Table 4.

Summary of Studies Reporting Sex Differences for Metabolic Dysfunction Among People With HIV

Author, Year [Ref]	Study Design Study Size (% PWH) No. of Men and Women	Study Population (Location, Race/Ethnicity, Age)	Outcomes Measured	Key Findings	Limitations
Diabetes and insulin resistance
Butt et al, 2009 [62]	Case-control N = 6567 (51% PWH) 6226 men, 342 women	•\tVeterans enrolled in VACS across 8 major US cities •\t64% Black, 22% White, 10% Hispanic •\tMean age: 50 y	Odds of prevalent diabetes mellitus [T2D] stratified by HIV status	•\tAmong PWH, adjusted odds of prevalent T2D was higher for men than women (aOR, 2.51 [95% CI, .96–6.52]) •\tAmong people without HIV, adjusted odds of prevalent T2D was higher for men than women (aOR, 1.65 [95% CI, 1.09–2.49])	Veterans with HIV may not be representative of general population with HIV. Women were severely underrepresented. Did not capture menopause status.
Ledergerber et al, 2007 [63]	Longitudinal cohort N = 6513 (27 798 PY) (100% PWH) 4494 men, 2019 women	•\tPWH enrolled in Swiss HIV Cohort Study •\t84% White, 11% Black •\tMedian age: 38 y	Incidence rate of diabetes per 1000 PY stratified by HIV status	•\tIn univariable models, incidence of T2D was 5.12 among MWH (95% CI, 4.20–6.24) and 2.89 among WWH (95% CI, 1.95–4.28) •\tMWH vs WWH had higher incidence of T2D in univariate (IRR, 1.77 [95% CI, 1.14–2.75]) and multivariate (IRR, 2.5 [95% CI, 1.5–4.2]) models	Did not include persons without HIV for comparison. Did not capture menopause status.
Koethe et al, 2016 [65]	Cross-sectional N = 70 (100% PWH) 40 men, 30 women	•\tPWH cared for at Vanderbilt Comprehensive Care Clinic in Nashville, TN •\t46% White, 54% non-White •\tMedian age: 44 y (men), 46 y (women)	Effect modification of FMI on relationship between sex and glucose tolerance and other plasma metabolites	•\tWWH vs MWH had significantly higher insulin sensitivity and less reduction in insulin sensitivity per unit of FMI (–0.017 vs –0.055kg/m2, P<.05 for sex∗FMI interaction) in multivariate model •\tWWH vs MWH had significantly lower insulin release and lower rise in insulin levels per FMI unit (0.009 vs 0.038kg/m2, P < .05 for sex∗FMI interaction) in multivariate model	Did not include persons without HIV for comparison. Did not capture menopause status.
Arama et al, 2013 [66]	Cross-sectional N = 89 (100% PWH) 51 men, 38 women	•\tYoung nondiabetic PWH cared for at National Institute of Infectious Diseases in Bucharest, Romania •\t100% White •\tMedian age: 32 y (men), 21 y (women)	Association between metabolic parameters (adiponectin, leptin, triglycerides) and QUICKI values determined by sex-specific regression analysis with corresponding correlation coefficients	•\tRelationship between IR and certain adipokines differed by sex. •\tMWH vs WWH had greater IR prevalence (72.5% vs 57.6%) •\tAmong MWH, those with IR had lower serum adiponectin (8.3 vs 14.1 μg/mL, P<.05) and higher serum triglycerides (217 vs 117.5mg/dL, P<.05) compared to those without IR •\tAmong WWH, those with IR had higher serum leptin (5.3 vs 2.8ng/mL, P<.05) compared with those without IR	Study population was small. Cohort included younger participants thus not those with active aging. Did not capture menopause status.
El-Sadr et al, 2005 [67]	Cross-sectional N = 419 (100% PWH) 331 men, 88 women	•\tART-naive PWH enrolled in CPCRA 058 & CPCRA 061 substudies from 49 clinics throughout US. •\t60% Black, 30% White, 10% Latinx •\tMean age: 38 y	•\tAssociation between demographic and HIV disease characteristics on serum lipids and glucose homeostasis	•\tWWH vs MWH had greater mean fasting insulin levels (12.1 vs 8.9 microunits/mL, P<.05) and mean IR score (2.6 vs 2.0, P<.05) •\tWWH vs MWH had greater fasting insulin (β = .1, P < .05) and IR (β = .103, P<.05) in multivariate analysis	Did not include persons without HIV for comparison. Did not capture menopause status.
