Prevalence of non-communicable diseases among individuals with HIV infection by antiretroviral therapy status in Dar es Salaam, Tanzania

Irene Kato; Basil Tumaini; Kisali Pallangyo

doi:10.1371/journal.pone.0235542

. 2020 Jul 9;15(7):e0235542. doi: 10.1371/journal.pone.0235542

Prevalence of non-communicable diseases among individuals with HIV infection by antiretroviral therapy status in Dar es Salaam, Tanzania

Irene Kato ^1,^‡,^*, Basil Tumaini ^1,^‡, Kisali Pallangyo ¹

Editor: Kwasi Torpey²

PMCID: PMC7347196 PMID: 32645054

Abstract

Background

Long-term antiretroviral therapy has modified the clinical course of HIV infection to a chronic condition associated with increased risk of developing non-communicable diseases (NCDs). Information is scant, from sub-Saharan Africa, on the prevalence of NCDs and associated factors among individuals on ART.

Methodology

We consecutively enrolled individuals with HIV infection who were ART naïve and those on ART for ≥5 years (LTART) attending health facilities in Dar es Salaam. Participant's blood pressure, anthropometric measurements, and fasting blood glucose were recorded. Participants with impaired fasting blood glucose underwent an oral glucose tolerance test. A venous blood sample was sent to the lab for biochemical tests. Chi-square test was used to compare proportions, Poisson regression with robust standard errors was used to determine associations between variables.

Results

Overall, 612 individuals with HIV infection were enrolled, half of whom were ART naïve. Females comprised 71.9% and 68.0% of participants in the LTART and ART naïve study arms, respectively, p = 0.290. The mean age (±SD) was 44.9 ± 12.7 years and 37.5 ± 11.8 years among LTART and ART naïve participants, respectively, p<0.001. Hypertension was documented in 25.2% in those on LTART compared to 6.9% among ART naïve subjects, p<0.001. Impaired glucose tolerance was found in 22.9% and 4.6% among LTART compared to ART naïve subjects, p<0.001. Diabetes mellitus was detected in 17.0% of those on LTART compared to 3.9% ART naïve participants, p<0.001. Hypercholesterolemia was found in 30.4% of individuals on LTART compared to 16.7% of ART naïve subjects, p<0.001, and hypertriglyceridemia was found in 16.0% of participants on LTART compared to 9.5% of ART naïve, p = 0.015. LTART use, age ≥40 years, history of smoking, and body mass index were independently associated with NCDs.

Conclusion

Hypertension, impaired glucose tolerance, diabetes mellitus, hypercholesterolemia, and hypertriglyceridemia were associated with long-term use of antiretroviral drugs.

Introduction

HIV has affected parts of the world variably with sub-Saharan Africa having about two-thirds of the total number of people living with HIV (PLWHIV). The introduction of antiretroviral therapy has changed the natural history of HIV infection with a decrease in mortality due to AIDS-related illnesses, opportunistic infections and malignancies [1].

HIV disease and antiretroviral therapy (ART) have been shown to increase the risk of metabolic syndrome predisposing to type 2 diabetes mellitus, cardiovascular and renal diseases [2]. Consequently, in addition to the usual risk factors for non-communicable diseases (NCDs) seen in the general population, PLWHIV may have additional risks. Endothelial dysfunction, as well as metabolic disorders associated with HIV-related chronic inflammation and the use of antiretroviral drugs that cause toxicity through direct or indirect effects, may be responsible for the observed excess risk of NCDs [2,3].

With over 35 million people living and aging with HIV, a new global challenge of addressing morbidity and mortality due to NCDs in PLWHIV is looming [4]. NCDs tend to increase with age and are prevalent in PLWHIV where HIV disease and its treatment are being implicated in the causation. The use of effective ART has led to significant increases in the survival and quality of life for people with HIV giving an average life expectancy increase of approximately 13 years in the western countries [5].

Information is scant, from sub-Saharan Africa, on the prevalence of NCDs among individuals on long-term ART including their risk factor profile. Such information is vital to inform clinicians, hospital managers and policymakers in the provision of optimum care for individuals with HIV infection as well as maintain the gains already made in the fight against HIV.

This study aimed at determining the prevalence of selected NCDs and associated factors among individuals with HIV infection on long-term ART (≥5 years) compared to ART naïve subjects receiving health care facility services in Dar es Salaam.

Materials and methods

Ethics statement

Ethical approval for the study was obtained from the Research and Publication Committee of Muhimbili University of Health and Allied Sciences. Permission to conduct the study was obtained from Muhimbili National Hospital administration as well as Kinondoni and Temeke Municipal councils. Written informed consent was obtained from all participants before enrolment. The confidentiality of patient information was ensured.

Study design and population

This was an analytical cross-sectional study among individuals with HIV infection in Dar es Salaam, a city with a population of over 4 million people. It was conducted from September to December 2017, at HIV care and treatment clinics (CTC) and provider-initiated testing and counseling (PITC) rooms of 4 centers: Muhimbili National Hospital–a tertiary referral hospital; Mwananyamala hospital and Temeke hospital–regional referral hospitals; and Mbagala hospital–a district hospital. Each of the four sites serves 60–200 individuals with HIV infection daily, irrespective of their specific geographical residence within the Dar es Salaam region. We consecutively enrolled registered individuals with HIV infection aged ≥18 years, who were either newly diagnosed and ART naïve or had been on ART for ≥5 years. Individuals with HIV infection who were pregnant were excluded.

Sample size estimation

To determine the minimum sample size required, we used the formula for comparing two proportions, n = (Z_α/2+Z_β)²*(p₁(1-p₁) + p₂(1-p₂))/(p₁-p₂)², where, Z_α/2 is the critical value of the Normal distribution at α/2 (for a confidence level of 95%, α is 0.05 and the critical value is 1.96), Z_β is the critical value of the Normal distribution at β (for a power of 80%, β is 0.2 and the critical value is 0.84) and p₁ and p₂ are the expected sample proportions of the two groups or proportions observed in a similar study. We used p₁ = 32% and p₂ = 22%, basing the estimates on the prevalence of hypertension in people with HIV infection on ART versus ART naïve, respectively, in a study conducted in Dar es Salaam and Mbeya regions in Tanzania [6]. Thus, n = 306 for each group, giving a total sample size of 612.

