DEMOGRAPHIC

AND

HEALTH

SURVEYS

DHS WORKING PAPERS

2015 No. 119

Rune N. Phimemon

Michael J. Mahande

Habib O. Ramadhani

September 2015

This document was produced for review by the United States Agency for 

International Development.

Factors Associated with Changes in Uptake 

of HIV Testing among Young Women 

(age 15–24) in Tanzania 

from 2003 to 2012

Factors Associated with Changes in Uptake of HIV Testing 

among Young Women (age 15–24) in Tanzania 

from 2003 to 2012

Rune N. Phimemon1,2 

Michael J. Mahande2 

Habib O. Ramadhani1,2

ICF International 

Rockville, Maryland, USA 

September 2015 

1

Kilimanjaro Christian Medical Centre, Moshi, Tanzania 

2

Kilimanjaro Christian Medical University College, Moshi, Tanzania 

Corresponding author: Michael J. Mahande, Department of Epidemiology and Applied Biostatistics, 

KCMUCo, jmmahande@gmail.com 
ACKNOWLEDGMENTS 

We are grateful to the USAID for funding the research project through the DHS Fellows program 

implemented by ICF International. Our gratitude extends to Joy Fishel for her constructive 

comments that helped to improve our manuscript and to other reviewers. We thank Sarah 

Staveteig, Wenjuan Wang and other DHS facilitators for their support throughout the DHS training 

period. 

Editor: Bryant Robey 

Document Production: Natalie La Roche 

The DHS Working Papers series is a prepublication series of papers reporting on research in 

progress that is based on Demographic and Health Surveys (DHS) data. This research is carried 

out with support provided by the United States Agency for International Development (USAID) 

through The DHS Program (#AID-OAA-C-13-00095). The views expressed are those of the 

authors and do not necessarily reflect the views of USAID or the United States Government. 

The DHS Program assists countries worldwide in the collection and use of data to monitor and 

evaluate population, health, and nutrition programs. For additional information about the DHS 

Program contact: DHS Program, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 

20850, USA. Phone: +1 301-407-6500; Fax: +1 301-407-6501; Email: reports@dhsprogram.com; 

Internet: www. dhsprogram.com. 

Recommended citation: 

Phimemon, Rune N., Michael J. Mahande, and Habib O. Ramadhani. 2015. Factors Associated 

with Changes in Uptake of HIV Testing among Young Women (age 15–24) in Tanzania from 2003 

to 2012. DHS Working Papers No. 119. Rockville, Maryland, USA: ICF International.
iii 

ABSTRACT 

This study explored the factors associated with changes in uptake of HIV testing in 

Tanzania, based on an analysis of data from the 2003–04 Tanzania HIV/AIDS Indicator Survey 

(THIS) and the 2007–08 and 2011–12 Tanzania HIV/AIDS and Malaria Indicator Surveys 

(THMIS). The study population consisted of young women age 15–24 at the time of the survey. 

Multivariate decomposition analysis was used to assess factors associated with the changes in HIV 

testing uptake between the 2003-04 and 2007-08 surveys and between the 2007-08 and 2011-12 

surveys. 

HIV testing uptake among the study population was 7%, in 2003-04, 31% in 2007-08 and 

40% in 2011-12. The time period of the survey had an important effect on uptake of HIV testing 

independent of other covariates. Women’s characteristics that were significantly associated with 

higher odds of HIV testing across the surveys were age (20–24), education level (primary and 

secondary), ever being married, having at least one lifetime sexual partner, having a sexually 

transmitted infection (STI) or STI symptoms and attending antenatal care (ANC). 

According to the decomposition models used in the study, changes in women’s 

characteristics (endowments) in the 2003–04 surveys compared with the 2007–08 survey would 

have resulted in a decrease in HIV testing uptake in the absence of the changes in effects of these 

characteristics, which contributed most of the changes in HIV testing uptake. Comparing 2007–08 

with 2011–12, the changes in endowments contributed to 21% of the changes in HIV testing 

uptake, while 78% of the changes were attributed to coefficients. 

Keywords: HIV testing, uptake

1 

INTRODUCTION 

Approximately 35.3 million people were estimated to be HIV infected in 2012 (UNAIDS 

2013). In recent years increased coverage of anti-retroviral therapy (ART) has led to a decline in 

morbidity and mortality related to HIV and its associated opportunistic infections (Ivers et al. 2005; 

Ferradini et al. 2006; Barth et al. 2008). Studies have showed a global decline in HIV epidemics 

among general populations (Beyrer & Abdool Karim 2013). Despite these successes, variation in 

HIV testing uptake exists across regions (Staveteig et al. 2013). In 2010, for example, in Burundi, 

Tanzania and Rwanda uptake of HIV testing among men and women was 37%, 55% and 75% 

respectively (Staveteig et al. 2013), suggesting that where a person lives may influence their 

likelihood of being tested for HIV. 

HIV counselling and testing (HTC) is an integral component of HIV preventive strategies. 

