Examination of Sleep and Obesity in Children and Adolescents in the United States

2021 ◽  
pp. 089011712110291
Author(s):  
Puneet Kaur Chehal ◽  
Livvy Shafer ◽  
Solveig Argeseanu Cunningham
Keyword(s):  
Body Mass Index ◽  
Children And Adolescents ◽  
Sleep Duration ◽  
Body Mass ◽  
The United States ◽  
Weight Category ◽  
Lower Odds ◽  
Logistic Regression Models ◽  
Child Height ◽  
Nationally Representative

Purpose: This study contributes to the growing literature on the association between sleep and obesity by examining the associations between hours of sleep, consistency of bedtime, and obesity among children in the US. Design: Analysis of a nationally representative sample of non-institutionalized children from the 2016-17 National Survey of Children’s Health. Setting: US, national. Subjects: Children ages 10-17 years (n = 34,640) Measures: Parent reported weeknight average hours of sleep and consistency of bedtime. Body mass index classified as underweight, normal, overweight or obesity using parent-reported child height and weight information, classified using CDC BMI-for-Age Growth Charts. Analysis: Multivariate logistic regression models were used to estimate associations between measures of sleep and body mass index weight category adjusting for individual, household and neighborhood characteristics. Results: An additional hour of sleep was associated with 10.8% lower odds of obesity, net of consistency in bedtime. After controlling for sleep duration, children who usually went to bed at the same time on weeknights had lower odds of obesity (24.8%) relative to children who always went to bed at the same time. Conclusion: Sleep duration is predictive of lower odds of obesity in US children and adolescents. Some variability in weeknight bedtime is associated with lower odds of obesity, though there were no additional benefits to extensive variability in bedtime.

Fitness and Fatness: Body Mass Index versus Percent Body Fat

2019 ◽  
Vol 8 (4) ◽  
pp. 131-137
Author(s):  
Jennifer Bunn ◽  
Danielle Eustace ◽  
Taylor Miskech ◽  
John Manor ◽  
Michael Jiroutek
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
The United States ◽  
Normal Weight ◽  
Cardiovascular Fitness ◽  
Percent Body Fat ◽  
Tissue Mass ◽  
Weight Category ◽  
Health And Nutrition

ABSTRACT Background: Body mass index (BMI) is frequently used to evaluate risk of disease, but can be misleading because it does not account for different types of tissue mass (e.g., bone, muscle, fat). The purpose of this study was to classify adults in the United States according to cardiovascular fitness (CVF), BMI, and body fat using the National Health and Nutrition Examination Survey (NHANES) data. Methods: The three most current NHANES datasets (6,648 records) were included. Counts, means, and 95% confidence intervals (CI) determined the distribution of CVF across percent of body fat and BMI categories. Results: According to BMI, approximately 42.3% of participants were classified as either underweight or normal weight, and 24.9% were classified as obese. According to percent of body fat, 13.5% of subjects were classified as lean, while 68.4% of subjects were in the high percent body fat group. In regard to BMI, 9.9% and 6.7% of the overweight and obese populations, respectively, were classified in the highest third of CVF. According to adiposity, 6.6% and 21.0% of the moderate and high percent body fat population fell into the same category, respectively. Conclusion: Two-thirds of the population ranked below the 35th percentile for body fat (high percent body fat), with more of these individuals in the low CVF category than any other. The largest categorization for BMI was the normal-weight category. This supports that BMI may be misleading, and that utilizing percent body fat and CVF may provide a better indication of health.

scholarly journals Mean body weight, height, waist circumference, and body mass index among children and adolescents : United States, 1999–2018

2021 ◽  
Author(s):  
Cheryl D. Fryar ◽  
◽  
Deanna Kruszon-Moran ◽  
Qiuping Gu ◽  
Margaret Carroll ◽  
...  
Keyword(s):  
United States ◽  
Body Mass Index ◽  
Body Weight ◽  
Waist Circumference ◽  
Children And Adolescents ◽  
Body Mass ◽  
The United States ◽  
Recumbent Length

This report presents trends in mean weight, recumbent length, height, waist circumference, and body mass index among children and adolescents in the United States from 1999 through 2018.

