|Year : 2022 | Volume
| Issue : 3 | Page : 292-299
Prevalence, Pattern and Sociodemographic Correlates of Psychosocial Disorders in Obese Adolescents in Enugu, Nigeria
Okechukwu N Ozoalor1, Anthony N Ikefuna2, Ann E Aronu2, Ngozi C Ojinnaka2
1 Lily Hospitals Ltd, Warri, Delta State, Nigeria
2 Department of Paediatrics, College of Medicine, University of Nigeria Teaching Hospital, Enugu, Nigeria
|Date of Submission||06-Oct-2021|
|Date of Acceptance||07-Jan-2022|
|Date of Web Publication||2-Jun-2022|
Ann E Aronu
Department of Paediatrics, College of Medicine, University of Nigeria Teaching Hospital, Ituku-Ozalla Campus, Enugu
Source of Support: None, Conflict of Interest: None
Background: Adolescent obesity is a serious public health issue. Inconsistent findings on its association with mental health problems are reported. Objective: This study aimed to determine the prevalence, pattern, and sociodemographic correlates of psychosocial disorders among obese adolescents in Enugu metropolis, Nigeria. Materials and Methods: A cross-sectional study was conducted over a 5-month period in 16 secondary schools in Enugu, Nigeria. A multi-staged systematic sampling technique was used to select participating schools. A total of 4364 adolescents aged 10–19 years from these schools were screened for obesity by measuring their height and weight, and calculating their body mass indices (BMIs), which were plotted on the Centers for Disease Control and Prevention BMI percentile chart. Seventy-four obese students were identified, and from their respective class registers, systematic sampling scheme was applied in selection of equal number of apparently healthy normal BMI (5th–84th percentile) controls matched for age and sex. The youth version of the Pediatric Symptom Checklist was used to screen for psychosocial disorder in the study participants. Results: The prevalence of psychosocial disorder was 17.6% and 12.2% among the obese and control adolescents, respectively (P = 0.02). Attention and externalizing problems were the highest among the obese adolescents, whereas psychosocial disorders were more in females than males (28.1% vs 9.5%; χ2 = 4.34, P = 0.04). Conclusion: Obese adolescents have a higher prevalence of psychosocial disorder compared to controls, with attention and externalizing problems being most common, and this was influenced by gender. Periodic assessment of the mental health of obese adolescents is advocated.
Keywords: Adolescent, Enugu, mental health problems, obesity, psychosocial disorder
|How to cite this article:|
Ozoalor ON, Ikefuna AN, Aronu AE, Ojinnaka NC. Prevalence, Pattern and Sociodemographic Correlates of Psychosocial Disorders in Obese Adolescents in Enugu, Nigeria. Int J Med Health Dev 2022;27:292-9
|How to cite this URL:|
Ozoalor ON, Ikefuna AN, Aronu AE, Ojinnaka NC. Prevalence, Pattern and Sociodemographic Correlates of Psychosocial Disorders in Obese Adolescents in Enugu, Nigeria. Int J Med Health Dev [serial online] 2022 [cited 2022 Aug 10];27:292-9. Available from: https://www.ijmhdev.com/text.asp?2022/27/3/292/346435
| Introduction|| |
The increasing trend in childhood overweight and obesity has been an issue of concern for both developed and developing countries.,,, Overweight and obesity are both terms used for ranges of weight generally considered unhealthy for a given height. Body mass index (BMI) is widely used to define overweight and obesity in adults, and it is the result of dividing weight in kilograms by height squared in meters because it correlates with body fat. Due to changing adiposity during childhood, the BMI percentile rather than absolute BMI is used for classifying overweight and obesity in children and adolescents with a percentile of 85th–94th and ≥95th classified as overweight and obesity, respectively, whereas a percentile from 5th to 84th is classified as normal weight. Ani et al. reported obesity prevalence of 4.1% among adolescents in urban areas of Enugu State, Nigeria.
