Indian Journal of Spatial Science. Education, Religion, Development and Regional Patterns of Fertility in West Bengal

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1 Indian Journal of Spatial Science EISSN: homepage: ISSN: Education, Religion, Development and Regional Patterns of Fertility in West Bengal 1 Kalyan Sundar Som Prof. R. P. Mishra 2 PhD Research Scholar, UGC SRF, Dr. Hari Singh Gour Central University, Sagar, M. P Professor of Geography, Dr. Hari Singh Gour Central University, Sagar, M. P. & Director, Population Research Center (M.P.& C.G), 1 2 Article Info Article History Received on: 4 November 2016 Accepted in Revised Form on: 20 January 2017 Available Online on and from: 23 March 2017 Key Words Replacement Level Multi-religious Society Gender Bias Religious Fertility Educational Fertility Fertility & Development Abstract The current study analyses the impact of religion, education, and development on the spatial pattern of fertility in West Bengal, where different religions groups live together. Using the data from Fertility Tables of Census of India, 2011, it has considered the parameters of 'parity progression ratios', 'projected parity progression ratios',' TFR', 'age-order specific fertility rates', and 'cumulated order-specific fertility rates' and accordingly analysed. Multiple regression analysis has been used to determine the impact of development and use of contraceptive on fertility in West Bengal, while logistic regression analysis to understand the impact of religion and education on fertility. West Bengal has the lowest total fertility rate (TFR, 2.42) in the country (TFR, 2.89) and its spatial pattern shows that its four southern districts (Haora, Kolkata, South 24 Parganas and Purba Mednipur) and four eastern districts (Burdwan, Nadia, North 24 Parganas and Hugli) have lower TFR ISSS. All Rights Reserved Introduction Fertility differentials by religion and regions have been recorded and analysed in recent decades in our country. Religion does not have any direct impact on fertility but its impact on fertility is recorded by its different characteristics (Goldscheider & Uhlenbeng, 1969 and Day 1984). However, most of the studies conducted have recorded that Muslims' fertility is higher than others religious groups (Algarajan and Kulkarni, 1998). However, some studies have been conducted in the context of Hindu-Muslim fertility differentials and concluded Hindus' fertility is lower than Muslims' (Visaria 1974, Balasubramanian 1984, Das & Pandey, 1985 and Sharif, 1999). In India, the total fertility rate (TFR) has been recorded as 2.98 (Census of India, 2011), where Meghalaya is on the top (TFR, 5.19) of the list and West Bengal lies at the bottom (TFR, 2.41) in India. Present study has analysed the spatial variations of the TFR in West Bengal, that finally helped the identification of the impact of religion on fertility in the state. Among various religious groups, three (Buddhist's , Sikh's , Jain's ) have TFR below the replacement level while two (Hindu's and Muslim's ) are close to the replacement level of fertility. On the other hand, Muslims fertility (TFR ) is much higher than the replacement level (TFR - 2.1). Imai and Sato (2010) strengthen the proposition of the negative association between education and fertility rate by reducing gender bias through the level of education of women and men in Indian context. Education or schooling is expected to contribute to the measures of female autonomy (Basu 2002). It is believed that educated women have more freedom in decision making on a range of domestic and extra domestic matters and also have greater reproductive autonomy than the uneducated ones (Basu, 1992; Morgan and Niraula, 1995; Vlassoff, 1996; Jejeebhoy, 1 Advanced Science Index...ID=1260

2 1995; Sathar 1996). But some studies have shown that only after reaching a certain minimum threshold of education among women does the negative association between these two variables (Education and Fertility) becomes prominent (Jaffe, 1959; Coachrane, 1979 &1983; Encarnaction, 1974; Stycos, 1965). Objectives of Study The main objectives of the present study is to 1. To analyse the spatial pattern of fertility in West Bengal. 2. To analyse the status of fertility among religious groups, educational groups and its spatial pattern. 3. To identify the factors determining the nature and pattern of fertility in West Bengal. 