Vital statistics >> SRS Newletters >> eCENSUSIndia : Issue Number 13 : 2002
 
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Features article on Vital rates by Natural Divisions in India
Updated article on Vital rates by Natural Divisions in India

Understanding the Vital Rates - Births, Deaths and Infant Mortality Rate - at Natural Division Level

            As a result of the concerted efforts undertaken by the government and some other agencies it has been possible to substantially lower the vital rates in India. Various health programmes including Maternal Health Care (MCH) programme, universal immunization, safe motherhood and the family planning programme have directly contributed toward this visible decline in the last two decades. Table 1 summarizes the decline of the vital rates in India over 1971 to 2000.
 

Table 1
Vital rates for India - 1971 - 2000

YearCrude Birth RateCrude Death RateInfant Mortality Rate
197136.914.9129
197634.415.0129
198133.912.5110
198632.611.196
1991*29.59880
199627.59.072
200025.88.568

Source : Sample Registration System, Office of the Registrar General, India
*-Excludes Jammu & Kashmir

            At the state level, however, the trend in decline of vital rates shows a mixed pattern. Whereas some states have shown remarkable improvements in the pursuit of lowering the birth rate, death rate and infant mortality rate mainly due to the seriousness with which the programmes mentioned above were implemented over the years, some other states could achieve only limited progress. The Hindi speaking heartland of the country, comprising of Rajasthan, Himachal Pradesh, Haryana, Uttar Pradesh, Madhya Pradesh and Bihar, where about 44% of the population of the country live, significant decline in the vital rates is still far away with the sole exception of Himachal Pradesh. Table 2 would illustrate this further:
 

Table 2
Crude birth rate, Crude death rate and Infant mortality rate by states, 1997-99

Birth rate

INDIA (26.4), Kerala (18.0), Tamil Nadu (19.1), West Bengal (21.5), Andhra Pradesh (22.2), Maharashtra (22.2), Karnataka (22.3), Punjab (22.4), Himachal Pradesh (23.0), Orissa (25.4), Gujarat (25.5), Haryana (27.6), Assam (27.7), Madhya Pradesh (31.2), Bihar (31.5), Rajasthan (31.6), Uttar Pradesh (32.9)

Death rate

INDIA (8.8), Kerala (6.4), West Bengal (7.4), Punjab (7.5), Maharashtra (7.5), Himachal Pradesh (7.7), Karnataka (7.7), Gujarat (7.8), Haryana (8.0), Tamil Nadu (8.2), Andhra Pradesh (8.5), Rajasthan (8.7), Bihar (9.4), Assam (9.9), Uttar Pradesh (10.4), Orissa (10.9), Madhya Pradesh (10.9)

Infant Mortality rate

INDIA (70.5), Kerala (14.1), Maharashtra (48.0), Tamil Nadu (52.6), Punjab (52.8), West Bengal (53.6), Karnataka (61.4), Himachal Pradesh (61.4), Gujarat (63.2), Andhra Pradesh (65.2), Bihar (67.0), Haryana (68.6), Assam (76.0), Rajasthan (83.1), Uttar Pradesh (85.1), Madhya Pradesh (94.0), Orissa (96.9)


            As the Hindi Belt also includes one of the most densely populated area of the country, the Gangetic Plains, the slow decline in vital rates is adversely affecting the overall efforts in improving the living condition of the population in this area. It is important to consider the disaggregated vital rates at the sub-state level in districts or regions. One of the reasons for not publishing vital rates at district level is the insufficient sample size on which the rates are estimated based on Sample Registration System (SRS) survey. Lower the sample size, higher the error, which is likely to creep in while estimating the vital rates. Though census releases indirect estimation of vital rates at district level on the basis of the decennial census data, the decade long gap in the availability of data at district level restricts its effective use in formulating intervention strategy and evaluation at regular short intervals, which otherwise is available every year through SRS.

            In this article an attempt has been made to analyse the data at the natural division level, which comprises of a number of administrative districts. The estimation of vital rates at natural division level has less sampling errors than at district level. Furthermore many scholars are now holding the view that due mainly to greater homogeneity and uniformity in the cultural ethos and socio-economic and demographic conditions of the people living in the natural divisions than in the form of administrative districts, it is possible to delineate the areas of disparity by natural divisions. The picture emerging seems to represent a more realistic pattern of the differences or similarities existing for a particular characteristic. The natural division used here for the analysis conforms to the natural divisions used by the NSSO.