Abstract
Aim
To describe the distribution of childhood obesity and their related comorbidities in <12-year-old children assessed at a South African tertiary hospital from 2012 to 2022.
Methods
In this retrospective electronic chart review, data extracted comprised socio-demographic and lifestyle histories, physical examination and biochemical analyses. World Health Organisation child growth reference defined obesity as z-score ≥2 standard deviations (SD) for 5-19-year-olds, and z-score ≥3 SD for <5-year-olds. Systolic blood pressure and/or diastolic blood pressure ≥95th percentile and 90–94th percentile for age, gender and height, defined hypertension and prehypertension, respectively. Type 2 diabetes and prediabetes diagnoses were based on oral glucose tolerance tests or random blood glucose levels. Dyslipidaemia was deemed present with any abnormality of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides.
Results
Among 430 participants, 52.1 % (n = 224) male, 27.9 % (n = 120) ≤5-years-old and 64.7 % black African, unhealthy lifestyle behaviours were prevalent: 42.3 % spent <30 min/day on physical activity, 43.5 % spent >2 h/day on screen time and 47.9 % consumed soft drinks daily. Family history of obesity (41.9 %), diabetes (40.5 %) and hypertension (40.0 %) was common. Among participants, hypertension (46.1 %) and prehypertension (12.8 %) were high. Type 2 diabetes was low at 1.6 % but prediabetes was 3.3 %. Any dyslipidaemia was prevalent at 30.2 %.
Conclusions
The high burden of cardiometabolic comorbidities in children with obesity warrants concerted interventions at young ages to prevent worsening of comorbidities and the reversal of prehypertension and prediabetes. Unhealthy dietary habits, low activity levels and sedentary behaviours in children need to be urgently targeted to reduce obesity and its comorbidities.
Keywords: Childhood obesity, Hypertension, Type 2 diabetes, Dyslipidaemia, Lifestyle
Graphical abstract
1. Introduction
The late 20th century witnessed the emergence of childhood obesity, which has now spread to all corners of the globe including Sub-Saharan Africa. On the African continent, South Africa has amongst the highest prevalence of childhood overweight and obesity and this is predicted to increase in the future [1,2]. However, the condition is often unrecognised by parents and frequently not diagnosis by clinicians [3], despite the potential for severe health consequences. As a result, overweight and obesity has become a major and serious, yet neglected, public health problem that threatens to overwhelm both developed and developing regions [4,5].
Overweight and obesity in children is a multisystem disease with potentially devastating consequences that affect both physiological and psychosocial well-being [6,7]. The adverse outcomes may present during childhood and continue into adolescence and adulthood [1,8]. With the rise of obesity levels in childhood, chronic conditions that were once considered diseases of middle age are now prevalent in children [3]. The onset of these chronic conditions in childhood implies greater life years lost than if the onset was in adulthood [3].
Obesity in childhood and adolescence, as in adults, is associated with higher risk for the development of insulin resistance, type 2 diabetes mellitus, and numerous cardiovascular abnormalities. Although the end points for cardiovascular risks such as ischaemic heart disease and stroke are not necessarily evident in childhood or adolescence, most of the major risk factors manifest during this period. These include high systolic and diastolic blood pressures (BPs), dyslipidaemia and endothelial dysfunction, among other abnormalities detected [7,8]. Childhood obesity also increases the risk for developing respiratory, gastrointestinal, endocrine and skeletal problems. These include asthma or an exacerbation of existing asthma, low-grade systemic inflammation, obstructive sleep apnoea, early onset of puberty, foot and other skeletal abnormalities, and non-alcoholic fatty liver disease [3,8,9].
Despite the increasing prevalence of childhood obesity in South Africa [8], there is a dearth of data on the comorbidities associated with childhood obesity in the country. This is of concern because of the greater likelihood that obesity in childhood will be carried into adulthood [3] as well as the serious long-term consequences associated with obesity. Therefore, the aim of this study was to describe the distribution of childhood obesity and their related comorbidities in children <12 years of age who were assessed at Inkosi Albert Luthuli Central Hospital (IALCH) in KwaZulu-Natal (KZN) from 2012 to 2022.
