Children grow and horses race: is the adiposity rebound a critical period for later obesity?

BACKGROUND: The adiposity rebound is the second rise in body mass index that occurs between 3 and 7 years. An early age at adiposity rebound is known to be a risk factor for later obesity. The aim here is to clarify the connection between the age at rebound and the corresponding pattern of body mass index change, in centile terms, so as to better understand its ability to predict later fatness. DISCUSSION: Longitudinal changes in body mass index during adiposity rebound, measured both in original (kg/m(2)) and standard deviation (SD) score units, are studied in five hypothetical subjects. Two aspects of the body mass index curve, the body mass index centile and the rate of body mass index centile crossing, determine a child's age at rebound. A high centile and upward centile crossing are both associated separately with an early rebound, while a low centile and/or downward centile crossing correspond to a late rebound. Early adiposity rebound is a risk factor for later fatness because it identifies children whose body mass index centile is high and/or crossing upwards. Such children are likely to have a raised body mass index later in childhood and adulthood. This is an example of Peto's "horse racing effect". The association of centile crossing with later obesity is statistical not physiological, and it applies at all ages not just at rebound, so adiposity rebound cannot be considered a critical period for future obesity. Body mass index centile crossing is a more direct indicator of the underlying drive to fatness. SUMMARY: An early age at adiposity rebound predicts later fatness because it identifies children whose body mass index centile is high and/or crossing upwards. Such children are likely to have a raised body mass index later. Body mass index centile crossing is more direct than the timing of adiposity rebound for predicting later fatness

Childhood body mass index trajectories: modeling, characterizing, pairwise correlations and socio-demographic predictors of trajectory characteristics

Background: Modeling childhood body mass index (BMI) trajectories, versus estimating change in BMI between specific ages, may improve prediction of later body-size-related outcomes. Prior studies of BMI trajectories are limited by restricted age periods and insufficient use of trajectory information. Methods: Among 3,289 children seen at 81,550 pediatric well-child visits from infancy to 18 years between 1980 and 2008, we fit individual BMI trajectories using mixed effect models with fractional polynomial functions. From each child's fitted trajectory, we estimated age and BMI at infancy peak and adiposity rebound, and velocity and area under curve between 1 week, infancy peak, adiposity rebound, and 18 years. Results: Among boys, mean (SD) ages at infancy BMI peak and adiposity rebound were 7.2 (0.9) and 49.2 (11.9) months, respectively. Among girls, mean (SD) ages at infancy BMI peak and adiposity rebound were 7.4 (1.1) and 46.8 (11.0) months, respectively. Ages at infancy peak and adiposity rebound were weakly inversely correlated (r = -0.09). BMI at infancy peak and adiposity rebound were positively correlated (r = 0.76). Blacks had earlier adiposity rebound and greater velocity from adiposity rebound to 18 years of age than whites. Higher birth weight z-score predicted earlier adiposity rebound and higher BMI at infancy peak and adiposity rebound. BMI trajectories did not differ by birth year or type of health insurance, after adjusting for other socio-demographics and birth weight z-score. Conclusions: Childhood BMI trajectory characteristics are informative in describing childhood body mass changes and can be estimated conveniently. Future research should evaluate associations of these novel BMI trajectory characteristics with adult outcomes

Body mass index, adiposity rebound and early feeding in a longitudinal cohort (Raine study)

Objective: This study examined the influence of type and duration of infant feeding on adiposity rebound and the tracking of body mass index (BMI) from birth to 14 years. Methods: A sample of 1330 individuals over eight follows-ups was drawn from the Western Australian Pregnancy Cohort (Raine) Study. Trajectories of BMI from birth to adolescence using linear mixed model (LMM) analysis investigated the influence of age breastfeeding stopped and age other milk introduced (binomial 4-month cut-point). A sub-sample of LMM predicted BMI was used to determine BMI and age at nadir for early infant feeding groups. Results: Chi square analysis between early feeding and weight status (normal weight, overweight and obese) groups found a significant difference between age breastfeeding stopped (p Conclusions: Early infant feeding was important in the timing and BMI at adiposity rebound. The relationship between infant feeding and BMI remained up to age 14 years. Although confounding factors cannot be excluded, these findings support the importance of exclusive breastfeeding for longer than four months as a protective behaviour against the development of adolescent obesity

Summer effects on body mass index (BMI) gain and growth patterns of American Indian children from kindergarten to first grade: a prospective study

<p>Abstract</p> <p>Background</p> <p>Overweight and obesity are highly prevalent among American Indian children, especially those living on reservations. There is little scientific evidence about the effects of summer vacation on obesity development in children. The purpose of this study was to investigate the effects of summer vacation between kindergarten and first grade on growth in height, weight, and body mass index (BMI) for a sample of American Indian children.</p> <p>Methods</p> <p>Children had their height and weight measured in four rounds of data collection (yielded three intervals: kindergarten, summer vacation, and first grade) as part of a school-based obesity prevention trial (Bright Start) in a Northern Plains Indian Reservation. Demographic variables were collected at baseline from parent surveys. Growth velocities (Z-score units/year) for BMI, weight, and height were estimated and compared for each interval using generalized linear mixed models.</p> <p>Results</p> <p>The children were taller and heavier than median of same age counterparts. Height Z-scores were positively associated with increasing weight status category. The mean weight velocity during summer was significantly less than during the school year. More rapid growth velocity in height during summer than during school year was observed. Obese children gained less adjusted-BMI in the first grade after gaining more than their counterparts during the previous two intervals. No statistically significant interval effects were found for height and BMI velocities.</p> <p>Conclusions</p> <p>There was no indication of a significant summer effect on children's BMI. Rather than seasonal or school-related patterns, the predominant pattern indicated by weight-Z and BMI-Z velocities might be related to age or maturation.</p> <p>Trial registration</p> <p>Bright Start: Obesity Prevention in American Indian Children Clinical Trial Govt ID# <a href="http://www.clinicaltrials.gov/ct2/show/NCT00123032">NCT00123032</a></p

