Nutritional status of Ugandan women living with HIV/AIDS : anthropometry and body composition assessment

Human immunodeficiency virus (HIV) that leads to acquired immune deficiency syndrome (AIDs) reduces immune function, resulting in opportunistic infections and later death. Use of antiretroviral therapy (ART) increases chances of survival, however, with some concerns regarding fat re-distribution (lipodystrophy) which may encompass subcutaneous fat loss (lipoatrophy) and/or fat accumulation (lipohypertrophy), in the same individual. This problem has been linked to Antiretroviral drugs (ARVs), majorly, in the class of protease inhibitors (PIs), in addition to older age and being female. An additional concern is that the problem exists together with the metabolic syndrome, even when nutritional status/ body composition, and lipodystrophy/metabolic syndrome are unclear in Uganda where the use of ARVs is on the increase. In line with the literature, the overall aim of the study was to assess physical characteristics of HIV-infected patients using a comprehensive anthropometric protocol and to predict body composition based on these measurements and other standardised techniques. The other aim was to establish the existence of lipodystrophy, the metabolic syndrome, andassociated risk factors. Thus, three studies were conducted on 211 (88 ART-naïve) HIV-infected, 15-49 year-old women, using a cross-sectional approach, together with a qualitative study of secondary information on patient HIV and medication status. In addition, face-to-face interviews were used to extract information concerning morphological experiences and life style. The study revealed that participants were on average 34.1±7.65 years old, had lived 4.63±4.78 years with HIV infection and had spent 2.8±1.9 years receiving ARVs. Only 8.1% of participants were receiving PIs and 26% of those receiving ART had ever changed drug regimen, 15.5% of whom changed drugs due to lipodystrophy. Study 1 hypothesised that the mean nutritional status and predicted percent body fat values of study participants was within acceptable ranges; different for participants receiving ARVs and the HIV-infected ART-naïve participants and that percent body fat estimated by anthropometric measures (BMI and skinfold thickness) and the BIA technique was not different from that predicted by the deuterium oxide dilution technique. Using the Body Mass Index (BMI), 7.1% of patients were underweight (<18.5 kg/m2) and 46.4% were overweight/obese (≥25.0 kg/m2). Based on waist circumference (WC), approximately 40% of the cohort was characterized as centrally obese. Moreover, the deuterium dilution technique showed that there was no between-group difference in the total body water (TBW), fat mass (FM) and fat-free mass (FFM). However, the technique was the only approach to predict a between-group difference in percent body fat (p = .045), but, with a very small effect (0.021). Older age (β = 0.430, se = 0.089, p = .000), time spent receiving ARVs (β = 0.972, se = 0.089, p = .006), time with the infection (β = 0.551, se = 0.089, p = .000) and receiving ARVs (β = 2.940, se = 1.441, p = .043) were independently associated with percent body fat. Older age was the greatest single predictor of body fat. Furthermore, BMI gave better information than weight alone could; in that, mean percentage body fat per unit BMI (N = 192) was significantly higher in patients receiving treatment (1.11±0.31) vs. the exposed group (0.99±0.38, p = .025). For the assessment of obesity, percent fat measures did not greatly alter the accuracy of BMI as a measure for classifying individuals into the broad categories of underweight, normal and overweight. Briefly, Study 1 revealed that there were more overweight/obese participants than in the general Ugandan population, the problem was associated with ART status and that BMI broader classification categories were maintained when compared with the gold standard technique. Study 2 hypothesized that the presence of lipodystrophy in participants receiving ARVs was not different from that of HIV-infected ART-naïve participants. Results showed that 112 (53.1%) patients had experienced at least one morphological alteration including lipohypertrophy (7.6%), lipoatrophy (10.9%), and mixed alterations (34.6%). The majority of these subjects (90%) were receiving ARVs; in fact, all patients receiving PIs reported lipodystrophy. Period spent receiving ARVs (t209 = 6.739, p = .000), being on ART (χ2 = 94.482, p = .000), receiving PIs (Fisher’s exact χ2 = 113.591, p = .000), recent T4 count (CD4 counts) (t207 = 3.694, p = .000), time with HIV (t125 = 1.915, p = .045), as well as older age (t209 = 2.013, p = .045) were independently associated with lipodystrophy. Receiving ARVs was the greatest predictor of lipodystrophy (p = .000). In other analysis, aside from skinfolds at the subscapular (p = .004), there were no differences with the rest of the skinfold sites and the circumferences between participants with lipodystrophy and those without the problem. Similarly, there was no difference in Waist: Hip ratio (WHR) (p = .186) and Waist: Height ratio (WHtR) (p = .257) among participants with lipodystrophy and those without the problem. Further examination showed that none of the 4.1% patients receiving stavudine (d4T) did experience lipoatrophy. However, 17.9% of patients receiving EFV, a non-nucleoside reverse transcriptase inhibitor (NNRTI) had lipoatrophy. Study 2 findings showed that presence of lipodystrophy in participants receiving ARVs was in fact far higher than that of HIV-infected ART-naïve participants. A final hypothesis was that the prevalence of the metabolic syndrome in participants receiving ARVs was not different from that of HIV-infected ART-naïve participants. Moreover, data showed that many patients (69.2%) lived with at least one feature of the metabolic syndrome based on International Diabetic Federation (IDF, 2006) definition. However, there was no single anthropometric predictor of components of the syndrome, thus, the best anthropometric predictor varied as the component varied. The metabolic syndrome was diagnosed in 15.2% of the subjects, lower than commonly reported in this population, and was similar between the medicated and the exposed groups (χ 21 = 0.018, p = .893). Moreover, the syndrome was associated with older age (p = .031) and percent body fat (p = .012). In addition, participants with the syndrome were heavier according to BMI (p = .000), larger at the waist (p = .000) and abdomen (p = .000), and were at central obesity risk even when hip circumference (p = .000) and height (p = .000) were accounted for. In spite of those associations, results showed that the period with disease (p = .13), CD4 counts (p = .836), receiving ART (p = .442) or PIs (p = .678) were not associated with the metabolic syndrome. While the prevalence of the syndrome was highest amongst the older, larger and fatter participants, WC was the best predictor of the metabolic syndrome (p = .001). Another novel finding was that participants with the metabolic syndrome had greater arm muscle circumference (AMC) (p = .000) and arm muscle area (AMA) (p = .000), but the former was most influential. Accordingly, the easiest and cheapest indicator to assess risk in this study sample was WC should routine laboratory services not be feasible. In addition, the final study illustrated that the prevalence of the metabolic syndrome in participants receiving ARVs was not different from that of HIV-infected ART-naïve participants.

