The Limitations of Transforming Very High Body Mass Indexes into z -Scores among 8.7 Million 2- to 4-Year-Old Children

Freedman, David S.; Butte, Nancy F.; Taveras, Elsie M.; Goodman, Alyson B.; Ogden, Cynthia L.; Blanck, Heidi M.

doi:10.1016/j.jpeds.2017.03.039

Cited by 72 publications

(55 citation statements)

References 26 publications

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“…However, this is the first study to demonstrate that behavioral regulation early in life confers risk for the development of severe obesity. The use of BMI percentiles and z scores, which are compressed at their highest scores, may have masked trajectories of severe obesity in past studies (34,35). As illustrated in our findings, the use of BMI percentiles to plot trajectories ( Figure 1A) did not adequately capture variability in BMI among youth in the severe obesity trajectory.…”

Section: Discussionmentioning

confidence: 72%

Biobehavioral Dysregulation and its Association with Obesity and Severe Obesity Trajectories from 2 to 15 Years of Age: A Longitudinal Study

Francis

Rollins

Bryce

2020

Obesity

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Objective This study aimed to identify obesity trajectories from childhood to adolescence (2‐15 years of age) and investigate differences in behavioral, eating, and adrenocortical regulation by trajectory membership. Methods A total of 1,077 households from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development were included. Anthropometrics were measured 11 times between ages 15 months and 15 years. Behavioral self‐regulation was assessed at ages 3 and 4 years. Disordered eating behaviors and awakening cortisol were assessed at age 15 years. Results Latent growth curve modeling identified four BMI trajectories: two nonoverweight trajectories based on average BMI at the 40th and 70th percentiles and overweight/obesity and severe obesity trajectories. Youth in the severe obesity trajectory exhibited lower behavioral self‐regulation in early childhood and lower awakening cortisol at age 15 years compared with youth in the nonoverweight trajectories. Youth in the overweight/obesity and severe obesity trajectories showed higher levels of disordered eating behaviors at age 15 years. Conclusions Obesity trajectories were associated with biobehavioral markers of dysregulation in early childhood and adolescence. Dysregulation across biobehavioral domains was particularly apparent among youth who developed severe obesity. Further work is needed to better understand resilience factors that distinguish youth who develop obesity and severe obesity from those who do not.

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Section: Discussionmentioning

confidence: 72%

Biobehavioral Dysregulation and its Association with Obesity and Severe Obesity Trajectories from 2 to 15 Years of Age: A Longitudinal Study

Francis

Rollins

Bryce

2020

Obesity

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“…BMI‐SDS was calculated using the least mean squares method based on German references . In addition, the degree of obesity was expressed as percentage of the 95th percentile (%BMIP95) of the Center of Disease Control and Prevention (CDC) BMI percentiles (2‐20 years), as recommended recently in the Endocrine Society Clinical Practice Guideline for paediatric obesity …”

Section: Methodsmentioning

confidence: 99%

Methylphenidate in children with monogenic obesity due to LEPR or MC4R deficiency improves feeling of satiety and reduces BMI‐SDS—A case series

Brandt¹,

Schnurbein²,

Lennerz

et al. 2019

Pediatric Obesity

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Summary Background The clinical phenotype of patients with monogenic obesity due to mutations in the leptin receptor (LEPR) or melanocortin 4 receptor (MC4R) gene is characterized by impaired satiety and hyperphagia, leading to extreme, sometimes life‐threatening weight gain. Subjects/methods In a case series, we analysed the effect of an off‐label methylphenidate (MPH) use for 1 year as an individual treatment approach on eating behaviour (Child Eating Behaviour Questionnaire [CEBQ]), appetite (visual analogue scales) and body mass index (BMI) trajectories in five patients with severe obesity due to mutations in the LEPR (n = 3) or MC4R (n = 2) gene. Results After 1 year use of MPH (20 mg/day divided in two to three doses), BMI (Δ BMIT0−T1 truex¯: −0.7 ± 0.9 kg/m2), BMI standard deviation score (SDS) (Δ BMI‐SDST0−T1 truex¯: −0.32 ± 0.20), and %BMIP95 (Δ %BMIP95T0−T1 truex¯: −6.6 ± 7.8%) decreased. BMI‐SDS velocity decreased from +0.17 ± 0.22 to −0.30 ± 0.20. Appetite and CEBQ subscale scores for “food responsiveness” and “enjoyment of food” decreased. We observed adverse effects with increase in self‐reported frequency of disordered sleep, nervousness, hyperactivity, and tics. Conclusions The observed decrease in BMI trajectories with MPH use for one year is clinically meaningful in this group of patients, since the natural course would have been associated with a pronounced increase in BMI, leading to comorbidities and complications over time.

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“…As previously described (Freedman et al, 2016, 2017b), the CDC’s Paediatric and Nutrition Surveillance Study (PedNSS) was a state-based public health surveillance system that monitored the nutritional status from birth to age 5 years of primarily low-income children. All procedures followed were in accordance with the ethical standards of CDC and approval was obtained from the relevant committee on human subjects.…”

Section: Methodsmentioning

confidence: 99%

“…For example, the value of (BMI ÷ M) L for a 4-year-old girl with a BMI of 30 would be ~0.1, resulting in a BMI z of 3.4 SDs; the maximum possible BMI z for that sex/age, irrespective of the actual BMI, is 3.8 SDs. Between 24–59 months of age, the maximum possible BMI z in the CDC growth charts decreases from 11.9 to 3.5 SDs among girls, while the pattern among boys is concave, with the peak (~10 SDs) at about 39 months of age (Freedman et al, 2017b). …”

Section: Methodsmentioning

confidence: 99%

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Longitudinal changes in BMIz-scores among 45 414 2–4-year olds with severe obesity

Freedman

Butte

Taveras

et al. 2017

Annals of Human Biology

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Background BMI z-scores (BMIz) based on the Centers for Disease Control and Prevention (CDC) growth charts among children do not accurately characterise BMI levels among children with very high BMIs. These limitations may be particularly relevant in longitudinal and intervention studies, as the large changes in the L (normality) and S (dispersion) parameters with age can influence BMIz. Aim To compare longitudinal changes in BMIz with BMI expressed as a percentage of the 95th percentile (%BMIp95) and a modified z-score calculated as log(BMI/M)/S. Subjects and methods A total of 45 414 2–4-year-olds with severe obesity (%BMIp95 ≥ 120). Results Changes in very high BMIz levels differed from the other metrics. Among severely obese 2-year-old girls, for example, the mean BMIz decreased by 0.6 SD between examinations, but there were only small changes in BMIp95 and modified BMIz. Some 2-year-old girls had BMIz decreases of >1 SD, even though they had large increases in BMI, %BMIp95 and modified BMIz. Conclusions Among children with severe obesity, BMIz changes may be due to differences in the transformations used to estimate levels of BMIz rather than to changes in body size. The BMIs of these children could be expressed relative to the 95th percentile or as modified z-scores.

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The Limitations of Transforming Very High Body Mass Indexes into z -Scores among 8.7 Million 2- to 4-Year-Old Children

Cited by 72 publications

References 26 publications

Biobehavioral Dysregulation and its Association with Obesity and Severe Obesity Trajectories from 2 to 15 Years of Age: A Longitudinal Study

Biobehavioral Dysregulation and its Association with Obesity and Severe Obesity Trajectories from 2 to 15 Years of Age: A Longitudinal Study

Methylphenidate in children with monogenic obesity due to LEPR or MC4R deficiency improves feeling of satiety and reduces BMI‐SDS—A case series

Longitudinal changes in BMIz-scores among 45 414 2–4-year olds with severe obesity

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