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Click Here To Order NowHealth, Employment, Gender, and Age
Health, Employment, Gender, and Age
INTRODUCTION
Health is a word that represents different things to different people at different times and different situations. It is a state of psychological, physical, and social well-being, and not just the lack of disease or illness (W.H.O). It is the general condition of a person’s mind and body, usually meaning being free from ailment, pain or injury.
Many people around the world disregard or does not know the significance of good health. When talking about health many people refer to the condition of the body. However, it does not mean being free from the physical pain or free from any disease symptoms. The mind is an important factor during the assessment of a good health (Raphael, 2009).
The significance of good health is not limited to a certain race, religion, gender age, creed or caste. The origin of many diseases can be traced in the mind; a person will be healthy if his or her mind is calm and clear. Many people may feel agitated or unhappy at a psychological level, although they do not have material problems. These are the effects of an unbalanced mind.
What we eat either poisons or nourishes us (White, 2001). Over processed food contain preservatives that act like slow poison. In the modern food handling processes, the emphasis is to the long life of the food. For us to keep our bodies healthy, it is important for us to follow a balanced diet, which consists of fresh vegetable proteins, milk products, beans and dried fruits.
Many factors affect the health of an individual and the community. The environment and the condition one have played a significant role in determining their health status. Broadly the factors that affect the health of an individual are social and economic environment, for example, the income of an individual, physical environment and the person’s characteristics and behaviour (Blaxter, 2010).
The most prevalent of all health problems are the chronic diseases such as stroke, diabetes, cardiovascular diseases and arthritis (Centre for disease control and prevention, 2005a) the prevalence of chronic diseases increase in adulthood, especially late adulthood. For example, heart diseases are more prevalent among people who are 65 years and above (CDC 2005b)
The onset of health problems increases out of pocket health care expenses. For those aged 65 and above and qualify for Medicare, out of pocket increases with the cost of a health condition
Poverty in childhood has a lasting effect limiting life expectancy and worsening health for the rest of the child’s health, even if social conditions subsequently improve. At the same time, health promoting social environments can enhance health status and health outcome at any point across the life course.
Public health has focused on what was believed to be the most prevalent source of mortality, disease injury and disabilities. In late 19th and 20th century, public health concentrated particularly on the physical environment, improvement, for example, clean water supplies, sanitation workplace safety healthier- housing and safe food. This caused an increase in lifetime expectancy.
LITERATURE REVIEW
Health and Employment
Job loss is defined as a life event that removes an individual involuntarily from paid employment (prussia1995). Unemployment is defined as the state of being unengaged in a gainful occupation (Hanish 1999). While job loss is a single event occurring at a fixed point in time, it is a state that lasts over time. Job loss and unemployment form a continuum of experience with the job loss event at one hand and an on-going state of unemployment at the other end (Hanish 199)
A large body of large has studied the relationship between social economic status and health. One stream of research suggests that social economic status is an important determinant of health status because individuals in a lower social are more exposed and vulnerable to psychological risk factors (lifestyle characteristics and living conditions) than those in higher social economic status (Wilson 2001). Other studies have investigated how income is related to cause of death. Results show that there is a strong inverse relationship between income and mortality (Mellor & Milyo 2002). In summary, there is evidence in literature that individuals in low social economic status receive less medical care, are exposed to, and are more vulnerable to risk factors, affecting health status either by direct relationships or by interaction with social status (Rodrigues 2004).
Those in poor health are limited in their ability to accumulate income and wealth because they work fewer hours or are unemployed due to disability (lee &kim 2003 Wu 2003). Employment determines the level of income that an individual attains Smith and Kington (1997) used the assets and health dynamics of the oldest old to study the relationship between health and wealth. The study found evidence that household income is inversely related to health. Specifically, the correlation between current period household income and health reflected a negative causation from health to social economic status rather than the opposite.
Smith1998 used the first three waves of the health and retirement study to examine the two-way interaction employment status and health; he separated new health conditions to study their economic impact. The results of the study provided evidence that the new health events such as the onset of chronic conditions have negative effects on wealth accumulation for those over the age of 50. Smith 1999 examined the size of the association between health and household wealth, out of pocket expenses and total medical expenses. Results indicated that health changes over time could be associated employment.
Some researchers have examined demographic factors that affect the relationship between job loss and negative psychological outcomes. This includes financial strain, the length of unemployment, race, age and education level. These studies have produced no definite evidence to indicate that certain groups demonstrate more psychological distress than others do. In summary the research has yielded non-uniform results regarding the impact of demographic variable on the mental health of unemployed individuals.
For example, studies on older unemployed people have suggested that older workers have more difficulty finding re-employment and suffer greater psychological distress when compared to younger people who are out of work. (Spitzer, 2011), yet other studies indicate that have found that older workers who experience involuntary job loss and subsequent periods of unemployment are able to adjust psychologically to their work life situations better, and maintain their high levels of self-esteem and life satisfaction. (Spitzer, 2011).
