Chapter IV Interstate Analysis of Health Outcomes

Chapter IV Interstate Analysis of Health Outcomes

CHAPTER IV INTERSTATE ANALYSIS OF HEALTH OUTCOMES 4.1 Health Outcomes: Meaning and Importance It is well acknowledged by all that health is an integral part of human development. Good health has a multi-dimensional effect. It not only influences economic outcomes but social outcomes also. Better health positively influences learning abilities of children such as better rate of school completion, higher mean years of schooling etc. Good health status also raises the efficiency of human capital formation by individuals and households (Strauss and Thomas 1998; Schultz 1999). Now, the standard of good health that the people of a country enjoy is reflected through their health outcomes. Health outcomes can be defined as a change in the health status of an individual, group of individuals or population which is attributed to a planned intervention or a series of interventions, regardless of whether such an intervention was intended to change health status. Practically, health outcomes are medium of assessing the quality of life of the people. It mainly reflects two things how long people live, i.e., mortality and how healthy people feel while alive, i.e., morbidity. So, the importance of health outcomes cannot be ignored. For the last few years, India s health system has been experiencing some major changes mainly in terms of mortality and morbidity. Mortality changes demographic dimension of a country, which really affects its socioeconomic development. The health status of a community is largely reflected by this

Interstate Analysis of Health Outcomes 75 mortality mortality by sex, mortality by cause, and the most importantly, mortality by age. Mortality is also an important ingredient of population change. It is very much important for population projection; necessary for demographic studies too. In evaluating health status of the population as well as health system, understanding the trends in mortality over a period of time is necessary. The public health administrators heavily depend upon mortality trends to assess the public health policies. Morbidity is also considered as another important indicator which reflects health status of the people. In essence, morbidity means incidence of illness or it can be referred as "disease load". It is the state of disease of an individual, or the incidence of illness in a population. The estimates of morbidity in general and the disease specific incidence rates in particular would serve as valuable information to the health planners and administrators for appropriate and timely measures to monitor, control and eradicate the diseases (Dilip 2002). It will also enable the administrators to allocate resources for health facilities such as hospitals, physicians, medicines etc, and also to provide basic infrastructure such as sanitation, drinking water and the like. Recently morbidity estimates have been used to assess the burden of diseases (Duriasamy 1998). 4.2 Measures of Health Outcomes The present health situation in India is often described as dismal or disturbing (Bose 2008). Despite a lot of improvements after independence in every sphere of life the health scenario in most parts of India is still a cause for concern. Levels of infant and neonatal mortality (NM), child malnutrition, female

Interstate Analysis of Health Outcomes 76 anaemia, non-institutional delivery, etc are higher in some states of India than that of some countries of Sub-Saharan Africa (Mukherjee and Karmakar 2008). Mortality rate is a kind of mirror that shows the health condition of a society. Some health outcomes related to mortality, which create a lot of interest from the policy prescription perspectives, are Infant Mortality Rate, Under-five Mortality Rate, Maternal Mortality Ratio, Crude Death Rate (CDR) etc. Besides mortality and morbidity, life expectancy at birth is a very important pointer of quality of life that the people enjoy in a community. 4.2.1 Life Expectancy at Birth An important outcome of health status of people is life expectancy. It is often used to gauge the overall health position of the population. When a country moves forward, its life expectancy at birth is expected to rise gradually. Life expectancy at birth is defined as the average number of years that a new born infant is expected to live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life. According to the latest available data, in 2012 India s life expectancy at birth was 65.8 years (UNDP 2013). Undoubtedly, India has shown tremendous achievement in the area of life expectancy at birth as it was only 32.7 years in 1947 (SRS). It has almost doubled in last sixty years, which is a remarkable demographic and social achievement. It was 49.7 years during 1970-75 and then increased to the level of 63.0 years in 2000-04; and further improved and stood at 63.5 years during 2002-06. This implies decrease in death rate and betterment of quality of health services in India (GOI 2011). However, the decadal increase has slowed down from 5.7 years in the 1970s to 3.2 years in the 1990s. The overall life expectancy has increased by 14.1 years in the rural areas and 9.9 years in the urban areas during the period 1970-75 to 2002-06 (GOI 2010). As far as life expectancy of

Interstate Analysis of Health Outcomes 77 male and female are concerned, it has increased from 50.5 years in 1970 to 61.8 years in 2003 for males. For females it has increased from 49 years in 1970 to 63.5 years in 2003 (CBHI 2007). As per data, in 2002-006 life expectancy for male and female was 62.6 years and 64.2 years respectively (Abridged Life Tables, 2002-2006). Unfortunately, the scenario is not same all over the country. There is a wide variation across the states. While in Kerala life expectancy at birth is as high as 74 years, life expectancy at birth varies between 58 years and 62 years in the states like Assam, Bihar, Madhya Pradesh, Orissa, Rajasthan, and Uttar Pradesh (GOI 2010). Besides interstate differentials, there exist rural-urban, male-female differences also. Table: 4.1: LEB by Sex and Residence, India and Bigger States, 2002-06 Total Rural Urban India/State Total Male Female Total Male Female Total Male Female India 63.5 62.6 64.2 62.1 61.2 62.7 68.8 67.1 70.0 Andhra Pradesh 64.4 62.9 65.5 63.1 61.7 64.3 67.8 66.1 69.4 Assam 58.9 58.6 59.3 57.9 57.7 58.3 67.6 67.1 68.3 Bihar 61.6 62.2 60.4 60.7 61.7 59.7 67.5 66.7 68.3 Gujarat 64.1 62.9 65.2 62.7 61.7 63.7 66.6 65.3 68.4 Haryana 66.2 65.9 66.3 65.4 65.4 65.2 69.2 67.4 70.7 Himachal Pradesh 67.0 66.5 67.3 66.9 66.4 67.0 69.1 67.5 70.8 Karnataka 65.3 63.6 67.1 63.7 61.8 65.6 69.5 68.1 70.5 Kerala 74.0 71.4 76.3 73.8 71.4 76.1 74.6 70.8 76.7 Madhya Pradesh 58.0 58.1 57.9 56.6 56.7 56.3 65.1 64.2 66.0 Maharashtra 67.2 66.0 68.4 65.2 64.0 66.3 71.2 69.6 72.8 Orissa 59.6 59.5 59.6 58.8 58.8 58.8 66.4 64.3 67.7 Punjab 69.4 68.4 70.4 68.5 67.7 69.2 71.2 69.7 72.7 Rajasthan 62.0 61.5 62.3 60.6 60.4 60.7 67.0 66.7 67.2 Tamil Nadu 66.2 65.0 67.4 64.5 63.5 65.5 69.6 67.6 71.8 Uttar Pradesh 60.0 60.3 59.5 59.2 59.7 58.5 64.0 63.2 64.6 West Bengal 64.9 64.1 65.8 63.5 62.6 64.3 69.9 68.9 71.3 Source: Abridged Life Tables, 2002-2006 - Registrar General, India

