Supplementary appendix This appendix formed part of the original submission and has been peer reviewed. We post it as supplied by the authors. Supplement to: Guilmoto CZ, Saikia N, Tamrakar V, Bora JK. Excess under-5 female mortality across India: a spatial analysis using 2011 census data. Lancet Glob Health 2018; 6: e650 58.
Appendix to: Excess female under-five deaths in India: estimates, regional distribution and socioeconomic correlates by Christophe Z Guilmoto, Nandita Saikia, Vandana Tamrakar, and Jayanta Kumar Bora Contents Appendix 1: Summary birth history method to estimate under-five mortality rate...2 Appendix 2: Application of the summary birth history method to the 2011 census data...4 Appendix 3: Estimation of the number of excess female births under five...6 References...7 Appendix 4: Estimated U5MR rate by sex, excess female under-five mortality rate, annual number of excess female deaths, India, states, and districts (attached as a supplementary document)...8 1
Appendix 1. Summary birth history method to estimate under-five mortality rate The indirect method of estimating of child mortality using fertility data was developed by demographers Brass and Coale in the 1960s (Brass 1964; Brass and Coale 1968) for countries lacking reliable death registration statistics. The so-called Brass method, also known as Summary Birth History (Hill 2013), is based only on two basic questions collected from women classified by age groups: 1) the number of children ever born and 2) the proportion still alive (or dead) at the time of the survey. The original Brass method has recorded several refinements by Trussell (Trussell 1975) and Palloni-Heligman (Palloni and Heligman1985) is widely used by international agencies (UN 1983; UN 1990; Hill 2013) as a standard procedure for the indirect estimation of infant and child mortality rates in countries with limited or deficient data. The summary birth history method was in particular one of the methods used by the United Nations Inter-agency Group for Child Mortality Estimation to track country specific changes in the key indicator for Millennium Development Goal 4 (Hill et al 2012). A recent comparative study confirmed the consistency and quality of the summary birth method for populations experiencing smooth mortality decline (Silva 2012), a situation applicable to India where mortality decline has been gradual over the last decades. Method, Assumptions, Steps and Limitations The only two pieces of information required for the application of summary birth history method are a) the aggregated numbers of children ever born and b) the children surviving reported by women classified by age group. The basic principle of this method is that the proportion of dead children among children born to women by age reflects the level of child mortality and that the proportions of deceased children can be converted into mortality rates with the help of fertility and child models. Since young mothers generally have young children, the proportion of children dead for such mothers reflects child mortality risks below age 1 or 2. In contrast, older mothers have a mix of young and older children that have been exposed to the risk of dying for longer periods. Estimation of under-five mortality using Brass method depends on several assumptions, viz. 1) The model patterns used represent the age patterns of fertility and child mortality. 2) Child mortality does not differ by five-year age grouping of mothers. 3) Mortality risks of children and of mothers are not correlated. 4) Mortality change has been both gradual and unidirectional in the recent past. 5) Cross-sectional average numbers of children ever born by age reflect the cohort patterns of childbearing. All these but the second assumption are applicable in the Indian scenario. The assumption that mortality of children does not vary by five-year grouping of mothers is generally incorrect. Children of young mothers appear to have systematically higher mortality than children born to women after age 25. As a result, indirect estimates derived from women aged 15-19 and 20-24 years tend to over-estimate the population-level child mortality. To avoid this, we used the best estimation strategy described in appendix 2. The third assumption is not valid in countries with high HIV prevalence and where there is a strong correlation between child and adult mortality. 2
The steps to apply the summary birth history method are the following: 1. Computation of the average number of children ever born and the proportions dead, For each five-year group (x, x + 5) of women, we divide the reported number of children born 5CEBx by the number of women 5Nx (irrespective of marital status) to compute the average number of children born (5Px). The proportions of children dead (5PDx) are calculated by dividing the number of children dead by the number ever born. 2. Selection a model life table family. Following the review of literature (Saikia et al 2013), we used South Asian pattern of United Nations model life tables. 3. Estimation of the mean age at fertility This age m is computed from age-specific fertility rates 5fx as follows: m 45 5 f x( x 2) x 15,5 45 5 x 15,5 f x, where x+2 is the mid-point of age group (x to x+5); 4. Estimation of mortality probabilities from the proportions of children deceased Once a model life table family j has been identified, the appropriate parameters a(x,j), b(x,j) and c(x,j) and d(x,j) are substituted into the following equation: 5 n q0 PD x 5 P15 5 P20 a( x, j) b( x, j) c( x, j) d( x, j) m P P 5 20 where nq0 is the probability of dying from birth till age n and the coefficients a, b, c and d are derived from standard values (UN Population Division 1983; 1991). 5. Estimation of the time reference of mortality estimates The time reference t(x) of each nq0 are computed with the following formula by using the parameters e(x,j), f(x,j) and g(x,j) computed from the model life table family j : t( x) P 15 5 20 e( x, j) f ( x, j) 5 f ( x, j ), 5 P20 5 P25 The coefficients can be found in UN Population Division (1983; 1991). 5 25 P 3
