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Background: Increasing empirical evidence suggests that exposure to nature (natural vegetation, or “greenness”) influences health. Studies have shown that greenness is related to lower diabetes risk possibly through mediation of physical activity, harmful environmental exposures, or mental health. However, to our knowledge, no previous study has reported on associations between greenness and insulin resistance in children. We hypothesize that children are more sensitive to environmental exposures particularly during critical windows of susceptibility. Our research aims to evaluate the early life association between greenness and insulin resistance and assess vulnerable life-periods in which individuals are more susceptible to their surroundings. Methods: We use data from Project Viva, a longitudinal cohort study designed to study prenatal factors, pregnancy outcomes, and child health. From 1999 to 2002, we recruited pregnant women from a multispecialty group practice in Massachusetts. Of the 1,036 who attended the early teen research visit, we considered 460 participants who provided fasting blood and had complete data for all covariates and exposure at infancy (less than one year), early childhood (median age 3.3 years), mid-childhood (median age 7.7 years) and early teens (median age 13.2). We defined greenness exposure surrounding each participant’s address using 30m resolution Landsat satellite imagery [Normalized Difference Vegetation Index] at infancy (under one year of age), early childhood, mid-childhood, and early teens. Our main outcome measurement was the homeostatic model assessment to estimate insulin resistance (HOMA-IR) at the early teen visit. Results: In models adjusted for age, race, sex, mother’s education, father’s education, household income and median household income from the census tract at delivery, living in the highest quintile of greenness in the 90-m area at the early teen visit was associated with 0.65 lower HOMA-IR (95%CI: -1.52, -0.40) than those in the lowest quintile. The observed association between higher greenness exposure and lower HOMA-IR in early teens was consistent for the 270-m area, although slightly attenuated, and no longer significant for the 1230-m area (mean HOMA-IR was 3.06, SD=2.08). We found no associations of exposure to greenness in the 90-m, 270-m or 1230-m areas around participants’ home at infancy, early childhood, or mid-childhood with early teenage HOMA-IR. Conclusions: Higher levels of green vegetation, especially closer to the home, at the early teen visit were associated with lower insulin resistance at the same time period. Early exposure to green space during infancy, early childhood and mid-childhood was not associated with HOMA-IR as an early teenager. Early childhood longitudinal studies including geographic contextual factors across diverse populations are needed to confirm or refute these findings.

Background: Blood pressure treatment strategies and targets are generally similar for most patients with hypertension, apart from individuals with certain specific comorbidities such as diabetes. We hypothesize that there is latent heterogeneity in the population of adults with hypertension and that this may be associated with differential risk of mortality and might suggest opportunities for more tailored treatment strategies. Our study of adults with hypertension in the US explores whether clusters of social and health-related characteristics exist, how trends in clusters have varied between 1999 and 2012, and how risk of mortality varies between clusters. Methods: In a nationally representative sample of adults (&gt 18 years) with hypertension (physician diagnosed, systolic &ge 140 mmHg or diastolic &ge 90 mmHg, or taking hypertension -related medication) from the National Health and Nutrition Examination Survey from 1999 to 2012 (Total N=16,855), we used a hierarchical cluster analysis approach to identify hypertension sub-groups according to chronic diseases, social factors, and health behaviors. Results: We found significant heterogeneity among hypertensive participants across time, according to 7 distinct clusters: Young Mexican-Americans with good health (55% of sample); Low-income non-White elderly with good health behaviors (7%); Elderly obese who smoke (18%); Men with poor health who drink and smoke (1%); Normal weight individuals with high prevalence of cancer (16%); Low-income and fit individuals with poor health (1%); and Obese and morbidly obese with high prevalence of chronic conditions (2%). The prevalence of each of these clusters remained relatively constant throughout the last decade, although there was an increase in the “Elderly obese who smoke” cluster from 14% to 18%. Mortality risk varied by subgroup. For example, the odds of dying for “Obese and morbidly obese with high prevalence of chronic conditions” were 1.73 times higher compared to “Young Mexican-Americans with good health” (p-value Conclusions: Sociodemographic and clinical clusters among hypertensive individuals in the U.S. remained stable over a decade, with higher risk of mortality associated with specific clusters. Recognizing these clinically-identifiable phenotypes may highlight opportunities to develop and evaluate targeted interventions that account for complex and inter-related clinical and social factors. Further, there is an opportunity through clinical trials to determine whether these clusters merit different blood pressure treatment strategies.