Higher prevalence of kidney function impairment among older people living with HIV in Uganda

Higher prevalence of kidney function impairment among older people living with HIV in Uganda | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Higher prevalence of kidney function impairment among older people living with HIV in Uganda Amutuhaire Judith Ssemasaazi, Robert Kalyesubula, Yukari C Manabe, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4364155/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background People living with HIV (PLWH) are at risk of kidney function impairment due to HIV-related inflammation, antiretroviral therapy (ART), diabetes mellitus, and hypertension. Older persons may experience a higher burden of chronic kidney disease (CKD) as kidney function declines with increasing age. There is a paucity of data comparing the prevalence of kidney function impairment in older PLWH to that in HIV-uninfected people in sub-Saharan Africa. Methods We conducted a cross-sectional study among people aged ≥ 60 years living with and without HIV in Kampala, Uganda who were matched 1:1 by community location. We collected data on sociodemographics, comorbidities, and HIV-related clinical characteristics. We defined kidney function impairment as an estimated glomerular filtration rate(eGFR) < 60mls/min/1.73m 2 with or without proteinuria. We constructed multivariable logistic regression models to study associations between participant characteristics and kidney function impairment. Results We enrolled 278 people (median age 66 years); 50% were PLWH, and 51.8% were female. Overall, the prevalence of kidney function impairment was 23.0% (95% CI:18.4%-28.4%); 33.1% (95% CI: 25.7%-41.4%) versus 12.9% (95% CI: 8.3%-19.7%) among people living with and without HIV (p-value < 0.01). The prevalence of proteinuria among PLWH versus people without HIV was 43.9% (95% CI:35.8%-52.3%) versus 19.4% (95% CI:13.6%-26.9%) p-value < 0.01. Living with HIV (OR = 3.89(95% CI: 2.04–7.41), p-value < 0.01), older age (OR = 1.13, (95% CI:1.07–1.20), p-value < 0.01), female sex (OR = 1.95, (95% CI:1.06–3.62), p-value = 0.03) and a prior diagnosis of hypertension (OR = 2.19(95% CI:1.02–4.67), p-value = 0.04) were significantly associated with kidney function impairment. Conclusions HIV infection is strongly associated with kidney function impairment among older PLWH. Prioritizing routine measurements of kidney function and proteinuria in older PLWH will enable early detection and institution of measures to reduce the progression of kidney disease. Older persons kidney function impairment sub-Saharan Africa Figures Figure 1 Figure 2 Background Globally, access to antiretroviral therapy (ART) has averted at least 20 million HIV-related deaths over the last two decades; therefore, more people are aging with HIV [ 1 ]. Aging with HIV is associated with an increased risk of multimorbidity [ 2 ] such as noncommunicable diseases (NCDs) including chronic kidney disease (CKD) [ 3 , 4 ]. Nephron senescence is a recognized age-related change that eventually leads to a decline in kidney function and increases the risk of CKD in older persons [ 5 ]. In people living with HIV (PLWH); aging, chronic inflammation which persists during suppressive ART, and nephrotoxic ART such as tenofovir disoproxil fumarate (TDF) [ 5 – 7 ] converge to increase the risk of CKD by threefold [ 8 ]. Moreover, traditional risk factors for CKD such as diabetes mellitus and hypertension are more prevalent among PLWH [ 2 , 9 ]. Chronic kidney disease is a progressive disease that manifests with several indicators of kidney function impairment such as proteinuria [ 10 ]. Kidney failure is associated with increased morbidity, poor quality of life, and increased risk of death among PLWH [ 11 – 14 ]. In low-income countries (LICs) such as Uganda, there is limited access to life-saving dialysis and kidney transplants to manage end-stage kidney disease(ESKD)/kidney failure and even when available, the costs exceed the average income for most patients [ 15 , 16 ]. Studies in the general population have documented the association of HIV with kidney disease in both low- and high-resource settings[ 17 – 20 ], but there is a paucity of data documenting the excess prevalence of kidney function impairment in older PLWH in Uganda and sub-Saharan Africa. We sought to determine the additional prevalence of kidney function impairment in older people living with HIV compared to those without HIV in Uganda. Methods Study design and setting We conducted a cross-sectional study at the Infectious Diseases Institute (IDI) clinic in Mulago, Kampala, Uganda between April and August 2023. The IDI is an implementing partner for the President’s Emergency Plan for AIDS Relief (PEPFAR) with clinics in 18 districts in the country. The IDI flagship adult clinic at Mulago Hospital takes care of more than 8,000 HIV-infected patients and among these patients, more than 1000 are aged ≥ 60 years. We consecutively enrolled PLWH aged ≥ 60 years who were attending the HIV clinic at IDI and people without HIV recruited within a 2-kilometer distance of the same communities where the participating PLWH lived. The participants were recruited on a 1:1 ratio. We defined older people as those aged ≥ 60 years per the United Nations definition [ 21 , 22 ]. Participants were excluded if they could not provide blood or urine samples for study measurements. Data collection tools and procedures We collected data using an electronic structured questionnaire developed in Research Electronic Data Capture (REDCap) developed by Vanderbilt University [ 23 ]. HIV-uninfected participants were counseled and tested for HIV before enrollment in the study. For each participant, we collected sociodemographic data (sex, age in years, education level, income status), and anthropological measurements (height in meters and weight in kg) using calibrated scales and calculated the body mass index in kg/m 2 . We collected information on comorbidities (diabetes mellitus, hypertension, other cardiovascular disease, liver disease, and others), prescriptions and over-the-counter drugs, past or present history of smoking, history of current alcohol use, and history of HIV, which included duration of ART, antiretroviral drugs (previous and current regimens), history and duration of TDF use, most recent viral load and CD4 count. We measured blood pressure using a standardized automated Omron M2 basic blood pressure monitor with consistent positioning (patients were seated upright with back and arm support). We took three readings and calculated the average. We measured fasting blood sugar in mmol/l using a point-of-care calibrated on-call plus glucometer manufactured by ACON laboratories, USA. For participants with no prior history of diabetes mellitus, a diagnosis of diabetes mellitus was made if one had elevated blood glucose (nonfasting ≥ 11.1 mmol/L or fasting ≥ 7 mmol/L) in the presence of symptoms. If elevated values were found in someone asymptomatic; a repeat fasting blood sugar was performed on a subsequent day to confirm the diagnosis. We collected an early morning urine sample from each patient for measurement of urine protein by dipstick urinalysis and a venous blood sample for measurement of serum creatinine. We defined kidney function impairment as an estimated glomerular filtration rate (eGFR) < 60 mls/min per 1.73 m 2 with or without proteinuria on a dipstick urine test. This creatinine-based eGFR was calculated from the 2009 version of the chronic kidney disease epidemiology collaboration) (CKD-EPI) (CKD-EPI 2009) [ 24 ] without correcting for race [ 25 , 26 ]. We used the CKD-EPI 2009 which is widely used in clinical practice and a recent study showed it to perform better than the race-free creatinine-based CKD-EPI 2021 equation in sub-Saharan Africa [ 27 ]. We categorized the stages of kidney function impairment by eGFR as stage 1: ≥90, stage 2:≥60-<90, stage 3: ≥30-<60, stage 4:≥15-<30 and stage 5: <15mls/min/1.73m 2 [ 28 ]. We measured proteinuria using Siemens Multistix GP Urine Test Strips and we categorized it as negative if no protein was detected or positive if at least trace protein (≥ 30mg/dl) was detected. Data Analysis We exported the data to STATA version 14 (Stata Corp LLC, College Station, TX). We reported the proportions of participants with kidney function impairment and proteinuria in both groups with 95% confidence interval (95% CI) and compared them with a chi-square test. The additional prevalence of kidney function impairment due to HIV was reported as a difference between the proportions in the group of PLWH and people without HIV with its 95% CI and a p-value corresponding to the z-statistic for testing the significance of a difference in proportions between two groups. We summarized other categorical variables as proportions and continuous variables as medians with interquartile ranges (IQR). Comparisons were based on a chi-square test for categorical variables otherwise Fisher’s exact test was used if any of the cells had ≤ 5 observations. Comparisons for continuous variables were based on the Wilcoxon rank sum test. We performed logistic regression with HIV as the main exposure and performed a stratified analysis by HIV status to study associations between various participant characteristics and kidney function impairment. We considered the level of significance at a p-value ≤ 0.2 for bivariate analysis and p ≤ 0.05 for multivariate analysis. We assessed confounding factors by comparing unadjusted and adjusted models, interactions using the loglikelihood ratio test, and goodness of fit of the model using the Hosmer–Lemeshow test. Results We enrolled 278 men and women aged ≥ 60 years; 50% were PLWH and 51.8% were female. PLWH and those living without HIV were similar except for smoking status, use of non-HIV related medications, prior history of tuberculosis, median systolic and diastolic blood pressure, body mass index, and proteinuria ( Table 1 ). Table 1 Characteristics of study participants Characteristics Overall N = 278 PLWH, N = 139 No HIV, N = 139 P-value n (%) n (%) n (%) Median Age in Years (IQR) 66 (63–70) 66 (64–70) 65 (62–70) 0.06 Sex 0.15 Female 144 (51.8) 66 (47.5) 78 (56.1) Male 134 (48.2) 73 (52.5) 61 (43.9) Highest level of education 0.81 None-primary level 116 (41.7) 57 (41.0) 59 (42.5) secondary-tertiary level 162 (58.3) 82 (59.0) 80 (57.5) Monthly household income in USDs 0.61 ≥ 1 USD per day 190 (68.4) 93 (66.9) 97 (69.8) ≤ 1 USD per day 88 (31.6) 46 (33.1) 42 (30.2) Smoking 0.01 No 228 (82.0) 106 (76.3) 122 (87.8) Yes 50 (18.0) 33 (23.7) 17 (12.2) Alcohol consumption 0.15 No 197 (70.9) 104 (74.8) 93 (66.9) Yes 81 (29.1) 35 (25.2) 46 (33.1) Non-HIV related comorbidities 0.13 No chronic illness 54 (19.4) 22 (15.8) 32 (23.0) At least one chronic illness 224 (80.6) 117 (84.2) 107 (77.0) Prior diagnosis of Hypertension 0.54 No 117 (42.1) 56 (40.3) 61 (43.9) Yes 161 (57.9) 83 (59.7) 78 (56.1) Prior diagnosis of Diabetes mellitus 0.73 No 240 (86.3) 119 (85.6) 121 (87.0) Yes 38 (13.7) 20 (14.4) 18 (13.0) Non-HIV related medications 0.03 No chronic medication 75 (27.0) 30 (21.6) 45 (32.4) Anti-hypertensives and anti-diabetes medications 144 (51.8) 83 (59.7) 61 (43.9) Others 59(21.2) 26 (18.7) 33 (23.7) Prior diagnosis of tuberculosis < 0.01 No 219 (78.8) 80 (57.5) 139 (100.0) Yes 59 (21.2) 59 (42.5) 0 (0) Median Systolic Blood Pressure (IQR) 130 (121–140) 128 (118–134) 134 (125–150) < 0.01 Median Diastolic Blood Pressure (IQR) 82 (75–90) 80 (73–85) 86 (77–95) < 0.01 Median Fasting Blood Sugar (IQR) 5.6 (4.9–6.3) 5.6 (5.0-6.4) 5.4 (4.9-6.0) 0.17 Body mass index < 0.01 25.0 127 (45.7) 49(35.2) 78 (56.1) Proteinuria < 0.01 Negative 190 (68.4) 78 (56.1) 