| Abstract|| |
To achieve MDGs, it is important to understand ailing and hospitalization that occurs in India. In this regard, data were used from two surveys of NSSO's, i.e., 52 nd round and 60 th round which were collected in 1995-1996 and 2004. Some research has been carried out to examine ailing and hospitalization, but, they were only village level/district level or state level studies. Studies on ailing and hospitalization for all India are few. There are a number of factors that influence ailing and hospitalization such as demographic (age, sex, and residence), social (religion, social group, and marital status), household (structure, source of drinking water, water treatment, and availability of latrine, drainage facility, and source of energy for cooking), and economic (education, activity status, and landholding). Multivariate analyses were used for examining the relationships. The overall odds ratio of logistic regression shows that the Hindus, never married people have higher chance of ailing and hospitalization in India. As expected young males residing in urban areas have lower chance of ailing and hospitalization. Southern and western people of India were more likely to be ailing and hospitalized than persons in other parts of India.
Keywords: Ailing, morbidity, treatment and hospitalization
|How to cite this article:|
Prasad S. Morbidity pattern and treatment in India. Ann Trop Med Public Health 2012;5:458-67
| Introduction|| |
There are eight UN's millennium development goals (MDGs) to be achieved by 2015 that represent the world's main development challenges. Out of eight goals, three goals 4, 5, and 6 are related to health, i.e., reduce child mortality, improve maternal health, and combat HIV/AIDS, malaria and other diseases. The targets of these goals is to reduce by two thirds, between 1990 and 2015, the under-five mortality rate, reduce by three quarters, between 1990 and 2015, maternal mortality ratio, and halt by 2015 and begun to reverse the spread of HIV/AIDS. There are three indicators for monitoring progress to reduce child mortality rate, i.e., under-five mortality rate, infant mortality rate, and proportion of one-year-old children immunized against measles, and two indicators to improve maternal health, i.e., maternal mortality ratio, and proportion of births attended by skilled health personnel. Similarly, indicators for monitoring progress to combat HIV/AIDS, malaria, and other diseases-HIV prevalence among pregnant women ages 15-24, condom use rate of the contraceptive prevalence rate (condom use at last high-risk sex, and percentage of 15-24 year olds with comprehensive correct knowledge of HIV/AIDS), and ratio of school attendance of orphans to school attendance of non-orphans ages 10-14.
According to present data that are available from Sample Registration System,  infant mortality rate (IMR) is high in the rural areas (55 per 1000 live births) than in urban areas (34 per 1000 live births). There are six regions of India-north, central, east, north-east, west and south. The highest death rate was reported in the central parts of India followed by eastern part. In the central region, Madhya Pradesh has highest (67 per 1000 live births) Infant Mortality Rate (IMR) whereas in the eastern region the state of Orissa (now Odisha) has the highest IMR (65 per 1000 live births). In north India highest IMR is in the Rajasthan (59 per 1000 live births), whereas it is highest in the Andhra Pradesh (49 per 1000 live births) in the south region. The IMR is highest in the Assam (61 per 1000 live births) followed by in Meghalaya (59 per 1000 live births) in the north-east region. The IMR is high in the state of Gujarat in the western region (48 per 1000 live births). These IMRs have come down compared to last five years. However, in order to achieve MDGs, it is important to reduce morbidity and hospitalization in India. National Sample Survey (NSS) Data which I analyzed in this paper on ailing and hospitalization for whole country are available in two rounds surveys, i.e., 52 nd (1998-99) and 60 th (2006). ,
According to the survey, as given in [Table 1], there were 1.4% and 2.4% of the population hospitalized during 365 days before the survey. And majority (90.1%) of them was recorded as one time hospitalized, and rests were two and more than two times hospitalized. There were 24.6% and 19.5% in earlier survey (52 nd round) and 30.1% and 36.0% in later survey (60 th round) were ailing one day and 15 days before the survey, respectively.
|Table 1: Percentage reporting hospitalized and ailing in India, 1995-96 and 2004|
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It has been noted that ailing is higher than hospitalization in India. According to NSSO an ailment may not cause any necessity of hospitalization, confinement to bed or restricted activity. An ailing member is a normal member of the household who was suffering from any ailment during the reference period. And admission for treatment of ailment and discharge thereof from the hospital will be considered as case of hospitalization irrespective of the duration of stay in the hospital. It may also be noted that hospitalization in the cases of normal pregnancy and childbirth will not be treated as hospitalization cases.
