INTRODUCTION: Most previous studies on food insecurity and cardiovascular disease risk factors are cross-sectional. Without longitudinal data, it is unclear whether food insecurity precedes poor health and how exposure timing impacts these relationships. METHODS: Data from 2000 to 2001, 2005 to 2006, and 2010 to 2011 of the Coronary Artery Risk Development in Young Adults study were used. Food insufficiency-a screener measure related to food insecurity-was assessed in 2000-2001 and 2005-2006 using a single item. Cardiovascular disease risk factors were objectively assessed in 2010-2011. Impacts of food insufficiency patterns (food sufficient, food insufficient in 2000-2001 only, food insufficient in 2005-2006 only, food insufficient in both 2000-2001 and 2005-2006) on cardiovascular disease risk factors were estimated using inverse probability weighting of marginal structural models. Covariates that change over time were adjusted for using stabilized weights; baseline covariates were adjusted for in the marginal structural models. Analyses were conducted in 2020-2021. RESULTS: The baseline sample included 2,596 participants (56% women, 47% White). In unadjusted analyses, all food insufficiency patterns were associated with higher BMI, waist circumference, and blood pressure than food sufficiency. After accounting for covariates, estimates were attenuated but still consistent with adverse effects of food insufficiency, particularly among women. CONCLUSIONS: After covariate adjustment, food insufficiency was associated with several cardiovascular disease risk factors. Findings from this study should be replicated in other settings and populations. If verified, this evidence could provide justification for intervening in food insecurity to reduce future cardiovascular disease risk.

Psychosocial factors are associated with the achievement of optimal cardiovascular disease risk factor (CVDRF) levels. To date, little research has examined multiple psychosocial factors simultaneously to identify distinguishing psychosocial profiles among individuals with CVDRF. Further, it is unknown whether profiles are associated with achievement of CVDRF levels longitudinally. Therefore, we characterized psychosocial profiles of individuals with CVDRF and assessed whether they are associated with achievement of optimal CVDRF levels over 15 years. We included 1148 CARDIA participants with prevalent hypertension, hypercholesterolemia and/or diabetes mellitus in 2000-2001. Eleven psychosocial variables reflecting psychological health, personality traits, and social factors were included. Optimal levels were deemed achieved if: Hemoglobin A1c (HbA1c) < 7.0%, low-density lipoprotein (LDL) cholesterol < 100 mg/dl, and systolic blood pressure (SBP) < 140 mm Hg. Latent profile analysis revealed three psychosocial profile groups "Healthy", "Distressed and Disadvantaged" and "Discriminated Against". There were no significant differences in achievement of CVDRF levels of the 3 targets combined across profiles. Participants in the "Distressed and Disadvantaged" profile were less likely to meet optimal HbA1c levels compared to individuals in the "Healthy" profile after demographic adjustment. Associations were attenuated after full covariate adjustment. Distinct psychosocial profiles exist among individuals with CVDRF, representing meaningful differences. Implications for CVDRF management are discussed.

Research has shown that recessions are associated with lower cardiovascular mortality but unemployed individuals have a higher risk of cardiovascular disease (CVD) or death. We used data from eight consecutive exams (1985-2011) of the CARDIA cohort, modeled in fixed-effect panel regressions, to investigate simultaneously the associations of CVD risk factors with (a) the employment status of individuals, and (b) macroeconomic conditions prevalent at the state where the individual lives. We found that unemployed individuals had lower levels of blood pressure, HDL-cholesterol, and physical activity, and significantly higher depression scores, but they were like their counterparts in smoking status, alcohol consumption, LDL cholesterol levels, body mass index, and waist circumference. One percentage point higher unemployment rate at the state level was associated with lower systolic (-0.41 mmHg, 95%CI: -0.65, -0.17) and diastolic (-0.19, 95%CI: -0.39, 0.01) blood pressure, higher physical activity levels, higher depressive symptom scores, and lower waist circumference and smoking. We conclude that levels of CVD risk factors tend to improve during recessions, but mental health tends to deteriorate. Unemployed individuals are significantly more depressed, and likely have lower levels of physical activity and HDL.

