The objective of this technical report is to provide clinicians with actionable evidence-based information upon which to make treatment decisions. In addition, this report will provide an evidence base on which to inform clinical practice guidelines for the management and treatment of overweight and obesity in children and adolescents.
To this end, the goal of this report was to identify all relevant studies to answer 2 overarching key questions: (KQ1) “What are effective clinically based treatments for obesity?” and (KQ2) “What is the risk of comorbidities among children with obesity?” See Appendix 1 for the conceptual framework and a priori Key Questions.
Obesity is a common concern in pediatric practice. In caring for patients with obesity or patients who may be at risk for developing obesity, clinicians have many unanswered questions. Examples of these questions include: What is the best way to identify excess adiposity, and does the identification of obesity provide opportunities for treatment? If so, what evidence-based interventions for obesity treatment, delivered at least in part by clinicians in office-based settings, are most effective? Among children and adolescents identified as having obesity, does screening for comorbidities result in improved health outcomes?
Many previous studies, most notably conducted by the US Preventive Services Task Force, have synthesized research regarding the treatment of obesity.1 Unfortunately, some important gaps remain unfilled. The US Preventive Services Task Force recommendation was that obesity treatment should include at least 26 hours of contact, including clinical care and other behavioral intervention (eg, guided physical activity). However, subsequent studies have failed to demonstrate a consistent hours-based dose-response. In addition, feasibility studies have clearly shown how unrealistic it is for primary care or tertiary care providers to deliver this many hours of treatment in real-world, clinical settings.2 Additional information is needed about resources or partnerships that help reach that contact hour goal, the essential components delivered during these contact hours, the period of time over which this care is delivered, and information about lower-intensity strategies with some effectiveness.
Of particular concern for primary care pediatricians is the need to understand how to approach recommendations for screening comorbidities in their patients with obesity. Although previous recommendations have supported screening for common comorbidities, such as dyslipidemia and diabetes, there has been conflicting evidence regarding timing and effectiveness of screening. Additional data are now available that provide clinicians and researchers with information about comorbidity prevalence and severity by obesity class. The intent is to help the clinician screen for comorbidities when there is a high likelihood of detecting an abnormality and when detection of that abnormality leads to treatment options that can improve child health. Obesity classifications, including a more granular categorization of obesity as classes I through III, might assist clinicians in determining for whom screening would be most useful rather than viewing screening as a homogeneous approach for anyone whose BMI is >95th percentile.
Scope of the Review
This review was designed to answer 2 overarching key questions: (KQ1) “What are effective clinic-based treatments for obesity?” and (KQ2) “What is the risk of comorbidities among children with obesity?” We developed this focus based on the needs of clinicians and the evidence required to inform the future development of clinical practice guidelines. This review will not attempt to quantify the magnitude of the effect of obesity on child or adult outcomes. It will also not attempt to address treatment strategies for comorbidities (eg, hypertension), as other guidelines and reviews are available to guide such treatment.
Rationale for KQ1 (Intervention Studies)
Clinicians are a regular source of trusted information for parents, including issues related to nutrition and activity, which are key components of obesity prevention and treatment. Clinicians need to know what strategies have high-quality evidence for effectiveness in preventing and treating obesity. Additionally, physicians need guidance on which treatments are effective for their patient population and how to use available resources. The full results of KQ1 are reported in an accompanying technical report.3
Rationale for KQ2 (Comorbidity Studies)
Previous recommendations have included assessments of comorbidities, including hypertension, dyslipidemia, glucose, and others. It is not clear whether these assessments identify important health conditions or lead to improved treatment strategies. Additionally, it is not clear whether conducting these assessments would result in an adverse patient outcomes, such as further investigation for false-positive screening results. We will examine specific conditions previously recommended or that would reasonably require screening, as identified by the authors: dyslipidemia, hypertension, diabetes, liver function, depression, sleep apnea, and asthma. This is not intended to be a comprehensive list of all conditions comorbid with obesity but represents those most common and for which screening is potentially helpful.
We searched Pubmed and CENTRAL (for trials), completing the final search on April 6, 2018. An additional search was conducted to update the review, covering the time period April 7, 2018, through February 15, 2020. We combined the searches for both key questions because of significant overlap and to more efficiently review studies. Because our focus was on interventions that are relevant to primary care, we did not search other databases, such as ERIC or PsycInfo.
The complete search strategies are included in Appendix 2. Briefly, we searched for studies of children or adolescents, with a focus on overweight, obesity, or weight status; involving clinicians, health care, or other treatment or screening (KQ1); and examining common comorbidities (KQ2). For both questions, we limited only using key words, not filters, to ensure we included the newest studies that were not yet fully indexed. No date limits were placed on searches. In practice, this meant we reviewed studies from 1950 to 2020, although <2% were published before 1980.
The complete inclusion criteria are included in Appendix 3.
Inclusion Criteria Common to All Studies
All studies were required to include children ages 2 to 18 years, although studies could also include young adults up to age 25 if stratified from older adult participants, as long as children under 18 were also included. Children could have other conditions (eg, asthma) as long as they were not known to cause obesity, such as Prader-Willi syndrome, obesogenic medication (eg, antipsychotics), or known genetic mutations (eg, MC4R) associated with obesity. All studies had to originate from the Organization for Economic Cooperation and Development member countries and had to be available in English.
Inclusion Criteria for KQ2 (Comorbidity Studies)
We included studies with a primary aim of comparing comorbidities among those with and without obesity or by severity of obesity. Obesity and the comorbidity had to be measured contemporaneously to reflect the practice of clinical screening. Obesity had to be categorized using a BMI-based measure into accepted categories (ie, healthy weight, overweight, class I obesity, class II obesity, class III obesity).
These categories could be based on percentiles or z-scores and could use the distributions relevant to the studied population (eg, World Health Organization [WHO] or the US Centers for Disease Control and Prevention [CDC]). Comorbidities had to include 1 or more of: lipids, blood pressure, liver function, glucose metabolism, obstructive sleep apnea, asthma, or depression.
