The human population of Indian Himalaya is 3,04,68,612, which is the highest among all mountain regions of the world. Although population growth is a global phenomenon, there are extreme variations in the distribution of the population in mountain region. This variation depends upon several factors like economic, political, geographic constraints. Demographers frequently use development status as the dependent variable to analyse the population growth rates. Such analyses indicate that population growth rates in underdeveloped regions tend to be higher than those in developed regions. Geographers classify regions and subregions according to geographical factors like soil, rainfall, mountains, river basins etc. Economists have also attempted classification of regions on the basis of economic criteria though owing to data constraints the work has not been fully elaborated. In the Indian context, the Swaminathan Committee has suggested that a district is the most appropriate administrative unit for compiling socio-demographic information. In view of the introduction of Panchayati Raj under the 73rd amendment of the constitution decentralisation will call for district level data for a large number of variables. For formulating plans and policies, as well as implementing, monitoring, and evaluation of development programmes, a district is the most meaningful unit, and therefore, districtwise data are absolutely essential.

The Himalayan region in India is spread over 12 states covering a geographical area of over 5 lakh km². We have taken a district as the smallest unit for the present study. All the tables presented in this volume are based on or derived from the data available in 1981 and 1991 census handbooks of India. Our objective is to present the information in a simplified format which would make comparisons easy. Finally, in order to understand the policy implications of the demographic scene, an overall assessment of population situation at the state and district lavel was made.

In the first part of this volume state lavel data for 12 administrative regions is presented. This includes different demographic parameters like population density, decal growth rate, sex ratio, SC/ST population, human settlement, urbanisation, and economic status etc. Out of 12 administrative regions in Indian Himalaya, 9 are full-fledged states (viz. Arunachal Pradesh, Himachal Pradesh, Jammu & Kashmir, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, and Tripura) and the remaining 3 (viz. hill regions of Assam, Uttar Pradesh, and West Bengal) form part of larger administrative units. While comparing the inter-state data this was the main constraint, apart from the non availability of information for Jammu & Kashmir.

The second part of the volume presents district level data in each state. The demographic parameters of all districts are compared with the respective parameters of the state and as well as with the entire Indian Himalayan region. While comparing data of 1981 and 1991 for India, it is important to note that the census enumeration did not take place in Assam in 1981 and in Jammu & Kashmir in 1991 because of disturbances. The figures for these two states for these years are based on estimates and may not convey an accurate picture.

The third part presents data on all 78 districts of Indian Himalaya in tabular form which are ranked according to different demographic parameters. The district boundaries used in the map are based on the Survey of India (SOI) maps. The attribute data (demographic data) were linked with the spatial database through a GIS (ARC VIEW) software to present the district database. The scale of maps is 1:7,000,000.

In the final part result of some statistical analyses are given. As more than 80% population of the region lives in the rural area, the female literacy rate in rural area was taken as an important index of development. On the basis of this index, the decadal growth rate was compared. The scatter diagrams present the available district level data (62 out of 78). The Standard Errors (SE) were calculated from deviation of actual value with the estimated one using the regression line equation at n-2 degree of freedom (where n is the size of population i.e. 62). As regards, the fact of larger deviation of the points represented by the districts scattered along with the regression line, the estimated value of the respective parameters +1 SE were considered as the confidence limits. Those particular districts were marked, which have major deviation (>estimated value +1SE and <estimated value -1SE) from the regression line drawn on Indian Himalaya as a whole. Inspite of larger dispersion for some districts, it could be predicted that about 75% of the districts will fall within the estimated value + 1 SE in the next century too. In addition to these indicators, the literacy also influences the working population of the region which comprise only about 40% of the total population. The number of non-workers has a direct relationship with the literacy rate, indicating more non-worker population in districts with high literacy, as compared to others. Finally the population scenario for 2001 is presented. The decadal growth rate and population density of last few decades were taken into consideration for projecting this. The highly dispersed districts were identified, where the projected figure may significantly deviate from the actual values.