Poster session on Health, mortality and longevity (1)

Two related objectives are the concern in this article. The first is to suggest a conceptual framework for explaining the association between poverty and Common Mental Disorder (CMD) and the mediating factors. The second is to examine statistically the hypothesized role of poverty and other demographic, socioeconomic and behavioral risk factors on CMD. Data from the Urban Inequity Study Survey (UIS) that was conducted in Cairo, the capital of Egypt in 2007 are used. About 2000 adult females and 2000 adult males were interviewed. Few percent of the study population has non/minimal depression (15% and 16% among males and females, respectively) One quarter of males and one third of females have mild depression and one third of each have moderate. Females exceed males in mild and moderate depression (64.6% vs. 59.2%). about 20% of the females and one quarter of the males have severe depression. Level of depression significantly declines with education, marriage, and age. Sad events and other difficult life situations such as; spinsterhood, divorce or widowhood, and difficulty of carrying out the daily physical functions are strong risk factors. Neither poverty nor living in poor neighborhood is risk factor. Males, contrary to females, are significantly impacted by their work conditions.

Modernization, urbanization, and western lifestyle contribute to the prevalence of sedentary lifestyle in Asia. However, few researches on how urban environment contribute to sedentary lifestyle were found. The aim of this study is to examine how urban residents perceive the extent of resources for exercise in urban environment is associated with their likelihood of having a sedentary lifestyle across four Asian countries (China, South Korea, Taiwan, and Japan). Data from the East Asia Social Survey (EASS) 2010 Health Module was used. The results show that China and South Korea, perceived resources for exercise in urban environments is associated with the prevalence of sedentary lifestyle. The association between perceived environment and sedentary lifestyle is particularly strong with South Korea. Further examination of age and gender-specific, education level and employment status specific association between perceived resources of urban environment and sedentary lifestyle is needed.

What explains the body mass index gap among racial groups over the last several decades? Prior research suggests that the socioeconomic disadvantaged position of minorities explains why non-Hispanic Blacks have higher prevalence of obesity than non-Hispanic Whites. The explanation is plausible and is supported by empirical evidence, but it is still not conclusive. First, we shouldn’t ignore the fact that the income distribution has changed dramatically within and across racial groups in the last several decades. How is changing in the distribution of income associated with the changing in distribution of BMI among racial group over period is still not clear.Secondly, existing literature mainly examines the association between covariates of interest and mean BMI by using OLS regression based analysis. There is little research pays attention to how socioeconomic status is associated with the relative position in the distribution of BMI. In addition, the distribution of BMI has changing over time across racial groups. In this research, I will apply quantile regression to estimate the association between socioeconomic status and the quantiles of BMI. Second, I will apply oaxaca-like decomposition to separate the changing gap in BMI distribution across racial groups into two factors: the difference in magnitude of covari

This paper identifies the spatial and temporal determinants of prostate cancer, breast cancer, and colorectal cancer, three prevalent forms of cancer in Canada. Specifically, we highlight the importance of age at residence in a cancer 'hotspot', arguing that an individual's migratory history and past places of residence are in certain circumstances better predictors of cancer in the present than current location. GIven that roughly a third of all Canadians move every five years, the ability to identify residential pathways has particular relevance. These data are the first in Canada to be able to measure the connection between current and previous places of residence and risk of contracting the three cancers mentioned above.

We aim to investigate long-term prostate cancer survivors’ quality of life (QoL) over time. We employ growth curve model to examine the panel data from a population-based survey of survivors with localized prostate cancer in southeast of U.S. (N=1008). Survivors on average are 3 years post-diagnosis at intake and followed-up annually for 3 years. QoL is measured using SF12. Time-invariant factors include age, race, and education at intake. Time-varying variables include family income, marital status, time since diagnosis, prostate cancer specific bowel, hormonal, sexual, and urinary symptoms (EPIC-26), and comorbid conditions (Charlson Index).
Being younger (p<.01), being black (p<.05), having higher family income (p<.0001), having college or higher education (p<.01), and having fewer bowel (p<.05), hormonal (p<.0001), urinary irritability (p<.01), and sexual (p<.05) symptoms and comorbidities (p<.001) predict better physical QoL over time. Being older (p<.0001), being married (p<.01), and having fewer hormonal (p<.001) and sexual (p<.05) symptoms and comorbidities (p<.05) predict better mental QoL over time.
Both time-invariant and time-varying factors contribute to survivors’ QoL over time. To improve their QoL, clinicians need to attend to both prostate cancer specific symptoms and aging-related factors.