Data collection

We interviewed participants to obtain socio-demographic characteristics including sex, age, marital status, occupation, and educational level; non-communicable disease risk factors such as smoking status and alcohol consumption; as well as the past medical history of hypertension and diabetes mellitus. Participants’ CTC cards were reviewed to obtain information on ART status, type of ART, and duration on ART. The level of physical activity was assessed using the Short Last 7 days Self-administered Format of the International Physical Activity Questionnaire [7].

Observing the procedure for office blood pressure measurement outlined in the European Society of Hypertension/European Society of Cardiology Guidelines for the management of arterial hypertension, we measured blood pressure (BP) using a standardized digital BP machine (AD Medical Inc.), having seated a participant comfortably for 5 minutes. In a seating patient, measurements were made in both arms; the 1st and 5th Korotkoff sounds were used to identify the systolic and diastolic blood pressures, respectively. Two BP readings spaced 1–2 min apart and an additional measurement if the first two were quite different was taken; the average of the last two BP readings was recorded, and the measurement from the arm with higher BP considered for analysis [8].

In a patient wearing no shoes, we measured height with a stadiometer and recorded to the nearest 0.5 centimeters, and weight using a SECA weighing scale, recording to the nearest 0.5 kilograms. Body mass index was then computed, the interpretation of which was adapted from WHO [9].

Individuals who had been in a fasting state for the past ≥8 hours had fasting blood glucose (FBG) and laboratory investigations done on the same day of enrollment. Participants not in a fasting state were requested to come in a fasting state the next day for FBG and other laboratory investigations. A capillary fingertip blood sample was obtained from each patient for FBG determination and two-hour postprandial blood glucose was assessed for participants with impaired FBG after giving 75mg of oral glucose mixed with 200mls of water. GlucoPlus^TM machines and check strips were used for blood glucose determination. Diabetes mellitus was regarded as fasting plasma glucose (FPG) level ≥7 mmol/L or a 2-h plasma glucose (PG) level ≥11.1 mmol/L during the postprandial blood glucose test or a previously diagnosed diabetes mellitus; impaired fasting glucose as FPG levels between 5.6 and 6.9 mmol/L; and impaired glucose tolerance as 2-h postprandial PG levels between 7.8 and 11.0 mmol/L, as per the American Diabetes Association diagnostic criteria [10].

A 5ml venous blood sample was drawn from each patient and put in a red-toped vacutainer. Samples were stored in a cool box and transported to the MUHAS Clinical Research laboratory at the end of the day where biochemical tests were done on the same day using the COBAS INTEGRA® 400 plus analyzer (Roche Diagnostics), observing standard operating procedures. Factors analyzed included serum creatinine, total cholesterol, triglycerides, HDL cholesterol, and LDL cholesterol. Serum creatinine was used to estimate the glomerular filtration rate using the MDRD equation [11] and values <60ml/min/1.73m² were regarded as renal dysfunction [12].

Statistical methods

Data was entered into EpiData version 3.1; IBM® SPSS® Statistics version 26 and Stata® version 13.0 were used for analysis. Categorical variables were summarized into frequencies and proportions. Differences in proportions across groups were compared using the Chi-square test. Continuous variables were summarized into means and standard deviations and compared between individuals with HIV infection on long-term ART and ART naïve using the student’s t-test. We employed Poisson regression with robust standard errors to identify the association between variables and the diagnosis of hypertension, impaired glucose tolerance, diabetes mellitus, dyslipidemia, and renal dysfunction. Factors with p<0.2 in bivariate analysis were included in the multivariable analysis model. P-values <0.05 were considered statistically significant.

Results

A total of 612 individuals were enrolled, half of whom were on ART for ≥5 years, referred to as long-term ART (LTART), and the other half were ART naïve.

Socio-demographic and clinical characteristics of study participants

Table 1 summarizes the socio-demographic and clinical characteristics of the 612 individuals with HIV infection by ART status. Overall, female participants were 428 (69.9%), and by ART status, there were 220/306 (71.9%) and 208/306 (68%) in the LTART and ART naïve study groups respectively (p = 0.209). Participants aged ≥40 years were 74.8% (229/306) of those on LTART compared to 35.9% (110/306) among ART naïve subjects, p<0.001. There was no significant difference with regard to smoking in the two groups. Low-intensity physical activities were recorded in 94.1% (288/306) versus 78.8% (241/306) among ART naïve and those on LTART, respectively (p<0.001). Current alcohol use and being overweight or obese were more prevalent in LTART than ART-naive participants 33.0% (101/306) vs 22.5% (69/306), p = 0.004 and 57.2% (175/306) vs 28.4% (87/306), p<0.001, respectively (also see S1 Table).

Table 1. Comparison of socio-demographic and clinical characteristics of individuals with HIV infection on LTART with ART naïve.

Characteristic	Total N = 612	ART status		p-value
Characteristic	Total N = 612	Naïve306 (50.0%)	ART ≥5 years306 (50.0%)	p-value
Mean age ± SD (years)	41.2 ± 12.8	37.5 ± 11.8	44.9 ± 12.7	<0.001
Age groups (years)
<40	273 (44.6%)	196 (64.1%)	77 (25.2%)
≥40	339 (55.4%)	110 (35.9%)	229 (74.8%)	<0.001
Sex
Male	184 (30.1%)	98 (32.0%)	86 (28.1%)
Female	428 (69.9%)	208 (68.0%)	220 (71.9%)	0.290
Marital status
Single	174 (28.4%)	98 (32.0%)	76 (24.8%)
Ever married	438 (71.6%)	208 (68.0%)	230 (75.2%)	0.049
Education level
None	46 (7.5%)	33 (10.8%)	13 (4.2%)
Primary school	358 (58.5%)	203 (66.3%)	155 (50.7%)
Above primary school	208 (34.0%)	70 (22.9%)	138 (45.1%)	<0.001
Occupation
Not employed	171 (27.9%)	79 (25.8%)	92 (30.1%)
Employed	115 (18.8%)	37 (12.1%)	78 (25.5%)	<0.001
Self employed	326 (53.3%)	190 (62.1%)	136 (44.4%)
Smoking
No	583 (95.3%)	287 (93.8%)	296 (96.7%)
Yes	29 (4.7%)	19 (6.2%)	10 (3.3%)	0.087
Alcohol
No	442 (72.2%)	237 (77.5%)	205 (67.0%)
Yes	170 (27.8%)	69 (22.5%)	101 (33.0%)	0.004
Level of physical activity
Moderate /vigorous intensity	83 (13.6%)	18 (5.9%)	65 (21.2%)	<0.001
Low intensity	529 (86.4%)	288 (94.1%)	241 (78.8%)
Mean BMI (kg/m²)	24.8 ± 6.1	22.8 ± 4.8	26.9 ± 6.6	<0.001
BMI
Underweight/Normal	350 (57.2%)	219 (71.6%)	131 (42.8%)
Overweight/obesity	262 (42.8)	87 (28.4%)	175 (57.2%)	<0.001
Family history of HTN
No	552 (90.2%)	272 (88.9%)	280 (91.5%)
Yes	60 (9.8%)	34 (11.1%)	26 (8.5%)	0.277
Family history of DM
No	571 (93.3%)	285 (93.1%)	286 (93.5%)
Yes	41 (6.7%)	21 (6.9%)	20 (6.5%)	0.872

