AIDS Care Psychological and Socio-medical Aspects of AIDS/HIV

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HIV testing of construction workers in the Western Cape, South Africa Paul Bowen, Rajen Govender, Peter Edwards & Keith Cattell To cite this article: Paul Bowen, Rajen Govender, Peter Edwards & Keith Cattell (2015) HIV testing of construction workers in the Western Cape, South Africa, AIDS Care, 27:9, 1150-1155, DOI: 10.1080/09540121.2015.1032877 To link to this article: http://dx.doi.org/10.1080/09540121.2015.1032877

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Date: 06 November 2015, At: 00:01

AIDS Care, 2015 Vol. 27, No. 9, 1150–1155, http://dx.doi.org/10.1080/09540121.2015.1032877

HIV testing of construction workers in the Western Cape, South Africa Paul Bowena*, Rajen Govenderb, Peter Edwardsc and Keith Cattella a Department of Construction Economics and Management, University of Cape Town, Cape Town, South Africa; bCentre for Social Science Research and Department of Sociology, University of Cape Town, Cape Town, South Africa; cSchool of Property, Construction & Project Management, RMIT University, Melbourne, VIC, Australia

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(Received 14 November 2014; accepted 16 March 2015) With an infection rate estimated at 14%, the South African construction industry is one of the economic sectors most adversely affected by the HIV/AIDS pandemic. Construction workers are considered a high-risk group. The provision and uptake of voluntary counselling and testing (VCT) is critical to reducing transmission rates. This study examined the testing behaviour of site-based construction workers in terms of demographic and lifestyle risk behaviour characteristics to help inform better strategies for work-based interventions by construction firms. A total of 512 workers drawn from six firms operating on 18 construction sites in the Western Cape province participated in the study. Twenty-seven per cent of the participants reported never having been tested for HIV. Results indicate that females (aOR = 4.45, 95% CI, 1.25–15.82), older workers (aOR = 1.40, 95% CI, 1.08–1.81), permanent workers (aOR = 1.67, 95% CI, 1.11–2.50) and workers whom had previously used a condom (aOR = 1.93, 95% CI, 1.02–3.65) were significantly more likely to have been tested. Ethnicity was not significantly related to prior testing. Identification of these subgroups within the industry has implications for the development of targeted work-based intervention programmes to promote greater HIV testing among construction workers in South Africa. Keywords: HIV testing; construction workers; demographics; risk behaviours; South Africa

Introduction The latest official South African National HIV Prevalence, Incidence and Behaviour Survey reports that South Africa has an overall national HIV prevalence of 12.2% (Shisana et al., 2014). The construction industry has been identified as one of the sectors most adversely affected by HIV/AIDS (Ambert, 2002; Bureau for Economic Research [BER], 2004; Harinarain & Haupt, 2014). Bowen, Dorrington, Distiller, Lake, and Besesar (2008), in a study of 10,243 construction workers report a prevalence of 13.9%. This is attributed to, inter alia, its fragmented nature (Chartered Institute of Building [CIOB], 2004), the predominance of small firms and migratory workforce (International Organization for Migration [IOM], 2010), and the diversity of construction work (Johnson & Budlender, 2002). The construction industry is also one of the least responsive to the pandemic (Meintjes, Bowen, & Root, 2007). Construction workers are thus perceived as a high-risk group. Voluntary counselling and testing (VCT) is central to controlling the spread of HIV/AIDS and providing care to those infected (Denison, O’Reilly, Schmid, Kennedy, & Sweat, 2008; Laurent, 2013; Shisana et al., 2014). VCT is critical in changing patterns of the risky sexual behaviour which places individuals at risk of infec‐ tion, most notably by decreasing the number of sexual

