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July 5, 2026Open Access

A Risk Score Model to Support Early Identification and Prevention of Type 2 Diabetes Incorporating Social Determinants of Health

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Why the study?

Can a risk score model incorporating social determinants of health and clinical factors predict Type 2 Diabetes?

Population

3,000 individuals from the CDC 2015 Behavioral Risk Factor Surveillance System dataset

Design

Other

Key result

A risk score model incorporating social determinants of health alongside clinical factors successfully identified predictors of Type 2 Diabetes.

Authors

DSDr. Kajal Rameshbhai Solanki

Discussion

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Overview

May inform diabetes risk models with social determinants; leaves open prospective validation before guiding prevention.

Key Points

  • The study aims to develop a predictive risk score model for early identification and prevention of Type 2 Diabetes by incorporating social determinants of health.
  • Utilized CDC 2015 Behavioral Risk Factor Surveillance System dataset (n=3000) divided into training (n=2700) and testing (n=300) datasets.
  • Applied various algorithms including Random Forest, SVM, Logistic Regression, Gradient Boosting, and XGBoost with 10-fold cross-validation.
  • Identified predictors of Type 2 Diabetes using logistic regression to generate a risk score incorporating clinical and social factors.
  • Identified significant positive predictors for Type 2 Diabetes including BMI, Age, and sex.
  • Emerging risk factors like higher income and access to healthcare were associated with lower predicted risk.
  • Demonstrated the risk score model's predictive power for targeted screening and preventive interventions.

Study Design

Type

Observational (n=3,000)

Structured PICO

Can a risk score model incorporating social determinants of health and clinical factors predict Type 2 Diabetes?

P
Population
3,000 individuals from the CDC 2015 BRFSS dataset used to develop and test a risk score model for Type 2 Diabetes.
E
Exposure
Logistic regression-based risk score model incorporating social determinants of health (SDOH) and clinical risk factors
O
Outcome
Prediction of Type 2 Diabetes (T2DM)

A logistic regression-based risk score incorporating social determinants of health alongside traditional clinical factors can effectively predict Type 2 Diabetes risk.

Cite This Study

Dr. Kajal Rameshbhai Solanki (2026) conducted an observational in Type 2 Diabetes (n=3,000). Risk score model incorporating social determinants of health was evaluated on Predictors of Type 2 Diabetes. A risk score model incorporating social determinants of health alongside clinical factors successfully identified predictors of Type 2 Diabetes.

synapsesocial.com/papers/6a49f68df5d1d45b28800e9dhttps://doi.org/10.5281/zenodo.21167435
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Machine Learning Model for Predicting the Risk of Developing Diabetes - T2DM Using Real-World Data from Kilifi, Kenya2025
  2. 2AI-driven analysis of diabetes risk determinants in U.S. adults: Exploring disease prevalence and health factors2025 · 1 citations
  3. 3Empowering Preventive Healthcare: Machine Learning-Based Diabetes Risk Screening Using Survey Data2025 · 1 citations
  4. 4Exploring Explainable Machine Learning for Predicting and Interpreting Self-Reported Diabetes among Tennessee Adults: Insights from the 2023 Behavioral Risk Factor Surveillance System (BRFSS)2025 · 7 citations
  5. 5A machine learning model for predicting obesity risk in patients with diabetes mellitus: analysis of NHANES 2007–20182025 · 2 citations