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Unique Epidemiologic Research

Rolv Skjærven

Department of Global Public Health and Primary Careand

Norwegian Institute of Public Health, Bergen

Unique Epidemiologic Research

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The importance of linked dataBy “linked”, epidemiologists mean a birth record that can be connected to other births from the same woman, or to other records for the same baby.

To appreciate the importance of linked data, we should first consider unlinked birth data. Much of what we know about infant mortality has come from birth certificates collected as part of vital statistics.

Most countries have laws that require collection of vital statistics, including legal records of births and deaths. These birth certificates typically exist in isolation, without being linkable to other deliveries by the same woman, or to later health problems occurring to that baby.

AJ Wilcox, 2007

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THE INTERNATIONAL IMPACT OF THEMEDICAL BIRTH REGISTRY OF NORWAY

In 1995, the US Centers for Disease Control and the US National Institutes of Health organized an international symposium on maternally-linked pregnancy outcomes. Along with the excellent linked Registries of Sweden and Denmark, the Medical Birth Registry of Norway was one of the centerpieces of that symposium. Ten years later, in 2005, a second international symposium was held, and once again, Norwegian researchers played a prominent role.

AJ Wilcox, 2007

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Medical birth registries started:Norway – 1967Iceland – 1972

Sweden/Denmark – 1973Finland – 1987

Number of infants born (2011):61322 (N) 4480 (I) 109766 (S)

59666 (D) 60258 (F)

How to do excellent research?

Topic for next yearsEPINOR summer school

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Promoting innovationand creativity in epidemiologyHiatt et al., Anals of Epidemiol, 2013

New and innovative thinking will be needed to develop and applymethods to empirical observation that complement our traditionalapproaches to hypothesis-driven research and making causal inferences.

I think there is true inspiration and there is synthesis. They are not mutually exclusive, they need to be paired.

One can collect data - observations - like Darwin did for months and months, on end classify, look for patterns and structure; but all the time the underlying direction of the synthesis is being guided by inspiration - a half understood idea, something you have 'received' in a dream or by relaxing.

In effect one side is sheer hard work and intellectually driven 'bottom up' analysis and the other is subconscious emotion and relaxation driven 'top down' inspiration.

For one you need reason and memory; for the other you need to cut out reason and memory because they get in the way.

For one you need a working environment, an office, files, computers, structure, for the other you need nature, play, music, unstructured environments and meditation.

Where good ideas come from

Rosemary Rock-Evans, 2014, comment to Steven Johnson’s Where good ideas come from

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During the last 20 years, more than 20 papers have been published in the leading weekly clinical journals

– the most influential journals in the field ofmedicine and public health.

Thirty papers have been published in the international specialty clinical journals in pediatrics, obstetrics and

other fields, and nearly 80 papers have appeared in major

epidemiology journals.

Norsk epidemiologi, 2007

The Medical Birth Registry of Norway –An International Perspective. AJ Wilcox

The leading weeklyclinical journals

We have now as many publications (40)as Sweden in epidemiologic research

based on theMedical Birth Registry

of Norway and Sweden, resp.

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Overall, we have a third ofSweden’s publications in

N Engl J Med, BMJ, Lancet, JAMA

…but

The leading weeklyclinical journals

We have uniqueregistry data in Norway

Go for the unique aspectsin the data!

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Family data is a unique «factor»

A narrow area for science,but these data dominate

our «top» papers

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In relation to a pregnancy, it will be wrong to say

that the risk for a specific pregnancycondition is X%

Most often risks are higher in 1st pregnancies, and risks in later pregnancies depends onwhat happened in previous pregnancies.

Some examples …

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Perinatal mortality and continuation ratesby outcome of previous births (1967-98)

Birth Order1 2 3 4

Peri

nata

l mor

talit

y (p

er 1

000)

20

30

40

50

60708090

200

300

10

100

Surviving childPerinatal loss

78

70

84

72

62

64

36

60

33

64

21

72

79

37

Continuation rate

Update of earlier studies:Skjaerven et al.,1987, PPE & 1988, AJE

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Risk for preeclampsia, 1st to 4th birth, by outcome of previous births. Singleton births, same partner for all births, Norway 1967-2009

Birth order1 2 3 4

Per C

ent

0

5

10

15

20

25

30

35

40

45

Conclusions:

After one preeclamptic pregnancy, the risk for the next pregnancy is

between 10 and 15 %, regardless of birth order.

After two or more preeclamptic pregnancies,

the risk is between 30 and 40%.

