Body fatness or anthropometry for assessment of unhealthy weight status? Comparison between methods in South African children and adolescents

Craig, Eva; Reilly, John J.; Bland, Ruth

doi:10.1017/s1368980012004338

Cited by 17 publications

(36 citation statements)

References 40 publications

(91 reference statements)

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“…On the other hand, being underweight (also associated with negative health outcomes) [12, 19, 20] remains a significant problem in LMICs [21, 22] despite increased efforts to address it [23]. In 2009, the WHO estimated 155 million or one in 10 school-age (5 – 17 years old) children worldwide to be either overweight or obese.…”

Section: Introductionmentioning

confidence: 99%

The prevalence of underweight, overweight, obesity and associated risk factors among school-going adolescents in seven African countries

et al. 2014

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BackgroundThe burden caused by the coexistence of obesity and underweight in Low and Middle Income Countries is a challenge to public health. While prevalence of underweight among youth has been well documented in these countries, overweight, obesity and their associated risk factors are not well understood unlike in high income countries.MethodsCross-sectional data from the Global School-based Student Health Survey (GSHS) conducted in seven African countries were used for this study. The survey used a clustered design to obtain a representative sample (n = 23496) from randomly selected schools. 53.6% of the sample was male, and participants ranged in age from 11-17 years old. Body Mass Index (BMI) was calculated using age and sex adjusted self-reported heights and weights. Classification of weight status was based on the 2007 World Health Organization growth charts (BMI-for-age and sex). Multivariable Logistic Regression reporting Odds Ratios was used to assess potential risk factors on BMI, adjusting for age, sex, and country. Statistical analyses were performed with Stata with an alpha of 0.05 and reporting 95% confidence intervals.ResultsUnadjusted rates of being underweight varied from 12.6% (Egypt) to 31.9% (Djibouti), while being overweight ranged from 8.7% (Ghana) to 31.4% (Egypt). Obesity rates ranged from 0.6% (Benin) to 9.3% (Egypt). Females had a higher overweight prevalence for every age group in five of the countries, exceptions being Egypt and Malawi. Overall, being overweight was more prevalent among younger (≤12) adolescents and decreased with age. Males had a higher prevalence of being underweight than females for every country. There was a tendency for the prevalence of being underweight to increase starting in the early teens and decrease between ages 15 and 16. Most of the potential risk factors captured by the GSHS were not significantly associated with weight status.ConclusionsThe prevalence of both overweight and underweight was relatively high, demonstrating the existence of the double burden of malnutrition among adolescents in developing countries. Several factors were not associated with weight status suggesting the need to explore other potential risk factors for overweight and underweight, including genetic factors and socioeconomic status.

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Section: Introductionmentioning

confidence: 99%

The prevalence of underweight, overweight, obesity and associated risk factors among school-going adolescents in seven African countries

et al. 2014

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“…The majority of studies were conducted within eight of South Africa's nine provinces (i.e. the country's principal administrative districts); specifically: Eastern Cape (n = 3), 72,75,76 Free State (n = 1), 71 Gauteng (n = 25), 22,26,31,32,[35][36][37]40,46,[48][49][50][51][52][56][57][58][61][62][63]69,[77][78][79][80] KwaZulu -Natal (n = 3), 23,59,60 Limpopo (n = 4), 28,29,81,83 Mpumalanga (n = 8), 44,45,[66][67][68]73,82,86 North West (n = 9) 25,27,30,42,47,64,…”

Section: Resultsmentioning

confidence: 99%

“…34,38,39,70 Eleven pairs of studies were based on the same study sample and are therefore presented together. 28,29,38,39,44,45,[49][50][51][52][53][54][57][58][59][60]66,67,[75][76][77][78] The publication year ranged from 1997 to 2018. Sixteen studies used quantitative cross-sectional or longitudinal data (various ages between 10 and 19 years) from the Birth-to-Twenty (BTT) cohort, an urban longitudinal birth cohort in Soweto, Gauteng (n = 3273).…”

Section: Resultsmentioning

confidence: 99%

A review of adolescent nutrition in South Africa: transforming adolescent lives through nutrition initiative

