Introduction 21 3 21 3 21 1 3 4 21 16 15 Materials and methods Study design 13 20 Case definition and control selection N N N 5 10 12 15 Statistical analysis and data definitions Descriptive statistics of the characteristics of the patients were performed and reported in terms of mean and standard deviation (SD) for the quantitative variables (chronological age, birth weight, gestational age, etc.) and in terms of absolute frequencies and percentages for the qualitative variables. Firstly, a bivariate analysis was performed and the comparison of quantitative variables between two groups of subjects (i.e. cases vs controls) was made calculating the likelihood ratio test (LR test), and reporting the bivariate odds ratio (OR) and 95% confidence interval (CI). Comparison of frequency data was performed by the chi-square test or by the Fisher’s exact test in case of expected frequencies less than five. P Results Patient populations There were 145 case-patients included in the study (plus three cases not evaluated because of missing values). There were 61 males (42.1%) and 84 females (57.9%), with a median age of 3.5 months and a median birth weight of 3,050 grams. Seventeen of the 145 (11.7%) were born preterm (at less than 36 weeks of gestational age), two had congenital heart conditions and five had a previous history of chronic lung disease. P Risk factors associated with a higher likelihood to acquire RSV-induced LRTI, severe enough to lead to hospital admission In the bivariate analysis we considered several risk factors that could be associated with a higher likelihood to acquire RSV-induced LRTI, severe enough to lead to hospital admission. 1 n n P  Table 1 Distribution of risk factors associated with a higher likelihood to acquire RSV-induced LRTI, severe enough to lead to hospital admission   N  N N   N P OR (95%CI) Epidemic season  2003–2004 29 (20.0%) 56 (19.2%)  Reference  2002–2003 50 (34.5%) 68 (23.3%)  1.42 (0.80–2.53)  2001–2002 41 (28.3%) 122 (41.8%)  0.65 (0.37–1–15)  2000–2001 25 (17.2%) 46 (15.7%) P 1.05 (0.54–2.03) Epidemic period (October to April): Yes 137 (94.6%) 247 (84.6%) P 3.12 (1.43–6.81) Sex: Female 84 (57.9%) 168 (57.5%) P 1.02 (0.68–1.52) N 74 (51.7%) 165 (57.1%) P 0.81 (0.54–1.21) N 50 (44.6%) 75 (33.9%) P 1.57 (0.99–2.50) N 97 (72.9%) 155 (59.6%) P 1.83 (1.16–2.88) Chronological age at the beginning of RSV season  ≥12 months 6 (4.1%) 48 (16.4%) P Reference  6–11 months 31 (21.4%) 98 (33.6%)  2.53 (0.99–6.48)  3–5 months 48 (33.1%) 85 (29.1%)  4.52 (1.80–11.33)  <3 months 60 (41.4%) 61 (20.9%)  7.87 (3.13–19.75)  N 95 (69.3%) 151 (53.4%) P 1.98 (1.28–3.05) N  ≥2500 grams 113 (80.1%) 259 (92.2%) P a Reference  1500–2499 grams 24 (17.0%) 28 (7.2%)  1.96 (1.09–3.54)  <1500 grams 4 (2.8%) 2 (0.6%)  4.58 (0.83–25.39) N  ≥36 weeks 126 (88.1%) 269 (93.7%) P a Reference  33–35 weeks 8 (5.6%) 14 (4.9%)  1.22 (0.50–2.98)  <33 weeks 9 (6.3%) 4 (1.4%)  5.35 (1.45–15.89) N 36 (25.7%) 63 (22.0%) P 1.23 (0.76–1.96) N  None or <3 months 25 (71.4%) 68 (66.0%) P a Reference  3–6 months 9 (25.7%) 20 (19.4%)  1.22 (0.49–3.04)  ≥7 months 1 (2.9%) 15 (14.6%)  0.18 (0.02–1.44) N 138 (97.9%) 265 (78.0%) P 4.17 (1.23–14.08) N 126 (88.7%) 230 (81.0%) P 1.85 (1.02–3.36) P a 1 2 Table 2 N Explanatory variables   aOR 95% CI P a Chronological age at the beginning of RSV season  (reference category: ≥12 months) 6–11 months 2.467 0.879–6.925 P 3–5 months 4.153 1.506–11.451  <3 months 8.462 3.088–23.185  Birth weight category (reference category: ≥2,500 grams) 1,500–2,499 grams 2.433 1.289–4.595 P <1,500 grams 7.701 1.292–45.907  Birth order (reference category: first) ≥ second 1.924 1.210–3.058 P a The area under the ROC curve of the model was 0.712 Discussion Evaluating data collected over four consecutive years in Italy, we found that, in addition to the severity of the RSV epidemics in a specific year, a variety of risk factors were associated with a higher likelihood to acquire RSV-induced LRTI, severe enough to lead to hospital admission. The only condition related to demographic and social characteristics of the family was the number of children in the family (being at least the second baby was a “risk-factor”). Among factors related to the characteristics of the children, major predictors were chronological age of the child at the onset of RSV season, birth weight and gestational age category, birth order, daycare attendance and previous episodes of RSV infections. However, in the logistic regression analysis, only three predictors turned out to be significant: chronological age at the beginning of RSV season, birth weight category, and birth order. 1 2 8 11 14 17 1 10 17 19 6 3 5 7 10 14 22 1 21 3 5 10 21 In the present study, gestational age, a strong risk factor in the bivariate analysis, was not included in the logistic model because of the strong autocorrelation with birth weight. Indeed, a great proportion of children belonging to two lower gestational age categories (<33 weeks and 33–35 weeks) had a birth weight <2,500 grams. 10 1 3 5 7 10 18 19 21 1 3 5 7 10 18 19 21 1 3 5 7 10 18 19 21 5 Due to the low number of children with specific characteristics, other risk factors such as presence of chronic lung diseases or of congenital heart diseases, immunodeficiency, haematological malignancies, bone-marrow or organ transplants, and cystic fibrosis were not analysed. Moreover, since only in the second, third and fourth RSV season a limited number of children had received immunoprophylaxis with palivizumab, its protective effect could not be evaluated. In summary, evaluating four RSV seasons, characterized by inter-annual alternation of minor and major epidemics, we found, in addition to prematurity, a limited number of other conditions which appear to influence the severity of RSV-induced LTRI in infants and young children. However, before translating to clinical practice these indications, other similar studies performed in different countries are required, including a broader number of children and covering other RSV epidemic seasons. This information should be valuable to better determine hospital resource management and individualize RSV prophylaxis programs in preterm and term infants.