112 (80.6) At least Trace proteinuria 88 (31.6) 61 (43.9) 27 (19.4) IQR = interquartile range, PLWH = people living with HIV, USD = US dollars, others = other medication apart from those used to treat diabetes mellitus and hypertension. Among the 139 PLWH, the median CD4 count was 634 (IQR: 486–917) cells/mm 3 , 5.8% had a detectable viral load (> 50 copies/ml), 80.6% had WHO clinical stage 3 or 4 disease at the start of ART, 95.7% had ever used TDF in their ART regimen, and 66.2% were currently on a TDF-based regimen ( Table 2 ). Table 2 Characteristics of PLWH in the study HIV-related characteristics of older PLWH(N = 139) n, (%) WHO clinical stage at ART Stage I-II 27 (19.4) Stage III-IV 112 (80.6) Median CD4 count (IQR) 634 (486–917) Viral load Detectable (> 50 copies/ml) 8 (5.8) Undetectable (< 50 copies per ml) 131 (94.2) Current ART regimen Others 3 (2.2) Abacavir-based 44 (31.7) TDF-based 92 (66.1) Ever used TDF No 6 (4.30 Yes 133 (95.7) Median number of years on TDF (IQR) 5 (4–9) Median number of years on ART (IQR) 16 (11–18) Supplementary table 1 : PLWH = People living with HIV, TDF Tenofovir Disoproxil Fumarate, IQR = interquartile range Burden of kidney function impairment among study participants Overall, 23.0% (95% CI:18.4%-28.4%) had kidney function impairment. Among the PLWH, 33.1% (95% CI: 25.7%-41.4%) had kidney function impairment compared to 12.9% (95% CI: 8.3%-19.7%) among people without HIV, (p-value < 0.01); the additional prevalence of kidney function impairment in PLWH was 20.2% (95%CI: 10.6%-29.0%), p-value < 0.01. The median GFR among PLWH versus people without HIV was 68.4 (IQR:56.9–84.0) mls/min/1.73m2 versus 81.4 (IQR:71.4–90.4) mls/min/1.73m2, p-value < 0.01 ( Fig. 1 ). The prevalence of kidney function impairment among PLWH and people without HIV varied by disease stage. PLWH constituted the majority in stage 3 and stage 4 of kidney function impairment ( Fig. 2 ). Older PLWH had a higher prevalence of proteinuria 43.9% (95% CI:35.8–52.3) versus 19.4% (95% CI: 13.6–26.9) among older people without HIV, p-value < 0.01. Older age (OR = 1.13, (95% CI: 1.07–1.20), p-value < 0.01), being female (OR = 1.95, (95% CI: 1.06–3.62), p-value = 0.03) and living with HIV (OR = 3.89, (95% CI: 2.04–7.41), p < 0.01) were associated with kidney function impairment at multivariate analysis ( Table 3 ). Additionally, in a stratified analysis by HIV status, a prior diagnosis of hypertension (OR = 2.19, (95% CI:1.02–4.67), p-value = 0.04) was associated with kidney function impairment among older PLWH Table 3 Factors associated with kidney function impairment among people ≥ 60 years living with and without HIV Characteristic of participants Kidney function impairment, n (%) Bivariate Analysis Multivariate analysis Yes: 64 (23%) No: 214 (77%), Unadjusted OR (CI) P-value Adjusted OR (CI) P-value Median Age in Years (IQR) 68 (65–74) 65 (63–69) 1.08 (1.00-1.17) 0.04 1.13 (1.07–1.20) < 0.01 Sex Male 28 (43.7) 106 (49.5) 1 1 Female 36 (56.3) 108 (50.5) 1.72 (0.84–3.52) 0.14 1.95 (1.06–3.62) 0.03 Alcohol consumption No 50 (78.1) 147 (68.7) 1 Yes 14 (21.9) 67 (31.3) 0.42 (0.17–1.05) 0.06 0.63 (0.29–1.4) 0.26 HIV status People without HIV 18 (28.1) 121 (56.5) 1 1 Positive 46 (71.9) 93 (43.5) 3.32 (1.81–6.12) < 0.01 3.89 (2.04–7.41) < 0.01 Prior diagnosis of hypertension** No 20 (31.3) 97 (45.3) 1 1 Yes 44 (68.7) 117 (56.7) 1.82 (1.00-3.30) 0.05 1.73 (0.91–3.93) 0.09 Prior diagnosis of TB No 43 (67.3) 176 (82.2) 1 1 Yes 21 (32.8) 38 (17.8) 2.26 (1.21–4.24) 0.011 1.31 (0.62–2.80) 0.48 Median Diastolic Blood Pressure (IQR) 79.5 (74.5–87) 83 (75–91) 0.98 (0.95-1.00) 0.15 1.02(0.63–1.050 0.68 Non-HIV related comorbidities No chronic illness 7 (10.9) 47 (22.0) 1 1 At least one chronic illness 57 (89.1) 167 (78.0) 0.44 (0.19–1.02) 0.06 0.52 (0.16–1.71) 0.51 Ever used TDF* No 4 (8.7) 2 (2.1) 1 1 Yes 42 (91.3) 91 (97.9) 0.23 (0.04–1.32) 0.09 0.41 (0.07–2.53) 0.34 *Variables evaluated in a stratified analysis by HIV status only ** Variable was significant at multivariate analysis in PLWH in a stratified analysis by HIV status with OR = 2.19 (95%CI:1.02–4.67) and p-value = 0.04 Discussion Our study shows that one-third of the aging Ugandan HIV population had kidney function impairment that was significantly higher than the prevalence in community-matched HIV-uninfected controls. Data documenting the burden of kidney function impairment in aging HIV populations come mostly from high-income countries [ 8 , 19 , 29 ]. Overall, we found a high prevalence of kidney function impairment among people aged ≥ 60 years living with and without HIV in Uganda. Our data agree with studies that have shown that PLWH experience a high burden of kidney disease [ 19 , 29 , 30 ]. HIV infection significantly increases the odds of kidney function impairment [ 8 , 9 , 31 , 32 ] and various forms of HIV-associated nephropathy have been documented in previous research[ 9 , 33 ]. However, our study demonstrated an excess burden of kidney function impairment among older PLWH compared to previous prevalences reported in the general population of PLWH in Uganda[ 34 , 35 ] and other LICs[ 18 , 30 , 36 , 37 ]. These findings imply that there is a need for research and clinical care programs to evolve and prioritize kidney disease detection in the population of older PLWH. The prevalence of proteinuria in our study was at least two times higher in PLWH than in people without HIV. Other studies such as the AGE h IV cohort study [ 38 ] have shown that the burden of albuminuria is higher among people living with HIV than in people without HIV. However, our study reported higher estimates of proteinuria than what has been reported in non-African settings [ 38 , 39 ]. Previous studies have pointed to genetic risks for kidney injury such as the presence of the APOL1 gene which is unique to African populations and may account for racial disparities in the burden of CKD [ 40 – 43 ]. Proteinuria is a biomarker for kidney injury[ 28 ]; thus further research into context-specific risk factors for kidney disease is needed to understand the cause of kidney injury in older PLWH. Kidney disease is progressive; thus these findings of the excess prevalence of kidney function impairment and proteinuria may have implications for the health and survival of old PLWH in a country where there is limited access to life-saving therapies such as dialysis and renal transplants for kidney failure [ 15 , 16 ]. Increasing age and female sex were significantly associated with kidney function impairment in both PLWH and people without HIV. These findings are consistent with previous studies from Uganda and Africa where increasing age and female sex were associated with kidney disease in both PLWH and people without HIV [ 18 , 31 , 44 , 45 ]. Among older PLWH, a prior diagnosis of hypertension significantly increased the odds of kidney function impairment. Hypertension is a known traditional risk factor for CKD [ 46 ] and hypertensive nephrosclerosis is a well-recognized pathological process that eventually leads to kidney failure [ 47 ]. A high prevalence of hypertension has been reported among aging PLWH [ 2 , 48 ] and the association of such traditional risk factors with CKD is documented in previous studies [ 46 , 49 ]. The implementation of blood pressure control programs in older PLWH and hypertension can benefit kidney health as the same approach has been shown to improve outcomes in other populations at risk of hypertension-related kidney injury such as people with cardiovascular diseases and diabetes mellitus[ 50 ]. In our study, HIV was the strongest significantly associated factor with kidney function impairment. Unlike other studies, we did not find an association between diabetes mellitus[ 29 , 51 ] and kidney function impairment, smoking [ 9 , 52 , 53 ], body mass index (BMI), socioeconomic status (monthly household income) [ 44 , 54 ] or prior diagnosis of tuberculosis [ 55 ] [ 56 ] as other studies did. Unlike these previous studies, in our study, fewer participants reported a history of smoking, and there were fewer diabetic patients. The monthly household income was not different between PLWH and people without HIV or between people with and without kidney function impairment. Likewise, the BMI was not different between people with and without kidney function impairment and all the people who had a previous diagnosis of tuberculosis were among PLWH. Among the PLWH in our study, only a small proportion, 2.2%, had CD4 less than 200 cells per ml and only 5.8% had detectable viral loads (> 50copies/ml). Almost all (95.7%) of our PLWH had ever used TDF. These proportions may explain the lack of association between these variables and kidney function impairment in our study although previous studies have shown a significant association[ 8 , 18 , 57 , 58 ]. In our study, we observed higher prevalence of kidney function impairment in participants on abacavir-based regimens; most of the participants on abacavir-based regimens had previously been on TDF, but were switched over due to low eGFR. Previous studies on kidney function impairment among old people with HIV in Uganda and sub-Saharan Africa have not included uninfected controls. A strength of our study was a comparator group of older people without HIV from similar communities which allowed us to compare the characteristics between the two populations as well as the outcome and ascertain the excess prevalence of kidney function impairment attributable to HIV. A limitation of our study was that it was cross-sectional so we were unable to observe changes in kidney function over three months. In addition, we did not perform ultrasound scanning so we could not differentiate between acute and chronic kidney function impairment. We also used dipsticks to detect proteinuria which is a less specific method than the urine albumin to creatinine ratio (UACR). Conclusions There is an excess prevalence of kidney function impairment amongolder PLWH with one-third of our aging PLWH having impaired kidney function. In LICs, early ascertainment of kidney function in older PLWH should be prioritized with routine measurement of urine protein and kidney function. Furthermore, research into novel, cost-friendly biomarkers that could improve the early detection of CKD and its progression in HIV aging populations is needed to allow early intervention. Abbreviations AIDS: Acquired Immunodeficiency Syndrome ART: Antiretroviral therapy LICs : Low-income countries CKD : Chronic Kidney Disease CKD-EPI: Chronic Kidney Disease Epidemiology Collaboration ESRD/ESKD: End-Stage Renal Disease/End-Stage kidney disease/kidney failure eGFR: Estimated Glomerular Filtration Rate HIVAN: HIV Associated Nephropathy HIV: Human Immunodeficiency Virus IDI: Infectious Diseases Institute PLWH: People Living With HIV TDF: Tenofovir disoproxil fumarate Declarations Ethics approval and consent to participate Our study was approved by the Makerere University School of Medicine Research and Ethics Committee (SOMREC) (approval number-Mak-SOMREC-2022-538) and Uganda National Council of Science and Technology (UNCST) (approval number-HS2913ES. All participants provided informed consent Availability of data and materials The de-identified data set will be available upon acceptance for publication of the manuscript with a request to the study team through the corresponding author. Competing interest s The authors declare that they have no competing interests. Funding Source Research reported in this publication was supported by the National Institute Of Allergy And Infectious Diseases (NIAID), Eunice Kennedy Shriver National Institute Of Child Health & Human Development (NICHD), National Institute On Drug Abuse (NIDA), National Cancer Institute (NCI), and the National Institute of Mental Health (NIMH), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), Fogarty International Canter (FIC), National Heart, Lung, and Blood Institute (NHLBI), in accordance with the regulatory requirements of the National Institutes of Health under Award Number U01AI069911East Africa IeDEA Consortium. