sacco, Simona, Sadeghi, Masoumeh, Saeedi Moghaddam, Sahar, Safari, Saeed, Sahebkar, Amirhossein, Salehi, Sana, Salimzadeh, Hamideh, Samaei, Mehrnoosh, Samy, Abdallah M., Santos, Itamar S., Santric-Milicevic, Milena M., Sarrafzadegan, Nizal, Sarveazad, Arash, Sathish, Thirunavukkarasu, Sawhney, Monika, Saylan, Mete, Schmidt, Maria I., Schutte, Aletta E., Senthilkumaran, Subramanian, Sepanlou, Sadaf G., Sha, Feng, Shahabi, Saeed, Shahid, Izza, Shaikh, Masood A., Shamali, Mahdi, Shamsizadeh, Morteza, Shawon, Md Shajedur Rahman, Sheikh, Aziz, Shigematsu, Mika, Shin, Min-Jeong, Shin, Jae Il, Shiri, Rahman, Shiue, Ivy, Shuval, Kerem, Siabani, Soraya, Siddiqi, Tariq J., Silva, Diego A.S., Singh, Jasvinder A., Mtech, Ambrish Singh, Skryabin, Valentin Y., Skryabina, Anna A., Soheili, Amin, Spurlock, Emma E., Stockfelt, Leo, Stortecky, Stefan, Stranges, Saverio, Suliankatchi Abdulkader, Rizwan, Tadbiri, Hooman, Tadesse, Eyayou G., Tadesse, Degena B., Tajdini, Masih, Tariqujjaman, Md, Teklehaimanot, Berhane F., Temsah, Mohamad-Hani, Tesema, Ayenew K., Thakur, Bhaskar, Thankappan, Kavumpurathu R., Thapar, Rekha, Thrift, Amanda G., Timalsina, Binod, Tonelli, Marcello, Touvier, Mathilde, Tovani-Palone, Marcos R., Tripathi, Avnish, Tripathy, Jaya P., Truelsen, Thomas C., Tsegay, Guesh M., Tsegaye, Gebiyaw W., Tsilimparis, Nikolaos, Tusa, Biruk S., Tyrovolas, Stefanos, Umapathi, Krishna Kishore, Unim, Brigid, Unnikrishnan, Bhaskaran, Usman, Muhammad S., Vaduganathan, Muthiah, Valdez, Pascual R., Vasankari, Tommi J., Velazquez, Diana Z., Venketasubramanian, Narayanaswamy, Vu, Giang T., Vujcic, Isidora S., Waheed, Yasir, Wang, Yanzhong, Wang, Fang, Wei, Jingkai, Weintraub, Robert G., Weldemariam, Abrha H., Westerman, Ronny, Winkler, Andrea S., Wiysonge, Charles S., Wolfe, Charles D.A., Wubishet, Befikadu Legesse, Xu, Gelin, Yadollahpour, Ali, Yamagishi, Kazumasa, Yan, Lijing L., Yandrapalli, Srikanth, Yano, Yuichiro, Yatsuya, Hiroshi, Yeheyis, Tomas Y., Yeshaw, Yigizie, Yilgwan, Christopher S., Yonemoto, Naohiro, Yu, Chuanhua, Yusefzadeh, Hasan, Zachariah, Geevar, Zaman, Sojib Bin, Zaman, Muhammed S., Zamanian, Maryam, Zand, Ramin, Zandifar, Alireza, Zarghi, Afshin, Zastrozhin, Mikhail S., Zastrozhina, Anasthasia, Zhang, Zhi-Jiang, Zhang, Yunquan, Zhang, Wangjian, Zhong, Chenwen, Zou, Zhiyong, Zuniga, Yves Miel H., Murray, Christopher J.L., Fuster, Valentin, Barengo, Noël C., Beaton, Andrea Z., Bonny, Aimé, Carapetis, Jonathan, Chugh, Sumeet S., Criqui, Michael, DeCleene, Nicole, Fernández-Solà, Joaquim, Fowkes, Gerry, Kassebaum, Nicholas, Koroshetz, Walter, Temesgen, Awoke Misganaw, Mokdad, Ali, Moraes de Oliveira, Glaucia, Otto, Catherine, Owolabi, Mayowa, Reitsma, Marissa, Rigotti, Nancy, Sable, Craig, Shakil, Saate, Sliwa-Hahnle, Karen, Stark, Benjamin, Tleyjeh, Imad M., Zuhlke, Liesl, and Murray, Christopher
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- 2020
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31. 'If It Was Easy Somebody Would Have Fixed It': An Exploration of Loneliness and Social Isolation Amongst People Who Frequently Call Ambulance Services.
