India Population Strategy

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    United NationsPopulation Fund - In

    DISTRICT LEVEL 

    POPULATION PROJECTIONS

    IN EIGHT SELECTED STATES OF INDIA

    2006-2016

    DISTRICT LEVEL 

    POPULATION PROJECTIONS

    IN EIGHT SELECTED STATES OF INDIA

    2006-2016

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    RajasthanUttar Pradesh

    Bihar 

    Jharkhand

    Orissa

    Chhattisgarh

    Madhya Pradesh

    Maharashtra

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    DISTRICT LEVEL

    POPULATION PROJECTIONS

    IN SELECTED STATES OF

    INDIA – 2006 TO 2016

    DISTRICT LEVEL

    POPULATION PROJECTIONS

    IN SELECTED STATES OF

    INDIA – 2006 TO 2016

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    United Nations Population Fund - India

    UNFPA, the United Nations Population Fund, is an international development agency that promotes the right of every

    woman, man and child to enjoy a life of health and equal opportunity. UNFPA supports countries in using populationdata for policies and programmes to reduce poverty and to ensure that every pregnancy is wanted, every birth is safe,every young person is free of HIV/AIDS, and every girl and woman is treated with dignity and respect.

    This book may be freely reviewed, quoted,reproduced or translated, in full or in part,

    provided the source is acknowledged.

    Cover design: Rajat Ray, UNFPA - India

    First published in 2009© UNFPA

    Published by:

    UNFPA

    55 Lodi Estate

    New Delhi - 110003

    INDIA

    india.unfpa.org

    The information and views expressed in this document do not necessarily reflect the views of the United Nations

    Population Fund or the United Nations.

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    Foreword v

    Introduction 1

    Methodology 2

    Inputs Tables 4

    Results: District Level Population Projections

    Bihar 10

    Chattisgarh 48

    Jharkhand 66

    Madhya Pradesh 86

    Maharashtra 132

    Orissa 168

    Rajasthan 200

    Uttar Pradesh 234

    References 305

    CONTENTS

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    1. Dr. Ratan Chand, Chief Director, MOHFW, New Delhi

    2. Dr. K. Srinivasan, Honorary Visiting Professor, ISEC, Bangalore

    3. Mr. K. S. Natarajan, Consultant and Former Dy. Registrar General, GOI

    4. Dr. Arvind Pandey, Director, National Institute of Medical Statistics, New Delhi

    5. Dr. P. M. Kulkarni, Professor, JNU, New Delhi

    6. Mr. R. G. Mitra, Planning, Monitoring and Evaluation Officer, UNICEF, New Delhi

    7. Dr. Nesim Tumkaya, UNFPA Country Representative, India and Bhutan

    8. Dr. K. M. Sathyanarayana, Senior National Programme Officer, PDS, UNFPA, New Delhi

    9. Dr. Sanjay Kumar, National Programme Officer, M&E, UNFPA, New Delhi

    Research Assistance provided for

    the assignment at IIPS, Mumbai

    1. Ms. Neelanjana Pandey

    2. Mr. Praveen Pathak

    3. Ms. Puspita Dutta

    4. Ms. Archana Kujur

    Members of the Expert Group

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    FOREWORD

    The process of planning for development programmes in India, following the 73rd and 74th

    Constitutional Amendments, emphasizes devolution of powers to local-self governments and considers

    bottom-up planning as the most appropriate approach for success. To enable this process, basic data on

    population and relevant information for estimating indicators for small areas are necessary for the local

    programme managers to know where their administrative units stand in terms of major developmental

    indictors, what intra-variations exist and how programmatic inputs are to be devised?

    The Census of India, conducted decennially, provides population figures at the national and sub-

    national levels, right from the district to the village. However, data at sub-national levels are required

    annually for planning and for calculating monitoring indicators. In the absence of a well-defined

    denominator, assumptions using the state indicators have in the past been factored into the district

    annual planning exercise. Lack of data and information on these critical factors has impeded need-based

    planning and proper monitoring of development programmes. In fact, the Office of the Registrar General

    of India in 2006 projected the annual population of the country for national and state levels only for the

    period 2001-2016, and there has been no major attempt since then to provide sub-national estimates,

    especially at district level.

    In spite of consideration of the district as the fulcrum of decentralization, lack of basic population

    information at district level, prompted UNFPA to commission an exercise for estimating district-level

    population by age and sex for the eight states that include Bihar, Chhattisgarh, Jharkhand, Madhya

    Pradesh, Orissa, Rajasthan, Uttar Pradesh and Maharashtra. Seven of these states are common focus

    states for the GoI-UN Joint Programme on Convergence. District level population projections have been

    carried out for the period 2006-2016 at intervals of five years.

    Prof. Fouzdar Ram, Director, International Institute for Population Sciences (IIPS), carried out this

    exercise with technical inputs from Prof. P. M. Kulkarni of Jawaharlal Nehru University, New Delhi, my

    colleagues at UNFPA, Dr. Sathyanarayana and Dr. Sanjay Kumar and myself. Further, an Expert Group,

    comprising eminent demographers and statisticians reviewed and vetted the methodology adopted for

    this exercise, the results of which are presented in this publication.I hope that district programme planners and managers in these eight states will find the data

    useful in performing their tasks.

    Nesim Tumkaya

    UNFPA Representative for India

    vDistrict Level Population Projections

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    INTRODUCTION

    The importance of the population projections at sub-national levels, especially, at district level is well

    recognized, as it forms an important input for planning and program management. However, projected population

    data at this important administrative unit that are crucial for decentralized planning are not available though

    projections at the national and state-level are done periodically.

    Official committees of the Government of India (constituted by the Planning Commission or other

    commissions and departments) and individual experts have been carrying out the projection exercise (Registrar

    General of India, 1968, 1979, 1988, 1996, 2006; Cassen & Dyson, 1976; Srinivasan et.al 1984) and very recently long-

    term projections for India and large states (up to 2101) have been provided by the Population Foundation of India

    along with the Population Reference Bureau, USA. Yet, very few attempts have been made to carry out district-level

    population projections. This could primarily be due to the fact that projections at this level are full of

    uncertainties, especially, when one attempts to carry out long- term projections. It has been generally observed

    that the quality of projection deteriorates, as the duration of population projection increases (Stoto 1983; Agarwal

    2000). Moreover, the projection of population by age at the district level has been done very rarely; probably due

    to lack of data and selection of method that would provide reliable results, even for short duration. Further, district

    level projected age-wise population needs to be consistent with projected population at the state level.

    Given this background, the present exercise has attempted population projections of districts in eight

    states of India namely, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Maharashtra, Orissa, Rajasthan, and Uttar

    Pradesh, disaggregated by age and sex, for the years 2006, 2011 and 2016. The projections for states made by the

    Technical Group constituted by the National Commission on Population (Registrar General of India, 2006) have been

    used, as the basis for projections for districts within the respective states.

    1

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    METHODOLOGY

    A number of methods are used to project the population and the choice of method depends on

    administrative unit (i.e. national, state, district, urban, etc.) for which projections are being made and theavailability of data. The commonly used methods are:

    1. Cohort component projection method

    2. Mathematical methods

    3. Ratio method

    The Cohort Component Method of population projections requires detailed analysis of trends in fertility

    and mortality in order to make informed assumptions about the future. In addition, selection of a suitable life table

    is also a key factor for the accuracy of the projection. This approach is generally adopted for national level

    projections as well for large states in India. However, since information on fertility and mortality estimates is

    lacking at the district level, the choice of method falls on one of the other two methods or their variants. It has also

    been observed that the quality of projection is also a function of the level of population growth rate of the district.

    A detailed exercise has shown that the ratio method provides reasonably good projections for small areas such as

    the districts (Agarwal, 2000).

    While adopting the ratio method, however, adjustment of sub-national population projection (size) to

    national (or just higher level) is desirable as the population projections at higher levels are based on more detailedinformation about fertility, mortality and migration and by employing superior methods.

    In the present exercise the 'Ratio Method' is used to project population and age-sex structure of the districts

    in eight states of India. First, the shares of the district population to the state population were computed for the

    years 1981, 1991 and 2001. Based on the shares of the district at these Census dates, annual change in the share is

    computed and projected to the years 2006, 2011 and 2016. The projected shares of the district population are then

    applied to the state populations projected by the Registrar General of India (Registrar General of India, 2006) to get

    the projected district populations for the years 2006, 2011 and 2016. This was done separately for males and

    females.

    Subsequently, proportion of population in each group in a district was computed after adjusting the age

    disaggregated information for 'age not stated' category. The age structure of the population in future years was

    obtained by applying the total projected population of the district to the projected age proportions.

    For the district projections to be consistent with the state projections, it is essential that the sum of the

    projected district populations in an age group be the same as that projected by the Registrar General for the state

    for that age group and the sum of populations in all age groups in the district equals the projected total district

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    population for that year. For this purpose, row-wise and column-wise raking was done alternately. Two-three

    iterations were adequate to obtain a high degree of consistency.

    The national and state level population projections by the Technical Group were carried out using smoothed

    age distributions that minimize the effect of age misreporting. But the district shares used in the present exercise

    were based on unsmoothed distributions. Possibly because of this, the projected population of some cohorts at twopoints, say 2006 and 2011, showed apparent discrepancies in a few districts. In order to bring in internal

    consistency, the projections for an age group were fitted into specified ranges obtained from the cohort population

    five years earlier.

    The population projections are carried out for conventional five-year age groups. To obtain single year age

    distribution of the projected population, particularly in the younger ages, Sprague multipliers were used for each

    projection year.

    District level projections by the ratio method are determined by the state projections and extrapolations of

    the district shares. As trends in the district shares may not be steady mainly due to changes in inter-district

    migrations and intra-state imbalances in development, projection of district shares over a long period is not

    advisable. Therefore, the present exercise was limited up to the year 2016.