*Corresponding author. Email: [email protected] © 2015 Taylor & Francis

partners and by increasing condom use (Fonner, Denison, Kennedy, O’Reilly, & Sweat, 2012; Sherr et al., 2007). The uptake of testing services by individuals is significantly differentiated by a number of characteristics. Factors positively related to testing in South Africa include gender (women), older age, higher levels of education, greater knowledge of HIV and higher risk perception (Boulle et al., 2008; MacPhail, Pettifor, Moyo, & Rees, 2009; Ropelewski, Hulbert, & Latimer, 2011; Shisana et al., 2014), while factors negatively related to testing include inconsistent condom use (Hargreaves et al., 2007), excessive alcohol consumption (Parry et al., 2004), illegal drug use (Myers et al., 2013), fear (Venkatesh et al., 2011), stigma (Deacon, Uys, & Mohlahlane, 2009) and limited access to treatment (Asante, 2007). Despite extensive research into testing behaviour in South Africa, little relates directly to construction workers. Our research addresses that shortcoming. The success of work-based intervention management depends on worker cooperation, hence it is instructive to examine the factors which might differentiate the use of these services. This study examined the testing behaviour of construction workers in terms of demographic and lifestyle risk behaviour characteristics.

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Method

Statistical analysis

Study research design Primary data collection was undertaken using a survey questionnaire, self-administered in a supervised field set‐ ting on construction sites. The questionnaire was based on an instrument previously employed in the country (Kalichman & Simbayi, 2003, 2004). Convenience sam‐ pling was used for the selection of construction firms and sites, as well as the workers interviewed. The sample frame consisted of all employees present when researchers visited the site by prior arrangement. Ethical clearance was obtained from the University of Cape Town.

The data were analysed using IBM SPSS Ver. 22.0 for Macintosh (IBM Corporation, 2013). Chi-square tests were used to examine bivariate relationships between HIV testing status and demographic and behavioural factors. Logistic regressions were used to calculate un‐ adjusted and adjusted odds ratios (ORs). Variable selection for the regression analyses was based on the literature (Kalichman & Simbayi, 2003, 2004) and the bivariate analyses. Unless otherwise stated, frequencies and percentages provided relate to the number of valid responses to individual questions. For analysis purposes, participants’ ethnicity was re-categorised as either “Black”African or non-“Black” African (“Others”).

Participants and setting Participants were 512 site-based unskilled and skilled workers and site office-based staff from six firms on 18 sites in the Western Cape. Questionnaires were available in English, Afrikaans and isiXhosa, the most commonly spoken languages in the Western Cape. Participants were briefed on the nature of the study, and assured that their participation was entirely voluntary and that they could withdraw such participation at their will. They were further assured that all responses would remain entirely anonymous and confidential, and that such responses would not be identifiable or impact their status with their employer. Following this briefing, participants who provided informed consent then proceeded to complete the questionnaires. Generally, participants completed their questionnaires in site office metal shipping freight containers. At least three researchers were present for each site visit. Between them, the field researchers were proficient in all three languages. One researcher was female, and the other two were male. The time taken by participants to complete the questionnaire largely depended on their education level and literacy, varying between 30 minutes and one hour. The site visits, and associated data collection, occurred from June to August 2013. Measures Participants reported their HIV testing behaviour, demographic details and lifestyle risk behaviour characteristics. Risk behaviour items included alcohol consumption and cannabis (“dagga”) use, sexual intercourse with multiple partners in the preceding three months, use of and attitudes towards condoms, previously having been diagnosed with an STD and having had a genital ulcer. These measures were drawn from metrics developed and employed by Kalichman and Simbayi (2003, 2004). The full catalogue of items is shown in Table 1.

Results Participant characteristics A total of 512 questionnaires were completed. Participant characteristics are shown in Table 1. Most were male (91%) and 27% reported never having been tested. Participant age ranged from 18 to 69 years (mean = 36 years), with most being in the 21–30 years age group. Almost two-thirds (62%) of participants were “African”. Over a quarter (29%) had at most primary level education, while 52% had secondary level education. Sixty-two per cent were permanent employees. A fifth (20%) had two or more sex partners in the preceding three months, 79% had previously used a condom and 50% had used a condom at last coital act. Eight per cent reported having been diagnosed with an STD, 57% had consumed alcohol at least once in the preceding three months, and 12% had smoked dagga in the same period.

