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PMA2016/Rajasthan-R1 SOI

SNAPSHOT OF INDICATORS

Summary of the sample design for PMA2016/Rajasthan-R1:

In India, the PMA2020 survey collects data at the state level to allow for the estimation of key indicators to monitor progress in family planning - both at the population and the service delivery points (SDPs) levels. The survey was conducted in Rajasthan state in 2016.

PMA2016/Rajasthan is the first round of PMA2020 data collection in Rajasthan state, India. The survey used a two-­stage cluster design within the state and urban/rural strata. Primary sampling units were selected using probability proportional to size procedures within the state. The sample was powered to generate state-level estimates of all women mCPR with less than a 2% margin of error and a less than 3% margin of error for urban/rural estimates. To read more details on our survey methodology including the survey tools, training, data processing and response rates, please scroll to the end of the table below.

The table below provides a summary of key family planning indicators and their breakdown by respondent background characteristics. Estimates for all indicators are representative for the state. To view the breakdown by background characteristics of the respondents (including education level, wealth quintile, region etc.), please click on the respective indicator link. 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. Additional details on sample design, data collection and processing, response rates, and standard errors are available below the indicator tables.

Download the full SOI tables >>

PMA2020 Standard
Family Planning Indicators

Round 1
All Women Married Women
Utilization:
Contraceptive Use    
Contraceptive Prevalence Rate (CPR) 41.8 54.8
Modern Contraceptive Prevalence (mCPR) 39.5 51.7
Traditional Contraceptive Prevalence 2.9 3.8
Contraceptive Method Mix    
Contraceptive method mix (stacked bar charts for all/married women)    
Demand Indicators:
Unmet need for family planning 11.3 14.4
Demand for family planning 53.0 69.0
Percent of women with demand satisfied by modern contraception 73.3 73.6
Percent of recent births, by intention
Wanted then 81.4 81.5
Wanted later 13.6 13.6
Wanted no more 5.1 4.9
Access, Equity, Quality and Choice:
Percent of users who chose their current method by themselves or jointly with a partner/provider 77.7 78.1
Percent of users who paid for family planning services 19.9 20.1
Method Information Index Components    
Percent of current users who were informed about other methods 45.3 45.5
Percent of current users who were informed about side effects 58.3 58.0
Percent of current users who were told what to do if they experienced side effects 83.5 83.5
Percent of current users who would return and/or refer others to their provider 46.8 46.5
Percent of women receiving family planning information in the past 12 months 32.3 37.2

The PMA2016/Rajasthan-R1 Survey in Detail

Sample Design

Round 1 Sample Design

In India, the PMA2020 survey collects data at the state-level to allow for the estimation of key indicators to monitor progress in family planning - both at the population and the service delivery points (SDPs) levels. The resident enumerator (RE) model enables replication of the surveys twice a year for the first two years, and annually each year after that, to track progress.

For this first round of PMA2020 data collection in Rajasthan, India (PMA2016/Rajasthan), the project used a two-stage cluster design within the state and urban/rural strata and drew a sample of 147 enumeration areas (EAs) by the International Institute for Population Sciences from a master sampling frame to achieve a representative sample of Rajasthan state. The master frame of EAs was based on a master sampling frame from the International Institute for Population Sciences.

In each selected EA cluster, households and private health facilities were listed and mapped. Field supervisors randomly selected 35 households from the household listing using a random number generation phone application. A household roster was completed and all eligible women age 15-49 in selected households were approached and asked to provide informed consent to participate in the study. For the SDP survey, up to three private SDPs, including pharmacies, within each sampled EA cluster boundary were randomly selected from the listing. In addition, three public health SDPs—a health post, a health center, and a district hospital designated to serve the EA population—were selected.

Questionnaires

PMA2020 uses standardized questionnaires for households, females and SDPs to gather data about households and individual females that are comparable across program countries and consistent with existing national surveys. Prior to launching the survey in each country, local experts review and modify these questionnaires to ensure all questions are appropriate to each setting. All female questionnaires were translated into Hindi, and translations were reviewed for appropriateness. Three questionnaires were used to collect data from the PMA2016/Rajasthan-R1 survey: the household questionnaire, the female questionnaire and the service delivery point (SDP) questionnaire. These questionnaires were based on model surveys designed by PMA2020 staff at the Bill & Melinda Gates Institute for Population and Reproductive Health at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland, USA, the Indian Institute of Health Management Research (IIHMR) University in Jaipur, and fieldwork materials of the India National Family Health Survey.

All PMA2020 questionnaires are administered using Open Data Kit (ODK) software and Android smartphones. The questionnaires were in English and could be switched into local languages (Hindi) on the phone. The questionnaires were translated using available translations from similar population surveys and experts in translation. The interviews were conducted in the local language, or English in a few cases when the respondent was not comfortable with the local language. Female resident enumerators in each enumeration area (EA) administered the household and female questionnaires in the 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.

