Dataset Information

Prediction of Body Mass Index Using Concurrently Self-Reported or Previously Measured Height and Weight.

ABSTRACT:

Objective

To compare alternative models for the imputation of BMIM (measured weight in kilograms/measured height in meters squared) in a longitudinal study.

Methods

We used data from 11,008 adults examined at wave III (2001-2002) and wave IV (2007-2008) in the National Longitudinal Study of Adolescent to Adult Health. Participants were asked their height and weight before being measured. Equations to predict wave IV BMIM were developed in an 80% random subsample and evaluated in the remaining participants. The validity of models that included BMI constructed from previously measured height and weight (BMIPM) was compared to the validity of models that used BMI calculated from concurrently self-reported height and weight (BMISR). The usefulness of including demographics and perceived weight category in those models was also examined.

Results

The model that used BMISR, compared to BMIPM, as the only variable produced a larger R2 (0.913 vs. 0.693), a smaller root mean square error (2.07 vs. 3.90 kg/m2) and a lower bias between normal-weight participants and those with obesity (0.98 vs. 4.24 kg/m2). The performance of the model containing BMISR alone was not substantially improved by the addition of demographics, perceived weight category or BMIPM.

Conclusions

Our work is the first to show that concurrent self-reports of height and weight may be more useful than previously measured height and weight for imputation of missing BMIM when the time interval between measures is relatively long. Other time frames and alternatives to in-person collection of self-reported data need to be examined.

SUBMITTER: Cui Z

PROVIDER: S-EPMC5127553 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Prediction of Body Mass Index Using Concurrently Self-Reported or Previously Measured Height and Weight.

Cui Zhaohui Z Stevens June J Truesdale Kimberly P KP Zeng Donglin D French Simone S Gordon-Larsen Penny P

PloS one 20161129 11

<h4>Objective</h4>To compare alternative models for the imputation of BMIM (measured weight in kilograms/measured height in meters squared) in a longitudinal study.<h4>Methods</h4>We used data from 11,008 adults examined at wave III (2001-2002) and wave IV (2007-2008) in the National Longitudinal Study of Adolescent to Adult Health. Participants were asked their height and weight before being measured. Equations to predict wave IV BMIM were developed in an 80% random subsample and evaluated in t ...[more]

PMID: 27898706

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Project description:BACKGROUND:Electronic health (eHealth) interventions for children often rely on parent-reported child anthropometric measures. However, limited studies have assessed parental accuracy in reporting child height and weight via Web-based approaches. OBJECTIVE:The objective of this study was to determine the accuracy of parent-reported child height and weight, as well as body mass index and weight category that we calculated from these data. We also aimed to explore whether parent report was influenced by age, sex, weight status, or exposure to participation in a 12-week brief Web-based family lifestyle intervention. METHODS:This study was a secondary analysis of data from a 12-week childhood obesity pilot randomized controlled trial in families with children aged 4 to 11 years in Australia. We asked parents to report demographic information, including child height and weight, using an online survey before their child's height and weight were objectively measured by a trained research assistant at baseline and week 12. We analyzed data using the Lin concordance correlation coefficient (?c, ranging from 0 [poor] to ±1 [perfect] concordance), Cohen kappa coefficient, and multivariable linear regression models. RESULTS:There were 42 families at baseline and 35 families (83%) at week 12. Overall, the accuracy of parent-reported child height was moderate (?c=.94), accuracy of weight was substantial (?c=.96), and accuracy of calculated body mass index was poor (?c=.63). Parents underreported child height and weight, respectively, by 0.9 cm and 0.5 kg at baseline and by 0.2 cm and 1.6 kg after participating in a 12-week brief Web-based family lifestyle intervention. The overall interrater agreement of child body mass index category was moderate at baseline (?=.59) and week 12 (?=.54). The weight category calculated from 74% (n=31) and 70% (n=23) of parent-reported child height and weight was accurate at baseline and week 12, respectively. Parental age was significantly (95% CI -0.52 to -0.06; P=.01) associated with accuracy of reporting child height. Child age was significantly (95% CI -2.34 to -0.06; P=.04) associated with reporting of child weight. CONCLUSIONS:Most Australian parents were reasonably accurate in reporting child height and weight among a group of children aged 4 to 11 years. The weight category of most of the children when calculated from parent-reported data was in agreement with the objectively measured data despite the body mass index calculated from parent-reported data having poor concordance at both time points. Online parent-reported child height and weight may be a valid method of collecting child anthropometric data ahead of participation in a Web-based program. Future studies with larger sample sizes and repeated measures over time in the context of eHealth research are warranted. Future studies should consider modeling the impact of calibration equations applied to parent-reported anthropometric data on study outcomes.