Red lines:risk following preeclampsia

Skjaerven et al. ‘The epidemiology of preeclampsia with focus on family data’ In ‘Placental Bed Disorders’, Pijnenborg et al. (eds), 2011

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Generations and recurrence

Breech delivery (BMJ; 2008)

Preeclampsia (BMJ; 2005)

Malformations (NEJM, 1994 & 1999, JAMA 2001)

Breech deliveries and generations• Hypothesis: Both women and men

delivered in breech presentation contribute to increased risk of breech delivery in their offspring ??

• ”Inherited”from women (OR=2.2;1.9-2.5) from men ?? (OR=2.2; 1.8-2.7)

Nordtveit et al.,BMJ, 2008

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Breech deliveries and generations• Hypothesis: Both women and men

delivered in breech presentation contribute to increased risk of breech delivery in their offspring

• ”Inherited” as stronglyfrom men (OR=2.2; 1.8-2.7) as from women (OR=2.2;1.9-2.5)

Nordtveit et al.,BMJ, 2008

Figure 1. Risk for preeclampsia in the second generation, given a preeclamptic pregnancy in the first generation. (Shaded area

represents preeclamptic pregnancies.)

(Skjaerven et al., BMJ, 2005)

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Recurrence of malformationsfrom one generation to the next

• Focus the recurrence of similar or dissimilar defects (25 categories of defects)

– Sibling recurrence(Lie, Wilcox, Skjaerven; NEJM, 1994)

– Malformations, mother to offspring (Skjaerven, Wilcox, Lie; NEJM, 1999)

– Malformations, father to offspring (Lie, Wilcox, Skjaerven; JAMA, 2001)

Recurrence of malformations: siblings and generations

Recurrence Risks

Total Same Different• 1st to 2nd siblings: 2.5 7.6 1.7• mother to offspring: 1.6 6.8 1.0• father to offspring: 2.4 6.5 1.8

Attributable risks:– Affected mothers contribute to 5 out of 1000 registered

birth defects in the next generation – Affected fathers contribute to 16 out of 1000

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Preeclampsia risk increases with pregnancy interval.

Implications for the observed effects of parity and paternity.

Reference:Skjaerven, Wilcox, Lie, NEnglJMed, 2002

Pregnancy interval (years)

Prop

ortio

nof

birt

hs (%

)

0102030405060708090100110120130140

1 2 3 4 5 6 7 8 9 10

Pre

ecla

mps

ia ri

sk(%

)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

RISK AT FIRST PREGNANCY

Preeclampsia risk in 2nd pregnancy

OVERALL RISKAT SECOND PREGNANCY

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Preeclampsia risk in 2nd pregnancy,by interval since the 1st pregnancy

for mothers with the same partner and different partner

Pregnancy interval (years)1 2 3 4 5 6 7 8 9 10

Pree

clam

psia

(%)

0,0

0,5

1,0

1,5

2,0

2,5

3,0

SAME PARTNERS

DIFFERENTPARTNERS

Median pregnancy intervalfor 2nd births by- different fathers- same father

Distance (complete years)

Num

ber o

f birt

hs (%

)

0

10

20

30

Preeclampsia by distance between pregnancies,women with same and new partner in 2nd pregnancies

Distance is calculated from date of birth to date of conseption of next pregnancy

0 2 4 6 8 10 12 14

Pre

ecla

mps

ia R

isk

(%)

0.7

0.80.9

1.5

2

3

4

5

1

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Odds Ratio of preeclampsia for mothers who had changed partner between two pregnancies, and mothers who had the same partner for both pregnancies, for different scenarios of adjustment for potentially confounding factors.

2nd pregnancy 3rd pregnancy 4th pregnancy

1) Crude estimate 1.3 (1.2-1.5) 1.4 (1.2-1.5) 1.6 (1.2-2.2)

2) Adjusted for smokingduring pregnancy (*) 1.5 (1.3-1.7) 1.5 (1.2-1.8) 1.8 (1.3-2.6)

3) Adjusted for inter-birth interval 0.8 (0.7-0.9) 0.9 (0.8-1.2) 0.9 (0.6-1.3)

4) Adjusted for interval and smoking 0.9 (0.8-1.1) 1.0 (0.8-1.2) 1.0 (0.7-1.5)

5) Adjusted for interval, smoking and maternalage at last birth 0.9 (0.8-1.1) 1.0 (0.8-1.3) 1.0 (0.6-1.5)

(*) daily smoking versus no smoking

Odds Ratios with 95% C.I.

Conclusions

• Change of partner does not influence risk for preeclampsia in the next pregnancy

• The “primipaternity” effect is due to confounding by interval and smoking

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Main results: Low birthweight, preterm birth and perinatal deathall increased 2.0-2.5 fold, in 2nd birthfor women with a new partner.

