Eur J Epidemiol DOI 10.1007/s10654-014-9986-0

PERINATAL EPIDEMIOLOGY

Preterm and postterm birth in immigrant- and Swedish-born parents: a population register-based study Amal R. Khanolkar • Sara Wedre´n • Birgitta Esse´n • Pa¨r Spare´n • Ilona Koupil

Received: 21 August 2014 / Accepted: 29 December 2014 Ó Springer Science+Business Media Dordrecht 2015

Abstract Ethnic minorities/immigrant groups tend to have increased risk for preterm birth. Less is known about this risk in diverse immigrant groups, couples of mixed ethnic-origin and in relation to duration of residence. Data from the Swedish Medical Birth Register on 1,028,303 mothers who gave birth to 1,766,026 singleton live born infants (1982–2002), was linked to the Education and Total Population Registers. Immigrant parents were identified by country of birth. Risk of early preterm, late preterm and postterm birth was analyzed using multinomial logistic regression. Polish, Yugoslavian, Iranian, South Asian, East Asian and Sub-Saharan African parents, Swedish mothers

Electronic supplementary material The online version of this article (doi:10.1007/s10654-014-9986-0) contains supplementary material, which is available to authorized users. A. R. Khanolkar (&)
I. Koupil Centre for Health Equity Studies (CHESS), Stockholm University/Karolinska Institutet, Stockholm, Sweden e-mail: [email protected] A. R. Khanolkar
S. Wedre´n Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden Present Address: A. R. Khanolkar Institute of Child Health, University College London, 30, Guildford Street, London WC1N 1EH, UK B. Esse´n Department of Women’s and Children’s Health, International Maternal and Child Health, Uppsala University, Uppsala, Sweden P. Spare´n Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

who had children with non-Swedish fathers, and parents from two different immigrant groups had higher risk of early preterm birth [adjusted relative risk (RR) (95 % CI) 1.76 (1.24–2.50), 1.57 (1.31–1.87), 1.67 (1.30–2.14), 1.52 (1.07–2.16), 1.51 (1.08–2.10), 2.03 (1.32–3.12), 1.56 (1.45–1.67), and 1.55 (1.35–1.77) respectively] compared to Swedish-born parents. South Asian, Sub-Saharan African, and East Asian immigrants had a higher risk of late preterm birth compared to Swedish-born parents. North African and Middle Eastern, Somali, and Ethiopian/ Eritrean groups had increased risk of postterm birth [adjusted RR 1.31 (1.16–1.47), 2.57 (2.31–2.86), 1.85 (1.67–2.04) respectively]. Adjustment for covariates did not substantially change associations. Immigrant mothers resident \3 years had higher risk for early preterm and postterm birth compared to residents [10 years [adjusted RR 1.46 (1.24–1.71) and 1.16 (1.11–1.23) respectively]. In addition to higher risk of preterm birth in select immigrant groups, some immigrant groups are also at higher risk of postterm birth. Shorter duration of residence is associated with higher risk of non-term deliveries. Keywords Immigrant
Ethnicity
Preterm birth
Postterm birth
Perinatal
Sweden

Introduction Preterm and postterm birth, i.e. births before 37 completed gestational weeks or after 41 completed gestational weeks respectively, are associated with both short- and long-term health risks in the infant [1–5]. Preterm birth is one of the leading causes of neonatal mortality globally and is unequally distributed between ethnic and socioeconomic groups [6–16]. Less is known on ethnic variation in risk for

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postterm birth. While there has been significant progress in care for premature infants, reducing the prevalence of postterm birth is more challenging and rates have even increased in some regions [3, 16, 17]. A previous study on immigrants in Sweden found only slight differences in preterm birth rates between immigrants and Swedes [18]. Since the time of this study, Sweden has become more diverse and multicultural with larger numbers of non-European immigrants: 23 % of the population are either foreign-born or have both parents born abroad [19]. Thus, there is greater potential for differences in non-term births between Swedish and immigrant mothers today but the extent of these differences is not known. This is especially so, as maternal health and birth outcomes tend to vary by both socioeconomic status and ethnic-origin in high income countries [20–23]. Using data from the Swedish Medical Birth Register, which includes almost all births in the country, we studied the risk of early preterm, late preterm, and postterm birth among immigrant parents compared to Swedish-born parents. We considered a number of covariates such as socioeconomic characteristics or duration of residence in order to investigate possible mechanisms. Differences if any, in preterm and postterm births between Swedish and immigrant parents that appear to be mediated by modifiable factors will provide opportunities for targeted interventions for those groups that experience higher rates of adverse perinatal outcomes. The overall aim is to help reduce ethnic-related disparities and inequities in maternal and child health.

Methods Study population We undertook a register-based population study of 1,130,427 mothers who gave birth to 2,044,208 live singleton births during the period 1982–2002, resident in Sweden at time of birth and included in the Medical Birth Register (MBR). We chose 1982 onwards as information on cohabitation status and maternal smoking was collected from this year (considered as potential confounders) and it coincided with the introduction of ultrasound in gestational age estimation. The register holds detailed information on 98 % of all births in the country and on maternal characteristics (pre- and post-pregnancy anthropometrics, previous births, parity, diagnoses of illness, smoking habits and gestational duration), mode of delivery, birth circumstances, and anthropometrics of the infant [24]. We included 1,028,303 mothers (with 1,766,026 infants), i.e. 86 % of the eligible population, with complete information on all covariates for the analysis (Fig. 1). Using the unique