2. Methods
2.1. Study design and sample frame
This retrospective electronic chart review included all children <12 years of age who presented with childhood obesity at IALCH. IALCH is a tertiary referral hospital in Durban in the province of KZN and serves a population of approximately 11.5 million [10]. It is the only referral centre for paediatric patients with endocrine problems in the province. All children <12 years old presenting with obesity at IALCH from 2012 to 2022 were investigated and those with secondary causes of obesity were excluded from this analysis. The latter was determined on clinical examination with screening for signs of secondary causes of obesity, such as hypothyroidism, growth hormone deficiency, Down syndrome, etc. Secondary causes of obesity were excluded clinically where, if there had been no delay in linear growth, an endocrine cause was unlikely, and in the absence of dysmorphic features and developmental delays, a genetic cause was unlikely.
2.2. Data collection
All patient data are captured electronically at IALCH and were extracted from the electronic medical records by clinicians. Data extracted included socio-demographic variables relating to age, gender, birth weight, dietary history, physical activity and sedentary levels, and family medical history. Physical examination data captured included height and weight, BP, signs of acanthosis nigricans, signs of puberty, obesity-related comorbidities, etc. Anthropometry and BP measurements were taken by experienced nurses at the clinic visits. Paediatric endocrinologists conducted the in-depth physical examinations and referred patients for further investigations. Biochemical investigations extracted included blood glucose, glycated haemoglobin (HbA1c), insulin levels, lipid profiles, and thyroid and liver function tests, among other tests. X-ray findings captured included skeletal and respiratory abnormalities.
2.3. Definitions
Overweight and obesity: Obesity, corresponding to body mass index (BMI) ≥30 kg/m2, was defined using the World Health Organisation (WHO) child growth reference for 5-19-year-olds where z-score values for BMI-for-age were calculated using the WHO’s software http://www.who.int/growthref/en/. Obesity was defined as z-score ≥2 SD in 5–12-year-olds in this study [11]. For children <5 years of age, weight-for-length/height was determined and obesity defined as z-score ≥3 SD, according to the WHO criteria for children <5 years old [12,13].
Raised blood pressure: The definition of hypertension in children was based on BP percentile and defined as average systolic BP (SBP) and/or diastolic BP (DBP) that was ≥95th percentile for age, gender, and height [14,15]. Average SBP or DBP which was 90th percentile or more but less than 95th percentile in children was classified as high-normal BP or prehypertension. Average SBP and DBP less than 90th percentile for age, sex and height was considered normal BP in children.
Hyperglycaemia: Diabetes was diagnosed on fasting glucose ≥7.0 mmol/L, 2-h glucose post oral glucose tolerance test ≥11.1 mmol/L or random blood glucose ≥11.1 mmol/L [9]. Prediabetes comprised impaired glucose tolerance and impaired fasting glycaemia. Impaired glucose tolerance was defined as 2-h post glucose load plasma glucose between 7.8 mmol/L and 11.1 mmol/L. Impaired fasting glycaemia was identified on fasting plasma glucose levels between 6.1 mmol/l and 7.0 mmol/L with normal 2-h glucose levels (<7.8 mmol/L).
Dyslipidaemia: Lipid profile abnormalities included the following on fasting lipid screen: total cholesterol ≥5.2 mmol/L, raised low-density lipoprotein cholesterol (LDL-C) ≥3.4 mmol/L, high-density lipoprotein cholesterol (HDL-C) <1.0 mmol/L, and triglycerides ≥1.1 mmol/L for 0-9-year-olds and ≥1.5 mmol//L for 10-19-year-olds [16].
2.4. Statistical analyses
Data were analysed using STATA, version 16.0 (StataCorp., College Station, TX, USA). Continuous variables were described using means and standard deviations (SD) and categorical variables were presented as frequencies and percentages with 95 % confidence intervals (CI). Groups comparisons used analysis of variance for continuous variables and Pearson’s chi-squared or Fischer’s exact test (where applicable) for categorical variables. A p-value of less than 0.05 was deemed statistically significant.