    Some limitations of these projections need to be noted here. It is recognized that projections for smaller

    areas suffer from larger relative errors as compared to projections for larger areas. Thus, the district level

    projections would have larger relative errors than national or state level projections. The single year populations

    for ages 0, 1, 2.., 14 were obtained by the Sprague method separately for each sex and at each time point, and

    hence sex ratios and year-to-year changes based on the single year projections should not be used to draw

    inferences. It is, therefore, suggested that as far as possible one should pool the single year populations into 5-year

    age groups, 0-4, 5-9, 10-14, unless one specifically needs projections by single year of age. Further, it is to be noted

    that the totals for age-groups and for males and females may not exactly add up due to rounding off.

    Finally, any population projections are based on assumptions about demographic processes, namely,

    fertility, mortality, and migration, over the projection period. As the projections for states provided by the

    Technical Group have been used as the basis for projections for districts within states, the assumptions made by the

    Technical Group are implicitly taken for granted at the state level. Within the states, the district shares are assumed

    to follow recent trends. It is known that during the process of development there could be changes in the trends

    of district shares, and in such cases, the district shares may change in a manner different than projected here.

    This limitation is inherent in small area projections such as the district projections presented in this report.

    3

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    Source: Report of the Technical Group on Population Projections

    Constituted by the National Commission on Population,

    Office of the Registrar General & Census Commissioner of India, New Delhi, May 2006

    State Level

    Projected Population by Age and Sex,

    2006, 2011 & 2016

    INPUT TABLES

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    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    Projected Population by Age and Sex as on 1st March: 2001-2016

    BIHAR ('000)

    Projected Population by Age and Sex as on 1st March: 2001-2016

    CHATTISGARH

    5

    ('000)

    All ages 90752 47165 43586 97720 50640 47080 103908 53676 50231

    0-4 10989 5795 5193 10567 5567 4999 10120 5327 47935-9 12110 6219 5891 10695 5635 5060 10296 5416 4880

    10-14 11762 6156 5606 11929 6108 5821 10528 5528 5001

    15-19 10300 5534 4767 11494 5999 5495 11654 5948 5707

    20-24 7616 4126 3490 9919 5328 4591 11089 5782 5308

    25-29 6232 3190 3042 7379 3972 3407 9656 5158 4498

    30-34 5762 2812 2951 6054 3066 2988 7188 3837 3351

    35-39 5391 2637 2754 5618 2715 2903 5908 2965 2942

    40-44 4857 2452 2404 5270 2562 2708 5498 2640 2859

    45-49 4090 2121 1969 4718 2368 2350 5130 2478 2652

    50-54 3319 1752 1567 3943 2034 1909 4563 2278 2285

    55-59 2585 1372 1213 3143 1647 1496 3752 1921 1831

    60-64 2049 1061 989 2381 1260 1121 2918 1523 1395

    65-69 1666 853 813 1810 933 877 2129 1121 1008

    70-74 1202 628 575 1397 711 686 1545 789 756

    75-79 682 363 319 928 476 452 1106 550 556

    80+ 139 95 44 477 258 219 827 415 412

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    All ages 22594 11345 11249 24258 12177 12081 25879 12989 12890

    0-4 2563 1300 1264 2526 1283 1243 2537 1289 1248

    5-9 2594 1310 1283 2497 1268 1229 2467 1255 1212

    10-14 2556 1297 1259 2567 1297 1269 2473 1256 1216

    15-19 2412 1237 1175 2521 1281 1240 2534 1283 1251

    20-24 1993 1028 966 2365 1218 1147 2474 1262 1211

    25-29 1696 854 842 1958 1010 948 2326 1199 1127

    30-34 1593 788 805 1666 838 828 1926 993 933

    35-39 1507 747 760 1563 771 792 1637 821 816

    40-44 1342 677 665 1476 728 747 1533 753 780

    45-49 1109 566 543 1308 656 651 1441 708 733

    50-54 895 454 441 1066 539 527 1262 628 634

    55-59 710 353 357 838 418 420 1005 501 504

    60-64 572 271 301 646 314 333 770 377 394

    65-69 459 208 252 497 230 267 570 271 299

    70-74 326 143 183 374 164 210 414 186 228

    75-79 215 93 122 242 102 140 288 121 167

    80+ 50 19 31 148 58 89 223 86 137

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    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    Projected Population by Age and Sex as on 1st March: 2001-2016

    JHARKHAND('000)

    Projected Population by Age and Sex as on 1st March: 2001-2016

    MADHYA PRADESH

    6

    ('000)

    All ages 29298 15088 14211 31472 16198 15274 33652 17303 16349

    0-4 3207 1647 1561 3113 1599 1514 3212 1649 15635-9 3601 1828 1773 3136 1614 1522 3050 1570 1480

    10-14 3614 1858 1756 3563 1809 1754 3104 1597 1507

    15-19 3331 1745 1586 3574 1837 1737 3525 1789 1736

    20-24 2628 1390 1238 3280 1720 1560 3522 1812 1710

    25-29 2171 1117 1055 2586 1368 1218 3232 1696 1536

    30-34 1990 992 997 2135 1097 1038 2547 1346 1201

    35-39 1857 928 929 1954 973 981 2100 1077 1023

    40-44 1675 856 818 1820 908 912 1919 954 964

    45-49 1420 742 678 1632 833 800 1778 885 893

    50-54 1156 615 542 1368 713 655 1578 803 775

    55-59 893 477 416 1091 578 514 1298 674 624

    60-64 678 352 326 819 437 382 1009 533 476

    65-69 508 253 255 592 307 285 725 386 339

    70-74 342 169 174 418 209 209 497 258 239

    75-79 187 93 94 259 128 131 325 161 164

    80+ 39 25 13 132 68 64 231 112 119

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    All ages 66390 34617 31773 72200 37673 34527 77875 40661 37213

    0-4 8058 4260 3798 8019 4240 3779 8021 4242 3779

    5-9 7869 4056 3814 7856 4170 3686 7840 4161 3678

    10-14 7788 4056 3732 7802 4024 3778 7796 4141 3655

    15-19 7281 3875 3405 7716 4022 3694 7738 3994 3744

    20-24 6017 3253 2765 7196 3834 3362 7634 3983 3651

    25-29 5110 2697 2413 5936 3212 2725 7108 3790 3318

    30-34 4651 2373 2278 5038 2660 2378 5861 3172 2689

    35-39 4259 2166 2094 4579 2333 2246 4967 2619 2349

    40-44 3733 1945 1788 4177 2118 2059 4499 2287 2212

    45-49 3024 1607 1416 3642 1890 1751 4084 2064 2020

    50-54 2351 1249 1102 2910 1537 1373 3517 1815 1702

    55-59 1814 944 870 2214 1163 1051 2756 1441 1315

    60-64 1479 727 752 1665 850 814 2049 1059 990

    65-69 1241 589 652 1292 622 671 1474 739 735

    70-74 921 438 483 1019 473 546 1084 511 573

    75-79 640 307 333 692 322 371 790 358 432

    80+ 152 75 77 447 204 244 657 286 371

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    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    Projected Population by Age and Sex as on 1st March: 2001-2016

    MAHARASHTRA('000)

    Projected Population by Age and Sex as on 1st March: 2001-2016

    ORISSA

    7

    ('000)

    All ages 104804 54623 50181 112660 58844 53816 120076 62849 57226

    0-4 9742 5136 4606 9903 5224 4680 9691 5114 45785-9 10199 5285 4914 9798 5191 4607 9971 5286 4685

    10-14 10402 5441 4961 10269 5345 4924 9880 5258 4622

    15-19 10787 5714 5073 10581 5548 5034 10470 5464 5006

    20-24 10115 5451 4664 11084 5860 5224 10911 5710 5201

    25-29 8975 4832 4143 10213 5530 4683 11194 5948 5246

    30-34 8198 4273 3926 9000 4865 4136 10242 5566 4676

    35-39 7468 3825 3643 8174 4266 3908 8979 4859 4120

    40-44 6642 3431 3212 7391 3782 3609 8098 4223 3875

    45-49 5547 2929 2619 6529 3363 3166 7275 3714 3561

    50-54 4384 2335 2049 5389 2830 2559 6354 3257 3097

    55-59 3366 1766 1600 4195 2221 1974 5169 2698 2471

    60-64 2666 1305 1362 3132 1626 1506 3921 2054 1867

    65-69 2384 1073 1311 2385 1145 1241 2822 1439 1384

    70-74 1984 898 1086 2006 880 1126 2033 952 1080

    75-79 1356 638 718 1512 667 844 1562 666 896

    80+ 587 291 296 1099 503 596 1502 641 862

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    All ages 38887 19692 19196 40750 20602 20148 42479 21438 21041

    0-4 3599 1864 1735 3445 1784 1662 3357 1737 1620

    5-9 3879 1992 1887 3529 1827 1702 3385 1751 1633

    10-14 4109 2099 2010 3840 1970 1870 3496 1808 1688

    15-19 4052 2060 1993 4053 2070 1983 3790 1943 1846

    20-24 3554 1788 1766 3971 2020 1952 3976 2031 1945

    25-29 3200 1590 1610 3493 1754 1739 3910 1984 1925

    30-34 2994 1476 1518 3148 1559 1589 3442 1723 1719

    35-39 2770 1378 1392 2938 1442 1496 3095 1527 1568

    40-44 2477 1268 1208 2706 1341 1365 2877 1407 1470

    45-49 2071 1085 986 2406 1225 1181 2637 1299 1337

    50-54 1658 870 788 1991 1034 957 2322 1172 1150

    55-59 1291 661 630 1559 808 751 1885 967 918

    60-64 1044 514 530 1181 597 584 1441 737 704

    65-69 876 421 455 916 445 471 1052 524 528

    70-74 649 309 340 718 338 380 770 366 404

    75-79 460 222 238 488 224 264 559 253 306

    80+ 205 95 110 367 164 203 487 207 281

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    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    Projected Population by Age and Sex as on 1st March: 2001-2016

    RAJASTHAN('000)

    Projected Population by Age and Sex as on 1st March: 2001-2016

    UTTAR PRADESH

    8

    ('000)

