Essay On Cross County Mortality Disparities

For the past two decades Utah County has been ranked among those US counties with healthiest populations. In spite of this, assessment on life expectancy of the inhabitants of Utah State shows that some problems have cropped into the local occupants depriving them of their once notable rich health status (Novilla, Barnes, Hanson, West & Edwards, 2011). A close examination shows that there are inherent health disparities among Utah citizens and this is as a result of the notable variations in life expectancies among different groups. Research shows that in some parts of the Utah state, life expectancy is 80 years while in the other areas within the same state the life expectancy is 70 years. Research shows that Utah ranking

People were less likely to face poor retirement if they worked in managerial or professional jobs than someone who worked in unskilled or manual occupations. This is because the people who worked in manual would have earned lower wages and would not be as likely to get a private pension. Men that are in the professional classes have a life expectancy of 80 years from birth. However men from unskilled or manual classes have a life expectancy of 78.1 years. This also effects woman’s life expectancy as woman from professional classes have a life expectancy of 85.1 compared to those who are in the unskilled or manual classes and their life expectancy if 78.1 years. Causes of death also vary from different social classes. In the higher social classes it is less likely to suffer from, lung cancer, coronary heart disease, stokes and respiratory diseases. All of these increase within social disadvantages.

These disparities are obvious in some key measures of wellbeing including life expectancy, the risk for disease, and access to health care (Disparities in Health, 2015). Historically, the major factors contributing to shorter longevity and high rates of disease are overcrowding, poor sanitation and low availability of treatment facilities. However, the change of theses socioeconomic

One of the major obstacles for researchers in the field of Health Psychology and Aging is understanding the role of health disparities across different populations. Health disparities can be understood in terms of differences in some facet of health and well-being across different groups of people. The issue of health disparities across different populations is one that must be understood not only in the context of genetic and biological factors, but also in the context of a broader sociocultural perspective. The influence of health disparities are implied in the context of aging, but are discussed across the entire lifespan. The existence of health disparities in later life is often a product of a lifelong experience and life-course trajectory. This essay will address some of the major

First, there is Jim Taylor, Hospital CEO, District 16; second, Tondra Young, Clinical Lab Supervisor, District 24; lastly, Corey Anderson, Floor Technician, District 21. The population of each district decreases in average income, education level and life expectancy than its preceding district, beginning with district 16, Jim Taylor’s district. District 16 has an average combined household income of approximately $120,000/ annually. In this district, 65% of the population has a college degree and the life expectancy in this district is 82 years. Whereas, Tondra Young’s district, district 24, has an average combined household income of $70,000/annually and 15% of the population has a college degree. The life expectancy of district 24 is 75 years, that’s 7 years less than district 16. In district 21, Corey Anderson’s district, the average combined household income is less than $50,000/ annually and only 5% of the districts population have college degrees. Consequently, the life expectancy of district 21 is 70 years, 5 years less than district 24 and 12 years less than district 16 (Adelman 2008). The results of this study are indisputable: there is an obvious correlation between social/economic status and health status. As each districts average income and education level decrease, average life expectancy coincides. This leads to the next question: why does social and economic status so greatly influence health status?

Life expectancy, or the estimated years of life for a person or group of people, has increased over the years but it is still surprisingly lower than expected in places such as the United States. America ranks twenty-fourth on the life expectancy list under Japan, Australia, France Spain and Italy. What causes this disparity in the ranking and statistics in an advanced industrialized society such as the United States? There are major statistical factors that influence the United States ranking in world life expectancy, involving education level, poverty, race and gender. The diverse groups of people living in the United States affect the health statistics negatively, bringing in influences from education and income levels, race and

Theory Based Health Interventions applying Health Belief Model and Theory of Planned Behavior/Reasoned Action to the prevention of HIV and STDs

The United States is one of the countries profoundly affected by health disparities and inequities. One may argue this is attributable to its diverse ethnic and racial groups and wide geographical area coverage, but still, it is extremely undesirable to record that extent of health disparities and inequities. The 78.8 years life expectancy is just the average. Some states have a life expectancy of high as 86 years whereas as low as 68 years. The standard deviation of life expectancy across the states is very huge. For instance, the life expectancy in Summit County, Colorado is 86.6 years whereas in Oglala Lakota County, South Dakota, the life expectancy is 66.8 years (Welch, 2017). A margin of about 20 years is troubling, especially for a developed country like the United States. These disparities also apply for other health indices from region to region and ethnic group to another. Hence, this agenda is on the right