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ART: antiretroviral therapy; BMI: body mass index; DM: diabetes mellitus; HTN: hypertension.

NCDs among study subjects

As depicted in Table 2, hypertension was found in 6.9% (21/306), 95% CI: 4.0–9.7%, of ART naïve and 25.2% (77/306), 95% CI: 20.3–30.0%, among LTART study subjects, p<0.001. Of the 306 ART naïve subjects, 14 (4.6%), 95% CI: 2.2–6.9%, had impaired glucose tolerance compared to 22.9% (70/306), 95% CI: 18.2–27.6%, LTART study subjects, p<0.001. Likewise, 12 ART naïve subjects (3.9%), 95% CI: 1.7–6.1%, had diabetes mellitus compared to 52 (17.0%), 95% CI: 12.8–21.2% subjects on LTART, p<0.001. Hypercholesterolemia existed in 51 (16.7%), 95% CI: 12.5–20.9% of ART naïve subjects compared to 93 (30.4%), 95% CI: 25.2–35.6%, among participants on LTART, p<0.001. Hypertriglyceridemia was found in 29 (9.5%), 95% CI: 6.2–12.8%, of ART naïve subjects compared to 16.0%, 95% CI: 11.9–20.1%, of subjects on LTART, p = 0.015. Renal dysfunction was observed in 30 (4.9%), 95% CI: 3.2–6.6%, participants and was similar between individuals on LTART and ART naïve (also see S2 Table).

Table 2. Clinical and laboratory findings among 612 study subjects.

Variable	Total N = 612	ART status		p-value
Variable	Total N = 612	ART naïve n = 306	ART ≥5 years n = 306	p-value
Hypertension
Yes	98 (16.0%)	21 (6.9%)	77 (25.2%)	<0.001
No	514 (84.0%)	285 (93.1%)	229 (74.8%)
Impaired glucose tolerance
Yes	84 (13.7%)	14 (4.6%)	70 (22.9%)	<0.001
Other	528 (86.3%)	292 (95.4%)	236 (77.1%)
Diabetes mellitus
Yes	64 (10.5%)	12 (3.9%)	52 (17.0%)	<0.001
No	548 (89.5%)	294 (96.1%)	254 (83.0%)
Renal dysfunction
Yes	30 (4.9%)	17 (5.6%)	13 (4.2%)	0.454
No	582 (95.1%)	289 (94.4%)	293 (95.8%)
Hypercholesterolemia
Yes	144 (23.5%)	51 (16.7%)	93 (30.4%)	<0.001
No	468 (76.5%)	255 (83.3%)	213 (69.6%)
Hypertriglyceridemia
Yes	78 (12.7%)	29 (9.5%)	49 (16.0%)	0.015
No	534 (87.3%)	277 (90.5%)	257 (84.0%)
Low HDL cholesterol
Yes	158 (25.8%)	87 (28.4%)	71 (23.2%)	0.139
No	454 (74.2%)	219 (71.6%)	235 (76.8%)
High LDL cholesterol
Yes	157 (25.7%)	87 (28.4%)	70 (22.9%)	0.116
No	455 (74.3%)	219 (71.6%)	236 (77.1%)

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ART: antiretroviral therapy; HDL: high density lipoprotein; LDL: low density lipoprotein.

Association between established risk factors and NCDs among study subjects

Factors independently associated with hypertension, diabetes mellitus, impaired glucose tolerance, hypercholesterolemia, and hypertriglyceridemia among individuals with HIV infection were: use of ART for ≥5 years, adjusted PR 1.36, 95% CI: 1.13–1.65, p = 0.001; age ≥40 years, adjusted PR 2.04, 95% CI: 1.63–2.56, p<0.001; smoking, adjusted PR 0.45, 95% CI: 0.24–0.86, p = 0.016 and being overweight/obese, adjusted PR 1.52, 95% CI: 1.28–1.80, p<0.001; see Table 3 (also see S3 Table).

Table 3. Factors associated with NCDs among 612 individuals with HIV infection.

Variable	Total N = 612	NCDs^* n = 290	PR (95% CI)	p-value	Adjusted PR (95% CI)	p-value
ART status
Naïve	306	96 (31.4%)	1		1
≥5 years	306	194 (63.4%)	2.02 (1.68–2.44)	<0.001	1.36 (1.13–1.65)	0.001
Age group (years)
<40	273	70 (25.6%)	1		1
≥40	339	220 (64.9%)	2.53 (2.04–3.14)	<0.001	2.04 (1.63–2.56)	<0.001
Sex
Male	184	89 (48.4%)	1
Female	428	201 (47.0%)	0.97 (0.81–1.16)	0.748
Smoking status
Yes	29	6 (20.7%)	0.42 (0.21–0.87)	0.019	0.45 (0.24–0.86)	0.016
No	583	284 (48.7%)	1		1
Alcohol use
Yes	170	88 (51.8%)	1.13 (0.95–1.35)	0.168	0.95 (0.81–1.10)	0.494
No	442	202 (45.7%)	1		1
Physical activity
Low intensity	529	250 (47.3%)	1
Moderate/Vigorous	83	40 (48.2%)	1.02 (0.80–1.30)	0.873
BMI
Underweight/Normal	350	118 (33.7%)	1
Overweight/obesity	262	172 (65.6%)	1.95 (1.64–2.31)	<0.001	1.52 (1.28–1.80)	<0.001

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ART: antiretroviral therapy; BMI: body mass index; CI: confidence interval; NCDs: non-communicable diseases; PR: prevalence ratio.

