ESTIMATION OF INFANT MORTALITY AND UNDER-FIVE MORTALITY BY PLACE OF RESIDENCE AND RELIGION AND ITS PREDICTIVE FACTORS IN NORTHEAST INDIA

Background: Infant mortality rate (IMR) and under five mortality rates (UFMR) are the sensitive indicators to assess health status and indicators of overall progress of a country. In India, IMR and UFMR is relatively high, and is unable to achieve the Millennium Development Goal (MDG) by 2015. Northeastern states of India depict a captivating trend in child mortality according to the report of NFHS-4 (2015-16). Therefore, the objective of this study is to estimate infant and under five mortality by place of residence and religion. In addition, to determine the factors affecting infant and under-five death. Data and Methods: This study utilizes data of National Family Health Survey (NFHS-4). Eight northeastern states and 37,167 children under-five years were included in the analysis. Synthetic cohort probability method was used to calculate IMR and UFMR. To find the nature of the association between infant and under five death with selected socioeconomic characteristics, Bivariate analysis, and Binary logistic regression were used. Result: Study revealed that children in rural areas has higher risk of infant and under five mortality. Muslims has the highest IMR and UFMR i.e. 52 and 56 per 1000 live births respectively. Adjusted odds ratio shows that wealth index, size of child, sex of child, caesarean-section delivery has impact on infant and under five death at 95% CI and p-value (<=0.05). However, in contrary with existing literature, adjusted odds ratio shows that there is negative association between age of mother, mother education, place of delivery with infant and under five death at 95% CI and p-value (<=0.05).

India has made significant strides in reducing both infant mortality and under-five mortality but has been unable to achieve the Millennium Development Goal (MDG) by 2015 [8]. In India, there is huge differentials across states and socio-economic groups in terms of health outcomes, access and utilization of health services [9]. Due to its diversity, newborn and children exposure to varied disease is different between regions. Evidently, in India there is an enormous rural-urban difference in both infant and under-fivemortality, which indicates unequal distribution of resources in rural and urban areas [10]. In India, the effect of poverty on infant and under-five mortality reduced with time, whereas, female literacy had a consistent effect [11]. Place of residence, birth interval, antenatal care was found to be significantly associated with infant mortality [12]. Numerous studies conducted globally and India shows association of age of mother, education of women, size of the child, sex of child, birth order, wealth index, place of delivery, with infant and under five death. Analysis for rural India demonstrates the importance of mother's education and poverty level in explaining regional differences in infant mortality [8,13]. Mosley Chen Framework categorizes the determinants of infant and child mortality into three categories i.e. biological, socio-economic and environmental factors [14].
Northeastern states consist of eight states namely, Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura. Northeastern states of India depict a captivating trend in child mortality, and health care according to NFHS-4 (2015-16). Over the year there is substantial decline of IMR in Northeastern states of India i.e. 89, 64 and 76 per 1000 live births in NFHS-1 (1992-93) to 48, 30 and 27 per 1000 live births in NFHS 4 (2015-16) in Assam, Meghalaya and Tripura respectively, with similar trend for UFMR [7]. Overall, the Northeastern States has an infant mortality rate and under five mortality rates lower than the Indian average. One factor that seems to be affecting the under-five mortality rates is the location of residence. It is Higher in rural areas when compared to urban areas. Apparently, this has to do with both poverty and availability of healthcare services.
Northeast region is not only geographically isolated from the rest of the country due to poor infrastructure, it also has diverse socio-cultural practices of raising up children, which directly or indirectly affect the child mortality in the region, i.e., because of its geographical location and it's cultural and religious behavior which contributes significantly to the child mortality, makes it important to study the effect of various socio-demographic and cultural factors of individual as well as maternal factors on child mortality under the age of five specifically in northeast states of India. Northeastern states are socially advanced in terms of literacy, women empowerment, women autonomy, but lack behind the other states in terms of infrastructure facilities, economic development and accessibility. The lack of basic amenities is also directly or indirectly responsible for affecting on the early life of childhood than the other demographic, and genetic factors [15].
The health care sector is unevenly distributed throughout the country, and there is urban-rural disconnect, especially in the rural and the tribal areas and more in the northeastern states of India. Primary health care exist however no function or poor function. Although there has been improvement with the operation of National Rural Health Mission for affordable and accountable quality health services to rural areas, the improvement has been quite uneven across region, which have an impact on the health of children in the region. More over immunization coverage, antenatal care and institutional birth is low compared to the rest of the country, and morbidity levels are high, and relatively poor access to health care. Few researches on determinants child Mortality has so far been undertaking in the Northeastern India. Moreover, there are limited research on difference in child mortality by religion specifically in this region. Therefore, the present study aims to fill this gap.

