Markers of adiposity in HIV/AIDS patients: Agreement between waist circumference, waist-to-hip ratio, waist-to-height ratio and body mass index

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Abstract

Background

Waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) are all independent predictors of cardio-metabolic risk and therefore important in HIV/AIDS patients on antiretroviral therapy at risk of increased visceral adiposity. This study aimed to assess the extent of agreement between these parameters and the body mass index (BMI), as anthropometric parameters and in classifying cardio-metabolic risk in HIV/AIDS patients.

Methods

A secondary analysis of data from a cross-sectional study involving 200 HIV/AIDS patients was done. Anthropometric parameters were measured from participants using standard guidelines and central obesity defined according to recommended criteria. Increased cardio-metabolic risk was defined according to the standard cut-off values for all four parameters. Data were analyzed using STATA version 14.1.

Results

The prevalence of WC-defined central obesity, WHR-defined central obesity and WHtR > 0.50 were 33.5%, 44.5% and 36.5%, respectively. The prevalence of BMI-defined overweight and obesity was 40.5%. After adjusting for gender and HAART status, there was a significant linear association and correlation between WC and BMI (regression equation: WC (cm) = 37.184 + 1.756 BMI (Kg/m ²) + 0.825 Male + 1.002 HAART, (p < 0.001, r = 0.65)), and between WHtR and BMI (regression equation: WHtR = 0.223 + 0.011 BMI (Kg/m ²)– 0.0153 Male + 0.003 HAART, (p < 0.001, r = 0.65)), but not between WHR and BMI (p = 0.097, r = 0.13). There was no agreement between the WC, WHtR and BMI, and minimal agreement between the WHR and BMI, in identifying patients with an increased cardio-metabolic risk.

Conclusion

Despite the observed linear association and correlation between these anthropometric parameters, the routine use of WC, WHR and WHtR as better predictors of cardio-metabolic risk should be encouraged in these patients, due to their minimal agreement with BMI in identifying HIV/AIDS patients with increased cardio-metabolic risk. HAART status does not appear to significantly affect the association between these anthropometric parameters.

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Most cited references 19

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Waist circumference and not body mass index explains obesity-related health risk.

Ian Janssen, Peter Katzmarzyk, Robert Ross (2004)

The addition of waist circumference (WC) to body mass index (BMI; in kg/m(2)) predicts a greater variance in health risk than does BMI alone; however, whether the reverse is true is not known. We evaluated whether BMI adds to the predictive power of WC in assessing obesity-related comorbidity. Subjects were 14 924 adult participants in the third National Health and Nutrition Examination Survey, grouped into categories of BMI and WC in accordance with the National Institutes of Health cutoffs. Odds ratios for hypertension, dyslipidemia, and the metabolic syndrome were compared for overweight and class I obese BMI categories and the normal-weight category before and after adjustment for WC. BMI and WC were also included in the same regression model as continuous variables for prediction of the metabolic disorders. With few exceptions, overweight and obese subjects were more likely to have hypertension, dyslipidemia, and the metabolic syndrome than were normal-weight subjects. After adjustment for WC category (normal or high), the odds of comorbidity, although attenuated, remained higher in overweight and obese subjects than in normal-weight subjects. However, after adjustment for WC as a continuous variable, the likelihood of hypertension, dyslipidemia, and the metabolic syndrome was similar in all groups. When WC and BMI were used as continuous variables in the same regression model, WC alone was a significant predictor of comorbidity. WC, and not BMI, explains obesity-related health risk. Thus, for a given WC value, overweight and obese persons and normal-weight persons have comparable health risks. However, when WC is dichotomized as normal or high, BMI remains a significant predictor of health risk.

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Predicting cardiometabolic risk: waist-to-height ratio or BMI. A meta-analysis

Savvas Savva, Demetris Lamnisos, Anthony Kafatos (2013)

Background and objectives The identification of increased cardiometabolic risk among asymptomatic individuals remains a huge challenge. The aim of this meta-analysis was to compare the association of body mass index (BMI), which is an index of general obesity, and waist-to-height ratio (WHtR), an index of abdominal obesity, with cardiometabolic risk in cross-sectional and prospective studies. Methods PubMed and Embase databases were searched for cross-sectional or prospective studies that evaluated the association of both BMI and WHtR with several cardiometabolic outcomes. The strength of relative risk (RR) with 95% confidence interval (CI) was calculated using the optimal cutoffs of BMI and WHtR in cross-sectional studies, while any available cutoff was used in prospective studies. The pooled estimate of the ratio of RRs (rRR [=RRBMI/RRWHtR]) with 95% CIs was used to compare the association of WHtR and BMI with cardiometabolic risk. Meta-regression was used to identify possible sources of heterogeneity between the studies. Results Twenty-four cross-sectional studies and ten prospective studies with a total number of 512,809 participants were identified as suitable for the purpose of this meta-analysis. WHtR was found to have a stronger association than BMI with diabetes mellitus (rRR: 0.71, 95% CI: 0.59–0.84) and metabolic syndrome (rRR: 0.92, 95% CI: 0.89–0.96) in cross-sectional studies. Also in prospective studies, WHtR appears to be superior to BMI in detecting several outcomes, including incident cardiovascular disease, cardiovascular disease mortality, and all-cause mortality. The usefulness of WHtR appears to be better in Asian than in non-Asian populations. BMI was not superior to WHtR in any of the outcomes that were evaluated. However, the results of the utilized approach should be interpreted cautiously because of a substantial heterogeneity between the results of the studies. Meta-regression analysis was performed to explain this heterogeneity, but none of the evaluated factors, ie, sex, origin (Asians, non-Asians), and optimal BMI or WHtR cutoffs were significantly related with rRR. Conclusion The results of this meta-analysis support the use of WHtR in identifying adults at increased cardiometabolic risk. However, further evidence is warranted because of a substantial heterogeneity between the studies.