See the other technical report for a detailed description of KQ1 inclusion criteria.3
We used Covidence (Melbourne, Australia) to manage the review process. Covidence is a program for online collaboration and management of systematic reviews. All abstracts were reviewed by 2 independent reviewers for inclusion in full-text review. Articles were reviewed by 2 reviewers, with conflicts discussed and resolved. Articles excluded at this stage were assigned an exclusion reason, with a hierarchy as shown in Appendix 4.
Data Extraction and Quality Assessment
All articles deemed relevant for full text inclusion were categorized into different data extraction strategies. We did not include a specific quality assessment for the comorbidity studies.
KQ2 (Comorbidity Studies) Extraction
All studies were extracted by 2 reviewers. Extraction of these studies included reporting prevalence of comorbidities or mean values of laboratory parameters by weight classification. We included healthy weight, overweight, class I obesity, class II obesity, and class III obesity. However, because all classes of obesity severity are not always reported, these classes may include higher groups. For example, reporting of ≥95th percentile would only be considered class I obesity, although children at higher levels may be included. (See other technical report for detailed description of KQ1 extraction procedures.)
Data Synthesis and Analysis
Our primary method of data synthesis is narrative. To allow broad inclusion, we did not limit to specific designs or measures that would facilitate meta-analysis. We report on studies in each group, based on their type and design, and we report findings for outcomes other than BMI.
A total of 15 988 studies were screened in the title and abstract stage. Of these, 1642 were given a full-text review. Excluded studies (n = 1260) were most commonly not original research, did not compare comorbidities by obesity (KQ2), or were not health-care system based (KQ1). See Fig 1 for the complete PRISMA diagram. Of the 382 studies included, 215 were intervention studies and 167 were comorbidity studies. This paper focuses on the 167 comorbidity studies.
A total of 39 studies examined the prevalence of abnormal high-density lipoprotein (HDL),4–42 whereas 49 provided mean values for HDL.5–8,10,13,18,22,24,32,33,35,36,40–74 Table 1 reports the prevalence of abnormal HDL. Different countries report significantly different prevalence of abnormal HDL, with Korea having the highest prevalence18,30 and Japan the lowest.42 The majority of the 39 reported studies reporting the prevalence of abnormal HDL were conducted in the United States (24 of 39). Abnormal HDL was defined variably as <35 mg/dL, <40 mg/dL, and <50 mg/dL or <1.0 mmol/L. The most consistent findings were seen when using the definition of <40 mg/dL and when larger sample sizes were included. There was consistency of an inverse dose-response relationship, with increasing weight category associated with lower HDL. Few studies provided detailed information by obesity class, so less could be concluded when examining the prevalence of abnormal HDL within samples of increasing severity of obesity status. In general, overall prevalence of abnormal HDL increases from about 10% to 40% when children’s weight category was healthy weight versus obesity. The prevalence varied by age, with younger ages associated with lower prevalence of abnormal HDL. For example, in a study of 9- to 13-year-olds, those who had healthy weight had a prevalence of abnormal HDL of 10.2%, whereas those with obesity had a prevalence of abnormal HDL of 32.5%.15 In a study of 14- to 18-year-olds, those who had healthy weight had a prevalence of abnormal HDL of 13.2% and those with obesity had a prevalence of abnormal HDL of 38.9%.40 When studies report larger age ranges, it is difficult to see these distinctions, and the mean prevalence might be obfuscating the differences in prevalence at the younger versus older ages. A few studies stratified their findings by biological sex. In 2 US-based studies, there appears to be a higher prevalence of abnormal HDL in female children of both healthy weight and overweight, but the prevalence is similar regardless of sex once children are categorized as obese.12,20 Studies conducted in other countries also report differences by biological sex, but not always in the same direction or to the same degree.9,19,35,42 Caution should be used in interpreting these results when small sample sizes were used.
Table 2 reports the mean HDL values. Mean HDL values corroborate the findings regarding the prevalence of abnormal HDL, highlighting that age, sex, and country affect the findings of mean HDL values. Also apparent is the importance of sample size to lead to a stable mean value. Several of these studies reported mean values for large age ranges. In almost all of these studies, mean HDL decreases as weight category increases, validating the association between the 2.
A total of 26 studies examined the prevalence of abnormal low-density lipoprotein (LDL),4–10,12,13,15,16, 18,19,21–24,26,28,31,34–38,41 whereas 41 provided mean values for LDL.5–8, 10,13,18,22,24,33,35,36,40,41,43–46,50–52, 54–67,69,70,72–75 Table 3 reports the prevalence of abnormal LDL. Approximately half (n = 13) of the studies evaluated children 9 years or older, a time point associated with physiologic increases in LDL cholesterol.76 The remaining studies included children as young as 3 and up to 19 years of age. Sample size varied from 101 to 29 286; 13 of 23 studies reported sample sizes of 1000 or greater. One challenge in interpreting these data are the variation in definition of and reported units for abnormal LDL. Authors defined abnormal LDL as >110 mg/dL or >2.6 mmol/L through >130 mg/dL or >3.4 mmol/L. In 1 instance, authors used >75th percentile of National Cholesterol Education Program (NCEP) standards.24 In nearly all the studies, abnormal LDL was more prevalent in children with increasing BMI, and when comparing healthy weight with obesity, this difference consistently achieved statistical significance. The majority of studies did not include a significant number of children in each obesity classification; therefore, it is difficult to conclude whether abnormal LDL is more common by obesity classification. Among the 3 studies that reported male and female LDL separately, there was not a significant difference at any weight classification.5,9,12,19,35 Similarly to the LDL prevalence studies, the most evidence for mean LDL in populations includes children of school age and older (Table 4). Only 1 of the identified studies exclusively included children younger than 5 years46 ; therefore, it is difficult to draw conclusions in this younger age group. Sample size of the reported studies ranged from 41 to 2244. Several, but not all, studies reported male and female LDL levels separately. Mean LDL was reported in some cases in mg/dL and in other cases as mmol/L. Across all studies, mean LDL tended to increase with increasing BMI; however, only the difference between healthy weight and obese consistently achieved statistical significance. In 1 Korean study that evaluated mean LDL in 1998 and again in 2001, secular increases in mean LDL were also observed.17 Although in some cases, females have higher mean LDL than males at matched age and BMI, this difference was inconsistent and did not achieve statistical significance. However, the difference between mean LDL when comparing healthy weight and obesity was more pronounced in males than females. It is interesting to note that in all studies, even in the highest BMI subcategories, mean LDL values did not exceed commonly accepted definitions for normal.
