Condition

Obesity in Children and Adolescents

Editors: Fatima Cody Stanford MD, MPH, MPA, FAAP, FACP, FAHA, FTOS; Zbigniew Fedorowicz PhD, MSc, DPH, BDS, LDSRCS; Scott A. Barron MD, FAAP

Overview and Recommendations
Background Information
History and Physical
Diagnosis
Management
Complications and Prognosis
Prevention and Screening
Quality Improvement
Guidelines and Resources
Patient Information
References

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Background Information

Description

Obesity is the condition of having excess accumulation of body fat defined by body mass index (BMI) above the designated cutoff for age and sex.^1
,3
It is caused by a complex set of interacting factors that are related to genetics, behavior, and the physical and social environment.^1
,3

Definitions

Body mass index (BMI) is defined as weight in kilograms divided by height in meters squared (kg/m²).^1
,3
- BMI is the accepted standard for measuring overweight and obesity in children ≥ 2 years old.
- BMI provides a reasonable estimate of adiposity, though has some limitations.
  - It may overestimate adiposity in children who are short or who have relatively high muscle mass.
  - It may underestimate adiposity in children with reduced muscle mass.
  - It is less reliable in children due to changes in body composition at different stages of growth and development.
  - It may not be an appropriate measure of adiposity for all racial and ethnic groups.
Overweight and obesity in children aged 2-20 years may be classified based on BMI as follows:^1
,3
- Overweight is BMI ≥ 85th to < 95th percentile for age and sex.
- Obesity is BMI ≥ 95th percentile for age and sex.
- Severe obesity is BMI ≥ 120% of 95th percentile or BMI ≥ 35 kg/m², whichever is lower.
Obesity can also be classified into 3 classes:
- Class 1 obesity is BMI ≥ 95th percentile to < 120% of 95th percentile for age and sex.
- Class 2 obesity is BMI ≥ 120% to < 140% of 95th percentile or BMI ≥ 35 kg/m².
- Class 3 obesity is BMI ≥ 140% of 95th percentile or BMI ≥ 40 kg/m².

Epidemiology

Prevalence

Worldwide trends reveal that obesity is increasingly affecting children in low- and middle-income countries, not just those in industrialized and developed countries as seen historically.³
- STUDY SUMMARY
  worldwide prevalence of obesity 5.6% in girls and 7.8% in boys aged 5-19 years in 2016, with prevalence ≥ 20% in several regions including United States
  SYSTEMATIC REVIEW: Lancet 2017 Dec 16;390(10113):2627
  based on systematic review of observational studies
  
  systematic review of 2,416 population-based studies from 200 countries evaluating prevalence of underweight, overweight, and obesity in 128.9 million persons ≥ 5 years old between 1975 and 2016
  
  1,947 studies reported mean body mass index (BMI) in 31.5 million children and adolescents aged 5-19 years
  
  worldwide age-standardized prevalence of obesity comparing 1975 vs. 2016 (no p values reported)
  0.7% vs. 5.6% in girls
  
  0.9% vs. 7.8% in boys
  
  obesity prevalence increased in every country from 1975 to 2016, change was not statistically significant in some high-income countries
  
  countries with highest prevalence of obesity in 2016
  > 30% in girls in Nauru, Cook Islands, and Palau and boys in Cook Islands, Nauru, Palau, Niue, and American Samoa
  
  > 20% in some countries in Polynesia and Micronesia, Egypt, Kuwait, Qatar, Saudi Arabia, Bermuda, Puerto Rico, and United States
  
  Reference - Lancet 2017 Dec 16;390(10113):2627
- STUDY SUMMARY
  prevalence of overweight or obesity in children and adolescents about 23% in developed countries and 13% in developing countries in 2013
  SYSTEMATIC REVIEW: Lancet 2014 Aug 30;384(9945):766
  based on systematic review of observational studies
  
  systematic review of 543 observational studies and 1,769 health surveys and reports from 183 countries evaluating prevalence of overweight or obesity between 1980 and 2013
  
  age-standardized prevalence of overweight or obesity in children and adolescents aged 2-19 years in 2013
  in developed countries
  23.8% (95% CI 22.9%-24.7%) in males
  
  22.6% (95% CI 21.7%-23.6%) in females
  
  in developing countries
  12.9% (95% CI 12.3%-13.5%) in males
  
  13.4% (95% CI 13%-13.9%) in females
  
  global prevalence of overweight or obesity significantly increased in 2013 compared to 1980
  
  Reference - Lancet 2014 Aug 30;384(9945):766, editorial can be found in Lancet 2014 Aug 30;384(9945):728

Obesity trends in the United States include:^1
,3

Increasing prevalence with age
Increasing prevalence of severe obesity in children
Higher prevalence in Hispanic, Black, and American Indian children compared to White and Asian children
Higher prevalence among lower- compared to higher-income populations
STUDY SUMMARY
prevalence of obesity increases with age in patients aged 2-19 years in United States from 2013 to 2014
CROSS-SECTIONAL STUDY: JAMA 2016 Jun 7;315(21):2292
based on cross-sectional population-based survey study

40,780 patients aged 2-19 years from National Health and Nutrition Examination Surveys (NHANES) between 1988 and 2014 were evaluated

prevalence of obesity (body mass index ≥ 95th percentile) from 2013 to 2014
17% overall

9.4% in children aged 2-5 years

17.4% in children aged 6-11 years

20.6% in adolescents aged 12-19 years

prevalence of severe obesity (body mass index ≥ 120% of 95th percentile) from 2013 to 2014
6% overall

1.7% in children aged 2-5 years

4.3% in children aged 6-11 years

9.1% in adolescents aged 12-19 years

children aged 2-19 years had increasing obesity (p < 0.001) and extreme obesity (p < 0.001) from 1988 to 2014

Reference - JAMA 2016 Jun 7;315(21):2292, editorial can be found in JAMA 2016 Jun 7;315(21):2277

STUDY SUMMARY

prevalence of obesity and severe obesity is highest in Hispanic and African American children and children whose household head has a lower education level

CROSS-SECTIONAL STUDY: JAMA 2018 Jun 19;319(23):2410

based on cross-sectional population-based survey

6,863 children and adolescents aged 2-19 years from NHANES between 2013 and 2016 were evaluated

Prevalence of Obesity and Severe Obesity by Race/Ethnicity and Education of Household Head

Prevalence of Obesity and Severe Obesity by Race/Ethnicity and Education of Household Head
Demographic Variable		Obesity	Severe Obesity
Racial/ethnic group - all		17.8%	5.8%
Hispanic		23.6%	8.4%
Non-Hispanic Black		20.4%	7.9%
Non-Hispanic White		14.7%	4.4%
Non-Hispanic Asian		9.8%	1.3%
Education of household head	≤ high school diploma	22.3%	7.7%
	Some college	18.1%	6%
	College degree	11.6%	3.3%

Reference - JAMA 2018 Jun 19;319(23):2410

Risk Factors

Overview of Risk Factors for Obesity in Children

A complex host of interacting factors may increase the risk for childhood obesity, including:^1
,3

Endocrine Disorders

Less than 1% of children and adolescents with obesity have endocrine disorders as the cause of their obesity.¹
Endocrine disorders that may contribute to obesity include:
- Cushing syndrome (endogenous glucocorticoid excess)¹
- Hypothyroidism^1
  ,3
- Growth hormone deficiency^1
  ,3
- Hypercortisolemia³
- Pseudohypoparathyroidism type 1a (Albright hereditary osteodystrophy)^1
  ,3

Neurologic and Hypothalamic Conditions

Neurologic and hypothalamic conditions that may contribute to obesity include:
- Brain injury or tumors such as diencephalic tumors or cranial trauma¹
- Hypothalamic lesions (craniopharyngioma) after surgery and/or cranial radiation¹
- Inflammatory disease affecting the hypothalamus¹
- Rapid-onset obesity with hypothalamic dysfunction, hypoventilation, and autonomic dysregulation (ROHHAD)¹
- Rapid-onset obesity with hypothalamic dysfunction, hypoventilation, and autonomic dysregulation with neural crest tumors (ROHHADNET)¹

Medications and Procedures

Medications that may contribute to weight gain include:¹
- Glucocorticoids
- Tricyclic antidepressants
- Antipsychotics including risperidone and olanzapine
- Antiseizure medications
- Sulfonylureas
- Antibiotics, particularly antibiotic exposure in infancy

Evidence Synopsis

Studies on the effect of early antibiotic use and the risk of obesity are conflicting. Antibiotic use in infancy may increase the risk of childhood obesity. The effect appears to vary by age and number of exposures, with exposure before age 6 months and multiple exposures resulting in greater risk of childhood obesity.