Studies using mathematical models have revealed that about 50% of new HIV infections are from 

HIV-infected persons who are unaware of their HIV status, making it more difficult to prevent the 

spread of the infection (Hall et al. 2012). While early diagnosis and treatment are associated with 

good treatment outcomes (Gianella et al. 2011), delayed diagnosis and treatment increase the 

disease burden and represent missed opportunities for prevention (Siegfried et al. 2010; Miro et 

al. 2011). 

Knowing one’s HIV status may influence change in personal behaviour, a critical part of 

efforts to prevent HIV (WHO 2005; Cock et al. 2010). Individuals tested positive for HIV are 

likely to be linked to HIV care and treatment. Among the benefits of linking patients in HTC are 

reducing mother-to-child transmission, preventing uninfected partners from becoming infected, 

improving the quality of life, reducing morbidity and mortality related to opportunistic infections 

and reducing the frequency of hospitalizations (Mabuto et al. 2014). High cost associated with the 

management of HIV-infected patients underscores the importance of preventive efforts in 

addressing HIV (Ng’ang'a et al. 2014). 

The concept of test and treat has been studied, and results have shown that receiving HIV 

treatment was associated with a 96% reduction in new infections among sero-discordant couples. 

These findings highlight the need to increase HIV testing uptake and treatment (Cohen et al. 2011). 

Furthermore, one of the prevailing concepts of HIV prevention effort is increasing the number of 
2 

patients being tested and treated. Increasing those receiving ART in the population reduces 

community viral load (CVL). The idea behind reducing CVL is that as the number of individuals 

being tested and receive ART increases, greater numbers of HIV-infected persons will be 

virologically suppressed, leading to reduced CVL, and consequently reduced incidence of HIV 

infection in the general population (Das et al. 2010). 

Tanzania is one of the sub-Saharan countries heavily affected by the HIV epidemic. 

According to the 2007–08 HIV/AIDS and Malaria Indicator survey (TACAIDS 2008), the 

prevalence of HIV declined from 7% in 2004 to 6% in 2008. Decreases were greatest among men 

in the urban areas but the overall change was not statistically significant (TACAIDS 2008). More 

recently, the 2011–12 survey (TACAIDS 2013) indicated an overall decline in national HIV 

prevalence from 6% in 2007–08 5%, though this decline was also not statistically significant 

(TACAIDS 2013). Despite these declines in HIV prevalence, in 2012 only 62% of women and 

47% of men age 15–49 had ever tested for HIV and received their results, leaving a large 

proportion of people unaware of their HIV status (TACAIDS 2014). Higher levels of HIV testing 

uptake are needed in a test and treat model if reduction in HIV incidence is to be realized (Granich 

et al. 2009; Dodd et al. 2010; Alsallaq et al. 2013) 

The principal focus of this paper is among young women at high risk of HIV acquisition 

in Tanzania. While previous surveys indicated a consistent decline in HIV prevalence among boys 

age 15–24, the decline is notable among girls age 15-19 but not among women aged 20-24 

(TACAIDS 2014). Among other factors, difference in HIV prevalence in this subgroup of 

population could be attributed by early age at sexual debut and early marriages among young 

women compared with young men. Early age at sexual debut was also noted to be associated with 

increased risk of HIV infection among young women in Kenya (Gitonga et al. 2012). It is 

particularly critical for young women at the debut of their sexual and reproductive lives to have 

access to information about their HIV status through routine HIV testing. 

The Tanzanian Government in collaboration with international donors have significantly 

expanded and decentralized centers for HIV testing care and treatment. Between 2004 and 2007 

Tanzania made changes in national HIV/AIDS policy to increase availability and access to care 

and treatment services, meanwhile building capacity of health care workers (TACAIDS 2008). In 

2004, the government started to provide care and treatment services such as free anti-retroviral 
3 

drugs. In 2007, the government rolled out the care and treatment services closer to the community 

(health centres and dispensaries). During the same year, a new approach, Provider Initiated Testing 

and Counseling (PITC), was adopted to complement the voluntary counselling and testing 

approach to allow more people who come into contact with health care providers to be offered 

HIV testing to determine their HIV serostatus. In addition, the national HIV counselling and testing 

campaign was launched in 2007 by the President of Tanzania as an effort to mobilize more people 

to undergo HIV testing to determine their HIV serostatus and to establish linkages between 

prevention, care, treatment and social support. Furthermore, in 2008 Tanzania established a law 

against stigma and discrimination for people living with HIV/AIDS (PLWHA) to intensify 

community actions (TACAIDS 2008). 

Despite of these extensive efforts, uptake of HIV testing among young women is relatively 

low. Understanding factors associated with HIV testing uptake in this population is critical. In the 

present study, we first explored the trend in HIV testing uptake among young women age 15–24 

between 2003–04 and 2011–12. Secondly, we evaluated individual and contextual factors 

associated with the changes in HIV testing uptake comparing the 2003–04 THIS, the 2007–08 

THMIS and the 2011–12 THMIS. 

