# Neighborhood environment and incident diabetes, a neighborhood environment-wide association study (‘NE-WAS’): Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

## TL;DR

This study explores how neighborhood environments might relate to diabetes in Hispanic/Latino populations but finds no clear neighborhood-based patterns.

## Contribution

The paper introduces a novel 'NE-WAS' approach to analyze neighborhood-level factors linked to diabetes incidence.

## Key findings

- No specific neighborhood measures or clusters were consistently associated with diabetes incidence.
- Individual-level factors like age and family history strongly correlate with diabetes.
- Principal component analysis did not reveal meaningful patterns linking neighborhoods to diabetes.

## Abstract

The prevalence of type 2 diabetes is increasing among the Hispanic/Latino population. Type 2 diabetes incidence rates vary between neighborhoods, but no single aspect of the neighborhood environment is known to cause type 2 diabetes. Using data from the Hispanic Community Health Study/Study of Latinos cohort of 16,415 Hispanic/Latino adults in four major US cities, we conducted a neighborhood environment-wide association study to identify neighborhood measures or clusters of measures associated with diabetes incidence. Two-hundred and four neighborhood measures were calculated at the census tract level or within a 1-km buffer of participants’ residential addresses. Independent covariate-adjusted and survey-weighted Poisson regressions were run for each neighborhood measure and incident diabetes. Principal component analysis of neighborhood measures was conducted to reduce dimensionality. No coherent pattern of neighborhood measures or principal component scores were associated with diabetes incidence within the cohort, though established individual-level risk factors such as age and family history were strongly associated with diabetes incidence. Results from our analysis did not indicate specific neighborhood measures, clusters, or patterns. Individual, rather than neighborhood, factors distinguish incident diabetes cases from non-cases.