It is evident that life expectancy rate - a major indicator of population health- varies amongst different tiers of socio-economic status. This is because, According to statistic Canada, Canadian women in the lowest income group experience life expectancy that is 3.2 years less than those in the highest income group whereas, Canadian men in the lowest income group, experience a life expectancy rate that is 4.7 years less than those in the highest income group(Mcmullin, J., Davis, L, 2010, Pg. 188). This goes to show that those with higher Socio-economic class get live longer compared to those with lower socio-economic class. Another social determinant of health outcomes amongst different groups of people is education. In Canada, a percentage

People often talk of a battle between the sexes, but women have the last laugh on men when it comes to how long we live. This advantage in lifespan was not always so pronounced, however. An article in realclearscience.com reveals that for men and women born in the early to mid 1800s, the mortality rate of men to women was around 1.2 when looking at the numbers of each who died at age 60. This means 120 men dieing at that age for every 100 women. By the end of the 19th century, however, this mortality ratio had climbed to 1.6 and it was over 2 by through the early 20th century. It is believed that heart disease and smoking together were the main cause of the difference as men were both more likely to smoke and to get heart disease.

A report published by the Orgainsation for Economic Co-operation and Development (OECD) identifies lifespan as key societal wellness barometer. [1] The group is a forum created to improve financial, physical and mental wellbeing for all global citizens. [2] Through the organization, governments collaborate to improve the human condition. Using data gathered from various global sources, the group members make recommendations designed to improve humanity’s welfare. The research scope varies from high-level census data to detailed worldwide tax rates. Among these data, the organization recognizes remarkable improvements in human life expectancy over the last half century, which is now 80-years long. [1]

In this segment our paper we chose the year 2014 due to the amount of reliable information currently available for both countries. For comparison purposes we will begin with presenting a variety of demographic statistics about the United States. In 2014 the United States had a population of approximately 318 million people and an estimated GDP of $17.3 trillion dollars. That very same year, health expenditure in the United States totaled an astonishing $9,024 per capita, which was approximately 16.6% of GDP. This was the highest amongst OECD countries with Switzerland having the second highest heath expenditure of $6,787 per capita (OECD, 2016). One could easily assume that increased health expenditure would equate to longer life expectancy. However, in 2014 life expectancy in the United States was 78.8 years as opposed to 83.3 years in Switzerland (OECD, 2016). As we look further into the total health spending of the United States for 2014, publicly funded health insurance accounted for 49.3% of health spending. Privately funded health insurance (provided through employers) 39.2% of health spending and out-of-pocket spending accounted for the remaining 0.2% of health spending (OECD, 2016).

The life in the U.S compared to that of the Soviet Union during the 60’s is an amazing phenomenon of a declining life expectancy in a highly developed country just like in the case of the Soviet Union during the 60’s down to the 70’s. The result of the life expectancy rate in the Soviet Union shows that there is only a small part to true informal changes in the state of living. However, the weak point of the measures of life expectancy is of vital importance, although another factor is the unfavourable selection of risks by war, thereby making a less valuable comparison between the international and inter temporal. Another factor is the logical difference between period and the measurement of the group of people sharing a common factor

When considering health psychology it is important to recognise the various models it is made up of. The basis of this essay will be to take a look at the health belief model and the theory of planned behaviour, considering their historical origins, the positives and negatives of applying these approaches and examples of when they have been used. After some analysis it may offer some insight into possible improvements that could be implemented from further research. Also included will be an overview of how the models compare to each other and critical evaluation of research from this field.

From Week 4 lecture, I have learnt about the Theory of Planned Behaviour. Initially, I thought that if a person intend to do something, they will put in their best effort to do it. However, I realized that I was wrong because ‘intention does not always accurately predict behaviour when there is a reflex or conditioned response involved.’(Long-Crowell, 2003) For example, ‘my friend with a phobia may intend to stay calm and collected when faced with their fear, but may end up having a panic attack instead.’(Long-Crowell, 2003) After this lecture, I have learnt that this theory explores the relationship between attitudes and behaviour. A person who have the intention to change is determined by attitude, subjective norms and perceived behavioural control. For example, a person who know about the negative effects are more willing to quit smoking.