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personal identity number assigned to all residents in Sweden, we linked data from the Education and Total Population Registers. In Sweden, the first prenatal visit generally occurs between the 8th and 12th week of gestation [25]. Immigrants (those not born in Sweden) were identified by their country of birth (nativity) obtained from the Total Population Register. Only births to parents of the same nativity were considered to belong to a particular immigrant group. Births to parents born in different countries were classified into one of three groups: (1) Swedish born mothers and non-Swedish born fathers, (2) Swedish born fathers and non-Swedish born mothers and (3) NonSwedish born mothers and non-Swedish born fathers of differing nativity. As Sweden has attracted a larger number of immigrants from certain specific countries, we first identified infants with both parents from countries with the largest immigrant populations, defined as having a minimum of N = 3,000; Finland, Poland, Turkey, Iran, Iraq, Lebanon, Syria, Ethiopia and Eritrea, Somalia, and Chile. Based on geographical origin, the remaining infants not classified in the preceding ten countries were grouped into: Sweden (reference), Western Europe and North America, Eastern Europe, Former Yugoslavia, Latin America, North Africa and Middle East (Arab league nations), South Asia, East Asia and Sub-Saharan Africa. In total there were 21 categories of immigrant groups including ten individual countries, nine regional groupings and three categories where parents originated from different countries. This system of categorization of immigrant groups was used in all analyses. Maternal education and cohabitation status were accessed from the Education Register and MBR respectively. Maternal education (highest level achieved) was grouped as: B9 years elementary education, 2 or 3 years senior high school, \3 years post-secondary education, and C3 years post-secondary education. Mother’s cohabitation status was categorized as married/cohabiting and single. Duration of residence in Sweden was calculated by subtracting the birth date of the infant from the date of first immigration of the mother (obtained from the Immigration Register) and was categorized as: \3, 3–10, C11 years. Information on maternal age, weight, height, parity, gestational duration, smoking and hypertension in pregnancy were obtained from the MBR. Maternal age at delivery was categorised into \25, 25–29, 30–34, 35–39 and C40 years. Parity was classified as one, two and three or more deliveries. Weight and height used to calculate prepregnancy BMI (weight in kg divided by height in m2) were recorded at first antenatal check-up. Mothers were classified as underweight (\18.5 kg/m2), normal (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), obese class I (30–34.9 kg/m2) and obese classes II & III (C35 kg/m2—combined due to

A population register-based study

Fig. 1 Flow chart explaining how the study sample for this investigation was conceived

small numbers) according to WHO criteria. Gestational age at delivery was estimated by ultrasound (around 17th week of pregnancy). If ultrasound was unavailable, gestational age was defined as the time from last menstrual period (LMP) to birth. Ultrasound was chosen over LMP if there was a discrepancy between the two. Mothers were grouped into early preterm (\32 completed weeks of gestation), late preterm (32–36 weeks), term (37–41 weeks) and postterm (C42 weeks) births [26]. Smoking habits (recorded at the time of registration at antenatal clinics) generally reflect smoking habits during the first trimester. Mothers were grouped into: (1) non-smokers, (2) smokers (\10 cigarettes/day) and (3) smokers (C10 cigarettes/day). Mothers with hypertensive disorders corresponding to the following ICD codes in the MBR were considered to have hypertension during pregnancy: ICD-8:401, 637, ICD-9:642 and ICD-10:O10-11, O13-16.

Overall, mothers of infants excluded because of any missing data (N = 278,034) were on average 0.67 cm shorter, had 0.32 units lower BMI, and slightly higher proportions of both lowest and highest educated mothers and higher proportion of single mothers compared to mothers of infants included in analysis (N = 1,766,026). In mothers with missing data, the Swedish, Iranian and mixed-ethnicity groups had slightly higher proportions of both lowest and highest educated mothers while in other ethnic groups only the lowest educated group was missing in higher proportion but these differences were small. Patterns of missing data differed substantially between immigrant groups. While 12 % of Swedish mothers had missing data on at least one variable, corresponding proportions of missing data were higher in Finnish (38 %), Somali (36 %), Latin American (28 %) and highest in Western European (54 %) mothers.

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Statistical analyses Associations between immigrant group and maternal characteristics were analyzed using univariable linear regression or Chi square tests for differences of proportions for continuous and categorical variables respectively. We assessed if prevalence of early and late preterm and postterm birth differed between the first and second half of the study-period, i.e. between 1982–1991 and 1992–2002 in three study samples: (1) immigrants only, (2) Swedishborn parents only and (3) the entire study population. We calculated relative risk (RR) of early and late preterm and postterm birth with term birth as the baseline, comparing infants of various immigrant groups to infants of Swedish-born parents using multivariable multinomial logistic regression. The multinomial logistic regression model calculates the relative risk ratio, which is the ratio of two relative risks and is interpreted for a unit change in the predictor variable. It can be interpreted as the RR. Five models were constructed: Model 1—minimally adjusted for infant’s sex and birth year, Model 2—additionally adjusted for maternal age and parity, Model 3—additionally adjusted for maternal education and cohabitation status, Model 4—additionally adjusted for smoking and Model 5—additionally adjusted for hypertension in pregnancy. We also ran a model additionally adjusted for maternal height in a smaller sample of 945,035 mothers (that delivered 1,500,168 infants) adjusted for confounders as Model 5 above. Lastly, we tested the effect of duration of residence in Sweden on the risk for early and late preterm birth and postterm birth in the sample of 221,245 immigrant parents (i.e. the study sample excluding Swedish-born women or all live births in Sweden to Swedish-born parents) adjusted for confounders as in Model 5 above. Robust standard errors allowing for clustering of infants within families were used in all regression models. The study was approved by the Regional Ethics review board in Stockholm (Ethical permits 03-466, 2008/1482-32 and 2009/1084-32). Statistical analyses were conducted using STATA 12 (College Station, TX, USA).

