HIV/AIDS Research and Treatment

Open journal

ISSN 2377-8377

HIV/AIDS and Contraceptive Method Choice: Demographic and Socio-Economic Correlates of Contraceptive Method Choice Among HIV-Positive Women Practising Family Planning in Kenya

Monica A. Magadi*

Monica A. Magadi, PhD
Professor School of Social Sciences University of Hull Hull, HU6 7RX, UK Tel. +44(0)1482 462032; E-mail: m.magadi@hull.ac.uk

INTRODUCTION

                 Kenya has a generalized HIV epidemic, driven primarily by hetero sexual transmission. According to recent estimates, national HIV prevalence among adults aged 15-64 years was 5.6% in 2012, translating to an estimated 1.2 million adults living with HIV.1 Women are disproportionately affected (prevalence of 6.9% for females versus 4.4% for males in 2012) and wide regional variations exist in the country. Despite a recent overall national decline in HIV prevalence among adults aged 15-64 in Kenya from 7.2% in 2007 to 5.6% in 2012, the prevalence in the worst affected region of Nyanza Province remained unchanged at about 15% during the same period.1 Prevailing trends for women of reproductive age (aged 15-49 years) mirror these national patterns-the prevalence declined from around 9% in 2003 to 7% in 2012, but remained unchanged at about 18% in the highest prevalence region of Nyanza province. An earlier study revealed unique reproductive experiences of women in the highest HIV prevalence setting of Nyanza province,2 suggesting an intricate link between HIV and reproductive behaviour. Notwithstanding impressive strides in HIV testing and treatment coverage in the country during recent years,3 the number of people living with HIV has remained high. It has been noted that as Kenya’s HIV epidemic continues to evolve, there is need for continued evidence-based action to respond to emerging challenges,4 which include addressing the reproductive needs of the large number of women living with HIV.

HIV-positive women have special family planning needs. Of particular concern is the apparent greater risk of unintended pregnancy among HIV-positive than HIV-negative women5,6 which may be attributable to overall lower uptake of contraceptives7 or use of less effective methods5 by HIV-positive women. These patterns have implications for overall maternal and child health in settings of high HIV prevalence such as sub-Saharan Africa (SSA), including vertical transmission of HIV from mother to child. Furthermore, the apparent link of some hormonal contraceptives, especially injectables, to increased HIV transmission8,9 has important implications for contraceptive method choice in high HIV prevalence SSA settings with wide spread use and rising popularity of injectables.

It is important to improve understanding of the extent to which HIV-positive women are using suitable family planning (FP) methods, consistent with their reproductive goals and desires. It has been noted that the risks of unprotected sex, sexually transmitted infections, infertility and unintended pregnancy are inextricably linked,10 making the issue of using appropriate methods of protection a critical one. Condom use has been recognized as the mainstay of dual protection of HIV infection and unintended pregnancy,11 but acceptability remains low in most settings of sub-Saharan Africa (SSA), especially in long-term relationships.12 Furthermore, inconsistent condom use has been noted as a major cause of concern, leading to unplanned pregnancies among women living with HIV.5

Although all the available reversible methods of contraception can generally be used by women at risk of HIV infection and by HIV infected women, hormonal contraception, especially injectables, have been linked to increased risk of HIV infection and transmission.8,9,13 Therefore, the increasing popularity and dominance of injectable contraceptives in most SSA countries14,15,16 have far-reaching repercussions for contraceptive method choice in settings of high HIV risk. Integrated services have been linked to increased use of condoms and reduced use of other modern contraceptives.17 A better understanding of the link between HIV/AIDS and contraceptive method choice in settings adversely affected by HIV/AIDS will help inform effective integration of HIV/AIDS and FP services.

This paper focuses on the association between HIV/AIDS factors and contraceptive method choice among women currently using contraceptives in Kenya. An earlier qualitative study in a low contraceptive prevalence setting in Kenya had noted that for some HIV-positive women, their HIV status dictated their contraceptive decisions.18 Besides HIV status, other HIV/AIDS-related factors, including: HIV risk perception, HIV/AIDS stigma, HIV/AIDS awareness and previous HIV testing are considered of interest as they may also influence individual’s contraceptive choice. For instance, it is possible that in settings where most individuals do not know their HIV status, perceived HIV risk may be a more important determinant of contraceptive behaviour than actual HIV status. The specific objectives are to:

examine the effect of HIV/AIDS on contraceptive method choice among women in Kenya; and

identify demographic and socio-economic correlates of contraceptive method choice among HIV-positive women using family planning.

MATERIAL AND METHODS 

The Data 

This study is based on secondary analysis of data from the Kenya Demographic and Health Surveys (KDHS) conducted in 2003 and 2008.16,19 These two surveys included HIV testing for nationally-representative samples, providing a unique opportunity to anonymously link HIV test results to the full survey record at individual level. From an overall sample of 16,639 women of reproductive age (aged 15-49 years) included in the two surveys (8195 in 2003 and 8444 in 2008), a total of 9132 women (i.e survey respondents residing in every other household) were eligible for HIV testing. The protocol for HIV testing in the two KDHS surveys was as follows:

