Investigating the Relationship between Body Mass Index and Pain in the Spine in Children or Adolescents: A Systematic Review

Abstract

Background:

Neck pain (NP), back pain (BP), and low back pain (LBP) are generally defined as “pain in the spine.” With the increasing prevalence of childhood obesity, secondary problems such as pain in the spine have arisen. The purpose of this review was to investigate the relationship between body mass index (BMI) and pain in the spine in children or adolescents.

Methods:

Publications were searched in PubMed, Web of Science, Scopus, and Google Scholar databases up to December 12, 2020. The search strategy in the database consisted of free text words and MeSH terms.

Results:

Twelve studies were reviewed. It was determined that different methods were used in all 12 studies to evaluate pain. In the evaluation of overweight/obesity, these studies performed BMI assessment by dividing body weight in kilograms by height squared. Five studies showed a relationship between LBP and BMI, two studies showed a relationship between BP and BMI, and two studies showed a relationship between NP and BMI.

Conclusions:

The review shows that there is a relationship between BMI and pain in the spine, especially LBP. There may be factors affecting this condition such as mechanical loading and hormonal metabolic activity in childhood and adolescence. Different methods are used in the studies in literature for the assessment pain in the spine and BMI, overweight, and obesity.

Introduction

Childhood obesity is seen by the World Health Organization (WHO) as one of the most serious health problems of the 21st century.¹ According to WHO data, more than 38 million children under the age of 5 years were reported to be overweight or obese in 2019,¹ and more than 340 million children and adolescents aged 5 to 19 were overweight or obese in 2016.¹ This information emphasizes that the risk of persistent obesity increases in childhood between the ages of 3 and 7, and this period is critical for growth.²

With the increasing prevalence of childhood obesity, some secondary health problems, including cardiovascular, endocrine, pulmonary, and musculoskeletal disorders, have also arisen.^3,4 It has been reported that 80% of children with obesity will continue to be obese in adulthood and secondary problems will continue.⁵ The studies investigating the relationship between pain, one of the musculoskeletal problems, and body mass index (BMI) in children/adolescents, have mostly examined the pain caused by lower extremity problems.^6–13,42 There are also reviews in the literature focusing on pains in the different parts of the body,^14,15 but there are very few studies regarding the pain in the spine. When neck pain (NP), back pain (BP), and low back pain (LBP) are considered musculoskeletal system, starting in the early years of life in children and adolescent and continuing in adulthood, it is generally defined as “pain in the spine.”^16,17 Investigation of this issue is important since the pain in the spine experienced in childhood/adolescent may continue in adulthood.^18,19

Researches indicate that if a person develops (LBP) at a young age, it will likely to continue for life.^18,20 Overweight/obesity has been shown to cause a threefold increased risk for LBP development in the pediatric population.¹⁹ It was indicated that increasing overweight/obesity resulted in higher frequency of pain in the spine in children and adolescents, and the severity of these pains could increase in adulthood.¹⁸ The most common pain regions of spine reported for adults include NP, BP, and LBP, and the prevalence in children and adolescents ranged from 7% to 72%. It would therefore seem to be of interest to examine the factors related to NP, BP, and LBP in childhood and adulthood.¹⁶ Considering the body region where weight gain is intensified, it can be seen that an increase in BMI, lack of muscle strength during the growth years, an increase in the load on the whole musculoskeletal structure, posture disorders, carrying heavy schoolbags, decreased physical activity level, increased sedentary time, family attitude, and psychosocial factors create a vicious circle resulting in increased pain in the spine.^{16,19,21–29}

In studies investigating the relationship between BMI/obesity/overweight and NP, BP, and LBP in children/adolescents, different scales and questionnaires have been used for the assessment of NP, BP, and LBP and only the presence of pain has been questioned.^25,30–36 However, a recent literature search conducted revealed that tools for the assessment of pain in the spine in terms of NP, BP, and LBP in the pediatric population have not been sufficiently investigated and are lacking. Since the pain is subjective, the assessment of pain could be difficult in children/adolescents for various reasons, such as use of different methods, pain duration, and inadequate pain assessors. The pain in the pediatric population may intensify with transition to adulthood; hence, the necessity of an appropriate investigation emerges.¹⁸ The purpose of this review is to present the relationship between BMI and the pain in the spine in children or adolescents.

Methods

This systematic review was performed using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The protocol of the systematic review was stored in PROSPERO (registration no. CRD42020148715). The BMI in the studies was calculated by dividing the weight (kg) by the square of the height (m),³⁷ and the status of overweight/obesity was determined by classifying BMI values by age, sex, and race with respect to 95th percentile (underweight: <5%, normal: 5%< to <85%, overweight: 85%< to <95%, obesity: ≥95%). The calculation of BMI-Z scores was conducted according to the Centers for Disease Control and Prevention (CDC) guidelines.^33,38

Search Question

The search question of this study was created on the basis of PICOS (participants, intervention, comparison, outcome, study design). The search question of this review was “Whether there is a relationship between BMI and pain in the spine in children or adolescents?” In this systematic review, studies evaluating BMI, overweight or obesity, and pain in the spine in children or adolescents and investigating the relationship between the two variables were examined.

Search Strategy

Publications about the assessment of BMI/overweight/obesity and NP, BP, LBP in children/adolescents were searched in PubMed, Web of Science (WOS), and Scopus databases. The most recent review date of the literature was December 12, 2020. The search strategy in the database consisted of free text words and MeSH terms. The search strategy keywords are presented in Table 1.

Table 1.

Search Strategy Keywords

PubMed, Scopus
Group 1	Group 2	Group 3
BMI OR	Childhood OR	NP OR
BMI OR	Child OR	BP OR
Obesity OR	Adolescent OR	LBP OR
Overweight OR	Teenager OR	Backache OR
Obese OR	Teens OR	Back ache OR
Pediatric obesity OR	Youth OR	Cervical pain OR
Morbid obesity	Adolescence	Neck ache OR Neckache
WOS
Group 1	Group 2	Group 3
Obesity OR	Childhood OR	NP OR
Overweight OR	Child OR	BP OR
Obese OR	Adolescent OR	LBP OR
Pediatric obesity OR	Teenager OR	Backache OR
Morbid obesity OR	Teens OR	Back ache OR
BMI OR	Youth OR	Cervical pain OR
BMI	Adolescence	Neck ache OR Neckache

BMI, body mass index; BP, back pain; LBP, low back pain; NP, neck pain; WOS, Web of Science.

Eligibility Criteria

Inclusion criteria

(1)

Aged 2 to 18 years.

(2)

Articles that reported/evaluated pain in the spine.

(3)

Articles written in English/Turkish and published after 2013 (There were reviews^14,15 in the literature examining the relationship between general musculoskeletal pain, problems, and BMI before 2013. In this context, we wanted to review the articles after 2013 and update the information. Current articles after 2013 investigating the relationship between “pain in the spine and BMI” were determined as inclusion criteria. Moreover, Gasparyan et al. suggested that the last 7 years can be screened for review³⁹).

