Data source and sampling
The study is a cross sectional study and utilized the data from NFHS-4 which is publicly available through (https://dhsprogram.com/data/dataset/India_Standard-DHS_2015.cfm?flag=1). Thus, no further ethical approval is required. NFHS 4 was conducted during January 20, 2015 and December 4, 2016 across 640 districts spread over 36 states and union territories of India. Districts in India are the second basic and policy relevant administrative units. NFHS 4 is the Indian version of Demographic Health Survey (DHS) that used standard survey instruments across the country. NFHS used a stratified two stage cluster design to conduct the survey and used the 2011 census sampling frame to select the primary sampling units (PSU). Census enumeration blocks in urban areas and villages in rural areas constitute the sampling frame of PSUs. PSUs were then selected using probability proportional to size (PPS) from the sampling frame. Prior to the main survey, a complete household mapping and listing was done in the selected rural and urban PSUs and within the selected PSUs, the number of households (300 at least) were sub divided into segments of 100–150 households. And finally two of the segments were randomly selected using systematic sampling with probability proportional to segment size. In the second stage, 22 households were randomly selected with systematic sampling from the rural and urban clusters of segments. The details of sampling design, instrument and survey findings are available for public use [19]. The study sample consists of 199,889 children aged 12–59 months. Of the total 211,773 children, information on the three doses of HBV vaccine was not available for 11,884 children and these observations were dropped from the study.
Identification of the children with hepatitis B vaccination uptake
During the survey, as a part of the core questionnaire, the mothers were asked to show the vaccination card to collect the information on various doses of vaccination including hepatitis B. In case mothers could not show or did not have vaccination card at the time of survey, they were asked whether the child received the doses of hepatitis B vaccine. A child is said to be vaccinated against hepatitis B if he/she was found vaccinated either in card or from mothers reporting. Those mothers who reported “Do not Know” were treated as not vaccinated (1.8% of total cases). This is the standard recommendation by Demographic Health Survey (DHS) to estimate the vaccination coverage among the children [20]. Among 199,889 children aged 12–59 months, only 109, 085 received all the three doses of hepatitis B vaccine. Although NFHS collects the information on the birth dose of hepatitis B, but NFHS provides an estimate of children receiving the three doses of hepatitis B received at 6, 10 and at 14 weeks from the day of birth, independent of the birth dose. As the present study is based upon NFHS data, we considered the last three doses of hepatitis B being received at 6, 10 and 14 weeks to create the outcome variable in this study. Table 6 in Appendix provides hepatitis B vaccine uptake information for all the three doses other than the birth dose among the study children.
It is likely to be some recall bias (non-sampling bias) in the data and it could be in either direction-over reporting or under reporting. Although, checking the validity of mother’s recall was beyond the scope of the study but to reduce the non sampling bias due to mother’s recall, we controlled the socio-economic and demographic factors which mostly determine the pattern of recall bias among mothers [21]. In another account to take care of the sampling bias, we used the “svy” command in Stata version 12.0 SE (STATA Corp LP, College Station,TX) with sampling weights to address the corresponding sampling bias and to get the unbiased estimates.
The analyses have been carried out at district level and at individual level (child). Prior to unit level analyses, the district level analysis is a comprehensive effort to understand the analogy of district level coverage of hepatitis B vaccination and its determinants in a spatial setting because, after states, district is the second administrative and policy relevant unit where demographic events and population health indicators are estimated to track and monitor the health conditions of the general population in India.
Outcome variable
The outcome variable for the district level analysis is the proportion of children aged 12–59 months who received 3 doses of hepatitis B vaccine. In case of child level analyses, the outcome variable is the hepatitis B vaccination status of the child (whether immunized against hepatitis B or not). A child who was given all the three doses of hepatitis B vaccines considered to be vaccinated against hepatitis B virus otherwise not. Thus, the hepatitis B vaccination status of a particular child is a binary variable where ‘1’ is yes which denotes the child received all the three doses and ‘0’ otherwise.
Independent variables
A set of socio-economic and demographic indicators at the district level were used to predict the coverage of hepatitis B vaccine. These include the - (1) percentage of women with 10 or more years of schooling, (2) percentage of mothers who had full antenatal care (ANC), (3) percentage of mothers who received postnatal care (PNC) from a doctor/nurse/LHV/ANM/midwife/other health personal within 2 days of delivery (4) percentage of mothers who received financial assistance under Janani Suraksha Yojana (JSY) scheme for births delivered in an Institution, (5) percentage of institutional births (6) percentage of households with electricity connection, (7) percentage of households with an improved drinking-water source,Footnote 2 (8) percentage of children under age 5 years whose birth was registered and (9) percentage of breastfeeding children receiving an adequate diet.Footnote 3
Spatial analyses
District level variations and determinants were examined using spatial analyses. According to Census of India 2011, there are 640 districts across 36 states and union territories with an average population size of 2 million [22]. These districts vary enormously in demographic, social, economic and health indicators. NFHS-4 for the first time had the distinction of providing demographic and health estimates at the district level.