Interstate Analysis of Health Outcomes 78 It is quite evident from the table 4.1 that life expectancy at birth varies significantly across the states and also between male and female. Where a woman living in urban Kerala expects to live 76.7 years, a woman of rural Madhya Pradesh can expect merely 56.3 years of living. It clearly describes the regional gap in life expectancy at birth. Life expectancy differentials are more prominent in case of socioeconomic status as the mortality burden falls disproportionately on economically disadvantaged and lower-caste groups (Subarmanian et al. 2007; Dyson & Moore 1983). India s life expectancy is lower than the global average of 67.5 years, and even lesser than the average life expectancy of most of the countries that won their independence from colonial rule at about the same time such as China, Vietnam, Sri Lanka, and so on (GOI 2010). 4.2.2 Infant Mortality and Under-five Mortality The health status of a populace is best judged by its infant mortality rate and under-five mortality rate. Infant mortality is defined as the probability of dying before the first birthday. It is the deaths under one year of age in a year per 1000 live births. It is an indicator of the health status not only of the infants, but also of the whole population and of their social and economic status in the country. It is an important indicator of child health and development (Planning Commission 2006). It is generally seen that nearly one-third of all deaths occur in the first year of life (Bhatt 2004). The major medical causes of infant deaths in India are perinatal conditions (46 per cent), respiratory infections (22 per cent), diarrhoeal disease (10 per cent), other infectious and parasitic diseases (8 per cent), and congenital anomalies (3.1 per cent) (GOI 2012-13) as well as poor nutrition. According to

Interstate Analysis of Health Outcomes 79 WHO, poor neonatal conditions are significantly responsible for young deaths (http://www.unicef.org/mdg/childmortality.html). In general, infant mortality has three components: Perinatal Mortality: where the infant dies within 7 days from birth, Neonatal Mortality: where death takes place between 0 and 29 days; and Postneonatal Mortality: where, death takes place between 1 and 12 months. It has been estimated that 60 per cent of the infants die during first month of life, i.e., during the neonatal period (Smucker et al. 1980). In 2011 almost 30 per cent of global neonatal death took place in India (UNICEF 2012a). Perinatal and neonatal mortality are largely determined by gestational age and care at delivery. Perinatal and neonatal mortality constitute a larger proportion of the IMR. As infant mortality declines, postneonatal mortality shows more rapid declines. Recently, the rate of reduction in infant mortality has slowed down considerably. For the period from 1990 to 2008 IMR has declined by only 34 per cent (UNICEF 2011). At the time of independence in 1947 India s IMR was 146. Then it declined to 129 in 1971, it came down to 110 in the year 1981,and reduced to 80 in 1991, then declined to 66 in 2001, and it was 42 in the year 2012 (SRS Various Years). The rate of decline in IMR is approximately 71% from 1947 to 2012. It is really a commendable achievement for Indian healthcare system. Still this IMR is quite high compared to other developed and developing countries, and if it continues, India is likely to miss the MDG target of 28 IMR by 2015. In the year 1977, World Health Assembly of WHO took up the mission of Health for All. As a part of this strategy, India declared the reduction of infant and child mortality as its major goals to achieve Health for All by 2000. India s Population Policy 2000 had an objective to reduce high level of infant mortality to

Interstate Analysis of Health Outcomes 80 less than 30 per 1000 live births by the year 2010. But unfortunately in 2012 India s IMR (42) was much higher than the target level. In India rural IMR has always been higher than the urban IMR. India s rural IMR declined from 138 in 1971 to 119 in 1981, then it came down to 87 in 1991. In the year 2001, it further plummeted to 72 and in 2012 it was 46. In urban areas, IMR dropped from 82 in 1971 to 62 in 1981. Again, it further declined to 53 in 1991 and in the year 2001, it became 42. It was 28 in 2012. In case of Male-Female IMR, the scenario is mixed. In the year 1982, male IMR was 106, slightly higher than female IMR (104). In the year 1991, male and female IMR were 81 and 80 respectively. But from 1995 onwards female IMR has always been higher than male IMR. In 2001 male IMR was 64, whereas female IMR was 68. In the year 2012, female IMR (44) was higher than male IMR (41) (SRS Various Years). Figure 4.1: IMR and LEB in India 160 140 120 100 80 60 40 20 0 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 Year IMR LEB Based on SRS data

