Multiple faces of the health transition

Health is a good indicator of well-being of people of a country. Life expectancy has been used to represent the health aspect. Developed countries of the world have achieved considerable increase in life expectancy due to advancement in medical science. However, developing countries are still struggling hard to achieve the same level. Cause-elimination life tables focus on the hypothetical question - what would be a cohort’s mortality experience if a particular cause of death is eliminated. The objective of this study is to find out gain in life expectancy by age and sex after eliminating a specific cause of death. The study has used the Medical Certification of Cause of Death data of SRS, mid-year population provided by Technical Group on Population Projections for five selected states of India namely, Bihar, Kerala, Maharashtra, Rajasthan and Tamil Nadu. Data are categorized into five causes of death. Initial results show that gain in life expectancy is higher for male when all selected causes of death except circulatory diseases are eliminated, which has higher gains in females. This technique is useful in finding out potential benefits of disease elimination and is an essential tool for health policymakers and planners to set-up priorities for intervention programmes.

We assess the changing age pattern of mortality in India and bigger states by applying a mortality model during 1970-2006. Using survey data from India and a two dimensional system of model life table, we provide further evidence about changes in country and state-level patterns mortality differentials by sex and assess the potential role of major causes of death. We also study the contribution of major causes of death to the female-male mortality gap. The preliminary findings confirm that since the 1980s, health advantage of the Indian females against males has been growing. This occurred despite persisting female disadvantage below age 5. The biggest contribution to the life expectancy gap between females and males in the second half of the 1990s came from non-communicable diseases and external causes of death. We also found a notable geographical variation in sex-specific mortality patterns. While more advanced states showed female longevity advantages already in the 1970s, the laggard states displayed similar mortality levels for males and females even during the most recent periods. In order to better understand the path and timing of health transition and its determinants in India, it is necessary to consider changing sex-specific mortality patterns and their geographical diversity.

Female advantage in life expectancy in India is glaring. In this study we examine the gender differences in life expectancy and life disparity and estimated age specific mortality contribution in the gender differences. Complete life tables generated from data on death rates and abridged life tables from 1970-75 through 2006-10 from Sample Registration System (SRS) in India are used to estimate life expectancy at age x (ex), life disparity at age x (e+), threshold age at death and evaluate age with extremal impact on life disparity. General stepwise replacement algorithm is used for decomposition of both the indicators. The results indicate that the average increase in life expectancy and average decline in life disparity is higher for females. Higher threshold age at death among females resulted in increasing life disparity among males and decreasing life disparity among females for the similar age. The age having extremal impact on life disparity is higher for females. The decomposition analysis shows that the recent gender difference in life expectancy is attributed to negative contribution of adult mortality in India and difference in life disparity is attributed to positive contribution of adult mortality.

The GOI’s “Empowered Action Group” (EAG) states of Bihar and Jharkhand, Madhya Pradesh and Chhattisgarh, Orissa, Rajasthan, Uttar Pradesh and Uttaranchal and Assam as well from their responsibility to enhance the status of females right from girl children to mothers. As a result of which high risk of maternal deaths are still prevailing in the first decade of 21st century. Nearly two-third of the maternal deaths in the country are reported to occur in the EAG states and Assam. The state, Kerala all along depicted low MMR with better socio-demographic characteristics. Tamil Nadu, Karnataka and Andhra Pradesh, to a greater extent follow the path of Kerala. It is now highly expected that those EAG states should follow the path of Kerala. In order to do so they must develop their socio economic and other factors including particularly health sector, infrastructure and others. The present study hence is done to point out those factors through multivariate analysis and result is discussed.

The present study is an attempt to examine the factors affect on mortality of children under age three in Madhya Pradesh (a state in India) based on data collected from NFHS-III 2005-06. The differentials of mortality for children under age of three in Madhya Pradesh are observed as mother’s age at child birth, preceding birth interval, sex of child, birth order, mother’s work status, and economic standard of the household. The result clearly shows that child death increases with increase in birth order. Child death is also higher among the women belonging to household with low wealth index, younger and illiterate women than their counterparts. The multivariate survival analysis technique i.e. Cox proportional hazard model has been used to identify the determinants of children under age three mortality. The interesting finding shows that the relative importance of demographic factors in influencing child mortality supersedes the socio-economic factors. This study may help policy maker to take appropriate action against under-three mortality in the State Madhya Pradesh.