‘…. all eligible women and men who were interviewed were asked to voluntarily provide some drops of blood for HIV testing. …tested with a Vironostika Anti-HIV-1/2 Plus enzyme-linked immunosorbent assay (ELISA) test kit (DADE Behring HIV-1/2) for verification purposes. All positive samples and 5 percent of negative samples were then tested with a Murex HIV-1/2 Micro ELISA System. For quality assurance, all positive samples and a 10 percent random sample of the negative samples were retested at the KEMRI HIV laboratory using the same testing algorithm of both Vironostika and Murex Micro ELISA systems. Finally, 30 discrepant samples were tested by polymerase chain reaction (PCR) DNA at KEMRI laboratory’.16(pp. 9-10)

                        Our study sample included all women tested for HIV who were using contraceptive methods at the time of the survey (27% in 2003 and 39% in 2008), making a total of 3190 respondents (for Objective i analysis). About eight percent of this sample was HIV-positive, representing a sample of 255 HIV-positive women (for Objective ii analysis). The comparative nature of DHS data allows for pooling of data across surveys to achieve sufficient samples and monitor trends. Pooling data across the two surveys is deemed necessary due to the limited size of HIV-positive sample of women using contraceptives in each of the two surveys.

Contraceptive method choice is the outcome variable of interest while HIV/AIDS-related factors (i.e. whether previously tested for HIV, HIV/AIDS awareness, HIV/AIDS stigma, HIV risk perception and sero-status) constitute the key explanatory variables. The study takes into consideration a number of other key explanatory variables, recognizing that the association between HIV/AIDS and contraceptive method choice is likely to be influenced by a range of background demographic and socio-economic moderating factors or confounders associated with both HIV/AIDS and contraceptive method choice. A summary description of study variables is presented in Table 1.

 

Table 1: A summary description of variables included in the study.
VARIABLE Description
Dependent variable
Contraceptive method choice Current contraceptive method used, classified as: hormonal (pill/injectable); condom; abstinence; and other. ‘Other’ comprised mainly sterilization and long-term methods.
HIV/AIDS-related factors
HIV status Binary variable, coded as 1=if respondent is HIV-positive; 0=negative.
Previously tested for HIV Binary variable, coded as 1 if responded was previously tested for HIV; 0=has never been tested
Knows someone with or died of HIV/AIDS Binary variable, coded as 1 if respondent knows someone with or who died of HIV/AIDS; and 0=otherwise.
HIV/AIDS comprehensive knowledge A composite awareness index derived from a series of questions on misconceptions about HIV/AIDS, knowledge of how HIV is transmitted and ways to avoid infection. The resulting score classified into quintiles (1-4), with lowest awareness coded as 1.
HIV/AIDS Stigma A composite index derived from a set of four DHS questions on HIV/AIDS stigma. The resulting score is classified as 0 for ‘low’ stigma or 1 for ‘high’ stigma.
Perceived risk of HIV/AIDS Classified as: 0= no/low risk; or 1= moderate/high perceived risk
Demographic and background socio-economic factors
Respondent’s age Three age-group categories: 15-24, 25-34 and 35+.
Respondent’s parity The total number of children ever born, classified into four categories: 0, 1-2, 3-4 and 5+
Respondent’s marital status Marital or union status at time of survey, classified as: never married, currently married (monogamous/polygamous), widowed, divorced/separated
Fertility intention Future fertility intention, coded as 1 if respondent wants no more children; 0=otherwise
Recent sexual activity Period since last sex, classified as: within one week, 1-4 weeks, 1-6 months; and more than 6 months
Respondent’s education Highest educational attainment classified into: no formal education; primary level, and secondary and above.
Household wealth index DHS composite wealth index20 based on household possessions and amenities, classified into quintiles: poorest, poorer, middle; richer and richest
Respondent’s religion Religious affiliation, classified into: Catholic, Protestant/other Christian, and Muslim and other
Respondent’s ethnicity Classified into four categories: Kikuyu, Luo, Luhya and other
Region of residence Seven provinces: Central, Coast, Eastern/North Eastern, Nairobi, Nyanza, Rift Valley and Western
Urban/rural residence Binary variable, coded as 1=urban or; 0=rural residence.
METHODS OF ANALYSIS

The analysis involved both descriptive bivariate analysis and multivariate modelling. Chi-Square tests were used to assess significance of bivariate associations in cross-tabulations, while multivariate analysis was based on multinomial logistic regression analysis of factors associated with contraceptive method choice. The response (dependent) variable in our analysis-contraceptive method choice – was classified into four mutually exclusive categories: hormonal method (pills and injectables), condoms, periodic abstinence, and other methods (mainly sterilization and other long-term methods). Although dual use of condoms with other contraceptives was considered of particular interest, this was not used as a distinct category because of very small numbers. Dual contraceptive methods, combining condoms with other methods were classified as ‘condoms’, since use of condoms was of particular interest.

Preliminary analysis assessed potential clustering of contraceptive method choice within communities or clusters, but there was no evidence of significant intra-cluster correlations. Hence, the analysis was based on single-level rather than multi-level models. The general equation for the multinomial logistic regression used in the analysis takes the form:

 

Log [π(s)(r)] = b(s)0 + b(s)1 X(s)1 + b(s)2 X(s)2 + … +b(s)k X(s)k ;         S=2, 3, 4.

 

Where:

π(s) is the probability of using a particular contraceptive method (s);

π(r) is the probability of using reference-category contraceptive method – r=hormonal (1);

b(s)0 is the regression intercept/constant for contraceptive method (s);

X(s)1-k are covariates for k explanatory variables for contraceptive method (s); and

b(s)1-k are the associated usual regression parameter estimates.