A total of 38 studies examined the prevalence of abnormal triglycerides (TG),4–26,28–32,34–42 whereas 48 provided mean values for TG.5–8,10,13,18,22,24,32,35,36,40–60,62–75,77 Table 5 reports the prevalence of abnormal TG. About half of the 38 reported studies were conducted in the United States (20 of 38). Country comparisons are not possible given the variety of cutoff values employed. However, there is consistency of a dose-response relationship with increasing weight category associated with higher TG prevalence in most settings studied. Few studies provide detailed information broken down by obesity class, so less can be concluded when examining the prevalence of abnormal TG and increasing severity of obesity status. When studies report larger age ranges, it is difficult to see these distinctions, and the mean prevalence might be masking any potential differences in prevalence at the younger versus older ages. A few studies stratified their findings by gender, but the pattern of high TG prevalence was not always in the same direction or to the same degree. Caution should be used in interpreting these results when small sample sizes were used.
Table 6 reports the mean TG values. The sample sizes of the studies presented vary from 41 to 3978. In almost all of these studies, mean TG value increases as weight category increases, validating the association between the 2. In the majority of studies, the mean TG value is <130 mg/dL.
A total of 23 studies examined the prevalence of abnormal total cholesterol,6–10,12,13,15,16,18,19,21–24, 27,28,34–38,78 whereas 42 provided mean values for total cholesterol.5–8,10,13,18,22, 24,32,33,35,36,43–47,49–55,57–59, 61–66,69–75,79 In large (>20 000) population based studies, the prevalence of abnormal cholesterol (>200 mg/dL) in children of normal weight ranged from 7.5% to 8.3%, in children with overweight ranged from 10.0% to 12.7%, and in children with obesity ranged from 14.5% to 16.9% (Table 7).15,16,21 There was a significant difference in prevalence of elevated cholesterol between children of normal weight and children with overweight and obesity. In 6 medium-sized studies of children (n = 2000–9000), 2 studies did not provide statistical testing. In the remaining 4 studies, 2 studies used >200 mg/dL as a cutoff for abnormal cholesterol, and 2 studies used >170 mg/dL and >4.4 mmol/L. One study showed a significant difference in the prevalence of elevated cholesterol among children of normal weight and children with obesity; a second study was significant only for males. One study did not report results for normal weight children. The range of prevalence of elevated total cholesterol for children with healthy weight was 16.9% to 31%, for children who were overweight was 10.0% to 34.5%, and for children with obesity was 14.3% to 35.5%. There were 16 studies of children including 100 to 1412 children. Three studies did not provide statistical testing. Of the remaining 13 studies, 6 used 200 mg/dL as a cutoff for abnormal values, 4 used 170 mg/dL, and 2 used NCEP guidelines. Five studies did not include children with healthy weight. In the 7 studies remaining, 4 showed significant differences in total cholesterol between children with healthy weight and children with obesity.
Of the 42 studies reporting mean cholesterol levels, 3 studies did not report statistical testing (Table 8). Of the remaining 39 studies, 13 reported significant differences between mean cholesterol levels in children with healthy weight and children with obesity. One study reported significant differences in males but not females, 1 study reported significant differences in females but not males, and a third reported differences in both sexes.
An additional 6 studies examined the prevalence of dyslipidemia.13,26,80–83 Table 9 reports the prevalence of dyslipidemia (n = 6). The likely reason for the low number of studies in this category is the high variance in how dyslipidemia is defined. In 2 of these studies, similar criteria were listed: low HDL, high LDL, and high TG. In 1 study, a total cholesterol >200 mg/dL was also required for the diagnosis of dyslipidemia. In another study, being on a cholesterol-lowering medication also allowed patients to meet criteria. A third study relied on physician diagnosis of dyslipidemia only. The sample sizes for 2 of these studies were more than 10 000 participants. In general, the prevalence of dyslipidemia increased when comparing healthy weight with overweight and overweight with obesity. When comparing healthy weight with obesity, the prevalence (or odds ratio) nearly doubled. Caution should be used when interpreting these results given the inconsistent definition of dyslipidemia.
A total of 7 studies examined the prevalence of abnormal hemoglobin A1c (HbA1c),13,26,28,34,37,38,41 whereas 12 provided mean values for HbA1c.6,13,40,41,46,55,63,67,73,79,81,82 The participants in the 6 studies reporting abnormal HbA1c ranged in age from 3 to 19 years, with 1 study only reporting the mean age of 17 years (Table 10).26 This same study also deviated from the standard definitions of weight classification and defined an abnormal HBA1c level as greater than 6.5%, whereas the other 5 studies ranged from greater than 5.6% to 6%. One study did not report the sample size whereas others ranged in size from 101 to 8579. The prevalence of abnormal glucose in overall cohorts ranged from 1% to 17%, with the latter reported in a cohort of children 3 to 19 years of age. Using data from the National Health and Nutrition Examination Survey (NHANES) 1999 to 2012, 1 study cited a statistically significant difference between glucose levels among the overweight and obese groups (class I, II, and/or III obesity).38
Most studies of mean HbA1c values did not report significant differences by weight, although none examined differences by obesity severity (Table 11). The only study with a large sample size (n = 11 348) included children with type 1 diabetes mellitus seen in an endocrine clinic; there were no differences in mean HbA1c by weight status.82 An additional study showed statistically significant, but very small, differences by weight category.55
A total of 37 studies examined the prevalence of abnormal glucose,5,6,8–14,17–23,25,26,28–32, 37–42,71,77,78,80,84–86 whereas 39 provided mean values for glucose.5,6,8,10,13,18,22,32,35,36,40,41,43,44, 46–49,52,54–56,58–62,65,66,68,70,71,73–75 Thirty-seven studies reported prevalence of abnormal glucose across weight groups in cohorts ranging from 3 to 19 years of age (Table 12). Twelve of these studies reported significant differences, with 9 of these studies including a healthy group comparator. Of those studies indicating significant differences, prevalence sharply increased across increasing weight category, including a multifold higher prevalence in youth with obesity versus those with healthy weight. Eight studies reported data from nationally representative datasets, including in the United States and Korea, with 5 of these studies reporting significant differences in prevalence across weight categories.
