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Lucille Palenapa IDEW Presentation Fri, Jun 27, 2008

Identifying Predictors for Pertussis Disease in Texas Infants Utilizing Surveillance and Birth Certificate Data from 1999-2003. Lucille Palenapa IDEW Presentation Fri, Jun 27, 2008. Overview. Review project Objective Methodology Results Recommendations Q&A. Pertussis Challenges.

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Lucille Palenapa IDEW Presentation Fri, Jun 27, 2008

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  1. Identifying Predictors for Pertussis Disease in Texas Infants Utilizing Surveillance and Birth Certificate Data from 1999-2003 Lucille Palenapa IDEW Presentation Fri, Jun 27, 2008

  2. Overview • Review project • Objective • Methodology • Results • Recommendations • Q&A

  3. Pertussis Challenges • Difficult to diagnose & distinguish • Often ruled out based on vaccine history • Lab results often not reliable • Difficult to obtain sterile sample **Need to facilitate earlier identification of disease • Establish risk factors for pertussis disease

  4. Texas Birth Certificate Data • Utilized in past research to assess risk factors for infectious diseases • Comprehensive source of infant, maternal and paternal characteristic data

  5. Objective • Identify significant risk factors for pertussis disease in infants <12 months of age in Texas utilizing surveillance and birth certificate data from 1999-2003

  6. Methodology • Case-infant defined: • Infant reported to DSHS as a confirmed or probable pertussis case • <12 months at onset • Born in Texas from 1999-2003 • Control-infant defined: • Randomly selected by same date of birth as case-infant • Not reported as pertussis case to DSHS • Born in Texas from 1999-2003

  7. Exclusion criteria • Infants who were: • Ruled out or lost to follow-up • Not born in Texas • >12 months at disease onset • > 1 case of pertussis in 5-year study (counted only once)

  8. Methodology • Retrospective case-control study • 5 year data (1999-2003) • DSHS pertussis surveillance data • Control group • Texas birth certificate data • DSHS IRB submission

  9. Methodology (Data Collection) • After IRB approval, collected: • Surveillance Data: • Identified infants reported to DSHS as (confirmed and probable) pertussis cases who were <12 months at onset for each respective year (1999-2003) • Birth certificate data: • Received large birth data files (avg 300-365K records w/ avg 200 fields /year)

  10. Methodology (cont.) • SAS Statistical Software Utilized: • Recode and reformat birth certificate data into readable format • Match cases to birth certificate data: • Matched on name and date of birth • Quality assurance done by hand to ensure match of surveillance case to birth data • 451 cases • 3 controls randomly selected for each case based on same date of birth • 1353 controls

  11. Methodology (cont.) • 15 variables initially chosen for analysis • 2 variables (birth length & medicaid participation) eliminated because data completeness <50% • Variables chosen based on indications of biological feasibility and on previous epidemiological studies

  12. Table 1. Variables Selected for Analysis from Texas Birth Certificate Variable % missing Selected (Yes/No) (Infant Charac.) Birth length 51.2 No Birth sequence 0.0 Yes Birth type 0.0 Yes Birth weight 0.1 Yes Gestational age 1.9 Yes No. siblings living 0.3 Yes Sex 0.0 Yes

  13. Table 1. Variables Selected for Analysis from Texas Birth Certificate (cont.) Variable % missing Selected (Yes/No) (Maternal Charac.) Age 0.0 Yes Alcohol Use 0.1 Yes Education 2.2 Yes Hispanic Origin 0.4 Yes Marital Status 0.2 Yes Medicaid 64.9 No Prenatal Care 4.9 Yes Tobacco Use 0.7 Yes

  14. Analysis • Descriptive statistics • Multivariate logistic regression model: • Reducing confounders: • 10% odds ratio analyses, removal of variables not causing at least 10% change in OR

  15. Results

  16. Table 2. Mean Values of Continuous Variables Describing Infant and Maternal Characteristics by Case Status Variable Case Control n=451 n=1353 Infant Charac. Birth weight (gms) 3182.6 3306.7 Gestational age (wks) 40.1 39.4 No. siblings living 1.5 2.1 Maternal Charac. Age (yrs) 24.8 26.4 Education (yrs) 13.7 14.1