scholarly journals Accuracy of Parent-Reported Child Height and Weight and Calculated Body Mass Index Compared With Objectively Measured Anthropometrics: Secondary Analysis of a Randomized Controlled Trial

10.2196/12532 ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. e12532 ◽  
Author(s):  
Li Kheng Chai ◽  
Clare E Collins ◽  
Chris May ◽  
Carl Holder ◽  
Tracy L Burrows
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Controlled Trial ◽  
Secondary Analysis ◽  
Web Based ◽  
Weight Category ◽  
Randomized Controlled ◽  
Child Height ◽  
Reported Data ◽  
Objectively Measured

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 (ρc, 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 (ρc=.94), accuracy of weight was substantial (ρc=.96), and accuracy of calculated body mass index was poor (ρc=.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 (κ=.59) and week 12 (κ=.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.

scholarly journals Accuracy of Parent-Reported Child Height and Weight and Calculated Body Mass Index Compared With Objectively Measured Anthropometrics: Secondary Analysis of a Randomized Controlled Trial (Preprint)

2018 ◽  
Author(s):  
Li Kheng Chai ◽  
Clare E Collins ◽  
Chris May ◽  
Carl Holder ◽  
Tracy L Burrows
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Controlled Trial ◽  
Secondary Analysis ◽  
Web Based ◽  
Weight Category ◽  
Randomized Controlled ◽  
Child Height ◽  
Reported Data ◽  
Objectively Measured

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 (ρc, 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 (ρc=.94), accuracy of weight was substantial (ρc=.96), and accuracy of calculated body mass index was poor (ρc=.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 (κ=.59) and week 12 (κ=.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 modelling the impact of calibration equations applied to parent-reported anthropometric data on study outcomes.

Obesity and its Impact on Health

2021 ◽  
pp. 485-487
Author(s):  
Veerabhadrappa G Mendagudli ◽  
Shivaleela S Sarawad
Keyword(s):  
United States ◽  
Body Mass Index ◽  
Children And Adolescents ◽  
Body Mass ◽  
The United States ◽  
Overweight And Obesity ◽  
The Body ◽  
Obese Children ◽  
Obese People ◽  
The World

Obesity has almost tripled globally since 1975. More than 1.9 billion people aged 18 and up were overweight in 2016. Over 650 million of them were obese. In 2016, 39% of adults aged 18 and up were overweight, with 13% being obese. Overweight and obesity kill more people than underweight in the majority of the world's population. In the year 2019, 38 million children under the age of 5 were overweight or obese. In 2016, over 340 million children and adolescents aged 5 to 19 years old were overweight or obese. Obesity can be avoided. Currently, India has over 135 million obese people. Until recently, the body mass index (BMI) was used to measure obesity. By 2020, there will be 158 million obese children around the world, rising to 206 million by 2025 and 254 million by 2030. In reality, India will have the most obese children after China, with 27,481,141 or 27 million, well ahead of the United States' 17 million.

scholarly journals Cardiovascular Endurance, Body Mass Index, Physical Activity, Screen Time, and Carotenoid Intake of Children: NHANES National Youth Fitness Survey

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Joan A. Vaccaro ◽  
Fatma G. Huffman
Keyword(s):  
Body Mass Index ◽  
Heart Rate ◽  
Body Mass ◽  
Heart Function ◽  
The United States ◽  
Normal Weight ◽  
Heart Rate Reserve ◽  
Weight Category ◽  
Health And Nutrition ◽  
Cardiovascular Endurance

Background. Approximately 17% of children aged 6–11 years were classified as obese in the United States. Obesity adversely affects physical functioning and leads to reduced quality of life. Heart function for overweight and obese children has not been reported.Methods. Data for this study were from NHANES National Youth Fitness Survey (NNYFS) conducted in conjunction with the National Health and Nutrition Examination Survey (NHANES) in 2012. This study used data from children aged 6–12 (N=732) that had the cardiorespiratory endurance measure, body mass index for age and sex, and dietary data (N=682). Cardiovascular endurance was estimated by heart rate reserve.Results. Compared to the highest percentile of heart rate reserve, those in the first percentile had 3.52 (2.36, 5.24) odds and those in the second percentile had 3.61 (1.84, 7.06) odds of being in the overweight/obese as compared to the under/normal weight category. Considering the highest percentile, boys had a heart rate reserve of 35%, whereas girls had a heart rate reserve of 13% (less than half that of boys).Conclusion. Having an overweight or obese classification for children in this study demonstrated a compromise in cardiovascular endurance. Parental awareness should be raised as to the detrimental consequence of overweight and heart health.