Appendix 2. Application of the summary birth history method to the 2011 census data Indirect estimates derived from information on various age groups of women provide a set of under-five mortality estimates corresponding to various reference period. While indirect estimates derived from younger women tend to overestimate the population-level under-five mortality, the same based on older women tend to underestimate the population level underfive mortality (Hill 2013). Therefore, we need to choose estimates that best represent the population-level U5MRs. To choose the best estimates, we did a detailed consistency analysis of census-based U5MRs with that obtained from National Family Health Survey (IIPS and Macro International 2007) Sample Registration System (Registrar General India 2012) and WHO (2017) estimates. Figure 1 compares estimates of U5MRs (female and male respectively) from the census with estimates from SRS (Sample Registration System), WPP, WHO and NFHS (National Family Health Survey). Census based estimates are shown by a red color line. Figure 1. Comparison of U5MR from Census based on information of women from various cohorts and other sources, India Figure 1 Note: Cs2011=2011 Census based estimates; SRSLT: estimates from Sample Registration System life tables; WPP2015: estimates from World Population Prospects, 2015; WHO LT: estimates from WHO life tables; NFHS 3=Estimates from National Family and Health Survey 2005-2006. Each census under-five mortality rate is estimated on the basis of information by one particular age group of women. For instance, according to the information of 15-19 aged women, the under-five female mortality is 143 (per 1000 live births) in 2010. As already pointed out, estimates based on the information of women aged 15-24 are often unreliable and appear distinctly higher than corresponding SRS or WHO estimates. The highest level of concordance between census-based U5MRs and other estimates is observed for the estimates derived from the age group 35-39, which will be therefore retained for our district estimates. Figure 2 compare estimates based on 35-39 age groups with estimates from other non-census sources. The reference period computed for these estimates is 2000-05. 4
Figure 2. Comparison of U5MR from Census based on information women aged 35-39 and other sources, India Figure 2 Note: Cs2011=2011 Census based estimates; SRSLT: estimates from Sample Registration System life tables; WPP2015: estimates from World Population Prospects, 2015; WHO LT: estimates from WHO life tables; NFHS 3=Estimates from National Family and Health Survey 2005-2006. 5
Appendix 3. Estimation of the number of female births under five To convert excess female mortality rates into absolute numbers of excess deaths, we first compute the size of the birth cohorts in 1996-2011 by using the census figures and survival estimates during the decade preceding the census: where f B0 B f 0 (1996,2011) ( 1996,2011) 14 N f 0 (2011)* 14 =Female births between 1996 to 2011; 1 S f 0 14 N f 0 (2011) =Females of aged 0-14 during 2011 census f 14 S 0 = Female survival probability between age 0 and 14 taken from South Asian Life table for corresponding levels of female U5MR obtained in our indirect estimation. We divide this number of births during 1996-2011 to get the average size of annual birth cohorts. 6
References of appendices Brass W., & Coale A. J., (1968). Methods of analysis and estimation. In Brass, W, AJ Coale, P Demeny, DF Heisel, et al. (Eds), The Demography of Tropical Africa. pp. 88-139. Princeton NJ: Princeton University Press. Brass, W., United Nations Economic and Social Council, and United Nations Economic Commission for Africa (1964 11). 1964. Uses of census and survey data for the estimation of vital rates. Paper presented at the UN ECA African Seminar on Vital Statistics, Addis Ababa, December 14 19. Hill, K. (2013). Indirect estimation of child mortality. In Moultrie TA, RE Dorrington, AG Hill, K Hill, IM Timæus and B Zaba (Eds), Tools for Demographic Estimation. Pp. 148-164. Paris: International Union for the Scientific Study of Population. demographicestimation.iussp.org Hill, K., You, D., Inoue, M., & Oestergaard, M. Z. (2012). Child mortality estimation: accelerated progress in reducing global child mortality, 1990 2010. PLoS medicine, 9(8), e1001303. International Institute for Population Sciences (IIPS) and Macro International.. National Family Health Survey (NFHS-3), 2005 06: India: Mumbai: IIPS,2007 Palloni, A., & Heligman, L. (1985). Re-estimation of structural parameters to obtain estimates of mortality in developing countries. Population Bulletin of the United Nations, (18), 10. Registrar General India. SRS Based Abridged Life Tables 2003-07 to 2006-10. SRS Analytical Studies. Report No 1 of 2012. New Delhi, 2012. http://www.censusindia.gov.in/ vital_statistics/ SRS_Based/ SRS_Based.html (accessed 11 August 2017). Saikia, N., Singh, A., & Ram, F. (2013). Adult male mortality in India: An application of the widowhood method. Asian Population Studies, 9(3), 244-263. Silva, R. (2012). Child mortality estimation: consistency of under-five mortality rate estimates using full birth histories and summary birth histories. PLoS medicine, 9(8), e1001296. Trussell, T. J. (1975). A re-estimation of the multiplying factors for the Brass technique for determining childhood survivorship rates. Population studies, 29(1), 97-107. UN (1990). Step by step guide to the estimation of child mortality. Population Studies, No 107. Available at http://www.un.org/en/development/desa/population/publications/pdf/mortality/st epguide_childmort.pdf Accessed on 28 th November 2017. UN Population Division. 1983. Manual X: Indirect Techniques for Demographic Estimation. New York: United Nations, Department of Economic and Social Affairs, ST/ESA/SER.A/81. http://www.un.org/esa/population/techcoop/demest/manual10/ manual10.html UN Population Division. 1991. Child Mortality in Developing Countries. New York: United Nations, Department of Economic and Social Affairs, ST/ESA/SER.A/123. WHO 2017. Life Tables by Country India. http://apps.who.int/gho/data/ view.main. 60740? lang=en (accessed 11 August 2017). 7