2.5. Ethics approval
The study was conducted in accordance with the principles of the International Declaration of Helsinki, 2013. The study was approved by the Biomedical Research and Ethics Committee of the University of Kwazulu-Natal (BE206/17) and the South African Medical Research Council’s (SAMRC) Ethics Committee (protocol ID EC002-2/2017). The KZN Department of Health and the management of IALCH also approved the study.
3. Results
Among 430 participants with obesity in the study, 52.1 % were male, and 27.9 % were <5 years of age (Table 1). The mean (SD) age was 7.3 (3.6) years and similar in males (7.3 (3.7)) and females (7.3 (3.5)). Most participants were black (64.7 %) followed by Indian/Asian (27.9 %); notably, 85.8 % of <5-year-old participants with obesity were black. There was a high prevalence of family history of obesity (41.9 %), diabetes (40.5 %) and hypertension (40.0 %) among parents or grandparents.
Table 1.
Profile of obese participants.
| Number | Total: N (%) | 0–5 years: N (%) | 5–12 years: N (%) | p-value | |
|---|---|---|---|---|---|
| Number | 430 | 120 | 310 | ||
| Sociodemographic characteristics | |||||
| Sex | 430 | 0.910 | |||
| Male | 224 (52.1) | 62 (51.7) | 162 (52.3) | ||
| Female | 206 (47.9) | 58 (48.3) | 148 (47.7) | ||
| Birth weight (kg), mean (SD) | 382 | 3.2 (0.6) | 3.3 (0.5) | 3.1 (0.7) | 0.040 |
| Population group | 430 | <0.001 | |||
| Black | 278 (64.7) | 103 (85.8) | 175 (56.5) | ||
| Indian/Asian | 120 (27.9) | 12 (10.0) | 108 (34.8) | ||
| Mixed ancestrya | 22 (5.1) | 5 (4.2) | 17 (5.5) | ||
| White | 10 (2.3) | 0 (0.0) | 10 (3.2) | ||
| Lifestyle behaviours | |||||
| Physical activity duration | 219 | <0.001 | |||
| <30 min/day | 182 (42.3) | 25 (20.8) | 157 (50.6) | ||
| 30–60 min/day | 29 (6.7) | 16 (13.3) | 13 (4.2) | ||
| >60 min/day | 8 (1.9) | 3 (2.5) | 5 (1.6) | ||
| Screen time | 209 | 0.740 | |||
| <2 h/day | 22 (5.1) | 5 (4.2) | 17 (5.5) | ||
| >2 h/day | 187 (43.5) | 37 (30.8) | 150 (48.4) | ||
| Daily soft drink intake | 230 | 206 (47.9) | 39 (32.5) | 167 (53.9) | <0.001 |
| Family medical history (parents and grandparents) | |||||
| Obesity | 412 | 180 (41.9) | 51 (42.5) | 129 (41.6) | 0.910 |
| Diabetes | 430 | 174 (40.5) | 28 (23.3) | 146 (47.1) | <0.001 |
| Hypertension | 430 | 172 (40.0) | 37 (30.8) | 135 (43.5) | 0.016 |
| Heart attack | 430 | 39 (9.1) | 3 (2.5) | 36 (11.6) | 0.002 |
| Stroke | 430 | 22 (5.1) | 3 (2.5) | 19 (6.1) | 0.150 |
| Asthma | 430 | 19 (4.4) | 5 (4.2) | 14 (4.5) | 0.870 |
| Clinical features | |||||
| Acanthosis Nigricans | 342 | 302 (70.2) | 40 (33.3) | 262 (84.5) | <0.001 |
| Skeletal abnormalities | 430 | 43 (10.0) | 14 (11.7) | 29 (9.4) | 0.470 |
| Snoring/Stertor | 328 | 74 (17.2) | 19 (15.8) | 55 (17.7) | 0.340 |
| Asthma | 295 | 44 (10.2) | 12 (10.0) | 32 (10.3) | 0.650 |
| Obstructive Sleep Apnoea | 303 | 42 (9.8) | 7 (5.8) | 35 (11.3) | 0.051 |
| Adeno Tonsillar Hypertrophy | 298 | 50 (11.6) | 8 (6.7) | 42 (13.5) | 0.019 |
Mixed ancestry defined as being of Khoisan, white, black and Malay heritage.