(4)

Randomized controlled, cohort (prospective/retrospective), cross-sectional, case–control, pre-post studies.

Exclusion criteria

(1)

Reviews, editorial opinions-suggestions, discussion papers.

(2)

Spinal/orthopedic deformities (scoliosis, kyphosis, etc.), systemic diseases, and psychological problems in children/adolescents.

(3)

Non-full text publications; letters to the editor/case reports/abstracts/posters.

Study Selection

First of all, the studies were screened by examining the titles and abstracts of the articles according to inclusion/exclusion criteria. Second, it was checked whether articles meeting the inclusion criteria were full text. Titles/abstracts were screened by two independent researchers.

Assessment of Methodological Quality

The methodological quality assessment was conducted using list of Van Rijn et al.,³⁶ Padula et al.,⁴⁰ and Sanderson et al.⁴¹ (Table 2). The list was formed with 18 items. While all 18 items were evaluated in the longitudinal studies, only 14 were included in the cross-sectional studies. The use of this list in systematic reviews has recently increased.⁴³ Two independent researchers rated the methodological quality of each criterion as “positive, negative, uncertain, not applicable.” Both researchers discussed and resolved differences of opinion, and a final score was calculated. The final score of each study was calculated by dividing sum of the positive criteria by the total number of items. If the number of positive scores was over 12, the methodological quality of the study was accepted to be high, between 6 and 12 to be medium and under 6 to be low.^36,40,41

Table 2.

Risk-of-Bias Assessment: Scoring Options Included Positive, Negative, Unclear

Criteria for quality score
Study population
(1) Study groups (complaints and no complaints) are clearly defined	Positive if at least two of the following three items in both groups were reported: age, gender, and weight status or BMI
(2) Participation ≥70%	Positive if the participation of overweight and normal weight groups was ≥70%
(3) Number of cases ≥50	Positive if number of cases (people with complaint) ≥50
Assessment of overweight
(4) Overweight definition	Positive if BMI cutoff values for overweight definition were mentioned
(5) Assessment of overweight	Positive if assessment of weight and height was described
(6) Blind for complaint status	Positive if weight status was measured by an independent person without knowledge of the complaint status
Assessment of complaint
(7) Complaint definition	Positive if a definition of the musculoskeletal complaint was given
(8) Assessment of complaint	Positive if the method of assessment was described
(9) Blind for weight status	Positive if the complaint was measured without knowledge of the weight status
Study design
(10) Longitudinal design	Positive if the study design was longitudinal
(11) Inclusion and exclusion criteria	Positive if inclusion and exclusion criteria were described
(12) Follow-up period ≥1 year	Positive if the follow-up period was ≥1 year
(13) Information on study completers versus withdrawals	Positive if demographic information was given for completers and withdrawals
Analysis and data presentation
(14) Data presentation	Positive if risk estimates were presented or if raw data were given that allowed the calculation of risk estimates, such as odds or prevalence ratios or relative risks
(15) Consideration of confounders	Positive if the confounders that were considered were described
(16) Control for confounding	Positive if the method used to control for confounding was described

Data Extraction

As can be seen in Table 3, the data in the studies were listed in order by first author, publication attributes, participants, outcome measurements, other assessments, results, and discussion.

Table 3.