Ailing and hospitalization are influenced by various factors. These factors are demographic, social, household, economic and regional factor. The demographic factors such as age, sex, and residence status influence the ailing and hospitalization. For example, Ghosh  showed that prevalence of acute respiratory infection (ARI) and malaria is higher in rural residence than urban. Male child suffer more than female children.  Yuan et al.,  studied that hospitalization rate was high among 12 years children due to any asthma. Joshi et al.,  also showed that elderly had more morbidity and were more distressed physically, psychologically, or both. The hospitalization and morbidity rate was higher among the older age population in rural areas in small households.  Among middle aged women there were more hospitalizations for gallbladder disease.  Female had more cardiovascular diseases than male counterparts of similar age.  In urban areas, males are significantly higher suffered from Tuberculosis (TB) than females, and males living in poor conditions is over three times more as compared to males with high standard of living while two and half times more among females with lower standard of living group. 
Differential disease pattern and hospitalization were found by religion and marital status (social factor). The prevalence of infectious diseases was higher among non-Hindu persons.  According to Swain et al.,  jaundice was not significantly different from currently married and prevalence of asthma was higher among widows. Children of Christian mothers were somewhat more likely to have suffered from ARI than other children in Zimbabwe. 
Some of the studies show that type of structure, type of latrine, drainage facilities, source of drinking water, water treatment, and energy for fuel is the major cause of diseases and hospitalization (household factor). Sharma et al.  studied that poor people and Schedule Tribes (STs) in rural residence are more vulnerable to tuberculosis because of living and working conditions. Oxygen is required for blood purification and blood circulation. It also affects digestion and nutrient absorption. The indoor air pollution is a chief cause of morbidity among children and women. Energy for cooking used in household is also influence ailing. Mishra  observed that children in households using wood, dung or straw for cooking were more than twice as likely to have suffered from ARI as children from households used LPG/natural gas or electricity. Similar study also showed that moderate-to-severe anemia was higher among the children in households used bio-fuels than among children in households used cleaner fuels.  Stored drinking water into tanks and presence of animals in the household environment attracts mosquitoes and this is the main cause of Chikungunia disease in the Kerala.  The diarrhea and shigellosis are water borne disease and it was found in the urban areas where open drainage system and damage pipeline of water supply, and the density of cases decreased as the distance from the leak increased. 
Education level, labor activity status, and landholding (economic factor), affected ailing and hospitalization. Literatures show that those who illiterate and those in labor forces have higher incidence of hospitalization. The ILO (2005) reported the highest incidence rate of injury; conjunctivitis and burn were among the labor force. The labor engaged in bleaching, calendaring, dying and sizing, and power loom suffered from fever, cough, and eye sore.  Studies also show that those who have large landholding the rate of incidence of health problem than small and medium farmers. Mother's education influence prevalence of ARI among the children.  Higher standard of living (SLI) and higher level of women's education were inversely associated with common mental disorders (CMDs) in rural areas. 
The ailing and hospitalization pattern is not uniform in all the states/regions. Some studies such as Swain et al.,  the prevalence of asthma was high among widows in all the states, but T.B. was highest in Bihar (east region) and lowest in Himachal Pradesh (north region), whereas malaria and jaundice was highest in the Northeast region. Mishra  also studied different ARI prevalence in the different regions of the Zimbabwe. The commonly reported sicknesses were colds, coughs, fever and headaches, rheumatic pains, skin diseases, asthma, bronchitis, chicken pox and injuries, symptoms related to minor respiratory ailments were common, and it was confirmed by the doctor in the village that respiratory illnesses are more common that other ailments. There were some chronic cases of mental disorders, which were being treated, in a psychiatric institution. Generally, people used western medicine to cure illnesses. Of the persons reported sick, 56% used western medicine, 18% used ayurveda and 16% used homoeopathic medicines as the first step to cure their sickness. The rest used magico-religious practices and self-medication to cure illness. 
| Objectives|| |
- To describe the population who were ailing and those who have been hospitalized.
