In this assignment, I will be writing about the patterns and trends in health and illness among different social groups. I will be writing about how health is measured and the difficulties that could occur while measuring health. The social groups that I will be writing about are social class, gender, ethnicity, age, and locality.
When measuring the trends of health in health and illness there are three different ways to measure these: government statistics, charitable organizations pressure groups academic researchers, and other authors.
Academic researchers and other authors when measuring trends in health and illness base their statistics and research on places like universities.
Charitable organizations and pressure groups when measuring trends in health and illness collect their data and publish them on different websites. An example of a website where you can find published statistics of these kinds is www.mind.org.uk.
Government statistics when looking at trends of health and illness come from work and research done by the Office of National Statistics. They provide information on a lot of different healthcare issues. Some of these include birth rates, death rates, infant mortality rates, suicide rates, morbidity rates, and appointments at GP surgeries and hospitals. They look at the trends over some time whilst considering different social factors that could affect these trends. Some of the social factors that they look at are age, sex, geographical location, and social class. The mortality rates used in government statistics are from official death certificates. Morbidity rates that are used in government statistics come from GPs, hospital appointments, hospital admissions, and registrations of notifiable diseases.
When measuring patterns and trends in different social groupings difficulties can take place. I will now be writing about some of the difficulties that can take place. One difficulty in measuring health is that when looking at morbidity rates and how the statistics for them are collected it might not be accurate because not all people go to the doctors or a hospital when they get an illness, a lot of people just stay home and recover using over the counter medicine. When looking at the patterns and trends for the number of people with a specific disease difficulties could take place because if they go to two different doctors and tell the two different doctors their symptoms each doctor may diagnose them with a different illness and that would impact the statistics. The clinical iceberg is very important in the discussion of difficulties in measuring health. The clinical iceberg is the official statistics on levels of illness because people believe that the true levels of illness are not disclosed because of things like not all ill people going to see a doctor or go to the hospital. This is the same for the causes of death.
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When looking at social class and patterns and trends of health and illness it is believed that depending on the social class the statistics for ill-health and life expectancy will be different. It is most likely that people in the higher classes will have a longer life expectancy because of access to private health and expensive medicines. The Black Report (1980) provided information on the reasons why statistics were different in different social classes. The Black report has four explanations for reasons as to why there might be a difference in levels of illness and life expectancy in the different social classes. These are:
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- The statistical artifact explanation
- Natural or social selection
- Cultural or behavioral explanations
- Material or structural explanations.
I will be writing about each of these explanations.
The statistical artifact explanation believes that the differences are because of the age in each of the social classes. The explanation is that there are more elderly people in the lower classes and people working in dangerous jobs so this is the reason why there are a difference in levels of illness and life expectancy in the different social classes.
Natural or social selection aims to prove that people are in the lower classes of society because of poor health. They believe that because of poor health people are not able to succeed academically and therefore they will become part of the lower class in society.
The cultural or behavioral explanation believes in the choices of people and therefore this explanation believes that the reason for the difference in levels of illness and life expectancy among the different classes is that the lower class makes bad choices and chooses to smoke and drink a lot.
The material or structural explanation believes that the difference in levels of illness and life expectancy between the higher and the lower classes is because of the wealth divide and the difference in income between both of these groups. This means that the lower class will have poor diets, poor housing, and poor environments leading to more illness and a shorter life expectancy.
When looking at gender and patterns and trends of health and illness it is believed that women have higher life expectancy than men with women living up to around five years longer than men although women are more prone to illness and for babies mortality rates for babies boys are higher than baby girls. There are three different social factors that contribute to these differences these are:
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- Risk factors
- Economic inequalities
- The impact of the female role
I will now be writing about all of these factors and how they contribute to these differences. It is believed that the risk factors that contribute to the higher death rate of men are because men are seen to take more risks in life and men tend to smoke and drink more than women. This is statistically proven in England in 2018 16.4% of men were reported to be smoking compared to 12.6% of women. The economic inequalities show that even though there are laws promoting equality between men and women, they are still not paid equally. Statistics show that after 3 years of graduating 40% of men were earning over £25,000 a year compared to 26% of women. The last factor I will be writing about is the Impact of the female role. Women have more responsibility than men for doing housework and this could result in depression. Women often have to live on a budget and have to work long hours with little time for rest. A factor that contributes to the longer life expectancy of women is that even though women have higher rates of stress-related illnesses, they are more willing to speak about these problems with their doctors so that they can get help.
When looking at ethnicity and patterns and trends of health and illness there is a big focus on living areas, about health and illness. People believe that individuals from minority ethnic groups live in deprived areas with housing that is not good and high rates of pollution and this can cause things like asthma. This is why some people believe that people of minority ethnic groups have poor health because of the poverty they are living in. Statistics show that Asian children have a high chance of getting rickets. Another factor that affects health and illness ethnicity is because things like religion and cultural beliefs are not being understood or accepted this could affect whether the individual can get medical help or not. Language barriers are also another factor that affect the patterns and trends of health and illness, this is because people may not be able to relay what is wrong with them so they may not be able to get diagnosed or get help.
When looking at age about the patterns and trends of health and illness there is a lot of focus on the older members of society and this is because of their age they are most likely to get more illnesses and diseases like dementia and Alzheimers. This was statistically proven in 2007 when a survey proved that 1 in 5 people over the age of 80 have dementia. The elderly people are more likely to need to go to the hospital for minor illnesses like colds because they have a weak immune system so if they do not seek medical help it can lead to things like pneumonia.
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Essay on Importance of Statistics in Healthcare.
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