GENDER
The gender and health paradoxes are well documented; women live longer than men do, although have higher morbidity rates. Men experience more life threatening chronic diseases and die young, whereas women live longer but have more nonfatal acute and chronic conditions and disability (Bird, & Rieker, 2008). Although men’s and women’s health overall rate of serious mental illness is similar, the most common mental health disorders differ by gender (Bird, & Rieker, 2008). These perplexing patterns raise many questions for social and biomedical scientist and clinicians. At issue is whether the origin of these health differences is physiological, social or both.
In studies of health, a gap still exists around gender differences, and around the issues, this paradox raises about the multifaceted connection between social and biological processes. The studies have failed to assess gender and to explain why rational people are not effectively making health a priority in their everyday lives. Research shows that, the complexity of the gender differences extends beyond narrow concepts of the relative disadvantage or advantage of men and women’s biological or the social organization of their lives.
Neither biological nor social research alone can answer the complex question regarding the antecedents of the puzzling gender differences in health (Bird, & Rieker, 2008). Only a synthesis of this perspective can move forward the much needed interdisciplinary dialogue and investigation to close the knowledge gap (Neun, 2010)
Lois Verbrugge and Deborah Wingard (1987) argued that neither a strictly biomedical interpretation of the data or one based on social factors adequately explains gender based health disparities. The ample data documenting differential in health and mortality. Decades later, little has changed in our understanding of gender based health disparities. Intuitively the answer lies neither in an exclusively biological nor an exclusively sociology vision of reality but in a combination of both (Raphael, 2009).
AGE
Higher rates of ill health are prevalent among people in low economic social status. However, these differences vary with age. The age at which deterioration of health begins varies with the social economic status; the various health condition will start earlier for people with low social economic status. A study conducted by Gortmarker and wise (1997) showed that the old are more exposed to chronic disease like cancer diabetes and cardiovascular disease. It also showed that people who survive to old age are different from those who do not survive.
Social economic disparities in health exist across the whole life course. The gap is largest during early childhood and middle age (siegrist and marmot 2006), at early stages, the poor are associated with high prenatal mortality, infant mortality, prematurity, low birth weight and late birth (gortmaker and wise 1997). At middle age lower social economic status people are associated with high prevalence of heart diseases and high blood pressure, high incidence of diabetes and high prevalence of orthopedic impairment associated with injury (Haan et al 1989). During old age, The physical fragility of human beings becomes a major factor of health (Siegrist and marmot 2006)
HYPOTHESES
One of the hypothesis of the study is that women are more exposed to health conditions than men. The significant differences in gender associated with health conditions are vital for understanding those who are more likely to suffer from various health condition. As Bird & Rieker, (2008) study showed, women live longer than men yet they have higher morbidity rates. Men experience more life threatening chronic diseases and die young, whereas women live longer but have more nonfatal acute and chronic conditions and disability. (Bird, & Rieker, 2008).
The second hypothesis is that the old are more exposed to health condition various health conditions than the young and the youthful. As the study conducted by (Gortmarker and wise 1997) showed, the old are more exposed to chronic disease like cancer diabetes and cardiovascular disease
The third hypothesis is that those who are unemployed are more likely to suffer various health conditions than those who are employed. Studies have shown an inverse relationship between health and employment. Those who are unemployed are more likely to suffer from psychological distress. Those who are employed and suffer from various health conditions are unable to accumulate enough wealth to cater for their health needs.
Methods
Participants
This study was conducted by Harvard school of public health it collected responses from a pool of U.S households. This was done through a general social survey. The target sample size for GSS was 10000 until 1998. It was later increased to 2500 in 1999. Each survey was an independently drawn sample of English speaking persons 18 years of age or over, living in non-institutional households within the United States
Materials
The survey would involve a series of questions for participants regarding their health conditions. The questions used to determine the dependent variable health status. The survey also asked for demographic information including age, and whether one was employed or not. Responses include age, in years; gender as male or female and responses to status employment include either full time or part time employment
Procedures
SPSS software was used to analyze the collected data from the households. Missing cases were deleted from the data, and all variables were recorded to two decimal places to produce contingency tables for the statistical analysis. Approximately 71 per cent responded to the survey questions. The order in which the procedures were conducted began with the use of analytic functions, to generate the frequency tables to describe the sample. Next, the cross tabs function was used to generate contingency tables, followed by the use of chi-square statistics function to test the null hypothesis for each independent variable.
Results
Frequency tables were used to determine the results on the health conditions it describes the health condition of the individuals who participated in this study. The study revealed that, of the total 1278 examined 25.4 per cent had an excellent health condition, 46.1% had good health conditions while 22.7% and 5.8% had a fair and poor health conditions respectively.
Responses on the independent variable on the status of employment indicate that, of the total respondent of 4901, only 1402 were valid responses. Of the valid responses, 75.9% were in full time employment while 24.1% were part time employed. 74% of the responses were either missing or invalid.
The second independent variable was based on gender; the total valid responses were 2044. Of the total valid responses, 43.6% were male, and 56.4 % were females. Invalid responses were 2857 this represented 58.3 % of the total responses.