Perinatal death in relation to mother’s and father’s

gestational age and birthweight

Skjaerven et al., BMJ, 1997

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Perinatal death by maternal birthweight

Maternal birthweight (lower cutp)1000 1500 2000 2500 3000 3500 4000 4500 5000

RR

(95%

C.I.

)

0.80.9

1.5

2

3

4

5

1

Skjærven et al., BMJ, 1997 and Nordtveit et al., PPE, 2010

Perinatal death by parental birthweight

Maternal birthweight (lower cutp)

1000

1500

2000

2500

3000

3500

4000

4500

5000

RR

(95%

C.I.

)

0.80.9

1.5

2

3

4

5

1

Paternal birthweight (lower cutp)

1000

1500

2000

2500

3000

3500

4000

4500

5000

RR

(95%

C.I.

)

0.80.9

1.5

2

3

4

5

1

Mother Father

Nordtveit et al., 2010

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Tandberg et al.; BJOG 2011

Perinatal death in twins and singletons by maternal gestational age

Perinatal death in low birth weight (<2500g) by maternal birthweight

Maternal birthweight (lower cutp)1000 1500 2000 2500 3000 3500 4000 4500 5000

RR

(95%

C.I.

)

0.3

0.4

0.50.60.70.80.9

1.5

2

3

1

Skjærven et al., BMJ 1989 (update 2011)SSkjaerven et al.,1997 (reanalyzed)

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Preeclampsia and maternal mortality

- Evaluating risk for unaffected sisters

Bjørn Egil Vikse et al. , 2012, Clin J Am Soc Nephrol, & 2008, N Engl J Med, 2008

Unaffected sisters?

Based on population data, more than 8 million individuals,

we can find sisters to mothers in MBR

- Assuming that sisters carry similar underlying risk of chronic disease, this hypothesis will shed light on whether preeclampsia changes the mortality risk for a woman, or is simply an indicator of risk irrespective of the pregnancy condition.

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Preeclampsia and end stage renal disease:

HR(adj) =5.9 (4.3-8.0)

Unaffected sisters: HR(adj) =1.01 (0.62-1.7)

Bjørn Egil Vikse et al. , 2012, Clin J Am Soc Nephrol, & 2008, N Engl J Med, 2008

An example

The Barker Hypothesis

Early origin of adult diseases

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Birthweight and smoking as an adult

Early origin of adult diseases or

confounding due to social factors?

Kvalvik et al., PPE, 2015

The Barker Hypothesis

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06/10/2016 47

Errors in gestational age

Am.J.Publ.Health, 89, 213-218, 1999

O b se rve d b irth w e ig h t a t 3 2 w e eks g e sta tio n a l a g e

B irth w e ig h t (ro u n d e d 1 0 0 g r)0 500 1000 1500 2000 2500 3000 3500 4000 4500

Per

Cen

t

0

1

2

3

4

5

6

7

8

9

10

11

In c lu dedE x c lu ded

3 2 w e eks

p re te rm -3 2w dis tr1

T o ta l: M ean = 2088 SD = 750 n = 5129In c lu d ed : M ean = 1802 S D = 447 n = 4154

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Errors ingestationalage

50

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Pregnancy complications and long term maternal death

due to cardiovascular causes

The Medical Birth Registry of Norway

• All births in Norway 1967-2016 - 50 years with population based birth registration

• Close to 3 million births, for 1.6 million women• Personal identifiers for mother, father and child• Linked to - Death registry, Cancer registry

- Population registry- Education registry

• Internal linkage - Siblings and Generations

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State of the art?

Pregnancy complication in 1st birthCVD mortality

Pregnancy complications and long term maternal death

BMJ 2007, Meta-analysis, Bellamy et al.The relative risks (95% confidence intervals)

for ischaemic heart disease 2.2 (1.9 to 2.5) after 12 years,for stroke 1.8 (1.5 to 2.3) after 10 years

Almost all studies have been based on preeclampsia in 1st pregnancy

and no focus on effects of later reproduction

Cardiovascular deaths and preeclampsia

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Risk for preeclampsia, 1st to 4th singleton birth, by preeclampsia in previous births, Norway 1967-2014

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Fig 1 Cumulative risk of cardiovascular death for women according to pre-eclampsia status at first pregnancy and number of subsequentlifetime pregnancies

Cumulative risk of cardiovascular death in strata of outcome of first pregnancy.In each panel we compare mortality for women with one lifetime birth (green) , and women with two or more lifetime births (red) .

HR were adjusted for maternal age, year of first birth and maternal education

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Maternal deaths by lifetime number of pregnancies and term/preterm preeclampsia in first singleton pregnancy.

