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). Overall, the prevalence of physical IPV in developed European countries varies between 10% and 26% ( Michalski, 2005 ; Papadakaki et al, 2009 ). The objective of this research is to compare the prevalence of physical IPV in ten developing countries in four regions as identified by the Demographics and Health Survey (DHS): Sub-Saharan Africa with Mali and Nigeria; North Africa/West Asia with Egypt and Jordan; South and Southeast Asia with Cambodia, Pakistan and the Philippines; and Latin America and the Caribbean with Haiti, the Dominican Republic, and Peru

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Key messages This is the first study to measure interviewer effects regarding the reporting of intimate partner violence in the Demographic and Health Survey. Previous experience conducting the Demographic and Health Survey was significantly associated with lower odds of a respondent reporting physical intimate partner violence. Using the fieldworker data set will help improve the rigour of Demographic and Health Survey analyses and identify interviewer effects in other countries. Introduction Globally, one in three women will report intimate

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areas (Carr-Hill, 2017). The remainder of the chapter is in two sections. First, we briefly describe the problems of population statistics and poverty estimates; the specific problems with household surveys and why they are less reliable than censuses in estimating populations and measuring poverty rates; and finally the characteristics of citizen-led surveys in general. Second, we present a comparison of the estimates from the citizen-led surveys with contemporaneous demographic and health surveys at a national level and then for the three capital cities; and

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); and that better-planned sanitation reduces women’s risk of experiencing violence. Methods Data We used the 2007 Bangladesh Demographic and Health Survey (BDHS), the more recent dataset that includes questions on partner violence administered to a sub-sample of a national sample of women. A two-stage complex sampling procedure was used to identify households and individuals. The domestic violence module was administered by trained researchers to a sub-sample that agreed to answer questions about their experiences of partner violence. The researchers ascertained

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absolute poverty within the context of the child rights framework of the UN Convention on the Rights of the Child (UNCRC). Estimates of child poverty and deprivation for Haiti were made using the 2000 and 2005 rounds of the Haiti Demographic and Health Surveys (also referred to as Enquête Mortalité, Morbidité et Utilisation des Services, EMMUS). Three Demographic and Health Surveys have been conducted in Haiti − in 1994/95, 2000 and 2005. A fourth is currently underway (2011). This chapter uses data from the 2000 and 2005/06 surveys (EMMUS III and IV). Full

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-income countries without an adequate system of civil registration and so unable to make inter-censal estimates of population. Roy Carr-Hill demonstrates that current assumptions of population size miss large numbers of the poorest of the poor, possibly by as much as 8% of the world population, making estimates of poverty by UN and the World Bank arguably worthless. While donors have promoted the use of international standardised household surveys, a possible alternative is citizen surveys. Comparisons are made between citizen surveys and contemporaneous demographic and

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constructing child malnutrition indicators meant that it was necessary to use additional data from the UNICEF Multiple Indicator Cluster Surveys and Demographic and Health Surveys. This strategy made it possible to construct models to estimate the probability of malnutrition. Then those models were applied in more traditional household surveys, thus incorporating this essential dimension in estimating child poverty in the region. Conceptual approach: the notion of child poverty The term ‘poverty’ has differing connotations, and major semantic differences are sometimes

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to uncover the components of child poverty in different regions or age group or by gender. The Alkire-Foster method deals systematically with these issues and can be easily applied to child poverty measurement to enhance the headcount Global child poverty and well-being 104 measure. In this chapter we explain how this can be done, and illustrate the case by measuring multidimensional child poverty in Bangladesh using four rounds of the Demographic and Health Survey. We begin by reviewing the context of composite measures of child poverty. A key partner in

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children grow up and develop. Table 11.1 shows the proportion of children suffering one or more severe deprivations in Tanzania in 2004/05, according to the deprivations measure Table 11.1: Child poverty in Tanzania, 2004/05 (% of children) Tanzania 87.8 All rural 96.0 All urban 57.7 Dar es Salaam 41.3 Mainland 87.8 Zanzibar 62.8 Source: Own calculations based on Democratic and Health Survey 2004/05 data Global child poverty and well-being 268 described in the previous section. The information, extracted from the Demographic and Health Survey, is also

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, in no small part, to the availability of high quality, nationally representative household and individual level survey micro data. The best known sources include the United States Agency for International Development’s (USAID) Demographic and Health Surveys, UNICEF’s Multiple Indicator Cluster Surveys, the World Bank’s Living Standards Measurement Surveys and the World Health Organization’s (WHO) World Health Surveys. Some authors have used other surveys (see Chapters Twelve, Thirteen, Fourteen and Twenty) that include monetary data, and thus have been able

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