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health The “Diagnosis and treatment of non-communicable diseases and geriatric syndromes in the HIV aging population in sub-Saharan Africa (HASA)” study, part of the EDCTP2 program supported by the European Union grant agreement number TMA2017GSF-1936. This publication was supported by the Fogarty International Center of the National Institutes of Health under Award Number D43TW009771. The content is solely the authors' responsibility and does not necessarily represent the official views of the National Institutes of Health. Authors’ contributions AJS: Conceptualization, protocol writing, data collection, organizing and analyzing the data, writing the original draft of the manuscript and editing. RK: Conceptualization, protocol writing, supervision, manuscript review and editing YM: Manuscript writing and editing PM: Conceptualization, manuscript review and editing SN: Data collection and curation FS: Data collection and curation EN: Manuscript writing and editing PBK: Conceptualization, supervision, manuscript review and editing BC: Conceptualization, acquisition of funding, supervision, writing and editing the manuscript References UNAIDS, The path that ends AIDS: UNAIDS Global AIDS Update 2023. Geneva: Joint United Nations Programme on HIV/AIDS; 2023. Licence: CC BY-NC-SA 3.0 IGO. 2023. Guaraldi, G., et al., Aging with HIV vs. HIV Seroconversion at Older Age: A Diverse Population with Distinct Comorbidity Profiles. PLOS ONE, 2015. 10 (4): p. e0118531. Haregu, T.N., et al., Epidemiology of comorbidity of HIV/AIDS and non-communicable diseases in developing countries: a systematic review. J Glob Health Care Syst, 2012. 2 (1): p. 1-12. Hirschhorn, L.R., et al., Cancer and the ‘other’noncommunicable chronic diseases in older people living with HIV/AIDS in resource-limited settings: a challenge to success. Aids, 2012. 26 : p. S65-S75. O’Sullivan, E.D., J. Hughes, and D.A. Ferenbach, Renal Aging: Causes and Consequences. Journal of the American Society of Nephrology, 2017. 28 (2): p. 407-420. Klatt, N.R., et al., Immune activation and HIV persistence: implications for curative approaches to HIV infection. Immunol Rev, 2013. 254 (1): p. 326-42. Hamzah, L., et al., Treatment-limiting renal tubulopathy in patients treated with tenofovir disoproxil fumarate. Journal of Infection, 2017. 74 (5): p. 492-500. Islam, F.M., et al., Relative risk of renal disease among people living with HIV: a systematic review and meta-analysis. BMC Public Health, 2012. 12 (1): p. 234. Heron, J.E., C.I. Bagnis, and D.M. Gracey, Contemporary issues and new challenges in chronic kidney disease amongst people living with HIV. AIDS Research and Therapy, 2020. 17 (1): p. 11. Liu, D. and L.-L. Lv, New understanding on the role of proteinuria in progression of chronic kidney disease. Renal Fibrosis: Mechanisms and Therapies, 2019: p. 487-500. Sarfo, F.S., et al., High prevalence of renal dysfunction and association with risk of death amongst HIV-infected Ghanaians. Journal of Infection, 2013. 67 (1): p. 43-50. Ryom, L., et al., Serious clinical events in HIV-positive persons with chronic kidney disease. AIDS, 2019. 33 (14): p. 2173-2188. Matías-García, P.R., et al., DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function. Clinical Epigenetics, 2021. 13 (1): p. 121. Legrand, K., et al., Perceived Health and Quality of Life in Patients With CKD, Including Those With Kidney Failure: Findings From National Surveys in France. American Journal of Kidney Diseases, 2020. 75 (6): p. 868-878. Kalyesubula, R., U.C. Brewster, and G. Kansiime, Global Dialysis Perspective: Uganda. Kidney360, 2022. Kalyesubula, R., et al., Nephrology in Uganda. Nephrology Worldwide, 2021: p. 75-83. Kaboré, N.F., et al., Chronic kidney disease and HIV in the era of antiretroviral treatment: findings from a 10-year cohort study in a west African setting. BMC Nephrology, 2019. 20 (1): p. 155. Fiseha, T. and A. Gebreweld, Renal function in a cohort of HIV-infected patients initiating antiretroviral therapy in an outpatient setting in Ethiopia. PLOS ONE, 2021. 16 (1): p. e0245500. Petersen, N., et al., Prevalence of impaired renal function in virologically suppressed people living with HIV compared with controls: the Copenhagen Comorbidity in HIV Infection (COCOMO) study*. HIV Medicine, 2019. 20 (10): p. 639-647. Abd ElHafeez, S., et al., Prevalence and burden of chronic kidney disease among the general population and high-risk groups in Africa: a systematic review. BMJ open, 2018. 8 (1): p. e015069. UNFPA, Ageing in the Twenty-First Century: A Celebration and A Challenge. United Nations Population Fund (UNFPA), New York, and HelpAge International, London.2012. 2012. Kowal, P. and J. Dowd, Definition of an older person. Proposed working definition of an older person in Africa for the MDS Project. 2001. Patridge, E.F. and T.P. Bardyn, Research electronic data capture (REDCap). Journal of the Medical Library Association: JMLA, 2018. 106 (1): p. 142. Levey, A.S., et al., A new equation to estimate glomerular filtration rate. Ann Intern Med, 2009. 150 (9): p. 604-12. Shi, J., et al., Calculating estimated glomerular filtration rate without the race correction factor: Observations at a large academic medical system. Clinica Chimica Acta, 2021. 520 : p. 16-22. Zingano, C.P., et al., 2009 CKD-EPI glomerular filtration rate estimation in Black individuals outside the United States: a systematic review and meta-analysis. Clinical Kidney Journal, 2022. 16 (2): p. 322-330. Fabian, J., et al., Measurement of kidney function in Malawi, South Africa, and Uganda: a multicentre cohort study. Lancet Glob Health, 2022. 10 (8): p. e1159-e1169. Levey, A.S., et al., Nomenclature for kidney function and disease—executive summary and glossary from a Kidney Disease: Improving Global Outcomes (KDIGO) consensus conference. European Heart Journal, 2020. 41 (48): p. 4592-4598. Heron, J.E., et al., The prevalence and risk of non-infectious comorbidities in HIV-infected and non-HIV infected men attending general practice in Australia. PloS one, 2019. 14 (10): p. e0223224. Glaser, N., et al., The prevalence of renal impairment in individuals seeking HIV testing in Urban Malawi. BMC Nephrology, 2016. 17 (1): p. 186. Muiru, A.N., et al., The epidemiology of chronic kidney disease (CKD) in rural East Africa: A population-based study. PLOS ONE, 2020. 15 (3): p. e0229649. Penner, J., et al., High rates of kidney impairment among older people (≥ 60 years) living with HIV on first-line antiretroviral therapy at screening for a clinical trial in Kenya. PLOS ONE, 2023. 18 (6): p. e0285787. Wyatt, C.M., Kidney disease and HIV infection. Topics in antiviral medicine, 2017. 25 (1): p. 13. Kansiime, S., D. Mwesigire, and H. Mugerwa, Prevalence of non-communicable diseases among HIV positive patients on antiretroviral therapy at joint clinical research centre, Lubowa, Uganda. PLOS ONE, 2019. 14 (8): p. e0221022. Nyende, L., et al., Prevalence of renal dysfunction among HIV infected patients receiving Tenofovir at Mulago: a cross-sectional study. BMC nephrology, 2020. 21 : p. 1-6. Wyatt, C.M., et al., Prevalence of Kidney Disease in HIV-Infected and Uninfected Rwandan Women. PLOS ONE, 2011. 6 (3): p. e18352. Ekrikpo, U.E., et al., Chronic kidney disease in the global adult HIV-infected population: A systematic review and meta-analysis. PLOS ONE, 2018. 13 (4): p. e0195443. Kooij, K.W., et al., Higher Prevalence and Faster Progression of Chronic Kidney Disease in Human Immunodeficiency Virus–Infected Middle-Aged Individuals Compared With Human Immunodeficiency Virus–Uninfected Controls. The Journal of Infectious Diseases, 2017. 216 (6): p. 622-631. Barzilay, J.I., et al., Hospitalization Rates in Older Adults With Albuminuria: The Cardiovascular Health Study. The Journals of Gerontology: Series A, 2020. 75 (12): p. 2426-2433. Kasembeli, A.N., et al., APOL1 risk variants are strongly associated with HIV-associated nephropathy in black South Africans. Journal of the American Society of Nephrology, 2015. 26 (11): p. 2882-2890. Behar, D.M., et al., Absence of APOL1 risk variants protects against HIV-associated nephropathy in the Ethiopian population. American journal of nephrology, 2011. 34 (5): p. 452-459. Elliott, M.D., et al., Clinical and genetic characteristics of CKD patients with high-risk APOL1 genotypes. The Journal of the American Society of Nephrology, 2023. 34 (5): p. 909-919. Friedman, D.J. and M.R. Pollak, APOL1 Nephropathy: From Genetics to Clinical Applications. Clinical Journal of the American Society of Nephrology, 2021. 16 (2): p. 294-303. Kalyesubula, R., et al., Kidney disease in Uganda: a community based study. BMC nephrology, 2017. 18 (1): p. 1-9. Mwemezi, O., et al., Renal Dysfunction among HIV-Infected Patients on Antiretroviral Therapy in Dar es Salaam, Tanzania: A Cross-Sectional Study. International Journal of Nephrology, 2020. 2020 : p. 8378947. Luyckx, V.A., et al., Reducing major risk factors for chronic kidney disease. Kidney International Supplements, 2017. 7 (2): p. 71-87. Costantino, V.V., et al., Molecular mechanisms of hypertensive nephropathy: renoprotective effect of losartan through Hsp70. Cells, 2021. 10 (11): p. 3146. Guaraldi, G., J. Milic, and C. Mussini, Aging with HIV. Current HIV/AIDS Reports, 2019. 16 : p. 475-481. Ajayi, S.O., et al., Prevalence of Chronic Kidney Disease as a Marker of Hypertension Target Organ Damage in Africa: A Systematic Review and Meta-Analysis. International Journal of Hypertension, 2021. 2021 : p. 7243523. Chen, T.K., et al., Reducing Kidney Function Decline in Patients With CKD: Core Curriculum 2021. American Journal of Kidney Diseases, 2021. 77 (6): p. 969-983. Ene-Iordache, B., et al., Chronic kidney disease and cardiovascular risk in six regions of the world (ISN-KDDC): a cross-sectional study. The Lancet Global Health, 2016. 4 (5): p. e307-e319. Althoff, K.N., et al., Contributions of traditional and HIV-related risk factors on non-AIDS-defining cancer, myocardial infarction, and end-stage liver and renal diseases in adults with HIV in the USA and Canada: a collaboration of cohort studies. The lancet HIV, 2019. 6 (2): p. e93-e104. Safaa, M.M., Diabetes Mellitus Control and Chronic Kidney Disease. American Journal of Chemistry and Pharmacy, 2023. 2 (2): p. 9-14. Betzler, B.K., et al., Association between Body Mass Index and Chronic Kidney Disease in Asian Populations: A Participant-level Meta-Analysis. Maturitas, 2021. 154 : p. 46-54. Hodel, N.C., et al., The epidemiology of chronic kidney disease and the association with non-communicable and communicable disorders in a population of sub-Saharan Africa. PLOS ONE, 2018. 13 (10): p. e0205326. Canney, M., et al., Incidence of and Risk Factors for Active Tuberculosis Disease in Individuals With Glomerular Disease: A Canadian Cohort Study. American Journal of Kidney Diseases, 2023. 82 (6): p. 725-736. Ryom, L., A. Mocroft, and J. Lundgren, HIV therapies and the kidney: some good, some not so good? Current HIV/AIDS Reports, 2012. 9 (2): p. 111-120. Achhra, A.C., et al., Chronic kidney disease and antiretroviral therapy in HIV-positive individuals: recent developments. Current HIV/AIDS Reports, 2016. 