Urs Eiholzer1, Chris Fritz2, Anika Stephan2. 1. Center for Paediatric Endocrinology Zurich (PEZZ), Moehrlistrasse 69, CH-8006, Zurich, Switzerland. urs.eiholzer@pezz.ch. 2. Center for Paediatric Endocrinology Zurich (PEZZ), Moehrlistrasse 69, CH-8006, Zurich, Switzerland.
Abstract
BACKGROUND: Novel height, weight and body mass index (BMI) references for children in Switzerland reveal an increase in BMI compared to former percentile curves. This trend may be the result of children with parents originating from Southern European countries having a higher risk of being overweight compared to their peers with parents of Swiss origin. We examined the association of generational, migration-related and socioeconomic factors on BMI in Switzerland and expect the results to lead to more targeted prevention programs. METHODS: From contemporary cross-sectional data, we calculated subgroup-specific BMI percentiles for origin. Results for children of Swiss origin were compared with historical BMI data from Zurich. We tested for the association of overweight and obesity with origin and compared the distributions of BMI percentile ranks. Logistic regression analyses were applied to predict probabilities of being overweight or obese by origin and the Swiss neighborhood index of socioeconomic position (SSEP). RESULTS: Compared to the BMI from two generations ago, the newly calculated BMI increased only slightly for children with both parents from Switzerland; 1.2% of these girls and 1.6% of these boys are obese. In the Swiss population, 13% of the children have parents from Southern Europe and the proportion of obesity is 57 and 42% in these boys and girls, respectively. Their BMI medians correspond to those of their parents' countries of origin. For the probability of being overweight or obese, the SSEP differences are less important than the status of origin. CONCLUSION: We identified children with both parents from Southern Europe as the main influence driving the increase in BMI in Switzerland over the past 50 years. A differentiated consideration of the proportions of various migrant groups within cross-sectional samples is essential when monitoring BMI. Ignoring fluctuations can lead to false conclusions.
BACKGROUND: Novel height, weight and body mass index (BMI) references for children in Switzerland reveal an increase in BMI compared to former percentile curves. This trend may be the result of children with parents originating from Southern European countries having a higher risk of being overweight compared to their peers with parents of Swiss origin. We examined the association of generational, migration-related and socioeconomic factors on BMI in Switzerland and expect the results to lead to more targeted prevention programs. METHODS: From contemporary cross-sectional data, we calculated subgroup-specific BMI percentiles for origin. Results for children of Swiss origin were compared with historical BMI data from Zurich. We tested for the association of overweight and obesity with origin and compared the distributions of BMI percentile ranks. Logistic regression analyses were applied to predict probabilities of being overweight or obese by origin and the Swiss neighborhood index of socioeconomic position (SSEP). RESULTS: Compared to the BMI from two generations ago, the newly calculated BMI increased only slightly for children with both parents from Switzerland; 1.2% of these girls and 1.6% of these boys are obese. In the Swiss population, 13% of the children have parents from Southern Europe and the proportion of obesity is 57 and 42% in these boys and girls, respectively. Their BMI medians correspond to those of their parents' countries of origin. For the probability of being overweight or obese, the SSEP differences are less important than the status of origin. CONCLUSION: We identified children with both parents from Southern Europe as the main influence driving the increase in BMI in Switzerland over the past 50 years. A differentiated consideration of the proportions of various migrant groups within cross-sectional samples is essential when monitoring BMI. Ignoring fluctuations can lead to false conclusions.
Authors: E Cacciari; S Milani; A Balsamo; E Spada; G Bona; L Cavallo; F Cerutti; L Gargantini; N Greggio; G Tonini; A Cicognani Journal: J Endocrinol Invest Date: 2006 Jul-Aug Impact factor: 4.256
Authors: A Cattaneo; L Monasta; E Stamatakis; S Lioret; K Castetbon; F Frenken; Y Manios; G Moschonis; S Savva; A Zaborskis; A I Rito; M Nanu; J Vignerová; M Caroli; J Ludvigsson; F S Koch; L Serra-Majem; L Szponar; F van Lenthe; J Brug Journal: Obes Rev Date: 2009-07-10 Impact factor: 9.213
Authors: A Miranda Fredriks; Stef van Buuren; Sara E R Jeurissen; Friedo W Dekker; S Pauline Verloove-Vanhorick; Jan Maarten Wit Journal: Eur J Pediatr Date: 2003-08-26 Impact factor: 3.183