The second part of the analysis focused on HIV-positive women (Objective ii) and examined factors associated with contraceptive method choice among HIV-positive women. Due to sample size limitations, this part of the analysis was confined to bivariate associations. It was necessary to merge some of the categories of explanatory variables with relatively few HIV-positive women using contraceptives at the time of the survey to achieve sufficient samples for valid Chi-Square tests.

RESULTS

 Associations between HIV/AIDS and Contraceptive Method Choice 

The bivariate associations between HIV/AIDS-related factors and contraceptive method choice among current users are resented in Table 2.

Table 2: Contraceptive method choice among current users by HIV/AIDS-related factors.
HIV/AIDS factor Method currently used (percent) Cases
Hormonal condoms abstain other
HIV sero status**

Negative

Positive

 

48.9

41.5

 

20.0

29.5

 

14.5

14.1

 

16.7

14.9

 

2935

255

Previously tested for HIV***

No

Yes

 

44.6

51.7

 

19.4

22.0

 

18.2

10.9

 

17.8

15.4

 

1543

1637

Knows someone who has or died of HIV/AIDS**

No

Yes

 

47.8

48.5

 

22.8

20.4

 

17.9

13.8

 

11.5

17.3

 

430

2746

HIV/AIDS awareness***

Lowest

Lower

Higher

Highest

 

42.2

47.9

50.2

50.1

 

23.3

18.7

20.0

22.0

 

19.5

16.4

14.2

10.1

 

14.9

16.9

15.7

17.9

 

463

877

948

902

HIV/AIDS Stigma*

Low

high

 

46.3

50.1

 

21.4

20.0

 

15.9

13.1

 

15.9

16.8

 

1519

1671

Perceived HIV/AIDS risk***

Mod-high or has AIDS

No-low risk

 

46.4

51.3

 

24.8

14.1

 

13.6

15.7

 

15.1

18.9

 

1902

1288

All 48.3 20.7 14.4 16.6 3190
*Chi-Square p<0.05; **p<0.01; ***p<0.001

 

Condom use is higher among HIV-positive women (30%) than those who were negative (20%), but hormonal contraceptives (pill and injectables) is the predominant method among both HIV-infected (42%) and uninfected (49%) women currently using contraceptives. Current users who were previously tested for HIV, had personal acquaintance with HIV/AIDS victims or had higher HIV/AIDS awareness are generally more likely to use hormonal contraceptives, but less likely to use periodic abstinence compared to counterparts who never tested, knew no one living with or died of HIV/AIDS, or had lower HIV/AIDS awareness. Those who perceive themselves to be at a moderate or high risk of HIV infection are more likely to use condoms (25%) than those who perceive themselves to be at no or low risk (14%).

Multivariate results based on multinomial regression analysis (Table 3) reveals independent associations between HIV/AIDS-related factors and contraceptive method choice, once background socio-economic and demographic factors are controlled for. The parameter estimates from multinomial Logistic regression are presented in the form of relative risk (RR) factors, with 95% confidence intervals, to ease interpretation. A relative risk factor greater than 1.00 implies that the factor is associated with higher use of a particular contraceptive method than the reference category (i.e. hormonal method), while a value less than 1.00 implies lower use.

 

Table 3: HIV/AIDS and other determinants of contraceptive method choice.
Parameter (reference categories in brackets) Condom Periodic abstinence Sterilization/other
RR (95% CI of RR)   RR (95% CI of RR)   RR (95% CI of RR)  
2008 survey (2003) 3.45 (2.29, 5.21) * 0.91 (0.68, 1.21)   0.75 (0.58, 0.96) *
HIV positive (negative) 2.41 (1.58, 3.67) * 1.58 (1.02, 2.46) * 1.17 (0.78, 1.77)  
Previously tested (no) 1.12 (0.84, 1.49)   0.71 (0.55, 0.91) * 1.07 (0.85, 1.35)  
HIV awareness (lowest)

– lower

– higher

– highest

 

0.88 (0.58, 1.34)

1.01 (0.66, 1.52)

0.76 (0.50, 1.15)

   

0.78 (0.55, 1.11)

0.87 (0.61, 1.24)

0.60 (0.42, 0.87)

* 0.97 (0.68, 1.38)

1.05 (0.73, 1.50)

1.02 (0.72, 1.46)

 
Perceived HIV /AIDS mod-high risk (no-low) 1.02 (0.76, 1.35)   0.98 (0.77, 1.26)   0.96 (0.76, 1.20)  
Age group (15-24)

– 25-34

– 35+

 

1.23 (0.85, 1.77)

2.58 (1.61, 4.16)

* 1.19 (0.83, 1.72)

2.59 (1.66, 4.03)

* 2.22 (1.41, 3.48)

5.30 (3.23, 8.69)

*

*

Parity (0)

– 1-2

– 3-4

– 5+

 

0.06 (0.03, 0.10)

0.02 (0.01, 0.05)

0.02 (0.01, 0.04)

*

*

*

0.13 (0.07, 0.24)

0.10 (0.05, 0.20)

0.17 (0.08, 0.35)

*

*

*

0.24 (0.10, 0.55)

0.23 (0.10, 0.56)

0.34 (0.14, 0.85)

*

*

*

Education (none)

– Primary

– Sec+

1.16 (0.51, 2.63)

1.31 (0.56, 3.06)

  1.44 (0.75, 2.76)

1.64 (0.83, 3.23)

  0.70 (0.41, 1.20)

0.97 (0.55, 1.70)

 
Wealth index (poorest)