Fat quantity and distribution
Bares et al, 2018 [73]	Longitudinal N = 3801 (100% PWH) 3041 men, 760 women	•\tART-naive PWH enrolled in 3 ACTG ART initiation trials in the US •\t38% White, 37% Black, 22% Hispanic •\tMean age: 38 y	Association between sex and changes in BMI at 96wk post–ART initiation	•\tWWH vs MWH had greater absolute BMI increase (+1.91 vs +1.39kg/m2 [95% CI, .29–.75], P<.05) and relative BMI increase (+7.65% vs +5.92%) over 96wk post–ART initiation in multivariate analyses •\tWWH had mean BMI increase of 0.59kg/m2 more than MWH over 96wk post–ART initiation (P<.05) in multivariate analyses	Did not include persons without HIV for comparison. Did not capture menopause status.
Hadigan et al, 2001 [74]	Case-control N = 404 (25% PWH) 268 men, 136 women	•\tPWH from Boston area and persons without HIV from Framingham Offspring Study •\tPWH: 77% White, 11% Black, 11% Hispanic •\tMean age: 41 y	Group differences in anthropometric measurements and metabolic parameters stratified by sex and HIV status	•\tDifferences in the waist-to-hip ratio for women vs men were observed in control population (0.82 vs 0.94, P<.05) but not among PWH with lipodystrophy (0.96 vs 0.98, P>.05) •\tWWH had a greater waist-to-hip ratio compared with HIV-negative women (+0.14, P<.05) •\tMWH had a greater waist-to-hip ratio compared with HIV-negative men (+0.04, P<.05)	Sex difference analyses were not adjusted.
Joy et al, 2008 [75]	Cross-sectional N = 413 (74% PWH) 236 men, 177 women	•\tPWH enrolled in metabolic studies at Massachusetts General Hospital and persons without HIV recruited from Boston community •\t55% White, 30% Black, 12% Hispanic •\tMean age: 42 y	Group differences in regional fat distribution (SAT, VAT, and total extremity fat) stratified by sex and BMI category	•\tMWH had 1.1kg less extremity fat than HIV-negative men; and WWH had 0.85kg less extremity fat than HIV-negative women •\tIn normal and overweight categories, MWH had less SAT compared with HIV-negative men (P<.05), whereas WWH had similar amount of SAT compared with HIV-negative women (P>.05) •\tIn the obese category, WWH had greater SAT than women without HIV (+72.3cm2, P<.05); however, there was no significant difference in SAT by HIV serostatus for men (P=.87)	PWH had a high prevalence of metabolic abnormalities (eg, lipodystrophy); therefore findings may not be generalizable to all PWH. Did not capture menopause status.
Chen et al, 2019 [80]	Cross-sectional N = 125 (84% PWH) 79 men, 46 women	•\tPWH enrolled in BOBCAT study, a diet and behavior change intervention, in Cleveland, Ohio •\t89% Black •\tMean age: 52 y	Effect modification of sex on relationship between BMI and inflammation markers (IL-6, hs-CRP) stratified by sex and HIV status	•\tIn adjusted models (not stratified by HIV), women vs men had a stronger correlation between BMI and hs-CRP (r = 0.584 vs r = 0.189, P=.06), and between BMI and IL-6 (r = 0.560 vs r = 0.096, P<.05) •\tAmong all participants (men and women), HIV status did not significantly modify the effect of BMI on hs-CRP or of BMI on IL-6	Control group was very small. Did not capture menopause status.
Galli et al, 2003 [81]	Cross-sectional N = 2258 (100% PWH) 1585 men, 673 women	•\tPWH enrolled in Lipodystrophy Italian Multicentre Study across 5 cities •\tRace/ethnicity data not available •\tMedian age: 37 y (men), 35 y (women)	Odds of ATAs since ART initiation in specific regions and patterns (Marrakesh categories) stratified by sex	•\tMWH vs WWH had lower adjusted odds of ATA in any given region (all P<.05) •\tMWH vs WWH had lower adjusted odds of pure lipohypertrophy (aOR, 0.58, P<.05) and combined lipodystrophy (aOR, 0.28, P<.05) •\tThe adjusted odds of pure lipoatrophy was not significantly different from MWH vs WWH (aOR, 0.89, P=.52)	ATAs were self-reported, which could introduce bias. Did not include persons without HIV for comparison. Did not capture menopause status.