METHODS 

Study Design and Population 

In Tanzania, the Demographic Health Surveys (DHS), HIV/AIDS Indicator Surveys 

(THIS) and HIV/AIDS and Malaria Indicator Surveys (THMIS) have collected nationally 

representative data at regular intervals through cross-sectional surveys. Three such surveys 

including HIV serostatus testing have been conducted: 2003–04, 2007–08 and 2011–12. We used 

data from the THIS and THMIS to evaluate trends in uptake of HIV testing and factors associated 

with the changes in HIV testing uptake among young women age 15-24 from Tanzanian Mainland. 

Secondary data analyses were performed using the 2003–04 THIS as well as the 2007–08 and 

2011–12 THMIS. 

 
4 

Selection of the Study Participants and Data Sources 

The study population was restricted to young women (age 15–24), as this group is 

considered as one of the potentially high-risk populations for HIV infection. The final weighted 

total sample size was 9,252, from the three successive surveys (Figure 1). 

Data collection 

Prior to each survey, and in consultation with stakeholders and donors, a Technical 

Working Group in Tanzania adapted standardized questionnaires from DHS and AIS surveys for 

the health needs of Tanzania. These questionnaires were then translated into Kiswahili. During the 

surveys, after obtaining informed consent, standardized questionnaires were administered to 

participating individuals. Among other things, questionnaires captured information on sociodemographic characteristics (age, gender, marital status, education, residence, religion, 

employment, asset ownership); biological (ever had a sexually transmitted infection (STI) in the 

last 12 months, received HIV test results) and antenatal care (ANC) for recent births. 

 
5 

Figure 1. Selection of study subjects 

>24: women older than age 24 

Variables and Definitions 

The outcome variable is the proportion of young women who reported that they were tested 

for HIV and received test results within two years preceding the surveys. 

Independent variables 

The independent variables explored in this study are summarized in Table 1. These include 

the following: 

Socio-demographic variables: Respondent’s age (15–19, 20–24), place of residence (rural, 

urban), administrative zone (Central, Lake, Northern, Eastern, Western, South West Highlands 

Southern Highlands, and Southern), employment status (employed, not employed), number of 

lifetime sexual partners (0, 1, 2, >2). Those with missing values on number of lifetime sexual 

partners were assumed to be >2). 

Zones were used rather than administrative regions in order to have consistency across the 

surveys. Between 2003 and 2012, some of the regions were split to form new districts and regions, 

and thus the 2011–12 survey has more administrative regions than the 2003–-04 survey. All the 

regions, however, (new and old) belong to the same zones and the geographical coverage of the 

zones has remained consistent throughout the surveys. Composition of the administrative regions 

All women age 15-49

2003/04 2007/08 2011/12

6,862 9,343 10,967

Unweighted =

2,843

Weighted =2,388

Unweighted =

3,816

Weighted =3,165

Unweighted =

4,404

Weighted =3,699

Above 24 

years old

4,020

Above 24 

years old

5,527

Above 24 

years old

6,563

Not tested 

in survey

0

Not tested 

in survey

231

Not tested 

in survey

250
6 

in their respective zones is follows; Eastern (Morogoro, Coastal, Dar es Salaam), Northern 

(Kilimanjaro, Tanga, Arusha), Lake (Mwanza, Geita, Mara, Simiyu, Shinyanga), Central 

(Dodoma, Manyara, Singida), Western (Kigoma, Tabora), South-west highlands (Katavi, Rukwa, 

Mbeya), Southern highland (Iringa, Njombe, Ruvuma) and Southern (Lindi, Mtwara). 

Biological variables 

Reported having an STI or symptoms of STI in the last 12 months, or not. Birth and 

antenatal clinic visit in the past two years preceding the surveys. Women who had a birth in the 

two years prior to the survey were asked whether they received any ANC (any number of visits) 

from any provider for their most recent birth. Respondents were grouped accordingly; those who 

did not give birth in the past two years, those who gave birth and received any ANC, those who 

gave birth but did not attend any ANC. 

Statistical Analysis 

Statistical analyses were conducted using STATA version 12. To evaluate the trend in 

uptake of HIV testing across three consecutive surveys, we performed descriptive analyses of HIV 

testing stratified by selected variables. Analyses were done separately for the periods 2003–2007, 

2007–2011 and 2003–2011. Pooled logistic regression models were run for each of the two subperiods (2003-04 to 2007-08 and 2007-8 to 2010-11) to determine whether year of survey was 

associated with testing uptake independently from other factors. The change in HIV testing uptake 

between the three cross-sectional surveys can be attributed to the change in the distribution of 

selected characteristics (compositional changes or endowments) as well as the change in the effects 

of the selected characteristics (effects changes or differences in coefficients). 

