Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2·5 air pollution, 1990–2019 : an analysis of data from the Global Burden of Disease Study 2019
- Burkart, Katrin, Causey, Kate, Cohen, Aaron, Wozniak, Sarah, Salvi, Devashri, Abbafati, Cristiana, Adekanmbi, Victor, Adsuar, Jose, Ahmadi, Keivan, Alahdab, Fares, Al-Aly, Ziyad, Alipour, Vahid, Alvis-Guzman, Nelson, Amegah, Adeladza, Andrei, Catalina, Andrei, Tudorel, Ansari, Fereshteh, Arabloo, Jalal, Aremu, Olatunde, Aripov, Timur, Babaee, Ebrahim, Banach, Maclej, Barnett, Anthony, Bärnighausen, Till, Bedi, Neeraj, Behzadifar, Masoud, Béjot, Yannick, Bennett, Derrick, Rahman, Muhammad Aziz
- Authors: Burkart, Katrin , Causey, Kate , Cohen, Aaron , Wozniak, Sarah , Salvi, Devashri , Abbafati, Cristiana , Adekanmbi, Victor , Adsuar, Jose , Ahmadi, Keivan , Alahdab, Fares , Al-Aly, Ziyad , Alipour, Vahid , Alvis-Guzman, Nelson , Amegah, Adeladza , Andrei, Catalina , Andrei, Tudorel , Ansari, Fereshteh , Arabloo, Jalal , Aremu, Olatunde , Aripov, Timur , Babaee, Ebrahim , Banach, Maclej , Barnett, Anthony , Bärnighausen, Till , Bedi, Neeraj , Behzadifar, Masoud , Béjot, Yannick , Bennett, Derrick , Rahman, Muhammad Aziz
- Date: 2022
- Type: Text , Journal article
- Relation: The Lancet Planetary Health Vol. 6, no. 7 (2022), p. e586-e600
- Full Text:
- Reviewed:
- Description: Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Interpretation: Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Funding: Bill & Melinda Gates Foundation. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Muhammad Aziz Rahman” is provided in this record**
- Authors: Burkart, Katrin , Causey, Kate , Cohen, Aaron , Wozniak, Sarah , Salvi, Devashri , Abbafati, Cristiana , Adekanmbi, Victor , Adsuar, Jose , Ahmadi, Keivan , Alahdab, Fares , Al-Aly, Ziyad , Alipour, Vahid , Alvis-Guzman, Nelson , Amegah, Adeladza , Andrei, Catalina , Andrei, Tudorel , Ansari, Fereshteh , Arabloo, Jalal , Aremu, Olatunde , Aripov, Timur , Babaee, Ebrahim , Banach, Maclej , Barnett, Anthony , Bärnighausen, Till , Bedi, Neeraj , Behzadifar, Masoud , Béjot, Yannick , Bennett, Derrick , Rahman, Muhammad Aziz
- Date: 2022
- Type: Text , Journal article
- Relation: The Lancet Planetary Health Vol. 6, no. 7 (2022), p. e586-e600
- Full Text:
- Reviewed:
- Description: Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Interpretation: Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Funding: Bill & Melinda Gates Foundation. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Muhammad Aziz Rahman” is provided in this record**
- Causey, Kate, Salvi, Devashri, Abbafati, Cristiana, Adekanmbi, Victor, Adsuar, Jose, Ahmadi, Keivan, Alahdab, Fares, Andrei, Catalina, Arabloo, Jalal, Aripov, Timur, Babaee, Ebrahim, Barnett, Anthony, Bedi, Neeraj, Béjot, Yannick, Bernstein, Robert, Bijani, Ali, Brenner, Hermann, Butt, Zahid, Cantu-Brito, Carlos, Chauhan, Bal Govind, Choi, Jee-Young Jasmine, Dai, Xiaochen, Dandona, Lalit, Dandona, Rakhi, Daryani, Ahmad, Davletov, Kairat, Dharmaratne, Samath, Diaz, Daniel, Duncan, Bruce, Fattahi, Nazir, Fazlzadeh, Mehdi, Fernandes, Eduarda, Filip, Irina, Foigt, Nataliya, Freitas, Marisa, Gill, Paramjit