RESEARCH ARTICLE


Assessing the Role of Individual and Neighbourhood Characteristics in HIV Testing: Evidence from a Population Based Survey



Maninder Singh Setia*, 1, Amelie Quesnel-Vallee1, 2, Sarah Curtis3, John Lynch4
1 Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
2 Department of Sociology, McGill University, Montreal, Quebec, Canada
3 Department of Geography, University of Durham, Durham, UK
4 Division of Health Sciences, University of South Australia, Adelaide, Australia


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© Setia et al.; Licensee Bentham Open.

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to this author at the Department of Epidemiology and Biostatistics, 1020 Pine Avenue West, Montreal, QC, H3A 1A2, Canada; Tel: 001-514-398-1269; Fax: 001-514-398-8851; E-mail: maninder.setia@mail.mcgill.ca


Abstract

Background:

Individuals living in deprived neighbourhoods have poor health outcomes, including human immunodeficiency virus (HIV) infection mortality. We assessed the association between individual and neighbourhood characteristics, and HIV testing across Canada.

Methods:

We used logistic regression modelling to evaluate this association in 2219 men and 2815 women, aged 18-54 years, in Canada, using data from the National Population Health Survey (1996/7),. Socio-economic characteristics and presence of a sexually transmitted infection (STI) were the individual level characteristics. Small area of residence was classified according to categories of material and social deprivation; these were the ’neighbourhood’ variables in the model.

Results:

Ethnic minority women were less likely to report an HIV test than white women (OR 0.44, 95% CI: 0.23 to 0.86). Women without a regular doctor were significantly less likely to report ever having had an HIV test (OR 0.57, 95% CI: 0.35 to 0.93). Adjusting for individual level characteristics, we found that men and women living in the most materially deprived neighbourhoods were slightly less likely to report HIV testing than those living in the least deprived neighbourhoods (Men - OR 0.61, 95% CI: 0.34 to 1.08; Women - OR 0.62, 95% CI: 0.38 to 1.00).

Discussion:

Thus, living in poor neighbourhoods was associated with poor uptake of an HIV test. These economic disparities should be taken in account while designing future prevention strategies. Ethnic minority women were less likely to go for HIV testing and culturally appropriate messages may be required for prevention in ethnic minorities.

Keywords: HIV testing, ethnic minorities, highly active antiretroviral therapy, neighbourhoods..



Introduction

The Public Health Agency of Canada has reported a total of 68,604 human immunodeficiency virus (HIV) infections until 2007 [1]. Men who have sex with men accounted for 62% of total new HIV infections in the period from 1985-1991, however, this proportion had reduced to 41% in 2007. There was a simultaneous increase in the number of infections due to heterosexual transmission (7% in 1985-1991 and 12% in 2007) [1]. The introduction of highly active antiretroviral therapy has resulted in reduction of complications and mortality in HIV infected individuals. However, HIV infected individuals will access the therapy and related prevention services only if they are aware of their HIV status. Thus HIV testing forms a core component of HIV prevention and care [2].

Canada has a universal health care system; the HIV testing facilities include nominal or name-based testing, non-nominal testing, and anonymous testing in various provinces [3]. However, it is estimated that about 27% of HIV infected Canadians are not aware of their status [4]. HIV testing may depend on various factors – perception of risk, clinical indicators, and access to health services. The testing pattern may also vary according to cultural practices; it may be different among those from ethnic minorities compared with the White Canadian population, and women may be particularly disadvantaged [5-7]. A recent review identified HIV testing patterns among women in Canada to be an important research area [8]. This may be useful to design prevention and care programmes for these communities in Canada. Another factor often discussed in health care access is the role of the neighbourhood in which individuals live. Studies have demonstrated that AIDS incidence and mortality is higher in economically deprived areas in non-industrialised as well as industrialised countries [9-4]. Although geographical mapping has shown that HIV services are less accessible in economically disadvantaged neighbourhoods in Toronto [15] an analysis of predictors of uptake of an HIV test in different neighbourhoods across Canada has never been done.

Thus, the present study was designed to evaluate the association between socioeconomic factors and HIV testing in men and women in Canada, both at the individual and neighbourhood level.

Methods

This study is a cross-sectional analysis of data from the National Population Health Survey (NPHS; 1996/97) [16]. Though NPHS is a longitudinal survey with seven data waves with 12 years of follow-up, the variable on HIV testing was available only in the 1996/7 wave. It is nationally representative dataset and provides information on the social, demographic, economic, occupational, environmental, and health characteristics of the Canadian population. We linked these data from the NPHS to information relating to Dissemination areas (DA) of residence in 1996 - the smallest unit of disseminating census data – using composite small area classifications for corresponding areas derived from the Canadian Census data (2001). The data included 2219 men and 2815 women, aged 18-54 years, residing in 1945 (mean 1.1) and 2460 (mean 1.1) DAs respectively.

