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Factors influencing the uptake of voluntary HIV counseling and testing in rural Ethiopia: a cross sectional study

BMC Public HealthBMC series – open, inclusive and trusted201616:239

https://doi.org/10.1186/s12889-016-2918-z

Received: 20 August 2015

Accepted: 1 March 2016

Published: 8 March 2016

Abstract

Background

Voluntary counseling and testing (VCT) has been one of the key policy responses to the HIV/AIDS epidemic in Ethiopia. However, the utilization of VCT has been low in the rural areas of the country. Understanding factors influencing the utilization of VCT provides information for the design of context based appropriate strategies that aim to improve utilization. This study examined the effects of socio-demographic and behavioral factors, and health service characteristics on the uptake of VCT among rural adults in Ethiopian.

Methods/design

This study was designed as a cross sectional study. Data from 11,919 adults (6278 women aged 15–49 years and 5641 men aged 15–59 years) residing in rural areas of Ethiopia who participated in a national health extension program evaluation were used for this study. The participants were selected from ten administrative regions using stratified multi-stage cluster sampling. Multivariate logistic regression analysis was performed accounting for factors associated with the use of VCT service.

Results

Overall, men (28 %) were relatively more likely to get tested for HIV than women (23.7 %) through VCT. Rural men and women who were young and better educated, who perceived having small risk of HIV infection, who had comprehensive knowledge, no stigmatization attitude and discussed about HIV/AIDS with their partner, and model-family were more likely to undergone VCT. Regional state was also strongly associated with VCT utilization in both men and women. Rural women who belonged to households with higher socio-economic status, non-farming occupation, female-headed household and located near health facility, and who visited health extension workers and participated in community conversation were more likely to use VCT. Among men, agrarian lifestyle was associated with VCT use.

Conclusions

Utilization of VCT in the rural communities is low, and socio-economic, behavioral and health service factors influence its utilization. For increasing the utilization of VCT service in rural areas, there is a need to target the less educated, women, poor and farming families with a focus on improving knowledge and reducing HIV/AIDS related stigma. Strategy should include promoting partner and community conversations, accelerating model-family training, and using alternative modes of testing.

Keywords

HIV/AIDS VCT utilization HEP HEWs Model-family Community conversation Rural Ethiopia

Background

Ethiopia, Africa’s second most populous nation, is among the most affected by the HIV epidemic in Sub-Saharan Africa, where unprotected heterosexual contact and mother-to-child transmission are the main routes of transmission [1, 2]. HIV/AIDS, which continues to be a major development challenge for Ethiopia with an estimated adult prevalence of 1.5 % in 2011, has stabilized in the past decade with heterogeneity between different geographic areas [3]. Although the HIV prevalence in rural Ethiopia was relatively low (0.9 %) [3], small market towns are becoming hotspots bridging the urban-to-rural spread of HIV [4]. Moreover, the rural population with disproportionately low access to HIV/AIDS services is vulnerable to the risk of HIV infection, and the further spread of HIV to rural population is likely to increase as the communication and transport infrastructure improves [5].

Voluntary counseling and testing (VCT) has been one of the key policy responses to the HIV/AIDS epidemic, principally as a primary prevention strategy and as an entry point to other HIV/AIDS related services [6]. While undergoing VCT services, individuals learn about their sero-status and gain knowledge on avoiding risky behaviors to protect themselves and others [79]. VCT also serves as the basis for accessing HIV treatment and care as well as emotional support that enable individuals to cope with HIV-related anxiety and plan for their future [79].

Despite its strategic importance, the VCT uptake has been low in Ethiopia, as elsewhere in Africa [3, 1013]. In 2005, the VCT uptake in Ethiopia was extremely low with only 4 % of women and 6 % of men ever tested for HIV [11], which increased to 38.8 and 41.1 %, respectively in 2011 following the rapid scale up of primary health care facilities, under the rural Health Extension Program (HEP), and increased accessibility to free anti-retroviral drugs [3]. However, the VCT uptake in 2011 was lower among rural residents (30.9 % for women and 36 % for men) compared to the urban residents (63.8 % of women and 58.5 % of men).

It is widely accepted that the uptake of VCT is influenced by socio-demographic characteristics such as age, gender, marital status, educational attainment, socio-economic status, and area of residence [1217], behavioral and psychosocial factors such as high risk sexual partner, HIV/AIDS related knowledge, confidentiality, self-perceived risk, stigma and discrimination, and perceived benefits of VCT [10, 1222], and health service delivery environment [11, 14, 15, 23, 24].

Understanding the factors influencing the utilization of VCT provides information for the design of context based appropriate strategies to improve access. Nevertheless, studies undertaken to understand factors affecting VCT utilization among rural population of Ethiopia are limited [12, 25]. This study therefore seeks to examine the effects of socio-demographic and behavioral factors, and health service characteristics, with a focus on HEP, on the uptake of VCT among rural Ethiopian adults using a nationally representative sample.

