# Assessment of Policies through Prediction of Long-term Effects on Cardiovascular Disease Using Simulation (APPLE CDS)

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2020 · $897,090

## Abstract

Project Summary/Abstract
Dietary behaviors are key modifiable risk factors in averting cardiovascular disease (CVD), the leading cause
of morbidity, mortality, and disability in the United States (US). Despite national and local initiatives to promote
healthy dietary behaviors, unhealthy diets remain a difficult, perplexing population health problem requiring
initiatives and solutions at the community and population levels. Prior to investing in implementation, health
practitioners and policymakers—often working with limited resources—need to compare the population health
impact of different food policies and programs to then determine priorities. The goal of this project,
Assessment of Policies through Prediction of Long-term Effects on Cardiovascular Disease Using
Simulation (APPLE CDS), is to compare the effects of food policies and programs on CVD-related outcomes
and health care costs for adults. This will be useful to aid local government and community organizations in
priority setting and decision-making. Policy and program assessment will be conducted using agent-based
modeling, an efficient, novel technique that has been underutilized in public health research. We assembled a
team of experts in CVD, nutrition, public health, health economics, and computer simulation modeling who are
committed to working together to identify realistic pathways that can be used to improve dietary behaviors. The
Specific Aims are to: (1) develop an agent-based model to assess and compare the impact of alternative food
policies and programs on dietary behaviors, blood pressure, body mass index (BMI), and diabetes across
different neighborhoods in NYC and (2) link the agent-based model with the well-established, validated NYC
CVD Policy Model to project the long-term impact of different food policies and programs on cardiovascular
disease outcomes (e.g., hypertension, coronary heart disease, stroke), quality-adjusted life years (QALYs),
and health care costs. We will leverage the rich community-level health data on dietary behaviors collected by
the NYC Department of Health and Mental Hygiene (DOHMH) to parameterize and validate the model. In
addition, our close partnerships with the NYC DOHMH and a broad range of community-based organizations
across the city will ensure that simulation results will be used to select and optimize implementation of the most
cost-effective, neighborhood-specific food policies and programs to improve population health. Finally, the
NYC experience can serve as an example by which other local health departments and community-based
organizations may make more informed decisions for their own priority setting and program implementation.

## Key facts

- **NIH application ID:** 10089006
- **Project number:** 7R01HL141427-03
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Yan Li
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $897,090
- **Award type:** 7
- **Project period:** 2018-08-15 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10089006

## Citation

> US National Institutes of Health, RePORTER application 10089006, Assessment of Policies through Prediction of Long-term Effects on Cardiovascular Disease Using Simulation (APPLE CDS) (7R01HL141427-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10089006. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*