This study is an attempt to identify the determinant factors of quality of life in Dimapur and its periphery. Dimapur town is the most important and cosmopolitan commercial centre of Nagaland, India. We delineate the township into five concentric rings around the CBD and every ring into several sectors. Then twenty one sites have been chosen randomly from these sectors; four each from the first and the second sectors, five each from the third and the fourth sectors, and three from the fifth sector (control). From each site, we have selected eleven households randomly to collect information on the scheduled variables - 113 in number - reflecting various aspects of quality of life (e.g. education, housing, utilities and amenities, accessibility, waste disposal and environment, income & expenditure, entertainment, health condition, etc.). In total, we have surveyed two hundred thirty one (231) households. Factor analysis is used for resolving the multivariate complex of data into a handful of composite variables identified as: (1) High-End Consumption, (2) Low-End Consumption; (3) Consumption of Public Goods, Commons and Negative Spillovers, (4) Supplementary Consumption, and (5) Health-related Attributes. A regression analysis of spatial distribution of mean factor scores over the sectors of the township reveals that mean scores of factors #1, #2, and #4 (that are closely related with standard of living) are lower in the CBD and rise as we move away to sectors #2 and #3. They attain their peak in sector #3 and after that the experience a decline as we move away further to sectors #4 and #5. On the other hand, factor #3, monotonically decreases as we move away from the central business district (CBD) to the periphery. The CBD is more crowded and polluted. It caters to the largest floating population who over-use the public facilities there. Factor #5 (related with poor health conditions) scores higher in the CBD and as we move away to sectors # 3 and #4, a decline is observed. Health conditions are poorer in the CBD and better in sectors #3 and #4. But due to poor conditions of living, health in the rural areas scores poorer. We conclude that standard of living and consumption of public goods/services including negative spillover determine quality of life. The QOL in the medial sector between the CBD and the periphery is better than that in other sectors mainly due to higher standard of living but QOL due to consumption of public goods/externalities monotonically improves as we move away from the CBD. The overall index of quality of life has a weak relationship with the nature of employment of the respondents. The advance Nagas (Semas, Angamis, Aos and Lothas) score favourably on the Factors of QOL relating to the standard of living, but they also share the negative spillovers of urban living more in proportion. Zeliangs and Kukis score unfavourably on the standard of living but they share the urban externalities and negative spillover of urban living lesser in proportion.