The outcome variable of interest was whether individuals have had an HIV test other than for insurance or blood donation. The individual variables use as explanatory of this outcome were for 1996: socio-demographic variables - age, the living condition of individuals, educational level, income category, the province of residence, and ethnicity; clinical indicator - presence of a sexually transmitted infection (STI) in the past two years; and access indicator - whether they have a regular doctor or not. Ethnic minority status was determined by self-reporting of ethnicity. Two geographic variables describing the individual’s 1996 area of residence were also used as explanatory variables in the model; the material deprivation index and the social deprivation index, developed by Pampalon and colleagues, using 2001 census data for each of the DAs in Canada [17]. The material deprivation indicator takes into account the education level, employment status, and income; thus, reflects the economic poverty in the concerned populations. The social deprivation measure, takes into account the living condition of individuals (alone, separated, single parent families) and represents the level of social isolation or social cohesion in the population in the respective areas. As discussed earlier, economically deprived neighbourhoods reported higher AIDS cases and related mortality [9-4]. Based on the Postal Code correspondence file [18] we identified the DA in which the respondent lived in 1996. The DA identifier was used to link the individual data with geographical information on local material and social deprivation indicators.

We used STATA (version 10) (StataCorp, College Station, Texas, USA) to conduct the logistic regression analysis for the present study. The ‘boot strap’ method with 500 replications was used for calculating standard errors to allow for representativeness of this complex survey design. We initially analysed the proportion of HIV testing in the various individual and geographic level predictor categories; these were population weighted proportions. The modelling was conducted in the following sequence: 1) we initially performed analysis between the outcome and each of the explanatory variables (individual and geographic); 2) a multivariate analysis of the outcome and each of the individual level explanatory variables; 3) The next group of models were to test if the geographic level variables (separately for material and social deprivation indices)were associated with the outcome after controlling for individual level attributes. These data were not analysed in a multi-level model because the average number of individuals in each DA was 1.1, but options in STATA were used to adjust errors for any effects of clustering of some individuals in the same areas. We performed the linear contrast tests for trend to asses for any trends in the material and social deprivation quintiles [19]. All the models were initially built for the whole cohort, followed by models for men and women separately. The latter was done to assess if any of the explanatory variables had different effects in these two genders.

The study was approved for secondary data analysis by the Institutional Review Board of McGill University.

Results

Descriptive data

The mean ages (standard deviation) of men and women were 37.1 (+ 9.6) and 36.3 (+ 9.6) years respectively. Overall, more women had tested for HIV than men (20% versus 15%, p<0.01) in our sample. Of the 146 ethnic minority men, 25% were Chinese, 23% were black, and 17% were South Asian. However, among the 139 ethnic minority women, 22% were South Asian, 21% were Chinese, and 16% were Black. The proportion of HIV testing was highest in men (21%) and women (27%) aged 25 to 34 years. However, 36% of men and 44% of women reporting a STI in the past two years had tested for HIV (Table 1). The most common reason reported for HIV testing was ‘peace of mind’ in both men (43%) and women (32%). About 19% of women reported ‘pregnancy’ as a reason for getting tested. However, only 5% of men and women reported ‘risky sexual behaviours’ as the reason for the HIV test.

Table 1.

Proportion of People Reporting HIV Testing (Total = 5034; 2219 Males and 2815 Females) from the National Population Health Survey, Canada*


Characteristics Total
N=5034
[Population = 11540425]
Separated by Gender
Males
N=2219
[population=5756447]
Females
N=2815
[population = 5783978]
n Proportion HIV Tested n Proportion HIV Tested (%) n Proportion HIV Tested
All 5034 18 2219 15 2815 20
Individual level Variables
Age groups (years)
18-24 658 19 264 13 394 24
25-34 1452 24 618 21 834 27
35-44 1666 17 736 13 930 20
45-54 1258 10 601 11 657 9
p < 0.00 p < 0.00 p < 0.00
Living conditions
Living with partner/children 3815 16 1733 14 2082 19
Single parent with dependent children 773 20 387 21 386 21
Living alone/unattached 446 25 99 0.18 347 27
p < 0.00 p=0.03 p=0.02
Education
Less than secondary 619 12 304 12 315 13
Secondary education 703 12 315 9 388 15
Some post-secondary 1406 22 624 19 782 24
College/University 2306 18 976 15 1330 21
p < 0.00 p=0.01 p < 0.00
Income group
Lowest 704 23 240 19 464 26
Low-Mid 1399 17 591 12 808 20
Upper-Mid 2141 18 1011 17 1130 19
Upper 790 15 377 12 413 19
p = 0.02 p=0.05 p=0.18
Province
Others 2486 13 1071 12 1415 15
Ontario 1163 21 519 17 644 25
Quebec 904 16 425 16 479 17
British Columbia 481 18 204 15 277 20
p < 0.00 p=0.15 p < 0.00
Ethnicity
White 4749 18 2073 15 2676 21
Ethnic minorities 285 14 146 15 139 13
p=0.18 p=0.94 p=0.05
Has a regular doctor
Yes 4288 18 1746 15 2542 21
No 746 15 473 16 273 13
p = 0.13 p=0.68 p=0.01
Had an STI in the past
Yes 114 41 37 36 77 44
No 4920 17 2182 15 2738 19
p < 0.00 p < 0.00 p < 0.00
Geographic Variables
Material deprivation quintile
1st (least deprived) 799 20 317 20 482 21
2nd 917 19 411 15 506 23
3rd 1041 17 492 14 549 20
4th 1116 18 513 14 603 23
5th (most deprived) 1161 13 486 13 675 13
p = 0.05 p=0.29 p=0.03
Social deprivation quintile
1st (least deprived) 1019 13 450 10 569 16
2nd 1104 16 491 13 613 18
3rd 1018 17 463 16 555 18
4th 955 19 443 14 512 24
5th (most deprived) 938 24 372 23 566 25
p < 0.00 p < 0.00 p = 0.03