Multivariate decomposition models, which are used for portioning changes over time into 

components attributable to changing effects and changing composition or characteristics, were 

used to determine factors associated with changes in HIV testing uptake across the survey periods 

The difference observed in HIV testing uptake was decomposed into components attributable to 

differences in characteristics between surveys (i.e. compositional differences or endowments) and 

group differences in effects of characteristics (i.e. differences in coefficients or behavioural 

responses). For example, changes in HIV testing can be due to differences in distribution of 

employment status as well as due to the effects of employment between surveys. 
7 

All analyses performed in this study were weighted for probability sampling and nonresponse, as is standard in all surveys that are part of the DHS Program. Because we restricted our 

outcome to respondents who had HIV serostatus results, we used HIV weight. All associations 

were deemed statistically significant at cut off p-value of less than 0.05. Complex sampling (multistage sampling and stratification) and 95% confidence intervals were considered and SVY set 

(STATA survey prefix) command was for survey data. 

Ethical Consideration 

The THIS and THMIS surveys received approval by the Tanzania National Institute of 

Medical Research (NIMR), the Institutional Review Board (IRB) of ICF International, and the 

U.S. Centers for Disease Control and Prevention (CDC). All adult respondents gave informed 

consent. As part of the DHS fellowship, the authors submitted a proposal to the DHS Program/ICF 

International and received permission to download and use the data for this study. The DHS 

Program authorized data access; and the data was used solely for the purpose of the current study. 

RESULTS 

Trends in Uptake of HIV Testing 

Figure 2 depicts trends in the uptake for HIV testing and receiving results in the two years 

preceding the survey, for three consecutive surveys among the study population. HIV testing 

uptake increased remarkably, from 7% in 2003-04 to 31% in 2007-08 and 40% in 

2011–12. 
8 

Figure 2. Percentage of women age 15-24 who tested for HIV and received results over the 

3 successive surveys 

Characteristics of the Study Participants 

Table 1 shows the socio-demographic characteristics of the study participants. In all three 

surveys, women age 15–19 outnumbered those age 20-24, and over 65% were living in rural areas. 

Most women had a primary level of education (71% in 2003-04, 70% in 2007–08 and 60% in 

2011–12). Concerning their lifetime number of sexual partners, 31% of women reported no sexual 

partners, 34% reported one lifetime sexual partner, and 9% reported two lifetime sexual partners. 

The 2003–04 survey seemed to have a higher proportion of women reporting more than two 

lifetime sexual partners (18%) compared with the 2007–08 and 2011–12 surveys both at 14%. 

Most women were employed (63% in 2003–04, 607% in 2007–08 and 64% in 2011–12). 

The percentage of women who were HIV-positive declined from 4% in 2003–04 to 3% in 2011–

12. Across the three surveys, most of the women had not had a birth in the two years preceding 

the survey—at 66%, 68% and 68% for the 2003–04, 2007–08 and 2011–12 surveys respectively. 

About one-third of the women, 31%, reported giving birth and attending ANC in the two years 

preceding the survey, across the three surveys. 

 

6.5%

30.8%

39.8%

0

5

10

15

20

25

30

35

40

45

2003/4 2007/8 2011/12

Percentage
9 

Table 1. Percentage distribution of socio-demographic characteristics of the 

respondents for Tanzania HIV/AIDS and Malaria Indicator Surveys (2003, 2007, and 

2011) 

Characteristics 

2003

(n=2,388) 

2007 

(n=3,165) 

2011 

(n=3,699) 

Age (year) 

15-19 51.7 53.1 55.9 

20-24 48.3 46.9 44.1 

Residence 

Urban 34.2 26.1 26.6 

Rural 65.8 73.9 73.4 

Region 

Central Zone 10.8 8.0 9.0 

Lake zone 25.4 28.9 28.9 

Northern Zone 13.0 13.0 11.8 

Eastern Zone 24.4 15.5 16.0 

Western Zone 8.1 11.6 9.6 

South West Highlands Zone 9.3 9.6 10.2 

Southern Highlands Zone 7.8 7.5 9.7 

Southern Zone 5.2 5.8 4.8 

Educational level 

No education 17.2 17.9 13.3 

Primary 71.3 70.4 59.5 

Secondary and above 11.6 11.6 27.1 

Marital status 

Never married 51.2 51.2 55.2 

Ever Married 48.8 48.9 44.8 

Number of life sex partners 

0 29.8 31.0 31.7 

1 33.9 34.0 36.0 

2 18.1 20.0 18.1 

3+ 18.1 14.9 14.2 

Blood test result 

HIV negative 96.0 96.2 97.2 

HIV positive 4.0 3.8 2.8 

Currently working 

Not working 37.0 40.3 36.2 

Working 63.0 59.7 63.8 

Had STI in last 12 months? 

No 98.6 98.4 98.2 

Yes 1.4 1.6 1.8 

Birth and attended ANC 

No birth <2 years preceding the survey 66.4 68.2 68.1 

Had birth within 2 years and attended ANC 30.6 31.3 30.9 

Had birth within 2 years but not attended ANC 3.0 0.6 0.9 

 
10 

Changes in HIV Testing in Relation to Women’s Characteristics 

Table 2 summarizes changes in uptake of HIV testing in relation to participant’s 

characteristics. In order to assess the change, analysis of HIV testing was divided in two phases—

between the 2003–04 and 2007–08 surveys, and between the 2007–08 and 2011–12 surveys. 

