Identification
IDNO
UGA_1995_DHS_v01_M
Title
Demographic and Health Survey 1995
Country
| Name | Country code |
|---|---|
| Uganda | UGA |
Abstract
The 1995 Uganda Demographic and Health Survey (UDHS-II) is a nationally-representative survey of 7,070 women age 15-49 and 1,996 men age 15-54. The UDHS was designed to provide information on levels and trends of fertility, family planning knowledge and use, infant and child mortality, and maternal and child health. Fieldwork for the UDHS took place from late-March to mid-August 1995. The survey was similar in scope and design to the 1988-89 UDHS. Survey data show that fertility levels may be declining, contraceptive use is increasing, and childhood mortality is declining; however, data also point to several remaining areas of challenge.
The 1995 UDHS was a follow-up to a similar survey conducted in 1988-89. In addition to including most of the same questions included in the 1988-89 UDHS, the 1995 UDHS added more detailed questions on AIDS and maternal mortality, as well as incorporating a survey of men. The general objectives of the
1995 UDHS are to:
- provide national level data which will allow the calculation of demographic rates, particularly fertility and childhood mortality rates;
- analyse the direct and indirect factors which determine the level and trends of fertility;
- measure the level of contraceptive knowledge and practice (of both women and men) by method, by urban-rural residence, and by region;
- collect reliable data on maternal and child health indicators; immunisation, prevalence, and treatment of diarrhoea and other diseases among children under age four; antenatal visits; assistance at delivery; and breastfeeding;
- assess the nutritional status of children under age four and their mothers by means of anthropometric measurements (weight and height), and also child feeding practices; and
- assess among women and men the prevailing level of specific knowledge and attitudes regarding AIDS and to evaluate patterns of recent behaviour regarding condom use.
MAIN RESULTS
- Fertility:
Fertility Trends. UDHS data indicate that fertility in Uganda may be starting to decline. The total fertility rate has declined from the level of 7.1 births per woman that prevailed over the last 2 decades to 6.9 births for the period 1992-94. The crude birth rate for the period 1992-94 was 48 live births per I000 population, slightly lower than the level of 52 observed from the 1991 Population and Housing Census. For the roughly 80 percent of the country that was covered in the 1988-89 UDHS, fertility has declined from 7.3 to 6.8 births per woman, a drop of 7 percent over a six and a half year period.
Birth Intervals. The majority of Ugandan children (72 percent) are born after a "safe" birth interval (24 or more months apart), with 30 percent born at least 36 months after a prior birth. Nevertheless, 28 percent of non-first births occur less than 24 months after the preceding birth, with 10 percent occurring less than 18 months since the previous birth. The overall median birth interval is 29 months.
Fertility Preferences. Survey data indicate that there is a strong desire for children and a preference for large families in Ugandan society. Among those with six or more children, 18 percent of married women want to have more children compared to 48 percent of married men. Both men and women desire large families.
- Family planning:
Knowledge of Contraceptive Methods. Knowledge of contraceptive methods is nearly universal with 92 percent of all women age 15-49 and 96 percent of all men age 15-54 knowing at least one method of family planning. Increasing Use of Contraception. The contraceptive prevalence rate in Uganda has tripled over a six-year period, rising from about 5 percent in approximately 80 percent of the country surveyed in 1988-89 to 15 percent in 1995.
Source of Contraception. Half of current users (47 percent) obtain their methods from public sources, while 42 percent use non-governmental medical sources, and other private sources account for the remaining 11 percent.
- Maternal and child health:
High Childhood Mortality. Although childhood mortality in Uganda is still quite high in absolute terms, there is evidence of a significant decline in recent years. Currently, the direct estimate of the infant mortality rate is 81 deaths per 1,000 births and under five mortality is 147 per 1,000 births, a considerable decline from the rates of 101 and 180, respectively, that were derived for the roughly 80 percent of the country that was covered by the 1988-89 UDHS.
Childhood Vaccination Coverage. One possible reason for the declining mortality is improvement in childhood vaccination coverage. The UDHS results show that 47 percent of children age 12-23 months are fully vaccinated, and only 14 percent have not received any vaccinations.
