Kari Moore, Mariana Lazo, Ana Ortigoza, D Alex Quistberg, Brisa Sanchez, Binod Acharya, Tania Alfaro, Maria Fernanda Kroker-Lobos, Mariana Carvalho De Menezes, Olga Lucia Sarmiento, Amanda C de Souza Andrade, Carolina Perez Ferrer, Akram Hernandez Vasquez, Waleska Teixeira Caiaffa, Ana V Diez Roux
{"title":"Data Resource Profile: Harmonized health survey data for 240 cities across 11 countries in Latin America: the SALURBAL project.","authors":"Kari Moore, Mariana Lazo, Ana Ortigoza, D Alex Quistberg, Brisa Sanchez, Binod Acharya, Tania Alfaro, Maria Fernanda Kroker-Lobos, Mariana Carvalho De Menezes, Olga Lucia Sarmiento, Amanda C de Souza Andrade, Carolina Perez Ferrer, Akram Hernandez Vasquez, Waleska Teixeira Caiaffa, Ana V Diez Roux","doi":"10.1093/ije/dyae171","DOIUrl":"https://doi.org/10.1093/ije/dyae171","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"54 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703366/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142948355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Grace Joshy, Karen Bishop, Hang Li, Lauren Moran, Michelle Gourley, Jennifer Welsh, Rosemary Korda, Emily Banks, Tim Adair, Chalapati Rao
Background: Deaths in Australia and other high-income countries increasingly involve multiple conditions. However, key burden of disease measures typically only use the underlying cause of death (UC). We quantified sex and cause-specific years of life lost (YLL) based on UC compared with a method integrating multiple causes of death.
Methods: Causes of death for all deaths in Australia (2015-17), mapped to 136 groups based on International Classification of Diseases 10th revision (ICD-10), were ascribed using (1) the UC only and (2) a multiple cause weighting (WT) strategy. Applying the Global Burden of Disease 2010 life table, YLLUC and YLLWT rates were calculated for each sex and cause of death and compared using relative and absolute measures.
Results: All-cause YLL rates were 113.4/1000 for males and 79.9/1000 for females. Cancers, cardiovascular diseases, external causes, respiratory diseases and nervous system diseases were the five biggest contributors to YLL for each method. For the top 20 causes combined, YLLWT rates were 10% lower for males (YLLWT = 74.93/1000 vs YLLUC = 67.38/1000) and 7% lower for females (YLLWT = 51.34/1000; YLLUC = 47.90/1000); YLLWT rates were lower for ischaemic heart disease and all cancers, but higher for diabetes and dementia, and for chronic obstructive pulmonary disease in males. With multiple cause weighting, renal failure emerged among the top 20 causes of YLL, as did atrial fibrillation and hypertension among females. YLLWT rates for substance abuse, mood disorders, hypertension and schizophrenia were relatively high compared with YLLUC.
Conclusion: The YLLWT metric highlights epidemiologically important conditions that are less often selected as the UC.
