A generalizable framework for the development of a Continuous Metabolic Syndrome Risk Score in small populations. - PROJECT SUMMARY We aim to develop a continuous metabolic syndrome (cMS) risk score by integrating traditional clinical risk factors for metabolic syndrome (MetS) with indicators of household socioeconomic well-being (including annual income, food security, and household size), behavioral factors (e.g., tobacco use), stress levels, and cultural resilience or protective factors. This effort will utilize advanced statistical modeling techniques applied to clinical research data from a Yup’ik Alaska Native study population. Heart disease remains the leading cause of death among Alaska Native men and ranks second, after cancer, for women and the Alaska Native population overall. Among Yup’ik people, heart disease mortality is 30% higher than the national average across all racial groups. Traditional binary MetS criteria fall short in capturing gradual shifts in disease risk, limiting opportunities for early preventive health interventions. In contrast, a cMS risk score provides a clinically meaningful metric that is sensitive to subtle changes in an individual’s health status over time, offering a more precise assessment of cardiometabolic disease risk. The study has two primary objectives: (1) To develop and validate a sex-specific cMS risk score using standard MetS components (waist circumference, blood pressure, fasting plasma glucose, triglycerides, and HDL-cholesterol) for the Yup’ik population; and (2) To evaluate whether the predictive power of the cMS score improves with the inclusion of additional established cardiometabolic risk factors (non-HDL-C, TC/HDL-C and LDL-C/HDL-C ratios, hemoglobin A1c), socioeconomic indicators, behavioral factors, stress measures, and cultural resilience factors such as speaking Yup’ik and following a traditional Yup’ik way of life. Cardiometabolic health determinants in small populations remain underexplored, where clinical, social, and cultural dimensions, including resilience, play a critical role. This study will be the first to jointly model both risk and protective factors in constructing the cMS score, providing a generalizable framework for developing tailored cMS risk scores for other populations that reflect their unique risk and protective health profiles.