    All ages 62276 32466 29811 67830 35394 32436 72948 38090 34858

    0-4 7341 3930 3411 7329 3924 3405 7096 3799 32975-9 7739 4050 3690 7192 3860 3331 7193 3860 3333

    10-14 7636 4020 3616 7688 4023 3664 7145 3835 3310

    15-19 6982 3718 3264 7570 3988 3583 7622 3990 3632

    20-24 5682 3046 2635 6883 3671 3212 7467 3939 3528

    25-29 4749 2487 2262 5604 3002 2603 6797 3622 3176

    30-34 4200 2135 2065 4685 2448 2237 5535 2959 2576

    35-39 3785 1913 1872 4142 2100 2042 4625 2411 2214

    40-44 3330 1712 1619 3725 1873 1852 4082 2060 2022

    45-49 2765 1447 1317 3266 1669 1597 3658 1829 1829

    50-54 2212 1164 1048 2689 1396 1293 3183 1614 1569

    55-59 1707 886 820 2106 1094 1013 2571 1319 1252

    60-64 1356 670 685 1590 812 778 1974 1009 965

    65-69 1134 537 598 1225 592 633 1448 724 724

    70-74 863 402 461 973 447 527 1064 500 564

    75-79 628 285 343 691 307 384 792 347 445

    80+ 167 64 103 472 190 282 695 274 422

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    All ages 183282 96589 86693 200763 105798 94966 218089 114903 103185

    0-4 23766 12757 11009 24826 13320 11506 25175 13500 11675

    5-9 22686 11802 10884 23076 12420 10656 24174 12998 11177

    10-14 22985 12140 10845 22381 11636 10745 22781 12252 10530

    15-19 21048 11353 9695 22531 11907 10624 21926 11401 10525

    20-24 16379 8980 7399 20358 11031 9327 21810 11571 10239

    25-29 13263 7031 6233 15931 8725 7207 19865 10750 9116

    30-34 11653 5906 5747 12925 6825 6100 15567 8497 7069

    35-39 10567 5285 5282 11364 5728 5636 12629 6636 5993

    40-44 9405 4818 4588 10310 5129 5181 11111 5571 5540

    45-49 7908 4143 3765 9130 4646 4484 10036 4960 5076

    50-54 6421 3403 3018 7616 3961 3654 8826 4460 4366

    55-59 5041 2674 2367 6061 3182 2879 7233 3728 3505

    60-64 4079 2090 1989 4639 2432 2207 5630 2922 2707

    65-69 3403 1720 1683 3602 1822 1780 4154 2150 2005

    70-74 2522 1301 1220 2839 1414 1426 3071 1528 1544

    75-79 1799 942 857 1949 974 974 2258 1086 1173

    80+ 357 242 114 1225 645 580 1842 894 948

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    District Population Projection

    BIHAR 

    Pashchim

    Champaran

    Purba Champaran

    Sheohar 

    Sitamarhi

    Madhubani

    Supaul  Araria

    Kishanganj

    Purnia

    Katihar 

    Madhepura

    Saharsa

    DarbhangaMuzaffarpur 

    Gopalganj

    Siwan

    Saran

    Vaishali

    Samastipur 

    Begusarai

    Khagaria

    Bhagalpur 

    Banka

    Munger 

    LakhisaraiSheikhpura

    Nalanda

    PatnaBhojpur Buxar 

    Kaimur

    RohtasJehanabad

     Aurangabad Gaya   NawadaJamui

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    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Araria

