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Health, wellbeing, and disability among older people infected or affected by HIV in Uganda and South Africa

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Health, wellbeing, and disability among older people infected or affected by HIV in Uganda and South Africa
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  Health, wellbeing, and disabilityamong older people infected or affected by HIV in Uganda andSouth Africa Makandwe Nyirenda 1,2 *, Marie-Louise Newell 1,3 ,Joseph Mugisha 4,5 , Portia C. Mutevedzi 1 , Janet Seeley 4,6 ,Francien Scholten 4 and Paul Kowal 7,8 1  Africa Centre for Health and Population Studies, University of KwaZulu-Natal, Somkhele,South Africa;  2 School of Social Sciences, University of Southampton, Highfield, Southampton, UK; 3 Centre for Paediatric Epidemiology and Biostatistics, UCL Institute of Child Health, London, UK; 4 Medical Research Council/Uganda Research Unit on AIDS, Uganda Virus Research Institute,Entebbe, Uganda;  5 London School of Hygiene and Tropical Medicine, London, UK;  6 School of International Development, University of East Anglia, Norwich, UK;  7 Multi-Country Studies Unit,World Health Organization, Geneva, Switzerland;  8 Research Centre on Gender, Health and Ageing,University of Newcastle, Newcastle, Australia Objecti  v e : To describe and compare the health status, emotional wellbeing, and functional status of olderpeople in Uganda and South Africa who are HIV infected or affected by HIV in their families. Methods : Data came from the general population cohort and Entebbe cohort of the Medical ResearchCouncil/Uganda Virus Research Institute, and from the Africa Centre Demographic Information Systemthrough cross-sectional surveys in 2009/10 using instruments adapted from the World Health Organization(WHO) Study on Global Ageing and adult health (SAGE). Analysis was based on 932 people aged 50 yearsor older (510 Uganda, 422 South Africa). Results : Participants in South Africa were slightly younger (median age   60 years in South Africa, 63 inUganda), and more were currently married, had no formal education, were not working, and were residing ina rural area. Adjusting for socio-demographic factors, older people in South Africa were significantlyless likely to have good functional ability [adjusted odds ratio (aOR) 0.72, 95% CI 0.53    0.98] than thosein Uganda, but were more likely to be in good subjective wellbeing (aOR 2.15, 95% CI 1.60    2.90).South Africans were more likely to be obese (aOR 5.26, 95% CI 3.46    8.00) or to be diagnosed withhypertension (aOR 2.77, 95% CI 2.06    3.73). Discussion and conclusions : While older people’s health problems are similar in the two countries, markedsocio-demographic differences influence the extent to which older people are affected by poorer health.It is therefore imperative when designing policies to improve the health and wellbeing of older people insub-Saharan Africa that the region is not treated as a homogenous entity. Keywords:  South Africa ;  Uganda ;  older people ;  health status ;  functional ability ;  subjecti  v e wellbeing  Received: 24 July 2012; Revised: 4 November 2012; Accepted: 27 December 2012; Published: 23 January 2013 I n sub-Saharan Africa and other developing coun-tries, there is limited information on the generalhealth and wellbeing of persons aged 50 years andabove, and even less is available on the topic of olderadults and HIV (1    5). HIVremains a major public healthchallenge in sub-Saharan Africa, with Uganda andSouth Africa among the worst affected. According tothe 2011 Uganda AIDS Indicator Survey, an estimated6.7% of the population in Uganda was HIV infected (6).South Africa on the other hand, with an estimated adultHIV prevalence rate of 16.2%, has the world’s highestnumber of people living with HIV: around 5.6 million (7),with nearly 2 million on antiretroviral treatment (ART).It has been suggested that there may have been a declinein annual HIV incidence rates in certain age groupsbetween 2001 and 2009 (8). Studies on people aged 50 (page number not for citation purpose)    CLUSTER: IMPROVING HEALTH AND LIVING CONDITIONS FOR ELDERLY POPULATIONS Glob Health Action 2013. # 2013 Makandwe Nyirenda et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License (http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and reproduction inany medium, provided the srcinal work is properly cited. 