Poster session on Health, mortality and longevity (1)

It is well known that there are substantial area variations in child mortality rates in the coastal region of Tanzania. Area variations in mortality may be due to characteristics that relate to the area itself (contextual factors) or to characteristics of the individuals who live in these areas (sociodemographic factors). We extend this body of research by hypothesizing that even within rural areas, there exists spatial disparity in child mortality and that this disparity varies by cause of mortality. The objective of this study is to investigate the geographical disparities of cause-specific under-five mortality in Rufiji Health Demographic Surveillance System (HDSS).
We combined all deaths of children under five that occurred between 2007 and 2010 for each village within the Rufiji HDSS and multiple it by the proportion of deaths assigned to each cause to yield the cause-specific under-five mortality rate at the village level. We rank mortality rates and focus on the leading four causes and contributors to geographical disparity: malaria, pneumonia, birth asphyxia and prematurity/low birth weight.
A total 2801 under-five deaths were recorded. We observe geographical disparities of cause-specific under-five mortality in Rufiji HDSS. These disparities may be due to in socioeconomic differences and healthcare accessibility.

Our study focuses on the impact of family environment on the health status of 10 year-old children. We distinguish physical and mental health as well as perceived and diagnosed problems. Data come from the Quebec Longitudinal Study of Child Development (QLSCD) that started collecting information in 1998 on a representative cohort of 2120 children aged 5 months. We create an indicator based on information reported by mothers and children at age ten. It consists of three mutually exclusive categories: 1) no health problem; 2) at least one perceived health problem but no diagnosed problem; 3) at least one diagnosed health problem. We use multinomial logistic regression models to assess whether the factors influencing the probability of having a diagnosed problem or a perceived problem are the same. We repeat the same model for three alternative indicators that consider either only physical health problems, only mental health problems, or both types of problems together. We include a range of risk factors drawn for family environment; some are time-invariant (e.g. age of mother at birth) others vary at each survey wave (e.g. poverty status). We expect to find that duration of poverty episodes and age at onset have different effects on perceived or diagnosed health.

Undoubtedly urban poor/slum population is deprived a lot facing the maximum brunt of the inequity in the cities. In this light it becomes imperative to find out what effect is cast by the proportion of slum population the inequity with respect to resources within the same slums and the human development index on the infant mortality rate in Mumbai and its 24 administrative wards. The second objective is to determine contribution of socio-economic inequality in infant mortality in Mumbai slums. The data for study has been gleaned from Human Development Report, Mumbai, 2009, Census of India, 2001 and National Family Health Survey-2005-06. The ward wise analysis with respect to three different regions of Greater Mumbai clearly shows that most of the wards of City Island had infant death around below 35 whereas most of the wards of Eastern suburbs had infant deaths more than 55 per 1000 live births. Some wards of Eastern suburbs such as M/E-Chembur East, M/W-Chembur West and L-Kurla call for special attention because these wards are having high concentration of slum population, low level of human development index and high burden of population on available health facilities which resulted into increase in the level of infant mortality rate during eight years time period.

This study attempts to evaluate principal components concomitant to infant mortality. IMR is affected by several factors belonging to maternal characteristics, child characteristics, utilization of health services and socioeconomic status of the people. Each of these factors includes a large number of variables. Categorical Principal Component Analysis (CATPCA) method is applied as a data reduction tool to reduce dimensionality in data. Data for this work have been taken from NFHS III. The analysis produced a three-dimensional solution, which explains 50.47% of the variance with reliability of 89.1% (cronbach’s α 0.891). Total 26.17% variance is explained in dimension one, 12.49% variance in dimension two and 11.81% in third dimension. Maternal factors explain total 26.83% variance and child factors explain total 18.58% variance. Out of ten samples of size n/2 from the same data set, nine samples give similar results.
 

Background: Health knowledge is developed through the experiences gathered by an individual, which makes him or her able to understand health problems. In Indian context, the study assess health knowledge of women of age group 15 to 49 years and its association with the prevalence of short-term morbidities, medical care and medical expenditure among children in age group 0-59 months.
Methods:The health knowledge and practice index and other several variables are constructed based on the information available from nationwide data (IHDS, 2005). Principal Component Analysis (PCA) is used to construct health knowledge index. Binary logistic regression and multinomial logistic regression analysis and MCA are used Results: Though, there is positive impact of education on health, still, immaculate health knowledge is required for mother to understand her child’s health problems. Enhanced health knowledge among mothers’ causes reduction in the prevalence of short-term morbidities among their children. Besides medical care, spending on medical care is also dependent on the fact that, to what extent women rationally take decision on taking care of their children’s health. . Willingness to pay for medical care is guided by their health knowledge. Health knowledge is established as a key determinant of prevalence of child morbidities.