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

Training

The PMA2016/Rajasthan fieldwork training started with a centralized training of field supervisors and central staff in Spring 2016. The training was led by PMA2020 staff from the Bill & Melinda Gates Institute for Population and Reproductive Health of the Johns Hopkins Bloomberg School of Public Health, with support from the Indian Institute of Health Management Research (IIHMR) University in Jaipur and endorsement and technical support provided by the International Institute for Population Sciences (IIPS) and the Ministry of Health and Family Welfare (MOHFW). Field supervisors, supported by the central team and PMA2020 team, then became the trainers for the subsequent resident enumerator (RE) training sessions that took place before the start of data collection.

Throughout the training, resident enumerators (REs) and supervisors were evaluated based on their performance on phone-based assessments. The RE training was conducted primarily in Hindi, whereas some small group review sessions were conducted in other local languages.

Supervisors received additional training prior to and after the RE training to further strengthen their supervision skills, including instruction on conducting re-interviews, carrying out random spot checks, and dealing with the local/community leaders and engaging the communities.

Data Collection and Processing

Data collection was conducted between June and September 2016. 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 IIHMR in Jaipur, Rajasthan 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 September.

Once all data were on the server, data analysts cleaned and de-identified the data, applied survey weights, and prepared the final dataset for analysis using Stata. The findings were shared at the state and national levels with government and community stakeholders at two dissemination events in December 2016.

Response Rates

The table below shows response rates for household and female respondents by residence (rural/urban) for PMA2016/Rajasthan-R1. A total of 5,116 households were selected for the Round 1 survey; 5,002 households were found to be occupied at the time of the fieldwork. Of the occupied households, 4,870 (97.4%) consented to a household-level interview. The response rate at the household level was higher in rural (97.8%) than in urban (96.1%) areas.

In the occupied households that provided an interview, a total of 5,506 eligible women age 15 to 49 years were identified. Overall, 96.4% of the eligible women were available and consented to the interview. The female response rate was slightly higher in the rural (96.8%) relative to the urban (95.2%) enumeration areas (EAs). Only de facto females are included in the analyses; the final completed de facto female sample size was 5,306.

    PMA2016/Rajasthan-R1
Result   Urban Rural Total
Household interviews              
Households selected   1,284 3,832 5,116
Households occupied   1,241 3,761 5,002
Households interviewed   1,192 3,678 4,870
Household response rate* (%)   96.1 97.8 97.4
             
Interviews with women age 15 to 49
Number of eligible women**   1,463 4,043 5,506
Number of eligible women interviewed   1,393 3,913 5,306
Eligible women response rate (%)   95.2 96.8 96.4
*Household response rate=number of household interviews/households occupied

**Eligible women response rates include only women identified in completed household interviews

Eligible women response rate = eligible women interviewed/eligible women

Sample Error Estimates

The following table shows sample errors for the PMA2020 indicators described above. For more information about PMA2020 indicators, including estimate type and base population, click here.

Variable Value[R] Standard Error Confidence Interval
R-2SE R+2SE
All women age 15-49
Currently using a modern method 0.397 0.017 0.363 0.431
Currently using a traditional method 0.029 0.006 0.017 0.040
Currently using any contraceptive method 0.420 0.017 0.386 0.453
Currently using injectables 0.011 0.004 0.004 0.019
Currently using male condoms 0.095 0.010 0.076 0.114
Currently using implants 0.003 0.002 -0.002 0.008
Chose method by self or jointly in past 12 months 0.774 0.037 0.702 0.847
Paid fees for family planning services in past 12 months 0.186 0.017 0.151 0.220
Informed by provider about other methods 0.465 0.033 0.400 0.530
Informed by provider about side effects 0.582 0.040 0.503 0.660
Satisfied with provider: Would return and refer friend/relative to provider 0.472 0.041 0.391 0.552
Visited by health worker who talked about family planning in past 12 months 0.323 0.028 0.268 0.379
Women in union age 15-49
Currently using a modern method 0.518 0.021 0.476 0.560
Currently using a traditional method 0.038 0.008 0.023 0.053
Currently using any contraceptive modern method 0.550 0.021 0.509 0.591
Currently using injectables 0.015 0.005 0.005 0.024
Currently using male condoms 0.123 0.011 0.101 0.146
Currently using implants 0.004 0.003 -0.002 0.010
Chose method by self or jointly in past 12 months 0.778 0.035 0.709 0.847
Paid fees for family planning services in past 12 months 0.187 0.018 0.152 0.222
Informed by provider about other methods 0.467 0.033 0.403 0.532
Informed by provider about side effects 0.579 0.039 0.502 0.657
Satisfied with provider: Would return and refer friend/relative to provider 0.469 0.040 0.390 0.549
Visited by health worker who talked about family planning in past 12 months 0.372 0.031 0.311 0.432