Diabetologia

, Volume 53, Issue 4, pp 641–651

Birthweight and the risk of childhood-onset type 1 diabetes: a meta-analysis of observational studies using individual patient data

  • C. R. Cardwell
  • L. C. Stene
  • G. Joner
  • E. A. Davis
  • O. Cinek
  • J. Rosenbauer
  • J. Ludvigsson
  • C. Castell
  • J. Svensson
  • M. J. Goldacre
  • T. Waldhoer
  • J. Polanska
  • S. G. A. Gimeno
  • L.-M. Chuang
  • R. C. Parslow
  • E. J. K. Wadsworth
  • A. Chetwynd
  • P. Pozzilli
  • G. Brigis
  • B. Urbonaitė
  • S. Šipetić
  • E. Schober
  • C. Ionescu-Tirgoviste
  • C. E. de Beaufort
  • D. Stoyanov
  • K. Buschard
  • C. C. Patterson
Article

Abstract

Aims/hypothesis

We investigated whether children who are heavier at birth have an increased risk of type 1 diabetes.

Methods

Relevant studies published before February 2009 were identified from literature searches using MEDLINE, Web of Science and EMBASE. Authors of all studies containing relevant data were contacted and asked to provide individual patient data or conduct pre-specified analyses. Risk estimates of type 1 diabetes by category of birthweight were calculated for each study, before and after adjustment for potential confounders. Meta-analysis techniques were then used to derive combined ORs and investigate heterogeneity between studies.

Results

Data were available for 29 predominantly European studies (five cohort, 24 case–control studies), including 12,807 cases of type 1 diabetes. Overall, studies consistently demonstrated that children with birthweight from 3.5 to 4 kg had an increased risk of diabetes of 6% (OR 1.06 [95% CI 1.01–1.11]; p = 0.02) and children with birthweight over 4 kg had an increased risk of 10% (OR 1.10 [95% CI 1.04–1.19]; p = 0.003), compared with children weighing 3.0 to 3.5 kg at birth. This corresponded to a linear increase in diabetes risk of 3% per 500 g increase in birthweight (OR 1.03 [95% CI 1.00–1.06]; p = 0.03). Adjustments for potential confounders such as gestational age, maternal age, birth order, Caesarean section, breastfeeding and maternal diabetes had little effect on these findings.

Conclusions/interpretation

Children who are heavier at birth have a significant and consistent, but relatively small increase in risk of type 1 diabetes.

Keywords

Birthweight Epidemiology Meta-analysis Risk factors Type 1 diabetes mellitus 

Introduction

Recent global estimates suggest that approximately 70,000 children per year are diagnosed with type 1 diabetes [1]. Worryingly, this incidence rate is almost universally increasing by around 4% annually [2, 3]. Although the aetiology of the disease is largely unknown, these increases within genetically stable populations suggest the role of environmental influences. It has been proposed that events occurring early in life could be of particular importance [4].

Birthweight is associated with various perinatal factors such as maternal age, gestational age, maternal weight and nutritional status, and maternal diseases [5]. High birthweight has been associated with an increased risk of childhood cancers such as leukaemia [6] and brain tumours [7].

Numerous studies have investigated the role of birthweight in childhood-onset type 1 diabetes. The findings of this research seem inconsistent, as some studies have concluded that high birthweight is associated with increased diabetes risk [8] or reduced diabetes risk [9], while others have shown no association with type 1 diabetes risk [10]. Interpretation of these findings is made more difficult because studies have reported associations using many different categorisations of birthweight [8, 11, 12, 13, 14], with some [15, 16] only reporting findings for the extremes of birthweight and others [17, 18, 19, 20, 21] not reporting their birthweight results in any detail, concentrating instead on other findings. This could lead to reporting bias if the decision to report birthweight findings was influenced by whether or not results were interesting or ‘statistically significant’. Finally, many studies had limited power to detect associations with birthweight due to inadequate sample size.

We performed the first meta-analysis using individual patient data to: (1) assess the evidence of an association between birthweight and type 1 diabetes; (2) explore the shape of any association; and (3) adjust the observed association for potential confounders (such as gestational age, maternal age and maternal diabetes).

