In the early 1990s, Georgia entered a long period of dramatic changes as it moved from a centralized, totalitarian government, characteristic of the U.S.S.R, to an autonomous administrative, economical, political, and socio-cultural system whose priorities are state capacity building, transition to a democratic society, and development of a market economy. Since its independence from the Soviet Union in April 1991, Georgia has gone through a conflict with secessionist regions in Abkhazia and South Ossetia and a civil war. During these challenging years, Georgia faced divisive ethnic disputes, economic hardships, and profound societal transformation, including rapid deterioration of the health care sector. The status of women's health in Georgia has suffered greatly during the last decade. The 1999 Reproductive Health Survey (99GERHS), the first population based national survey of this type ever conducted in Georgia, documented poor reproductive health indicators compared with other Eastern European and former Soviet Union countries.
The 99GERHS, conducted by the National Center for Disease Control, Tbilisi, with technical assistance from the Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta (DRH/CDC), interviewed a sample of 7,798 women 15-44 years of age, including an oversample of 1,655 internally displaced women living in government facilities. The oversample was applied for a programmatic reason—to evaluate the reproductive health status of the internally displaced women at the end of the reproductive health program implemented by UNHCR since 1994—and a methodologic reason— to ensure that the survey sample represent all women in Georgia, living either in residential dwellings or internally displaced housed in non-residential government facilities. The overall response rate was 99%. The survey was designed to collect information from a representative sample of reproductive-age women throughout Georgia. The questionnaire covered a wide range of topics related to reproductive health for all women regardless of marital status and included additional questions on family-life education and sexual behavior for women aged 15-24 years.
Almost two of three women (61%) with completed interviews were married or in a consensual union. One of two women had more than a secondary education. The majority population was Georgian (83%) followed by Azeri (9%), Armenian (5%) and Russian (1%) ethnic groups. Georgian was the main language spoken in 83% of households, followed by Azeri (8%), Armenian (4%) and Russian (3%). Although 94% of households had a television set, only 46% of respondents stated that they watch television daily, presumably because of the electricity shortage (7 hours per day, on average); similarly, only 30% of respondents stated that they listen to the radio daily. The average viewing and listening time among those who watch TV or listen to the radio daily was 4 and 3 hours, respectively. Only 16% and 6% of respondents reported seeing or hearing family planning messages on the television or radio, respectively.
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 a marital history, sexual experience, pregnancy history and contraceptive use. Additional questions investigated maternal and child health indicators, health risk behaviors which may affect reproductive health (including smoking and drinking habits), women's health screening practices, and intimate partner violence (IPV).
The survey was designed to collect information from a representative sample of women of reproductive age throughout Georgia, excluding South Ossetia and Abkhazia.
6,143 respondents were selected from the universe of all females between the ages of 15 and 44, regardless of marital status, who were living in households in Georgia (excluding South Ossetia and Abkhazia) when the survey was carried out.
Producers and sponsors
Georgian Center for Disease Control (NCDC)
Georgian Ministry of Labor
Health and Social Affairs
Center for Medical Statistics and Information
Division of Reproductive Health
United States Centers for Disease Control and Prevention
Technical assistance in survey design, sampling, questionnaire development, training, data processing, and report writing
United States Agency for International Development
United Nations Population Fund
United Nations Children's Fund
Results of the 99GERHS are based on in-person, face-to-face interviews with 7,798 women at their homes. The survey was designed to collect information from a representative sample of women of reproductive age throughout Georgia. Of the total, 6,143 respondents were selected from the universe of all females between the ages of 15 and 44, regardless of marital status, who were living in households in Georgia (excluding South Ossetia and Abkhazia) when the survey was carried out. In addition to the household sample, a separate sample of 1,655 internally displaced (IDP) women, who formerly resided in Abkhazia and South Ossetia and currently are living in state facilities, was performed in parallel with the household survey. This strata was added to provide a complete picture of reproductive health and women's needs in Georgia. Although about half of the IDPs in Georgia live in private dwellings (either alone or with relatives), an important segment continues to live in improvised households in communal centers (located in hotels, schools, kindergartens, farms, factories and other official buildings). Currently, it is estimated that over 100,000 IDPs are living in collective centers (UNHCR, 1999). The IDP sample of the 99GERHS was selected from the universe of IDP families living in government facilities (collective centers); these women would have otherwise been omitted from the survey, which used households in residential dwellings as the sample frame. The 1,655 women selected in the IDP sample were representative of all IDP women living in state facilities in Georgia and detailed information about their reproductive health status was published separately in the 99GERHS preliminary report (Serbanescu et al., 2000). In this final report, the IDP sample, with proper statistical weighting due to the fact that they were over-sampled, was combined with the household sample to allow the survey results to represent all women of reproductive age residing in Georgia, regardless of their housing arrangements.