{"title":"Quantifying years of life lost in Australia: a multiple cause of death analysis.","authors":"Grace Joshy, Karen Bishop, Hang Li, Lauren Moran, Michelle Gourley, Jennifer Welsh, Rosemary Korda, Emily Banks, Tim Adair, Chalapati Rao","doi":"10.1093/ije/dyae177","DOIUrl":"https://doi.org/10.1093/ije/dyae177","url":null,"abstract":"<p><strong>Background: </strong>Deaths in Australia and other high-income countries increasingly involve multiple conditions. However, key burden of disease measures typically only use the underlying cause of death (UC). We quantified sex and cause-specific years of life lost (YLL) based on UC compared with a method integrating multiple causes of death.</p><p><strong>Methods: </strong>Causes of death for all deaths in Australia (2015-17), mapped to 136 groups based on International Classification of Diseases 10th revision (ICD-10), were ascribed using (1) the UC only and (2) a multiple cause weighting (WT) strategy. Applying the Global Burden of Disease 2010 life table, YLLUC and YLLWT rates were calculated for each sex and cause of death and compared using relative and absolute measures.</p><p><strong>Results: </strong>All-cause YLL rates were 113.4/1000 for males and 79.9/1000 for females. Cancers, cardiovascular diseases, external causes, respiratory diseases and nervous system diseases were the five biggest contributors to YLL for each method. For the top 20 causes combined, YLLWT rates were 10% lower for males (YLLWT = 74.93/1000 vs YLLUC = 67.38/1000) and 7% lower for females (YLLWT = 51.34/1000; YLLUC = 47.90/1000); YLLWT rates were lower for ischaemic heart disease and all cancers, but higher for diabetes and dementia, and for chronic obstructive pulmonary disease in males. With multiple cause weighting, renal failure emerged among the top 20 causes of YLL, as did atrial fibrillation and hypertension among females. YLLWT rates for substance abuse, mood disorders, hypertension and schizophrenia were relatively high compared with YLLUC.</p><p><strong>Conclusion: </strong>The YLLWT metric highlights epidemiologically important conditions that are less often selected as the UC.</p>","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"54 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background The Republic of Korea has reported the highest suicide rate globally since 2018. Previous studies have highlighted disability as a significant risk factor for suicide. However, comprehensive examination on the association between suicide mortality and severities and types of disabilities, and on how these associations vary according to sociodemographic characteristics, health behaviours and comorbidity profiles has never been performed. Methods We performed a retrospective cohort study of a nationally representative sample of 3 591 398 individuals subject to the health check-up provided by the Korean National Health Insurance in 2009, including individuals with (n = 126 508) and without (n = 3 734 890) disabilities, and followed-up until December 2021 Results Overall, the presence of disability was associated with an increased risk of suicide mortality [hazard ratio (HR), 1.38; 95% confidence interval (CI), 1.30–1.47] compared to the absence of disability. This risk was more pronounced in individuals with Grade 1–3 disabilities (HR, 1.68; 95% CI, 1.52–1.85) than those with Grade 4–6 disabilities (HR, 1.28; 95% CI, 1.20–1.47). Among various types of disabilities, individuals with a disability associated with a mental disorder had the highest HR (HR, 4.49; 95% CI, 3.38–5.97), followed by those with visual impairment (HR, 1.47; 95% CI, 1.26–1.73), brain damage (HR, 1.45; 95% CI, 1.18–1.79), hearing impairment (HR, 1.35; 95% CI, 1.15–1.58) and extremity disability (HR, 1.30; 95% CI, 1.21–1.40). Stratified analyses revealed that the suicide risk associated with disabilities was more pronounced in individuals with specific sociodemographic characteristics and health behaviours. Conclusion Our findings highlight the need to prioritize policy efforts to address suicide mortality among people with disabilities, considering the distinct risks associated with disability types and severity.
{"title":"Longitudinal association between disability and suicide mortality in Republic of Korea","authors":"Hwa-Young Lee, Dong Wook Shin, Kyung-Do Han, Ichiro Kawachi","doi":"10.1093/ije/dyae163","DOIUrl":"https://doi.org/10.1093/ije/dyae163","url":null,"abstract":"Background The Republic of Korea has reported the highest suicide rate globally since 2018. Previous studies have highlighted disability as a significant risk factor for suicide. However, comprehensive examination on the association between suicide mortality and severities and types of disabilities, and on how these associations vary according to sociodemographic characteristics, health behaviours and comorbidity profiles has never been performed. Methods We performed a retrospective cohort study of a nationally representative sample of 3 591 398 individuals subject to the health check-up provided by the Korean National Health Insurance in 2009, including individuals with (n = 126 508) and without (n = 3 734 890) disabilities, and followed-up until December 2021 Results Overall, the presence of disability was associated with an increased risk of suicide mortality [hazard ratio (HR), 1.38; 95% confidence interval (CI), 