Abstract

The primary objective of the 2017 Indonesia Dmographic and Health Survey (IDHS) is to provide up-to-date estimates of basic demographic and health indicators. The IDHS provides a comprehensive overview of population and maternal and child health issues in Indonesia. More specifically, the IDHS was designed to: - provide data on fertility, family planning, maternal and child health, and awareness of HIV/AIDS and sexually transmitted infections (STIs) to help program managers, policy makers, and researchers to evaluate and improve existing programs; - measure trends in fertility and contraceptive prevalence rates, and analyze factors that affect such changes, such as residence, education, breastfeeding practices, and knowledge, use, and availability of contraceptive methods; - evaluate the achievement of goals previously set by national health programs, with special focus on maternal and child health; - assess married men’s knowledge of utilization of health services for their family’s health and participation in the health care of their families; - participate in creating an international database to allow cross-country comparisons in the areas of fertility, family planning, and health.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-54

Universe

The survey covered all de jure household members (usual residents), all women age 15-49 years resident in the household, and all men age 15-54 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2017 IDHS sample covered 1,970 census blocks in urban and rural areas and was expected to obtain responses from 49,250 households. The sampled households were expected to identify about 59,100 women age 15-49 and 24,625 never-married men age 15-24 eligible for individual interview. Eight households were selected in each selected census block to yield 14,193 married men age 15-54 to be interviewed with the Married Man's Questionnaire. The sample frame of the 2017 IDHS is the Master Sample of Census Blocks from the 2010 Population Census. The frame for the household sample selection is the updated list of ordinary households in the selected census blocks. This list does not include institutional households, such as orphanages, police/military barracks, and prisons, or special households (boarding houses with a minimum of 10 people).

The sampling design of the 2017 IDHS used two-stage stratified sampling: Stage 1: Several census blocks were selected with systematic sampling proportional to size, where size is the number of households listed in the 2010 Population Census. In the implicit stratification, the census blocks were stratified by urban and rural areas and ordered by wealth index category.

Stage 2: In each selected census block, 25 ordinary households were selected with systematic sampling from the updated household listing. Eight households were selected systematically to obtain a sample of married men.

For further details on sample design, see Appendix B of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2017 IDHS used four questionnaires: the Household Questionnaire, Woman’s Questionnaire, Married Man’s Questionnaire, and Never Married Man’s Questionnaire. Because of the change in survey coverage from ever-married women age 15-49 in the 2007 IDHS to all women age 15-49, the Woman’s Questionnaire had questions added for never married women age 15-24. These questions were part of the 2007 Indonesia Young Adult Reproductive Survey Questionnaire. The Household Questionnaire and the Woman’s Questionnaire are largely based on standard DHS phase 7 questionnaires (2015 version). The model questionnaires were adapted for use in Indonesia. Not all questions in the DHS model were included in the IDHS. Response categories were modified to reflect the local situation.

Cleaning operations

All completed questionnaires, along with the control forms, were returned to the BPS central office in Jakarta for data processing. The questionnaires were logged and edited, and all open-ended questions were coded. Responses were entered in the computer twice for verification, and they were corrected for computer-identified errors. Data processing activities were carried out by a team of 34 editors, 112 data entry operators, 33 compare officers, 19 secondary data editors, and 2 data entry supervisors. The questionnaires were entered twice and the entries were compared to detect and correct keying errors. A computer package program called Census and Survey Processing System (CSPro), which was specifically designed to process DHS-type survey data, was used in the processing of the 2017 IDHS.

Response rate

Of the 49,261 eligible households, 48,216 households were found by the interviewer teams. Among these households, 47,963 households were successfully interviewed, a response rate of almost 100%.

In the interviewed households, 50,730 women were identified as eligible for individual interview and, from these, completed interviews were conducted with 49,627 women, yielding a response rate of 98%. From the selected household sample of married men, 10,440 married men were identified as eligible for interview, of which 10,009 were successfully interviewed, yielding a response rate of 96%. The lower response rate for men was due to the more frequent and longer absence of men from the household. In general, response rates in rural areas were higher than those in urban areas.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors result from mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2017 Indonesia Demographic and Health Survey (2017 IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017 IDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017 IDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2017 IDHS is a STATA program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in Appendix C of the survey final report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar year - Reporting of age at death in days - Reporting of age at death in months

See details of the data quality tables in Appendix D of the survey final report.