Mortality of Twins and Singletons

Yin Bun Cheung, Ph.D.

Paul Yip, Ph.D.

Johan Karlberg, M.D., Ph.D.

Readings

Objectives: mortality patterns

• Understand the patterns of gestational age-specific neonatal mortality in twins and singletons.

• Appreciate the (non-) comparability between twins and singletons.

Objectives: statistical models

• Learn a flexible way to handle interaction / effect-modification.

• Interpretation of a (logistic) regression model in different ways.

Mortality by gestational age

• Does the mortality difference between twins & singletons depend on gestational age?

• Do twins and singletons have the same gestational age pattern of mortality?

Difficulties in research

• Sample size

• Referral bias

• Statistical adjustment / matching

A study based on Swedish Medical Birth Registry

• All births born in Sweden in 1982-1995.

• Includes 32,942 twins and 1.5 million singletons.

• Details in Reading 1.

Cumulative distribution of GA

0

25

50

75

100

24 26 28 30 32 34 36 38 40 42

Gestational age (weeks)

Per

cen

t

.

Singletons

Twins

Odds ratios of short GA in twins and singletons

Risk factors Twins Singletons

Mother smoke 1.16* 1.39*

Prior still-birth 0.87 1.57*

Goodness-of-fit P=0.08 P=0.14

* P<0.05

Varying-coefficient model

Mortality impact of twin pregnancy as a function of GA:

Log odds=a1+b1GA+b2GA2+ (a2+c1GA+c2GA2)Twin+...

Varying-coefficient model

As a model of separate curves:

Log odds in singletons:

a1+b1GA+b2GA2

Log odds in twins:

(a1+a2)+(b1+c1)GA+(b2+c2)GA2

Birth weight SDS by GA

-3-2-10123

28 30 32 34 36 38 40 42

Gestational age (weeks)

Mea

n SD

S

SingletonsTwins

Size at birth in twins

Growth restriction in twins concentrates in late pregnancy.

•Physical constraints in utero?

•Limited placental function?

•Selection bias?

Neonatal deaths per 1000

020406080

100120140160180200

28 30 32 34 36 38 40 42

Gestational age (weeks)

Neo

nat

al d

eath

SingletonsTwins

A varying-coefficient logistic regression model

• The impact of twin pregnancy as a quadratic function of GA.

• Adjusted for confounders, e.g. prior still-birth, smoking.

• With & without adjustment for size at birth.

Log OR, fully adjusted

-2

-1

0

1

2

3

4

5

28 30 32 34 36 38 40 42

Gestational age (weeks)

Log

odd

s ra

tio

Log odds, fully adjusted

-6

-4

-2

0

2

4

28 30 32 34 36 38 40 42

Gestational age (weeks)

Log

odd

s

Singletons

Twins

Is twin birth hazardous? Why?

• Twins had lower odds of death prior to 36 weeks of GA; higher odds thereafter.

• Longer GA was related to lower mortality. But the decline was sharper in singletons than in twins.

Log OR, not adjusted for size at birth

-2

-1

0

1

2

3

4

5

28 30 32 34 36 38 40 42

Gestational age (weeks)

Log

odd

s ra

tio

Log odds, not adjusted for size at birth

-6

-4

-2

0

2

4

28 30 32 34 36 38 40 42

Gestational age (weeks)

Log

odd

s

Singletons

Twins

The role of fetal growth and size at birth?

• Without adjustment for size at birth the log OR climbed up faster after around 34 weeks.

• Twins’ mortality reached it’s lowest point at 38 weeks; it turned upward after that.

Clinical interpretations

• Twins have an earlier development

• In utero environment in late pregnancy not good for twins

• Residual confounding

Optimal GA for twins

The optimal gestational age for twins appeared to be 37-39 weeks in terms of neonatal mortality.

This is earlier than singletons’.

Readings1 Cheung YB, Yip P, Karlberg J. Mortality of

twins and singletons by gestational age. Am J Epidemiol 2000;152:1107-16.

2 Lie RT. Intersecting perinatal mortality curves by gestational age -- are appearances deceiving? Am J Epidemiol 2000;152:1117-19.

3 Cheung YB, Yip P, Karlberg J. Respond to “Are appearances deceiving”. Am J Epidemiol 2000;152:1120.