13 (3): p. 149-157. Additional Declarations No competing interests reported. Supplementary Files SupplementarymaterialsubmittedbyAmutuhaireJudithSsemasaazi.doc Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4364155","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":298626997,"identity":"436ae83e-5bab-4de7-a55e-6e17f0321625","order_by":0,"name":"Amutuhaire Judith Ssemasaazi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYLACxgYGHiCVwMBjwJDADxJJKCCgAUmLQYJkA4hpQFgLBPAwGCQYHACx8Gjhn3bG/DHvDjsZ8/aGZxJvCv7kGZ9fnfjhgQGDPL/YAaxaJG7nGDbznknmkTlzIE1yjoFBsdmNt5slgA4znDk7Abs1YC1tzDwSEglp0kC/JG67cXYDSEuCwW3sWuQhWup5JOQfQLRsnnF28w98WgwgWg4DbWGAaNnA37sNry2Gt9MKZ85tO84jwZOQbDnHwDhxxg3ebRYJBhI4/SJ3O3nDh7dt1fYS7GcSb7z5I5fY3392880fFTby/NI4vI8APFAVEmBagpByEGA/AKH5DxCjehSMglEwCkYQAABTgF9kYObOugAAAABJRU5ErkJggg==","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":true,"prefix":"","firstName":"Amutuhaire","middleName":"Judith","lastName":"Ssemasaazi","suffix":""},{"id":298626998,"identity":"fb9d0f67-86f0-4ac9-9d43-78408e84ae58","order_by":1,"name":"Robert Kalyesubula","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"","lastName":"Kalyesubula","suffix":""},{"id":298626999,"identity":"cc9f3200-1ee9-480d-af12-1f4690e3e15e","order_by":2,"name":"Yukari C Manabe","email":"","orcid":"","institution":"Infectious Diseases Institute","correspondingAuthor":false,"prefix":"","firstName":"Yukari","middleName":"C","lastName":"Manabe","suffix":""},{"id":298627001,"identity":"51ad5bca-f0b2-481c-b520-a9a1a02a83f8","order_by":3,"name":"Phoebe Mbabazi","email":"","orcid":"","institution":"Infectious Diseases Institute","correspondingAuthor":false,"prefix":"","firstName":"Phoebe","middleName":"","lastName":"Mbabazi","suffix":""},{"id":298627003,"identity":"77ee9ed2-ca38-4f21-a4da-ace4642f627b","order_by":4,"name":"Susan Naikooba","email":"","orcid":"","institution":"Infectious Diseases Institute","correspondingAuthor":false,"prefix":"","firstName":"Susan","middleName":"","lastName":"Naikooba","suffix":""},{"id":298627007,"identity":"c27710d2-bba5-4b5c-9940-17f723dc712c","order_by":5,"name":"Faizo Ssekindi","email":"","orcid":"","institution":"Infectious Diseases Institute","correspondingAuthor":false,"prefix":"","firstName":"Faizo","middleName":"","lastName":"Ssekindi","suffix":""},{"id":298627010,"identity":"5e207511-3826-4ac9-8bcd-16f6948619c5","order_by":6,"name":"Esther Nasuuna","email":"","orcid":"","institution":"Infectious Diseases Institute","correspondingAuthor":false,"prefix":"","firstName":"Esther","middleName":"","lastName":"Nasuuna","suffix":""},{"id":298627011,"identity":"4e9511bc-f565-4fa7-9b2d-fa78f5bd821c","order_by":7,"name":"Pauline Byakika Kibwika","email":"","orcid":"","institution":"Makerere University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Pauline","middleName":"Byakika","lastName":"Kibwika","suffix":""},{"id":298627012,"identity":"e66e7152-a904-46a4-b521-67f6ea8ffc54","order_by":8,"name":"Barbara Castelnuovo","email":"","orcid":"","institution":"Infectious Diseases Institute","correspondingAuthor":false,"prefix":"","firstName":"Barbara","middleName":"","lastName":"Castelnuovo","suffix":""}],"badges":[],"createdAt":"2024-05-03 12:41:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4364155/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4364155/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56409062,"identity":"366cb39c-ec75-4c87-933e-c26782fdf77e","added_by":"auto","created_at":"2024-05-13 19:52:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":13869,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMedian estimated GFR of people aged ≥60 years living with and without HIV in Uganda.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4364155/v1/82c1955fa3678b7f4cec487b.png"},{"id":56409063,"identity":"ae3ee993-14d3-42d8-bff0-07bb95d5e9cb","added_by":"auto","created_at":"2024-05-13 19:52:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":23289,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of kidney function impairment among PLWH and people without HIV stratified by disease stage (GFR categories).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4364155/v1/e0c11dc5a062b37957bfa18f.png"},{"id":57509896,"identity":"a72a529c-68fc-41c6-b0aa-fae9c8ab599a","added_by":"auto","created_at":"2024-05-31 16:18:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1136722,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4364155/v1/fd20e011-ddfd-4ac8-8228-4d4271f7defa.pdf"},{"id":56409064,"identity":"102b2dba-2274-44be-a689-117bd9de9498","added_by":"auto","created_at":"2024-05-13 19:52:37","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":162304,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarymaterialsubmittedbyAmutuhaireJudithSsemasaazi.doc","url":"https://assets-eu.researchsquare.com/files/rs-4364155/v1/392a18128e612a3cce365fb4.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Higher prevalence of kidney function impairment among older people living with HIV in Uganda","fulltext":[{"header":"Background","content":"\u003cp\u003eGlobally, access to antiretroviral therapy (ART) has averted at least 20\u0026nbsp;million HIV-related deaths over the last two decades; therefore, more people are aging with HIV [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Aging with HIV is associated with an increased risk of multimorbidity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] such as noncommunicable diseases (NCDs) including chronic kidney disease (CKD) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Nephron senescence is a recognized age-related change that eventually leads to a decline in kidney function and increases the risk of CKD in older persons [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In people living with HIV (PLWH); aging, chronic inflammation which persists during suppressive ART, and nephrotoxic ART such as tenofovir disoproxil fumarate (TDF) [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] converge to increase the risk of CKD by threefold [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Moreover, traditional risk factors for CKD such as diabetes mellitus and hypertension are more prevalent among PLWH [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Chronic kidney disease is a progressive disease that manifests with several indicators of kidney function impairment such as proteinuria [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Kidney failure is associated with increased morbidity, poor quality of life, and increased risk of death among PLWH [\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In low-income countries (LICs) such as Uganda, there is limited access to life-saving dialysis and kidney transplants to manage end-stage kidney disease(ESKD)/kidney failure and even when available, the costs exceed the average income for most patients [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Studies in the general population have documented the association of HIV with kidney disease in both low- and high-resource settings[\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], but there is a paucity of data documenting the excess prevalence of kidney function impairment in older PLWH in Uganda and sub-Saharan Africa. We sought to determine the additional prevalence of kidney function impairment in older people living with HIV compared to those without HIV in Uganda.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional study at the Infectious Diseases Institute (IDI) clinic in Mulago, Kampala, Uganda between April and August 2023. The IDI is an implementing partner for the President\u0026rsquo;s Emergency Plan for AIDS Relief (PEPFAR) with clinics in 18 districts in the country. The IDI flagship adult clinic at Mulago Hospital takes care of more than 8,000 HIV-infected patients and among these patients, more than 1000 are aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years.\u003c/p\u003e \u003cp\u003eWe consecutively enrolled PLWH aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years who were attending the HIV clinic at IDI and people without HIV recruited within a 2-kilometer distance of the same communities where the participating PLWH lived. The participants were recruited on a 1:1 ratio. We defined older people as those aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years per the United Nations definition [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Participants were excluded if they could not provide blood or urine samples for study measurements.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection tools and procedures\u003c/h2\u003e \u003cp\u003eWe collected data using an electronic structured questionnaire developed in Research Electronic Data Capture (REDCap) developed by Vanderbilt University [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. HIV-uninfected participants were counseled and tested for HIV before enrollment in the study.\u003c/p\u003e \u003cp\u003eFor each participant, we collected sociodemographic data (sex, age in years, education level, income status), and anthropological measurements (height in meters and weight in kg) using calibrated scales and calculated the body mass index in kg/m\u003csup\u003e2\u003c/sup\u003e. We collected information on comorbidities (diabetes mellitus, hypertension, other cardiovascular disease, liver disease, and others), prescriptions and over-the-counter drugs, past or present history of smoking, history of current alcohol use, and history of HIV, which included duration of ART, antiretroviral drugs (previous and current regimens), history and duration of TDF use, most recent viral load and CD4 count. We measured blood pressure using a standardized automated Omron M2 basic blood pressure monitor with consistent positioning (patients were seated upright with back and arm support). We took three readings and calculated the average. We measured fasting blood sugar in mmol/l using a point-of-care calibrated on-call plus glucometer manufactured by ACON laboratories, USA. For participants with no prior history of diabetes mellitus, a diagnosis of diabetes mellitus was made if one had elevated blood glucose (nonfasting\u0026thinsp;\u0026ge;\u0026thinsp;11.1 mmol/L or fasting\u0026thinsp;\u0026ge;\u0026thinsp;7 mmol/L) in the presence of symptoms. If elevated values were found in someone asymptomatic; a repeat fasting blood sugar was performed on a subsequent day to confirm the diagnosis.\u003c/p\u003e \u003cp\u003eWe collected an early morning urine sample from each patient for measurement of urine protein by dipstick urinalysis and a venous blood sample for measurement of serum creatinine. We defined kidney function impairment as an estimated glomerular filtration rate (eGFR)\u0026thinsp;\u0026lt;\u0026thinsp;60 mls/min per 1.73 m\u003csup\u003e2\u003c/sup\u003e with or without proteinuria on a dipstick urine test. This creatinine-based eGFR was calculated from the 2009 version of the chronic kidney disease epidemiology collaboration) (CKD-EPI) (CKD-EPI 2009) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] without correcting for race [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. We used the CKD-EPI 2009 which is widely used in clinical practice and a recent study showed it to perform better than the race-free creatinine-based CKD-EPI 2021 equation in sub-Saharan Africa [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. We categorized the stages of kidney function impairment by eGFR as stage 1: \u0026ge;90, stage 2:\u0026ge;60-\u0026lt;90, stage 3: \u0026ge;30-\u0026lt;60, stage 4:\u0026ge;15-\u0026lt;30 and stage 5: \u0026lt;15mls/min/1.73m\u003csup\u003e2\u003c/sup\u003e [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe measured proteinuria using Siemens Multistix GP Urine Test Strips and we categorized it as negative if no protein was detected or positive if at least trace protein (\u0026ge;\u0026thinsp;30mg/dl) was detected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eWe exported the data to STATA version 14 (Stata Corp LLC, College Station, TX).