Informations and Results of the 12 Included Studies

Publication (author/year/country/place/type of study)	Participants		Assessments			Results	Discussion
Publication (author/year/country/place/type of study)	Age/gender	Sample size (n)	Weight status assessment	Pain location	Pain assessment/assessor/time	Results	Discussion
Hershkovich 2013/Israel/Military/Cross-sectional⁴⁴	17 years/43.3% female	829.791	BMI (kg/m²)Underweight (<5%), normal weight (5% to <85%), overweight (85% to <95%), and obese (≥95%) (CDC)	Lower back	—Patients diagnosed with low BP/—/—	The mean BMI (kg/m²):22.04 ± 3.8 for males; 21.8 ± 3.7 for females.25,416 (5.4%) males and 10,442 (2.9%) females of 829,791 participants have LBP.In males and females, higher BMI is correlated with LBP (p < 0.001).In males and females, height is correlated with the prevalence of LBP (p < 0.001).	The relationship between LBP and increased BMI may be due to pathophysiology and reasons related to mechanical loading and metabolic activity, such as adipose tissue and cytokines.
Mikkonen 2013/Finland/University Hospital/Prospective cohort³¹	At 7, 16, 18, 19 years/55.9% female	1660	BMI (kg/m²)WC	Lower back	Pain location was questioned on body model/—/in lasting 6 months, after 19 years	In boys, BMI (7–16 years) is correlated with incident LBP at 18 years.In girls, BMI (16–18 years) is correlated with incident LBP at 18 years.In boys, WC (16–19 years) is correlated with incident LBP at 19 years (and after adjustment for smoking and physical activity). In girls, there are no correlations between WC and LBP.	The gender differences with regard to time periods in the association between BMI and LBP may be related to differences in growth,especially the distribution of adipose tissue or the proportion of lean tissue, in psychosocial factors.
Wirth 2013/Switzerland/⁴⁵	6–16 years/53.7% female	836	BMI (kg/m²)	Pain in the spine regions	Lifetime prevalance, severity, recurrence, pain in the spine consequences/chiropractors/last month	Thoracic pain was positively associated with high BMI (p = 0.027).There were no correlations between BMI and LBP or NP.	The increase in backpack weight may have made the localization region of the pain in the spine the focal point on the back. The high point of pain may be the back, as the high BMI may increase the load on the spine.
Minghelli 2015/Portugal/Public Schools/Cross-sectional, observational, analytical²⁵	10–16 years/54.8% female	966	BMI (kg/m²)	Lower back	LBP Questionnaire/—/last 1 year	25% of participants with LBP have overweight/obesity, but this status has no significance.LBP presence for overweight participants n (%) = 84 (18.4), participants with obesity n (%) = 28 (6.1).	The relationship between BMI and pain in the spine may be examined as a result of the effect of risk factors such as a change in spinal curvature (cervical, thoracic, lumbal) caused by a change in the center of gravity due to increased abdominal circumference and weakness of the abdominal muscles.
Sano 2015/Japan/Schools/Cohort⁴⁶	At 9, 10, 11, 12, 13, 14 years/At 9 years: 52% femaleAt 10 years: 51% femaleAt 11 years: 51% femaleAt 12 years: 50% femaleAt 13 years: 50% femaleAt 14 years: 48% female	At 9 years: 3973At 10 years: 5023At 11 years: 5031At 12 years: 5260At 13 years: 5092At 14 years: 5097	BMI (kg/m²)	Lower back	Anonymous Questionnaires, severity/—/—	^: In the results, a relationship was found between BMI and LBP at any age.The BMI means of 9-year-old participants with LBP: 18.3 ± 3.5 kg/m².^At 10 year BMI mean: 18.7 ± 3.9 kg/m².^At 11 year BMI mean: 18.4 ± 3.2 kg/m².^At 12 year BMI mean: 18.9 ± 2.9 kg/m².^At 13 year BMI mean: 19.3 ± 2.5 kg/m².^At 14 year BMI mean: 19.9 ± 2.6 kg/m².^*
Santos 2017/USA/Pediatric Pain Clinic/Retrospective⁴⁷	8–18 years/68.7% female	99	BMI (kg/m²)95th percentile	Abdomen, back, head, diffuse or localized musculoskeletal pain	Pain Frequency Severity-Duration ScalePain catastrophizing/—/in last 2 weeks	Aproximately 45% of participants with BP are in the risk and aproximately 25% are in the obesity category. The BMI mean (kg/m²): 24.3 ± 6.3.Most frequently pain locations in the abdomen/pelvic area/flank (39.8%), head (36.9%), and back (24%).Pain locations for back n = 23, for neck/shoulder n = 14.Youths with obesity report longer pain duration (mean = 41.91 months, p = .039) than youth normal weight (17.06 months).	Pediatric pain specialists may see children who have weight management difficulties more frequently in clinics.
Scarabottolo 2017/Brazil/Public Schools/Cross-sectional²⁹	17 years/55% female	1011	BMI (kg/m²)WC	Neck, lower back, back, upper back, and lower extremity	Nordic Questionnaire/—/last 7 days	Reported pain in NP: 176 (17.4%), in LBP: 182 (18.0%)NP n (%) boys: 71 (15.7) girls: 105 (18.9). LBP n (%): boys 71 (15.7), girls 111 (20).Older adolescents (14–17 years) have a higher percentage of cervical pain (24.4%), LBP (25.1%) than younger (11.9%–12.4%) (p < 0.001).WC (cm) boys: 68.8 (9.7), girls: 68 (9.6). Abdominal obesity is associated with LBP, but not NP (p = 0.055).	Abdominal obesity is associated with LBP, but not NP.
Dianat 2018/Iran/School/Cross-sectional analytical⁴⁸	11–14 years/52% female	1611	BMI (kg/m²)	Neck and shoulder	Questions about prevalence of neck and shoulder pain/—/past month	In the results, a relationship was found between BMI and NP.It has been reported that children with low BMI (BMI <17.33) may experience less NP (p < 0.05).
Noormohammadpour 2019/Iran/High school/Prospective Cross-sectional⁴⁹	13–18 years/100% female	372	BMI (kg/m²)	Lower back	Questions (experience of LBP in the last year/month/48 hours)	There was no relationship between BMI and LBP.The BMI means of participants with lifetime history of LBP: 22 ± 4.2 kg/m².The BMI means of participants with history of 3 months LBP: 22.7 ± 5.5 kg/m².The BMI means of participants with last month history of LBP: 22.3 ± 4.2 kg/m².
Azabagic 2019/Bosnia and Herzegovina/—/Longitudinal cohort³⁸	9–14 years/50% female	1315	BMI (kg/m²)Underweight (<5%), normal weight (5% to <85%), overweight (85% to <95%), and obese (≥95%) (CDC)	Neck, shoulder, wrist, upper back, lower back, knee, ankle	Nordic Questionnaire/—/for 7 days or 1 year	In the excessive BMI classification, among the pains with the highest pain rate, chronic LBP is 2.6%, acute NP is 3.1% with the highest pain.The highest pain rate of individuals with obesity status is chronic LBP with 2.3% and chronic NP with 2.1%.Excessive BMI and obesity are a risk factor for the development of NP and BP (OR = 1.212, 95% CI, 1.020–1.322).The number of participants with overweight: 243 (18.5%)The number of participants with obesity status: 166 (12.6%)
Schwertner 2020/Brazil/School/Retrospective	15–18 years/74% female	330	The BMI classification (normal, overweight, obese) Cole method. The cutoff point of 17 kg/m²WC	Lower back	Oliveria Questionnaire on LBP in Youths/—/last 3 months, throughout life	71% of participants normal BMI: 22 ± 3.9 kg/m², mean WC: 70.5 ± 9.4 cm.There was no relationship between BMI and LBP.
Palmer 2020/Catalonia/Catalan Universal Health care System/Longitudinal Cohort⁵¹	4–15 years/48.58% female	466.997	BMIz categories (underweight, normal weight, overweight, obese)	Neck, back, lower back	The rate of being diagnosed with BP (all spine regions) and experiencing the frequency of BP(all spine regions)/pediatric doctor or nurse/—	Overweight and obesity status in children increase the risk of BP at any region (lumbar-4.33%, thoracic-2.46%, cervical-2.86%).Adjusting for confounders a child with obesity has a 34% excess risk of developing BP (all spinal regions) before the age of 15 years.	Children who are overweight and obese have an increased risk of BP, which can lead to persistence of both factors into adulthood.

BMIZ, BMI for age Z-score; CDC, Centers for Disease Control and Prevention; CI, confidence interval; CRP, chronic regional pain; CWP, chronic widespread pain; NRS, Numeric Rating Scale; SD, standard deviation; WC, waist circumference.

Results

Study Selection

The flow diagram is shown in Figure 1. Articles published in last 7 years were included in the scope of this systematic review,³⁹ and literature search identified 343 studies. Among those 343 publications, 287 articles were found to be not related to BMI/overweight/obesity and pain in the spine in children/adolescents and 35 articles were excluded due to duplication. Consequently only 21 studies were left to include in the review. However, it was determined that 9 out of 21 articles were published before 2013; hence, they were excluded and total of 12 studies were examined and results of the included studies are given in Table 3.

Figure 1.

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram of the process on identifying and selecting studies.

Study Characteristics

All the studies included (n = 12) in the review were in English language and published between 2013 and 2020. Sample sizes varied between 99 and 829,791. The mean age, body weight, pain intensity, pain duration, and pain frequency could not be calculated, because the mean age in 2 studies,^31,46 the mean BMI in 3 studies,^25,29,45 the pain intensity in 8 studies,^{25,29,31,38,46,49–51} the duration of pain in 9 studies,^{25,29,31,38,44,46,48,50,51} and the pain frequency in 10 studies^{25,29,31,38,44,46,48–51} were not specified. In addition, the reason for not being able to calculate the pain intensity and BMI was that different methods were used in the assessment of pain and BMI in the included studies and there was no standardization.

The Methodological Quality Assessment

The Cohen Kappa value was found to be 0.85 indicating a high reliability. The final methodological quality assessment is shown in Table 4. While methodological quality of seven studies was high,^{31,38,45,46,49–51} five studies had medium methodological quality.^{25,29,44,47,48}

Table 4.