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Risk of lipodystrophy in HIV-1-infected patients treated with protease inhibitors: a prospective cohort study.

Richard A. Phillips, J Blanch, J Mallolas … (2001)

Risk factors for lipodystrophy in patients infected with HIV-1 treated with highly active antiretroviral therapy (HAART) containing HIV-1 protease inhibitors are poorly understood. We aimed to identify the risk factors for lipodystrophy in antiretroviral-naive HIV-1-infected adults on HAART. Moderate or severe body-fat changes were clinically assessed and categorised as subcutaneous lipoatrophy, central obesity, or both, in all consecutive antiretroviral-naïve HIV-1-infected adults who began HAART with two nucleoside reverse transcriptase inhibitors plus at least one protease inhibitor from October, 1996, to September, 1999. A person-years analysis was used to calculate the incidence of types of lipodystrophy, and Cox proportional hazards models were used to describe the univariate and multivariate factors associated with progression to any lipodystrophy. After a median follow-up of 18 months, 85 (17%) of the 494 patients developed some type of lipodystrophy. The incidences of any lipodystrophy, lipodystrophy with subcutaneous lipoatrophy, and lipodystrophy with central obesity were 11.7 (95% CI 9.2-14.2), 9.2 (7.0-11.4), and 7.7 (5.7-9.7) per 100 patient-years. An increased risk for any lipodystrophy was found among women as compared with men (relative hazard 1.87 [1.07-3.28]), heterosexuals (2.86 [1.50-5.48]), and homosexuals (2.17 [1.07-4.42]) as compared with intravenous drug users, with increasing age (1.33 per 10 years older [1.08-1.62]), and with the duration of exposure to antiretroviral therapy (1.57 per 6 months extra [1.30-1.88]) but not with any individual antiretroviral agent. The factors associated with an increased risk for lipodystrophy with subcutaneous lipoatrophy or lipodystrophy with central obesity were very similar to those associated with any lipodystrophy. The duration of indinavir use may represent an additional contribution for the development of lipodystrophy with central obesity (1.26 per 6 months extra [0.99-1.60]); p=0.064). Risk factors associated with development of any lipodystrophy, lipodystrophy with subcutaneous lipoatrophy, and tipodystrophy with central obesity in patients infected with HIV-1 who were receiving HAART containing protease inhibitors are multifactorial and overlapping, and cannot be exclusively ascribed to the duration of exposure to an particular antiretroviral agent.

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Author and article information

Contributors

Christian Akem Dimala:

ORCID: http://orcid.org/0000-0002-0064-0126

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Writing – original draftRole: Writing – review & editing

Roland Cheofor Ngu: Role: ValidationRole: Writing – original draftRole: Writing – review & editing

Benjamin Momo Kadia: Role: InvestigationRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing

Frank-Leonel Tianyi: Role: ValidationRole: Writing – original draftRole: Writing – review & editing

Simeon Pierre Choukem: Role: ConceptualizationRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing

Amanda Willig: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 22 March 2018

Publication date Collection: 2018

Volume: 13

Issue: 3

Electronic Location Identifier: e0194653

Affiliations

[1 ] Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom

[2 ] Orthopaedics Department, Southend University Hospital, Essex, United Kingdom

[3 ] Health and Human Development (2HD) Research Network, Douala, Cameroon

[4 ] Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom

[5 ] Medical Doctors (M.D) Research Group, Douala, Cameroon

[6 ] Foumbot District Hospital, Foumbot, Cameroon

[7 ] Grace Community Health and Development Association, Kumba, Cameroon

[8 ] Mayo-Darle District Hospital, Mayo-Darle, Cameroon

[9 ] Diabetes and Endocrinology Unit, Department of Internal Medicine, Douala General Hospital, Douala, Cameroon

[10 ] Department of Internal Medicine and Paediatrics, Faculty of Health Sciences, University of Buea, Buea, Cameroon

University of Alabama at Birmingham, UNITED STATES

Author notes

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: Christian.Akem.Dimala1@ 123456alumni.lshtm.ac.uk

Author information

Christian Akem Dimala http://orcid.org/0000-0002-0064-0126

Article

Publisher ID: PONE-D-17-18643

DOI: 10.1371/journal.pone.0194653

PMC ID: 5864036

PubMed ID: 29566089

SO-VID: 9ad0826a-2ed4-4d18-8066-6381959cf6b9

License:

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 15 May 2017

Date accepted : 29 January 2018

Page count

Figures: 9, Tables: 5, Pages: 18

Funding

The authors received no specific funding for this work.

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Data Availability All relevant data are within the paper and its Supporting Information files.

Markers of adiposity in HIV/AIDS patients: Agreement between waist circumference, waist-to-hip ratio, waist-to-height ratio and body mass index

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Abstract

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Conclusion

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Most cited references 19

Waist circumference and not body mass index explains obesity-related health risk.

Predicting cardiometabolic risk: waist-to-height ratio or BMI. A meta-analysis

Risk of lipodystrophy in HIV-1-infected patients treated with protease inhibitors: a prospective cohort study.

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