    11

    0 (< 1 yr) 56144 30485 25659 63959 32780 31179 57757 30284 27473

    1 60979 32325 28654 62761 32643 30117 59858 31304 28554

    2 64694 33717 30976 62007 32561 29446 61309 31999 29310

    3 67383 34702 32680 61633 32525 29108 62190 32412 29779

    4 69142 35321 33822 61575 32527 29047 62585 32584 30001

    5 70068 35613 34455 61765 32558 29207 62575 32559 30017

    6 70256 35620 34636 62140 32610 29530 62243 32378 29866

    7 69803 35382 34421 62633 32673 29959 61671 32084 29587

    8 68803 34940 33863 63180 32741 30439 60940 31719 29221

    9 67353 34334 33020 63714 32804 30911 60133 31325 28808

    10 65439 33524 31915 64268 32834 31434 59148 30836 28312

    11 63044 32468 30576 64871 32804 32067 57885 30183 27702

    12 60819 31615 29204 64979 32802 32177 57342 29958 27384

    13 59082 31168 27915 64332 32857 31475 57968 30423 27545

    14 57597 30922 26675 63156 32903 30253 59295 31291 28003

    15 – 19 257361 143358 114003 295635 160181 135453 307237 162923 144314

    20 – 24 191054 101411 89643 254719 134028 120690 291063 148549 142514

    25 – 29 169295 86516 82779 195723 105192 90531 260297 138827 121470

    30 – 34 157272 76293 80979 168405 84809 83596 199313 105831 93482

    35 – 39 151577 76220 75357 160485 79755 80730 171261 88309 82952

    40 – 44 129693 66250 63444 143575 70642 72933 152348 74035 78313

    45 – 49 104958 57548 47410 123508 65672 57836 136649 70086 66563

    50 – 54 78245 41085 37160 95147 48816 46331 112229 55715 56514

    55 – 59 58496 32484 26012 72550 39804 32746 88228 47351 40877

    60 – 64 44623 22699 21924 52889 27520 25369 65956 33840 32116

    65 – 69 35898 18704 17194 39792 20871 18921 47640 25513 22126

    70 – 74 25537 13569 11968 30285 15696 14589 34094 17729 16364

    75+ 17635 10560 7075 30952 17556 13396 43463 23714 19749

    TOTAL 2392251 1248834 1143418 2610638 1361165 1249471 2812675 1463761 1348916

    0 – 14 970606 502136 468471 946973 490622 456349 902899 471339 431562

    6 – 14 582196 299973 282225 573273 295028 278245 536625 280197 256428

    15 – 59 1297952 681165 616786 1509746 788899 720847 1718623 891625 826998

    60+ 123694 65533 58161 153918 81643 72275 191153 100797 90356

    473063 548392 623449

  • 8/19/2019 India Population Strategy

    19/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Aurangabad

    12

    0 – 14 836801 431634 405172 804044 414750 389291 752887 391811 361076

    6 – 14 520169 265236 254936 504570 256446 248122 462523 238863 223661

    15 – 59 1235409 630963 604446 1425111 724501 700610 1608986 812654 796332

    60+ 147593 80121 67471 165349 90108 75241 191879 104666 87213

    454118 522185 588094

    0 (< 1 yr) 47687 26312 21375 53334 27780 25554 46802 25109 21692

    1 50174 26944 23231 50840 26772 24067 47660 25282 22378

    2 52310 27533 24777 49277 26138 23139 48325 25437 22889

    3 54111 28074 26037 48528 25828 22700 48834 25578 23256

    4 55589 28558 27032 48480 25795 22684 49221 25709 23512

    5 56761 28977 27784 49015 25991 23025 49522 25833 23688

    6 57641 29325 28316 50020 26366 23655 49772 25955 23817

    7 58243 29592 28651 51379 26872 24506 50006 26078 23929

    8 58582 29772 28810 52975 27462 25513 50261 26205 24056

    9 58672 29857 28815 54695 28088 26608 50571 26341 24230

    10 58490 29856 28635 56559 28780 27778 50824 26479 24345

    11 58014 29777 28237 58587 29573 29013 50909 26614 24295

    12 57446 29531 27916 59983 30014 29969 51597 26797 24800

    13 56876 29075 27802 60360 29891 30469 53218 27049 26169

    14 56205 28451 27754 60012 29400 30611 55365 27345 28020

    15 – 19 260382 130122 130260 290614 140767 149846 298298 141036 157262

    20 – 24 195555 103475 92080 256436 134505 121931 289415 147225 142190

    25 – 29 154873 79371 75502 184772 99573 85199 244041 130510 113530

    30 – 34 142307 69948 72358 149877 76443 73435 178983 96182 82801

    35 – 39 126691 62824 63867 132510 64930 67580 139967 71199 68768

    40 – 44 114005 58361 55645 124134 61213 62922 130097 63364 66733

    45 – 49 95924 49426 46498 111022 55354 55668 121322 58201 63121

    50 – 54 80769 43498 37271 96571 50850 45721 111767 56996 54771

    55 – 59 64903 33938 30965 79174 40867 38308 95098 47941 47157

    60 – 64 52412 28718 23694 61101 34183 26918 75258 41563 33695

    65 – 69 41058 21375 19683 44764 23459 21305 52932 28324 24607

    70 – 74 32216 17587 14629 37578 20025 17553 41783 22338 19445

    75+ 21906 12441 9466 21906 12441 9466 21906 12441 9466

    TOTAL 2219803 1142718 1077090 2394504 1229360 1165142 2553752 1309131 1244621

  • 8/19/2019 India Population Strategy

    20/313

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Banka

    13

    0 – 14 651479 340157 311321 606294 317094 289200 550504 290038 260467

    6 – 14 397751 208680 189069 373793 195954 177840 333213 177156 156058

    15 – 59 949929 498763 451167 1058242 553234 505008 1152648 598042 554606

    60+ 112731 58386 54344 132678 68624 64054 156364 80337 76028

    349821 388101 421951

    0 (< 1 yr) 36863 20131 16733 40128 20691 19436 34393 18146 16247

    1 39771 21026 18745 39052 20261 18791 35457 18495 16961

    2 42092 21779 20313 38415 20023 18392 36242 18776 17466

    3 43871 22398 21473 38157 19950 18207 36785 18998 17788

    4 45152 22888 22264 38216 20017 18199 37123 19169 17954

    5 45979 23255 22724 38533 20198 18335 37291 19298 17993

    6 46395 23506 22889 39048 20467 18581 37326 19396 17930

    7 46444 23646 22798 39700 20799 18902 37264 19470 17795

    8 46171 23683 22488 40429 21167 19263 37142 19529 17613

    9 45619 23623 21996 41175 21545 19630 36996 19584 17412

    10 44789 23459 21330 41969 21940 20029 36773 19612 17160

    11 43682 23185 20496 42842 22356 20485 36419 19595 16824

    12 42556 22869 19687 43277 22613 20664 36418 19688 16731

    13 41542 22540 19001 43032 22620 20412 36986 19957 17029

    14 40553 22169 18384 42321 22447 19874 37889 20325 17564

    15 – 19 182712 101650 81062 199986 108218 91768 198099 104911 93188

    20 – 24 140001 76420 63581 177851 96263 81588 193706 101791 91915

    25 – 29 120894 61850 59044 136659 73524 63134 173232 92489 80742

    30 – 34 112776 55646 57130 115064 58904 56160 132606 71509 61097

    35 – 39 108146 53740 54405 109579 53808 55771 111534 56852 54682

    40 – 44 94626 49416 45210 99814 50251 49563 100952 50211 50741

    45 – 49 77631 40665 36967 87044 44144 42899 91794 44821 46973

    50 – 54 63441 33209 30233 73507 37594 35914 82642 40892 41750

    55 – 59 49703 26167 23536 58737 30527 28210 68084 34565 33519

    60 – 64 40143 20321 19822 45336 23478 21858 53888 27515 26373

    65 – 69 33612 16853 16759 35500 17923 17577 40511 20902 19609

    70 – 74 24009 12745 11264 27130 14048 13082 29111 15124 13987

    75+ 14967 8467 6500 24711 13175 11536 32855 16796 16058

    TOTAL 1714139 897306 816832 1797213 938952 858261 1859517 968417 891101

  • 8/19/2019 India Population Strategy

    21/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Begusarai

    14

    0 – 14 1002247 525922 476327 954714 501305 453408 891180 471623 419558

    6 – 14 618136 324789 293349 591787 310238 281548 540595 287623 252971

    15 – 59 1419293 738640 680653 1636933 848058 788875 1840847 946207 894640

    60+ 152522 79462 73060 186096 96333 89763 227514 116673 110841

    518062 595865 669362

    0 (< 1 yr) 61322 33461 27861 66638 34537 32101 58616 31095 27521

    1 62373 33223 29150 62605 32755 29850 58558 30814 27744

    2 63473 33212 30261 59867 31553 28314 58471 30617 27854

    3 64583 33387 31196 58271 30863 27408 58377 30502 27875

    4 65668 33710 31958 57662 30616 27046 58300 30466 27835

    5 66692 34140 32552 57884 30743 27141 58263 30506 27758

    6 67618 34639 32979 58784 31176 27608 58289 30619 27669

    7 68410 35166 33244 60208 31846 28361 58399 30804 27596

    8 69031 35682 33349 61999 32685 29314 58619 31057 27562

    9 69445 36147 33298 64005 33624 30381 58970 31375 27595

    10 69666 36566 33101 66244 34665 31579 59315 31711 27603

    11 69711 36944 32767 68735 35811 32924 59516 32017 27499

    12 69285 37018 32267 70456 36639 33817 60399 32517 27882

    13 68249 36661 31588 70906 36939 33967 62307 33299 29008

    14 66721 35966 30756 70450 36853 33597 64781 34224 30557

    15 – 19 301975 164360 137615 340205 179971 160234 348002 180068 167934

    20 – 24 225588 122421 103167 294969 158715 136254 331761 173278 158483

    25 – 29 177153 91121 86032 210747 113963 96783 277391 148863 128528

    30 – 34 157968 78216 79752 165894 85210 80684 197430 106803 90627

    35 – 39 146951 71556 75396 153259 73726 79533 161329 80621 80708