Interstate Analysis of Health Outcomes 81 During the last 40 years, neonatal mortality has reduced significantly. In the year 1971 it was 75.2; in 1981 it was 69.9, it was 51.1 in 1991; it became 40.4 in the year 2001 and it was 33 in 2010. In case of postneonatal mortality, it was 54.2 in 1971, and 40.5 in 1981; in 1991 it was 29.3, whereas it was 25.8 in 2001 and it came down to 16 in the year 2009.In case of perinatal mortality, it was 53.4 in 1971; it became 54.6 in 1981; then it came down to 46 in 1991 and again it declined to 36.5 in 2001. It was 35 in the year 2009 (SRS Various Years). In India, social groups, such as scheduled castes, scheduled tribes, and other backward classes, have been historically under-privileged, and tend to have poorer socioeconomic indicators than the general population (Sharma 2008). Three rounds of National Family Health Survey provide a variety of data on childhood mortality for India. It is found from these reports that there is a considerable difference in different childhood mortality among different castes. SCs and STs bear higher burden of IMR than the other castes of people. Interstate variation in IMR is also a very common feature in India. In the year 2012, among the bigger states, the highest IMR has been recorded in Madhya Pradesh and the lowest IMR has been found in Kerala with 56 and 12 IMR respectively. Among the smaller states the lowest IMR has been observed in Goa and Manipur, both having 10 IMR. If the performance of EAG states is considered, it is quite pathetic. The IMRs in these states are as follows: Bihar: 43, Chhattisgarh: 47, Jharkhand: 38, Madhya Pradesh: 56, Orissa: 53, Rajasthan: 49, Uttar Pradesh: 53 and Uttarakhand: 34. Assam (55) is another state which also has very high IMR. However, the states like Goa (10), Manipur (10), Kerala (12), Nagaland (18), Tamil Nadu (21), Maharashtra (25), Sikkim (24), Delhi (25), Punjab (28) and Tripura (28) have already been successful in achieving the MDG target of IMR (SRS 2013a).

Interstate Analysis of Health Outcomes 82 Table 4.2: Time Series Data of IMR, India: Total, Rural, Urban, Male, Female Year Total Rural Urban Male Female 1980 114 124 65 113 115 1981 110 119 62 - - 1982 105 114 65 106 104 1983 105 114 66 105 105 1984 104 113 66 104 104 1985 97 107 59 96 98 1986 96 105 62 96 97 1987 95 104 61 95 96 1988 94 102 62 96 94 1989 91 98 58 92 90 1990 80 86 50 78 81 1991 80 87 53 81 80 1992 79 85 53 79 80 1993 74 82 45 73 75 1994 74 80 52 75 73 1995 74 80 48 73 76 1996 72 77 46 71 73 1997 71 77 45 70 72 1998 72 77 45 70 73 1999 70 75 44 70 71 2000 68 74 44 67 69 2001 66 72 42 64 68 2002 63 69 40 62 65 2003 60 66 38 57 64 2004 58 64 40 58 58 2005 58 64 40 56 61 2006 57 62 39 56 59 2007 55 61 37 55 56 2008 53 58 36 52 55 2009 50 55 34 49 52 2010 47 51 31 46 49 2011 44 48 29 43 46 2012 42 46 28 41 44 Source: SRS 2009

Interstate Analysis of Health Outcomes 83 The under-five mortality rate is the probability (expressed as a rate per 1,000 live births) of a child born in a specified year dying before reaching the age of five subject to current age-specific mortality rates. It is a major indicator of level of child health and overall development of a nation. It is also considered as the best barometer of social and economic progress of the country. It is an MDG indicator, too. High child mortality is a global problem. But thanks to better nutrition, health care, and standards of living, child deaths have been reduced significantly worldwide over the last few decades. Since 1990 the global under-five mortality rate has declined significantly. It has dropped from 87 deaths per 1000 live births in 1990 to 51 in 2011, yet, insufficient to achieve the MDG target of 31 per 1000 live births by 2015. In the year 2011, globally, 6.9 million children under the age of five died. The leading causes of death were pneumonia (18 per cent of all under-five deaths); preterm birth complications (14 per cent); diarrhoea (11 per cent); intrapartum related complications (complications during birth; 9 per cent); and malaria (7 per cent) and other causes (41 per cent) (http://www.who.int/ mediacentre/factsheets/fs178/en/). Worldwide, more than one third of under-five deaths are attributable to undernutrition. About half of under-five deaths occur in only five countries: India, Nigeria, Democratic Republic of the Congo, Pakistan and China. Among them, India (24 percent) and Nigeria (11 percent) together account for more than a third of all under-five deaths (UNICEF 2012a). India s U5MR varies significantly among the states. About 50 per cent of all under-five deaths occur in the first month of life. Progress in reducing the IMR and U5MR has been uneven across the states, with the poor-performing states in the

Interstate Analysis of Health Outcomes 84 north, central and east showing far higher rates than those of the better performing states in the south and west (Ved and Dua 2005). According to the latest available data, India s U5MR for the year 2011 was 55. In the rural areas it was 61 and in urban areas it was 35. India s male U5MR for the same year was 51 whereas it was 59 for female. Assam (78) recorded highest U5MR, followed by Madhya Pradesh (77), Uttar Pradesh (73), and Orissa (72). As far as other EAG states are concerned, U5MR in Bihar was 59, in Chhattisgarh it was 57, for Jharkhand and Rajasthan it was 54 and 64, respectively. Among the bigger states, the lowest U5MR was recorded in Kerala (13). As per data of 2011, besides Kerala, Delhi (32), Tamil Nadu (25), Maharashtra (28), Punjab (38), West Bengal (38) and Karnataka (40) have already been successful in achieving the MDG goal of U5MR, which is 42 per 1000 live births. However, if the present trends of reduction of U5MR continue then the states like Jammu & Kashmir (45), Andhra Pradesh (45) and Himachal Pradesh (46) will achieve the MDG target very soon (SRS 2013b). The under-five mortality rate, including infant, neonatal and child mortality rates, started to decline since the late 1970s, and till 1993 the rate of decline was substantial. However, the decline was slow during 1993 98. The country s goal to achieve a U5MR of less than 100 per 1000 live-births and reducing the IMR to less than 60 per 1000 live-births by the year 2000 could not be achieved despite improved interventions and an increase in the overall resources (Sharma 2008). The under-five mortality rate and infant mortality rate are the two best judges to interpret the health status of children. United Nations has also emphasised