STUDY SUMMARY
antibiotic exposure during infancy might be associated with increased risk of overweight and obesity in childhood
SYSTEMATIC REVIEW: Obesity (Silver Spring) 2020 Apr;28(4):793
Pediatricsantibiotic exposure during infancy might be associated with increased risk of overweight and obesity in childhood (Obesity (Silver Spring) 2020 Apr)08/14/2020 12:14:34 PM
PubMed29893794American journal of epidemiologyAm J Epidemiol20181001187102159-21672159 based on systematic review of observational studies with heterogeneity

systematic review of 23 cohort studies evaluating association between exposure to antibiotics prenatally or during infancy (< 24 months old) and childhood overweight and obesity in 1,253,035 children and mothers

antibiotic exposure prenatally or in infancy overall associated with increased risk for overweight or obesity in childhood (risk ratio [RR] 1.13 (95% CI 1.06-1.2), significant but CI may include differences that may not be clinically important

compared to no exposure, exposure to antibiotics in infancy associated with
increased risk of overweight or obesity in childhood overall (RR 1.14, 95% CI 1.06-1.23) in analysis of 13 studies with results limited by significant heterogeneity and CIs that are significant but include differences that may not be clinically important

increased risk of overweight or obesity in childhood with exposure to > 1 antibiotic course during infancy in subgroup analyses by number of courses
RR 1.22 (95% CI 1.06-1.41) for 2-3 courses in analysis of 4 studies, significant but CI includes differences that may not be clinically important

RR 1.22 (95% CI 1.1-1.34) for ≥ 4 courses in analysis of 3 studies

compared to no exposure, prenatal exposure to antibiotics
no significant association with overweight or obesity in childhood for prenatal exposure to antibiotics overall in 5 studies

associated with increased risk for overweight or obesity in childhood with exposure during second trimester (RR 1.13, 95% CI 1.06-1.22) in subgroup analysis of 2 studies, significant but CI includes differences that may not be clinically important

Reference - Obesity (Silver Spring) 2020 Apr;28(4):793
STUDY SUMMARY
antibiotic exposure in infancy, particularly before age 6 months and with repeated exposures, may increase risk of overweight and obesity in childhood
SYSTEMATIC REVIEW: Diabetes Obes Metab 2018 Jun;20(6):1508
based on systematic review of observational studies

systematic review of 13 observational studies assessing association between antibiotic use in infancy and overweight and obesity in 527,504 children

studies assessed antibiotic use before age 24 months and overweight, obesity or body mass index (BMI) after age 24 months

factors associated with increased risk of overweight or obesity in childhood
exposure to antibiotics in infancy (odds ratio [OR] 1.11, 95% CI 1.02-1.2) in analysis of 8 studies with 331,596 children

exposure to > 1 antibiotic treatment (OR 1.24, 95% CI 1.09-1.43) in analysis of 5 studies with 41,288 children

exposure to antibiotics before age 6 months (OR 1.2, 1.04-1.37) in analysis of 5 studies with 295,296 children

no significant association between overweight or obesity in childhood and
exposure to only 1 antibiotic treatment in infancy

exposure to antibiotics after age 6 months

Reference - Diabetes Obes Metab 2018 Jun;20(6):1508
STUDY SUMMARY
any antibiotic use before age 24 months may be associated with small increase in risk of overweight and obesity at age 5 years
COHORT STUDY: Pediatrics 2018 Dec;142(6).doi:10.1542/peds.2018-0290
based on retrospective cohort study

362,550 children were assessed for any antibiotic use at age < 24 months and height and weight at age 0-12 months, 12-30 months, and 48-72 months

58% had ≥ 1 antibiotic prescription before age 24 months

28% of children had overweight or obesity at age 5 years

any antibiotic use before age 24 months associated with increased risk of overweight or obesity at age 5 (adjusted odds ratio 1.05, 95% CI 1.03-1.07)

Reference - Pediatrics 2018 Dec;142(6).doi:10.1542/peds.2018-0290
STUDY SUMMARY
antibiotic exposure at ≤ 6 months old may not be associated with increased weight gain at age 2-5 years
COHORT STUDY: JAMA 2016 Mar 22-29;315(12):1258
based on retrospective cohort study

38,522 singleton children born at ≥ 35 weeks gestation with birth weight ≥ 2,000 g and in ≥ fifth percentile for gestational age were followed until age 7 years or end of study

children with complex chronic conditions or those receiving long-term antibiotics or multiple systemic corticosteroid prescriptions were excluded

14% were exposed to antibiotics at age ≤ 6 months

compared to unexposed children, antibiotic exposure at age ≤ 6 months associated with slight and nonsignificant increase in weight gain at age 2-5 years
difference in weight gain rate +0.7% (95% CI -0.1% to +1.5%)

weight gain rate equivalent to about +0.05 kg (0.11 lbs) (95% CI -0.004 kg [- 0.009 lbs] to +0.11 kg [+ 0.24 lbs])

Reference - JAMA 2016 Mar 22-29;315(12):1258

Procedures, such as adenoidectomy and adenotonsillectomy, may contribute to overweight and obesity:
- Children may have had higher than expected weight gain following adenotonsillectomy in a systematic review of 9 studies with 795 children (Otolaryngol Head Neck Surg 2011 Feb;144(2):154).
- STUDY SUMMARY
  adenotonsillectomy at ≤ 7 years old associated with overweight and obesity at age 8 years
  COHORT STUDY: Pediatrics 2009 Apr;123(4):1095
  based on birth cohort study in 3,963 children followed for 8 years
  
  increased risk of obesity for
  adenotonsillectomy (adjusted odds ratio [OR] 2.36, 95% CI 1.41-3.97)
  
  adenoidectomy alone (adjusted OR 1.94, 95% CI 1.02-3.7)
  
  increased risk of overweight for
  adenotonsillectomy (OR 1.61, 95% CI 1.23-2.1)
  
  adenoidectomy alone (OR 1.26, 95% CI 0.9-1.74)
  
  Reference - Pediatrics 2009 Apr;123(4):1095

Genetic Factors

Genetic factors are reported to account for 30%-50% of variation in adiposity.¹
Single gene syndromes are reported to account for < 1% of obesity in tertiary care centers.¹
Genetic syndromes that typically result in early-onset obesity, exhibit characteristic syndromic features, and include:^1
,3
- Prader-Willi syndrome - most common syndrome associated with obesity
- Bardet-Biedl syndrome (Online Mendelian Inheritance in Man [OMIM] #209900)
- Cohen syndrome (OMIM #216550)
- Alstrom syndrome (OMIM #203800)
- Beckwith-Wiedemann syndrome
- Carpenter syndrome (OMIM #201000)
- Fragile X syndrome
- Rubinstein-Taybi syndrome (OMIM #180849)
- Borjeson-Forssmann-Lehman syndrome (OMIM #301900)
- MOMO syndrome (macrosomia, obesity, macrocephaly, and ocular abnormalities) (OMIM #157980)
- Turner syndrome
Genetic variants currently identified in children with obesity include:^1
,3
- Melanocortin 4 receptor (MC4R) (the most common single gene variant associated with obesity)
- FTOrs9939609
- FLJ35779 (rs2112347)
- Haploinsufficiency
- Leptin and leptin receptor deficiency (only a few cases primarily from consanguineous families have been reported)
- Proopiomelanocortin deficiency
- Proprotein convertase I deficiency
Epigenetic factors also play a role in obesity risk.¹

