Demographic and Health Survey 2016 - Uganda

Abstract
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The 2016 Uganda Demographic and Health Survey (2016 UDHS) was implemented by the Uganda Bureau of Statistics. The survey sample was designed to provide estimates of population and health indicators including fertility and child mortality rates for the country as a whole, for the urban and rural areas separately, and for each of the 15 regions in Uganda (South Central, North Central, Busoga, Kampala, Lango, Acholi, Tooro, Bunyoro, Bukedi, Bugisu, Karamoja, Teso, Kigezi, Ankole, and West Nile).

The primary objective of the 2016 UDHS project is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2016 UDHS collected information on:
• Key demographic indicators, particularly fertility and under-5, adult, and maternal mortality rates
• Direct and indirect factors that determine levels of and trends in fertility and child mortality
• Contraceptive knowledge and practice
• Key aspects of maternal and child health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators such as antenatal visits and assistance at delivery
• Child feeding practices, including breastfeeding, and anthropometric measures to assess the nutritional status of women, men, and children
• Knowledge and attitudes of women and men about sexually transmitted infections (STIs) and HIV/AIDS, potential exposure to the risk of HIV infection (risk behaviours and condom use), and coverage of HIV testing and counselling (HTC) and other key HIV/AIDS programmes
• Anaemia in women, men, and children
• Malaria prevalence in children as a follow-up to the 2014-15 Uganda Malaria Indicator Survey
• Vitamin A deficiency (VAD) in children
• Key education indicators, including school attendance ratios, level of educational attainment, and literacy levels
• The extent of disability
• Early childhood development
• The extent of gender-based violence

The information collected through the 2016 UDHS is intended to assist policymakers and program managers in evaluating and designing programs and strategies for improving the health of the country’s population.

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 15-54

Kind of data
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Sample survey data [ssd]

Sampling procedure
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The sampling frame used for the 2016 UDHS is the frame of the Uganda National Population and Housing Census (NPHC), conducted in 2014; the sampling frame was provided by the Uganda Bureau of Statistics. The census frame is a complete list of all census enumeration areas (EAs) created for the 2014 NPHC. In Uganda, an EA is a geographic area that covers an average of 130 households. The sampling frame contains information about EA location, type of residence (urban or rural), and the estimated number of residential households.

The 2016 UDHS sample was stratified and selected in two stages. In the first stage, 697 EAs were selected from the 2014 Uganda NPHC: 162 EAs in urban areas and 535 in rural areas. One cluster from Acholi subregion was eliminated because of land disputes. Households constituted the second stage of sampling.

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

Mode of data collection
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Face-to-face [f2f]

Cleaning operations
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All electronic data files for the 2016 UDHS were transferred via IFSS to the UBOS central office in Kampala, where they were stored on a password-protected computer. The data processing operation included registering and checking for inconsistencies, incompleteness, and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. The central office also conducted secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by four staff (two programmers and two data editors) who took part in the main fieldwork training. They were supervised by three senior staff from UBOS. Data editing was accomplished with CSPro software. Secondary editing and data processing were initiated in August 2016 and completed in January 2017.

Response rate
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A total of 20,791 households were selected for the sample, of which 19,938 were occupied. Of the occupied households, 19,588 were successfully interviewed, which yielded a response rate of 98%.

In the interviewed households, 19,088 eligible women were identified for individual interviews. Interviews were completed with 18,506 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 5,676 eligible men were identified and 5,336 were successfully interviewed, yielding a response rate of 94%. Response rates were higher in rural than in urban areas, with the ruralurban difference being more pronounced among men (95% and 90%, respectively) than among women (98% and 95%, respectively).

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 2016 Uganda Demographic and Health Survey (UDHS) 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 2016 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 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 2016 UDHS 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.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final 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
- Completeness of information on siblings
- Sibship size and sex ratio of siblings
- Pregnancy-related mortality trends

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

摘要
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2016年乌干达人口与健康调查（2016 UDHS）由乌干达统计局实施。该调查样本旨在为整个国家、城市和农村地区分别以及乌干达的15个地区（南中、北中、布索加、坎帕拉、朗戈、阿乔利、托罗、布尼奥罗、布凯迪、布吉苏、卡拉莫贾、特索、基盖齐、安科莱和尼罗河西部）提供人口和健康指标估计，包括生育率和儿童死亡率。