* NCDs considered: hypertension, impaired glucose tolerance, diabetes mellitus, hypercholesterolemia, and hypertriglyceridemia.

Discussion

Females constituted over two-thirds of the study participants; there was no significant difference in the sex distribution between the two arms of the study. Female predominance has been a consistent finding in hospital-based HIV studies in Tanzania and elsewhere in Africa [6,13–16]. This may be explained by the higher HIV prevalence rates among females compared to males in the Tanzania general population and the fact that females have higher health-seeking behavior than males [17]. The mean age of the study participants on long-term ART (LTART) was higher than that of ART naïve participants. This observation is similar to reports from other African studies [6,15,16] and could partly be due to beneficial effects of ART use on life expectancy. Moderate/vigorous-intensity physical activities were significantly more prevalent among individuals on LTART than ART naïve, which may be because of implementing health advice regularly offered to individuals at Care and Treatment Clinics.

The prevalence of hypertension was significantly higher among individuals on LTART compared to ART naïve participants and is in-keeping with findings from other studies in Tanzania, Cameroon, and Italy [6,16,18,19]. Furthermore, the prevalence of hypertension was observed to increase with the duration of ART use. These findings are similar to those from a multicenter AIDS cohort study which demonstrated a link between the duration of ART and elevated blood pressure, suggesting that prolonged ART use was independently associated with the development of hypertension [20]. Indeed, higher prevalence rates of hypertension ranging from 44.4%-48.2% were reported from other studies [21–23]. The high prevalence of hypertension among adults with HIV infection on LTART is likely to be multifactorial. It is important to point out here that following primary infection by HIV, the body usually mounts a robust cellular and humoral immune response but rarely able to clear the virus. Consequently, a chronic state characterized by elevated levels of antigen-antibody immune complexes sets in. Inflammation is well recognized in the pathophysiology of hypertension [24]. Hypertension was also associated with being aged 40 years and above similar to findings from several other studies in Africa [6,16,25]. Loss of elasticity in arterial blood vessels occurs with increasing age and is an important factor in the development of high blood pressure [26].

The overall prevalence of impaired glucose tolerance (IGT) was 22.9% among subjects on long-term ART and 4.6% in ART naïve subjects (p<0.001). The estimated IGT prevalence among adults in the general population in Tanzania is 9.5% [27]. Consequently, the results of this study not only show high prevalence rates of IGT among individuals with HIV infection on ART but also show IGT rates increase with the duration of ART use. A study done in South Africa reported a prevalence of IGT of 3–4 fold among participants with HIV infection on ART compared to ART naïve participants [28]. Another study done in Mwanza Tanzania reported a 3.5-fold higher prevalence of IGT among ART experienced participants compared to ART naïve [29]. These findings affirm a strong association between ART use and increased prevalence of IGT. The increased rate of IGT among individuals with HIV infection on ART could be due to a number of factors. Such factors include HIV stress-induced hyperglycemia, type of ART used, and several other factors. We are not able to determine if any of these individuals with elevated IGT will develop diabetes mellitus in the future. Longitudinal studies may provide answers as to what proportion, if any, of individuals with ART use-related IGT go on to develop clinical diabetes mellitus.

The prevalence of diabetes mellitus (DM) was higher among subjects on LTART compared to the ART naïve group and was about 4-fold higher than the estimated prevalence among adults in the general population [27]. In a study conducted from CTC clinics in Dar es Salaam and Mbeya, Kagaruki et al reported prevalence rate of DM similar to that in the general adult population [6]. However, part of limitations of their study was poor turn-up of participants for follow-up biochemical tests including fasting blood glucose. Furthermore, their finding differs from most published data. The high prevalence of DM in our study is similar to reports from other studies [30–33]. A multicenter AIDS cohort study reported a fourfold increase in the prevalence of DM in HAART-exposed subjects [34]. The high prevalence of DM among individuals with HIV infection on LTART is most certainly multifactorial. ARTs such as protease inhibitors contribute to insulin resistance via a direct effect on insulin-mediated glucose transport leading to dysglycemia [35]. Because of ART use, survival among people with HIV infection has improved for age-related underlying genetic, diet, and lifestyle risks to developing type 2 diabetes mellitus and other NCDs, as it would be in the general population. Hence, individuals with HIV infection on ART should be regularly screened for DM, in particular, those above the age of 40 years.

The prevalence of renal dysfunction in this study was similar to a study from Cameroon [36] and did not appear to be associated with duration of ART use. Higher rates of renal dysfunction have been reported from other studies [15,37,38]. Renal disease in individuals with HIV infection is not uncommon and may be due to several factors including direct kidney injury by the virus and associated immune responses and/or ARV drugs such as tenofovir disoproxil fumarate and several others [39]. It is likely that study subjects on LTART may have had HIV infection for longer periods than ART naïve subjects. Nonetheless, there was no statistically significant difference in the prevalence of renal dysfunction between the two groups. Since our findings do not suggest increased rates of renal dysfunction among individuals on LTART, these drugs may reduce and/or delay the occurrence of kidney damage. However, the burden of renal diseases in individuals with HIV infection is complicated by the fact that the reduction in the prevalence of HIV-associated nephropathy accomplished by the administration of ART is offset by comorbid disease in the aging HIV population as well as ART nephrotoxicity [40].

Hypercholesterolemia was found in about a third of study subjects on LTART compared to 16.7% among ART naïve participants similar to reports of other studies in sub-Saharan Africa [6,41,42]. In vitro studies have pointed out the likely direct atherogenic effects of some antiretroviral medications like ritonavir on the vascular endothelium, macrophages, and platelets through the promotion of cholesterol accumulation or a reduction in cholesterol efflux from macrophages, decrease in endothelial nitric oxide production and cytotoxicity to endothelial cells [24]. Likewise, hypertriglyceridemia was higher among participants on LTART compared to ART naïve similar to a report of a systematic review and meta-analysis [43].