Appendix 4. Estimated U5MR rate by sex, excess female under-five mortality rate, annual number of excess female deaths, India, states, and districts (attached as a supplementary document) (i) State U5MR (per 1000 live births) Male Female Excess female mortality rate below 5 8 95% confidence interval Lower bound Upper bound Annual number of excess female deaths below 5 95% confidence interval Lower bound Upper bound Jammu & Kashmir 64.7 64.2 10.2 5.4 15.0 1436 761 2111 Himachal Pradesh 62.1 55.3 3.5-1.3 8.3-264 97-624 Punjab 57.4 61.9 14.3 9.5 19.1 3234 2152 4316 Chnadigargh 50.6 48.6 6.9 2.1 11.6 58 18 99 Uttarakhand 62.2 68.3 16.4 11.7 21.2 1735 1230 2239 Haryana 70.9 81.1 21.6 16.8 26.4 5319 4142 6496 Delhi 61.0 76.7 26.0 21.2 30.8 3942 3216 4668 Rajasthan 86.2 98.6 25.4 20.6 30.2 20963 17021 24905 Uttar Pradesh 94.3 111.0 30.5 25.7 35.2 76782 64729 88836 Bihar 80.2 96.7 28.9 24.1 33.6 42538 35490 49586 Sikkim 68.7 60.2 2.7-2.1 7.5 16-12 43 Arunachal Pradesh 103.4 105.3 16.4 11.6 21.2 297 211 384 Nagaland 74.4 83.2 20.6 15.8 25.4 490 377 604 Manipur 52.9 52.6 8.9 4.1 13.7 260 120 401 Mizoram 68.0 64.8 7.9 3.1 12.7 98 39 158 Tripura 82.8 85.2 15.0 10.3 19.8 545 372 718 Meghalaya 114.3 120.6 21.5 16.7 26.3 942 732 1152 Assam 85.1 87.8 15.6 10.8 20.3 5693 3943 7443 West Bengal 67.1 66.8 10.6 5.8 15.4 9167 5040 13293 Jharkhand 88.4 93.0 17.8 13.0 22.5 7536 5506 9565 Odisha 100.8 100.1 13.5 8.7 18.3 5897 3810 7985 Chhattisgarh 100.7 92.3 5.9 1.1 10.7 1736 324 3149
Madhya Pradesh 104.2 111.8 22.1 17.3 26.9 19302 15123 23480 Gujarat 65.8 70.9 16.0 11.2 20.7 9331 6534 12128 Daman and Diu 47.2 39.3 0.5-4.3 5.3 1-8 9 Dadra and Nagar Haveli 61.7 56.1 4.7-0.1 9.5 17 0 35 Maharashtra 60.0 59.8 9.8 5.1 14.6 9850 5063 14637 Andhra Pradesh 76.1 71.8 7.8 3.0 12.5 5889 2259 9518 Karnataka 76.9 75.0 10.2 5.5 15.0 5744 3064 8424 Goa 64.0 55.1 1.8-3.0 6.6 25-42 91 Lakshadweep 81.3 72.1 3.3-1.5 8.1 2-1 5 Kerala 32.7 27.8 1.4-3.4 6.1 358-902 1617 Tamil Nadu 63.3 61.7 9.0 4.2 13.8 825 385 1264 Puducherry 58.7 60.1 11.3 6.6 16.1-402 -232-572 Andaman & Nicobar Island 61.1 58.4 7.6 2.8 12.4-44 -16-72 India 79.7 85.2 18.5 13.1 22.6 239317 169138 292991 (ii) State Dist Name U5MR (per 1000 live births) Male Female Excess female mortality rate below 5 95% confidence interval Lower bound Upper bound Annual number of excess female deaths below 5 95% confidence interval Lower bound Jammu & Kashmir Kupwara 80.7 82.7 14.5 9.7 19.3 188 126 251 Jammu & Kashmir Badgam 46.0 48.5 10.8 6.0 15.5 108 60 156 Jammu & Kashmir Leh(Ladakh) 94.5 105.8 4.0-0.8 8.8 4-1 9 Jammu & Kashmir Kargil 177.9 161.9 0.6-4.1 5.4 1-7 9 Jammu & Kashmir Punch 73.4 76.0 14.3 9.5 19.0 87 58 116 Jammu & Kashmir Rajouri 59.3 65.0 15.7 10.9 20.5 119 83 156 Jammu & Kashmir Kathua 52.5 53.9 10.5 5.7 15.3 63 34 92 Upper bound 9
Jammu & Kashmir Baramula 67.9 64.2 7.4 2.6 12.2 86 30 143 Jammu & Kashmir Bandipore 84.8 76.1 4.1-0.7 8.9 19-3 42 Jammu & Kashmir Srinagar 57.1 57.6 10.2 5.4 15.0 113 60 167 Jammu & Kashmir Ganderbal 65.9 68.6 13.5 8.7 18.2 49 32 67 Jammu & Kashmir Pulwama 58.3 54.7 6.3 1.5 11.1 38 9 67 Jammu & Kashmir Shupiyan 68.4 56.4-0.9-5.7 3.8-3 -18 12 Jammu & Kashmir Anantnag 63.3 58.8 6.0 1.3 10.8 84 18 151 Jammu & Kashmir Kulgam 72.7 68.7 7.6 2.8 12.4 38 14 62 Jammu & Kashmir Doda 75.8 73.5 9.7 4.9 14.5 51 26 76 Jammu & Kashmir Ramban 85.3 76.4 4.0-0.8 8.8 16-3 34 Jammu & Kashmir Kishtwar 80.3 80.9 13.1 8.3 17.8 39 24 53 Jammu & Kashmir Udhampur 70.9 71.0 11.5 6.7 16.3 70 41 99 Jammu & Kashmir Reasi 81.6 78.0 9.0 4.2 13.8 37 17 56 Jammu & Kashmir Jammu 45.0 46.8 9.9 5.1 14.6 116 60 173 Jammu & Kashmir Samba 42.4 47.9 13.2 8.4 18.0 35 22 48 Himachal Pradesh Chamba 65.6 61.3 6.5 1.7 11.3 36 10 62 Himachal Pradesh Kangra 68.0 49.0 1.4-3.4 6.1 16-42 74 Himachal Pradesh Lahul & Spiti 60.5 58.3 8.0 3.2 12.8 2 1 3 Himachal Pradesh Kullu 70.3 65.3 6.4 1.6 11.2 26 7 45 Himachal Pradesh Mandi 54.5 55.4 10.3 5.5 15.1 90 48 132 Himachal Pradesh Hamirpur 68.0 35.1 1.0-3.8 5.8 4-13 21 Himachal Pradesh Una 68.0 47.8 5.0 0.2 9.8 22 1 43 Himachal Pradesh Bilaspur 68.0 47.4 4.0-0.8 8.8 12-2 27 Himachal Pradesh Solan 66.0 58.9 3.7-1.0 8.5 19-5 43 Himachal Pradesh Sirmaur 88.8 72.0-3.5-8.3 1.3-19 -45 7 Himachal Pradesh Shimla 64.1 60.0 6.5 1.7 11.3 43 11 74 Himachal Pradesh Kinnaur 74.0 64.7 2.5-2.3 7.2 2-2 5 Punjab Gurdaspur 51.5 53.3 10.8 6.0 15.6 199 110 287 Punjab Kapurthala 52.1 54.1 11.1 6.3 15.9 72 41 103 Punjab Jalandhar 53.1 53.1 9.2 4.4 14.0 156 75 236 Punjab Hoshiarpur 50.6 53.9 12.2 7.4 17.0 154 93 214 10
Punjab Shahid Bhagat Singh Nagar 66.9 63.4 7.5 2.7 12.2 36 13 59 Punjab Fatehgarh Sahib 50.3 59.1 17.6 12.8 22.4 80 59 102 Punjab Ludhiana 50.1 53.1 11.8 7.0 16.6 331 197 466 Punjab Moga 86.1 77.4 4.3-0.5 9.1 35-4 75 Punjab Firozpur 62.6 68.4 16.3 11.5 21.1 299 211 387 Punjab Muktsar 82.7 71.2 1.2-3.5 6.0 9-27 46 Punjab Faridkot 63.6 72.2 19.1 14.4 23.9 98 74 123 Punjab Bathinda 63.1 65.4 12.8 8.0 17.6 141 89 194 Punjab Mansa 78.0 81.8 16.0 11.2 20.8 104 73 135 Punjab Patiala 55.5 65.9 19.9 15.1 24.6 303 230 376 Punjab Amritsar 45.9 56.9 19.2 14.4 24.0 391 294 488 Punjab Tarn Taran 52.7 66.7 23.2 18.4 28.0 233 185 282 Punjab Rupnagar 57.8 65.5 17.5 12.7 22.3 96 70 122 Punjab Sahibzada Ajit Singh Nagar 43.5 49.2 13.5 8.8 18.3 108 70 146 Punjab Sangrur 72.1 82.3 21.8 17.0 26.6 297 232 362 Punjab Barnala 63.8 67.7 14.5 9.7 19.3 70 47 93 Chnadigargh Chandigarh 50.6 48.6 6.9 2.1 11.6 58 18 99 Uttarakhand Uttarkashi 74.3 76.1 13.5 8.8 18.3 51 33 69 Uttarakhand Chamoli 49.6 54.9 14.1 9.3 18.9 57 38 77 Uttarakhand Rudraprayag 50.3 55.7 14.2 9.4 19.0 37 24 49 Uttarakhand Tehri Garhwal 59.6 63.3 13.8 9.0 18.6 94 61 126 Uttarakhand Dehradun 51.7 53.7 11.0 6.2 15.8 166 94 239 Uttarakhand Garhwal 50.0 50.7 9.5 4.7 14.2 64 32 97 Uttarakhand Pithoragarh 48.2 55.4 15.8 11.0 20.6 75 52 97 Uttarakhand Bageshwar 52.8 51.4 7.7 3.0 12.5 21 8 34 Uttarakhand Almora 52.8 53.8 10.2 5.4 15.0 66 35 97 Uttarakhand Champawat 67.5 80.0 23.5 18.7 28.3 70 56 84 Uttarakhand Nainital 60.8 66.0 15.4 10.6 20.2 147 101 192 Uttarakhand Udham Singh Nagar 67.1 74.4 18.3 13.5 23.1 334 247 422 Uttarakhand Hardwar 81.3 95.7 27.0 22.2 31.7 583 480 687 Haryana Panchkula 57.2 63.9 16.4 11.6 21.2 79 56 103 11