Race and Ethnicity

Obesity prevalence varies by race and ethnicity.¹

Obesity is more common in Mexican American, Black American, and Native American children compared to non-Hispanic White children in the United States.¹

STUDY SUMMARY

early childhood risk factors for obesity appear to be more common in African American and Hispanic children than in White children

COHORT STUDY: Pediatrics 2010 Apr;125(4):686

based on prospective cohort study

1,343 White, 355 African American, and 128 Hispanic mother-child pairs were assessed during prenatal period and child's first 4 years for risk factors associated with childhood obesity

Prevalence of Risk Factors for Childhood Obesity Compared With White Children

Prevalence of Risk Factors for Childhood Obesity Compared With White Children
Risk Factors	OR in African American Children	OR in Hispanic Children
Prevalence increased compared with White children
Gestational diabetes	NS	3.08 (95% CI 1.51-6.25)
Rapid weight gain (highest quartile of change) from birth to age 6 months	2.01 (95% CI 1.3-3.1)	NS
Lack of exclusive breastfeeding through age 6 months	NS	2.84 (95% CI 1.19-6.74)
Introduction of solid foods at age < 4 months	1.91 (95% CI 1.23-2.97)	2.04 (95% CI 1.11-3.77)
Maternal restriction of child's feedings at age 1 year	6.18 (95% CI 3.29-11.6)	3.35 (95% CI 1.59-7.05)
High pressure on child to eat at age 1 year	2.14 (95% CI 1.36-3.36)	2.32 (95% CI 1.19-4.52)
Mean sleep duration < 12 hours/day at age 6 months to 2 years	3.7 (95% CI 2.3-5.95)	2.53 (95% CI 1.16-5.5)
Television in room where child sleeps at age 4 years	7.65 (95% CI 4.7-12.44)	7.99 (95% CI 3.72-17.14)
Drinking sugar-sweetened beverages at age 2 years	4.11 (95% CI 2.52-6.69)	2.48 (95% CI 1.12-5.51)
Fast food consumption at age 3 years	1.65 (95% CI 1.01-2.71)	3.14 (95% CI 1.19-8.31)
Prevalence decreased compared with White children
Excessive gestational weight gain	0.68 (95% CI 0.52-0.91)	0.66 (95% CI 0.44-0.99)
Maternal smoking in early pregnancy	0.47 (95% CI 0.3-0.74)	NS
Large for gestational age	0.33 (95% CI 0.21-0.53)	0.35 (95% CI 0.17-0.75)
No breastfeeding	0.38 (95% CI 0.25-0.59)	0.31 (95% CI 0.16-0.6)
Abbreviations: NS, difference not significant; OR, odds ratio.

Reference - Pediatrics 2010 Apr;125(4):686

Perinatal Factors, Birth Weight, and Weight Gain in Infancy and Early Childhood

Perinatal factors, including maternal smoking during pregnancy, maternal prepregnancy obesity, and high infant birth weight may increase the risk of childhood obesity.¹
The trajectory of weight gain in infancy and childhood may increase the risk of later obesity, including:
- Rapid weight gain in infancy (Obes Rev 2005 May;6(2):143)
- Early adiposity rebound (Pediatrics 1998 Mar;101(3):E5)
Evidence from systematic reviews and select studies:
- STUDY SUMMARY
  maternal prepregnancy obesity, high infant birth weight, and weight gain in highest percentiles during infancy each associated with later obesity in children and adolescents
  SYSTEMATIC REVIEW: Arch Dis Child 2012 Dec;97(12):1019
  based on systematic review limited by clinical heterogeneity
  
  systemic review of 30 prospective cohort studies with ≥ 2 years of follow-up evaluating factors in infants < 1 year old that may contribute to risk of obesity
  
  median follow-up 6 years (range 2-14 years)
  
  heterogeneity in definitions of obesity and age at follow-up limited analyses
  
  risk factors for obesity included
  maternal prepregnancy weight status
  BMI ≥ 30 kg/m² (odds ratio [OR] at 7 years 4.25, 95% CI 2.86-6.32) in 1 study, similar results at 9-14 years in 1 additional study
  
  BMI 25-29.9 kg/m² (OR at 3 years 1.37, 95% CI 1.18-1.58) in 1 study
  
  high birth weight
  > 4 kg compared to 3-4 kg (OR at 4.5 years 2.3, 95% CI 1.3-7.2) in 1 study
  
  > 3.86 kg compared to 3.18-3.85 kg (OR at 4-5 years 2.17, 95% CI 1.22-3.87) in 1 study
  
  ≥ 4.25 kg compared to 3-3.25 kg (OR at 3-6 years 2.17, 95% CI 1.83-2.59) in 1 study
  
  elevated monthly weight gain from birth to 5 months old
  highest 20th percentile compared to lowest 20th percentile (OR at 4.5 years 3.9, 95% CI 1.9-7.9) in 1 study
  
  highest 33rd percentile compared to lowest 33rd percentile (OR at 9-14 years 1.63, 95% CI 1.05-2.53) in 1 study
  
  Reference - Arch Dis Child 2012 Dec;97(12):1019
- STUDY SUMMARY
  prepregnancy maternal body mass index > 25 kg/m² associated with increased birth weight for gestational age and infant adiposity
  COHORT STUDY: Pediatr Obes 2018 Jan;13(1):46
  based on cohort study
  
  1,074 mother-infant pairs (mean maternal age 32 years) were assessed
  
  161 mother-infant pairs with full data set were included in study
  
  prepregnancy BMI > 25 kg/m² in 44%
  
  comparing prepregnancy BMI > 25kg/m² vs. prepregnancy BMI < 25 kg/m²
  mean birth weight for gestational age 71.6 percentile vs. 63.5 percentile (p = 0.04)
  
  mean skin fold thickness 5.16 mm vs. 4.73 mm (p = 0.02)
  
  no significant difference in infant birth weight by prepregnancy BMI
  
  Reference - Pediatr Obes 2018 Jan;13(1):46
- STUDY SUMMARY
  maternal smoking during pregnancy appears to increase risk of childhood obesity or overweight
  SYSTEMATIC REVIEW: Arch Dis Child 2012 Dec;97(12):1019
  based on systematic review limited by heterogeneity
  
  systemic review of 30 cohort studies evaluating factors in infants < 1 year old that may contribute to risk of obesity at age 2-14 years
  
  BMI values for definition of obesity and age at follow-up varied among studies
  
  maternal smoking during pregnancy associated with increased risk of obesity (odds ratio 1.47, 95% CI 1.3-1.7) in analysis of 7 studies with 57,859 children
  
  Reference - Arch Dis Child 2012 Dec;97(12):1019
- STUDY SUMMARY
  birth weight > 4 kg associated with increased risk of obesity later in life
  SYSTEMATIC REVIEW: PLoS One 2012;7(10):e47776
  based on systematic review limited by significant heterogeneity
  
  systematic review of 58 cohort and 8 case-control studies evaluating relationship between birth weight and later risk of overweight in 643,902 patients aged 1-75 years
  
  birth weight > 4 kg associated with increased risk of obesity (odds ratio 1.66, 95% CI 1.55-1.77) in analysis of 45 studies
  