Methods

Setting

The federal government structure of Ethiopia is composed of nine Regional States and two City Administrations (Addis Ababa and Dire-Dawa). The regions are Afar, Amhara, Benshangul-Gumuz, Oromia, Gambela, Harari, SNNP (Southern Nations and Nationalities and Peoples), Somali and Tigray. The regions are divided into woredas (districts), which are further divided into kebeles (the lowest administrative government units). Majority (83.6 %) of the people in Ethiopia reside in rural areas with about 10 % practicing pastoral and agro-pastoral livelihood. There are about 15,000 rural kebeles in the country, each with an average of 5000 inhabitants. The rural population has access to Primary Health Care Unit (PHCU), which is the lowest-tier in the healthcare delivery system comprising a cluster of five health posts and a referral health center. Over 15,000 health posts and 3000 health centers have been established to cover all rural areas in the country with PHCU. Over 38,000 high-school completed female Health Extension Workers (HEWs) who received one year training on HEP have been deployed to the health posts (at least two HEWs per health post). The candidates were recruited from their prospective villages to limit staff turnover and address gender, social and cultural factors in service provision. Volunteer community health workers (CHWs) who are trained as model family support the community level activities of HEWs.

The HEP package comprises 16 services covering family health, communicable diseases, and sanitation and hygiene programs. With the aims to develop personal and social skills, and increase health awareness that enable individuals to promote their own health, HEP focuses on promotive and preventive interventions with limited curative services. In addition to the promotive and preventive HIV/AIDS services, HEWs who are deployed in high HIV prevalent areas also provide HIV counseling and testing (HCT). The referral health centers are staffed with higher health professionals and all provide HCT services.

Study design and sampling methods

This study is part of a comprehensive HEP evaluation survey conducted in 2010 with the aim to assess the implementation process and effect of HEP on health outcomes of the rural population. The evaluation was designed as a multi-level cross-sectional study involving household, health worker, and health facility surveys. The data for this article came from the household survey.

The households were sampled from rural kebeles using a stratified multi-stage cluster sampling method with region as strata, and district, kebele and household as primary, secondary, and tertiary sampling units, respectively. The sampling frame comprised 679 districts with 14,723 rural kebeles from the 10 regions (including the rural areas of Dire Dawa). The sampling procedure involved selection of 71 districts and 312 kebeles through systematic-random sampling with probability-proportional-to-size. A cross-sectional sample of 7128 households was selected from the 312 kebeles using the random-walk method used in the Expanded Program of Immunization cluster surveys. Household level data was collected using five modules: Socio-demographic (20 items), Family Health (90 items), Malaria and Tuberculosis (69 items), HIV/AIDS (57 items), and Hygiene and Sanitation (34 items), which were developed with some modification to the Ethiopian Demographic and Health Survey (EDHS) questionnaires [11]. The module on household socio-demographic characteristics was administered to the heads of 7098 households. The HIV/AIDS module was administered to 12,060 adults (women aged 15–49 years and men aged 15–59 years).

Consent and confidentiality of study data

The study has received approval from the national ethics review committee of the Ethiopian Federal Ministry of Science and Technology, and the institutional review board of the Columbia University (IRB-AAAC8935). Study subjects were recruited in person by survey supervisors. The need for written informed consent was waived, and oral consent was obtained from each respondent using an approved information statement. Strict confidentiality of information and anonymity of data have been kept throughout the study. Data collection was carried out in January and February of 2010.

Measurements

For the analysis reported in this paper, we used data from 11,919 adults (6278 women and 5641 men) with matching data on socio-demographic and HIV/AIDS. The dependent variable was VCT utilization. The independent variables included socio-demographic, behavioral and programmatic factors. The socio-demographic variables were: gender, age, marital status, educational level, primary occupation of household head, region of residence, settlement type (pastoralist/agro-pastoral and agrarian), household’s socioeconomic status and religion. Socio-economic status (SES) index variable was constructed for each household from a set of self-reported assets and living condition variables that reflect economic status using principal component analysis and households were grouped into five clusters using k-means clustering in STATA/IC 12.0 [26].

The programmatic variables included walking distance to the nearest health facility (<=10, 10–30 and >30 min), contact with HEWs (proactively visiting HEWs and visited by HEW at home), exposure to HIV/AIDS related information (never exposed, exposed through mass media, and exposed through community conversation), model-family and availability of volunteer CHWs in the village. HIV/AIDS related communications involving health workers, HEWs, community volunteers, community members and school were all considered as community conversation activities.

The behavioral variables included high-risk sexual partner in the past 12 months, self-perceived risk of HIV infection (four categories: no, small, moderate/great risk and don’t know), belief that HIV/AIDS is fatal, belief that HIV/AIDS can be cured, HIV/AIDs knowledge index and stigma scale, and conversation with partner about HIV. Knowledge index was constructed by combining the responses to 7 sets of questions: a healthy-looking person can have the HIV virus; HIV can’t be transmitted by mosquito bites, supernatural means and sharing food; and HIV can be prevented through abstinence, being faithful to one uninfected partner and condom use. The scores were categorized into four groups: none (0–1), low (2–3), moderate (4) and high (5–7). The stigma index was constructed using four standard questions: willingness to care if a relative becomes ill with HIV; willingness to buy fresh vegetable from a food seller who has the HIV virus; allowing child to play with a child who has HIV virus; and keeping secret about a family member infected with HIV virus. The scores were categorized into four groups: no (0–1), low (2), moderate (3) and high (4) stigma.