The prevalence of unhealthy lifestyle behaviours was high; 42.3 % spent <30 min daily on physical activity and 43.5 % spent >2 h daily on screen time demonstrating high levels of sedentary behaviour (Table 1). Unhealthy dietary intake was reflected in that almost half (47.9 %) the participants reported daily intake of soft drinks. The most common comorbid clinical characteristics likely attributable to obesity were acanthosis nigricans (70.2 %), snoring/stertor (17.2 %), adeno-tonsillar hypertrophy (11.6 %), asthma (10.2 %), skeletal abnormalities (10.0 %) and obstructive sleep apnoea (9.8 %).
Among all participants, the percentiles for weight-for-age, BMI-for-age and weight-for-length/height were >99.0 % while the height-for-age percentile was 67.7 % (Table 2). At 46.1 % and 12.8 %, the hypertension and prehypertension burdens, respectively, were high. Type 2 diabetes prevalence was low at 1.6 % but prediabetes was 3.3 %. Any dyslipidaemia was prevalent at 30.2 %.
Table 2.
Anthropometry and cardiometabolic characteristics of obese participants.
| Number | Total | 0–5 years | 5–12 years | p-value | |
|---|---|---|---|---|---|
| Number | 430 | 120 | 310 | ||
| Anthropometry, mean (SD) | |||||
| Height (cm) | 430 | 124.9 (24.1) | 92.8 (13.9) | 137.3 (13.3) | <0.001 |
| Height-for-age percentile | 430 | 67.7 (30.5) | 75.8 (28.8) | 64.6 (30.6) | <0.001 |
| Height-for-age z-score | 430 | 1.0 (2.6) | 1.9 (4.4) | 0.6 (1.3) | <0.001 |
| Weight (kg) | 430 | 49.5 (22.3) | 24.2 (8.7) | 59.3 (17.8) | <0.001 |
| Weight-for-age percentile | 300 | 99.2 (4.9) | 99.1 (6.0) | 99.3 (4.0) | 0.700 |
| Weight-for-age z-score | 300 | 5.1 (3.8) | 6.3 (5.3) | 4.3 (1.9) | <0.001 |
| Body mass index (kg/m2) | 430 | 30.0 (6.7) | 27.5 (5.5) | 31.0 (6.9) | <0.001 |
| BMI-for-age percentile | 430 | 99.9 (0.3) | 99.9 (0.02) | 99.8 (0.4) | <0.001 |
| BMI-for-age z-score | 430 | 5.0 (2.6) | 6.7 (3.0) | 4.4 (2.1) | <0.001 |
| Weight-for-length/height percentile | 116 | 99.9 (0.03) | 99.9 (0.03) | 99.9 (.) | 0.910 |
| Weight-for-length/height z-score | 116 | 6.8 (3.1) | 6.8 (3.1) | 3.71 (.) | 0.330 |
| Blood pressure | |||||
| Systolic (mmHg) | 379 | 116.6 (15.1) | 110.1 (16.2) | 118.6 (14.2) | <0.001 |
| Diastolic (mmHg) | 379 | 66.6 (12.8) | 63.4 (15.1) | 67.6 (11.8) | 0.006 |
| Hypertension stage | 335 | <0.001 | |||
| Normal | 82 (19.1) | 11 (9.2) | 71 (22.9) | ||
| Pre-hypertension | 55 (12.8) | 10 (8.3) | 45 (14.5) | ||
| Stage 1 hypertension | 140 (32.6) | 31 (25.8) | 109 (35.2) | ||
| Stage 2 hypertension | 58 (13.5) | 30 (25.0) | 28 (9.0) | ||
| Glycaemia | |||||
| Fasting glucose (mmol/l) | 233 | 4.63 (0.83) | 4.65 (0.70) | 4.63 (0.85) | 0.880 |
| 2-h glucose (mmol/l) | 186 | 6.06 (2.35) | 6.85 (5.42) | 5.98 (1.75) | 0.130 |
| Random glucose (mmol/l) | 43 | 5.77 (2.62) | 4.96 (0.66) | 6.16 (3.10) | 0.160 |
| Glycated haemoglobin (%) | 210 | 5.80 (0.89) | 5.48 (0.53) | 5.85 (0.92) | 0.045 |
| Type 2 diabetes mellitus, n (%) | 265 | 7 (1.6) | 1 (0.8) | 6 (1.9) | >0.999 |
| Pre-diabetes, n (%) | 235 | 14 (3.3) | 1 (0.8) | 13 (4.2) | >0.999 |
| Fasting insulin (pmol/l) | 197 | 22.0 (17.9) | 13.3 (11.7) | 23.0 (18.2) | 0.022 |
| Homa IR | 92 | 5.0 (8.3) | 3.9 (3.2) | 5.1 (8.8) | 0.670 |
| Lipids (mmol/l) | |||||
| Total cholesterol | 266 | 4.0 (0.9) | 3.7 (0.7) | 4.1 (1.0) | 0.015 |
| High-density lipoprotein cholesterol | 253 | 1.2 (0.4) | 1.1 (0.3) | 1.2 (0.4) | 0.280 |
| Low-density lipoprotein cholesterol | 247 | 2.4 (1.0) | 2.2 (0.7) | 2.5 (1.1) | 0.130 |
| Triglycerides | 262 | 1.1 (0.6) | 1.1 (0.7) | 1.1 (0.6) | 0.590 |
| Dysglycaemia | 265 | 21 (4.9) | 2 (1.7) | 19 (6.1) | 0.750 |