Wrottesley

Pedro

Fall

et al. 2019

South African Journal of Clinical Nutrition

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In South Africa, urbanisation is associated with substantial burdens of adolescent overweight and obesity, making teenagers vulnerable to longer-term non-communicable diseases. In addition, as potential future parents, the nutritional status of adolescents is increasingly recognised as a key driver of health and well-being in the next generation. This review reported on the available literature examining nutritional status and dietary intakes and practices, as well as their determinants, in South African adolescents. Study design and methods: Medline (Pubmed), Web of Science and EMBASE were searched for relevant articles published between 1994 and May 2018. Applicable search terms and phrases were identified in study titles and/or abstracts and fulltext articles were reviewed according to inclusion/exclusion criteria. Data were extracted according to specific review objectives. Results: A total of 67 relevant studies were identified. Only one study used a biochemical marker to describe adolescent nutritional status (vitamin D status; 25(OH)D). Overweight and obesity prevalence increased in South African adolescents over the reference period, with national increases of 6% in boys and 7% in girls between 2002 and 2008. Girls and urbandwellers were particularly vulnerable to excess adiposity. Dietary intakes demonstrated a transition towards energy-dense, processed foods high in sugar and fat, but low in essential micronutrients. Food choices were driven by the adoption of obesogenic behaviours in the teenage years, including irregular breakfast consumption and fewer family meals, increased snacking and low levels of physical activity. Conclusion: South African adolescents-particularly girls-are increasingly burdened by obesity as a result of urbanisationassociated shifts in dietary intake and eating behaviours. However, the implications for micronutrient status and long-term nutritional health are not known. Additionally, more data on the clustering of diet, activity and sedentary behaviours in adolescent boys and girls is needed, as well as on behaviour patterns to facilitate healthy growth and reduced adiposity.

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“…Most studies among children and adolescents in Africa apply BMI-based criteria to estimate overweight and obesity [9]. Nonetheless, at the continental level, the diagnostic accuracy of the published BMI references to detect excess body fat among children is largely unknown; only few studies have compared the BMI criteria against a criterion measure of body fat [10,11]. The present study aims to evaluate the diagnostic accuracies of the three international BMI the CDC, IOTF, and WHO based criteria in defining obesity using deuterium dilution as a criterion method in a sample of Ghanaian primary school children.…”

Section: Introductionmentioning

confidence: 99%

Diagnostic Accuracy of Body Mass Index in Defining Childhood Obesity: Analysis of Cross-Sectional Data from Ghanaian Children

Adom

Kengne

Villiers

et al. 2019

IJERPH

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Background: Screening methods for childhood obesity are based largely on the published body mass index (BMI) criteria. Nonetheless, their accuracy in African children is largely unknown. The diagnostic accuracies of the World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC), and the International Obesity Taskforce (IOTF) BMI-based criteria in defining obesity using deuterium dilution as a criterion method in a sample of Ghanaian children are presented. Methods: Data on anthropometric indices and percent body fat were collected from 183 children aged 8–11 years. The sensitivity, specificity, and predictive values were calculated. The overall performance of the BMI criteria was evaluated using the receiver operating characteristics area under the curve (AUC). Results: Overall sensitivity of WHO, CDC, and IOTF were 59.4% (40.6–76.3), 53.1% (34.7–70.9), and 46.9% (29.1–65.3) respectively. The overall specificity was high, ranging from 98.7% by WHO to 100.0% by IOTF. The AUC were 0.936 (0.865–1.000), 0.924 (0.852–0.995), and 0.945 (0.879–1.000) by the WHO, CDC, and IOTF criteria respectively for the overall sample. Prevalence of obesity by the WHO, CDC, IOTF, and deuterium oxide-derived percent body fat were 11.5%, 10.4%, 8.2%, and 17.5% respectively, with significant positive correlations between the BMI z-scores and percent body fat. Conclusions: The BMI-based criteria were largely specific but with moderate sensitivity in detecting excess body fat in Ghanaian children. To improve diagnostic accuracy, direct measurement of body fat and other health risk factors should be considered in addition to BMI.

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Body fatness or anthropometry for assessment of unhealthy weight status? Comparison between methods in South African children and adolescents

Cited by 17 publications

References 40 publications

The prevalence of underweight, overweight, obesity and associated risk factors among school-going adolescents in seven African countries

The prevalence of underweight, overweight, obesity and associated risk factors among school-going adolescents in seven African countries

A review of adolescent nutrition in South Africa: transforming adolescent lives through nutrition initiative

Diagnostic Accuracy of Body Mass Index in Defining Childhood Obesity: Analysis of Cross-Sectional Data from Ghanaian Children

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