1.30–1.47] compared to the absence of disability. This risk was more pronounced in individuals with Grade 1–3 disabilities (HR, 1.68; 95% CI, 1.52–1.85) than those with Grade 4–6 disabilities (HR, 1.28; 95% CI, 1.20–1.47). Among various types of disabilities, individuals with a disability associated with a mental disorder had the highest HR (HR, 4.49; 95% CI, 3.38–5.97), followed by those with visual impairment (HR, 1.47; 95% CI, 1.26–1.73), brain damage (HR, 1.45; 95% CI, 1.18–1.79), hearing impairment (HR, 1.35; 95% CI, 1.15–1.58) and extremity disability (HR, 1.30; 95% CI, 1.21–1.40). Stratified analyses revealed that the suicide risk associated with disabilities was more pronounced in individuals with specific sociodemographic characteristics and health behaviours. Conclusion Our findings highlight the need to prioritize policy efforts to address suicide mortality among people with disabilities, considering the distinct risks associated with disability types and severity.","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"28 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142805446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anna A Sordo, Anna A Do, Melissa J Irwin, David J Muscatello
Background Estimates of excess deaths provide critical intelligence on the impact of population health threats including seasonal respiratory infections, pandemics and environmental hazards. Timely estimates of excess deaths can inform the response to COVID-19. However, access to timely mortality data is challenging due to the time interval between the death occurring and the date the death is registered and available for analysis (‘registration interval’). Development Using data from the New South Wales, Australia, Births Deaths and Marriages Registry, we developed a Poisson regression model that estimated near-complete weekly counts, for a given week of death, from partially-complete death registration counts. A 10-weeks lag was considered, and a 2-year baseline of historical registration intervals was used to correct lag weeks. Application Validation of estimated counts found that the root-mean-square error (as a percentage of mean observed near-complete registrations) was less than 7% for lag week 3, and <5% for lag weeks 4–9. We incorporated this method utilizing an existing rapid weekly mortality surveillance system. Counts corrected for registration interval replaced observed values for the most recent weeks. Excess death estimates, based on corrected counts, were within 1.2% of near-complete counts available 9 weeks from the end of the analysis period. Conclusions This study demonstrates a method for estimating recent death counts to correct for registration intervals. Estimates obtained at a 3-week lag were acceptable, while those at greater than 3 weeks were optimal.
{"title":"Development of a registration interval correction model for enhancing excess all-cause mortality surveillance during the COVID-19 pandemic","authors":"Anna A Sordo, Anna A Do, Melissa J Irwin, David J Muscatello","doi":"10.1093/ije/dyae145","DOIUrl":"https://doi.org/10.1093/ije/dyae145","url":null,"abstract":"Background Estimates of excess deaths provide critical intelligence on the impact of population health threats including seasonal respiratory infections, pandemics and environmental hazards. Timely estimates of excess deaths can inform the response to COVID-19. However, access to timely mortality data is challenging due to the time interval between the death occurring and the date the death is registered and available for analysis (‘registration interval’). Development Using data from the New South Wales, Australia, Births Deaths and Marriages Registry, we developed a Poisson regression model that estimated near-complete weekly counts, for a given week of death, from partially-complete death registration counts. A 10-weeks lag was considered, and a 2-year baseline of historical registration intervals was used to correct lag weeks. Application Validation of estimated counts found that the root-mean-square error (as a percentage of mean observed near-complete registrations) was less than 7% for lag week 3, and &lt;5% for lag weeks 4–9. We incorporated this method utilizing an existing rapid weekly mortality surveillance system. Counts corrected for registration interval replaced observed values for the most recent weeks. Excess death estimates, based on corrected counts, were within 1.2% of near-complete counts available 9 weeks from the end of the analysis period. Conclusions This study demonstrates a method for estimating recent death counts to correct for registration intervals. Estimates obtained at a 3-week lag were acceptable, while those at greater than 3 weeks were optimal.","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"62 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142596756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nora A Escher, Rodrigo M Carrillo-Larco, Jennie C Parnham, Katherine Curi-Quinto, Suparna Ghosh-Jerath, Christopher Millett, Paraskevi Seferidi
Background: Examining trajectories of undernutrition and overnutrition separately limits understanding of the double burden of malnutrition. We investigated transitions between normal, stunting, overweight and concurrent stunting and overweight (CSO) and associations with sociodemographic factors in children and adolescents.