= The proportions are weighted for the population, hence only proportions are provided.

Table 2.

Models Showing Crude and Adjusted Association between Individual and Geographic Characteristics, and Outcome (HIV Testing) in 5034 Individuals from the National Population Health Survey, Canada


Characteristics Model I:
Crude Association for Individual and Geographic Characteristics
Model II:
Adjusted Association for Individual Characteristics
Model III: Adjusted Association for Individual and Geographic Characteristics
Material Deprivation Social Deprivation
Individual level Variables
Gender
Male 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Females 1.42 (1.18 - 1.71) 1.33 (1.10 - 1.61) 1.32 (1.09 - 1.61) 1.32 (1.08 - 1.60)
Age groups (years)
18-24 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
25-34 1.36 (1.01 – 1.85) 1.49 (1.10 - 2.03) 1.49 (1.10 - 2.02) 1.47 (1.08 - 2.00)
35-44 0.86 (0.61 – 1.21) 0.97 (0.69 - 1.36) 0.96 (0.68 - 1.34) 0.98 (0.70 - 1.38)
45-54 0.47 (0.33 – 0.67) 0.53 (0.37 - 0.77) 0.52 (0.36 - 0.75) 0.54 (0.37 - 0.77)
Living with partner/children 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Single parent with dependent children 1.69 (1.31 – 2.18) 1.57 (1.19 - 2.07) 1.56 (1.18 - 2.05) 1.42 (1.06 - 1.90)
Living alone/unattached 2.01 (1.44 – 2.81) 1.71 (1.21 - 2.42) 1.73 (1.22 - 2.43) 1.62 (1.15 - 2.30)
Education      
Less than secondary 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Secondary education 1.00 (0.64 - 1.56) 0.91 (0.57 - 1.43) 0.87 (0.55 - 1.39) 0.91 (0.57 - 1.44)
Some post-secondary 1.96 (1.35 - 2.84) 1.73 (1.17 - 2.56) 1.64 (1.11 - 2.44) 1.71 (1.15 - 2.53)
College/University 1.58 (1.09 - 2.30) 1.38 (0.93 - 2.06) 1.29 (0.86 - 1.92) 1.38 (0.92 - 2.05)
Income group
Lowest 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Low-Mid 0.65 (0.47 - 0.92) 0.70 (0.50 - 0.99) 0.69 (0.49 - 0.97) 0.71 (0.50 - 0.99)
Upper-Mid 0.71 (0.52 - 0.95) 0.79 (0.58 - 1.07) 0.75 (0.54 - 1.03) 0.81 (0.59 - 1.09)
Upper 0.60 (0.41 - 0.87) 0.68 (0.46 - 1.02) 0.62 (0.41 - 0.95) 0.72 (0.48 - 1.07)
Province
Others 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Ontario 1.74 (1.38 - 2.19) 1.81 (1.42 - 2.32) 1.75 (1.36 - 2.25) 1.81 (1.41 - 2.31)
Quebec 1.27 (0.99 - 1.64) 1.38 (1.05 - 1.80) 1.36 (1.04 - 1.79) 1.31 (0.99 - 1.73)
British Columbia 1.40 (1.04 - 1.89) 1.41 (1.04 - 1.93) 1.39 (1.02 - 1.89) 1.38 (1.00 - 1.89)
Ethnicity
White 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Ethnic minorities 0.76 (0.49 - 1.18) 0.65 (0.41 - 0.1.01) 0.66 (0.42 - 1.03) 0.65 (0.41 - 1.02)
Has a regular doctor
Yes 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
No 0.80 (0.59 - 1.08) 0.81 (0.58 - 1.12) 0.79 (0.57 - 1.09) 0.78 (0.56 - 1.09)
Had an STI in the past
No 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Yes 3.38 (2.12 - 5.37) 2.73 (1.71 - 4.36) 2.73 (1.69 - 4.40) 2.65 (1.67 - 4.22)
Geographic Variables
Material deprivation quintile
st (least deprived) 1.00 (reference) 1.00 (reference)
2nd 0.91 (0.66 - 1.25) 0.91 (0.65 - 1.28)
3rd 0.78 (0.58 - 1.06) 0.73 (0.52 - 1.01)
4th 0.89 (0.65 - 1.22) 0.85 (0.61 - 1.19)
5th (most deprived) 0.61 (0.45 - 0.83) 0.61 (0.43 - 0.88)*
Social deprivation quintile
1st (least deprived) 1.00 (reference) 1.00 (reference)
2nd 1.26 (0.92 - 1.72) 1.17 (0.85 - 1.62)
3rd 1.34 (0.94 - 1.91) 1.31 (0.91 - 1.88)
4th 1.54 (1.10 - 2.14) 1.42 (1.01 - 2.01)
5th (most deprived) 2.09 (1.51 - 2.89) 1.66 (1.17 - 2.34)**