    40 – 44 131420 65849 65571 142685 68812 73873 149026 70968 78058

    45 – 49 113366 57721 55645 130833 64433 66401 142480 67483 74997

    50 – 54 92766 48706 44060 110632 56757 53876 128444 63760 64684

    55 – 59 72106 38689 33416 87708 46471 41237 104986 54364 50621

    60 – 64 55024 28607 26417 63961 33997 29964 78510 41161 37349

    65 – 69 44570 22765 21805 48453 24916 23537 57098 29994 27104

    70 – 74 31432 16302 15130 36558 18482 18076 40509 20549 19960

    75+ 21497 11788 9708 37124 18938 18186 51397 24969 26428

    TOTAL 2574062 1344024 1230040 2777744 1445697 1332046 2959541 1534503 1425039

  • 8/19/2019 India Population Strategy

    22/313

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Bhagalpur

    15

    0 – 14 1003313 520972 482343 949550 493379 456172 878263 460056 418208

    6 – 14 631860 328336 303524 600572 311314 289259 541864 285112 256752

    15 – 59 1477461 802400 675061 1695954 918037 777916 1900104 1020616 879488

    60+ 166635 88161 78474 203210 107065 96145 248134 129609 118525

    486346 555787 622090

    0 (< 1 yr) 55234 29566 25668 61803 31183 30620 53848 27826 26022

    1 58351 30701 27650 59006 30431 28575 55035 28555 26480

    2 61133 31748 29385 57318 30019 27299 55962 29112 26850

    3 63579 32705 30875 56602 29910 26692 56676 29530 27146

    4 65690 33571 32120 56719 30067 26651 57224 29842 27383

    5 67466 34345 33121 57530 30455 27076 57654 30079 27575

    6 68907 35026 33881 58899 31035 27864 58011 30274 27737

    7 70012 35614 34398 60687 31773 28914 58344 30460 27884

    8 70783 36107 34676 62754 32630 30124 58699 30668 28031

    9 71220 36505 34715 64964 33570 31394 59123 30931 28192

    10 71309 36756 34553 67308 34538 32770 59441 31140 28301

    11 71039 36808 34231 69777 35477 34301 59479 31188 28291

    12 70472 36914 33558 71584 36447 35137 60393 31809 28584

    13 69633 37173 32460 72331 37451 34880 62673 33318 29355

    14 68485 37433 31052 72268 38393 33875 65701 35324 30377

    15 – 19 311723 180165 131558 350362 197223 153139 355703 196158 159545

    20 – 24 223051 130689 92362 290966 169171 121795 326616 184838 141777

    25 – 29 183048 97168 85880 217248 121030 96218 285386 157826 127561

    30 – 34 166163 83783 82380 174090 90999 83091 206777 113722 93054

    35 – 39 160262 80136 80126 165903 81981 83922 173918 89191 84728

    40 – 44 142818 74240 68578 154696 77508 77187 161252 79815 81437

    45 – 49 119021 63408 55613 137037 70726 66312 148942 74060 74882

    50 – 54 97553 52007 45547 116068 60484 55585 134490 67849 66641

    55 – 59 73821 40803 33018 89583 48917 40666 107020 57157 49862

    60 – 64 59047 30137 28911 68477 35747 32730 83888 43182 40706

    65 – 69 48750 25556 23194 52873 27900 24973 62183 33499 28684

    70 – 74 35386 19014 16373 41061 21527 19534 45409 23885 21524

    75+ 23452 13455 9997 40799 21891 18908 56654 29043 27611

    TOTAL 2647409 1411533 1235878 2848713 1518481 1330233 3026501 1610281 1416221

  • 8/19/2019 India Population Strategy

    23/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Bhojpur

    16

    0 – 14 896118 469384 426735 825788 432595 393195 746624 394410 352211

    6 – 14 571356 299570 271787 525544 274702 250844 460534 244458 216073

    15 – 59 1347302 704220 643082 1525144 793988 731156 1678725 867485 811240

    60+ 170168 91702 78466 187763 101526 86237 214121 115807 98314

    475889 537850 590472

    0 (< 1 yr) 47454 25421 22033 53858 27297 26560 45514 23651 21864

    1 50523 26678 23845 51010 26427 24583 46723 24360 22363

    2 53293 27863 25431 49251 25951 23300 47637 24922 22714

    3 55763 28967 26796 48450 25820 22630 48306 25361 22946

    4 57932 29983 27949 48476 25989 22488 48785 25698 23086

    5 59797 30902 28894 49199 26409 22790 49125 25960 23165

    6 61357 31717 29640 50487 27033 23455 49379 26168 23211

    7 62612 32419 30192 52211 27814 24397 49599 26347 23252

    8 63558 33001 30558 54239 28705 25534 49838 26520 23318

    9 64196 33453 30743 56441 29659 26782 50148 26711 23437

    10 64509 33766 30744 58797 30661 28135 50375 26865 23510

    11 64483 33926 30556 61287 31697 29590 50364 26925 23438

    12 64185 33944 30241 63226 32556 30671 51203 27313 23890

    13 63643 33817 29826 64261 33124 31138 53361 28209 25151

    14 62813 33527 29287 64595 33453 31142 56267 29400 26866

    15 – 19 288403 156322 132080 318144 167580 150564 310208 159808 150399

    20 – 24 208093 116438 91656 268260 148877 119382 297189 160268 136921

    25 – 29 167308 87421 79887 196230 107702 88528 254405 138590 115815

    30 – 34 152082 75219 76863 157462 80793 76669 184580 99752 84829

    35 – 39 137434 67051 70383 141314 68113 73201 146520 73359 73161

    40 – 44 125637 63934 61703 134484 65908 68576 138351 66965 71386

    45 – 49 104812 52297 52515 119257 57516 61741 127922 59288 68634

    50 – 54 91605 48686 42919 103734 53887 49847 117847 59260 58587

    55 – 59 71929 36852 35077 86260 43612 42648 101702 50195 51508

    60 – 64 59627 31880 27747 68336 37328 31008 82620 44534 38086

    65 – 69 47326 24519 22806 50724 26456 24269 58876 31358 27518

    70 – 74 37408 20439 16970 42896 22879 20017 46818 25052 21766

    75+ 25807 14864 10943 25807 14864 10943 25807 14864 10943

    TOTAL 2413588 1265306 1148283 2538695 1328109 1210588 2639470 1377702 1261765

  • 8/19/2019 India Population Strategy

    24/313

  • 8/19/2019 India Population Strategy

    25/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Darbhanga

    18

    0 – 14 1410735 741744 668992 1361115 715706 645408 1282058 679920 602140

    6 – 14 876525 456937 419589 852717 443110 409606 786271 414973 371298

    15 – 59 2007875 1043066 964808 2330480 1205522 1124959 2643191 1357625 1285566

    60+ 225272 113728 111543 275865 138567 137298 339406 169068 170337

    727369 841627 952811

    0 (< 1 yr) 82155 45196 36959 91687 47764 43923 81104 43370 37735

    1 85263 46147 39115 86735 46067 40668 81817 43744 38073

    2 88123 47083 41041 83583 45005 38578 82434 44067 38368

    3 90710 47981 42730 82001 44495 37506 82982 44347 38635

    4 92998 48820 44178 81761 44457 37304 83484 44596 38888

    5 94961 49580 45380 82631 44808 37823 83966 44823 39143

    6 96572 50240 46332 84384 45468 38916 84452 45038 39415

    7 97807 50779 47029 86790 46354 40435 84968 45251 39717

    8 98639 51175 47465 89619 47387 42232 85537 45472 40064

    9 99043 51407 47636 92641 48483 44158 86185 45712 40472

    10 99059 51485 47574 95936 49667 46269 86760 45922 40838

    11 98730 51418 47311 99581 50962 48619 87113 46056 41058

    12 97693 51035 46658 101810 51763 50047 88146 46410 41736

    13 95789 50254 45535 101778 51780 49998 90234 47113 43121

    14 93193 49144 44049 100178 51246 48932 92876 47999 44877

    15 – 19 415419 222564 192855 472052 245679 226374 487378 248007 239371

    20 – 24 305655 166504 139150 403112 217740 185372 457625 239969 217656

    25 – 29 246834 127411 119423 296177 160696 135481 393475 211872 181603

    30 – 34 229938 111287 118651 243560 122386 121175 292565 155020 137545

    35 – 39 220301 107971 112330 231741 112215 119526 246075 123753 122322

    40 – 44 199199 99896 99303 218142 105296 112845 229961 109609 120353

    45 – 49 165008 87856 77151 192077 99072 93004 211127 104915 106212

    50 – 54 127942 67250 60692 153901 79045 74857 180347 89630 90717

    55 – 59 97578 52325 45253 119717 63392 56325 144638 74850 69788

    60 – 64 80221 39319 40902 94056 47196 46860 116528 57624 58904

    65 – 69 67856 34649 33207 74405 38251 36154 88498 46476 42022

    70 – 74 45897 22761 23136 53843 25997 27846 60219 29180 31039

    75+ 31298 17000 14299 53561 27123 26437 74160 35788 38372

    TOTAL 3643881 1898539 1745344 3967460 2059795 1907664 4264655 2206614 2058043

  • 8/19/2019 India Population Strategy

    26/313

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Gaya

    19

    0 – 14 1453178 747044 706133 1394492 717198 677296 1302433 675584 626850

    6 – 14 906946 464144 442801 879240 448790 430451 803714 416684 387031

    15 – 59 2129163 1089391 1039772 2454717 1250349 1204369 2770941 1402720 1368221

    60+ 241064 128272 112792 269645 144109 125536 312968 167478 145490

    790322 908457 1022393

    0 (< 1 yr) 80003 43819 36184 90644 46802 43842 80203 42629 37574

    1 85534 45295 40239 86905 45126 41780 81698 42721 38977

    2 90188 46675 43513 84685 44159 40526 82907 42910 39997

    3 94018 47943 46075 83790 43805 39985 83883 43183 40700

    4 97076 49085 47991 84026 43967 40059 84679 43527 41152

    5 99413 50083 49330 85202 44549 40653 85349 43930 41419

    6 101083 50922 50161 87124 45455 41669 85946 44378 41568