Abstract P233: Handgrip Strength Modifies the Association Between Body Mass Index and Blood Pressure in Children and Adolescents of the United States: Experience in NHANES 2011-2014

Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Rui Zhang ◽  
Liqiang Zheng ◽  
Wei Chen ◽  
Shengxu Li
Keyword(s):  
Blood Pressure ◽  
Body Mass Index ◽  
Children And Adolescents ◽  
Body Mass ◽  
Muscular Strength ◽  
Linear Models ◽  
Handgrip Strength ◽  
The United States ◽  
Beneficial Effects ◽  
Unit Increase

Background: Body mass index (BMI), a measure of obesity, is strongly associated with blood pressure (BP) in children and adolescents. Handgrip strength is a measure of muscular strength and body fitness. We hypothesized that handgrip strength modifies the relationship between BMI and BP. Methods: The sample included 3,947 children and adolescents (50.4% boys and 49.6% girls) aged 8-19 years who participated in the National Health and Nutrition Examination Surveys (NHANES) 2011-2014. The sum of the maximum handgrip strength from both hands, standardized to age- and sex-specific z-scores, was used. General linear models were used for data analyses. Results: As expected, BMI was positively correlated with systolic BP (partial correlation coefficient r=0.17, P<0.0001). After adjustment for age, race, sex, and handgrip strength, each BMI unit increase was associated with 0.47 (0.03, standard error) mm Hg increase in systolic BP (P<0.0001). Further, handgrip strength significantly (P=0.0002) attenuated the association between BMI and systolic BP. In those with handgrip strength below the median, each BMI unit increase was associated with 0.59 (0.04) mm Hg increase in systolic BP; such increase was only 0.38 (0.03) mm Hg in those with handgrip strength above the median, representing a 36% reduction in the effect size of BMI on systolic BP. Conclusion: These results suggest that high fitness, measured by handgrip strength, attenuates the adverse effect of obesity on blood pressure levels in children and adolescents, which indicates that increasing muscular strength and body fitness will have beneficial effects on obesity-associated elevated BP in children and adolescents.

scholarly journals Associations between Body Mass Index, Sleep Duration, and Reported Snoring and Sleepiness Symptoms, By Age Stratification

2020 ◽  
Vol 5 (10) ◽  
pp. 1263-1268
Author(s):  
David W. Lin ◽  
Weijie V. Lin
Keyword(s):  
Body Mass Index ◽  
Sleep Duration ◽  
Body Mass ◽  
Secondary Analysis ◽  
The United States ◽  
Sample Population ◽  
Cross Sectional ◽  
Subjective Sleep ◽  
Relationship Of ◽  
Age Stratification

To further clarify the associations between sleep and body mass index (BMI) using the most recent dataset from the National Health and Nutrition Examination Survey (NHANES). Our study is notable for the inclusion of analyses with age subpopulations and subjective sleep symptoms. Cross-sectional study was performed using the NHANES 2017-18 dataset. Weighted multivariate regressions were utilized. NHANES is a standardized survey conducted biennially in the United States, for a sample population which is weighted to represent national demographics. 6161 participants met inclusion criteria. Measurements were collected via NHANES protocol, with objective measurements collected by trained technicians and self-reported measurements collected via questionnaire. Our results corroborate a roughly U-shaped relationship of sleep duration with BMI, varying with age. Greatest magnitudes were observed in a bimodal age ranges of 18-30 and 61-75, with decreases in BMI of 0.248 and 0.385 associated with each marginal hour of sleep. Our secondary analysis with daytime sleepiness and snoring have a significant association with BMI. Snoring symptoms showed a decreasing magnitude of association with BMI as age increases; for ages 18-30, snoring at least once a week correlated with an increase in BMI of 3.571, while for ages 61-75, this correlated with an increase of 1.619. Our study adds to existing literature on the relationship of sleep and BMI. Age stratification methods were used to further clarify associations. Subjective sleep symptoms were used in a secondary analysis to identify clinical screening questions for adverse effects of sleep on BMI.

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