1 Citation: Glob Health Action 2013,  6 : 19201 -  http://dx.doi.org/10.3402/gha.v6i0.19201  and above in Uganda and South Africa estimate the HIVincidence rates in these populations at 0.2 and 0.5%,respectively (9, 10). Furthermore, although incidencerates are low, an increasing number of older people areliving with HIV as a result of improved survival on ART(11    14). However, although HIV is a recognised publichealth problem in both Uganda and South Africa,neither country has much data on the effects of HIV onthe health and wellbeing among older people infected oraffected by HIV (15).Studies from Kenya (16), Tanzania (17), Ghana (18),and South Africa (19, 20) have provided recent empiricalevidence on the health status of older people. A short-coming of these studies is that HIV status was notassessed, whereas other studies exclusively focused onHIV-infected older persons (21, 22). Other researches onthe health status of older people in sub-Saharan Africahave thus far largely been based on qualitative studies(23) or have utilised a limited set of health domains (24).This article is a follow-up of separate analyses con-ducted in Uganda and South Africa (25, 26), using surveydata collected in 2009/10 with standardised World HealthOrganization (WHO) questionnaires and analytical in-struments (27). Previous findings from these analysesshowed age to be a key determinant of health andfunctional ability in both countries, with men reportingbetter health and functional status than women (25, 26).In Uganda, apart from lower body mass index (BMI),HIV-infected older adults on ARTreported similar healthand functional ability as HIV-uninfected participants(25). In South Africa, HIV-infected and HIV-uninfectedwomen were significantly less likely than men to reportvery good or good health. HIV-infected South Africanshad better functional ability, quality of life, and overallhealth status than HIV-uninfected participants (26).In the analysis presented here, data from the twostudies have been pooled for a systematic, comparativeanalysis of the health and wellbeing of older people. Theaim of this article is to describe and compare self-ratedhealth, subjective wellbeing and functioning of olderpeople in Uganda and South Africawho are HIV infectedor affected by HIV in their families. Methods Study setting  Data used in this analysis were collected from thegeneral population cohort and Entebbe cohort of theMedical Research Council/Uganda Virus Research In-stitute (MRC/UVRI) in Uganda (25), and from theAfrica Centre surveillance area in rural South Africa(26) through cross-sectional surveys in 2009/10. Thegeneral population cohort (GPC) is located in ruralKalungu district, southwestern Uganda, established bythe MRC/UVRI in 1989. The GPC collects demographicand behavioural information, such as births, deaths,access to health care, and sexual partnerships in annualsurveillance rounds. The Entebbe cohort was establishedby MRC/UVRI in 1994 to conduct epidemiological andclinical studies relating to HIV/AIDS. Further detailsabout the open population cohort and the Entebbecohort have been previously described (28    30).The Africa Centre surveillance is located in northernrural KwaZulu-Natal, South Africa. The surveillance areais predominantly rural, only less than 10% of theapproximately 90,000 household members under surveil-lance live in areas defined as urban. Demographic, social,and health information, such as births, deaths, migrations,and health care utilisation, are collected from all consent-ing households and their members (31) in twice yearlysurveillance rounds since 2000. In addition, social andeconomic information such as household asset ownership,sanitation facilities, energy sources, and access to socialamenities is collected in special annual modules of thedemographic surveillance. A nested annual sexual beha-viour and HIV surveillance