Monitoring maternal mortality is extremely challenging due to issues with data availability and quality. The maternal mortality estimates published by the WHO in 2012 include data adjustment parameters to account for data quality issues, but there is a discrepancy between the WHO assumption about, and observed variability in, misclassification errors in VR observations. Bayesian modeling approaches can be used to provide more data-driven insights into maternal mortality estimates and data adjustment parameters. We propose a Bayesian time series model for the VR adjustment parameters to assess the extent of VR misclassification errors and to provide a plausible assessment of the uncertainty associated with VR observations for which no external quantification of misreporting is available. We find that the proposed model gives a distribution for VR adjustments that is more comparable to the observed biases than the WHO expert distribution. However, given the lack of, and issues with maternal mortality data, validation of modeling assumptions and findings is challenging; more research on measuring maternal mortality and assessing data quality is urgently needed.

In Nigeria, health care delivery is affected by several factors such as inadequate health work force, untimely delivery of medicines and vaccines, low quality of care, improper implementation of health policies, and poor service delivery. These factors have led to the poor performance of the country’s health system. Moreover, these factors affect health care services in emerging communities and urban slums of south west, Nigeria. The study aims to examine the nature of health care in emerging communities and urban slums. One of the specific objectives include; to explore the social processes by which health care services emerge and evolve in emerging communities and urban slums of South West, Nigeria. The study adopts a triangulation of qualitative and quantitative research methods. Data is being collected using household surveys; in-depth-interviews; key informant interviews and focus group discussions. The study will provide information on the varied nature of health care delivery in emerging communities and urban slums; help in the conceptualisation of health care delivery and utilisation in urban slums and emerging communities; and contribute to strengthening health care systems in emerging communities and urban slums of south west, Nigeria.
Keywords: Access, Utilisation, Emerging Communities, Urban Slums

In every corner of the world, city dwellers suffer disproportionately from poor health and these inequities leads to differences in their social and living conditions. The objectives of this study are: to compare the child immunization status among urban poor and non poor in the selected eight cities of India and to understand the effect of maternal health and socio economic characteristics in child immunization status by comparing urban poor/non poor and overall comparison of urban with the rural India. Data for analysis is drawn from NFHS –III. The analysis finds that the percentage of women age 20-24 married by age 18 and had home delivery is more than twice in urban poor and in rural as against urban non poor. Percentage of children immunized and births assisted by a health provider is 39.9 and 50.7 percent respectively in urban poor and is higher than rural India. Immunization coverage is much lower for urban poor than for non poor children in all the selected cities except Chennai. Educational status is low in urban poor as compared to urban non poor in both the sex in India. Thus, there is an obvious need to improve educational and health status of city dwellers.

Population censuses are particularly important in countries lacking timely and reliable system of vital statistics. It provides the only opportunity for estimating vital rates that would not otherwise be available. Most countries therefore rely heavily on censuses to obtain information on fertility and mortality rates especially at sub national levels. Most censuses in Africa, reliable estimates of the basic mortality data have always been suspect. The use of indirect methods has been employed to estimate key indicators based on Brass Type methods (UN 1983). However, in recent times many researchers have argued that demographic trends observed do not match the strong mathematical and other assumptions regarding the use of these procedures. In the Kenyan 2009 census, the indirect techniques (both adult and childhood) produced implausible results and therefore mortality indicators were obtained from deaths in the last 12 months. Data on deaths in the last 12 months have been criticized to underestimate mortality levels because of omissions in reporting. The main objective of this study is to evaluate the utility of using this approach for mortality estimations.

This paper examines the differentials in utilization of child health services between the Scheduled Tribes and Non-scheduled populations in the Odisha state of India. Data from the National Family Health Survey-3 (NFHS-3) carried out during 2005-06 are used. Besides, information from the field survey and Focus Group Discussions (FGDs) conducted in Sambalpur and Rayagada districts of Odisha are used. Logistic regression models have been employed to see the net effect of individual socioeconomic factors on utilization of preventive as well as curative child health services. Results show that utilization rate of child health care services is substantially lower among the Scheduled Tribes as compared to non-scheduled populations. Though utilization of child health care services is associated with a range of socioeconomic factors, the social group differences in utilization as revealed by the logistic regression models, is largely explained by the variations in the mother’s level of education. The unexplained differences could be attributed to the health seeking behavior as revealed in FGDs conducted among both the groups. Besides neglect of hospital staff and the feeling of ‘out of place’ at the health centre and lack of social capital are found to be linked with low utilization of child health services among the scheduled tribes.