| Hypertension | 335 | 198 (46.0) | 61 (50.8) | 137 (44.2) | 0.001 |
| Dyslipidaemia | 268 | 130 (30.2) | 16 (13.3) | 114 (36.8) | 0.600 |
Normal blood pressure (BP): <90th percentile; Prehypertension: systolic BP and/or diastolic BP from 90 to 94th percentile.
Stage 1 hypertension ≥95th percentile to < 95th percentile + 12 mmHg; Stage 2 hypertension ≥95th percentile + 12 mmHg [28].
4. Discussion
To our knowledge, this is the first study to describe the burden associated with childhood obesity in South Africa. This study highlights the high cardiometabolic burden associated with obesity in children even at an early age. Worryingly, over a quarter of included participants were <5 years old. Almost half the participants had hypertension while over one in 10 had prehypertension. Furthermore, dysglycaemia (diabetes and pre-diabetes) was diagnosed in 5 % of participants with obesity. These findings accorded with the unhealthy lifestyle behaviours reported in a large proportion of participants. Low physical activity levels with high rates of sedentary behaviour and regular intake of sugar sweetened beverages, all key risk factors for the development of obesity and cardiometabolic diseases, were highly prevalent.
That hypertension and prehypertension were the most prevalent comorbidity underscores the role of obesity in the development of these diseases even in childhood. The risk for hypertension is more than 2.5 times higher in children with obesity compared with normal weight children; this rises to almost 5-fold higher in children with BMI >40 kg/m2 [17]. Overweight is likely the most important factor associated with elevated BP in childhood responsible for >50 % of the risk for developing hypertension [15]. Children with obesity and hypertension have a greater risk of cardiovascular morbidity and mortality, which underscores the importance of preventing childhood obesity [17,18].
Although the prevalence of prediabetes was twice that of diabetes, it is likely that ∼10–15 % of children with prediabetes will progresses to diabetes per year, with higher rates in those with severe obesity [19]. Like hypertension, the high burden of dysglycaemia diagnosed in childhood in this study may be related to obesity. Severe obesity is the predominant risk factor for type 2 diabetes in the young [20]. Childhood obesity correlates closely with type 2 diabetes; there has been a 3-fold increase in the prevalence of diabetes in children over the last 30 years [19].
The high prevalence of risky lifestyle behaviours in this study underlines their importance in the development of obesity. Lifestyle changes in childhood with lower physical activity levels and higher sedentary behaviours such as television viewing, as well as the consumption of high-caloric sugar sweetened beverages promote the development of overweight/obesity in children [6,21]. The uptake of these lifestyle behaviours in young children may be guided by the behaviours of their parents or caregivers in the home environment [22]. This may be reflected in the high prevalence of obesity among parents or grandparents demonstrated in this study, and is supported by the association of maternal BMI and obesity with childhood obesity observed in systematic reviews [22,23]. Nevertheless, there are likely additional mechanisms for the development of childhood obesity; together with shared familial environmental characteristics, genetics may also be a contributing factor [24]. A child with at least one obese parent has a four-fold greater risk for obesity with evidence indicating that the greatest risk for childhood obesity is obesity in one or both parents [3,25].
