Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c
- Zhou, Bin, Sheffer, Kate, Bennett, James, Gregg, Edward, Danaei, Goodarz, Singleton, Rosie, Shaw, Jonathan, Mishra, Anu, Lhoste, Victor, Carrillo-Larco, Rodrigo, Kengne, Andre, Phelps, Nowell, Heap, Rachel, Rayner, Archie, Stevens, Gretchen, Paciorek, Chris, Riley, Leanne, Cowan, Melanie, Savin, Stefan, Vander Hoorn, Stephen, Lu, Yuan, Pavkov, Meda, Imperatore, Giuseppina, Aguilar-Salinas, Carlos, Ahmad, Noor, Anjana, Ranjit, Davletov, Kairat, Farzadfar, Farshad, González-Villalpando, Clicerio, Charchar, Fadi
- Authors: Zhou, Bin , Sheffer, Kate , Bennett, James , Gregg, Edward , Danaei, Goodarz , Singleton, Rosie , Shaw, Jonathan , Mishra, Anu , Lhoste, Victor , Carrillo-Larco, Rodrigo , Kengne, Andre , Phelps, Nowell , Heap, Rachel , Rayner, Archie , Stevens, Gretchen , Paciorek, Chris , Riley, Leanne , Cowan, Melanie , Savin, Stefan , Vander Hoorn, Stephen , Lu, Yuan , Pavkov, Meda , Imperatore, Giuseppina , Aguilar-Salinas, Carlos , Ahmad, Noor , Anjana, Ranjit , Davletov, Kairat , Farzadfar, Farshad , González-Villalpando, Clicerio , Charchar, Fadi
- Date: 2023
- Type: Text , Journal article
- Relation: Nature Medicine Vol. 29, no. 11 (2023), p. 2885-2901
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- Description: Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29–39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance. © 2023, The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Fadi Charchar" is provided in this record**
- Authors: Zhou, Bin , Sheffer, Kate , Bennett, James , Gregg, Edward , Danaei, Goodarz , Singleton, Rosie , Shaw, Jonathan , Mishra, Anu , Lhoste, Victor , Carrillo-Larco, Rodrigo , Kengne, Andre , Phelps, Nowell , Heap, Rachel , Rayner, Archie , Stevens, Gretchen , Paciorek, Chris , Riley, Leanne , Cowan, Melanie , Savin, Stefan , Vander Hoorn, Stephen , Lu, Yuan , Pavkov, Meda , Imperatore, Giuseppina , Aguilar-Salinas, Carlos , Ahmad, Noor , Anjana, Ranjit , Davletov, Kairat , Farzadfar, Farshad , González-Villalpando, Clicerio , Charchar, Fadi
- Date: 2023
- Type: Text , Journal article
- Relation: Nature Medicine Vol. 29, no. 11 (2023), p. 2885-2901
- Full Text:
- Reviewed:
- Description: Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29–39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance. © 2023, The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Fadi Charchar" 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
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- 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.
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