Childhood Nutritional Status. Overall, 38 percent of Ugandan children under age four are classified as stunted (low height-for-age) and 15 percent as severely stunted. About 5 percent of children under four in Uganda are wasted (low weight-for-height); 1 percent are severely wasted. Comparison with other data sources shows little change in these measures over time.
- AIDS:
Virtually all women and men in Uganda are aware of AIDS. About 60 percent of respondents say that limiting the number of sexual partners or having only one partner can prevent the spread of disease. However, knowledge of ways to avoid AIDS is related to respondents' education. Safe patterns of sexual behaviour are less commonly reported by respondents who have little or no education than those with more education. Results show that 65 percent of women and 84 percent of men believe that they have little or no chance of being infected.
Availability of Health Services. Roughly half of women in Uganda live within 5 km of a facility providing antenatal care, delivery care, and immunisation services. However, the data show that children whose mothers receive both antenatal and delivery care are more likely to live within 5 km of a facility providing maternal and child health (MCH) services (70 percent) than either those whose mothers received only one of these services (46 percent) or those whose mothers received neither antenatal nor delivery care (39 percent).
The 1995 UDHS was a follow-up to a similar survey conducted in 1988-89. In addition to including most of the same questions included in the 1988-89 UDHS, the 1995 UDHS added more detailed questions on AIDS and maternal mortality, as well as incorporating a survey of men. The general objectives of the
1995 UDHS are to:
- provide national level data which will allow the calculation of demographic rates, particularly fertility and childhood mortality rates;
- analyse the direct and indirect factors which determine the level and trends of fertility;
- measure the level of contraceptive knowledge and practice (of both women and men) by method, by urban-rural residence, and by region;
- collect reliable data on maternal and child health indicators; immunisation, prevalence, and treatment of diarrhoea and other diseases among children under age four; antenatal visits; assistance at delivery; and breastfeeding;
- assess the nutritional status of children under age four and their mothers by means of anthropometric measurements (weight and height), and also child feeding practices; and
- assess among women and men the prevailing level of specific knowledge and attitudes regarding AIDS and to evaluate patterns of recent behaviour regarding condom use.
MAIN RESULTS
- Fertility:
Fertility Trends. UDHS data indicate that fertility in Uganda may be starting to decline. The total fertility rate has declined from the level of 7.1 births per woman that prevailed over the last 2 decades to 6.9 births for the period 1992-94. The crude birth rate for the period 1992-94 was 48 live births per I000 population, slightly lower than the level of 52 observed from the 1991 Population and Housing Census. For the roughly 80 percent of the country that was covered in the 1988-89 UDHS, fertility has declined from 7.3 to 6.8 births per woman, a drop of 7 percent over a six and a half year period.
Birth Intervals. The majority of Ugandan children (72 percent) are born after a "safe" birth interval (24 or more months apart), with 30 percent born at least 36 months after a prior birth. Nevertheless, 28 percent of non-first births occur less than 24 months after the preceding birth, with 10 percent occurring less than 18 months since the previous birth. The overall median birth interval is 29 months.
Fertility Preferences. Survey data indicate that there is a strong desire for children and a preference for large families in Ugandan society. Among those with six or more children, 18 percent of married women want to have more children compared to 48 percent of married men. Both men and women desire large families.
- Family planning:
Knowledge of Contraceptive Methods. Knowledge of contraceptive methods is nearly universal with 92 percent of all women age 15-49 and 96 percent of all men age 15-54 knowing at least one method of family planning. Increasing Use of Contraception. The contraceptive prevalence rate in Uganda has tripled over a six-year period, rising from about 5 percent in approximately 80 percent of the country surveyed in 1988-89 to 15 percent in 1995.
Source of Contraception. Half of current users (47 percent) obtain their methods from public sources, while 42 percent use non-governmental medical sources, and other private sources account for the remaining 11 percent.
- Maternal and child health:
High Childhood Mortality. Although childhood mortality in Uganda is still quite high in absolute terms, there is evidence of a significant decline in recent years. Currently, the direct estimate of the infant mortality rate is 81 deaths per 1,000 births and under five mortality is 147 per 1,000 births, a considerable decline from the rates of 101 and 180, respectively, that were derived for the roughly 80 percent of the country that was covered by the 1988-89 UDHS.