Methods: We used data from the Young Lives cohort in India, Peru and Vietnam, which follow children 1-15 (N = 5413) and 8-22 years (N = 2225) over five rounds between 2002 and 2016. We estimated transitions between nutritional states using a Markov chain model and estimated sociodemographic associations employing a logit parametrization.
Results: Transitions into stunting peaked in ages 1-5 years (India: 22.9%, Peru: 17.6%, Vietnam: 14.8%), while stunting reversal was highest during adolescence across all countries. Transitions into overweight peaked in ages 19-22, while overweight reversal increased in ages 1-5 and 12-15 years. Transitions away from stunting to overweight were rare; more commonly, stunted individuals developed overweight while remaining stunted, leading to a CSO state. In Peru, 20.2% of 19-year-olds who were stunted reached CSO by age 22, with 4% shifting from stunted to overweight. Reversion to a normal state is least likely for those in a CSO state. Household wealth gradually reduced the likelihood of transitioning into stunting [odds ratios (ORs) for wealthiest quartile in Peru: 0.29, 95% confidence interval (CI) 0.20-0.41; India: 0.43, 95% CI 0.32-0.57; Vietnam: 0.36, 95% CI 0.26-0.50), with stunting reversal only being more likely in the two wealthiest quartiles across all countries (ORs for wealthiest quartile in Peru: 2.39, 95% CI 1.57-3.65; India: 1.28, 95% CI 1.05-1.54; Vietnam: 1.89, 95% CI 1.23-2.91). In Vietnam, only the richest quartile was at higher risk of transitioning into overweight (OR 1.87, 95% CI 1.28-2.72), while in Peru and India, the risk gradually rose across all wealth quartiles (ORs for wealthiest quartile in Peru: 2.84, 95% CI 2.14-3.77; India: 2.99, 95% CI 1.61-5.54).
Conclusions: Childhood and adolescence represent critical periods for prevention and reversal of stunting and overweight, thereby averting the development of CSO later in life. Context-specific interventions are crucial for preventing disparate transitions towards the double burden of malnutrition across socioeconomic groups.
背景：分别研究营养不良和营养过剩的轨迹会限制人们对营养不良双重负担的理解。我们调查了儿童和青少年在正常、发育迟缓、超重和同时发育迟缓和超重（CSO）之间的转变，以及与社会人口因素的关系：我们使用了来自印度、秘鲁和越南 "年轻生命 "队列的数据，这些数据对 1-15 岁（5413 人）和 8-22 岁（2225 人）的儿童进行了 2002 至 2016 年间的五轮跟踪调查。我们使用马尔科夫链模型估计了营养状况之间的转变，并使用对数参数估计了社会人口关联：1-5岁是发育迟缓转变的高峰期（印度：22.9%；秘鲁：17.6%；越南：14.8%），而发育迟缓的逆转在所有国家的青春期都是最高的。过渡到超重在 19-22 岁达到高峰，而超重逆转在 1-5 岁和 12-15 岁增加。从发育迟缓转为超重的情况很少见；更常见的情况是，发育迟缓的人在保持发育迟缓的同时出现超重，导致CSO状态。在秘鲁，发育迟缓的 19 岁儿童中有 20.2%在 22 岁时达到 CSO，其中 4%从发育迟缓转为超重。处于 CSO 状态的人最不可能恢复到正常状态。家庭财富逐渐降低了转为发育迟缓的可能性[秘鲁最富有四分位数的几率比（ORs）：0.29，95%置信区间（CI）0.20-0.41；印度：0.43，95%置信区间（CI）0.41]：0.43，95% 置信区间 (CI)：0.32-0.57；越南：0.36，95% 置信区间 (CI)：0.26-0.50），在所有国家中，只有最富裕的两个四分位数更有可能发生发育迟缓逆转（秘鲁最富裕四分位数的 ORs：2.39，95% 置信区间 (CI)：1.57-3.65；印度最富裕四分位数的 ORs：1.28，95% 置信区间 (CI)：0.29-0.41）：印度：1.28，95% CI 1.05-1.54；越南：1.89，95% CI 1.23-2.91）。在越南，只有最富裕的四分位数的人过渡到超重的风险较高（OR 1.87，95% CI 1.28-2.72），而在秘鲁和印度，所有富裕的四分位数的人过渡到超重的风险逐渐上升（秘鲁最富裕的四分位数的OR：2.84，95% CI 2.14-3.77；印度：2.99，95% CI 1.61-5.54）：儿童和青少年时期是预防和扭转发育迟缓和超重的关键时期，可避免日后出现 CSO。针对具体情况的干预措施对于防止不同社会经济群体向营养不良双重负担过渡至关重要。
{"title":"Longitudinal transitions of the double burden of overweight and stunting from childhood to early adulthood in India, Peru, and Vietnam.","authors":"Nora A Escher, Rodrigo M Carrillo-Larco, Jennie C Parnham, Katherine Curi-Quinto, Suparna Ghosh-Jerath, Christopher Millett, Paraskevi Seferidi","doi":"10.1093/ije/dyae151","DOIUrl":"10.1093/ije/dyae151","url":null,"abstract":"<p><strong>Background: </strong>Examining trajectories of undernutrition and overnutrition separately limits understanding of the double burden of malnutrition. We investigated transitions between normal, stunting, overweight and concurrent stunting and overweight (CSO) and associations with sociodemographic factors in children and adolescents.