The 2001 Azerbaijan Reproductive Health Survey (AZRHS01) is the first population-based national survey of its kind conducted in Azerbaijan.
Azerbaijan has undergone major socioeconomic and political changes: the war with Armenia, forced migration and population displacement, economic hardships, and deterioration of health and social services. These changes have affected practically all aspects of life for its people. The reported flaws associated with official statistics have prohibited any meaningful attempts at informed decision making, planning, and program evaluation in reproductive health. A nationwide survey was recommended to assess the reproductive health status of the population during this transition period, a period of profound changes in health needs and access to health care services. The national reproductive health survey conducted in Azerbaijan in 2001 (AZRHS01) is the first nationwide population-based survey aimed at providing a wide array of information about the current status of women's health in that country. The survey will aid in identifying unmet programmatic needs and will serve as a baseline for future studies and evaluations. The AZRHS01 was specifically designed to meet the following objectives:
- To assess fertility, abortion, contraception, and various other reproductive health issues in Azerbaijan.
- To enable policy makers, program managers, and researchers to evaluate existing reproductive health programs and develop new strategies.
- To study factors that affect fertility, contraceptive use, and maternal and infant health, such as geographic and sociodemographic factors, breast-feeding patterns, use of induced abortion, and availability of family planning services.
- To identify characteristics of women at risk for unintended pregnancy.
- To identify high-risk groups and focus additional reproductive health studies on them.
- To obtain data on the knowledge, attitudes, and behavior of young adults 15-24 years of age.
- To provide data on the level of reported STI symptoms and knowledge about transmission and prevention of AIDS.
- To provide data on women living in prolonged displacement.
Similar to the survey conducted in Georgia, completed in 2000, the AZRHS01 included an oversample of refugee women and women internally displaced by war and ethnic cleansing to document their specific health needs. The disruption associated with living in improvised settings makes safe motherhood difficult, limits contraceptive access and use, increases the risks of HIV/AIDS and other STIs, neglects the special needs of adolescents, and may increase the risk of violence against women. Public health surveillance systems often exclude data collection and analysis essential to addressing the specific issues of IDP/Rs. To our knowledge, no country or organization has attempted parallel documentation of the reproductive health status of a nation and an internally displaced group within the country. By collecting information from the general population and from IDP/Rs, the AZRHS01 can document specific needs associated with displacement, account for differences in reproductive health status between the two populations, and provide a useful tool for evaluating existing reproductive health programs and activities that specifically address displaced women and children.
The Division of Reproductive Health, U.S. Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, coordinated survey activities and provided technical assistance to the local implementing agency, the Adventist Development and Relief Agency (ADRA), Baku, Azerbaijan.
Funding was provided by the United States Agency for International Development (USAID)—through the umbrella agreement managed by Mercy Corps (MC)—the United Nations Population Fund (UNFPA), and United Nations High Commissioner for Refugees (UNHCR).
Kind of Data
Sample survey data [ssd]
The questionnaire included information on each woman's education, employment, living arrangements, and other background characteristics as well as histories of marriage, divorce, cohabitation, sexual activity, pregnancy, and contraceptive use. Additional questions investigated health risk behaviors that may affect reproductive health (e.g., smoking and drinking habits), women's health screening practices, and intimate partner violence.
The AZRHS01 is based on face-to-face interviews with 7,668 women at their homes. The survey was designed to collect information from a representative sample of women of reproductive age throughout Azerbaijan (excluding the autonomous region of Nakhchivan and the occupied territories of Nagorno-Karabakh and surrounding areas).
The universe from which the respondents were selected included all females between the ages of 15 and 44 years, regardless of marital status, who were living in households in Azerbaijan when the survey was carried out
Producers and sponsors
Adventist Development and Relief Agency (ADRA)
Azerbaijan State Committee for Statistics
Division of Reproductive Health of the United States Centers for Disease Control and Prevention
Technical assistance in survey design, sampling, questionnaire development, training, data processing, and report writing
U.S. Agency for International Development
United Nations Population Fund
United Nations High Commissioner for Refugees
The household survey used a stratified multistage sampling design using the recent 1999 census as the sampling frame (State Committee of Statistics of the Azerbaijan Republic [SCS], 2000). For the AZRHS01, the geographic area of the Azerbaijan Republic was divided into four independent sampling strata. The strata were created by grouping regions with a similar concentration of IDPs and refugees (IDP/Rs), as recorded by the United Nations High Commissioner for Refugees (UNHCR, 2000). The sample was selected with probability proportional to the population size (PPS) within each stratum. Stratum 1 included six rayons that each consisted of more than 30% of their population constituted by IDP/Rs: Fizuli (53%), Xanlar (51%), Barda (44%), Naftalan (40%), Aghjabedi (32%), and Bilasuvar (31%). Stratum 2 included five rayons in which the IDP/Rs represented 20%-30% of the population: Imishli (25%), Saatli (23%), Belagan (22%), Mingechevir (21%), and Terter (20%). Stratum 3 included only the Baku district, which also had a relatively high concentration of IDP/Rs (14%). Stratum 4 included all other rayons, except those in Nakhchivan and the occupied territories of Nagorno-Karabakh and surrounding areas.