has been operating amongadults aged 15 years and above since 2003. The adult HIVprevalence in the South African study site has beenestimated at around 22% with prevalence by age as highas 50% among women aged 30    34 years (32). The AfricaCentre surveillance has been described in detail elsewhere(31, 33) or www.africacentre.com. Study population  In both Uganda and South Africa, the study sample wasmade up of persons aged 50 years and above who residedwithin the respective surveillance populations. The studyrandomly selected 100 older persons in each of the fivedistinct groups based on the surveillance fieldsite censusrecords and nested surveys described above. Refusalswere less than 1%. The categorisation into the five groupswas based on the following criteria:1) Older persons who were HIV infected and on ARTfor a year or longer;2) Older persons who were HIV infected and not yet onART or on ART for three or less months;3) Older persons living with an adult child who wasHIV infected and on ART;4) Older persons who had an adult child who died of HIV-related death; and5) Older person who was HIV uninfected and had noadult child who was HIV infected.The fifth group was the comparison group but could onlybe established in the Ugandan study as in South Africa,with the high HIV prevalence (32), older HIV-uninfectedpeople not affected by HIV in the family were rare. Makandwe Nyirenda et al. 2 (page number not for citation purpose) Citation: Glob Health Action 2013,  6 : 19201 -  http://dx.doi.org/10.3402/gha.v6i0.19201  Data collection  Data from both sites were collected using structuredquestionnaires adapted from survey instruments of theWHO’s Study on global AGEing (SAGE) and adulthealth (27, 34). The health measurement tools included inthe survey instruments have been validated and shown tobe applicable across different settings (35    38). The toolswere translated into respective local languages andmodified to take into account the local context. Thequestionnaires had four main parts: demographic andhousehold information; health and wellbeing assessment;care-giving and care-receiving patterns; and anthropo-metric measurements. At the Uganda site, in addition tomeasured weight and height, objective health measures,including blood pressure, hand grip strength, near anddistant vision, walking speed, and cognition, werecollected. Blood samples were collected at the SouthAfrican site. In both sites, face-to-face interviews wereused to collect data on persons aged 50 years and above,with further details published elsewhere (25, 26). Variables  Age, sex, marital status, education, occupation, place of residence, and measures of household wealth werecollected. Age reporting was checked against surveillancerecords. Income quintiles were generated from householdownership of durable goods, dwelling characteristics(type of floors, walls, and cooking stove), and accessto services, such as improved water, sanitation, andcooking fuel. An ‘asset ladder’ was generated and usinga Bayesian post-estimation (empirical Bayes) method,households were arranged on the asset ladder, where theraw continuous income estimates were transformed intoquintiles. In addition, a question about self-perceivedfinancial status was asked, ‘Compared to 3 years ago,would you say your financial situation now is better orworse off?’.Multiple measures of health and wellbeing were used inthis analysis as outcome variables (functional disability,emotional well-being, prevalence of self-reported hyper-tension, BMI, and self-rated general overall health).The WHO Disability Assessment Schedule (WHODAS)(39) was used to assess the functional ability of studyparticipants. A series of questions were asked on theability of participants to perform tasks, such as walking,standing, stooping, and climbing a flight of stairs. The12-item WHODAS instrument (38) was used to obtain ameasure of functional ability, with results transformed toa scale of 0    100, where 0 represented poorest functionalability (highest disability) and 100 represented thebest functional ability (lowest disability). The science of measuring happiness often includes both experiencedwellbeing