SNAPSHOT OF INDICATORS
Summary of the sample design for PMA2015/Kenya-R3:
PMA2020 uses a two-stage cluster design with residential area (urban and rural) and county as strata, sampling across nine counties in Kenya: Nairobi, Kilifi, Nandi, Nyamira, Kiambu, Bungoma, Siaya, Kericho and Kitui. The first stage of sampling was a selection of nine of Kenya’s 47 counties, using probability proportional to size procedures. Within the nine counties, clusters were selected proportional to the urban/rural distribution. The final sample was designed to generate estimates of all women modern contraceptive prevalence rate with less than 3% margin of error at both the national and urban/rural level.
The table below provides a summary of key family planning indicators at the national level and their breakdown by background characteristics. Disaggregation by administrative unit was done at the county level.
To view the breakdown by background characteristics of the respondents, please click on the respective indicator link. Distribution of respondents by background characteristics is available here. Distribution of SDPs by background characteristics is available here.
Additional details on sample design, data collection and processing, response rates, and standard errors are available below the indicator tables.
The PMA2015/Kenya-R3 Survey in Detail
Round 1 Sample Design
PMA2014/Kenya Round 1 used a multi-stage cluster design with urban/rural and county as strata. The first stage of sampling was at the county level using probability proportional to size procedures to select nine out of 47 counties: Nairobi, Kilifi, Nandi, Nyamira, Kiambu, Bungoma, Siaya, Kericho and Kitui. Within the nine selected counties, 120 enumeration areas (EAs) were selected proportional to size with urban/rural stratification. The sample was powered to generate national and urban/rural estimates of all woman mCPR with less than 3% margin of error.
In each selected EA, field supervisors randomly selected up to three private service delivery points (SDPs) to be interviewed by an RE using the SDP questionnaire. The field supervisors themselves administered the SDP questionnaires at an additional three public SDPs that serve each EA - the lowest, second-lowest and third-lowest level public health SDPs designated to serve each EA (a dispensary, a health center and a referral hospital), either at the sub-county or county level.
Round 3 Sample Update
The majority of SDPs are repeated in each round, forming a panel survey. If an EA had more than three private SDPs identified during the listing process, then a new sample of the private SDPs is selected during each round.
All PMA2020 questionnaires are administered using Open Data Kit (ODK) software and Android smartphones. The PMA2015/Kenya-R3 questionnaires appeared in Kiswahili in addition to English. Female resident enumerators in each enumeration area (EA) administered the household and female questionnaires in selected households.
The household questionnaire gathers basic information about the household, such as ownership of livestock and durable goods, as well as characteristics of the dwelling unit, including wall, floor and roof materials, water sources, and sanitation facilities. This information is used to construct a wealth quintile index.
The first section of the household questionnaire, the household roster, lists basic demographic information about all usual members of the household and visitors who stayed with the household the night before the interview. This roster is used to identify eligible respondents for the female questionnaire. In addition to the roster, the household questionnaire also gathers data that are used to measure key water, sanitation, and hygiene (WASH) indicators, including regular sources and uses of water, sanitation facilities used and prevalence of open defecation by household members.
The female questionnaire is used to collect information from all women age 15 to 49 who were listed on the household roster at selected households. The female questionnaire gathers specific information on: education; fertility and fertility preferences; family planning access, choice and use; quality of family planning services; exposure to family planning messaging in the media; and the burden of collecting water on women.
In each selected enumeration area, field supervisors randomly selected up to three private SDPs to be interviewed by a resident enumerator using the SDP questionnaire. The field supervisors themselves administered the SDP questionnaires at an additional three public SDPs that serve each EA. The SDP questionnaire collected information about the provision and quality of reproductive health services and products, integration of health services, and water and sanitation within the health facility.
Training, Data Collection and Processing
All training participants at the two-week training were given comprehensive instruction on how to complete the household, female, and service delivery point (SDP) questionnaires. In addition to PMA2020 survey training, all participants received training on contraceptive methods by a Kenyan obstetrician/gynecologist.
