# Project 1: Addressing Sleep Duration, Regularity, and Efficiency: A Multidimensional Sleep Health Intervention for Reducing Ethnic Disparities in Cardiometabolic Health (The DREAM Study)

> **NIH NIH P50** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2021 · $697,044

## Abstract

ABSTRACT:
Cardiovascular disease (CVD) and cancer, the leading causes of mortality in Latinx, share many risk factors,
including cardiometabolic risk factors. Latinx have some of the highest prevalence rates for obesity and type 2
diabetes (T2D), and in New York City, one of the highest hypertension (HTN) burdens. Improving multiple
domains of cardiometabolic health (CMH) through contextual behavioral interventions can have far-reaching
effects for reducing the burden of multiple morbidities. Despite a strong evidence base supporting the role of
sleep as a major contributor to CMH, including work by our team, most lifestyle interventions have targeted diet
or physical activity and not sleep. Sleep is amenable to intervention, and can improve CMH through
complementary or synergistic biologic pathways with other lifestyle factors. Insufficient, irregular, and poor
quality sleep is widely prevalent, affecting >50% of US adults with a disproportionately higher burden in racial
and ethnic minorities, and sleep health disparities have been shown to account for a large portion of racial and
ethnic disparities in CMH. We will conduct community engagement and stakeholder participatory research to
refine and culturally adapt a multidimensional sleep health (MDSH) intervention for Latinx adults (Aim 1). Using
a parallel two-arm randomized controlled trial (RCT) design, we will evaluate the effect of the MDSH
intervention on improving blood pressure (BP), glycemic control indicators, and anthropometric markers of
adiposity (Aim 2). We will enroll 300 midlife to older Latinx men and women at high risk for multiple chronic
diseases, identified through the New York-Presbyterian Hospital cancer screening centers, and randomize to
either a control arm that receives standard Life's Simple 7 cardiovascular health educational materials or
an intervention arm that, in addition to Life's Simple 7 materials, receives a MDSH intervention based on
evidence-based sleep hygiene education and established behavior change techniques (personalized sleep
health feedback, goal setting, self-monitoring, motivational enhancement). We will further leverage this RCT to
explore the effect of sleep on markers of systemic inflammation that are related to both CVD and cancer
risk. Finally, using the Consolidated Framework for Implementation Research and working closely with the
COMMUNITY Center Implementation Science Core, we will use mixed methods to understand implementation
determinants, processes, and outcomes, ensuring the successful completion and future expansion of this work
(Aim 3). Community health workers, with experience working with the NYC Latinx communities, will deliver the
intervention, and we will assemble a community and stakeholder collaborative panel, with support from the
COMMUNITY CONNECTOME, that will actively participate in all aspects of the aims. Findings will inform the
development and implementation of scalable and sustainable personalized population health ...

## Key facts

- **NIH application ID:** 10437180
- **Project number:** 1P50MD017341-01
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Nour Makarem
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $697,044
- **Award type:** 1
- **Project period:** 2021-09-24 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10437180

## Citation

> US National Institutes of Health, RePORTER application 10437180, Project 1: Addressing Sleep Duration, Regularity, and Efficiency: A Multidimensional Sleep Health Intervention for Reducing Ethnic Disparities in Cardiometabolic Health (The DREAM Study) (1P50MD017341-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10437180. Licensed CC0.

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