More rapid increase in BMI from age 5-15 is associated with elevated weight status at age 24 among non-Hispanic white females

Tracking changes in weight status in primary school children in Birmingham: an analysis of the National Child Measurement Programme - a retrospective cohort study

One-in-four 4-5 years and more than one-in-three 10-11 years have excess weight in England.

AIM

To identify characteristics associated with (1) having overweight, obesity and severe obesity at 11 years and (2) rapid weight gain (defined as increasing weight status by one or more body mass index (BMI) categories) between the ages of 4-5 and 10-11 years.

METHOD

Using National Child Measurement Programme data, BMI at reception (4-5 years) and year 6 (10-11 years) were linked for 15 390 children. Weight categories were identified at both time points using BMI centile classifications.For each child, the number of BMI categories they crossed between reception and year 6 was identified. Logistic regression models were fitted to explore associations with sociodemographic characteristics of children with excess weight at age 10-11 years and with children experiencing rapid weight gain between reception and year 6.

RESULTS

Overall, 61.9% of children remained in their original weight category; 30% whose weight increased by ≥1 weight categories and 11.7% by ≥2 weight categories. Only 7.8% had decreased ≥1 weight categories and 0.9% had decreased ≥2 weight categories.Adjusting for other sociodemographic characteristics, girls were less likely than boys to increase ≥2 weight categories between reception and year 6 (OR 0.64; 95% CI 0.58 to 0.71; p<0.001). Compared to white children, Asian and mixed-ethnicity children had higher odds of rapid weight gain. Children with the highest deprivation were over 6 times more likely to increase ≥2 weight categories between reception and year 6 compared with children with the lowest deprivation (OR 6.1; 95% CI 1.92 to 19.10; p<0.01).

CONCLUSION

Male children, children of Asian and mixed ethnicity and children with high deprivation are at higher risk of rapid weight gain and should be targeted for intervention.

A novel systematic pipeline for increased predictability and explainability of growth patterns in children using trajectory features

OBJECTIVE

Longitudinal patterns of growth in early childhood are associated with health conditions throughout life. Knowledge of such patterns and the ability to predict them can lead to better prevention and improved health promotion in adulthood. However, growth analyses are characterized by significant variability, and pattern detection is affected by the method applied. Moreover, pattern labelling is typically performed based on ad hoc methods, such as visualizations or clinical experience. Here, we propose a novel pipeline using features extracted from growth trajectories using mathematical, statistical and machine-learning approaches to predict growth patterns and label them in a systematic and unequivocal manner.

METHODS

We extracted mathematical and clinical features from 9577 children growth trajectories embedded with machine-learning predictions of the growth patterns. We experimented with two sets of features (CAnonical Time-series Characteristics and trajectory features specific to growth), developmental periods and six machine-learning classifiers. Clinical experts provided labels for the detected patterns and decision rules were created to associate the features with the labelled patterns. The predictive capacity of the extracted features was validated on two heterogenous populations (The Applied Research Group for Kids and the 2004 Pelotas Birth Cohort, based in Canada and Brazil, respectively).

RESULTS

Features predictive ability measured by accuracy and F1 score was ≥ 80% and ≥ 0.76 respectively in both cohorts. A small number of features (n = 74) was sufficient to distinguish between growth patterns in both cohorts. Slope, intercept of the trajectory, age at peak value, start value and change of the growth measure were among the top identified features.

CONCLUSION

Growth features can be reliably used as predictors of growth patterns and provide an unbiased understanding of growth patterns. They can be used as tool to reduce the effort to repeat analysis and variability concerning anthropometric measures, time points and analytical methods, in the context of the same or similar populations.

A synthesis of early antecedents of eating behavior and weight status in girls: The legacy of girls' NEEDS project

Dr. Leann Birch, an innovator in the field of children's eating behavior, was the first scientist to synergize the fields of developmental psychology and nutrition science. One of Leann's groundbreaking projects was the Girls' NEEDS Project (GNP), an NIH-funded observational study of the longitudinal development of eating and weight-related behaviors of girls across middle childhood and adolescence. At the time of GNP, obesity prevalence during childhood had roughly doubled during the previous two decades, research interest in dieting had increased as societal expectations of the 'thin ideal' got even thinner, and little was known about how environmental factors such as parenting influenced the development of maladaptive eating and weight-related behaviors. GNP resulted in over 70 publications, covering a range of topics from girls' dietary intake and physical activity to parental influences on girls' eating behavior, thus laying the groundwork for many topics in the obesity, food parenting, and dieting literature today. Therefore, this narrative review aims to summarize and synthesize the literature that resulted from the GNP and provide implications for future work building from this foundation.

Using Latent Class Growth Modeling to Examine Longitudinal Patterns of Body Mass Index Change from Adolescence to Adulthood

BACKGROUND

Few studies use longitudinal designs to assess patterns of body mass index (BMI) change from adolescence to adulthood or incorporate severe obesity as a unique subgroup.

OBJECTIVE

To examine patterns of BMI trajectories from adolescence to adulthood and identify demographic characteristics associated with each BMI trajectory pattern.