Overweight/obesity was more prevalent among participants on LTART compared to ART naïve study subjects and was higher than the reported prevalence of overweight/obesity in a previous study in Dar es Salaam [44]. In the Temprano trial, the prevalence of overweight/obesity among individuals with HIV infection increased from 27 to 32 percent after 24 months of initiation of ART [45]. Our study was conducted in an urban setting where overweight and obesity are on the rise. Likewise, many countries have reported increased prevalence of overweight and obesity in persons with HIV infection even before ART initiation, consistent with trends in the general population. Of note is that overweight/obesity in people with HIV infection may be a result of several factors. It may reflect increased food intake to prevent weight loss considered to be a principal feature of AIDS in many communities. Indeed, there is a misconception in some communities/cultures that a person whose weight is increasing does not have HIV infection. Overweight and obesity may also result from chronic inflammation in HIV which predisposes the adipose tissue to become metabolically active and a source of bioactive peptides which, via a complex interplay of factors, lead to the release of cytokines, interleukins, and leptin, a key pro-inflammatory adipokine associated with inflammation in the setting of obesity. Some markers of inflammation have been associated with greater gains in fat after initiation of ART [46].

The selected NCDs were associated with long-term use of ART, advancing age, and being overweight/obese. The negative association between NCDs and smoking was unexpected and is contrary to known associations [47–49]. We are unable to adequately account for this finding. However, it is worth noting that the prevalence of smoking among participants on LTART was 3.3% and 6.2% among ART-naive. Furthermore, only 0.9% of females and 13.6% of males in this study reported being smokers compared to 27.9% among adult males and 7.2% among females in Dar es Salaam [50]. Since the health information given regularly during clinic visits includes the negative impacts of smoking on health, some participants may have heeded to the advice, hence the small number of study subjects who reported being smokers. On the other hand, participants may have underreported smoking for fear of offending the healthcare providers who would have advised them not to smoke or due to other reasons. Indeed, in many African cultures and practices, women are not expected to smoke, and hence, due to these social pressures, underreporting is likely to be common.

The findings from this study show a strong association between long-term ART use and high prevalence rates of NCDs among residents of Dar es Salaam similar to observations reported from Europe, North America, and elsewhere.

Study limitation

This study was not designed to determine which particular antiretroviral drugs or regimens were associated with the selected NCDs. Serum creatinine was used to assess kidney function; this can underestimate kidney damage.

Conclusion

Hypertension, impaired glucose tolerance, diabetes mellitus, hypercholesterolemia, and hypertriglyceridemia were significantly associated with long-term use of antiretroviral therapy. Individuals with HIV infection on long-term ART, especially those aged ≥40 years, require screening for NCDs.

Supporting information

S1 Table. Comparison of socio-demographic and clinical characteristics of individuals with HIV infection in 3 ART status groups.

(DOCX)

Click here for additional data file.^{(15.8KB, docx)}

S2 Table. Clinical and laboratory findings among study subjects in 3 ART status groups.

(DOCX)

Click here for additional data file.^{(14.5KB, docx)}

S3 Table. Factors associated with hypertension, impaired glucose tolerance, diabetes mellitus, renal dysfunction, hypercholesterolemia, hypertriglyceridemia, low HDL cholesterol, and high LDL cholesterol among individuals with HIV infection.

(DOCX)

Click here for additional data file.^{(30.7KB, docx)}

S1 Appendix. Interview tool.

(DOCX)

Click here for additional data file.^{(15.9KB, docx)}

Acknowledgments

The authors are grateful to Dr. Candida Moshiro for her guidance in statistical work and the research assistants who assisted in recruitment of study participants and data collection.

Data Availability

All relevant data are uploaded to the OSF database and publicly accessible via the following URL: https://osf.io/vczy9/?view_only=fa6643e3f077493d8f28a584b30b1fe0.

Funding Statement

The author(s) received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0235542.r001

Decision Letter 0

Kwasi Torpey

20 Feb 2020

PONE-D-20-00114

Prevalence of non-communicable diseases among HIV-infected patients by antiretroviral therapy status in Dar es Salaam, Tanzania

PLOS ONE

Dear Dr Kato,

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Reviewer #2: Partly

Reviewer #3: Partly

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Nicely written article. Although my primary research area is epidemiology of respiratory infections (with a focus on influenza/EID), the article was easy to read and understand. My concerns are highlighted below. Would also request you to run a plagiarism check in the discussion section for improving certain sentences.

• Research assistants are mentioned in methods. May include them in acknowledgements as appropriate.

• The study tool / questionnaire might be provided in annexure if appropriate. Specifically, I wanted to know if family history of HIV was enquired.

• Table 1 shows significantly higher number of people in ART 5+ years for “employed” and “moderate/vigorous intensity”. You might mention this in discussion with possible reasons if any (ex: specific employment/activity program by government/hospital/NGO)

• Discussion section: line nos 207, 226, 240, 249, 255-56, 261-62 might require some language editing.

• Line 239-241 refers to study from USA but the study listed in reference is from South Africa (reference number 39). Kindly check

Reviewer #2: PONE-D-20-00114

General comments

1. The study is well written but still requires some copy editing.

2. The authors should consider writing “participants with HIV” rather than HIV/AIDS patients. The people in the research are participants in the research rather than patients being treated. In addition, it is not good practice to put the disease (HIV) before the person (patient). They are people with the disease, not the disease with the people.

3. The authors should also consider removing the “AIDS” on HIV/AIDS, as the term AIDS usually implies advanced HIV infection.

Materials and methods

1. Were the questionnaires assessing smoking and alcohol validated, and how?

2. How many times were blood pressure and anthropometry measured per participant. How reliable were these measurements?

4. How accurate is the GlucoPlus machine that was used for blood glucose measurement?

5. Please explain, briefly, what the ADA diagnostic criteria were.

7. Sample size – can the authors explain how the sample size was reached?

9. How was physical activity measured and then categorised?

10. Outcomes – the authors need to explain how each outcome was measured and defined and what guidelines and criteria were used.

11. On line 119, do the authors mean that all variables collected were categorical in nature?

12. Still on the analysis, what variables were considered for the logistic regression? What criteria was used for selecting these variables?

13. The authors state that there was a logistic regression, but do not explain how the outcome was defined.

14. The equal numbers between the groups are interesting. Was enrolment stopped when the numbers were equal?

15. In Results, lines 153-159, did the authors investigate whether this observed trend was not due to age?

16. Table 3 – logistic regression. Please explain why smoking is protective in this study, contrary to known effect.

18. The analysis requires re-working and the Discussion modified after that.

References

Reference number 1 “Joint United Nations Programme on HIV/AIDS (UNAIDS). Global Aids Update 2016. Geneva: UNAIDS, 2016.” is incomplete. Please add a link (URL) for where the resource can be accessed.

