Association between socially disadvantaged groups and metabolics syndrome in European children. Results from the IDEFICS study

Abstract

Introduction The metabolic syndrome (MetS) is an important cluster of cardiovascular disease risk factors. MetS is diagnosed if at least three of the four components, namely visceral obesity, dyslipidaemia, hyperglycaemia, and hypertension, exceed certain cut-off values, where the cut-offs vary depending on sex, age and the proposed definition. Social disadvantages in early life are hypothesized to have negative implications for health through potentially modifiable lifestyle (such as diet, physical activity and sedentary behaviours). Classical socioeconomic status (SES) indicators such as parental education or income have been found to be associated with MetS in adults. The extent to which the accumulation of these disadvantages and other social disadvantages can affect children's MetS risk is still unknown. Methods In the IDEFICS study, 16,228 children aged 2.0–9.9 years from eight European countries were examined at baseline and after 2-years of follow-up and 2401 of these children were eligible for this analysis. Sociodemographic variables, children's well-being score and lifestyle factors were reported by parents via questionnaires. Six socially disadvantaged groups were defined, including two low socioeconomic status groups (children whose parents had a low education and who had low-income) and four social vulnerable groups (children whose parents were migrants, children whose parents lack a social network, children from non-traditional families and children with unemployed parents). MetS risk was assessed through z-score standardization of the 4 components assessed using the following variables: waist circumference, blood pressure (mean of systolic and diastolic), blood lipids (mean of triglycerides and inverse HDL levels) and insulin resistance (homeostasis model assessment, HOMA-IR). Linear mixed effects models were used to study the association between: –social disadvantages and children's total MetS score at baseline and follow-up; –patterns of social disadvantages over time and children's total MetS score at follow-up; –accumulation of social disadvantages and children's total MetS score at baseline and follow-up. Models were adjusted for sex, age, and education and income for social vulnerable groups. In a second step, models were additionally adjusted for children's well-being score and lifestyle factors (fruit and vegetables consumption, physical activity, screen time) to assess whether social disadvantages have an effect independent of lifestyle factors on the metabolic risk. Results Children from low-income families at both time points (0.20 [0.03; 0.37]; β estimate and 99% confidence interval), children from non-traditional families at both time points (0.14 [0.02; 0.26]), children whose parents were unemployed at baseline and follow-up (0.31 [0.05; 0.57]) and children who accumulated more than 3 vulnerabilities (0.21 [0.04; 0.37]) showed a significantly higher MetS score compared to non-vulnerable groups. Conclusions Social disadvantages in children have been found to be related with a higher metabolic risk independently of diet, physical activity, sedentary behaviours and well-being. Interventions that focus on these socially disadvantaged groups should be developed to tackle health disparities.