# Particulate Matter (PM) Metals and Racial Disparity in Cardiovascular (CVD) Risk Factors

> **NIH NIH K01** · FLORIDA INTERNATIONAL UNIVERSITY · 2022 · $175,207

## Abstract

Summary/Abstract
Given the complex composition of pollutants such as particulate matter PM in the environment, it is
believed that our exposure is not limited to one chemical at a time but to several possible mixtures with
varying composition and mix ratios. These mixtures could be formed because they are emitted at the
same time from the same source origin as latent factors. As a result, humans are more susceptible to
exposure to these mixtures as characterized by these latent factors. Factor analysis is one tool used in
the literature to define mixtures. Unfortunately statistical methods of identifying mixtures are limited.
Additionally, exposure to PM chemicals during pregnancy is known to be harmful to both mother and
child. To address the problem a new method of identifying mixtures exposure based on extension of the
traditional factor analysis combined with source apportionment methods will be used. This proposal will
test the following hypothesis: Hypothesis 1: Exposure to PM mixture metals during pregnancy increased
the risk of cardiovascular disease (CVD) risk factors among black and Hispanic minorities and vary by
trimester. Hypothesis 2: CVD risk factors are mediators between PM metals exposure and child
development, through the following Aims. 1) Quantify mixtures and estimate mother's exposure during
various trimesters of pregnancy. We will use the newly developed Bayesian extended factor analysis
(FA), based on the flexibility of Bayesian statistics and the decomposition of the error covariance matrix
combined with SAM models to estimate metal mixtures. We will perform a spatio-temporal analysis of
the mixtures using Generalized Additive Mixed Models(GAMM). We will use the inverse distance
weighting method to estimate mother's inhaled quantities during each trimester of pregnancy. 2)
Investigate CVD risk factors difference among black and white and interaction between air pollution and
race/ethnicity by trimester. We will use logistic regression analysis and generalized spatial linear model
for this aim. 3) Investigate CVD risk factors moderating between mixture metals exposure and infant
mortality. We will use structural equation modeling (SEM) to investigate wich risk factors is in the
pathway between exposure and child mortality. Results from the proposed studies could have
implications in identifying mixtures exposures, their chemical toxicity and relative implication in CVD
during pregnancy.

## Key facts

- **NIH application ID:** 10329979
- **Project number:** 5K01HL146944-03
- **Recipient organization:** FLORIDA INTERNATIONAL UNIVERSITY
- **Principal Investigator:** Boubakari Ibrahimou
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $175,207
- **Award type:** 5
- **Project period:** 2020-02-17 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10329979

## Citation

> US National Institutes of Health, RePORTER application 10329979, Particulate Matter (PM) Metals and Racial Disparity in Cardiovascular (CVD) Risk Factors (5K01HL146944-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10329979. Licensed CC0.

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