Prevalence of abnormal glucose in overall cohorts ranged from 0% to 26.1%, with the latter reported in a cohort of adolescents undergoing bariatric surgery.26 This study also reported the highest prevalence of abnormal glucose among the studies reviewed, with 37.5% of adolescents with class III obesity indicated with abnormal glucose. Seven studies reported prevalence separately by biological sex, although there were no consistent differences, with males having higher prevalence in 4 studies and females having higher prevalence in 2 studies. Importantly, studies varied in definition of abnormal glucose, with 18 studies using the threshold of ≥100 mg/dL, 7 studies using the threshold of ≥110 mg/dL, and 2 studies using the threshold of ≥126 mg/dL.
Thirty-nine studies reported mean glucose levels across weight groups in cohorts ranging from 3 to 20 years of age, with 12 studies detecting significant differences (Table 13). Eight of these studies included a healthy weight comparator, whereas 4 demonstrated significant differences in glucose levels among the overweight and obese (class I, II, and/or III obesity) groups. Significant differences in mean glucose level across weight groups were observed in multiple age ranges, including studies that consisted of both children and adolescents, as well as a study of exclusively preschool-aged children.46 However, none of the subgroups had a mean glucose value above the standard threshold of ≥100 mg/dL (≥5.5 mmol/L) to indicate elevated fasting glucose.
A total of 14 studies examined the prevalence of abnormal insulin,6,9,12,19,22–24,26,28,34,39,41,42,84 whereas 32 provided mean values for insulin.6,8,22,24,32,35,36,40–44,46, 47,49,52,54,55,58–62,65,66,70,71,73,75,84,87,88 Table 14 indicates that 8 of 12 studies observed significant differences in prevalence of abnormal insulin across weight categories, with a range of 0% in a sample of 3- to 18-year-old participants who were overweight in the United States34 to 80% among 9- to 16-year-old participants with obesity in Canada.19 Prevalence estimates were reported from samples enrolled in the United States (8 studies), 2 studies each in Australia and Canada, and 1 study each in Italy and Japan; however, none of the studies were indicated as nationally representative. Eight studies had less than 500 participants, but the sample sizes ranged from 62 to 6358. Three studies enrolled participants from clinic-based settings, including a pediatric gastroenterology clinic, a pediatric weight management program, and a bariatric surgery program. Several definitions of abnormal insulin were used, making it difficult to compare actual prevalence estimates across studies. In several studies, youth with obesity had a four- to fivefold higher prevalence of abnormal insulin compared with youth with healthy weight. There were also differences observed within obesity classification: for example, youth with class II or higher obesity had a threefold higher prevalence of abnormal insulin than their peers with class I obesity.22 One study that did not observe significant differences in abnormal insulin prevalence across weight categories comprised patients who were all enrolled in a bariatric surgery program, so patients had comorbidities at the time of entry.26 The 1 study that examined abnormal insulin prevalence by age did not observe differences between 6- to 11-year-old versus 12- to 19-year-old youth.24 Three studies reported prevalence stratified by biological sex; in 2 of the studies, females had higher prevalence of abnormal insulin compared with males.
Thirty of the 32 studies (Table 15) reporting mean values of insulin observed significant differences across weight categories; the other 2 studies did not statistically test for differences among weight categories. Although most (22 of 32) studies examined differences between 2 weight categories (healthy versus combined overweight and obese), 10 of the 32 studies reported mean insulin values for at least 3 weight categories; in every case, there was a noticeable dose-gradient relationship of insulin across the multiple weight categories and the P value was significant. These differences were noted among healthy versus overweight versus obesity groups as well as a study of adolescents that observed differences among healthy, overweight, obesity class I, and obesity class II+.24 Most of the cohorts spanned the age range from childhood to adolescence, although 1 study observed significant differences in insulin values among 3- to 5-year-old children who were overweight versus those who had obesity,46 and a second study also observed significant differences among 6- to 8-year-old children with healthy weight versus those with obesity.52 Two studies reported mean values by age24,71 ; in both cases, the insulin levels were higher in adolescents versus children, and the insulin values were noticeably higher among the youth with higher weight status.
A total of 10 studies examined the prevalence of abnormal homeostatic model assessment for insulin resistance (HOMA-IR),7,9,12,26,32,35, 40,71,88,89 whereas 25 provided mean values for HOMA-IR.7,32,35,36,40,41,43, 45,46,49,52,54,58,59,61–63,65,66,70,71,73,75, 81,90 Prevalence of abnormal HOMA-IR ranged from 0% in healthy adolescents71 to 70.8% in adolescents with class III obesity who were enrolled in a bariatric surgery program26 (Table 16). However, definitions of abnormal HOMA-IR differed in every study, so it is difficult to compare prevalence estimates. Prevalence was reported for cohorts from the United States (5 studies) and Europe (5 studies); however, none were indicated as nationally representative cohorts. Prevalence of abnormal HOMA-IR was significantly different across weight categories in 7 of the 9 studies; 1 study did not statistically examine differences across weight categories and another study did not observe differences, but the sample only consisted of adolescents with obesity who were undergoing bariatric surgery (with no differences among class I, class II, or class III obesity; Michalsky/US).26 One study reported prevalence by age group with a stark difference in abnormal HOMA-IR in both children and adolescents with obesity (approximately 41%) versus participants with healthy weight (0% to 3%) (Valerio/Italy).71 Two studies reported prevalence stratified by biological sex; in both cases, prevalence of abnormal HOMA-IR was higher among females compared with males (Caserta/Italy; Serap/Turkey).9,35
Studies reporting mean HOMA-IR across weight categories (Table 17) corroborated the findings of the prevalence of abnormal HOMA-IR. Twenty-three of the 25 studies reported significant differences in HOMA-IR value across weight categories. Most of these studies examined differences between healthy weight versus overweight and obesity combined. However, 6 studies examined differences across 3 weight categories, showing a gradient of HOMA-IR values among healthy weight, overweight, and obesity. One study reported mean values separately by age group, with adolescents having higher HOMA-IR values than children in both the healthy weight and obesity categories.71 Four studies reported mean HOMA-IR values stratified by sex; there was not a consistent pattern in differing values between females and males.