The third independent variable was age. There was a 41.6 % valid response to this independent variable. Of the valid responses, 2.8% were within 1-20 age brackets; this was a total of 58 people. Thirty five per cent were within 21-40 age bracket while 36.9%, 20.6% and 4.6% of the valid responses, were within 41-60, 61-80 and 61-80 age brackets respectively.
First, there is a hypothesis that women are more exposed to health conditions than men are. The number observed for females were more than those observed in the males were. Of the total male responses 25.4% reported an excellent health condition, 49.2% reported a good health condition while 19.7% and 5.7% reported a fair and poor health condition respectively. Of the total valid female responses on the dependent, 25.5% reported an excellent health condition, 43.5% reported a good health condition, 25.2% and 5.9% reported a fair and poor health condition respectively.
The Pearson chi square test indicated a value of 6.479, the likelihood ratio was 6,515 and the linear by linear association was 1.482.
The second hypothesis was that the old are more exposed to health conditions than the young are. The per cent of the age group 1-20 that reported an excellent health condition. While 60%, 20%, and zero per cent reported a good fair and poor health conditions respectively. For the age group between 21 and 40, 31.1% reported an excellent health condition, while 46.4% 20.6% and 1.7% reported a good, fair and poor health conditions respectively. 25.1% of the people within 41-60 age range reported an excellent health condition while 46.5%, 20.6% and 7.8% reported a good, fair and a poor health condition. The per cent dropped to 18.6% for the age group within 61-80 age brackets. Those reporting a good, fair and a poor health conditions were 45.8%, 26.5% and 9.1% respectively. The final age group was 81-100. For this age group, 13.7% reported an excellent health condition while 35.3%, 41.2% and 9.8% reported a good fair and poor health condition.
It is clear from the results that the old reported higher percentages of poor and fair health condition than the young did. For example, age group 81-100 reported a 9.8% poor health condition while those below 20 years reported zero per cent poor health condition.
The Pearson chi – square was 51.186 while the likelihood ratio was 55.412. The linear by linear association was 37.011
The third hypothesis was that the unemployed are exposed to more health conditions than the employed. Of the total respondents that were employed 27.7% reported an excellent health condition while 51.4% , 18% and 2.9% reported a good , fair and poor health conditions. The percentage of part time workers that reported an excellent health condition was 31% while 48% 19%and 2% reported a good, fair and a poor health conditions respectively. The Pearson chi square was 1.481%, the likelihood ratio was 1.504 while the linear-by-linear association was 0.43.
Discussion
Nobody wants to feel the discomfort associated with any disease, actually, most people fear pain and death and discomforts associated with diseases. There is more to being healthy than avoiding death and pain. Health is a pillar of having a successful life, accomplished life and being happy. It is therefore important that one should avoid diseases as much as possible.
The first hypothesis of this study is that women are more exposed to health conditions than men are). Comparing the responses of both men and women, both reported almost the same percentage of excellent health condition, but men reported a higher percentage of good health condition than the women did. On the other end, both men and women reported almost a similar percentage of poor health condition. These results may therefore be not sufficient to conclude that women are more exposed to health conditions than men are.
The second hypothesis was that the old are more exposed to more health conditions than the young are. A closer look on the results reveals that the percentage of individuals reporting an excellent health condition decrease as age increased. The same applies to those reporting a good health condition. However, there was a direct relationship between those reporting a fair health condition and age. In addition, the percentage of those reporting a poor health condition increased as the age increased. The above statistics therefore prove that the old are more vulnerable to various health conditions.
The third hypothesis was that the unemployed are more likely to be exposed to health conditions. From the results only 27.7% of the respondent whore are fully employed, reported an excellent health condition, compared to31% who are part-time employee. At the other extreme end the percentage of full time workers that reported a poor health condition was, 2.9% compared to a 2% of the part time employees. It is therefore still hard to conclude that the unemployed are more exposed to health conditions.
References
Cutler, D. M., & Wise, D. A. (2008). Health at older ages: The causes and consequences of declining disability among the elderly. Chicago: University of Chicago Press.
Bird, C. E., & Rieker, P. P. (2008). Gender and health: The effects of constrained choices and social policies. Cambridge: Cambridge University Press.
Raphael, D. (2009). Social determinants of health: Canadian perspectives. Toronto: Canadian Scholar’s Press.
Spitzer, D. L. (2011). Engendering migrant health: Canadian perspectives. Toronto: University of Toronto Press.
White, L. (2001). Foundations of nursing: Caring for the whole person. Albany, N.Y: Delmar/Thomson Learning.
Davis, J.A. and Smith, T. W. (2011) General social surveys, 1972-2010 [machine-readable data file]
Santerre, R. E., & Neun, S. P. (2010). Health economics: Theories, insights, and industry studies. Mason (Ohio: South-Western Cengage Learning.
Blaxter, M. (2010). Health. Cambridge, UK: Polity.
Marmot, M. G., Wilkinson, R., & World Health Organization. (2003). The solid facts: Social determinants of health. Copenhagen: Centre for Urban Health, World Health Organization.
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