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Sampling Theory
Published in Marcello Pagano, Kimberlee Gauvreau, Heather Mattie, Principles of Biostatistics, 2022
Marcello Pagano, Kimberlee Gauvreau, Heather Mattie
The individual elements in a population being studied are called study units or sampling units; each element might be a person, a family, a city, a hospital, a clinic, an object, or anything else that is the unit of analysis in a population. For example, suppose we wish to determine the average amount of alcohol consumed each week by 15- to 17-year-old teenagers living in the Commonwealth of Massachusetts. In this case, the study units would be teenagers between the ages of 15 and 17 residing in Massachusetts at a particular time. Not all health surveys have people as the study unit. For example, the previously mentioned Demographic and Health Surveys are nationally-representative household surveys. Here, the sampling unit is a household.
What are the problems?
Published in Théodore H MacDonald, Health, Trade and Human Rights, 2018
In the third world, and especially among the poorest populations, many of the standard measures of wealth or poverty are not applicable. The ‘Demographic and Health Survey’ (DHS) programme, originally set up in Latin America in the early 1990s, is now proving to be one of the most powerful measures of health status in the third world ever devised. It is a survey research project which is being carried out in Africa, Asia and Latin America. Arising from pilot studies, the DHS is based on measures such as the ownership of (or access to) a refrigerator, television and radio; possession of a car, motorcycle or bicycle; how the household dwelling is constructed and from which materials; the dwelling’s source of drinking water; how toilet facilities are mediated; as well as the employment of domestic staff. Obviously, some of the index criteria, such as access to drinking water, for example, are also direct criteria for health status (Skidmore, 2002).
Interlocking Inequalities Related to Water and Sanitation, Nutrition and Healthcare Access
Published in Oliver Cumming, Tom Slaymaker, Equality in Water and Sanitation Services, 2018
In this chapter, we explore if, and how, inequalities in access to water and sanitation are co-distributed with other inequalities that may interact with or compound the public health and development impact of poor water and sanitation access. To do this, we consider three SDG sectors – water and sanitation (SDG 6), nutritional status (SDG 2) and healthcare (SDG 3) – and explore patterns of inequality by socioeconomic status (SDG 1) and urban/rural settings (SDG 10) for six low-income countries. For each of these sectors, we select basic indicators and use freely available Demographic and Health Surveys (DHS) (Figure 11.1). For SDG 6, to ensure availability of water and sanitation for all, we use child-level data on household access to basic improved water and sanitation facilities, as defined by the Joint Monitoring Programme (JMP),1 but did not include sharing by households in our classification. For SDG 2, to eliminate hunger we used moderate to severe stunting as defined by height-for-age measurements that were less than two standard deviations below mean z-scores, standardized to WHO growth reference standards4 as an indicator for undernutrition.5 For SDG 3, to ensure healthy lives and promote well-being for all, we used access to a full course (three-dose) of Diphtheria, Pertussis and Tetanus (DPT) vaccination as an indicator for access to healthcare, that was also recommended as a core impact indicator for MDG 4.5
A novel outlier statistic in multivariate survival models and its application to identify unusual under-five mortality sub-districts in Malawi
Published in Journal of Applied Statistics, 2023
Tsirizani M. Kaombe, Samuel O. M. Manda
We applied the proposed outlier statistic along with the standard method of visual inspection of standardised residuals [10] on child survival data from the 2015–16 MDHS. The MDHS was conducted between 19 October 2015 and 18 February 2016, and it collected child survival data from women respondents aged between 15 and 49 years, who provided birth histories. The survey used two-stage stratified sampling, with emuneration areas and households as primary and secondary sampling units, respectively [13]. We studied a total of 17,286 children who were born during the 5 years preceding implementation of the survey. These children were clustered at the 28 districts in Malawi, and each district was further split into rural and urban areas. Thus, for this study, we used the 56 subdistricts to illustrate the usefulness of our proposed multivariate survival data outlier detection method. The Demographic and Health Surveys (DHS) program provides free and publicly available datasets that can be accessed upon submitting a request at https://dhsprogram.com/data/new-user-registration.cfm.
Prevalence, Trends, and Factors Associated with Teen Motherhood in Nigeria: An Analysis of the 2008–2018 Nigeria Demographic and Health Surveys
Published in International Journal of Sexual Health, 2023
Yusuf Olushola Kareem, Zubaida Abubakar, Babatunde Adelekan, Edward Kwabena Ameyaw, Fred Yao Gbagbo, Erika Goldson, Ulla Mueller, Sanni Yaya
The data used for this study was extracted from 2008, 2013, and the most recent (2018) Nigeria Demographic and Health Surveys (NDHS). These three survey rounds were utilized to ascertain the patterns of pregnancy and childbearing among sexually active adolescents over the 10-years period as well as factors associated with this event. The Demographic and Health Survey (DHS) usually collects data that are comparable across several survey waves to provide information on the country’s demographic and health indicators, and these data are used to inform policies, monitor the progress and impact of programmes. The DHS adopts a multi-stage stratified cluster sampling. The first stage involves the selection of enumeration areas after the stratification of the country into urban and rural. Then, the next stage involved the selection of respondents from the selected households. Before pooling the datasets from the three DHS rounds, we denormalized the weight and adjusted for the population size of the adolescents for the different surveys using the World Bank Staff Estimates (Ajakaye & Ibukunoluwa, 2020). The total sample size of the pooled datasets was 9,106 adolescents and these included 2954, 3199, and 2953 adolescents from 2008, 2013, and 2018 NDHS, respectively.
Prevalence and Associates of Natural Menopause and Surgical Menopause Among Indian Women Aged 30 to 49 Years: An Analysis of the National Family Health Survey
Published in Women's Reproductive Health, 2021
Data used were from the last two rounds of the NFHS and were collected during 2005–2006 and 2015–2016, which are available in the public domain (DHS Program, 2019). The NFHSs are India’s Demographic and Health Surveys (DHS) and are carried out by the International Institute of Population Sciences, Mumbai, India, with technical assistance by ICF International and the former Macro International. Since 1992–1993, the NFHS has been an important data source for demography, maternal and child health, and nutrition for India and its states. The NFHS collects data from a nationally representative sample. The NFHS 2005–2006 provides state-level estimates and interviews of 124,385 women aged 15 to 49 years from 29 Indian states and union territories. The NFHS 2015–2016 also provides estimates at the district level and therefore has a much larger sample size. The NFHS 2015–2016 provides district-level estimates and interviewed 699,686 women aged 15 to 49 years from all 640 Indian districts. The survey uses a uniform sample design, questionnaire (translated into 18 Indian languages), and field procedure to facilitate comparability throughout India, and it provides high-quality data. The details of survey procedures of NFHS have been published elsewhere (IIPS & ICF, 2017; IIPS & Macro International, 2007).