Haryana Ambala 52.7 59.9 16.3 11.6 21.1 145 103 188 Haryana Yamunanagar 62.7 73.6 21.4 16.6 26.1 228 177 279 Haryana Kurukshetra 64.1 73.1 19.7 14.9 24.4 162 122 201 Haryana Kaithal 98.3 91.9 7.7 2.9 12.4 78 29 127 Haryana Karnal 85.9 86.5 13.6 8.8 18.3 192 124 259 Haryana Panipat 64.3 76.7 23.1 18.3 27.9 281 223 339 Haryana Sonipat 59.7 72.9 23.3 18.5 28.1 311 247 375 Haryana Jind 74.8 92.0 29.1 24.3 33.9 377 315 439 Haryana Fatehabad 76.1 93.6 29.5 24.7 34.3 274 229 318 Haryana Sirsa 62.1 73.5 21.8 17.0 26.6 260 203 318 Haryana Hisar 67.6 82.5 25.9 21.1 30.7 426 348 505 Haryana Bhiwani 66.5 79.6 24.0 19.2 28.8 380 304 456 Haryana Rohtak 58.0 70.1 22.0 17.2 26.8 206 161 251 Haryana Jhajjar 63.5 65.7 12.7 7.9 17.5 106 66 146 Haryana Mahendragarh 71.8 87.4 27.1 22.3 31.9 228 188 268 Haryana Rewari 68.5 86.0 24.0 19.2 28.8 196 157 235 Haryana Gurgaon 47.1 58.3 19.6 14.8 24.3 265 201 330 Haryana Mewat 110.3 132.5 37.2 32.4 41.9 681 593 769 Haryana Faridabad 54.0 65.8 21.1 16.4 25.9 382 295 468 Haryana Palwal 73.5 99.0 37.2 32.4 42.0 489 426 552 Delhi North West 54.2 69.1 24.3 19.5 29.1 822 660 983 Delhi North 46.2 58.6 20.7 15.9 25.4 160 123 197 Delhi North East 61.4 69.7 18.6 13.8 23.4 424 315 533 Delhi East 59.0 61.8 12.8 8.0 17.6 184 115 252 Delhi New Delhi 59.2 146.9 22.0 17.2 26.8 25 20 31 Delhi Central 53.5 47.1 2.9-1.9 7.7 13-9 36 Delhi West 60.6 73.1 22.7 17.9 27.5 489 386 592 Delhi South West 71.7 102.8 22.0 17.2 26.8 442 346 538 Delhi South 67.2 87.7 25.0 20.2 29.8 638 516 760 Rajasthan Ganganagar 74.1 77.7 15.3 10.6 20.1 301 207 395 Rajasthan Hanumangarh 72.1 125.4 19.0 14.2 23.8 368 276 461 12
Rajasthan Bikaner 67.4 75.1 18.7 13.9 23.4 563 419 707 Rajasthan Churu 70.3 78.7 19.8 15.0 24.6 488 370 606 Rajasthan Jhunjhunun 65.0 71.6 17.3 12.6 22.1 385 279 492 Rajasthan Alwar 78.2 90.3 24.4 19.6 29.1 1070 860 1280 Rajasthan Bharatpur 77.5 106.2 40.8 36.0 45.6 1333 1176 1489 Rajasthan Dhaulpur 84.1 123.4 52.1 47.4 56.9 864 785 943 Rajasthan Karauli 81.0 120.2 51.7 46.9 56.5 964 875 1053 Rajasthan Sawai Madhopur 88.0 114.0 39.2 34.4 44.0 633 556 710 Rajasthan Dausa 89.4 113.7 37.6 32.8 42.4 774 676 872 Rajasthan Jaipur 62.5 71.3 19.3 14.5 24.1 1366 1027 1705 Rajasthan Sikar 61.4 70.7 19.5 14.8 24.3 571 431 711 Rajasthan Nagaur 84.6 113.8 42.1 37.3 46.8 1735 1538 1933 Rajasthan Jodhpur 70.3 89.0 30.0 25.2 34.8 1393 1171 1615 Rajasthan Jaisalmer 66.3 92.3 36.9 32.1 41.7 343 298 387 Rajasthan Barmer 73.9 92.3 30.1 25.4 34.9 1118 941 1295 Rajasthan Jalor 80.1 94.6 26.9 22.1 31.7 662 545 780 Rajasthan Sirohi 94.1 108.0 27.6 22.9 32.4 364 301 427 Rajasthan Pali 107.7 112.5 19.6 14.8 24.4 481 364 599 Rajasthan Ajmer 102.5 112.5 24.4 19.6 29.2 728 585 871 Rajasthan Tonk 101.7 106.4 19.1 14.3 23.8 317 238 397 Rajasthan Bundi 90.8 99.4 22.0 17.2 26.8 279 218 340 Rajasthan Bhilwara 117.5 112.4 10.3 5.5 15.1 295 158 432 Rajasthan Rajsamand 111.9 117.7 20.8 16.0 25.6 291 224 358 Rajasthan Dungarpur 93.1 99.5 20.0 15.2 24.8 369 281 458 Rajasthan Banswara 131.0 143.5 28.6 23.8 33.3 735 612 859 Rajasthan Chittaurgarh 108.8 114.3 20.3 15.5 25.1 340 260 420 Rajasthan Kota 69.7 74.1 15.7 10.9 20.5 305 212 399 Rajasthan Baran 101.8 109.2 21.8 17.1 26.6 320 250 390 Rajasthan Jhalawar 89.3 95.4 19.4 14.6 24.2 317 239 395 Rajasthan Udaipur 105.6 126.0 35.1 30.3 39.9 1371 1184 1558 Rajasthan Pratapgarh 115.7 119.3 18.9 14.1 23.7 220 164 275 13
Uttar Pradesh Saharanpur 85.7 110.8 38.0 33.2 42.8 1578 1380 1777 Uttar Pradesh Muzaffarnagar 86.2 109.6 36.4 31.6 41.2 1856 1612 2100 Uttar Pradesh Bijnor 97.7 106.7 23.0 18.2 27.8 1060 840 1281 Uttar Pradesh Moradabad 100.7 119.7 33.3 28.5 38.0 2147 1838 2455 Uttar Pradesh Rampur 93.4 108.0 28.3 23.5 33.1 899 747 1051 Uttar Pradesh Jyotiba Phule Nagar 94.5 111.6 30.8 26.0 35.6 754 637 871 Uttar Pradesh Meerut 77.5 93.9 28.5 23.7 33.3 1087 904 1269 Uttar Pradesh Baghpat 76.1 94.1 30.0 25.2 34.8 446 375 517 Uttar Pradesh Ghaziabad 83.3 100.0 29.4 24.6 34.2 1505 1260 1750 Uttar Pradesh Gautam Buddha Nagar 75.1 95.5 32.3 27.5 37.1 577 492 663 Uttar Pradesh Bulandshahr 93.4 116.0 36.3 31.5 41.0 1552 1348 1757 Uttar Pradesh Aligarh 93.6 122.4 42.5 37.7 47.3 1964 1744 2185 Uttar Pradesh Mahamaya Nagar 76.9 101.5 36.7 31.9 41.4 709 616 801 Uttar Pradesh Mathura 95.0 124.7 43.4 38.6 48.2 1380 1228 1532 Uttar Pradesh Agra 77.3 111.8 46.7 41.9 51.4 2497 2241 2753 Uttar Pradesh Firozabad 88.2 118.0 43.1 38.3 47.9 1361 1210 1512 Uttar Pradesh Mainpuri 95.3 129.6 48.1 43.3 52.9 1141 1028 1255 Uttar Pradesh Budaun 116.0 145.3 44.6 39.9 49.4 2382 2127 2637 Uttar Pradesh Bareilly 102.4 124.9 36.9 32.1 41.7 2156 1877 2436 Uttar Pradesh Pilibhit 97.0 126.2 43.2 38.4 48.0 1150 1023 1277 Uttar Pradesh Shahjahanpur 100.7 123.0 36.6 31.8 41.3 1497 1301 1693 Uttar Pradesh Kheri 108.6 127.4 33.7 28.9 38.5 1842 1580 2104 Uttar Pradesh Sitapur 117.4 143.5 41.5 36.7 46.2 2583 2285 2881 Uttar Pradesh Hardoi 114.4 139.9 40.7 36.0 45.5 2243 1979 2506 Uttar Pradesh Unnao 106.1 117.4 25.9 21.1 30.7 973 793 1152 Uttar Pradesh Lucknow 78.4 83.4 17.2 12.5 22.0 785 567 1002 Uttar Pradesh Rae Bareli 110.9 111.0 15.1 10.4 19.9 635 435 836 Uttar Pradesh Farrukhabad 88.8 113.7 38.2 33.4 42.9 917 802 1032 Uttar Pradesh Kannauj 92.0 112.3 33.9 29.1 38.7 717 616 818 Uttar Pradesh Etawah 80.2 100.7 32.9 28.1 37.7 599 512 686 Uttar Pradesh Auraiya 85.9 97.8 25.0 20.2 29.8 406 328 484 14
Uttar Pradesh Kanpur Dehat 91.5 108.5 30.5 25.8 35.3 634 534 733 Uttar Pradesh Kanpur Nagar 77.6 90.7 25.2 20.5 30.0 1074 870 1277 Uttar Pradesh Jalaun 71.9 87.9 27.5 22.8 32.3 499 413 586 Uttar Pradesh Jhansi 81.5 97.1 28.2 23.4 33.0 578 480 676 Uttar Pradesh Lalitpur 104.9 135.4 45.1 40.4 49.9 763 682 844 Uttar Pradesh Hamirpur 83.2 107.1 36.6 31.8 41.4 471 409 532 Uttar Pradesh Mahoba 94.8 116.6 35.6 30.8 40.4 381 330 432 Uttar Pradesh Banda 95.6 122.9 41.1 36.3 45.9 982 868 1097 Uttar Pradesh Chitrakoot 97.5 121.9 38.4 33.6 43.2 539 472 606 Uttar Pradesh Fatehpur 104.6 120.4 30.3 25.6 35.1 1006 847 1164 Uttar Pradesh Pratapgarh 94.6 99.1 18.3 13.5 23.1 730 539 921 Uttar Pradesh Kaushambi 124.8 136.2 27.2 22.4 31.9 622 513 732 Uttar Pradesh Allahabad 112.8 131.2 33.5 28.7 38.3 2507 2149 2865 Uttar Pradesh Bara Banki 118.3 132.1 29.2 24.4 34.0 1270 1062 1478 Uttar Pradesh Faizabad 99.3 105.4 20.3 15.5 25.0 622 475 768 Uttar Pradesh Ambedkar Nagar 92.5 97.3 18.3 13.6 23.1 544 402 686 Uttar Pradesh Sultanpur 89.9 98.5 21.9 17.1 26.7 1048 820 1277 Uttar Pradesh Bahraich 108.2 127.0 33.6 28.8 38.3 1695 1454 1937 Uttar Pradesh Shrawasti 104.4 137.2 47.4 42.6 52.2 763 686 840 Uttar Pradesh Balrampur 100.5 121.6 35.3 30.5 40.1 1114 963 1265 Uttar Pradesh Gonda 85.4 105.1 32.7 27.9 37.4 1513 1292 1735 Uttar Pradesh Siddharthnagar 103.7 114.9 25.7 20.9 30.5 982 799 1164 Uttar Pradesh Basti 89.9 99.5 23.0 18.2 27.7 750 593 906 Uttar Pradesh Sant Kabir Nagar 85.7 95.9 23.1 18.3 27.9 539 427 650 Uttar Pradesh Mahrajganj 111.1 119.8 23.7 18.9 28.5 863 689 1037 Uttar Pradesh Gorakhpur 79.0 87.7 21.0 16.2 25.8 1104 853 1356 Uttar Pradesh Kushinagar 106.4 109.7 18.0 13.2 22.8 855 628 1083 Uttar Pradesh Deoria 72.0 76.3 15.8 11.0 20.6 611 426 796 Uttar Pradesh Azamgarh 75.4 76.7 13.2 8.4 18.0 779 497 1061 Uttar Pradesh Mau 88.2 96.4 21.4 16.6 26.1 616 478 753 Uttar Pradesh Ballia 74.3 80.4 17.9 13.1 22.7 691 507 876 15