– Poorer

– Middle

– Richer

– Richest

 

0.93 (0.54, 1.59)

0.68 (0.39, 1.18)

0.90 (0.52, 1.54)

0.72 (0.39, 1.34)

  0.91 (0.57, 1.45)

0.77 (0.48, 1.23)

0.77 (0.48, 1.22)

0.65 (0.37, 1.12)

  0.77 (0.48, 1.22)

0.66 (0.42, 1.05)

1.06 (0.68, 1.67)

0.99 (0.59, 1.66)

 
Religion (Catholic)

– Protestant

– Muslim/ Other

0.83 (0.62, 1.13)

1.66 (0.97, 2.85)

  0.83 (0.63, 1.08)

1.52 (0.93, 2.50)

  1.20 (0.93, 1.54)

1.78 (1.07, 2.96)

*
Ethnic group (Kikuyu)

– Luhya

– Luo

– Other

 

2.23 (1.21, 4.45)

4.42 (2.46, 8.30)

2.19 (1.33, 3.60)

*

*

*

1.16 (0.65, 2.09)

1.64 (0.91, 2.97)

1.57 (1.03, 2.40)

* 0.49 (0.29, 0.83)

0.60 (0.36, 1.02)

0.74 (0.52, 1.07)

*

 

 

Region (Central)

– Nairobi

– Coast

– Eastern/North Eastern

– Nyanza

– R.Valley

– Western

 

1.58 (0.83, 3.04)

1.26 (0.63, 2.50)

0.92 (0.46, 1.83)

1.27 (0.64, 2.54)

1.82 (0.97, 3.42)

2.02 (0.93, 4.39)

  1.10 (0.61, 1.98)

0.87 (0.48, 1.58)

0.66 (0.38, 1.16)

0.67 (0.37, 1.24)

1.99 (1.22, 3.27)

0.72 (0.35, 1.45)

*

 

1.38 (0.85, 2.25)

0.92 (0.54, 1.55)

0.61 (0.37, 1.00)

1.58 (0.95, 2.62)

1.18 (0.76, 1.82)

1.79 (0.98, 3.25)

 

 

*

 

 

 

Urban residence (rural) 1.08 (0.70, 1.66)   1.12 (0.75, 1.67)   0.88 (0.62, 1.25)  
Want another child (no) 0.86 (0.64, 1.17)   1.64 (1.24, 2.16) * 0.61 (0.46, 0.81) *
Marital status

– married-monogamous

– married-polygamous

– div./sep./widowed

 

0.15 (0.09, 0.26)

0.21 (0.11, 0.42)

0.54 (0.30, 0.95)

*

*

*

0.82 (0.46, 1.44)

0.54 (0.27, 1.09)

0.45 (0.22, 0.92)

*  

1.98 (0.89, 4.42)

2.35 (1.00, 5.55)

1.45 (0.62, 3.43)

 
Last sexual activity (within one week)

– within one month

– 1-6 months

– > 6 month

 

1.21 (0.87, 1.70)

1.33 (0.87, 2.04)

0.52 (0.28, 0.95)

* 1.32 (0.98, 1.78)

1.67 (1.10, 2.52)

1.52 (0.85, 2.72)

 

*

 

1.37 (1.05, 1.78)

1.20 (0.79, 1.83)

1.58 (0.92, 2.73)

*

 

 

* – sig at 5% level (p<0.05)

 

The results suggest that HIV status is a significant determinant of method choice, with HIV-positive women being more likely to use condoms or periodic abstinence rather than hormonal contraceptives (pills or injectables). Women who are HIV-positive are more than twice as likely to use condoms rather than hormonal contraceptives compared to their counterparts of similar characteristics who are HIV-negative (RR=2.41). There is little evidence that the other HIV/AIDS factors relating to HIV/AIDS awareness, previous testing for HIV or HIV/AIDS risk perception have a significant association with choice of condoms or other contraceptive methods (i.e. sterilization and other) versus hormonal contraceptives. However, those with higher HIV/AIDS awareness (RR=0.60) or previously tested for HIV (RR=0.71) are less likely to use periodic abstinence versus hormonal methods, compared to their counterparts of similar characteristics who have lower HIV/AIDS awareness or never been previously tested for HIV.

The results show little evidence of significant variations in contraceptive method choice by background socio-economic factors controlled for in the analysis such as urban/rural residence, educational attainment or household wealth, once the effects of other important factors are controlled for. However, there is some evidence of method choice being affected by ethnicity, religion and region of residence. Women of all ethnic groups are significantly more likely to use condoms rather than hormonal contraceptives, compared to Kikuyu women of similar characteristics.

Although age and parity are expected to be positively correlated, they show opposite patterns on method choice. Higher parity is associated with lower use of condoms, periodic abstinence and sterilization/other methods versus hormonal contraceptives, while the opposite is the case for older age. Those who want more children in future are more likely to use periodic abstinence (RR=1.64) and less likely to use sterilization/other (RR=0.61) versus hormonal contraceptives. Those who are currently married are less likely to use condoms versus hormonal than never married women of similar characteristics (RR=0.15 for monogamous married; RR=0.21 for polygamous married). Also, the previously married (i.e. divorced/separated and widowed) are less likely to use condoms (RR=0.54) or abstinence (RR=0.45) than the never married counterparts of similar characteristics.