Correlates of prior HIV testing Table 2 indicates the unique and relative significance of the relationship between HIV testing status and the various participant characteristics (unadjusted and adjusted). The objective was not to undertake comparisons across multiple reference categories for every variable. Demographic factors: older age (OR = 1.33, 95% CI, 1.10–1.60), female gender (OR = 3.08, 95% CI, 1.19– 7.99), higher levels of education (OR = 1.54, 95% CI, 1.14–2.07) and more permanent nature of employment (OR = 1.89, 95% CI, 1.35–2.63) were significantly associated with testing in the unadjusted model. Older age (aOR = 1.40, 95% CI, 1.08–1.81), female gender (aOR = 4.45, 95% CI, 1.25–15.82) and more permanent nature of employment (aOR = 1.67, 95% CI, 1.11–2.50) remained significantly associated in the adjusted model.

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Table 1. Characteristics of participating construction workers. Tested for HIV

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Characteristics Demographic Age 20 and younger 21–30 31–40 41–50 51 and over Gender Male Female Race/ethnicity “Others” “Black” African Level of education Primary or less Secondary Tertiary or higher Firm employed by Firm A Firm B Firm C Firm D Firm E Firm F Nature of employment Permanent Temporary/contract Casual Marital status Married/long-term relationship Single Behavioural Multiple sex partners (≥2)a No Yes Ever used a condom No Yes Condom use at last coital act No Yes Like using a condom No Yes Has been diagnosed with an STD No Yes Has had a genital ulcer No Yes

Never tested for HIV

Total

%

n

%

n

%

22 167 138 99 62

4.5 34.2 28.3 20.3 12.7

10 111 111 76 48

2.8 31.2 31.2 21.3 13.5

12 56 27 23 14

9.1 42.4 20.5 17.4 10.6

χ2 p-value 0.002

0.013b 459 44

91.3 8.7

329 39

89.4 10.6

130 5

96.3 3.7 0.535b

193 311

38.3 61.7

138 231

37.4 62.6

55 80

40.7 59.3

143 259 96

28.7 52.0 19.3

94 191 79

25.8 52.5 21.7

49 68 17

36.6 50.7 12.7

180 79 88 119 15 27

35.4 15.6 17.3 23.4 3.0 5.3

141 59 63 77 7 25

37.9 15.9 16.9 20.7 1.9 6.7

39 20 25 42 8 2

28.7 14.7 18.4 30.9 5.9 1.5

304 167 21

61.8 33.9 4.3

242 112 11

66.3 30.7 3.0

62 55 10

48.8 43.3 7.9

319 169

65.4 34.6

239 119

66.8 33.2

80 50

61.5 38.5

401 102

79.7 20.3

299 68

81.5 18.5

102 34

75.0 25.0

0.017

0.004

0.001

0.284b

0.134b

0.026b 106 398

21.0 79.0

68 300

18.5 81.5

38 98

27.9 72.1 0.227b

251 251

50.0 50.0

177 190

48.2 51.8

74 61

54.8 45.2 0.418b

222 281

44.1 55.9

158 210

42.9 57.1

64 71

47.4 52.6 0.358b

453 41

91.7 8.3

331 33

90.9 9.1

122 8

93.8 6.2

474 20

96.0 4.0

351 12

96.7 3.3

123 8

93.9 6.1

0.195b

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Table 1. (Continued) Tested for HIV Characteristics Alcohol usea None Once More than once Dagga (Cannabis) usea Never Once More than once

Never tested for HIV

Total

%

n

%

n

%

217 55 227

43.5 11.0 45.5

168 39 160

45.8 10.6 43.6

49 16 67

37.1 12.1 50.8

441 18 41

88.2 3.6 8.2

330 12 25

89.9 3.3 6.8

111 6 16

83.5 4.5 12.0

χ2 p-value 0.227

0.127

a

Reported for the past three months. Fisher’s exact test used rather than chi-square test for independence.

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b

Table 2. Simple and multiple logistic regression models for the relationship between HIV/AIDS testing status and characteristics of construction workers. Adjustedb

Unadjusted Characteristics Demographic Age Gender Race/ethnicity Level of education Employer firm Nature of employment Marital status Behavioural Multiple sex partners (≥2)a Ever used a condom Condom use at last coital act Like using a condom Has been diagnosed with an STD Has had a genital ulcer Alcohol usea Dagga (Cannabis) usea

