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Seminar Paper, 2017
13 Pages, Grade: A
What is morbidity?
Review of literature
Data source and methodology
Short term morbidity
Long term diseases are our own creation. Most men are unable to resist the work-holism, sedentary living environment, blind pleasure psychosis, suffocating dispositions, exchanging conscience and faith with wealth, consumption-based happiness indices, the absence of regular sleep, leisure, socializing, taking junk food, and finally the mad march against indomitable time. The India is ageing, it is natural and inevitable so, the risk of having, at least, one chronic disease, such as hypertension, diabetes, arthritis, cancers, T.B, B.P increases with age, this is not so much a function of chronological age per se but a reflection of the life-long accumulation of risk factors.
Morbidity is measured by the World Health Organisation (WHO) using DALYs (Disability Adjusted Life Years), the amount of life left due to disease or conditions. Globally, morbidity is higher in LEDCs than MEDCs. In MEDCs, the primary source of morbidity is from disease due to poor lifestyles and diseases from old age. The survival rate from these diseases is much higher in MEDCs too. The major sources of morbidity in LEDCs are prenatal conditions, Cancer, heart desires, B.P and TB with much lower survival rates. Morbidity is affected by certain risk factors. In these factors are malnutrition, social diseases (i.e. T.B, AIDS), unsanitary hygiene & living conditions, a lack of clean water and poor living standards. In these main factors are blood pressure, as a lack of physical activity and lifestyle choices such as a smoking, alcohol, tobacco and poor diets. Morbidity is effect of human life diesgur, so fithealthy life is the growth of medicine treatment.
Improving health status around the world today is an important social objective, which has obvious direct payoffs in terms of longer and better lives for millions. There is also a growing consensus that improving health can have equally large indirect payoffs through accelerating economic growth. Population ageing is escorted by the “epidemiological transition” – a shift in the patterns of morbidity and the causes of mortality.
Today India is facing a dual burden of communicable and non-communicable diseases where nutrition and other life style factors play important roles. Population living in metropolitan areas are more prone to such morbidities because of environmental factor and life style. Loss of life and morbidity are important components of human welfare. Connections between mortality and morbidity are an area of wider discussions in the present Indian context. The current health scenario in India is often described as “dismal” or “disturbing”. Even though the life expectancy of Indian has increased in the last few decades, the level of morbidity is still in pathetic condition. Socially advanced metropolitan like Mumbai, Punjab and West Bengal have lower infant mortality and greater life expectancy for its people, but in contrast, have high morbidity rate also contrary to that morbidity rate is low in states like Bihar, Madhya Pradesh and Rajasthan, Orissa Uttar Pradesh (BIMARU state). One of the major reasons put forwarded the low-level achievement in health in India is the systematic lack of investment by the government, which adversely affects the poor. This may be due to the fact that states which are economically and educationally well off early report their ailments, and will be more vulnerable to life style related diseases.
Morbidity is an incidence of ill- health.
Morbidity can be calculated as
Morbidity measures are of two fundamental types
1) Self perceived morbidity- refers to measures that are perceived and reported by an individual, usually in response to inquiries illness. It depends upon an individual’s perception of illness.
2) Observed morbidity- is assessed through an independent observer employing specific methods that can be repeated with some degree of consistency.
Lifestyle is a multidimensional concept that is difficult to capture in a single measure. Conventional indicators such as infant mortality rate or life expectancy at birth, anthropometric measures or nutritional status are generally used to measure the health status of the population since they are comparatively simple to analyse and data is easily available (Indian human development survey). However, in recent times, many studies have used self-reported illness to measure health status because of its consistent relationships with future mortality in India.
The study reveals that morbidity pattern has a significant association with BMI. It stresses the growing need to prevent obesity to control the morbidity and mortality among the potential age groups. Padma kumar (2007) observes that the lifestyle of the population changed a lot mostly in the 19th and 20th century, leading to changes in health status. These changes are not always for the good. Due to change in life style, to Hazira (2010), physical activity is declining along with growing affluence. Fast food becomes more prevalent in urban areas. Changing lifestyle causes in the number of cases of coronary heart diseases. Ageing of the population in any cases is giving fuse to a steep increase in the incidence of many chronic diseases, some of which are triggered by an adverse lifestyle.
Ratnani (2008) finds that genetic factors predispose certain people to diabetes. He suggests diet and exercise can determine whether those genetic factors actually manifest in the diseases. Heredity is like a cannon and obesity pulls the trigger. So knowledge about these differences is of particular importance, so that people can take precaution.
1) To assess the long term morbidity among the residents of metropolitan areas.
2) To assess the Short term morbidity among the residents of metropolitan areas.
For this study, IHDS-2 (2011-12) is used. As the title of the paper suggests, the study is restricted to six metropolitan samples. The metropolitan areas are Kolkata, Delhi, Chennai, Mumbai, Bangalore and Hyderabad. Because, the people in the metropolitan areas willingly or unwillingly have to follow sedentary life style. Further, only the sample belonging to the age group 15 -59 years are retained for the analysis. It is done indirectly to understand the how the morbidity may affect the economic condition of the population. The total sample retained for the analysis is 11895. However, data relating to smoking and drinking are available only for 2059 samples.
