PMA2017/Kenya-R6, the sixth round of data collection in Kenya, 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 11 out of 47 counties: Nairobi, Kilifi, Nandi, Nyamira, Kiambu, Bungoma, Siaya, Kericho, Kitui, Kakamega, and West Pokot. The round 6 sample included the two new counties, Kakamega and West Pokot, which were added in round 5. The same set of enumeration areas used from round 5 were selected, adjacent to the areas enumerated in the first four survey rounds. Within the 11 selected counties, 151 EAs were then selected by the Kenya National Bureau of Statistics.
Households were surveyed and occupants enumerated. All eligible females age 15 to 49 were contacted and consented for interviews. The final sample included 6,106 households, 5,876 females and 417 health facilities (97.8%, 99.0% and 97.2% response rates respectively). Data collection was conducted between November and December 2017.
The sample was powered to generate national estimates of all women mCPR with less than 3% margin of error. The survey was also able to generate estimates on family planning services by including a random sample of up to three private service delivery points within each EA’s boundary. In addition, three public health service delivery points that serve the EA population were also selected—a dispensary, a health center and a referral hospital, either at the sub-county or county level.
The table below provides a summary of key family planning indicators and their breakdown by respondent background characteristics.
|All Women||Married Women|
|Contraceptive Prevalence Rate (CPR)||45.0||60.5|
|Modern Contraceptive Prevalence (mCPR)||43.7||59.0|
|Traditional Contraceptive Prevalence||1.3||1.5|
|Demand for Family Planning and Fertility Preferences:|
|Unmet need for family planning||12.5||14.9|
|Demand for family planning||57.5||75.4|
|Percent of all/married women with demand satisfied by modern contraception||76.0||78.2|
|Percent of recent births, by intention:|
|Wanted no more||14.5||12.1|
|Access, Equity, Quality and Choice|
|Percent of users who chose their current method by themselves or jointly with a partner/provider||94.9||95.3|
|Percent of users who paid for family planning services||73.5||73.3|
|Method Information Index:|
|Percent of current users who were informed about other methods||67.2||71.4|
|Percent of current users who were informed about side effects||63.3||66.5|
|Percent of current users who were told what to do if they experienced side effects||91.1||90.7|
|Percent of current users who would return and/or refer others to their provider||92.0||92.5|
|Percent of women receiving family planning information in the past 12 months||9.9||12.5|
The PMA2017 Kenya Round 6 Survey in Detail
Round 1 Sample Design
During the first round in Kenya (2014) a multi-stage cluster design with urban/rural and county as strata was used. 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 5 and 6 Sample Update
All households, health service delivery points and key landmarks in each EA were listed and mapped by the REs to create a frame for the second stage of the sampling process. Field supervisors randomly selected 42 households using a phone-based random number-generating application. A household roster was completed and all eligible women age 15-49 were approached and asked to provide informed consent (and assent if aged 15-17) to participate in the study.
The majority of public 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, random sample of three private SDPs is selected during each round.
The final sample included 6,106 households, 5,876 females and 417 health facilities (97.8%, 99.0% and 97.2% response rates respectively). Data collection was conducted between November and December 2017.
The household, female and health facility questionnaires were based on model surveys designed by PMA2020 staff at the Bill & Melinda Gates Institute for Population and Reproductive Health and fieldwork materials of the 2008-09 Kenyan Demographic and Health Survey.
All PMA2020 questionnaires are administered using Open Data Kit (ODK) software and Android smartphones. The PMA2017/Kenya-R6 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 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 WASH 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; and exposure to family planning messaging in the media.
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 SDP.
Training, Data Collection & Processing
The objective of the refresher training was to address the gaps and errors identified during any previous rounds of data collection, to understand the questionnaire changes for Round 6, to refresh the knowledge and skills on questionnaire content and the art of asking questions through paired interviews. In addition, field staff were also reminded of key survey protocols they needed to abide by, including consent administration and research ethics.
Throughout the refresher training, REs and supervisors were evaluated based on their performance on several written and phone-based assessments and class participation. The RE trainings were conducted primarily in English, some small group sessions were conducted in Kiswahili. 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.
Data Collection & ProcessingData collection was conducted between November and December 2017. Unlike traditional paper-and-pencil surveys, PMA2020 uses ODK Collect, an open-source software application, to collect data on mobile phones. All the questionnaires were programmed using this software and installed onto all project smartphones. The ODK questionnaire forms are programmed with automatic skip-patterns and built-in response constraints to reduce data entry errors.
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 Bill & Melinda Gates Institute at Johns Hopkins School of Public Health in Baltimore, Maryland 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 December.
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® software.
In the occupied households that provided an interview, a total of 5,977 eligible women age 15 to 49 years were identified. Overall, 98.9% of the eligible women were available and consented to the interview. The female response rate was slightly higher in the rural (99.4%) relative to the urban (98.4%) enumeration areas (EAs). Only de facto females are included in the analyses; the final completed de facto female sample size was 5,876.
During the survey, 429 SDPs were identified of which 417 SDPs completed the survey (97.2% response rate).
Weights were adjusted for non-response at the household and individual levels and applied to all household and individual estimates in this report. SDP estimates are not weighted.
|PMA2017/Kenya Round 6|
|Household response rate* (%)||95.4||99.3||97.8|
|Interviews with women age 15-49|
|Number of eligible women**||2,057||3,877||5,934|
|Number of eligible women interviewed||2,024||3,852||5,876|
|Eligible women response rate† (%)||98.4||99.4||99.0|
**Eligible women response rates include only women identified in completed household interviews
†Eligible women response rate = eligible women interviewed/eligible women