Statistical analysis

Descriptive statistics were generated to characterize the study subjects. Univariate analysis was employed to independently assess the statistical association of the independent factors and the dependent variable. All socio-demographic variables were entered into a multivariate logistic model, while other variables were considered based on cut-off p-value (<0.1) after testing multicollinarity between all variables. The analysis was carried out for men and women separately in STATA version 12, and survey weights were specified to account for sampling design in generating results that included odds ratios (OR) and 95 % confidence intervals (CI).

Results

Characteristics of the study population

A total of 11,919 people were included in the analysis (Table 1). The median age was 28 years for women (52.7 %) and 33 years for men (47.3 %). Majority of respondents came from male-headed (85 %) and farming households (90 %). Majority (78.9 %) were married and about 58 % (70.9 % of women and 47.1 % of men) had never attended or completed one year of formal education. About 14.5 % of respondents were from pastoral or agro-pastoral communities.
Table 1

Background characteristics of study population by gender, rural Ethiopia, 2010

 

Total

Women

Men

Variables

N

%

N

%

N

%

Socio-demographic variables

      

Overall

11,919

 

6278

52.7

5641

47.3

Age group, year

      
 

15–19

1342

11.3

770

12.3

572

10.1

 

20–24

1785

15.0

1123

17.9

662

11.7

 

25–29

2196

18.4

1357

21.6

839

14.9

 

30–39

3635

30.5

1921

30.6

1714

30.4

 

40+

2961

24.8

1107

17.6

1854

32.9

Marital status

      
 

Married

9400

78.9

4973

79.3

4427

78.5

 

Never married

1860

15.6

758

12.1

1102

19.6

 

Divorced/Widowed

651

5.5

542

8.6

109

1.9

Educational level

      
 

Never attended/<1 year

6934

58.2

4386

70.9

2548

47.1

 

Primary

2835

23.8

1183

19.1

1652

30.5

 

Secondary or higher

1832

15.4

619

10.0

1213

22.4

Gender of household head

      
 

Female

1794

15.1

1233

19.7

561

10.0

 

Male

10,113

84.8

5041

80.4

5072

90.0

Occupation of household head

      
 

Farmer

10,688

89.7

5599

90.3

5089

91.3

 

Gov't employee/merchant

569

4.8

314

5.1

255

4.6

 

Other

519

4.4

291

4.7

228

4.1

Religion

      
 

Orthodox

4749

39.8

2493

39.8

2256

40.1

 

Islam

4122

34.6

2170

34.6

1952

34.7

 

Protestant

2527

21.2

1331

21.3

1196

21.3

 

Other

494

4.1

270

4.3

224

4.0

Socio-economic status index

      
 

Low

2084

17.5

1123

17.9

961

17.1

 

Low-middle

4192

35.2

2233

35.6

1959

34.8

 

Middle

3586

30.1

1863

29.7

1723

30.6

 

High-middle

1720

14.4

884

14.1

836

14.8

 

High

329

2.8

170

2.7

159

2.8

Settlement pattern

      
 

Pastoral/agro-pastoral

1724

14.5

909

14.5

815

14.5

 

Agrarian

10,195

85.5

5369

85.5

4826

85.6

Region

      
 

Tigray

1152

9.7

622

9.9

530

9.4

 

Afar

358

3.0

191

3.0

167

3.0

 

Amhara

2677

22.5

1409

22.4

1268

22.5

 

Oromia

2852

23.9

1461

23.3

1391

24.7

 

Benshangul-Gumuz

644

5.4

330

5.3

314

5.6

 

SNNP

2063

17.3

1052

16.8

1011

17.9

 

Gambela

1128

9.5

649

10.3

479

8.5

 

Dire Dawa

137

1.1

83

1.3

54

1.0

 

Harari

170

1.4

93

1.5

77

1.4

 

Somali

738

6.2

388

6.2

350

6.2

Behavioral variables

      

Risk partner in past 12 months

      
 

No

11,694

98.1

6177

98.4

5517

97.8

 

Yes

225

1.9

101

1.6

124

2.2

Self-perceived risk of HIV

      
 

No risk

7128

59.8

3581

57.0

3547

62.9

 

Small risk

1183

9.9

573

9.1

610

10.8

 

Moderate/great risk

708

5.9

360

5.7

348

6.2

 

Don’t know

2900

24.3

1764

28.1

1136

20.1

Believes HIV/AIDS is fatal

      
 

No

2113

17.7

1336

21.3

777

13.8

 

Yes

9806

82.3

4942

78.7

4864

86.2

Believes HIV/AIDS can be cured

      
 

No

10,321

86.6

5458

86.9

4863

86.2

 

Yes

1598

13.4

820

13.1

778

13.8

HIV/AIDS knowledge index

      
 