Although it has been scientifically proven that obesity is a risk factor for many medical conditions such as diabetes mellitus, hypertension, obstructive sleep apnea, increased risk of fractures, hypertension, cardiovascular disease, and psychological effects,, the current evidence linking obesity and psychological disorders is not clear., While some authors have identified an association between these two conditions, others have failed to observe a significant relationship.,,,, Psychosocial disorders are diagnosable conditions characterized by changes in thinking, mood, or behavior (or a combination of these) that are associated with distress or impaired functioning. Disorders such as low self-esteem, depression, aggression, anxiety, behavioral problems, and conduct disorders have been variously reported by some authors among obese children and adolescents.,,, Vila et al. reported association between childhood obesity and psychosocial disorder. They noted that 58% of obese adolescents had psychosocial disorders, with anxiety, disruptive behavior disorder, and affective disorder being the most common. Blanco et al. reported association between childhood obesity and psychosocial disorder. They noted high rates of anxiety, depression, and weight-related teasing, as well as low self-esteem, among obese adolescents. Uleanya et al. in Enugu, Nigeria, in 2015 carried out a descriptive cross-sectional study among secondary school adolescents to determine the burden of psychosocial disorders among overweight and obese adolescents (10–18 years) using various psychometric tools (Beck Depression Scale, Revised Children’s Manifest Anxiety Scale, Rosenberg Self-Esteem Scale, and Internalized Stigma of Mental Illness Scale). They found that obesity was associated with depression, anxiety, low self-esteem, and discrimination stigma giving a total prevalence of 60.2%. Specific tools for individual psychosocial variables were used to assess each disorder, increasing the reliability of the result. However, there was no control group, so no definite conclusion could be drawn on the documented prevalence.
Adolescence is a period of rapid biological, psychological, and social transition associated with a need for identity formation and peer acceptance. The World Health Organization defines this as the period ranging from 10 to 19 years with early adolescence as 10–14 years and late adolescence as 15–19 years. During adolescence, there is a high level of emotional distress and turmoil with about 1–20% of general adolescent population suffering from various types of mental health problems. This may be due to heightened responsiveness to incentives and the brain being more susceptible to stress at this age when impulse control is still relatively immature, and also the need for identity formation and peer acceptance. For instance, depression has been documented as the most prevalent mental disorder among this age group, with greater than 25% of adolescents showing at least mild symptoms of this condition. Chinawa et al.. documented moderate and severe depression among adolescents attending secondary schools in Southeast Nigeria.
Although there are studies on obesity and psychosocial disorders in adolescents, there is paucity of studies on the above topic in Africa as a whole and Nigeria in particular. This study therefore aimed to determine the prevalence, pattern, and psychosocial correlates of psychosocial disorders among obese adolescents in Enugu metropolis.
| Materials and Methods|| |
The study was conducted in Enugu metropolis, which is made up of three local government areas (LGAs), namely, Enugu East, Enugu North, and Enugu South LGAs. There are a total of 120 registered secondary schools (75 private schools and 45 public schools) in the three LGAs that constitute the Enugu metropolis. Enugu East has 46 secondary schools comprising 33 private and 13 public schools with a total population of 9334 (5276 in private schools and 4058 in public schools). Enugu North has 30 secondary schools comprising 16 private and 14 public schools with a total population of 6348 (1560 in private schools and 4788 in public schools), whereas Enugu South has 44 secondary schools comprising 26 private and 18 public schools with a total population of 10851 (5649 in private schools and 5202 in public schools).
The study population consisted of secondary school adolescents aged 10–19 years in Enugu metropolis. The subjects for this study were apparently healthy adolescents with BMI equal to or greater than the age-gender-specific 95th percentile (obese adolescents) from these schools, whereas the controls were apparently healthy sex and age-matched classmates of the subjects with BMI within 5th–84th percentile.
Participants were included if they were apparently healthy obese secondary school adolescents and their non-obese controls aged 10–19 years in Enugu, after written informed consent was provided by parents/guardians and an assent form filled by all participants.
Excluded were obese adolescents who had any known chronic illness or were on drugs associated with obesity (e.g. steroids, antipsychotic drugs, and sodium valproate).
Ethical approval and consent
Ethical clearance was sought and obtained from the Health Research and Ethics Committee of the University of Nigeria Teaching Hospital, whereas a formal permission in writing was obtained from the Post Primary School Management Board, Ministry of Education Enugu State. Thumb-printed and/or signed informed consent was obtained from parents/guardians after explaining the study to them. The child’s assent was also obtained.
Sample size and sampling technique
This was estimated using the formula for sample size calculation for a difference in proportions (equal sized groups).
where n = number of subjects required in each group, p1 and p2 = proportions in the obese adolescents as p1 and p2 in the normal-weight adolescents (32% and 7.4%, respectively), and cp.power = a constant defined by the values of the P-value set at 0.05 and power at 95% with a constant of 13.
