Patterns and predictors of cigarette smoking among HIV-infected patients in northern Nigeria

Iliyasu, Zubairu; Gajida, AU; Abubakar, I S; Shittu, Oladapo; Babashani, Musa; Aliyu, Muktar H.

doi:10.1258/ijsa.2012.012001

Cited by 18 publications

(19 citation statements)

References 15 publications

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“…Our findings are consistent with previous reports of CVD risk factor prevalence among ART‐experienced PWH in South Africa: hypertension (12% to 39%) ; Stage 2 hypertension (14% to 66%) ; impaired glucose tolerance (16% to 21%) ; diabetes (2% to 8%) ; and self‐reported tobacco smoking (1% to 31%) . This substantial prevalence of CVD risk factors among a patient population who attends clinic on a routine basis underscores an important opportunity to screen for these intervenable risk factors.…”

Section: Discussionsupporting

confidence: 91%

Cardiovascular risk factors among ART‐experienced people with HIV in South Africa

et al. 2019

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Introduction People with HIV ( PWH ) are at increased risk for atherosclerotic cardiovascular disease ( CVD ). Screening for CVD risk factors is recommended but not routine in South African HIV clinics. We sought to describe the prevalence of CVD risk factors among antiretroviral treatment ( ART )‐experienced patients in South Africa. Methods We performed a prospective, observational cross‐sectional study of PWH (>21 years, excluding pregnant women) on ART in South Africa. We interviewed patients regarding CVD risk factors, and obtained two blood pressure ( BP ) measurements and random/fasting glucose via a point‐of‐care glucometer. Standardized chart reviews provided individuals' HIV ‐specific data. We defined hypertension as: self‐reported use of antihypertensives or mean systolic BP ( SBP ) ≥140 mmHg or diastolic BP ( DBP ) ≥90 mmHg (Stage 1) or SBP ≥160 mmHg or DBP ≥100 mmHg (Stage 2). We defined diabetes as self‐reported use of insulin/oral hypoglycaemics or fasting (random) glucose ≥7.0 (≥11.1) mmol. We obtained risk ratios ( RR ) for hypertension from a multivariable log‐binomial regression model, adjusting for age, sex and diabetes. Results From March 2015 to February 2016, 458 participants enrolled with median age 38 years (interquartile range ( IQR ) 33 to 44 years) and median CD 4 466/μL ( IQR 317 to 638/μL); 78% were women. Participants were on ART for a median of four years, with 33% on ART ≥6 years. Almost a quarter (106/458) met the study definition for hypertension, of whom 45/106 (42%) were previously diagnosed, 23/45 (51%) were on medication and 4/23 (17%) were controlled. Eight participants had asymptomatic hypertensive urgency ( BP ≥180/110 mmHg). Of the 458 participants, 26 (6%) met the study definition for diabetes, half of whom (13/26) were already diagnosed; 11/13 (85%) were on treatment, of whom 4/11 (36%) had normal glucose. Age was the only significant predictor of hypertension ( RR , 1.04; 95% CI , 1.03 to 1.06, p < 0.0001) in the multivariable model. Conclusions Hypertension and diabetes were prevalent among PWH prescribed ART in South Africa with less than half diagn...

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Section: Discussionsupporting

confidence: 91%

Cardiovascular risk factors among ART‐experienced people with HIV in South Africa

et al. 2019

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“…We also documented multiple reversible traditional CVD risk factors in an HIV clinical cohort. For instance, a fifth of our clinical cohort reported cigarette smoking, which is similar to the prevalence of cigarette smoking in HIV clinical cohorts in Nigeria [ 14 ], while our rates are lower than smoking rates which are in excess of 40% from North American cohorts, the higher rates in men and the difference in distribution of HIV between men and women in our setting compared to North America in part may explain this difference [ 15 , 16 ]. Hypertension rates in our clinical cohort on PI`s were significantly less than 19%, 29% and 38% among other regional HIV clinical cohorts on predominantly NNRTI containing ART in South Africa and Tanzania [ 12 , 13 , 17 ].…”