4. To examine the impact of religions, education, and development on the fertility in West Bengal. Methodology 1. Tabulations and Database: a) To work out parity progression ratios (parity by age groups of women aged or more) the data from Census Fertility Table, 2011 (F-2-19 for religious and F for education group) have been used. b) To work out Projected Parity Progression Ratios - (i) Parity by age group of women (aged or less) taken and then calculated from Census Fertility Table, 2011 (F-2-19 and F-3-19). (ii) Number of children born during the preceding the Census, classified by mother's age (in 5 year groups) and number of children ever born from 2011 Census data (F and F-11-19) have been considered. 2. Techniques of Analysis a) TFR andasofr The AOSFRs have been computed using the number of birth data of previous year (F and F Tables of Census of India, 2011), and then to project forward the parity distribution that would be expected for each cohort if those rates continue for the rest of the cohort's childbearing age. This is done by calculating the orderspecific equivalent of total fertility, that is the cumulated fertility rates for birth of the i-th order, cumulated for all age groups. (i) Age-order specific fertility rates: From the tabulation of births in the last year by age group (F and F Tables of Census of India,2011) and parity of mother (F-2-19 and F-3-19 Tables of Census of India,2011), age specific fertility rates for women in each age group 15-19,., have been by using following equation: Where, denotes births in the last year by mother age and parity and has the total number of women in the age group (Moultrie and Zaba). Again, women of unstated parity excluded from the denominator. (ii) Cumulated order-specific fertility r a t e s : Upto age (x+5) for order i, it has been calculated by using following equation: It follows that is a measure of the additional proportional of women expected to achieve parity -I between age x+5 and the end of the reproductive period, on the assumption that future fertility will remain the same as current fertility (Moultrie and Zaba). b) Multiple regression analysis has been done to determine the impact of development (female literacy rate, urbanization, GDP, economic growth rate and live births) and use of contraceptive on population fertility of West Bengal. c)logistic regression analysis has been used to understand the impact of religion on fertility. For this TFR has been converted in dichotomous variables, where less than 2.1(replacement level) TFR assigned as 1 and above 2.1 TFR assigned as two. 2.1 as used referenced because replacement level of the TFR is 2.1. Seven religious groups have been considered and the Hindu religion has been considered as a reference category. For the analysis of impact of education on the fertility the state has been divided into six educational categories and illiterate has been considered as a reference point. On the other hand, the state has been classified into five regions i.e. north, central, east, south and west based on the similar socio-cultural background of the population. Result and Discussion Spatial Pattern of Fertility: The state has the lowest total fertility rate (TFR) 2.42 in the country, where country's average TFR is 2.89 (Census, 2011). State's average TFR was 2.98 in 2001 (census 2001) and had th 8 position in the country after Tamil Nadu, Punjab, Andhra Pradesh, Karnataka, Goa, Gujarat, Tripura. Map 1 shows that four southern districts (Haora, Kolkata, South twenty four pargana and Purba Mednipur) and four eastern districts (Burdwan, Nadia, North twenty four pargana and Hugli) have lower TFR than other districts of the state. Nadia (2.12), North Twenty Four Pargana (2.07), Hugli (2.11) and Kolkata (1.78) have reached below the replacement level of fertility and Burdwan (2.20) and Haora have very nearer to reach the replacement level of fertility. On the other hand, Uttar dinajpur (3.39) and Maldah (3.03) are the districts having higher fertility in the state. Four districts are in the highest TFR category and five districts are in the lowest TFR category in the state (Fig.1). Spatial Pattern of Religious Fertility: Muslim population has recorded highest fertility (TFR-2.909) among all the religious groups while Buddhist 2 Advanced Science Index...ID=1260