Interstate Analysis of Health Outcomes 85 the importance of child survival and so it has incorporated child survival among its Millennium Development Goals. Goal 4 of MDGs underlines the need to reduce child mortality. It states to reduce under-five mortality rate by two-third between 1990 and 2015. For this purpose two basic indicators have been identified as underfive mortality rate and infant mortality rate. There have been considerable efforts to reduce under-five mortality rate and infant mortality rate in the country over the last three decades. Though U5MR has been declining continuously, India is unlikely to achieve the target of MDG of 42 per 1000 live births by 2015 (http://www.undp.org/ content/india/en/home/mdgoverview/overview/mdg4/). It has been found that children born into poverty are almost twice more likely to die before the age of five than those from wealthier families and children of educated mothers. Even children of those mothers who have only primary schooling are more likely to survive than the children whose mothers have no education (http://www.un.org/millenniumgoals/ childhealth.html). In order to reduce U5MR, it is important to strengthen the health system with universal coverage. Among the children in the age group of 1 4 years, about half of the deaths are caused by respiratory diseases, anaemia, diarrhoea, dysentery, malaria, typhoid and influenza. This implies that, given prompt recognition at home, accurate diagnosis (clinical and laboratory-based), and early and complete therapy, the majority of these conditions are completely amenable to treatment (Pelletier et al. 1995). So, it is essential to expand the immunisation programme reaching every section of the society. Simultaneously prevention and effective case management of pneumonia, diarrhoea, sepsis, malaria control, and preventive care of HIV/ AIDS are equally important. Survival and improved health of mothers, care for the

Interstate Analysis of Health Outcomes 86 newborns, better nutrition for child and mother; and investing in better reproductive health have to be taken care of. Sufficient antenatal care, skilled assistance at the time of delivery etc are some of the other factors influencing child health and survival. 4.2.3 Maternal Health and Maternal Mortality Maternal health refers to the health of women during pregnancy, childbirth and the postpartum period (http://www.who.int/topic/maternal_health/en). Maternal mortality indicates the health status of the mothers and thus possesses a great significance for health planners and administrators. It reflects how successfully the clinical health services reach to every section of the society, especially to the poor. It is thus considered as an important measure to assess the country s progress in health. Deaths due to child bearing (pregnancy) and child birth are known as maternal mortality. The Tenth Revision of International Classification of Diseases (ICD-10) defines a maternal death as the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes. Realising the subjectivity of the 42 days period and recognising the fact that modern life-sustaining procedures and technologies can prolong dying and delay death, ICD-10 introduced a new category, the Late Maternal Death, which is defined as the death of a woman from direct or indirect obstetric causes for more than 42 days but less than one year after termination of pregnancy (CBHI 2007). Maternal death is generally measured by three terms- Maternal Mortality Ratio, Maternal Mortality Rate and the Life Time Risk of maternal death. However, the most commonly used measure is Maternal

Interstate Analysis of Health Outcomes 87 Mortality Ratio. The Maternal Mortality Ratio is the ratio of the number of maternal deaths during a given time period per 100,000 live births during the same timeperiod. This measures the risk of death once a woman gets pregnant. The Maternal Mortality Rate is the number of maternal deaths during a given period per 100,000 women of reproductive age 15-49. It reflects the frequency with which women are exposed to risk through fertility. The Lifetime Risk of maternal deaths is defined as the probability that a 15 year old woman will eventually die from a maternal cause when competing causes of death are taken into account. It takes into account both probability of becoming pregnant and the probability of dying from a maternal cause during a woman s reproductive years. Almost 6,00,000 women die each year from pregnancy-related causes, of them 99 per cent belong to the developing countries. Maternal mortality indices show a great disparity between countries, much more than even infant mortality, which is most often taken as the measure of comparative disadvantage. For developing countries it is about 50 times higher than that of developed countries. About 1 in 48 women in developing countries dies from pregnancy-related causes compared to only about 1 in 1,800, for developed countries (Radkar and Parasuraman 2007). Maternal health is a serious problem in India, where an estimated 1,36,000 women die needlessly each year from causes related to pregnancy, childbirth and abortion. The three countries, India, Pakistan and Bangladesh account for 28 per cent of the world's births and 46 per cent of its maternal deaths (Motashaw 1997). Women residing in rural areas, belonging to backward castes and having a low standard of living are the most vulnerable in terms of maternal mortality. A lesser number of maternal deaths in the urban areas

Interstate Analysis of Health Outcomes 88 reflect the easier access of the city-dwellers to medical services (WHO 1991). In India also the differentials in maternal deaths are observed by caste and standard of living of women along with the place of residence, indicating that lower socioeconomic groups experience maternal mortality more (Anandlakshmy et al. 1993). Low level of education among females specifically enhances the risk of maternal death appreciably (SRS 2006). In India, a number of factors are responsible for maternal deaths. Anaemia is a very common problem for Indian women, which sometimes becomes fatal to them causing maternal death. Lack of emergency obstetrical care, especially in rural areas, lack of consciousness for antenatal care, postnatal care (PNC), etc are other factors that also cause maternal deaths. Most of the maternal deaths occur mainly due to haemorrhages, obstructed labour, eclampsia, sepsis, complications due to unsafe abortion, infection, high blood pressure etc. Maternal mortality is strongly associated with the services provided. Proper antenatal, natal and postnatal care would certainly lower the number of maternal deaths significantly. Antenatal checkups would definitely identify the problem on time and suggest referrals, if required. This would help save the life of the mother and the child. The major problems that need to be addressed are the absence of links between communities, subcentre and referral facilities, shortages of equipment and trained staff at referral facilities and a lack of emergency transport (Arora 2005). A major factor which determines the pregnant women's risk of death is the lack of access to well-equipped healthcare services (WHO 1991). These services should be made more accessible to all, especially to those who are poor and residing in remote areas, where the services are provided insufficiently and inefficiently.