Results There were differences in prevalence of risk factors for preterm and postterm birth between Swedish and immigrant groups (Table 1). Swedish mothers were the tallest and along with Western European and North American, Eastern European, Polish, and East Asian mothers, had the highest proportions of normal BMI. The highest proportions of overweight and obesity were found in North African and Middle Eastern, Iraqi, Somali, and Sub-

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Saharan African mothers (overweight C30 % and obesity C8 %). North African and Middle Eastern, Lebanese, Somali, Syrian, Turkish and East Asians had the highest proportions of lowest educated mothers while Western European and North American, Eastern European, Polish, and Iranian groups had the largest proportions of highly educated mothers (C20 %). Finnish mothers had highest proportion of smokers (19 %) whereas North African and Middle Eastern, Iraqi, Somali, South Asian, East Asian, Ethiopian, and Sub-Saharan African mothers had the lowest (B3 %). Mean gestational age for the study sample was 278.8 days (39.4 weeks). Gestational age distributions appeared shifted to the left by 2–3 days in offspring of South Asian, East Asian and Sub-Saharan African parents, and to the right by 2–3 days in Somali and Ethiopian groups in comparison to offspring of Swedish parents (Table 1; Fig. 2). There were no differences in prevalence of early preterm and term birth in the entire study population, but proportion of postterm birth increased from 6.96 to 7.40 % between 1982–1991 and 1992–2002. While overall risk of early and late preterm birth in immigrants reduced (from 0.81 to 0.70 % and 4.89 to 4.18 % respectively) between 1982–1991 and 1992–2002, we found a significant increase in postterm birth prevalence (6.67–7.00 %). There were no differences in prevalence of early preterm birth in Swedishborn parents but risk for late preterm birth significantly reduced from 4.54 to 4.11 % and postterm birth increased from 7.02 to 7.50 % between those two periods. Higher prevalence of early and late preterm birth combined was found in South Asians (7.1 %), Sub-SaharanAfricans (6.2 %), Polish (6 %) and East Asians (5.8 %). We found the highest prevalence of postterm birth in the Somali (16.3 %), Ethiopian and Eritrean (13 %), and North African and Middle Eastern (9.3 %) groups (Table 1). In model 1 (adjusted for sex and birth year), Polish, Yugoslavian, Iranian, and Sub-Saharan Africans had higher risk of early preterm birth compared to Swedish-born parents (RR 1.76, (95 % CI 1.25–2.50), 1.48, (1.24–1.76), 1.46, (1.14–1.87) and 1.81, (1.18–2.78), respectively; Table 2). Couples of mixed nativity, i.e. Swedish-born mothers and non-Swedish-born fathers or parents from two different immigrant groups were at higher risk for early preterm birth [unadjusted RR 1.67 (95 % CI 1.56–1.80) and 1.51 (1.32–1.73) respectively]. Swedish fathers and non-Swedish mothers also had a slight increase in risk for early preterm birth [unadjusted RR 1.13 (95 % CI 1.03–1.24)]. Only the Chilean group had decreased risk of early preterm birth [RR 0.55 (0.31–0.94)]. Adjustment for covariates only marginally changed RRs of early preterm term birth in the above groups compared to Swedish-born mothers (Table 2).

1.3

Obese class II & III (%)

21.4

17.7 17.1

2 or 3 years senior high school

Post-secondary \3 years

Post-secondary C3 years

13.6 7.9 3.8

Smoking 1–9 cigs/day %

[9 cigs/day (%)

Hypertension in pregnancy (%) 163,647 (11) 7,917 (0.5) 62,117 (4.3) 104,231 (7.3)

Delivery by cesarean section (%)

Early preterm (%)

Late preterm (%)

Postterm (%)

Years resident in Sweden

b

287

75th Percentile (days)

278.6

332 (6.9)

198 (4.1)

29 (0.6)

476 (10)

9.2

2.4

9.4

13.4

286

273

278.9 273

(days)

25th Percentile (days)

39.4

3.6

96.4

23.4

12.1

35.7

39.4

Single

Gestational age (weeks)

96.0 4.0

Married/cohabitating

Cohabitation status (%)

10.5 54.7

B9 years elementary education

Mother’s education (%) 28.8

31.6

36.7

[2

35.4

41.9

2

33.0

1.5

4.7

16.9

70.0

6.8

23.0

165.0

29.4

4,798

Western Europe and North America

One

Mother’s parity (%)

18.4 4.6

Normal (%)

Obese class I (%)

71.0

Underweight (%)

Overweight (%)

23.2 4.6

Mother’s pre-pregnancy BMI (kg/m2)a

28.5 166.7

Mother’s height (cm)a

1,435,286

Number of subjects

Mother’s age (years)

Sweden

Immigrant group

789 (6.5)

582 (4.8)

67 (0.5)

1,581 (13)

14.4

3.6

18.4

18.8

286

272

278.0

39.3

8.5

91.5

8.5

9.0

51.5

31.0

37.8

33.9

28.3

1.3

5.3

19.3

67.8

6.2

23.2

163.9

29.5

12,124

Finland

202 (6.5)

136 (4.4)

17 (0.5)

351 (11)

5.5

1.9

3.4

9.8

286

272

277.8

39.3

6.8

93.2

27.5

15.5

45.7

11.3

15.7

39.1

45.2

0.8

4.2

17.4

72.3

5.4

22.9

164.3

29.1

3,112

Eastern Europe

226 (6.4)

176 (5.0)

34 (1.0)

378 (11)

6.5

2.6

7.7

15.4

286

272

277.8

39.3

9.5

90.5

21.3

17.0

50.3

11.4

15.8

40.1

44.1

0.4

2.0

13.4

77.5

6.7

22.2

164.7

29.6

3,510

Poland

1,289 (7.6)

625 (3.7)

139 (0.8)

1,471 (9)

6.2

2.0

7.0

15.8

287

274

279.0

39.4

4.4

95.6

7.6

8.8

52.8

30.8

27.4

38.2

34.4

1.5

6.2

24.2

64.2

4.0

23.9

164.9

27.7

16,986

Yugoslavia

370 (9.3)

149 (3.7)

16 (0.4)

433 (11)

5.2

1.7

1.0

2.1

287

274

279.7

39.5

3.4

96.6

11.5

12.0

35.4

41.0

37.5

29.8

32.7

2.0

9.6

32.2

53.0

3.2

24.9

161.6

28.9

3,985

North Africa and Middle East

530 (5.7)

