Multiple faces of the health transition

This research work explores the rate at which HIV/AIDS affects the whole populace of South Africa. It actually focuses on the trend at which HIV/AIDS follows for a period of 10 years, (2011-2020). HIV/AIDS is more of a developmental challenge than merely a health issue. It erodes the economy of a country completely unless urgency is applicable. Skills and ideas which are meant to make life a better place for people become untransferable. A lot of dreams become shattered and unfulfilled due to this deadly pandemic. Children who are meant to enjoy good parental up-bringing and morals are orphans. Every day, 14,000 people become infected with HIV/AIDS. This makes various research works on the production of more effective therapy, one of the world’s top public health priorities. Inspite of various research works on the production of effective therapies, no researcher has been able to come up with a lasting solution to this deadly pandemic. The available therapies, that is, the antiretroviral therapies, (ART) are meant to control the symptoms, and it is not even as if the ART are readily available and accessible by all the people living with the virus. This study aims at forecasting the trend at which HIV/AIDS death will follow for a period of 10 years, (2011-2020) based on the past record, based on the study recommendations.

During the last century, India experienced drastic improvement in life expectancy. Did the extra years gained to the life expectancy have really improved the quality of life? Such question becomes prominent when one considers the changes in morbidity. So far, no study has been available by combining mortality and morbidity changes to a single index by representing health status in India. This paper is an exploration of quality of life by using Disability Free Life Expectancy (DFLE) rates in India. It followed methodology forwarded by Sullivan (1971). It used three levels of disability rates -perceived morbidity, restricted activity and also confined to bed by using the data from SRS and NSSO. It found that DFLE is declined in higher rates in advanced states indicating a considerable decline in the quality of life with the advancement in life expectancy, especially to the older ages. Females and urbanites have considerable decline in quality of life than that of males and rural people. The study also found that prominent role of chronic/degenerative diseases in losses in DFLE. All the three levels of disability for DFLE found similar pattern. It concludes that mere increase in longevity does not mean better life. It is high time for India to have effective interventions to improve the quality of life along with life expectancy.

We examine the social network (SN) – self-rated health (SRH) association for groups defined by age, sex and partnership, using survey data for older Australians. Models predict fair/poor SRH vs good/very good/excellent. Explanatory variables cover 3 network dimensions (social engagement (SE)/instrumental support (IS)/emotional support (ES)), distinguishing between family-, friend- and group-based networks. Sociodemographics, disability, mental health and subjective e(x) are included. SE is not associated with SRH except in the presence of an interaction between disability and SE. Only for unpartnered is more SE(family) associated with better SRH, and this is tempered by a reversed effect at higher levels of disability. This reversed effect also occurs more widely. For the oldest group, more SE(friends) is associated with worse SRH, although this is reduced at higher levels of disability. We find a ‘beneficial’ effect of group activity for most groups. IS(family) is associated with better SRH for males and those aged 60-69 but with poorer SRH for those aged 50-59. ES(friends) is associated with better SRH for males only. IS(friends) and ES(family) are not associated with SRH. These varying associations among demographic groups has implications for strategies and policies to support health and wellbeing in later life.

Public health expenditure has a clear tendency of increase in Spain in recent years. Assessing its determinants is extremely important to predict future health consumption and adjust government policies to attend future demand. Population aging is among one of the most important variables that trigger health expenditures. Deeper analysis is needed to understand which is the share of health costs growth attributable to population aging, regarding other factors like technological change or budget level allocated to health expenditures. We use a hospital cost survey to analyze the age profile of public expenditures on hospitals during the last decade in Spain. Results show that during these years average hospital spending by age grew constantly for almost all age groups, but especially among the elderly. Health care for people 80 years of age or above increased 141% from 2000 to 2009, even though they represent only 13% of the total hospital expenditure.

The specific objectives of the present study are to analyze the differentials in prevalence; progression of use of tobacco and major determinants of quitting of smoking as well as use of smokeless tobacco. The rationale behind this study is to spread the awareness about the disease and deaths due to tobacco consumption. This study utilized the data from the Global Adult Tobacco Survey India (GATS India). This paper is an attempt to find the progression of use of tobacco in all the regions of India by using the Kaplan-Meier Survival Analysis and Cox's Proportional Hazards Regression. The Cox proportional-hazards regressions model is broadly applicable and the most widely used method of survival analysis. The prevalence is high in Bihar (54%), Chhattisgarh (53%), and Jharkhand (50%) and the lowest in Goa (9 %), Punjab (12 %).the probability of quitting tobacco among females is 1.35 times (p<.01) higher compared to their male counterparts. The probability of quitting tobacco is found to be 37.6 percent less among people from the North-East than among people from the northern region. However, the chances of quitting the use of smokeless tobacco are less in the North-East (HR=0.48), followed by the central (HR=0.94).