Reviewer #3: This is an important study in a setting where NCDs are becoming a priority research area. The aims were to determine the prevalence of NCDs and their risk factors amongst HIV infected patients on ART, with specific reference to the timing of ART use (long term vs naive). This would imply an internal control group that would allow the authors to infer the risk of time on ART for development of NCDs. The design is cross -sectional. I have identified some major methodological issues for the authors to address, which i think could have affected both the prevalence estimates as well as the risk factor associations.

1. Please report the assumptions used in the sample size estimation. What was the minimum difference of clinical importance?

2. For the risk factor analysis it appears that all NCDs were combined into a composite outcome. This is not specified nor defined anywhere. Composite outcomes themselves can be problematic especially where the risk factors for one of the outcomes is not the same as for the other outcomes. If you are using a composite outcome you should justify that it is sound to combine the outcomes and that valid inferences on risk factors to the composite outcome can be made. Otherwise, consider using each outcome as a separate outcome for the risk factor analysis.

4. I would like to see 95% confidence intervals reported around all your prevalence estimates. It is not merely sufficient to report the estimate on its own without making an inference to the population from which the sample was drawn.

6. In the discussion, the risk factors are not discussed at all.

**********

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Reviewer #1: No

Reviewer #2: Yes: Tawanda Chivese

Reviewer #3: Yes: Tonya Marianne Esterhuizen

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PLoS One. 2020 Jul 9;15(7):e0235542. doi: 10.1371/journal.pone.0235542.r002

Author response to Decision Letter 0

1 May 2020

Dear Editor,

We appreciate the opportunity to revise and resubmit our manuscript titled “Prevalence of non-communicable diseases among individuals with HIV infection by antiretroviral therapy status in Dar es Salaam, Tanzania”. We thank the Editor and reviewers for revision recommendations. We believe the revised manuscript is strengthened by the recommendations. We have provided a table with the reviewers’ comments and our responses. Two versions are submitted, one with tract changes and the other without as recommended.

Editor

Review comments Responses Location of the response in the revised manuscript

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. File naming and text formatting for the manuscript and supporting information now meets PLOS ONE's requirements. -

2. Please include copies of the interview guide(s) used in the study, in both the original language and English, as Supporting Information, or include a citation if they have been published previously. A copy of the interview guide used in the study has been provided as Supporting Information. The investigator and research assistants used the English version and could translate it during the interview. S1 Appendix

Responses to Reviewers’ Comments

Reviewer 1

Review comments Responses Location of the response in the revised manuscript

Nicely written article. Although my primary research area is epidemiology of respiratory infections (with a focus on influenza/EID), the article was easy to read and understand. My concerns are highlighted below. Would also request you to run a plagiarism check in the discussion section for improving certain sentences. Thank you for the complements.

We have run a plagiarism check and made appropriate editing in the discussion. In the discussion

Research assistants are mentioned in methods. May include them in acknowledgements as appropriate. Research assistants are now included in the Acknowledgments instead of Materials and Methods. Line 102, lines 327-8

The study tool / questionnaire might be provided in annexure if appropriate. Specifically, I wanted to know if family history of HIV was enquired. We did not collect information about the family history of HIV infection.

The study tool is provided. S1 Appendix, attached

Table 1 shows significantly higher number of people in ART 5+ years for “employed” and “moderate/vigorous intensity”. You might mention this in discussion with possible reasons if any (ex: specific employment/activity program by government/hospital/NGO) The following description has been added in the discussion: “Moderate/vigorous-intensity physical activities were more prevalent among individuals on LTART than ART naïve, which may be because of implementing health advice regularly offered to individuals at Care and Treatment Clinics”. Lines 215-217

Discussion section: line nos 207, 226, 240, 249, 255-56, 261-62 might require some language editing. We have edited the discussion as suggested. In the discussion

Line 239-241 refers to study from USA but the study listed in reference is from South Africa (reference number 39). Kindly check Thank you for pointing out the error.

We have corrected the typographical error and rewritten the sentence. Lines 273-276

Reviewer 2

Review comments Responses Location of the response in the revised manuscript

General comments

1. The study is well written but still requires some copy editing. Thank you for the complement.

Copy editing has been undertaken. Throughout text

Use of “HIV/AIDS patients” has been dropped from the manuscript and replaced with “individuals with HIV infection”. Throughout text

3. The authors should also consider removing the “AIDS” on HIV/AIDS, as the term AIDS usually implies advanced HIV infection. The word HIV disease has been used instead of HIV/AIDS, as recommended. Throughout text

Materials and methods

1. Were the questionnaires assessing smoking and alcohol validated, and how? We did not assess smoking and alcohol intake other than whether someone smokes or takes alcohol. Lines 102-104

2. How many times were blood pressure and anthropometry measured per participant. How reliable were these measurements? Blood pressure and anthropometric measurements were done at time of enrollment. The measurement of blood pressure was done according to the European Society of Hypertension/ European Society of Cardiology Guidelines for the management of arterial hypertension (Reference number 8 in the manuscript text). Lines 108-120

3. On line 101, the authors state, “HIV-infected patients who had been in a fasting state for the past 8 hours had fasting blood glucose and laboratory investigations done on the same day of enrolment”. How was fasting status ascertained? Individuals were asked about their last food intake. Those who had not taken food in the previous 8 hours or more were considered to be in a fasting state, and a blood sample was taken. Line 121-124

4. How accurate is the GlucoPlus machine that was used for blood glucose measurement? The machine is widely used, has been used in several studies, and is reliable. However, a study conducted in South Africa to assess the accuracy and reliability of glucose monitoring devices, including GlucoPlusTM reported satisfactory clinical accuracy, although all of the assessed devices had greater than 5% deviation (meeting ISO guidelines but missing ADA guidelines).

(Essack Y, Hoffman M, Rensburg M, Van Wyk J, Meyer CS, Erasmus R. A comparison of five glucometers in South Africa. Journal of Endocrinology, Metabolism and Diabetes of South Africa. 2009;14(2):102-5) Line 126-7

5. Please explain, briefly, what the ADA diagnostic criteria were. A brief description of the diagnostic criteria utilized has been included. Lines 127-132

6. On line 110, the authors state, “A 5ml venous blood sample was drawn from each patient and put in a red-toped vacutainer…”. Were these samples in the fasted state? What do the authors mean by “cool environment”, bearing in mind the humidity and high temperatures in Tanzania during the study period September to December. Blood samples were drawn on the first day from patients who had been fasting for at least 8 hours or next day for patients who were instructed to fast.