The Methodological Quality Assessment. Scoring Options Included Positive (+), Negative (−), Unclear (uc), Not Applicable (na)

Study	Study groups are clearly defined	Participation ≥70	No. of cases ≥50	Overweight definition	Assessmentof overweight	Blind complaintstatus	Complaint definition	Assessment of complaint	Blind weight status	Prospective design	Inclusion and exclusion criteria	Follow-up period ≥1 year	Information completers versus withdrawals	Research question	Data presentation identifying confounders	Consideration of confounders	Control for confounding	Statistical methods	Total percentage (%)	Methodological quality
Hershkovich et al.⁴⁴	+	+	+	+	+	−	+	+	−	−	−	−	−	+	−	−	−	+	50	Medium
Mikkonen et al.³¹	+	+	+	+	+	−	+	+	−	+	−	−	−	+	+	+	+	+	72	High
Wirth et al.⁴⁵	+	+	+	+	+	−	+	+	−	+	+	−	+	+	−	−	−	+	67	High
Minghelli et al.²⁵	+	+	+	+	+	−	+	+	−	−	−	−	−	+	−	−	−	+	50	Medium
Sano et al.⁴⁶	+	+	+	+	+	−	+	+	−	+	−	+	+	+	−	−	−	+	67	High
Santos et al.⁴⁷	+	−	+	+	+	−	+	+	−	−	+	−	−	+	−	−	−	+	50	Medium
Scarabottolo et al.²⁹	+	−	+	+	+	−	+	+	−	−	−	−	−	+	+	+	+	+	61	Medium
Dianat et al.⁴⁸	+	+	+	+	+	−	+	+	−	+	−	−	+	+	−	−	−	+	61	Medium
Noormohammadpour et al.⁴⁹	+	+	+	+	+	−	+	+	−	+	+	−	+	+	−	−	−	+	67	High
Azabagic and Pranjic³⁸	+	+	+	+	+	−	+	+	−	+	+	−	+	+	−	−	−	+	67	High
Schwertner et al.⁵⁰	+	+	+	+	+	−	+	+	−	+	+	−	+	+	+	+	+	+	83	High
Palmer et al.⁵¹	+	+	+	+	+	−	+	+	−	+	+	−	+	+	+	+	+	+	83	High

High, high frequency of positive values “+” ≥67% corresponds to a score ≥12; Medium, medium frequency of positive values “+” 66% to 34% corresponds to a score 6 < 12; Low, low frequency of positive values “+” ≤33% corresponds to a score ≤6; na, not applicable; uc, unclear.

The assessment of BMI/overweight/obesity and pain complaints has been presented appropriately in the studies. Three studies have identified confounders, including sex, age, smoking, socioeconomic status, nationality, and leisure time physical activity.^29,31,50,51

Outcome Measurements

Pain in the spine and BMI/overweight/obesity assessments

When the studies were examined, 12 studies evaluated the pain but each used a different method for its assessment. The methods used for pain assessment were LBP Questionnaire,²⁵ Nordic Questionnaire,^29,38 asking about pain location on body model,³¹ just diagnosed LBP,⁴⁴ lifetime prevalance-severity-recurrence of pain in the spine,⁴⁵ anonymous questionnaires-pain severity,⁴⁶ Pain Frequency-Severity-Duration Scale,⁴⁷ questions about prevalence and experience of neck-shoulder-LBP,^48,49 Oliveria Questionnaire on LBP in Youths,⁵⁰ and diagnosed by pediatrician.⁵¹

Three studies evaluated pain duration, severity, and localization.^31,45,47 In 10 studies LBP,^{25,29,31,38,44,46,47,49–51} in 5 studies NP,^{29,38,45,48,51} and in 4 studies BP were assessed.^29,38,47,51

In the evaluation of BMI/overweight/obesity, all studies (n = 12) calculated BMI by dividing body weight in kilograms by height squared (kg/m²).^{25,29,31,38,44–51} Six studies used BMI percentiles.^38,44,47,50 Three studies used waist circumference (WC).^29,31,50

The relationship between BMI and pain in the spine

The relationship between BMI and pain in the spine was examined in 12 studies; 7 studies were found to be methodologically high, and 5 studies were found to have medium quality and their results were discussed. Five of these studies showed a relationship between BMI and NP⁴⁸; thoracic pain (TP)⁴⁵; and LBP^31,44,46; four studies did not show a relationship between BMI and LBP.^24,25,49,50

According to age and gender classification, Mikkonen et al. reported a relationship between LBP and BMI in boys aged 7–16 years and in girls aged 16–18 years. It was found that WC was associated with LBP in males aged 16–19 years, but there was no correlation between WC and LBP in girls (75% risk ratio).³¹ In contrast, Hershkovich et al. reported a relationship between high BMI and LBP in both genders. Height was reported to increase the risk of LBP in both genders.⁴⁴ Sano et al. determined that there was a relationship between BMI and LBP at any age.⁴⁶ The methodological quality of those three studies was found to be high^31,46 or medium.⁴⁴ However, despite the studies conducted by Noormohammadpour et al. and Schwertner et al. being of high methodological quality, no relationship between BMI and LBP was found.^49,50

Wirth et al. reported that there was a relationship between BMI and TP (p = 0.027), but no relationship was found between BMI and LBP or NP.⁴⁵ Similarly, Dianat et al. indicated a relationship between BMI and NP.⁴⁸ They concluded that children with low BMI (BMI <17.33) could experience less NP (p < 0.05).⁴⁸ And it was determined that those two studies were of high and medium methodological quality.

The relationship between overweight/obesity and pain in the spine

While two studies reported that there was a relationship between overweight and LBP,^31,44 no relationship between overweight and LBP was found in another study.²⁵ Mikkonen et al. and Herskovic et al. showed a relationship between BMI and LBP and these studies had high and medium methodological quality, respectively.^31,44 However, although the study conducted by Minghelli et al. was of a medium level methodological quality, the relationship between overweight and LBP was not reported.²⁵

Three studies in the scope of the present review showed a relationship between obesity and LBP.^29,44,51 One study revealed that there was no relationship between obesity and LBP.²⁵ Among the studies investigating the relationship between obesity and NP, two studies reported a relationship,^38,51 while no relationship was found in other studies.²⁹ In one study, the relationship between obesity and BP was not assessed and, ratio of obesity and BP was provided.⁴⁷ In contrast, a study reported a relationship between obesity and BP.⁵¹ Hershkovic et al. showed a relationship between obesity and LBP and that the study was found to have medium methodological quality. In males and females, higher BMI is correlated with LBP (p < 0.001).⁴⁴ Scarabottolo et al. reported that abdominal obesity was associated with LBP, and this study had medium methodological quality.²⁹ Palmer et al. reported a relationship between obesity and LBP and indicated that the risk of LBP was 4.33% in children with obesity.⁵¹ The study of Minghelli et al. had medium methodological quality; 25% of participants with LBP had overweight/obesity, but it was considered that this situation had no impact.²⁵ Minghelli et al. did not indicate a relationship between obesity and LBP.²⁵