    7 102137 51586 50551 89600 46589 43011 86522 44858 41664

    8 102628 52059 50569 92436 47854 44583 87131 45358 41773

    9 102607 52325 50282 95441 49153 46287 87826 45864 41962

    10 102041 52426 49615 98666 50578 48088 88436 46402 42035

    11 100895 52405 48490 102167 52219 49948 88791 46999 41793

    12 99654 51954 47700 104518 53046 51472 90064 47446 42617

    13 98544 50941 47602 105032 52587 52445 92754 47654 45100

    14 97357 49526 47831 104256 51309 52948 96244 47725 48519

    15 – 19 451312 223686 227626 504026 242076 261950 517144 242394 274749

    20 – 24 344799 182710 162089 451531 237182 214349 508621 259126 249494

    25 – 29 269444 139267 130176 321026 174398 146629 423828 228506 195322

    30 – 34 246488 122101 124387 259249 133219 126030 309468 167481 141987

    35 – 39 217725 108629 109097 227416 112125 115291 240117 122874 117244

    40 – 44 193934 99658 94277 210879 104402 106477 220919 108032 112886

    45 – 49 162686 84679 78006 188038 94741 93297 205398 99612 105786

    50 – 54 134504 72002 62502 160653 84072 76582 187085 94797 92288

    55 – 59 108271 56659 51612 131899 68134 63764 158362 79898 78464

    60 – 64 85329 45902 39428 99340 54587 44753 122307 66325 55982

    65 – 69 69271 35343 33929 75421 38742 36679 89147 46780 42368

    70 – 74 51077 27469 23608 59497 31221 28275 66127 34815 31312

    75+ 35387 19558 15829 35387 19558 15829 35387 19558 15829

    TOTAL 3823405 1964706 1858698 4118855 2111656 2007201 4386342 2245782 2140561

  • 8/19/2019 India Population Strategy

    27/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Gopalganj

    20

    0 – 14 914902 467791 447114 855008 437108 417897 780100 402465 377636

    6 – 14 576600 292198 284404 541288 273298 267990 481479 247096 234384

    15 – 59 1237783 599102 638681 1401166 674417 726749 1546785 737736 809049

    60+ 161515 83044 78471 193468 99077 94391 232170 117985 114185

    460953 520106 573502

    0 (< 1 yr) 50588 27005 23583 56181 28323 27857 48246 25029 23217

    1 53197 27985 25212 53228 27452 25775 48983 25448 23535

    2 55601 28919 26683 51434 26968 24466 49608 25807 23801

    3 57784 29792 27992 50649 26817 23832 50143 26113 24030

    4 59725 30591 29134 50723 26946 23776 50610 26374 24236

    5 61407 31301 30106 51505 27304 24201 51031 26598 24433

    6 62812 31910 30902 52845 27837 25008 51428 26792 24636

    7 63922 32402 31520 54594 28492 26102 51823 26965 24858

    8 64717 32764 31954 56600 29216 27384 52237 27123 25115

    9 65181 32981 32200 58714 29958 28756 52693 27274 25419

    10 65317 33055 32263 60940 30713 30227 53030 27363 25667

    11 65130 32984 32146 63284 31481 31803 53086 27335 25751

    12 64488 32685 31803 64819 31955 32864 53799 27512 26287

    13 63330 32115 31215 65088 31983 33105 55555 28029 27526

    14 61703 31302 30401 64404 31663 32741 57828 28703 29125

    15 – 19 271285 137897 133388 301168 148462 152706 303547 146116 157431

    20 – 24 174634 88719 85916 225011 113269 111742 249361 121579 127782

    25 – 29 145052 68036 77016 170040 84253 85786 220525 108358 112167

    30 – 34 135188 59905 75283 139898 64557 75341 164048 80186 83861

    35 – 39 128650 57817 70833 132214 58649 73565 137132 63370 73762

    40 – 44 119520 55847 63673 126853 56906 69947 130419 57724 72695

    45 – 49 104414 50416 53998 117830 54933 62897 125184 56017 69167

    50 – 54 88237 44299 43938 103288 50612 52676 116477 55141 61336

    55 – 59 70802 36165 34637 84865 42776 42090 100092 49245 50847

    60 – 64 57234 29225 28009 65560 34239 31320 79291 40835 38456

    65 – 69 46537 23359 23178 49853 25196 24657 57885 29897 27988

    70 – 74 34658 17782 16876 39722 19860 19861 43368 21759 21609

    75+ 23086 12678 10408 38334 19781 18553 51627 25495 26132

    TOTAL 2314200 1149937 1164266 2449642 1210602 1239037 2559055 1258186 1300870

  • 8/19/2019 India Population Strategy

    28/313

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Jamui

    21

    0 – 14 590935 307342 283592 572209 297850 274358 540739 283749 256988

    6 – 14 369054 192403 176649 360522 187576 172944 333692 176243 157447

    15 – 59 875177 454040 421137 1021309 527430 493878 1164981 597485 567496

    60+ 89935 47136 42799 110876 57943 52933 137073 71069 66004

    329020 382714 435602

    0 (< 1 yr) 31302 16965 14338 37163 19006 18157 33319 17490 15829

    1 34250 18037 16213 35679 18433 17246 33924 17638 16286

    2 36659 18957 17702 34801 18129 16672 34416 17805 16611

    3 38571 19733 18838 34452 18057 16395 34816 17988 16828

    4 40028 20370 19658 34556 18182 16375 35146 18187 16959

    5 41071 20877 20194 35036 18467 16569 35426 18398 17028

    6 41743 21259 20484 35812 18876 16937 35678 18621 17057

    7 42085 21524 20561 36810 19372 17437 35922 18852 17070

    8 42139 21677 20461 37951 19921 18029 36180 19090 17089

    9 41946 21727 20219 39157 20486 18671 36472 19333 17139

    10 41474 21669 19805 40443 21085 19357 36721 19574 17147

    11 40689 21498 19191 41819 21739 20079 36848 19804 17044

    12 40008 21276 18732 42760 22135 20626 37371 20050 17321

    13 39622 21032 18589 43010 22124 20886 38511 20321 18189

    14 39348 20741 18607 42760 21838 20922 39989 20598 19391

    15 – 19 183384 95758 87626 206444 104631 101813 214089 106023 108066

    20 – 24 135031 73069 61962 179498 96305 83194 204673 106581 98092

    25 – 29 109680 56245 53435 132650 71527 61123 177007 94718 82289

    30 – 34 100251 50205 50046 107033 55580 51452 129137 70583 58554

    35 – 39 93006 45994 47012 98612 48186 50426 105237 53389 51848

    40 – 44 82727 42600 40127 91313 45305 46008 96687 47385 49302

    45 – 49 70162 36424 33738 82320 41363 40957 90884 43951 46933

    50 – 54 57103 30342 26761 69234 35957 33277 81489 40968 40522

    55 – 59 43834 23403 20430 54205 28576 25629 65779 33887 31892

    60 – 64 33613 17650 15963 39723 21319 18404 49432 26172 23260

    65 – 69 26170 13021 13149 28924 14491 14433 34554 17695 16859

    70 – 74 18737 10103 8634 22155 11657 10498 24888 13138 11750

    75+ 11414 6363 5052 20074 10476 9598 28199 14064 14135

    TOTAL 1556047 808517 747528 1704393 883223 821169 1842793 952303 890488

  • 8/19/2019 India Population Strategy

    29/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Jehanabad

    22

    0 – 14 616590 320268 296320 594073 308517 285559 556853 291801 265053

    6 – 14 384477 196603 187873 374279 190706 183573 343637 177926 165711

    15 – 59 939422 479976 459446 1080908 550013 530894 1219022 616548 602474

    60+ 116386 62658 53728 130530 70527 60003 151650 82007 69643

    348072 399129 448563

    0 (< 1 yr) 33822 18946 14876 38581 20343 18239 34313 18656 15657

    1 36296 19781 16515 37043 19784 17259 34935 18800 16135

    2 38352 20485 17867 36134 19456 16679 35441 18932 16509

    3 40018 21063 18955 35774 19326 16448 35853 19053 16801

    4 41325 21522 19802 35882 19364 16519 36193 19165 17028

    5 42300 21868 20432 36380 19538 16842 36481 19269 17212

    6 42974 22106 20868 37185 19817 17368 36741 19369 17372

    7 43376 22243 21133 38220 20170 18049 36992 19465 17527

    8 43535 22285 21250 39402 20566 18836 37258 19560 17698

    9 43479 22236 21243 40653 20973 19680 37560 19656 17904

    10 43186 22103 21082 42001 21425 20577 37826 19757 18069

    11 42629 21890 20739 43475 21954 21521 37987 19868 18118

    12 42107 21609 20498 44451 22208 22243 38525 19978 18548

    13 41753 21266 20487 44631 22025 22606 39648 20082 19566

    14 41438 20865 20573 44261 21568 22693 41100 20191 20909

    15 – 19 194390 96489 97901 214306 103085 111221 220427 103479 116948

    20 – 24 150402 80095 70307 196236 103597 92639 216794 111023 105771

    25 – 29 119606 61767 57838 143070 77660 65410 189351 102004 87347

    30 – 34 110079 54222 55857 116238 59406 56832 139097 74892 64205

    35 – 39 97046 48288 48758 101768 50039 51729 107717 54977 52741

    40 – 44 85934 44235 41698 93813 46528 47285 98522 48266 50256

    45 – 49 71441 36486 34955 82902 40957 41946 90779 43137 47643

    50 – 54 61091 32959 28132 72111 38040 34071 83630 42728 40902

    55 – 59 49435 25435 23999 60462 30701 29761 72705 36042 36663

    60 – 64 40774 22028 18747 47658 26297 21361 58821 32033 26788

    65 – 69 32904 17108 15795 35967 18826 17142 42618 22778 19840

    70 – 74 24762 13330 11432 28958 15211 13747 32265 17004 15261

    75+ 17946 10193 7753 17946 10193 7753 17946 10193 7753

    TOTAL 1672398 862903 809493 1805511 929057 876457 1927525 990356 937170

  • 8/19/2019 India Population Strategy

    30/313

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Kaimur (Bhabua)