  Reference - PLoS One 2012;7(10):e47776
- STUDY SUMMARY
  differences in rapid infant weight gain may explain racial and ethnicity disparities in childhood BMI z-score
  COHORT STUDY: Pediatrics 2018 Jan;141(1).doi:10.1542/peds.2017-0865
  based on retrospective cohort study
  
  10,700 children were followed from age 9 months to kindergarten entry and were assessed for race and ethnicity, obesity risk factors, and BMI z-score
  
  54.6% were White, 23.3% were Hispanic, 15.8% were African American, 3.5% were Asian, and 2.9% were American Indian
  
  rate of infant weight gain in first 9 months was the major contributor to racial/ethnic gap in BMI z-score, accounting for 70.5% of gap for White and African American boys
  
  Reference - Pediatrics 2018 Jan;141(1).doi:10.1542/peds.2017-0865
- STUDY SUMMARY
  weight in highest quartile at age 8 months and 18 months, and adiposity rebound by age 43 months may be associated with increased risk of obesity at age 7 years
  COHORT STUDY: BMJ 2005 Jun 11;330(7504):1357
  based on prospective cohort study
  
  8,234 children aged 7 years from Avon longitudinal study of parents and children in United Kingdom
  
  factors associated with increased risk of obesity at 7 years old
  weight at age 8 months in highest quartile (adjusted odds ratio [OR] 3.13, 95% CI 1.4-6.9)
  
  weight at age 18 months in highest quartile (adjusted OR 2.7, 95% CI 1.3-5.6)
  
  catch-up growth between birth and age 2 years (adjusted OR 2.6, 95% CI 1.1-6.2)
  
  adiposity rebound by age 43 months (adjusted OR 15, 95% CI 5.3-42.3)
  
  parental obesity
  paternal obesity (adjusted OR 2.54, 95% CI 1.7-3.8)
  
  maternal obesity (adjusted OR 4.25, 95% CI 2.9-6.3)
  
  both parents with obesity (adjusted OR 10.4, 95% CI 5.1-21.3)
  
  Reference - BMJ 2005 Jun 11;330(7504):1357, editorial can be found in BMJ 2005 Jun 11;330(7504):1339, commentary can be found in BMJ 2005 Aug 20;331(7514):452
- STUDY SUMMARY
  overweight at age 5 years associated with increased risk of incident obesity by age 14 years
  COHORT STUDY: N Engl J Med 2014 Jan 30;370(5):403
  based on prospective cohort study
  
  7,738 children entering kindergarten in 1998 (mean age 5.6 years) in United States were followed for 9 years
  
  12.4% had obesity and 14.9% were classified as overweight at baseline
  
  incidence of obesity per 1,000 person-years
  17.2 in children of normal weight at baseline
  
  91.5 in children overweight at baseline
  
  overweight associated with increased risk of obesity compared to normal weight (incidence ratio 5.3, 95% CI 4.3-6.6)
  
  Reference - N Engl J Med 2014 Jan 30;370(5):403, editorial can be found in N Engl J Med 2014 Jan 30;370(5):475

Parental and Family Factors

The relationship between parental obesity and obesity in children and adolescents has long been established.¹
The risk of obesity in children is reported to increase by 2-3 times if 1 parent has obesity and up to 15 times if 2 parents have obesity.¹
Parents may increase the risk of childhood obesity through psychosocial and/or behavioral factors that may include:^1
,3
- Stress and depression, particularly maternal stress
- Feeding style, including indulgent or restrictive feeding (Front Psychol 2015;6:1849full text)
- Modeling eating behaviors
- Use of food for reward or punishment
- Parenting style, such as authoritarian or indulgent parenting styles
- Physical, emotional, and sexual abuse
- Maternal lifestyle factors, including diet, physical activity, smoking, and alcohol consumption
Evidence from systematic reviews and select studies:
- STUDY SUMMARY
  chronic maternal depression after childbirth may be associated with child obesity
  SYSTEMATIC REVIEW: Prev Med 2014 Feb;59:60
  based on systematic review
  
  systematic review of 9 prospective studies evaluating the relationship between maternal depression at any stage after childbirth and child obesity
  
  chronic depression (depression on multiple measurement occasions) but not episodic depression (depression at single measurement occasion) associated with increased risk of child obesity
  
  Reference - Prev Med 2014 Feb;59:60
- STUDY SUMMARY
  psychological stress in families may be associated with obesity in children
  COHORT STUDY: J Pediatr 2008 Dec;153(6):839
  based on prospective cohort study
  
  7,443 Swedish families reporting psychological stress across 4 domains including
  serious life events
  
  parenting stress
  
  lack of social support
  
  parental worries
  
  obesity in 4.2% of children aged 5-6 years
  
  increased risk of obesity in children from families that reported stress in at least 2 of 4 domains (adjusted odds ratio 2.6, 95% CI 1.3-5.4)
  
  Reference - J Pediatr 2008 Dec;153(6):839
- STUDY SUMMARY
  harsh physical punishment and maltreatment in childhood may increase risk of obesity in adulthood
  CROSS-SECTIONAL STUDY: Pediatrics 2013 Aug;132(2):e333
  based on cross-sectional study
  
  34,266 adults ≥ 20 years old as part of National Epidemiologic Survey on Alcohol and Related Conditions evaluated for history of harsh physical punishment and childhood maltreatment and current physical health
  
  harsh physical punishment defined as pushing, grabbing, shoving, slapping, and hitting
  
  childhood maltreatment defined as severe physical abuse, sexual abuse, emotional abuse, neglect, or exposure to intimate partner violence before 18 years old
  
  compared to children experiencing no harsh physical punishment or child maltreatment, increased risk of obesity in patients with history of
  harsh physical punishment (odds ratio [OR] 1.24, 95% CI 1.05-1.47)
  
  child maltreatment (OR 1.2, 95% CI 1.13-1.28)
  
  Reference - Pediatrics 2013 Aug;132(2):e333, editorial can be found in Pediatrics 2013 Aug;132(2):e500
- STUDY SUMMARY
  authoritarian, permissive, or neglectful parenting styles associated with risk of overweight in first grade
  COHORT STUDY: Pediatrics 2006 Jun;117(6):2047
  based on retrospective cohort study
  
  872 first-grade children were assessed for parenting style, height, and weight
  
  11.1% had obesity
  
  parenting style classified as
  authoritative - high expectations for self-control and high sensitivity and emotional involvement
  
  authoritarian - high expectations for self-control and low sensitivity and emotional involvement
  
  permissive - low expectations for self-control and high sensitivity and emotional involvement
  
  neglectful - low expectations for self-control and low sensitivity and emotional involvement
  
  adjusted prevalence of obesity by parenting style
  3.9% in 179 children with authoritative mothers (reference group)
  
  17.1% in 298 children with authoritarian mothers (odds ratio [OR] 4.88, 95% CI 2,15-11.1)
  
  9.8% in 132 children with permissive mothers (OR 2.84, 95% CI 1.1-7.35)
  
  9.9% in 263 children with neglectful mothers (OR 2.67, 95% CI 1,12-6.38)
  
  Reference - Pediatrics 2006 Jun;117(6):2047
- STUDY SUMMARY
  maternal healthy lifestyle practices including maintenance of healthy body weight, moderate-to-vigorous exercise ≥ 150 minutes/week, not smoking, and light-to-moderate alcohol intake associated with decreased risk of obesity in children and adolescents
  COHORT STUDY: BMJ 2018 Jul 4;362:k2486
  Endocrine_and_Metabolic_Disorders Nutrition Pediatricsmaternal healthy lifestyle practices including maintenance of healthy body weight (body mass index 18.5-24.9 kg/m2), moderate-to-vigorous exercise ≥ 150 minutes/week, not smoking, and light-to-moderate alcohol intake associated with decreased risk of obesity in children and adolescents (BMJ 2018 Jul 4)09/19/2018 10:54:00 AM29973352
  based on prospective cohort study
  