Palmer et al. and Azabagic and Pranjic reported a relationship between obesity and NP, and these studies had a high methodological quality.^38,51 Obesity was recognized to be an important risk factor for the development of chronic NP.³⁸ On the contrary, Scarabottolo et al. did not find a relationship between abdominal obesity and NP, and this study was of medium methodological quality.²⁹ Although the study of Santos et al. was of medium methodological quality, no assessment was performed for the relationship between obesity and BP in the study.⁴⁷

Discussion

In this review, the relationship between BMI and pain in the spine in children or adolescents was systematically reviewed in the light of the studies in the literature, and the researches that included participants from different clinics and schools were examined. Neck, back, and lower back regions were examined as pain regions in the spine. The main finding of this systematic review is that there is a relationship between BMI and pain in the spine, especially LBP. In addition, it was determined that there was no common assessment method to evaluate pain in the spine in relation to BMI/overweight/obesity in children/adolescents. There are systematic reviews in the literature investigating musculoskeletal pain and complications in children with overweight and obesity, and although those examined all musculoskeletal pain, unlike our systematic review, these reviews presented similar results in terms of pain regions especially LBP in the spine studied.^14,15 However, this systematic review provides up-to-date findings by more specifically examining the relationship between BMI and pain in the spine in children/adolescents.

Pain in the spine, referred to as NP, BP, and LBP, is frequently reported in childhood and early adolescence, especially between the ages of 11 and 15 years.¹⁷ It is accepted that the pain in the spine experienced in childhood and adolescence continues in adulthood at the end of adolescence.^16,52,53 A similar inference can be made for obesity. It was stated in a meta-analysis that children and adolescents who were obese had five times more risk of being obese in adulthood compared to children and adolescents with no obesity.⁵⁴ Therefore, it can be inferred that obesity and pain in the spine that started in early stages of life will continue in adulthood.^17,51,54 Although the reviews and meta-analyses of the limited studies in the literature have investigated adults, it was stated that obesity is a risk factor especially for LBP.^55,56,58 In addition, in a systematic review investigating the frequency of pain in the spine in adolescents, it has been reported that frequency of experiencing pain was 3%–8% for NP, 9.5%–72% for BP, and 7%–72% for LBP.¹⁶ Krul et al. stated that NP and BP were more commonly observed in children who were overweight.⁵⁹ In reviews conducted to demonstrate the relationship between BMI and NP, Dianat et al. reported that there was a relationship between BMI and NP⁴⁸ in children and adolescents, and Azabagic and Pranjic indicated that excessive BMI and obesity are risk factors for the development of acute NP³⁸ in children and adolescents; Palmer et al. determined that children with obesity had 2.86% higher risk of pain in the cervical region compared to children with normal weight.⁵¹ However, Scarabottolo et al. and Wirth et al. found no relationship between obesity or BMI and NP.^29,45 Two out of three studies reporting the relationship between obesity and pain in the spine had a high level of evidence,^38,51 while there was a medium level of evidence in the last one.⁴⁸ In the studies indicating no relationship between obesity and pain in the spine, level of evidence was found to be high in one study and medium in the other. Nordic Questionnaire was used in two studies for the assessment of NP.^29,38 Two studies assessed the pain by asking participants about the prevalence of NP.^45,48 One study that showed the relationship evaluated the pain as a doctor's diagnosis.⁵¹ It could be concluded from the results of included studies that there was an uncertainty in the relationship between NP and BMI or obesity. The inference about NP obtained in the present systematic review is similar to the results demonstrated in the review published by Jeffries et al.¹⁶ It is our consideration that the relationship between NP and BMI should be investigated more comprehensively in children and adolescents. Because in children and young people, NP can be experienced more frequently in relation to situations such as incorrect sitting posture at school and difficulties related to doing excessive homework and seeing the board in class. Studies have shown that factors such as improper sitting position, excessive homework, and having difficulty seeing the board in the classroom were associated with NP in children and adolescents.^60–62

From the articles included in the systematic review, Wirth et al. reported that TP was positively correlated to high BMI.⁴⁵ Azabagic and Pranjic stated that there was a relationship between acute and chronic BP and body weight.³⁸ Palmer et al. determined that children with obesity had 2.46% higher risk of pain in the thoracic region compared to children with normal weight.⁵¹ However, Scarabottolo et al. and Santos et al. indicated that there was no relationship between BMI or obesity and BP.^29,47 All three studies reporting the relationship between BMI or obesity and BP had a high level of evidence,^38,45,51 while two studies showing no association were of moderate level of evidence.^29,47 Some studies^29,47 did not investigate the relationship between BMI and BP. When BP in children and adolescents is considered, the back region can be considered to be pain prone as the region where the external weight is carried. Hence in addition to carrying a weight such as backpack in the back, weight gain of body can also affect the pain. It has been stated that high BMI and carrying heavy backpacks caused BP.⁶³ Stovitz et al. stated that a 10 kg increase in weight caused a 1.09 U increase in BP, and a 1 kg/m² increase in BMI caused a 1.02 U increase in BP.³³ Dockrell et al. reported that backpack carried by children with overweight/obesity was heavier than those with healthy weight, and they suggested that future studies could focus on school bag weight with increased BMI in children.⁶⁴ The increase in backpack weight may have made the location of the BP the focal point on the back. The greatest pain can be felt in the back, as the load on the spine increases with increasing BMI.

A recent systematic review examining the relationships between obesity and pain stated that there were many studies in the literature, but the evidence was not convincing.⁶⁵ The review summarized the relationship between obesity and pain in terms of mechanical, behavioral, and physiological aspects by conducting a literature search.⁶⁵ Considering the mechanical mechanism of the spine, it was stated that excessive weight in the body created a mechanical load on the spinal discs, weight-bearing joints, and muscles. In other words, the increase in body weight can affect the pain either directly as seen in joint damage or indirectly, due to creating load on the spine.^65,66 The systematic review and meta-analysis explained the mechanical mechanism using the study conducted by Singh et al.^65,66 It was reported that the compression force on the L5-S1 disc varied biomechanically in individuals with obesity and normal weight; and the limit in compression force was 3400 N. If this limit is exceeded in individuals with obesity, the compression force increases. For this reason, it is stated that individuals with obesity have a higher tendency of developing LBP due to overload.^65,66 In a systematic review explaining the relationship between BMI and LBP, Hershkovich et al. reported that higher BMI was associated with LBP⁴⁴; Azabagic and Pranjic stated that there was a relationship between acute LBP and body weight.³⁸ Mikkonen et al. reported a relationship between LBP and BMI in boys aged 7–16 years and in girls aged 16–18 years. WC was found to be associated with LBP in males aged 16–19 years.³¹ Sano et al. presented a relationship between BMI and LBP for the children with the age of 10–14 years.⁴⁶ Scarabottolo et al. reported that abdominal obesity was associated with LBP.²⁹ Palmer et al. determined that children with obesity had 4.33% higher risk of pain in the lower back region compared to children with normal weight.⁵¹ A study investigating the relationship between pain severity and BMI found that increased BMI resulted in higher pain severity in LBP and concluded that increased BMI was an important risk factor affecting pain severity.³⁴ All studies included in that systematic review are of either high^31,38,46,51 or medium^29,44 level of evidence. Considering all articles included in our study, although the relationship between BP, LBP, and BMI/overweight/obesity was unclear, studies showing a relationship indicated that the lower back region could be more affected in terms of stress and pain in the spine. The relationship between LBP and increased BMI may be due to the metabolic activity such as adipose tissue and cytokines in addition to reasons related to mechanical loading mentioned above. The effect of metabolic activity on the relationship between BMI and LBP may be related to differences in growth, particularly the distribution of adipose tissue or the proportion of lean tissue. In adolescence, girls are prone to gain weight, and adipose tissue is stored in the chest, abdominal, and hip region. In young males, adipose tissue accumulation occurs around the abdominal region. Postural changes due to the effect of gravity on weight gain and the weakness of the abdominal muscles may increase the load and pain on the lower back region.^34,67,68

