Demographic and Health Survey 2019-2020 - Gambia

Abstract
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The 2019-20 Gambia Demographic and Health Survey (2019-20 GDHS) is a nationwide survey with a nationally representative sample of residential households. The survey was implemented by The Gambia Bureau of Statistics (GBoS) in collaboration with the Ministry of Health (MoH).

The primary objective of the 2019-20 GDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2019-20 GDHS:
▪ collected data on fertility levels and preferences; contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; maternal mortality; gender; nutrition; awareness about HIV/AIDS; self-reported sexually transmitted infections (STIs); and other health issues relevant to the achievement of the Sustainable Development Goals (SDGs)
▪ obtained information on the availability of, access to, and use of mosquito nets as part of the National Malaria Control Programme
▪ gathered information on other health issues such as injections, tobacco use, hypertension, diabetes, and health insurance
▪ collected data on women’s empowerment, domestic violence, fistula, and female genital mutilation/cutting
▪ tested household salt for the presence of iodine
▪ obtained data on child feeding practices, including breastfeeding, and conducted anthropometric measurements to assess the nutritional status of children under age 5 and women age 15-49
▪ conducted anaemia testing of women age 15-49 and children age 6-59 months
▪ conducted malaria testing of children age 6-59 months

Geographic coverage
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National coverage

Analysis unit
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- Household
- Individual
- Children age 0-5
- Woman age 15-49
- Man age 15 to 59

Universe
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The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-59, and all children aged 0-5 resident in the household.

Kind of data
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Sample survey data [ssd]

Sampling procedure
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The sampling frame used for the 2019-20 GDHS was based on an updated version of the 2013 Gambia Population and Housing Census (2013 GPHC) conducted by GBoS. The census counts were updated in 2015-16 based on district-level projected counts from the 2015-16 Integrated Household Survey (IHS). Administratively, The Gambia is divided into eight Local Government Areas (LGAs). Each LGA is subdivided into districts and each district is subdivided into settlements. A settlement, a group of small settlements, or a part of a large settlement can form an enumeration area (EA). These units allow the country to be easily separated into small geographical area units, each with an urban or rural designation. There are 48 districts, 120 wards, and 4,098 EAs in The Gambia; the EAs have an average size of 68 households.

The sample for the 2019-20 GDHS was a stratified sample selected in two stages. In the first stage, EAs were selected with a probability proportional to their size within each sampling stratum. A total of 281 EAs were selected.

In the second stage, the households were systematically sampled. A household listing operation was undertaken in all of the selected clusters. The resulting lists of households served as the sampling frame from which a fixed number of 25 households were systematically selected per cluster, resulting in a total sample size of 7,025 selected households. Results from this sample are representative at the national, urban, and rural levels and at the LGA levels.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection
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Computer Assisted Personal Interview [capi]

Research instrument
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Five questionnaires were used for the 2019-20 GDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. These questionnaires, based on The DHS Program’s standard questionnaires, were adapted to reflect the population and health issues relevant to The Gambia. Suggestions were solicited from various stakeholders representing government ministries, departments, and agencies; nongovernmental organisations; and international donors. All questionnaires were written in English, and interviewers translated the questions into the appropriate local language to carry out the interview.

Cleaning operations
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All electronic data files were transferred via the Internet File Streaming System (IFSS) to the GBoS central office. The IFSS automatically encrypts the data and sends the data to a server, and the server in turn downloads the data to the data processing supervisor’s password-protected computer in the central office. The data processing operation included secondary editing, which required resolution of computeridentified inconsistencies and coding of open-ended questions. The data were processed by two IT specialists and three secondary editors who took part in the main fieldwork training; they were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing and data processing were initiated in November 2019 and completed in May 2020.

Response rate
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All 6,985 households in the selected housing units were eligible for the survey, of which 6,736 were occupied. Of the occupied households, 6,549 were successfully interviewed, yielding a response rate of 97%. Among the households successfully interviewed, 1,948 interviews were completed in 2019 and 4,601 in 2020.