Project description:BackgroundChildren with familial dysautonomia (FD) are smaller and grow more slowly than the general population. It is unknown whether this abnormal growth is due to comorbidities that patients with FD live with, or if it is a direct effect of the disease-causing homozygous ELP-1 mutations. Here, we created growth curves for weight, height, and body mass index (BMI) in male and female children with FD to monitor the nutritional status of patients with FD.MethodsWe used the New York University (NYU) FD Registry which includes data from 680 individuals with FD who were followed longitudinally since birth. We generated sex-specific FD growth charts for three age ranges (birth to 36 months, 2 to 20 years, and 2 to 40 years) and compared them to the general population. We generated Kaplan-Meier curves to test the hypothesis that FD patients with low BMI had shorter survival than the rest of the cohort.ResultsGrowth charts generated from 591 individuals with FD show that these patients grow more slowly, reach less height, and gain less weight than the general population. The impact of FD on height was more pronounced in girls than in boys. However, both groups showed markedly low weights, which resulted in low BMI. Low weight, but not height, is already evident at birth. In a subpopulation of FD patients, we found that treatment with growth hormone or spinal fusion surgery helped patients achieve the expected growth characteristic of FD patients, but these treatments did not lead FD patients to achieve the growth pattern of the general population. Contrary to our hypothesis, low BMI had no impact on patient survival.ConclusionsPediatric patients with FD have lower height, weight, and BMI compared to the general pediatric population, but this does not appear to affect survival. Growth curves specific to the FD population are an important tool to monitor growth and nutritional status in pediatric patients with FD when the general population growth curves are of limited use.

Project description:ImportanceThere is a lack of evidence on the association of birth weight, childhood body mass index (BMI), change in BMI during childhood, and childhood height with subsequent risks of hidradenitis suppurativa (HS) in adulthood.ObjectiveTo investigate the association of birth weight, childhood BMI, change in BMI during childhood, and childhood height with subsequent risks of HS in adulthood in a large Danish population-based cohort.Design, setting, and participantsThis cohort study included 347 200 schoolchildren from the Copenhagen School Health Records Register born from 1930 to 1996 who were linked to the Danish National Patient Register of hospital discharge diagnoses to identify cases of HS. Birth weight was reported by parents or guardians, whereas childhood weight and height were measured by school physicians or nurses at ages 7 through 13 years. Cox proportional hazards regressions were used to estimate hazard ratios (HRs) and 95% CIs. Statistical analysis was performed from February 20, 2019, to May 15, 2019.Main outcomes and measuresA diagnosis of HS as recorded in the Danish National Patient Register.ResultsAmong the 347 200 children included in the study (175 750 boys) during the follow-up period from 1977 to 2017, 1037 individuals (677 females; median age at diagnosis, 39 years [range, 15-73 years]) received a diagnosis of HS. A nonlinear (U-shaped) association was found between birth weight and HS, such that both the lightest (2.00-2.75 kg; HR, 1.36 [95% CI, 1.10-1.68]) and the heaviest babies (4.26-5.50 kg; HR, 1.39 [95% CI, 1.01-1.93]) had increased risks of HS compared with normal-weight babies (3.26-3.75 kg; P = .04 for deviation from linearity). The risk of HS increased significantly with increasing BMI z score at each age from 7 to 13 years, from an HR of 1.32 (95% CI, 1.24-1.40) per BMI z score at 7 years of age to an HR of 1.50 (95% CI, 1.40-1.61) per BMI z score at 13 years of age. Compared with children with a normal weight at 7 and 13 years of age, those with a normal weight at 7 years of age and overweight at 13 years of age had a significantly increased risk of HS (HR, 2.11 [95% CI, 1.63-2.74]) and children with persistent overweight at both ages also had an increased risk of HS (HR, 2.61 [95% CI, 2.02-3.38]). Children with overweight at 7 years of age but with normal weight at 13 years of age did not have a significantly increased risk of HS (HR, 1.05 [95% CI, 0.67-1.67]). Childhood height at all ages was not associated with risk of HS (children at 7 years had an HR of 1.00 [95% CI, 0.94-1.07], and those 13 years had an HR of 1.06 [95% CI, 0.99-1.13], per z score).Conclusions and relevanceThis cohort study found that both the lightest and heaviest babies had increased risks of HS. Childhood BMI was positively and significantly associated with risk of HS development in adulthood. These findings suggest that returning to normal weight before puberty reduces risks of HS to levels observed in children who were never overweight. Childhood height was not associated with risk of HS.