Singh, Habtewold, Tesfa, Hamadeh, Randah, Hasanpoor, Edris, Heibati, Behzad, Househ, Mowafa, Jaafari, Jalil, Jakovljevic, Mihajlo, Jha, Ravi Prakash, Jonas, Jost, Khafaie, Morteza, Khatab, Khaled, Kivimäki, Mika, Koyanagi, Ai, Lee, Paul, Lewycka, Sonia, Li, Shanshan, Lim, Lee-Ling, Mahotra, Narayan, Majeed, Azeem, Maleki, Afshin, Mamun, Abdullah, Martini, Santi, Meharie, Birhanu, Menezes, Ritesh, Mestrovic, Tomislav, Miazgowski, Tomasz, Mini, G. K., Mirica, Andreea, Mohan, Viswanathan, Moraga, Paula, Morrison, Shane, Mueller, Ulrich, Mukhopadhyay, Satinath, Mustafa, Ghulam, Nangia, Vinay, Ningrum, Dina, Owolabi, Mayowa, P A, Mahesh, Pourjafar, Hadi, Rafiei, Alireza, Rai, Rajesh, Raoofi, Samira, Renzaho, Andre, Ronfani, Luca, Sabour, Siamak, Sadeghi, Ehsan, Sarmiento-Suárez, Rodrigo, Schutte, Aletta, Sharafi, Kiomars, Sheikh, Aziz, Shirkoohi, Reza, Shuval, Kerem, Soyiri, Ireneous, Topor-Madry, Roman, Ullah, Irfan, Vacante, Marco, Violante, Francesco, Waheed, Yasir, Wolfe, Charles, Yamada, Tomohide, Yonemoto, Naohiro, Yu, Chuanhua, Zaman, Sojib, Brauer, Michael
- Authors: Causey, Kate , Salvi, Devashri , Abbafati, Cristiana , Adekanmbi, Victor , Adsuar, Jose , Ahmadi, Keivan , Alahdab, Fares , Andrei, Catalina , Arabloo, Jalal , Aripov, Timur , Babaee, Ebrahim , Barnett, Anthony , Bedi, Neeraj , Béjot, Yannick , Bernstein, Robert , Bijani, Ali , Brenner, Hermann , Butt, Zahid , Cantu-Brito, Carlos , Chauhan, Bal Govind , Choi, Jee-Young Jasmine , Dai, Xiaochen , Dandona, Lalit , Dandona, Rakhi , Daryani, Ahmad , Davletov, Kairat , Dharmaratne, Samath , Diaz, Daniel , Duncan, Bruce , Fattahi, Nazir , Fazlzadeh, Mehdi , Fernandes, Eduarda , Filip, Irina , Foigt, Nataliya , Freitas, Marisa , Gill, Paramjit Singh , Habtewold, Tesfa , Hamadeh, Randah , Hasanpoor, Edris , Heibati, Behzad , Househ, Mowafa , Jaafari, Jalil , Jakovljevic, Mihajlo , Jha, Ravi Prakash , Jonas, Jost , Khafaie, Morteza , Khatab, Khaled , Kivimäki, Mika , Koyanagi, Ai , Lee, Paul , Lewycka, Sonia , Li, Shanshan , Lim, Lee-Ling , Mahotra, Narayan , Majeed, Azeem , Maleki, Afshin , Mamun, Abdullah , Martini, Santi , Meharie, Birhanu , Menezes, Ritesh , Mestrovic, Tomislav , Miazgowski, Tomasz , Mini, G. K. , Mirica, Andreea , Mohan, Viswanathan , Moraga, Paula , Morrison, Shane , Mueller, Ulrich , Mukhopadhyay, Satinath , Mustafa, Ghulam , Nangia, Vinay , Ningrum, Dina , Owolabi, Mayowa , P A, Mahesh , Pourjafar, Hadi , Rafiei, Alireza , Rai, Rajesh , Raoofi, Samira , Renzaho, Andre , Ronfani, Luca , Sabour, Siamak , Sadeghi, Ehsan , Sarmiento-Suárez, Rodrigo , Schutte, Aletta , Sharafi, Kiomars , Sheikh, Aziz , Shirkoohi, Reza , Shuval, Kerem , Soyiri, Ireneous , Topor-Madry, Roman , Ullah, Irfan , Vacante, Marco , Violante, Francesco , Waheed, Yasir , Wolfe, Charles , Yamada, Tomohide , Yonemoto, Naohiro , Yu, Chuanhua , Zaman, Sojib , Brauer, Michael
- Date: 2022
- Type: Text , Journal article
- Relation: The Lancet. Planetary health Vol. 6, no. 7 (2022), p. e586-e600
- Full Text: false
- Reviewed:
- Description: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Bill & Melinda Gates Foundation.
