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新西兰儿童肥胖预测模型。

A prediction model for childhood obesity in New Zealand.

机构信息

A Better Start-National Science Challenge, Auckland, New Zealand.

Liggins Institute, University of Auckland, Auckland, New Zealand.

出版信息

Sci Rep. 2021 Mar 18;11(1):6380. doi: 10.1038/s41598-021-85557-z.

Abstract

Several early childhood obesity prediction models have been developed, but none for New Zealand's diverse population. We aimed to develop and validate a model for predicting obesity in 4-5-year-old New Zealand children, using parental and infant data from the Growing Up in New Zealand (GUiNZ) cohort. Obesity was defined as body mass index (BMI) for age and sex ≥ 95th percentile. Data on GUiNZ children were used for derivation (n = 1731) and internal validation (n = 713). External validation was performed using data from the Prevention of Overweight in Infancy Study (POI, n = 383) and Pacific Islands Families Study (PIF, n = 135) cohorts. The final model included: birth weight, maternal smoking during pregnancy, maternal pre-pregnancy BMI, paternal BMI, and infant weight gain. Discrimination accuracy was adequate [AUROC = 0.74 (0.71-0.77)], remained so when validated internally [AUROC = 0.73 (0.68-0.78)] and externally on PIF [AUROC = 0.74 [0.66-0.82)] and POI [AUROC = 0.80 (0.71-0.90)]. Positive predictive values were variable but low across the risk threshold range (GUiNZ derivation 19-54%; GUiNZ validation 19-48%; and POI 8-24%), although more consistent in the PIF cohort (52-61%), all indicating high rates of false positives. Although this early childhood obesity prediction model could inform early obesity prevention, high rates of false positives might create unwarranted anxiety for families.

摘要

已经开发出了几种儿童期肥胖预测模型,但没有一种适用于新西兰多样化的人群。我们的目的是利用新西兰儿童成长研究(Growing Up in New Zealand ,Guinz )队列中的父母和婴儿数据,开发和验证一种预测新西兰 4-5 岁儿童肥胖的模型。肥胖定义为体重指数(BMI)年龄和性别≥95 百分位数。Guinz 儿童的数据用于推导(n=1731)和内部验证(n=713)。使用超重预防婴儿研究(POI)和太平洋岛屿家庭研究(PIF)队列的数据进行外部验证(n=383 和 n=135)。最终模型包括:出生体重、母亲孕期吸烟、母亲孕前 BMI、父亲 BMI 和婴儿体重增加。区分准确性足够高[AUROC=0.74(0.71-0.77)],内部验证时仍然如此[AUROC=0.73(0.68-0.78)],在 PIF 上验证时也仍然如此[AUROC=0.74(0.66-0.82)]和 POI [AUROC=0.80(0.71-0.90)]。阳性预测值在风险阈值范围内变化,但都很低(Guinz 推导为 19-54%;Guinz 验证为 19-48%;POI 为 8-24%),尽管在 PIF 队列中更一致(52-61%),这表明存在大量假阳性。尽管这种儿童期肥胖预测模型可以为早期肥胖预防提供信息,但高比例的假阳性可能会给家庭带来不必要的焦虑。

相似文献

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A prediction model for childhood obesity in New Zealand.新西兰儿童肥胖预测模型。
Sci Rep. 2021 Mar 18;11(1):6380. doi: 10.1038/s41598-021-85557-z.
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