None

4151

34.8

2597

41.4

1554

27.6

 

Low

2592

21.7

1328

21.2

1264

22.4

 

Moderate

3007

25.2

1455

23.2

1552

27.5

 

High

2169

18.2

898

14.3

1271

22.5

HIV/AIDS stigma scale

      
 

No stigma

4222

35.4

1907

30.4

2315

41.0

 

Low stigma

2049

17.2

1020

16.3

1029

18.2

 

Moderate stigma

3009

25.2

1671

26.6

1338

23.7

 

High stigma

2639

22.1

1680

26.8

959

17.0

Talked with partner about HIV

      
 

No

6436

54.0

3668

58.4

2768

49.1

 

Yes

5483

46.0

2610

41.6

2873

50.9

Programmatic variables

      

Walking distance to HF

      
 

<=10 min

9510

79.8

5016

79.9

4494

79.7

 

10–30 min

1639

13.8

861

13.7

778

13.8

 

30+ minutes

770

6.5

401

6.4

369

6.5

Proactively visited HEW

      
 

No

7242

60.8

3839

62.5

3403

62.2

 

Yes

4373

36.7

2304

37.5

2069

37.8

HEW visited home

      
 

No

6511

54.6

3474

57.0

3037

55.9

 

Yes

5016

42.1

2624

43.0

2392

44.1

Source of HIV information

      
 

Never exposed

1207

10.1

833

13.3

374

6.6

 

Only to mass media

745

6.3

338

5.4

407

7.2

 

Community conversations

9967

83.6

5107

81.4

4860

86.2

Model-family

      
 

No

11,221

94.1

5917

95.4

5304

95.1

 

Yes

555

4.7

283

4.6

272

4.9

VHPs in village

      
 

No

5594

46.9

2995

47.7

2599

46.1

 

Yes

6325

53.1

3283

52.3

3042

53.9

About 2 % of respondents reported high-risk sexual partner in the 12 months prior to the survey, and majority (59.8 %) perceived no risk of HIV infection, while only 5.9 % perceived moderate or great risk. Only 18.2 % (14.3 % of women and 22.5 % of men) had comprehensive knowledge about HIV/AIDS. While 35.4 % (30.4 % of women and 41 % of men) had no stigma towards people living with HIV, about 22 % (26.8 % of women and 17 % of men) had high levels of stigma.

About 80 % of respondents reside within 10 min walking distance to health facility. About 37 % proactively visited HEWs during the month prior to the survey. Majority (83.6 %) was exposed to HIV/AIDS related information through community conversations. Overall, 25.8 % (23.7 % for women and 28 % for men) had been tested for HIV. Over half (53.1 %) of respondents were from villages with active CHWs, and only 4.7 % were from model-family households.

Univariate logistic regression

The result of univariate logistic regression analysis by gender is presented in Table 2. Socio-demographic factors significantly associated with VCT uptake among both women and men were: age and educational attainment, occupation of household head, wealth index, agro-ecological zone, and region. The results showed that self-perceived risk of HIV, belief on whether HIV/AIDS is fatal, and conversation with partner about HIV/AIDS were significantly associated with VCT uptake in both men and women. VCT uptake increased significantly with increased levels of HIV/AIDS related knowledge index, while it decreased significantly with increasing stigma scale. Risky sexual partner in the past 12 months was significantly associated with VCT uptake only among women. Contact with HEWs, sources of HIV information, model-family, and CHWs were significantly associated with the use of VCT in both genders. However, proximity to a health facility was only significantly associated with VCT uptake among women.
Table 2

Result of logistic regression of the association between VCT uptake and explanatory factors by gender, rural Ethiopia 2010

 

Women

Men

Variables

Unadjusted

Adjusted

Unadjusted

Adjusted

 

OR

95 % CI

OR

95 % CI

OR

95 % CI

OR

95 % CI

Socio-demographic variables

Age group, year

      
 

15–19

1

 

1

 

1

 

1

 
 

20–24

1.43

1.13–1.80

1.43

1.06–1.92

1.93

1.51–2.47

1.68

1.19–2.37

 

25–29

1.07

0.80–1.44

1.13

0.73–1.76

1.99

1.50–2.63

1.84

1.26–2.68

 

30–39

0.85

0.65–1.11

0.85

0.57–1.27

1.51

1.16–1.96

1.33

0.86–2.06

 

40+

0.56

0.42–0.73

0.66

0.45–0.96

1.09

0.82–1.46

1.08

0.67–1.72

Marital status

      
 

Married

1

 

1

 

1

 

1

 
 

Never married

1.3

0.99–1.71

0.69

0.47–1.02

0.95

0.78–1.17

0.76

0.54–1.09

 

Divorced/Widowed

1.38

1.01–1.90

1.11

0.71–1.75

0.86

0.42–1.76

1.03

0.47–2.26

Educational level

      
 

Never attended/<1 year

1

 

1

 

1

 

1

 
 

Primary

2.41

1.90–3.06

1.71

1.29–2.26

2.04

1.56–2.68

1.68

1.35–2.09

 

