Method-specific attributes that influence choice of future contraception among married women in Nairobi s informal settlements

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Method-specific attributes that influence choice of future contraception among married women in Nairobi s informal settlements Joyce Mumah, African Population and Health Research Center (APHRC) John Casterline, Ohio State University Kazuyo Machiyama, London School of Hygiene and Tropical Medicine (LSHTM) Marylene Wamukoya, APHRC Caroline Kabiru, Population Council John Cleland, LSHTM

Background Huge literature on contraceptive method choice Factors that influence method choice include: Information, availability, access and affordability, counselling, client-provider interaction and bias, socio-demographic correlates, opinions and fears about specific methods etc. Despite this extensive evidence base, it remains uncertain which factors are most influential in predisposing women towards certain methods and against others

Causal framework for reasons for unmet need for FP Generic disapproval of pregnancy prevention Method-specific barriers to use (Access, perceived effectiveness & safety, perceived & actual side effects of use, appropriateness, familiarity, ease of use, others) Perceived low risk of getting pregnant Weak, inconsistent or ambivalent fertility preferences Unmet need for family panning Partner-related factors

STUDY AIM Which perceived method-specific attributes most powerfully predict future intentions to use one of the three dominant methods* by women who are not currently using a method in Nairobi

Methods

METHODS Study Setting: Nairobi Urban Health & Demographic Surveillance System (NUHDSS) First urban-based longitudinal HDSS platform in SSA Established in 2002 65,000 (55% males) individuals in 24,000 HH in two slum communities (Korogocho and Viwandani) Data collection: Baseline data collection: September December 2016 A total of 2,812 married women aged 15-39 recruited in Nairobi Follow-up round currently ongoing in Nairobi (and in Homa Bay and Matlab)

METHODS Beguy et al. Int. J. Epidemiol. 2015;44:462-471

Methods Measures Contraceptive methods: Pills, Injectables, Implants Attributes include: Familiarity, access, perceived effectiveness, safety, side effects, ease of use, satisfaction with use among social networks, own past use and satisfaction, and partner approval Explanatory variables: Age, number of living children, educational attainment, and current fertility preferences Analysis: McFadden conditional logit regression allows for analysis of discrete choice

Results

Table 1: Percent distribution of demographic characteristics of women in Nairobi Current age Highest level of education Total % 15-24 23.1 25-39 76.9 No education/some primary 21.1 Completed primary 39.4 Secondary+ 39.6 Fertility Preference Want soon/want within 2 years/undecided 22.3 Want to wait 2+ years 47.3 Wants none/no more 27.7 Other preference^ 2.7 Current contraceptive use Injectables 32.4 Implants 19.8 Pills 8.4 Other methods 14.8 Not using 24.7 Total (N) 2812 Other fertility preferences include sterilized, cannot get pregnant, not asked n=76

Table 2: Percent distribution of methods non-users would prefer to use in the future among those intending use in the next 12 months Nairobi, 2016 Total Intention to use among non-users Total % n Intend to use in <12 months 59.9 416 Injectables 30.3 210 Implants 11.2 78 Pills 5.8 40 Other methods 12.7 88 Intend to use in 12+ months/do not intend to use 39.8 276 Not asked about intent 0.3 2 100 694 This panel only includes the women who are not currently using a method (350 women in Korogocho and 344 women in Viwandani)

Table 3: % of respondents with specific negative opinions about selected methods, among women not currently using a method and intend to use injectables, implants or pills within the next 12 months in Nairobi, 2016 Negative opinions Injectables Implants Pills % % % Hard to obtain 2 9 7 FP use among social network (Most) 69 38 20 Experiences of friend, relatives or neighbors (unsatisfactory) 11 18 33 Not effective at preventing pregnancy 11 12 36 Cause serious health problems 17 20 12 Interfere with menstruation 77 62 41 Cause unpleasant side effects 56 57 44 Unsafe to use for a long time 60 53 68 Causes infertility 30 26 16 Husband disapproves 20 38 40 Past use (past user not satisfied) 27 6 20 Mean number of negatives 3.5 3.5 4.1 TOTAL (N) 317 317 317

Table 4: Intention to use injectables, implants and pills within 12 months among non-users and pregnant women who know all three methods, Nairobi 2016 Excludes husband's approval Includes husband's approval OR p-value OR p-value Effects of Method Attributes Easy to find 1.75 0.288 1.5 0.456 Social network tried & satisfied 1.92 0.003 1.8 0.007 Effectively prevents pregnancy 2.11 0.029 1.88 0.065 Doesn't cause health problems 1.18 0.595 1.11 0.752 Doesn't interfere with menses 2.05 0.006 2.15 0.004 Doesn't cause side effects 0.92 0.718 0.86 0.498 Safe for long use 1.73 0.033 1.63 0.062 Doesn't cause infertility 1.73 0.067 1.5 0.193 Past use & satisfaction (Ref: Never used) Ever used + satisfied 3.56 0.001 2.97 0.001 Ever used + dissatisfied 1.02 0.939 0.84 0.58 Husband approves of method 3.2 0.001 N 317 317

Discussion and Conclusion Current method mix is skewed 3 methods dominate Profile of intentions closely mimics current method mix Degree of skewness justifies focus on these methods High levels of current and past use do not necessarily imply positive perceptions Modern contraceptive use regarded with anxiety about effect on health

Discussion and Conclusion Apart from partner s approval, largest influence on future method choice was satisfactory past use Underscores the importance of having alternatives Interference with menses, satisfaction with a method by woman s social network, methods perceived to be safe to use for a long time were influential attributes Side effects and health concerns appear to not have significant influence on future choice of method

The STEP UP (Strengthening Evidence for Programming on Unintended Pregnancy) Research Programme Consortium is coordinated by the Population Council in partnership with the African Population and Health Research Center; icddr,b; the London School of Hygiene and Tropical Medicine; and Marie Stopes International. STEP UP is funded by UK aid from the UK Government.

Thank you Contact: jmumah@aphrc.org