Youth-Led Public Health Research · Santa Clara County
A data-driven analysis of obesity disparities across 370 census tracts reveals a stark east-west divide — and a roadmap for closing it.
Source: CDC PLACES 2025 · ACS 2019–2023 · Random Forest Model (Test R² = 0.96)
Using CDC PLACES 2025 data and machine learning across 370 census tracts, this research identifies the strongest predictors of obesity at the neighborhood level — and where the greatest need for intervention lies.
Depression, smoking, and housing insecurity predict obesity better than race, income, or education — even when both sets of factors are given to the model together. Mental health is an obesity intervention, not a separate concern.
SHAP Analysis · Random ForestAn east/west fault line runs through the county. East San Jose, Alum Rock, Gilroy, and Morgan Hill carry the highest burden. Cupertino, Saratoga, and the Palo Alto corridor sit at the bottom — a roughly 5× gap in composite risk scores.
Composite Risk Score · 370 TractsTracts with the highest obesity have the lowest checkup and cholesterol screening rates. The communities that need preventive care most are getting it least — a critical equity finding with direct policy implications.
Care Gap · Equity FindingThe composite risk score — combining RF prediction, depression, smoking, housing insecurity, and care gaps — identifies where intervention resources are most urgently needed.
Whether you lead a community organization, shape public policy, or cover public health — there is a role for you in this work.
Community Organizations & Nonprofits
The composite risk score and city-level findings give community organizations a defensible, data-driven tool to prioritize neighborhoods and justify resource allocation in grant applications and program design.
Request the data package →Government & Policymakers
The research supports targeted investment in mental health access, housing stability, and preventive care in the highest-burden tracts. A policy brief is available for city and county stakeholders.
Request the policy brief →Media & Press
A high school researcher using machine learning to expose a 5× health gap between East and West San Jose — and connecting the dots to depression, housing, and preventive care access. A press kit is available on request.
Request the press kit →Henri Smit is a junior at Crystal Springs Uplands School in Hillsborough, CA, with a deep passion for healthcare, public health, and the power of data to drive meaningful change in underserved communities.
This research grew out of Henri's role on the Youth Action Committee at Sacred Heart Community Service and his belief that data literacy is one of the most powerful tools available to the next generation of community advocates.
Whether you are a community organization, a policymaker, a journalist, or simply someone who cares about health equity in Santa Clara County — we would love to hear from you.