Test for trend p=0.01

** Test for trend p=0.004.

Table 3.

Models Showing Crude and Adjusted Association between Individual and Geographic Characteristics, and Outcome (HIV Testing) in 2219 Males and 2815 Females Separately from the National Population Health Survey, Canada


Characteristics Model I:
Crude Association between Individual
and Geographic Characteristics
Model II:
Adjusted Association for Individual
Level Characteristics
Males
OR (95% CI)
Females
OR (95% CI)
Males
OR (95% CI)
Females
OR (95% CI)
Individual level Variables
Age groups (years)
18-24 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
25-34 1.69 (1.01 - 2.83) 1.32 (0.88 - 1.99) 1.90 (1.11 – 3.25) 1.32 (0.88 - 1.99)
35-44 1.00 (0.58 - 1.72) 0.88 (0.57 - 1.35) 1.22 (0.69 – 2.16) 0.88 (0.57 - 1.35)
45-54 0.74 (0.43 - 1.28) 0.35 (0.22 - 0.56) 0.90 (0.51 - 1.61) 0.35 (0.22 - 0.56)
Living conditions
Living with partner/children 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Single parent with dependent children 1.89 (1.32 - 2.71) 1.59 (1.11 - 2.28) 1.58 (1.06 - 2.36) 1.59 (1.11 - 2.28)
Living alone/unattached 1.70 (0.90 - 3.22) 1.70 (1.13 - 2.55) 1.73 (0.87 - 3.43) 1.70 (1.13 - 2.55)
Education
Less than secondary 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Secondary education 0.75 (0.37 - 1.52) 0.95 (0.49 - 1.86) 0.78 (0.38 - 1.60) 0.95 (0.49 - 1.86)
Some post-secondary 1.72 (1.00 - 2.94) 1.68 (0.92 - 3.08) 1.66 (0.94 - 2.96) 1.68 (0.92 - 3.08)
College/University 1.30 (0.74 - 2.28) 1.39 (0.77 - 2.53) 1.25 (0.68 - 2.27) 1.39 (0.77 - 2.53)
Income group
Lowest 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Low-Mid 0.58 (0.33 - 1.00) 0.78 (0.50 - 1.21) 0.59 (0.33 - 1.00) 0.78 (0.50 - 1.21)
Upper-Mid 0.82 (0.50 - 1.32) 0.73 (0.49 - 1.09) 0.85 (0.50 - 1.44) 0.73 (0.49 - 1.09)
Upper 0.54 (0.31 - 0.95) 0.76 (0.44 - 1.30) 0.59 (0.32 - 1.11) 0.76 (0.44 - 1.30)
Province
Others 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Ontario 1.53 (1.08 - 2.17) 2.15 (1.55 - 2.99) 1.45 (1.00 - 2.11) 2.15 (1.55 - 2.99)
Quebec 1.47 (1.03 - 2.12) 1.36 (0.94 - 1.97) 1.44 (0.97 - 2.13) 1.36 (0.94 - 1.97)
British Columbia 1.37 (0.84 - 2.23) 1.56 (1.06 - 2.29) 1.27 (0.76 - 2.11) 1.56 (1.06 - 2.29)
Ethnicity
White 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Ethnic minorities 1.02 (0.59 - 1.76) 0.44 (0.23 - 0.86) 0.97 (0.56 - 1.70) 0.44 (0.23 - 0.86)
Has a regular doctor
Yes 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
No 1.09 (0.72 - 1.64) 0.57 (0.35 - 0.93) 0.99 (0.65 - 1.53) 0.57 (0.35 - 0.93)
Had an STI in the past
No 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Yes 3.21 (1.49 - 6.93) 3.16 (1.76 - 5.69) 2.56 (1.07 - 6.14) 3.16 (1.76 - 5.69)
Geographic Variables
Material deprivation quintile
1st (least deprived) 1.00 (reference) 1.00 (reference)
2nd 0.73 (0.43 – 2.24) 1.12 (0.76 – 1.66)
3rd 0.65 (0.38 – 1.10) 0.93 (0.65 – 1.33)
4th 0.64 (0.38 – 1.08) 1.16 (0.79 – 1.70)
5th (most deprived) 0.63 (0.38 – 1.03) 0.60 (0.41 – 0.89)
Social deprivation quintile
1st (least deprived) 1.00 (reference) 1.00 (reference)
2nd 1.43 (0.86 – 2.40) 1.13 (0.73 – 1.75)
3rd 1.65 (0.93 – 2.94) 1.15 (0.73 – 1.80)
4th 1.48 (0.86 – 2.51) 1.62 (1.05 – 2.50)