- To examine the influence of various factors on ailing and hospitalization.
| Data Source and Methodology|| |
In the present study I have used NSSO 52 nd round data on "Morbidity and Treatment of Ailments0" and 60 th round data on "Morbidity and Health Care". These data provide an opportunity to examine the ailing and hospitalization in India. The NSSO 52 nd survey is based on the enquiry on morbidity and health care conducted during July 1995 to June 1996. This survey is related to curative aspects of the general health care system in India and also the mother and child health (MCH) care programs. The survey of the NSSO 60th round conducted in 2004, related to " Household Consumers' Expenditure", " Employment and Unemployment" and "Morbidity and Health Care".
In this study I have selected, ailments for which the patients were hospitalized during the last 365 days preceding the date of survey. Particulars of these ailments and their treatment as inpatients in hospitals during the reference period were collected in block 4 and 7 of the questionnaire in 52 nd and 60 th round survey respectively.
This study depends on the secondary source of data, so, the information about some other desired variables was not available. Also some of the variables were not available in the both surveys. For example in 52 nd round survey, the information regarding religions, treatment of water, landholdings was not available, but in 60 th round survey has data on these variables.
| Study Variable|| |
I used three response variables. They are follows:
- Ailing one day before the survey (No = 0 and Yes = 1, recoded)
- Ailing 15 days before the survey (No = 0 and Yes = 1, recoded)
- Hospitalization 365 days before the survey (No = 0 and Yes = 1, recoded)
| Results|| |
Statistical analyses have been carried out in order to study the factors that influences ailing and hospitalization in both the survey, i.e., 52 nd and 60 th round. In the analyses that follow, I first present the description of the variables used in the study. I then show here trends of hospital usage in India. Finally, multivariate logistic regression analyses have been done to understand the net effect of the predictors' variables on response variables, by controlling for other predictor variables.
1. Percentage distribution of ailing and hospitalization in India
Percentage distribution of the ailing and hospitalization cases in India has been presented in [Table 2]. The data have been presented as, i.e., demographic, social, household, economic, health factors, and region.
|Table 2: Percentage distribution of persons by ailing one and 15 days, and hospitalization 365 days before the survey, 1995-96 and 2004|
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[Table 2] indicates the relationship between ailing by different variables. I find that old (60+ years) persons were more ailing one day and 15 days before the survey in both the surveys. There were 11.7% of old aged in 52 nd round and 26.0% in 60 th round survey. The next highest category is 45-59 year old persons in both the survey. The lowest ailing was reported among 0-14 and 15-29 year old. The findings are expected as aged persons generally report more ailments. Females were more ailing than males in one day and 15 days before the survey, 6.2% and 9.7% in later survey, respectively, whereas in earlier the survey this percentage was 3.0 and 5.6, respectively. Urban resident have higher ailment percentage in later survey but it was similar per cent in earlier survey. The figures in [Table 2] further indicate that older persons were hospitalized more than younger ones in both the surveys. There were 3.8% of them in 52 nd round and 6.1% in 60 th round survey followed by 45-59 year age group. Lowest percentage of persons hospitalized during 365 days before the survey was in the 0-14 year age group. There was not much difference in males and females hospitalization in both the surveys. Urban residents reported more hospitalization than rural residents.
Information about the religion was not collected, in the 52 nd round. In the 60 th round highest percentage of ailing person were from others religion followed by Muslims. SCs were more ailing during one and 15 days before the survey in 52 nd round survey whereas, others caste reported high ailing in 60 th round survey. The persons who are widow and separated were more ailing one day and 15 days before the survey. [Table 2] further indicates that among Hindu population 2.3% were hospitalized and a similar picture was present among Muslim community. But, other religions (Christian, Sikh, Jain, Buddhist, Zoroastrianism, and others) about 4.0% for were hospitalized. According to 52 nd round 1.3% each STs and others caste were hospitalized whereas only 2.0% of SCs were hospitalized. In 60 th round survey there is a slight variation in hospitalization among STs, OBCs and other caste persons, but SCs were lowest in this category. In both the surveys, I have found high per cent of widow/divorced and separated persons have used hospital treatments followed by currently married women. Less than 1% of the never married persons were hospitalized in earlier round of the survey which is 1.4% in the later round survey.