  24,289 children from the Growing Up Today Study (GUTS) who were born to 16,945 women from the Nurses’ Health Study II (NHSII) were evaluated
  children aged 9-14 years at time of enrollment and completed self-administered follow-up questionnaires every 1-2 years
  
  women aged 25-42 years at time of enrollment and completed follow-up questionnaires every 2-4 years
  
  5.3% of children developed obesity over median 5-year follow-up
  
  maternal factors associated with decreased risk of obesity in children
  BMI 18.5-24.9 kg/m² (adjusted risk ratio [RR] 0.44, 95% CI 0.39-0.5) compared to underweight, overweight, or obesity
  
  moderate-to-vigorous exercise ≥ 150 minutes/week (adjusted RR 0.79, 95% CI 0.69-0.91) compared to no moderate-to-vigorous exercise or moderate-to-vigorous exercise 1-149 minutes/week
  
  current nonsmoker (adjusted RR 0.69, 95% CI 0.56-0.86) compared to current smoker
  
  light-to-moderate alcohol intake (1-14.9 g/day) (adjusted RR 0.88, 95% CI 0.79-0.99) compared to no alcohol intake or intake ≥ 15 g/day
  
  maternal healthy diet (based on Alternate Healthy Eating Index 2010 diet score) not significantly associated with risk of obesity in children
  
  Reference - BMJ 2018 Jul 4;362:k2486
- STUDY SUMMARY
  higher maternal consumption of ultra-processed foods during childrearing period associated with increased risk of child overweight or obesity
  COHORT STUDY: BMJ 2022 Oct 5;379:e071767
  based on cohort study
  
  19,958 children born to 14,553 mothers in Nurses' Health Study II and Growing Up Today Study I and II cohorts in the United States were followed until child's age was 18 years or until onset of child overweight or obesity
  
  mother-child pairs with maternal energy intake < 600 or > 3,500 kcal/day, pregnancy during follow-up, and child overweight, obesity, or missing BMI at baseline were excluded
  
  maternal consumption of ultra-processed foods during childrearing period was categorized into 5 groups
  mean 3.4 servings/day (group 1)
  
  mean 5.2 servings/day (group 2)
  
  mean 6.6 servings/day (group 3)
  
  mean 8.4 servings/day (group 4)
  
  mean 12.1 servings/day (group 5)
  
  child overweight or obesity was defined using International Obesity Task Force age- and sex-specific BMI cutoff values
  
  overall, 12.4% of children developed overweight or obesity during median follow-up of 4 years
  
  rates of child overweight or obesity
  11.5% among children born to mothers in group 1
  
  11% among children born to mothers in group 2 (not significant vs. group 1)
  
  12.6% among children born to mothers in group 3 (not significant vs. group 1)
  
  12% among children born to mothers in group 4 (not significant vs. group 1)
  
  14.9% among children born to mothers in group 5 (adjusted relative risk 1.26, 95% CI 1.08-1.47 vs. group 1)
  
  no significant association between maternal consumption of ultra-processed foods during peripregnancy and increased risk of child overweight or obesity
  
  Reference - BMJ 2022 Oct 5;379:e071767

Diet-Related Factors

Several dietary practices may increase the risk of obesity in childhood, including:^1
,3
- Early feeding practices, including not exclusively breastfeeding and bottle feeding at age 24 months
- Consumption of sugar-sweetened beverages
- Skipping breakfast
- Eating sweet snacks
- Eating fast foods and foods consumed away from home
- Eating large portion sizes
- Limited access to healthy options
Evidence from systematic reviews and select studies:
- STUDY SUMMARY
  no breastfeeding and partial breastfeeding with formula supplementation at 6 months may each increase risk of overweight at age 1 year compared to exclusive breastfeeding
  COHORT STUDY: Pediatrics 2018 Oct;142(4).doi:10.1542/peds.2018-1092
  based on prospective cohort study
  
  2,553 mother-child pairs in Canada were assessed for breastfeeding initiation and cessation, use of formula, introduction of other fluids and solid foods, and overweight status in infant at 12-month follow-up
  
  96.6% initiated breastfeeding, and 43.5% were breastfeeding at 12 months
  
  73.9% had solid foods at < age 6 months
  
  4.9% were overweight at 12 months
  
  factors associated with increased risk of overweight at 12 months, compared to exclusive breastfeeding at 6 months
  no breastfeeding at 6 months (adjusted odds ratio [OR] 3.2, 95% CI 1.58-6.51)
  
  partial breastfeeding with formula at 6 months (OR 2.03, 95% CI 1-4.11)
  
  duration of breastfeeding and risk of overweight at 12 months, compared to breastfeeding ≥ 12 months and adjusted for timing of solid food introduction
  never breastfeeding (adjusted OR 2.58, 95% CI 1-6.62)
  
  breastfeeding < 3 months (adjusted OR 4.06, 95% CI 2.21-7.45)
  
  breastfeeding 3 months to < 6 months (adjusted OR 1.99, 95% CI 1.02-3.86)
  
  breastfeeding 6 months to < 12 months (adjusted OR 1.64, 95% CI 0.98-2.74)
  
  partial breastfeeding without formula (just solid foods) at 6 months and brief use of formula in hospital were not associated with overweight at 12 months
  
  Reference - Pediatrics 2018 Oct;142(4).doi:10.1542/peds.2018-1092
- STUDY SUMMARY
  bottle use at age 24 months associated with increased risk of obesity at age 5.5 years
  COHORT STUDY: J Pediatr 2011 Sep;159(3):431
  based on prospective cohort study
  
  6,750 children from Early Childhood Longitudinal Study evaluated at age 5.5 years for obesity
  
  17.6% prevalence of obesity at age 5.5 years, and 22.3% of children were using a bottle at age 24 months
  
  bottle use at age 24 months associated with increased risk of obesity (adjusted odds ratio 1.33, 95% CI 1.05-1.68)
  
  Reference - J Pediatr 2011 Sep;159(3):431
- STUDY SUMMARY
  increased consumption of sugar-sweetened beverages associated with increased risk of overweight or obesity
  SYSTEMATIC REVIEW: BMJ 2012 Jan 15;346:e7492
  based on systematic review
  
  systematic review of 68 studies (30 randomized trials, 38 cohort studies) evaluating association between intake of dietary sugars and body weight in adults and children
  
  compared to low consumption, increased consumption of sugar-sweetened beverages associated with increased risk of having overweight or obesity compared to lowest intake (odds ratio 1.55, 95% CI 1.32-1.82) in analysis of 5 prospective cohort studies with 12,317 children followed for ≥ 12 months
  
  Reference - BMJ 2012 Jan 15;346:e7492
- STUDY SUMMARY
  100% fruit juice consumption may not be associated with significant increase in BMI z-score in healthy-weight children and adolescents
  SYSTEMATIC REVIEW: Pediatrics 2017 Apr;139(4).doi:10.1542/peds.2016-2454
  based on systematic review of observational studies
  
  systematic review of 8 prospective cohort studies evaluating association between 100% fruit juice consumption and change in BMI in 34,470 children and adolescents
  
  mean BMI at baseline 16.2-18.6 kg/m²
  
  follow-up duration ranged from 6 months to 10 years
  
  clinically significant change in BMI z-score defined as 0.25-0.5 units
  
  change in BMI z-score per 1 serving/day increment of 100% fruit juice over 1 year
  0.046 units (95% CI 0.0-0.093 units) in analysis of 3 studies with 8,238 children aged 1-6 years
  
  0.0 units (95% CI -0.001 to +0.001 units) in analysis of 5 studies with 19,799 patients aged 7-18 years
  
