ArticleHeliyon2020
Comparative assessment of anthropometric and bioimpedence methods for determining adiposity.
Article in Heliyon, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Bioelectrical impedance analysis predicts prehypertension and hypertension: A hospital-based cross-sectional study.Journal of family medicine and primary care · 2024Article
- Body composition is related to cognitive function among young adults in Ghana.BMC psychology · 2024Article
- Sedentary Behaviors and Health Outcomes among Young Adults: A Systematic Review of Longitudinal Studies.Healthcare (Basel, Switzerland) · 2022Review
- Haematological Indices and Antioxidant Enzyme Activity in Ghanaian Stroke Patients.BioMed research international · 2022Article
- Comparative Assessment of the Utility of Anthropometric and Bioelectrical Impedance Indices as Potential Predictors of Hypertension within a Ghanaian Adult Population: A Cross-Sectional Study.International journal of hypertension · 2022Article
- Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundObesity is a risk factor for different chronic conditions. Over the years, obesity has become a pandemic and it is therefore important that effective diagnostic tools are developed. Obesity is a measure of adiposity and it has become increasingly evident that anthropometric measures such as body mass index (BMI) used to estimate adiposity are inadequate. This study therefore examined the ability of different anthropometric measurements to diagnose obesity within a cross-section of Ghanaian women.
methodsWe obtained anthropometric measurements and used that to generate derived measures of adiposity such as body adiposity index (BAI) and conicity index. Furthermore we also measured adiposity using a bioimpedance analyser. Associations between these measurements and percentage body fat (%BF) were drawn in order to determine the suitability of the various measures to predict obesity. The prevalence of obesity was determined using both %BF and BMI.
resultsBMI, Waist and hip circumference and visceral fat (VF) were positively correlated with % BF whereas skeletal muscle mass was negatively correlated. Prevalence of obesity was 16% and 31.6% using BMI and %BF respectively. Receiver operating characteristic (ROC) analysis showed that these differences in prevalence was due to BMI based misclassification of persons who have obesity as overweight. Similar, shortfalls were observed for the other anthropometric measurements using ROC.
conclusionsNo single measure investigated could adequately predict obesity as an accumulation of fat using current established cut-off points within our study population. Large scale epidemiological studies are therefore needed to define appropriate population based cut-off points if anthropometric measurements are to be employed in diagnosing obesity within a particular population.
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