1. A Threshold Effect in the Relation of Stressful Life Events and Preterm Delivery Nedra Whitehead, Ph.D.

2. Background

3. §Biological studies l Suggest stress may affect the timing of delivery through Premature hormonal stimulation of labor; or Immunosupression resulting in increased risk of chorioamnionitis §Epidemiological studies l have been inconsistent Different measures of stress related to preterm delivery in different studies Some studies find no relationship

4. A possible reason for inconsistent results: the specified model is not correct §Two types of models have been tested: l Discrete model (Model A in figure) Women are dichotomized as stressed or not- stressed. Average risk is the same among all stressed women. l Logistic model (Model B in figure) Each additional unit of stress causes a linear increase in the log-odds of the outcome

5. A possible model which has not been tested: §Threshold model (Model C in figure) l Stress does not cause poor pregnancy outcome until a certain level is reached. l Above the threshold, each unit of stress causes a linear increase in the log odds of the outcome

6. Models of Relationship between Stress and Pregnancy Outcome Stress Level No threshold (A) Threshold (C) Discrete exposure (B)

7. Methods §Data were collected by the Pregnancy Risk Assessment Monitoring System (PRAMS) §Method described by Ulm 1 was used to estimate and test for a threshold effect 1 Ulm K. A statistical method for assessing a threshold in epidemiological studies. Stat Med 1991;10:341-9.

8. PRAMS Pregnancy Risk Assessment Monitoring System §What is PRAMS? l Ongoing state population-based surveillance system l Study population: women who recently delivered a live-born infant l Maternal attitudes, behaviors, and experiences during pregnancy and early infancy l Core and state-specific items

9. PRAMS Sampling and Data Collection Methods §Sampling frame: state birth certificate files §High-risk women are oversampled §States annual sample size: 1600-3000 §Data collected 2-6 months after delivery §Uses Dillman’s 2 Total Design Method l Questionnaire mailed 2-3 times l Mail non-responders interviewed by telephone 2 Dillman DA. Mail and telephone surveys: the total design method. 1st ed. New York, NY: John Wiley & Sons, Inc., 1978

10. States and Response Rates StateYears of DataNo. RespondentsResponse Rate Alabama1992 - 19955,64674.9 Alaska1990 - 199510,14273.2 Florida1993 - 19956,99178.6 Georgia1993 - 19955,67471.7 Indiana1993 - 19945,09270.9 Maine1990 - 19955,95581.1 Michigan1993 - 19955,12279.7 New York*1993 - 19954,01473.3 Oklahoma1990 - 199510,12473.1 South Carolina1993 - 19955,88170.3 West Virginia1990 - 19959,73979.1 Total1990 - 199574,38075.0

11. Analytic Methods §Estimating and testing threshold l Fit a logistic model for each possible value of the threshold from 0 (minimum number of events) to 17 (one less than maximum number of events) l Graph the log-likelihood values by the threshold level for the model

12. l Estimated threshold, , is the threshold value from the model with the maximum likelihood value §To determine if a threshold exists, test l Null hypothesis: H 0 :  = 0 l Alternative hypothesis: H 1 :  > 0 l Test statistic: Log-likelihood statistic, R = -2 (ln L (  =0) - ln L(  =  ) l For constrained parameter, , Pr [R] = 0.5 + the probability from 0 to R of the standard normal distribution

13. §The null hypothesis is rejected if R > 1.64  95% C.I. on  includes all values of J which fulfill the condition: D(J) = 2×(ln L(  ) ! ln L(J)) < P 2 1,.95

14. Other Variables & Interactions in the Regression Model §Other Variables l Maternal race l Maternal age l Marital status l SES indicators l Unintended pregnancy l Pregnancy history l Parity l Tobacco use l Alcohol use §Interactions l Maternal age l Maternal race l Marital status l Maternal education l SES indicators l Unintended pregnancy l Pregnancy history l Parity

15. Risk of Poor Pregnancy Outcome by Number of Life Events 0 5 10 15 20 25 30 012345 6 789101112131415161718 Number of Events Percent Preterm (%)

16. Results - Bivariate comparison §Risk of preterm delivery increased among women who experienced more life events

17. Number of EventsNumber of WomenPreterm Delivery (%) 025,280 7.74 115,0688.80 211,9999.22 38,3519.32 45,1839.93 53,23110.45 61,99812.63 71,20812.67 870412.96 941012.58 1018015.07 1110714.90 124313.79 132014.12 141317.74 15618.51 16519.50 17228.17 181928.41

18. Modeling results §Threshold effects l Only among singleton births Inconsistent by parity and time period –Threshold of 5 for multiparous women from 1990-1993 –Threshold of 2 for primiparous women from 1994-1995 §Association of life events with preterm delivery Was significant only for the two models with a significant threshold effect Was weak (OR: 1.06/event, 1.07/event) even when significant

19. Modeling Results, cont.. §Inconsistencies in results remained when analysis done by state, year of birth and maternal race

20. Preterm Delivery, Singletons -6 -4 -2 0 2 4 6 8 10 0123456789 11121314151617 Threshold Level (Number of Life Events) Difference in Ln-Likelihood Primiparas 90-93 Primiparas 94-95Multiparas 90-93 Multiparas 94-95

21. Preterm Delivery, Multiple Births -2 -1.5 -0.5 0 0.5 012345678910 Threshold Level Difference in Log-Likelihood Multi 90-93 Multi 94-95

22. Threshold Effect between Number of Life Events and Preterm Delivery

23. Conclusions §Threshold model may fit the relation of stress and preterm delivery better than model with out threshold among some women §Results do not support a biological relation between stress and preterm delivery l Biological effect might vary by parity or plurality but is unlikely to vary by time