Dietary Factors and Cardiovascular Disease Among Young Adults, Ages 20–40

A pooled NHANES 2011 to 2018 analysis of dietary and clinical predictors of CVD

Damian Job Kahamba, MPH�Epidemiology and Biostatistics�College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health�Florida Agricultural and Mechanical University

Florida A&M University • College of Pharmacy and Pharmaceutical Sciences • Institute of Public Health

Introduction

Young adult cardiovascular risk is often overlooked.

1 in 5

U.S. deaths

attributable to cardiovascular disease annually

20 to 40

Age range studied

the NHANES sample used in this analysis

Diet

Modifiable exposure

addressable early, before midlife disease sets in

Why now: The Bogalusa Heart Study and the PDAY study both show atherosclerotic plaque forming as early as adolescence, driven by the lifestyle and dietary patterns set in young adulthood. Stroke rates among adults 20 to 44 nearly doubled from 1993 to 2015 (from 17 to 28 per 100,000), yet most CVD risk tools, including the Framingham and Pooled Cohort Equations, were developed and validated for older adults. This gap is why we asked: which dietary and clinical factors are associated with CVD among U.S. adults aged 20 to 40?

Florida A&M University • College of Pharmacy and Pharmaceutical Sciences • Institute of Public Health

Methods

Pooled NHANES 2011 to 2018 (4 cycles) — how the analytic sample was built

4 Cycles

Pooled NHANES Sample

2011 to 2018 continuous NHANES, domain defined to ages 20 to 40

6,903

Descriptive Sample

non-missing CVD status and dietary survey weight (WTDRD1)

2,538

Multivariable Sample

complete data across all 16 predictors (36 CVD-positive cases)

Candidate Predictors Assessed (16 total)

Continuous (7)�Age, Sodium Ratio, Cholesterol Ratio, Saturated Fat Ratio, Unsaturated Fat Ratio, Fiber Ratio and HbA1c

Categorical (9)�Smoking Status, Diabetes Status, Kidney Disease, Sleep Disorder, Physical Activity, Alcohol Use, BMI Category, Gender, and Race/Ethnicity

Analysis & Weighting: We calculated weighted descriptive statistics (SURVEYMEANS/SURVEYFREQ), then tested each predictor against CVD status using SURVEYREG (continuous) and Rao-Scott chi-square (categorical). All 16 predictors were entered into a multivariable logistic regression (PROC SURVEYLOGISTIC) in SAS Studio. Every model incorporated NHANES's stratum (SDMVSTRA), cluster (SDMVPSU), and pooled dietary weight (WTDRD1 ÷ 4) to generalize estimates to the U.S. population.

Florida A&M University • College of Pharmacy and Pharmaceutical Sciences • Institute of Public Health

Key Findings

Multivariate logistic regression, n = 2,538 (36 CVD cases)

1.31%

CVD prevalence

weighted prevalence, U.S. adults 20 to 40 (~87.7M people)

#1

Dietary fiber

strongest bivariate predictor of CVD (p < 0.0001)

4.3×

Kidney disease

higher odds of CVD (95% CI 1.34–13.90, p = 0.015)

5.3×

Diabetes

higher odds of CVD (95% CI 1.04–26.88, p = 0.045)

3.2×

Non-Hispanic Black adults

higher odds vs. non-Hispanic White (p = 0.019)

Florida A&M University • College of Pharmacy and Pharmaceutical Sciences • Institute of Public Health

Limitations & Next Steps

Why a validated predictive model wasn't feasible with this sample

Key Limitations

• Cross-sectional design cannot establish causality or temporal order between diet and CVD
• Self-reported CVD status is subject to recall bias and likely underdiagnosis
• Small event count. There were only 36 CVD cases across 16 predictors

Toward a Predictive Model

The goal: Translate these associations into a public-facing CVD probability calculator for young adults.��Limitation: Small sample size of CVD-positive cases (n=36) led to quasi-complete separation; thus, effect estimates for the continuous dietary variables were unreliable (CIs extremely wide/unbounded).��Next step: a larger, adequately powered, ideally longitudinal sample is needed before a validated predictive tool can be deployed with confidence.

Florida A&M University • College of Pharmacy and Pharmaceutical Sciences • Institute of Public Health

Thank You

Student�Damian Job Kahamba, MPH�Epidemiology & Biostatistics

Institute of Public Health�Florida A&M University��damian1.kahamba@famu.edu�kjobdamian@gmail.com | 850.300.3550

Faculty Advisor�Sarah Buxbaum, Ph.D.�Associate Professor of Biostatistics�Institute of Public Health�Florida A&M University��sarah.buxbaum@famu.edu�Direct: 850.412.5494

Florida A&M University • College of Pharmacy and Pharmaceutical Sciences • Institute of Public Health