OR

95%CI

OR

95%CI

1.33** 3.08* 1.15 1.54** 0.91 1.89*** 0.80

1.10–1.60 1.19–7.99 0.77–1.72 1.14–2.07 0.80–1.03 1.35–2.63 0.53–1.21

1.40* 4.45* 1.24 1.44 0.89 1.67* 1.19

1.08–1.81 1.25–15.82 0.70–2.20 0.97–2.12 0.76–1.04 1.11–2.50 0.68–2.09

0.68 1.71* 1.30 1.20 1.52 0.53 0.84 0.72*

0.43–1.09 1.08–2.70 0.88–1.94 0.81–1.78 0.68–3.38 0.21–1.32 0.68–1.03 0.52–0.99

0.78 1.93* 1.13 0.84 2.15 0.70 0.84 1.10

0.43–1.41 1.02–3.65 0.62–2.06 0.46–1.55 0.79–5.86 0.18–2.73 0.65–1.09 0.72–1.69

a

Reported for the past three months. Model adjusted for all covariates. *p < 0.05; **p < 0.01; ***p < 0.001

b

Ethnicity was not associated with prior testing in either the unadjusted or adjusted models. Behavioural factors: Previous use of a condom (OR = 1.71, 95% CI, 1.08–2.70) was significantly associated with prior testing in the unadjusted model and in the adjusted model (aOR = 1.93, 95% CI, 1.02–3.65). Use of dagga (OR=0.72, 95% CI, 0.52–0.99) in the preceding three months was significantly negatively associated with prior testing in the unadjusted model, but not in the adjusted model. No other behavioural factors were associated with prior testing in either the unadjusted or adjusted models.

Discussion In this study, 73% of the participants reported prior testing for HIV. This testing rate exceeds the 66% population-level testing behaviour reported by Shisana et al. (2014). The higher rate observed here is arguably indicative of a more proactive intervention by participating firms, a factor that in itself led to their participation in the study and accordingly cannot be regarded as representative of the sector. Construction workers who are younger, male, employed on a temporary or casual (day-to-day occasional employee) basis and who have never used a condom are significantly

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less likely to have tested for HIV. Younger workers may be less inclined to perceive a need for testing due to misplaced optimism regarding future health (Ropelewski et al., 2011). Women were over four times more likely than men to have been tested. This may be due to attendance at antenatal clinics and the emphasis placed on testing pregnant women (Kaufman et al., 2014; MacPhail et al., 2009; Ropelewski et al., 2011). Excluding pregnant women, differentiation on the basis of gender has been attributed to men’s propensity to underestimate their HIV risk (Obermeyer & Osborn, 2007). Nature of employment was associated with testing behaviour. Permanent employees reflected the highest testing rates for workers, predictably so as many firms limit programme participation to permanent workers for budgetary reasons (Bowen, Allen, Edwards, Cattell, & Simbayi, 2014; Bowen, Cattell, Edwards, & Marks, 2010). Workers who had previously used a condom were more likely to have tested for HIV, while ethnicity was unrelated to prior testing. Both findings align with Kalichman and Simbayi’s (2003) study. Results emanating from this study provide new information about factors that potentially influence HIV testing in the South African construction industry. However, these must be tempered by limitations of the study which include the cross sectional nature of the survey, the geographical bias of the sample (Western Cape), and the potential underreporting of risk behaviours. Notwithstanding these limitations, this study indicates that (1) it may be sub-groups rather than the entire industry workforce that may be considered high risk, and (2) the characteristics of these subgroups may reflect that observed in the general population. Consequently, efforts to improve the testing rate in the construction industry can be better focused and managed by absorbing learning from interventions in the general population. Most importantly, work-based interventions should especially target construction workers who are younger, male and employed on a temporary or casual basis. Acknowledgements The authors wish to express their appreciation to the HSRC for permitting them to draw on relevant HSRC questionnaires in the compilation of the survey questionnaire employed in this study.

Disclosure statement No potential conflict of interest was reported by the authors.

Funding This work is based on research supported by the National Research Foundation of South Africa [grant number (UID) 85376]. The Grantholder acknowledges that opinions, findings and conclusions or recommendations expressed in any publication

generated by the NRF supported research are those of the authors, and that the NRF accepts no liability whatsoever in this regard.

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HIV testing of construction workers in the Western Cape, South Africa.

With an infection rate estimated at 14%, the South African construction industry is one of the economic sectors most adversely affected by the HIV/AID...
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