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}
Lidiane Toledo, Rodrigo Rodrigues, Flávia Alves, Fillipe Guedes, Jacyra Azevedo Paiva de Araújo, John A Naslund, Maurício L Barreto, Vikram Patel, Daiane Borges Machado
Background: Youth psychiatric hospitalizations have been associated with negative outcomes, including premature death and post-discharge self-harm. Identifying risk factors for youth psychiatric hospitalization is crucial for informing prevention strategies. We aimed to evaluate the risk factors for psychiatric hospitalizations among low-income youth in Brazil.
Methods: This cohort study used interpersonal violence and psychiatric hospitalization data linked to the 100 Million Brazilian Cohort baseline. We considered 9 985 917 youths aged 5-24 years who enrolled at the baseline, between 2011 and 2018. We estimated the incidence rate (IR) with 95% confidence interval (CI) for psychiatric hospitalization by calculating the number of hospitalizations per person-year in 100 000 individuals at risk. The multilevel, multivariate Cox proportional hazards regression estimated the hazard risks (HR) with 95% CI for psychiatric hospitalization.
Results: The IR of psychiatric hospitalization was 12.28 per 100 000 person-years (95% CI, 11.96-12.6). Interpersonal violence victimization was the main risk factor for youth psychiatric hospitalization (HR, 5.24; 95% CI, 4.61-5.96). Other risk factors for psychiatric hospitalization included living with the oldest family member who had low education (HR, 2.51; 95% CI, 2.16-2.91) or was unemployed (HR, 1.49; 95% CI, 1.36-1.62), living with seven or more family members (HR, 1.84; 95% CI, 1.49-2.26) and being male (HR, 1.28; 95% CI, 1.21-1.36).
Conclusions: Urgent action is needed to prevent youth from suffering violence. Addressing this may alleviate the mental health burden in developmental ages, benefiting youth, families and the government through reduced costs in preventable psychiatric hospitalizations.
{"title":"Risk of psychiatric hospitalization in low-income youth: longitudinal findings from the 100 Million Brazilian Cohort.","authors":"Lidiane Toledo, Rodrigo Rodrigues, Flávia Alves, Fillipe Guedes, Jacyra Azevedo Paiva de Araújo, John A Naslund, Maurício L Barreto, Vikram Patel, Daiane Borges Machado","doi":"10.1093/ije/dyae153","DOIUrl":"10.1093/ije/dyae153","url":null,"abstract":"<p><strong>Background: </strong>Youth psychiatric hospitalizations have been associated with negative outcomes, including premature death and post-discharge self-harm. Identifying risk factors for youth psychiatric hospitalization is crucial for informing prevention strategies. We aimed to evaluate the risk factors for psychiatric hospitalizations among low-income youth in Brazil.</p><p><strong>Methods: </strong>This cohort study used interpersonal violence and psychiatric hospitalization data linked to the 100 Million Brazilian Cohort baseline. We considered 9 985 917 youths aged 5-24 years who enrolled at the baseline, between 2011 and 2018. We estimated the incidence rate (IR) with 95% confidence interval (CI) for psychiatric hospitalization by calculating the number of hospitalizations per person-year in 100 000 individuals at risk. The multilevel, multivariate Cox proportional hazards regression estimated the hazard risks (HR) with 95% CI for psychiatric hospitalization.</p><p><strong>Results: </strong>The IR of psychiatric hospitalization was 12.28 per 100 000 person-years (95% CI, 11.96-12.6). Interpersonal violence victimization was the main risk factor for youth psychiatric hospitalization (HR, 5.24; 95% CI, 4.61-5.96). Other risk factors for psychiatric hospitalization included living with the oldest family member who had low education (HR, 2.51; 95% CI, 2.16-2.91) or was unemployed (HR, 1.49; 95% CI, 1.36-1.62), living with seven or more family members (HR, 1.84; 95% CI, 1.49-2.26) and being male (HR, 1.28; 95% CI, 1.21-1.36).</p><p><strong>Conclusions: </strong>Urgent action is needed to prevent youth from suffering violence. Addressing this may alleviate the mental health burden in developmental ages, benefiting youth, families and the government through reduced costs in preventable psychiatric hospitalizations.</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/PMC11578595/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142681623","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":"Also long overdue: consideration of collider bias in guidelines and tools for systematic reviews and meta-analyses of observational studies.","authors":"Judith J M Rijnhart, Ava Rabbers, Santina Rizzuto","doi":"10.1093/ije/dyae147","DOIUrl":"https://doi.org/10.1093/ije/dyae147","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":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142575822","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}
