Causal Inference in Studying the Long-Term Health Effects of Disasters: Challenges and Potential Solutions
AbstractTwo 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 associati...
Source: American Journal of Epidemiology - March 17, 2021 Category: Epidemiology Source Type: research

Associations of Binge Drinking With the Risks of Ischemic Heart Disease and Stroke: A Study of Pooled Norwegian Health Surveys
AbstractNorwegian health survey data (1987 –2003) were analyzed to determine if binge drinking increases the risk of incident major events from ischemic heart disease (IHD) and stroke. Among current drinkers reporting average alcohol intakes of 2.00–59.99 g/day (n = 44,476), frequent binge drinking (≥5 units at least once per month) was not associated with a greater risk of IHD (adjusted hazard ratio (HR) = 0.91, 95% confidence interval (CI): 0.76, 1.09) or stroke (adjusted HR = 0.98, 95% CI: 0.81, 1.19), in comparison with participants who reported that they never or only infrequently (less than once per month...
Source: American Journal of Epidemiology - March 15, 2021 Category: Epidemiology Source Type: research

Sheltering in Place and the Likelihood of Nonnatural Death
AbstractIncreasing hospitalizations for COVID-19 in the United States and elsewhere have ignited debate over whether to reinstate shelter-in-place policies adopted early in the pandemic to slow the spread of infection. The debate includes claims that sheltering in place influences deaths unrelated to infection or other natural causes. Testing this claim should improve the benefit/cost accounting that informs choice on reimposing sheltering in place. We used time-series methods to compare weekly nonnatural deaths in California with those in Florida. California was the first state to begin, and among the last to end, shelter...
Source: American Journal of Epidemiology - March 15, 2021 Category: Epidemiology Source Type: research

A Changing Landscape of Health Opportunity in the United States: Increases in the Strength of Association Between Childhood Socioeconomic Disadvantage and Adult Health Between the 1990s and the 2010s
AbstractUnderstanding the changing health consequences of childhood socioeconomic disadvantage (SED) is highly relevant to policy debates on inequality and national and state goals to improve population health. However, changes in the strength of association between childhood SED and adult health over historic time are largely unexamined in the United States. The present study begins to address this knowledge gap. Data were from 2 national samples of adults collected in 1995 (n = 7,108) and 2012 (n = 3,577) as part of the Midlife in the United States study. Three measures of childhood SED (parents’ occupational prestig...
Source: American Journal of Epidemiology - March 12, 2021 Category: Epidemiology Source Type: research

Schnake-Mahl and Bilal Respond to “Structural Racism and COVID-19 Mortality in the US”
AbstractIn their commentary, Zalla et al. (Am J Epidemiol. 2021;190(8):1439 –1446) argue that the approach taken by the Centers for Disease Control and Prevention, comparing the proportion of coronavirus disease 2019 (COVID-19) deaths by race/ethnicity with a weighted population distribution, ignores how systemic racism structures the composition of places. While the Cent ers for Disease Control and Prevention have abandoned their measure, they did so because of the changing geographic distribution of COVID-19, not because the measure underestimates racial disparities. We further Zalla et al.’s argument, advocating for...
Source: American Journal of Epidemiology - March 12, 2021 Category: Epidemiology Source Type: research

A Geography of Risk: Structural Racism and Coronavirus Disease 2019 Mortality in the United States
AbstractCoronavirus disease 2019 (COVID-19) is disproportionately burdening racial and ethnic minority groups in the United States. Higher risks of infection and mortality among racialized minorities are a consequence of structural racism, reflected in specific policies that date back centuries and persist today. Yet our surveillance activities do not reflect what we know about how racism structures risk. When measuring racial and ethnic disparities in deaths due to COVID-19, the Centers for Disease Control and Prevention statistically accounts for the geographic distribution of deaths throughout the United States to refle...
Source: American Journal of Epidemiology - March 12, 2021 Category: Epidemiology Source Type: research

Disparities in Coronavirus Disease 2019 Mortality by Country of Birth in Stockholm, Sweden: A Total-Population –Based Cohort Study
AbstractPreliminary evidence points to higher morbidity and mortality from coronavirus disease 2019 (COVID-19) in certain racial and ethnic groups, but population-based studies using microlevel data are lacking so far. We used register-based cohort data including all adults living in Stockholm, Sweden, between January 31, 2020 (the date of the first confirmed case of COVID-19) and May 4, 2020 (n = 1,778,670) to conduct Poisson regression analyses with region/country of birth as the exposure and underlying cause of COVID-19 death as the outcome, estimating relative risks and 95% confidence intervals. Migrants from Middle ...
Source: American Journal of Epidemiology - March 12, 2021 Category: Epidemiology Source Type: research

Parametric-Regression –Based Causal Mediation Analysis of Binary Outcomes and Binary Mediators: Moving Beyond the Rareness or Commonness of the Outcome
AbstractIn the causal mediation framework, several parametric-regression –based approaches have been introduced in the last decade for estimating natural direct and indirect effects. For a binary outcome, a number of proposed estimators use a logistic model and rely on specific assumptions or approximations that may be delicate or not easy to verify in practice. To cir cumvent the challenges prompted by the rare outcome assumption in this context, an exact closed-form natural-effects estimator on the odds ratio scale was recently introduced for a binary mediator. In this work, we further push this exact approach and exte...
Source: American Journal of Epidemiology - March 9, 2021 Category: Epidemiology Source Type: research