Confidence interval (CI) was set at 95% (to increase the chances of detecting a difference between the groups if one exists). The final number for each group was 62 participants.
10% attrition = 10/100 × 62 = 6.2.
n = 62 + 6.2 = 68.2, which is approximately 70 in each arm (i.e. obese and control).
The minimum total sample size therefore = 140.
Selection of schools
A stratified and multistage sampling was used to select the schools from the three LGAs that make up Enugu metropolis. A list of all secondary schools (private and public) in Enugu East, Enugu North, and Enugu South was obtained from the Enugu State Ministry of Education. All the schools were grouped into private and public schools. There are 33 private and 13 public schools in Enugu East LGA in a ratio of 2.5:1, whereas in Enugu North LGA, there are 16 private and 14 public schools in the ratio of 1.1:1. Enugu South LGA has 26 private and 18 public secondary schools in the ratio of 1.4:1. The number as well as the ratio of secondary schools selected in these study areas was based on the above ratio. Selection was done by simple random sampling (balloting) without replacement. Five private and two public schools were selected in Enugu East LGA, two private and two public schools in Enugu North LGA, and three private and two public schools in Enugu South LGA. A total of 16 secondary schools were selected. There were a total of 26,533 students in the schools in the three LGAs.
Selection of subjects and control
On the first day of visit to the individual schools, a formal introduction of the researcher was made to the school authority, and information on the study, its objectives, and letter of authorization from the Enugu State Post Primary School Board were presented to them. The required number of subjects from each school was determined using the Neyman allocation formula for stratified sampling, viz:
The allotted sample size was divided proportionately between the junior and senior sections of each selected school with the total number of student in each section constituting the sample frame. In each section, the participants were selected by simple random sampling using a statistical table of random numbers until the required number is obtained. The selected students were screened for obesity by measuring their height and weight, and calculating their BMIs, which was plotted on the Centers for Disease Control and Prevention BMI percentile chart, and all obese subjects who met the predetermined criteria were given a written consent form to take home to their parents/guardians. The obese adolescents whose parents/guardians gave their consent were included in the study. A systematic sampling scheme was applied in the selection of equal number of age- and sex-matched apparently healthy normal BMI (5th–84th percentile) controls from their respective class registers who met the criteria for each stratum. A consent form was subsequently given to them to take home to their parents/guardians. The first student was selected by simple random sampling, and every other fifth student was selected until the required number was achieved.
Measurement of anthropometric parameters
This was done with the help of four research assistants who were resident doctors in the Department of Pediatrics and were conversant with anthropometric measurement. They willingly agreed to assist in the study. They were recruited and trained by the researcher on filling of the questionnaire. Demonstrations were equally done on outcome variables such as weight and height. Body weight was measured to the nearest 0.1 kg using a digital scale. The scale was set at zero point before each use, measurement was done twice, and the average reading was taken to ensure accuracy. Each student was measured wearing light clothing, with their shoes removed. Standing height was taken to the nearest 0.1 cm, as the maximum distance to the uppermost position on the head from the heels, with the individual standing barefoot, using locally constructed, well-calibrated meter rule with a length of 200 cm. The rule was taped to the wall with an adhesive tape to maintain stability. The student was asked to stand with his/her back against the board. The back, scapulae, and buttocks were in contact with the vertical board if possible, or whichever part of the body touched the board first. The weight of the student was evenly distributed on both feet. He/She was asked to place the legs together, bringing the ankles or knees together, whichever came together first (often they will come together simultaneously). If the child had knock knees, the feet were separated so that the medial borders of the knees were in contact, but not overlapping. The child was instructed to stand erect (stand up straight and look straight ahead). The child’s position was verified from both the front and the left side of the body. Next, the child’s head was positioned in the Frankfort horizontal plane. In this position, an imaginary line can be drawn from the bottom of the eye socket (orbital margin) to the external opening of the ear (external auditory canal).
BMI was calculated as weight in kilograms divided by height squared in meters. This was plotted for each subject on the percentile chart.
This form was designed by the researchers. Data on the form included age/date of birth (which was confirmed by sighting their birth certificates), sex, parents’ occupation/education, and residential address.
