The development of simple anthropometric measures to diagnose antiretroviral therapy-associated lipodystrophy in resource limited settings

  • Zulfa Abrahams1,

    Affiliated with

    • Joel A Dave1,

      Affiliated with

      • Gary Maartens2,

        Affiliated with

        • Maia Lesosky3 and

          Affiliated with

          • Naomi S Levitt1Email author

            Affiliated with

            AIDS Research and Therapy201411:26

            DOI: 10.1186/1742-6405-11-26

            Received: 14 May 2014

            Accepted: 21 July 2014

            Published: 4 August 2014

            Abstract

            Background

            Lipohypertrophy does not appear to be an adverse ART reaction while lipoatrophy is clearly associated with the use of stavudine (d4T) and zidovudine (AZT). In low and middle income countries d4T has only recently been phased out and AZT is still widely being used. Several case definitions have been developed to diagnose lipodystrophy, but none of them are generalizable to sub-Saharan Africa where black women have less visceral adipose tissue and more subcutaneous adipose tissue than white women. We aimed to develop a simple, objective measure to define lipoatrophy and lipohypertrophy by comparing patient report to anthropometric and dual-energy X-ray absorptiometry (DXA) -derived variables.

            Methods

            DXA and anthropometric measures were obtained in a cross sectional sample of black HIV-infected South African men (n = 116) and women (n = 434) on ART. Self-reported information on fat gain or fat loss was collected using a standard questionnaire. Receiver operating characteristic (ROC) curves were used to describe the performance of anthropometric and DXA-derived variables using patient reported lipoatrophy and lipohypertrophy as the reference standard.

            Results

            Lipoatrophy and lipohypertrophy were more common in women (25% and 33% respectively) than in men (10% and 13% respectively). There were insufficient numbers of men with DXA scans for meaningful analysis. The best predictors of lipoatrophy in women were the anthropometric variables tricep (AUC = 0.725) and thigh skinfold (AUC =0.720) thicknesses; and the DXA-derived variables percentage lower limb fat (AUC = 0.705) and percentage lower limb fat/height (AUC = 0.713). The best predictors of lipohypertrophy in women were the anthropometric variable waist/hip ratio (AUC = 0.645) and the DXA-derived variable percentage trunk fat/percentage limb fat (AUC = 0.647).

            Conclusions

            We were able to develop simple, anthropometric measures for defining lipoatrophy and lipohypertrophy, using a sample of black HIV-infected South African women with DXA scans. This is of particular relevance in resource limited settings, where health professionals need simple and inexpensive methods of diagnosing patients with lipoatrophy and lipohypertrophy.

            Keywords

            HIV Lipoatrophy Lipohypertrophy Lipodystrophy DXA Anthropometry Sub-Saharan africa Antiretroviral therapy

            Background

            Antiretroviral therapy (ART) has significantly reduced the morbidity and mortality of people infected with HIV [1], however, long-term use of ART has been associated with a number of metabolic complications such as dysglycaemia, insulin resistance, dyslipidaemia and lipodystrophy [2]. Lipodystrophy is characterized by either subcutaneous fat loss (lipoatrophy), which is most noticeable in the face, limbs, and buttocks, or fat accumulation (lipohypertrophy) seen in the abdomen, breast or posterior neck, or a combination of both [3, 4].

            Both subjective and objective methods have been used to diagnose lipodystrophy, resulting in a number of case definitions. The most widely used subjective methods of diagnosis are patient perception and report [5, 6], physician examination and report [7], and physician confirmation of patient report [811]. Objective measures include imaging by dual-energy X-ray absorptiometry (DXA) [6, 12, 13] and computed tomography (CT) scans [12, 14]. These imaging measures are expensive and not widely available in resource limited settings. Anthropometric and DXA-derived variables have also been developed, in an attempt to provide standard measures of defining lipodystrophy [1517]. Furthermore, criteria established to define lipodystrophy did not include data from any African country. These diagnostic criteria may not be generalizable to sub-Saharan Africans, as there are important ethnic differences in fat distribution, especially in black women who have less visceral adipose tissue and more subcutaneous adipose tissue than white women [1820].

