The determinants of low fertility in rural and urban West Bengal, India Sayantani Chatterjee International Institute for Population Sciences, Mumbai 1. Background India, at the national level, is currently undergoing fertility transition with its Total Fertility Rate falling from a mammoth 5.2 in 1971 to a mere 2.3 in 2013 (Sample Registration System, 2014). However, the fertility levels and patterns vary widely from region to region in India. The northern part of India is characterized by high fertility rates, but the southern part is differentiated by a below replacement level fertility (Sample Registration System, 2014; Guilmoto and Rajan, 2002). West Bengal, lies in the eastern part of the country. The unique geographical features of West Bengal include Himalayas in the extreme north, the Rarh regions in the west, the fertile Gangetic plains in the south-eastern regions and the coastal Sunderbans in the south engulfed by Bay of Bengal . W ith a population of 91,347,736, West Bengal stands out to be the fourth most populous state in India with 31.87% of them residing in urban areas (Census of India, 2011). Situated in an obscure location, West Bengal lies between the much talked about North- South demographic divide of India (Dyson and Moore, 1983; Bhat 1996). Lying somewhere in the middle of the North-South Demographic Divide, from the very beginning West Bengal shows a fertility rate which is lower than the national level (Bangladesh was a part of undivided Bengal before independence). There was a decline in fertility rates in urban areas which was followed by the reduction in fertility rates in rural areas. Fertility in the urban areas in early 1980s was quite low as compared to the rural areas which started following a downward slope in the late 1980s which still continues. Thus, the urban-rural gap in fertility measures have narrowed down over time in the state. Rural-urban differential in fertility patterns dates back to the early studies on fertility (Robinson, 1961; Kuznets, 1974) and the ideas are still consistent with the contemporary works (Guilmoto and Rajan, 2002; Sample Registration System, 2014; Khan, 2013). Although Kuznetz (1974) found that the gap in fertility was moderate in case of developing countries such as South Asia and Africa when compared to the developed countries. In India, there is moderate difference in rural and urban sectors at the state levels. Not too many studies have investigated the rural-urban diffusion processes within the state boundaries. Even though the fertility levels have remained low in West Bengal, the determinants of low fertility affecting the rural and urban places need not be the same. Say, a factor such as son preference might be more dominant in rural village which might evoke the fertility process in the rural areas but such sex discrimination might be non-existent in the urban places. Age at marriage is a pronounced factor affecting fertility as it raises the mean age at first childbearing following the conjecture that fertility is concentrated within marriages in India (Nag, 1984; Bongaarts, 2001; Das, 2004). Fertility rates provided by Sample Registration System in India (SRS) over the years vividly explain the periodic changes in the fertility indicators in different states, often classifying them in terms of rural-urban or sex differentials. Studies have time and again shown that the district- level fertility rates are not homogenous and are often contoured by very specific causes. The districts of India, serving as the bridge between state and household level, provides an extensive scope to identify inherent factors affecting fertility at macro-level. Notably, the state capital Kolkata (formerly known as Calcutta) underwent fertility transition from 1970s and had achieved the lowest Total Fertility Rate (2.0) in the country (Bhat, 1996) before any other place, 1
a rank it maintains to date (in 2011, TFR for West Bengal was 1.7 and for Kolkata it was 1.2) (Bhat, 1996; Guilmoto and Rajan, 2013; Census of India, 2011). There have been considerable efforts to render estimates of fertility rates of districts of India using indirect methods (Bhat, 1996; Guilmoto and Rajan, 2002, 2013). The most commonly used methods of indirect methods for the estimation of fertility rates are P/F ratio method, Arriaga Method, Rele Method, Bougue- Palmore’s method and the Reverse Survival (RSV) Method. Among all these, RSV is the most widely used technique. Bhat (1996) used this method to obtain district level estimates of Crude Birth Rates (CBRs) and Total Fertility Rates (TFRs) (the most commonly used rates for understanding fertility) based on population aged 0-6 years using data from 1981 and 1991 censuses of India. Following his footsteps, Guilmoto and Rajan (2002, 2013) used this technique based on 0-6 population to obtain estimates for CBRs for all 594 districts of India. Later, they used the ratio of TFR to CBR to derive estimates of TFR. In the recent times, Mohanty et al. (2016) using 0-6 population and RSV technique estimated CBR and TFR for all districts of India for 2001 and 2011. Das and Mohanty (2012) estimated CBR and TFR using the same technique using data from 0-6 population from Census of India, 2011 and other data from DLHS 3 (2007-08). There are many studies which have outlined the state pattern of fertility transition and what prioritize it but there is still a dearth of studies focusing solely on the levels and patterns of fertility within state borders. The district-level fertility estimates are available from previous studies (Guilmoto & Rajan, 2002, 2013) but the rural urban gaps in fertility estimates were not captured. State-level variations in rural-urban fertility also shown by Sample Registration System (SRS). This present study tries to consolidate these two aspects for West Bengal which shows some interesting characteristics such as relying more on traditional methods of contraception, higher usage of modern contraceptives in the rural place than in urban places, people enlightened with the the knowledge of contraception and trying to limit pregnancies from 1940s onwards. Bearing these ideas, the primary objective of the paper is to compute fertility estimates by place of residence for all districts of West Bengal to understand whether rural-urban differences prevail in fertility rates at district-level. The second objective of the paper is to explore what district-level factors affect low fertility in the state. 2. Methodology 2.1 Sources of Data The present study is based on various sources of data. Primarily, for estimating the fertility rates, data were obtained from Census of India, 2011 (http://censusindia.gov.in). Census is conducted in every ten years in India with the reference date and time as of 1 st March, 12 am. It covers extensive information on different parameters of population and provides scope to analyse fertility, migration, mortality, development etc. According to the census reports of India, 2011, the total population of India is 1,210,854,977 comprising of 623,724,248 males and 586,469,174 females. Since, this present paper deals with West Bengal, we focused on 91,276,115 individuals of which 62,183,113 and 29,093,002 constitute rural and urban populations respectively. The life table populations were derived from the life tables readily available from Sample Registration System Reports (http://www.censusindia.gov.in/Vital_Statistics/SRS_Life_Table/Srs_life_Table.html). The questionnaire of Census of India does not focus on fertility preferences of couples, hence the data pertinent to any contraception use by currently married women in the age group 15-49 years were obtained using District Level Household and Facility Survey (DLHS) 3 (2007-08) which provides information on district-level contraception use by currently married women in 2
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