Samples were stored and transported to the laboratory in a cool box for biochemical analysis. “Cool environment” has been changed to “cool box” which is what was used. Lines 133-136

7. Sample size – can the authors explain how the sample size was reached? A section detailing the sample size calculation has been added in the Materials and Methods section. Lines 91-100

8. Exposures – the authors surely have data on the type of ART… Were all patients on one regimen, please describe the regimen and composition. If the regimen were different, perhaps an analysis based on these different regimen would be informative? Of 306 individuals with HIV infection on long-term ART, 174 (56.9%) reported having had a change of the ART regimen at least once. This may, therefore, complicate inferences on the association between ART regimens and NCDs, since information on the duration of different ART regimens was incomplete. -

9. How was physical activity measured and then categorised? Physical activity was assessed using the International Physical Activity Questionnaire – Short form (attached in Appendix 1). However, we included in the database and analyzed only whether a participant engages in vigorous physical activities (from question 1 & 2), moderate intensity physical activities (from question 3 & 4) or low intensity physical activities (question 5-7). Lines 106-7

S1 Appendix

10. Outcomes – the authors need to explain how each outcome was measured and defined and what guidelines and criteria were used. Guidelines and criteria used for each outcome are provided in the Materials and methods section of the manuscript. Line 108-110, 120, 127-132, 139

11. On line 119, do the authors mean that all variables collected were categorical in nature? We have edited the section to describe that both categorical and continuous variables were analyzed. Lines 142-6

12. Still on the analysis, what variables were considered for the logistic regression? What criteria was used for selecting these variables? The composite NCD included the following: hypertension, impaired glucose tolerance, diabetes mellitus, hypercholesterolemia, and hypertriglyceridemia. They are clinical manifestations or complications of metabolic syndrome. We aimed at determining the association between the above conditions and established risk factors for NCDs. Factors with p<0.2 in bivariate analysis were included in the multivariable Poisson regression with robust standard errors. Lines 146-150, 191-203

13. The authors state that there was a logistic regression, but do not explain how the outcome was defined. See our responses to comments number 10 and 12 above. (See also lines 202-203)

14. The equal numbers between the groups are interesting. Was enrolment stopped when the numbers were equal? Yes. The enrolment was stopped when the required number in a particular group was reached. Line 152-3

15. In Results, lines 153-159, did the authors investigate whether this observed trend was not due to age? Multivariable Poisson regression with robust standard errors (as in table 3) revealed that both ART status and age were independently associated with the NCDs. Lines 173-183

See also table 3 (line 197) and Supplementary Information, S3 Tables.

16. Table 3 – logistic regression. Please explain why smoking is protective in this study, contrary to known effect. This observation was in deep contrast to our expectations, and it is likely to be due to confounding factors. We have discussed the finding in the Discussion section. Lines 301-313

17. In the logistic regression, continuous exposures should not have been categorised, unless there were strong reasons to do so, i.e. if the study aim was to investigate the effect of age>40 or BMI>certain cut-offs. The primary aim was to examine the effect of ART Thank you for the suggestion. A table with a Poisson regression model without categorization of age and BMI is provided in the Supplementary information. We are, however, of the opinion that such categorization, e.g., of BMI, is of clinical importance and was thus presented in the main text. Line 191-199 (Table 3)

Supplementary Information (S3 Tables)

18. The analysis requires re-working and the Discussion modified after that. We did re-analysis and modified the respective sections. Lines 173-183, 191-199,

Table 3, S3 Tables

Discussion

References

Reference number 1 “Joint United Nations Programme on HIV/AIDS (UNAIDS). Global AIDS Update 2016. Geneva: UNAIDS, 2016.” is incomplete. Please add a link (URL) for where the resource can be accessed A URL has been added to reference number 1. Line 330-332

Reviewer 3

Review comments Responses Location of the response in the revised manuscript

This is an important study in a setting where NCDs are becoming a priority research area. The aims were to determine the prevalence of NCDs and their risk factors amongst HIV infected patients on ART, with specific reference to the timing of ART use (long term vs naive). This would imply an internal control group that would allow the authors to infer the risk of time on ART for development of NCDs. The design is cross -sectional. I have identified some major methodological issues for the authors to address, which i think could have affected both the prevalence estimates as well as the risk factor associations. Thank you for pointing out the significance of the study.

As stated in the last sentence of the Introduction, the study aimed at “determining the prevalence of selected NCDs and associated factors among individuals with HIV infection …”

Our study was not designed to determine risk factors for NCDs among people with HIV infection. We are sorry for the misunderstanding. Lines 70-72

1. Please report the assumptions used in the sample size estimation. What was the minimum difference of clinical importance? A section on sample size estimation and assumptions made has been added. Lines 92-100

Current analysis of NCD-associated factors considers the following into the composite outcome: hypertension, impaired glucose tolerance, diabetes mellitus, hypercholesterolemia, and hypertriglyceridemia (stated in text and footnotes of Table 3). The justification is that; they represent clinical manifestations or complications of metabolic syndrome. Indeed, the analysis of factors associated with each of the included outcomes individually yielded similar results. We have provided the analysis of each outcome in the supplementary information Lines 191-203 (Table 3)

Supplementary Information (S3 Tables)

3. The sampling design seemed to be cluster sampling, with the primary sampling units as hospitals and the secondary units as patients. This has an effect on prevalence estimates since prevalence within a specific facility can be more similar than between facilities. The authors need to incorporate cluster sampling design effect into their sample size calculation and into the analysis of the results. We did not employ cluster sampling. Although we included four different health care facilities, which tends to convey the idea of cluster sampling, the facilities receive individuals with HIV infection from all over Dar es Salaam. Since the facilities serve individuals from overlapping geographical areas in Dar es Salaam region and utilize the same Tanzania HIV treatment guidelines, we decided not to utilize cluster sampling design effect into sample size estimation and data analysis. There were over 80 administrative areas/wards included making analysis based on the specific geographical location not useful. Lines 81-90, 92-100, 146-8.