Interstate Analysis of Health Outcomes 89 Estimating maternal deaths is difficult all over the world, unless there exists a comprehensive death registration system including the cause of death. In India very limited data are available for MMR. SRS data show that India has recorded a remarkable decline in MMR of 35 per cent from 327 in 1999-2001 to 212 in 2007-09. The decline in MMR from 1990 to 2009 is 51 per cent. It was as high as 437 in 1990 (CSO 2011). MMR has declined by approximately 16% from 2007-09 to 2010-12. However, indirect estimates by the World Health Organisation shows that India had about 120,000 to 140,000 maternal deaths in 2002 (SRS 2006). 19 per cent of global maternal death took place in India in the year 2010 (WHO 2012). Table 4.3: Maternal Mortality Ratio: India and its Major States India/Sates 1997-98 1999-01 2001-03 2004-06 2007-09 2010-12 India 398 327 301 254 212 178 Andhra Pradesh 197 220 195 154 134 110 Bihar/Jharkhand 531 400 371 312 261 219 Gujarat 46 202 172 160 148 122 Haryana 136 176 162 186 153 146 Karnataka 245 266 228 213 178 144 Kerala 150 149 110 95 81 66 Madhya Pradesh/ Chhattisgarh 441 407 379 335 269 230 Maharashtra 166 169 149 130 104 87 Orissa 346 424 358 303 258 235 Punjab 280 177 178 192 172 155 Rajasthan 508 501 445 388 318 255 Tamil Nadu 131 167 134 111 97 90 Uttar Pradesh/ Uttarakhand 606 539 517 440 359 292 West Bengal 303 218 194 141 145 117 Source: Registrar General of India, Ministry of Home Affairs (SRS Estimates)

Interstate Analysis of Health Outcomes 90 Figure 4.2: MMR in India 398 327 301 254 212 178 1997-98 1999-01 2001-03 2004-06 2007-09 2010-12 MMR Based on SRS Estimates In a big country like India which is characterised by different social, cultural, economic background, the levels of maternal mortality vary significantly across the regions and states, mainly because of variant access to emergency obstetrical care, prevalence of anaemia among woman, education level of women, prenatal care etc. It has been found in a SRS study that about 65 per cent of maternal deaths take place in Empowered Action Group states such as Bihar and Jharkhand, Orissa, Madhya Pradesh and Chhattisgarh, Rajasthan, Uttar Pradesh and Uttaranchal along with Assam. About one fourth (22.9 per cent) of the total maternal deaths have been reported in Uttar Pradesh/ Uttarakhand. But, only about 10 per cent of the total maternal deaths have been reported by the southern states (Andhra Pradesh, Kerala, Karnataka and Tamil Nadu) (SRS 2006). As per latest data of 2010-12, among the southern states, Kerala (66) and Tamil Nadu (90) have already been successful in

Interstate Analysis of Health Outcomes 91 achieving the goal of MDG for MMR but, Karnataka lags significantly behind with a MMR of 144. Maharashtra (87) has also achieved the MDG target of MMR. However, EAG states with high burden of MMR are far away from the MDG target of MMR. According to the MDG, India requires to reduce its MMR to 109 per 100,000 live births by 2015. By this time Kerala, Tamil Nadu and Maharashtra have been successful in achieving this target. But if the prevailing rate of decline persists, it would be difficult for India to achieve the MDG target. However, the bright line of the trends is that the rate of decline in MMR has increased gradually. It has reduced by 8 per cent in 2001-03, by 16 per cent during 2003-06 and by 17 per cent during 2006-09. Another worth mentioning fact is that during 2004-06 Kerala was the only state to achieve the MDG target set for India. In 2007-09 two other states namely Tamil Nadu and Maharashtra have joined the group. The states like Andhra Pradesh, Gujarat, Haryana, Karnataka and West Bengal are expected to join them very soon (CSO 2011). High MMR is not only a major concern for India, rather it is a global problem. So, reduction in MMR is an area of high priority. The International Conference on Population and Development in 1994 recommended reduction in maternal mortality globally by at least 50 per cent of the 1990 levels by the year 2000 and further one half by the year 2015. Realising the importance of maternal health, United Nations has incorporated MMR in their Millennium Development Goals. Goal 5 of MDGs speaks about improvement of maternal health, and thus target has been specified to reduce MMR by three quarters between 1990 and 2015.

Interstate Analysis of Health Outcomes 92 The Millennium Development Goals have set the target of achieving 200 maternal deaths per lakh of live births by 2007 and 109 per lakh of live births by 2015 (SRS 2006). Maternal death is associated with significant social and economic loss. Children who lose their mothers are the worst sufferers. The probability of children to die under five years of age increases if their mothers die. As most of the maternal deaths are preventable, it is very important for the women to have access to antenatal care during pregnancy, to avail services of skill attendant at the time of child birth, and to have access to postnatal care. To reduce maternal mortality, it is important to avert unwanted and too-early pregnancies, for which women need access to family planning. Safe abortion is also very important to prevent maternal death. Poverty, distance of health station, lack of information and awareness, inadequate services, cultural practices are some factors which sometimes create obstruction for accessing health care services during pregnancy. So, to improve maternal health these barriers need to be addressed properly and adequately. 4.2.4 Crude Birth Rate and Crude Death Rate Crude Birth Rate (CBR) is defined as the number of live births per 1,000 population estimated at midyear. Subtracting the crude death rate (CDR) from the crude birth rate gives the rate of natural increase, which is equal to the rate of population change in the absence of migration. It is generally used to determine the rate of population growth. It depends on the fertility level as well as age structure of population. India s CBR has declined from 40.8 in the year 1947 to 29.5 in the year 1991 and again to 22.1 in the year 2010 and to 21.6 in the year 2012 (SRS Various Years). It is a considerable decline of approximately 47 per cent. However, if we