            Lipohypertrophy does not appear to be an adverse ART reaction as participants on different ART drug regimens gained similar amounts of trunk fat over time [21]. Lipoatrophy, in contrast is clearly an adverse ART reaction. The use of stavudine (d4T) and zidovudine (AZT) is associated with subcutaneous fat loss and is partially reversed after changing to abacavir or tenofovir [21, 22]. Lipoatrophy remains common in low and middle income countries where d4T has only recently been phased out and AZT is still widely used [23]. However, even if lipohypertrophy is not associated with ART, lipodystrophy, and lipoatrophy in particular, is independently associated with an increased risk of vascular disease [24, 25]. Therefore recognising lipodystrophy is important to identify patients at risk for vascular disease so that screening can be targeted for other vascular risk factors, while recognising lipoatrophy is important so that d4T or AZT can be substituted.

            The aim of our study was to develop a simple, objective measure to define lipoatrophy and lipohypertrophy by comparing patient report to anthropometric and DXA-derived variables in a sample of black South Africans on ART.

            Results

            Participant characteristics are presented in Table 1. The study sample consisted of 550 participants on ART. Based on patient report, 121 (22%) had lipoatrophy and 157 (29%) had lipohypertrophy. Both lipoatrophy and lipohypertrophy were significantly more common in females than in males (p ≤ 0.001). Participants with lipoatrophy had spent a significantly longer period of time on ART (25 vs. 17 months) and a longer time on d4T (15.5 vs. 13 months).
            Table 1

            Characteristics of participants on ART

            Variable

            Lipoatrophy*

            P-value**

            Lipohypertrophy***

            P-value**

            With n = 121 Median [IQR]

            Without n = 429 Median [IQR]

            With n = 157 Median [IQR]

            Without n = 393 Median [IQR]

            Age

            34 [30–42]

            35 [30–41]

            0.256

            34 [29–41]

            35 [30–41]

            0.198

            Current CD4 count

            397 [249–539]

            315 [218–481]

            0.023

            389 [248–548]

            314 [220–481]

            0.015

            Time on ART (months)

            25 [14–32]

            17 [10–27]

            0.001

            20 [12–31]

            17 [11–28]

            0.080

            Time on Stavudine (months)

            15.5 [10–26]

            13 [8–19]

            0.004

            13 [8–21]

            13 [9–20]

            0.961

             

            n [%]

            n [%]

             

            n [%]

            n [%]

             

            Sex

                  

              Males

            12 [10.34]

            104 [89.66]

            0.001

            15 [12.93]

            101 [87.07]

            <0.001

              Females

            109 [25.12]

            325 [74.88]

             

            142 [32.72]

            292 [67.28]

             

            Highest standard passed

                  

              No schooling

            6 [18.8]

            26 [81.3]

            0.289

            9 [28.13]

            23 [71.88]

            0.272

              Primary school

            14 [15.4]

            77 [84.6]

             

            20 [21.98]

            71 [78.02]

             

              Secondary school

            96 [23.4]

            315 [76.6]

             

            121 [29.44]

            290 [70.56]

             

              Tertiary

            5 [31.3]

            11 [68.8]

             

            7 [43.75]

            9 [56.25]

             

            ART Regimen

                  

              First-line

            99 [22.30]

            345 [77.70]

            0.730

            130 [29.28]

            314 [70.72]

            0.608

              Second-line

            22 [20.75]

            84 [79.25]

             

            27 [25.47]

            79 [74.53]

             

            *based on patient report, those with moderate or severe fat loss in 2 or more regions.

            **Wilcoxon Rank-sum (Mann–Whitney) tests for continuous variables and chi-square tests for binary variables.

            ***based on patient report, those with moderate or severe fat gain in 2 or more regions.

            Anthropometric variables are shown separately for women and men (Tables 2 and 3 respectively). In women, all median skinfold measurements, with the exception of sub-scapular skinfold thickness, were significantly lower in participants with lipoatrophy compared with those without lipoatrophy. Measurements for waist circumference, waist/hip ratio and supra-iliac skinfold thickness were significantly higher in women with lipohypertrophy compared with those without lipohypertrophy. There were no statistically significant differences in anthropometric variables in males with and without lipoatrophy (Table 3). Males with lipohypertrophy had a significantly (P = 0.008) greater thigh circumference than those without (13.5 mm vs. 8.1 mm).
            Table 2