</p><p><strong>Methods: </strong>We used data from the Young Lives cohort in India, Peru and Vietnam, which follow children 1-15 (N = 5413) and 8-22 years (N = 2225) over five rounds between 2002 and 2016. We estimated transitions between nutritional states using a Markov chain model and estimated sociodemographic associations employing a logit parametrization.</p><p><strong>Results: </strong>Transitions into stunting peaked in ages 1-5 years (India: 22.9%, Peru: 17.6%, Vietnam: 14.8%), while stunting reversal was highest during adolescence across all countries. Transitions into overweight peaked in ages 19-22, while overweight reversal increased in ages 1-5 and 12-15 years. Transitions away from stunting to overweight were rare; more commonly, stunted individuals developed overweight while remaining stunted, leading to a CSO state. In Peru, 20.2% of 19-year-olds who were stunted reached CSO by age 22, with 4% shifting from stunted to overweight. Reversion to a normal state is least likely for those in a CSO state. Household wealth gradually reduced the likelihood of transitioning into stunting [odds ratios (ORs) for wealthiest quartile in Peru: 0.29, 95% confidence interval (CI) 0.20-0.41; India: 0.43, 95% CI 0.32-0.57; Vietnam: 0.36, 95% CI 0.26-0.50), with stunting reversal only being more likely in the two wealthiest quartiles across all countries (ORs for wealthiest quartile in Peru: 2.39, 95% CI 1.57-3.65; India: 1.28, 95% CI 1.05-1.54; Vietnam: 1.89, 95% CI 1.23-2.91). In Vietnam, only the richest quartile was at higher risk of transitioning into overweight (OR 1.87, 95% CI 1.28-2.72), while in Peru and India, the risk gradually rose across all wealth quartiles (ORs for wealthiest quartile in Peru: 2.84, 95% CI 2.14-3.77; India: 2.99, 95% CI 1.61-5.54).</p><p><strong>Conclusions: </strong>Childhood and adolescence represent critical periods for prevention and reversal of stunting and overweight, thereby averting the development of CSO later in life. Context-specific interventions are crucial for preventing disparate transitions towards the double burden of malnutrition across socioeconomic groups.</p>","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"53 6","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11565240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142638936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Response: Rheumatoid arthritis and cancer risk in the Million Women Study.","authors":"TienYu Owen Yang, Sarah Floud, Gillian K Reeves","doi":"10.1093/ije/dyae144","DOIUrl":"10.1093/ije/dyae144","url":null,"abstract":"","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"53 6","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11534085/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142575834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUNDPrevious studies with large data have been widely reported that exposure to fine particulate matter (PM2.5) is associated with all-cause mortality; however, most of these studies adopted ecological time-series designs or have included limited study areas or individuals residing in well-monitored urban areas. However, nationwide cohort studies including cause-specific mortalities with different age groups were sparse. Therefore, this study examined the association between PM2.5 and cause-specific mortality in South Korea using the nationwide cohort.METHODSA longitudinal cohort with 187 917 National Health Insurance Service-National Sample Cohort participants aged 50-79 years in enrolment between 2002 and 2019 was used. Annual average PM2.5 was collected from a machine learning-based ensemble model (a test R2 = 0.87) as