Throughout the two-week training, REs were evaluated based on their performance on several written and phone-based assessments, mock field exercises and class participation. As all questionnaires were completed on project smartphones, the training also familiarized participants with Open Data Kit (ODK) and smartphone use in general. The two-week training training included three days of field exercises, during which participants entered a mock enumeration area (EAs) to practice listing, mapping and conducting household, female and SDP interviews; recording all responses on their project phones; and submitting to a practice cloud server—a centralized data storage system. The RE trainings were conducted primarily in English, whereas some small group sessions were conducted in Kiswahili.
For the refresher training, all training participants were given instructions on survey changes to the tools since the previous round.
The REs and supervisors were all evaluated based on their performance on phone-based assessments. Similar to the two-week training, the two-day refresher trainings was conducted primarily in English, whereas some small group sessions were conducted in Kiswahili.
Data Collection and Processing
The ODK application enabled REs and supervisors to collect and transfer survey data to a central ODK Aggregate cloud server. This instantaneous aggregation of data also allowed for concurrent data processing and course corrections while PMA2020 was still active in the field. Throughout data collection, central staff at ICRH-K in Kenya and the data manager at the Gates Institute at Johns Hopkins in Baltimore routinely monitored the incoming data and notified field staff of any potential errors, missing data or problems found with form submissions on the central server. The use of mobile phones combined data collection and data entry into one step; therefore, data entry was completed when the last interview form was uploaded at the end of data collection in July.
Once all data were on the server, data analysts cleaned and de-identified the data, applied survey weights, and prepared the final data set for analysis using Stata® version 14 software.
In the occupied households that provided an interview, a total of 4,452 eligible women age 15 to 49 years were identified. Overall, 98.7% of the eligible women were available and consented to the interview. The female response rate was slightly higher in the rural (99.3%) relative to the urban (97.8%) enumeration areas (EAs). Only de facto females are included in the PMA analyses; the final completed de facto female sample size was 4,396.
The final SDP sample include 358 facility interviews, of which 348 were completed for a response rate of 97.2%.
|Household response rate* (%)||94.0||99.1||97.0|
|Interviews with women ages 15 to 49|
|Number of eligible women**||1,709||2,743||4,452|
|Number of eligible women interviewed||1,671||2,725||4,396|
|Eligible women response rate† (%)||97.8||99.3||98.7|
**Eligible women response rates include only women identified in completed household interviews
†Eligible women response rate = eligible women interviewed/eligible women
Sample Error Estimates
|Variable||Value[R]||Standard Error||Confidence Interval|
|All women age 15-49|
|Currently using a modern method||0.465||0.016||0.433||0.498|
|Currently using a traditional method||0.016||0.003||0.010||0.021|
|Currently using any contraceptive method||0.481||0.016||0.448||0.513|
|Currently using injectables||0.231||0.011||0.210||0.252|
|Currently using male condoms||0.039||0.005||0.030||0.049|
|Currently using implants||0.102||0.007||0.088||0.115|
|Chose method by self or jointly in past 12 months||0.974||0.005||0.964||0.984|
|Paid fees for family planning services in past 12 months||0.466||0.024||0.419||0.512|
|Informed by provider about other methods||0.659||0.021||0.617||0.700|
|Informed by provider about side effects||0.613||0.026||0.562||0.664|
|Satisfied with provider: Would return and refer friend/relative to provider||0.876||0.019||0.839||0.913|
|Visited by health worker who talked about family planning in past 12 months||0.105||0.010||0.085||0.124|
|Women in union age 15-49|
|Currently using a modern method||0.588||0.017||0.555||0.622|
|Currently using a traditional method||0.022||0.004||0.014||0.031|
|Currently using any contraceptive modern method||0.611||0.017||0.578||0.644|
|Currently using injectables||0.310||0.014||0.283||0.336|
|Currently using male condoms||0.025||0.005||0.016||0.034|
|Currently using implants||0.138||0.009||0.120||0.156|
|Chose method by self or jointly in past 12 months||0.977||0.005||0.967||0.986|
|Paid fees for family planning services in past 12 months||0.453||0.025||0.403||0.503|
|Informed by provider about other methods||0.681||0.021||0.639||0.722|
|Informed by provider about side effects||0.642||0.026||0.591||0.693|
|Satisfied with provider: Would return and refer friend/relative to provider||0.894||0.016||0.862||0.927|
|Visited by health worker who talked about family planning in past 12 months||0.119||0.011||0.097||0.142|