            Anthropometric measurements of female participants on ART

            Variable

            Lipoatrophy*

            P-value**

            Lipohypertrophy***

            P-value**

            With n = 106 Median [IQR]

            Without n = 312 Median [IQR]

            With n = 142 Median [IQR]

            Without n = 292 Median [IQR]

            Height (m)

            1.6 [1.5-1.6]

            1.6 [1.5-1.6]

            0.603

            1.6 [1.6-1.6]

            1.6 [1.5-1.6]

            0.112

            Weight (kg)

            65.4 [56.0-74.5]

            68.1 [58.9-80.9]

            0.019

            69.5 [60.7-80.4]

            67.1 [57.6-79.3]

            0.127

            BMI

            26.2 [23.8-29.3]

            27.1 [24.1-31.6]

            0.036

            27.4 [24.6-31.3]

            26.65 [23.9-31.2]

            0.187

            Sagittal Abdominal Diameter (cm)

            20.5 [19.0-23.0]

            20.0 [18.5-23.0]

            0.552

            21 [19–24]

            20 [18–23]

            0.004

            Circumferences

                  

              Waist (cm)

            86.3 [79.5-96.3]

            87.0 [78.5-97.0]

            0.704

            90.7 [80.3-98.5]

            86 [78.4-95]

            0.003

              Hip (cm)

            98.0 [92.0-104.0]

            102.0 [95.0-112.0]

            <0.001

            100 [95–110]

            101 [94–110]

            0.824

              Waist/hip ratio

            0.90 [0.83-0.94]

            0.85 [0.80-0.90]

            <0.001

            0.89 [0.83-0.93]

            0.84 [0.79-0.90]

            <0.001

              Mid-upper arm (cm)

            27.0 [25.0-29.0]

            29.0 [26.5-32.0]

            <0.001

            28 [26–32]

            28 [26–32]

            0.789

              Mid-thigh (cm)

            54.5 [51.0-59.0]

            57.0 [53.0-63.0]

            <0.001

            56 [52–61]

            57[ 52–63]

            0.589

            Skinfolds

                  

              Bicep (mm)

            6.0 [4.4-8.4]

            8.1 [5.7-11.7]

            <0.001

            7.1 [5.2-10.7]

            8 [5.4-11.45]

            0.189

              Tricep (mm)

            13.3 [9.5-17.4]

            18.4 [13.6-26.0]

            <0.001

            16.2 [12–22]

            18.3 [13–25.15]

            0.059

              Abdomen (mm)

            20.4 [11.9-30.0]

            24.4 [16.8-35.3]

            0.001

            24.1 [15.9-35.8]

            23.6 [15.0-31.2]

            0.210

              Thigh (mm)

            23.8 [15.4-32.8]

            34.7 [24.2-44.7]

            <0.001

            29.8 [20.5-42.5]

            32.0 [22.5-43.5]

            0.359

              Sub-Scapular (mm)

            16.9 [12.5-23.0]

            19.2 [12.2-28.8]

            0.058

            20 [14.8-29.4]

            18.5 [11.7-27.1]

            0.050

              Supra-iliac (mm)

            13.2 [7.7-18.7]

            15.1 [8.8-22.8]

            0.033

            16.6 [9.9-24.0]

            13.9 [8.2-21.7]

            0.022

              Calf (mm)

            10.8 [8.0-17.5]

            17.5 [12.2-24.2]

            <0.001

            15.6 [9.2-21.3]

            17.3 [11.4-23.6]

            0.061

            *based on patient report, those with moderate or severe fat loss in 2 or more regions.

            **Wilcoxon Rank-sum (Mann–Whitney) tests for continuous variables and chi-square tests for binary variables.

            ***based on patient report, those with moderate or severe fat gain in 2 or more regions.

            Table 3

            Anthropometric measurements of male participants on ART

            Variable

            Lipoatrophy*

            P-value**

            Lipohypertrophy***

            P-value**

            With n = 12 Median [IQR]

            Without n = 104 Median [IQR]

            With n = 15 Median [IQR]

            Without n = 101 Median [IQR]

            Height (m)

            1.7 [1.6-1.7]

            1.7 [1.6-1.7]

            0.942

            1.7 [1.6-1.8]

            1.7 [1.7-1.7]

            0.954

            Weight (kg)

