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% (
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.
Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019
- Reitsma, Marissa, Kendrick, Parkes, Ababneh, Emad, Abbafati, Cristiana, Rahman, Muhammad Aziz
- Authors: Reitsma, Marissa , Kendrick, Parkes , Ababneh, Emad , Abbafati, Cristiana , Rahman, Muhammad Aziz
- Date: 2021
- Type: Text , Journal article
- Relation: The Lancet Vol. 397, no. 10292 (2021), p. 2337-2360
- Full Text:
- Reviewed:
- Description: Background: Ending the global tobacco epidemic is a defining challenge in global health. Timely and comprehensive estimates of the prevalence of smoking tobacco use and attributable disease burden are needed to guide tobacco control efforts nationally and globally. Methods: We estimated the prevalence of smoking tobacco use and attributable disease burden for 204 countries and territories, by age and sex, from 1990 to 2019 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We modelled multiple smoking-related indicators from 3625 nationally representative surveys. We completed systematic reviews and did Bayesian meta-regressions for 36 causally linked health outcomes to estimate non-linear dose-response risk curves for current and former smokers. We used a direct estimation approach to estimate attributable burden, providing more comprehensive estimates of the health effects of smoking than previously available. Findings: Globally in 2019, 1·14 billion (95% uncertainty interval 1·13–1·16) individuals were current smokers, who consumed 7·41 trillion (7·11–7·74) cigarette-equivalents of tobacco in 2019. Although prevalence of smoking had decreased significantly since 1990 among both males (27·5% [26·5–28·5] reduction) and females (37·7% [35·4–39·9] reduction) aged 15 years and older, population growth has led to a significant increase in the total number of smokers from 0·99 billion (0·98–1·00) in 1990. Globally in 2019, smoking tobacco use accounted for 7·69 million (7·16–8·20) deaths and 200 million (185–214) disability-adjusted life-years, and was the leading risk factor for death among males (20·2% [19·3–21·1] of male deaths). 6·68 million [86·9%] of 7·69 million deaths attributable to smoking tobacco use were among current smokers. Interpretation: In the absence of intervention, the annual toll of 7·69 million deaths and 200 million disability-adjusted life-years attributable to smoking will increase over the coming decades. Substantial progress in reducing the prevalence of smoking tobacco use has been observed in countries from all regions and at all stages of development, but a large implementation gap remains for tobacco control. Countries have a clear and urgent opportunity to pass strong, evidence-based policies to accelerate reductions in the prevalence of smoking and reap massive health benefits for their citizens. Funding: Bloomberg Philanthropies and the Bill & Melinda Gates Foundation. © 2021 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 5 including Federation University Australia affiliate “Muhammad Aziz Rahman" is provided in this record**
- Authors: Reitsma, Marissa , Kendrick, Parkes , Ababneh, Emad , Abbafati, Cristiana , Rahman, Muhammad Aziz
- Date: 2021
- Type: Text , Journal article
- Relation: The Lancet Vol. 397, no. 10292 (2021), p. 2337-2360
- Full Text:
- Reviewed:
- Description: Background: Ending the global tobacco epidemic is a defining challenge in global health. Timely and comprehensive estimates of the prevalence of smoking tobacco use and attributable disease burden are needed to guide tobacco control efforts nationally and globally. Methods: We estimated the prevalence of smoking tobacco use and attributable disease burden for 204 countries and territories, by age and sex, from 1990 to 2019 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We modelled multiple smoking-related indicators from 3625 nationally representative surveys. We completed systematic reviews and did Bayesian meta-regressions for 36 causally linked health outcomes to estimate non-linear dose-response risk curves for current and former smokers. We used a direct estimation approach to estimate attributable burden, providing more comprehensive estimates of the health effects of smoking than previously available. Findings: Globally in 2019, 1·14 billion (95% uncertainty interval 1·13–1·16) individuals were current smokers, who consumed 7·41 trillion (7·11–7·74) cigarette-equivalents of tobacco in 2019. Although prevalence of smoking had decreased significantly since 1990 among both males (27·5% [26·5–28·5] reduction) and females (37·7% [35·4–39·9] reduction) aged 15 years and older, population growth has led to a significant increase in the total number of smokers from 0·99 billion (0·98–1·00) in 1990. Globally in 2019, smoking tobacco use accounted for 7·69 million (7·16–8·20) deaths and 200 million (185–214) disability-adjusted life-years, and was the leading risk factor for death among males (20·2% [19·3–21·1] of male deaths). 6·68 million [86·9%] of 7·69 million deaths attributable to smoking tobacco use were among current smokers. Interpretation: In the absence of intervention, the annual toll of 7·69 million deaths and 200 million disability-adjusted life-years attributable to smoking will increase over the coming decades. Substantial progress in reducing the prevalence of smoking tobacco use has been observed in countries from all regions and at all stages of development, but a large implementation gap remains for tobacco control. Countries have a clear and urgent opportunity to pass strong, evidence-based policies to accelerate reductions in the prevalence of smoking and reap massive health benefits for their citizens. Funding: Bloomberg Philanthropies and the Bill & Melinda Gates Foundation. © 2021 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 5 including Federation University Australia affiliate “Muhammad Aziz Rahman" is provided in this record**
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