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Australian national birthweight percentiles by sex and gestational age for twins, 2001–2010

  • Zhuoyang Li1, 2,
  • Mark P. Umstad3, 4,
  • Lisa Hilder2,
  • Fenglian Xu1 and
  • Elizabeth A. Sullivan1, 2Email author
BMC Pediatrics201515:148

https://doi.org/10.1186/s12887-015-0464-y

Received: 5 May 2015

Accepted: 25 September 2015

Published: 8 October 2015

Abstract

Background

Birthweight remains one of the strongest predictors of perinatal mortality and disability. Birthweight percentiles form a reference that allows the detection of neonates at higher risk of neonatal and postneonatal morbidity. The aim of the study is to present updated national birthweight percentiles by gestational age for male and female twins born in Australia.

Methods

Population data were extracted from the Australian National Perinatal Data Collection for twins born in Australia between 2001 and 2010. A total of 43,833 women gave birth to 87,666 twins in Australia which were included in the study analysis. Implausible birthweights were excluded using Tukey’s methodology based on the interquartile range. Univariate analysis was used to examine the birthweight percentiles for liveborn twins born between 20 and 42 weeks gestation.

Results

Birthweight percentiles by gestational age were calculated for 85,925 live births (43,153 males and 42,706 females). Of these infants, 53.6 % were born preterm (birth before 37 completed weeks of gestation) while 50.2 % were low birthweight (<2500 g) and 8.7 % were very low birthweight (<1500 g). The mean birthweight decreased from 2462 g in 2001 to 2440 g in 2010 for male twins, compared with 2485 g in 1991–94. For female twins, the mean birthweight decreased from 2375 g in 2001 to 2338 g in 2010, compared with 2382 g in 1991–94.

Conclusions

The birthweight percentiles provide clinicians and researchers with up-to-date population norms of birthweight percentiles for twins in Australia.

Keywords

Twins Birth weight Gestational age Small for gestational age

Background

Birthweight remains one of the strongest predictors of perinatal mortality and disability [1, 2]. Birthweight percentiles form a reference that incorporates weight and gestational age of infants at birth and are used as an adjunct for detecting neonates with suspected intra-uterine growth impairment and those at higher risk of neonatal and postneonatal morbidity. Twin births account for about 3 % of all births in Australia but make a significantly greater contribution to perinatal morbidity and mortality than singleton births [3]. Australia’s first birthweight percentiles for twin births based on national population data were published in 1999 using live twins born during 1991–94 [4]. Marked socio-demographic changes in maternal characteristics and clinical practice have occurred during the period since this publication including increased maternal age, reduced smoking rate, and increased usage of assisted reproductive technology [2].

The aim of the study is to present updated national birthweight percentiles for all male and female liveborn twins born in Australia over the 10-year period between 2001 and 2010.

Methods

Population-based data on twins born in Australia between January 2001 and December 2010 were obtained from Australian Institute of Health and Welfare National Perinatal Data Collection (NPDC). The NPDC is a national collation of jurisdictional population-based cross sectional data collections of pregnancy, childbirth and perinatal outcomes. Information is included in the NPDC on both live births and stillbirths of at least 400 g birthweight or at least 20 weeks gestation.

Records with missing birthweight, infant sex or gestational age values were excluded from calculating the birthweight-by-gestation percentiles. In addition, records with implausible birthweight were identified using Tukey’s methodology [5] based on the interquartile range. Birthweights for each sex and gestational age combination that fell below the first quartile minus twice the interquartile range (lower Tukey limit) or above the third quartile plus twice the interquartile range (higher Tukey limit) were considered outliers and were excluded from the analyses.

Level of remoteness was based on the geographical location of the usual residence of the mother, and was classified into five groups: major cities of Australia, inner regional Australia, outer regional Australia, remote Australia and very remote Australia.