Development of height-weight based equation for assessment of body composition in Sri Lankan children

Objective To develop a height and weight based equation to estimate total body water (TBW) in Sri Lankan children. Methods Cross sectional descriptive study done involving 5–15 year old healthy children. Height and weight were measured. TBW was assessed using isotope dilution method (D2O) and fat free mass (FFM) calculated. Multiple regression analysis was used to develop prediction equation and validated using PRESS statistical technique. Height, weight and sex code (male=1; female=0) were used as prediction variables. Results This study provides height and weight equation for the prediction of TBW in Sri Lankan children. To the best of our knowledge there are no published height weight prediction equations validated on South Asian populations. Conclusion Results of this study need to be affirmed by more studies on other closely related populations by using multicomponent body composition.

Use of Skin-Fold Thickness in Sri Lankan Children: Comparison of Several Prediction Equations

Objective There are many prediction equations available in the literature for the assessment of body composition from skinfold thickness (SFT). This study aims to cross validate some of those prediction equations to determine the suitability of their use on Sri Lankan children. Methods Height, weight and SFT of 5 different sites were measured. Total body water was assessed using the isotope dilution method (D2O). Percentage Fat mass (%FM) was estimated from SFT using prediction equations described by five authors in the literature. Results Five to 15 year old healthy, 282 Sri Lankan children were studied. The equation of Brook gave Ihe lowest bias but limits of agreement were high. Equations described by Deurenberg et al gave slightly higher bias but limits of agreement were narrowest and bias was not influence by extremes of body fat. Although prediction equations did not estimate %FM adequately, the association between %FM and SFT measures, were quite satisfactory. Conclusion We conclude that SFT can be used effectively in the assessment of body composition in children. However, for the assessment of body composition using SFT, either prediction equations should be derived to suit the local populations or existing equations should be cross-validated to determine the suitability before its application.

Segmental bioelectrical impedance in the assessment of body composition of Sri Lankan children

Abstract: Over the years bioelectrical impedance assay (BIA) has gained popularity in the assessment of body composition. However, equations for the prediction of whole body composition use whole body BIA. This study attempts to evaluate the usefulness of segmental BIA in the assessment of whole body composition. A cross sectional descriptive study was conducted at the Professorial Paediatric Unit of Lady Ridgeway Hospital, Colombo, involving 259 (M/F:144/115) 5 to 15 year old healthy children. The height, weight, total and segmental BIA were measured and impedance indices and specific resistivity for the whole body and segments were calculated. Segmental BIA indices showed a significant association with whole body composition measures assessed by total body water (TBW) using the isotope dilution method (D2O). Impedance index was better related to TBW and fat free mass (FFM), while specific resistivity was better related to the fat mass of the body. Regression equations with different combinations of variables showed high predictability of whole body composition. Results of this study showed that segmental BIA can be used as an alternative approach to predict the whole body composition in Sri Lankan children.