Result (table 1) presents percentage of substance use by background characteristics. In this study smoking cigarette, chewing tobacco, drinking alcohol and smoking bidi/hookah are considered as using substance. Percentage of smoking, drinking and smoking bidi/hookah is significantly higher among male than that of female. But chewing tobacco is higher for female. Percentage of smokers and drinkers are comparatively higher in the middle age group (30-34). But the percentage of tobacco users is highest among the youngest age group (15-29), whereas smoking bidi/hookah is highest among the older age group (45-59). Use of substance – cigarette - is found to be increasing with the level of education, whereas it is completely opposite for smoking bidi/hookah. No clear pattern is observed with education and drinking alcohol and chewing tobacco.
Percentage of smokers and drinking alcohol are higher among the never married respondents than people from other marital status. Drinking is highest among the divorced/widowed. Chewing tobacco is highest among the divorced/widowed. Smoking is found to be highest among Hindus. Use of tobacco is highest among the ‘other’ (other than Hindu or Muslim) religious group.
Use of substance – cigarette – is highest among the people in the technical occupation, whereas smoking bidi/hookah is maximum among the farmers. The use of substance by owning number of assets (table 1) shows that with the increase in number of assets, the percentage of smokers increase, whereas there is no distinct inverse relation with smoking bidi/hookah. But no distinct pattern is observed between number of assets and use of tobacco and drinking alcohol.
IHDS provides information on major morbidity like high blood pressure, cancer, heart disease and tuberculosis. It is found that (table -2) percentage of female suffering from high blood pressure is higher than male. With the increase in age, the percentage of people suffering from all the types of morbidity increases. Result shows that percentage of respondents belonging to Islam religion is slightly higher than other religion. It is found that percentage of respondents suffering from any of the four major diseases is highest among the respondent with highest level of education. Percentage of people suffering from blood pressure problem is highest among divorced/ widowed and having any major morbidity is also highest among this group. Percentage of having any major morbidity is marginally highest among the middle income group.
While trying to find out the percentage of respondents by different metropolitan areas, it is found that percentage of people suffering from any major disease is highest in Kolkata, followed by Hyderabad, whereas it is lowest in Mumbai.
In the present study, having fever in last 30 days, having cough in last 30 days and having diarrhoea is considered as having any short term morbidity. Result (table 4) shows that percentage of people suffering from short term morbidity is highest among the older age people (45 – 49 years). Substantially higher percentage of female has reported to have suffered from short term morbidity. There is a distinct inverse relationship between short term morbidity and level of education. With the increase in level of education, the percentage of people having short term morbidity declines. Divorced/ widowed are found to have more short term morbidity. Relationship between numbers of household assets (proxy for economic condition) shows that with the improvement in economic condition percentage of people suffering from short term morbidity declines. A person suffering from any short term morbidity is found in Hyderabad followed by Kolkata, whereas it is lowest in Chennai.
Result of multivariate analysis – binary logistic regression – shows that compared to younger people (15-29 years), older people are more likely suffer from short term morbidity. Compared to male, female are more likely to face the problem of short term ailment. Compared to illiterate people, respondent with some level of education are less likely to suffer from any short term ailment. Compared to currently married people, widowed are more likely to have short term morbidity. It is found that compared to Mumbai sample, respondents from Delhi, Kolkata, Bangalore and Hyderabad are more likely to have short term morbidity, whereas it is opposite for Chennai. It means, compared to Mumbai, people from Chennai is less likely suffered from short term morbidity.
Our findings indicate high level of morbidity condition relating to life style or substance use among the residents of metropolitan areas in India. Smoking tobacco, chewing tobacco, and drinking alcohol are quite prevalent. The presence of such a high burden of the risk factors among participants of urban metro population is observed. It requires urgent interventions in order to prevent and control the further morbidity burden of non-communicable diseases.
Most of these risk factors are modifiable and can be improved. Patients with T.B and B.P may be suggested to adopt a healthy life style such as reducing daily salt and, quitting smoking and engaging in more physical activities. Furthermore safe walking tracks, playgrounds, and relaxation avenues should also be made available to allow more people to engage in physical activities and relaxation programs. Besides this, screening the community for presence of cancer is necessary. Kolkata and Hyderabad has high prevalence of the problem of blood pressure, and their proper and tamely intervention can definitely reduce the morbidity and mortality from this disease.
This study shows that compared to younger people (15-29 years), older people are more likely suffer from short term morbidity in the Metropolitan areas in India. In metropolitan areas of India, female are more likely to face the problem of short term ailment. Compared to currently married people, widowed are more likely to report to suffer from short term morbidity. It is found that compared to Mumbai sample, respondents from Delhi, Kolkata, Bangalore and Hyderabad are more likely to have short term morbidity, whereas it is opposite for Chennai. It means, compared to Mumbai, people from Chennai is less likely suffered from short term morbidity.
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Table No-1:Percentage of respondent with long term morbidity and background characteristics
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Table No-2:Percentage distributions of respondents by short term morbidity
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Table No: 3 Percentage of respondents by short term morbidity and background characteristics
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Table No-4: Results of binary logistic regression
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