Computerised Algorithms Showed Promise in Identifying Swedish Children With Atypical Growth Patterns

计算机算法在识别具有非典型生长模式的瑞典儿童方面展现出潜力

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Abstract

AIM: We used computerised algorithms comparing the performance of the growth assessment criteria recommended in Sweden with those used in Finland and established by the International Obesity Task Force (IOTF). METHODS: Historical data from 3214 Swedish children (51.6% girls) at 4, 6, and 8 years of age were compared with five Finnish screening parameters: the height standard deviation score (height-SDS), body mass index standard deviation score (BMI-SDS), differences in those over time and deviations from target height. In addition, BMI cut-offs in the Swedish, Finnish, and IOTF growth references were compared. RESULTS: The Finnish screening algorithms identified up to 1.8% of Swedish children with low height-SDS or a negative change in height-SDS, and up to 1.5% with high height-SDS or a positive change in height-SDS. They also identified 26.4% more children with BMI corresponding to underweight, overweight or obesity than the IOTF measure. The Swedish cut-off identified a larger proportion than the Finnish algorithms: 17.4% of boys and 13.6% of girls were short at 4 years of age, while 15.5% of boys and 18.6% of girls were tall. Most children with atypical values were identified by this age. CONCLUSION: Computerised Finnish algorithms could identify Swedish children with atypical growth patterns.

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