In the interviewed households, 12,481 women age 15-49 were identified for individual interviews; interviews were completed with 11,865 women, yielding a response rate of 95%, a 4 percentage point increase from the 2013 GDHS. Among men, 5,337 were eligible for individual interviews, and 4,636 completed an interview; this yielded a response rate of 87%, a 5 percentage point increase from the previous survey.

Sampling error estimates
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The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. 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 2019-20 Gambia Demographic and Health Survey (GDHS) to minimise 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 2019-20 GDHS 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 among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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% 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 2019-20 GDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal
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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 years
- Reporting of age at death in days
- Reporting of age at death in months
- Standardisation exercise results from anthropometry training
- Height and weight data completeness and quality for children
- Height measurements from random subsample of measured children
- Number of enumeration areas completed by month, according to Local Government Area, The Gambia DHS 2019-20
- Percentage of children age 6-59 months classified as having malaria according to RDT, by month and Local Government Area, The Gambia DHS 2019-20
- Completeness of information on siblings
- Sibship size and sex ratio of siblings

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

摘要
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2019-20 冈比亚人口与健康调查（2019-20 GDHS）是一项全国性调查，样本选取了具有全国代表性的居住户家庭。该调查由冈比亚统计局（GBoS）与卫生部（MoH）合作实施。

2019-20 GDHS 的主要目标是提供最新的人口与健康基本指标估计值。具体而言，2019-20 GDHS：
▪ 收集了生育水平与偏好、避孕使用、孕产妇及儿童健康、婴儿、儿童和新生儿死亡率水平、孕产妇死亡率、性别、营养、对艾滋病/艾滋病病毒的了解、自我报告的性传播感染（STI）以及其他与健康可持续发展目标（SDGs）实现相关的健康问题数据；
▪ 获取了关于国家疟疾控制计划中蚊帐的可用性、获取和使用情况的信息；
▪ 收集了关于其他健康问题，如注射、烟草使用、高血压、糖尿病和健康保险的信息；
▪ 收集了关于女性赋权、家庭暴力、产钳和女性生殖器切割/割礼的数据；
▪ 对家庭食盐进行了碘含量检测；
▪ 收集了关于儿童喂养实践，包括母乳喂养，的数据，并对 5 岁以下儿童和 15-49 岁妇女的营养状况进行了人体测量学评估；
▪ 对 15-49 岁妇女和 6-59 个月大的儿童进行了贫血测试；
▪ 对 6-59 个月大的儿童进行了疟疾测试。

地理覆盖范围
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全国覆盖

分析单元
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- 家庭
- 个人
- 0-5 岁儿童
- 15-49 岁妇女
- 15 至 59 岁男性

总体
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调查涵盖了所有法定家庭成员（常住居民）、所有 15-49 岁妇女、所有 15-59 岁男性以及所有居住在户内的 0-5 岁儿童。

数据类型
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样本调查数据 [ssd]

抽样程序
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2019-20 GDHS 的抽样框架基于 GBoS 执行的 2013 年冈比亚人口与住房普查（2013 GPHC）的更新版本。2015-16 年根据 2015-16 年综合家庭调查（IHS）的区级预测计数更新了普查计数。在行政上，冈比亚被划分为八个地方政府区域（LGAs）。每个 LGA 被划分为区，每个区被划分为定居点。一个定居点、一组小定居点或大定居点的一部分可以形成一个调查小区（EA）。这些单位使国家能够轻松地分割成小地理区域单位，每个单位都有城市或乡村的标识。冈比亚有 48 个区、120 个区和 4,098 个 EA；EA 的平均规模为 68 户。

2019-20 GDHS 的样本是在两个阶段选择的分层样本。在第一阶段，根据每个抽样层的规模比例选择了 EA。总共选择了 281 个 EA。

在第二阶段，对家庭进行了系统抽样。在所有选定的集群中进行了家庭清单操作。由此产生的家庭清单作为抽样框架，从每个集群中系统地选择了 25 户家庭，总共选择了 7,025 户家庭。该样本的结果在全国、城市和农村层面以及地方政府区域层面具有代表性。

有关样本选择的更多详细信息，请参阅最终报告的附录 A。

数据收集方式
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计算机辅助个人访谈 [capi]