Univariate analysis was used to examine the birthweight distributions and to determine the interquartile range for each gestational age for twins born in Australia. After removing outliers exact percentiles of birthweight in grams were calculated for each gestational week between 20 and 42 weeks. Results for the 5th and 95th percentile are presented only for gestational ages with a minimum of 100 records and the 10th and 90th percentile are plotted only for gestational ages with a minimum of 50 records, to be consistent with previously published Australian birthweight percentiles [2, 4]. Student t-test was used to examine the mean birthweight difference between twins born in 1991–94 and 2010. General linear model was used to investigate the trends for mean birthweight for male and female twins born between 2001 and 2010. All analyses were carried out using SAS for Windows, version 9.3 (SAS Inc, Cary, NC).

Ethics approval for this study was granted by the Human Research Ethics Advisory Panel of the University of New South Wale, Australia (Reference number: 2013-7-07) and Australian Institute of Health and Welfare Ethics Committee (Reference number: EO 2013/2/17). As secondary data analysis of de-identified data set, additional consent from participants was not required. Approval for use of data was provided by all states and territories.

Results

Between 2001 and 2010, a total of 43,833 women gave birth to 87,666 twins in Australia. Table 1 presents the maternal demographic and obstetric characteristics of these women. 1741 (2.0 %) births (1737 stillbirths and 4 births with unknown vital status at birth) were not considered further.
Table 1

Maternal characteristics of women who gave birth to twins, Australia, 2001-2010

Maternal characteristics

Number & percentage

Total

43,833 (100.0 %)

Maternal age (years)

   < 20

873 (2.0 %)

  20-24

4076 (9.3 %)

  25-29

10,468 (23.9 %)

  30-34

15,944 (36.4 %)

  35-39

10,412 (23.8 %)

   > =40

2055 (4.7 %)

  Not stated

5 (0.0 %)

Parity

  Primiparas

17,971 (43.3 %)

  Multiparas

23,466 (56.6 %)

  Not stated

37 (0.1 %)

Country of birth

  Australia

31,682 (72.3 %)

  Overseas

11,944 (27.2 %)

  Not stated

207 (0.5 %)

Smoking during pregnancy

  Yes

4271 (13.9 %)

  No

25,968 (84.7 %)

  Not stated

420 (1.4 %)

Remoteness

  Major Cities

30,579 (69.8 %)

  Inner Regional

8136 (18.6 %)

  Outer Regional

3959 (9.0 %)

  Remote

738 (1.7 %)

  Very remote

367 (0.8 %)

  Not stated

17 (0.0 %)

Among the 85,925 live births (43,153 males and 42,706 females), 53.6 % were born preterm (birth before 37 completed weeks of gestation) while 50.2 % were low birthweight (<2500 g) and 8.7 % were very low birthweight (<1500 g) (Table 2). More than half of liveborn twins were admitted to a special care nursery or neonatal intensive care unit (58.6 %) or required some type of active resuscitation measures (54.0 %) (Table 2). The median length of stay in hospital for twins was 6 days (interquartile range: 5 – 13 days). The 121 (0.1 %) records missing one or more of the key variables (sex, birthweight and gestational age), and 134 (0.2 %) lower Tukey limit and 207 (0.2 %) higher Tukey limit outliers were excluded. Percentiles were calculated for the remaining 85,436 infants.
Table 2

Live twin births, Australia, 2001-2010

Infant characteristics

Number & percentage

Total

85,925 (100.0 %)

Sex

  Male

43,153 (50.2 %)

  Female

42,706 (49.7 %)

  Not stated

66 (0.1 %)

Birthweight (g)

   < 1500

7461 (8.7 %)

  1500-2499

35,689 (41.5 %)

  2500-2999

30,403 (35.4 %)

  3000-3999

12,262 (14.3 %)

   > =4000

68 (0.1 %)

  Not stated

42 (0.0 %)

Gestational age (weeks)

  20-27

2845 (3.3 %)

  28-31

5501 (6.4 %)

  32-36

37,745 (43.9 %)

  37-41

39,792 (46.3 %)