5th (most deprived) 2.63 (1.61 – 4.30) 1.73 (1.12 – 2.66)
Individual level Variables
Age groups (years)
18-24 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
25-34 1.89 (1.10 - 3.25) 1.33 (0.88 - 1.99) 1.90 (1.10 - 3.26) 1.32 (0.88 - 1.99)
35-44 1.20 (0.68 - 2.15) 0.86 (0.56 - 1.33) 1.24 (0.70 - 2.21) 0.89 (0.58 - 1.37)
45-54 0.87 (0.49 - 1.58) 0.34 (0.21 - 0.55) 0.93 (0.52 - 1.67) 0.35 (0.22 - 0.56)
Living conditions
Living with partner/children 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Single parent with dependent children 1.56 (1.04 - 2.33) 1.61 (1.12 - 2.30) 1.39 (0.90 - 2.13) 1.46 (0.99 - 2.16)
Living alone/unattached 1.77 (0.88 - 3.55) 1.67 (1.12 - 2.49) 1.67 (0.85 - 3.29) 1.58 (1.04 - 2.39)
Education
Less than secondary 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Secondary education 0.76 (0.37 - 1.57) 0.91 (0.46 - 1.79) 0.76 (0.36 - 1.57) 0.96 (0.49 - 1.86)
Some post-secondary 1.59 (0.90 - 2.81) 1.56 (0.85 - 2.86) 1.70 (0.95 - 3.03) 1.63 (0.89 - 2.98)
College/University 1.14 (0.63 - 2.06) 1.29 (0.70 - 2.37) 1.24 (0.68 - 2.26) 1.38 (0.76 - 2.51)
Income group        
Lowest 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Low-Mid 0.60 (0.32 - 1.11) 0.74 (0.48 - 1.15) 0.59 (0.33 - 1.15) 0.78 (0.51 - 1.20)
Upper-Mid 0.84 (0.49 - 1.46) 0.68 (0.45 - 1.01) 0.87 (0.51 - 1.46) 0.74 (0.50 - 1.10)
Upper 0.54 (0.28 - 1.05) 0.70 (0.40 - 1.22) 0.61 (0.33 - 1.15) 0.78 (0.46 - 1.34)
Province
Others 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Ontario 1.39 (0.95 - 2.04) 2.08 (1.49 - 2.90) 1.44 (0.99 - 2.10) 2.17 (1.56 - 3.02)
Quebec 1.44 (0.97 - 2.16) 1.33 (0.92 - 1.92) 1.38 (0.91 - 2.07) 1.30 (0.89 - 1.92)
British Columbia 1.28 (0.76 - 2.13) 1.50 (1.02 - 2.21) 1.23 (0.73 - 2.08) 1.54 (1.04 - 2.27)
Ethnicity
White 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Ethnic minorities 1.00 (0.56 - 1.77) 0.45 (0.23 - 0.87) 1.00 (0.56 - 1.79) 0.43 (0.22 - 0.82)
Has a regular doctor
Yes 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
No 0.96 (0.62 - 1.50) 0.56 (0.34 - 0.92) 0.96 (0.62 - 1.50) 0.55 (0.33 - 0.89)
Had an STI in the past
No 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)
Yes 2.72 (1.07 - 6.92) 3.09 (1.69 - 5.66) 2.44 (1.02 - 5.85) 3.08 (1.71 - 5.56)
Geographic Variables Material deprivation quintile
1st (least deprived) 1.00 (reference) 1.00 (reference)
2nd 0.70 (0.39 - 1.26) 1.09 (0.71 - 1.66)
3rd 0.60 (0.33 - 1.08) 0.83 (0.56 - 1.24)
4th 0.59 (0.35 - 1.02) 1.11 (0.73 - 1.71)
5th (most deprived) 0.61 (0.34 - 1.08)* 0.62 (0.38 - 1.00)**
Social deprivation quintile
1st (least deprived) 1.00 (reference) 1.00 (reference)
2nd 1.39 (0.82 - 2.35) 1.08 (0.68 - 1.70)
3rd 1.72 (0.96 - 3.09) 1.11 (0.68 - 1.79)
4th 1.35 (0.77 - 2.37) 1.57 (1.00 - 2.49)
5th (most deprived) 2.12 (1.25 - 3.61) 1.42 (0.89 - 2.27)††

Test for trend p=0.07

** Test for trend p=0.09.

† Test for trend p=0.02

†† Test for trend p=0.04.

Complete Cohort Models

Crude associations and adjusted associations between various individual and neighbourhood level characteristics are presented in Table 2. We are only referring to the adjusted estimates in the subsequent discussion.