Section: Discussionmentioning

confidence: 52%

Cholesterol Screening and Statin Prescription is Low Among HIV-Infected Patients on Protease-Inhibitor Regimens in Botswana

Mosepele¹,

Letsatsi²,

Mokgatlhe³

et al. 2017

TOAIDJ

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“…The differences in study results could also be attributed to differences in the profile of HIV-positive populations in developed countries compared with LMICs (eg, mostly male vs mostly female, respectively). Very few studies have examined tobacco use prevalence among people living with HIV in LMICs; most of these studies are also of small non-random subsamples and only present data on tobacco smoking 32, 33, 34, 35. Few of these studies make comparisons with the general population prevalence or that among HIV-negative individuals.…”

Section: Discussionmentioning

confidence: 99%

Tobacco use among people living with HIV: analysis of data from Demographic and Health Surveys from 28 low-income and middle-income countries

Mdege

Shah

Ayo‐Yusuf

et al. 2017

The Lancet Global Health

100

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SummaryBackgroundTobacco use among people living with HIV results in excess morbidity and mortality. However, very little is known about the extent of tobacco use among people living with HIV in low-income and middle-income countries (LMICs). We assessed the prevalence of tobacco use among people living with HIV in LMICs.MethodsWe used Demographic and Health Survey data collected between 2003 and 2014 from 28 LMICs where both tobacco use and HIV test data were made publicly available. We estimated the country-specific, regional, and overall prevalence of current tobacco use (smoked, smokeless, and any tobacco use) among 6729 HIV-positive men from 27 LMICs (aged 15–59 years) and 11 495 HIV-positive women from 28 LMICs (aged 15–49 years), and compared them with those in 193 763 HIV-negative men and 222 808 HIV-negative women, respectively. We estimated prevalence separately for males and females as a proportion, and the analysis accounted for sampling weights, clustering, and stratification in the sampling design. We computed pooled regional and overall prevalence estimates through meta-analysis with the application of a random-effects model. We computed country, regional, and overall relative prevalence ratios for tobacco smoking, smokeless tobacco use, and any tobacco use separately for males and females to study differences in prevalence rates between HIV-positive and HIV-negative individuals.FindingsThe overall prevalence among HIV-positive men was 24·4% (95% CI 21·1–27·8) for tobacco smoking, 3·4% (1·8–5·6) for smokeless tobacco use, and 27·1% (22·8–31·7) for any tobacco use. We found a higher prevalence in HIV-positive men of any tobacco use (risk ratio [RR] 1·41 [95% CI 1·26–1·57]) and tobacco smoking (1·46 [1·30–1·65]) than in HIV-negative men (both p<0·0001). The difference in smokeless tobacco use prevalence between HIV-positive and HIV-negative men was not significant (1·26 [1·00–1·58]; p=0·050). The overall prevalence among HIV-positive women was 1·3% (95% CI 0·8–1·9) for tobacco smoking, 2·1% (1·1–3·4) for smokeless tobacco use, and 3·6% (95% CI 2·3–5·2) for any tobacco use. We found a higher prevalence in HIV-positive women of any tobacco use (RR 1·36 [95% CI 1·10–1·69]; p=0·0050), tobacco smoking (1·90 [1·38–2·62]; p<0·0001), and smokeless tobacco use (1·32 [1·03–1·69]; p=0·030) than in HIV-negative women.InterpretationThe high prevalence of tobacco use in people living with HIV in LMICs mandates targeted policy, practice, and research action to promote tobacco cessation and to improve the health outcomes in this population.FundingSouth African Medical Research Council and the UK Medical Research Council.

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Patterns and predictors of cigarette smoking among HIV-infected patients in northern Nigeria

Cited by 18 publications

References 15 publications

Cardiovascular risk factors among ART‐experienced people with HIV in South Africa

Cardiovascular risk factors among ART‐experienced people with HIV in South Africa

Cholesterol Screening and Statin Prescription is Low Among HIV-Infected Patients on Protease-Inhibitor Regimens in Botswana

Tobacco use among people living with HIV: analysis of data from Demographic and Health Surveys from 28 low-income and middle-income countries

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