An important reason for occurrence of diseases, especially those that are exogenous in nature, is the household factors. Members of the households that are endowed with better water and sanitation facilities generally tend to have lower incidence of diseases that are related to them. For example, occurrence of diarrhea among household members is directly linked with the use of clean water and hygiene. The earlier survey showed high ailing among those were living in kutcha (non-cemented) house, whereas, later survey shows reverse pictures. The members of household who have used other source of drinking water were more ailing in comparison with who have been used bottle, tap, tube-well and hand pump water. High ailing was reported among those who have used treated water. A surprising result in both the surveys is that high ailing was found among the household members, who have covered drainage system in the house. Again I found in both the surveys, household members were more ailing who have latrine facility in the house. And members of household who used LPG for cooking were more ailing as compared with, who have used fire woods and others source of energy for cooking.
According to the earlier round survey 2.2% of the members of household living in kutcha house were hospitalized and 1.8% those living in pucca (cemented) house were hospitalized but later round survey showed reverse pictures, i.e., 2.8% and 1.9% of the member hospitalized living in pucca and kutcha house respectively. The lowest per cent of those who have tube well and hand pump water for drinking were hospitalized and highest were those who have used bottled and tap water and 3.6% of them hospitalized used treated water for drinking and 2.0% of them hospitalized did not use treated water for drinking. There was not much difference in hospitalization for drainage facilities; 2.3% of the household members hospitalized have no drainage facility in the house whereas 2.4% and 1.8% were those who have covered and open drainage facility in house in the earlier survey. The 60 th round survey showed 2.2%, 3.0%, and 2.4% of them hospitalized have open, covered and no drainage facility in house, respectively. The household members were more hospitalized where latrine facilities were present than those having no latrine facility. The highest percentages of the household members hospitalized have LPG for cooking in house, and 3.3% of them were hospitalized.
Illiterate were more ailing one day and 15 days before the survey, but, less hospitalized. Highly educated peoples were more hospitalized than primary level and illiterate in both the rounds. Both surveys show that not in labor force population were more ailing but less hospitalized. A slight difference was found between small and large land holding. The persons having less than one hectare land were more ailing and hospitalized than those having more than one hectare land. This is not as expected outcome. The 52 nd round survey reported highest percentage of persons ailing 1 day and 15 days before the survey and these were due to the diseases such as eye diseases (25.6% and 28.6%), endocrine (21.1% and 24.5%), circulatory (18.7% and 24.3%), genito-urinary (16.7% and 22.5%), neuro-psychiatric (12.8% and 18.7%), and neoplasms (14.5% and 18.5%). But I have found in 60 th round survey highest ailing was due to circulatory (55.6% and 60.0%), followed by endocrine (55.4% and 58.4%), respiratory (50.1% and 56.8%), and neuro-psychiatric (48.4% and 54.3%). It indicates that some diseases have increased by two to three times during the nearly ten year interval. Respiratory and circulatory diseases fluctuated more in this period.
Among the hospitalized, highest per cent were those who were suffering from infectious and parasitic diseases in the both surveys, followed by circulatory and respiratory diseases. Later survey shows highest per cent of them hospitalized due to genito-urinary diseases and accident and violence. According to the 52 nd round survey the persons who were ailing one day and 15 days before the survey 19.4% and 24.6% of them were hospitalized, respectively. And 60 th round survey showed 12.7% and 9.5% of the population was hospitalized who have been ailing one day and 15 days before the survey, respectively. Among ailing and hospitalized persons in India the highest per cent of them belong to south and west region followed by central and eastern part. A reason for this may be in south India in general, persons are better educated and more health conscious, and there may be better reporting.
