Amerta Nutrition (Nov 2024)

Dietary Intake, Lifestyle Factors, and Metabolic Risk: Insights from Health Check-Ups at a Private Healthcare Facility in Coimbatore, India

  • Shanthi Dhandapani,
  • Kamar Afshan,
  • Sesham Shreya,
  • Catherine Lily Vincy,
  • V. Yuvaraj,
  • V. Krithika

DOI
https://doi.org/10.20473/amnt.v8i4.2024.632-641
Journal volume & issue
Vol. 8, no. 4
pp. 632 – 641

Abstract

Read online

Background: Over the last decade (2014–2024), the global prevalence of metabolic risk factors such as dyslipidemia (5-8%), hypertension (5-10%), obesity (10-15%) and elevated blood glucose levels (10-15%) has been steadily increasing. Objectives: To determine the correlation among the dietary consumption, lifestyle factors, and metabolic risk factors among the respondent of age 18-65 years. Methods: The respondent (n=419) were enrolled from August 2023 to February 2024 in Coimbatore, India. The sociodemographic characteristics, dietary intake, stress levels, and physical activity were measured using questionnaires. The respondent’s anthropometry, HbA1c level, blood pressure, and liver function tests were examined, and those with abnormal liver enzymes underwent abdominal ultrasonography for fatty liver diagnosis. The descriptive, Chi square and Kendall’s tau correlation coefficient were performed for statistical analysis. Results: This research showed a weak correlation among protein intake of the respondent and obesity (r=0.084 and p-value=0.026). A significant association was observed among blood pressure range and the consumption of fat (r=0.079, p-value=0.039), protein (r=0.158, p-value<0.001). Correspondingly, the intake of nutrient such as energy (r=0.102, p-value<0.001), carbohydrate (r=0.089, p-value<0.001), and fat (r=0.156, p-value<0.001) was positively correlated with an increased hyperglycaemic risk. Further, energy (r=0.202, p-value<0.001), carbohydrate (r=0.146, p-value<0.001) consumption level had positive correlation with fatty liver disease. Conclusions: A significant positive correlation as observed between and metabolic risk factors and dietary intake. Modifying the interventions to target these risk factors may aid lower the risk of hypertension, obesity, hyperglycaemia, and fatty liver disease in diverse inhabitants.

Keywords