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Moseley, Lisa, Scott, Jason, Fidler, Gayle, Agarwal, Gina, Clarke, Cathy, Hammond‐Williams, Jonathan, Ingram, Carrie, McDonnell, Aidan, and Collins, Tracy
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HEALTH services accessibility ,RESEARCH funding ,INTERVIEWING ,LONELINESS ,EMERGENCY medical services ,THEMATIC analysis ,AMBULANCES ,RESEARCH methodology ,MEDICAL needs assessment ,DATA analysis software ,SOCIAL isolation ,ACTIVITIES of daily living ,COVID-19 ,PSYCHOSOCIAL factors - Abstract
Introduction: The aim of the study was to explore social isolation and loneliness in those who frequently contacted the ambulance service, what factors contributed to this and how unmet needs could be addressed. Methods: Semi‐structured interviews with staff from the ambulance service and service users who were identified as frequently contacting the ambulance service. Service users also completed the UCLA loneliness scale and personal community maps. Data were analysed thematically before triangulation with the UCLA loneliness scale and personal community maps. Results: The final analysis was drawn from 15 staff and seven service user participants. The relationship between social isolation and loneliness and contacting the ambulance service was a contributing, but not the driving, factor in contacting the ambulance service. For service users, we identified three key themes: (1) impact on activities of daily living and loneliness and/or isolation as a result of a health condition; (2) accessing appropriate health and social care services to meet needs; (3) the link between social isolation and/or loneliness and contact with the ambulance service. The analysis of staff data also highlighted three key themes: (1) social isolation and/or loneliness in their role; (2) access to other appropriate health and social care services; (3) the impact of austerity and Covid‐19 on social isolation and/or loneliness. Conclusions: Our research emphasises the complex nature of social isolation and loneliness, including the cyclic nature of poor health and social isolation and loneliness, and how this contributes to contact with the ambulance service. Patient or Public Contribution: The advisory group for the study was supported by a public and patient representative who contributed to the design of the study documentation, data analysis and authorship. [ABSTRACT FROM AUTHOR]
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- 2024
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32. Effect of a Legal Clinic Program Within an Urban Primary Health Care Center on Social Determinants of Health: A Program Evaluation
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Agarwal, Gina, primary, Pirrie, Melissa, additional, Edwards, Dan, additional, Delleman, Bethany, additional, Crowe, Sharon, additional, Tye, Hugh, additional, and Mallin, Jayne, additional
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- 2024
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33. Older adults living in social housing in Canada: the next COVID-19 hotspot?
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Pirrie, Melissa and Agarwal, Gina
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- 2021
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34. “You are the only other person in the world that knows that about me”: Family physician stories of proximity to patients experiencing social inequity
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Molinaro, Monica L., primary, Shen, Katrina, additional, Tandon, Chitrini, additional, Agarwal, Gina, additional, Inglis, Gabrielle, additional, and Vanstone, Meredith, additional
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- 2023
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35. Development of indicators for avoidable emergency medical service calls by mapping paramedic clinical impression codes to ambulatory care sensitive conditions and mental health conditions in the UK and Canada
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Agarwal, Gina, primary, Siriwardena, Aloysius Niroshan, additional, McLeod, Brent, additional, Spaight, Robert, additional, Whitley, Gregory Adam, additional, Ferron, Richard, additional, Pirrie, Melissa, additional, Angeles, Ricardo, additional, Moore, Harriet, additional, and Gussy, Mark, additional
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- 2023
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36. Reshaping healthcare delivery for elderly patients: the role of community paramedicine; a systematic review
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van Vuuren, Julia, Thomas, Brodie, Agarwal, Gina, MacDermott, Sean, Kinsman, Leigh, O’Meara, Peter, and Spelten, Evelien
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- 2021
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37. The effect of COVID-19 on emergency medical service call volumes and patient acuity: a cross-sectional study in Niagara, Ontario
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Ferron, Richard, Agarwal, Gina, Cooper, Rhiannon, and Munkley, Douglas
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- 2021
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38. Participation in the Cardiovascular Health Awareness Program (CHAP) by older adults residing in social housing in Quebec: Social network analysis
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Deville-Stoetzel, Nadia, Kaczorowski, Janusz, Agarwal, Gina, Lussier, Marie-Thérèse, and Girard, Magali
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- 2021
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39. Cardiometabolic risk factors in social housing residents: A multi-site cross-sectional survey in older adults from Ontario, Canada.