\u003c/p\u003e \u003cp\u003eWe reported the proportions of participants with kidney function impairment and proteinuria in both groups with 95% confidence interval (95% CI) and compared them with a chi-square test.\u003c/p\u003e \u003cp\u003eThe additional prevalence of kidney function impairment due to HIV was reported as a difference between the proportions in the group of PLWH and people without HIV with its 95% CI and a p-value corresponding to the z-statistic for testing the significance of a difference in proportions between two groups.\u003c/p\u003e \u003cp\u003eWe summarized other categorical variables as proportions and continuous variables as medians with interquartile ranges (IQR). Comparisons were based on a chi-square test for categorical variables otherwise Fisher\u0026rsquo;s exact test was used if any of the cells had\u0026thinsp;\u0026le;\u0026thinsp;5 observations. Comparisons for continuous variables were based on the Wilcoxon rank sum test.\u003c/p\u003e \u003cp\u003e We performed logistic regression with HIV as the main exposure and performed a stratified analysis by HIV status to study associations between various participant characteristics and kidney function impairment. We considered the level of significance at a p-value\u0026thinsp;\u0026le;\u0026thinsp;0.2 for bivariate analysis and p\u0026thinsp;\u0026le;\u0026thinsp;0.05 for multivariate analysis. We assessed confounding factors by comparing unadjusted and adjusted models, interactions using the loglikelihood ratio test, and goodness of fit of the model using the Hosmer\u0026ndash;Lemeshow test.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe enrolled 278 men and women aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years; 50% were PLWH and 51.8% were female.\u003c/p\u003e \u003cp\u003ePLWH and those living without HIV were similar except for smoking status, use of non-HIV related medications, prior history of tuberculosis, median systolic and diastolic blood pressure, body mass index, and proteinuria \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(\u003c/span\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of study participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall N\u0026thinsp;=\u0026thinsp;278\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePLWH, N\u0026thinsp;=\u0026thinsp;139\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo HIV, N\u0026thinsp;=\u0026thinsp;139\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Age in Years (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (63\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (64\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65 (62\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144 (51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (47.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134 (48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (52.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHighest level of education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone-primary level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116 (41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (41.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59 (42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esecondary-tertiary level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162 (58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82 (59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80 (57.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly household income in USDs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1 USD per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190 (68.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93 (66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97 (69.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1 USD per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e228 (82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (76.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122 (87.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol consumption\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197 (70.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104 (74.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93 (66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81 (29.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-HIV related comorbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo chronic illness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt least one chronic illness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e224 (80.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117 (84.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107 (77.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior diagnosis of Hypertension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117 (42.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (40.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161 (57.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (59.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior diagnosis of Diabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240 (86.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (85.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121 (87.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-HIV related medications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo chronic medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (27.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45 (32.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-hypertensives and anti-diabetes medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144 (51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (59.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59(21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior diagnosis of tuberculosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e219 (78.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (57.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e139 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Systolic Blood Pressure (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130 (121\u0026ndash;140)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128 (118\u0026ndash;134)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e134 (125\u0026ndash;150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Diastolic Blood Pressure (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 (75\u0026ndash;90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (73\u0026ndash;85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86 (77\u0026ndash;95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Fasting Blood Sugar (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.6 (4.9\u0026ndash;6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.6 (5.0-6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.4 (4.9-6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody mass index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18.5kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.5\u0026ndash;25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134 (48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81 (58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53 (38.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127 (45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49(35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProteinuria\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190 (68.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112 (80.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt least Trace proteinuria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIQR\u0026thinsp;=\u0026thinsp;interquartile range, PLWH\u0026thinsp;=\u0026thinsp;people living with HIV, USD\u0026thinsp;=\u0026thinsp;US dollars, others\u0026thinsp;=\u0026thinsp;other medication apart from those used to treat diabetes mellitus and hypertension.\u003c/p\u003e \u003cp\u003eAmong the 139 PLWH, the median CD4 count was 634 (IQR: 486\u0026ndash;917) cells/mm\u003csup\u003e3\u003c/sup\u003e, 5.8% had a detectable viral load (\u0026gt;\u0026thinsp;50 copies/ml), 80.6% had WHO clinical stage 3 or 4 disease at the start of ART, 95.7% had ever used TDF in their ART regimen, and 66.2% were currently on a TDF-based regimen \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(\u003c/span\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of PLWH in the study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV-related characteristics of older PLWH(N\u0026thinsp;=\u0026thinsp;139)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en, (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHO clinical stage at ART\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage I-II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (19.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage III-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112 (80.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian CD4 count (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e634 (486\u0026ndash;917)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eViral load\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDetectable (\u0026gt;\u0026thinsp;50 copies/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (5.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUndetectable (\u0026lt;\u0026thinsp;50 copies per ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131 (94.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent ART regimen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbacavir-based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (31.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTDF-based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (66.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEver used TDF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (4.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133 (95.