    23

    0 – 14 550433 289799 260631 530944 279854 251090 500765 265924 234841

    6 – 14 332059 175325 156733 323413 170504 152910 299399 160133 139267

    15 – 59 774879 404449 370430 897852 466322 431530 1016678 524254 492424

    60+ 100559 53517 47042 112968 60336 52633 131229 70169 61060

    287086 332019 375171

    0 (< 1 yr) 32779 17688 15091 36670 18807 17863 32780 17179 15600

    1 34759 18424 16335 35304 18391 16912 33316 17447 15869

    2 36315 19019 17296 34380 18128 16252 33664 17643 16021

    3 37479 19481 17997 33842 17997 15845 33850 17776 16074

    4 38283 19820 18463 33635 17978 15657 33903 17855 16048

    5 38759 20042 18716 33700 18049 15651 33853 17891 15962

    6 38939 20157 18782 33983 18191 15792 33728 17893 15835

    7 38856 20173 18684 34425 18383 16043 33555 17869 15686

    8 38542 20096 18445 34972 18604 16368 33364 17831 15533

    9 38028 19937 18090 35567 18834 16733 33184 17787 15397

    10 37309 19690 17619 36230 19078 17151 32960 17721 15240

    11 36383 19351 17032 36982 19343 17640 32640 17614 15026

    12 35463 18992 16471 37381 19476 17905 32662 17611 15051

    13 34656 18646 16010 37214 19406 17809 33217 17774 15443

    14 33883 18283 15600 36659 19189 17469 34089 18033 16056

    15 – 19 153382 83223 70159 174021 91762 82259 179004 92317 86687

    20 – 24 117277 62307 54970 154429 81332 73097 174662 89227 85435

    25 – 29 96793 50686 46107 115962 63777 52184 153485 83787 69699

    30 – 34 91073 44930 46143 96318 49299 47019 115268 62150 53118

    35 – 39 81733 41299 40434 85843 42871 42973 90868 47077 43791

    40 – 44 73613 37439 36173 80487 39423 41064 84534 40892 43641

    45 – 49 63313 32574 30739 73585 36631 36954 80583 38595 41988

    50 – 54 54265 29373 24892 64007 33879 30128 74237 38062 36175

    55 – 59 43430 22618 20812 53200 27348 25852 64036 32147 31889

    60 – 64 34650 18596 16055 40563 22238 18325 50068 27088 22980

    65 – 69 28639 14631 14007 31354 16127 15227 37154 19522 17632

    70 – 74 22077 11784 10293 25859 13464 12394 28814 15053 13761

    75+ 15193 8506 6687 15193 8506 6687 15193 8506 6687

    TOTAL 1425871 747765 678103 1541765 806512 735253 1648671 860347 788325

  • 8/19/2019 India Population Strategy

    31/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Katihar

    24

    0 – 14 1073900 552370 521529 1040270 535500 504771 984868 511053 473816

    6 – 14 645943 330068 315874 631926 322201 309727 587124 303929 283195

    15 – 59 1419790 748029 671760 1642069 861507 780562 1857667 967522 890145

    60+ 138948 70397 68551 170594 86274 84320 209883 105400 104483

    486323 560484 633147

    0 (< 1 yr) 66784 35831 30953 74540 37907 36632 67100 34890 32209

    1 69172 36500 32672 70443 36490 33952 66768 34781 31988

    2 71119 37028 34091 67592 35463 32129 66435 34633 31802

    3 72643 37422 35221 65829 34779 31050 66110 34461 31650

    4 73758 37688 36070 64998 34395 30604 65804 34274 31530

    5 74481 37833 36648 64942 34265 30677 65527 34085 31442

    6 74827 37863 36964 65503 34344 31159 65289 33907 31382

    7 74813 37783 37029 66524 34588 31937 65100 33751 31349

    8 74453 37601 36852 67848 34950 32898 64972 33630 31342

    9 73765 37323 36442 69318 35387 33931 64913 33554 31359

    10 72758 36913 35846 70988 35876 35113 64828 33458 31370

    11 71445 36335 35109 72916 36393 36522 64620 33275 31345

    12 69864 35805 34059 73879 36783 37097 64833 33410 31423

    13 68041 35411 32630 73298 36953 36345 65689 34030 31659

    14 65977 35034 30943 71652 36927 34725 66880 34914 31966

    15 – 19 290601 161671 128930 330966 179093 151873 341777 180999 160778

    20 – 24 206824 112917 93907 273387 148001 125386 310416 163154 147262

    25 – 29 179684 91942 87743 210068 113036 97032 277605 148237 129368

    30 – 34 169388 83264 86124 179829 91723 88106 212566 114234 98332

    35 – 39 163214 81841 81373 171372 84924 86448 181720 93447 88274

    40 – 44 139101 70834 68267 152674 74876 77797 160977 77973 83005

    45 – 49 116483 63080 53403 135899 71337 64561 149406 75611 73795

    50 – 54 87370 45201 42169 105335 53228 52107 123459 60334 63125

    55 – 59 67124 37278 29846 82540 45288 37251 99741 53534 46207

    60 – 64 49576 24634 24942 58258 29627 28631 72190 36187 36003

    65 – 69 41088 20269 20818 45155 22433 22722 53718 27282 26436

    70 – 74 29143 14803 14340 34266 16957 17309 38331 19035 19296

    75+ 19142 10691 8452 32915 17257 15658 45644 22896 22748

    TOTAL 2632638 1370797 1261840 2852933 1483281 1369653 3052418 1583975 1468444

  • 8/19/2019 India Population Strategy

    32/313

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Khagaria

    25

    0 – 14 563531 298994 264536 541763 287806 253955 509326 272565 236761

    6 – 14 339982 180929 159050 330160 175473 154687 304579 164184 140394

    15 – 59 761211 403551 357660 879469 464229 415240 992375 519829 472546

    60+ 80796 42478 38318 98422 51508 46914 120555 62530 58024

    274558 316297 356587

    0 (< 1 yr) 35405 19569 15837 39116 20559 18556 34967 18767 16200

    1 36335 19549 16787 36694 19404 17290 34540 18358 16182

    2 37124 19587 17537 35002 18595 16406 34182 18052 16130

    3 37772 19669 18103 33948 18092 15856 33890 17839 16051

    4 38276 19781 18495 33444 17851 15593 33664 17710 15955

    5 38637 19910 18727 33399 17832 15567 33504 17655 15849

    6 38854 20041 18813 33725 17992 15733 33407 17665 15742

    7 38927 20162 18765 34332 18291 16041 33374 17732 15642

    8 38854 20258 18595 35130 18685 16445 33403 17846 15557

    9 38634 20316 18318 36030 19133 16896 33494 17998 15496

    10 38282 20337 17945 37071 19647 17424 33607 18173 15434

    11 37812 20322 17489 38292 20235 18057 33705 18358 15347

    12 37150 20183 16966 38960 20596 18364 33974 18568 15406

    13 36266 19877 16389 38728 20583 18145 34486 18803 15682

    14 35203 19433 15770 37892 20311 17582 35129 19041 16088

    15 – 19 156876 87991 68885 177234 96718 80516 181796 97113 84683

    20 – 24 119000 65020 53980 156038 84540 71498 175985 92573 83412

    25 – 29 96247 50428 45819 114821 63183 51638 151548 82773 68775

    30 – 34 87759 43501 44258 92422 47523 44899 110294 59726 50568

    35 – 39 81451 41057 40394 85186 42439 42747 89919 46476 43443

    40 – 44 72511 36938 35574 78949 38733 40216 82684 40064 42620

    45 – 49 60454 32150 28304 69965 36043 33922 76403 37918 38485

    50 – 54 48822 25853 22969 58390 30218 28172 67977 34050 33927

    55 – 59 38091 20613 17478 46463 24832 21631 55769 29136 26633

    60 – 64 30237 15722 14515 35248 18737 16511 43384 22747 20637

    65 – 69 23878 12277 11602 26032 13474 12558 30761 16262 14499

    70 – 74 16351 8633 7718 19071 9820 9251 21190 10948 10242

    75+ 10330 5846 4484 18072 9477 8595 25220 12573 12647

    TOTAL 1405538 745022 660514 1519654 803543 716109 1622256 854925 767331

  • 8/19/2019 India Population Strategy

    33/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Kishanganj

    26

    0 – 14 588066 299183 288883 579872 295099 284769 556777 285798 270976

    6 – 14 349735 173613 176122 348257 172357 175896 328066 164998 163067

    15 – 59 791069 411951 379118 924929 480212 444717 1060765 547280 513484

    60+ 67215 33966 33249 84050 42504 41546 105040 52780 52259

    257554 299466 342597

    0 (< 1 yr) 37683 20944 16739 42598 22390 20209 38954 21012 17942

    1 38869 21039 17830 40232 21364 18868 38685 20676 18008

    2 39759 21051 18708 38495 20541 17953 38350 20320 18030

    3 40377 20989 19388 37316 19904 17412 37972 19956 18016

    4 40748 20864 19884 36625 19433 17191 37573 19593 17980

    5 40895 20683 20212 36349 19110 17240 37177 19243 17933

    6 40843 20457 20385 36419 18914 17505 36804 18918 17886

    7 40615 20195 20420 36764 18828 17935 36477 18627 17850

    8 40236 19906 20330 37311 18833 18478 36219 18382 17838

    9 39731 19600 20131 37990 18909 19080 36053 18193 17860

    10 39040 19242 19799 38768 19035 19732 35857 18018 17839

    11 38108 18797 19311 39612 19189 20423 35513 17813 17700

    12 37366 18495 18871 40260 19366 20893 35754 17859 17894

    13 37002 18433 18569 40564 19555 21009 36885 18276 18609

    14 36794 18488 18306 40569 19728 20841 38504 18912 19591

    15 – 19 170487 88580 81907 195652 98652 97000 204853 100915 103938

    20 – 24 112898 64568 48330 151922 86196 65726 174899 96503 78396

    25 – 29 98571 50510 48061 116735 62901 53835 156412 83637 72775

    30 – 34 91340 44150 47190 98717 49542 49175 119767 63386 56381

    35 – 39 91078 44768 46310 94075 45688 48387 101143 51010 50133

    40 – 44 79094 40236 38858 88376 43297 45080 94479 45714 48765

    45 – 49 64568 35152 29416 76688 40478 36210 85483 43509 41974

    50 – 54 48146 24567 23579 59092 29440 29652 70222 33819 36404

    55 – 59 34886 19419 15467 43672 24018 19653 53507 28788 24719

    60 – 64 25010 12323 12687 29919 15091 14828 37590 18686 18904

    65 – 69 19734 9672 10063 22079 10897 11181 26631 13440 13192

    70 – 74 13568 6939 6629 16240 8093 8147 18420 9211 9209

    75+ 8903 5032 3871 15811 8422 7389 22398 11443 10955

    TOTAL 1446350 745100 701250 1588850 817814 771032 1722581 885859 836720

  • 8/19/2019 India Population Strategy

    34/313

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Lakhisarai

    27

    0 – 14 336209 175835 160374 313991 164419 149576 286825 151340 135484

    6 – 14 204139 106742 97399 192530 100532 92001 172630 91457 81172

    15 – 59 467883 241815 226068 525535 270295 255239 576053 294033 282021

    60+ 54017 28112 25905 59035 30844 28191 66813 34939 31874

    172718 193441 211628

    0 (< 1 yr) 19733 10879 8855 21404 11171 10234 18500 9890 8610

    1 20962 11196 9765 20618 10813 9805 18841 9938 8903

    2 21938 11466 10472 20098 10579 9519 19073 9976 9097

    3 22681 11689 10992 19812 10452 9360 19214 10005 9209

    4 23211 11866 11344 19725 10416 9309 19280 10028 9252

    5 23545 11997 11547 19804 10456 9348 19287 10046 9241

    6 23703 12084 11619 20015 10556 9460 19253 10061 9192

    7 23704 12127 11577 20325 10699 9626 19194 10076 9118

    8 23566 12126 11441 20701 10871 9830 19128 10092 9036

    9 23310 12082 11228 21107 11055 10053 19071 10112 8958

    10 22927 11996 10931 21553 11257 10296 18986 10128 8858

    11 22410 11867 10544 22044 11483 10562 18839 10134 8705

    12 21910 11700 10210 22343 11608 10735 18909 10176 8733

    13 21497 11499 9998 22335 11574 10761 19320 10274 9046

    14 21112 11261 9851 22107 11429 10678 19930 10404 9526

    15 – 19 96465 51271 45194 105931 54679 51252 105565 53266 52299

    20 – 24 73138 39042 34095 93215 49330 43885 102139 52438 49701

    25 – 29 58550 30125 28424 67893 36725 31168 87058 46734 40324

    30 – 34 51930 25634 26296 53157 27223 25934 61631 33247 28384

    35 – 39 47957 23534 24423 48751 23637 25114 49995 25174 24821

    40 – 44 44215 22139 22076 46774 22542 24233 47548 22626 24922

    45 – 49 38753 19876 18877 43118 21395 21722 45639 21786 23853

    50 – 54 31881 16800 15080 37060 19084 17976 41917 20889 21028

    55 – 59 24995 13394 11602 29635 15681 13955 34559 17871 16688