Project description:IntroductionObesity during childhood is a serious and growing chronic disease with consequences for lifelong health. In an effort to advance research into the preclinical indicators of pediatric obesity, we examined longitudinal assessments of uric acid concentrations in saliva among a cohort of healthy children from age 6-months to 12-years (n's per assessment range from 294 to 727).MethodsUsing data from a subsample of participants from the Family Life Project (an Environmental influences on Child Health Outcomes Program cohort), we: (1) characterized salivary uric acid (sUA) concentrations from infancy to early adolescence by sex and race; (2) assessed changes in sUA levels across development; and (3) evaluated associations between sUA concentrations and measures of child weight, height, and body mass index (BMI). Across four assessments conducted at 6-, 24-, 90-, and 154-months of age, 2,000 saliva samples were assayed for UA from 781 participants (217 participants had sUA data at all assessments).ResultsThere were no significant differences in sUA concentrations by sex at any assessment, and differences in sUA concentrations between White and non-White children varied by age. At the 90- and 154-month assessments, sUA concentrations were positively correlated with measures of child weight, height, and BMI (90-month: weight- ρ(610) = 0.13, p < 0.01; height- ρ(607) = 0.10, p < 0.05; BMI- ρ(604) = 0.13, p < 0.01; 154-month: weight- ρ(723) = 0.18, p < 0.0001; height- ρ(721) = 0.10, p < 0.01; BMI- ρ(721) = 0.17, p < 0.0001). Group based trajectory modeling identified two groups of children in our sample with distinct patterns of sUA developmental change. The majority (72%) of participants showed no significant changes in sUA across time ("Stable" group), while 28% showed increases in sUA across childhood with steep increases from the 90- to 154-month assessments ("Increasing" group). Children in the Increasing group exhibited higher sUA concentrations at all assessments (6-month: t(215) = -5.71, p < 0.001; 24-month: t(215) = -2.89, p < 0.01; 90-month: t(215) = -3.89, p < 0.001; 154-month: t(215) = -19.28, p < 0.001) and higher weight at the 24- and 90-month assessments (24-month: t(214) = -2.37, p < 0.05; 90-month: t(214) = -2.73, p < 0.01).DiscussionOur findings support the potential utility of sUA as a novel, minimally-invasive biomarker that may help advance understanding of the mechanisms underlying obesity as well as further surveillance and monitoring efforts for pediatric obesity on a large-scale.

Dataset Information

Prediction of Body Mass Index Using Concurrently Self-Reported or Previously Measured Height and Weight.

Objective

Methods

Results

Conclusions

Publications

Prediction of Body Mass Index Using Concurrently Self-Reported or Previously Measured Height and Weight.

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