The excess weight increases the strain on the musculoskeletal system and the risk of injury and pain, ultimately restricting all body movements and increasing immobility. Consequently, this situation may lead to weight gain, due to increased sedentary lifestyle and the vicious cycle of pain.²⁸ The literature states that children with obesity and chronic pain experience 6.6 times more problems in physical functions than children with obesity without pain, that sedentary time and inactivity play an important role in BMI and obesity in children, and that physical inactivity is a factor that can cause NP, BP, and LBP.^69–73

A relationship between BMI and LBP was reported by Wirth et al., Noormohammadpour et al., and Schwertner et al.^45,49,50 On the contrary, the study conducted by Minghelli et al. found no relationship between LBP and overweight or obesity.²⁵ Although some studies indicated a relationship between NP, BP, LBP, and BMI, some studies found no relationship between those variables. However it should be noted that factors such as pain assessment methods, pain severity, frequency, and duration of the studies differed in those studies. In addition, confounder factors such as age or gender were not taken into consideration in some studies, and therefore, results were found to be different. In addition, it was unclear whether the pain in the spine was acute or chronic, as the duration was not questioned in all studies. Azabagic and Pranjic evaluated the pain regions in the spine as acute or chronic and stated that chronic BP was associated with body weight, and obesity and exposure to weight had an effect on chronic pain.³⁸ Since the evaluation criteria of the studies in the review were not standard and the relationships between BMI or weight status and pain severity, frequency, and duration remained uncertain, it is our opinion that more comprehensive studies are needed.

Several studies suggest that there is a strong association between overweight or obesity and LBP.^57,74 Childhood obesity is an indicator of adult obesity and that treatment and preventive programs are important.⁵⁴ Pediatric pain specialists may see children with weight management difficulties more frequently in clinics. In this review, Santos et al. showed that 50% of the sample was obesity/overweight, and risky children also applied to clinics.⁴⁷ Wilson et al. reported a relationship between BP and high BMI percentile in children/adolescents and found that the BMI percentile and BP relationship was stronger in older adolescents who needed treatment for pain.²⁸ The relationship between overweight and obesity in the adolescent group and NP, BP, and LBP will be alarming in adulthood, suggesting a future cost burden and the need for intervention in the childhood.⁵⁷

It is noteworthy to state that families reported high scores on pain catastrophe and disability of their children in relation to pain and obesity. In Santos's study, families of girls with obesity reported higher disability scores.⁴⁷ It could be speculated that parents may give a “protective response” that facilitates weight gain, depending on their concerns about the pain their children are experiencing.^15,47 In addition, pain severity and pain reporting may be reflected differently in children and families. Family protective behavior, chronic pain, and weight gain cycles also need to be investigated.

Strengths and Limitations

To our knowledge, this is the first study to have systematically reviewed the relationship between BMI and pain in the spine in children/adolescents.

When strengths and limitations were examined, it was seen that there was no standardization in weight, height, BMI, and pain assessment studies. In some studies, self-reported height and weight may not reflect the actual values. In addition it was found that different BMI, BMI percentile, or WC were used in the studies. It is known that the use of BMI in adults gives sufficiently accurate results, whereas BMI percentile in the pediatric group gives more accurate results for age and gender.

There was no common method suggested in the literature regarding the assessment of NP, BP, and LBP in children/adolescents. In the studies included in the review, the questions were asked with yes/no responses, but the severity, frequency, and duration of pain were not questioned. Therefore, it is difficult to assess the pain in the same standardization.

The methodological quality levels of studies included in the present review were medium and high. In the results of Minghelli et al.,²⁵ Scarabottolo et al.,²⁹ Noormohammadpour et al.,⁴⁹ and Schwertner et al.,⁵⁰ no significant relationship between BMI/overweight/obesity and NP, BP, LBP was reported, but the level of evidence was high^49,50 or medium^25,29 in terms of methodological evaluation. The difference in the methods used to evaluate these outcome discrepancies may be due to the lack of accurate interpretation of the evaluators in the studies and is open to discussion.

Pain and BMI follow-up could not be performed because the studies included in the review were cross-sectional.

When potential confounders in the studies were examined, it was observed that the factors such as age, sex, psychosocial factors, social status, and school performance were rearranged and analyses were not performed. Confounder variables should be taken into consideration in the future studies, since analysis of the confounders in the studies would contribute to the power of the research.

Implications

NP, BP, and LBP can be observed in children/adolescent with overweight/obesity. There are deficiencies in the comprehensive assessment of factors such as NP, BP, LBP, or BMI. Further studies are needed to shed light on the evaluation of children/adolescents with overweight/obesity in all these aspects.

Conclusion

In the articles reviewed, it was seen that different methods were used in pain in the spine and BMI assessments. Therefore, it was understood that the relationship between BMI and pain in the spine could not be directly examined. However, in the light of the articles examined, some situations have come to the fore. When looking at the relationship between NP and BMI, no definitive results were seen. It was observed that NP in children and adolescents was mostly associated with sitting posture at school and doing homework.

In the relationship between BP and BMI, the factor of pain may be the back region where the local load due to carrying a backpack occurs.

In the relationship between LBP and BMI, the fact that the lumbar region carries the whole spine load and especially the increase in age and metabolic weight gain on the whole spine at the beginning of puberty reveals the relationship between BMI and LBP.

BMI is associated with NP, BP, and LBP, especially with LBP, due to mechanical loading and hormonal metabolic activity in childhood and adolescence. Different methods were used in the studies for the assessment of NP, BP, and LBP and BMI, overweight, and obesity. There is a need for high-quality randomized controlled, prospective cohort studies to enable better evaluation methods in the field.

Footnotes

Funding Information

No funding was received for this article.

Author Disclosure Statement

No competing financial interests exist.

References

World Health Organization. www.who.int/dietphysicalactivity/childhood/en (Last accessed January 2021 ).

Williams

, Goulding

. Patterns of growth associated with the timing of adiposity rebound. Obesity, 2009; 17:335–341.

Dietz

, Robinson

. Clinical practice. Overweight children and adolescents. N Engl J Med, 2005; 352:2100–2109.