354 (3.8)

57 (0.6)

1,037 (11)

3.6

1.8

0.6

1.8

286

273

278.2

39.3

3.0

97.0

18.9

15.4

32.1

33.6

31.2

32.3

36.5

2.0

8.6

34.0

52.7

2.6

25.0

160.1

28.6

9,245

Iraq

435 (6.3)

258 (3.7)

34 (0.5)

548 (8)

5.4

1.5

6.0

10.2

286

273

278.5

39.7

4.2

95.8

4.9

9.4

32.7

53.0

46.0

26.1

27.9

2.7

8.6

28.0

57.6

3.0

24.6

161.5

26.5

6,960

Lebanon

Table 1 Descriptive characteristics of 1,766,026 singleton offspring delivered by 1,028,303 mothers in Sweden 1982–2002; by parents’ ethnic group

584 (16.3)

97 (2.7)

21 (0.6)

511 (14)

4.1

3.3

0.6

1.5

290

276

282.7

39.9

19.2

80.8

5.3

4.1

42.1

48.5

54.5

23.8

21.7

4.4

14.1

32.9

43.3

5.2

25.7

164.1

28.0

3,593

Somalia

203 (5.1)

138 (3.5)

17 (0.4)

297 (7)

5.6

1.2

4.0

7.2

285

273

278.2

39.3

2.8

97.2

5.7

13.5

37.5

43.3

36.5

29.5

34.0

1.5

6.8

27.6

61.6

2.5

24.3

161.0

27.4

3,963

Syria

767 (6.7)

482 (4.2)

60 (0.5)

1,030 (9)

9.0

1.7

6.4

13.5

286

273

278.2

39.3

2.9

97.1

2.2

3.0

34.2

60.6

42.0

28.8

29.2

1.1

6.3

25.5

63.5

3.5

24.0

160.0

26.8

11,462

Turkey

A population register-based study

123

123 1.0

Obese class II & III (%)

15.2

17.0 21.3

2 or 3 years senior high school

Post-secondary \3 years

Post-secondary C3 years

1.0 1.9

[9 cigs/day (%)

Hypertension in pregnancy (%) 1,408 (18) 65 (0.8)

Early preterm (%)

Years resident in Sweden

Delivery by cesarean section, yes (%)

4.8

5.1

Smoking \10 cigs/day (%)

b

285

75th Percentile (days)

31 (0.7)

727 (17)

5.0

2.9

0.1

0.3

283

270

275.5

277.0 271

(days)

25th Percentile (days)

38.9

2.6

97.4

16.1

13.8

40.1

39.2

Single

Gestational age (weeks)

95.7 4.3

Married/cohabitating

Cohabitation status (%)

11.1 50.6

B9 years elementary education

Mother’s education 30.0

26.4

39.1

[2

34.0

45.7

2

39.6

0.9

4.2

23.7

62.7

8.4

23.2

158.3

29.9

4,300

South Asia

One

Mother’s parity (%)

25.0 4.8

Obese class I (%)

64.6

Normal (%)

Overweight (%)

23.7

161.2

Mother’s height (cm) 4.6

26.8

Mother’s age (years)

Underweight (%)

7,898

Number of subjects

Mother’s pre-pregnancy BMI (kg/m2)

Iran

Immigrant group

Table 1 continued

27 (0.6)

826 (19)

6.0

2.5

0.6

1.8

289

275

281.0

39.7

19.6

80.4

3.7

5.4

53.2

37.7

33.4

32.3

34.3

1.0

4.6

24.1

61.9

8.4

23.4

160.7

28.0

4,364

Ethiopia and Eritrea

44 (0.8)

561 (10)

6.2

1.4

0.2

1.0

282

270

275.2

38.9

7.7

92.3

10.5

4.9

31.4

53.1

26.9

34.0

39.0

0.10

1.0

7.8

73.1

18.1

21.1

156.8

28.9

5,817

East Asia

15 (0.8)

286 (15)

6.0

2.7

2.3

5.5

284

272

277.1

39.2

12.7

87.3

19.2

14.3

46.7

19.8

32.0

36.0

32.0

1.4

6.2

23.6

65.1

3.6

23.8

158.6

28.6

1,940

Latin America

13 (0.3)

638 (15)

6.7

2.4

1.5

11.7

284

271

276.8

39.1

14.5

85.5

5.5

7.9

55.0

31.6

38.2

34.9

26.9

2.4

8.0

28.4

58.2

3.0

24.6

158.7

29.1

4,186

Chile

21 (1.0)

359 (17)

5.2

3.7

0.6

2.3

285

271

276.7

39.1

11.8

88.2

11.7

12.0

48.4

27.9

35.5

29.7

34.8

2.7

12.8

30.1

49.8

4.5

25.1

164.2

28.6

2,112

Sub-Saharan Africa

990 (0.9)

12,645 (12)

NA

3.2

12.0

16.6

286

273

278.2

39.3

14.6

85.4

16.4

15.4

52.7

15.5

20.8

33.0

46.2

1.8

5.1

18.5

69.0

5.5

23.3

166.8

28.3

107,672

Swedish mothers and non-Swedish fathers

528 (0.6)

11,841 (14)

14.1

3.2

8.6

13.9

286

272

278.2

39.3

5.5

94.5

21.1

15.7

47.9

15.3

21.7

35.7

42.6

1.2

4.2

17.5

70.8

6.3

23.0

163.9

28.4

84,571

Swedish fathers and non-Swedish mothers

236 (0.8)

3,299 (12)

9.4

2.2

6.8

11.5

286

272

277.9

39.3

14.9

85.1

15.2

12.0

45.3

27.5

25.9

32.6

41.5

1.8

5.7

22.3

64.9

5.3

23.6

162.7

29.3

28,142

Non-Swedish fathers and nonSwedish mothers

A. R. Khanolkar et al.

Not applicable to Swedish-born mothers

1,230 (4.4)