The socioeconomic class of the families of both the subjects and the controls was determined using the model by Oyedeji. This model makes use of the occupation and educational qualification of the parents for scoring. The criteria used in the classification were graded 1 to 5, with class 1 being the highest social class and class 5, the lowest. Each parent was scored separately by finding the average score of the two criteria (education and occupation) to the nearest whole number. The mean score for both parents to the nearest whole number was the social class assigned to the child. This was graded from 1 to 5 with class 1 representing the highest social class and class 5 representing the lowest social class. This method of sub-classification of Oyedeji’s classification has been used by various researchers.,,,,
If any of the parents is dead, the social class assigned to the student was determined by that of the living parent or guardian only. For the purpose of this study, classes 1 and 2 of the Oyedeji classification represented upper social class, class 3 represented the middle class, and classes 4 and 5 represented the lower social class.
The psychosocial status of the adolescents with obesity and controls was assessed using a self-administered youth version of the Pediatric Symptom Checklist (YPSC). This tool has been used to assess the prevalence of psychosocial dysfunction in the Nigerian adolescents and youth. The Pediatric Symptom Checklist is a psychosocial screening questionnaire designed to recognize emotional, cognitive, and behavioral dysfunction for prompt initiation of appropriate intervention. It consists of three subscales; the attention subscale, the internalizing subscale, and the externalizing subscale. These subscales describe the patterns of psychosocial dysfunction. A cumulative score of 30 or more on the YPSC is indicative of psychosocial dysfunction.
Administration of the study tools
The study tool was administered by the researcher to the participants in a quiet room already mapped out for this purpose by the school authorities. This was done during their break periods. Prior to the administration of the study tools, the trusts of the students were gained and instructions on the filling of the questionnaire were given to them. These included that it was not an examination, only options that best describe how they felt should be chosen, their answers should be independent of their neighbor’s, and in the instance of any clarification, they should approach the researcher or his/her assistants. The study tools were self-administered with the whole process of administration taking an average of 15 min. At the successful completion of the data collection, the researcher thanked both the students and the school authorities for their assistance and cooperation. The questionnaires were subsequently locked up in a secure location and the electronic version of the data stored in the personal computer of the researcher and secured with a password to ensure confidentiality.
The data obtained were recorded and analyzed using the Statistical Package for Social Sciences version 20. Mean and standard deviation were used to summarize quantitative variables such as age, whereas proportion and percentage were used to summarize categorical variables such as sex and social class. Student’s t-test was used to test for the significance between the mean ages of the subjects and controls. Comparison of the categorical variables of the groups was performed using the chi-square tests. A P-value less than 0.05 was considered statistically significant.
| Results|| |
Over a period of 14 weeks (September 2016–January 2017), a total of 4364 adolescents aged 10–19 years were studied and 96 students were obese (BMI percentile ≥ 95th), giving a prevalence of 2.2%. Of these, eight declined from the study without any definite reason, consent to participate in the study was not given by parents of five students, and seven had inconsistent answers in the administered questionnaire and were subsequently excluded. The remaining 74 obese students and 74 apparently healthy normal-weight classmates who were recruited as control, matched for age and sex, were screened for psychosocial disorders.
[Table 1] shows the sociodemographic characteristics of the respondents. A total of 97 (65.5%) respondents were aged 10–14 years, out of which 43 (58.1%) were obese and 54 (73.0%) were normal-weight adolescents. The subjects were made up of 42 (56.8%) males and 32 (43.2%) females giving a male:female ratio of 1.3:1. The control was similarly distributed. Also 49 (66.2%) obese and 47(63.5%) non-obese subjects belonged to the upper social class. There was no statistically significant difference between the obese and non-obese subjects for age (χ2 = 3.62, P = 0.057), sex (χ2 = 0.11, P = 0.741), and social class (χ2 = 0.74, P = 0.690).
Using the YPSC, 13(17.6%) obese students and nine (12.2%) controls had psychosocial disorder [Table 2]. There was a statistically significant association between BMI and psychosocial disorder using the YPSC (P = 0.02, odds ratio = 2.02; 95% CI = 0.85–4.80). The obese adolescents were two times more likely to develop psychosocial disorder than the control.
|Table 2: Prevalence of psychosocial disorders in obese and non-obese adolescents using the YPSC|
Click here to view
[Table 3] shows the pattern of psychosocial disorders using the YPSC. Out of 13 obese adolescents who had psychosocial disorders, 11 (84.6%) were positive on the attention problem subscale, and 10 (76.9%) and 11 (84.6%) on the internalizing and externalizing problem subscales, respectively. Also among the non-obese adolescents who had psychosocial disorders, seven (77.8%), six (66.7%), and nine (100%) were positive on the attention, internalizing, and externalizing problem subscales.