Childhood Vaccination Coverage. One possible reason for the declining mortality is improvement in childhood vaccination coverage. The UDHS results show that 47 percent of children age 12-23 months are fully vaccinated, and only 14 percent have not received any vaccinations.
Childhood Nutritional Status. Overall, 38 percent of Ugandan children under age four are classified as stunted (low height-for-age) and 15 percent as severely stunted. About 5 percent of children under four in Uganda are wasted (low weight-for-height); 1 percent are severely wasted. Comparison with other data sources shows little change in these measures over time.
- AIDS:
Virtually all women and men in Uganda are aware of AIDS. About 60 percent of respondents say that limiting the number of sexual partners or having only one partner can prevent the spread of disease. However, knowledge of ways to avoid AIDS is related to respondents' education. Safe patterns of sexual behaviour are less commonly reported by respondents who have little or no education than those with more education. Results show that 65 percent of women and 84 percent of men believe that they have little or no chance of being infected.
Availability of Health Services. Roughly half of women in Uganda live within 5 km of a facility providing antenatal care, delivery care, and immunisation services. However, the data show that children whose mothers receive both antenatal and delivery care are more likely to live within 5 km of a facility providing maternal and child health (MCH) services (70 percent) than either those whose mothers received only one of these services (46 percent) or those whose mothers received neither antenatal nor delivery care (39 percent).
Kind of Data
Sample survey data
Coverage
Geographic Coverage
The 1995 Uganda Demographic and Health Survey (UDHS-II) is a nationally-representative survey. For the purpose of the 1995 UDHS, the following domains were utilised: Uganda as a whole; urban and rural areas separately; each of the four regions: Central, Eastern, Northern, and Western; areas in the USAID-funded DISH project to permit calculation of contraceptive prevalence rates.
Unit of Analysis
- Household
- Women age 15-49
- Men age 15-54
- Children under four
- Women age 15-49
- Men age 15-54
- Children under four
Universe
The population covered by the 1995 UDHS is defined as the universe of all women age 15-49 in Uganda. But because of insecurity, eight EAs could not be surveyed (six in Kitgum District, one in Apac District, and one in Moyo District). An additional two EAs (one in Arua and one in Moroto) could not be surveyed, but substitute EAs were selected in their place.
Producers and sponsors
Authoring entity/Primary investigators
| Agency Name | Affiliation |
|---|---|
| Department of Statistics | Ministry of Finance & Economic Planning |
Producers
| Name | Role |
|---|---|
| Macro International Inc | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| U.S. Agency for International Development | USAID | Funding |
| Government of Uganda | Funding |
Other Identifications/Acknowledgments
| Name | Role |
|---|---|
| Population Secretariat | Collaboration |
| Ministry of Health | Collaboration |
Sampling
Sampling Procedure
A sample of 303 primary sampling units (PSU) consisting of enumeration areas (EAs) was selected from a sampling frame of the 1991 Population and Housing Census. For the purpose of the 1995 UDHS, the following domains were utilised: Uganda as a whole; urban and rural areas separately; each of the four regions: Central, Eastern, Northern, and Western; areas in the USAID-funded DISH project to permit calculation of contraceptive prevalence rates.
Districts in the DISH project area were grouped by proximity into the following five reporting domains:
- Kasese and Mbarara Districts
- Masaka and Rakai Districts
- Luwero and Masindi Districts
- Jinja and Kamuli Districts
- Kampala District
The sample for the 1995 UDHS was selected in two stages. In the first stage, 303 EAs were selected with probability proportional to size. Then, within each selected EA, a complete household listing and mapping exercise was conducted in December 1994 forming the basis for the second-stage sampling. For the listing exercise, 11 listers from the Statistics Department were trained. Institutional populations (army barracks, hospitals, police camps, etc.) were not listed.
From these household lists, households to be included in the UDHS were selected with probability inversely proportional to size based on the household listing results. All women age 15-49 years in these households were eligible to be interviewed in the UDHS. In one-third of these selected households, all men age 15-54 years were eligible for individual interview as well. The overall target sample was 6,000 women and 2,000 men. Because of insecurity, eight EAs could not be surveyed (six in Kitgum District, one in Apac District, and one in Moyo District). An additional two EAs (one in Arua and one in Moroto) could not be surveyed, but substitute EAs were selected in their place.