            65.5 [59.7-68.6]

            63.5 [57.0-74.4]

            0.895

            67.4 [57.8-78.3]

            62.7 [57.3-73.4]

            0.408

            BMI

            23.3 [20.2-23.9]

            22.4 [20.6-25.2]

            0.772

            23.6 [21.1-25.5]

            22.3 [20.5-24.8]

            0.324

            Sagittal Abdominal Diameter (cm)

            17.0 [16.0-19.5]

            18.0 [17.0-20.0]

            0.384

            17.0 [16.0-22.0]

            18.0 [17.0-20.0]

            0.967

            Circumferences

                  

              Waist (cm)

            81.75 [77–84.9]

            80.4 [75.0-90.2]

            0.953

            83.8 [75.0-97.0]

            79.8 [75.8-89.5]

            0.338

              Hip (cm)

            90 [87–93.5]

            90.0 [85.0-97.0]

            0.768

            91.0 [85.0-97.0]

            90.0 [85.0-96.0]

            0.556

              Waist/hip ratio

            0.89 [0.85-0.95]

            0.91 [0.87-0.94]

            0.740

            0.93 [0.86-0.97]

            0.90 [0.86-0.94]

            0.325

              Mid-upper arm (cm)

            27.0 [24–28.5]

            26.0 [24.0-29.0]

            0.877

            27.0 [25.0-29.0]

            26.0 [24.0-29.0]

            0.817

              Mid-thigh (cm)

            50.5 [43.5-52.5]

            49.0 [46.0-54.0]

            0.401

            49.0 [46.0-56.0]

            49.0 [46.0-54.0]

            0.567

            Skinfolds

                  

              Bicep (mm)

            3.9 [3.4-4.2]

            3.5 [3.0-4.5]

            0.329

            4.1 [3.2-4.8]

            3.5 [3.0-4.3]

            0.180

              Tricep (mm)

            6.8 [5.6-8.2]

            6.4 [5.1-9.3]

            0.921

            8.4 [5.0-11.4]

            6.4 [5.1-8.7]

            0.444

              Abdomen (mm)

            13.5 [10.5-16.9]

            12.3 [8.5-30.1]

            1.00

            15.8 [9.3-28.2]

            12.3 [8.5 -18.1]

            0.309

              Thigh (mm)

            8.4 [7.2-14.8]

            8.5 [6.0-12.4]

            0.490

            13.5 [8.4-21.1]

            8.1 [6.0-11.3]

            0.008

              Sub-Scapular (mm)

            9.4 [6.5-13.2]

            8.3 [6.3-13.4]

            0.605

            10.5 [5.7-18.0]

            8.2 [6.5-11.1]

            0.770

              Supra-iliac (mm)

            6.3 [4.4-6.8]

            6.2 [4.9-9.4]

            0.196

            6.4 [4.7-12.1]

            6.2 [4.9-8.5]

            0.934

              Calf (mm)

            5.5 [4.8-9.0]

            5.8 [4.4-8.2]

            0.739

            6.8 [5.4-10.5]

            5.5 [4.4-7.7]

            0.094

            *based on patient report, those with moderate or severe fat loss in 2 or more regions.

            **Wilcoxon Rank-sum (Mann–Whitney) tests for continuous variables and chi-square tests for binary variables.

            ***based on patient report, those with moderate or severe fat gain in 2 or more regions.

            DXA-derived measures are shown for women only (Table 4), as there were insufficient numbers of men with DXA scans for meaningful analysis. Women with lipoatrophy as well as those with lipohypertrophy, had significantly higher percentage trunk fat/lower limb fat and percentage trunk fat/total limb fat and significantly lower percentage lower limb fat/BMI. Women with lipoatrophy had significantly less percentage limb fat while women with lipohypertrophy had significantly more percentage trunk fat.ROC curves for lipoatrophy and lipohypertrophy were generated and reported in female participants for anthropometric and DXA-derived variables with the highest AUC’s (Figure 1). For lipoatrophy, the two anthropometric variables with the highest AUC were tricep skinfold thickness (AUC = 0.725) and thigh skinfold thickness (AUC = 0.720) and for lipohypertrophy they were waist/hip ratio (AUC = 0.645) and waist circumference (AUC = 0.589). For lipoatrophy, the two DXA-derived variables with the highest AUC were the percentage of lower limb fat standardised to height (AUC = 0.713) and percentage lower limb fat (AUC = 0.705) and for lipohypertrophy they were percentage trunk fat/percentage total limb fat (AUC = 0.647) and percentage trunk fat/ percentage lower limb fat (AUC = 0.646). An illustration of anthropometric and DXA-derived variables in females is shown in Figure 2.
            Table 4