In the complete model with individual level characteristics we found that women were more likely to have had an HIV test than men. People who had an STI in the past two years were more likely to report an HIV test than those who had not. After adjusting for all individual level variables, we found that people living in the most materially deprived neighbourhoods reported a lower HIV test uptake than those living in the least deprived neighbourhoods. However, the reverse was true for social deprivation. Thus, people living in the most socially deprived neighbourhoods were more likely to report an HIV test than those living in the least socially deprived neighbourhoods. The tests for trend were significant for the material and social deprivation quintiles. The correlation between the material and social deprivation indices represented in our data was -0.07 in our data.

Models in Men and Women

We have described the crude and adjusted associations in men and women separately in Table 3. We refer to the adjusted association (Table 3, Models II and III) in the subsequent discussion.

We found that ethnic minority women were less likely to report an HIV test than white women, although this difference was not seen in ethnic minority men. Women without a regular doctor were less likely to report ever having had an HIV test, a feature again not seen in men. Women living in Ontario were more likely to have ever had an HIV test than other Canadian provinces. After adjusting for individual level characteristics, we found that men and women living in most materially deprived neighbourhoods reported lower HIV testing than those living in least deprived neighbourhoods, although the OR in the males was not significant. However, men and women living in most socially deprived neighbourhoods were significantly more likely to report an HIV test than those living in the least socially deprived neighbourhoods.

Discussion

Women were more likely to have had an HIV test than men in Canada in 1996/7. However, ethnic minority women reported lower HIV testing than white women. Further, women who did not have a regular doctor were less likely to report ever having an HIV test. About 36% of men and 44% of women who reported having an STI in the past two years had been tested for HIV. Adjusting for all the individual level predictor variables, people living in the most materially deprived neighbourhoods in Canada were about 40% less likely to have ever had an HIV test compared with those living in the least deprived neighbourhoods.

HIV testing by individuals may depend on various factors: perception of risk, access to testing services, and perception of social stigma associated with the infection as well as practical implications of testing positive, emotional trauma, and fear of social rejection [5]. HIV testing is higher in individuals who perceive themselves to be at risk [20]. Ethnic minorities often present late to HIV clinics as they are less likely to undergo HIV testing, a feature common to most industrialised countries [21-23]. In our population, although ethnic minority men had similar HIV testing rates as white men, the ethnic minority women reported significantly lower testing rates than white women. Gardezi and coworkers found that ethnic minority women in Toronto did not consider themselves at risk partly because of their religious beliefs and cultural norms [24]. Although we did not have information on perception of risk, HIV testing was lowest in ethnic minority women. These quantitative findings may echo qualitative reports risk perception may differ in ethnic minority men and women. Another aspect of healthcare access is the cultural relevance of these services for ethnic minorities [25]. The Toronto Public Health Department, for example, provides HIV counselling services in 16 languages other than the two official languages [26]. Culturally sensitive programmes may potentially increase the comfort and eventually the access for HIV related services [27, 28].

The overall higher HIV testing in women may be due to testing during pregnancy (19%). Indeed, women not having access to a regular doctor had lower HIV testing than those having a regular doctor, although a similar effect was not seen in men. Thus, potentially most of the HIV testing in these women appears to be physician driven. Massive community outreach programmes including HIV testing may increase the proportion of women undergoing an HIV test [29].

Apart from individual access to physician services; structural access barriers may potentially be responsible for low rates of testing. Spatial analysis of HIV services in Toronto neighbourhoods demonstrated that preventive services were concentrated in downtown areas and were less accessible in other areas [30]. Similarly another study from Toronto found fewer HIV services in economically disadvantaged and immigrant neighbourhoods [15]. These findings support our results that men and women living in most materially deprived neighbourhoods were less likely to report HIV testing. It has also been reported that people who have strong community ties may not access these services to avoid the ‘gossip’ in these communities [24]. Particularly, ethnic minorities may not go for HIV testing due to the fear of the stigma associated with it [5]. In our study, those living in most socially deprived neighbourhoods (increased social isolation) were more likely to report a test than those living in least socially deprived neighbourhoods. There is weak negative correlation at area level between social and material deprivation. These measures are proxies for different aspects of socio-economic conditions at the local level, and have been demonstrated to vary independently [17]. Thus improving the services in deprived neighbourhoods may potentially increase the HIV testing in individuals living in these areas. Stronger social cohesion and community ties in less socially deprived neighbourhoods should be used to improve the HIV prevention and care messages among individuals living in these areas.

Targeting individuals who access health care services with high risk behaviour is also a useful strategy to improve HIV testing. In our study, although, individuals with an STI had a higher proportion of HIV tests than the general population, only 36% of male and 44% of the females had had an HIV test.; however, the overall numbers for presence of an STI were small and these results should be evaluated in this context. Though the Canadian policy is to offer an HIV test to anyone with known risk behaviour [31] this is potentially an important area of intervention to improve HIV testing services among individuals at risk. Further, providing easy access to anonymous testing facilities may help to improve the testing in indiviudals at risk [3].