Interstate Analysis of Health Outcomes 93 compare India s CBR with other developed and some neighbouring countries, India lags behind them except Pakistan. There is an extensive interstate disparity in India in CBR. Rural urban difference is also prominent. In the year 2012, CBR in rural India was higher (23.1) than urban India (17.4). For the same year Bihar recorded the highest CBR (27.7) whereas Goa was the home of the lowest CBR (13.1). In some other states like Assam (22.5), Chhattisgarh (24.5), Jharkhand (24.7), Madhya Pradesh (26.6), Rajasthan (25.9) and Uttar Pradesh (27.4), CBR was more than the national average (SRS 2013a). Table 4.4: CBR, CDR of India: Comparison with Developed and Neighbouring Countries, 2011 Country CBR, 2011 CDR, 2011 Canada 11 7 U.K. 13 9 U.S.A. 13 8 India 21.8 7.1 China 12 7 Pakistan 27 7 Bangladesh 20 6 Bhutan 20 7 Sri Lanka 18 7 Source: World Bank (http://www.worldbank.org/indicators/sp.dyn.cbrt.in) Crude Death Rate is the number of deaths that occur during the year per 1000 population estimated at midyear. Though it is a rough indicator of mortality scenario of a country, it is capable of precisely showing the current mortality impact on population growth. At the time of independence, in the year 1947 India s CDR was 27.4. Then it dropped to 25.1 in the year 1951 and it came down to 9.8 in the year 1991. It again declined to 7.4 in the year 2007. During 2008, it stood at 7.4 but

Interstate Analysis of Health Outcomes 94 then declined to 7.3 in the year 2009. In the year 2010, it further declined to 7.2 and in the year 2012, it was 7.0 (SRS Various Years). It has declined approximately by 74.5 per cent since 1947. In the year 2012, the rural CDR was 7.6 whereas in urban areas it was 5.6. For the year 2012, the highest CDR has been found in Madhya Pradesh (8.1) and the lowest CDR has been found in Nagaland (3.2). The states like Andhra Pradesh (7.4), Assam (7.9), Chhattisgarh (7.9), Madhya Pradesh (8.2), Karnataka (7.1), Orissa (8.5), Tamil Nadu (7.4), Uttar Pradesh (7.7) and Meghalaya (7.6) have recorded more CDR than the national average (SRS 2013a). Figure 4.3: Crude Birth Rate and Crude Death Rate in India 40 35 30 25 20 15 10 5 0 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 Year CBR CDR Based on SRS data 4.3 Interstate Variations in Health Outcomes Health inequality between and within the countries is a matter of growing concern internationally (Marmot 2005). India, being a country of diverse cultural, religion and socioeconomic conditions, witnesses a great deal of interstate variations in different health outcomes.

Interstate Analysis of Health Outcomes 95 Interstate variation in health outcomes is quite clear from the table 4.5. IMR varies from 10 in Goa to 56 in Madhya Pradesh. U5MR ranges from 13 in Kerala to 77 in Madhya Pradesh. A wide disparity is found in MMR also. It is lowest again in Kerala (66) and highest in Uttar Pradesh (292). Negligence to women s health is also evident from NFHS-3 data. Percentage of women suffering from any kind of anaemia is found highest in Jharkhand (69.5 per cent), which is an EAG state. Almost similar kind of situation is found in other EAG states also. Percentage of women suffering from any kind of anaemia in Bihar is 67.4, and in Chhattisgarh it is 57.5. It is 56 per cent in Madhya Pradesh. Rajasthan has 53.1 per cent women suffering from any anaemia and in Uttarakhand and Uttar Pradesh these values are 55.2 per cent and 49.9 per cent respectively. Again, Kerala ranks top, bearing minimum percentage of women suffering from any anaemia. Percentage of children suffering from severe underweight is found highest in Madhya Pradesh (27.3 per cent) an EAG state. As far as other EAG states are concerned; Bihar has 24.1 per cent children suffering from severe underweight; it is 16.4 per cent in Chhattisgarh; 26.1 per cent in Jharkhand; 13.4 per cent in Orissa; 15.3 per cent in Rajasthan; 15.7 per cent in Uttarakhand and 16.4 per cent in Uttar Pradesh. Kerala has the lowest burden of severe underweight children. It is 4.7 per cent in Kerala (NFHS-3).

Interstate Analysis of Health Outcomes 96 Table 4.5: Selected Health Outcomes in India and Major States States LEB 2002-06 IMR 2012 U5MR 2011 MMR 2010-12 CBR2012 CDR 2012 % Children Severe Underweight 2005-06 % Women Anaemic(any anaemia) 2005-06 Column 1 2 3 4 5 6 7 8 India 63.5 42 55 178 21.6 7.0 15.8 55.3 Andhra Pradesh 64.4 41 45 110 17.5 7.4 9.9 62.9 Bihar 61.6 43 59 219 27.7 6.6 24.1 67.4 Chhattisgarh - 47 57-24.5 7.9 16.4 57.5 Delhi - 25 32-17.3 4.2 8.7 44.3 Goa - 10 - - 13.1 6.6 6.7 38 Gujarat 64.1 38 52 122 21.1 6.6 16.3 55.3 Haryana 66.2 42 51 146 21.6 6.4 14.2 56.1 Himachal Pradesh 67.0 36 46-16.2 6.7 11.4 43.3 Jammu & Kashmir - 39 45-17.6 5.4 8.2 52.1 Jharkhand - 38 54-24.7 6.8 26.1 69.5 Karnataka 65.3 32 40 144 18.5 7.1 12.8 51.5 Kerala 74.0 12 13 66 14.9 6.9 4.7 32.8