            DXA-derived measurements of female participants on ART

            Variable

            Lipoatrophy*

            P-value**

            Lipohypertrophy***

            P-value**

            With n = 29 Median [IQR]

            Without n = 143 Median [IQR]

            With n = 46 Median [IQR]

            Without n = 126 Median [IQR]

            DXA-derived measures

                  

            Arm fat (%)

            37.4 [30.8-44.1]

            38.3 [31.8-47.1]

            0.380

            39.8 [31.5-48.3]

            38.1 [31.7-45.1]

            0.319

            Lower limb fat (%)

            37.6 [31.5-40.6]

            43.4 [36.6-49.7]

            0.001

            39.2 [33.3-49.7]

            41.8 [36.3-48.8]

            0.761

            Trunk fat (%)

            34.7 [29.9-38.0]

            35.1 [27.9-43.1]

            0.719

            37.9 [30.7-45.3]

            34.4 [26.6-40.4]

            0.019

            Lower limb fat/ht (%)

            23.6 [19.7-25.4]

            27.4 [23.4-31.5]

            0.001

            25.4 [21.9-31.1]

            26.5 [23.2-29.7]

            0.631

            Total limb fat/ht (%)

            22.7 [20.8-27.0]

            25.4 [22.0-29.9]

            0.015

            25.4 [20.8-31.1]

            25.2 [21.8-29.1]

            0.825

            Lower limb fat/BMI (%)

            1.3 [1.2-1.7]

            1.6 [1.3-1.8]

            0.049

            1.4 [1.2-1.6]

            1.6 [1.3-1.8]

            0.019

            Total limb fat/BMI (%)

            1.3 [1.3-1.6]

            1.5 [1.3-1.6]

            0.193

            1.3 [1.2-1.5]

            1.5 [1.3-1.7]

            0.006

            Trunk fat/lower limb fat (%)

            0.94 [0.76-1.15]

            0.83 [0.66-0.96]

            0.017

            0.93 [0.80-1.10]

            0.81 [0.66-0.94]

            0.003

            Trunk fat/ total limb fat (%)

            1.0 [0.8-1.0]

            0.9 [0.7-1.0]

            0.045

            0.93 [0.85-1.03]

            0.85 [0.72-0.97]

            0.003

            *based on patient report, those with moderate or severe fat loss in 2 or more regions.

            **Wilcoxon Rank-sum (Mann–Whitney) tests for continuous variables and chi-square tests for binary variables.

            ***based on patient report, those with moderate or severe fat gain in 2 or more regions.

            http://static-content.springer.com/image/art%3A10.1186%2F1742-6405-11-26/MediaObjects/12981_2014_Article_316_Fig1_HTML.jpg
            Figure 1

            ROC curves for the 2 anthropometric and DXA-derived variables with the highest AUC for lipoatrophy and lipohypertrophy in female participants on ART.

            http://static-content.springer.com/image/art%3A10.1186%2F1742-6405-11-26/MediaObjects/12981_2014_Article_316_Fig2_HTML.jpg
            Figure 2

            Lipoatrophy variables for female participants on ART with ROC AUCs of ≥0.6 and their 95% confidence intervals in descending order of AUC.

            Optimum cut-points for lipoatrophy and lipohypertrophy variables, based on likelihood ratios, were selected. Table 5 shows the sensitivity, specificity, likelihood ratios and predictive values for the two anthropometric and DXA-derived variables with the highest AUC for lipoatrophy and lipohypertrophy at the optimum cut-points.
            Table 5

            Variables for prediction and classification used to identify lipoatrophy and lipohypertrophy cut-points

