Self-reporting and measurement of body mass index in adolescents: refusals and validity, and the possible role of socioeconomic and health-related factors

BACKGROUND: Body mass index assessment using self-reported height and weight (BMIsr) can encounter refusals and under/over-reporting while for assessment with measured data (BMIm) refusals can be more frequent. This could relate to socioeconomic and health-related factors. We explored these issues by investigating numerous potential factors: gender, age, family structure, father’s occupation, income, physical/sports activity, subjective weight perception, school performance, unhealthy behaviours, physical/psychological health, social relationships, living environment, having sustained violence, sexual abuse, and involvement in violence. METHODS: The sample included 1559 adolescents from middle schools in north-eastern France. They completed a questionnaire including socioeconomic and health-related data, self-reported height/weight, measured height/weight, and weight perception (participation rate 94%). Data were analysed using logistic regression models. RESULTS: BMIsr encountered under-reporting (with change in BMI category, 11.8%), over-reporting (6.0%), and reporting refusals (3.6%). BMIm encountered more numerous refusals (7.9%). Reporting refusal was related to living with a single parent, low school performance, lack of physical/sports activity, sustained violence, poor psychological health, and poor social relationships (gender/age-adjusted odds ratios 1.95 to 2.91). Further to these factors, measurement refusal was related to older age, having divorced/separated parents, a father being a manual worker/inactive, insufficient family income, tobacco/cannabis use, involvement in violence, poor physical health, and poor living environment (1.30 to 3.68). Under-reporting was related to male gender, involvement in violence, poor psychological health, and overweight/obesity (as assessed with BMIm) (1.52 to 11). Over-reporting was related to male gender, younger age, alcohol consumption, and underweight (1.30 to 5.35). Weight perception was linked to reporting refusals and under/over-reporting, but slightly linked to measurement refusal. The contributions of socioeconomic and health-related factors to the associations of weight perception with reporting refusal and under/over-reporting ranged from −82% to 44%. There were substantial discrepancies in the associations between socioeconomic/health-related factors and overweight/obesity assessed with BMIsr and BMIm. CONCLUSIONS: BMIsr and BMIm were affected by numerous biases related to vulnerability which were also obesity risk factors. BMIsr encountered under/over-reporting which were related to some socioeconomic and health-related factors, weight perception, and BMIm. BMIm was more affected by refusals than BMIsr due to socioeconomic and health-related factors. Further research is needed.