Since one objective of the survey was to produce estimates of specific demographic and health indicators for the areas included in the DISH project, the sample design allowed for oversampling of households in these districts relative to their actual proportion in the population. Thus, the 1995 UDHS sample is not self-weighting at the national level; weights are required to estimate national-level indicators. Due to the weighting factor and rounding of estimates, figures may not add to totals. In addition, the percent total may not add to 100.0 due to rounding.
Districts in the DISH project area were grouped by proximity into the following five reporting domains:
- Kasese and Mbarara Districts
- Masaka and Rakai Districts
- Luwero and Masindi Districts
- Jinja and Kamuli Districts
- Kampala District
The sample for the 1995 UDHS was selected in two stages. In the first stage, 303 EAs were selected with probability proportional to size. Then, within each selected EA, a complete household listing and mapping exercise was conducted in December 1994 forming the basis for the second-stage sampling. For the listing exercise, 11 listers from the Statistics Department were trained. Institutional populations (army barracks, hospitals, police camps, etc.) were not listed.
From these household lists, households to be included in the UDHS were selected with probability inversely proportional to size based on the household listing results. All women age 15-49 years in these households were eligible to be interviewed in the UDHS. In one-third of these selected households, all men age 15-54 years were eligible for individual interview as well. The overall target sample was 6,000 women and 2,000 men. Because of insecurity, eight EAs could not be surveyed (six in Kitgum District, one in Apac District, and one in Moyo District). An additional two EAs (one in Arua and one in Moroto) could not be surveyed, but substitute EAs were selected in their place.
Since one objective of the survey was to produce estimates of specific demographic and health indicators for the areas included in the DISH project, the sample design allowed for oversampling of households in these districts relative to their actual proportion in the population. Thus, the 1995 UDHS sample is not self-weighting at the national level; weights are required to estimate national-level indicators. Due to the weighting factor and rounding of estimates, figures may not add to totals. In addition, the percent total may not add to 100.0 due to rounding.
Response Rate
Out of 8,093 households selected, 7,671were occupied, the shortfall being a result mostly of vacant houses. Of the existing households, 7,550 were interviewed, for a response rate of 98 percent. The main reason for non-response was the interviewer's failure to find a respondent at home after at least three visits.
In the interviewed households, 7,377 eligible women were identified and of these, 7,070 were interviewed, yielding a response rate of 96 percent. In the subsample of households selected for the man's interview, 2,224 eligible men were identified, of which 1,996 were successfully interviewed (90 percent response). The principal reason for non-response among both eligible men and visits to the household. The lower response rate among men than women was due to the more frequent and longer absences of men.
The response rates are lower in urban areas due to long absence of respondents. One-member households are more common in urban areas and are more difficult to interview as they keep their houses locked up most of the time. In urban settings, neighbours often do not know the whereabouts of such people.
In the interviewed households, 7,377 eligible women were identified and of these, 7,070 were interviewed, yielding a response rate of 96 percent. In the subsample of households selected for the man's interview, 2,224 eligible men were identified, of which 1,996 were successfully interviewed (90 percent response). The principal reason for non-response among both eligible men and visits to the household. The lower response rate among men than women was due to the more frequent and longer absences of men.
The response rates are lower in urban areas due to long absence of respondents. One-member households are more common in urban areas and are more difficult to interview as they keep their houses locked up most of the time. In urban settings, neighbours often do not know the whereabouts of such people.
Data Collection
Dates of Data Collection (YYYY/MM/DD)
| Start date | End date |
|---|---|
| 1995-03 | 1995-08 |
Mode of data collection
Face-to-face
Supervision
Supervisors and editors were trained exclusively for three days to discuss their duties and responsibilities. Emphasis was given to the importance of ensuring data quality.
Type of Research Instrument
Four questionnaires were used in the 1995 UDHS.
a) A Household Schedule was used to list the names and certain individual characteristics of all usual members of the household and visitors who had spent the previous night in the household. Some basic information was collected on characteristics of each person listed, including his/her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. In addition, the Household Questionnaire collected information on characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, and ownership of various consumer and durable goods.
b) The Women's Questionnaire was used to collect information from women age 15-49. These women were asked questions on the following topics:
- Background characteristics (education, residential history, etc.)