As is the case with many studies, this study also had its limitations. Though we used the presence of an STI in the past two years as a marker of high risk behaviour, we did not have information on the sexual behaviours or sexual preferences of individuals; a previous study though has demonstrated that HIV testing is higher in individuals who were more at risk [32]. Lack of information on risk behaviours other than STIs may be another potential limitation of the study. Ethnic minority status is not a homogenous entity - they represent multiple groups which may be missed in this category [33]. The area data applied to respondents’ place of residence in 1996/7 were collected 5 years later than the survey data, which may have resulted in some inaccuracy in our estimate of likely area conditions in 1996/7. Data on HIV testing were collected in 1996/7, making them of historic rather than contemporary relevance. However, more recent data do suggest that ethnic minority women do not consider themselves to be at risk for HIV and fewer HIV services are available in economic deprived areas; this may influence testing [15, 24]. Since, NPHS is an ongoing survey; it will be useful to collect recent information on HIV testing again, and assess the changes, if any, in the testing patterns. Interestingly, it was around 1996 that highly active antiretroviral therapy was introduced in care of HIV patients, and massive information and treatment campaign was initiated globally. Further, Rapid tests for HIV were approved in 2005 in Canada for “Point of Care settings” [34]. This may have resulted in changes in the awareness and testing levels. Thus, recent information on HIV testing could then be used to compare the testing behaviours over time and design our prevention and care programmes accordingly.

In spite of the above limitations, the study provides useful information on HIV testing in Canada. First, the results show that living in economically deprived neighbourhoods was associated with lower HIV testing. These economic disparities should be taken in account while designing future prevention strategies and improving access for these individuals. Second, though HIV positivity has increased in ethnic minorities in the past few years as per National statistics in Canada [1], testing for HIV in these population groups was relatively low, particularly for women. Thus, ethnic minorities, particularly women, according to our results should have been the focus of active public health interventions. Assuming similar conditions still prevail now, this suggests that culturally appropriate and relevant messages be developed for HIV prevention in ethnic minorities and campaigns may need to be focused in deprived areas where minority groups tend to be concentrated. With increased immigration from Asian and African nations, these results assume added significance in current HIV prevention programmes in Canada. Further, though international studies have discussed disparities in AIDS cases and mortality according to neighbourhood; [9-4] testing has not been adequately addressed. Thus, these findings should also be explored in nations with high immigration; results from these neighbourhood analyses will potentially help us formulate our prevention programmes through better access to HIV testing facilities.

ACKNOWLEDGEMENTS

The study is funded by Canadian Institutes of Health Research (MOP 77880, PI AQV). MSS is funded by CIHRIHSPR Fellowship and CIHR-RRSPQ Public Health Training Programme for his doctoral studies at McGill University. Additional funding was from CIQSS-Matching Grant for 2007.