            Lipoatrophy variable cut-point

            N

            Sensitivity

            Specificity

            Likelihood ratio positive test

            Likelihood ratio negative test

            Positive predictive value

            Negative predictive value

            % correctly classified

            Tricep skinfold ≤14.5 mm

            418

            0.62

            0.71

            2.13

            0.53

            0.42

            0.85

            68.66*

            Thigh skinfold ≤28.0 mm

            417

            0.67

            0.65

            1.93

            0.51

            0.39

            0.85

            65.70*

            % Lower limb fat/height ≤ 24.7

            418

            0.19

            0.85

            1.28

            0.95

            0.30

            0.76

            68.42*

            Lower limb fat (%) ≤ 39.1

            418

            0.19

            0.84

            1.20

            0.96

            0.29

            0.75

            67.70*

            Lipohypertrophy variable cut-point

                    

            Waist/Hip Ratio ≥ 0.899

            434

            0.44

            0.75

            1.75

            0.75

            0.46

            0.73

            64.75**

            Waist Circumference ≥ 88.5 cm

            434

            0.57

            0.59

            1.40

            0.73

            0.41

            0.73

            58.53**

            Trunk fat/total limb fat (%) ≥0.8895

            172

            0.50

            0.70

            1.66

            0.72

            0.38

            0.79

            64.5**

            Trunk fat/leg fat (%) ≥ 0.8816

            172

            0.72

            0.61

            1.84

            0.46

            0.40

            0.86

            64.0**

            *percentage of those classified with and without lipoatrophy using the new cut-point compared to those defined by subject-report.

            **percentage of those classified with and without lipohypertrophy using the new cut-point compared to those defined by subject-report.

            Discussion

            We showed that simple anthropometric measures were at least as good as DXA-derived measures to diagnose lipoatrophy and lipohypertrophy in African women on ART. The best predictors of lipoatrophy in women were the anthropometric variables tricep and thigh skinfold thicknesses; and the DXA-derived variables percentage lower limb fat and percentage lower limb fat/height. The best predictors of lipohypertrophy in women were the anthropometric variable waist/hip ratio and the DXA-derived variable percentage trunk fat/percentage limb fat. Women with lipoatrophy had considerably smaller limb circumferences, limb skinfold thicknesses and lower percentages of limb fat than women without lipoatrophy, despite similar BMIs. Lipoatrophy and lipohypertrophy were both more common in women than in the small sample of men.

            Previous studies, conducted in high-income countries, developed objective measures for lipodystrophy, thus combining lipoatrophic and lipohypertrophic individuals [1517]. They proposed the use of fat mass ratio (FMR), defined as the ratio between the percentage of trunk fat mass and the percentage of lower-limb fat mass. We however sought to investigate lipoatrophy and lipohypertrophy as separate entities. Identification of lipoatrophy is important as it is an adverse antiretroviral drug reaction, which improves on switching antiretroviral drugs [21]. Although lipohypertrophy is thought to be a consequence of treating HIV infection rather than an adverse antiretroviral drug reaction [21], like lipoatrophy, it is associated with an increased risk of vascular disease [26] therefore it is worth identifying so that appropriate screening and prevention interventions can be implemented.

            Despite the subjective nature of assessing lipoatrophy and lipohypertrophy by using patient self-report, previous studies have shown a strong correlation between patient and physician reported lipodystrophy scores [2729]. In South Africa, as well as in many other African countries, nurses, rather than physicians, prescribe antiretroviral therapy and follow up patients. For these reasons we used patient self-report [5, 6] as the reference measure to define lipoatrophy and lipohypertrophy.

            Our study, like several others [11, 21], showed a significant association between lipoatrophy and time on ART, and time on d4T in particular. As South Africa has only recently phased out d4T, and AZT is still being used, it is not unexpected that a quarter of the women and a tenth of the men, had lipoatrophy. The prevalence of lipoatrophy found in this study is not easy to compare with other studies as studies from high-income countries focussed on men [12, 24], while most studies from Africa looked at the prevalence of lipodystrophy [3032] rather than studying the two entities of lipoatrophy and lipodystrophy separately. Our finding that tricep skinfold thickness was a predictor of lipoatrophy is supported by other studies. George et al. [33], using a small sample of HIV-infected South Africans, found that after 2 years of exposure to ART, patients had significantly decreased tricep skinfold thicknesses. Similarly, a Ugandan study using a sample of HIV-infected men and women [32], found that decreased tricep skinfold thicknesses was associated with the use of AZT.