and evaluative wellbeing. In this study, evalua-tive wellbeing was measured using the WHO Quality of Life instrument (WHOQOL) (35). The eight-item versionof WHOQOL assesses satisfaction with, amongst otherthings, life, health, and living conditions. The resultingraw score from the eight questions ranged from 8 to40. This was later transformed into a scale from 0 to 100,where 100 represented best subjective wellbeing.Measurements of height and weight were taken of all participants. These measurements were used to com-pute the BMI, using a standard formula of weight inkilograms over height in metres (squared). WHO’s BMIclassifications were used where BMI of less than 18.5 isconsidered under-weight, while between 25.0 and 29.9are considered over-weight, and 30  is considered obese(40). BMI is presented as a mean value or, when in theregression model, is collapsed into a dichotomous vari-able (not obese  BMI B 30 or obese BMI ] 30). Preva-lence of hypertension was calculated based on respondentself-report to a question,  Ha v e you e v er been told by ahealth care professional that you ha v e high blood pressure/ hypertension?   Self-rated health was obtained from a singleoverall general health question,  In general, how would yourate your health today?   This question has been demon-strated to be a relatively robust indicator of health andmortality across different settings (36, 41), even though ithas some consistency and comparability shortcomings.The response categories were based on a 5-point Likert-type scale: ‘very good’, ‘good’, ‘moderate’, ‘bad’, and‘very bad’. The first three categories were collapsed into arating of ‘good’ and the last two into ‘bad’. Data analysis  Indicators of health, functioning, and wellbeing wereexamined in bivariate and multivariable analyses. Amultivariable logistic regression analysis was done toassess the health and wellbeing status of participants inUganda relative to those in South Africa. This relation-ship was assessed adjusting for age, sex, education,occupation status, household wealth quintiles, change inself-perceived household financial status, and rural versusperi-urban place of residency. For these analyses, adichotomous variable of good versus poor physical healthor subjective wellbeing was generated. The categorisationinto good or poor physical health was based on fallingabove or below an overall WHODAS median value of 80.5 for the pooled sample. For subjective wellbeing, anoverall WHOQoL median cut-off value of 62.5 was used.Stata statistical software version 11.2 was used for allanalyses (42).Ethics approval was obtained from the Uganda VirusResearch Institute, Science and Ethics Committee and theNational Council for Science and Technology for theUganda project, and from the University of KwaZulu-Natal Biomedical Research Ethics committee for theSouth Africa project. Impact of HIV on the health, well-being and disability among older people Citation: Glob Health Action 2013,  6 : 19201 -  http://dx.doi.org/10.3402/gha.v6i0.19201  3 (page number not for citation purpose)  Results A total of 932 participants (510 in Uganda and 422 inSouth Africa) were included in the final sample. Womenmade up 75% (South Africa) and 61% (Uganda) of therespective samples (Table 1). Overall, participants inUganda were slightly older than in South Africa; medianage was 63 years in Uganda (66 years men, 62 yearswomen) and 60 years in South Africa, for both men andwomen. A major difference pertained to employmentstatus where 94% of the sample in South Africa was notworking, but 81% of the Uganda participants reported tobe working. Other significant differences in the studysamples were observed in marital status, educationattainment, self-perceived financial status, and place of residency (Table 1).Table 2 shows age    sex adjusted physical functionalability, subjective wellbeing, and BMI for older people inSouth Africa and Uganda. In both countries and across Table 1 . Socio-demographic characteristics of study participants by country South Africa Uganda  n  %  n  %  p Median age (age range) 60 (50    94) 63 (50    96)Sex  B 0.001Male 106 25.1 198 38.8Female 316 74.9 312 61.2 Age