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Agarwal, Gina, Lee, Janice, Keshavarz, Homa, Angeles, Ricardo, Pirrie, Melissa, and Marzanek, Francine
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OLDER people , *CARDIOVASCULAR diseases risk factors , *HEART metabolism disorders , *DISEASE risk factors , *QUALITY of life - Abstract
Objective: This study describes cardiometabolic diseases and related risk factors in vulnerable older adults residing in social housing, aiming to inform primary care initiatives to reduce health inequities. Associations between sociodemographic variables, modifiable risk factors (clinical and behavioural), health-related quality of life and self-reported cardiometabolic diseases were investigated. Design, setting, and participants: This was a cross-sectional study with an interviewer-administered questionnaire. Data was collected from residents aged 55 years and older residing in 30 social housing apartment buildings in five regions in Ontario, Canada. Outcome measures: The proportion of cardiometabolic diseases and modifiable risk factors (e.g., clinical, behavioural, health status) in this population was calculated. Results: Questionnaires were completed with 1065 residents: mean age 72.4 years (SD = 8.87), 77.3% were female, 87.2% were white; 48.2% had less than high school education; 22.70% self-reported cardiovascular disease (CVD), 10.54% diabetes, 59.12% hypertension, 43.59% high cholesterol. These proportions were higher than the general population. Greater age was associated with overweight, high cholesterol, high blood pressure and CVD. Poor health-related quality of life was associated with self-reported CVD and diabetes. Conclusions: Older adults residing in social housing in Ontario have higher proportion of cardiovascular disease and modifiable risk factors compared to the general population. This vulnerable population should be considered at high risk of cardiometabolic disease. Primary care interventions appropriate for this population should be implemented to reduce individual and societal burdens of cardiometabolic disease. [ABSTRACT FROM AUTHOR]
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- 2024
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40. Conceptualising social prescribing in urgent and emergency care
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Cooper, Matthew, Nazar, Hamde, Flynn, Darren, Redelsteiner, Christoph, Agarwal, Gina, and Scott, Jason
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- 2024
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41. Perceived value and benefits of the Community Paramedicine at Clinic (CP@clinic) programme: a descriptive qualitative study
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Marzanek, Francine, primary, Nair, Kalpana, additional, Ziesmann, Andrea, additional, Paramalingam, Aarani, additional, Pirrie, Melissa, additional, Angeles, Ricardo, additional, and Agarwal, Gina, additional
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- 2023
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42. Reasons for Calling EMS
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Angeles, Ricardo, primary, McLeod, Brent, additional, Lee, Janice, additional, Mahmuda, Sabnam, additional, Stocic, Alix, additional, Howard, Michelle, additional, and Agarwal, Gina, additional
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- 2023
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43. Adapting the Community Paramedicine at Clinic (CP@clinic) program to a remote northern first nation community: a qualitative study of community members’ and local health care providers’ views
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Keenan, Amelia, primary, Sadri, Pauneez, additional, Marzanek, Francine, additional, Pirrie, Melissa, additional, Angeles, Ricardo, additional, and Agarwal, Gina, additional
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- 2023
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44. Assessing health literacy among older adults living in subsidized housing : a cross-sectional study
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Agarwal, Gina, Habing, Kendra, Pirrie, Melissa, Angeles, Ric, Marzanek, Francine, and Parascandalo, Jenna
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- 2018
45. Legal needs of patients attending an urban family practice in Hamilton, Ontario, Canada: an observational study of a legal health clinic
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Agarwal, Gina, Pirrie, Melissa, Edwards, Dan, Delleman, Bethany, Crowe, Sharon, Tye, Hugh, and Mallin, Jayne
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- 2020
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46. Family physicians’ moral distress when caring for patients experiencing social inequities: a critical narrative inquiry in primary care
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Molinaro, Monica L, primary, Shen, Katrina, additional, Agarwal, Gina, additional, Inglis, Gabrielle, additional, and Vanstone, Meredith, additional
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- 2023
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47. Feasibility of implementing a community cardiovascular health promotion program with paramedics and volunteers in a South Asian population
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Agarwal, Gina, Bhandari, Manika, Pirrie, Melissa, Angeles, Ricardo, and Marzanek, Francine
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- 2020
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48. Poverty and food insecurity of older adults living in social housing in Ontario: a cross-sectional study
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Pirrie, Melissa, Harrison, Leila, Angeles, Ricardo, Marzanek, Francine, Ziesmann, Andrea, and Agarwal, Gina
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- 2020
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49. Disconnected relationships between primary care and community-based health and social services and system navigation for older adults: a qualitative descriptive study
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Valaitis, Ruta, Cleghorn, Laura, Ploeg, Jenny, Risdon, Cathy, Mangin, Derelie, Dolovich, Lisa, Agarwal, Gina, Oliver, Doug, Gaber, Jessica, and Chung, Harjit
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- 2020
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50. Examining Interprofessional teams structures and processes in the implementation of a primary care intervention (Health TAPESTRY) for older adults using normalization process theory
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Valaitis, Ruta, Cleghorn, Laura, Dolovich, Lisa, Agarwal, Gina, Gaber, Jessica, Mangin, Derelie, Oliver, Doug, Parascandalo, Fiona, Ploeg, Jenny, and Risdon, Cathy
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- 2020
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