Secondary and higher

3.1

2.28–4.20

1.66

1.21–2.28

3.12

2.36–4.13

2.37

1.79–3.14

Gender of household head

      
 

Female

1

 

1

 

1

 

1

 
 

Male

0.9

0.62–1.30

0.53

0.39–0.73

1.77

1.14–2.75

1.11

0.80–1.54

Occupation of household head

      
 

Farmer

1

 

1

 

1

 

1

 
 

Gov't employee/merchant

2.58

1.79–3.70

1.65

1.13–2.41

1.95

1.46–2.61

1.41

0.89–2.24

 

Other

1.02

0.60–1.72

1.29

0.64–2.59

0.66

0.39–1.11

1.06

0.53–2.12

Religion

      
 

Orthodox

1

 

1

 

1

 

1

 
 

Islam

0.88

0.54–1.43

1.84

1.22–2.78

0.8

0.48–1.32

1.56

1.06–2.31

 

Protestant

1.21

0.77–1.89

0.98

0.61–1.57

1.45

0.99–2.12

1.27

0.78–2.06

 

Other

0.9

0.48–1.67

1.37

0.64–2.94

0.79

0.46–1.34

1.27

0.49–3.28

Socio-economic status index

      
 

Low

1

 

1

 

1

 

1

 
 

Low-middle

1.44

1.04–2.00

1.24

0.94–1.64

1.52

1.07–2.16

1.21

0.88–1.66

 

Middle

2.01

1.35–3.00

1.30

0.93–1.80

1.77

1.21–2.60

1.01

0.72–1.43

 

High–middle

2.46

1.63–3.74

1.43

1.03–1.98

2.4

1.60–3.60

1.11

0.75–1.64

 

High

4.48

2.53–7.94

1.86

1.12–3.09

3.36

1.99–5.68

1.3

0.73–2.29

Settlement pattern

      
 

Pastoral

1

 

1

 

1

 

1

 
 

Agrarian

2.02

1.04–3.90

1.4

0.78–2.50

3.08

1.79–5.30

1.92

1.15–3.20

Region

      
 

Tigray

1

 

1

 

1

 

1

 
 

Afar

0.35

0.18–0.67

0.38

0.14–1.00

0.31

0.18–0.56

0.43

0.16–1.2

 

Amhara

0.42

0.22–0.82

0.69

0.41–1.16

0.56

0.29–1.1

0.84

0.46–1.54

 

Oromia

0.26

0.14–0.47

0.34

0.16–0.74

0.36

0.19–0.68

0.4

0.18–0.85

 

Benshangul-Gumuz

0.31

0.12–0.82

0.53

0.21–1.33

0.37

0.17–0.81

0.44

0.15–1.27

 

SNNP

0.57

0.31–1.06

0.74

0.36–1.53

0.78

0.45–1.35

0.73

0.37–1.47

 

Gambela

0.19

0.09–0.36

0.36

0.16–0.83

0.18

0.09–0.38

0.21

0.08–0.54

 

Dire Dawa

0.75

0.17–3.26

1.81

0.46–7.10

0.67

0.41–1.11

1.92

0.82–4.52

 

Harari

0.19

0.11–0.35

0.50

0.23–1.10

0.14

0.09–0.24

0.2

0.1–0.42

 

Somali

0.02

0.01–0.07

0.03

0.01–0.11

0.03

0.01–0.08

0.08

0.03–0.21

Behavioral variables

Risk partner in past 12 months

      
 

No

1

 

1

 

1

 

1

 
 

Yes

1.93

1.16–3.21

1.91

0.79–4.64

1.86

0.95–3.66

1.91

0.63–5.83

Self perceived risk of HIV

      
 

No risk

1

 

1

 

1

 

1

 
 

Small risk

1.99

1.29–3.06

2.34

1.35–4.07

1.46

0.94–2.25

1.86

1.15–3.02

 

Moderate/great risk

0.73

0.42–1.26

0.95

0.60–1.51

1.01

0.59–1.74

1.26

0.86–1.84

 

Don’t know

0.25

0.17–0.36

0.73

0.50–1.09

0.27

0.19–0.40

0.62

0.42–0.90

Believes HIV/AIDS is fatal

      
 

No

1

 

1

 

1

 

1

 
 

Yes

3.71

2.58–5.34

0.88

0.61–1.28

3.52

2.50–5.00

1.27

0.89–1.82

Believes HIV/AIDS can be cured

      
 

No

1

   

1

   
 

Yes

1.25

0.91–1.73

  

0.94

0.69–1.27

  

HIV/AIDS knowledge index

      
 

None

1

 

1

 

1

 

1

 
 

Low

3.45

2.43–4.91

1.50

1.06–2.13

2.71

1.86–3.93

1.50

1.05–2.15

 

Moderate

4.51

3.12–6.51

1.57

1.11–2.23

3.71

2.45–5.63

1.56

1.05–2.33

 