Uttar Pradesh Jaunpur 94.3 101.7 21.1 16.3 25.9 1215 940 1491 Uttar Pradesh Ghazipur 91.8 97.8 19.5 14.8 24.3 891 673 1109 Uttar Pradesh Chandauli 72.8 84.3 23.2 18.4 28.0 563 447 679 Uttar Pradesh Varanasi 87.0 95.9 22.0 17.2 26.8 916 717 1115 Uttar Pradesh Sant Ravidas Nagar (Bhadohi) 104.5 131.5 41.6 36.8 46.4 892 790 995 Uttar Pradesh Mirzapur 104.8 126.0 35.8 31.0 40.6 1184 1026 1342 Uttar Pradesh Sonbhadra 95.1 110.7 29.5 24.7 34.3 761 637 884 Uttar Pradesh Etah 90.8 127.8 50.5 45.7 55.2 1169 1058 1280 Uttar Pradesh Kanshiram Nagar 111.5 131.3 34.9 30.1 39.6 694 598 789 Bihar Pashchim Champaran 86.4 99.2 25.9 21.1 30.6 1520 1239 1801 Bihar Purba Champaran 83.9 105.2 34.1 29.4 38.9 2609 2243 2974 Bihar Sheohar 91.2 125.1 47.3 42.6 52.1 464 417 511 Bihar Sitamarhi 87.0 116.6 42.7 37.9 47.5 2156 1914 2397 Bihar Madhubani 71.2 89.9 30.2 25.4 34.9 1907 1604 2209 Bihar Supaul 74.3 84.7 22.2 17.4 27.0 734 576 892 Bihar Araria 93.8 109.4 29.4 24.6 34.2 1295 1084 1505 Bihar Kishanganj 111.8 114.3 17.5 12.8 22.3 474 344 603 Bihar Purnia 99.7 112.9 27.3 22.6 32.1 1369 1130 1609 Bihar Katihar 96.7 105.3 22.6 17.8 27.4 1069 842 1295 Bihar Madhepura 73.0 88.0 26.6 21.8 31.4 791 649 933 Bihar Saharsa 69.6 89.7 31.4 26.6 36.2 880 746 1014 Bihar Darbhanga 83.4 104.1 33.5 28.7 38.2 1876 1608 2145 Bihar Muzaffarpur 80.7 100.4 32.1 27.4 36.9 2089 1778 2400 Bihar Gopalganj 83.2 86.0 15.6 10.8 20.4 569 394 743 Bihar Siwan 70.6 78.3 19.0 14.3 23.8 859 643 1075 Bihar Saran 71.4 83.2 23.3 18.5 28.1 1261 1002 1520 Bihar Vaishali 74.8 97.7 34.7 30.0 39.5 1606 1385 1828 Bihar Samastipur 73.0 93.4 32.0 27.3 36.8 1954 1662 2245 Bihar Begusarai 72.6 93.7 32.7 27.9 37.5 1382 1180 1585 Bihar Khagaria 65.9 86.9 31.9 27.1 36.7 791 673 910 Bihar Bhagalpur 63.0 80.4 27.9 23.1 32.7 1150 953 1347 16
Bihar Banka 71.2 90.7 31.0 26.2 35.8 874 739 1009 Bihar Munger 61.8 80.2 28.8 24.0 33.6 500 417 584 Bihar Lakhisarai 64.1 82.3 28.8 24.0 33.6 404 337 471 Bihar Sheikhpura 75.3 91.8 28.4 23.7 33.2 262 218 306 Bihar Nalanda 78.6 90.4 24.0 19.2 28.8 952 762 1141 Bihar Patna 80.3 98.7 30.8 26.0 35.6 2258 1908 2608 Bihar Bhojpur 78.7 95.8 29.4 24.6 34.2 1061 888 1234 Bihar Buxar 86.2 102.6 29.4 24.6 34.2 682 571 793 Bihar Kaimur (Bhabua) 97.7 111.0 27.3 22.5 32.1 643 530 755 Bihar Rohtas 81.3 95.5 26.7 21.9 31.5 1076 884 1269 Bihar Aurangabad 81.1 94.2 25.6 20.8 30.3 913 742 1083 Bihar Gaya 92.0 105.7 27.3 22.5 32.0 1689 1393 1985 Bihar Nawada 66.1 82.2 26.9 22.2 31.7 835 687 983 Bihar Jamui 71.9 88.7 28.3 23.5 33.1 692 575 809 Bihar Jehanabad 82.1 101.7 32.2 27.4 37.0 503 428 578 Bihar Arwal 95.6 112.8 31.1 26.3 35.9 312 264 360 Sikkim North District 59.3 71.4 22.1 17.3 26.9 10 8 12 Sikkim West District 77.1 70.8 5.8 1.0 10.6 8 1 15 Sikkim South District 67.0 62.6 6.6 1.8 11.4 10 3 16 Sikkim East District 66.6 51.1-4.6-9.3 0.2-11 -23 1 Arunachal Pradesh Tawang 120.5 102.1-2.9-7.6 1.9-1 -4 1 Arunachal Pradesh West Kameng 106.2 100.8 9.2 4.5 14.0 9 4 14 Arunachal Pradesh East Kameng 101.2 201.8 13.0 8.2 17.8 18 12 25 Arunachal Pradesh Papum Pare 83.4 80.9 10.3 5.5 15.1 22 12 33 Arunachal Pradesh Upper Subansiri 129.3 130.8 17.5 12.7 22.3 20 15 26 Arunachal Pradesh West Siang 76.5 79.0 14.6 9.8 19.4 20 13 26 Arunachal Pradesh East Siang 57.5 57.5 9.8 5.1 14.6 11 6 16 Arunachal Pradesh Upper Siang 75.3 67.1 3.8-1.0 8.5 2 0 4 Arunachal Pradesh Changlang 78.9 79.3 12.6 7.8 17.4 25 15 34 Arunachal Pradesh Tirap 102.0 108.7 21.1 16.3 25.9 33 26 41 Arunachal Pradesh Lower Subansiri 79.0 72.9 6.2 1.4 11.0 6 1 10 17
Arunachal Pradesh Kurung Kumey 173.1 196.1 39.7 35.0 44.5 64 56 71 Arunachal Pradesh Dibang Valley 107.0 125.5 33.3 28.5 38.1 3 3 4 Arunachal Pradesh Lower Dibang Valley 88.3 87.9 12.9 8.1 17.6 9 5 12 Arunachal Pradesh Lohit 82.4 88.2 18.5 13.7 23.2 35 26 44 Arunachal Pradesh Anjaw 158.2 157.2 15.8 11.0 20.6 5 3 6 Nagaland Mon 74.1 143.7 18.0 13.2 22.8 62 45 78 Nagaland Mokokchung 54.3 70.1 25.1 20.3 29.9 47 38 55 Nagaland Zunheboto 63.7 55.8 2.6-2.2 7.4 4-4 12 Nagaland Wokha 79.4 83.5 16.5 11.7 21.2 30 21 39 Nagaland Dimapur 66.1 66.1 10.9 6.1 15.7 45 25 65 Nagaland Phek 71.3 68.8 8.9 4.1 13.7 19 9 29 Nagaland Tuensang 92.2 98.9 20.3 15.5 25.1 57 43 70 Nagaland Longleng 62.5 75.1 23.0 18.2 27.8 15 12 18 Nagaland Kiphire 108.8 105.0 11.1 6.3 15.9 12 7 18 Nagaland Kohima 53.5 56.9 12.7 7.9 17.5 38 24 52 Nagaland Peren 89.4 102.7 26.6 21.8 31.4 33 27 39 Manipur Senapati 48.9 64.3 24.0 19.2 28.8 126 101 151 Manipur Tamenglong 58.4 56.8 8.2 3.5 13.0 13 5 20 Manipur Churachandpur 54.6 53.0 7.8 3.0 12.6 22 9 36 Manipur Bishnupur 50.9 50.5 8.5 3.7 13.3 21 9 32 Manipur Thoubal 51.0 48.7 6.6 1.8 11.4 31 8 53 Manipur Imphal West 51.7 50.0 7.4 2.6 12.2 35 12 57 Manipur Imphal East 54.0 42.3-2.4-7.2 2.4-11 -33 11 Manipur Ukhrul 57.6 57.8 10.0 5.3 14.8 20 10 30 Manipur Chandel 61.1 61.0 10.2 5.4 15.0 14 8 21 Mizoram Mamit 94.4 94.5 13.9 9.1 18.7 16 10 21 Mizoram Kolasib 66.0 61.2 6.1 1.3 10.9 6 1 11 Mizoram Aizawl 43.8 42.5 6.6 1.8 11.3 26 7 44 Mizoram Champhai 51.7 42.5-0.2-5.0 4.6 0-7 7 Mizoram Serchhip 49.9 46.2 5.1 0.3 9.9 4 0 7 Mizoram Lunglei 76.4 78.7 14.3 9.5 19.1 27 18 36 18