2016 UDHS项目的首要目标是提供最新的人口和健康基本指标估计。具体而言，2016 UDHS收集了以下信息：
• 关键人口指标，特别是生育率和5岁以下、成人以及孕产妇死亡率
• 决定生育率和儿童死亡率水平及趋势的直接和间接因素
• 避孕知识与实践
• 孕产妇和儿童健康的关键方面，包括儿童免疫接种覆盖率、5岁以下儿童腹泻和其他疾病的患病率和治疗情况，以及孕产妇保健指标，如产前检查和分娩时的援助
• 儿童喂养实践，包括母乳喂养，以及用于评估妇女、男性和儿童营养状况的体格测量
• 妇女和男性对性传播感染（STIs）和艾滋病（HIV/AIDS）的知识和态度，潜在暴露于HIV感染风险（风险行为和安全套使用），以及HIV检测和咨询（HTC）以及其他关键HIV/AIDS项目的覆盖率
• 妇女、男性和儿童的贫血症
• 儿童疟疾患病率，作为对2014-15年乌干达疟疾指标调查的后续
• 儿童维生素A缺乏症（VAD）
• 关键教育指标，包括学校入学率、教育水平和识字率
• 残疾程度
• 早期儿童发展
• 性别暴力的程度

通过2016 UDHS收集的信息旨在帮助政策制定者和项目管理人员评估和设计改善国家人口健康的计划和策略。

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
- 15-54岁男性

数据类型
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样本调查数据 [ssd]

抽样程序
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2016 UDHS使用的抽样框架是2014年进行的乌干达国家人口和住房普查（NPHC）的框架；抽样框架由乌干达统计局提供。普查框架是针对2014年NPHC创建的所有普查统计区域（EA）的完整清单。在乌干达，EA是一个地理区域，覆盖平均130户家庭。抽样框架包含有关EA位置、居住类型（城市或农村）以及估计的住宅户数量等信息。

2016 UDHS样本分为两个阶段进行分层和选择。在第一阶段，从2014年乌干达NPHC中选择了697个EA：162个位于城市地区，535个位于农村地区。由于土地纠纷，阿乔利次区域的一个集群被排除在外。家庭构成了抽样的第二阶段。

有关样本设计的更多详细信息，请参阅最终报告的附录A。

数据收集方式
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面对面 [f2f]

清理操作
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所有2016 UDHS的电子数据文件都通过IFSS传输到乌干达统计局坎帕拉中央办公室，在那里它们被存储在密码保护的计算机上。数据处理操作包括注册和检查不一致性、不完整性和异常值。数据编辑和清理包括结构和一致性检查，以确保现场工作的完整性。中央办公室还进行了二级编辑，这需要解决计算机识别的不一致性和开放式问题的编码。数据处理由四名工作人员（两名程序员和两名数据编辑员）完成，他们参与了主要现场工作培训。他们由UBOS的三名高级工作人员监督。数据编辑使用CSPro软件完成。二级编辑和数据处理于2016年8月开始，并于2017年1月完成。

应答率
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总共选择了20,791个家庭作为样本，其中19,938个被占用。在占用的家庭中，19,588个被成功采访，应答率为98%。

在采访的家庭中，确定了19,088名符合条件的妇女进行个别采访。完成了18,506名妇女的采访，应答率为97%。在为男性调查选择的子样本家庭中，确定了5,676名符合条件的男性，其中5,336名被成功采访，应答率为94%。农村地区的应答率高于城市地区，男女之间的城乡差异在男性（95%和90%）中比在女性（98%和95%）中更为明显。

抽样误差估计
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样本调查的估计受两种类型的误差影响：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时出现的错误的结果，例如未能找到和采访正确的家庭，采访者或受访者对问题的误解，以及数据输入错误。尽管在实施2016年乌干达人口与健康调查（UDHS）期间采取了众多努力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从统计上进行评估的。

另一方面，抽样误差可以统计评估。2016 UDHS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，使用相同的设计和预期规模。每个这样的样本都会产生与实际选定样本结果略有不同的结果。抽样误差是所有可能样本之间差异的衡量标准。尽管变异性程度无法准确得知，但它可以从调查结果中估计。

抽样误差通常以特定统计量（平均值、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，其中可以合理地假定真实人口值的范围。例如，对于从样本调查中计算的任何给定统计量，该统计量的值将在95%的所有可能样本的相同大小和设计范围内加减两倍标准误差。

如果受访者样本被选为简单随机样本，则可以使用简单的公式来计算抽样误差。然而，2016 UDHS样本是多阶段分层设计的结果，因此有必要使用更复杂的公式。抽样误差使用SAS计算，使用ICF开发的程序。这些程序使用泰勒线性化方法来估计均值、比例或比率等调查估计的方差。使用Jackknife重复复制法对更复杂的统计量，如生育率和死亡率，进行方差估计。

抽样误差估计的更详细描述见调查最终报告的附录B。

数据评估
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数据质量表
- 家庭年龄分布
- 符合条件和被采访的妇女年龄分布
- 符合条件和被采访的男性年龄分布
- 报告的完整性
- 按日历年份的出生
- 死亡时年龄的报告（按天数）
- 死亡时年龄的报告（按月份）
- 兄弟姐妹信息的完整性
- 兄弟姐妹的大小和性别比
- 与孕产妇死亡率相关的趋势

有关数据质量表的详细信息，请参阅调查最终报告的附录C。