  Reference - Pediatrics 2017 Apr;139(4).doi:10.1542/peds.2016-2454
  
  DynaMed Commentary
  Included studies varied in adjustment for covariates. Consideration should be given to other dietary factors associated with fruit juice consumption that may affect obesity risk.
- STUDY SUMMARY
  children skipping breakfast may increase risk of overweight and obesity, and parents skipping breakfast may increase risk of children skipping breakfast
  COHORT STUDY: Int J Obes (Lond) 2018 Oct;42(10):1724
  based on prospective cohort study
  
  43,663 children (mean age 1.5 years) were followed until age 12 years and assessed for breakfast consumption, parents' breakfast consumption, and BMI
  
  children skipping breakfast associated with increased risk of overweight and obesity
  overweight (odds ratio [OR] 1.18, 95% CI 1.05-1.32)
  
  obesity (OR 2.16, 95% CI 1.55-2.99)
  
  parents skipping breakfast associated with child skipping breakfast
  mother (OR calculated for multiple ages, ranging from OR 1.9, 95% CI 1.56-2.31 to OR 2.98, 95% CI 2.28-3.9)
  
  father (OR calculated for multiple ages, ranging from OR 1.42, 95% CI 1.33-1.51 to 2.43, 95% CI 1.9-3.11)
  
  Reference - Int J Obes (Lond) 2018 Oct;42(10):1724
- STUDY SUMMARY
  higher food insecurity at age 15 years may be associated with faster increase in BMI in female children
  COHORT STUDY: J Pediatr 2018 Nov;202:115
  Family_Medicine Pediatricshigher food insecurity at age 15 years may be associated with faster increase in BMI in girls (J Pediatr 2018 Nov)10/30/2019 02:36:28 PM
  based on prospective cohort study
  
  559 participants (52% female) had assessment of food insecurity and BMI from age 15 to 31 years
  
  higher food insecurity at age 15 years associated with faster increase in BMI over time (p < 0.05); consistent results in females but not in males
  
  faster increase in food insecurity from age 15 to 29 years associated with faster increase in BMI from age 16 to 31 years (p < 0.05)
  
  Reference - J Pediatr 2018 Nov;202:115

Physical Activity and Screen Time

Low levels of physical activity and more engagement in sedentary activities such as use of televisions, computers, and other screens are positively associated with overweight and obesity in children and adolescents.^1
,3
Neighborhood features such as walkability and access to parks and playgrounds may affect physical activity levels (Int J Behav Nutr Phys Act 2017 Nov 16;14(1):158).
Evidence from systematic reviews and select studies:
- STUDY SUMMARY
  reduced physical activity and physical fitness associated with overweight in adolescents
  SYSTEMATIC REVIEW: BMC Pediatr 2013 Feb 1;13:19
  based on systematic review
  
  systematic review of 2 prospective cohort and 12 cross-sectional studies comparing level of activity and physical fitness to overweight in adolescents aged 11-23 years
  
  inverse relationship between physical fitness and overweight reported in all studies
  
  inverse relationship between physical activity and overweight reported in 4 studies
  
  Reference - BMC Pediatr 2013 Feb 1;13:19
- STUDY SUMMARY
  decline in physical activity during adolescence associated with increase in body mass index
  COHORT STUDY: Lancet 2005 Jul 23;366(9482):301
  based on prospective cohort study
  
  1,152 African American girls and 1,135 White girls aged 9-10 years had BMI assessed annually for 7-10 years
  
  activity was assessed at baseline, ages 3, 5, and 7-10 years
  
  BMI difference at ages 18-19 years comparing inactive vs. active adolescents
  + 2.98 kg/m² for African Americans girls (p < 0.0001)
  
  + 2.1 kg/m² for White girls (p < 0.0001)
  
  each decline in activity of 10 metabolic equivalent-times/week associated with increase in BMI of
  0.14 kg/m² for African Americans girls
  
  0.09 kg/m² for White girls
  
  moderately active girls had BMI changes midway between those for active and inactive girls
  
  Reference - Lancet 2005 Jul 23;366(9482):301, editorial can be found in Lancet 2005 Jul 23-29;366(9482):268, commentary can be found in Lancet 2005 Dec 10;366(9502):2003
- STUDY SUMMARY
  lack of sports team participation, television use ≥ 3 hours per day, and tobacco use may each be associated with increased body mass index in adolescents
  CROSS-SECTIONAL STUDY: Prev Chronic Dis 2018 Nov 8;15:E137
  based on cross-sectional study
  
  15,624 adolescents from 2015 Youth Risk Behavior Survey were assessed for obesity, physical activity, screen time, and tobacco use
  
  13.9% had obesity
  
  factors associated with increased risk of obesity
  not being on a sports team (adjusted odds ratio [OR] 1.61, 95% CI 1.31-1.98)
  
  using tobacco products (adjusted OR 1.42, 95% CI 1.14-1.77)
  
  watching television ≥ 3 hours/day (adjusted OR 1.38, 95% CI 1.09-1.76)
  
  Reference - Prev Chronic Dis 2018 Nov 8;15:E137
- STUDY SUMMARY
  increased television (TV) viewing associated with obesity and overweight
  COHORT STUDY: BMJ 2005 Jun 11;330(7504):1357COHORT STUDY: Arch Pediatr Adolesc Med 2006 Apr;160(4):417CROSS-SECTIONAL STUDY: Pediatrics 2013 Sep;132(3):468
  based on 2 prospective cohort studies and 1 cross-sectional studies
  
  cohort study of 8,234 children aged 7 years form Avon longitudinal study of parents and children in United Kingdom
  television watching > 8 hours/week at age 3 years associated with increased risk of obesity at age 7 years (adjusted odds ratio 1.55, 95% CI 1.13-2.12)
  
  Reference - BMJ 2005 Jun 11;330(7504):1357, editorial can be found in BMJ 2005 Jun 11;330(7504):1339, commentary can be found in BMJ 2005 Aug 20;331(7514):452
  
  cohort study of 1,016 children evaluated at ages 36 and 54 months for BMI and TV viewing
  exposure to ≥ 2 hours of TV per day associated with increased risk of overweight at
  age 36 months (odds ratio [OR] 2.92, 95% CI 1.36-6.24)
  
  age 54 months (OR 1.71, 95% CI 1.03-2.83)
  
  Reference - Arch Pediatr Adolesc Med 2006 Apr;160(4):417
  
  cross-sectional study of 1,714 children aged 10-12 years evaluated for health behaviors associated with childhood obesity
  18.4% boys and 15.8% girls had obesity
  
  ≥ 2 hours television viewing per day associated with increased risk of obesity in
  boys (odds ratio [OR] 1.19, 95% CI 1.07-1.32)
  
  girls (OR 1.19, 95% CI 1.06-1.34)
  
  Reference - Pediatrics 2013 Sep;132(3):468
- STUDY SUMMARY
  TV in child's bedroom may increase risk for overweight
  COHORT STUDY: Int J Obes (Lond) 2017 Oct;41(10):1503CROSS-SECTIONAL STUDY: Int J Obes (Lond) 2007 Apr;31(4):644
  based on 1 cohort study and 1 cross-sectional study
  
  cohort study of 12,556 children from United Kingdom Millennium Cohort Study assessed for TV in bedroom, screen time, BMI, and overweight and followed from age 7 to 11 years
  25% of boys and 30% of girls were overweight at age 11 years
  
  TV in bedroom at age 7 years associated with increased risk of overweight at age 11 in
  girls (adjusted relative risk [RR] 1.31, 95% CI 1.15-1.48)
  
  boys (adjusted RR 1.21, 95% CI 1.07-1.36)
  
  watching TV or DVD ≥ 3 hours associated with increased risk of overweight among girls only (adjusted RR 1.27, 95% CI 1.07-1.52, compared to < 1 hour during weekday)
  
  no significant association between TV or DVD use and BMI in boys at age 11 years
  
  Reference - Int J Obes (Lond) 2017 Oct;41(10):1503
  
  cross-sectional study of 2,343 children aged 9-12 years comparing weight status to presence of TV in bedroom
  overweight in 27.3% with TV in bedroom compared to 17.7% without (adjusted odds ratio 1.32, 95% CI 1.03-1.7)
  