Matched Versus Unmatched Analysis of Matched Case-Control Studies
AbstractAlthough the need for addressing matching in the analysis of matched case-control studies is well established, debate remains as to the most appropriate analytical method when matching on at least 1 continuous factor. We compared the bias and efficiency of unadjusted and adjusted conditional logistic regression (CLR) and unconditional logistic regression (ULR) in the setting of both exact and nonexact matching. To demonstrate that case-control matching distorts the association between the matching variables and the outcome in the matched sample relative to the target population, we derived the logit model for the m...
Source: American Journal of Epidemiology - March 9, 2021 Category: Epidemiology Source Type: research

Data Sources That Enumerate People Experiencing Homelessness in the United States: Opportunities and Challenges for Epidemiologic Research
We describe the appropriate uses and limitations of each data source in the context of infectious disease epidemiology. These data sources provide an opportunity to expand current research and develop actionable analyses. (Source: American Journal of Epidemiology)
Source: American Journal of Epidemiology - March 6, 2021 Category: Epidemiology Source Type: research

Association of Anthropometric Measures With the Risk of Prostate Cancer in the Multiethnic Cohort
AbstractIn studies of anthropometric measures and prostate cancer risk, conducted primarily in White men, positive associations with advanced disease have been reported. We assessed body size in relation to incident prostate cancer risk in 79,950 men from the Multiethnic Cohort, with 8,819 cases identified over 22 years (1993 –2015). Height was associated with increased risk of advanced prostate cancer (≥68 inches (≥ 173 cm) vs.<  66 inches (168 cm); hazard ratio (HR) = 1.24, 95% confidence interval (CI): 1.04, 1.48) and high-grade disease (HR = 1.15, 95% CI: 1.02, 1.31). Compared with men of normal weight...
Source: American Journal of Epidemiology - March 6, 2021 Category: Epidemiology Source Type: research

Thirteen Questions About Using Machine Learning in Causal Research (You Won ’t Believe the Answer to Number 10!)
AbstractMachine learning is gaining prominence in the health sciences, where much of its use has focused on data-driven prediction. However, machine learning can also be embedded within causal analyses, potentially reducing biases arising from model misspecification. Using a question-and-answer format, we provide an introduction and orientation for epidemiologists interested in using machine learning but concerned about potential bias or loss of rigor due to use of “black box” models. We conclude with sample software code that may lower the barrier to entry to using these techniques. (Source: American Journal of Epidemiology)
Source: American Journal of Epidemiology - March 6, 2021 Category: Epidemiology Source Type: research

Invited Commentary: Machine Learning in Causal Inference —How Do I Love Thee? Let Me Count the Ways
AbstractIn this issue of theJournal, Mooney et al. (Am J Epidemiol. 2021;190(8):1476 –1482) discuss machine learning as a tool for causal research in the style of Internet headlines. Here we comment by adapting famous literary quotations, including the one in our title (from “Sonnet 43” by Elizabeth Barrett Browning (Sonnets From the Portuguese, Adelaide Hanscom Leeson, 1850)). We emphasize that any use of machine learning to answer causal questions must be founded on a formal framework for both causal and statistical inference. We illustrate the pitfalls that can occur without such a foundation. We conclude with som...
Source: American Journal of Epidemiology - March 6, 2021 Category: Epidemiology Source Type: research

Sodium/Glucose Cotransporter 2 Inhibitors and the Risk of Diabetic Ketoacidosis: An Example of Complementary Evidence for Rare Adverse Events
AbstractEvidence from observational studies may be considered complementary to that of randomized controlled trials (RCTs), particularly when assessing rare outcomes of drug therapies. Sodium/glucose cotransporter 2 (SGLT-2) inhibitors are a novel class of antidiabetic agents that have been linked to an increased risk of diabetic ketoacidosis (DKA). We conducted a systematic review and separately meta-analyzed data from RCTs (n = 18; 2013–2019) and cohort studies (n = 7; 2017–2020) to assess the consistency of the magnitude of association between SGLT-2 inhibitors and DKA risk. We illustrate the strengths and weakn...
Source: American Journal of Epidemiology - March 6, 2021 Category: Epidemiology Source Type: research

The Early Life Course of Body Weight and Gene Expression Signatures for Disease
We examined the way body-weight patterns through the first 4 decades of life relate to gene expression signatures of common forms of morbidity, including cardiovascular disease (CVD), type 2 diabetes (T2D), and inflammation. As part of wave V of the nationally representative National Longitudinal Study of Adolescent to Adult Health (1997 –2018) in the United States, mRNA abundance data were collected from peripheral blood (n = 1,132). We used a Bayesian modeling strategy to examine the relative associations between body size at 5 life stages—birth, adolescence, early adulthood, young adulthood, and adulthood—and gen...
Source: American Journal of Epidemiology - March 2, 2021 Category: Epidemiology Source Type: research