Correlates of Contraceptive Method Choice among HIV-Positive Women

An examination of contraceptive method choice among HIV positive women by HIV/AIDS related factors (Table 4) provides no evidence of significant variations by HIV/AIDS knowledge or knowing someone who has died of or living with HIV. However, HIV risk perception in marginally significant (p<0.1), suggesting that those who perceived themselves to be at moderate or high risk of HIV infection were more likely to use condoms and less likely to use hormonal contraceptives than those who perceived themselves to be at no or low risk. More conclusive patterns were observed with respect to previous HIV testing, with HIV-positive women who were previously tested for HIV being more likely to use condoms and less likely to use hormonal contraceptives than those who have never been tested (p<0.05). The importance of previous HIV testing is further highlighted in Figure 1, comparing contraceptive method choice of HIV-positive and HIV-negative women by previous HIV testing.

 

Table 4: Method choice among HIV-positive current users by HIV/AIDS-related factors.
HIV/AIDS factor Method currently used (percent) Cases
Hormonal condoms abstain other
Previously tested for HIV*

No

Yes

 

46.0

37.9

 

19.0

37.1

 

16.0

12.9

 

19.0

12.1

 

107

148

Knows someone who has or died of HIV/AIDS (ns)

No

Yes

 

45.9

41.2

 

27.0

30.7

 

16.2

12.1

 

10.8

16.1

 

37

216

HIV/AIDS awareness(ns)

Lowest

Lower

Higher

Highest

 

30.6

49.0

40.3

43.2

 

36.1

27.5

30.6

27.2

 

22.2

7.8

15.3

12.3

 

11.1

15.7

13.9

17.3

 

35

55

76

89

Perceived HIV/AIDS risk (†)

Mod-high or has AIDS

No-low risk

 

37.2

49.4

 

34.6

20.0

 

14.7

12.9

 

13.5

17.6

 

157

98

All 41.5 29.5 14.1 14.9 255
*Chi-Square p<0.05; **p<0.01; ***p<0.001; † p<0.10.

 

Figure 1: Comparing contraceptive method choice of HIV-positive and HIV-negative women by previous HIV testing

Comparing contraceptive method choice of HIV-positive and HIV-negative women by previous HIV testing.

Figure 1 reveals that there is no difference in method choice between HIV-positive and HIV-negative women who never previously tested for HIV, but notably higher use of condoms (37% vs 19%) accompanied with lower use of hormonal methods (38% vs 46%) among HIV-positive than HIV-negative women previously tested for HIV. These patterns suggest that the observed higher use of condoms rather than hormonal contraceptives by HIV-positive compared to HIV-negative women (Tables 2 and 3) only applies to those previously tested for HIV.

A further examination of contraceptive method choice among HIV-positive women by background characteristics (Table 5) reveal important patterns by a number of factors. Highly significant associations (p<0.001) are observed with respect to parity, marital status and year of survey, with condom use being notably higher than use of hormonal methods among those of parity zero (90.5% condoms vs 9.5% hormonal), never married women (66.7% vs 23.3%) and in 2008 (40.9% vs 29.9%). Observed trends suggest a notable shift from use of hormonal methods to condoms by HIV-positive women. In 2003, a large majority of HIV-positive women using contraceptives were using hormonal methods (61%), with only a small minority (9%) using condoms. By 2008, these patterns had reversed, with condom use increasing from 9% to 41%, while use of hormonal methods declined from 61% to 30%.

 

Table 5: Contraceptive method choice among HIV-positive women by background characteristics.
Background characteristic Contraceptive method currently used (%) Unweighted Cases
Hormonal Condoms Abstinence Other
Survey year ***

– 2003

– 2008

 

61.1

29.9

9.3

40.9

12.8

14.9

16.3

14.3

 

84

171

Age group *

– 15-24

– 25-34

– 35+

60.0

41.2

33.3

22.5

33.3

27.6

15.0

9.6

19.5

2.5

15.8

19.5

 

41

118

96

Parity ***

– 0

– 1-2

– 3-4

– 5+

9.5

48.1

52.0

33.3

90.5

28.6

22.7

19.7

0.0

11.7

12.0

22.7

0.0

11.7

13.3

24.2

 

22

80

83

70

Education *

– none / Primary

– Sec+

 

45.6

34.4

24.4

38.8

16.8

10.0

13.4

16.7

 

160

95

Wealth index (ns)

– poorest / Poorer

– Middle

– Richer

– Richest

32.6

37.1

41.7

46.6

30.2

25.7

31.7

29.1

14.0

17.1

13.3

13.6

23.3

20.3

13.3

10.7

 

47

37

60

111

Religious affiliation (ns)

– Catholic

– Protestant/Muslim/ Other

41.5

41.5

33.8

27.8

7.7

16.5

16.9

14.2

 

72

183

Ethnic group **

– Kikuyu

– Luhya

– Luo

– Other

40.0

25.0

37.9

56.2

22.5

28.1

39.8

18.8

10.0

21.9

13.6

14.1

27.5

25.0

8.7

10.9

 

46

38

100

71

Region of residence (ns)

– Nairobi

– Central

– Coast/ Eastern/N. Eastern

– Nyanza

– R.Valley

– Western

43.9

42.9

50.0

36.7

41.0

39.1

29.3

21.4

23.3

40.5

23.1

21.7

9.8

10.7

16.7

12.7

25.6

13.0

17.1

25.0

10.0

10.1

10.3

26.1

 

43

30

38

84

27

33

Residence

– rural

– urban

36.6

50.0

31.4

26.1

16.3

10.2

15.7

13.6

 

143

112

Want another child †

– no /later

– yes

39.6

44.6

31.5

26.1

10.7

19.6

18.1

9.8

 

159

96

Marital status ***

– never married

– married

– div./sep./widowed

23.3

43.6

45.9

66.7

20.1

34.4

6.7

18.8

4.9

3.3

17.4

14.8

 

34

162

59

Last sexual activity

– within one week

– within one month

– 1-12 months

47.0

37.1

34.4

26.6

30.6

34.4

14.5

16.1

11.5

12.0

16.1

19.7

 

130

60

65

Total 41.5 29.5 14.1 14.9 255
*Chi-Square p<0.05; **p<0.01; ***p<0.001; † p<0.10.