The associations between the sociodemographic characteristics and psychosocial disorder in the obese and non-obese adolescents are shown in [Table 4]. Out of the 43 subjects aged 10–14 years, eight (18.6%) had YPSC score ≥30 and five (16.1%) subjects aged ≥15 had scores in the same range; the difference was however not statistically significant (χ2 = 0.08, P = 0.782).
|Table 4: Associations between sociodemographic characteristics and psychosocial disorders in the obese and non-obese using the YPSC|
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Psychosocial disorders using the YPSC was more in females than those in males (28.1% vs 9.5%). The difference was statistically significant (χ2 = 4.34, P = 0.04).
As regards social class, five (10.2%) out of the 49 subjects in the upper class scored in the psychosocial range. There was no statistically significant difference in the prevalence of psychosocial disorder among the subjects with regard to social class (χ2 = 5.73, P = 0.06).
Although among the non-obese adolescents, psychosocial disorder was more in the age group 10–14 (13.0%), among females (17.6%) and those in the middle social class (16.7%), there was however no statistically significant association between age (χ2 = 0.120, P = 0.729), sex (χ2 = 1.771, P = 0.183), social class (χ2 = 453, P = 0.797), and psychosocial disorder using the YPSC.
| Discussion|| |
In this study, 17.6% of obese adolescents reported psychosocial problems compared to 12.2% of the non-obese adolescents (controls) using the YPSC. The difference in the psychosocial disorders in the two groups was statistically significant (P = 0.02). This difference may be due to the stress associated with having a chronic disorder such as obesity, which is one of the most common chronic disorders among adolescents worldwide. Stress associated with marginalization, peer acceptance, and identity formation is common in adolescence. Obesity stigma, teasing, and bullying, which are pervasive, have been reported to mediate psychosocial disorders in obese adolescents.,,
The 17.6% prevalence was however lower than 60.2% reported by Uleanya et al. in adolescent obese students in Enugu. The higher prevalence rate documented by Uleanya et al. compared to that by the present study may be related to the type and sensitivity of the assessment measures. Uleanya et al. used different tools (Rosenberg Self-Esteem Scale, Internalized Stigma of Mental Illness Scale and Revised Children’s Manifest Anxiety Scale) to assess disorders of the individual psychosocial variables. The YPSC is only a screening tool and not diagnostic, and therefore does not classify children into specific disorders.
Using the YPSC in this study, 84.6% of the obese adolescents who had psychosocial disorders had attention problems, whereas 76.9% and 84.6% had internalizing problems (depression, anxiety) and externalizing problems (conduct disorders, oppositional defiant disorders), respectively. The prevalence of 76.9% and 84.6% for internalizing and externalizing problems, respectively, from this study was higher than that of 53.1% and 38.5% for internalizing and externalizing problems, respectively, observed by Pervanidou et al. in Greece. The difference in prevalence however is possibly due to categories of obese adolescents used by the two studies. Whereas this study assessed obese adolescents attending secondary schools, Pervanidou et al. studied only children and adolescents who were already attending the obesity clinic and having both medical and psychological interventions for their condition.
Psychosocial disorder among the obese using the YPSC in this study was commoner among those aged 10–14 years (18.6%) than those aged ≥15 years (16.1%) although the result is not statistically significant. The reason for this is not clear but may be explained by findings of Gunawardana et al. who noted that a lack of suitable clothing/as a result of unavailability of children’s clothing in large sizes and bullying affected their physical and psychosocial quality of life. This is in contrast with the findings of Uleanya et al. who noted psychosocial disorders among obese adolescents to be more among those who were ≥15 years. This is expected because adolescents become more aware of their body image as they grow older.
Psychosocial disorders were found to be commoner among the females (28.1%) compared to the males (9.5%) with the difference being statistically significant (P = 0.04). This may be due to the fact that females are more concerned about their physical appearances, especially body image, than their male counterparts owing to sociocultural influences such as feminine identity, which is typically characterized by eating smaller portions and preferring healthier options to maintain appearance, as well as a greater emphasis on “thinness” as a cultural ideal in girls. It has been documented that obese girls are less likely to get married compared to their non-obese counterparts; hence, the thought of relationships and marriage could be a bigger source of emotional instability. Lawrence et al. observed that males tend to detach themselves from emotions of situations and are more emotionally inhibited than females. Siziya and Mazaba and Uleanya et al. also noted psychosocial disorders to be more prevalent among females than their male counterparts.
