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A new concept called complex multimorbidity provides a more reliable measure of disease burden than multimorbidity based on a simple count of diseases, by categorizing diseases according to the body system they affect. This study examined associations between sleep measures and complex multimorbidity among Chinese and Korean Americans in the Baltimore-Washington DC Metropolitan Area, using cross-sectional data (n = 400) from the Screening to Prevent Colorectal Cancer study (2018-2020). Sleep disturbance was measured using the 8-item Patient Reported Outcomes Measurement Information System Sleep Disturbance scale and sleep apnea risk was assessed using the Berlin questionnaire. Complex multimorbidity was defined as the coexistence of 3 or more of body system disorders assessed by self-report of physician-diagnosed diseases. Poisson regression models with adjustments indicated that individuals with sleep disturbance had 2.15 times the prevalence of having complex multimorbidity (95% confidence interval (CI): 1.07, 4.29). Individuals with a high risk of sleep apnea had 1.19 times the prevalence of having complex multimorbidity (95% CI: 0.47, 3.01). These findings suggest a need for interventions to increase awareness of the importance of sleep among health-care providers and the public and to educate them about causes, signs, and treatment of sleep disturbance and sleep apnea.

Two frequently encountered but underrecognized challenges for causal inference in studying the long-term health effects of disasters among survivors include 1) time-varying effects of disasters on a time-to-event outcome and 2) selection bias due to selective attrition. In this paper, we review approaches for overcoming these challenges and demonstrate application of the approaches to a real-world longitudinal data set of older adults who were directly affected by the 2011 Great East Japan Earthquake and Tsunami (n = 4,857). To illustrate the problem of time-varying effects of disasters, we examined the association between degree of damage due to the tsunami and all-cause mortality. We compared results from Cox regression analysis assuming proportional hazards with those derived using adjusted parametric survival curves allowing for time-varying hazard ratios. To illustrate the problem of selection bias, we examined the association between proximity to the coast (a proxy for housing damage from the tsunami) and depressive symptoms. We corrected for selection bias due to attrition in the 2 postdisaster follow-up surveys (conducted in 2013 and 2016) using multivariable adjustment, inverse probability of censoring weighting, and survivor average causal effect estimation. Our results demonstrate that analytical approaches which ignore time-varying effects on mortality and selection bias due to selective attrition may underestimate the long-term health effects of disasters.

Both early life and adult socioeconomic status (SES) predict late-life level of memory; however, evidence is mixed on the relationship between SES and rate of memory decline. Further, the relative importance of different life-course periods for rate of late-life memory decline has not been evaluated. We examined associations between life-course SES and late-life memory function and decline. Health and Retirement Study participants (n = 10,781) were interviewed biennially from 1998-2012 (United States). SES measurements for childhood (composite score including parents' educational attainment), early adulthood (high-school or college completion), and older adulthood (income, mean age 66 years) were all dichotomized. Word-list memory was modeled via inverse-probability weighted longitudinal models accounting for differential attrition, survival, and time-varying confounding, with nonrespondents retained via proxy assessments. Compared to low SES at all 3 points (referent), stable, high SES predicted the best memory function and slowest decline. High-school completion had the largest estimated effect on memory (β = 0.19; 95% confidence interval: 0.15, 0.22), but high late-life income had the largest estimated benefit for slowing declines (for 10-year memory change, β = 0.35; 95% confidence interval: 0.24, 0.46). Both early and late-life interventions are potentially relevant for reducing dementia risk by improving memory function or slowing decline.

Identifying subpopulations that are particularly vulnerable to long-term adverse health consequences of disaster-related trauma is needed. We examined whether adverse childhood experiences (ACEs) potentiate the association between disaster-related trauma and subsequent cognitive disability among older adult disaster survivors. Data were from a prospective cohort study of older adults who survived the 2011 Great East Japan Earthquake. The baseline survey pre-dated the disaster by 7 months. We included participants who completed follow-up surveys (2013 and 2016) and did not have a cognitive disability before the disaster (n  = 602). Disaster-related traumas (i.e. home loss, loss of friends or pets) and ACEs were retrospectively assessed in 2013. Cognitive disability levels in 2016 were objectively assessed. After adjusting for pre-disaster characteristics using a machine learning–based estimation approach, home loss (0.19, 95% confidence interval (CI): 0.09, 0.28) was, on average, associated with greater cognitive disability. Among individuals with ACEs, home loss was associated with even higher cognitive disability levels (0.64, 95% CI: 0.24, 1.03). Losses of friends (0.18, 95% CI: 0.05, 0.32) and pets (0.13, 95% CI: 0.02, 0.25) were associated with higher cognitive disability levels only among those with ACEs. Our findings suggest that individuals with a history of ACEs may be particularly vulnerable to adverse health consequences related to disasters. [ABSTRACT FROM AUTHOR]