Interstate Analysis of Health Outcomes 97 States LEB 2002-06 IMR 2012 U5MR 2011 MMR 2010-12 CBR2012 CDR 2012 % Children Severe Underweight 2005-06 % Women Anaemic(any anaemia) 2005-06 Madhya Pradesh 58.0 56 77 230 26.6 8.1 27.3 56 Maharashtra 67.2 25 28 87 16.6 6.3 11.9 48.4 Orissa 59.6 53 72 235 19.9 8.5 13.4 61.2 Punjab 69.4 28 38 155 15.9 6.8 8 38 Rajasthan 62.0 49 64 255 25.9 6.6 15.3 53.1 Tamil Nadu 66.2 21 25 90 15.7 7.4 6.4 53.2 Uttaranchal - 34 - - 18.5 6.1 15.7 55.2 Uttar Pradesh 60.0 53 73 292 27.4 7.7 16.4 49.9 West Bengal 64.9 32 38 117 16.1 6.3 11.1 63.2 Note : Jharkhand, Chhattisgarh and Uttarakhand are included in Bihar, Madhya Pradesh and Uttar Pradesh respectively. Source: Col.1: Abridged Life Tables, 2002-2006 - Registrar General, India Col.3: SRS 2013b Col.4: SRS 2013c Col.2, Col.5, Col.6 : SRS 2013a Col.7 and Col.8: NFHS-3

Interstate Analysis of Health Outcomes 98 Table 4.6: Caste Wise Mortality Rates in Major States of India Neonatal Mortality Postneonatal Mortality # Infant Mortality 1 q 0 Under five Mortality 5 q 0 States SC ST OBC Others SC ST OBC Others SC ST OBC Others SC ST OBC Others Andhra Pradesh 66.3 (63.4) 47.6 46.3 21.8 (30.7) 15.2 7.7 88.1 (94.1) 62.8 54.0 96.1 (112.0) 73.1 63.2 Bihar 48.8-36.6 51.6 22.2-20.6 30.6 71.0-57.2 82.2 113.1-84.7 108.9 Chhattisgarh 32.1 67.0 58.3 (63.3) 31.0 23.6 21.1 (19.8) 63.1 90.6 79.4 (83.1) 78.1 128.5 98.3 (109.3) Delhi 23.5 * (30.6) 26.6 13.9 * (8.5) 10.8 37.4 * (38.5) 37.4 51.3 - (47.5) 43.2 Goa * * (26.3) 15.0 * * (0.0) 7.2 * * (26.3) 22.2 * * (33.6) 29.2 Gujarat 45.9 (53.0) 48.8 35.9 19.6 (33.0) 17.7 11.4 65.4 (86.0) 66.5 47.3 86.6 (115.8) 78.1 55.7 Haryana 29.2-30.0 20.7 24.0-22.1 15.4 53.3-52.1 36.1 73.9-62.3 49.7 Himachal Pradesh Jammu & Kashmir (40.8) * (29.1) 24.0 (15.6) * (7.8) 4.2 (56.4) * (36.9) 28.2 (63.4) * 36.9 33.1 (45.7) (11.2) (26.0) 34.0 (16.9) (23.1) (19.3) 10.7 (62.6) (34.3) (45.3) 44.7 72.2 * (55.1) 53.3 Jharkhand (52.3) 64.3 45.0 60.7 (24.4) 28.7 21.9 14.8 (76.7) 93.0 66.9 75.5 (121.3) 138.5 100.8 92.7 Karnataka 44.8 (36.0) 37.3 29.0 12.4 (9.9) 15.7 14.5 57.2 (45.8) 53.0 43.5 65.4 (77.9) 63.8 60.4 Kerala * * 11.5 13.9 * * 0.0 6.0 * * 11.5 19.9 * * 12.9 20.7

Interstate Analysis of Health Outcomes 99 Neonatal Mortality Postneonatal Mortality # Infant Mortality 1 q 0 Under five Mortality 5 q 0 Madhya Pradesh 50.2 56.5 53.3 39.6 31.7 39.0 25.7 27.2 81.9 95.6 79.0 66.8 110.1 140.7 97.6 79.9 Maharashtra 35.8 32.5 39.4 34.3 9.4 18.9 11.2 6.2 45.2 51.4 50.6 40.5 50.2 69.8 57.8 47.4 States SC ST OBC Others SC ST OBC Others SC ST OBC Others SC ST OBC Others Orissa 46.4 54.0 52.5 31.7 27.2 24.7 13.5 21.4 73.7 78.7 66.0 53.1 91.8 136.3 83.5 64.2 Punjab 29.5 - * 30.6 16.7 - * 13.5 46.2 - * 44.1 61.5 - * 50.5 Rajasthan 65.3 38.4 45.6 44.7 31.0 34.8 21.3 13.4 96.4 73.2 66.9 58.1 123.1 113.8 80.8 69.9 Tamil Nadu 25.2 * 26.7 * 12.1 * 11.5 * 37.4 * 38.2 * 48.3 * 44.6 * Uttaranchal 53.3 * (36.1) 27.3 17.0 * (27.9) 16.5 70.2 * (64.0) 43.8 97.3 * (83.9) 52.2 Uttar Pradesh 60.2-58.9 38.1 30.5-25.2 33.3 90.7-84.1 71.4 135.1-111.0 87.7 West Bengal 28.7 * * 42.9 10.1 * * 13.8 38.8 * * 56.6 46.6 * * 70.4 Source: NFHS-3 Values in ( ) are based on 250-499 unweighted cases # Computed as the difference between the infant and neonatal mortality rates *Not shown, based on fewer than 250 unweighted cases