4.1. Recommendations
The high burden of elevated BP, dysglycaemia and other related complications in these children with obesity who have a mean age of <8 years illustrates the importance of preventing obesity as well as screening for and managing the disease and its comorbidities. Interventions targeting individual behaviours with improvements in diets and physically active lifestyles are the mainstay of obesity care, as recommended by the Pediatric Obesity Clinical Practice Guidelines [26]. However, these need to be adapted to the given population considering the resources available and the cultural differences present [26]. For example, cultural perceptions related to feeding behaviours and appropriate child weight influence not only the development of childhood obesity [22] but also the awareness of the need for the child to reduce weight. This highlights the need for further research to develop tailored interventions targeting the local population.
Nevertheless, the development of obesity is complex with multifactorial influences such as genetics, environmental, cultural, and economic factors, etc. [22]. In the Report of the Commission on Ending Childhood Obesity, the World Health Organisation proposed that, in addition to targeting the behavioural determinants of obesity, the approach should be multi-faceted [27]. This would encompass addressing the political, socio-economic, and environmental contributors to childhood obesity. Stakeholder commitment and participation from governmental and non-governmental organisations and the healthcare and private sector, among others, would be crucial for success.
4.2. Study strengths and limitations
The strengths of this study are the large number of children with obesity included and the comprehensive assessment of the obesity-related comorbidities. The absence of a non-obese group prevented comparison of the associated risk factors and comorbidities between children with obesity and their counterparts. The recording of a single BP measurement is a limitation and may lead to incorrect estimates of BP levels. The cross-sectional study design precludes conclusions on causality. The large amount of missing data precluded thorough comparisons across sub-groups and likely affected the accuracy of the estimates. For example, data on self-reported screen time was available for 209 (48.6 %) participants only. Finally, the study was based on a non-random sample, which may affect the generalisability of the findings.
5. Conclusions
This study underscores the seriousness of childhood obesity by describing the high prevalence of obesity-related comorbidities in young children. Concerted interventions at young ages are warranted to prevent the worsening of cardiometabolic comorbidities and the reversal of prehypertension and prediabetes. Unhealthy dietary habits, low activity levels and sedentary behaviours in children must be urgently targeted to reduce obesity and its comorbidities. There is a need to 1) implement measures to curb the uptake, 2) regularly screen and monitor the development, and 3) facilitate the optimal management of childhood obesity. This study additionally highlights the importance of referring children with obesity for investigation and management of comorbidities. These children who presented to IALCH for comprehensive assessment of their obesity were followed up and reviewed regularly for improvements in their obesity status as well as for control of their comorbidities. Further research is needed to develop interventions for the treatment and prevention of childhood obesity targeting the local population. Importantly, programmes to increase awareness of the growing burden of childhood obesity and its associated consequences are urgently needed to galvanise stakeholder action.
Ethics approval and consent to participate
The study was approved by the Biomedical Research and Ethics Committee of the University of Kwazulu-Natal (BE206/17), the SAMRC Ethics Committee (protocol ID EC002-2/2017), the Kwazulu-Natal Department of Health and management of Inkosi Albert Luthuli Central Hospital.
Consent for publication
Not applicable.
Availability of data and material
All relevant data are presented in the main paper.
Authors' contributions
Manuscript conception: NP, YG, APK; acquisition of data: YG, JS, ST; data cleaning: YG, YB; data analysis and preparation of the tables: YB; drafting of the manuscript: NP; critical revision of the manuscript: YG, YB, APK, JS, ST; approval of the final version: all co-authors.
Declaration of artificial intelligence (AI) and AI-assisted technologies utilized in the writing process
None.
Funding
Data acquisition was partially funded by the SAMRC through baseline allocation to the Non-Communicable Diseases Research Unit.
Competing interests
None of the authors have any competing interests to declare.
Acknowledgements
None.
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Data Availability Statement
All relevant data are presented in the main paper.