3 population has the lowest fertility (TFR-1.951) in the state. It is interesting to mention here that Christians fertility (TFR-2.398) has higher than the Hindu population (TFR-2.225). Sikh, Jain and Other religious category have the fertility of 2.004, and respectively. Out of 19 districts, five districts have reached the below replacement level fertility (TFR<2.1) while nine districts are low ( ) and five districts are moderate ( ) category among Hindu population. On the other hand, no one districts reached below replacement level in case of Muslim population in the state. Among Muslims seven districts have high TFR (>3.01) and seven districts are moderate while only five districts have low TFR. Sikh, Buddhist, Jain have reached below the replacement level fertility in 12, 13 and 9 districts respectively in the state (Table 1). During the district level analysis it is found that Puruliya (TFR-2.95) has highest fertility in terms of Hindu population, while Kolkata (TFR-1.62) has the lowest. Muslims fertility has the highest in the state of Uttar Dinajpur (TFR-4.20) while it is lowest in Kolkata (TFR- 2.38). Uttar Dinajpur (TFR -3.03) has highest Christian fertility while lowest in the district of Kolkata (TFR -1.66). Sikhs, Buddhists and Jains have highest fertility in the districts of Nadia, South 24 Pargana and Dakhsin Dinajpur and lowest in the districts of Uttar Dinajpur, Bankura and Darjeeling (Fig. 2). Spatial Pattern of Educational Fertility: In the state, strong difference exit from illiterate TFR (2.66) to graduate and above TFR (1.62). It is interesting to mention here that education below middle level have little impact on fertility while from below Matric to Secondary (BMA) level and higher have reached to the replacement level of fertility. In the educational group of below primary (BP), primary but below middle (BMI), BMA and below graduate (BG) TFR have recorded 2.50, 2.39, 2.18 and 2.08 respectively in the state. All the districts of the state have recorded below replacement level of fertility among the graduation and above education level of reproductive women. Out of 19 districts, nine have below replacement level fertility while seven are low fertility and three are moderate fertility in case of respondent have achieved matric or secondary but below graduate level. In case of reproductive women Middle but below matric or secondary, only seven districts have reached replacement level of fertility contrast with twelve districts have low and moderate fertility. Kolkata has the only district where the entire educational category recorded below replacement level of fertility. In case of below middle (1 district), below primary (2 districts) and illiterate population (5 districts) have higher fertility (Table 2). Illiterate, below primary and below middle level of education recorded highest fertility in the district of Uttar Dinajpur (TFR-3.73), Uttar Dinajpur (TFR-3.31) and Maldah (TFR-3.02), while Kolkata has the lowest in all three categories. Same condition is recorded in the case of other three education levels (below secondary, graduate and Graduate & above) (Fig. 3). Age-Specific Fertility Rate: In West Bengal, among all the religious groups the highest fertility has recorded in the age group of years. Only Muslims (0.152) population has the higher age specific rate than the state average (0.140). Among lower age group (15-19 years) specific fertility rate has higher than the country average (0.1146). It indicates that the state population has started fertility in very early age but other important things are that they start to stop their fertility in the age group after (25-29 year). It is an indication of more adoption of sterilization method. Muslims have highest age specific fertility while Jains have the lowest one in lower age group in the state (Fig. 4). After the age group of years Muslims fertility has constantly higher when comparison made with others. Above fact clearly indicates that the lower adoption of permanent contraception method (sterilization). This is due to pure religion effect hypothesis that the attribute the differentials to difference in theological perceptions which directly influence the fertility like contraception and abortion (Chamie, 1977 and Iyer 2002). Religious (Hindu-Muslim) Fertility Differentials: In the state, Hindu and Muslim are two major religious groups in the population as in the country. Muslims fertility has higher than the Hindus fertility in all the districts of West Bengal. H-M (Hindu-Muslim) fertility differentials index value in the state is 0.28, while in the country it is Darjeeling and Uttar Dinajpur have higher H-M differentials. Six districts (Puruliya, Kolkata, Maldah, Murshidabad, South 24 Pargana) have moderate H-M fertility differentials and eleven districts have low H-M fertility differentials (Fig.5). Impact of Religion and Education on