Diabetes is seen as a global epidemic inflicting millions, mostly in developing nations and disadvantaged groups in developed nations. In the Philippines, about 3-4 million are believed to have diabetes. Worse, another 3-4 million may be at risk or already have this deadly condition but do not know it.

Patients with Type 2 Diabetes Mellitus (T2DM) have multiple responsibilities, including lifestyle modifications, dietary restrictions, self-monitoring of glucose levels, screening for complications, and adherence to medications. Depressive conditions, eating disorders, poor family relationships, and other psychological problems are common in patients and are associated with poor glycemic control. Studies have shown that family support has a great impact on management of diseases. In this light, this study aims to explore the relationship between family dysfunction and the glycemic control.

The study sample includes 68 patients of Angono General Hospital and Taytay Emergency Hospital with T2DM from September to November 2009. Both descriptive and inferential analyses were utilized in the study. The results show that there is an association between family function and the management of diabetes. This indicates that the family, as a source of support is an integral part in managing disease, particularly

With the longevity improvements it is pertinent to know whether the extended years of life are going to be spend in healthy or worsened state. Financing health which is one of the critical determinants of health outcomes is further determined by population structure as the higher prevalence of morbidity among elderly causes elevated health expenditure which turns into more requirement of money under the assumption that the elderly are treated equally to younger. With longevity improvements and age structural transition the old aged population is expected to grow from 6.7 (2001) to 19.1 percent by 2050 in India. This needs a simultaneous future growth of health expenditure in India. The study found that though, number of healthy years has increased but this increase is not in the same pace as increase in life expectancy. Moreover, age structure transition has role in health spending and if it is taken into account in projection, health spending will reach at 6.5 percent as percent to GDP in 2050. Though, per capita health spending is found to be significantly higher among elderly, its contribution is very high among young population because of large size.

While chronologically old age is considered to begin from the sixties, biological maturity and ageing in the human body initiates much earlier. In women, menopause marks the beginning of such a process with sudden imbalance in the hormonal and physiological functions of the body.

Present paper aims at understanding age at menopause, its symptomatology and post-menopausal health problems among women of Assam, India.

Data were sourced from field survey of 447 menopausal women aged 40-55 years selected from urban, rural and tribal settings in Assam. Selection of respondents was purposive in nature and performed using quota sampling procedure.

Mean age at onset of menopause among India women is 47±2 years, those under study experiencing it as early as 44 years, much below the global and national average.

The most prominent symptoms were not the typical vasomotor symptoms of menopause (hot flushes/night sweats) rather those indicating their poor health, and are often associated with old-age. Ideally, the classic symptoms of menopause subside within a few years after menopause due to body’s internal mechanism to adjust to the natural changes. However, it was seen that among the women under study many of these problems intensified as they progressed to old age affecting their quality of life.

Maternal and child health reflects the level of development of both community as well as the performance of the health care delivery system. Maternal mortality in India, estimated at 437 maternal deaths per 100,000 live births. The existing health system does not sufficiently meet the needs of pregnant women, particularly for complications of pregnancy and obstetrical emergencies. For the present study, Malegaon city has chosen in Maharashtra state where the Muslims form numerical majority (66 percent). The vital statistical indicators for the city, indicates that CBR (28.6) and CDR (8.9) is very high as compared to state average i.e. 9.1 CDR and 18.1 CBR in Maharashtra. Infant mortality (49 per 1,000 live births) is also higher in the city than state average for Muslim (28/1,000 live births). The health systems fail to provide quality of health care services to the people. Both primary as well secondary data will be used for this study. The main objective of the study is to see the availability, pattern of utilization of MCH services among Muslim communities in the study area. Data will be analyzed through SPSS and GIS software and will be presented in graphical and tabular form.

There are two aims in this study. The first is to estimate Healthy life expectancy in Sudan (HLE) using cross-sectional data (2008-2010). The second is to identify the most important risk factors affecting health status of population in the country.
Healthy life expectancies are calculated using models that incorporate measures of mortality and morbidity. Age-specific death rates account for the mortality component. Age-specific rates of population morbidity, disability, or some other aspect of health account for the morbidity component. These two components are combined using a mathematical function that transforms the two sets of partial measures into a single composite measure using a life table methodology.
National mortality data were obtained from two sources, the National Health Statistics (NHS, 2009) of Federal Ministry of Health (FMOH) and fifth population census (CBS, 2008). Health data come from National Health Statistics (2009) of FMOH and the Sudan Household Health Survey (SHHS, 2010).
The life table techniques as well as the binary logistic regression models were used to estimate the (HLE) and to identify the risk factors of health status.
It is expected that a significant difference will be between life expectancy and healthy life expectancy due to the poor health status of population in Sudan.