Understanding the perceptions people in a particular society have about malaria is a valuable socio-cultural factor necessary for its control. Studies however done in Upper East Region about the socio-cultural issues of malaria are limited. A cross sectional study was conducted in Chuchuliga, an irrigation community in the Builsa District of the Upper East Region, to find out the perceptions people have about malaria, and their treatment- seeking behaviours. The simple random sampling technique was used to draw 53 households. Descriptive statistics were employed for the quantitative data analysis, while the qualitative data were analysed using thematic analysis from a focus group discussion and interviews. The study finds that while people in Chuchuliga have adequate knowledge on the causes and symptoms of malaria, they do not know how the disease is transmitted. Their treatment strategies and attitudes towards the disease are also poor; as they indulge in practices like taking left-over drugs and indiscriminate drinking of concoctions prepared from plants. Men in Chuchuliga are the vulnerable group to malaria because of such socio-cultural factors as funeral celebrations, farming practices and alcoholism. Sensitisation on malaria and alcoholism is therefore necessary for effective control of malaria in Chuchuliga.

Here we look at recent attempts to measure simultaneously trends in mortality and morbidity in African populations. We begin with the measures of health which are currently available for African populations including partially complete incidence data and survey data which include both self-report and objectively measured aspect of health. The relationships between different measures of health are discussed in some detail, making the point that standard measures of health status developed in high income populations seem to produce reliable and consistent results in Africa as well. The issues of selection which arise when we study the health of the elderly in relatively high mortality populations are reviewed.

Using the short form 36 as measures of self-reported health, we examined the levels and differentials of the norm-based scores in adult women in Accra Ghana. From their birth histories, we can discern strong differentials in under five mortality that are associated with education and a number of other socio-economic indices in the expected direction. Turning to the women's current health status, we find much narrower differentials in the indices of their self-reported health and indeed in several objective measures of health including height, weight, blood pressure and histories of recent hospitalization.

About 80 percent of maternal deaths result from obstetric complications and a majority of these deaths can be prevented with timely medical treatment. The objective of this paper is to explore the barriers in receiving timely appropriate care for obstetric complications in rural Uttar Pradesh. World-wide one of the highest number of maternal deaths occurs in rural Uttar Pradesh. For this study the data from the latest RCH-DLHS-3 (2007-2008) and primary survey conducted during 2007-2009 has been used. Univariate, bivariate and multivariate logistic regression analysis has been conducted to examine the effect of demographic, socio-economic, health status, health-seeking behaviour and community variables on the obstacles in receiving health treatment for obstetric complications. This study answers several questions which are vital for improving maternal health such as, is economic development essential for reducing number of maternal deaths?; distance vs. road connectivity to health facilities; quality of care (QOC) vs. location of health facility; Does ANC improve treatment seeking behavior for obstetric complications? Based on the findings of the study potential areas for policy and research aimed at improving maternal health have also been discussed.

India accounts for about one-quarter of maternal deaths worldwide with the highest number of deaths occurring in the state of Uttar Pradesh. Utilization of antenatal, natal and postnatal care is important for reducing maternal morbidity and mortality. Uttar Pradesh, however, is characterized by low uptakes of maternal health services. Using RCH-DLHS-2 (2002-2004) dataset, present study attempts to investigate the importance of community and individual level variables in explaining factors affecting the utilization of antenatal, delivery and postnatal services in Uttar Pradesh by using techniques of simple logistic regression analysis and multilevel logistic regression analysis. Multilevel analysis has number of advantages over logistic regression analysis. From the analysis it is evident that the standard error of the coefficients under both the techniques present different picture. When data has hierarchical structure more and more community level variables emerge as significant associates of antenatal, natal and postnatal services.

Every year 358,000 maternal deaths take place. About 80 percent of maternal deaths result from obstetric complications and a majority of these deaths can be prevented with timely treatment. Women experiencing obstetric complication do not obtain adequate care in time due to three delays: delay in making the decision to seek care, delay in reaching an obstetric facility and delay in receiving care once the facility has been reached. According to UNFPA ‘three delay model’ is most appropriate for analysis of determinants of maternal mortality. Therefore, the objective of this paper is to examine the ‘three delays’ in receiving adequate care by women experiencing obstetric complications. Findings show that a high proportion of women experience ‘three delays’. Further study reveals that major obstacles in the decision to seek care (delay I) are low status of women, underestimation of illness severity, household responsibilities, perceived physical accessibility and QOC. Women experience delay in reaching facility (delay II) due to distance, road connectivity, unavailability of transport and cost. Availability of poor QOC in health facilities leads to further delays (delay III). Multivariate logistic regression shows that demographic, socio economic, health status, health seeking behaviour and community variables affect ‘three delays’