OBESITY AND ITS IMPACT ON METABOLIC HEALTH: PATTERNS, DETERMINANTS, AND ASSOCIATED COMORBIDITIES

Abstract

Obesity is an emerging population health issue that is linked to poor metabolic health consequences and heightened risk of obesity-related comorbidities. This paper has analyzed patterns of obesity, determinants and metabolic health risk indicators using the Estimation of Obesity Levels Based On Eating Habits and Physical Condition dataset on the UCI Machine learning Repository. A quantitative cross-sectional research design was applied on the basis of secondary data of 2,111 participants at Mexico, Peru and Colombia. The outcome variable was the level of obesity which was categorised into seven groups whereas the independent variables were classified into demographic, anthropometric, dietary, behavioural, lifestyle and family-history variables. The distribution of obesity and the determinants were evaluated using descriptive statistics, comparative analysis, chi-square tests and binary logistic regression. The findings indicated that 46.57% of the respondents were obese. The progress of BMI and body weight in obesity categories confirmed the existence of a strong anthropometry pattern. Family history with overweight was identified as the strongest predictor of obesity and frequent consumption of high-caloric foods, food consumption between meals, passive transportation, alcohol use, and low calorie-consumption monitoring were also found to be important indicators of obesity-related risk factors. Protective associations were observed between physical activity and monitoring calories. Metabolic health and comorbidity implications were determined by the severity of obesity and lifestyle related risk factors. The results indicate that there is a need to have integrated obesity prevention strategies that emphasize on the regulation of the dietary intake, active living, awareness on the prevention of obesity at the family level, and behavioural self-monitoring.