Fertility: The impact of religion and education is clearly found in this study. It is evident from the data presented in the Table 3,4,5 and 6, it is found that both the religion and educational level have their impact on the fertility but impact of religion is the most prominent factor while deciding the level of fertility. Statistical Test of Predictors The statistical significance of individual regression coefficients (B) is tested using the Wald chi-square statics (Table 5 & 6). Table-5 shows that Hindu, Muslim, Sikh and Buddhist population were significant predictors of TFR of more than 2.41(Sig. <0.05), while Jain population were significant at the level of 0.1. The test of intercept i.e. Constant and Christian population (Table 5) merely suggests that an intercept should be included in the model. For the present data set, the test result (Sig. <0.1) suggested that an alternate model 3 Advanced Science Index...ID=1260

4 without intercept might be applied. It is evident from Table 6 that education level is significant predictors of TFR of more than 2.41(Sig. <0.05). Below graduate (BG), Below Secondary (BMI) and Illiterate population were significant predictors of TFR of more than 2.41(Sig. <0.05) (Table-6). Results Muslim population has 10 times higher occurrence of more than 2.41 TFR as compared to fertility of the Other religious group. All others religious groups have inverse impact of the religious perception on fertility when compare made with the Other religious group. Hindus have ¼ times lower probability to occurrence more than 2.41 TFR as compared to the Other religious group in 2 the state. Christian has / 5 time lower probability to occurrence more than 2.41 TFR as compared to Other religious group. Above mention facts prove that religious difference has highly persisted between Muslims and all other religious groups (Table-5). In case of education, there is not a single case occurred where fertility above 2.41 when graduation and above education level. Illiterate population has 3.75 times probability to record higher 2.41 fertility in the state. Secondary level of educated women has 6 times lower chance to record the TFR above 2.41 as compare to illiterate fertility. Development and Fertility In India population control is performing by two approaches (i) the 'contraceptive for control population fertility and their development' and (ii) the 'development is the best contraceptive'. The meaning of development is changing throughout the period of time i.e. initially 'development' was 'economic development' while later on it has changed towards 'social development' (Dreze and Mutrhi, 2000) and ultimately now it is known as socio-economic development. Present study is based on three indicators, they are social (Female literacy rate, Urbanization and Live birth), economic development indicators (average gross domestic product, and average Economic growth rate, ) and use of contraception (Table 7). The correlation matrix (Table 8) shows that there is very high (-0.85) inverse correlation between total fertility rate (TFR) and female literacy rate (FLR). Female literacy rate has high positive correlation with urbanization, GDP and EGR. These facts prove that education is most prominent and versatile indicator of development in the study area which has also mentioned in various studies (Dube and Mishra, 1981).Correlation between population fertility and use of contraception is very low in this state. Female literacy rate, Urbanization, GDP and Live birth explain 76.05% variability of TFR with significance level of Regression analysis proved that second approach is more useful for curbing the population size and control over fertility (Table 9). The higher female literacy has stimulated the schooling age of women, working environment and that has influenced female autonomy and ultimately it helps in desired family size and low fertility (Basu, 2002). Female literacy rate has mainly controlled above three variables therefore the parsimony variable (female literate rate) and population fertility regression analysis tested. The result shows that female literate rate explain the 71.88% total fertility rate in west Bengal with high significance level (0.001) (Table 10). Conclusion Total fertility rate (TFR) in India has recorded (Census of India, 2011), where Meghalaya is on the top (TFR, 5.19) and West Bengal is on the bottom (TFR, 2.41) in the country. Muslim population has recorded highest fertility (TFR-2.909) among all the religious groups while Buddhist population has the