Identifying Predictors for Pertussis Disease in Texas Infants Utilizing Surveillance Records and Birth Certificate Data from 1999-2003
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Using a retrospective case-control design, this study investigated possible risk factors for the development of disease by matching pertussis surveillance data from 1999 to 2003 to birth certificate data. The aim of this study was to identify significant risk factors for the development of pertussis by analyzing infant, maternal, and paternal variables available through birth certificate data. Cases were established through the matching of pertussis disease surveillance to appropriate birth certificate data. A 3:1 control group was created by matching date of birth and pulling birth certificate data for comparison. Multivariate logistic regression statistical techniques were applied in analysis of data. When analysis was completed, 6 out of 16 variables selected for data analysis were found to be significant with adjusted odds ratios greater than the value of 2. The six significant predictors were number of siblings living >5 (OR=3.1, 95% Cl 1.4- 7.2), paternal age <19 (OR=2.9, 95% Cl 1.7-5.1), paternal educational level of >12 and <15 years (OR=2.4, 95% Cl 1.5-3.8), infant birth type of multiple (OR=2.2, 95% Cl 1.1- 4.4), infant birth weight 1500-2499 grams (OR=2.2, 95% Cl 1.3-3.7), and mother’s cigarette use (OR=2.3, 95% Cl 1.3-3.5). Overall, this study showed evidence that the odds of pertussis infection in infants increased as number of siblings increased. Infants with five or more siblings were over three times as likely to develop pertussis than infants without siblings. Younger paternal age and mother’s cigarette use also demonstrated increased odds for infants to develop pertussis infection. The elevated risk effect for all six significant predictors is large enough that further study is warranted to investigate the effect of these variables on pertussis development in infants.
CitationPalenapa, L. L. (2008). Identifying predictors for pertussis disease in Texas infants utilizing surveillance records and birth certificate data from 1999-2003 (Unpublished thesis). Texas State University-San Marcos, San Marcos, Texas.
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