- Reproductive history
- Knowledge and use of family planning methods
- Fertility preferences
- Antenatal and delivery care
- Breastfeeding and weaning practices
- Vaccinations and health status of children under age four
- Marriage and sexual activity Husband's occupation and education
- Woman's employment, occupation, and earnings
- Awareness and behaviour regarding
- AIDS and other sexually transmitted diseases
- Adult mortality including maternal mortality
- Height and weight of children under age four and their mothers.
c) The Men' s Questionnaire was used to collect information from a subsample of men age 15-54 (those living in every third household). The Men's Questionnaire collected much of the same information found in the Women's Questionnaire, but was shorter because it did not contain questions on reproductive history and maternal and child health.
d) The Service Availability Questionnaire was used to collect community level information on the health and family planning services near each selected LC 1 (see section 1.1 for explanation). An enumeration area sometimes consists of more than one LC1. In such cases, one questionnaire was completed for each of the LC I s within the selected enumeration area.
The questionnaires were developed in English by a Steering Committee which was chaired by the Population Secretariat. All except the Service Availability Questionnaire were translated into and printed in six major languages (Ateso, Luganda, Lugbara, Luo, Runyankole/Rukiga, and Runyoro/Rutoro).
a) A Household Schedule was used to list the names and certain individual characteristics of all usual members of the household and visitors who had spent the previous night in the household. Some basic information was collected on characteristics of each person listed, including his/her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. In addition, the Household Questionnaire collected information on characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, and ownership of various consumer and durable goods.
b) The Women's Questionnaire was used to collect information from women age 15-49. These women were asked questions on the following topics:
- Background characteristics (education, residential history, etc.)
- Reproductive history
- Knowledge and use of family planning methods
- Fertility preferences
- Antenatal and delivery care
- Breastfeeding and weaning practices
- Vaccinations and health status of children under age four
- Marriage and sexual activity Husband's occupation and education
- Woman's employment, occupation, and earnings
- Awareness and behaviour regarding
- AIDS and other sexually transmitted diseases
- Adult mortality including maternal mortality
- Height and weight of children under age four and their mothers.
c) The Men' s Questionnaire was used to collect information from a subsample of men age 15-54 (those living in every third household). The Men's Questionnaire collected much of the same information found in the Women's Questionnaire, but was shorter because it did not contain questions on reproductive history and maternal and child health.
d) The Service Availability Questionnaire was used to collect community level information on the health and family planning services near each selected LC 1 (see section 1.1 for explanation). An enumeration area sometimes consists of more than one LC1. In such cases, one questionnaire was completed for each of the LC I s within the selected enumeration area.
The questionnaires were developed in English by a Steering Committee which was chaired by the Population Secretariat. All except the Service Availability Questionnaire were translated into and printed in six major languages (Ateso, Luganda, Lugbara, Luo, Runyankole/Rukiga, and Runyoro/Rutoro).
Data Collectors
| Name |
|---|
| Statistics Department of the Ministry of Finance and Economic Planning |
Data Processing
Cleaning Operations
All the questionnaires for the UDHS were returned to the Statistics Department for data processing, which consisted of office editing, coding of open-ended questions, data entry, and editing of computer- identified errors. All data were processed on microcomputers. Data entry and editing were accomplished using the computer program ISSA (Integrated System for Survey Analysis) that was specially designed for the DHS programme. Data processing was performed during April-October 1995.
Data Appraisal
Estimates of Sampling Error
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the UDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between 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 standarderrorfor 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 UDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the UDHS is the ISSA Sampling Error Module (ISSAS). This module used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jacknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
The Jacknife repeated replication method derives estimates of complex rates from each of several replications of the parent sample, and calculates standard errors for these estimates using simple formulae. Each replication considers all but one clusters in the calculation of the estimates. Pseudo-independent replications are thus created. In the UDHS, there were 295 non-empty clusters. Hence, 295 replications were created.
In addition to the standard error, ISSAS computes the design effect (DEFT) for each estimate, which is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value greater than 1.0 indicates the increase in the sampling error due to the use of a more complex and less statistically efficient design. ISSAS also computes the relative error and confidence limits for the estimates.