group 0.00250    59 190 45.0 178 34.960    69 128 30.3 150 29.470    79 74 17.5 127 24.980   30 7.1 55 10.8Marital status  B 0.001Never married 116 27.5 7 1.4Married 206 48.8 165 32.4Separated/divorced 8 1.9 105 20.6Widowed 91 21.6 233 45.7Missing 1 0.2 0 0.0Education level  B 0.001NFE/AEO 201 47.6 118 23.1Primary 165 39.1 293 57.5Secondary 52 12.3 71 13.9Tertiary 4 0.9 25 4.9Missing 0 0.0 3 0.6Employment status  B 0.001Working 24 5.7 411 80.6Not working 395 93.6 87 17.1Missing 3 0.7 12 2.4Financial status  B 0.001Better 67 15.9 20 3.9 About the same 136 32.2 56 11.0Much worse 219 51.9 426 83.5Missing 0 0.0 8 1.6Wealth quintiles 1.000First (lowest) 85 20.1 102 20.0Second 84 19.9 102 20.0Third 86 20.4 102 20.0Fourth 84 19.9 102 20.0Fifth (highest) 83 19.7 102 20.0Place of residency 0.042Peri-urban/urban 182 43.1 254 49.8Rural 240 56.9 256 50.2 Makandwe Nyirenda et al. 4 (page number not for citation purpose) Citation: Glob Health Action 2013,  6 : 19201 -  http://dx.doi.org/10.3402/gha.v6i0.19201  Table 2  . Age    sex adjusted mean functional ability, subjective wellbeing, and body mass index by study group, sex, and country (95% confidence interval in parenthesis) South Africa UgandaStudy groups Male Female Both sexes Male Female Both sexesFunctional ability a Functional abilityHIV  , on ART 87.2 (84.7    89.6) 78.2 (74.7    81.7) 81.9 (79.6    84.2) 79.8 (74.4    85.1) 76.9 (72.4    81.4) 77.9 (74.5    81.4)HIV  , no ART/ART B 3 months 77.1 (73.5    80.6) 68.9 (65.7    72.1) 70.8 (68.2    73.4) 79.9 (75.0    84.7) 67.7 (60.4    75.0) 71.7 (66.5    76.8)Has HIV  adult child 83.4 (79.9    87.0) 70.0 (66.2    73.7) 73.9 (71.1    76.8) 78.6 (73.8    83.4) 71.0 (67.0    75.0) 73.5 (70.4    76.6)Has adult child, died with HIV 76.0 (69.5    82.6) 68.3 (64.8    71.8) 70.6 (67.4    73.7) 82.5 (77.3    87.6) 73.1 (69.6    76.6) 76.2 (73.3    79.0)Comparison b n/a n/a n/a 79.1 (74.4    83.8) 72.2 (69.1    75.4) 74.5 (71.9    77.1)Total 79.6 (76.6    82.5) 69.4 (67.5    71.4) 72.7 (71.1    74.4) 78.6 (76.3    80.9) 71.1 (69.1    73.1) 73.5 (72.0    75.1)Subjective wellbeing c Subjective wellbeingHIV  , on ART 66.4 (62.9    69.8) 60.0 (56.2    63.8) 62.6 (59.9    65.2) 64.6 (60.5    68.7) 59.0 (56.0    62.1) 61.0 (58.5    63.4)HIV  , no ART/ART B 3 months 61.2 (56.9    65.5) 53.6 (48.9    58.4) 55.4 (51.6    59.2) 59.5 (55.8    63.1) 53.2 (47.3    59.2) 55.3 (51.1    59.4)Has HIV  adult child 62.6 (60.6    64.5) 59.5 (56.6    62.4) 60.4 (58.3    62.5) 56.75 (1.6    61.7) 53.9 (50.8    56.9) 54.8 (52.2    57.4)Has adult child, died with HIV 62.0 (55.0    69.0) 57.2 (54.6    59.7) 58.6 (55.9    61.3) 55.3 (48.7    61.9) 54.1 (51.1    57.2) 54.5 (51.6    57.5)Comparison b n/a n/a n/a 57.5 (53.8    61.3) 54.9 (51.5    58.2) 55.6 (53.2    58.3)Total 62.4 (59.7    65.0) 57.4 (55.7    59.0) 59.0 (57.6    60.4) 57.9 (56.0    59.8) 54.8 (53.4    56.3) 55.8 (54.7    57.0)Body mass index Body mass indexHIV  , on ART 25.3 (23.2    27.4) 26.9 (25.3    28.4) 26.2 (25.0    27.5) 24.9 (19.0    30.9) 24.3 (19.0    29.6) 24.5 (20.5    28.5)HIV  , no ART/ART B 3 months 24.4 (22.9    25.9) 27.5 (25.7    29.2) 26.7 (25.4    28.1) 20.4 (19.6    21.2) 24.6 (21.9    27.3) 23.3 (21.4    25.1)Has HIV  adult child 25.7 (24.6    26.8) 30.3 (28.8    31.8) 29.0 (27.9    30.0) 21.1 (19.4    22.9) 26.6 (24.3    28.8) 24.8 (23.2    26.4)Has adult child, died with HIV 24.8 (22.8    26.9) 31.2 (29.5    32.9) 29.3 (28.0    30.7) 36.3 (22.4    50.3) 26.9 (24.6    29.1) 30.0 (25.2    34.7)Comparison b n/a n/a n/a 24.4 (20.4    28.5) 28.0 (24.4    31.7) 26.9 (24.1    29.6)Total 24.5 (23.4    25.8) 29.4 (28.6    30.3) 27.8 (27.1    28.5) 23.8 (21.7    25.9) 25.9 (24.3    27.5) 25.2 (24.0    26.5) a Functional ability, as measured by a WHODAS, with score transformed to 0 to 100, where 0 represents poorest functional ability (highest disability) and 100 best functional ability (lowestdisability). b Study group only established in Uganda, not in South Africa. c Subjective well-being, as measured by a WHOQoL, with score transformed into a scale from 0 to 100, where 100 represented best subjective wellbeing. 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