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian number of years on TDF (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (4\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian number of years on ART (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (11\u0026ndash;18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eSupplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: PLWH\u0026thinsp;=\u0026thinsp;People living with HIV, TDF Tenofovir Disoproxil Fumarate, IQR\u0026thinsp;=\u0026thinsp;interquartile range\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBurden of kidney function impairment among study participants\u003c/h2\u003e \u003cp\u003eOverall, 23.0% (95% CI:18.4%-28.4%) had kidney function impairment. Among the PLWH, 33.1% (95% CI: 25.7%-41.4%) had kidney function impairment compared to 12.9% (95% CI: 8.3%-19.7%) among people without HIV, (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01); the additional prevalence of kidney function impairment in PLWH was 20.2% (95%CI: 10.6%-29.0%), p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003cp\u003eThe median GFR among PLWH versus people without HIV was 68.4 (IQR:56.9\u0026ndash;84.0) mls/min/1.73m2 versus 81.4 (IQR:71.4\u0026ndash;90.4) mls/min/1.73m2, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01 \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(\u003c/span\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe prevalence of kidney function impairment among PLWH and people without HIV varied by disease stage. PLWH constituted the majority in stage 3 and stage 4 of kidney function impairment \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(\u003c/span\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOlder PLWH had a higher prevalence of proteinuria 43.9% (95% CI:35.8\u0026ndash;52.3) versus 19.4% (95% CI: 13.6\u0026ndash;26.9) among older people without HIV, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003cp\u003eOlder age (OR\u0026thinsp;=\u0026thinsp;1.13, (95% CI: 1.07\u0026ndash;1.20), p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01), being female (OR\u0026thinsp;=\u0026thinsp;1.95, (95% CI: 1.06\u0026ndash;3.62), p-value\u0026thinsp;=\u0026thinsp;0.03) and living with HIV (OR\u0026thinsp;=\u0026thinsp;3.89, (95% CI: 2.04\u0026ndash;7.41), p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were associated with kidney function impairment at multivariate analysis \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(\u003c/span\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Additionally, in a stratified analysis by HIV status, a prior diagnosis of hypertension (OR\u0026thinsp;=\u0026thinsp;2.19, (95% CI:1.02\u0026ndash;4.67), p-value\u0026thinsp;=\u0026thinsp;0.04) was associated with kidney function impairment among older PLWH\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with kidney function impairment among people\u0026thinsp;\u0026ge;\u0026thinsp;60 years living with and without HIV\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic of participants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eKidney function impairment, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eBivariate Analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes: 64 (23%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo: 214 (77%),\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnadjusted OR (CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdjusted OR (CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Age in Years (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (65\u0026ndash;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65 (63\u0026ndash;69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.08 (1.00-1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.13 (1.07\u0026ndash;1.20)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (43.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (50.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.72 (0.84\u0026ndash;3.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.95 (1.06\u0026ndash;3.62)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol consumption\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (78.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147 (68.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.42 (0.17\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.63 (0.29\u0026ndash;1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHIV status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeople without HIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121 (56.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (71.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93 (43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.32 (1.81\u0026ndash;6.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.89 (2.04\u0026ndash;7.41)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior diagnosis of hypertension**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97 (45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (68.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117 (56.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.82 (1.00-3.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.73 (0.91\u0026ndash;3.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior diagnosis of TB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (67.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176 (82.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.26 (1.21\u0026ndash;4.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.31 (0.62\u0026ndash;2.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Diastolic Blood Pressure (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.5 (74.5\u0026ndash;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (75\u0026ndash;91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98 (0.95-1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02(0.63\u0026ndash;1.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-HIV related comorbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo chronic illness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt least one chronic illness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (89.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167 (78.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44 (0.19\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.52 (0.16\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEver used TDF*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (91.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 (97.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23 (0.04\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41 (0.07\u0026ndash;2.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Variables evaluated in a stratified analysis by HIV status only \u003csup\u003e**\u003c/sup\u003eVariable was significant at multivariate analysis in PLWH in a stratified analysis by HIV status with OR\u0026thinsp;=\u0026thinsp;2.19 (95%CI:1.02\u0026ndash;4.67) and p-value\u0026thinsp;=\u0026thinsp;0.04\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study shows that one-third of the aging Ugandan HIV population had kidney function impairment that was significantly higher than the prevalence in community-matched HIV-uninfected controls. Data documenting the burden of kidney function impairment in aging HIV populations come mostly from high-income countries [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Overall, we found a high prevalence of kidney function impairment among people aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years living with and without HIV in Uganda. Our data agree with studies that have shown that PLWH experience a high burden of kidney disease [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. HIV infection significantly increases the odds of kidney function impairment [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and various forms of HIV-associated nephropathy have been documented in previous research[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, our study demonstrated an excess burden of kidney function impairment among older PLWH compared to previous prevalences reported in the general population of PLWH in Uganda[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and other LICs[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These findings imply that there is a need for research and clinical care programs to evolve and prioritize kidney disease detection in the population of older PLWH.\u003c/p\u003e \u003cp\u003eThe prevalence of proteinuria in our study was at least two times higher in PLWH than in people without HIV. Other studies such as the AGE\u003csub\u003eh\u003c/sub\u003eIV cohort study [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] have shown that the burden of albuminuria is higher among people living with HIV than in people without HIV. However, our study reported higher estimates of proteinuria than what has been reported in non-African settings [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Previous studies have pointed to genetic risks for kidney injury such as the presence of the APOL1 gene which is unique to African populations and may account for racial disparities in the burden of CKD [\u003cspan additionalcitationids=\"CR41 CR42\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Proteinuria is a biomarker for kidney injury[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]; thus further research into context-specific risk factors for kidney disease is needed to understand the cause of kidney injury in older PLWH.\u003c/p\u003e \u003cp\u003eKidney disease is progressive; thus these findings of the excess prevalence of kidney function impairment and proteinuria may have implications for the health and survival of old PLWH in a country where there is limited access to life-saving therapies such as dialysis and renal transplants for kidney failure [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIncreasing age and female sex were significantly associated with kidney function impairment in both PLWH and people without HIV. These findings are consistent with previous studies from Uganda and Africa where increasing age and female sex were associated with kidney disease in both PLWH and people without HIV [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong older PLWH, a prior diagnosis of hypertension significantly increased the odds of kidney function impairment. Hypertension is a known traditional risk factor for CKD [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] and hypertensive nephrosclerosis is a well-recognized pathological process that eventually leads to kidney failure [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. A high prevalence of hypertension has been reported among aging PLWH [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] and the association of such traditional risk factors with CKD is documented in previous studies [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The implementation of blood pressure control programs in older PLWH and hypertension can benefit kidney health as the same approach has been shown to improve outcomes in other populations at risk of hypertension-related kidney injury such as people with cardiovascular diseases and diabetes mellitus[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study, HIV was the strongest significantly associated factor with kidney function impairment. Unlike other studies, we did not find an association between diabetes mellitus[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] and kidney function impairment, smoking [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], body mass index (BMI), socioeconomic status (monthly household income) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] or prior diagnosis of tuberculosis [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] as other studies did. Unlike these previous studies, in our study, fewer participants reported a history of smoking, and there were fewer diabetic patients. The monthly household income was not different between PLWH and people without HIV or between people with and without kidney function impairment. Likewise, the BMI was not different between people with and without kidney function impairment and all the people who had a previous diagnosis of tuberculosis were among PLWH.\u003c/p\u003e \u003cp\u003eAmong the PLWH in our study, only a small proportion, 2.2%, had CD4 less than 200 cells per ml and only 5.8% had detectable viral loads (\u0026gt;\u0026thinsp;50copies/ml). Almost all (95.7%) of our PLWH had ever used TDF. These proportions may explain the lack of association between these variables and kidney function impairment in our study although previous studies have shown a significant association[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. In our study, we observed higher prevalence of kidney function impairment in participants on abacavir-based regimens; most of the participants on abacavir-based regimens had previously been on TDF, but were switched over due to low eGFR.