1,811 (6.4) 5,854 (6.9)

3,958 (4.7) 4,978 (4.6)

7,480 (7.0) 136 (6.4)

111 (5.2) 197 (4.7)

Data available for only 542,342 mothers of 835,438 singleton offspring; a

NA not applicable

145 (3.3)

Postterm (%)

227 (6.4) 337 (4.3)

429 (5.4)

Late preterm (%)

210 (4.9)

564 (13.0)

b

71 (3.7)

106 (5.4)

296 (5.0)

194 (3.3)

187 (4.5)

Latin America Iran Immigrant group

Table 1 continued

South Asia

Ethiopia and Eritrea

East Asia

Chile

Sub-Saharan Africa

Swedish mothers and non-Swedish fathers

Swedish fathers and non-Swedish mothers

Non-Swedish fathers and nonSwedish mothers

A population register-based study

South Asian-, Sub-Saharan African-, and East Asianborn parents (latter not significant after adjustment for maternal socioeconomic indicators) had a higher risk of late preterm birth compared to Swedish-born parents [unadjusted RR 1.52 (1.33–1.73), 1.26 (1.03–1.53) and 1.16 (1.03–1.31); Table 2]. Yugoslavian, Somali, and Syrian parents had decreased risk of late preterm birth. North African and Middle Eastern, Somali and Ethiopian/Eritrean parents had increased RRs of postterm birth [unadjusted RR 1.27 (1.13–1.43), 2.34 (2.11–2.60), 1.83 (1.66–2.03)] compared to infants of Swedish-born parents (Table 2). Decreased RRs of postterm birth were found in Eastern European, Polish, Iraqi, Syrian, Iranian and Latin Americans. Lowest RR of postterm birth was observed in South Asian, East Asian, and Chilean (Table 2) parents. Adjustment for covariates did not appreciably change these associations. Figure 3 summarizes RR of preterm and postterm birth across the different immigrant groups. In analysis restricted to mothers with information on height, adjustment for height did not substantially change the previously observed RR for preterm and postterm birth by ethnicity (data not shown). Immigrant mothers resident in Sweden for \3 years had increased risk of early preterm birth [adjusted RR 1.46 (1.24–1.71)] compared to mothers resident for [10 years. Those resident \3 and 3–10 years had increased risk of postterm birth [adjusted RR 1.16 (1.11–1.23) and 1.12 (1.07–1.17)] respectively (Table S1).

Discussion Main findings Several large immigrant groups are at higher risk of preterm, and/or postterm birth in Sweden which is not explained by variation in infant sex, maternal age and parity. The risk of non-term birth in immigrant parents decreases with longer residence in Sweden. Mixed ethnicity: Swedish-born mothers who had children with non-Swedish fathers, and parents from two differing foreign countries had increased risks of early preterm birth. Overall risk for preterm birth was 5 %, comparable with other high-income countries [9, 14]. Studies from the US showed that Black women are at higher risk of preterm birth compared to non-Hispanic whites, even among college educated women [9, 27]. We found lower risk of preterm birth among North African and Middle Eastern groups as previously reported [28]. In this study, these groups had increased risk of postterm birth. The few studies that specifically analyzed risk of adverse perinatal outcomes in mixed ethnicity couples are mostly restricted

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Fig. 2 Comparison of gestational age distribution (in days) for mothers of selected ethnic groups

to White–Black mixed couples [29]. Confirming previous findings, we found mixed ethnicity couples had higher risk of preterm birth. Strengths and limitations Our study was based on data of a well maintained high quality nationwide population-based perinatal register which includes all births and helps minimize selection bias. Data on infant sex, birth year, maternal age, gestational age and nativity had [98 % coverage. Proportions of preterm and postterm birth by ethnic group were very similar in the total eligible sample when compared with the study sample included in analysis. Misclassification of country of birth is minimized as data is collected routinely for official statistical purposes. Differences in risk of preterm and postterm birth between Swedish-born and immigrant parents could be due to differences in lifestyle, genetics and/or other components of ethnicity not measured here. While self-identified ethnicity is considered to be the gold standard, country of birth is regarded as a good proxy when the former is unavailable [30]. Unlike similar studies that often analyze differences in the largest ethnic/immigrant groups; we included all immigrant groups, either as individual countries if sufficient in size or as regional groups. We found that parents from North Africa and Middle East had an increased risk of postterm birth which was not observed for immigrants from

123

Iraq. This highlights the importance of studying individual countries wherever possible as grouping several nations together (even though they might be perceived as being culturally and geographically similar) might mask distinct differences between neighbouring countries. However, we acknowledge this is often not possible in similar studies due to low statistical power and lack of data on country of origin but we emphasize that it must be attempted wherever possible. We considered both maternal and paternal ethnicities thereby accounting for potentially different mechanisms that may take place in mixed ethnicity couples (e.g. intermixing of different cultures and genetic effects) and better defined immigrant/ethnic groups. Using ultrasound data in addition to LMP as in the Swedish MBR, helps reduce inaccuracies inherently associated when gestational age is calculated by LMP alone. For the period 1982–2002, ultrasound was used to estimate gestational age in 60 % of all pregnancies. There is a possibility for differential misclassification of gestational duration, with higher degree of misclassification in immigrant groups, leading to an overestimation of their nonterm births. Patel et al. [31] found that the entire gestational age distribution was shifted to the left by 1 week in South Asians and Blacks and that fetuses of these groups probably matured faster. We observed similar but smaller shifts in gestational age distributions in East and South Asians, Somali and Ethiopian/Eritrean mothers. Such shifts in gestational age

A population register-based study Table 2 Risk ratios (RR) for early preterm (\32 weeks), late preterm (32–36 weeks) and postterm (C42 weeks) births in 1,766,026 singleton offspring of immigrant parents compared to Swedish-born parents. Sweden and term birth (37–41 weeks) are reference categories Immigrant group