Validity of BMI as a measure of obesity in Australian white Caucasian and Australian Sri Lankan children

Background: Body mass index (BMI) is used to diagnose obesity. However, its ability to predict the percentage fat mass (%FM) reliably is doubtful. Therefore validity of BMI as a diagnostic tool of obesity is questioned. Aim: This study is focused on determining the ability of BMI-based cut-off values in diagnosing obesity among Australian children of white Caucasian and Sri Lankan origin. Subjects and methods: Height and weight was measured and BMI (W/H2) calculated. Total body water was determined by deuterium dilution technique and fat free mass and hence fat mass derived using age- and gender-specific constants. A %FM of 30% for girls and 20% for boys was considered as the criterion cut-off level for obesity. BMI-based obesity cut-offs described by the International Obesity Task Force (IOTF), CDC/NCHS centile charts and BMI-Z were validated against the criterion method. Results: There were 96 white Caucasian and 42 Sri Lankan children. Of the white Caucasians, 19 (36%) girls and 29 (66%) boys, and of the Sri Lankans 7 (46%) girls and 16 (63%) boys, were obese based on %FM. The FM and BMI were closely associated in both Caucasians (r = 0.81, P<0.001) and Sri Lankans (r = 0.92, P<0.001). Percentage FM and BMI also had a lower but significant association. Obesity cut-off values recommended by IOTF failed to detect a single case of obesity in either group. However, NCHS and BMI-Z cut-offs detected cases of obesity with low sensitivity. Conclusions: BMI is a poor indicator of percentage fat and the commonly used cut-off values were not sensitive enough to detect cases of childhood obesity in this study. In order to improve the diagnosis of obesity, either BMI cut-off values should be revised to increase the sensitivity or the possibility of using other indirect methods of estimating the %FM should be explored.

Validity of currently used cutoff values of body mass index as a measure of obesity in Sri Lankan children

The aim of the study was to determine the reliability of body mass index based (BMI) cutoff values in diagnosing obesity among Sri Lankan children. Height, weight, waist circumference (WC) and hip circumference (HC) in 282 children were measured. Total body water was determined by deuterium dilution and fat mass (FM) derived using age and gender specific constants. A percentage FM of 30% for girls and 25% for boys were considered as cutoff levels for obesity. Two hundred and eighty two children (M/F: 158/124) were studied and 99 (80%) girls and 72 (45.5%) boys were obese based on % body fat. Eight (6.4%) girls and nine (5.7%) boys were obese based on International Obesity Task Force (IOTF) cutoff values. Percentage FM and WC centile charts were able to diagnose a significant proportion of children as true obese children. The FM and BMI were closely associated in both girls (r = 0.82, p < 0.001) and boys (r = 0.87, p < 0.001). Percentage FM and BMI had a very low but significant association; girls (r = 0.32, p < 0.001) and boys (r = 0.68, p < 0.001). FM had a significant association with WC and HC. BMI based cutoff values had a specificity of 100% but a very low sensitivity, varying between 8% and 23.6%. BMI is a poor indicator of the percentage fat and the commonly used cutoff values were not sensitive to detect cases of childhood obesity in Sri Lankan children.

Assessment of body composition in Sri Lankan children: Validation of a bioelectrical impedance prediction equation

Objective: To develop bioelectrical impedance analysis (BIA) equations to predict total body water (TBW) and fat-free mass (FFM) of Sri Lankan children. Subjects/Methods: Data were collected from 5- to 15-year-old healthy children. They were randomly assigned to validation (M/F: 105/83) and cross-validation (M/F: 53/41) groups. Height, weight and BIA were measured. TBW was assessed using isotope dilution method (D2 O). Multiple regression analysis was used to develop preliminary equations and cross-validated on an independent group. Final prediction equation was constructed combining the two groups and validated by PRESS (prediction of sum of squares) statistics. Impedance index (height2/impedance; cm2/Ω), weight and sex code (male = 1; female = 0) were used as variables. Results: Independent variables of the final prediction equation for TBW were able to predict 86.3% of variance with root means-squared error (RMSE) of 2.1l. PRESS statistics was 2.1l with press residuals of 1.2l. Independent variables were able to predict 86.9% of variance of FFM with RMSE of 2.7 kg. PRESS statistics was 2.8 kg with press residuals of 1.4 kg. Bland Altman technique showed that the majority of the residuals were within mean bias±1.96 s.d. Conclusions: Results of this study provide BIA equation for the prediction of TBW and FFM in Sri Lankan children. To the best of our knowledge there are no published BIA prediction equations validated on South Asian populations. Results of this study need to be affirmed by more studies on other closely related populations by using multi-component body composition assessment.