Field work was conducted between November 7, 1999 and March 31, 2000. The desired sample was about 6,000 respondents for the household sample, including an oversample of women in the Imereti region, and 1,500 respondents for the IDP sample. Because the response rates were higher than expected, the actual sample size exceeds the projected sample size.
The household survey utilized a multistage sampling design using an updated sampling frame prepared by the State Department of Statistics (SDS) for the Multiple Indicator Cluster Survey conducted by UNICEF in collaboration with NCDC in July 1999. The MICS survey was designed to collect nationwide data (excluding Abkhazia and South Ossetia due to political instability) with subnational estimates. Twelve regions of the country were combined into seven survey regions and separate sampling was performed in each survey region. Grouping of regions was done taking into account the geographic location and similarity of socio-economic characteristics of the population. The SDS sampling frame contains all Georgian regions, districts, sectors, census enumeration units, census areas, and household addresses. The size of the smallest unit, the census area, contains 20-60 households; the following unit by size is the census enumeration unit incorporating 4-5 census areas with a size from 67 to 900 households; the sector is the combination of 3-5 census enumeration areas. All sectors are grouped in 53 raions (districts) that make up 12 regions (regrouped in seven regions for the MICS sampling frame). Some of the seven regions grouped for the UNICEF survey are small in size and do not always allow for independent estimates (e.g., Kakheti, Adjara). Thus, in this report the Kakheti region is part of the North-East region and Adjara is part of the West region.
The first stage of the three-stage sample design was a selection of census sectors with probability proportional to the number of households. This was accomplished by using a systematic sample with a random start in each strata; this first stage selection included 300 sectors as follows: Tbilisi (73), Imereti-Urban (28), Other-Urban (59), Imereti-Rural (27) and Other-Rural (113). In the second stage of sampling, clusters of households were randomly selected in each census sector chosen in the first stage. Cluster size determination was based on the number of households required to obtain an average of 20 completed interviews per cluster (38 households, on average). 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 the ages of 15 and 44 was selected at random for interview (if there was more than one woman in the household).
The 99GERHS sample includes two oversamples: a) a regional oversampling and b) an oversampling among the internally displaced population living in government facilities. Imereti region was oversampled for programmatic reasons. As in several other recent reproductive health surveys in eastern Europe conducted with CDC technical assistance (the 1996 and 1999 three-oblast surveys in Russia, the 1999 national survey in Romania and the 1999 national survey in Ukraine), the oversampling in Imereti region illustrates how surveys may be designed and integrated in the development, monitoring, and evaluation of new reproductive health programs. The oversampling of Imereti region was specifically designed to measure the impact of a region wide Women's Reproductive Health Project, a multi-faceted effort involving national and international cooperating agencies (USAID and American International Health Alliance). The project aims at reducing the reliance on induced abortion by increasing access and availability to effective contraceptive methods and promoting healthy behaviors among women, such as routine gynecologic exams, cervical and breast cancer screening. The project encompasses various interventions, such as the establishment of modern women's health clinics, training of health professionals, development of EEC messages, social marketing, and provision of high-quality contraceptive supplies and services.
The IDP oversample was also applied for programmatic reasons—to evaluate the reproductive health status of the IDP women at the end of the reproductive health program implemented by UNHCR since 1994. In addition, it was dictated by the fact that the SDS household sample did not include internally displaced households living in non-residential government facilities (collective centers). This sample also used a three-stage design. The first stage constituted of a selection of 74 collective centers throughout Georgia, proportional to the number of IDPs living in all collective centers. Most centers were located in Samegrelo, Zemo Svaneti, and Guria regions (23), Tbilisi (20), and Imereti region (19). Because information on unoccupied IDP households and the average number of women aged 15-44 per IDP household were not available, cluster size was inferred from the household sample in urban areas, since most IDP collective centers were in urban areas. Similar to the household sample, in each of the DP households selected, only one woman between the ages of 15 and 44 was selected at random for interview. The IDP sample was labeled as the sixth strata of the 99GERHS. In the preliminary report, data for the IDP women were presented separately for programmatic reasons. In the final report, however, data for all reproductive-age women in Georgia are presented as a whole and the IDP status is identified in most stratified analyses.