Mizoram Lawngtlai 125.9 121.2 11.2 6.4 16.0 19 11 27 Mizoram Saiha 78.5 69.8 3.6-1.2 8.4 3-1 6 Tripura West Tripura 72.3 70.9 10.2 5.4 15.0 154 81 226 Tripura South Tripura 80.7 92.4 24.2 19.4 28.9 217 174 260 Tripura Dhalai 98.5 96.0 11.6 6.8 16.4 51 30 72 Tripura North Tripura 100.1 102.3 16.4 11.6 21.2 127 90 164 Meghalaya West Garo Hills 147.2 150.6 20.0 15.2 24.8 186 142 231 Meghalaya East Garo Hills 118.3 106.3 3.5-1.3 8.3 16-6 38 Meghalaya South Garo Hills 126.3 128.6 18.1 13.4 22.9 39 29 49 Meghalaya West Khasi Hills 104.3 108.0 18.3 13.5 23.0 116 86 146 Meghalaya Ribhoi 119.0 152.3 15.0 10.2 19.8 63 43 83 Meghalaya East Khasi Hills 90.2 96.7 19.9 15.2 24.7 213 162 264 Meghalaya Jaintia Hills 127.5 119.3 7.8 3.0 12.6 52 20 84 Assam Kokrajhar 97.7 117.0 33.3 28.5 38.1 368 315 420 Assam Dhubri 116.1 121.7 20.9 16.1 25.7 584 450 717 Assam Goalpara 94.4 99.0 18.3 13.5 23.1 241 178 303 Assam Barpeta 88.7 103.4 27.9 23.2 32.7 624 517 730 Assam Morigaon 100.8 98.9 12.4 7.6 17.2 158 97 218 Assam Nagaon 90.1 89.5 12.8 8.1 17.6 463 291 636 Assam Sonitpur 81.2 92.9 24.2 19.4 29.0 540 433 647 Assam Lakhimpur 74.1 73.2 10.9 6.1 15.6 132 74 191 Assam Dhemaji 65.2 73.5 19.0 14.2 23.8 156 117 196 Assam Tinsukia 61.1 65.5 14.7 9.9 19.4 210 142 279 Assam Dibrugarh 61.1 62.7 11.8 7.0 16.6 154 92 217 Assam Sivasagar 65.2 62.3 7.9 3.1 12.6 88 34 141 Assam Jorhat 63.2 61.7 9.0 4.2 13.8 92 43 140 Assam Golaghat 74.3 69.5 7.0 2.2 11.8 78 25 131 Assam Karbi Anglong 100.9 108.4 21.8 17.0 26.6 267 208 325 Assam Dima Hasao 78.1 78.6 12.7 7.9 17.4 32 20 44 Assam Cachar 76.7 74.2 9.5 4.7 14.3 187 93 281 Assam Karimganj 95.7 93.8 12.0 7.2 16.7 191 115 267 19
Assam Hailakandi 101.5 93.0 5.8 1.0 10.6 50 9 91 Assam Bongaigaon 88.6 89.0 13.6 8.8 18.4 123 80 166 Assam Chirang 91.4 99.6 21.7 16.9 26.5 130 101 158 Assam Kamrup 78.7 78.9 12.4 7.6 17.2 202 124 280 Assam Kamrup Metropolitan 62.5 60.5 8.4 3.6 13.2 85 37 134 Assam Nalbari 65.2 65.7 11.3 6.5 16.0 87 50 124 Assam Baksa 83.3 91.3 20.7 16.0 25.5 215 166 265 Assam Darrang 105.5 102.6 11.7 6.9 16.5 143 85 202 Assam Udalguri 92.6 94.1 15.1 10.3 19.9 143 98 188 West Bengal Darjiling 58.0 57.4 9.3 4.5 14.1 155 75 234 West Bengal Jalpaiguri 78.4 74.0 7.9 3.1 12.6 300 117 483 West Bengal Koch Bihar 73.4 76.4 14.6 9.9 19.4 414 279 550 West Bengal Uttar Dinajpur 84.9 88.8 16.8 12.0 21.6 668 478 858 West Bengal Dakshin Dinajpur 82.2 74.2 4.6-0.2 9.4 76-3 156 West Bengal Maldah 89.1 90.7 14.9 10.1 19.7 745 506 984 West Bengal Murshidabad 83.7 83.3 12.3 7.5 17.1 1021 624 1418 West Bengal Birbhum 73.6 76.8 15.0 10.2 19.8 541 368 714 West Bengal Barddhaman 60.3 62.2 12.0 7.3 16.8 811 489 1134 West Bengal Nadia 62.4 60.3 8.3 3.5 13.1 369 157 581 West Bengal North Twenty Four Parganas 61.9 58.8 7.3 2.5 12.1 582 201 963 West Bengal Hugli 52.3 50.5 7.3 2.5 12.1 317 109 525 West Bengal Bankura 51.1 51.6 9.4 4.6 14.2 312 154 471 West Bengal Puruliya 53.4 57.1 13.0 8.2 17.8 407 257 557 West Bengal Haora 54.2 51.6 6.8 2.0 11.6 280 82 478 West Bengal Kolkata 69.9 68.5 9.9 5.1 14.6 287 148 426 West Bengal South Twenty Four Parganas 70.9 68.5 9.0 4.3 13.8 744 350 1138 West Bengal Paschim Medinipur 56.9 55.2 7.9 3.2 12.7 436 174 699 West Bengal Purba Medinipur 61.4 66.8 15.7 10.9 20.5 750 522 978 Jharkhand Garhwa 105.0 115.8 25.4 20.6 30.2 503 408 598 Jharkhand Chatra 100.0 105.5 19.6 14.9 24.4 307 232 381 Jharkhand Kodarma 74.2 76.2 13.8 9.0 18.6 135 88 182 20
Jharkhand Giridih 73.5 85.1 23.3 18.5 28.1 802 637 967 Jharkhand Deoghar 73.4 86.9 25.2 20.4 30.0 501 406 596 Jharkhand Godda 93.4 107.7 27.9 23.1 32.7 512 424 599 Jharkhand Sahibganj 108.2 113.3 19.9 15.1 24.7 337 256 417 Jharkhand Pakur 122.0 115.4 9.1 4.3 13.8 122 57 186 Jharkhand Dhanbad 78.2 80.8 14.9 10.1 19.6 448 304 592 Jharkhand Bokaro 76.8 80.2 15.4 10.6 20.2 368 254 482 Jharkhand Lohardaga 96.1 90.7 8.5 3.7 13.3 55 24 86 Jharkhand Purbi Singhbhum 54.7 55.1 9.8 5.0 14.6 217 111 323 Jharkhand Palamu 93.0 99.0 19.7 14.9 24.5 532 403 662 Jharkhand Latehar 99.8 103.9 18.3 13.5 23.0 201 149 254 Jharkhand Hazaribagh 81.3 83.5 14.8 10.0 19.6 335 227 443 Jharkhand Ramgarh 76.9 77.8 13.0 8.2 17.8 144 91 197 Jharkhand Dumka 91.7 96.3 18.1 13.3 22.9 304 224 385 Jharkhand Jamtara 105.6 120.1 29.2 24.4 34.0 301 251 350 Jharkhand Ranchi 79.5 82.1 15.0 10.2 19.8 492 335 648 Jharkhand Khunti 119.0 121.5 17.9 13.2 22.7 127 93 161 Jharkhand Gumla 99.8 102.0 16.4 11.6 21.2 233 165 301 Jharkhand Simdega 133.2 119.8 2.7-2.1 7.5 21-16 58 Jharkhand Pashchimi Singhbhum 122.9 126.3 19.1 14.3 23.9 404 303 504 Jharkhand Saraikela-Kharsawan 85.1 76.3 4.1-0.7 8.9 50-8 109 Odisha Bargarh 76.6 72.2 7.7 2.9 12.5 102 39 165 Odisha Jharsuguda 81.0 71.7 3.2-1.6 8.0 17-8 42 Odisha Sambalpur 89.3 84.6 8.5 3.8 13.3 82 36 128 Odisha Debagarh 107.8 99.9 6.9 2.1 11.7 23 7 38 Odisha Sundargarh 95.8 88.9 6.9 2.2 11.7 151 47 255 Odisha Kendujhar 93.2 90.8 11.2 6.4 16.0 227 130 324 Odisha Mayurbhanj 78.3 79.9 13.9 9.1 18.7 399 261 536 Odisha Baleshwar 85.5 88.1 15.5 10.8 20.3 370 256 484 Odisha Bhadrak 87.2 93.8 19.8 15.0 24.6 306 232 380 Odisha Kendrapara 92.7 95.9 16.8 12.0 21.5 229 164 295 21
Odisha Jagatsinghapur 76.9 82.3 17.5 12.8 22.3 163 118 207 Odisha Cuttack 87.6 91.1 16.7 11.9 21.5 375 268 483 Odisha Jajapur 83.9 87.5 16.4 11.6 21.2 287 203 370 Odisha Dhenkanal 93.2 99.9 20.3 15.6 25.1 230 176 284 Odisha Anugul 100.9 106.5 19.9 15.1 24.6 252 192 313 Odisha Nayagarh 106.2 114.1 22.6 17.8 27.3 201 159 244 Odisha Khordha 85.0 84.8 12.7 7.9 17.5 245 153 338 Odisha Puri 92.4 95.2 16.4 11.6 21.2 245 173 316 Odisha Ganjam 103.8 108.3 19.0 14.2 23.8 701 524 877 Odisha Gajapati 142.0 138.7 13.2 8.4 17.9 99 63 135 Odisha Kandhamal 176.0 160.1 0.8-4.0 5.6 8-39 55 Odisha Baudh 118.1 110.9 8.2 3.4 12.9 43 18 68 Odisha Subarnapur 82.7 77.8 7.8 3.0 12.6 47 18 76 Odisha Balangir 106.6 96.6 4.7-0.1 9.5 82-1 165 Odisha Nuapada 117.7 108.3 6.0 1.2 10.8 43 9 78 Odisha Kalahandi 132.5 117.8 1.5-3.3 6.2 27-62 116 Odisha Rayagada 140.7 136.8 12.5 7.7 17.3 159 98 219 Odisha Nabarangapur 133.8 127.9 10.3 5.5 15.1 175 94 256 Odisha Koraput 141.9 132.7 7.3 2.5 12.1 134 46 221 Odisha Malkangiri 149.6 143.9 10.9 6.2 15.7 97 54 139 Chhattisgarh Koriya 113.0 108.4 10.5 5.7 15.3 81 44 118 Chhattisgarh Surguja 95.7 95.7 13.9 9.1 18.6 415 272 558 Chhattisgarh Jashpur 108.2 100.2 6.7 2.0 11.5 66 19 113 Chhattisgarh Raigarh 90.7 82.9 5.6 0.8 10.4 87 13 162 Chhattisgarh Korba 95.0 83.3 2.1-2.6 6.9 29-36 94 Chhattisgarh Janjgir - Champa 87.0 80.3 6.3 1.6 11.1 116 29 204 Chhattisgarh Bilaspur 101.4 96.4 9.4 4.6 14.2 305 150 461 Chhattisgarh Kabeerdham 110.2 106.4 11.2 6.4 15.9 124 71 177 Chhattisgarh Rajnandgaon 119.5 108.2 4.1-0.6 8.9 74-11 159 Chhattisgarh Durg 92.4 78.3-0.6-5.4 4.2-20 -187 147 Chhattisgarh Raipur 86.4 79.7 6.3 1.6 11.1 292 72 512 22