Comprehensive knowledge

8.39

5.37–13.11

2.32

1.45–3.72

5.98

3.85–9.30

1.96

1.23–3.13

HIV/AIDS stigma scale

      
 

No stigma

1

 

1

 

1

 

1

 
 

Low stigma

0.68

0.51–0.90

0.84

0.65–1.09

0.59

0.47–0.74

0.70

0.56–0.87

 

Moderate stigma

0.42

0.32–0.56

0.67

0.49–0.92

0.38

0.30–0.49

0.58

0.42–0.80

 

High stigma

0.22

0.14–0.72

0.65

0.46–0.93

0.25

0.17–0.36

0.56

0.38–0.80

Talked with partner about HIV

      
 

No

1

 

1

 

1

 

1

 
 

Yes

4.5

3.58–5.7

2.27

1.86–2.77

3.93

2.94–5.25

2.09

1.61–2.71

Programmatic variables

        

Walking distance to HF

      
 

<=10 min

1

 

1

 

1

 

1

 
 

10–30 min

0.55

0.37–0.81

0.76

0.60–0.97

0.76

0.57–1.02

0.80

0.64–1.00

 

30+ minutes

0.45

0.27–0.76

0.60

0.42–0.87

0.62

0.36–1.05

0.76

0.56–1.03

Proactively visited HEW

      
 

No

1

 

1

 

1

 

1

 
 

Yes

2.16

1.74–2.69

1.40

1.13–1.73

1.86

>1.5–2.30

1.23

099–1.52

HEW visited home

      
 

No

1

 

1

 

1

 

1

 
 

Yes

2.16

1.66–2.81

1.22

0.97–1.54

2

1.55–2.60

1.22

0.98–1.53

Exposure to HIV information

      
 

Never exposed

1

 

1

 

1

 

1

 
 

Only to mass media

8.31

3.34–20.71

5.42

1.89–15.54

6.07

2.08–17.76

1.91

0.69–5.29

 

Community conversations

19.68

8.61–45–02

5.92

2.38–14.72

12

4.55–31.59

2.52

0.96–6.65

Household graduated as model-family

      
 

No

1

 

1

 

1

 

1

 
 

Yes

3.06

2.09–4.48

1.50

1.03–2.18

4.34

2.81–6.70

2.65

1.72–4.07

VHPs in village

      
 

No

1

 

1

 

1

 

1

 
 

Yes

3.12

2.14–4.54

1.44

1.00–2.06

2.91

2.02–4.19

1.37

0.98–1.90

Multivariate logistic regression

Women

The result of multivariable logistic regression by gender is presented in Table 2. Socio-demographic factors independently associated with increased VCT uptake among women were: 20–24 years age group (OR = 1.4; 95 % CI 1.1–1.9); attainment of primary (OR = 1.7; 95 % CI 1.3–2.3) and secondary/higher (OR = 1.7; 95 % CI 1.2–2.3) education; household head being merchant or government employee (OR = 1.7; 95 % CI 1.2–2.8); Islam religion (OR = 1.8; 95 % CI 1.2–2.8); and wealth index – middle-high (OR = 1.4; 95 % CI 1.03–2.0) and high (OR = 1.9; 95 % CI 1.1–3.1); while male-headed household was associated with decreased uptake of VCT (OR = 0.5; 95 % CI 0.4–0.7). Women’s marital status and agro-ecological settlement were not significantly associated with VCT uptake.

Women who perceived themselves to be at small risk of HIV were 2.3 times more likely to receive VCT in comparison with those who perceived to have no risk. The odds of VCT uptake among women with comprehensive HIV/AIDS knowledge were 2.3 (95 % CI 1.45–3.72) times higher than those who lacked any HIV/AIDS related knowledge. The uptake of VCT was higher among women who talked about HIV with their partner (OR = 2.27; 95 % CI 1.86–2.77). The uptake of VCT among women with high levels of stigma was significantly lower (OR = 0.65; 95 % CI 0.46–0.93) in comparison with those who showed positive attitude.

Women who walk for more than 30 min to reach the nearest health facility were less likely (OR = 0.60; 95 % CI 0.42–0.87) to receive VCT in comparison with those who reside within 10 min walking distance. The odds of VCT uptake among women who proactively visit HEWs were 1.40 (95 % CI 1.13–1.73) times higher than among those women who did not visit HEWs. The uptake of VCT was higher among women who received HIV information through community conversations (OR = 5.92; 95 % CI 2.38–14.72) in comparison with those who were not exposed to any HIV related information. The odds of VCT uptake among women from model-family were 1.50 (95 % CI 1.03–2.18) times higher than among those from non-model family. Likewise, the odds of VCT uptake among women from villages with active CHWs were 1.44 (95 % CI 1.00–2.06) times higher than among those from villages without CHWs.

Men

Socio-demographic factors independently associated with increased VCT uptake among men were: 20–29 years age group (20–24 years: OR = 1.7; 95 % CI 1.2–2.4 and 25–29 years: OR = 1.8; 95 % CI 1.3–2.7); attainment of primary (OR = 1.7; 95 % CI 1.4–2.1) and secondary/higher (OR = 2.4; 95 % CI 1.8–3.1) education; Islam religion (OR = 1.6; 95 % CI 1.1–2.3); and agrarian (settled) dwellers (OR = 1.9; 95 % CI 1.2–3.2). Marital status, household head’s gender, occupation and wealth index were not significantly associated with VCT uptake among men respondents.

