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Background: Assessing exposure to infections in early childhood is of interest in many epidemiological investigations. Because exposure to infections is difficult to measure directly, epidemiological studies have used surrogate measures available from routine data such as birth order and population density. However, the association between population density and exposure to infections is unclear. We assessed whether neighbourhood child population density is associated with respiratory infections in infants. Methods: With the Basel-Bern lung infant development study (BILD), a prospective Swiss cohort study of healthy neonates, respiratory symptoms and infections were assessed by weekly telephone interviews with the mother throughout the first year of life. Using population census data, we calculated neighbourhood child density as the number of children < 16 years of age living within a 250 m radius around the residence of each child. We used negative binomial regression models to assess associations between neighbourhood child density and the number of weeks with respiratory infections and adjusted for potential confounders including the number of older siblings, day-care attendance and duration of breastfeeding. We investigated possible interactions between neighbourhood child population density and older siblings assuming that older siblings mix with other children in the neighbourhood. Results: The analyses included 487 infants. We found no evidence of an association between quintiles of neighbourhood child density and number of respiratory symptoms (p = 0.59, incidence rate ratios comparing highest to lowest quintile: 1.15, 95%-confidence interval: 0.90–1.47). There was no evidence of interaction with older siblings (p = 0.44). Results were similar in crude and in fully adjusted models. Conclusions: Our study suggests that in Switzerland neighbourhood child density is a poor proxy for exposure to infections in infancy. [ABSTRACT FROM AUTHOR]

Background: Many studies have observed space-time clustering of childhood leukemia (CL) yet few have attempted to elicit etiological clues from such clustering. We recently reported space-time clustering of CL around birth, and now aim to generate etiological hypotheses by comparing clustered and nonclustered cases. We also investigated whether the clustering resulted from many small aggregations of cases or from a few larger clusters. Methods: We identified cases of persons born and diagnosed between 1985 and 2014 at age 0–15 years from the Swiss Childhood Cancer Registry. We determined spatial and temporal lags that maximized evidence of clustering based on the Knox test and classified cases born within these lags from another case as clustered. Using logistic regression adjusted for child population density, we determined whether clustering status was associated with age at diagnosis, immunophenotype, cytogenetic subtype, perinatal and socioeconomic characteristics, and pollution sources. Results: Analyses included 1,282 cases of which 242 were clustered (born within 1 km and 2 years from another case). Of all investigated characteristics only the t(12;21)(p13;q22) translocation (resulting in ETV6-RUNX1 fusion) differed significantly in prevalence between clustered and nonclustered cases (40% and 25%, respectively; adjusted OR 2.54 [1.52–4.23]; p = 0.003). Spatio-temporal clustering was driven by an excess of aggregations of two or three children rather than by a few large clusters. Conclusion: Our findings suggest ETV6-RUNX1 is associated with space-time clustering of CL and are consistent with an infection interacting with that oncogene in early life leading to clinical leukemia. [ABSTRACT FROM AUTHOR]