  17. Table 3. Distribution of Categorical Variables Describing Maternal Characteristics by Case Status Variable Case Control n=451 n=1353 Does mother use alcohol? Yes 5 (1.1) 8 (0.6) No 445 (98.9) 1334 (99.4) Education >12 yrs 188 (42.7) 414 (31.3) <12 252 (57.2) 911 (68.8) Is mother of Hispanic origin? Yes 242 (54.0) 640 (47.4) No 206 (45.9) 709 (52.6) Maternal Status (Mother married?) Yes 277 (61.4) 932 (69.0) No 174 (38.6) 418 (30.9)

  18. Table 3. Distribution of Categorical Variables Describing Maternal Characteristics by Case Status (cont.) Variable Case Control n=451 n=1353 Number of prenatal visits >1 420 (97.9) 1264 (98.2) 0 9 (2.1) 23 (1.8) Mother’s Race White* 399 (88.5) 1160 (85.8) Black 41 (9.1) 146 (10.8) Native-American 1 (0.2) 1 (0.1) Asian 9 (2.0) 39 (2.9) Pacific Islander 0 (0.0) 4 (0.3) Unknown 1 (0.2) 3 (0.2) Does mother smoke cigarettes? Yes 42 (9.3) 70 (5.2) No 408 (90.7) 1271 (94.8)

  19. Table 4. Crude Odds Ratios and 95% Confidence Intervals for Infant Pertussis According to Maternal Characteristics Variable Case Control Effect n=451 n=1353 OR (95% CI) Maternal age (yrs) <19 103 178 2.3 (1.6-3.1) 20-29 238 749 1.2 (0.9-1.6) 30-39 103 401 Referent >40 7 25 1.1 (0.5-2.6) Maternal education (yrs) <8 48 125 2.1 (1.3-3.3) >8 and <12 280 698 2.2 (1.6-3.0) >12 and <15 60 219 1.5 (0.9-2.2) >16 52 283 Referent Is mother of Hispanic origin? Yes 242 640 1.3 (1.1-1.6) No 206 709 Referent

  20. Table 4. Crude Odds Ratios and 95% Confidence Intervals for Infant Pertussis According to Maternal Characteristics (cont.) Variable Case Control Effect n=451 n=1353 OR (95% CI) Mother married Yes 277 932 Referent No 174 418 1.4 (1.1-1.7) Does mother smoke cigarettes? Yes 42 70 1.9 (1.3-2.8) No 408 1341 Referent

  21. Table 5. Crude Odds Ratios and 95% Confidence Intervals for Infant Characteristics Variable Case Control Effect n=451 n=1353 OR (95% CI) Infant birth sequence 1st 426 1320 Referent >2nd 25 33 2.3 (1.4-4.0) Infant birth type Single 426 1320 Referent Multiple 25 33 2.4 (1.4-4.0) Infant birth weight (gms) <1499 8 22 1.2 (0.5-2.7) 1500-2499 50 61 2.7 (1.8-3.9) >2500 393 1270 Referent

  22. Table 5. Crude Odds Ratios and 95% Confidence Intervals for Infant Characteristics (cont.) Variable Case Control Effect n=451 n=1353 OR (95% CI) Infant gestational age (wks) <37 110 245 1.5 (1.2-1.9) >38 327 1087 Referent Infant sex Male 218 710 Referent Female 233 643 1.2 (0.9-1.9) No. of siblings living 0 146 526 Referent 1-4 290 787 1.3 (1.1-1.7) >5 14 23 2.2 (1.4-4.4)

  23. Final Data Analyses • Multivariate logistic regression: • 6 variables selected as significant predictors of pertussis disease • 10% adjusted odds ratio: • No variable eliminated • 6 variables still remained

  24. Table 6. Crude Odds and Adjusted Ratios and 95% Confidence Intervals of Significant Predictors for Pertussis Variable Case Control Effect Adj. Effect n=451 n=1353 OR (95% CI) OR (95% CI) Infant birth type Single 422 1290 Referent Referent Multiple 25 33 2.4 (1.4-4.0) 1.9 (1.0-3.4) Infant birth weight <1499 8 20 1.2 (0.5-2.7) 1.4 (0.6-3.4) 1500-2499 48 60 2.7 (1.8-3.9) 2.1 (1.4-3.3) >2500 391 1243 Referent Referent No. of siblings living 0 144 520 Referent Referent 1-4 289 780 1.3 (1.1-1.7) 1.8 (1.4-2.3) >5 14 23 2.2 (1.4-4.4) 3.1 (1.5-6.5)