Chhattisgarh Mahasamund 124.7 104.8-4.2-9.0 0.6-47 -101 7 Chhattisgarh Dhamtari 93.1 84.2 4.7-0.1 9.5 40-1 80 Chhattisgarh Uttar Bastar Kanker 92.4 82.3 3.4-1.3 8.2 28-11 67 Chhattisgarh Bastar 131.3 118.2 3.1-1.7 7.8 55-31 140 Chhattisgarh Narayanpur 115.7 110.0 9.6 4.8 14.4 19 10 29 Chhattisgarh Dakshin Bastar Dantewada 135.3 124.2 5.1 0.4 9.9 36 3 69 Chhattisgarh Bijapur 117.3 113.2 11.3 6.5 16.1 40 23 57 Madhya Pradesh Sheopur 131.0 151.0 36.1 31.3 40.9 345 299 390 Madhya Pradesh Morena 74.1 115.2 52.8 48.0 57.6 1237 1125 1349 Madhya Pradesh Bhind 70.7 107.5 48.2 43.4 53.0 916 825 1007 Madhya Pradesh Gwalior 86.4 99.8 26.4 21.6 31.2 540 442 638 Madhya Pradesh Datia 104.2 124.8 35.1 30.3 39.9 314 271 357 Madhya Pradesh Shivpuri 119.0 150.0 46.4 41.7 51.2 1087 975 1199 Madhya Pradesh Tikamgarh 101.4 127.1 40.0 35.2 44.8 742 653 831 Madhya Pradesh Chhatarpur 118.6 138.5 35.3 30.5 40.1 829 717 941 Madhya Pradesh Panna 141.1 149.7 25.0 20.3 29.8 347 281 414 Madhya Pradesh Sagar 109.8 123.2 28.3 23.6 33.1 827 687 967 Madhya Pradesh Damoh 113.2 127.0 29.0 24.2 33.7 456 381 531 Madhya Pradesh Satna 125.8 137.1 27.2 22.4 32.0 763 629 897 Madhya Pradesh Rewa 100.0 105.5 19.7 14.9 24.5 566 429 704 Madhya Pradesh Umaria 138.2 143.4 21.5 16.8 26.3 186 145 227 Madhya Pradesh Neemuch 87.8 86.9 12.2 7.5 17.0 106 65 148 Madhya Pradesh Mandsaur 89.6 88.3 12.1 7.3 16.9 175 106 245 Madhya Pradesh Ratlam 102.7 101.0 12.7 8.0 17.5 223 139 306 Madhya Pradesh Ujjain 78.3 84.3 18.3 13.5 23.1 394 291 497 Madhya Pradesh Shajapur 89.1 98.7 22.9 18.1 27.7 408 323 494 Madhya Pradesh Dewas 81.6 91.5 22.4 17.7 27.2 409 322 497 Madhya Pradesh Dhar 76.8 82.9 18.1 13.4 22.9 505 372 638 Madhya Pradesh Indore 69.3 68.7 10.6 5.8 15.4 335 184 486 Madhya Pradesh Khargone (West Nimar) 88.4 88.7 13.5 8.8 18.3 324 210 439 Madhya Pradesh Barwani 108.7 106.2 12.4 7.7 17.2 259 159 358 23
Madhya Pradesh Rajgarh 102.4 107.0 19.1 14.3 23.9 363 272 454 Madhya Pradesh Vidisha 111.2 124.4 28.2 23.4 33.0 549 456 642 Madhya Pradesh Bhopal 73.5 77.7 15.9 11.1 20.6 376 262 489 Madhya Pradesh Sehore 112.3 116.1 19.0 14.2 23.7 310 231 388 Madhya Pradesh Raisen 107.7 114.1 21.2 16.4 26.0 360 278 441 Madhya Pradesh Betul 127.5 118.2 6.7 1.9 11.5 121 34 207 Madhya Pradesh Harda 114.3 125.0 25.9 21.1 30.7 179 146 213 Madhya Pradesh Hoshangabad 102.4 108.4 20.5 15.7 25.3 276 212 341 Madhya Pradesh Katni 144.1 144.8 17.3 12.5 22.0 283 205 361 Madhya Pradesh Jabalpur 108.5 108.6 14.9 10.1 19.7 361 245 477 Madhya Pradesh Narsimhapur 109.5 106.8 12.2 7.4 17.0 140 85 195 Madhya Pradesh Dindori 130.5 124.8 10.4 5.6 15.1 92 49 134 Madhya Pradesh Mandla 114.3 103.9 4.8 0.1 9.6 59 1 117 Madhya Pradesh Chhindwara 108.0 104.3 11.1 6.3 15.9 254 145 363 Madhya Pradesh Seoni 96.9 95.6 12.6 7.8 17.4 193 120 267 Madhya Pradesh Balaghat 109.1 96.7 2.5-2.3 7.3 45-41 131 Madhya Pradesh Guna 98.0 116.8 32.9 28.1 37.7 545 466 624 Madhya Pradesh Ashoknagar 119.4 137.7 33.8 29.0 38.5 386 331 441 Madhya Pradesh Shahdol 136.7 136.8 16.4 11.6 21.2 220 156 285 Madhya Pradesh Anuppur 128.9 117.7 4.7-0.1 9.5 42 0 84 Madhya Pradesh Sidhi 129.6 140.9 27.3 22.5 32.1 437 360 513 Madhya Pradesh Singrauli 139.5 142.8 19.7 15.0 24.5 342 259 424 Madhya Pradesh Jhabua 127.1 127.5 16.3 11.5 21.1 267 189 345 Madhya Pradesh Alirajpur 139.6 132.3 9.0 4.3 13.8 109 51 166 Madhya Pradesh Khandwa (East Nimar) 103.4 110.4 21.5 16.7 26.3 355 276 435 Madhya Pradesh Burhanpur 78.5 82.7 16.5 11.7 21.3 153 108 197 Gujarat Kachchh 67.1 70.2 14.1 9.3 18.9 324 214 434 Gujarat Banas Kantha 62.4 67.4 15.5 10.7 20.2 584 404 765 Gujarat Patan 71.0 79.8 20.2 15.5 25.0 285 218 353 Gujarat Mahesana 74.9 70.6 7.5 2.7 12.3 133 49 218 Gujarat Sabar Kantha 74.6 74.4 11.7 6.9 16.5 298 176 420 24
Gujarat Gandhinagar 71.7 80.7 20.5 15.7 25.2 251 193 310 Gujarat Ahmadabad 57.5 72.0 24.3 19.6 29.1 1500 1205 1795 Gujarat Surendranagar 52.4 60.9 17.6 12.8 22.4 319 232 406 Gujarat Rajkot 63.8 65.0 11.8 7.0 16.6 388 231 545 Gujarat Jamnagar 58.0 58.9 10.7 5.9 15.5 219 122 317 Gujarat Porbandar 60.1 59.9 9.9 5.1 14.6 53 27 78 Gujarat Junagadh 61.7 63.8 12.4 7.6 17.2 321 198 445 Gujarat Amreli 58.8 62.5 13.6 8.9 18.4 190 123 257 Gujarat Bhavnagar 49.5 59.3 18.5 13.7 23.2 541 401 681 Gujarat Anand 85.0 90.6 18.5 13.7 23.3 358 265 450 Gujarat Kheda 85.4 92.7 20.3 15.5 25.0 457 349 564 Gujarat Panch Mahals 77.0 77.9 13.0 8.2 17.8 356 225 487 Gujarat Dohad 89.9 87.9 11.4 6.6 16.2 349 203 496 Gujarat Vadodara 72.3 78.4 17.7 12.9 22.5 672 490 853 Gujarat Narmada 84.3 77.4 6.0 1.2 10.8 38 8 68 Gujarat Bharuch 76.3 74.2 9.9 5.2 14.7 143 74 212 Gujarat The Dangs 68.7 76.1 18.6 13.8 23.3 58 43 73 Gujarat Navsari 67.3 62.0 5.7 0.9 10.4 61 9 112 Gujarat Valsad 60.0 65.6 15.7 10.9 20.4 257 178 335 Gujarat Surat 52.1 62.1 19.1 14.3 23.9 972 729 1215 Gujarat Tapi 67.6 68.4 11.9 7.1 16.7 87 52 122 Daman and Diu Diu 59.4 49.0-0.4-5.2 4.4 0-3 2 Daman and Diu Daman 41.4 34.3 0.5-4.3 5.2 1-5 7 Dadra and Nagar Haveli Dadra & Nagar Haveli 61.7 56.1 4.7-0.1 9.5 17 0 35 Maharashtra Nandurbar 73.2 73.2 11.7 6.9 16.5 226 133 318 Maharashtra Dhule 69.7 77.3 18.8 14.0 23.6 395 294 495 Maharashtra Jalgaon 65.8 71.2 16.2 11.4 21.0 634 447 821 Maharashtra Buldana 65.0 64.3 10.1 5.3 14.9 248 131 366 Maharashtra Akola 66.9 64.1 8.1 3.4 12.9 135 56 215 Maharashtra Washim 59.3 61.4 12.2 7.4 17.0 142 86 198 Maharashtra Amravati 60.6 57.1 6.6 1.9 11.4 168 47 288 25
Maharashtra Wardha 58.8 52.4 3.6-1.2 8.4 37-12 86 Maharashtra Nagpur 63.7 60.0 6.9 2.1 11.7 265 81 448 Maharashtra Bhandara 77.8 72.2 6.6 1.8 11.4 69 19 119 Maharashtra Gondiya 99.6 85.3-0.2-4.9 4.6-2 -60 56 Maharashtra Gadchiroli 95.4 85.2 3.6-1.1 8.4 38-12 89 Maharashtra Chandrapur 81.5 73.4 4.5-0.3 9.3 85-5 175 Maharashtra Yavatmal 78.2 76.0 10.0 5.3 14.8 266 139 392 Maharashtra Nanded 61.6 62.9 11.7 6.9 16.4 412 243 581 Maharashtra Hingoli 63.8 68.2 14.9 10.2 19.7 187 127 247 Maharashtra Parbhani 59.4 62.4 13.1 8.3 17.8 250 158 342 Maharashtra Jalna 64.4 68.4 14.7 9.9 19.5 302 204 401 Maharashtra Aurangabad 61.5 63.9 12.7 7.9 17.5 479 298 659 Maharashtra Nashik 64.4 65.7 11.9 7.1 16.7 728 436 1020 Maharashtra Thane 63.1 59.9 7.3 2.5 12.1 719 250 1188 Maharashtra Mumbai Suburban 51.8 52.1 9.3 4.5 14.1 654 317 991 Maharashtra Mumbai 59.1 55.0 5.9 1.1 10.7 124 23 224 Maharashtra Raigarh 59.6 56.9 7.4 2.6 12.2 170 60 280 Maharashtra Pune 46.9 45.6 7.1 2.3 11.9 543 177 910 Maharashtra Ahmadnagar 53.0 53.2 9.4 4.6 14.2 379 185 572 Maharashtra Bid 47.4 54.2 15.2 10.4 20.0 375 257 494 Maharashtra Latur 67.0 67.1 11.1 6.3 15.8 270 153 387 Maharashtra Osmanabad 56.7 59.1 12.1 7.3 16.9 186 113 259 Maharashtra Solapur 54.5 59.1 14.0 9.2 18.7 559 367 750 Maharashtra Satara 49.9 49.6 8.5 3.7 13.3 205 90 320 Maharashtra Ratnagiri 37.5 32.6 2.0-2.7 6.8 27-36 90 Maharashtra Sindhudurg 57.6 47.9 0.1-4.7 4.9 0-29 30 Maharashtra Kolhapur 47.0 49.0 10.4 5.6 15.2 313 169 456 Maharashtra Sangli 52.5 51.9 8.5 3.7 13.3 195 86 305 Andhra Pradesh Adilabad 77.8 76.8 11.2 6.4 15.9 296 169 423 Andhra Pradesh Nizamabad 75.0 69.4 6.3 1.5 11.0 151 35 266 Andhra Pradesh Karimnagar 52.9 47.1 3.4-1.4 8.2 103-41 247 26