Diabetes mortality and trends before 25 years of age : an analysis of the global burden of disease study 2019
- Cousin, Ewerton, Duncan, Bruce, Stein, Caroline, Ong, Kanyin, Vos, Theo, Abbafati, Cristiana, Abbasi-Kangevari, Mohsen, Abdelmasseh, Michael, Abdoli, Amir, Abd-Rabu, Rami, Abolhassani, Hassan, Abu-Gharbieh, Eman, Accrombessi, Manfred, Adnani, Qorinah, Afzal, Muhammad, Agarwal, Gina, Agrawaal, Krishna, Agudelo-Botero, Marcela, Ahinkorah, Bright, Ahmad, Sajjad, Ahmad, Tauseef, Ahmadi, Keivan, Ahmadi, Sepideh, Ahmadi, Ali, Ahmed, Ali, Ahmed Salih, Yusra, Akande-Sholabi, Wuraola, Akram, Tayyaba, Al Hamad, Hanadi, Al-Aly, Ziyad, Rahman, Muhammad Aziz
- Authors: Cousin, Ewerton , Duncan, Bruce , Stein, Caroline , Ong, Kanyin , Vos, Theo , Abbafati, Cristiana , Abbasi-Kangevari, Mohsen , Abdelmasseh, Michael , Abdoli, Amir , Abd-Rabu, Rami , Abolhassani, Hassan , Abu-Gharbieh, Eman , Accrombessi, Manfred , Adnani, Qorinah , Afzal, Muhammad , Agarwal, Gina , Agrawaal, Krishna , Agudelo-Botero, Marcela , Ahinkorah, Bright , Ahmad, Sajjad , Ahmad, Tauseef , Ahmadi, Keivan , Ahmadi, Sepideh , Ahmadi, Ali , Ahmed, Ali , Ahmed Salih, Yusra , Akande-Sholabi, Wuraola , Akram, Tayyaba , Al Hamad, Hanadi , Al-Aly, Ziyad , Rahman, Muhammad Aziz
- Date: 2022
- Type: Text , Journal article
- Relation: The Lancet Diabetes and Endocrinology Vol. 10, no. 3 (2022), p. 177-192
- Full Text:
- Reviewed:
- Description: Background: Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods: We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990–2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. Findings: In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73·7% (68·3 to 77·4) were classified as due to type 1 diabetes. The age-standardised death rate was 0·50 (0·44 to 0·58) per 100 000 population, and 15 900 (97·5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0·13 (0·12 to 0·14) per 100 000 population in the high SDI quintile, 0·60 (0·51 to 0·70) per 100 000 population in the low-middle SDI quintile, and 0·71 (0·60 to 0·86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r2=0·62). From 1990 to 2019, age-standardised death rates decreased globally by 17·0%. **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Muhammad Aziz Rahman" is provided in this record**
- Description: Background: Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods: We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990–2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. Findings: In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73·7% (68·3 to 77·4) were classified as due to type 1 diabetes. The age-standardised death rate was 0·50 (0·44 to 0·58) per 100 000 population, and 15 900 (97·5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0·13 (0·12 to 0·14) per 100 000 population in the high SDI quintile, 0·60 (0·51 to 0·70) per 100 000 population in the low-middle SDI quintile, and 0·71 (0·60 to 0·86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r2=0·62). From 1990 to 2019, age-standardised death rates decreased globally by 17·0% (
- Authors: Cousin, Ewerton , Duncan, Bruce , Stein, Caroline , Ong, Kanyin , Vos, Theo , Abbafati, Cristiana , Abbasi-Kangevari, Mohsen , Abdelmasseh, Michael , Abdoli, Amir , Abd-Rabu, Rami , Abolhassani, Hassan , Abu-Gharbieh, Eman , Accrombessi, Manfred , Adnani, Qorinah , Afzal, Muhammad , Agarwal, Gina , Agrawaal, Krishna , Agudelo-Botero, Marcela , Ahinkorah, Bright , Ahmad, Sajjad , Ahmad, Tauseef , Ahmadi, Keivan , Ahmadi, Sepideh , Ahmadi, Ali , Ahmed, Ali , Ahmed Salih, Yusra , Akande-Sholabi, Wuraola , Akram, Tayyaba , Al Hamad, Hanadi , Al-Aly, Ziyad , Rahman, Muhammad Aziz
- Date: 2022
- Type: Text , Journal article
- Relation: The Lancet Diabetes and Endocrinology Vol. 10, no. 3 (2022), p. 177-192
