This study demonstrates the reliability and validity of the Clergy Occupational Distress Index (CODI). The five-item index allows researchers to measure the frequency that clergy, who traditionally have not been the subject of occupational health studies, experience occupational distress. We assess the reliability and validity of the index using two samples of clergy: a nationally representative sample of clergy and a sample of clergy from nine Protestant denominations. Exploratory factor analysis and Cronbach's scores are generated. Construct validity is measured by examining the association between CODI scores and depressive symptoms while controlling for demographic, ministerial, and health variables. In both samples, the five items of the CODI load onto a single factor and the Cronbach's alpha scores are robust. The regression model indicates that a high score on the CODI (i.e., more frequent occupational distress) is positively associated with having depressive symptoms within the last 4 weeks. The CODI can be used to identify clergy who frequently experience occupational distress and to understand how occupational distress affects clergy's health, ministerial career, and the functioning of their congregation.

Differences by nativity status for cardiovascular disease (CVD) risk factors have been previously reported. Recent research has focused on understanding how other acculturation factors, such as length of residence, affect health behaviors and outcomes. This study examines the association between CVD risk factors and nativity/length of US residence. Using cross-sectional data from 15,965 adults in the 2011-2016 National Health and Nutrition Examination Surveys (analyzed in 2018), prevalence ratios and predicted marginals from logistic regression models are used to estimate associations of CVD risk factors (i.e., hypertension, hypercholesterolemia, diabetes, overweight/obesity and smoking) with nativity/length of residence (< 15 years, ≥15 years) in the US. In sex-, age-, education-and race and Hispanic origin-adjusted analyses, a higher percentage of US (50 states and District of Columbia) born adults (86.4%) had ≥1 CVD risk factor compared to non-US born residents in the US < 15 years (80.1%) but not ≥15 years (85.1%). Compared to US born counterparts, regardless of length of residence, hypertension overall and smoking among non-Hispanic white and Hispanic adults were lower among non-US born residents. Overweight/ obesity overall and diabetes among Hispanic adults were lower among non-US born residents in the US < 15 years. In contrast, non-US born non-Hispanic Asian residents in the US < 15 years had higher prevalence of diabetes. Non-US born adults were less likely to have most CVD risk factors compared to US born adults regardless of length of residence, although, for smoking and diabetes this pattern differed by race and Hispanic origin.

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In recently developed hierarchical age-period-cohort (HAPC) models, inferential questions arise: How can one assess or judge the significance of estimates of individual cohort and period effects in such models? And how does one assess the overall statistical significance of the cohort and/or the period effects? Beyond statistical significance is the question of substantive significance. This paper addresses these questions. In the context of empirical applications of linear and generalized linear mixed-model specifications of HAPC models using data on verbal test scores and voter turnout in U.S. presidential elections, respectively, we describe a two-step approach and a set of guidelines for assessing statistical significance. The guidelines include assessments of patterns of effects and statistical tests both for the effects of individual cohorts and time periods as well as for entire sets of cohorts and periods. The empirical applications show strong evidence that trends in verbal test scores are primarily cohort driven, while voter turnout is primarily a period phenomenon.