Background The concept of ‘cardiovascular health’ (CVH) was introduced as a global measure of one’s cardiovascular health. Previous studies established the relationship between neighborhood characteristics and individual cardiovascular risk factors. However, the relationship between neighborhood environment and overall CVH remains unknown. Methods and Results We analyzed data from the MESA baseline exam (2000–2002). Mean age was 61.6 years and 52% were female. Ideal, intermediate and poor categories of cholesterol, body mass index, diet, physical activity, fasting glucose, blood pressure and smoking were defined according to the AHA 2020 Strategic Goals, assigned an individual score and summed to create an overall score. CVH scores were categorized into ideal (11–14 points), intermediate (9–10) and poor (0–8). Neighborhood exposures included favorable food store and physical activity resources densities (by 1-mile buffer), reported healthy food availability, walking/physical activity environment, safety and social cohesion (by census tract). Multinomial logistic regression was used to determine the association of each characteristic with ideal and intermediate CVH, adjusted for demographics and neighborhood socioeconomic status (SES). Over 20% of MESA participants had an ideal CVH score at baseline. In fully adjusted models, favorable food stores (OR= 1.22, 1.06–1.40), physical activity resources (OR=1.19, 1.08–1.31), walking/physical activity environment (OR=1.20, 1.05–1.37) and neighborhood SES (OR=1.22, 1.11–1.33) were associated with higher odds of having an ideal CVH score. Conclusions Neighborhood environment including favorable food stores, physical activity resources, walking/physical activity environment and neighborhood SES are associated with ideal CVH. Further research is needed to investigate the longitudinal associations between neighborhood environment and CVH.

Objective To examine the associations between gestational weight gain (GWG) exceeding Institute of Medicine (IOM) guidelines and neonatal adiposity in the five North American field centers of the Hyperglycemia and Adverse Pregnancy Outcome study. Methods GWG was categorized as less than, within, or greater than 2009 IOM guidelines. Birthweight, body fat percentage, cord serum C-peptide, and sum of neonatal flank, subscapular, and triceps skin fold thicknesses were dichotomized as >90th percentile or ≤90th percentile obtained by quantile regression. Logistic regression analysis was used. Results Of the 5297 participants, 11.6% gained less, 31.9% gained within, and 56.5% gained more than the recommendation. With adjustment for glucose tolerance levels, normal and overweight women who gained more than the recommendation had increased odds of delivering infants with sum of skin folds >90th percentile (OR =1.75 and 4.77, respectively) and percentage body fat >90th percentile (OR =2.41 and 2.59, respectively), and normal weight and obese women who gained more than the recommendation had increased odds of delivering infants with birthweight >90th percentile (OR =2.80 and 1.93, respectively) compared to women who gained within the recommendation. Conclusions This analysis showed independent associations between exceeding IOM GWG recommendations and neonatal adiposity in normal and overweight women, controlling for glucose tolerance levels.

Evidence suggests an association between exposure to cadmium and dysglycemia. To investigate this matter, we examined the relationship between urinary cadmium and prediabetes in the cross sectional National Health and Nutrition Examination Survey (NHANES). NHANES participants for the years 2005 through 2010 aged ≥40 years were included in the analysis. Participants with nephropathy, overt diabetes, or missing required data were excluded. To assess the non-linear relationship between cadmium and Prediabetes, non-parametric logistic regression with B spline expansion of urinary cadmium/creatinine ratio was performed. This analysis revealed a complex non-linear association between higher cadmium levels and prediabetes. This relationship persisted, though with varying magnitudes across smoking groups (never smokers, moderate smokers, heavy smokers). In a conventional logistic regression analysis, this relationship was less evident with significantly increased OR for prediabetes was found in the highest quintile of urine cadmium compared to the lowest quintile in the overall population and in moderate smokers. In an age stratified analysis, a significant linear association was found only in the age groups 60–69 and ≥70. We conclude that there is a significant non-linear, complex relationship between urinary Cd levels, age, smoking habits and odds of prediabetes.