- Full Text:
- Reviewed:
- Description: Background: Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods: We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990–2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. Findings: In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73·7% (68·3 to 77·4) were classified as due to type 1 diabetes. The age-standardised death rate was 0·50 (0·44 to 0·58) per 100 000 population, and 15 900 (97·5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0·13 (0·12 to 0·14) per 100 000 population in the high SDI quintile, 0·60 (0·51 to 0·70) per 100 000 population in the low-middle SDI quintile, and 0·71 (0·60 to 0·86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r2=0·62). From 1990 to 2019, age-standardised death rates decreased globally by 17·0%. **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Muhammad Aziz Rahman" is provided in this record**
- Description: Background: Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods: We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990–2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. Findings: In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73·7% (68·3 to 77·4) were classified as due to type 1 diabetes. The age-standardised death rate was 0·50 (0·44 to 0·58) per 100 000 population, and 15 900 (97·5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0·13 (0·12 to 0·14) per 100 000 population in the high SDI quintile, 0·60 (0·51 to 0·70) per 100 000 population in the low-middle SDI quintile, and 0·71 (0·60 to 0·86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r2=0·62). From 1990 to 2019, age-standardised death rates decreased globally by 17·0% (
Global burden of chronic respiratory diseases and risk factors, 1990–2019: an update from the Global Burden of Disease Study 2019
- Momtazmanesh, Sara, Moghaddam, Sahar, Ghamari, Seyyed-Hadi, Rad, Elaheh, Rezaei, Negar, Shobeiri, Parnian, Aali, Amirali, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abdelmasseh, Michael, Abdoun, Meriem, Abdulah, Deldar, Md Abdullah, Abu, Abedi, Aidin, Abolhassani, Hassan, Abrehdari-Tafreshi, Zahra, Achappa, Basavaprabhu, Adane, Denberu, Adane, Tigist, Addo, Isaac, Adnan, Mohammad, Adnani, Qorinah, Ahmad, Sajjad, Ahmadi, Ali, Ahmadi, Keivan, Ahmed, Ali, Ahmed, Ayman, Rashid, Tarik, Al Hamad, Hanadi, Alahdab, Fares, Ur Rahman, Mohammad Hifz, oh, oi, oj, ok;, Rahman, Mosiur, Rahman, Muhammad Aziz
- Authors: Momtazmanesh, Sara , Moghaddam, Sahar , Ghamari, Seyyed-Hadi , Rad, Elaheh , Rezaei, Negar , Shobeiri, Parnian , Aali, Amirali , Abbasi-Kangevari, Mohsen , Abbasi-Kangevari, Zeinab , Abdelmasseh, Michael , Abdoun, Meriem , Abdulah, Deldar , Md Abdullah, Abu , Abedi, Aidin , Abolhassani, Hassan , Abrehdari-Tafreshi, Zahra , Achappa, Basavaprabhu , Adane, Denberu , Adane, Tigist , Addo, Isaac , Adnan, Mohammad , Adnani, Qorinah , Ahmad, Sajjad , Ahmadi, Ali , Ahmadi, Keivan , Ahmed, Ali , Ahmed, Ayman , Rashid, Tarik , Al Hamad, Hanadi , Alahdab, Fares , Ur Rahman, Mohammad Hifz , oh, oi, oj, ok; , Rahman, Mosiur , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: eClinicalMedicine Vol. 59, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Background: Updated data on chronic respiratory diseases (CRDs) are vital in their prevention, control, and treatment in the path to achieving the third UN Sustainable Development Goals (SDGs), a one-third reduction in premature mortality from non-communicable diseases by 2030. We provided global, regional, and national estimates of the burden of CRDs and their attributable risks from 1990 to 2019. Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we estimated mortality, years lived with disability, years of life lost, disability-adjusted life years (DALYs), prevalence, and incidence of CRDs, i.e. chronic obstructive pulmonary disease (COPD), asthma, pneumoconiosis, interstitial lung disease and pulmonary sarcoidosis, and other CRDs, from 1990 to 2019 by sex, age, region, and Socio-demographic Index (SDI) in 204 countries and territories. Deaths and DALYs from CRDs attributable to each risk factor were estimated according to relative risks, risk exposure, and the theoretical minimum risk exposure level input. Findings: In 2019, CRDs were the third leading cause of death responsible for 4.0 million deaths (95% uncertainty interval 3.6–4.3) with a prevalence of 454.6 million cases (417.4–499.1) globally. While the total deaths and prevalence of CRDs have increased by 28.5% and 39.8%, the age-standardised rates have dropped by 41.7% and 16.9% from 1990 to 2019, respectively. COPD, with 212.3 million (200.4–225.1) prevalent cases, was the primary cause of deaths from CRDs, accounting for 3.3 million (2.9–3.6) deaths. With 262.4 million (224.1–309.5) prevalent cases, asthma had the highest prevalence among CRDs. The age-standardised rates of all burden measures of COPD, asthma, and pneumoconiosis have reduced globally from 1990 to 2019. Nevertheless, the age-standardised rates of incidence and prevalence of interstitial lung disease and pulmonary sarcoidosis have increased throughout this period. Low- and low-middle SDI countries had the highest age-standardised death and DALYs rates while the high SDI quintile had the highest prevalence rate of CRDs. The highest deaths and DALYs from CRDs were attributed to smoking globally, followed by air pollution and occupational risks. Non-optimal temperature and high body-mass index were additional risk factors for COPD and asthma, respectively. Interpretation: Albeit the age-standardised prevalence, death, and DALYs rates of CRDs have decreased, they still cause a substantial burden and deaths worldwide. The high death and DALYs rates in low and low-middle SDI countries highlights the urgent need for improved preventive, diagnostic, and therapeutic measures. Global strategies for tobacco control, enhancing air quality, reducing occupational hazards, and fostering clean cooking fuels are crucial steps in reducing the burden of CRDs, especially in low- and lower-middle income countries. Funding: Bill & Melinda Gates Foundation. © 2023 The Authors
- Authors: Momtazmanesh, Sara , Moghaddam, Sahar , Ghamari, Seyyed-Hadi , Rad, Elaheh , Rezaei, Negar , Shobeiri, Parnian , Aali, Amirali , Abbasi-Kangevari, Mohsen , Abbasi-Kangevari, Zeinab , Abdelmasseh, Michael , Abdoun, Meriem , Abdulah, Deldar , Md Abdullah, Abu , Abedi, Aidin , Abolhassani, Hassan , Abrehdari-Tafreshi, Zahra , Achappa, Basavaprabhu , Adane, Denberu , Adane, Tigist , Addo, Isaac , Adnan, Mohammad , Adnani, Qorinah , Ahmad, Sajjad , Ahmadi, Ali , Ahmadi, Keivan , Ahmed, Ali , Ahmed, Ayman , Rashid, Tarik , Al Hamad, Hanadi , Alahdab, Fares , Ur Rahman, Mohammad Hifz , oh, oi, oj, ok; , Rahman, Mosiur , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: eClinicalMedicine Vol. 59, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Background: Updated data on chronic respiratory diseases (CRDs) are vital in their prevention, control, and treatment in the path to achieving the third UN Sustainable Development Goals (SDGs), a one-third reduction in premature mortality from non-communicable diseases by 2030. We provided global, regional, and national estimates of the burden of CRDs and their attributable risks from 1990 to 2019. Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we estimated mortality, years lived with disability, years of life lost, disability-adjusted life years (DALYs), prevalence, and incidence of CRDs, i.e. chronic obstructive pulmonary disease (COPD), asthma, pneumoconiosis, interstitial lung disease and pulmonary sarcoidosis, and other CRDs, from 1990 to 2019 by sex, age, region, and Socio-demographic Index (SDI) in 204 countries and territories. Deaths and DALYs from CRDs attributable to each risk factor were estimated according to relative risks, risk exposure, and the theoretical minimum risk exposure level input. Findings: In 2019, CRDs were the third leading cause of death responsible for 4.0 million deaths (95% uncertainty interval 3.6–4.3) with a prevalence of 454.6 million cases (417.4–499.1) globally. While the total deaths and prevalence of CRDs have increased by 28.5% and 39.8%, the age-standardised rates have dropped by 41.7% and 16.9% from 1990 to 2019, respectively. COPD, with 212.3 million (200.4–225.1) prevalent cases, was the primary cause of deaths from CRDs, accounting for 3.3 million (2.9–3.6) deaths. With 262.4 million (224.1–309.5) prevalent cases, asthma had the highest prevalence among CRDs. The age-standardised rates of all burden measures of COPD, asthma, and pneumoconiosis have reduced globally from 1990 to 2019. Nevertheless, the age-standardised rates of incidence and prevalence of interstitial lung disease and pulmonary sarcoidosis have increased throughout this period. Low- and low-middle SDI countries had the highest age-standardised death and DALYs rates while the high SDI quintile had the highest prevalence rate of CRDs. The highest deaths and DALYs from CRDs were attributed to smoking globally, followed by air pollution and occupational risks. Non-optimal temperature and high body-mass index were additional risk factors for COPD and asthma, respectively. Interpretation: Albeit the age-standardised prevalence, death, and DALYs rates of CRDs have decreased, they still cause a substantial burden and deaths worldwide. The high death and DALYs rates in low and low-middle SDI countries highlights the urgent need for improved preventive, diagnostic, and therapeutic measures. Global strategies for tobacco control, enhancing air quality, reducing occupational hazards, and fostering clean cooking fuels are crucial steps in reducing the burden of CRDs, especially in low- and lower-middle income countries. Funding: Bill & Melinda Gates Foundation. © 2023 The Authors
Mapping geographical inequalities in oral rehydration therapy coverage in low-income and middle-income countries, 2000-17
- Wiens, Kirsten, Lindstedt, Paulina, Blacker, Brigette, Johnson, Kimberly, Baumann, Mathew, Schaeffer, Lauren, Abbastabar, Hedayat, Abd-Allah, Foad, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abegaz, Kedir, Abejie, Ayenew, Abreu, Lucas, Abrigo, Michael, Abualhasan, Ahmed, Accrombessi, Manfred, Acharya, Dilaram, Adabi, Maryam, Adamu, Abdu, Adebayo, Oladimeji, Adedoyin, Rufus, Adekanmbi, Victor, Adetokunboh, Olatunji, Adhena, Beyene, Afarideh, Mohsen, Ahmad, Sohail, Ahmadi, Keivan, Ahmed, Anwar, Ahmed, Muktar, Rahman, Muhammad Aziz
- Authors: Wiens, Kirsten , Lindstedt, Paulina , Blacker, Brigette , Johnson, Kimberly , Baumann, Mathew , Schaeffer, Lauren , Abbastabar, Hedayat , Abd-Allah, Foad , Abdelalim, Ahmed , Abdollahpour, Ibrahim , Abegaz, Kedir , Abejie, Ayenew , Abreu, Lucas , Abrigo, Michael , Abualhasan, Ahmed , Accrombessi, Manfred , Acharya, Dilaram , Adabi, Maryam , Adamu, Abdu , Adebayo, Oladimeji , Adedoyin, Rufus , Adekanmbi, Victor , Adetokunboh, Olatunji , Adhena, Beyene , Afarideh, Mohsen , Ahmad, Sohail , Ahmadi, Keivan , Ahmed, Anwar , Ahmed, Muktar , Rahman, Muhammad Aziz
- Date: 2020
- Type: Text , Journal article
- Relation: The Lancet Global Health Vol. 8, no. 8 (2020), p. e1038-e1060
- Full Text:
- Reviewed:
- Description: Background: Oral rehydration solution (ORS) is a form of oral rehydration therapy (ORT) for diarrhoea that has the potential to drastically reduce child mortality; yet, according to UNICEF estimates, less than half of children younger than 5 years with diarrhoea in low-income and middle-income countries (LMICs) received ORS in 2016. A variety of recommended home fluids (RHF) exist as alternative forms of ORT; however, it is unclear whether RHF prevent child mortality. Previous studies have shown considerable variation between countries in ORS and RHF use, but subnational variation is unknown. This study aims to produce high-resolution geospatial estimates of relative and absolute coverage of ORS, RHF, and ORT (use of either ORS or RHF) in LMICs. Methods: We used a Bayesian geostatistical model including 15 spatial covariates and data from 385 household surveys across 94 LMICs to estimate annual proportions of children younger than 5 years of age with diarrhoea who received ORS or RHF (or both) on continuous continent-wide surfaces in 2000–17, and aggregated results to policy-relevant administrative units. Additionally, we analysed geographical inequality in coverage across administrative units and estimated the number of diarrhoeal deaths averted by increased coverage over the study period. Uncertainty in the mean coverage estimates was calculated by taking 250 draws from the posterior joint distribution of the model and creating uncertainty intervals (UIs) with the 2·5th and 97·5th percentiles of those 250 draws. Findings: While ORS use among children with diarrhoea increased in some countries from 2000 to 2017, coverage remained below 50% in the majority (62·6%; 12 417 of 19 823) of second administrative-level units and an estimated 6 519 000 children (95% UI 5 254 000–7 733 000) with diarrhoea were not treated with any form of ORT in 2017. Increases in ORS use corresponded with declines in RHF in many locations, resulting in relatively constant overall ORT coverage from 2000 to 2017. Although ORS was uniformly distributed subnationally in some countries, within-country geographical inequalities persisted in others; 11 countries had at least a 50% difference in one of their units compared with the country mean. Increases in ORS use over time were correlated with declines in RHF use and in diarrhoeal mortality in many locations, and an estimated 52 230 diarrhoeal deaths (36 910–68 860) were averted by scaling up of ORS coverage between 2000 and 2017. Finally, we identified key subnational areas in Colombia, Nigeria, and Sudan as examples of where diarrhoeal mortality remains higher than average, while ORS coverage remains lower than average. Interpretation: To our knowledge, this study is the first to produce and map subnational estimates of ORS, RHF, and ORT coverage and attributable child diarrhoeal deaths across LMICs from 2000 to 2017, allowing for tracking progress over time. Our novel results, combined with detailed subnational estimates of diarrhoeal morbidity and mortality, can support subnational needs assessments aimed at furthering policy makers' understanding of within-country disparities. Over 50 years after the discovery that led to this simple, cheap, and life-saving therapy, large gains in reducing mortality could still be made by reducing geographical inequalities in ORS coverage. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Muhammad Aziz Rahman” is provided in this record**
- Authors: Wiens, Kirsten , Lindstedt, Paulina , Blacker, Brigette , Johnson, Kimberly , Baumann, Mathew , Schaeffer, Lauren , Abbastabar, Hedayat , Abd-Allah, Foad , Abdelalim, Ahmed , Abdollahpour, Ibrahim , Abegaz, Kedir , Abejie, Ayenew , Abreu, Lucas , Abrigo, Michael , Abualhasan, Ahmed , Accrombessi, Manfred , Acharya, Dilaram , Adabi, Maryam , Adamu, Abdu , Adebayo, Oladimeji , Adedoyin, Rufus , Adekanmbi, Victor , Adetokunboh, Olatunji , Adhena, Beyene , Afarideh, Mohsen , Ahmad, Sohail , Ahmadi, Keivan , Ahmed, Anwar , Ahmed, Muktar , Rahman, Muhammad Aziz
