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<p>Microplastics (MPs), synthetic polymer particles &lt;5 mm, are emerging environmental contaminants with potential cardiometabolic relevance. We conducted a cross-sectional analysis of 709 coastal census tracts ( &lt; 200 meters from shoreline) by linking NOAA marine microplastic measurements with chronic disease prevalence estimates from the CDC PLACES database. A total of 154 demographic, socioeconomic, and environmental variables including age, sex, race, median household income, Social Vulnerability Index, insurance coverage, and PM2.5 were incorporated to adjust for confounding. Adjusted Poisson regression models showed that tracts with the highest microplastic exposure had higher prevalence of stroke (PR = 1.21, 95% CI: 1.13–1.29), diabetes (PR = 1.17, 95% CI: 1.10–1.24), and hypertension (PR = 1.10, 95% CI: 1.06–1.14) compared with low-exposure areas. Among all covariates, XGBoost models with SHAP interpretation identified microplastic concentration as an important environmental predictor of stroke prevalence. These ecological findings suggest microplastics were associated with chronic disease patterns and warrant further investigation.</p>

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Marine microplastic concentration and associations with stroke and chronic disease prevalence

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月16日

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  • Sai Rahul Ponnana,
  • El-Hussain Shamsa,
  • Zhuo Chen,
  • Tejas Rajagopalan,
  • Tong Zhang,
  • Santosh Sirasapalli,
  • Skanda Moorthy,
  • Jean-Eudes Dazard,
  • Sadeer Al-Kindi,
  • Salil V. Deo

摘要

Microplastics (MPs), synthetic polymer particles <5 mm, are emerging environmental contaminants with potential cardiometabolic relevance. We conducted a cross-sectional analysis of 709 coastal census tracts ( < 200 meters from shoreline) by linking NOAA marine microplastic measurements with chronic disease prevalence estimates from the CDC PLACES database. A total of 154 demographic, socioeconomic, and environmental variables including age, sex, race, median household income, Social Vulnerability Index, insurance coverage, and PM2.5 were incorporated to adjust for confounding. Adjusted Poisson regression models showed that tracts with the highest microplastic exposure had higher prevalence of stroke (PR = 1.21, 95% CI: 1.13–1.29), diabetes (PR = 1.17, 95% CI: 1.10–1.24), and hypertension (PR = 1.10, 95% CI: 1.06–1.14) compared with low-exposure areas. Among all covariates, XGBoost models with SHAP interpretation identified microplastic concentration as an important environmental predictor of stroke prevalence. These ecological findings suggest microplastics were associated with chronic disease patterns and warrant further investigation.