Kumar

, Kelly

. Review of childhood obesity: From epidemiology, etiology, and comorbidities to clinical assessment and treatment. Mayo Clin Proc, 2017; 92:251–265.

O'Connor

, Evans

, Burda

, et al. Screening for obesity and intervention for weight management in children and adolescents: Evidence report and systematic review for the US Preventive Services Task Force. JAMA, 2017; 317:2427–2444.

Stolzman

, Irby

, Callahan

, Skelton

. Pes planus and paediatric obesity: A systematic review of the literature. Clin Obes, 2015; 5:52–59.

Villarroya

, Esquivel

, Tomas

, et al. Assessment of the medial longitudinal arch in children and adolescents with obesity: Footprints and radiographic study. Eur J Pediatr, 2009; 168:559–567.

Tenenbaum

, Hershkovich

, Gordon

, et al. Flexible pes planus in adolescents: Body mass index, body height, and gender—An epidemiological study. Foot Ankle Int, 2013; 34:811–817.

Riddiford-Harland

, Steele

, Baur

. Are the feet of obese children fat or flat? Revisiting the debate. Int J Obes (Lond), 2011; 35:115–120.

10.

Riddiford-Harland

, Steele

, Storlien

. Does obesity influence foot structure in prepubescent children?. Int J Obes Relat Metab Disord, 2000; 24:541–544.

11.

Kessler

, Koebnick

, Smith

, Adams

. Childhood obesity is associated with increased risk of most lower extremity fractures. Clin Orthop Relat Res, 2013; 471:1199–1207.

12.

Lusky

, Barell

, Lubin

, et al. Relationship between morbidity and extreme values of body mass index in adolescents. Int J Epidemiol, 1996; 25: 829–834.

13.

Tyler

, McHugh

, Mirabella

, et al. Risk factors for noncontact ankle sprains in high school football players: The role of previous ankle sprains and body mass index. Am J Sports Med, 2006; 34:471–475.

14.

Paulis

, Silva

, Koes

, van Middelkoop

. Overweight and obesity are associated with musculoskeletal complaints as early as childhood: A systematic review. Obes Rev, 2014; 15:52–67.

15.

Smith

, Sumar

, Dixon

. Musculoskeletal pain in overweight and obese children. Int J Obes, 2014; 38:11–15.

16.

Jeffries

, Milanese

, Grimmer-Somers

. Epidemiology of adolescent spinal pain: A systematic overview of the research literature. Spine (Phila Pa 1976), 2007; 32:2630–2637.

17.

Aartun

, Hartvigsen

, Wedderkopp

, et al. Spinal pain in adolescents: Prevalence, incidence, and course: A school-based two-year prospective cohort study in 1,300 Danes aged 11–13. BMC Musculoskelet Disord, 2014; 15:187.

18.

Hwang

, Louie

, Phillips

. et al. Low back pain in children: A rising concern. Eur Spine J, 2019; 28:211–213.

19.

Samartzis

, Karppinen

, Mok

, et al. A population-based study of juvenile disc degeneration and its association with overweight and obesity, low back pain, and diminished functional status. J Bone Joint Surg Am, 2011; 93:662–670.

20.

Paranjape

, Ingole

. Prevalence of back pain in secondary school students in an urban population: Cross-sectional study. Cureus, 2018; 10:e2983.

21.

Dianat

, Alipour

, Asghari Jafarabadi

. Prevalence and risk factors of low back pain among school age children in Iran. Health Promot Perspect, 2017; 7:223–229.

22.

Dianat

, Sorkhi

, Pourhossein

, et al. Neck, shoulder and low back pain in secondary schoolchildren in relation to schoolbag carriage: Should the recommended weight limits be gender-specific?. Appl Ergon, 2014; 45:437–442.

23.

Murphy

, Buckle

, Stubbs

. A cross-sectional study of self-reported back and neck pain among English schoolchildren and associated physical and psychological risk factors. Appl Ergon, 2007; 38:797–804.

24.

O'Sullivan

, Beales D

J S

, mith

, Straker

. Low back pain in 17 year olds has substantial impact and represents an important public health disorder: A cross-sectional study. BMC Public Health, 2012; 5:100.

25.

Minghelli

, Oliveira

, Nunes

. Association of obesity with chronic disease and musculoskeletal factors. Rev Assoc Med Bras, 2015; 61:347–354.

26.

Hills

, Andersen

, Byrne

. Physical activity and obesity in children. Br J Sports Med, 2011; 45:866–870.

27.

Mikkonen

, Heikkala

, Paananen

, et al. Accumulation of psychosocial and lifestyle factors and risk of low back pain in adolescence: A cohort study. Eur Spine J, 2016; 25:635–642.

28.

Wilson

, Samuelson

, Palermo

. Obesity in children and adolescents with chronic pain: Associations with pain and activity limitations. Clin J Pain, 2010; 26:705–711.

29.

Scarabottolo

, Pinto

, Oliveira

, et al. Back and neck pain prevalence and their association with physical inactivity domains in adolescents. Eur Spine J, 2017; 26:2274–2280.

30.

Deere

, Clinch

, Holliday

, et al. Obesity is a risk factor for musculoskeletal pain in adolescents: Findings from a population-based cohort. Pain, 2012; 153:1932–1938.

31.

Mikkonen

, Laitinen

, Remes

, et al. Association between overweight and low back pain: A population-based prospective cohort study of adolescents. Spine (Phlia Pa 1976), 2013; 38:1026–1033.

32.

de Sa Pinto

, de Barros Holanda

, Radu

, et al. Musculoskeletal findings in obese children. J Paediatr Child Health, 2006; 42:341–344.

33.

Stovitz

, Pardee

, Vazquez

, et al. Musculoskeletal pain in obese children and adolescents. Acta Paediatr, 2008; 97:489–493.

34.

Akdag

, Cavlak

, Cimbiz

, Camdeviren

. Determination of pain intensity risk factors among school children with nonspecific low back pain. Med Sci Monit, 2011; 17:PH12–PH15.

35.

De Paula

AJF

, Silva

, Paschoarelli

, Fujii

. Backpacks and school children's obesity: Challenges for public health and ergonomics. Work, 2012; 41:900–906.

36.

van Rijn

, Huisstede

, Koes

, Burdorf

. Associations between work-related factors and specific disorders of the shoulder—A systematic review of the literature. Scand J Work Environ Health, 2010; 36:189–201.

37.

Centers for Disease Control and Prevention. https://www.cdc.gov/obesity/childhood/defining.html (Last accessed July 3, 2018).

38.

Azabagic

, Pranjic

. The site of musculoskeletal pain in school children with excessive body weight and obesity in Bosnia and Herzegovina. Mater Sociomed, 2019; 31:88–92.

39.

Gasparyan

, Ayvazyan

, Blackmore

, Kitas

. Writing a narrative biomedical review: Considerations for authors, peer reviewers, and editors. Rheumatol Int, 2011; 31:1409–1417.