Overall, HIV testing uptake increased by 24 percentage points between 2003–04 and 2007–08, 

and 9 percentage points between 2007–08 and 2011–12, reflecting a more rapid rate of change in 

the former phase than in the latter. HIV testing uptake increased both among women age 15–19 

and 20–24; however, the change was greater among women age 20–24. Among women residing 

in urban areas, uptake of HIV testing increased by 27 percentage points between the 2003–04 and 

2007-08 surveys, nearly six times the change from 2007–08 to 2011-12, at 5 percentage points. 

Within the surveys, the change in HIV testing uptake was greater among married women 

compared with unmarried women, and also greater among HIV-positive women compared with 

HIV–negative women. Compared with women with no birth in the two years preceding the survey, 

the change in HIV testing was greater among those who had a birth and attended ANC (46 

percentage points versus 14 percentage points in phase 1, and 20 percentage points versus 4 

percentage points in phase 2. The change in HIV testing uptake in phase 1 was much greater among 

women with more than two lifetime sexual partners, at 38 percentage points, than among women 

with no sexual partners, at 5 percentage points, while in phase 2 the difference was smaller (see 

Table 2). 

 
11 

Table 2. Trends in HIV testing among women age 15-24: The percentage who have been tested for HIV 

and received the results in the two years preceding the survey, by socio-demographic characteristics 

for TMHIS 2003, 2007 and 2011 

2003/04 

(n=2,388) 

2007/08 

(n=3,165) 

2011/12 

(n=3,699) 

Percentage point difference in 

HIV testing 

Characteristics 

Phase 1 

2007-2003 

Phase 2

2011-2007 2011-2003

Age(year) 

15-19 5.8 21.3 27.1 15.5 5.8 21.3 

20-24 7.3 41.5 55.9 34.2 14.4 48.6 

Residence 

Urban 13.0 39.9 44.6 26.9 4.7 31.6 

Rural 3.2 27.5 38.1 24.3 10.6 34.9 

Zones 

Central Zone 5.2 25.8 37.9 23.7 6.1 29.8 

Lake zone 5.3 23.9 36.5 26.8 7.3 34.1 

Northern Zone 8.3 33.1 37.7 28.4 8.7 37.1 

Eastern Zone 11.9 39.1 42.9 21.4 15.6 37.0 

Western Zone 5.8 40.5 45.0 25.4 11.2 36.6 

South West Highlands Zone 3.9 18.9 32.1 15.0 13.2 28.2 

Southern Highlands Zone 3.1 41.7 48.4 38.6 6.7 45.3 

Southern Zone 1.6 30.0 47.4 28.4 17.4 45.8 

Educational level 

No education 2.5 25.2 33.5 22.7 8.3 31.0 

Primary 5.9 30.5 40.1 24.6 9.6 34.2 

Secondary and above 16.3 40.7 42.5 24.4 1.8 26.2 

Marital status 

Never married 6.8 20.2 27.9 13.4 7.7 21.1 

Ever Married 6.3 41.8 54.5 35.5 12.7 48.2 

Number sex partners in lifetime 

0 4.5 9.6 13.7 5.1 4.1 9.2 

1 7.9 38.5 48.3 30.6 9.8 40.4 

2 7.5 40.7 57.4 33.2 16.7 49.9 

3+ 6.4 43.9 54.4 37.5 10.5 48.0 

Blood test result 

HIV negative 6.6 30.5 39.3 23.9 8.8 32.7 

HIV positive 6.5 36.3 57.0 29.8 20.7 50.5 

Currently working 

Not working 8.7 25.1 34.0 16.4 8.9 25.3 

Working 5.3 34.6 42.9 29.3 8.3 37.6 

Had STI in last 12 months? 

No 6.4 30.5 39.4 24.1 8.9 33.0 

Yes 17.2 49.2 62.2 32.0 13.0 45.0 

Birth and attended ANC 

No birth <2 years preceding the survey 8.3 22.6 26.5 14.3 3.9 18.2 

Had birth within 2 years and attended 

ANC 2.8 48.6 69.0 45.8 20.4 66.2 

Had birth within 2 years but not attended 

ANC 6.9 25.3 44.9 18.4 19.6 38.0 

Overall Total 6.6 30.8 39.8 24.2 9.0 33.2 

 
12 

Factors Associated with Uptake of HIV Testing across the Surveys 

Table 3 shows the results from the pooled logistic regression models for the factors 

associated with HIV testing uptake across the two survey phases. Of the factors examined, factors 

that were found to be associated with women’s likelihood to test for HIV and receive results 

included having an education (primary or secondary), ever being married, having had at least one 

lifetime sexual partner and ANC attendance within the two years preceding the survey. Having 

had an STI was also associated with HIV testing uptake, but the association was not statistically 

significant. The coefficient on survey year (using earlier survey as a reference) was positive and 

statistically significant in both surveys. This indicates that, above and beyond the standard 

demographic characteristics predicting HIV testing, women in more recent surveys were more 

likely to have been tested. This difference may relate to changes in the policy environment, for 

example programs encouraging testing, and to greater accessibility of testing sites. 