lowest fertility (TFR-1.951) in the state. Christians fertility (TFR-2.398) has higher than the Hindu population (TFR-2.225). Sikh, Jain and Other religious category have the fertility of 2.004, and respectively.among various religious groups, three religious groups (Buddhists- 1.95, Sikhs-2.00, Jains-2.10) have TFR below the replacement level while two religious groups (Hindus and Muslims-2.34) are near to the replacement level of fertility. On the other hand, Muslims fertility (TFR-2.91) has very much higher than the replacement level of fertility (TFR-2.1). In the state strong difference exit from illiterate TFR (2.66) to graduate and above TFR (1.62). Education below middle level have little impact on fertility while from below Matric to Secondary (BMA) level and higher have reached to the replacement level of fertility. Among all the religious groups the highest fertility has recorded in the age group of years. Only Muslims (0.152) population has the higher age specific rate than the state average (0.140). Among lower age group (15-19 years) specific fertility rate has higher than the country average (0.1146). There is very high ( ) inverse correlation between total fertility rate (TFR) and female literacy rate (FLR). Female literacy rate has high positive correlation with urbanization, GDP and EGR. Female literate rate explain the percent total fertility rate in west Bengal with high significance level (0.001).This study Clear the dichotomy and suggest that the development approach is more appropriate rather than contraceptive approach to control population fertility in the state. References 1. Alagarajan, Manoj and Kulkarni, P.M. (1998): Fertility Differentials by Religion in Kerala: A Period Parity Progression Ratio Analysis, Demography India, Vol. 27, No.-1, Pp Balasubramanian, K. (1984): Hindu-Muslim Differentials in Fertility and Population Growth in India: Role of Proximate Variable, Artha Vijnana, Vol. 26, No.-3, Pp Basu, A. M. (1992): Culture, the Status of Women 4 Advanced Science Index...ID=1260

5 and Demographic Behaviour; Illustrated with the Case of India, Oxford, Clarendon Press. 4. Basu, A. M. (2002): Why does Education Lead to Lower Fertility? A critical Review of Some of the Possibilities, World Development, Vol. 30 No. 10, Pp Census of India (2011): Fertility Tables (F-Series) Registrar General India, New Delhi. 6. Chamie, J. (1977): Religious Differentials in Fertility: Lebanon 1971, Population Studies, Vol. 31, No.-2, Pp Coachrane, S. H. (1979): Fertility and Education: What do We Really Know? (World Bank Occasional Papers No. 26), Baltimore, MD: The John Hopkins University Press. 8. Coachrane, S. H. (1983): Effects of Education and Urbanization on Fertility, in R. A. Bulatao and R. D. Lee (Eds.), Determinates of Fertility in Developing Countries (Vol.2, Pp ), New York, Academic Press. 9. Das, N and D Pandey (1985): Fertility Differentials by Religion in India: An Analysis of 1971, Census Fertility Data, Canadian Studies in Population, Vol. 12, No.-2, Pp Day, L. H. (1984): Minority-Group Status and Fertility: A More Detailed Test of Hypothesis, Sociological Quarterly, Vol. 25, No.-4, Pp Dreze J and Murthi M (2000): Fertility, Education and Development, Discussion Paper (DEDPS 20), London School of Economics and Political Science. 12. Dubey, R. S and Mishra R. P. (1981): Level of Education : A Versatile Indicator of Regional Development, Geographical Review of India, Vol. 43, No. 3, Pp Goldscheider, C and Uhlenbeg, P. R. (1969): Minority Group Status and Fertility, American Journal of Sociology, Vol. 74, No.-4, Pp Imai, K. S. and Sato, T (2010): Fertility, Prenatal Education and Development in India: New Evidence from National Household Survey Data (Discussion Paper), Research Institute for Economics and Business Administration, Kobe University, Kobe, Japan. 15. Iyer, S. (2002): Demography and Religion in India, Oxford University Press. 16. Jaffe, A. J. (1959): People, Jobs and Economic Developme nt, Glencoe, IL: Free Press. 17. Jejeebhoy, S. J. (1995): Women's Education, Autonomy and Reproductive Behaviour: Experience from developing countries, Oxford, Clarendon Press. 18. Morgan, S. P. and Nirula, B. (1995): Gender Inequality and Fertility in Two Nepali Villages, Population and Development Review, Vol. 21, No Moultrie, T and Zaba, B (2013): Parity Progression Ratios, in Moultrie, Tom and et al. (eds.), Tools for Demographic Estimation, Pp , UNFPA and IUSSP, Cape Town. 20. Sathar, Z. A. (1996): Women's Schooling and Autonomy as factors in fertility Change in Pakistan; Some Empirical Evidence, In R. Jeffery, and A. M. Basu (Eds.) Girl's Schooling, Women's Autonomy and Fertility Change in South Asia New Delhi, Sage. 21. Sharif, Abusaleh (1995): Socio-economic and Demographic Differentials between Hindu and Muslim in India, Economic and Political Weekly, Vol. 30, No.