Most cohorts included both children and adolescents or only adolescents; however, the 1 cohort that did include young children (ages 3–5 years) did not observe a significant differences in HOMA-IR across weight categories.46 A cohort of children ages 6 to 8 years did observe significantly higher HOMA-IR values among children with obesity versus children with healthy weight.52
Other Glucose Metabolism
Additional studies reported the prevalence of prediabetes (n = 3),13,85,91 diabetes mellitus (n = 8),13,26,33,71,83,85,87,92 and metabolic syndrome (n = 16).10,11,14, 17,20,29–32,35,42,49,93–96 Three studies reported prevalence of prediabetes (Table 18). The population-based study in Mexico defined prediabetes as 2-hour glucose tolerance test result of 140 to 200 mg/dL. Prediabetes was higher in children with overweight or obesity versus children with healthy weight.85 A second population-based Canadian study showed greater risk of prediabetes for children with obesity versus children with healthy weight.91
The 8 studies reporting the prevalence of diabetes (Table 19) used varying definitions of diabetes, based on fasting plasma glucose, glucose tolerance tests, HbA1c, diagnosis, or use of medications. Most studies showed significantly higher prevalence of diabetes among children with obesity or severe obesity, although overall prevalence was low. Prevalence of diabetes >3% was seen only in a pediatric endocrinology clinic33 and among bariatric surgery candidates.26
Of the 16 studies assessing the prevalence of metabolic syndrome (Table 20), the largest sample size was 4450 and the smallest sample was 101. Seven studies reported the prevalence of metabolic syndrome as the presence of 3 or more components of metabolic syndrome in cohorts ranging from 6 to 24 years of age, with 3 of the studies conducted in the United States. The remainder of the studies (8) reported the presence of metabolic syndrome using the following criteria: Adult Treatment Panel (ATP) III (2 studies), NCEP ATP III (2 studies), 3 components plus risks (2 studies), 3 components plus abnormalities (1 study), and International Diabetes Foundation (IDF) (1 study). Of the 16 studies, 14 included a healthy weight comparison, and 11 of the studies reported a significant association between the prevalence of metabolic syndrome and overweight. Of the studies that defined the presence of metabolic syndrome as having 3 or more components and compared prevalence across children with normal weight, overweight, and obesity, the prevalence of metabolic syndrome ranged from 0% to 4.7% among children with healthy weight and increased to 14.5% to 35% among children and adolescents with class I obesity. Of the 2 studies that defined metabolic syndrome as ATP III and compared prevalence across children with healthy weight, overweight, and obesity, the prevalence of metabolic syndrome ranged from 0.3% to 1.6%, which increased to 39% for children with class I obesity in 1 study. One of the 2 studies did not report prevalence for class I obesity. Of the 2 studies that defined metabolic syndrome as NCEP ATP III and compared prevalence across children with healthy weight, overweight, and obesity, the prevalence of metabolic syndrome ranged from ranged from 1% to 1.5%, which increased to 28.6% to 41% for children with class 1 obesity. Of the 2 studies that defined metabolic syndrome using 3 components plus risk and compared prevalence across children with healthy weight, overweight, and obesity, the reported prevalence of metabolic syndrome ranged from 0% to 0.8% for females and 1.7% for males, which increased to 1.6% to 24.6% for female children and 35% for male children with class 1 obesity. One study defined metabolic syndrome as 3 components plus abnormalities and the reported prevalence across children with healthy weight, overweight, and obesity was 0.2% among children with healthy weight and 25.6% among children and adolescents with class 1 obesity. When using the IDF definition of metabolic syndrome, the reported prevalence was 1.6% among children with healthy weight and 28% among children and adolescents with class 1 obesity. In addition, 3 studies reported statistical comparisons by biological sex. However, only 1 supported a significant relationship between metabolic syndrome and unhealthy weight status for both males and females. Prevalence comparisons were not available within studies for different age subgroups.
Systolic Blood Pressure
A total of 21 studies examined the prevalence of abnormal systolic blood pressure (SBP),5,7,8,10,13,15,18, 19,24,35–39,63,97–101 whereas 52 provided mean values for SBP.5,7,8,10,13,18,22,24,32,33,35,36,39,40, 42–46,48–50,54–56,59–66,68,71–75,77,79,83, 90,97,99,102–108 Twenty-one studies, including children ages 3 to 19 years, examined the prevalence of elevated SBP in relation to excess weight (Table 21). Within the 17 studies formally testing such an association, 14 included a healthy weight comparison group, and all but 1 of these reported a significant association between the prevalence of elevated SBP and overweight or obesity.
Reported frequencies further suggest a progressive increase in the prevalence of high SBP with increasing adiposity, although limited information is available regarding differences across classes of obesity, because only 1 study specifically focused on such categories. Studies supporting an association between elevated SBP and unhealthy weight status included samples based within the United States (n = 7) and other countries (n = 10) as well as population-based and more targeted samples. Five studies reported statistical comparisons by biological sex, all of which supported a significant relationship between elevated SBP and unhealthy weight status for both males and females. Five studies based on samples within a preteen or young-teenage range (eg, 9–13 years) supported an association between higher SBP and unhealthy weight. Prevalence comparisons were not available within studies for different age subgroups, and no studies focused specifically on young children (eg, ≤8 years).