 
13 

Table 3. Pooled multivariate logistic regression for factors associated with HIV testing 

uptake among women age 15-24 across 2 surveys 

Phase 1 Phase 2 

2003/04-2007/08 2007/08-2011/12

 HIV testing uptake 

Surveys OR (95% CI) OR (95% CI) 

Characteristics 

Survey year 8.71 (6.80 - 11.15) 1.34 (1.11 - 1.61) 

Age (year) 

15-19 1.0 1.0 

20-24 1.02 (0.80 - 1.30) 1.27 (1.07 - 1.50)** 

Residence 

Urban 1.0 1.0 

Rural 0.46(0.36 - 0.58)*** 0.53(0.44 - 0.63)*** 

Region 

South West Highlands Zone 1.0 1.0 

Central Zone 1.35 (0.83 - 2.19) 1.50 (1.06 - 2.14)** 

Lake zone 1.34 (0.89 - 2.02) 1.15 (0.87 - 1.53) 

Northern Zone 2.13 (1.42 - 3.19)*** 1.94 (1.34 - 2.83)** 

Eastern Zone 1.89 (1.25 - 2.85)** 1.74 (1.27 - 2.39)** 

Western Zone 3.15 (2.06 - 4.83)*** 2.65 (1.85 - 3.80)*** 

Southern Highlands Zone 2.08 (1.34 - 3.23)** 2.19 (1.59 - 3.02)*** 

Southern Zone 1.44 (0.84 - 2.46) 1.72 (1.07 - 2.77)** 

Educational level 

No education 1.0 1.0 

Primary 1.90(1.46 - 2.46)*** 1.99(1.57 - 2.52)*** 

Secondary and above 5.46(3.76 - 7.94)*** 4.81(3.48 - 6.63)*** 

Marital status 

Never married 1.0 1.0 

Ever married 1.49(1.15 - 1.92)** 1.36(1.13 - 1.64)*** 

Number sex partners in lifetime 

0 1.0 1.0 

One 4.44(3.21 - 6.15)*** 3.88(3.09 - 4.88)*** 

Two 4.74(3.30 - 6.82)*** 4.59(3.52 - 5.99)*** 

More than two 4.62(3.12 - 6.84)*** 4.77(3.55 - 6.40)*** 

Blood test result 

HIV negative 1.0 1.0 

HIV positive 0.86 (0.55 - 1.35) 1.14 (0.74 - 1.75) 

Currently working 

Not working 1.0 1.0 

Working 0.99 (0.79 - 1.26) 1.09 (0.91 - 1.32) 

Had STI in last 12 months? 

No 1.0 1.0 

Yes 1.62 (0.97 - 2.77) 1.54 (0.97 - 2.44) 

Birth and attended ANC 

No birth <2 years preceding the survey 1.0 1.0 

Had birth within 2 years and attended ANC 1.47(1.18 - 1.83)** 3.10(2.60 - 3.69)*** 

Had birth within 2 years but not attended ANC 1.22(0.48 - 3.10) 1.51(0.83 - 2.75) 

* = significant at 0.05; ** = significant at 0.01; *** = Significant at <0.001 

 
14 

The results from multivariate decomposition regression models are shown in Tables 4a & 

4b. According to the model, in 2003–04 compared with 2007–08, changes in population 

characteristics (endowments) would have resulted in a decline in overall HIV testing in the absence 

of any changes of the effects of these characteristics on the likelihood of being tested. 

Compositional changes such as increased proportion of women residing in rural areas would have 

contributed to decreased odds in HIV testing uptake among women in the absence of the effects 

of other characteristics. Our findings also revealed that a change in uptake of HIV testing in 2003–

04 compared with 2007–08 was attributed to the changes in the effects of characteristics on testing 

factors (coefficients). 

Comparing the 2007–08 and 2011–12 surveys, the changes in endowments contributed to 

22% of the changes in HIV testing uptake, whereas 78% of the changes in HIV testing uptake was 

attributed to differences in the effects of those characteristics (coefficients). Both endowments and 

coefficients were statistically significant in both multivariate decomposition models. Increased 

education level of women (having any level of education versus having none) made it much more 

likely that women would be test for HIV. The increase in the proportion of women with any 

education should have made it more likely for women to be tested, regardless of any changes in 

effects. 

