The relationships between dietary patterns and socioeconomic status with anthropometric and body composition indices in Iranian preschool children: A cross‐sectional study

Abstract

Abstract Background The prevalence of overweight and obesity among Iranian children is on the rise. Dietary patterns (DPs) and socioeconomic status ( socioeconomic status (SES)) may relate to children's excess weight as a predictor of the risk of obesity in adulthood that may vary by geographical regions. Aim The relationship between DPs and the development of obesity in preschool children has not been adequately evaluated. The present study evaluates this relationship by considering SES. Methods A total of 320 preschool children (4–6 years) were randomly selected from three different areas of Mashhad based on economic status. Dietary intake was evaluated using a semi‐quantitative food frequency questionnaire completed by the children's parents. Anthropometric and body composition variables were measured by means of valid tools and standard methods. socioeconomic status data were collected through a researcher‐made questionnaire. Results Three dominant DPs of ‘healthy’, ‘unhealthy’, and ‘meat‐free’ were identified using factor analysis. The prevalence of overweight and obesity among the children who followed meat‐free DP was significantly higher than that of other children (p = 0.004). The means and standard deviations of energy intake, body mass index (BMI), waist circumference, fat‐free mass, and fat mass were 1187.97 ± 356.87 Kcal/day, 16.23 ± 2.28 kg/m2, 54.28 ± 6.49 cm, 16.24 ± 2.23 kg, and 4.62 ± 2.70 kg respectively. Being in the higher levels of SES was significantly related to height (p = 0.02), energy intake (p < 0.001), BMI (p = 0.003), waist circumference (p = 004), and fat mass (p = 0.002). Conclusions Adherence to meat‐free DP and being in the highest levels of SES may be associated with a greater chance of developing overweight and obesity. Therefore, meat consumption and SES can be used to predict childhood overweight and obesity.

Keywords

• anthropometry
• dietary pattern
• socioeconomic status
• statistical factor analyses