   > =42

26 (0.0 %)

  Not stated

16 (0.0 %)

Presentation

  Vertex

58,727 (68.3 %)

  Breech

23,605 (27.5 %)

  Other

2566 (3.0 %)

  Not stated

1027 (1.2 %)

Apgar score at 5 minutes

  0-3

1124 (1.3 %)

  4-6

1810 (2.1 %)

  7-10

82,849 (96.4 %)

  Not stated

142 (0.2 %)

Resuscitation

  Yes

46,427 (54.0 %)

  No

34,581 (40.2 %)

  Not stated

4917 (5.7 %)

Admission to NICU

  Yes

47,674 (58.6 %)

  No

33,370 (41.0 %)

  Not stated

278 (0.3 %)

Length of stay

  Less than 1 day

2645 (3.1 %)

  1 day

1502 (1.7 %)

  2 day

2582 (3.0 %)

  3 day

5102 (5.9 %)

  4 day

9289 (10.8 %)

  5 day

12,231 (14.2 %)

  6 day

9704 (11.3 %)

  7-13 days

21,520 (25.0 %)

  14-20 days

9138 (10.6 %)

  21-27 days

4858 (5.7 %)

  28 or more days

7204 (8.4 %)

  Not stated

150 (0.2 %)

Figure 1 shows birthweight percentiles by gestational age for liveborn twins by infant sex; exact birthweight percentiles are shown in Table 3 and Table 4. The mean birthweight slightly decreased from 2462 g in 2001 to 2440 g in 2010 for male twins (p = 0.49). For female twins, the mean birthweight significantly decreased from 2375 g in 2001 to 2338 g in 2010 (p < 0.001) (Fig. 2). Compared with twins born in Australian 1991–94, the mean birthweight was significantly lower for twins born in 2010 for both male (2485 g versus 2440 g, p < 0.001) and female (2382 g versus 2338 g, p < 0.001).
Fig. 1

Birthweight percentiles for liveborn twins, by sex, Australia, 2001–2010

Table 3

Birthweight percentiles for male liveborn twins, Australia, 2001-2010

Gestation (weeks)

No. of births

Mean (g)

Standard deviation

Birthweight percentile (g)

p3

p5

p10

p25

p50

p75

p90

p95

p97

20

42

338

50

.

.

.

300

340

369

.

.

.

21

90

402

73

.

.

320

355

400

450

495

.

.

22

131

495

72

320

350

400

450

510

540

580

600

620

23

166

560

77

400

440

470

505

560

610

650

695

718

24

216

666

96

477

490

525

617

673

724

784

820

840

25

234

760

114

510

540

610

695

760

840

900

940

968

26

297

883

161

555

610

686

775

880

986

1080

1156

1205

27

323

1010

161

616

716

804

912

1019

1116

1200

1270

1300

28

478

1153

201

720

780

890

1030

1160

1290

1410

1450

1505

29

563

1297

219

757

875

1000

1180

1327

1450

1545

1625

1660

30

720

1453

246

930

991

1128

1314

1477

1600

1755

1850

1928

31

1059

1628

255

1120

1172

1285

1470

1632

1790

1942

2060

2120

32

1638

1784

292

1180

1275

1400

1596

1799

1972

2155

2245

2316

33

2040

1999

304

1410

1469

1590

1815

2010

2200

2370

2486

2555

34

3408

2179

328

1530

1618

1760

1970

2180

2400

2600

2704

2780

35

4503

2382

340

1755

1830

1950

2155

2380

2600

2810

2950

3040

36

7319

2589

359

1910

1995

2135

2350

2595

2820

3044

3185

3280

37

10665

2768

355

2100

2190

2315

2530

2765

3000

3215

3356

3470

38

7601

2901

357

2240

2320

2450

2665

2894

3130

3365

3510

3620

39

1129

2982

364

2260

2415

2538

2730

2980

3220

3460

3600

3695

40

308

3031

427

2275

2330

2470

2743

3040

3275

3600

3790

3960

41

25

3199

558

.

