Familial environment in high- and middle-low-income municipalities: a survey in Italy to understand the distribution of potentially obesogenic factors

Objectives: To explore the familial and social environment in high- and middle-low-income municipalities in Italy to evaluate the distribution of potentially obesogenic factors. A hybrid methodological approach was chosen. A survey of 1215 Italian children was performed to collect information regarding child, family and peer characteristics; additionally, income data were derived from national estimates based on zip codes.

Study design: A cross-sectional study conducted via computer-assisted telephone interviews (CATI).

Methods: A CATI facility was used to interview 1215 Italian children aged 6-10 years. Information regarding family composition; body mass index (BMI) of the child, father and mother; mother's perception of the child's weight; levels of physical activity of the child, father and mother; time spent watching television or playing video games; use of social networks; leisure-time habits; and dietary habits of peers was collected. Income per year per person was obtained from the Italian National Institute of Statistics estimates. Municipalities were divided into two groups: one representing the highest ranking income from the total Italian income distribution, and one representing middle-low incomes. Differences between middle-low-income and high-income groups for child and parent BMIs, social networks, and dietary and leisure-time habits were compared using Wilcoxon and McNemar tests, as appropriate. Multivariate analysis was conducted using logistic regression.

Results: In total, 604 high-income children and 611 middle-low-income children were identified. A significant difference in father's BMI was found between middle-low- and high-income groups: 10.5% of fathers in middle-low-income municipalities were obese, compared with 3.8% in high-income areas (P < 0.001). On the contrary, this analysis found no association between income group and the mother's BMI. In this sample, middle-low-income children participated in less physical activity than high-income children (22.7% vs 34.8% participated in sporting activities for more than 3 h per week, P < 0.001), and spent more time in sedentary activities, such as watching television. However, middle-low-income children were not isolated and were surrounded by a wider social network than high-income children (80.4% vs 69% had more than three friends, P < 0.001).

Conclusions: Significant differences were found in the distribution of obesogenic behaviours between middle-low- and high-income municipalities, suggesting that social factors as well as the physical environment should be considered in the development of health policies and interventions to reduce childhood obesity.