With the development of society and economy, personal and social burdens of chronic diseases became bigger, while it used to be infections and acute diseases that gave most burdens to society and economy. Therefore, it was tried to suggest what group should be specially managed by identifying the frequency of chronic diseases according to socio-demographic characteristics such as age, sex, marital status and job in the adult group in Korea. The materials used for this study were the results of Standard Adult Survey on 2,118 adults representing Korean adults abstracted by compounded sample survey by Integrated Safety Management of Hazardous Substances and Human Exposure Assessment Foundation Agency which was founded by the National Institute of Food and Drug Safety Evaluation in March, 2010 to evaluate the status of hazardous materials’ exposure status through food and drug. The indexes showing socio-demographic characteristics used for this analysis were obtained through survey results. The subjects were asked to answer if they had hypertension, diabetes or kidney diseases. Data were analyzed through Chi-Square Test to see if there was significant difference as well as to identify the diagnosis frequency of such diseases according to socio-demographic characteristics.

Improving accountability for commitments made in maternal and neonatal health has become a global priority in the race to accelerate progress on MDGs 4 and 5. At a time when tax-payers are also demanding strong, quantitative evidence that aid programmes represent value for money, new methods to attribute tangible impact to such accountability programmes are required. Conducting this type of analysis is challenging for accountability programmes. The outcomes of accountability activities are not easily quantifiable and the overall approach is still in the process of building an evidence-base.

In this article, we describe a methodology to project the number of maternal and neonatal lives saved by a programme aiming to strengthen accountability for MNH. Extensive evidence on the effectiveness of various bio-medical interventions for maternal and neonatal health has been incorporated within the Lives Saved Tool (LiST) software, developed by the Johns Hopkins School of Public Health. Our method extends the application of LiST beyond its bio-medical scope by assuming that greater accountability, through the more efficient use of health resources, causes a proportional increase in the coverage of all life-saving MNH services.

Most analyses of differentials and trends in health and mortality find the anticipated relationship between measured outcomes and a range of socio-economic status variables including education, income status of employment and wealth. From a multi-year longitudinal study of health and mortality in Accra called the Women’s Health Study of Accra (WHSA), we produce a much finer grained analyses of health and mortality differentials within an urban area (Weeks, Hill et al. 2006; Douptcheva and Hill 2011). First, in some of the communities designated as ‘slums’ by UN Habitat, child mortality and adult morbidity are surprisingly good. The socio-demographic profile of the population, shaped heavily by migration, modifies the risk profile (Fink, Weeks et al. 2012). Secondly, the anticipated differentials in both self-reported and objectively measured dimensions of adult health are very narrow and often in the opposite direction anticipated (Darko, Adanu et al. 2012). Thirdly, there is evidence of pronounced neighbourhood effects where even for those poorer than the mean for the whole neighbourhood, place of residence can mitigate some of the otherwise adverse health outcomes associated with poverty (Weeks, Getis et al. 2010).These empirical facts present a challenge to conventional theory on the determinants of health outcomes.

A single summery index of mortality can never replace the set of age-specific death rates, it has been found to be extremely useful for a wide variety of purposes. The choice of index depends upon the purposes for which it is to be used, and is important as different indexes can produce very different results. This study examines the variation in mortality and mortality trends in India and its major states from the 1970-75 to 2002-2006 using data from the Sample Registration System (SRS). Several indicators were developed to study mortality .The most basic indicators are: CDR, IMR, ASDR, and LEB and several other indicators were also existed. Arithmetic mean of the Age Specific Death Rates and Geometric Mean of the Age Specific Death Rates (or the Del Index) are examples. Input data used in deriving the DI and OMI Age Specific Death Rates (ASDRs) of the 16 age groups: 0-1, 1-4, 5-9, 10-14, -----65-69, and 70+ “Age Structure of Mortality in India and Its Bigger States“ Del Index refers to the geometric mean of the age-specific death rates as a summery index of mortality, which was postulated by the versatile Demographer Robert Schoen in the year of 1970.

The purpose of this paper is to both quantify women's empowerment in Egyptian context and examine whether any significant improvement in their situation has been achieved since 1995. Further, the association between women's empowerment and child health will be examined. It is argued that women with higher status are better able to make positive investments in their children's chances of living in better health. Data used in the study come from the Egypt Demographic and health surveys in 1995, 2005, and 2008. Women's empowerment is quantified using constructed indices: mobility index, attitude towards gender index, attitude towards domestic violence index, women's involvement in domestic decision making, and media exposure. The evidence suggested that women's status in Egypt is significantly changed in the period between 1995 and 2008. Further, child survival benefit from women's empowerment. Some policy implications of the findings and measurement issues pertaining to women’s empowerment are discussed.