Fifty-two studies including children ages 2 to 19 years provided mean values for SBP across different weight groups, including 21 studies from the United States (with 2 from Puerto Rico) and studies from 15 other countries, spanning 4 continents (Table 22). Within the 46 studies formally testing differences across means, 37 included a healthy weight comparison group, 32 of which reported significant increases in mean SBP with excess weight. Among studies with a healthy weight comparator, 8 specifically compared the healthy weight and overweight group or tested a trend, with 6 supporting significant increases in SBP with unhealthy weight. Seven other studies compared only groups with overweight and obesity or different classes of obesity, with 6 reporting significant increases in SBP with increasing adiposity. These findings and reported means add support to observed differences in prevalence by weight status group—that is, that SBP increases progressively with the degree of overweight or obesity. Studies reporting mean SBP also add to previous insights by providing additional comparisons within sex and age subgroups. Of the 18 studies including formal subgroup comparisons, 16 compared weight status categories within both males and females. Most reported significant differences across weight groups in the expected direction for both males and females. Only 3 studies reported comparisons for subgroups by age, and 2 of these only compared younger and older children and adolescents, although 2 studies also compared means by age for both males and females. Also, 1 study compared means for 4 age subgroups, ranging from 2 to 5 years to 16 to 19 years.102 In addition to the general observation of increased SBP with age, significant differences in SBP were reported by weight status for all comparisons, regardless of age or sex. Although few studies addressed changes in SBP for very young children, it should also be noted that 2 other studies reported similar findings for cohorts 6 years or younger.46,105 Combined prevalence and mean tables for SBP support progressive increases in SBP and the prevalence of elevated SBP with increasing adiposity. The available studies further suggest that this finding holds in males and females and is likely generalizable across age, although limited evidence is still available relevant to younger subgroups.
Diastolic Blood Pressure
A total of 19 studies examined the prevalence of abnormal diastolic blood pressure (DBP),5,7,8,10,13,15,18, 24,25,35–39,63,97,98,100,101 whereas 51 provided mean values for DBP.5,7,8,10,13,18,22,24,32,33,35,36,39,40, 42–46,48–50,54–56,59–66,68,71–75,77,79,83, 90,97,99,102,103,105–108 Sixteen studies reported on the prevalence of abnormal DBP across weight groups in cohorts ranging from 3 to 19 years of age, with 7 of the studies conducted in the United States (Table 23). The majority of the studies (13 of 19) defined abnormal DBP as a DBP >95th percentile for age, height, and biological sex. Five studies defined abnormal DBP as DBP >90th percentile, and 1 study from Canada defined abnormal DBP as DBP >75th percentile. Of the studies that defined abnormal DBP as >95th percentile and compared prevalence across children with healthy weight, overweight, and obesity, the prevalence of abnormal DBP ranged from 0% to 9.4% among children with healthy weight and increased to 4% to 20% among children and adolescents with class 1 obesity. Of the studies that defined abnormal DBP as >90th percentile, prevalence of abnormal DBP for children with normal weight ranged from 4% to 9.7%, which increased to 9% to 29.4% (among males) for children with class 1 obesity. Across all studies, age ranged from 3 to 19 years, with only 2 studies examining abnormal DBP by age group.24,25 Two studies reported data from NHANES, the larger study of which (n = 8579) showed a significant increase in prevalence of abnormal DBP among children with increasing weight status (overweight and class III obesity).37,38 For studies that examined significant differences in abnormal DBP across weight categories (13 of 19), 8 showed a significantly higher prevalence of abnormal DBP among children in a higher weight category compared with children in a lower weight category. Among the largest study (n = 29 286), prevalence increased from 9.4% in children with healthy weight to 20.1% in children with class I obesity.15
A total of 51 studies examined mean DBP (Table 24); 28 of them reported significant differences in mean DBP by weight status. Notably, of the population-based studies, none reported consistently higher DBP among those with obesity. One reported higher DBP among females8 and another only in 11- to 18-year-old males.50 Studies showing a significant difference in DBP by weight status indicated a stepwise increase in DBP as weight increased from healthy weight to obesity. Only 1 school-based study included severe obesity, reporting significantly higher DBP in children with class II obesity compared with those with class I obesity.22 With the exception of some clinic samples, the mean reported DPB was <70 mm Hg, even among children with obesity.
An additional 61 studies examined the prevalence of hypertension (Table 25).6,7,9,11–14,16,17,20–23,26, 29–33,37,40,42,77,78,80–83,92,102,108–137 All studies reported on the prevalence across weight groups, with the majority of studies comparing hypertension prevalence between children of healthy weight and those with obesity. Fifteen studies reported on prevalence of hypertension among children and teenagers with increasing obesity severity (class I to class III), whereas 4 studies examined prevalence of hypertension among children with healthy weight and overweight. All studies except 133 that examined the association between hypertension and weight group showed significant differences in the prevalence of hypertension between weight categories, with increasing prevalence of hypertension with increasing weight category. The studies were conducted in various countries; 34 reported US data. The majority of the studies (n = 37) defined hypertension as SBP or DBP >95th percentile for age, biological sex, and height. Of these studies, hypertension prevalence for children of healthy weight across age groups ranged from 1% to 14% compared with 4% to 30% for children with obesity. As expected, prevalence was lowest in early childhood (4% to 6% for children with healthy weight and 8% for children with obesity) and highest among teenagers (2% to 10% for teenagers with healthy weight and 3% to 39% among teenagers with obesity). Studies that defined hypertension as SBP or DBP >90th percentile for age, sex, and height (n = 13) showed similar prevalence both for children with healthy weight (5% to 12%) and those with obesity (18% to 24%) across all age groups. For studies (n = 2) with the large population samples (n > 20 000) of children ages 6 to 19 years and the most rigorous definition of hypertension (SBP or DBP >95th percentile on 3 repeated measures), hypertension prevalence was ∼1% for children with healthy weight and ∼5% for children with obesity, increasing to 9% for children with class II obesity.