.

.

2805

3015

3500

.

.

.

42

8

2969

459

.

.

.

2500

2980

3400

.

.

.

Table 4

Birthweight percentiles for female liveborn twins, Australia, 2001-2010

Gestation (weeks)

No. of births

Mean (g)

Standard deviation

Birthweight percentile (g)

p3

p5

p10

p25

p50

p75

p90

p95

p97

20

49

299

57

.

.

.

260

296

330

.

.

.

21

94

374

58

.

.

300

340

370

415

450

.

.

22

107

459

75

300

330

350

420

460

508

545

570

580

23

143

517

83

325

350

405

470

520

570

620

640

650

24

176

635

87

425

480

530

589

638

700

731

751

780

25

167

728

113

520

547

580

656

730

800

878

907

920

26

241

845

141

525

580

660

760

864

930

1000

1052

1090

27

308

951

186

550

598

710

840

983

1060

1180

1240

1290

28

384

1090

169

745

795

870

991

1112

1200

1280

1345

1365

29

542

1219

211

750

808

930

1101

1235

1360

1465

1536

1601

30

697

1355

244

850

896

1010

1210

1375

1530

1655

1725

1760

31

990

1551

239

1030

1105

1227

1415

1568

1700

1833

1930

1990

32

1618

1713

262

1182

1248

1365

1550

1730

1880

2020

2140

2220

33

2037

1895

288

1320

1400

1530

1713

1900

2086

2250

2360

2430

34

3322

2085

308

1482

1555

1685

1885

2090

2292

2480

2570

2635

35

4558

2267

324

1640

1715

1850

2060

2270

2480

2670

2790

2875

36

7145

2464

339

1825

1905

2035

2240

2460

2680

2900

3030

3130

37

10695

2656

340

2020

2100

2225

2430

2650

2880

3090

3230

3326

38

7720

2774

339

2145

2230

2349

2545

2765

2990

3215

3350

3435

39

1154

2884

373

2185

2280

2420

2630

2875

3140

3360

3500

3570

40

320

2958

438

2110

2180

2368

2668

3000

3240

3518

3653

3800

41

22

2976

322

.

.

.

2795

2933

3220

.

.

.

42

11

3001

497

.

.

.

2540

2910

3440

.

.

.

Fig. 2

Mean birthweight of liveborn twins, by sex, Australia, 2001–2010

Discussion

We developed the contemporary population-based birthweight percentile charts to provide an up-to-date reference for twins born in Australia.

Growth in twin pregnancies slows progressively from around 32 weeks until term [6]. When comparing the dataset in this study with a singleton population from a similar time period [2] this phenomenon is confirmed. The median gestation-specific birthweight for twins were remarkably similar to those for singletons from a similar era until around 32 weeks gestation. The difference then becomes progressively more pronounced, reaching 640 g for males and 480 g for females at 40 weeks. It has been postulated that this slowing of growth late in a multiple pregnancy is a physiologically adaptive process that favours developmental maturity at the expense of fetal size [6]. However, there is a limit to this physiological adaptation and eventually the growth restriction becomes a pathological process. This is evidenced by studies consistently highlighting the risks of late fetal death in twins, particularly in relation to growth restriction [79].

Twin pregnancies have an increased risk of adverse outcome compared to single pregnancies. The increase in perinatal mortality and morbidity is primarily related to preterm delivery, complications of monochorionicity, and fetal growth restriction. Accurate population data is required to accurately diagnose growth restriction in twin pregnancies.