Neonatal anthropometry: a tool to evaluate the nutritional status and predict early and late risks

Neonatal anthropometry is an inexpensive, noninvasive and convenient tool for bedside evaluation, especially in sick and fragile neonates. Anthropometry can be used in neonates as a tool for several purposes: diagnosis of foetal malnutrition and prediction of early postnatal complications; postnatal assessment of growth, body composition and nutritional status; prediction of long-term complications including metabolic syndrome; assessment of dysmorphology; and estimation of body surface. However, in this age group anthropometry has been notorious for its inaccuracy and the main concern is to make validated indices available. Direct measurements, such as body weight, length and body circumferences are the most commonly used measurements for nutritional assessment in clinical practice and in field studies. Body weight is the most reliable anthropometric measurement and therefore is often used alone in the assessment of the nutritional status, despite not reflecting body composition. Derived indices from direct measurements have been proposed to improve the accuracy of anthropometry. Equations based on body weight and length, mid-arm circumference/head circumference ratio, and upper-arm cross-sectional areas are among the most used derived indices to assess nutritional status and body proportionality, even though these indices require further validation for the estimation of body composition in neonates

Cross-sectional associations between sleep duration, sedentary time, physical activity, and adiposity indicators among Canadian preschool-aged children using compositional analyses

Abstract Background Sleep duration, sedentary behaviour, and physical activity are three co-dependent behaviours that fall on the movement/non-movement intensity continuum. Compositional data analyses provide an appropriate method for analyzing the association between co-dependent movement behaviour data and health indicators. The objectives of this study were to examine: (1) the combined associations of the composition of time spent in sleep, sedentary behaviour, light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (MVPA) with adiposity indicators; and (2) the association of the time spent in sleep, sedentary behaviour, LPA, or MVPA with adiposity indicators relative to the time spent in the other behaviours in a representative sample of Canadian preschool-aged children. Methods Participants were 552 children aged 3 to 4 years from cycles 2 and 3 of the Canadian Health Measures Survey. Sedentary time, LPA, and MVPA were measured with Actical accelerometers (Philips Respironics, Bend, OR USA), and sleep duration was parental reported. Adiposity indicators included waist circumference (WC) and body mass index (BMI) z-scores based on World Health Organization growth standards. Compositional data analyses were used to examine the cross-sectional associations. Results The composition of movement behaviours was significantly associated with BMI z-scores (p = 0.006) but not with WC (p = 0.718). Further, the time spent in sleep (BMI z-score: γ sleep  = −0.72; p = 0.138; WC: γ sleep  = −1.95; p = 0.285), sedentary behaviour (BMI z-score: γ SB  = 0.19; p = 0.624; WC: γ SB  = 0.87; p = 0.614), LPA (BMI z-score: γ LPA  = 0.62; p = 0.213, WC: γ LPA  = 0.23; p = 0.902), or MVPA (BMI z-score: γ MVPA  = −0.09; p = 0.733, WC: γ MVPA  = 0.08; p = 0.288) relative to the other behaviours was not significantly associated with the adiposity indicators. Conclusions This study is the first to use compositional analyses when examining associations of co-dependent sleep duration, sedentary time, and physical activity behaviours with adiposity indicators in preschool-aged children. The overall composition of movement behaviours appears important for healthy BMI z-scores in preschool-aged children. Future research is needed to determine the optimal movement behaviour composition that should be promoted in this age group

Prevalence of overweight and obesity in children aged 6–13 years—alarming increase in obesity in Cracow, Poland

This study in children aged 6–13 years (n = 1,499) was performed between October 2008 and March 2009. Height and weight measurements were taken to calculate BMI. The prevalence of overweight and obesity was determined by means of IOTF cut-offs with respect to age. Alarming is the fact that the percentage of obese children in Cracow increased dramatically from 1.04% in boys and 0.20% in girls in 1971 to 7% in boys and 3.6% in girls in 2009. In this report, a higher percentage of overweight boys was observed in rural boys (28.14%) than in urban ones (27.31%). Obesity was identified in an almost twice as high percentage of urban boys (7.78%) as in rural ones (3.52%). A higher percentage of overweight girls was registered in rural areas (16.49%) than in urban ones (16.09%). Obesity was prevailing in rural girls (4.12%) relative to their urban counterparts (3.44%). The highest number of overweight urban boys was diagnosed in the group of 12-year-olds (n = 48) and rural boys in the group of 10-year-olds (n = 39), as well as in urban girls aged 11 (n = 17) and rural girls aged 9 (n = 9). The highest number of obesity was observed in rural boys aged 12 (n = 3) and in urban boys aged 9 and 10 (n = 9 in both groups). In the group of girls, obesity prevailed in urban 9-year-olds (n = 5) and in rural 7-year-olds (n = 5). Conclusions: Overweight and obesity affect boys almost twice as frequently as girls. Obesity is twice as frequent in urban boys as in their rural peers