American journal of epidemiology最新文献

We investigated the association between unclean cooking fuel use and sleep problems in a nationally representative sample of adults aged ≥65 years from 6 low- and middle-income countries (China, Ghana, India, Mexico, Russia, and South Africa). Cross-sectional, community-based data from the WHO Study on global AGEing and adult health (SAGE) were analyzed. Unclean cooking fuel referred to kerosene/paraffin, coal/charcoal, wood, agriculture/crop, animal dung, and shrubs/grass. Outcomes related to sleep included self-reported nocturnal sleep problems, lethargy, poor sleep quality, and sleep duration. Multivariable logistic regression analysis was conducted. Data on 14 585 individuals aged ≥65 years were analyzed (mean [SD] age: 72.6 [11.5] years; 55.0% females). After adjustment for potential confounders, unclean cooking fuel use was associated with significant 1.51 (95% CI, 1.03-2.22) times higher odds for nocturnal sleep problems, while it was also associated with 1.64 (95% CI, 1.20-2.26) times higher odds for long sleep duration (ie, >9 vs >6 to 9 h), but not with other sleep-related outcomes. These findings suggest that the implementation of the United Nations Sustainable Development Goal 7, which advocates affordable, reliable, sustainable, and modern energy for all, may also have a positive impact on sleep problems, as well as a plethora of other health and environmental impacts. This article is part of a Special Collection on Cross-National Gerontology.

Early life conditions are associated with later life health. However, research in this area has been based on high-income countries, with limited research in low- and middle-income countries. We examine how childhood conditions are associated with mortality in older adulthood in the United States and Brazil, while evaluating the role of educational attainment and gender differences. Data come from the HRS and ELSI-Brazil. We use structural equation modeling to examine direct and indirect pathways from childhood conditions to mortality in older adulthood for men and women. Results showed substantial differences between Brazil and the United States. Childhood health was associated with increased mortality risk in the United States, not in Brazil. Adverse childhood conditions were associated with increased mortality in Brazil and the United States, but we found a large indirect pathway through educational attainment in the United States. Lastly, we found notable gender differences across both countries, with indirect pathways for United States men and Brazilian women (not their counterparts). Findings point to the malleability of the association of childhood conditions on adulthood mortality risk. Future work should consider how exposures and opportunities combine to influence life course developments of health and aging processes in diverse populations. This article is part of a Special Collection on Cross-National Gerontology.

Electronic health records (EHRs) present opportunities to study uterine fibroids and endometriosis within diverse populations. When using EHR data, it is important to validate outcome classification via diagnosis codes. We performed a validation study of 3 approaches ([1] International Classification of Diseases-10 (ICD-10) code alone, [2] ICD-10 code + diagnostic procedure, and [3] ICD-10 code + all diagnostic information) to identify incident uterine fibroids and endometriosis patients among n = 750 NYU Langone Health 2016-2023. Chart review was used to determine the true diagnosis status. When using a binary classification system (incident vs nonincident patient), Approaches 2 and 3 had higher positive predictive values (PPVs) for uterine fibroids (0.86 and 0.87 vs 0.78) and for endometriosis (0.70 and 0.73 vs 0.66), but Approach 1 outperformed the other 2 in negative predictive values (NPVs) for both outcomes. When using a 3-level classification system (incident vs prevalent vs disease-free patients), PPV for prevalent patients was low for all approaches, while PPV/NPV of disease-free patients was generally above 0.8. Using ICD-10 codes alone yielded higher NPVs but resulted in lower PPVs compared with the other approaches. Continued validation of uterine fibroids/endometriosis EHR studies is warranted to increase research into these understudied gynecologic conditions.

During the COVID-19 pandemic, accurate measurement of vaccination status was important for guiding prevention efforts. We assessed the accuracy of electronic health record (EHR) COVID-19 vaccination compared with survey self-reported vaccination status using data from a cross-sectional study among pregnant women and non-pregnant adults in the Vaccine Safety Datalink between 2021 and 2022, where self-report was considered the reference standard. We measured the sensitivity and specificity of EHR vaccine data compared with the self-reported measure and estimated vaccination rates from EHR data. EHR data were obtained initially in November 2021, updated in April 2022, and record reviewed in July 2022. Vaccination coverage increased in pregnant/formerly pregnant women and non-pregnant adult respondents by 23.9% and 9.2%, respectively, over 9 months. Estimates of sensitivity based on initial EHR data were 66.0% and 77.3% for pregnant women and non-pregnant people overall and between 41% and 66% for pregnant, non-Hispanic Black, and Hispanic, Spanish-speaking respondents. With matured, chart reviewed EHR data from April 2022, the sensitivity and specificity of EHR vaccine status relative to self-report were > 93%. EHR data were a reasonable source of COVID-19 vaccination status during the pandemic and showed high accuracy with self-reported data after allowing EHR data to mature.

Widowhood is among the most consequential stressful events for mental health. Although certain resources have been identified as protective of mental health following widowhood, these findings are based on US samples. This study uses novel harmonized data to evaluate differences in depressive symptoms and related factors among those recently widowed (ie, within the last 2 years) in the United States (Health and Retirement Study) and India (Longitudinal Aging Study in India). We find US widows have greater elevation in depressive symptoms (-0.36 SD) than widows in India (-0.15) on average. We identify 3 protective resources for widows that are dependent on country context: having close friends vs no friends (-0.58 vs -0.13) and living with others vs alone (-0.79 vs -0.23) are both larger for widows in the United States. Self-rated health that is good, fair, or poor is related to higher depressive symptoms for widows in the United States vs India (between 0.55 and 1.12). Findings suggest protective resources among recently widowed individuals designed to protect mental health following this stressful event will require consideration of country context. In particular, social engagement-based interventions may offer more significant benefits to widows in the United States.

