Suchergebnisse

BackgroundCompared to married mothers, mothers who are not married when they register their child's birth are at increased risk of having a low birthweight baby and infant death. Having a partner protects women from poor pregnancy outcomes to some extent but those who are living with, but not married to, their partner still do less well than those who are married. As it does not appear to be marriage itself which is protective, other factors such as maternal education and smoking, and household characteristics, such as accommodation type and familial support in the household, need to be examined.
AimTo explore the individual socio-demographic and household characteristics that are associated with low birthweight and infant death among unmarried mothers.
MethodsA population based cohort study will be conducted through the Administrative Data Research Network based on all registered live births 2010-2016 to women resident in Northern Ireland (NI).
General Register Office (GRO) birth records will be linked to the NI Maternity System and GRO infant death data to identify low birth weight (primary) and infant death (secondary) outcomes. Maternal individual socio-demographic and household characteristics will be provided through linkage to the 2011 census (ethnicity, highest level of education, support from family members living in the household); Enhanced Prescribing Database (maternal mental health prescriptions); 2010 NI Multiple Deprivation Measure (area level deprivation, including income and education domains, for the mother's home address at the time of birth) and Valuation and Lands Agency Rating List (capital value of property of mother's address).
Descriptive statistics and logistic regression will be used for the analysis.
ImpactIt is anticipated the findings will reduce the public health burden of low birthweight babies by directing interventions to targeted groups of mothers.

Poverty is multi-dimensional in nature and depends on interactions of various socio-economic factors. Several demographic and health factors can shape up the economic status of a household, and theory suggests that the ability of a household to earn a given level of income can depend on the characteristics internal to the household. While most studies done on poverty measurements rely on the income, expenditure and consumption data, this study has used data from Bangladesh Demographic and Health Surveys (DHS). The main objective of this paper is to identify the factors that have relative effect on poverty of the household. The principal component analysis was used to create an asset index which gave the Social Economic Status (SES) of each household. The variables were tested as a univariate model to see the effect on SES. Finally, a logistic regression was estimated based on this data with the SES (that is poor and non-poor) as the dependent variable and a set of demographic variables as the explanatory variables. The results presented in this paper suggest that the DHS data can be used to determine the correlates of poverty. The results also suggest that demographic and household data can describe poverty. The probability of a household being poor depends on the ownership of assets and other household data. A closer look was then taken to identify whether the results were driven by rural or urban property. The further analyses suggest that rural poverty is significantly affected by the demographic and household characteristics. The results were mostly driven by rural poverty rather than urban poverty. The paper has some policy values, as it suggests that rural people more suffer from the plight of poverty than do the urban people. Hence, the government needs to focus on improving the standard of living in rural areas of Bangladesh.

Energy issues and energy poverty became very important when dealing with global development challenges and sustainable development agenda, and as the years pass more precise indicators are formed to follow this phenomenon from various perspectives. One way to follow and analyze energy poverty is through the indicators proposed by the European Commission and the Survey on Income and Living Conditions (EU-SILC). Based on the main EU-SILC indicators for Serbia for 2020, this analysis explored a relationship between energy poverty and household income disaggregated by available data about regions, degree of urbanization, household types, and sex-age structure. It also tended to position Serbia within the European context regarding energy poverty. Based on the available data, it was found that people living in thinly populated areas expressed a higher share of vulnerabilities than those living in densely populated areas. Also, persons at risk of poverty are more vulnerable than the total population. When it comes to household types, people living in a single-person household are the most vulnerable, followed by the single-parent household with dependent children.

This paper presents evidence on how children's educational outcomes are affected by family, social and economic backgrounds in a developing economy by exploiting data from the Bangladesh Demographic and Health Survey (BDHS) 2011. In a developing country like Bangladesh, a child's educational outcome is not only dependent on government policies but also on the child's social and economic background. In this paper an attempt has been made to answer the question — how household conditions affect the educational attainments of children. To answer this question an examination of proximate factors associated with school dropouts has been conducted by developing Ordinary Least Square (OLS) and probit estimations to see if the models can explain the Bangladesh DHS data well. Any differential effects of the gender of the household head or across regions have been taken care of to arrive at the results. A set of independent variables has been identified representing the household status and family conditions. For the OLS model, the dependent variable chosen is the percentage of school dropouts from a particular household. For the Probit model, a dichotomous variable indicating whether the household has any number of school dropouts or not was calculated. The results showed that children from poor families with less educated parents have overall high dropout rates with a lasting effect on educational outcomes. Father's education plays a significant role in reducing the dropout rates, whereas the mother's education has negligible effect. It is also noted that families with more than 3 children and household members greater than 5 also have fewer number of children who are going to school. The place of residence, access to electricity and school transportation reduces the dropout rates. Also, the results for the probit model virtually mirror the OLS results. The OLS and probit do not diverge in sign or significance for most other variables either such as urban-rural location and father's education. This paper is a valuable contribution for assessing the policies taken by the Government of Bangladesh because Bangladesh's school dropout rate has increased over the last few years. This paper is the first of its kind as it uses a different methodology to assess the effect of household conditions on children's educational outcomes.

This chapter raises a number of questions concerning the partnership and family characteristics of the women and men in the sample. It also refers to theories which have explored such characteristics. The characteristics considered are family of origin, marital status, children, childcare and housework. Then gender is analysed as a determinant and the conclusions summarise the main findings in respect of the explanatory theories.

"This paper studies the effect that changing demographic patterns have had on the household saving rate in China. We undertake a quantitative investigation using an overlapping generations (OLG) model where agents live for 85 years. Consumers begin to exercise decision making when they are 18. From age 18 to 60, they work and raise children. Dependent children's utility enter into parent's utility where parents choose the consumption level of the young until they leave the household. Working agents give a portion of their labor income to their retired parents and save for their own retirement while the aged live on their accumulated assets and support from their children. Remaining assets are bequeathed to the living upon death. We parameterize the model and take future demographic changes, labor income and interest rates as exogenously given from the data. We then run the model from 1963 to 2009 and find that the model accounts for nearly all the observed increase in the household saving rate"--National Bureau of Economic Research web site