OBJECTIVE: The objective of this study was to examine the relation of factors that are present at birth to subsequent hospitalization for childhood pneumococcal disease. METHODS: We conducted a cohort study of all singletons born in 3 counties in western Denmark from 1980 through 2001, using population-based registries to obtain data on pregnancy- and birth-related variables and hospitalizations through age 12. We calculated incidence rates of pneumococcal disease hospitalization overall and within strata of study variables and used Poisson regression to estimate rate ratios for pneumococcal disease hospitalization while accounting for other birth characteristics. RESULTS: Among 338,504 eligible births, 1052 children were later hospitalized for pneumococcal disease. Pneumonia accounted for most hospitalizations (81.9%). The pneumococcal disease hospitalization rate was highest among 7- to 24-month-olds, followed by 0- to 6-month-olds and 25- to 60-month-olds. The highest rates, typically over 200 hospitalizations per 100,000 person-years, were in 0- to 6- and 7- to 24-month-old children who were born preterm or with low birth weight, a low 5-minute Apgar score, or birth defects. The hospitalization rate was lower for first-born children at 0 to 6 months but not at older ages. At older ages, hospitalization rates were not substantially different for children whose mothers smoked during pregnancy, but at 0 to 6 months, the rate was higher for children of multiparous nonsmokers than for others. Adjusted rate ratios were elevated across all age categories for several variables, including low birth weight, presence of birth defects, and low 5-minute Apgar. For several others, including preterm birth, maternal multiparity, age < or = 20 years, and non-Danish/European Union citizenship, adjusted rate ratios were elevated only for 0- to 6-month-olds. CONCLUSIONS: This large cohort study of hospitalization for childhood pneumococcal disease clarifies the roles of some gestation and birth factors while raising new questions about how these factors work.
OBJECTIVE: The objective of this study was to examine the relation of factors that are present at birth to subsequent hospitalization for childhood pneumococcal disease. METHODS: We conducted a cohort study of all singletons born in 3 counties in western Denmark from 1980 through 2001, using population-based registries to obtain data on pregnancy- and birth-related variables and hospitalizations through age 12. We calculated incidence rates of pneumococcal disease hospitalization overall and within strata of study variables and used Poisson regression to estimate rate ratios for pneumococcal disease hospitalization while accounting for other birth characteristics. RESULTS: Among 338,504 eligible births, 1052 children were later hospitalized for pneumococcal disease. Pneumonia accounted for most hospitalizations (81.9%). The pneumococcal disease hospitalization rate was highest among 7- to 24-month-olds, followed by 0- to 6-month-olds and 25- to 60-month-olds. The highest rates, typically over 200 hospitalizations per 100,000 person-years, were in 0- to 6- and 7- to 24-month-old children who were born preterm or with low birth weight, a low 5-minute Apgar score, or birth defects. The hospitalization rate was lower for first-born children at 0 to 6 months but not at older ages. At older ages, hospitalization rates were not substantially different for children whose mothers smoked during pregnancy, but at 0 to 6 months, the rate was higher for children of multiparous nonsmokers than for others. Adjusted rate ratios were elevated across all age categories for several variables, including low birth weight, presence of birth defects, and low 5-minute Apgar. For several others, including preterm birth, maternal multiparity, age < or = 20 years, and non-Danish/European Union citizenship, adjusted rate ratios were elevated only for 0- to 6-month-olds. CONCLUSIONS: This large cohort study of hospitalization for childhood pneumococcal disease clarifies the roles of some gestation and birth factors while raising new questions about how these factors work.
Authors: Ana M B Menezes; Ricardo B Noal; Juraci A Cesar; Pedro C Hallal; Cora Luiza Araújo; Samuel C Dumith; Fernando C Barros; Cesar G Victora Journal: Cad Saude Publica Date: 2010-10 Impact factor: 1.632
Authors: Kimberly M Shea; Timothy L Lash; Sussie Antonsen; Susan S Jick; Henrik T Sørensen Journal: Clin Epidemiol Date: 2015-07-15 Impact factor: 4.790
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