Regions with high concentrations of IDP/Rs (Strata 1 and 2) were oversampled for programmatic reasons. The oversampling in regions heavily populated by IDP/Rs was needed to include enough displaced women in the sample to allow independent estimates of their reproductive health status. This technique illustrates how surveys may be designed and integrated in the development, monitoring, and evaluation of targeted reproductive health programs. The oversampling of IDP/Rs was specifically designed to assess the reproductive health status of these women and measure the impact of the Azerbaijan Humanitarian Assistance Project (AHAP) funded by USAID and various projects targeting the IDP population supported by UNHCR and UNFPA. These projects aim to reduce the reliance on induced abortion by increasing access to and availability of effective contraceptive methods and by reducing the prevalence of STDs through the promotion of healthy behaviors among women (e.g., routine gynecologic exams) and child survival activities. These projects encompass various interventions, such as the establishment of modern health clinics for women; training of health professionals; development of information, education, and communication messages; social marketing; and provision of high-quality contraceptive supplies.
The first stage of the three-stage sample design was a selection of Census sectors with probability proportional to the number of households in each sector, after the sectors were grouped into four strata. This stage was accomplished by using a systematic sample with a random start in each stratum. During the first stage, 300 census sectors were selected and became primary sampling units (PSUs), as follows: Baku (80 PSUs), regions with more than 30% of the population being IDP/Rs (100 PSUs), regions with 20%-30% of the population being IDP/Rs (50 PSUs), and all other regions (70 PSUs). In the second stage of sampling, clusters of households were randomly selected in each census sector chosen in the first stage. The cluster size was based on the number of households required to obtain an average of 20 completed interviews per cluster. The total number of households in each cluster took into account estimates of unoccupied households, average number of women aged 15-44 per household, the interview of only one respondent per household, and an estimated response rate of 90% in urban areas and 92% in rural areas. Finally, in each of the households selected, one woman between age 15 and 44 was selected at random for interview (ifthere was more than one woman was in the household).
Because only one woman was selected from each household containing women of reproductive age, all results have been weighted to compensate for the fact that some households included more than one eligible female respondent. Survey results were also weighted to adjust for oversampling of households in the regions with a high concentration of IDP/R population and the undersampling in regions in which less than 20% of the population consisted of IDP/Rs.
Of the 11,162 households selected in the household sample, 8,246 included at least one eligible woman (aged 15-44 years). Of those, 7,668 women were successfully interviewed, yielding a response rate of 93%. About 5% of women were absent and could not be interviewed during several revisits. Virtually all respondents who were selected to participate and who could be reached agreed to be interviewed (the individual refusal rate was only 1.2%). Response rates were lower in Baku and its environs (86%) than in other urban areas (94%) and rural areas (96%).
The distribution of women in the sample by 5-year age groups differs slightly from the official estimates for the year 1999: the survey sample slightly overrepresents adolescent women (15- to 19- year-olds) and underrepresents women aged 25-29 by 2 percentage points, after confidence intervals are taken into account. The sample retains the same over- and underrepresentation for women aged 15-19 and 25-29 for both urban and rural residents. At least two factors may have contributed to the differences observed: (1) official estimates reflect the age composition recorded in 1999, 2 years before the survey took place, and (2) lower response rates occurred among 25- to 29-year-old women, who are most likely to be employed and not at home. The distribution of women in the sample by marital status (by 5-year age groups), however, does not differ significantly from the Census estimates.
Dates of Data Collection
Data Collection Mode
Data Collection Notes
The interviews were performed by 30 female interviewers, who were specially trained in interview techniques, survey procedures, and questionnaire content before the beginning of fieldwork.
Interviewer training was managed by the Adventist Development and Relief Agency Azerbaijan (ADRA), with the involvement of Shafag Rahimova, survey director; Conrad Vine, health coordinator; Farid Agamaliyev, project manager; Linda Fardy Hayes, survey consultant; and the U.S. Centers for Disease Control and Prevention (CDC) team (Florina Serbanescu and Natalia Melnikova for the reproductive health component and Geraldine Perry for the nutrition component). Interviewer training took place at the Ministry of Health International Training and Service Center just before data collection began; it consisted of 1 week of classroom training in fieldwork procedures and proper administration of the questionnaire and 1 week of practical training in the field with close monitoring by the trainers. At the end of the training period, six teams were selected, each consisting of four female interviewers, one nutritionist, and one supervisor. ADRA staff managed the fieldwork with technical assistance from the Division of Reproductive Health of the CDC.