Data source:
This study utilizes data of National Family Health Survey data, which were conducted during 2015-16 (NFHS-4). NFHS-4 covered a sample of 98,716 ever-married women aged 15-49. It provides information on maternal and child health, child mortality rates for India and each state/Union territory. NFHS-4 was conducted under the guidance of Ministry of Health and Family Welfare (MoHFW), Government of India, coordinated by the International Institute for Population Sciences, Mumbai. The NFHS-4 provide information on key indicators of all the districts, and produce reliable estimates of indicators for rural, urban and total of the districts as a whole. In Northeastern states of India, the States of Arunachal Pradesh, Assam, Manipur, Mizoram, Meghalaya, Nagaland, Sikkim and Tripura covered a sample of 14,294,28,447,13,593,92,02,12,279,10,790,5,293,4,804, evermarried women aged 15-49 respectively [7].

Variables:
Two outcome variables are used in this study i.e. infant death and under five death. The study incorporates several predictor variables to understand its linkage with the outcome variables. The socio-economic and demographic and lifestyle factors that have been used as predictor variable in the analysis are age of mother, education of mothers, size of the child, sex of child, birth order, religion, sex of the head of household, wealth index, social status, toilet facility, caesarean-section delivery, place of delivery, safe drinking facility, place of residence, state.
Methods:-NFHS 4 kids file was used for the analysis, and the unit of analysis in this study is the child. Proper sample weights were applied, taking into account the survey design. The mortality estimates were computed with synthetic cohort probabilities. This procedure is based on the procedure developed by Somoza (1980) and Rutstein (1984). Firstly, to calculates IMR and UFMR we have used Syncmrates command, Using STATA 14, [Texas 77845USA College Station, Stata corp]. Syncmrates is used to calculates mortality rates using the synthetic cohort probability method used in Demographic and Health Surveys (DHS), this method is based on the full birth history survey approach, whereby women are asked for the date of birth of each of their children, whether the child is still alive, and the age at death. Mortality rates are calculated over the five years preceding the month interview. Three variables are used to calculate Mortality rates i.e. date of birth, date of interview, and age at death. To calculate the conventional probabilities of dying, first calculated the probability of surviving through the subinterval by subtracting the probability of dying from one. Then they limit and, subtracted this product from one to give the probability of dying within the conventional limits: where n q x is the conventional probability of dying between ages x and x+n and q i are the subinterval probabilities of dying [16]. Bivariate analysis and Chi-square-Measure of association were used to examine the nature of association between under five death and certain background characteristics. In order to find out the determinants of infant and under five death, Binary logistic regression was used. If Yi is the dependent variable, Xi is a set of independent or explanatory variables, and βi"s are its coefficient, then the logistic regression equation is given by, where, the probability of an event occurring is p, the probability of the event not occurring is (1-p), and log odds of p and (1-p) provide the odds ratios [17].    there is a rural urban gap of 18 per 1000 live births, which is lower than total Northeastern states. On the otherhand the rural-urban gap in UFMR is 20 per 1000 live births which is higher than the total Northeastern states.   Table 5.Represent the percentage distribution of children under five years by background characteristics in northeastern states, India. More than 52% of children were among the mothers whose age at birth 13-24 years. Approximately 60.2% children born to mothers" whose level of education is secondary and above. About 79% of the children were having size average and above, and 51.8% of the children are male. The table shows that 40.9% of the child are of birth order one. And almost 89% of the children"s head of the households were male. The proportion of children was maximum among the Hindus i.e. 46.2%, followed by Muslims with 32.8% then Christians with 18.1% and of other religion was 2.9%. In the above table 26% children are from the poorest family, 21.4% children from the poorer family, 19.7% from the middle-income family, 18.3% from the richer family and 14.6% belong to the richest family. Maximum number of children 44.5% belong to others social group, 28.6% belong to ST, followed by, OBC 18.3% and minimum children in SC 8.6%. About 60.6% of children were living in household with improved toilet facilities, and 78.9% of children were living in households having safe drinking water facility. 68.2% women has child delivery in the institution. And 13.4% women has Caesarean-section delivery. 85.1% of the children under five years lives in rural areas. Approximately, 70% of children lives in the states of Assam.  80.25*** 78.89*** * significant at 5% level of significance, ** significant at 1% level of significance and *** significant at 0.1% level of significance In case of under-five death, the children with small size at birth have 2.10 (p=0.001) times higher risk of underfive death compared to those having size average and above. Female child has 0.80 (p=0.01) times lower risk of under-five death compared to the male child. Birth order two to three has 0.65 (p=0.001) lower risk of under-five death compared to birth order one. Among different religious practice in Northeastern states Christian has 0.67(p=0.05) times lower risk of under-five death. The children born to rich, middle, poorer, and poorest have 1.47 (p=0.05) times, 1.94 (p=0.01) times, 2.00 (p=0.01) times, 2.12 (p=0.001) times, higher risk of under-five mortality as compared with children born in the richest family. The child without c-section delivery has 1.47(p=0.05) times, higher risk of under-five death as compared to with c-section delivery. The Northeastern states i.e. Assam has 1.93 (p=0.05) times, Meghalaya has 1.59 (p=0.05) times, Mizoram has 2.68 (p=0.05) times, and Nagaland has 1.72 (p=0.05) times, higher risk of under-five death as compared with Manipur.