- Date: 2020
- Type: Text , Journal article
- Relation: The Lancet Global Health Vol. 8, no. 8 (2020), p. e1038-e1060
- Full Text:
- Reviewed:
- Description: Background: Oral rehydration solution (ORS) is a form of oral rehydration therapy (ORT) for diarrhoea that has the potential to drastically reduce child mortality; yet, according to UNICEF estimates, less than half of children younger than 5 years with diarrhoea in low-income and middle-income countries (LMICs) received ORS in 2016. A variety of recommended home fluids (RHF) exist as alternative forms of ORT; however, it is unclear whether RHF prevent child mortality. Previous studies have shown considerable variation between countries in ORS and RHF use, but subnational variation is unknown. This study aims to produce high-resolution geospatial estimates of relative and absolute coverage of ORS, RHF, and ORT (use of either ORS or RHF) in LMICs. Methods: We used a Bayesian geostatistical model including 15 spatial covariates and data from 385 household surveys across 94 LMICs to estimate annual proportions of children younger than 5 years of age with diarrhoea who received ORS or RHF (or both) on continuous continent-wide surfaces in 2000–17, and aggregated results to policy-relevant administrative units. Additionally, we analysed geographical inequality in coverage across administrative units and estimated the number of diarrhoeal deaths averted by increased coverage over the study period. Uncertainty in the mean coverage estimates was calculated by taking 250 draws from the posterior joint distribution of the model and creating uncertainty intervals (UIs) with the 2·5th and 97·5th percentiles of those 250 draws. Findings: While ORS use among children with diarrhoea increased in some countries from 2000 to 2017, coverage remained below 50% in the majority (62·6%; 12 417 of 19 823) of second administrative-level units and an estimated 6 519 000 children (95% UI 5 254 000–7 733 000) with diarrhoea were not treated with any form of ORT in 2017. Increases in ORS use corresponded with declines in RHF in many locations, resulting in relatively constant overall ORT coverage from 2000 to 2017. Although ORS was uniformly distributed subnationally in some countries, within-country geographical inequalities persisted in others; 11 countries had at least a 50% difference in one of their units compared with the country mean. Increases in ORS use over time were correlated with declines in RHF use and in diarrhoeal mortality in many locations, and an estimated 52 230 diarrhoeal deaths (36 910–68 860) were averted by scaling up of ORS coverage between 2000 and 2017. Finally, we identified key subnational areas in Colombia, Nigeria, and Sudan as examples of where diarrhoeal mortality remains higher than average, while ORS coverage remains lower than average. Interpretation: To our knowledge, this study is the first to produce and map subnational estimates of ORS, RHF, and ORT coverage and attributable child diarrhoeal deaths across LMICs from 2000 to 2017, allowing for tracking progress over time. Our novel results, combined with detailed subnational estimates of diarrhoeal morbidity and mortality, can support subnational needs assessments aimed at furthering policy makers' understanding of within-country disparities. Over 50 years after the discovery that led to this simple, cheap, and life-saving therapy, large gains in reducing mortality could still be made by reducing geographical inequalities in ORS coverage. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Muhammad Aziz Rahman” is provided in this record**
- «
- ‹
- 1
- ›
- »