Birth status

Sweden (reference group)

Model 1a

Model 2b

Model 3c

Model 4d

Model 5e

RR

RR

RR

RR

RR

95 % CI

1.00

95 % CI

1.00

95 % CI

1.00

95 % CI

1.00

95 % CI

1.00

Western Europe and North America

Early preterm

1.10

0.75–1.57

1.07

0.74–1.55

1.03

0.72–1.50

1.04

0.72–1.50

1.12

0.78–1.62

Late preterm Postterm

0.95 0.95

0.81–1.10 0.84–1.07

0.95 0.97

0.82–1.11 0.86–1.09

0.93 0.97

0.80–1.08 0.86–1.09

0.93 0.97

0.80–1.09 0.86–1.09

0.96 0.96

0.83–1.30 0.85–1.09

Finland

Early preterm

1.00

0.78–1.27

1.00

0.78–1.26

0.90

0.70–1.13

0.86

0.67–1.10

0.84

0.65–1.07

Eastern Europe

Poland

Yugoslavia

North Africa and Middle East Iraq

Lebanon

Somalia

Syria

Turkey

Iran

South Asia

Ethiopia and Eritrea

East Asia

Late preterm

1.07

0.98–1.17

1.08

0.99–1.18

1.01

0.93–1.10

1.00

0.90–1.08

0.98

0.90–1.07

Postterm

0.91

0.84–0.98

0.94

0.87–1.02

0.94

0.87–1.02

0.94

0.87–1.02

0.95

0.88–1.02

Early preterm

0.98

0.60–1.58

0.94

0.58–1.51

0.95

0.58–1.52

0.98

0.60–1.58

1.11

0.69–1.80

Late preterm

1.02

0.85–1.22

1.00

0.83–1.19

1.00

0.84–1.20

1.02

0.85–1.22

1.08

0.90–1.30

Postterm

0.87

0.75–1.01

0.86

0.74–0.99

0.85

0.74–0.98

0.85

0.73–0.98

0.85

0.73–0.97

Early preterm

1.76

1.25–2.50

1.65

1.17–2.34

1.63

1.15–2.31

1.64

1.16–2.32

1.76

1.24–2.50

Late preterm

1.15

0.98–1.34

1.12

0.95–1.31

1.11

0.95–1.30

1.11

0.95–1.30

1.15

0.98–1.34

Postterm

0.90

0.78–1.03

0.87

0.75–0.99

0.86

0.75–0.99

0.86

0.75–0.99

0.86

0.75–0.99

Early preterm

1.48

1.24–1.76

1.56

1.31–1.86

1.42

1.19–1.69

1.44

1.20–1.71

1.57

1.31–1.87

Late preterm

0.87

0.80–0.95

0.90

0.83–0.98

0.85

0.78–0.92

0.86

0.80–0.93

0.90

0.82–0.97

Postterm

1.02

0.96–1.08

1.08

1.02–1.14

1.08

1.02–1.15

1.08

1.01–1.14

1.07

1.01–1.14

Early preterm

0.73

0.43–1.24

0.75

0.44–1.26

0.67

0.40–1.13

0.75

0.44–1.26

0.86

0.51–1.45

Late preterm Postterm

0.90 1.27

0.74–1.06 1.13–1.43

0.90 1.33

0.75–1.08 1.18–1.49

0.85 1.33

0.70–1.01 1.18–1.49

0.86 1.32

0.75–1.07 1.17–1.48

0.95 1.31

0.80–1.14 1.16–1.47

Early preterm

1.10

0.83–1.42

1.10

0.85–1.44

1.04

0.80–1.36

1.14

0.87–1.50

1.30

1.00–1.70

Late preterm

0.91

0.82–1.02

0.92

0.82–1.03

0.88

0.79–1.00

0.92

0.83–1.03

0.98

0.88–1.10

Postterm

0.74

0.67–0.81

0.77

0.70–0.84

0.77

0.70–0.84

0.76

0.70–0.84

0.76

0.70–0.83

Early preterm

0.86

0.62–1.21

0.95

0.67–1.33

0.83

0.60–1.17

0.88

0.63–1.24

0.99

0.71–1.40

Late preterm

0.87

0.76–0.99

0.90

0.80–1.04

0.83

0.73–0.95

0.86

0.75–0.98

0.90

0.80–1.04

Postterm

0.82

0.74–0.92

0.92

0.82–1.03

0.92

0.82–1.03

0.92

0.82–1.02

0.91

0.81–1.01

Early preterm

1.15

0.73–1.80

1.30

0.82–2.02

1.08

0.70–1.70

1.24

0.80–1.95

1.27

0.81–2.00

Late preterm

0.72

0.57–0.89

0.77

0.61–0.96

0.68

0.55–0.85

0.73

0.60–0.92

0.74

0.60–0.93

Postterm

2.34

2.11–2.60

2.64

2.38–2.93

1.60

2.34–2.89

2.58

2.32–2.86

2.57

2.31–2.86

Early preterm

0.75

0.45–1.24

0.78

0.47–1.29

0.70

0.42–1.16

0.75

0.45–1.25

0.87

0.52–1.44

Late preterm

0.80

0.67–0.96

0.81

0.68–0.97

0.76

0.63–0.91

0.80

0.65–0.94

0.84

0.70–1.00

Postterm

0.66

0.56–0.77

0.71

0.60–0.83

0.71

0.61–0.83

0.70

0.60–0.83

0.70

0.60–0.82

Early preterm

0.94

0.73–1.22

1.00

0.77–1.30

0.84

0.65–1.10

0.90

0.70–1.17

0.99

0.76–1.28

Late preterm

0.96

0.87–1.06

0.99

0.90–1.09

0.89

0.80–0.98

0.92

0.83–1.02

0.96

0.87–1.06

Postterm Early preterm

0.91 1.46

0.84–0.98 1.14–1.87

1.00 1.38

0.92–1.08 1.08–1.77

1.00 1.37

0.93–1.09 1.07–1.75