研究工具
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2019-20 GDHS 使用了五份问卷：家庭问卷、妇女问卷、男性问卷、生物标志问卷和调查员问卷。这些问卷基于 The DHS Program 的标准问卷，并根据冈比亚的人口与健康问题进行了调整。从代表政府各部委、部门和机构的利益相关者、非政府组织和国际捐助者那里征求了建议。所有问卷都用英语编写，访谈员将问题翻译成适当的当地语言进行访谈。

数据清理操作
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所有电子数据文件都通过互联网文件流系统（IFSS）传输到 GBoS 中央办公室。IFSS 自动加密数据并将数据发送到服务器，服务器随后将数据下载到数据处理主管密码保护的计算机上。数据处理操作包括二级编辑，需要解决计算机识别的不一致性以及开放式问题的编码。数据由两位 IT 专家和三位参与主要现场工作培训的二级编辑处理；他们由 The DHS Program 的工作人员远程监督。数据编辑使用 CSPro 软件。在实地工作中，生成了现场检查表来检查各种数据质量参数，并给出了具体反馈以改进团队的表现。二级编辑和数据处理于 2019 年 11 月开始，并于 2020 年 5 月完成。

响应率
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在选定的住房单位中，所有 6,985 户家庭都有资格参加调查，其中 6,736 户有人居住。在这些有人居住的家庭中，有 6,549 户成功接受了访谈，响应率为 97%。在成功接受访谈的家庭中，2019 年完成了 1,948 份访谈，2020 年完成了 4,601 份。

在访谈的家庭中，确定了 12,481 名 15-49 岁妇女进行个人访谈；完成了 11,865 份妇女的访谈，响应率为 95%，比 2013 年 GDHS 高 4 个百分点。在男性中，有 5,337 人有资格进行个人访谈，完成了 4,636 份访谈；这导致了 87% 的响应率，比前一项调查高 5 个百分点。

抽样误差估计
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样本调查的估计受到两种类型误差的影响：非抽样误差和抽样误差。非抽样误差是实施数据收集和数据处理过程中所犯错误的结果，例如未能找到和访谈正确的家庭、访谈员或受访者对问题的误解以及数据输入错误。尽管在实施 2019-20 年冈比亚人口与健康调查（GDHS）期间采取了众多措施以最大限度地减少此类错误，但非抽样误差是无法避免且难以进行统计评估的。

另一方面，抽样误差可以统计评估。2019-20 GDHS 中选定的受访者样本只是从同一人口中可以选出的许多样本之一，使用相同的方案和预期规模。这些样本中的每一个都会产生与实际选定的样本结果略有不同的结果。抽样误差是所有可能样本变异性的度量。尽管变异程度并不完全清楚，但可以从调查结果中估计。

抽样误差通常以特定统计量（均值、百分比等）的标准误差来衡量，这是方差的平方根。标准误差可用于计算置信区间，在此区间内可以合理地假定真实值。

如果受访者样本被选为简单随机样本，就可以使用计算抽样误差的简单公式。然而，2019-20 GDHS 样本是多层次分层设计的产物，因此有必要使用更复杂的公式。抽样误差使用 SAS 计算得出，使用由 ICF 开发的程序。这些程序使用泰勒线性化方法来估计调查估计值（均值、比例或比率）的方差。对于更复杂的统计数据，如生育率和死亡率，使用 Jackknife 重复复制方法进行方差估计。

注意：关于抽样误差估计的更详细描述见调查报告附录 B。

数据评估
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数据质量表

- 家庭年龄分布
- 有资格和接受访谈的妇女年龄分布
- 有资格和接受访谈的男性年龄分布
- 报告的完整性
- 按日历年出生
- 死亡年龄按日历日的报告
- 死亡年龄按月份的报告
- 人体测量学培训标准化练习结果
- 儿童身高和体重数据完整性和质量
- 随机子样本测量儿童的身高测量
- 按月、按地方政府区域完成调查小区的数量，冈比亚 DHS 2019-20
- 根据快速诊断测试（RDT）按月和地方政府区域分类的 6-59 个月大儿童疟疾患病率
- 兄弟姐妹信息的完整性
- 兄弟姐妹的大小和性别比

有关数据质量表的详细信息，请参阅最终报告的附录 C。