            There were some limitations to our study. The cross sectional design, while allowing us to make associations, does not allow us to infer causality. With changes in fat distribution, repeated objective measures would have given us a better reference standard than patient report, even though patient report is commonly used [5, 6]. We did not have enough men with lipoatrophy or lipohypertrophy, to explore predictive anthropometric and DXA-derived variables. Finally, the likelihood ratios for the most predictive anthropometric and DXA-derived variables were only weakly diagnostic of self-report lipoatrophy and lipohypertrophy. Future research of longitudinal studies in African cohorts, using changes in DXA-derived variables as the reference standard, is needed to confirm the value of anthropometric measures for the diagnosis of lipoatrophy and lipohypertrophy.

            Conclusion

            Using a large sample of black HIV-infected South African women who had DXA scans performed, we were able to develop anthropometric measures for defining lipoatrophy and lipohypertrophy. The development of anthropometric measures which admittedly needs training and well maintained skinfold callipers to ensure their accuracy, are of particular relevance in resource limited settings, where health professionals need simple and inexpensive methods of diagnosing patients with lipoatrophy and lipohypertrophy.

            Methods

            Participants

            A convenience sample of HIV-infected black men and women presenting to ART clinics in Cape Town were selected. The recruitment procedure is described elsewhere [34]. The study sample comprised 116 male and 434 female participants on ART. At the time of the study two ART regimens were available to South Africans accessing primary health care facilities. The first-line regimen consisted of d4T, lamivudine (3TC) and efavirenz (EFV) or nevirapine, and a second-line regimen consisting of AZT with 3TC and lopinavir/ritonavir (LPV/r) [35].

            Testing procedures

            Questionnaires were used to collect socio-demographic information from participants. Their clinical records at the health facilities were reviewed to obtain data on ART regimen, time on ART, and CD4 count. Self-reported information on fat gain or fat loss was collected using a standard questionnaire [8]. Lipoatrophy was defined as moderate or severe fat loss in 2 or more regions and lipohypertrophy defined as moderate or severe fat gain in two or more areas [36].

            Anthropometric measurements: [weight, height, circumferences (waist, hip, mid-upper arm, and mid-thigh), skinfold thickness (bicep, tricep, subscapular, abdomen, suprailiac, thigh and calf) and sagittal abdominal diameter (SAD)] taken have previously been described [37]. DXA (Hologic Discovery-W, software version 12.7; scan region 195 × 65 cm2 and weight limit 160 kg) was used to measure fat mass and fat free soft tissue mass in a subsample of participants (females: n = 172; males: n = 53). DXA cut off lines positioned at anatomical markers were used to obtain fat mass for the whole body as well as for the various regions of interest. A more detailed description has been previously described [34].

            Ethical approval

            The study proposal was submitted and approved by the Research Ethics Committee of the Faculty of Health Sciences at the University of Cape Town. Written informed consent was obtained from all participants prior to participation in the study.

            Data analyses

            Data analysis was carried out using the STATA/SE statistical software package version 12.0 (StataCorp., College Station, TX, USA). Data were collected between February 2007 and June 2009. Participants were categorised into those with and those without lipoatrophy. Continuous variables were described as medians and inter-quartile ranges (IQR), and were compared using Wilcoxon Rank Sum tests. Binary variables were described using chi-square tests.

            Receiver operating characteristic (ROC) curves were used to describe the performance of a number of anthropometric and DXA-derived variables using patient reported lipoatrophy and lipohypertrophy as the reference standard. The area under the curve (AUC) was used to assess the diagnostic performance of each variable. In addition, sensitivity, specificity, likelihood ratios and predictive values were calculated for variables with the highest AUC at the optimum cut-points. Cut-point selection was based on positive likelihood ratios.

            Declarations

            Acknowledgements

            We thank Linda Bewerunge for doing the DXA scans, Sasha West for anthropometric measurements, and Carmen Delport for co-ordinating the study.

            Authors’ Affiliations

            (1)
            Division of Diabetic Medicine and Endocrinology, Department of Medicine, University of Cape Town
            (2)
            Division of Clinical Pharmacology, University of Cape Town
            (3)
            Department of Medicine, University of Cape Town

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            © Abrahams et al.; licensee BioMed Central Ltd. 2014

            This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​4.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.

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