1.00 1.46

0.92–1.08 1.13–1.87

0.99 1.67

0.91–1.07 1.30–2.14

Late preterm

0.99

0.88–1.11

0.97

0.86–1.08

0.96

0.86–1.08

0.99

0.88–1.11

1.06

0.94–1.20

Postterm

0.72

0.65–0.80

0.70

0.63–0.77

0.70

0.63–0.77

0.70

0.62–0.76

0.68

0.62–0.76

Early preterm

1.30

0.91–1.85

1.33

0.94–1.90

1.26

0.88–1.80

1.41

0.99–2.01

1.52

1.07–2.16

Late preterm

1.52

1.33–1.73

1.53

1.34–1.74

1.48

1.30–1.68

1.56

1.37–1.78

1.62

1.42–1.84

Postterm

0.66

0.57–0.76

0.68

0.58–0.78

0.68

0.58–0.78

0.67

0.58–0.78

0.67

0.58–0.77 0.87–1.85

Early preterm

1.18

0.81–1.73

1.24

0.85–1.81

1.04

0.71–1.52

1.18

0.80–1.72

1.27

Late preterm

0.84

0.70–1.01

0.86

0.72–1.04

0.77

0.64–0.93

0.82

0.68–1.00

0.85

0.71–1.02

Postterm

1.83

1.66–2.03

1.90

1.72–2.10

1.88

1.70–2.07

1.86

1.68–2.05

1.85

1.67–2.04

Early preterm

1.32

0.95–1.84

1.33

0.96–1.85

1.12

0.80–1.56

1.28

0.92–1.78

1.51

1.08–2.10

Late preterm

1.16

1.03–1.31

1.16

1.03–1.32

1.04

0.92–1.18

1.11

0.98–1.27

1.20

1.06–1.36

Postterm

0.43

0.37–0.50

0.44

0.38–0.51

0.44

0.38–0.51

0.44

0.37–0.50

0.43

0.37–0.50

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A. R. Khanolkar et al. Table 2 continued Immigrant group

Latin America

Chile

Sub–Saharan Africa

Model 1a

Model 2b

Model 3c

Model 4d

Model 5e

RR

95 % CI

RR

95 % CI

RR

95 % CI

RR

95 % CI

RR

95 % CI

Early preterm

1.36

0.82–2.27

1.36

0.82–2.27

1.31

0.79–2.18

1.42

0.85–2.37

1.53

0.92–2.55

Late preterm

0.83

0.65–1.06

0.84

0.66–1.08

0.82

0.64–1.05

0.86

0.67–1.10

0.88

0.70–1.13

Postterm

0.73

0.60–0.89

0.75

0.61–0.92

0.75

0.60–0.92

0.74

0.60–0.91

0.74

0.60–0.90

Early preterm

0.55

0.31–0.94

0.56

0.32–0.97

0.50

0.30–0.86

0.54

0.31–0.94

0.60

0.34–1.02

Late preterm

1.06

0.91–1.24

1.10

0.94–1.27

1.00

0.86–1.18

1.06

0.91–1.24

1.10

0.94–1.28

Postterm

0.60

0.51–0.69

0.64

0.55–0.74

0.63

0.54–0.73

0.63

0.54–0.73

0.62

0.53–0.72

Early preterm

1.81

1.18–2.78

1.87

1.22–2.88

1.72

1.12–2.65

1.92

1.25–2.96

2.03

1.32–3.12

Birth status

Late preterm

1.26

1.03–1.53

1.28

1.05–1.56

1.21

0.99–1.48

1.28

1.05–1.56

1.31

1.08–1.60

Postterm

0.87

0.73–1.05

0.91

0.76–1.10

0.91

0.75–1.09

0.90

0.75–1.08

0.90

0.74–1.08

Early preterm

1.67

1.56–1.80

1.60

1.50–1.71

1.54

1.43–1.64

1.50

1.40–1.61

1.56

1.45–1.67

Late preterm

1.08

1.04–1.11

1.04

1.01–1.07

1.01

0.98–1.05

1.00

0.97–1.03

1.02

0.99–1.05

Postterm

0.95

0.93–0.98

0.94

0.92–0.97

0.94

0.91–0.96

0.94

0.91–0.96

0.93

0.91–0.96

Swedish fathers and NonSwedish mothers

Early preterm

1.13

1.03–1.24

1.08

0.99–1.18

1.06

0.97–1.17

1.06

0.97–1.16

1.10

1.01–1.21

Late preterm Postterm

1.08 0.95

1.05–1.12 0.92–0.98

1.06 0.94

1.03–1.10 0.91–0.96

1.05 0.93

1.02–1.10 0.91–0.96

1.05 0.94

1.02–1.09 0.91–0.96

1.07 0.93

1.03–1.11 0.90–0.96

Non-Swedish fathers and Non-Swedish mothers

Early preterm

1.51

1.32–1.73

1.47

1.28–1.69

1.36

1.18–1.56

1.41

1.23–1.62

1.55

1.35–1.77

Late preterm

1.02

0.96–1.08

1.00

0.94–1.06

0.95

0.90–1.01

0.97

0.91–1.03

1.01

0.95–1.07

Postterm

0.87

0.82–0.91

0.88

0.84–0.92

0.87

0.83–0.91

0.87

0.82–0.91

0.86

0.82–0.91

Swedish mothers and NonSwedish fathers

a

Model 1: adjusted for infant sex and birth year, b Model 2: adjusted for model 1 ? maternal age and parity, c Model 3: adjusted for model 2 ? maternal education and cohabitation status, d Model 4: adjusted for model 3 ? maternal smoking in pregnancy, e Model 5: adjusted for model 4 ? hypertension in pregnancy