 

Evidence of significant associations (p<0.05) are also observed with respect to age group, educational attainment and ethnic group. Higher use of condoms than hormonal methods is observed among women with at least secondary education (condoms -38%; hormonal -34%) and among the Luo ethnic group (condoms -40%; hormonal -38%). With respect to age group, contraceptive method choice among the youth is potentially of concern. A large majority of HIV-positive young women aged 15-24 using contraceptives are using hormonal methods (60%) while only 23% are using condoms.

DISCUSSION AND CONCLUSIONS

The main objectives of the research reported in this paper were to: (i) examine the effect of HIV/AIDS on contraceptive method choice in Kenya; and (ii) Identify correlates of contraceptive method choice among HIV-positive women using contraceptives. The analysis of contraceptive method choice among current contraceptive users mainly aimed at ascertaining the extent to which HIV-positive women are using appropriate methods, commensurate with their reproductive goals and needs. Although dual use of condoms and other contraceptive methods would be of primary interest, inclusion of this classification was not possible, given the very small numbers using dual methods. Overall patterns of method choice are consistent with expected patterns, with women who are HIV-positive being more than twice as likely to use condoms rather than hormonal contraceptives compared to their counterparts who are HIV-negative. The observed higher use of condoms by HIV-positive women, especially those who know their HIV status, is consistent with findings elsewhere in Africa.17,21 For example, Lopez et al17 observed that HIV-positive women were more likely to discontinue their hormonal contraceptives, and more likely to use condoms.

Important demographic and socio-economic correlates of contraceptive method choice among HIV-positive women include parity, marital status, age group, education and ethnicity. Condom use is notably higher than use of hormonal methods among those of parity zero (condoms -90.5% vs hormonal -9.5%), never married women (66.7% vs 23.3%), those with at least secondary education (38% vs 34%) and among the Luo ethnic group (40% vs 38%). Overall prevailing trends in contraceptive method choice among HIV-positive women in Kenya which suggest a notable shift from use of hormonal methods to condoms, and the observed lower use of hormonal methods by HIV-positive compared to HIV-negative women are encouraging, especially given the possible link of hormonal contraception to increased risk of HIV infection in previous research8,9,13 and increasing popularity and dominance of injectable contraceptives in most SSA countries, including Kenya.14,15,16 Recent research evidence has been inconclusive, calling for further research to establish safety of hormonal contraceptives for HIV-positive women.22,23

However, observed patterns also identify some sub-groups of HIV-positive women in Kenya for whom contraceptive method choice is potentially of concern. First, the fact that a large majority (60%) of HIV-positive young women aged 15-24 using contraceptives are using hormonal methods and only 23% using condoms suggests that contraceptive method choice among HIV-positive youth is potentially of concern. It raises an issue on the extent to which HIV-positive youth in Kenya are able to access suitable contraceptive methods, commensurate with their reproductive needs and desires. Although Condom use is recognized as one of the main strategies for combating the spread of HIV, promoting condom use among the youth in Kenya can be controversial, especially as some believe it encourages early sexual experimentation.16 Nevertheless, our findings provide credence to an earlier recommendation on the need for particular attention to reproductive health information and services for HIV-positive adolescents.24 Second, the relatively low condom use among sub-groups that are known to have particularly high HIV prevalence such as previously married women25 is also of concern and warrants attention.

It is important to recognize than although use of condoms is recommended for HIV-positive individuals for prevention of HIV transmission, it is one of the least effective contraceptive methods. In a study in South Africa, Schwartz et al26 observed that women who reported condom use were just as likely to have an unplanned pregnancy as women who reported using no contraception at all. Use of dual methods, combining condoms with other contraceptive methods, is preferred to improve contraceptive effectiveness.27 However, dual method use in most sub-Saharan settings is low.21,28 A recent study in Namibia, Kenya and Tanzania observed low dual method use and low use of highly effective contraception among people living with HIV for whom contraceptive protection was predominantly through condom-only use.28 Dual contraceptive use in Kenya is very low as some couples believe it is unnecessary.29 Ralph et al9 highlighted the need for future priorities to include expanding contraceptive choice and identifying effective ways of promoting use of dual methods. Besides condoms, use of other contraceptive methods, especially long-term methods, have been promoted for women living with HIV. For instance, Kimani et al6 recommended greater use of long-term reversible contraceptives to reduce the risk of both vertical transmission of HIV as well as unintended pregnancy, while Siveregi et al7 recommended promoting long-term permanent methods in family planning counselling for both HIV-positive and HIV-negative women to improve overall contraceptive uptake and reduce unintended pregnancies. Kimani et al6 underscored the need to strengthen family planning services for women living with HIV to improve access to wide-ranging appropriate family planning services.