Two fieldwork coordinators (Saida Ismaylova and Mahbuba Khalilova) supervised the fieldwork implementation. Fieldwork lasted from April through July 2001. Each team was assigned to visit a number of primary sampling units in all regions of the country and traveled by car throughout the country on planned itineraries. Interviews were conducted at the homes of respondents and lasted, on average, about 40 minutes (79 interviews are missing information about the duration of the interview). Although most interviews were conducted in Azeri, a Russian-language questionnaire was also available. All interviewers were bilingual. Completed questionnaires were first reviewed in the field by team supervisors and then were taken by the fieldwork coordinators to the national State Committee of Statistics (SCS) headquarters for data processing.
The questionnaire included information on each woman's education, employment, living arrangements, and other background characteristics as well as histories of marriage, divorce, cohabitation, sexual activity, pregnancy, and contraceptive use. Additional questions investigated health risk behaviors that may affect reproductive health (e.g., smoking and drinking habits), women's health screening practices, and intimate partner violence. The questionnaire was developed in English, translated into Azeri and Russian, and translated back to ensure accuracy and linguistic equivalency.
Estimates of Sampling Error
The estimates for a sample survey are affected by two types of errors: non-sampling error and sampling error. Non-sampling error is the result of mistakes made in carrying out data collection and data processing, including the failure to locate and interview the right household, errors in the way questions are asked or understood, and data entry errors. Although intensive quality control efforts were made during the implementation of the AZRHS01 to minimize this type of error, non-sampling errors are impossible to avoid altogether and difficult to evaluate statistically. Sampling error is a measure of the variability between an estimate and the true value of the population parameter intended to be estimated, which can be attributed to the fact that a sample rather than a complete enumeration was used to produce it. In other words, sampling error is the difference between the expected value for any variable measured in a survey and the value estimated by the survey. This sample is only one of the many probability samples that could have been selected from the female population aged 15-44 using the same sample design and projected sample size. Each of these samples would have yielded slightly different results from the actual sample selected.
Because the statistics presented here are based on a sample, they may differ by chance variations from the statistics that would result if all women 15-44 years of age in Azerbaijan would have been interviewed. Sampling error is usually measured in terms of the variance and standard error (square root of the variance) for a particular statistic (mean, proportion, or ratio). The standard error (SE) can be used to calculate confidence intervals (CI) of the estimates within which we can say with a given level of certainty that the true value of population parameter lies. For example, for any given statistic calculated from the survey sample, there is a 95 percent probability that the true value of that statistic will lie within a range of plus or minus two SE of the survey estimate.
The chances are about 68 out of 100 (about two out of three) that a sample estimate would fall within one standard error of a statistic based on a complete count of the population. The estimated sampling errors for 95% confidence intervals (1.96 x SE) for selected proportions and sample sizes are shown in Table A.1 of the Final Report. The estimates in Table A.1 can be used to estimate 95% confidence intervals for the estimated proportions shown for each sample size. The sampling error estimates include an average design effect of 1.6, needed because the AZRHS01 did not employ a simple random sample but included clusters of elements in the second stage of the sample selection.
The selection of clusters is generally characterized by some homogeneity that tends to increase the variance of the sample. Thus, the variance in the sample for the AZRHS01 is greater than a simple random sample would be due to the effect of clustering. The design effect represents the ratio of the two variance estimates: the variance of the complex design using clusters, divided by the variance of a simple random sample using the same sample size (Kish L, 1967). For more details regarding design effects for specific reproductive health variables, the reader is referred to the Le and Verma report, which studied demographic and health surveys in 48 countries (Le TN and Verma JK, 1997). The pattern of variation of design effects is shown to be consistent across countries and variables. Variation among surveys is high but less so among variables. Urban - rural and regional differentials in design effects are small, which can be attributed to the fact that similar sample designs and cluster sizes were used across domains within each country. At the country level, the overall design effect, averaged over all variables and countries, is about 1.5 (we used 1.6 in Table A. 1 to be slightly more conservative).
To obtain the 95% CI for proportions or sample sizes not shown in the table, one may interpolate. For example, for a sample size of 200 and a point estimate of 25% (midway between 0.20/0.80 and 0.30/0.70), the 95% CI would be plus or minus 7.5 percentage points; for a sample size of 300 (midway between 200 and 400) and an estimate of 20%, the 95% CI would be plus or minus 6.0 percentage points.
Differences between estimates discussed in this report were found to be statistically significant at the five percent level using a two-tailed normal deviate test (p=0.05). This means that in repeated samples of the same type and size, a difference as large as the one observed would occur in only 5% of samples if there were, in fact, no differences between the proportion in the population.
The relative standard error of a statistic (also called "coefficient of variation") is the ratio of the standard error (SE) for that statistic to the value of the statistic. It is usually expressed as a percent of the estimate. Estimates with a relative standard error of 30% or more are generally viewed as unreliable by themselves, but they may be combined with other estimates to make comparisons of greater precision. For example, an estimate of 20% based on a sample size of only 50 observations yields a SE of 7% (one half the 95% confidence interval shown in Table A.1). The relative standard error would be 35% (the ratio of the SE of 7% to the estimate of 20%), too large for the estimate to be reliable.