5. In the risk factor analysis, logistic regression was used. This is not appropriate for estimating relative risks from a cross sectional study where the outcome is not rare (rare is <10%). Please see https://www.tandfonline.com/doi/full/10.1080/02664763.2013.840772 for more information. You could use a log-binomial model and it can be done in SPSS (https://www.ibm.com/support/pages/log-binomial-model) although I have never used it in this software and Stata or R would probably be a better option. Please consult a biostatistician to ensure you use the correct model and interpret it correctly. Remember also to adjust for the within-facility clustering due to the cluster sampling used. In assessing the variables for association with the NCDs, we present prevalence ratios and adjusted prevalence ratios instead of odds ratios and adjusted odds ratios. We used Poisson regression modeling with Log link and robust standard errors in Stata®. We have not adjusted for cluster design effect as that is not the sampling method utilized (as described in #3 above). Lines 191-201

(Also see lines 146-148)

6. In the discussion, the risk factors are not discussed at all. Thank you for the comment.

We have added a discussion on factors associated with the NCDs. Lines 301-313 and elsewhere in the Discussion

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PLoS One. doi: 10.1371/journal.pone.0235542.r003

Decision Letter 1

Kwasi Torpey

10 Jun 2020

PONE-D-20-00114R1

Prevalence of non-communicable diseases among individuals with HIV infection by antiretroviral therapy status in Dar es Salaam, Tanzania

PLOS ONE

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Reviewers' comments:

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Comments to the Author

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Reviewer #2: (No Response)

Reviewer #3: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: (No Response)

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: No

Reviewer #3: (No Response)

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Reviewer #2: Yes

Reviewer #3: (No Response)

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Reviewer #2: Yes

Reviewer #3: (No Response)

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6. Review Comments to the Author

Reviewer #2: General comments

The authors have addressed most of the initial suggestions very well. The statistical analysis still needs a little bit more input though:

1. Is there any justification for the statistical approach to modelling used here? In general p-values are not advisable as the criteria for inclusion of variables into models especially in observational studies where p-values could be significant due to chance and/or confounding. Variables that have either biological plausibility and/or evidence of association with the outcome could be included in models despite p-values. In this case, it appears that the variables included have both biological plausibility and literature-based associations with the outcome, so the authors need not change the analysis.

2. The protective effect of smoking reported in this study is, as the authors rightly point out, most likely due to measurement error. Further, the proportion of smokers (29/612 = 5%), and the numbers with outcome (n =6) are very small and may lead to biased estimates of the association. Smoking was not assessed with a validated questionnaire and underreporting is a big concern here. My humble suggestion is for the authors to remove the variable and explain this in either statistical methods or discussion. This may have more benefit than leaving the finding in the table where it may be misinterpreted with the associated potential for harm. I suspect that the model will remain largely unchanged except for the removal of smoking.

Reviewer #3: I have reviewed the revised manuscript based on my and other reviewer’s suggestions. It is now ready for publication and I have no further changes which need to be made.

1. Recommendation: Accept

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Reviewer #2: Yes: Tawanda Chivese

Reviewer #3: Yes: Tonya Marianne Esterhuizen

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PLoS One. 2020 Jul 9;15(7):e0235542. doi: 10.1371/journal.pone.0235542.r004

Author response to Decision Letter 1

16 Jun 2020

Dear Editor,

We appreciate the opportunity to revise and resubmit our manuscript titled “Prevalence of non-communicable diseases among individuals with HIV infection by antiretroviral therapy status in Dar es Salaam, Tanzania”. We thank the Editor and reviewers for revision recommendations. We believe the revised manuscript has been strengthened by the recommendations. We provide a response to the reviewer’s comments, a manuscript version with tract changes, and the other without as recommended.

General comments

The authors have addressed most of the initial suggestions very well. The statistical analysis still needs a little bit more input though:

Response:

We note the comments from the reviewer and agree that the analysis remains as presented.

Response:

Smoking is a known important factor associated with the development and/or severity of NCDs and should be elicited for in a study on the subject.

We share the views of the reviewer that the apparent ‘protective effect of smoking on NCDs’ as shown in the results section, could be misinterpreted and it is important to prevent this from happening. However, we are uncomfortable with the suggestion that observations on smoking be ‘swept under the carpet’. We believe that we are expected and indeed obliged, to explain the unexpected observation that ‘Smoking is protective to NCDs’. Indeed, we believe most of your readers would want to find out reasons for the observation against the universally accepted norm, which is what we have done in the discussion (interpretation of the finding/result). Consequently, we believe that data on smoking should be presented in the results section. However, having presented our reasoning, we would accept the decision of the editor on the matter.

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PLoS One. doi: 10.1371/journal.pone.0235542.r005

Decision Letter 2

Kwasi Torpey

18 Jun 2020

Prevalence of non-communicable diseases among individuals with HIV infection by antiretroviral therapy status in Dar es Salaam, Tanzania

PONE-D-20-00114R2

Dear Dr. Kato,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0235542.r006

Acceptance letter

Kwasi Torpey

26 Jun 2020

PONE-D-20-00114R2

Prevalence of non-communicable diseases among individuals with HIV infection by antiretroviral therapy status in Dar es Salaam, Tanzania

Dear Dr. Kato:

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Comparison of socio-demographic and clinical characteristics of individuals with HIV infection in 3 ART status groups.

(DOCX)

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S2 Table. Clinical and laboratory findings among study subjects in 3 ART status groups.

(DOCX)

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(DOCX)

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S1 Appendix. Interview tool.

(DOCX)

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Data Availability Statement

All relevant data are uploaded to the OSF database and publicly accessible via the following URL: https://osf.io/vczy9/?view_only=fa6643e3f077493d8f28a584b30b1fe0.

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PERMALINK

Prevalence of non-communicable diseases among individuals with HIV infection by antiretroviral therapy status in Dar es Salaam, Tanzania

Irene Kato

Basil Tumaini

Kisali Pallangyo

Roles

Abstract

Background

Methodology

Results

Conclusion

Introduction

Materials and methods

Ethics statement

Study design and population

Sample size estimation

Data collection

Statistical methods

Results

Socio-demographic and clinical characteristics of study participants

Table 1. Comparison of socio-demographic and clinical characteristics of individuals with HIV infection on LTART with ART naïve.

NCDs among study subjects

Table 2. Clinical and laboratory findings among 612 study subjects.

Association between established risk factors and NCDs among study subjects

Table 3. Factors associated with NCDs among 612 individuals with HIV infection.

Discussion

Study limitation

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Kwasi Torpey

Roles

Author response to Decision Letter 0

Decision Letter 1

Kwasi Torpey

Roles

Author response to Decision Letter 1

Decision Letter 2

Kwasi Torpey

Roles

Acceptance letter

Kwasi Torpey

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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