Fig. 3 Risk ratios with corresponding 95 % confidence intervals for early preterm, late preterm and postterm birth by ethnic groups in Sweden. Estimates are adjusted for infant sex, birth year, maternal age,

123

parity, education, cohabitation status, smoking, hypertension in pregnancy. Termbirth and Sweden are the reference categories

A population register-based study

distribution though limited to few ethnicities might cause overestimation/underestimation of preterm/postterm births in those ethnic groups. This will be problematic until the development of ethnic-specific guidelines for gestational age. Maternal height and body composition which vary by ethnicity could potentially affect the risk of preterm and postterm birth as shorter or smaller-built mothers are likely to have constitutionally smaller fetuses [25, 32]. NonEuropean mothers were shorter and in some ethnic groups also had higher mean BMI. We were unable to control for BMI as it was missing for a large proportion of mothers, but adjustment for height did not change the observed RR for preterm or postterm birth. A recent Swedish study found that maternal overweight and obesity increased risk for preterm delivery, however this study did not address the role of BMI in terms of inequalities across ethnic groups (Nordic vs. non-Nordic) and the role of BMI in causing ethnic differences in non-term birth still remains to be established in samples with better data completeness and greater statistical power [25]. Education was inversely associated with risk for preterm birth in univariate analysis comprising the entire study sample and in analyses stratified by some ethnic groups. However, it did not appear to mediate the differences in risk of non-term birth in adjusted models (main model— Table 2). This is surprising as education is considered the strongest predictor (of various socioeconomic indicators) of preterm birth [32, 33]. Interpretations Preterm birth Studies mostly focus on two possible explanations for ethnic differences in preterm birth: socioeconomic and biological [11]. A review including 32 studies on Black/ white differences in preterm birth suggests more complex mechanisms including three possible intermediaries between ethnic disparities and preterm birth: stress (acute and chronic), preconceptional health and genetic/epigenetic differences (hypothesised to induce vascular dysfunction, inflammation and/or hypothalamic–pituitary–adrenal axis (HPAX) dysfunction which lead to preterm birth) [11]. Maternal stress has received attention in regard to the HPAX, important in both response to psychosocial stress and in regulation and timing of birth [34]. Differential levels in corticotropin-releasing hormone and cortisol biomarkers were reported in ethnic minorities with increased risk for preterm birth [35, 36]. Stress (due to racial discrimination, adverse life events, anxiety) is associated with increased risk for preterm birth [37, 38]. Stress may occur before, or during pregnancy or could be a result of accumulation over the life time. Immigrants may

experience higher levels of stress due to segregation, institutionalized racism, lower income levels or in overcoming cultural and language barriers. Preconceptual health including prevalence of genital tract infections, hypertension and diabetes vary between ethnic groups and are linked to increased risk of preterm birth [11]. Despite the differences in prevalence of hypertension across ethnic groups, controlling for the same did not change the observed RR. Access to and quality of health care services may influence risk for non-term birth. We were unable to control for the same but a previous Swedish study showed Somali and Ethiopian/Eritrean mothers were at higher risk for perinatal mortality due to higher prevalence of suboptimal factors related to health care (miscommunication with health care providers, insufficient surveillance for suspected IUGR) [39]. Genetic differences (both within and between ethnic groups) may explain some of differences in risk observed with preterm birth. Studies have found genetic differences between ethnic groups in the underlying biological pathways that lead to preterm birth and genetic differences in maternal and foetal contributions to preterm birth [40, 41]. Postterm birth Risk factors for postterm birth include genetic predisposition, maternal obesity, higher maternal age, male fetal sex, fetal anencephaly, and previous postterm pregnancies [42]. High obesity prevalence in Somali and Northern African/ Middle Eastern women could contribute towards increased risk for postterm birth. Risk factors like higher BMI, stress, and socio-cultural differences could interact together in increasing prolonged pregnancy in these groups. While the genetic differences in preterm birth are largely thought to be driven by the maternal genotype, evidence now shows that differences in the risk for postterm birth might be explained by the paternal genotype [43]. Ethnic groups may have developed evolutionarily different mechanisms in gestational duration and initiation of labour along with differences in fetal growth and maturation as they were exposed to different environments [31]. Earlier Swedish studies showed an increased risk for adverse maternal outcomes including perinatal and pregnancy related mortality related to sub-optimal care in immigrants and particularly Somali mothers, which had the highest RR for postterm birth [39, 44–46]. Immigrant Somali women practiced different ‘survival’ childbirth strategies including reduced food intake, to diminish fetal growth thereby reducing risk for a cesarean section and mortality. Such behavioral strategies were based on past experiences in Somalia where maternal mortality is high [47]. Delayed antenatal care attendance could be a contributing factor that we were unable to control for.

123

A. R. Khanolkar et al.

Conclusion Ethnic-origin and short residency in the country are associated with increased risk for non-term birth. This study highlights the importance of studying specific immigrant groups, individual country of origin and groups of mixed ethnic origin compared to broader regional/ethnic groupings. Further investigations are needed to specifically study reasons behind postterm birth in Somali, Ethiopian/Eritrean and North African and Middle Eastern mothers. These immigrant groups should be made aware of potential adverse outcomes linked to postterm birth so they can make more informed choices when presented alternatives for delivery. Acknowledgments We would like to thank Professor Matteo Bottai, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden for his advice on the use of multinomial logistic regression. We would also like to acknowledge the Swedish Research Council for funding [Swedish Initiative for research on Microdata in the Social and Medical Sciences (SIMSAM) funding from (project 2008-7483)]. A. R. K and I. K are supported by a grant from the Swedish Research Council for Health, Working Life and Welfare (Grant Number 2006-1518). Conflict of interest interest.

8.

9.

10.

11.

12.

13.

14.

The authors report they have no disclosures of 15.

Ethical standard This study was approved by the regional ethics committee of Karolinska Institutet, Stockholm, Sweden (Dnr 03-466). 16.

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