To understand the spatial clustering of immunization across districts, Local Moran’s I indices were generated to measure the spatial autocorrelation. Similarly, bivariate LISA was used to analyze the association of certain characteristics of regions (districts) with the hepatitis B vaccine coverage across those districts. Such analyses has been increasingly used to understand the spatial heterogeneity in terms of demographic and public health indicators across the population [23]. Moreover, district level spatial analyses are helpful to assess the geographical disparity in health or other concerned indicators and identify the geographical pockets underprivileged in terms of the same [23, 24]. To check the empirical associations between the outcome and independent variables of the study, we preliminarily estimated the ordinary least square (OLS) model and conducted spatial diagnostics of the residuals in OLS model. As the event of study showed a statistically significant Moran’s I, we built up the spatial autoregressive models-spatial lag and spatial error model.
District level quintile maps were generated using Arc-GIS to understand the spatial pattern of child immunization coverage in India. Queen’s contiguity method of order 1 was used to create the spatial weight matrix (w) in the analyses. Arc-GIS version 10.1 and Geo-Da version 1.8.16.4 were used for the spatial analyses.
India digital map
The India shape file was obtained from GitHub through https://github.com/datameet/maps/tree/master/Districts and was used under the Creative Commons Attributions 2.5 India license. The projection of the map was in WGS 1984 UTM zone 43 N.
Unit (child) level analyses
The set of independent variables used in the unit level analyses are child level characteristics, maternal characteristics and household characteristics. The child level characteristics include age of the child (in months), year of birth, sex, birth order, child lives with whom. Age of the child is categorized into four groups (12–23, 24–35, 36–47 & 48–59) while the year of births of the study children are 2010, 2011, 2012, 2013, 2014 & 2015. The birth order refers to the order of the child among all live births to a mother and labeled as first, second, third, fourth etc. Previous studies also explored the variation in child health care utilizations in terms of the birth order of the child [25]. Sex of the child is another important variable considered in this study to find the gender differential of hepatitis B vaccine coverage among the study group of children. Sex is a bio-demographic characteristic of the child and children are classified as male and female. To understand the care given to the children and health care utilization for the children it is important to know whether the child lives with their mother or not. Although we did not find any previous study but we assume that children living with a parent are likely to receive better care. Here the variable is categorized into two following categories- children living with mother & lives elsewhere. The maternal characteristics included in the analyses are mother’s educational attainment, caste and religion. Mother’s educational attainment is classified as no education, up to primary educated, completed secondary education and higher secondary or more educated. Caste is another important social variable that depicts the economic and social well being of the households in India. In India, the population is classified into four caste groups, namely, scheduled caste (SC), scheduled tribe (ST), other backward class (OBC) and others. Among these groups, SC & STs are the most under privileged and secluded groups in India. The national, state and local government in India provides reservation benefits to SC, ST and OBCs in education, employment, health and other related programs. Similarly, we have used four religion groups (Hindu, Muslim, Christianity and others) in the analyses and these three are the major religious groups in India. Wealth quintile in DHS data is a measure to capture the economic well being of the household. It is derived from a set of 37 asset based variables using principal component analysis (PCA). For analytical purpose, the wealth index is grouped into five categories-poorest, poor, middle, richer & richest. Besides, we have used place of residence (rural/urban) and region (North, South, Central, West, East and North East) in the analyses. These classifications are similar to that of NFHS-4 [26].
Bivariate and multivariate regression analyses
Bivariate analysis was used to understand the differentials in vaccination coverage by socio-demographic characteristics. The conditional probabilities were estimated for hepatitis B vaccination conditioned on the background characteristics of the children. And the multivariate logistic regression was used to understand the determinants of hepatitis B vaccination at individual level. Child’s hepatitis B immunization status (received all the three doses of the vaccine -yes/no) has been modeled and adjusted to a set of independent factors. A total of 1, 99,889 children aged 12–59 months consisted the unit level analysis of this study. Stata version 12.0 SE (STATA Corp LP, College Station,TX) was used to analyse the data.