Of the 14,495 households selected in the sample, 55% included at least one eligible woman (aged 15 to 44 years). Households selected in the sample in urban areas were slightly more likely to refuse an interview than in rural areas, but the refusal rates were less than one percent. In the 7,896 households with at least one eligible woman, 7,798 women were successfully interviewed (only one respondent was randomly selected per household), yielding a response rate of 98.8%. Virtually all respondents who were selected to participate and who could be reached agreed to be interviewed and were very cooperative. Response rates were not significantly different by region, ranging from 98.3% in Tbilisi to 99.1% in Imereti and the North-Eastern regions
(including Kakheti, Shida Kartli, Mtskheta-Mtianeti and Racha Lechkhumi). The geographic distribution of the sample by region is very close to the official figures of the latest regional population estimates projected by the SDS. Compared to the cohort projections from the 1989 Census, the regional distribution of women in the sample (once adjusted for interviewing only one respondent per household and the over-sampling of the IDP women and Imereti region) closely resembles the official estimate of the population distribution.
Only Guria and Samegrelo appear to be slightly over-represented, presumably because they received a more active influx of IDPs from the neighboring region of Abkhazia. Since sample size does not permit individual regional estimates (with the exception of Tbilisi, where 26% of the Georgian population resides, and Imereti, which is oversampled to allow independent estimates), all other regions are grouped geographically. The geographical grouping allows for broad regional analyses but do not imply any cultural grouping. Thus, throughout the report, the North-East region includes Kakheti, Shida Kartli, Mtskheta-Mtianeti and Racha Lechkhumi, the South region includes Kvemo. Kartli and Samtskhe-Javakheti, and the West region includes Adjara, Guria, Samegrelo and Zemo Svaneti.
The percent distribution of women in the sample by five-year age groups is slightly different than the official estimates for the year 2000: the survey sample has slightly over-represented adolescent women (15-19 year-olds) and under-represented women aged 40-44 by two and one percentage point, respectively, once confidence intervals are taken into account. At least two factors may have contributed to the differences observed: 1) official estimates are projections of the age composition recorded by the 1989 census and thus dependent on assumptions used in projecting the aging of a cohort; and 2) official estimates cannot rigorously account for the ethnic displacement and migration triggered by the 1991-1993 armed conflicts.
The weights used for the final report include a component to adjust for oversampling of households in the Imereti region (urban and rural) and the oversampling of women in the IDP strata; another component of the final weight compensates for the fact that some households included more than one eligible respondent.
The survey can be used to make national estimates because of the elaborate and careful process used to "weight" the data—that is, to determine how many women in the population were represented by each woman in the sample.
Dates of Data Collection
Data Collection Mode
Data Collection Notes
The interviews were performed by 30 female interviewers, mostly physicians, specially trained in interview techniques, questionnaire content, and survey procedures prior to the beginning of field work. Fieldwork was managed by staff of the NCDC and MOH. Interviewer training was managed by the NCDC and MOH and the CDC team. Interviewer training took place at the NCDC headquarters just before data collection began and consisted of one week of classroom training in fieldwork procedures and proper administration of the questionnaire and one week of practical training in the field with close monitoring by the trainers. At the end of the training period, six female teams were selected, each consisting of four interviewers and one supervisor. The overall fieldwork implementation was supervised by two fieldwork coordinators.
Fieldwork lasted from November 1999 through March 2000. Each team was assigned to visit a number of primary sampling units in all regions of the country. Interviews were conducted at the homes of respondents and lasted, on average, about 40 minutes (excludes 95 interviews with missing information on duration of the interview). Although most interviews were conducted in Georgian, a Russian language questionnaire was also available. All interviewers were bi-lingual. Azeri speakers assisted teams in some PSUs. Completed questionnaires were first reviewed in the field by team supervisors and then were taken by the fieldwork coordinators to the MOH National Center for Medical Statistics and Information (CMSI) headquarters for data processing.
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 1999/2000 GERHS 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 Georgia 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 99GERHS 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 99GERHS 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%; 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%.
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.
In this text, terms such as "greater," "less," "increase," or "decrease" indicate that the observed differences were statistically significant at the 0.05 level using a two-tailed deviate test. Statements using the phrase "the data suggest" indicate that the difference was significant at the 0.10 level but not the 0.05 level. Lack of comment in the text about any two statistics does not mean that the difference was tested and not found to be significant.
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.
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.