The observed patterns with respect to previous HIV testing underscore the importance of HIV testing in enabling HIV-positive women choose suitable contraceptive methods. The higher use of condoms and lower use of hormonal methods among HIV-positive than HIV-negative women previously tested for HIV, while there is no difference in method choice between HIV-positive and HIV-negative women who never previously tested for HIV, suggests that the observed higher use of condoms rather than hormonal contraceptives by HIV-positive women is only applicable to those previously tested for HIV. This is consistent with finding from a recent study of the effects of the HIV treatment on contraceptive choice in South Africa, where an increase in contraceptive use (especially condoms) across the cascade, from lowest level among HIV-positive women who did not know their status to highest levels among women who had been on HIV treatment for a long period of time was observed.27 Similar findings have been observed in Malawi where women’s knowledge of their HIV-positive status was found to be a significant predictor of their family planning practice.30 Knowledge of HIV status is a prerequisite for appropriate action to address HIV-positive status. Despite a rising trend in HIV testing in Kenya and almost everyone previously tested having received their test results,16 a significant proportion of women of reproductive age (e.g. more than 40% in 2008) has never been tested for HIV, highlighting the need to intensify efforts to improve coverage in HIV counselling and testing in the country to enable women make informed choices to achieve their reproductive needs and desires.

Finally, some key data limitations which may have potential implications on our interpretation of some of the study findings are worth noting. First, the KDHS data used in this study are based on a cross-sectional design which limits our ability to establish temporal ordering of events of interest. We recognize that HIV/AIDS factors and contraceptive behaviour are intrinsically linked and while in this paper our focus is on the role of HIV/AIDS-related factors in influencing contraceptive method choice, we recognize that contraceptive behaviour (especially condom use) may indeed influence the risk of HIV infection. Therefore, we are unable to infer precise causal relationships from the patterns observed. It is important to recognize that the relationships observed provide evidence of simple associations rather than causal relationships. A second limitation relates to inadequate sample size which limits our statistical power to detect some important patterns in contraceptive method choice, especially among HIV-positive women. Even after pooling data across the two surveys, the sample of 255 HIV-positive women using contraceptives at the time of surveys is limited for meaningful multivariate analysis that would simultaneously take into consideration the effects of potential confounding factors in the relationships observed. Nevertheless, the bivariate associations provide useful patterns to enable identification of specific sub-groups that should be targeted by specific family planning and HIV/AIDS policies and programmes in Kenya and similar settings in SSA.

1. National AIDS and STI Control Programme (NASCOP), Ministry of Health. Kenya AIDS Indicator Survey 2012: Final Report. Nairobi, NASCOP. 2014. Web site. http://www.nacc.or.ke/images/documents/KAIS-2012.pdf. Accessed March 24, 2016.

2. Magadi MA, Agwanda A. Investigating the association between HIV/AIDS and recent fertility patterns in Kenya. Soc Sci Med. 2010; 71(2): 335-344. doi: 10.1016/j.socscimed.2010.03.040

3. Maina WK, Kim AA, Rutherford GW, et al. Kenya AIDS Indicator surveys 2007 and 2012: Implications for public health policies for HIV prevention and treatment. J Acquir Immune Defic Syndr. 2014; 66(Suppl 1): S130-S137. doi: 10.1097/QAI.0000000000000123

4. National AIDS Control Council (NACC) and National AIDS and STI Control Programme (NASCOP). The Kenya AIDS Epidemic Update 2011. Nairobi, Kenya. 2012. Web site. http://www.unaids.org/sites/default/files/en/dataanalysis/knowyourresponse/countryprogressreports/2012countries/ce_KE_Narrative_Report.pdf. Accessed March 24, 2016.

5. Schaan MM, Taylor M, Marlink R. Reproductive behaviour among women on antiretroviral therapy in Botswana: mismatched pregnancy plans and contraceptive use. Afr J AIDS Res. 2014; 13(3): 305-11. doi: 10.2989/16085906.2014.952654

6. Kimani J, Warren C, Abuya T, Mutemwa R, Mayhew S, Askew I. Family planning use and fertility desires among women living with HIV in Kenya Global health. BMC Public Health. 2015; 15(1): 909. doi: 10.1186/s12889-015-2218-z

7. Siveregi A, Dudley L, Makumucha C, Dlamini P, Moyo S, Bhembe S. Does counselling improve uptake of long-term and permanent contraceptive methods in a high HIV-prevalence setting? Afr J Prim Health Care Fam Med. 2015; 7(1): E1-E9. doi: 10.4102/phcfm.v7i1.779

8. Hefron R, Donnell D, Rees H, et al. Use of hormonal contraceptives and risk of HIV-1 transmission: a prospective cohort study. Lancet Infect Dis. 2012; 12(1): 19-26. doi: 10.1026/s1473-3099(11)70247-x

9. Ralph LJ, Gollub EL, Jones HE. Hormonal contraceptive use and women’s risk of HIV acquisition: Priorities emerging from recent data. Curr Opin Obstet Gynecol. 2015; 27(6): 487-495. doi: 10.1097/GCO.0000000000000228

10. Brady M. Preventing sexually transmitted infections and unintended pregnancy, and safeguarding fertility: Triple protection needs of young women. Reprod Health Matters. 2003; 11(22): 134-141. doi: 10.1016/S0968-8080(03)02289-4

11. Berer M. Dual protection: more needed than practised or understood. Reprod Health Matters. 2006; 14(28): 162-170. doi: 10.1016/S0968-8080(06)28262-4

