# Child Lung Development Following a Cookstove Intervention: Evidence from GRAPHS

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2024 · $745,160

## 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. A large
proportion of HAP-attributable deaths and DALYs are due to respiratory disease. Establishment of ideal lung
health in childhood is critical to reduce risk for future respiratory disease. We hypothesize that prenatal to age
1 exposure to HAP impairs lung health and programs future disease risk. We further hypothesize that higher
mucin gene expression in response to HAP exposure is a key biological mechanism, and that genotypes that
exhibit a stronger mucin response to HAP are more susceptible to HAP exposure. We propose to build on an
existing pregnancy cohort in Ghana – the Ghana Randomized Air Pollution and Health Study, or GRAPHS – to
assess how prenatal to age one HAP exposure affects lung health through age 13 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:** 10833156
- **Project number:** 5R01ES026991-07
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Darby Jack
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $745,160
- **Award type:** 5
- **Project period:** 2017-07-01 → 2028-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10833156

## Citation

> US National Institutes of Health, RePORTER application 10833156, Child Lung Development Following a Cookstove Intervention: Evidence from GRAPHS (5R01ES026991-07). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10833156. Licensed CC0.

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