In the current study, psychological disorder was found to be commonest among the middle socioeconomic class (35.7%) followed by the lower class (27.3%), with the upper class being the least common (10.2%). The difference however was not statistically significant (P = 0.06). Although some authors have shown that upper socioeconomic status increases the risk for psychosocial disorder in the obese, others however reported that lower socioeconomic class is implicated more in the development of psychosocial disorder.
Psychosocial disorders being commoner among the lower and middle socioeconomic classes than the upper socioeconomic class in this study may be as a result of children in the upper socioeconomic class having more access to both medical and psychological treatment.
| Conclusion|| |
The prevalence of psychosocial disorders was higher in the obese adolescents compared to the controls. There was no significant difference in the pattern of the disorders, but the females were more significantly affected than the males. Our findings support the need for periodic assessment of mental health of obese adolescents in Enugu.
- There is paucity of data on psychosocial disorders among obese adolescents in Nigeria, so majority of literature was from the western countries.
- Some schools despite being presented with written evidence of permission from the Ministry of Education outrightly refused the researcher access to their students.
Financial support and sponsorship
Conflict of interests
There are no conflicts of interest.
| References|| |
Olds T, Maher C, Zumin S, Péneau S, Lioret S, Castetbon K, et al
. Evidence that the prevalence of childhood overweight is plateauing: Data from nine countries. Int J Pediatr Obes 2011;6:342-60.
Lobstein T, Baur L, Uauy R; IASO International Obesity TaskForce. Obesity in children and young people: A crisis in public health. Obes Rev 2004;5:4-104.
Toriola AL, Moselakgomo VK, Shaw BS, Goon DT Overweight, obesity and underweight in a rural black South African children. S Afr J Clin Nutri 2012;25:57-61.
Peltzer K, Pengpid S Overweight and obesity and factors among school-aged adolescents in Ghana and Uganda. Int J Environ Res Public Health 2011;8:3859-70.
Hill GO Understanding and addressing the epidemic of obesity: An energy balance perspective. Endocr Rev 2006;27:750-6.
Taru M, Hesham E, David T, Jason R The prevalence of underweight, overweight, obesity and associated risk factors among school-going adolescents in seven African countries. BMC Public Health 2014;14:887.
Ani PN, Uvere PO, Ene-Obong HN Prevalence of overweight, obesity and thinness among adolescents in rural and urban areas of Enugu State, Nigeria. International Journal of Basic and Applied Sciences 2014;3:1-7.
Patterson RE, Frank LL, Kristal AR, White E A comprehensive examination of health conditions associated with obesity in older adults. Am J Prev Med 2004;27:385-90.
World Health Organization. Obesity and overweight, key facts. Available at: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight
(AccessedAugust 13, 2021).
Vaidya V Psychosocial aspects of obesity. Adv Psychosom Med 2006;27:73-85.
Lamertz CM, Jacobi C, Yassouridis A, Arnold K, Henkel AW Are obese adolescents and young adults at higher risk for mental disorders? A community survey. Obes Res 2002;10:1152-60.
Eremis S, Cetin N, Tamar M, Bukusoglu N, Akdeniz F, Goksen D Is obesity a risk factor for psychopathology among adolescents. Paediatr Int 2004;46:296-301.
Knopf D, Park J, Mulye T The mental health of adolescents: A national profile 2008. Available at: http://nahic.ucsf.edu/downloads/MentalHealthBrief
(Accessed August 31, 2015).
Halfon N, Larson K, Slusser W Associations between obesity and comorbid mental health, developmental, and physical health conditions in a nationally representative sample of US children aged 10 to 17. Acad Pediatr 2013;13:6-13.
Rankin J, Matthews L, Cobley S, Han A, Sanders R, Wiltshire HD, et al
. Psychological consequences of childhood obesity: Psychiatric comorbidity and prevention. Adolesc Health Med Ther 2016;7:125-46.
Centers for Disease Control and Prevention. Childhood obesity causes and consequences. Available at: www.cdc.gov/obesity/childhood/causes.html
(Accessed August 11, 2021).