    60 – 64 19271 9874 9397 21836 11442 10394 26111 13493 12619

    65 – 69 15836 8166 7671 16781 8711 8070 19265 10213 9052

    70 – 74 11287 5884 5403 12796 6503 6293 13814 7044 6770

    75+ 7622 4188 3433 7622 4188 3433 7622 4188 3433

    TOTAL 858109 445762 412347 898561 465559 433006 929691 480312 449378

  • 8/19/2019 India Population Strategy

    35/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Madhepura

    28

    0 – 14 666882 350616 316269 644016 339121 304893 609035 323090 285947

    6 – 14 400334 209239 191097 390114 203707 186403 362239 191860 170380

    15 – 59 925153 478188 446965 1072144 551475 520669 1213906 620036 593870

    60+ 92100 48418 43682 113325 59321 54004 139524 72413 67111

    348353 402532 454729

    0 (< 1 yr) 37450 21094 16357 42437 22527 19910 37930 20641 17289

    1 41409 22502 18907 42231 22517 19714 39935 21416 18520

    2 44427 23573 20854 42162 22532 19630 41341 21957 19384

    3 46589 24336 22253 42205 22566 19639 42223 22295 19928

    4 47981 24819 23162 42336 22611 19726 42655 22455 20200

    5 48692 25053 23639 42531 22661 19871 42712 22466 20246

    6 48806 25066 23740 42766 22709 20057 42469 22356 20113

    7 48410 24888 23523 43016 22748 20268 42002 22152 19849

    8 47591 24547 23044 43257 22773 20484 41384 21883 19501

    9 46435 24074 22361 43466 22776 20690 40692 21576 19116

    10 44924 23458 21466 43653 22759 20894 39849 21206 18643

    11 43039 22688 20351 43833 22723 21109 38782 20750 18033

    12 41390 21991 19399 43797 22621 21175 38314 20496 17819

    13 40275 21475 18800 43450 22430 21019 38821 20577 18244

    14 39464 21052 18413 42876 22168 20707 39926 20864 19062

    15 – 19 179326 95690 83637 203969 105715 98254 210215 106515 103699

    20 – 24 139060 72318 66742 181767 93686 88081 205978 102904 103074

    25 – 29 117999 59912 58086 141057 75348 65709 184206 97639 86567

    30 – 34 110856 53959 56897 117536 59385 58150 140932 75063 65868

    35 – 39 103502 52538 50964 108981 54678 54303 115583 60149 55434

    40 – 44 90263 45419 44844 98941 47926 51015 104116 49802 54314

    45 – 49 76424 40504 35920 89047 45711 43335 97703 48311 49392

    50 – 54 60182 31452 28730 72463 36998 35464 84763 41870 42893

    55 – 59 47541 26397 21145 58383 32027 26357 70411 37782 32628

    60 – 64 34149 17718 16430 40077 21260 18816 49563 25933 23630

    65 – 69 26438 13796 12642 29018 15242 13775 34452 18478 15975

    70 – 74 18389 9478 8910 21593 10847 10746 24107 12152 11955

    75+ 13124 7425 5699 22638 11971 10667 31402 15851 15552

    TOTAL 1684135 877223 806915 1829485 949917 879566 1962465 1015539 946927

  • 8/19/2019 India Population Strategy

    36/313

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Madhubani

    29

    0 – 14 1478761 770154 708605 1397827 728492 669337 1291387 678515 612870

    6 – 14 904329 467620 436707 863351 445405 417947 783028 410123 372904

    15 – 59 2144444 1093035 1051408 2430580 1233317 1197263 2693297 1356903 1336394

    60+ 246734 123642 123092 296133 147770 148364 355964 176194 179769

    815144 920731 1017903

    0 (< 1 yr) 84854 46584 38270 93584 48544 45040 81680 43464 38215

    1 90567 48571 41996 90274 47502 42773 83410 44165 39245

    2 95209 50207 45002 88222 46876 41346 84713 44706 40007

    3 98849 51508 47341 87259 46609 40650 85647 45107 40540

    4 101556 52491 49065 87215 46641 40574 86270 45387 40883

    5 103397 53173 50224 87922 46915 41007 86639 45563 41076

    6 104440 53569 50871 89210 47372 41839 86812 45654 41158

    7 104755 53697 51058 90912 47952 42960 86846 45679 41167

    8 104408 53572 50835 92857 48599 44258 86799 45656 41143

    9 103468 53212 50256 94878 49253 45625 86730 45604 41125

    10 101966 52625 49340 97070 49949 47121 86536 45502 41034

    11 99932 51820 48112 99530 50723 48807 86117 45326 40791

    12 97622 50852 46770 100761 51047 49714 86324 45298 41026

    13 95179 49754 45425 100065 50677 49388 87535 45519 42016

    14 92559 48519 44040 98068 49833 48235 89329 45885 43444

    15 – 19 414007 218720 195287 460119 236026 224093 463831 232552 231279

    20 – 24 319935 168071 151864 410035 213507 196528 454483 229460 225023

    25 – 29 268870 135225 133645 315536 167041 148495 406444 213492 192951

    30 – 34 251682 119864 131818 260739 128998 131741 305799 159670 146129

    35 – 39 240700 116625 124075 247641 118533 129108 256894 127759 129136

    40 – 44 218110 108027 110083 233608 111315 122292 240446 113119 127327

    45 – 49 181002 95425 85577 206069 105208 100861 221154 108736 112418

    50 – 54 141399 73197 68202 166354 84114 82241 190333 93074 97259

    55 – 59 108737 57881 50857 130479 68576 61903 153915 79042 74873

    60 – 64 87923 43126 44797 100824 50629 50195 121960 60355 61606

    65 – 69 72806 36574 36232 78080 39494 38586 90675 46869 43806

    70 – 74 50576 24437 26140 58030 27280 30750 63368 29898 33469

    75+ 35429 19506 15923 59200 30368 28832 79961 39072 40889

    TOTAL 3869939 1986832 1883105 4124540 2109579 2014963 4340648 2211613 2129033

  • 8/19/2019 India Population Strategy

    37/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Munger

    30

    0 – 14 435478 229017 206464 391547 206027 185523 350200 185819 164383

    6 – 14 278273 145143 133131 247432 128666 118767 216066 114058 102009

    15 – 59 685047 370305 314742 756828 407776 349052 807081 431679 375402

    60+ 77246 39785 37462 84003 43399 40604 94177 48649 45528

    225356 247523 262877

    0 (< 1 yr) 24401 13779 10623 25115 13370 11746 21476 11760 9716

    1 25052 13731 11321 24249 13026 11223 21946 11870 10076

    2 25771 13791 11980 23733 12805 10928 22313 11952 10362

    3 26536 13943 12593 23528 12696 10832 22597 12013 10584

    4 27326 14171 13156 23595 12690 10906 22815 12061 10754

    5 28119 14459 13660 23895 12774 11121 22987 12105 10882

    6 28892 14791 14101 24388 12940 11448 23131 12152 10979

    7 29623 15151 14472 25034 13176 11858 23264 12210 11054

    8 30292 15524 14768 25795 13472 12323 23407 12287 11120

    9 30874 15893 14981 26632 13818 12814 23577 12391 11185

    10 31355 16239 15116 27508 14183 13325 23726 12502 11224

    11 31715 16540 15175 28388 14539 13849 23808 12601 11208

    12 31910 16805 15105 29214 14970 14245 24171 12833 11338

    13 31909 17026 14883 29939 15501 14438 24967 13264 11703

    14 31703 17174 14530 30534 16067 14467 26015 13818 12198

    15 – 19 147741 83413 64328 155164 85252 69912 141698 76223 65476

    20 – 24 104432 61892 42541 132333 77834 54499 143594 82242 61351

    25 – 29 81642 43739 37903 94124 52894 41230 119522 66680 52842

    30 – 34 74740 37433 37307 76066 39504 36562 87335 47740 39595

    35 – 39 73201 35745 37456 72488 34971 37518 73457 36810 36647

    40 – 44 67385 34923 32462 70902 35413 35488 70012 34544 35468

    45 – 49 56318 30048 26270 62988 32558 30429 66177 32958 33219

    50 – 54 45774 24751 21024 52904 27972 24932 59257 30347 28909

    55 – 59 33813 18362 15451 39859 21378 18481 46029 24135 21894

    60 – 64 27124 13424 13700 30556 15478 15078 36185 18066 18118

    65 – 69 22536 11483 11053 23743 12180 11563 26993 14147 12847

    70 – 74 16654 8714 7940 18772 9577 9195 20067 10272 9795

    75+ 10931 6163 4768 10931 6163 4768 10931 6163 4768

    TOTAL 1197771 639107 558668 1232377 657202 575179 1251458 666147 585313

  • 8/19/2019 India Population Strategy

    38/313

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Muzaffarpur

    31

    0 – 14 1532954 803852 729103 1433995 752124 681874 1325769 701012 624758

    6 – 14 935630 487857 447774 870514 452481 418036 787224 415513 371712

    15 – 59 2267394 1173942 1093452 2593557 1336705 1256851 2880023 1471881 1408142

    60+ 271338 139506 131833 329379 168406 160973 398415 201931 196485

    815820 929741 1030860

    0 (< 1 yr) 104092 56254 47838 107964 55719 52245 94944 50057 44887

    1 100784 53933 46851 99508 52366 47142 92344 48865 43479

    2 98735 52348 46387 93373 49857 43515 90141 47820 42321

    3 97759 51404 46355 89300 48110 41191 88332 46929 41403

    4 97671 51004 46667 87031 47037 39994 86911 46197 40714

    5 98283 51052 47231 86305 46554 39751 85873 45631 40242

    6 99410 51452 47958 86864 46576 40288 85215 45236 39979

    7 100865 52107 48759 88449 47018 41431 84931 45019 39912

    8 102464 52921 49543 90800 47795 43005 85017 44985 40032

    9 104019 53797 50222 93657 48821 44837 85469 45142 40327

    10 105621 54726 50895 97018 50027 46992 86081 45362 40719

    11 107360 55697 51663 100879 51343 49537 86649 45518 41131

    12 107668 56183 51485 103702 52606 51096 88170 46281 41889

    13 105806 55916 49890 104716 53703 51013 91040 47922 43118

    14 102417 55058 47359 104429 54592 49837 94652 50048 44605

    15 – 19 454221 253490 200731 509156 276408 232749 510087 271030 239057

    20 – 24 337560 182633 154927 439164 235582 203582 488965 254580 234385

    25 – 29 270851 136828 134022 320595 170435 150160 417725 220352 197373

    30 – 34 258953 124049 134905 269362 134016 135346 317337 166578 150759

    35 – 39 247044 117967 129077 256355 120909 135447 266910 130866 136044

    40 – 44 228938 113946 114992 245960 117798 128162 254058 120138 133920

    45 – 49 193028 99217 93811 221652 110232 111419 238950 114329 124622

    50 – 54 155927 81862 74065 185025 94913 90111 212649 105550 107099

    55 – 59 120872 63950 56921 146288 76412 69875 173341 88458 84883

    60 – 64 96701 49275 47426 111844 58293 53551 135901 69844 66057

    65 – 69 79540 40483 39056 86036 44088 41948 100364 52542 47822

    70 – 74 56016 28362 27654 64825 31973 32851 71107 35195 35912

    75+ 39081 21385 17696 66674 34052 32623 91043 44350 46693

    TOTAL 4071686 2117300 1954388 4356930 2257235 2099698 4604207 2374824 2229384

  • 8/19/2019 India Population Strategy

    39/313District Level Population Projections

    Age 2 0 0 6 2 0 1 1 2 0 1 6

    Group Person Male Female Person Male Female Person Male Female

    2 0 0 6 2 0 1 1 2 0 1 6

    Person Male Female Person Male Female Person Male Female

    Age category &

    Eligible Women

    Estimated EligibleWomen (15-49)

    Nalanda

    32

    0 – 14 903795 470893 432901 809530 421958 387572 703616 369828 333786

    6 – 14 562009 291574 270432 508730 263245 245486 433707 227890 205815

    15 – 59 1373660 713153 660507 1471533 760928 710605 1536860 789553 747307

    60+ 164945 88057 76888 173546 93021 80524 188272 101034 87238

    495758 528742 550381

    0 (< 1 yr) 50275 27612 22663 52864 27422 25442 43336 23107 20229

    1 53675 28690 24986 50752 26612 24139 44188 23327 20861

    2 56503 29641 26862 49485 26154 23330 44874 23547 21327

    3 58797 30466 28331 48956 26001 22955 45423 23766 21656

    4 60596 31167 29430 49058 26105 22954 45863 23986 21878

    5 61940 31743 30197 49685 26419 23266 46225 24205 22020

    6 62866 32196 30670 50728 26896 23832 46537 24426 22111

    7 63415 32527 30888 52080 27489 24591 46828 24646 22182

    8 63625 32736 30889 53635 28151 25485 47128 24868 22260

    9 63535 328