Epidemiologists have access to various methods to reduce bias and improve statistical efficiency in effect estimation, from standard multivariable regression to state-of-the-art doubly-robust efficient estimators paired with highly flexible, data-adaptive algorithms ("machine learning"). However, due to numerous assumptions and trade-offs, epidemiologists face practical difficulties in recognizing which method, if any, may be suitable for their specific data and hypotheses. Importantly, relative advantages are necessarily context-specific (data structure, algorithms, model misspecification), limiting the utility of universal guidance. Evaluating performance through real-data-based simulations is useful but out-of-reach for many epidemiologists. We present a user-friendly, offline Shiny app REFINE2 (Realistic Evaluations of Finite sample INference using Efficient Estimators) that enables analysts to input their own data and quickly compare the performance of different algorithms within their data context in estimating a prespecified average treatment effect (ATE). REFINE2 automates plasmode simulation of a plausible target ATE given observed covariates and then examines bias and confidence interval coverage (relative to this target) given user-specified models. We present an extensive case study to illustrate how REFINE2 can be used to guide analyses within epidemiologist's own data under three typical scenarios: residual confounding; spurious covariates; and mis-specified effect modification. As expected, the apparent best method differed across scenarios and are suboptimal under residual confounding. REFINE2 may help epidemiologists not only chose amongst imperfect models, but also better understand common underappreciated problems, such as finite sample bias using machine learning.

We examined the independent and joint associations of five key social exposome components, including financial strain, neighborhood disorder, perceived discrimination, social strain, and traumatic life events, with cognitive function levels and decline. Data were from adults aged > 50 in the US Health and Retirement Study (HRS; n = 13 795; 2008-2020) and the English Longitudinal Study of Aging (ELSA; n = 9469; 2006-2019), and adults aged ≥65 in their Harmonized Cognitive Assessment Protocol (HCAP) subsamples (HRS-HCAP: n = 2749; 2016; ELSA-HCAP: n = 955; 2018). Using linear mixed-effects models and quantile-based g-computation, we found that all components, except traumatic life events, were associated with lower cognitive function. Simultaneously lowering all components by one quartile could improve cognitive function by 0.10 SD units (95% CI, 0.08-0.12) in the HRS, 0.13 SD units (95% CI, 0.10-0.16) in the ELSA, and 0.08 SD units (95% CI, 0.03-0.14) in the HRS-HCAP. Neighborhood disorder had the strongest negative association with cognitive function in the United States, while financial strain had the strongest association in England. No social exposome components were associated with faster cognitive decline. The associations of key social exposome components with cognitive function were consistent across countries, although the magnitude of the joint association was greater in England. This article is part of a Special Collection on Cross-National Gerontology.

While participant recruitment via social media is increasingly used, its cost-effectiveness remains unclear for pregnancy cohorts, especially across social media platforms and in the context of increasing threats from web robots (ie, bots) and fraudulent participants. Accordingly, we report on the implementation and results of online recruitment for a longitudinal cohort study about mental health in pregnancy and postpartum (Experiences of Pregnancy, EoP). We describe the following: (1) the cost-effectiveness of Facebook, Instagram, Reddit, and Twitter/X for recruiting individuals in their first trimester; (2) methods, experiences, and solutions for preventing bots and fraudulent participants; and (3) the representativeness of EoP compared to the US population and pregnancy cohorts recruited in person. Over 2.5 months (beginning June 2023), 574 participants were recruited at an advertising cost of US$6.19 per participant. Social media recruitment was highly time-efficient compared to in-person recruitment, reaching comparable sample sizes in 1/10th of the time. However, a range of safeguards to counter bots and fraudulent participants had to be implemented, resulting in 995 staff hours during recruitment. Experiences of Pregnancy also allowed reaching individuals without access to prenatal care but was not representative of the US population, suggesting stratified sampling would be needed to reach representativeness with online recruitment.

In this manuscript, we present the results of a series of workshops convened in conjunction with the 2023 Society for Epidemiologic Research annual meeting. The overall objective of the workshops was to develop a set of core competencies for PhD students in epidemiology. The topics presented in the list of competencies are organized using a framework similar to many graduate programs in epidemiology, proceeding from basic to advanced topics. Given the breadth of substantive topics in the fields of epidemiology and public health, this list of competencies focuses on methodologic topics that are relevant to all students, regardless of research interest. The final topic lists were developed based on discussions including a large and diverse group of epidemiologists with different areas of expertise. By creating this resource, we aim to facilitate training of future generations of epidemiologists.

Exposure to negative perceived individual and neighborhood determinants disproportionately impacts marginalized groups and can profoundly shape health behavior. We assessed the hypothesized relationship between exposure to adverse perceived individual and neighborhood determinants and rates of mammography. In this cohort study, we identified 31 568 female participants aged 40-74 without history of breast cancer in the All of Us Research Program. Participant-reported levels of perceived stress, everyday discrimination, perceived neighborhood physical disorder, perceived neighborhood social cohesion, and receipt of mammography were ascertained in the linked participant survey and electronic health record data. Fifty-two percent of participants had at least 1 mammogram during follow-up. Women reporting high stress were screened at lower rates compared to low-stress individuals. Higher discrimination (incidence rate ratio [IRR] = 0.92 [95% CI, 0.88-0.95]) and higher perceived stress (IRR = 0.84 [95% CI, 0.79-0.90) were both respectively associated with lower breast cancer screening rates, while perceived neighborhood physical disorder and social cohesion were not. Women reporting high stress and discrimination were also less likely to be compliant with screening guidelines. The associations between the determinants and breast cancer screening rates did not differ by race and ethnicity. Women who report highest levels of discrimination and stress may face additional barriers obtaining breast cancer screening.