CARDIOVASCULAR DEATHS (CHD and Stroke, combined) LIFETIME NUMBER OF PREGNANCIES

NUMBER OF WOMEN

MATERNAL DEATHS (per 1000)

HR (95%C.I.) Adj. for maternal age,

1st pregnancy

HR (95%C.I.) ADJUSTED (*)

Women with one pregnancy0 No preeclampsia 112208 596 (5.3) 2.1 (1.9-2.3) 2.0 (1.8-2.2)1 Term

preeclampsia4758 47 (9.9) 4.1 (3.1-5.5) 3.4 (2.6-4.6)

2 Pretermpreeclampsia

1426 29 (20.3) 10.6 (7.3-15.3) 9.4 (6.5-13.7)

Women with two or more pregnancies3 No preeclampsia 599973 1415 (2.4) 1.0 (ref.) 1.0 (ref.)4 Term

preeclampsia21950 68 (3.1) 1.5 (1.2-2.0) 1.5 (1.2-2.0)

5 Pretermpreeclampsia

4459 16 (3.6) 2.3 (1.4-3.8) 2.4 (1.5-3.9)

(*) HR=Hazard Ratio with 95% confidence interval, adjusted for maternal education , maternal age and year of 1st birth

Paternal deaths by lifetime number of pregnancies and term/preterm preeclampsia in first singleton pregnancy.

CARDIOVASCULAR DEATHS (CHD and Stroke, combined)

LIFETIME NUMBER OF PREGNANCIES HR (95%C.I.) ADJUSTED (*)

Men whose partner had one pregnancy0 No preeclampsia 1.7 (1.6-1.7)1 Term preeclampsia 1.6 (1.4-1.8)

2 Preterm preeclampsia 1.6 (1.2-2.1)

Men whose partner had two or more pregnancies3 No preeclampsia 1.0 (ref.)4 Term preeclampsia 0.99 (0.91-1.1)

5 Preterm preeclampsia 0.94 (0.75-1.2)

(*) HR=Hazard Ratio with 95% confidence interval, adjusted for paternal education , paternal age and year of 1st birth

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- no preeclampsia

20-39 40-49 50-59 60-690,50,60,8

1,52

34568

1520

3040

1

10

- preterm preeclampsia

20-39 40-49 50-59 60-69

HAZ

ARD

RAT

IO (9

5% C

.I.)

0,50,60,8

1,52

34568

1520

3040

1

10

- term preeclampsia

20-39 40-49 50-59 60-690,50,60,8

1,52

34568

1520

3040

1

10

MATERNAL AGE AT DEATH

20-39 40-49 50-59 60-69

HAZ

ARD

RAT

IO (9

5% C

.I.)

0,50,60,8

1,52

34568

15203040

1

10

MATERNAL AGE AT DEATH

20-39 40-49 50-59 60-690,50,60,8

1,52

34568

15203040

1

10

MATERNAL AGE AT DEATH

20-39 40-49 50-59 60-690,50,60,8

1,52

34568

1520

3040

1

10

ONE PREGNANCY

2+ PREGNANCIES

HAZARD RATIOS FOR MATERNAL DEATH (CVD) BY AGE-CATEGORIES AT DEATH

references

Gestational diabetes in 2nd pregnancy for women with preeclampsia in 1st, by gestational age and z-score of birthweight by gestational age in 1st, relative to women with no preeclampsia (week 39-42);excluding women with diabetes in 1st pregnancy.

Gestational week, 1st pregnancy

25-34 35-36 37-38 39-42

OR

(95%

C.I.

)

0,70,85

1,52

34567

8,5

15

1

10

z <= medianz > median

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The GOS syndrome(great obstetric syndrome)

7 factors:Preeclampsia, Preterm Birth, PerinatalDeath, Gestational Diabetes, Placental abruption, Fetal Growth Retardation,

Macrosomia

… and all siblings

These factors are interrelated, and they all have an effect on maternal longterm survival

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GOS syndrome and maternal CVD death

Total number of complications0 1 2 3 4 5 6

Haza

rd R

atio

0.8

1.52

34568

15

1

101 pregn.

2 pregn.

3 pregn.

4 pregn.

Ref.

Figure 7: Parity specific GOS risk by history

of GOS, 1st birth in 1967-2002, followed to 2014

(solid=yes; non-solid=no)

Birth order1 2 3 4

Per C

ent

15

20

25

30

35

40

45

50

55

60

65

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Preeclampsia and paradoxes:• Smoking reduce the occurrence of preeclampsia

(to almost the half for heavy smokers) • Breast cancer is reduced 20-30%

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Conclusions

Pregnancy complicationsand maternal longterm disease or death?

• Not only preeclampsia• Not only 1st pregnancy• Not only CVD mortality

the end