2. Odd ratios for ailing one day, 15 days, and hospitalized during 365 days before the survey
In this analysis, all the three dependent variables-ailing one day before the survey, ailing 15 days before the survey, and hospitalization during 365 days have dichotomous ('yes' and 'no') values. Results of odds ratio for ailing 1 day, 15 days before survey and hospitalization 365 days before the survey are described separately below:
Ailing one day and 15 days before the survey
[Table 3] shows the odds ratio for the ailing one day and 15 days before the survey and hospitalized during 365 days before the survey. The odds ratio shows old age (60+ years) population more than 14 times more likely in 52 nd round and nine times in 60 th round survey ailing one day before the survey than 0-14 age population, followed by 45-59 year and 30-44 year age group who were more likely to be ailing one day before the survey. But, those in 15-29 year age group were less likely to be ailing one day before the survey. Males were more likely to be ailing than females. Rural residents were more likely to be ailing than urban resident.
|Table 3: Odds ratio for ailing one day, 15 days, and hospitalization during 365 days before the survey for NSS 52nd and 60th round|
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Widow/divorced and separated were more likely to be ailing than never married in both the surveys. The members of household were more likely to be ailing one day before the survey that have no drainage, have latrine facility and used other source of energy (kerosene, dung cake, etc.) for cooking.
[Table 3] further shows that aged persons were about three times in 52 nd round and five times in 60 th round survey more likely to be ailing 15 days before the survey as compared to 0-14 year age group whereas 50.0% and 97.0% more likely to be ailing 45-59 year old were in both the surveys respectively. But, those of the 15-29 year age group were about 24.0% more likely to be ailing than younger. The odd ratios for age group show that as age increases the ailing gradually increases.
Muslims and other religions population were more likely to be ailing than Hindu community. About 11.0% of the Muslim and 36.0% of the other religious communities were more likely to be ailing than Hindu. The STs, SCs and OBCs were less likely to be ailing than others caste in the 60 th round whereas SCs were more likely to be ailing in 52 nd round survey. The currently married and widow/divorced and separated were more ailing than never married in later survey. In contrast to that currently married and widow were less likely to be ailing in earlier survey. Widow/divorced and separated were about 35.0% more likely to be ailing than never married.
In household factors, the persons living in kutcha house were less likely to be ailing than those living in pucca house. The odd ratios of source of drinking water shows that who those people used drinking water from tube well/hand pump and others source of water, were more likely to be ailing than those who have used bottled and tap water in 60 th round survey whereas 52 nd round survey showed reverse ratio. Surprisingly, those who have used treated drinking water were 15.0% more likely to be ailing in comparison to those who had not treated water before drinking. Nearly, 20.0% of the population were more likely to be ailing one day and 15 days before the survey, where no drainage facilities were available than open drainage in both the surveys. Those who had no latrine facility in house were less likely to be ailing. The members of households that used LPG and other source of energy for cooking more ailing than those used firewood and chip.
According to 60 th round survey persons who were literate and in labor force were less likely to be ailing than illiterate and those not in labors force categories whereas just the opposite result was found for the 52 nd round survey.
According to 52 nd round survey all the regions were less likely to be ailing one day and 15 days before the survey than North region. But, according to 60 th round survey the south, west and central Indian people were more ailing than north Indian people. South Indian people about 64.0% more likely to be ailing one day and 63.0% more likely to be ailing 15 days before the survey than north Indian people.
Hospitalization During 365 Days Before the Survey
Both surveys showed all age group people were more likely to be hospitalized than 0-14 age group population. As per the 52 nd round survey, the age group of 45-59 and 60+ years old persons were two to three times more likely to be hospitalized than younger (0-14 year) age group and in 60 th round survey it is six to ten times more likely. Females and urban residents were less likely to be hospitalized. Females were about 25.0% less likely to be hospitalized than males.
Non-Hindu populations were more likely to be hospitalized than Hindus. The SCs and OBCs were more likely to be hospitalized whereas STs were less likely to be hospitalized than others category in both the surveys. Currently married couple and widow/divorced and separated were more likely to be hospitalized 73.0% and 64.0%, respectively, than never married couple in 60 th round whereas in 52 nd round the corresponding figures were 50.0% and 35.0%, respectively.