DESIGN

Height, weight, and demographic characteristics were drawn from Waves I to V of the nationally representative school-based sample of the National Longitudinal Study of Adolescent to Adult Health (Add Health) conducted from 1994 to 2018 (data collection is ongoing).

PARTICIPANTS/SETTING

Participants included 3,315 (55.5% female) subjects responding to in-home interviews across all five Waves of Add Health.

MAIN OUTCOME MEASURES

BMI at each wave modeled over time.

STATISTICAL ANALYSES

Latent class growth modeling and logistic regression analysis using population sample weights.

RESULTS

Five classes of weight patterns best fit the sample. Twenty-nine percent of the sample had an always healthy BMI (class 1) and 34.9% changed from healthy weight to overweight (class 2). Moving from healthy weight to obese comprised 21.8% of the sample (class 3). BMI patterns increasing from overweight to obese (class 4) and from obese to severely obese (class 5) comprised 7.6% and 7.1% of the sample, respectively. Weight change was similar for males and females with some racial or ethnic minority participants more likely to be severely obese in adulthood.

CONCLUSIONS

Results emphasize the importance of tracking weight longitudinally and point to a nationally representative trend of increasing BMI during the transition to adulthood. There was no substantive decreasing trend identified in the sample. Findings highlight the need for effective early and ongoing intervention and prevention strategies and can aid in identification of vulnerable youth who are at the highest risk for moving to problematic weight categories.

Rate of change in body mass index at different ages during childhood and adult obesity risk

BACKGROUND

Childhood body mass index (BMI) predicts adult obesity. How growth trajectories during childhood relate to adult obesity risk is not well defined.

OBJECTIVE

We aimed to characterize BMI growth trajectories from childhood to midlife and to examine the associations between BMI growth rates at childhood age points and adult obesity risk.

METHODS

The longitudinal study included 2732 participants with repeated BMI measurements from childhood (4-19 y) to adulthood (20-51 y). A random-effects model was used to construct BMI growth curves by race and sex. Model-estimated levels and linear growth rates of BMI were linked to adult obesity in separate multivariable logistic regression models at individual childhood age points.

RESULTS

BMI followed cubic growth curves. Childhood BMI linear slope estimates were higher in adults with obesity than in adults without obesity (P < 0.001). The association between childhood BMI growth rate and adult obesity was significantly higher in puberty and postpuberty (12-19 y) than in early childhood (4-11 y) with a peak at age 14 (odds ratio = 3.1 and 95% confidence interval, 2.7-3.5).

CONCLUSIONS

Rates of change in BMI at different childhood ages are differentially associated with adult obesity. Puberty and postpuberty are crucial periods for the development of obesity in later life.

Developmental trajectories of body mass index from childhood into late adolescence and subsequent late adolescence-young adulthood cardiometabolic risk markers

Background

Reports on body mass index (BMI) trajectories from childhood into late adolescence, their determinants, and subsequent cardiometabolic risk markers, particularly among European populations have been few. Moreover, sex-specific investigation is necessary considering the sex difference in BMI, and the sex-specific association between BMI and some cardiometabolic risk markers.

Methods

Using a sample from the DOrtmund Nutritional and Anthropometric Longitudinally Designed study, we explored sex-specific trajectories of the BMI standard deviation score (SDS) from 4 to 18 years of age in 354 males and 335 females by latent (class) growth models. The determinants of trajectory were assessed by logistic regression. We identified cardiometabolic risk markers that were highly associated with BMI SDS trajectory by random forest regression, and finally we used generalized linear models to investigate differences in the identified cardiometabolic risk markers between pairs of trajectories.

Results

We observed four: ‘low-normal weight’, ‘mid-normal weight’, ‘high-normal weight’, and ‘overweight’, and three: ‘‘low-normal weight’, ‘mid-normal weight’, and ‘high-normal weight’ trajectories in males and females, respectively. Higher maternal prepregnancy BMI was associated with the ‘overweight’ trajectory, and with ‘high-normal weight’ trajectory in both sexes. In addition, employed mothers and first-born status were associated with ‘high-normal weight’ trajectory in females. BMI SDS trajectory was associated with high-density lipoprotein-cholesterol and interleukin-18 (IL-18) in males, and diastolic blood pressure and interleukin-6 (IL-6) in females. However, only males following the ‘overweight’ trajectory had significantly higher IL-18 when compared to their ‘low-normal weight’ counterpart.

Conclusions

We identified sex-specific distinct trajectories of BMI SDS from childhood into late adolescence, higher maternal prepregnancy BMI as a common determinant of the ‘high-normal weight’ and ‘overweight’ trajectories, and ‘overweight’ trajectory being associated with elevated IL-18 in late adolescence–young adulthood. This study emphasizes the role of maternal prepregnancy BMI in overweight, and highlights IL-18 as a cardiometabolic signature of overweight across life.

Electronic supplementary material

The online version of this article (10.1186/s12933-019-0813-5) contains supplementary material, which is available to authorized users.