Bacchetti et al, 2005 [82]	Cross-sectional N = 577 (74% PWH) 577 men, 0 women	•\tMWH enrolled in the FRAM study and controls recruited from the CARDIA study •\t56% White, 35% Black, 9% Hispanic •\tMean age: 40 y	Group differences in adipose tissue volumes at peripheral (cheeks, face, arms, buttocks, leg) and central sites (neck, chest, upper back, waist, abdominal fat); associations between peripheral and central fat distribution stratified by presence of lipoatrophy	•\tPeripheral lipoatrophy was more frequent among MWH vs HIV-negative men (39% vs 5%, P<.05) •\tCentral lipohypertrophy was less frequent among MWH vs HIV-negative men (40% vs 56%, P<.05) •\tAmong MWH, presence of central lipohypertrophy did not increase the odds of peripheral lipoatrophy (OR, 0.71 [95% CI, .47–1.06], P=.10)	Did not control for BMI. Did not include women but has a complementary study (described below).
Tien et al, 2006 [83]	Cross-sectional N = 325 (56% PWH) 0 men, 325 women	•\tWWH enrolled in the FRAM study and controls recruited from the CARDIA study •\t39% White, 54% Black, 6% Hispanic •\tMedian age: 39 y (WWH), 42 y (controls)	Group differences in adipose tissue volumes at peripheral (cheeks, face, arms, buttocks, leg) and central sites (neck, chest, upper back, waist, abdominal fat); associations between peripheral and central fat distribution stratified by presence of lipoatrophy	•\tPeripheral lipoatrophy was more frequent among WWH vs HIV-negative women (28% vs 4%, P<.05) •\tCentral lipohypertrophy prevalence was similar among WWH and HIV-negative women (62% vs 63%, P>.05) •\tAmong WWH, those with central lipohypertrophy were less likely to have peripheral lipoatrophy than those without central lipohypertrophy (OR, 0.39 [95% CI, .20–.75], P<.05)	Did not control for BMI
Liver Disease
Kardashian et al, 2017 [86]	Cross-sectional N = 229 (53% PWH) 142 men, 87 women	•\tWomen enrolled in WIHS from San Francisco and men enrolled in the Study of Visceral Adiposity, HIV, and HCV at the San Francisco VAMC •\t47% White, 45% Black •\tMean age: 50 y	Association of HIV and sex with LFF and steatosis (LFF >5%)	•\tIn unadjusted analysis, MWH had 81% greater LFF than WWH (95% CI, 32%–148%, P<.05); however, findings attenuated after adjustment (LFF 25% [95% CI, 9%–73%]) •\tHIV was associated with 82% lower adjusted odds of steatosis among women (P<.05), but no significant difference in the odds of steatosis among men (P=.633) •\tIn demographic-adjusted models, sex modified the effect of HIV on LFF (P<.05); however, this interaction attenuated in the fully adjusted model (P=.10)	Small study population
Guaraldi et al, 2008 [87]	Cross-sectional N = 225 (100% PWH) 163 men, 62 women	•\tPWH cared for at the metabolic clinic of University of Modena and Reggio Emilia School of Medicine in Italy •\tRace/ethnicity data not reported •\tMean age: 48 y	Prevalence and predictors on NAFLD among PWH and NAFLD diagnosed by CT (liver-to-spleen attenuation ratio <1.1)	•\tPrevalence of NAFLD was greater among MWH than WWH (44% vs 19%, P<.05) •\tPWH with NAFLD were 3.2 times more likely to be male than female in univariate analysis (95% CI, 1.59–6.49) and 2.5 times more likely to be male than female in multivariate analysis (95% CI, 1.07–5.81)	PWH had high prevalence of metabolic abnormalities and findings may not be generalizable to all PWH. Did not include persons without HIV for comparison.

Abbreviations: ACTG, AIDS Clinical Trial Group; aOR, adjusted odds ratio; ART, antiretroviral therapy; ATA, adipose tissue alteration; BMI, body mass index; BOBCAT, boosting health by changing activity ; CARDIA, Coronary Artery Risk Development in Young Adults; CI, confidence interval; CPCRA, Community Program for Clinical Research on AIDS; CT, computed tomography; FMI, fat mass index; FRAM, Study of Fat Redistribution and Metabolic Change in HIV Infection; HCV, hepatitis C virus; hs-CRP, high-sensitivity C-reactive protein; IL-6, interleukin 6; IR, insulin resistance; IRR, incidence rate ratio; LFF, liver fat fraction; MWH, men with HIV; NAFLD, nonalcoholic fatty liver disease; OR, odds ratio; PWH, persons with HIV; PY, person-years; QUICKI, Quantitative Insulin Sensitivity Check Index; r, correlation coefficient; SAT, subcutaneous adipose tissue; T2D, type 2 diabetes mellitus; TN, Tennessee; VACS, Veterans Aging Cohort Study; VAMC, Veterans Affairs Medical Center; VAT, visceral adipose tissue; WWH, women with HIV.