Background: National Health Surveys have been part of national health services in many countries, but their data are summary com- pilations and commonly used only for describing trends in health and living conditions. Aim: Tostatisticallydisclosenetworksofinteractingvariableswithin National Health Survey data. Sample and methods: We used anthropometric, educational, environ- mental and economic information of people of Sikkim, West Bengal, Telangana, and Gujarat, India, obtained by the Fifth Indian National Family Health Survey (NFHS-5).We applied a new statistical approach labeled as “St. Nicholas House Analysis” (SNHA). SNHA ranks absolute bivariate correlation coef- ficients in descending order according to magnitude. The method creates hierarchic “association chains” of correlation coefficients de- fined by sequences where reversing the start and end point does not alter the ordering of elements. Association chains characterize de- pendence structures within networks of extensively interacting variables. Results: SNHA disclosed fundamental differences in the network of anthropometric, educational, environmental and economic variables of the people of Sikkim, and the people of West Ben- gal, Telangana and Gujarat. Whereas relevant interactions among these variables were largely absent in the people of Sikkim, the variables formed characteristic star-shaped networks with wealth quintile and the possession of motorcycles in a strong central position, in the people of West Bengal, Telangana and Gujarat. Conclusion: Depicting association chains within net- works of extensively interacting variables such as health survey data appears to be a promising statisti- cal tool for disentangling the effects of environmen- tal circumstances, education, and social, economic, political and emotional (SEPE) factors on human growth.