Andhra Pradesh Medak 68.3 64.4 7.2 2.4 11.9 214 71 357 Andhra Pradesh Hyderabad 64.8 67.7 13.6 8.8 18.4 494 320 667 Andhra Pradesh Rangareddy 69.8 69.4 10.9 6.1 15.7 528 297 759 Andhra Pradesh Mahbubnagar 94.1 92.0 11.6 6.9 16.4 507 299 715 Andhra Pradesh Nalgonda 72.7 66.6 5.5 0.8 10.3 175 24 325 Andhra Pradesh Warangal 68.1 65.1 8.0 3.3 12.8 247 100 394 Andhra Pradesh Khammam 79.9 69.3 1.8-3.0 6.6 44-74 163 Andhra Pradesh Srikakulam 89.8 82.9 6.5 1.7 11.3 156 41 271 Andhra Pradesh Vizianagaram 118.0 108.1 5.6 0.8 10.4 119 17 221 Andhra Pradesh Visakhapatnam 92.5 88.3 9.4 4.6 14.2 361 178 544 Andhra Pradesh East Godavari 70.1 62.6 3.8-1.0 8.6 166-43 375 Andhra Pradesh West Godavari 68.2 59.8 2.7-2.1 7.5 88-66 243 Andhra Pradesh Krishna 91.9 79.8 1.5-3.3 6.3 54-121 229 Andhra Pradesh Guntur 59.7 57.7 8.1 3.3 12.8 327 133 522 Andhra Pradesh Prakasam 62.1 61.1 9.4 4.6 14.2 287 141 434 Andhra Pradesh Sri Potti Sriramulu Nellore 58.2 54.6 6.3 1.6 11.1 156 38 274 Andhra Pradesh Y.S.R. 62.8 59.5 7.2 2.4 12.0 187 63 312 Andhra Pradesh Kurnool 75.9 80.2 16.3 11.5 21.1 684 483 885 Andhra Pradesh Anantapur 102.2 102.7 14.9 10.1 19.7 561 381 741 Andhra Pradesh Chittoor 84.4 74.4 2.8-2.0 7.6 101-70 273 Karnataka Belgaum 71.4 72.5 12.6 7.8 17.4 594 368 819 Karnataka Bagalkot 91.4 88.5 10.6 5.8 15.3 220 120 319 Karnataka Bijapur 66.5 73.5 17.9 13.1 22.7 428 314 543 Karnataka Bidar 58.8 64.6 15.8 11.0 20.6 287 200 374 Karnataka Raichur 81.9 91.8 22.5 17.7 27.3 502 395 608 Karnataka Koppal 105.4 104.0 13.2 8.4 18.0 213 136 290 Karnataka Gadag 90.9 85.0 7.5 2.7 12.3 77 28 127 Karnataka Dharwad 71.0 69.0 9.4 4.6 14.2 159 78 241 Karnataka Uttara Kannada 59.7 66.3 16.7 11.9 21.5 201 143 258 Karnataka Haveri 73.5 74.3 12.5 7.7 17.3 191 118 264 Karnataka Bellary 96.9 96.2 13.3 8.5 18.1 358 229 486 27
Karnataka Chitradurga 87.6 80.3 5.8 1.1 10.6 87 16 158 Karnataka Davanagere 80.7 74.3 6.1 1.3 10.9 106 23 190 Karnataka Shimoga 84.6 75.1 3.4-1.4 8.2 51-21 124 Karnataka Udupi 60.3 58.6 8.5 3.7 13.2 71 31 110 Karnataka Chikmagalur 75.0 72.1 7.0 2.2 11.8 64 20 107 Karnataka Tumkur 87.7 84.0 9.5 4.7 14.3 208 103 313 Karnataka Bangalore 69.4 65.1 6.9 2.1 11.7 529 164 894 Karnataka Mandya 79.4 77.1 10.0 5.2 14.8 141 74 208 Karnataka Hassan 81.7 73.4 4.3-0.5 9.1 61-7 128 Karnataka Dakshina Kannada 50.8 53.5 11.6 6.8 16.4 190 112 268 Karnataka Kodagu 62.9 52.2-0.2-5.0 4.6-1 -23 21 Karnataka Mysore 79.0 76.9 10.2 5.4 15.0 256 136 376 Karnataka Chamarajanagar 82.1 82.1 12.6 7.8 17.4 104 65 144 Karnataka Gulbarga 67.8 75.7 18.9 14.1 23.7 540 404 677 Karnataka Yadgir 82.7 87.4 17.4 12.6 22.2 255 185 325 Karnataka Kolar 75.0 69.2 6.1 1.3 10.9 85 18 152 Karnataka Chikkaballapura 82.9 78.9 8.7 3.9 13.5 97 44 150 Karnataka Bangalore Rural 79.8 65.2-2.2-7.0 2.5-19 -58 21 Karnataka Ramanagara 67.3 62.8 6.4 1.7 11.2 56 14 97 Goa North Goa 58.0 50.4 2.3-2.5 7.1 13-14 41 Goa South Goa 70.0 60.8 2.2-2.6 7.0 11-13 35 Lakshadweep Lakshadweep 81.3 72.1 3.3-1.5 8.1 2-1 5 Kerala Kasaragod 29.0 27.7 4.3-0.5 9.0 49-6 104 Kerala Kannur 25.4 23.2 2.8-2.0 7.6 56-39 151 Kerala Wayanad 40.6 31.1-2.1-6.9 2.7-15 -49 19 Kerala Kozhikode 44.8 29.4-7.4-12.2-2.6-187 -307-66 Kerala Malappuram 30.8 28.5 3.6-1.2 8.4 151-49 350 Kerala Palakkad 33.2 26.9 0.0-4.8 4.7-1 -110 108 Kerala Thrissur 29.8 23.2-0.8-5.6 3.9-19 -129 90 Kerala Ernakulam 27.1 25.2 3.4-1.4 8.1 78-33 189 Kerala Idukki 34.5 26.9-1.1-5.8 3.7-9 -49 31 28
Kerala Kottayam 30.8 25.5 0.6-4.2 5.4 9-58 75 Kerala Alappuzha 33.4 33.5 6.3 1.6 11.1 95 23 167 Kerala Pathanamthitta 31.1 31.3 6.1 1.3 10.9 48 11 86 Kerala Kollam 31.5 30.9 5.4 0.6 10.2 107 12 201 Kerala Thiruvananthapuram 36.2 29.6 0.1-4.7 4.9 2-112 116 Tamil Nadu Thiruvallur 60.6 55.4 5.0 0.2 9.8 151 6 296 Tamil Nadu Chennai 53.0 45.2 1.4-3.4 6.2 47-116 209 Tamil Nadu Kancheepuram 65.4 58.8 4.2-0.6 9.0 134-19 288 Tamil Nadu Vellore 73.6 69.4 7.5 2.7 12.3 256 93 419 Tamil Nadu Tiruvannamalai 77.3 69.7 4.5-0.3 9.3 95-6 196 Tamil Nadu Viluppuram 72.3 66.9 6.2 1.4 10.9 194 44 345 Tamil Nadu Salem 72.4 75.3 14.5 9.7 19.3 403 270 536 Tamil Nadu Namakkal 70.1 66.8 8.0 3.2 12.8 98 40 157 Tamil Nadu Erode 73.4 62.4 0.7-4.0 5.5 12-64 88 Tamil Nadu The Nilgiris 61.0 53.6 2.8-1.9 7.6 16-11 44 Tamil Nadu Dindigul 66.4 73.7 4.0-0.8 8.8 70-14 154 Tamil Nadu Karur 67.0 63.0 7.0 2.2 11.7 57 18 96 Tamil Nadu Tiruchirappalli 67.4 63.7 7.3 2.6 12.1 161 56 265 Tamil Nadu Perambalur 66.4 85.3-5.0-9.8-0.2-25 -48-1 Tamil Nadu Ariyalur 66.4 89.6-5.0-9.8-0.2-33 -65-1 Tamil Nadu Cuddalore 57.3 56.3 8.8 4.0 13.6 194 89 299 Tamil Nadu Nagapattinam 61.4 54.0 2.9-1.9 7.6 39-26 104 Tamil Nadu Thiruvarur 66.4 53.8 1.0-3.8 5.8 10-38 58 Tamil Nadu Thanjavur 63.8 52.7-0.5-5.3 4.3-10 -103 83 Tamil Nadu Pudukkottai 54.3 50.1 5.2 0.4 10.0 73 6 141 Tamil Nadu Sivaganga 62.6 52.0-0.2-5.0 4.6-2 -55 50 Tamil Nadu Madurai 63.8 61.6 8.3 3.6 13.1 206 88 324 Tamil Nadu Theni 97.5 81.3-2.2-7.0 2.6-22 -70 26 Tamil Nadu Virudhunagar 83.1 68.2-2.2-7.0 2.5-36 -114 41 Tamil Nadu Ramanathapuram 53.6 51.2 6.9 2.1 11.7 78 24 133 Tamil Nadu Thoothukkudi 61.4 56.4 5.2 0.4 10.0 77 6 148 29
Tamil Nadu Tirunelveli 65.7 58.4 3.5-1.3 8.3 91-33 214 Tamil Nadu Kanniyakumari 44.0 37.6 1.5-3.3 6.3 22-46 90 Tamil Nadu Dharmapuri 110.3 90.6 5.0 0.2 9.8 68 3 132 Tamil Nadu Krishnagiri 66.4 76.2 4.0-0.8 8.8 69-14 152 Tamil Nadu Coimbatore 54.0 49.7 5.1 0.3 9.8 125 7 243 Tamil Nadu Tiruppur 62.3 55.0 3.0-1.8 7.8 56-32 144 Puducherry Yanam 69.1 64.4 4.0-0.8 8.8 2 0 5 Puducherry Puducherry 53.0 61.1 7.0 2.2 11.8 54 17 92 Puducherry Mahe 43.2 40.3 4.9 0.1 9.7 2 0 3 Puducherry Karaikal 66.4 58.3 1.0-3.8 5.8 2-7 10 Andaman & Nicobar Islands Nicobars 138.9 117.7-4.9-9.7-0.1-2 -3 0 Andaman & Nicobar Islands North & Middle Andaman 77.5 56.7-8.7-13.4-3.9-8 -13-4 Andaman & Nicobar Islands South Andaman 77.5 49.8-17.2-22.0-12.4-33 -42-24 30