  Reference - Int J Obes (Lond) 2007 Apr;31(4):644
- STUDY SUMMARY
  playing electronic games ≥ 4 hours/day and TV in bedroom may each be significantly associated with severe obesity in children
  CROSS-SECTIONAL STUDY: Child Obes 2019 Jan;15(1):21
  Pediatrics Primary_Careplaying electronic games ≥ 4 hours/day and TV in bedroom may each be significantly associated with severe obesity in children (Child Obes 2019 Jan)07/08/2019 11:04:50 AM
  based on cross-sectional study
  
  412 children (mean age 13.7 years) with obesity were assessed for time spent gaming (video or other electronic games), TV in bedroom, use of games with console, and parental limits on gaming
  
  44% had class 3 severe obesity (defined as BMI ≥ 140% of 95th percentile)
  
  playing electronic games ≥ 4 hours/day significantly associated with class 3 severe obesity compared to playing games < 4 hours/day (adjusted odds ratio 1.94, 95% CI 1.27-3)
  
  comparing children with class 3 severe obesity vs. other obesity
  TV in bedroom in 76% vs. 63% (p = 0.004)
  
  games played on console in 39% vs. 27% (p = 0.03)
  
  parental limits on type of games played in 7.3% vs. 16.3% (p = 0.006)
  
  Reference - Child Obes 2019 Jan;15(1):21

Reduced Sleep Duration and Sleep Quality

Less sleep and poor-quality sleep may be associated with childhood obesity.¹
STUDY SUMMARY
sleep duration may be inversely related to risk of obesity in children
SYSTEMATIC REVIEW: Sci Rep 2015 Nov 5;5:16160SYSTEMATIC REVIEW: Obesity (Silver Spring) 2008 Feb;16(2):265
based on 2 systematic reviews

systematic review of 25 prospective cohort studies assessing sleep duration and overweight and obesity in 56,584 children and adolescents
mean follow-up 3.4 years

comparing children with longest vs. shortest sleep duration, risk of overweight or obesity increased (odds ratio [OR] 1.76, 95% CI 1.39-2.23) in analysis of 7 studies

with every 1-hour increase in sleep, risk of overweight or obesity decreased (OR 0.79, 95% CI 0.70-0.89) in analysis of 8 studies

Reference - Sci Rep 2015 Nov 5;5:16160

systematic review of 3 cohort, 2 case-control, and 12 cross-sectional studies evaluating sleep duration and childhood overweight or obesity in 55,792 children aged 0-18 years
compared to age-specific sleep duration recommendations, reduced sleep duration associated with increased risk of overweight and obesity
odds ratio 1.58, 95% CI 1.26-1.98 in analysis of 11 studies

risk higher for shorter sleep durations

results limited by significant heterogeneity

Recommended Sleep Duration by Age
Recommended Sleep Duration by Age
< 5 Years 5-10 Years ≥ 10 Years

> 11 hours ≥ 10 hours ≥ 9 hours

Reference - Obesity (Silver Spring) 2008 Feb;16(2):265

Recommended Sleep Duration by Age
< 5 Years	5-10 Years	≥ 10 Years
> 11 hours	≥ 10 hours	≥ 9 hours

Psychosocial Factors in Childhood

Stress in children may increase the risk of obesity by contributing to eating as a coping strategy for suppressing negative emotions and decreasing physical activity.^1
,3
Depression in adolescents may increase the risk of obesity by:³
- Increasing appetite and unhealthy food choices
- Reducing sleep
- Reducing physical activity
- Contributing to the use of antidepressant medications that may cause weight gain
- Increasing insulin resistance
- STUDY SUMMARY
  major depressive disorder associated with obesity in adolescent males and non-Hispanic Black adolescents
  COHORT STUDY: J Behav Med 2012 Apr;35(2):149
  based on cohort of 4,150 adolescents from National Health and Nutrition Examination Survey (NHANES)
  
  major depressive disorder not significantly associated with obesity in overall analysis
  
  major depressive disorder associated with increased risk of obesity in
  males (adjusted odds ratio 2.7, 95% CI 1.1-7.1)
  
  non-Hispanic Black adolescents (adjusted odds ratio 3.1, 95% CI 1.1-8.3)
  
  Reference - J Behav Med 2012 Apr;35(2):149
STUDY SUMMARY
attention-deficit/hyperactivity disorder symptoms may be associated with overweight and obesity in adolescent girls
COHORT STUDY: Int J Obes (Lond) 2012 Jul;36(7):963
based on retrospective cohort study

11,159 children and adolescents aged 6-17 years evaluated for BMI and by hyperactivity/inattention subscale of Strengths and Difficulties Questionnaire

elevated scores associated with increased risk of obesity in girls aged 14-17 years (adjusted odds ratio 1.1, 95% CI 1.02-1.18)

Reference - Int J Obes (Lond) 2012 Jul;36(7):963

Environmental Exposures to Chemicals and Toxins

Exposure to environmental toxins, either in utero or early in life, may increase the risk of subsequent obesity (Annu Rev Pharmacol Toxicol 2019 Jan 6;59:89).
STUDY SUMMARY
increased urinary bisphenol A (BPA) level may be associated with increased obesity risk in children
CROSS-SECTIONAL STUDY: Pediatrics 2013 Sep;132(3):e637CROSS-SECTIONAL STUDY: JAMA 2012 Sep 19;308(11):1113
based on 2 cross-sectional studies

3,370 children aged 6-18 years in 2003-2010 NHANES were assessed for urinary bisphenol A (BPA) and BMI percentile measurements
compared with lowest BPA quartile (< 1.3 ng/mL), increased risk of obesity with BPA quartile
2 (1.3-2.6 ng/mL) (adjusted odds ratio [OR] 1.74, 95% CI 1.17-2.6)

3 (> 2.6-4.9 ng/mL) (adjusted OR 1.64, 95% CI 1.09-2.47)

4 (> 4.9 ng/mL) (adjusted OR 2.01, 95% CI 1.36-2.98)

Reference - Pediatrics 2013 Sep;132(3):e637, editorial can be found in Pediatrics 2013 Sep;132(3):e747

2,838 children aged 6-19 years in 2003-2008 NHANES study had measurement of urinary bisphenol A (BPA) concentration
34.1% were overweight and 17.8% had obesity

median urinary BPA level 2.8 ng/mL

prevalence of obesity significantly decreased in lowest urinary BPA quartile (p < 0.001 for each of 3 highest BPA quartiles vs. lowest BPA quartile)

no significant difference in prevalence of overweight comparing second, third, and highest quartile to lowest quartile

Reference - JAMA 2012 Sep 19;308(11):1113
STUDY SUMMARY
high levels of gestational lead exposure in children born to mothers with prepregnancy normal weight status associated with increased risk of childhood overweight or obesity among minority populations in the United States
COHORT STUDY: Int J Obes (Lond) 2022 Aug;46(8):1435
based on cohort study

1,442 mother-child pairs who completed ≥ 1 postnatal well-child care visit beyond age 2 years and had data for maternal BMI and red blood cell metal biomarkers measured within 24-72 hours after delivery in Boston Birth Cohort, United States were assessed
race or ethnicity was Black in 67%, Hispanic in 20%, unspecified in 8%, and White in 5%