REFERENCES

[1] Public Health Agency of Canada HIV AIDS (in Canada: Selected Surveillance Tables to June 30, 2007) Available from: http://www. phac-aspc.gc.ca/aids-sida/publication/survreport/pdf/tables0607.pdf 2009 [Accessed on 13 August];
[2] UNAIDS, W UNAIDS/WHO Policy on Statement on HIV Testing Available from: http://www.who.int/rpc/research_ethics/ hivtestingpolicy_en_pdf.pdf 2004 [Accessed on 13 August 2009];
[3] Public Health Agency of Canada HIV Testing and Infection Reporting on Canada Available from: http://www.phac-aspc.gc.ca/publicat/epiu-aepi/epi_update_may_04/3-eng.php [Accessed on 13 August 2009] 2004 [Accessed on 13 August 2009];
[4] Public Health Agency of Canada, HIV/AIDS: Populations at Risk Fact Sheet: People Living With HIV/AIDS Available from: http://www.phac-aspc.gc.ca/aids-sida/populations_e.html#pl 2008 [Accessed on 13 August 2009];
[5] Fakoya I, Reynolds R, Caswell G, et al. Barriers to HIV testing for migrant black Africans in Western Europe HIV Med 2008; 9(2): 23-5.
[6] Squires KE. Gender differences in the diagnosis and treatment of HIV Gend Med 2007; 4(4): 294-307.
[7] Stein MD, Crystal S, Cunningham WE, et al. Delays in seeking HIV care due to competing caregiver responsibilities Am J Public Health 2000; 90(7): 1138-40.
[8] Gatali M, Archibald C. Women and HIV BMC Women's Health 2004; 4(1): S27.
[9] Brugal MT, Borrell C, Diaz-Quijano E, Pasarin MI, Garcia-Olalla P, Villalbi JR. Deprivation and AIDS in a southern European city: different patterns across transmission group Eur J Public Health 2003; 13: 259-61.
[10] Gabrysch S, Edwards T, Glynn JR. The role of context: neighbourhood characteristics strongly influence HIV risk in young women in Ndola, Zambia Trop Med Int Health 2008; 13(2): 162-70.
[11] Mari-Dell'Olmo M, Rodriguez-Sanz M, Garcia-Olalla P, et al. Individual and community-level effects in the socioeconomic inequalities of AIDS-related mortality in an urban area of southern Europe J Epidemiol Community Health 2007; 61(3): 232-40.
[12] Msisha WM, Kapiga SH, Earls FJ, et al. Place matters: multilevel investigation of HIV distribution in Tanzania AIDS 2008; 22(6): 741-8.
[13] Wallace R, Wallace D. Socioeconomic determinants of health: community marginalisation and the diffusion of disease and disorder in the United States BMJ 1997; 314(7090): 1341-5.
[14] Zierler S, Fullilove M, Fullilove R, et al. Economic deprivation and AIDS incidence in Massachusetts Am J Public Health 2000; 90(7): 1064-73.
[15] Kaukinen C, Fulcher C. Mapping the social demography and location of HIV services across Toronto neighbourhoods Health Soc Care Community 2006; 14(1): 37-48.
[16] Statistics Canada, National Population Health Survey Available from: http://www.statcan.ca/cgi-bin/imdb/p2SV.pl?Function=get Survey&SurvId=3225&SurvVer=0&InstaId=15280&InstaVer=5&SDDS=3225&lang=fr&db=IMDB&dbl=E&adm=8&dis=2 2008 [Accessed on 13 August 2009];
[17] Pampalon R, Hamel D, Raymond G. Indice de défavorisation pour l’étude de la santé et du bien-être au Québec – Mise à jour 2001 Institut National de Santé Publique au Québec: Québec Accessed from: http://www.inspq.qc.ca/pdf/publications/295-IndiceDefavorisation_2001.pdf 2004.
[18] Gonthier D, Hotton T, Cook C, Wilkins R. Fusion des données de recensement par region et des données d’enquête dans les centre de données de recherché de Statistique Canada Bull Tech et d’Inf 2006; 3(1): 21-40.
[19] Vittingghoff E, Glidden DV, Shiboski SC, McCulloch CE. Regression Methods in Biostatistics 2004, New York, NY, USA: Springer Science+Business Media, Inc 2004; 1-333.
[20] de Wit JB, Adam PC. To test or not to test: psychosocial barriers to HIV testing in high-income countries HIV Med 2008; 9(2): 20-2.
[21] Anderson J, Melville R, Jeffries DJ, et al. Ethnic differences in women with HIV infection in Britain and Ireland. The study group for the mrc collaborative study of HIV infection in women AIDS 1996; 10(1): 89-93.
[22] Coenen T, Lundgren J, Lazarus JV, et al. Optimal HIV testing and earlier care: the way forward in Europe HIV Med 2008; 9(2): 1-5.
[23] Saul J, Erwin J, Bruce JC, et al. Ethnic and demographic variations in HIV/AIDS presentation at two London referral centres 1995-9 Sex Transm Infect 2000; 76(3): 215.
[24] Gardezi F, Calzavara L, Husbands W, et al. Experiences of and responses to HIV among African and Caribbean communities in Toronto, Canada AIDS Care 2008; 20(6): 718-25.
[25] Giger JN, Davidhizar R. Promoting culturally appropriate interventions among vulnerable populations Annu Rev Nurs Res 2007; 25: 293-316.
[26] Toronto Public Health AIDS & Sexual Health InfoLine Available from: http://www.toronto.ca/health/ai_index.htm 2008 [Accessed on 13 August 2009];
[27] Korner H. Late HIV diagnosis of people from culturally and linguistically diverse backgrounds in Sydney: the role of culture and community AIDS Care 2007; 19(2): 168-78.
[28] McMahon T, Fairley CK, Donovan B, et al. Evaluation of an ethnic media campaign on patterns of HIV testing among people from culturally and linguistically diverse backgrounds in Australia Sex Health 2004; 1(2): 91-4.
[29] rizwan m. Center for Disease Control and Prevention, Rapid HIV testing in outreach and other community settings--United States, 2004-2006 MMWR Morb Mortal Wkly Rep 2007; 56(47): 1233-7.
[30] Fulcher C, Kaukinen C. Mapping and visualizing the location HIV service providers: an exploratory spatial analysis of Toronto neighborhoods AIDS Care 2005; 17(3): 386-96.
[31] Public Health Agency of Canada, Human Immunodeficiency Virus Infections Ottawa, Canada Available from: http://www.phac-aspc.gc.ca/std-mts/sti_2006/pdf/508_HIV.pdf 2008 [[Accessed on 13 August 2009]];1-17.
[32] Houston S, Archibald CP, Strike C, et al. Factors associated with HIV testing among Canadians: results of a population-based survey Int J STD AIDS 1998; 9(6): 341-6.
[33] Bauder H. Visible minorities and urban analysis Can J Urban Res 2001; 10(1): 69-90.
[34] Canadian AIDS Society: Société Canadienne du SIDA Rapid HIV Testing in Canada 2007 Available from: http://www.cdnaids.ca/web/backgrnd.nsf/pages/cas-gen-0142 [[cited 2009 21 August]];