A total of 8 studies examined the prevalence of abnormal alanine aminotransferase (ALT),6,34,67,81,83,104,138,139 and 8 provided mean values for ALT.6,13,53,54,66,67,70,74 Three additional studies examined the prevalence of nonalcoholic fatty liver disease (NAFLD).5,67,70 The 8 studies examining the prevalence of abnormal ALT (Table 26) used a range of definitions from >20 U/L to >40 U/L and each of the 5 studies used a different cut point. Four studies found significant differences in prevalence of abnormal ALT between children with healthy weight and children with obesity.6,67,104,139 Two studies included only children with obesity; 1 found no significant difference between class I, II, or III obesity in prevalence of abnormal ALT,34 whereas another did.81 Two additional studies did not provide statistical analysis of prevalence.83,138
Four studies provided mean values for ALT (Table 27). Three studies compared mean ALT between children with healthy weight and children with overweight and obesity and found a significant difference in mean ALT between groups.6,53,54 A study of children with Down syndrome found no difference between mean ALT in children with healthy weight and children who were overweight.70 Four studies compared mean ALT in children with overweight and class I, II, III obesity, and 3 found significant differences in mean ALT between children with overweight and children with obesity.66,67,74
Aspartate Aminotransferase and NAFLD
A total of 2 studies examined the prevalence of abnormal aspartate aminotransferase (AST),34,138 whereas 4 provided mean values for AST.53,54,67,70 Of the 2 studies examining the prevalence of abnormal AST (Table 28), 1 from a pediatric endocrine clinic found no significant difference abnormal AST among children with class I, II, or III obesity.34 The other study did not provide statistical analysis of prevalence.138 A study of children with Down syndrome showed a significant difference between mean AST (Table 29) for children with healthy weight (35.00 U/L) and children with overweight (30.12 U/L).70 This same study showed almost double the prevalence of NAFLD (Table 30) in children who were overweight. Another study showed no significant differences by obesity severity for mean AST or NAFLD.67 A third study demonstrated greater prevalence of NAFLD among those with severe obesity, compared with class I obesity.5
Obstructive Sleep Apnea
Eight studies examined the prevalence of obstructive sleep apnea (OSA) (Table 31).5,6,13,83,135,140 By parent report, there was no significant difference in the prevalence of OSA among children with healthy weight, overweight, or obesity.6 Studies using polysomnography results show increasing prevalence of OSA as obesity severity increases.5,83,140,141 Studies using diagnosis of OSA also find increased OSA as obesity worsens.135,142
A total of 26 studies reported the prevalence of asthma (Table 32).135,142–166 Virtually all studies used parent-reported or self-reported asthma, although they varied in the reporting of current asthma or ever having asthma, as well as specifically asking for report of a physician diagnosis. Most studies showed significantly higher asthma in children with obesity compared with children healthy weight. One nationally representative US study of children 2 to 19 years of age showed 15.7% children with obesity had asthma, compared with 10.3% of children with healthy weight.144 Only 2 studies, both of a health plan population, included children with severe obesity, demonstrating a stepwise increase in asthma incidence and prevalence as weight status increased.148,149
A total of 6 studies examined the prevalence of depression,6,13,81,135, 167,168 whereas 3 provided mean values for depression inventories.167,169,170 The studies of the prevalence of depression (Table 33) showed conflicting findings. Three, based on Center for Epidemiologic Studies Depression Scale (CES-D) scores, self-report, and International Classification of Diseases, 10th Revision (ICD-10), codes showed no difference by weight status.81,135,167 Two others, using parent report and depression inventory, showed significantly higher depression as weight status increased.6,168 The mean values for depression inventories (Table 34) were more consistent; 2 demonstrated significantly higher scores at higher weight status,169,170 whereas another smaller study examining class III obesity did not.167
Overall, across most laboratory values, diagnoses, and age groups, obesity was associated with increased prevalence of abnormal values and/or greater comorbidity prevalence. In addition, more severe degrees of obesity were associated with greater abnormalities, in concordance with prior evidence.38 However, population-based data showed smaller differences, compared with samples drawn from clinical care. Additionally, these population-based samples typically showed that the great majority of children have normal values, even children with obesity, although abnormal values were more frequently observed in the higher age categories.
Implications for Lipid Screening
In general, prevalence of abnormal lipid values varied with weight classification. For HDL cholesterol, values decreased as weight classification increased, with prevalence of abnormal HDL approximately 10% in children with healthy weight and 40% for children with obesity. There were not enough data to determine whether prevalence of abnormal HDL varied within the obesity classification by severity. Mean HDL values also showed a decrease (worsening) with increasing weight classification. Similarly, the prevalence of abnormal LDL cholesterol also increased with increasing weight classification.
The prevalence of abnormal TG increased with increasing weight classification, with the magnitude differing depending on the abnormal cutoff value chosen. Mean TG also increased as weight classification increased.
Abnormal total cholesterol values were more common in children with obesity than in children with healthy weight. There was also a significant difference in mean total cholesterol between children with healthy weight and children with obesity. In these studies, a variety of cutoffs for abnormal lipid values were used, but although prevalence varied with the cutoffs, having obesity was in all studies associated with a higher prevalence of abnormal lipid levels.
Choosing the cutoff point considered to be clinically relevant is important to understanding the potential application of these data. For example, for the studies reporting TG abnormalities, many studies selected >110 mg/dL, whereas others selected >130 mg/dL or >150 mg/dL. The prevalence varies considerably depending on the cut-point selected. Multiple organizations, including the National Lipid Association and the Endocrine Society, indicate ≥150 mg/dL as elevated TG, and other organizations, such as the American Academy of Pediatrics and the American Heart Association, indicate that the value depends on age. High TG is considered to be >100 mg/dL for children younger than 10 years and >130 mg/dL for children 10 years and older. This cutoff is important to understand patterns of high TG in children, especially when the study samples included both younger and older children. An example of the effect of the cutoff value used on prevalence differences can be seen by 2 studies conducted by Ice et al. When conducting their study with a large sample of children ages 9 to 13 years and using the cutoff of >110 mg/dL, the prevalence of high TG was 14.2% (healthy weight), 29.8% (overweight), and 49.1% (obese). However, in their other study with a large sample size of children with a mean age of 10.8 and the cut-point of >150 mg/dL, the prevalence of abnormal TG was 4.4% (healthy weight), 12.4% (overweight), and 25% (obese). There were not enough data to determine whether the prevalence of abnormal values varied within the classification of obesity.
Implications for Glucose Screening
Most of the studies that reported prevalence or mean values related to glucose metabolism observed that children and adolescents with obesity had a multifold higher prevalence of abnormal glucose, insulin, and other glucose-related values compared with children of healthy weight. These differences by weight status were reported in preschool-aged children up to adolescents. However, there was limited information on the extent to which glucose and related measures varied across categories of obesity. A few studies noted a dose-response relationship between increasing obesity classification and fasting insulin level, but many studies only compared children with healthy weight versus children with obesity, so it is less clear when glucose metabolism aberrations occur or worsen across specific severities of obesity.