  25. Table 6. Crude Odds and Adjusted Ratios and 95% Confidence Intervals of Significant Predictors for Pertussis (cont.) Variable Case Control Effect Adj. Effect n=451 n=1353 OR (95% CI) OR (95% CI) Maternal cigarette use Yes 42 70 1.9 (1.3-2.8) 2.1 (1.3-3.5) No 405 1253 Referent Referent Maternal age <19 101 175 2.3 (1.6-3.1) 3.0 (2.1-4.4) 20-29 237 734 1.2 (0.9-1.6) 1.3 (1.0-1.7) 30-39 102 390 Referent Referent >40 7 24 1.1 (0.5-2.6) 1.0 (0.4-2.5) Maternal Hispanic Origin Yes 242 628 1.3 (1.1-1.6) 1.3 (1.0-1.5) No 205 695 Referent Referent

  26. Significant Predictor Variables Variable Adj. OR (95% CI) -Number of siblings >5 3.1 (1.5-6.5) -Maternal age <19 yrs 3.0 (2.1-4.4) -Infant low birth weight (1500-2499 gms) 2.1 (1.4-3.3) -Maternal cigarette use (Yes) 2.1 (1.3-3.5)

  27. Discussion & Recommendations

  28. Number of siblings living • No current literature w/ exact findings • Similar findings: • As no. of older siblings increased, delay in immunization increased for household infants and younger siblings (Reading, Surridge, & Adamson, 2004) • Infants from larger household size less likely to be fully immunized, more likely to have delayed immunization (Li & Taylor, 1993; Peckham, Bedford, Senturia, & Ades, 1989) • Later born siblings more likely to have delayed immunization than firstborn children (Higgins, 1990; Kaplan, Macie-Taylor, & Boldsen, 1992; Schaffer & Szilagyi, 1995) • Later born children more prone to infectious disease (Kaplan, 1990)

  29. Significant Maternal Variables • Maternal Age • Similar findings for young maternal age (Izurieta et al., 1996) • Adolescent aged mothers found to have significantly lower levels of antibodies for pertussis than older mothers (Gonik, 2005 & Healy, 2006)

  30. Significant Infant Predictors • Low birth weight (LBW) infant • Biologically feasible • Similar findings, LBW infants more likely to develop pertussis than normal birth weight infants (Langkamp & Davis, 1996)

  31. Maternal Cigarette Use • Similar findings established: • Maternal smoking increases the likelihood of respiratory infections in infants (Ahmer et al., 1999; Ahmer, et al., 1998; Geng, Savage, Razani-Boroujerdi & Sopori, 1996; Saadi, et al., 1996; Stocks & Dezateux, 2003) • Smoking during pregnancy assoc w/ several adverse outcomes: • Premature delivery • Spontaneous abortion • Growth restriction • Increased risk of SIDS

  32. Limitations of Study • Difficult to gauge the effects of many covariates with the statistical procedures used • Problem of multiple comparisons present, acceptance criterion may have been satisfied purely by chance • Use of birth certificate data to predict health outcomes has had mixed reviews • Method for reporting disease

  33. Recommendations • Increase awareness and knowledge of serious dangers of pertussis • Specially targeted education campaigns should include a focus on: • Infant households with large number of siblings • Teen mothers • Low birth weight infants • Pregnant mothers and mothers with infants who smoke

  34. Recommendations (cont.) • “Cocooning” strategy • “Immunization of family members and close contacts of the newborn” • Post-partum • Keep infants up-to-date on vaccinations • Tdap booster vaccine for adolescents and adults

  35. Benefits of Study • Aid clinicians by establishing risk factors to facilitate earlier recognition of disease and earlier consequent prophylaxis treatment of patient and close contacts • Reduce health care costs associated with pertussis • Reduce lost productivity

  36. Benefits of Study (cont.) • Protect those most vulnerable, the future of Texas…

  37. Study Contributors • Rita Espinoza • Marilyn Felkner • Richard Taylor • Eric Miller THANK YOU! Lucille Palenapa (512) 458-7111 x.6611 lucille.palenapa@dshs.state.tx.us

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