# Early life household air pollution, metal composition and cardiovascular health: Evidence from GRAPHS

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2022 · $618,733

## Abstract

Project summary
In low- and middle-income countries ~2.8 billion people are exposed daily to smoke from cooking fires, termed
household air pollution (HAP), resulting in an estimated 2.3M deaths and 91.4M DALYs in 2019. The largest
proportion of HAP-attributable deaths are due to cardiovascular disease. Establishment of cardiovascular
health in childhood is critical to reduce risk for future cardiovascular disease. We hypothesize that early life
(prenatal to age 1) exposure to HAP alters cardiovascular development and programs future disease risk. We
further hypothesize that the metal composition of air pollution drives toxicity. We propose to build on an
existing pregnancy cohort in Ghana – the Ghana Randomized Air Pollution and Health Study, or GRAPHS – to
assess how early life air pollution exposure and metals exposures affect cardiovascular health through age 12
years. We will use well-established, validated methods to assess these outcomes. In the long run, our research
will help build the evidence base for cost effective interventions to improve health by reducing HAP exposure.

## Key facts

- **NIH application ID:** 10504218
- **Project number:** 1R01ES034433-01
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Darby Jack
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $618,733
- **Award type:** 1
- **Project period:** 2022-09-07 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10504218

## Citation

> US National Institutes of Health, RePORTER application 10504218, Early life household air pollution, metal composition and cardiovascular health: Evidence from GRAPHS (1R01ES034433-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10504218. Licensed CC0.

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