Historically, the American Journal of Epidemiology (AJE) has played an important role in the development of social epidemiology as a field. To mark the centennial of the Journal , we invited commentaries from 3 sets of authors in which we asked them to reflect on the role of the AJE in advancing our understanding of the social determinants of population health and health disparities. Drs. Lisa Berkman, Mauricio Avendano, and Emilie Courtin discuss the promises and pitfalls of using experimental data (from both randomized trials and natural policy experiments) to interrogate the causal connection between social determinants and population health outcomes. Drs. Julie Palmer, Yvette Crozier, and Lynn Rosenberg look back on the first 25 years of the Black Women's Health Study and the contributions of that study to our understanding of racial disparities in health. Drs. Luisa Borrell and Natalie Crawford review the AJE 's contributions to the definition and use of race and ethnicity in epidemiologic research and make recommendations for strengthening diversity and inclusion in the profession. A common thread that emerges across the invited essays is the AJE 's commitment to publishing articles that engage in critical self-reflection of the discipline. [ABSTRACT FROM AUTHOR]

This study examined heterogeneity in the association between disaster-related home loss and functional limitations of older adults, and identified characteristics of vulnerable subpopulations. Data were from a prospective cohort study of Japanese older survivors of the 2011 Japan Earthquake. Complete home loss was objectively assessed. Outcomes in 2013 (n  = 3,350) and 2016 (n  = 2,664) included certified physical disability levels, self-reported activities of daily living, and instrumental activities of daily living. We estimated population average associations between home loss and functional limitations via targeted maximum likelihood estimation with SuperLearning and its heterogeneity via the generalized random forest algorithm. We adjusted for 55 characteristics of survivors from the baseline survey conducted 7 months before the disaster. While home loss was consistently associated with increased functional limitations on average, there was evidence of effect heterogeneity for all outcomes. Comparing the most and least vulnerable groups, the most vulnerable group tended to be older, not married, living alone, and not working, with preexisting health problems before the disaster. Individuals who were less educated but had higher income also appeared vulnerable for some outcomes. Our inductive approach for effect heterogeneity using machine learning algorithm uncovered large and complex heterogeneity in postdisaster functional limitations among Japanese older survivors. [ABSTRACT FROM AUTHOR]

On May 1, 2018, Scotland introduced a minimum price of 50 pence per unit of alcohol, which led to a reduction in alcohol consumption. As drink-driving is an important risk factor for motor vehicle collisions, we examined whether the minimum alcohol pricing was followed by a decrease in collisions. We took advantage of a case where the minimum price was introduced to 1 population during the study period (Scotland) and another population that served as the control group did not experience this intervention (England and Wales). We used data on the daily number of motor vehicle collisions resulting in death or injury in 2018 and used a differences-in-differences econometric approach, comparing trends before and after the introduction of the minimum price. Controlling for seasonality, we found a small relative decrease in collisions in Scotland compared with England and Wales (difference-in-difference interaction coefficient, −0.35; 95% confidence interval: −0.65, −0.04; P  = 0.03). Our results suggest that there was a relative decrease in motor vehicle collisions in Scotland of between 1.52 and 1.90, on average, in the first months after the introduction of the policy. More research is needed to understand any long-term impacts of minimum alcohol pricing. [ABSTRACT FROM AUTHOR]

Social epidemiology is concerned with how social forces influence population health. Rather than focusing on a single disease (as in cancer or cardiovascular epidemiology) or a single type of exposure (e.g. nutritional epidemiology), social epidemiology encompasses all the social and economic determinants of health, both historical and contemporary. These include features of social and physical environments, the network of relationships in a society, and the institutions, politics, policies, norms and cultures that shape all of these forces. This commentary presents the perspective of several editors at the Journal with expertise in social epidemiology. We articulate our thinking to encourage submissions to the Journal that: 1) expand knowledge of emerging and underresearched social determinants of population health; 2) advance new empirical evidence on the determinants of health inequities and solutions to advance health equity; 3) generate evidence to inform the translation of research on social determinants of health into public health impact; 4) contribute to innovation in methods to improve the rigor and relevance of social epidemiology; and 5) encourage critical self-reflection on the direction, challenges, successes, and failures of the field. [ABSTRACT FROM AUTHOR]