12. Williamson NJ, Liku K, Loughlin Mc, Nyamongo I, Nakayima F. A qualitative study of condom use among married couples in Kampala, Uganda. Reprod Health Matters. 2006; 14(28): 89-98. doi: 10.1016/S0968-8080(06)28268-5

13. Heikinheimo O, Lahteenmaki P. Contraception and HIV infection in women. Hum Reprod Update. 2009; 15(2): 165-176. doi: 10.1093/humupd/dmn049

14. Magadi MA, Curtis S. Trends and determinants of contraceptive method choice in Kenya. Stud Fam Plann. 2003; 34(3): 149-159. doi: 10.1111/j.1728-4465.2003.00149.x

15. Seiber EE, Bertrand JT, Sullivan TM. Changes in contraceptive method mix in developing countries. Int Fam Plan Perspect. 2007; 33(3): 117-123. Web site. https://www.guttmacher.org/about/journals/ipsrh/2007/09/changes-contraceptive-method-mix-developing-countries. Accessed March 24, 2016

16. Kenya National Bureau of Statistics (KNBS) and ICF Macro. Kenya Demographic and Health Survey 2008-09. Calverton, Maryland: KNBS and ICF Macro. 2010. Web site. http://dhsprogram.com/pubs/pdf/fr229/fr229.pdf. Accessed March 24, 2016.

17. Lopez LM, Hilgenberg D, Chen M, Denison J, Stuart G. Behavioral interventions for improving contraceptive use among women living with HIV. Cochrane Database Syst Rev. 2013; 1: CD010243. doi: 10.1002/14651858.CD010243.pub2

18. Imbuki K, Todd CS, Stibich MA, Shaffer DN, Sinei SK. Factors influencing contraceptive choice and discontinuation among HIV-positive women in Kericho, Kenya. Afr J Reprod Health. 2010; 14(4): 98-109. Web site. http://www.bioline.org.br/pdf?rh10070. Accessed March 24, 2016.

19. Central Bureau of Statistics (CBS) [Kenya], Ministry of Health (MOH) [Keya], and ORC Macro. Kenya Demographic and Health Survey 2003, Calverton, Maryland. 2004. Web site. http://www.dhsprogram.com/pubs/pdf/FR151/FR151.pdf. Accessed March 24, 2016.

20. Rutstein, SO, Johnston K. The DHS Wealth Index. DHS Comparative Reports. No.6. ORC Macro, Calverton, Maryland USA. 2004. Web site. http://www.childinfo.org/files/DHS_Wealth_Index_(DHS_Comparative_Reports).pdf. Accessed March 24, 2016.

21. Church K, Wringe A, Fakudze P, et al. Reliance on condoms for contraceptive protection among HIV care and treatment clients: A mixed methods study on contraceptive choice and motivation within a generalised epidemic. Sex Transm Infect. 2014; 90(5): 394-400. doi: 10.1136/sextrans-2013-051339

22. Phillips SJ, Polis CB, Curtis KM. The safety of hormonal contraceptives for women living with HIV and their sexual partners. Contraception. 2016; 93(1): 11-16. doi: 10.1016/j.contraception.2015.10.002

23. Balkus JE, Brown ER, Hillier SL, et al. Oral and injectable contraceptive use and HIV acquisition risk among women in four African countries: A secondary analysis of data from a microbicide trial. Contraception. 2016; 93(1): 25-31. doi: 10.1016/j.contraception.2015

24. Obare F, van der Kwaak A, Birungi H. Factors associated with unintended pregnancy, poor birth outcomes and post-partum contraceptive use among HIV-positive female adolescents in Kenya. BMC Women’s Health.2012; 12: 34. doi: 10.1186/1472-6874-12-34

25. Magadi MA, Desta M. A multilevel analysis of the determinants and cross-national variations of HIV seropositivity in sub-Saharan Africa: evidence from the DHS. Health Place. 2011; 17(5): 1067-1083. doi: 10.1016/j.healthplace.2011.06.004

26. Schwartz SR, Rees H, Mehta S, Venter WDF, Taha TE, Black V. High incidence of unplanned pregnancy after antiretroviral therapy initiation: Findings from a prospective cohort study in South Africa. PLoS ONE. 2012; 7(4): e36039. doi: 10.1371/journal.pone.0036039

27. Raifman J, Chetty T, Tanser F, et al. Preventing unintended pregnancy and HIV transmission: Effects of the HIV treatment cascade on contraceptive use and choice in rural Kwa Zulu-Natal. J Acquir Immune Defic Syndr. 2014); 67(4): S218-S227. doi: 10.1097/QAI.0000000000000373

28. Antelman G, Medley A, Mbatia R, et al. Pregnancy desire and dual method contraceptive use among people living with HIV attending clinical care in Kenya, Namibia and Tanzania. J Fam Plann Reprod Health Care. 2015; 41(1): e1. doi: 10.1136/jfprhc-2013-100784

29. Roxby AC, Ben-Youssef L, Marx G, et al. Dual contraceptive method use in HIV-serodiscordant Kenyan couples. J Fam Plann Reprod Health Care. 2016 pii: jfprhc-2015-101233. doi: 10.1136/jfprhc-2015-101233

30. Habte D, Namasasu J. Family planning use among women living with HIV: knowing HIV positive status helps – results from a national survey. Reprod Health. 2015; 12: 41. doi: 10.1186/s12978-015-0035-6

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