In terms of coefficients, the factors that appear to have a statistically significant 

association with uptake of HIV testing are attending ANC (44%), being age 20–24 (35%), 

having primary education (14%) and residing in a rural area (36%). 
15 

Table 4a. Decomposition changes in HIV testing among women age 15-24 in TMHIS 2003 to 2007 

HIV testing 

Due to Difference in 

Characteristics (E) 

Due to Difference in 

Coefficients (C) 

 Coefficient Percent Coefficient Percent

Age group 15-19 1.0 1.0 

20-24 -0.00007 -0.0288 0.0067 2.7657 

Residence Urban 1.0 1.0 

Rural -0.0089*** -3.666 0.0461** 19.052 

Zone South West Highlands Zone 1.0 1.0 

Central Zone -0.0024* -0.9758 0.0002 0.842 

Lake zone 0.0013 0.5495 -0.0014 -0.5948 

Northern Zone -0.0057*** -0.0035 0.0015 0.6041 

Eastern Zone -0.0064** -2.6346 0.0033 2.1948 

Western Zone 0.0079*** 3.2746 0.0049 2.009 

Southern Highlands Zone -0.0005*** -0.2239 0.0084 3.4742 

Southern Zone -0.0005 0.2094 0.0092 3.8014 

Educational level No education 1.0 1.0 

Primary -0.001*** -0.4253 -0.0137 -5.6564 

Secondary & above 0.0003*** 0.1225 0.0003 -0.1093 

Marital status Never married 1.0 1.0 

Ever married 0.0001** 0.0197 -0.0042 -1.722 

Number sex 

partners in lifetime 0 1.0 1.0 

One 0.0001*** 0.0481 0.0156 6.4606 

Two 0.0052 *** 2.1621 0.0121 5.0033 

More than two -0.0091 *** -3.7754 0.0170 7.0277 

Blood test result HIV negative 1.0 1.0 

HIV positive 0.0004 0.0145 0.0012 0.4751 

Currently working 

Not working 1.0 1.0 

Working -0.0006 -0.2258 0.0092 3.8152 

Had STI or 

symptoms of STI 

No 1.0 1.0 

Yes 0.0001 0.0205 -0.0022 -0.893 

Birth & ANC No birth 1.0 1.0 

 ANC & birth 0.0009*** 0.3740 0.0793*** 32.766 

 Birth but no ANC -0.0002 -0.0955 0.0001 0.0449 

Constant 0.0597*** 24.654 

Total -5.256** 105.26*** 

* Significant at 0.05; ** Significant at 0.01; *** Significant at <0.001 
16 

Table 4b. Decomposition changes in HIV testing among women age 15-24 in TMHIS 2007 to 2011 

HIV testing 

Due to Difference in 

Characteristics (E) 

Due to Difference in 

Coefficients (C) 

 Coefficient Percent Coefficient Percent

Age group 15-19 1.0 1.0 

20-24 -0.0019*** -2.0725 0.0320** 35.29 

Residence Urban 1.0 1.0 

Rural 0.0004** 0.4002 0.0330 36.382 

Region South West Highlands Zone 1.0 1.0 

Central Zone 0.0005 0.5898 -0.0030 -3.3221 

Lake zone -0.00001 -0.0116 -0.0072 -7.9518 

Northern Zone -0.0011** -1.2432 -0.0074 -8.1773 

Eastern Zone 0.0003 0.32511 -0.0119 -13.055 

Western Zone -0.003** -2.5389 -0.0144** -15.903 

Southern Highlands Zone 0.0024** 2.6182 -0.005 -5.5294 

Southern Zone -0.0012** -1.3627 0.0029 3.2135 

Educational level No education 1.0 1.0 

Primary -0.0143*** -15.803 0.0124 13.628 

Secondary & above 0.0423*** 46.653 -0.0022 -2.4257 

Marital status Never-married 1.0 1.0 

Ever-married -0.0022** -2.4582 -0.0032 -3.5296 

Number of sex 

partners in lifetime 0 1.0 1.0 

One 0.0039*** 4.3212 -0.0248 -27.32 

Two -0.0043*** -4.752 -0.0123 -13.525 

More than two -0.0015*** -1.6056 -0.0127 -14.034 

Blood test result HIV negative 1.0 1.0 

HIV positive -0.0009 -0.9805 0.00431 4.7497 

Currently working Not working 1.0 1.0 

Working 0.00001 0.0118 -0.0109 -12.1 

Had STI No 1.0 1.0 

Yes 0.0003 0.3193 0.0008 0.8537 

Birth & ANC No birth 1.0 1.0 

ANC & birth -0.0007*** -0.7741 0.0395*** 43.52 

Birth but no ANC 0.0004** 0.4654 0.0007 0.7629 

Constant 0.6022 66.371 

Total 22.1*** 77.9*** 

* Significant at 0.05; ** Significant at 0.01; *** Significant at <0.001 
17 

DISCUSSION 

Trends in Uptake of HIV Testing 

The present study demonstrated a rapid increase in uptake of HIV testing among women 

age 15–24 over the past eight years in Tanzania. Nearly 40% of the women age 15–24 included in 

the 2011–12 survey had been tested for HIV and received test result—six times the percentage as 

in the 2003–04 survey. A greater increase in uptake of HIV testing occurred between 2003–04 and 

2007–08 than occurred between 2007–08 and 2011–12. The increase could be attributable to the 

wider availability of rapid HIV testing kits (lowering cost of testing), the rolling out of free 

antiretroviral therapy, which started in December 2004, as well as national campaigns to promote 

testing (TACAIDS. 2008; Isingo et al. 2012). The increase in uptake of HIV testing may also be 

due to the Presidential mass campaign for HIV testing in 2007, as well as enactment of the law in 

2008 forbidding discrimination against people living with HIV (PLWH). Increased testing 

translates to an increased proportion of people who are aware of their status and thus possibly 

changing their behaviour in ways that reduce the risk of HIV infection. 