an exposure. We performed a time-varying Cox regression model to examine the association between long-term PM2.5 exposure and mortality. To reduce the potential estimation bias, we adopted generalized propensity score weighting method.RESULTSThe association with long-term PM2.5 (2-year moving average) was prominent in mortalities related to diabetes mellitus [hazard ratio (HR): 1.03 (95% CI: 1.01, 1.06)], circulatory diseases [HR: 1.02 (95% CI: 1.00, 1.03)] and cancer [HR: 1.01 (95% CI: 1.00, 1.02)]. Meanwhile, circulatory-related mortalities were associated with a longer PM2.5 exposure period (1 or 2-year lags), whereas respiratory-related mortalities were associated with current-year PM2.5 exposure. In addition, the association with PM2.5 was more evident in people aged 50-64 years than in people aged 65-79 years, especially in heart failure-related deaths.CONCLUSIONSThis study identified the hypothesis that long-term exposure to PM2.5 is associated with mortality, and the association might be different by causes of death. Our result highlights a novel vulnerable population: the middle-aged population with risk factors related to heart failure.
{"title":"Long-term exposure to PM2.5 and mortality: a national health insurance cohort study.","authors":"Jeongmin Moon,Ejin Kim,Hyemin Jang,Insung Song,Dohoon Kwon,Cinoo Kang,Jieun Oh,Jinah Park,Ayoung Kim,Moonjung Choi,Yaerin Cha,Ho Kim,Whanhee Lee","doi":"10.1093/ije/dyae140","DOIUrl":"https://doi.org/10.1093/ije/dyae140","url":null,"abstract":"BACKGROUNDPrevious studies with large data have been widely reported that exposure to fine particulate matter (PM2.5) is associated with all-cause mortality; however, most of these studies adopted ecological time-series designs or have included limited study areas or individuals residing in well-monitored urban areas. However, nationwide cohort studies including cause-specific mortalities with different age groups were sparse. Therefore, this study examined the association between PM2.5 and cause-specific mortality in South Korea using the nationwide cohort.METHODSA longitudinal cohort with 187 917 National Health Insurance Service-National Sample Cohort participants aged 50-79 years in enrolment between 2002 and 2019 was used. Annual average PM2.5 was collected from a machine learning-based ensemble model (a test R2 = 0.87) as an exposure. We performed a time-varying Cox regression model to examine the association between long-term PM2.5 exposure and mortality. To reduce the potential estimation bias, we adopted generalized propensity score weighting method.RESULTSThe association with long-term PM2.5 (2-year moving average) was prominent in mortalities related to diabetes mellitus [hazard ratio (HR): 1.03 (95% CI: 1.01, 1.06)], circulatory diseases [HR: 1.02 (95% CI: 1.00, 1.03)] and cancer [HR: 1.01 (95% CI: 1.00, 1.02)]. Meanwhile, circulatory-related mortalities were associated with a longer PM2.5 exposure period (1 or 2-year lags), whereas respiratory-related mortalities were associated with current-year PM2.5 exposure. In addition, the association with PM2.5 was more evident in people aged 50-64 years than in people aged 65-79 years, especially in heart failure-related deaths.CONCLUSIONSThis study identified the hypothesis that long-term exposure to PM2.5 is associated with mortality, and the association might be different by causes of death. Our result highlights a novel vulnerable population: the middle-aged population with risk factors related to heart failure.","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"19 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142448066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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