Men who perceived themselves to be at small risk of HIV were 1.86 (95 % CI 1.15–3.02) times more likely to receive VCT in comparison with those who perceived to have no risk; while men who could not state their perceived risk of HIV were less likely be tested (OR = 0.62; 95 % CI 0.42-0.90) compared to those with no risk. The odds of VCT uptake among men with comprehensive HIV/AIDS knowledge were 1.96 (95 % CI 1.23–3.13) times higher than among those men who lacked any HIV/AIDS related knowledge. The uptake of VCT was higher among men who talked with their partner about HIV (OR = 2.09; 95 % CI 1.61–2.71). The uptake of VCT among men with high levels of stigma towards people living with HIV was significantly lower (OR = 0.56; 95 % CI 0.38–0.80) in comparison with those who showed positive attitude.

The odds of VCT uptake among men from model-family were 2.65 (95 % CI 1.72–4.07) times higher than among their counter parts. All other programmatic variables included in this study were not significant predicators of VCT uptake among men.

Discussion

While the utilization of VCT improved considerably compared to 2005 levels, which is likely due to the increased number of health facilities providing HCT services, introduction of lay counselors and provider-initiated testing initiatives, and increased accessibility to free anti-retroviral drugs [3, 11], the uptake in rural areas was low in comparison with the urban areas [3]. This study examined the association between socio-demographic, behavioral and health service factors and VCT uptake in rural Ethiopia using a nationally representative cross sectional sample of adults. The findings in this study has shown that several socio-demographic, behavioral and health service related factors were associated with HIV testing among rural men and women.

The findings showed that the proportions ever tested were significantly higher among youth, which is somehow encouraging as youth are at particularly higher risk of HIV acquisition. Our findings agree with studies conducted in Ethiopia [3], and elsewhere in Africa [14, 19, 27].

Consistent with the national level EDHS data and other studies, the results show better-educated individuals are more likely to be tested for HIV [3, 16, 19, 28, 29]. Women from households with greater economic wealth were more likely to be tested for HIV consistent with other studies [3, 11]. Education and wealth are positively related to certain risk factors such as premarital sex [30], and associated with higher HIV prevalence [3]. Related with the effect of socio-economic status, women belonging to households whose primary occupation was trade and government job were more likely to use VCT [31].

The results showed significant difference in the uptake of VCT by region, which partly reflect the multicultural characteristics of the country and difference in the pace of implementation of the HEP. The percentage that has ever been tested for HIV ranged from about 2 % in Somali to nearly 50 % in Tigray. The lowest percentages of HIV testing were observed in regions with predominantly pastoral lifestyle, consistent with the overall poor health indicators reported for these regions [32]. The lower uptake of VCT in Gambella is critical as Gambela is one of the regions with the highest level of HIV prevalence (6.5 %) in the country [3]. The remote and harsh climatic condition and the highly mobile and geographically dispersed settlement coupled with poor infrastructure and social services could have contributed to the observed low uptake of VCT. However, the findings of our study suggest that agro-ecological zone had varied influence on VCT uptake in men and women. While belonging to an agrarian community was a strong predictor of VCT uptake among men, the association was non-significant among women. The overall low uptake of VCT among women regardless of agro-ecological zone suggests that all rural women face similar socio-cultural barriers on VCT utilization [20]. Respondents belonging to Muslim religion were more likely to be tested, which is in contrast to other studies that reported either lack of association [33], or the opposite findings [12].

With regard to behavioral factors, VCT uptake increased sharply with increased HIV/AIDS related knowledge, which is consistent with other studies [16, 34]. The observed strong inverse association between stigma and VCT uptake is consistent with other studies, and in light of the high levels of stigma, the findings suggest that fear of stigma and discrimination is an important barrier to HIV testing [10, 12, 13, 19, 35]. The result showed that respondents with a small-perceived risk of HIV were more likely to use VCT compared to those with no-perceived risk of HIV. The low uptake of VCT among those who perceived no risk of infection, which could be due to lack of motivation to undergo HIV testing, has negative effect on the overall VCT uptake as this perception was common (60 %). In contrast to rural Tanzania [17], but consistent with findings from rural Uganda and Southern African countries [3638], there was no evidence to suggest that a high-perceived risk of HIV was independently associated with VCT uptake. A study among youth in Ethiopia reported high-perceived risk of infection was associated with low VCT uptake [39], which could be due to fear of discrimination, in light of the prevalent stigma [22]. Individuals who talked with their partners about HIV/AIDS were more likely to use VCT, likely due to its positive effect on stigma and discrimination.

