Abstract Background This research concerns Araucanía, often called the Ninth Region, the poorest region of Chile where inequalities are most extreme. Araucanía hasn't enjoyed the economic success Chile achieved when the country returned to democracy in 1990. The Ninth Region also has the largest ethnic Mapuche population, located in rural areas and attached to small agricultural properties. Written and oral histories of diseases have been the most frequently used methods to explore the links between an ancestral population's perception of health conditions and their deprived environments. With census data and hospital records, it is now possible to incorporate statistical data about the links between poverty and disease among ethnic communities and compare results with non-Mapuche population. Data sources Hospital discharge records from Health Services North N = 24,126 patients, year 2003, and 7 hospitals), Health Services South (N = 81,780 patients and 25 hospitals); CAS-2/Family records (N = 527,539 individuals, 439 neighborhoods, 32 Comunas). Methods Given the over-dispersion of data and the clustered nature of observations, we used the global Moran's I and General G Gettis-Ord procedures to test spatial dependence. These tests confirmed the clusters of disease and the need to use spatial regression within a General Linear Mixed Model perspective. Results Health outcomes indicate significantly higher morbidity rates for the Mapuche compared to non-Mapuche in both age groups < 5 and 15–44, respectively; for the groups 70–79 and 80 + years of age, this trend is reversed. Mortality rates, however, are higher among Mapuches than non-Mapuches for the entire Ninth Region and for all age groups. Mortality caused by respiratory infections is higher among Mapuches than non-Mapuches in all age-groups. A major finding is the link between poverty and respiratory infections. Conclusion Poverty is significantly associated with respiratory infections in the population of Chile's Ninth Region. High deprivation areas are associated with poverty, and poverty is a predictor of respiratory infections. Mapuches are at higher risk of deaths caused by respiratory infections in all age groups. Exponential and spherical spatial correlation models were tested to estimate the previous association and were compared with non-spatial Poisson, concluding that significant spatial variability was present in the data.