Alison Fang-Wei Wu, Morag Henderson, Matt Brown, Tugba Adali, Richard J Silverwood, Darina Peycheva, Lisa Calderwood
{"title":"Cohort Profile: Next Steps-the longitudinal study of people in England born in 1989-90.","authors":"Alison Fang-Wei Wu, Morag Henderson, Matt Brown, Tugba Adali, Richard J Silverwood, Darina Peycheva, Lisa Calderwood","doi":"10.1093/ije/dyae152","DOIUrl":"10.1093/ije/dyae152","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/PMC11561396/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142619938","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}
We outline a geometric perspective on causal inference in cohort studies that can help epidemiologists understand the role of standardization in controlling for confounding. For simplicity, we focus on a binary exposure X, a binary outcome D, and a binary confounder C that is not causally affected by X. Rothman diagrams plot the risk of disease in the unexposed on the x-axis and the risk in the exposed on the y-axis. The crude risks define a point in the unit square, and the stratum-specific risks at each level of C define two other points in the unit square. Standardization produces points along the line segment connecting the stratum-specific points. When there is confounding by C, the crude point is off this line segment. The set of all possible crude points is a rectangle with corners at the stratum-specific points and sides parallel to the axes. When there are more than two strata, standardization produces points in the convex hull of the stratum-specific points, and there is confounding if the crude point is outside this convex hull. We illustrate these ideas using data from a study in Newcastle, United Kingdom, in which the causal effect of smoking on 20-year mortality was confounded by age.
我们从几何角度概述了队列研究中的因果推断,这有助于流行病学家理解标准化在控制混杂因素方面的作用。为简单起见,我们将重点放在二元暴露 X、二元结果 D 和不受 X 因果影响的二元混杂因素 C 上。罗斯曼图将未暴露者的患病风险绘制在 x 轴上,将暴露者的患病风险绘制在 y 轴上。粗风险定义了单位正方形中的一个点,而 C 各等级的分层风险定义了单位正方形中的另外两个点。标准化后,沿连接各层特定点的线段产生点。如果存在 C 的混淆,粗略点就会偏离这条线段。所有可能的粗糙点集合是一个矩形,角位于特定层点,边与轴平行。当有两个以上的分层时,标准化产生的点位于特定分层点的凸壳中,如果粗点位于凸壳之外,则存在混淆。我们使用英国纽卡斯尔的一项研究数据来说明这些观点,在这项研究中,吸烟对 20 年死亡率的因果效应与年龄有关。
{"title":"Rothman diagrams: the geometry of confounding and standardization.","authors":"Eben Kenah","doi":"10.1093/ije/dyae139","DOIUrl":"10.1093/ije/dyae139","url":null,"abstract":"<p><p>We outline a geometric perspective on causal inference in cohort studies that can help epidemiologists understand the role of standardization in controlling for confounding. For simplicity, we focus on a binary exposure X, a binary outcome D, and a binary confounder C that is not causally affected by X. Rothman diagrams plot the risk of disease in the unexposed on the x-axis and the risk in the exposed on the y-axis. The crude risks define a point in the unit square, and the stratum-specific risks at each level of C define two other points in the unit square. Standardization produces points along the line segment connecting the stratum-specific points. When there is confounding by C, the crude point is off this line segment. The set of all possible crude points is a rectangle with corners at the stratum-specific points and sides parallel to the axes. When there are more than two strata, standardization produces points in the convex hull of the stratum-specific points, and there is confounding if the crude point is outside this convex hull. We illustrate these ideas using data from a study in Newcastle, United Kingdom, in which the causal effect of smoking on 20-year mortality was confounded by age.</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/PMC11565235/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142638937","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}
Md Mijanur Rahman, Joachim Worthington, Julia Steinberg, Michael David
{"title":"Using G-methods to assess and mitigate bias from coarsening time intervals in evaluating colorectal cancer screening efficiency.","authors":"Md Mijanur Rahman, Joachim Worthington, Julia Steinberg, Michael David","doi":"10.1093/ije/dyae159","DOIUrl":"https://doi.org/10.1093/ije/dyae159","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":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142692906","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}
Matthew N Ahmadi,Pieter Coenen,Leon Straker,Emmanuel Stamatakis