Interstate Analysis of Health Outcomes 100 Table 4.6 shows the interstate differentials in neonatal, postneonatal, infant and under-five mortality rates in different social groups of people. It is seen from the table that in most of the states, SCs and STs bear the maximum burden of childhood mortality. As a whole the situation of the reserved category people is not very good in terms of child health. They were deprived, and there is no change in their fortunes so far. 4.4 Health Outcomes and Socioeconomic Factors The association between health outcomes and socioeconomic factors has been discussed in many studies both nationally and internationally. Apart from biological factors, different social and economic factors have considerable influence on health outcomes like life expectancy at birth, infant mortality rate, under-five mortality rate, maternal mortality ratio etc. In order to capture the association among the socioeconomic factors and health outcomes of twenty one major states of India Spearman s Rank Correlation has been used. The correlation has been shown among Life Expectancy at Birth (2002-06), Infant Mortality Rate (2012), Under-five Mortality Rate (2011), Maternal Mortality Ratio (2010-12), Total Fertility Rate (2011), Poverty Level (2011-12), Per capita Net State Domestic Product (NSDP) (in Rs. 2011-12), Total Literacy Rate (2011), Per capita Health Expenditure (in Rs. 2004-05) and HDI Value (2010-11). Data of IMR, U5MR, MMR, TFR, and LEB have been collected from Registrar General of India; data on poverty level are taken from Planning Commission 2013; per capita NSDP data have been taken from Directorate of Economics and Statistics; data on total literacy rate have been collected from Census 2011, data for per capita health expenditure have been collected from NHA 2009. HDI values have been taken from Inequality adjusted Human Development Index for India s States 2011, published by UNDP.

Interstate Analysis of Health Outcomes 101 Table 4.7: Health Outcomes and Socioeconomic Factors: Correlation Matrix LEB IMR U5MR MMR TFR Poverty Level LEB 1 -.808** -.877** IMR 1.949** -.788**.752** (.001) U5MR 1.906** -.728** (.001).786**.874** MMR 1.780** -.746**.507* (.027).610** (.007).440 (.078) TFR 1.618** (.006) Per Capita NSDP.722** (.001) -.690** (.001) -.746** -.645** (.005) -.713** (.001) Poverty Level 1 -.630** (.004) Total Literacy Rate.627** (.005) -.712** (.001) -.652** (.003) -.557* (.020) -.695** (.001) -.495* (.031) Per Capita NSDP 1.811** Per capita Health Expenditure.783** -.621** (.005) -.730** (.001) -.651** (.005) -.818** -.747**.677** (.001) Total Literacy Rate 1.732** Per capita Health Expenditure HDI Value.878** -.790** -.798** -.605* (.010) -.676** (.003) -.853**.828**.812** 1.814** HDI Value 1 ** Correlation is significant at the 0.01 level (2 tailed), *Correlation is significant at the 0.05 level (2 tailed)

Interstate Analysis of Health Outcomes 102 Table 4.7 shows significant correlations among the health outcomes and socioeconomic factors. The rank correlations are statistically significant and are in the expected directions. The rank correlations between LEB and poverty level, per capita NSDP, total literacy rate, per capita health expenditure and HDI value show highly statistically significant correlations. Negative sign between LEB and poverty level depicts the inverse relationship between them, showing an increase in poverty level is expected to bring a fall in LEB. Obviously increase in life expectancy will be reflected on HDI value, as life expectancy is an important component of HDI. Globally and historically, poverty has been found to be the major determinant of child as well as adult health (Spencer 2000). It has been well documented in different studies that poverty profoundly and adversely affects child health. It has been found that all aspects of health are worse among children living in poverty than among children from affluent families (Britton Jr. 1989). Maternal health is also influenced by the poverty level. Here, the positive association of poverty level with IMR, U5MR and MMR clearly supports this fact. The negative association between IMR and per capita NSDP and per capita health expenditure is because of the fact that the rise in per capita NSDP or per capita health expenditure will ensure better health status, which is expected to be reflected on health outcomes such as IMR. The same is true for U5MR also. Literacy rate also shows an inverse relation with IMR and U5MR. Higher level of population literacy makes people conscious about the health of their children which ensures reduction in IMR and U5MR (Amonker and Brinker 1997, Flegg 1982). Literacy of women and their husbands also have a significant role to reduce maternal death (Bhatia 1993).

Interstate Analysis of Health Outcomes 103 4.5 Conclusion India s health data depict that health outcomes in India have been showing trends of improvements over a period of time. Mortality, especially the infant mortality, has declined significantly, and at the same time, life expectancy at birth has been continuing its upward climb. But the fact remains that India s achievements in health outcomes yet to reach the satisfactory level. In some health outcomes India not only lags behind the developed countries, but sometime the neighbouring developing countries also. Besides, interstate variation is also worrisome. Research shows that there exist huge variations between the northern and southern states of India in respect of demographic behaviour (Naveentham and Dharmilngham 2002; Basu 1997; Miller 1981; Dyson and Moore 1983). The southern states are highly advanced in demographic parameters, while the EAG states are at the bottom of the spectrum (Visaria 2004a, b). Kerala is an example of social development which is reflected through its health outcomes. At the same time, eight EAG states are very poor in respect of demographic as well as the socioeconomic indicators (Singh 2012). It is quite unfortunate that India s MMR is very high. Among the states of India, maximum number of maternal deaths takes place in EAG states (Gupta 2013). Low level of socioeconomic development in addition to poor utilisation of health care services in these regions (NFHS 2; NFHS 3; DLHS 3) leads to poor maternal health outcomes. These eight states are very much responsible for the poor performance of India in major health outcomes. If the present trends continue, India is likely to miss the MDG target of IMR, U5MR and MMR.