Secular trends for a decrease in the overall mean birthweight for liveborn twins were observed for both male and females in Australia in the study period. In contrast the mean birthweight for liveborn singletons in Australia from a similar time period has been relatively stable [2]. The observed decline in the mean birthweight for twins over time was partially explained by the downward shift in the distribution of gestational age. The mean gestational age was 35.4 weeks for twins in 2001, compared with 35.1 weeks in 2010 [10, 11]. Preterm birth occurred in 51.2 % of twins in 2001 and 56.7 % in 2010 [10, 11]. This decreased mean gestational age and increased pre-term births rate among twins might be attributed to improved intrapartum survival at earlier gestations, earlier obstetric interventions and increased usage of assisted reproductive technology [12, 13].

Population-based birthweight percentile charts for twins are scarce [1417]. When comparing Australian birthweight percentile charts with others, significant differences in birth size are observed between populations. At 40 weeks gestation, the mean birthweight of Australian live born twins are markedly lower than Norwegian and Finnish counterparts [15, 17] but the median birthweight of Australian twins are heavier than Canadian and Japanese twins [14, 16]. Sankilampi et al. has stated that the differences in term birth size is largely associated with differences in genetic background rather than maternal nutrition or healthcare as this is comparable between these developed countries [17].

There is inherent appeal in the customisation of growth charts that incorporate maternal weight, height, ethnicity as well as plurality. The intent is to identify fetuses that are small as a consequence of growth restriction rather than constitutionally small for clinical decision-making. Several large observational studies have suggested that customised charts improve the identification of infants with intrauterine growth restriction compared with population based charts, although contrasting opinions exist [1822]. Birthweight centiles provide a population reference describing fetal growth in the population rather than a standard for assessing individual growth [23]. They also provide the basis for characterising newborn size for longitudinal studies of childhood outcomes. The usefulness of customised birthweight percentiles has been debated. The value of plurality-specific centiles has been established but the literature remains divided on the benefits of customisation for other characteristics and the need for multiple reference charts [24]. Maternal height and weight have been included in the NPDC from 2010, but agreed national standards have not yet been implemented. Further studies are required to examine whether customised growth charts adjusted for maternal size and ethnicity contributes to improved prediction of adverse perinatal outcomes.

The provision of these updated birthweight percentile charts allows clinicians and researchers to re-evaluate the success of pregnancy management by determining the rate of detection of growth restriction. As previously described, growth restriction is the major cause of late fetal death in twin pregnancies and its accurate diagnosis a focal point of good obstetric care.

One limitation of this study is that birthweight percentile charts do not measure intrauterine growth but rather size at birth. The birthweight of babies born prematurely is likely to be influenced by the pathological process leading to preterm birth and therefore likely to differ from those remaining in utero until term [25, 26]. It has been argued that the preterm births should be assessed using estimated fetal weight rather than birthweight percentile charts as preterm neonates are disproportionately affected by the fetal growth restriction [25]. However, the accuracy of estimated fetal weight is limited by the ability of obtaining accurate measurements included within the computation of estimated fetal weight and the formula used for computation [26, 27]. To date, there has been no Australian chart published for sonographic standards for estimated fetal weight and the Australasian Society for Ultrasound in Medicine’s position is that ‘No formula for estimating fetal weight has achieved an accuracy which enables us to recommend its use’ [27, 28]. In such cases, the population-based birthweight percentile charts presented in this study provide a valuable reference for clinicians and researchers assessing the prognosis of twins in Australia.

Conclusions

This study presents the up-to-date national population-based birthweight percentile charts for male and female live born twins in Australia. These new charts provide a valuable reference for clinicians and researchers correctly identifying high-risk twins in Australia.

Abbreviations

AIHW: 

Australian Institute of Health and Welfare

NPDC: 

National Perinatal Data Collection

Declarations

Acknowledgements

This research is based on data made available by the Australian Institute of Health and Welfare (AIHW). The authors acknowledge the AIHW for funding the NPDC and midwives and other health professionals for collecting data for the NPDC.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Faculty of Health, University of Technology Sydney
(2)
National Perinatal Epidemiology and Statistics Units, University of New South Wales
(3)
The Royal Women’s Hospital
(4)
The University of Melbourne Department of Obstetrics and Gynaecology

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© Li et al. 2015

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