There was a wide range of prevalence of abnormal HbA1c (1% to 17%), abnormal glucose (0% to 26%), abnormal insulin (0% to 80%), elevated HOMA-IR (0% to 71%), and metabolic syndrome (0% to 41%), depending on the weight status and age range of the sample and the definition used to classify abnormal values. Surprisingly, there were few studies reporting prevalence of prediabetes (1 study) or overt diabetes mellitus (6 studies) in this age range. There was great variability of mean glucose-related values within samples. However, for the most part, the reported subgroups did not have a majority of participants classified as abnormal, nor did the subgroups have a mean glucose or glucose-related value outside of the healthy range. An exception is a sample of Canadian youth ages 9 to 16 years with obesity that had an 80% prevalence of abnormal insulin, and 71% of adolescents with class III obesity entering a bariatric surgery program had abnormal HOMA-IR.26 The samples with higher prevalence and higher abnormal values were typically clinic-based, including from subspecialist clinics and/or weight management specialty clinics, including a bariatric surgery program. Among these more advanced cases of obesity, elevated insulin level was consistently high and was not differentiated by class of obesity.
There were no consistent sex differences in glucose-related measures. In general, glucose abnormalities increased in prevalence with increasing age, although there were noticeable elevations by obesity status in samples as young as preschool-aged children. There was a dearth of prevalence data available on nationally representative datasets, particularly for HOMA-IR. The presence of glucose abnormalities among youth with obesity supports the need for screening, but given the wide variability observed across population and clinic-based studies, taking into account other risk factors may be important to avoid unnecessary tests.
Implications for Blood Pressure Screening
The prevalence of elevated SBP was higher in children with overweight and obesity compared with children with healthy weight. This association was true in both males and females. Mean values of SBP were significantly different between children with healthy weight and children with overweight and obesity. Within the obesity classification, mean SBP increased with increasing BMI. The association between SBP and BMI was observed in all age groups study and in both males and females. DBP prevalence also varied with BMI across age groups and increased within increasing obesity classifications. Hypertension (defined as elevated SBP or DBP) prevalence increased with increasing BMI. Prevalence also increased with age.
The association of increased prevalence of SBP, DBP, and hypertension in children in children with overweight and obesity in addition to increased mean SBP and DBP supports BP screening these groups.
Implications for Other Screening
There are a limited number of studies examining prevalence of abnormal AST and ALT. Increases in prevalence were found between children with healthy weight and children with obesity. Two studies examined prevalence within obesity classifications and found no difference in prevalence. Differences in mean ALT were found between children with normal weight and those with obesity in addition to increases in mean ALT with increasing obesity classification.
One study of mean AST did not find any difference within obesity classification. Only 1 study documented prevalence of NAFLD, pointing to an important area of future research, particularly because this study observed a doubled prevalence of NAFLD in children with overweight compared with children with normal weight. Further, only 1 study reported prevalence of OSA. With so few data, it is difficult to make screening recommendations.
Asthma is consistently associated with obesity in children at a variety of ages. In contrast to the previously discussed comorbidities, however, asthma presents symptomatically.
Therefore, it is unclear whether the data demonstrate a need for increased asthma screening.
Data regarding the relationship between obesity and depression are particularly limited.
These data suggest there may be a relationship between obesity depression but are not adequate to make statements regarding the need for screening, specifically for children with obesity. All children 12 years and older should be screened for depression, regardless of weight status.171
Limitations of Current Research
There are several limitations of the current literature that warrant attention. First, the cross-sectional design of these studies prevented an examination of within-individual changes in comorbidity prevalence as it relates to fat accumulation and obesity and comorbidity incidence across the age range. This limitation makes it difficult for a primary care provider to determine when during a young patient’s life these screenings are most efficient, useful, and necessary. Many studies examined samples with wide age ranges and did not stratify by age group, making it difficult to identify a window of opportunity when screening may be most useful for early detection of a patient’s transition into pathophysiology. Further, although there were distinct differences in prevalence of abnormalities and mean laboratory values between children with normal weight versus those who were overweight and obese, more information is needed on the specific amount of body fat or level of BMI at which aberrations occur. Although screening youth with severe obesity may be commonly practiced, we currently have too few data to determine whether youth in the overweight range or at the low end of obesity should be screened.
The inconsistency in definitions of comorbidities is also challenging in this age range. It is difficult to compare prevalence estimates when studies use different thresholds for a clinically abnormal or pathologic level. Further, it is challenging for the primary care provider to develop treatment strategies without more concrete guidelines on how to interpret screening results. The inconsistency in definitions made it difficult to compare prevalence across countries, across race and ethnic groups, and across a variety of settings. There are insufficient data on national prevalence estimates, with many studies using convenience samples via school-based screening or specialty clinical settings. Less is known about the occurrence of obesity comorbidities in primary care settings as detected by providers. The utilization of large electronic medical record databases may be an efficient remedy to this lack of data.
Overall, across most laboratory values and diagnoses, obesity was associated with higher mean values and/or greater comorbidity prevalence. However, population-based data showed smaller differences, compared with samples drawn from clinical care. Additionally, these population-based samples typically showed that the great majority of children have normal values, even children with obesity.
We thank Chelsea Kracht, PhD, for her help in reviewing abstracts.
COMPANION PAPERS: Companions to this article can be found at http://www.pediatrics.org/cgi/doi/10.1542/peds.2022-060640, http://www.pediatrics.org/cgi/doi/10.1542/peds.2022-060641, and http://www.pediatrics.org/cgi/doi/10.1542/peds.2022-060642.
Technical reports from the American Academy of Pediatrics benefit from expertise and resources of liaisons and internal (AAP) and external reviewers. However, technical reports from the American Academy of Pediatrics may not reflect the views of the liaisons or the organizations or government agencies that they represent.
The guidance in this report does not indicate an exclusive course of treatment or serve as a standard of medical care. Variations, taking into account individual circumstances, may be appropriate.
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Adult Treatment Panel
Centers for Disease Control and Prevention
diastolic blood pressure
homeostatic model assessment for insulin resistance
International Diabetes Foundation
National Cholesterol Education Program
National Health and Nutrition Examination Survey
obstructive sleep apnea
systolic blood pressure
World Health Organization
FINANCIAL/POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.