BACKGROUNDPrevious studies have indicated that standing may be beneficially associated with surrogate metabolic markers, whereas more time spent sitting has an adverse association. Studies assessing the dose-response associations of standing, sitting and composite stationary behaviour time with cardiovascular disease (CVD) and orthostatic circulatory disease are scarce and show an unclear picture.OBJECTIVETo examine associations of daily sitting, standing and stationary time with CVD and orthostatic circulatory disease incidence.METHODSWe used accelerometer data from 83 013 adults (mean age ± standard deviation = 61.3 ± 7.8; female = 55.6%) from the UK Biobank to assess daily time spent sitting and standing. Major CVD was defined as coronary heart disease, heart failure and stroke. Orthostatic circulatory disease was defined as orthostatic hypotension, varicose vein, chronic venous insufficiency and venous ulcers. To estimate the dose-response hazard ratios (HR) we used Cox proportional hazards regression models and restricted cubic splines. The Fine-Gray subdistribution method was used to account for competing risks.RESULTSDuring 6.9 (±0.9) years of follow-up, 6829 CVD and 2042 orthostatic circulatory disease events occurred. When stationary time exceeded 12 h/day, orthostatic circulatory disease risk was higher by an average HR (95% confidence interval) of 0.22 (0.16, 0.29) per hour. Every additional hour above 10 h/day of sitting was associated with a 0.26 (0.18, 0.36) higher risk. Standing more than 2 h/day was associated with an 0.11 (0.05, 0.18) higher risk for every additional 30 min/day. For major CVD, when stationary time exceeded 12 h/day, risk was higher by an average of 0.13 (0.10, 0.16) per hour. Sitting time was associated with a 0.15 (0.11, 0.19) higher risk per extra hour. Time spent standing was not associated with major CVD risk.CONCLUSIONSTime spent standing was not associated with CVD risk but was associated with higher orthostatic circulatory disease risk. Time spent sitting above 10 h/day was associated with both higher orthostatic circulatory disease and major CVD risk. The deleterious associations of overall stationary time were primarily driven by sitting. Collectively, our findings indicate increasing standing time as a prescription may not lower major CVD risk and may lead to higher orthostatic circulatory disease risk.
{"title":"Device-measured stationary behaviour and cardiovascular and orthostatic circulatory disease incidence.","authors":"Matthew N Ahmadi,Pieter Coenen,Leon Straker,Emmanuel Stamatakis","doi":"10.1093/ije/dyae136","DOIUrl":"https://doi.org/10.1093/ije/dyae136","url":null,"abstract":"BACKGROUNDPrevious studies have indicated that standing may be beneficially associated with surrogate metabolic markers, whereas more time spent sitting has an adverse association. Studies assessing the dose-response associations of standing, sitting and composite stationary behaviour time with cardiovascular disease (CVD) and orthostatic circulatory disease are scarce and show an unclear picture.OBJECTIVETo examine associations of daily sitting, standing and stationary time with CVD and orthostatic circulatory disease incidence.METHODSWe used accelerometer data from 83 013 adults (mean age ± standard deviation = 61.3 ± 7.8; female = 55.6%) from the UK Biobank to assess daily time spent sitting and standing. Major CVD was defined as coronary heart disease, heart failure and stroke. Orthostatic circulatory disease was defined as orthostatic hypotension, varicose vein, chronic venous insufficiency and venous ulcers. To estimate the dose-response hazard ratios (HR) we used Cox proportional hazards regression models and restricted cubic splines. The Fine-Gray subdistribution method was used to account for competing risks.RESULTSDuring 6.9 (±0.9) years of follow-up, 6829 CVD and 2042 orthostatic circulatory disease events occurred. When stationary time exceeded 12 h/day, orthostatic circulatory disease risk was higher by an average HR (95% confidence interval) of 0.22 (0.16, 0.29) per hour. Every additional hour above 10 h/day of sitting was associated with a 0.26 (0.18, 0.36) higher risk. Standing more than 2 h/day was associated with an 0.11 (0.05, 0.18) higher risk for every additional 30 min/day. For major CVD, when stationary time exceeded 12 h/day, risk was higher by an average of 0.13 (0.10, 0.16) per hour. Sitting time was associated with a 0.15 (0.11, 0.19) higher risk per extra hour. Time spent standing was not associated with major CVD risk.CONCLUSIONSTime spent standing was not associated with CVD risk but was associated with higher orthostatic circulatory disease risk. Time spent sitting above 10 h/day was associated with both higher orthostatic circulatory disease and major CVD risk. The deleterious associations of overall stationary time were primarily driven by sitting. Collectively, our findings indicate increasing standing time as a prescription may not lower major CVD risk and may lead to higher orthostatic circulatory disease risk.","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"74 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443769","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}