24% of children were born preterm and 23% had low birth weight

children were followed up to age 15 years

child overweight or obesity was defined as BMI ≥ 85th percentile for age and sex at last follow-up visit beyond age 2 years

maternal prepregnancy overweight or obesity was defined as BMI ≥ 25 kg/m² (52.4% had overweight or obesity and 47.6% had normal weight)

maternal metal and micronutrient levels were stratified by tertiles; among mothers with overweight or obesity, high metal and micronutrient levels were defined as
mercury > 1.44 mcg/L

lead > 2.02 mcg/dL

cadmium > 0.54 mcg/dL

selenium > 260 mcg/dL

folate > 28.6 nmol/L

in children born to mothers with normal prepregnancy weight, rates of childhood overweight or obesity comparing high vs. low exposure to metal and micronutrient levels
lead 34.5% vs. 23.3% (relative risk 1.45, 95% CI 1.11-1.89)

mercury 32.2% vs. 27.2% (not significant)

cadmium 31.2% vs. 29% (not significant)

selenium 30.4% vs. 30.4% (not significant)

folate 30.2% vs. 30.8% (not significant)

no significant difference in rates of childhood overweight or obesity comparing high vs. low exposure to metal and micronutrient levels in children born to mothers with prepregnancy overweight or obesity

Reference - Int J Obes (Lond) 2022 Aug;46(8):1435

Associated Conditions

Dietary Deficiencies

Obesity in childhood is associated with nutritional deficiencies, including:
- Calcium
- Vitamin D
- Fat-soluble antioxidants vitamin A and vitamin E
- Reference - J Pediatr Gastroenterol Nutr 2013 Jan;56(1):99
STUDY SUMMARY
overweight and obesity associated with increased risk of vitamin D deficiency in children
CROSS-SECTIONAL STUDY: Pediatrics 2013 Jan;131(1):e152
based on cross-sectional study

12,292 children aged 6-18 years from National Health and Nutrition Examination Survey (NHANES) from 2003 to 2006 were assessed for vitamin D deficiency (25-hydroxyvitamin-D < 20 ng/mL)

prevalence of vitamin D deficiency 21% in those with healthy weight, 29% in those with overweight, 34% in those with obesity, and 49% in those with severe obesity

among children with severe obesity, prevalence of vitamin D deficiency 27% in White, 52% in Latino, and 87% in African American children

compared to healthy-weight children, increased risk of vitamin D deficiency in children with
overweight (adjusted odds ratio [OR] 1.7, 95% CI 1.2-2.4)

obesity (adjusted OR 1.8, 95% CI 1.3-2.5)

severe obesity (adjusted OR 2.3, 95% CI 1.1-4.5)

Reference - Pediatrics 2013 Jan;131(1):e152

Etiology and Pathogenesis

Causes

Obesity is most commonly attributed to an energy imbalance due to caloric intake in excess of physical expenditure in combination with genetic predisposition.¹
Less commonly, obesity may be caused by an underlying syndrome or endocrine disorder.¹

Pathogenesis

The pathogenesis of obesity is complex and not fully understood.
Two related but distinct processes are involved:
- A sustained positive energy balance in which energy intake exceeds energy expenditure
- An energy homeostasis that resets the body weight "set point" at a higher value, making it difficult to maintain weight loss
Many factors are thought to influence these processes, including:
- Metabolic efficiency, which may be largely genetically determined and prevents weight gain by affecting the ability to dispose of excess energy as heat and decreasing the ability to store energy as fat
- The sympathetic nervous system, which affects homeostasis and metabolism including promotion of pancreatic insulin release, adipose tissue lipolysis, skeletal muscle glucose uptake, and hepatic glucose mobilization
- Homeostatic and hedonic regulatory systems, which control food intake:
  - The homeostatic pathway stimulates eating behavior when energy stores are low with signals including circulating concentrations of nutrients, gastrointestinal hormones, insulin, leptin, and vagal afferents.
  - The hedonic pathway is reward-based and may override the homeostatic system.
  - An imbalance in the 2 systems is thought to contribute to obesity.
- Neurotransmitters including serotonin and dopamine:
  - Decreased serotonin signaling in the hypothalamus may promote overconsumption of food by impairing negative feedback from ingested energy on food intake.
  - Decreased dopaminergic signaling, which relays rewarding aspects of food-related stimuli, may promote overconsumption of food beyond homeostatic needs in order to compensate for lower reward sensations.
- Gastrointestinal hormones, which are secreted in response to fasting or exposure to ingested nutrients and affect eating behavior by promoting satiation or hunger, and include:
  - Ghrelin stimulates appetite, promotes meal initiation, and affects regulation of long-term energy balance.
  - Anorexigenic intestinal hormones (glucagon-like peptide 1, peptide YY, and cholecystokinin), are secreted in response to food intake and affect digestion, insulin secretion, postdigestive metabolism, and satiety.
- A leptin pathway abnormality resulting in decreased sensitivity to leptin levels, which increases food intake and suppresses energy expenditure
- Insulin:
  - Insulin orchestrates postprandial metabolism and contributes to nutritional feedback through effects on the hypothalamus that promote satiety and signal reward.
  - The insulin resistance that occurs with obesity may impair insulin-mediated nutritional feedback.
- Circadian rhythm misalignment due to altered timing of food intake, which can affect obesity through metabolic influences
- Genetic influences:
  - Genetic variants in leptin receptor affect obesity through impaired leptin receptor signaling.
  - Genetic influences are likely polygenic, in which the obesity phenotype is caused by the additional effect of variants in multiple genes.
- Epigenetic factors may increase susceptibility to environmental factors that affect obesity.
PubMed30639246Metabolism: clinical and experimentalMetabolism201903019226-3626References - Metabolism 2019 Mar;92:26, Endocr Rev 2017 Aug 1;38(4):267

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DynaMed Levels of Evidence

Quickly find and determine the quality of the evidence.

DynaMed provides easy-to-interpret Level of Evidence labels so users can quickly find and determine the quality of the best available evidence. Evidence may be labeled in one of three levels:

1Level 1 (likely reliable) Evidence

Representing research results addressing clinical outcomes and meeting an extensive set of quality criteria which minimizes bias.

There are two types of conclusions which can earn a Level 1 label: levels of evidence for conclusions derived from individual studies and levels of evidence for conclusions regarding a body of evidence.

2Level 2 (mid-level) Evidence

Representing research results addressing clinical outcomes, and using some method of scientific investigation, but not meeting the quality criteria to achieve Level 1 evidence labeling.

3Level 3 (lacking direct) Evidence

Representing reports that are not based on scientific analysis of clinical outcomes. Examples include case series, case reports, expert opinion, and conclusions extrapolated indirectly from scientific studies.

Grades of Recommendation

Guideline producers are now frequently using classification approaches for their evidence and recommendations, and these classifications are recognized and requested by guideline users. When summarizing guideline recommendations for DynaMed users, the DynaMed Editors are using the guideline-specific classifications and providing guideline classification approach when this is done.

Download the full version of Levels of Evidence

Condition

Obesity in Children and Adolescents

Background Information

Description

Definitions

Epidemiology

Prevalence

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Risk Factors

Overview of Risk Factors for Obesity in Children

Endocrine Disorders

Neurologic and Hypothalamic Conditions

Medications and Procedures

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Genetic Factors

Race and Ethnicity

Details

Perinatal Factors, Birth Weight, and Weight Gain in Infancy and Early Childhood

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Parental and Family Factors

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Diet-Related Factors

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Physical Activity and Screen Time

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Reduced Sleep Duration and Sleep Quality

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Psychosocial Factors in Childhood

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Environmental Exposures to Chemicals and Toxins

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Associated Conditions

Dietary Deficiencies

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Etiology and Pathogenesis

Causes

Pathogenesis

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DynaMed Levels of Evidence

Quickly find and determine the quality of the evidence.

1Level 1 (likely reliable) Evidence

2Level 2 (mid-level) Evidence

3Level 3 (lacking direct) Evidence

Grades of Recommendation