A Threshold Effect in the Relation of Stressful Life

Events and Preterm Delivery

Nedra Whitehead, Ph.D.

Background

Biological studies Suggest stress may affect the timing of

delivery through• Premature hormonal stimulation of labor; or• Immunosupression resulting in increased

risk of chorioamnionitis

Epidemiological studies have been inconsistent

• Different measures of stress related to preterm delivery in different studies

• Some studies find no relationship

A possible reason for inconsistent results: the specified model is not correct Two types of models have been tested:

Discrete model (Model A in figure)

• Women are dichotomized as stressed or not-stressed. • Average risk is the same among all stressed women.

Logistic model (Model B in figure)

• Each additional unit of stress causes a linear increase in the log-odds of the outcome

A possible model which has not been tested:Threshold model (Model C in figure)

Stress does not cause poor pregnancy outcome until a certain level is reached.

Above the threshold, each unit of stress causes a linear increase in the log odds of the outcome

Models of Relationship between Stress and Pregnancy Outcome

Stress Level

No threshold (A)

Threshold (C)

Discrete exposure (B)

Methods

Data were collected by the Pregnancy Risk Assessment Monitoring System (PRAMS)

Method described by Ulm1 was used to estimate and test for a threshold effect

1Ulm K. A statistical method for assessing a threshold in epidemiological studies. Stat Med 1991;10:341-9.

PRAMS Pregnancy Risk Assessment Monitoring System

What is PRAMS? Ongoing state population-based

surveillance system Study population: women who recently

delivered a live-born infant Maternal attitudes, behaviors, and

experiences during pregnancy and early infancy

Core and state-specific items

PRAMSSampling and Data Collection Methods

Sampling frame: state birth certificate filesHigh-risk women are oversampledStates annual sample size: 1600-3000Data collected 2-6 months after deliveryUses Dillman’s2 Total Design Method

Questionnaire mailed 2-3 times Mail non-responders interviewed by

telephone2 Dillman DA. Mail and telephone surveys: the total design method. 1st ed. New York, NY: John Wiley & Sons, Inc., 1978

States and Response RatesState Years of Data No. Respondents Response Rate

Alabama 1992 - 1995 5,646 74.9

Alaska 1990 - 1995 10,142 73.2

Florida 1993 - 1995 6,991 78.6

Georgia 1993 - 1995 5,674 71.7

Indiana 1993 - 1994 5,092 70.9

Maine 1990 - 1995 5,955 81.1

Michigan 1993 - 1995 5,122 79.7

New York* 1993 - 1995 4,014 73.3

Oklahoma 1990 - 1995 10,124 73.1

South Carolina 1993 - 1995 5,881 70.3

West Virginia 1990 - 1995 9,739 79.1

Total 1990 - 1995 74,380 75.0

Analytic MethodsEstimating and testing threshold

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)

Graph the log-likelihood values by the threshold level for the model

Estimated threshold, , is the threshold value from the model with the maximum likelihood value

To determine if a threshold exists, test Null hypothesis: H0: = 0

Alternative hypothesis: H1: > 0 Test statistic: Log-likelihood statistic,

• R = -2 (ln L (=0) - ln L( = ) For constrained parameter, , Pr [R] = 0.5

+ the probability from 0 to R of the standard normal distribution

The null hypothesis is rejected if R > 1.64

95% C.I. on includes all values of which fulfill the condition: D() = 2×(ln L() ln L()) < 2

1, .95

Other Variables & Interactions in the Regression ModelOther Variables

Maternal race Maternal age Marital status SES indicators Unintended pregnancy Pregnancy history Parity Tobacco use Alcohol use

Interactions Maternal age Maternal race Marital status Maternal education SES indicators Unintended

pregnancy Pregnancy history Parity

Risk of Poor Pregnancy Outcome by Number of Life Events

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Number of Events

Per

cen

t

Preterm (%)

Results - Bivariate comparison

Risk of preterm delivery increased among women who experienced more life events

Number of Events Number of Women Preterm Delivery (%)

0 25,280 7.741 15,068 8.802 11,999 9.223 8,351 9.324 5,183 9.935 3,231 10.456 1,998 12.637 1,208 12.678 704 12.969 410 12.5810 180 15.0711 107 14.9012 43 13.7913 20 14.1214 13 17.7415 6 18.5116 5 19.5017 2 28.1718 19 28.41

Modeling resultsThreshold effects

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

Modeling Results, cont..

Inconsistencies in results remained when analysis done by state, year of birth and maternal race

Preterm Delivery, Singletons

-6

-4

-2

0

2

4

6

8

10

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17Threshold Level (Number of Life Events)

Dif

fere

nce

in

Ln

-Lik

elih

oo

d

Primiparas 90-93 Primiparas 94-95 Multiparas 90-93 Multiparas 94-95

Preterm Delivery, Multiple Births

-2

-1.5

-1

-0.5

0

0.5

0 1 2 3 4 5 6 7 8 9 10Threshold Level

Dif

fere

nce

in

Lo

g-L

ikel

iho

od

Multi 90-93 Multi 94-95

Threshold Effect between Number of Life Events and Preterm Delivery

Group Number Threshold (95% CI)

R1 p-value Odds RatioOR (95% CI)

Singleton Births, Primiparous Women

1990-1993 11918 0 (0 -18) 0 1.0000 0.99 (0.97 - 1.02)

1994-1995 11574 2 (1- 3) 4.61 < 0.0000 1.06 (1.03 - 1.09)

Singleton Births, Multiparaous Women

1990-1993 15528 5 (3 - 18) 4.96 < 0.0000 1.07 (1.01 - 1.14)

1994-1995 13541 5 (0 - 18) 0.6 0.2743 1.03 (0.97 - 1.09)

Multiple Births, Multiparous Women

1990-1993 951 6 (0 - 18) 0.3 0.3821 1.03 (0.94 - 1.13)

1994-1995 929 6 (0 - 18) 1.17 0.1210 0.79 (0.55 - 1.15)

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 Biological effect might vary by parity or

plurality but is unlikely to vary by time