Importance: Despite cross-sectional evidence linking racial residential segregation to hypertension prevalence among non-Hispanic blacks, it remains unclear how changes in exposure to neighborhood segregation may be associated with changes in blood pressure. Objective: To examine the association of changes in neighborhood-level racial residential segregation with changes in systolic and diastolic blood pressure over a 25-year period. Design, Setting, and Participants: This observational study examined longitudinal data of 2280 black participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study, a prospective investigation of adults aged 18 to 30 years who underwent baseline examinations in field centers in 4 US locations from March 25, 1985, to June 7, 1986, and then were re-examined for the next 25 years. Racial residential segregation was assessed using the Getis-Ord Gi* statistic, a measure of SD between the neighborhood's racial composition (ie, percentage of black residents) and the surrounding area's racial composition. Segregation was categorized as high (Gi* > 1.96), medium (Gi* 0-1.96), and low (Gi* < 0). Fixed-effects linear regression modeling was used to estimate the associations of within-person change in exposure to segregation and within-person change in blood pressure while tightly controlling for time-invariant confounders. Data analyses were performed between August 4, 2016, and February 9, 2017. Main Outcomes and Measures: Within-person changes in systolic and diastolic blood pressure across 6 examinations over 25 years. Results: Of the 2280 participants at baseline, 974 (42.7%) were men and 1306 (57.3%) were women. Of these, 1861 (81.6%) were living in a high-segregation neighborhood; 278 (12.2%), a medium-segregation neighborhood; and 141 (6.2%), a low-segregation neighborhood. Systolic blood pressure increased by a mean of 0.16 (95% CI, 0.06-0.26) mm Hg with each 1-SD increase in segregation score after adjusting for interactions of time with age, sex, and field center. Of the 1861 participants (81.6%) who lived in high-segregation neighborhoods at baseline, reductions in exposure to segregation were associated with reductions in systolic blood pressure. Mean differences in systolic blood pressure were -1.33 (95% CI, -2.26 to -0.40) mm Hg when comparing high-segregation with medium-segregation neighborhoods and -1.19 (95% CI, -2.08 to -0.31) mm Hg when comparing high-segregation with low-segregation neighborhoods after adjustment for time and interactions of time with baseline age, sex, and field center. Changes in segregation were not associated with changes in diastolic blood pressure. Conclusions and Relevance: Decreases in exposure to racial residential segregation are associated with reductions in systolic blood pressure. This study adds to the small but growing body of evidence that policies that reduce segregation may have meaningful health benefits.

OBJECTIVE: In 2010, the American Diabetes Association (ADA) added hemoglobin A1c (A1C) to the guidelines for diagnosing type 2 diabetes. However, existing models for predicting diabetes risk were developed prior to the widespread adoption of A1C. Thus, it remains unknown how well existing diabetes risk prediction models predict incident diabetes defined according to the ADA 2010 guidelines. Accordingly, we examined the performance of an existing diabetes prediction model applied to a cohort of African American (AA) and white adults from the Coronary Artery Risk Development Study in Young Adults (CARDIA). RESEARCH DESIGN AND METHODS: We evaluated the performance of the Atherosclerosis Risk in Communities (ARIC) diabetes risk prediction model among 2,456 participants in CARDIA free of diabetes at the 2005-2006 exam and followed for 5 years. We evaluated model discrimination, calibration, and integrated discrimination improvement with incident diabetes defined by ADA 2010 guidelines before and after adding baseline A1C to the prediction model. RESULTS: In the overall cohort, re-estimating the ARIC model in the CARDIA cohort resulted in good discrimination for the prediction of 5-year diabetes risk (area under the curve [AUC] 0.841). Adding baseline A1C as a predictor improved discrimination (AUC 0.841 vs. 0.863, P = 0.03). In race-stratified analyses, model discrimination was significantly higher in whites than AA (AUC AA 0.816 vs. whites 0.902; P = 0.008). CONCLUSIONS: Addition of A1C to the ARIC diabetes risk prediction model improved performance overall and in racial subgroups. However, for all models examined, discrimination was better in whites than AA. Additional studies are needed to further improve diabetes risk prediction among AA. long as the work is properly cited, the use is educational and not for profit, and the work is not altered.