-46, Pp Stycos, J. M. (1965): Education and Fertility in Puerta Rico, Paper presented at the world conference, Belgrade, Serbia. 23. Visaria, L (1974): Religious Differentials in Fertility, in A. Bose et al. (eds.), Population in India's Development, Pp , Vikas Publishing House, Delhi. 24. Vlassoff, C. (1996): Against the Odds: The Channing Impact of Schooling on Female Autonomy and Fertility in an Indian Village, In R. Jeffery, and A. M. Basu (Eds.) Girl's Schooling, Women's Autonomy and Fertility Change in South Asia New Delhi, Sage. Table - 1: Religion * TFR Cross Tabulation Religion <2.1 TFR >3.01 Total Hindu 5 (26.32%) 9 (47.37%) 5 (26.32%) 0 19 Muslim 0 5 (26.32%) 7 (36.84%) 7 (36.84%) 19 Christian 5 (26.32%) 9 (47.37%) 4 (21.05%) 1 (5.26%) 19 Sikh 12 (63.16%) 2 (10.53%) 2 (10.53%) 3 (15.79%) 19 Buddhist 13 (72.22%) 1 (5.56%) 4 (22.22%) 0 18 Jain 9 (50%) 3 (16.67%) 4 (22.22%) 2 (11.11%) 18 Others 3 (15.79%) 5 (26.32%) 10(52.63%) 1 (5.26%) 19 Total 47 (35.88%) 34 (25.95%) 36 (27.48%) 14 (10.69%) 131 Source: Calculated by the authors by using 2011 Census data. Note: Percentage of each category is given in brackets. 5 Advanced Science Index...ID=1260

6 Table - 2: Educational Status of the Respondent * TFR Cross Tabulation Educational Status of the Respondent <2.1 TFR >3.01 Total Graduate and above 19 (100%) Matric or secondary but below graduate 9 (47.37%) 7 (36.84%) 3 (15.79%) 0 19 Middle but below matric or secondary 7 (36.84%) 9 (47.37%) 3 (15.79%) 0 19 Primary but below middle 1 (5.26%) 12 (63.16%) 5 (26.32%) 1 (5.26%) 19 Literate but below primary 1 (5.26%) 8 (42.11%) 8 (42.11%) 2 (10.53%) 19 Illiterate 1 (5.26%) 6 (31.58%) 7 (36.84%) 5 (26.32%) 19 Total Source: Calculated by the authors by using 2011 census data. Note: Percentage of each category is given in brackets Table - 5: Logistic Regression Analysis-Impact of Religion Count B S.E. Wald df Sig. Exp(B) Religion Hindu Muslim Christian Sikh Buddhist Jain Constant (Others) Source: Calculated by the authors by using 2011 Census data. Table -6: Logistic Regression Analysis-Impact of Education Count B S.E. Wald df Sig. Exp(B) Educational Status Graduate and above E Matric or Secondary but below Graduate Middle but below Matric or Secondary Primary but below Middle Literate but below Primary Constant (Illiterate) Source: Calculated by the authors by using 2011 census data 6 Advanced Science Index...ID=1260

7 Table - 7: Population fertility and Development Indicators, West Bengal Districts TFR FLR Urbanizati on GDP EGR Live Birth Contrace ptive use Uttar Dinajpur Maldah Puruliya Murshibad Jalpaiguri Koch Bihar Purba Mednipur Birbhum Bankura South 24 Parganas Paschim Mednipur Darjeeling Haora Dakhsin Dinajpur Burdwan Nadia Hugli North 24 Parganas Kolkata Source: (i) TFR are calculated by authors. (ii) FLR and Urbanization data used from Census (iii) Average GDP and EGR are calculated from data source data.govt.in (iv) Live birth and contraceptive data used from DLHS-4 Table - 8: Correlation matrix Population fertility and Development Indicators TFR FLR UR GDP EGR LB TFR 1 FLR UR GDP EGR LB Source: Calculated by authors. Table - 9: Population fertility and Development Indicators Estimate Std. Error t value Pr(> t ) (Intercept) 7.095e e ** Female Literacy Rate e e ** Urbanization e e Gross Domestic Product e e Live Birth e e Signif. codes: 0 *** ** 0.01 * Multiple R-squared: , Adjusted R-squared: 0.692, p-value: Source: calculated by authors. Table - 10: Population fertility and Female literacy rate Estimate Std. Error t value Pr(> t ) (Intercept) e-10 *** Female Literacy Rate e-06 *** Signif. codes: 0 *** ** 0.01 * Multiple R-squared: , Adjusted R-squared: , p-value: 4.566e-06 Source: calculated by authors 7 Advanced Science Index...ID=1260

8 Fig. 1 Fig. 2 Fig. 4: Age - Sex Fertility Pattern of West Bengal Fig. 3 4 Kalyan Sundar Som Senior Research Fellow (UGC) Department of General & Applied Geography Dr. H. S. G. Central U niversity, Sagar, M.P. kalyansundarsom@gmail.com Prof. R. P. Mishra Professor of Geography & Director, Population Research Centre (M.P. & C.G.) Department of General & Applied Geography Dr. H. S. G. Central U niversity, Sagar, M.P. Fig. 5 mishrarp80@gmail.com 8 Advanced Science Index...ID=1260