While all the programmatic factors affected VCT uptake among women, model-family was the only factor that affected VCT uptake among men. Women who resided further away from health facility were less likely to undergone VCT, likely due to household responsibilities limiting their time to travel long distance to seek health services. Women who were exposed to HIV-related information through community conversation were 5.9 times more likely to use VCT in comparison with women who were never exposed to such information. It has been reported that exposure to community conversation, particularly when individuals who were tested speak openly about HIV, led to greater acceptance and uptake of testing [37, 40, 41], which could be due to peer pressure [42]. The observed influence of volunteer CHWs and contact with HEWs in the uptake of VCT among women may be related to increased frequency of conversation about HIV. With regards to contact with HEWs, while proactive contact was associated with HIV testing, being visited at home by HEWs did not have noteworthy effect on HIV testing, which suggests that motivation play an important role, over and above the mere exposure to health information, in influencing HIV testing behaviors. On the other hand, the lack of influence of community conversation, CHWs and contact with HEWs on VCT uptake among men, and the strong influence of model-family on VCT uptake among men suggests that it takes intensive effort to bring about meaningful behavioral change among men. To graduate as a model-family, households undergo intensive theoretical and practical training on the various HEP services including HIV/AIDS for about 96 h, and are required to implement and adopt the HEP package [4].

In the present study, men were relatively more likely to get tested than women, which is consistent with EDHS data [3], and other studies from rural Uganda [43], South Africa [44], and Zimbabwe [16]. Socio-economic status and distance to health facility, which are important barriers to VCT use among women, could have contributed to the lower uptake among women [38]. Moreover, gender inequality and socio-cultural barriers could affect VCT demand among women [20]. In Ethiopia, fear of abandonment and divorce following discovery of HIV positive status were some of the barriers reported by women for freely seeking VCT services [22]. Although not all studies confirm gender differences in general attitudes toward testing [19]; women’s decisions about testing could be affected by their childbearing and breastfeeding plans, and their husband’s opinion [4547]. Our finding, on the other hand, contrast with reports of higher testing rates among women from a number of other studies [25, 31, 37, 4850], which could be due to more frequent interaction with health services during antenatal care and prevention of mother to child transmission programs [40, 41]. However, the observed disparity could be largely due to differences in the study design and study population (rural vs urban; national vs localized samples).

Limitations

The study has some limitations. Due to the cross-sectional design of the current study, causal inferences cannot be drawn from the associations. Since data was collected in face-to- face interviews, information bias might occur due to recall, sensitivity of questions, and social desirability factors. Information bias could have contributed to the low percentage (<2 %) of respondents who reported high-risk sexual behavior, which might have resulted in the lack of an association with HIV testing. Similarly, HIV testing status may be subjected to information bias. To minimize such bias, interviewers were trained to ask questions in a non-judgmental way, and respondents were assured that personal information would be confidential and de-identifiable. Moreover, engagement in high-risk sexual practice and undergoing HIV testing are easily remembered, and thus recall bias may not be a major challenge. Despite these limitations, the use of a large representative population-based sample allowing for greater generalizability and the examination of a wide range of explanatory factors were the main strengths of the current study.

Conclusion

Findings from the current study have important implications for developing intervention programs targeting rural areas in Ethiopia. First, the findings highlight individual- and community-level characteristics that influence the utilization of HIV testing, and the need for more intense efforts targeting the less educated, poor and farming families [51]. Second, the variation across regions and agro-ecological zones requires targeted capacity building and adopting appropriate delivery modalities such as mobile VCT services for pastoral regions. Third, promoting partner and community conversation, which has been the core government intervention in the national HIV/AIDS strategy [4], and speeding the scale-up of the model-family implementation should be given utmost priority to address the HIV related low knowledge and prevalent stigma. The recently introduced women development army network, which links five households to one model family, will be an important platform for effective community conversation and peer education [4]. Finally, making VCT a routine service in all health posts and provision of home-based VCT as well as provider initiated modes of testing would address the physical access barrier to rural women, while also tackling demand side barriers such as stigma and confidentiality [5153].

Availability of data and materials

The dataset supporting the conclusions of this article is available in the Open Science Framework repository (https://osf.io/7hqz8/files/).

Abbreviations

CHWs: 

community health workers

EDHS: 

Ethiopian Demographic and Health Survey

HCT: 

HIV counseling and testing

HEP: 

health extension program

HEW: 

health extension worker

HIV/AIDS: 

Human Immunodeficiency Virus/Acquired Immunodeficiency Disease Syndrome

PHCU: 

Primary Health Care Unit

PMTCT: 

prevention of mother to child transmission

SES: 

socio-economic status

SNNP: 

Southern Nations and Nationalities and People

VCT: 

voluntary counseling and testing

Declarations

Acknowledgements

The authors gratefully acknowledge the financial support from Blaustein Foundation, and UNICEF and WHO Ethiopia country offices. The authors would like to thank the survey coordinators, field workers, and study participants. The authors wish to thank the Federal Ministry of Health for allowing its staff to participate in the study.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Center for National Health Development in Ethiopia, Columbia University
(2)
The Earth Institute, Columbia University
(3)
College of Health Sciences, Mekelle University

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© Teklehaimanot et al. 2016