Sampling errors for the UDHS are calculated for selected variables considered to be of primary interest. The results are presented in an appendix to the Final Report for the country as a whole, for urban and rural areas, and for each of the four regions: Central, Eastern, Northern, and Western. For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table B.1 of the Final Report. Tables B.2 to B.8 present the value of the statistic (R), its standard error (SE), the number of unweighted (N) and weighted (WN) cases, the design effect (DEFT), the relative standard error (SE/R), and the 95 percent confidence limits (R±2SE), for each variable. The DEFT is considered undefined when the standard error considering simple ramdom sample is zero (when the estimate is close to 0 or I ).
In general, the relative standard error for most estimates for the country as a whole is small, except for estimates of very small proportions. There are some differentials in the relative standard error for the estimates of sub-populations. For example, for the variable contraceptive use for currently married women age 15-49, the relative standard errors as a percent of the estimated mean for the whole country, for urban areas, and for rural areas are 5.2 percent, 5.0 percent, and 6.2 percent, respectively.
The confidence interval (e.g., as calculated for contraceptive use for currently married women age 15-49) can be interpreted as follows: the overall national sample proportion is 0.148 and its standard error is .008. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e. 0.148--_2(.008). There is a high probability (95 percent) that the true average proportion of contraceptive use for currently married women age 15 to 49 is between 0.132 and 0.164.
A sampling error is usually measured in terms of the standarderrorfor 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 UDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the UDHS is the ISSA Sampling Error Module (ISSAS). This module used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jacknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
The Jacknife repeated replication method derives estimates of complex rates from each of several replications of the parent sample, and calculates standard errors for these estimates using simple formulae. Each replication considers all but one clusters in the calculation of the estimates. Pseudo-independent replications are thus created. In the UDHS, there were 295 non-empty clusters. Hence, 295 replications were created.
In addition to the standard error, ISSAS computes the design effect (DEFT) for each estimate, which is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value greater than 1.0 indicates the increase in the sampling error due to the use of a more complex and less statistically efficient design. ISSAS also computes the relative error and confidence limits for the estimates.
Sampling errors for the UDHS are calculated for selected variables considered to be of primary interest. The results are presented in an appendix to the Final Report for the country as a whole, for urban and rural areas, and for each of the four regions: Central, Eastern, Northern, and Western. For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table B.1 of the Final Report. Tables B.2 to B.8 present the value of the statistic (R), its standard error (SE), the number of unweighted (N) and weighted (WN) cases, the design effect (DEFT), the relative standard error (SE/R), and the 95 percent confidence limits (R±2SE), for each variable. The DEFT is considered undefined when the standard error considering simple ramdom sample is zero (when the estimate is close to 0 or I ).
In general, the relative standard error for most estimates for the country as a whole is small, except for estimates of very small proportions. There are some differentials in the relative standard error for the estimates of sub-populations. For example, for the variable contraceptive use for currently married women age 15-49, the relative standard errors as a percent of the estimated mean for the whole country, for urban areas, and for rural areas are 5.2 percent, 5.0 percent, and 6.2 percent, respectively.
The confidence interval (e.g., as calculated for contraceptive use for currently married women age 15-49) can be interpreted as follows: the overall national sample proportion is 0.148 and its standard error is .008. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e. 0.148--_2(.008). There is a high probability (95 percent) that the true average proportion of contraceptive use for currently married women age 15 to 49 is between 0.132 and 0.164.
Data Appraisal
Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of 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 UDHS to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Data access
Contact
| Name | Affiliation | URI | |
|---|---|---|---|
| MEASURE DHS | ICF International | archive@measuredhs.com | www.measuredhs.com |
Citation requirement
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Disclaimer and copyrights
Disclaimer
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.
Contacts
Contact
| Name | URI | |
|---|---|---|
| General Inquiries | info@measuredhs.com | www.measuredhs.com |
| Data and Data Related Resources | archive@measuredhs.com | www.measuredhs.com |
Metadata production
Document ID
DDI_UGA_1995_DHS_v01_M
Producers
| Name | Abbreviation | Role |
|---|---|---|
| World Bank, Development Economics Data Group | DECDG | Generation of DDI documentation |
Date of Production
2012-04-05