\u003c/p\u003e \u003cp\u003ePrevious studies on kidney function impairment among old people with HIV in Uganda and sub-Saharan Africa have not included uninfected controls. A strength of our study was a comparator group of older people without HIV from similar communities which allowed us to compare the characteristics between the two populations as well as the outcome and ascertain the excess prevalence of kidney function impairment attributable to HIV. A limitation of our study was that it was cross-sectional so we were unable to observe changes in kidney function over three months. In addition, we did not perform ultrasound scanning so we could not differentiate between acute and chronic kidney function impairment. We also used dipsticks to detect proteinuria which is a less specific method than the urine albumin to creatinine ratio (UACR).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThere is an excess prevalence of kidney function impairment amongolder PLWH with one-third of our aging PLWH having impaired kidney function. In LICs, early ascertainment of kidney function in older PLWH should be prioritized with routine measurement of urine protein and kidney function. Furthermore, research into novel, cost-friendly biomarkers that could improve the early detection of CKD and its progression in HIV aging populations is needed to allow early intervention.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eAIDS:\u0026nbsp;\u003c/strong\u003eAcquired\u0026nbsp;Immunodeficiency\u0026nbsp;Syndrome\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eART:\u0026nbsp;\u003c/strong\u003eAntiretroviral\u0026nbsp;therapy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLICs\u003c/strong\u003e: Low-income countries\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCKD\u003c/strong\u003e: Chronic Kidney Disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCKD-EPI:\u0026nbsp;\u003c/strong\u003eChronic Kidney Disease Epidemiology Collaboration\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eESRD/ESKD:\u0026nbsp;\u003c/strong\u003eEnd-Stage\u0026nbsp;Renal\u0026nbsp;Disease/End-Stage\u0026nbsp;kidney disease/kidney failure\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eeGFR:\u0026nbsp;\u003c/strong\u003eEstimated\u0026nbsp;Glomerular\u0026nbsp;Filtration\u0026nbsp;Rate\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHIVAN:\u0026nbsp;\u003c/strong\u003eHIV Associated Nephropathy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHIV:\u0026nbsp;\u003c/strong\u003eHuman Immunodeficiency Virus\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIDI:\u0026nbsp;\u003c/strong\u003eInfectious Diseases Institute\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePLWH:\u0026nbsp;\u003c/strong\u003ePeople Living With HIV\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTDF:\u0026nbsp;\u003c/strong\u003eTenofovir disoproxil fumarate\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study was approved by the Makerere University\u0026nbsp;School\u0026nbsp;of\u0026nbsp;Medicine Research and Ethics\u0026nbsp;Committee (SOMREC) (approval number-Mak-SOMREC-2022-538)\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand\u0026nbsp;Uganda National Council of Science and Technology (UNCST) (approval number-HS2913ES.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll participants provided informed consent\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe de-identified data set will be available upon acceptance for publication of the manuscript with a request to the study team through the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003es\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch reported in this publication was supported by the National Institute Of Allergy And Infectious Diseases (NIAID), Eunice Kennedy Shriver National Institute Of Child Health \u0026amp; Human Development (NICHD), National Institute On Drug Abuse (NIDA), National Cancer Institute (NCI), and the National Institute of Mental Health (NIMH),\u0026nbsp;National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), Fogarty International Canter (FIC), National Heart, Lung, and Blood Institute (NHLBI),\u0026nbsp;\u0026nbsp;in accordance with the regulatory requirements of the National Institutes of Health under Award Number U01AI069911East Africa IeDEA Consortium. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe \u0026ldquo;Diagnosis and treatment of non-communicable diseases and geriatric syndromes in the HIV aging population in sub-Saharan Africa (HASA)\u0026rdquo; study, part of the EDCTP2 program supported by the European Union grant agreement number TMA2017GSF-1936.\u003c/p\u003e\n\u003cp\u003eThis\u0026nbsp;publication was supported by the Fogarty International Center of the National Institutes of Health under Award Number D43TW009771.\u0026nbsp;\u0026nbsp;The content is solely the authors\u0026apos; responsibility and does not necessarily represent the official views of the National Institutes of Health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAJS:\u0026nbsp;\u003c/strong\u003eConceptualization, protocol writing, data collection, organizing and analyzing the data, writing the original draft of the manuscript and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRK:\u0026nbsp;\u003c/strong\u003eConceptualization, protocol writing, supervision, manuscript review and editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYM:\u0026nbsp;\u003c/strong\u003eManuscript writing and editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePM:\u0026nbsp;\u003c/strong\u003eConceptualization, manuscript review and editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSN:\u0026nbsp;\u003c/strong\u003eData collection and curation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFS:\u0026nbsp;\u003c/strong\u003eData collection and curation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEN:\u0026nbsp;\u003c/strong\u003eManuscript writing and editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePBK:\u0026nbsp;\u003c/strong\u003eConceptualization, supervision, manuscript review and editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBC:\u0026nbsp;\u003c/strong\u003eConceptualization, acquisition of funding, supervision, writing and editing the manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eUNAIDS, The path that ends AIDS: UNAIDS Global AIDS Update 2023. Geneva: Joint United Nations Programme on HIV/AIDS; 2023. Licence: CC BY-NC-SA 3.0 IGO. 2023.\u003c/li\u003e\n\u003cli\u003eGuaraldi, G., et al., Aging with HIV vs. HIV Seroconversion at Older Age: A Diverse Population with Distinct Comorbidity Profiles. PLOS ONE, 2015. \u003cstrong\u003e10\u003c/strong\u003e(4): p. e0118531.\u003c/li\u003e\n\u003cli\u003eHaregu, T.N., et al., Epidemiology of comorbidity of HIV/AIDS and non-communicable diseases in developing countries: a systematic review. J Glob Health Care Syst, 2012. \u003cstrong\u003e2\u003c/strong\u003e(1): p. 1-12.\u003c/li\u003e\n\u003cli\u003eHirschhorn, L.R., et al., Cancer and the \u0026lsquo;other\u0026rsquo;noncommunicable chronic diseases in older people living with HIV/AIDS in resource-limited settings: a challenge to success. Aids, 2012. \u003cstrong\u003e26\u003c/strong\u003e: p. S65-S75.\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Sullivan, E.D., J. Hughes, and D.A. Ferenbach, Renal Aging: Causes and Consequences. Journal of the American Society of Nephrology, 2017. \u003cstrong\u003e28\u003c/strong\u003e(2): p. 407-420.\u003c/li\u003e\n\u003cli\u003eKlatt, N.R., et al., Immune activation and HIV persistence: implications for curative approaches to HIV infection. Immunol Rev, 2013. \u003cstrong\u003e254\u003c/strong\u003e(1): p. 326-42.\u003c/li\u003e\n\u003cli\u003eHamzah, L., et al., Treatment-limiting renal tubulopathy in patients treated with tenofovir disoproxil fumarate. Journal of Infection, 2017. \u003cstrong\u003e74\u003c/strong\u003e(5): p. 492-500.\u003c/li\u003e\n\u003cli\u003eIslam, F.M., et al., Relative risk of renal disease among people living with HIV: a systematic review and meta-analysis. BMC Public Health, 2012. \u003cstrong\u003e12\u003c/strong\u003e(1): p. 234.\u003c/li\u003e\n\u003cli\u003eHeron, J.E., C.I. Bagnis, and D.M. Gracey, Contemporary issues and new challenges in chronic kidney disease amongst people living with HIV. AIDS Research and Therapy, 2020. \u003cstrong\u003e17\u003c/strong\u003e(1): p. 11.\u003c/li\u003e\n\u003cli\u003eLiu, D. and L.-L. Lv, New understanding on the role of proteinuria in progression of chronic kidney disease. Renal Fibrosis: Mechanisms and Therapies, 2019: p. 487-500.\u003c/li\u003e\n\u003cli\u003eSarfo, F.S., et al., High prevalence of renal dysfunction and association with risk of death amongst HIV-infected Ghanaians. Journal of Infection, 2013. \u003cstrong\u003e67\u003c/strong\u003e(1): p. 43-50.\u003c/li\u003e\n\u003cli\u003eRyom, L., et al., Serious clinical events in HIV-positive persons with chronic kidney disease. AIDS, 2019. \u003cstrong\u003e33\u003c/strong\u003e(14): p. 2173-2188.\u003c/li\u003e\n\u003cli\u003eMat\u0026iacute;as-Garc\u0026iacute;a, P.R., et al., DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function. Clinical Epigenetics, 2021. \u003cstrong\u003e13\u003c/strong\u003e(1): p. 121.\u003c/li\u003e\n\u003cli\u003eLegrand, K., et al., Perceived Health and Quality of Life in Patients With CKD, Including Those With Kidney Failure: Findings From National Surveys in France. American Journal of Kidney Diseases, 2020. \u003cstrong\u003e75\u003c/strong\u003e(6): p. 868-878.\u003c/li\u003e\n\u003cli\u003eKalyesubula, R., U.C. Brewster, and G. Kansiime, Global Dialysis Perspective: Uganda. Kidney360, 2022.\u003c/li\u003e\n\u003cli\u003eKalyesubula, R., et al., Nephrology in Uganda. Nephrology Worldwide, 2021: p. 75-83.\u003c/li\u003e\n\u003cli\u003eKabor\u0026eacute;, N.F., et al., Chronic kidney disease and HIV in the era of antiretroviral treatment: findings from a 10-year cohort study in a west African setting. BMC Nephrology, 2019. \u003cstrong\u003e20\u003c/strong\u003e(1): p. 155.\u003c/li\u003e\n\u003cli\u003eFiseha, T. and A. Gebreweld, Renal function in a cohort of HIV-infected patients initiating antiretroviral therapy in an outpatient setting in Ethiopia. PLOS ONE, 2021. \u003cstrong\u003e16\u003c/strong\u003e(1): p. e0245500.\u003c/li\u003e\n\u003cli\u003ePetersen, N., et al., Prevalence of impaired renal function in virologically suppressed people living with HIV compared with controls: the Copenhagen Comorbidity in HIV Infection (COCOMO) study*. HIV Medicine, 2019. \u003cstrong\u003e20\u003c/strong\u003e(10): p. 639-647.\u003c/li\u003e\n\u003cli\u003eAbd ElHafeez, S., et al., Prevalence and burden of chronic kidney disease among the general population and high-risk groups in Africa: a systematic review. BMJ open, 2018. \u003cstrong\u003e8\u003c/strong\u003e(1): p. e015069.\u003c/li\u003e\n\u003cli\u003eUNFPA, Ageing in the Twenty-First Century: A Celebration and A Challenge. United Nations Population Fund (UNFPA), New York, and HelpAge International, London.2012. 2012.\u003c/li\u003e\n\u003cli\u003eKowal, P. and J. Dowd, Definition of an older person. Proposed working definition of an older person in Africa for the MDS Project. 2001.\u003c/li\u003e\n\u003cli\u003ePatridge, E.F. and T.P. Bardyn, Research electronic data capture (REDCap). Journal of the Medical Library Association: JMLA, 2018. \u003cstrong\u003e106\u003c/strong\u003e(1): p. 142.\u003c/li\u003e\n\u003cli\u003eLevey, A.S., et al., A new equation to estimate glomerular filtration rate. Ann Intern Med, 2009. \u003cstrong\u003e150\u003c/strong\u003e(9): p. 604-12.\u003c/li\u003e\n\u003cli\u003eShi, J., et al., Calculating estimated glomerular filtration rate without the race correction factor: Observations at a large academic medical system. Clinica Chimica Acta, 2021. \u003cstrong\u003e520\u003c/strong\u003e: p. 16-22.