40.

Padula

, Comper

MLC

, Sparer

, Dennerlein

. Job rotation designed to prevent musculoskeletal disorders and control risk in manufacturing industries: A systematic review. Appl Ergon, 2017; 58:386–397.

41.

Sanderson

, Tatt

, Higgins

. Tools for assessing quality and susceptibility to bias in observational studies in epidemiology: A systematic review and annotated bibliography. Int J Epidemiol, 2007; 36:666–676.

42.

Hainsworth

, Miller

, Stolzman

, et al. Pain as a comorbidity of pediatric obesity. Infant Child Adolesc Nutr, 2012; 4:315–320.

43.

Seidel

, Ditchen

, Hoehne-Hückstädt

, et al. Quantitative measures of physical risk factors associated with work-related musculoskeletal disorders of the elbow: A systematic review. Int J Environ Res Public Health, 2019; 16:130.

44.

Hershkovich

, Friedlander

, Gordon

, et al. Associations of body mass index and body height with low back pain in 829,791 adolescents. Am J Epidemiol, 2013; 178:603–609.

45.

Wirth

, Knecht

, Humphreys

. Spine Day 2012: Spinal pain in Swiss school children- epidemiology and risk factors. BMC Pediatr, 2013; 13:159.

46.

Sano

, Hirano

, Watanabe

, et al. Body mass index is associated with low back pain in childhood and adolescence: A birth cohort study with a 6-year follow-up in Niigata City, Japan. Eur Spine J, 2015; 24:474–481.

47.

Santos

, Murtaugh

, Pantaleao

, et al. Chronic pain and obesity within a pediatric interdisciplinary pain clinic setting: A preliminary examination of current relationships and future directions. Clin J Pain, 2017; 33:738–745.

48.

Dianat

, Alipour

, Asgari Jafarabadi

. Risk factors for neck and shoulder pain among schoolchildren and adolescents. J Paediatr Child Health, 2018; 54:20–27.

49.

Noormohammadpour

, Borghei

, Mirzaei

, et al. The risk factors of low back pain in female high school students. Spine (Phila Pa 1976), 2019; 44:E357–E365.

50.

Schwertner

, Oliveira

RANS

, Koerich

MHAL

, et al. Prevalence of low back pain in young Brazilians and associated factors: Sex, physical activity, sedentary behavior, sleep and body mass index. J Back Musculoskelet Rehabil, 2020; 33:233–244.

51.

Palmer

, Poveda

, Martinez-Laguna

, et al. Childhood overweight and obesity and back pain risk: A cohort study of 466 997 children. BMJ Open, 2020; 10:e036023.

52.

Kamper

, Henschke

, Hestbaek

, et al. Musculoskeletal pain in children and adolescents. Braz J Phys Ther, 2016; 20:275–284.

53.

Leboeuf-Yde

, Kyvik

. At what age does low back pain become a common problem? A study of 29,424 individuals aged 12–41 years. Spine (Phila Pa 1976), 1998; 23:228–234.

54.

Simmonds

, Llewellyn

, Owen

, Woolacott

. Predicting adult obesity from childhood obesity: A systematic review and meta-analysis. Obes Rev, 2016; 17:95–107.

55.

Hartvigsen

, Hancock

, Kongsted

, et al. What low back pain is and why we need to pay attention. Lancet, 2018; 391:2356–2367.

56.

Zhang

T-T

, Liu

Y-L

, et al. Obesity as a risk factor for low back pain: A meta-analysis. Clin Spine Surg, 2018; 31:22–27.

57.

Shiri

, Karppinen

, Leino-Arjas

, et al. The association between obesity and low back pain: A meta-analysis. Am J Epidemiol, 2010; 171:135–154.

58.

Walsh

, Arnold

, Evans

, et al. The association between body fat and musculoskeletal pain: A systematic review and meta-analysis. BMC Musculoskelet Disord, 2018; 19:233.

59.

Krul

, van der Wouden

, Schellevis

, et al. Musculoskeletal problems in overweight and obese children. Ann Fam Med, 2009; 7:352–356.

60.

Gheysvandi

, Dianat

, Heidarimoghadam

, et al. Neck and shoulder pain among elementary school students: Prevalence and its risk factors. BMC Public Health, 2019; 19:1299.

61.

Prins

, Crous

, Louw

. A systematic review of posture and psychosocial factors as contributors to upper quadrant musculoskeletal pain in children and adolescents. Physiother Theory Pract, 2008; 24:221–242.

62.

Brink

, Louw

. A systematic review of the relationship between sitting and upper quadrant musculoskeletal pain in children and adolescents. Man Ther, 2013; 18:281–288.

63.

Spiteri

, Busuttil

, Aquilina

, et al. Schoolbags and back pain in children between 8 and 13 years: A national study. Br J Pain, 2017; 11:81–86.

64.

Dockrell

, Simms

, Blake

. Schoolbag carriage and schoolbag-related musculoskeletal discomfort among primary school children. Appl Ergon, 2015; 51:281–290.

65.

Chin

, Huang

, Akter

, Binks

. Obesity and pain: A systematic review. Int J Obes (Lond), 2020; 44:969–979.

66.

Singh

, Park

, Hwang

, Levy

. Severe obesity effect on low back biomechanical stress of manual load lifting. Work, 2015; 51:337–348.

67.

Tobias

, Deere

, Palmer

, et al. Joint hypermobility is a risk factor for musculoskeletal pain during adolescence: Findings of a prospective cohort study. Arthritis Rheum, 2013; 65:1107–1115.

68.

Adeyemi

, Rohani

, Abdul Rani

. Backpack-back pain complexity and the need for multifactorial safe weight recommendation. Appl Ergon, 2017; 58:573–582.

69.

Hainsworth

, Davies

, Khan

, Weisman

. Co-occurring chronic pain and obesity in children and adolescents: The impact on health-related quality of life. Clin J Pain, 2009; 25:715–721.

70.

Wittmeier

, Mollard

, Kriellaars

. Physical activity intensity and risk of overweight and adiposity in children. Obesity (Silver Spring), 2008; 16:415–420.

71.

Andersen

, Crespo

, Bartlett

, et al. Relationship of physical activity and television watching with body weight and level of fatness among children: Results from the Third National Health and Nutrition Examination Survey. JAMA, 1998; 279:938–942.

72.

Crespo

, Smit

, Troiano

, et al. Television watching, energy intake, and obesity in US children: Results from the third National Health and Nutrition Examination Survey, 1988–1994. Arch Pediatr, 2001; 155:360–365.

73.

Christofaro

, De Andrade

, Mesas

, et al. Higher screen time is associated with overweight, poor dietary habits and physical inactivity in Brazilian adolescents, mainly among girls. Eur J Sport Sci, 2016; 16:498–506.

74.

Koyanagi

, Stickley

, Garin

, et al. The association between obesity and back pain in nine countries: A cross-sectional study. BMC Public Health, 2015; 15:123.