Uleanya N, Aniwada E, Okeke C, Nwoha S, Obionu C Pattern and predictors of psychosocial disorders among overweight and obese children in Enugu, Southeast Nigeria. South African Journal of Child Health 2018;12:3-9.
Vila G, Zipper E, Dabbas M, Bertrand C, Robert JJ, Ricour C, et al
. Mental disorders in obese children and adolescents. Psychosom Med 2004;66:387-94.
Blanco M, Solano S, Alcántara AI, Parks M, Román FJ, Sepúlveda AR Psychological well-being and weight-related teasing in childhood obesity: A case-control study. Eat Weight Disord 2020;25:751-9.
World Health Organization. Adolescent health, key facts. Available at: https://www.who.int/southeastasia/health-topics/adolescent-health
(Accessed August 14, 2021).
Cassey B, Jones R, Todd A The adolescent brain. Ann N Y Acad Sci 2008;1124:111-26.
Chinawa JM, Manyike PC, Obu HA, Aronu AE, Odutola O, Chinawa AT Depression among adolescents attending secondary schools in South East Nigeria. Ann Afr Med 2015;14:46-51.
Whitley E, Ball J Statistics review 4: Sample size calculations. Crit Care 2002;6:335-41.
Oyedeji GA Socio-economic and cultural background of hospitalised children in Ilesh. Nigerian Journal of Paediatrics 1995;12:111-7.
Eziyi J, Amusa Y, Nwawolo C, Ezeanolue B Wax impaction in Nigerian school children. East and Central African Journal of Surgery 2011;16:40-5.
Okoroma C, Ekure E, Lesi F, Okunowo W, Tijani B, Okeiyi J Prevalence, profile and predictors of malnutrition in children with congenital heart defects: A case-control observational study. Arch Dis Child 2011;96:354-60.
Jarrett O, Fatunde O, Osinusi K, Lagunju I Prehospital management of febrile seizures in children seen at the University College Ibadan, Nigeria. Ann Ib Postgrad Med 2012;10:6-10.
Igwe WC, Ojinnaka NC Mental health of adolescents who abuse psychoactive substances in Enugu, Nigeria—A cross-sectional study. Ital J Pediatr 2010;36:53.
Weinberger NA, Kersting A, Riedel-Heller SG, Luck-Sikorski C The relationship between weight status and depressive symptoms in a population sample with obesity: The mediating role of appearance evaluation. Obes Facts2018;11:514-23.
van Vuuren CL, Wachter GG, Veenstra R, Rijnhart JJM, van der Wal MF, Chinapaw MJM, et al
. Associations between overweight and mental health problems among adolescents, and the mediating role of victimization. BMC Public Health 2019;19:612.
Pervanidou P, Bastaki D, Chouliaras G, Papanikolaou K, Kanaka-Gantenbein C, Chrousos G Internalizing and externalizing problems in obese children and adolescents: Associations with daily salivary cortisol concentrations. Hormones (Athens) 2015;14:623-31.
Gunawardana S, Gunasinghe CB, Harshani MS, Seneviratne SN Physical and psychosocial quality of life in children with overweight and obesity from Sri Lanka. BMC Public Health 2021;21:86.
Shah B, Tombeau Cost K, Fuller A, Birken CS, Anderson LN Sex and gender differences in childhood obesity: Contributing to the research agenda. BMJ Nutr Prev Health 2020;3: 387-90.
Gortmaker S, Must A, Perrin J, Sobol A, Dietz W Social and economic consequences of overweight in adolescents and young adulthood. N Eng J Med 1993;329:1008-12.
Lawrence J, Ashford K, Dent P Gender differences in coping strategies of undergraduate students and their impact on self-esteem and attainment. Active Learning in Higher Education 2006;7:273-81.
Siziya S, Mazaba ML Prevalence and correlates for psychosocial distress among in-school adolescents in Zambia. Front Public Health 2015;3:180.
Markowitz SM, Friedman M, Arent S Understanding the relation between obesity and depression: Causal mechanisms and implication for treatment. Clinical Psychology Science and Practice 2008;15:1-20.
McCarty CA, Kosterman R, Mason WA, McCauley E, Hawkins JD, Herrenkohl TI, et al
. Longitudinal associations among depression, obesity and alcohol use disorders in young adulthood. Gen Hosp Psychiatry 2009;31:442-50.
[Table 1], [Table 2], [Table 3], [Table 4]