The household factors further show that people living in kutcha house, have no latrine facility, have covered drainage facility were less likely to be hospitalized than those living in pucca house, have latrine facility, and have open drain household. Persons living in households where there were no drainage facilities were 31.0% and 23.0% more likely to be hospitalized in the 52 nd round and 60 th round, respectively. Persons who have used tube well and hand pump water for drinking and have not treated the water before drinking were less likely to be hospitalized than those who have used bottled and tap water and other source of drinking water, and have treated water before drink.
According to 60 th round survey persons who were literate and in labor force were more likely to be hospitalized than illiterate and those not in labor force categories whereas reverse result was found for the 52 nd round survey. Those in the labor were 35.0% less likely to be hospitalized during 365 days before the survey in 60 th round and 66.0% more likely in the 52 nd round.
Persons living in South and West were more likely to be hospitalized than North Indians, whereas Central, East and Northeast Indian people were less likely to be hospitalized than North Indian in both the surveys. The odds ratios are highly significant.
To sum up, most of the variables that are considered in logistic regression for ailing and hospitalizations are in the expected direction. However, some other variables emerged as having opposite effect for ailing and hospitalization. For example, people living in kutcha household and used drinking water from tube well without treatment were less likely to be hospitalized. The reasons for this are not clear. On other hand, old age male in rural areas have high chance of ailing. The households that have no drainage facilities, used energy other than LPG and firewood have high chance of ailing.
We also analyzed the pattern of diseases and availability of health facilities in the regions. The analyses showed that in all region people were suffering from infectious and parasitic diseases, circulatory, respiratory and other diseases. But most of the south Indian people were suffering from circulatory diseases compared with other parts of Indian in both rounds of survey. In terms of health infrastructure (public and private hospitals) south India is in leading in position in both the rounds and the worst condition is in the northeast region. In northeast region the availability of the private hospitals is less than one per cent whereas in south India there is 37% in public and private hospital availability. In south India, the state of Kerala is leading in terms of hospital availability followed by Andhra Pradesh and Tamilnadu.
| Conclusions|| |
There are eight millennium development goals (MDGs) to be achieved by 2015 that represent the world's main development challenges. Out of eight goals, three goals are related to health, i.e., reduce child mortality, improve maternal health, and combat HIV/AIDS, malaria and other diseases.
The odd ratios show that old aged persons were more likely to be ailing one day before the survey in both rounds. Males and rural residents were more likely to be ailing. Currently, married and widow/divorced and separated were more ailing one day before the survey and 15 days before the survey in comparison to those who were never married. The members of households having covered drainage, having latrine facilities and used LPG for cooking were more likely to be ailing. Persons not in labor force were more likely to be ailing.
The logistic regression analyses for hospitalization during 365 days before the survey shows that as age of the persons increases the hospitalization gradually increases. From the expected odds ratio I found that currently married and widow/divorced and separated were more likely to be hospitalized. The persons living in kutcha house have used treated water, having drainage and latrine facilities in the house were more hospitalized. The people from south Indian had higher percentage of hospitalized.
In terms of the policy of the government it is important that due attention is paid to old age persons who are more likely to be ailing and hospitalized. We have not examined how the old age persons obtained monetary and other resources for treatment purpose. This is a separate study all together. As rural residents were more ailing and hospitalized than urban residents, government should give more attention towards rural health infrastructure. Among the household factors, cooking facilities emerge as an important predictor of ailing and hospitalization. This may be related to overall socioeconomic conditions of households. But as there is enough evidence, as Sharma et al. (2004) report that indoor air pollution is a chief cause of morbidity especially for children and women. Indoor air pollution needs to be checked in houses. An advocacy program in these respects will be helpful.
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Centre for Study of Regional Development, School of Social Science, #253 Tapti Hostel, Jawaharlal Nehru University, New Delhi 110067
Source of Support: None, Conflict of Interest: None
[Table 1], [Table 2], [Table 3]