Determinants of HIV Testing Uptake 

The study found numerous factors associated with HIV testing uptake. The odds of HIV 

testing uptake were higher among women with primary and secondary education or higher as 

compared with women without any formal education. This finding is in agreement with a previous 

study among Ghanaian women which showed that higher education was strongly correlated with 

HIV testing uptake (Tenkorang and Owusu 2010). A possible explanation for this result could be 

that higher educational attainment provides more opportunities to clearly understand HIV infection 

and prevention. Moreover, women with more education are more likely to be employed and 

therefore have a better access to VCT services than women without formal education, as until 

about the year 2004 most VCT centers would charge clients a fee for service. 

Marital status also showed to be related to uptake of HIV testing. Married women were 

more likely to undergo HIV testing than unmarried women. Similar findings have been 

documented by other studies (Tenkorang and Owusu 2010; Ziraba et al. 2011). In our study, higher 

odds of HIV testing uptake among married women could be due to advocacy of faith-based 

institutions on the importance of having HIV testing before marriage in Tanzania. 
18 

Compared with women without sexual partners, the odds of HIV testing uptake were higher 

in those with at least one lifetime sexual partner, a finding that is consistent with previous findings 

from Tanzania , as in Tanzania HIV infection is predominantly transmitted sexually. 

The present study also found that attending ANC was also an important determinant for 

HIV testing. Women who had a birth within two years preceding the survey and attended ANC 

had increased odds of HIV testing compared with women who did not have a birth. No association 

of HIV testing uptake was noted among women who had a birth and did not attend ANC. As part 

of preventing mother-to-child transmission of HIV, women are required to test in order to receive 

ART for prevention and also to make decisions on breastfeeding and family planning practices. 

This requirement could explain higher HIV testing uptake among women who attended ANC. 

Analysis showed a difference in HIV testing uptake in relation to STI status. Having an STI or 

symptoms of an STI was associated with increased odds of HIV testing, although the association 

was not statistically significant, but may be clinically meaningful. Association between STI and 

HIV testing uptake also has been reported in other studies (Swenson et al. 2009). STIs are one of 

the risk factors for HIV infection and are often transmitted along with HIV. Individuals attending 

STI clinics are thus more likely to be counselled and eventually tested for HIV, which could 

explain higher odds of HIV testing uptake among this group. 

This study also revealed that HIV testing uptake changes with age difference. Women age 

20–24 had increased odds of HIV testing uptake compared with women age 15–19. Older age has 

been reported to be associated with an increased likelihood of being tested for HIV (Peltzer et al. 

2013).This could be due to the fact that older women are more likely to be sexually active, more 

likely to be married and more likely to be economically empowered than younger women. 

In addition, the study found that women who live in urban areas were more likely to test 

for HIV compared with rural women. Urban areas offer greater access to VCT services compared 

with rural areas, which may explain this finding. We also found zonal variations in uptake of HIV 

testing across the surveys. This could be explained by the regional variation in in availability of 

VCT services between zones. 

 
19 

Decomposition of the Changes in Uptake of HIV Testing 

Decomposition analyses discerned the sources in the changes of HIV testing uptake. 

Changes in the composition of women with different levels of education, attending ANC visits and 

place of residence contributed to observable change in uptake of HIV testing. For example, during 

the first phase a decrease in the proportion of women with primary education or an increase in the 

proportion of women residing in rural areas would have resulted in decrease in HIV testing uptake 

in the absence of the effects of these characteristics. Although changes in the population 

composition contributed to the change in the increase in HIV testing uptake, most of the HIV 

testing uptake was due to the changes in the effects of women’s characteristics. For example, 

attending ANC significantly contributed to the changes in HIV testing uptake in both first and 

second phases. 

Strengths and Limitations of the Study 

Unlike the standard logistic regression-based approaches that rely on individual-level data, 

multivariate regression decomposition in HIV testing provides opportunity for detailed 

explanations for the differences in the changes in HIV testing across the surveys. We were also 

not able to assess the true effect of HIV interventions performed across the survey periods, which 

also might have influenced the observed changes in HIV testing. 

Conclusions 

Uptake of HIV testing increased remarkably over the three surveys. The differences across 

surveys are to a large extent explained by ANC attendance. This is a reflection of a rapid expansion 

of HIV testing services into ANC in order to increase prevention of mother-to-child transmission 

of HIV (PMTCT) across all survey periods. Knowing one’s HIV status is the gateway to HIV 

treatment and prevention. However, the expansion in HIV testing has been greater among women 

with high-risk characteristics, and thus has become more targeted. Until testing is universal, an 

effective expansion strategy would be to prioritize those groups most likely to be infected. 

21 

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