\u003c/li\u003e\n\u003cli\u003eZingano, C.P., et al., 2009 CKD-EPI glomerular filtration rate estimation in Black individuals outside the United States: a systematic review and meta-analysis. Clinical Kidney Journal, 2022. \u003cstrong\u003e16\u003c/strong\u003e(2): p. 322-330.\u003c/li\u003e\n\u003cli\u003eFabian, J., et al., Measurement of kidney function in Malawi, South Africa, and Uganda: a multicentre cohort study. Lancet Glob Health, 2022. \u003cstrong\u003e10\u003c/strong\u003e(8): p. e1159-e1169.\u003c/li\u003e\n\u003cli\u003eLevey, A.S., et al., Nomenclature for kidney function and disease\u0026mdash;executive summary and glossary from a Kidney Disease: Improving Global Outcomes (KDIGO) consensus conference. European Heart Journal, 2020. \u003cstrong\u003e41\u003c/strong\u003e(48): p. 4592-4598.\u003c/li\u003e\n\u003cli\u003eHeron, J.E., et al., The prevalence and risk of non-infectious comorbidities in HIV-infected and non-HIV infected men attending general practice in Australia. PloS one, 2019. \u003cstrong\u003e14\u003c/strong\u003e(10): p. e0223224.\u003c/li\u003e\n\u003cli\u003eGlaser, N., et al., The prevalence of renal impairment in individuals seeking HIV testing in Urban Malawi. BMC Nephrology, 2016. \u003cstrong\u003e17\u003c/strong\u003e(1): p. 186.\u003c/li\u003e\n\u003cli\u003eMuiru, A.N., et al., The epidemiology of chronic kidney disease (CKD) in rural East Africa: A population-based study. PLOS ONE, 2020. \u003cstrong\u003e15\u003c/strong\u003e(3): p. e0229649.\u003c/li\u003e\n\u003cli\u003ePenner, J., et al., High rates of kidney impairment among older people (\u0026ge; 60 years) living with HIV on first-line antiretroviral therapy at screening for a clinical trial in Kenya. PLOS ONE, 2023. \u003cstrong\u003e18\u003c/strong\u003e(6): p. e0285787.\u003c/li\u003e\n\u003cli\u003eWyatt, C.M., Kidney disease and HIV infection. Topics in antiviral medicine, 2017. \u003cstrong\u003e25\u003c/strong\u003e(1): p. 13.\u003c/li\u003e\n\u003cli\u003eKansiime, S., D. Mwesigire, and H. Mugerwa, Prevalence of non-communicable diseases among HIV positive patients on antiretroviral therapy at joint clinical research centre, Lubowa, Uganda. PLOS ONE, 2019. \u003cstrong\u003e14\u003c/strong\u003e(8): p. e0221022.\u003c/li\u003e\n\u003cli\u003eNyende, L., et al., Prevalence of renal dysfunction among HIV infected patients receiving Tenofovir at Mulago: a cross-sectional study. BMC nephrology, 2020. \u003cstrong\u003e21\u003c/strong\u003e: p. 1-6.\u003c/li\u003e\n\u003cli\u003eWyatt, C.M., et al., Prevalence of Kidney Disease in HIV-Infected and Uninfected Rwandan Women. PLOS ONE, 2011. \u003cstrong\u003e6\u003c/strong\u003e(3): p. e18352.\u003c/li\u003e\n\u003cli\u003eEkrikpo, U.E., et al., Chronic kidney disease in the global adult HIV-infected population: A systematic review and meta-analysis. PLOS ONE, 2018. \u003cstrong\u003e13\u003c/strong\u003e(4): p. e0195443.\u003c/li\u003e\n\u003cli\u003eKooij, K.W., et al., Higher Prevalence and Faster Progression of Chronic Kidney Disease in Human Immunodeficiency Virus\u0026ndash;Infected Middle-Aged Individuals Compared With Human Immunodeficiency Virus\u0026ndash;Uninfected Controls. The Journal of Infectious Diseases, 2017. \u003cstrong\u003e216\u003c/strong\u003e(6): p. 622-631.\u003c/li\u003e\n\u003cli\u003eBarzilay, J.I., et al., Hospitalization Rates in Older Adults With Albuminuria: The Cardiovascular Health Study. The Journals of Gerontology: Series A, 2020. \u003cstrong\u003e75\u003c/strong\u003e(12): p. 2426-2433.\u003c/li\u003e\n\u003cli\u003eKasembeli, A.N., et al., APOL1 risk variants are strongly associated with HIV-associated nephropathy in black South Africans. Journal of the American Society of Nephrology, 2015. \u003cstrong\u003e26\u003c/strong\u003e(11): p. 2882-2890.\u003c/li\u003e\n\u003cli\u003eBehar, D.M., et al., Absence of APOL1 risk variants protects against HIV-associated nephropathy in the Ethiopian population. American journal of nephrology, 2011. \u003cstrong\u003e34\u003c/strong\u003e(5): p. 452-459.\u003c/li\u003e\n\u003cli\u003eElliott, M.D., et al., Clinical and genetic characteristics of CKD patients with high-risk APOL1 genotypes. The Journal of the American Society of Nephrology, 2023. \u003cstrong\u003e34\u003c/strong\u003e(5): p. 909-919.\u003c/li\u003e\n\u003cli\u003eFriedman, D.J. and M.R. Pollak, APOL1 Nephropathy: From Genetics to Clinical Applications. Clinical Journal of the American Society of Nephrology, 2021. \u003cstrong\u003e16\u003c/strong\u003e(2): p. 294-303.\u003c/li\u003e\n\u003cli\u003eKalyesubula, R., et al., Kidney disease in Uganda: a community based study. BMC nephrology, 2017. \u003cstrong\u003e18\u003c/strong\u003e(1): p. 1-9.\u003c/li\u003e\n\u003cli\u003eMwemezi, O., et al., Renal Dysfunction among HIV-Infected Patients on Antiretroviral Therapy in Dar es Salaam, Tanzania: A Cross-Sectional Study. International Journal of Nephrology, 2020. \u003cstrong\u003e2020\u003c/strong\u003e: p. 8378947.\u003c/li\u003e\n\u003cli\u003eLuyckx, V.A., et al., Reducing major risk factors for chronic kidney disease. Kidney International Supplements, 2017. \u003cstrong\u003e7\u003c/strong\u003e(2): p. 71-87.\u003c/li\u003e\n\u003cli\u003eCostantino, V.V., et al., Molecular mechanisms of hypertensive nephropathy: renoprotective effect of losartan through Hsp70. Cells, 2021. \u003cstrong\u003e10\u003c/strong\u003e(11): p. 3146.\u003c/li\u003e\n\u003cli\u003eGuaraldi, G., J. Milic, and C. Mussini, Aging with HIV. Current HIV/AIDS Reports, 2019. \u003cstrong\u003e16\u003c/strong\u003e: p. 475-481.\u003c/li\u003e\n\u003cli\u003eAjayi, S.O., et al., Prevalence of Chronic Kidney Disease as a Marker of Hypertension Target Organ Damage in Africa: A Systematic Review and Meta-Analysis. International Journal of Hypertension, 2021. \u003cstrong\u003e2021\u003c/strong\u003e: p. 7243523.\u003c/li\u003e\n\u003cli\u003eChen, T.K., et al., Reducing Kidney Function Decline in Patients With CKD: Core Curriculum 2021. American Journal of Kidney Diseases, 2021. \u003cstrong\u003e77\u003c/strong\u003e(6): p. 969-983.\u003c/li\u003e\n\u003cli\u003eEne-Iordache, B., et al., Chronic kidney disease and cardiovascular risk in six regions of the world (ISN-KDDC): a cross-sectional study. The Lancet Global Health, 2016. \u003cstrong\u003e4\u003c/strong\u003e(5): p. e307-e319.\u003c/li\u003e\n\u003cli\u003eAlthoff, K.N., et al., Contributions of traditional and HIV-related risk factors on non-AIDS-defining cancer, myocardial infarction, and end-stage liver and renal diseases in adults with HIV in the USA and Canada: a collaboration of cohort studies. The lancet HIV, 2019. \u003cstrong\u003e6\u003c/strong\u003e(2): p. e93-e104.\u003c/li\u003e\n\u003cli\u003eSafaa, M.M., Diabetes Mellitus Control and Chronic Kidney Disease. American Journal of Chemistry and Pharmacy, 2023. \u003cstrong\u003e2\u003c/strong\u003e(2): p. 9-14.\u003c/li\u003e\n\u003cli\u003eBetzler, B.K., et al., Association between Body Mass Index and Chronic Kidney Disease in Asian Populations: A Participant-level Meta-Analysis. Maturitas, 2021. \u003cstrong\u003e154\u003c/strong\u003e: p. 46-54.\u003c/li\u003e\n\u003cli\u003eHodel, N.C., et al., The epidemiology of chronic kidney disease and the association with non-communicable and communicable disorders in a population of sub-Saharan Africa. PLOS ONE, 2018. \u003cstrong\u003e13\u003c/strong\u003e(10): p. e0205326.\u003c/li\u003e\n\u003cli\u003eCanney, M., et al., Incidence of and Risk Factors for Active Tuberculosis Disease in Individuals With Glomerular Disease: A Canadian Cohort Study. American Journal of Kidney Diseases, 2023. \u003cstrong\u003e82\u003c/strong\u003e(6): p. 725-736.\u003c/li\u003e\n\u003cli\u003eRyom, L., A. Mocroft, and J. Lundgren, HIV therapies and the kidney: some good, some not so good? Current HIV/AIDS Reports, 2012. \u003cstrong\u003e9\u003c/strong\u003e(2): p. 111-120.\u003c/li\u003e\n\u003cli\u003eAchhra, A.C., et al., Chronic kidney disease and antiretroviral therapy in HIV-positive individuals: recent developments. Current HIV/AIDS Reports, 2016. \u003cstrong\u003e13\u003c/strong\u003e(3): p. 149-157.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Older persons, kidney function impairment, sub-Saharan Africa","lastPublishedDoi":"10.21203/rs.3.rs-4364155/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4364155/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePeople living with HIV (PLWH) are at risk of kidney function impairment due to HIV-related inflammation, antiretroviral therapy (ART), diabetes mellitus, and hypertension. Older persons may experience a higher burden of chronic kidney disease (CKD) as kidney function declines with increasing age. There is a paucity of data comparing the prevalence of kidney function impairment in older PLWH to that in HIV-uninfected people in sub-Saharan Africa.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional study among people aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years living with and without HIV in Kampala, Uganda who were matched 1:1 by community location. We collected data on sociodemographics, comorbidities, and HIV-related clinical characteristics. We defined kidney function impairment as an estimated glomerular filtration rate(eGFR)\u0026thinsp;\u0026lt;\u0026thinsp;60mls/min/1.73m\u003csup\u003e2\u003c/sup\u003e with or without proteinuria. We constructed multivariable logistic regression models to study associations between participant characteristics and kidney function impairment.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe enrolled 278 people (median age 66 years); 50% were PLWH, and 51.8% were female. Overall, the prevalence of kidney function impairment was 23.0% (95% CI:18.4%-28.4%); 33.1% (95% CI: 25.7%-41.4%) versus 12.9% (95% CI: 8.3%-19.7%) among people living with and without HIV (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The prevalence of proteinuria among PLWH versus people without HIV was 43.9% (95% CI:35.8%-52.3%) versus 19.4% (95% CI:13.6%-26.9%) p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Living with HIV (OR\u0026thinsp;=\u0026thinsp;3.89(95% CI: 2.04\u0026ndash;7.41), p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01), older age (OR\u0026thinsp;=\u0026thinsp;1.13, (95% CI:1.07\u0026ndash;1.20), p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01), female sex (OR\u0026thinsp;=\u0026thinsp;1.95, (95% CI:1.06\u0026ndash;3.62), p-value\u0026thinsp;=\u0026thinsp;0.03) and a prior diagnosis of hypertension (OR\u0026thinsp;=\u0026thinsp;2.19(95% CI:1.02\u0026ndash;4.67), p-value\u0026thinsp;=\u0026thinsp;0.04) were significantly associated with kidney function impairment.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHIV infection is strongly associated with kidney function impairment among older PLWH. Prioritizing routine measurements of kidney function and proteinuria in older PLWH will enable early detection and institution of measures to reduce the progression of kidney disease.\u003c/p\u003e","manuscriptTitle":"Higher prevalence of kidney function impairment among older people living with HIV in Uganda","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-13 19:52:27","doi":"10.21203/rs.3.rs-4364155/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dda574f1-228f-4602-8f78-e6193088d85d","owner":[],"postedDate":"May 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-31T16:10:51+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-13 19:52:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4364155","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4364155","identity":"rs-4364155","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}