Methods

Literature search

The main literature search was conducted using MEDLINE, through Ovid Online (www.ovid.com). The search strategy used the following terms: (‘Birth weight’ or birth weight or birthweight) and (‘Diabetes Mellitus, Type 1’ or [diabetes and Type 1] or IDDM), with the terms in inverted commas used as MEDLINE subject heading key words. Similar searches were conducted on Web of Science (http://apps.isiknowledge.com) and EMBASE (www.embase.com). Finally, to identify studies that investigated birthweight along with other risk factors, a more general search was conducted on MEDLINE using the terms: (‘Diabetes Mellitus, Type 1’ and [‘Case–control Studies’ or ‘Cohort Studies’]). The searches were limited to studies on humans published before July 2009. Abstracts were screened independently by two investigators (C. R. Cardwell, C. C. Patterson) to establish whether the studies were likely to provide relevant data based on the following inclusion criteria: (1) the studies identified a group with type 1 diabetes and a group without type 1 diabetes; and (2) they recorded birthweight in these two groups. Studies were excluded if they contained fewer than 100 cases or if they were family-based (because it is possible that the association between birthweight and diabetes is different in individuals with a higher genetic susceptibility). Citations generated from the more general MEDLINE search were initially screened to remove obviously irrelevant articles. Finally, the reference lists of all pertinent articles were hand-searched and corresponding authors of articles included in the review were asked if they were aware of any additional studies.

The corresponding author of each study included was requested to provide data on the association between birthweight and type 1 diabetes in the following categories: <2.5, 2.5–3.0, 3.0–3.5, 3.5–4.0, ≥4 kg. It was necessary to contact authors because it was generally not possible to extract such data from the published reports, as they reported birthweight using different categorisations or (in some cases) did not report their birthweight data at all. It was also necessary to contact authors to facilitate consistent adjustment of the association with birthweight for the following potential confounders: gestational age, maternal age, birth order, breastfeeding, Caesarean section and maternal diabetes. Authors were requested to provide raw data or to provide adjusted estimates of the association between birthweight and type 1 diabetes after conducting specified additional analyses.

Details of studies included (country, design, year of publication and response rates), participants with type 1 diabetes (source, age at onset) and control participants (source) were extracted by one reviewer (C. R. Cardwell) and confirmed by the corresponding authors of the respective studies.

Statistical analysis

Odds ratios and SEs were calculated for the association between diabetes and each category of birthweight for each study. Similarly, to investigate the trend across categories of birthweight, an OR (and SE) was calculated per increase in category (corresponding to approximately 500 g) using regression models appropriate to the design of the study. Unconditional and conditional logistic regression analyses were used to calculate ORs and SEs for the unmatched and matched case–control studies, respectively. In cohort studies with varying duration of participant follow-up, rate ratios and their SEs were used instead of ORs, which were not directly calculable. As type 1 diabetes is a rare disease, these measures should be approximately equal [22]. Poisson regression was used to adjust these rate ratios for differences in the year of birth between those developing diabetes and those not, a consequence of this study design, by adding a year of birth term to the regression model in addition to birthweight. Tests for heterogeneity between studies were conducted and random-effects models used to calculate pooled ORs [23]. Random-effects models were deemed more appropriate than fixed-effects models because it was anticipated that between-study heterogeneity would exist, due to the observational nature of studies. The I2 statistic was calculated to quantify the degree of such heterogeneity[24]. This statistic measures the percentage of total variation across studies due to heterogeneity. Publication/selection bias was investigated by checking for asymmetry in funnel plots of the study ORs against the standard error of the logarithm of the ORs [25].

A two-stage technique was used to calculate pooled estimates of the association between birthweight and diabetes after adjustment for potential confounders [26]. First, adjusted estimates and SEs were calculated within each study using regression models appropriate to the study design (logistic regression for case–control studies, conditional logistic regression for matched case–control studies and Poisson regression for cohort studies); regression models included diabetes as the outcome variable and birthweight and the potential confounder(s) of interest as explanatory variable(s). As explained previously, Poisson regression models additionally included terms to adjust for differences in year of birth between cases and controls in the cohort studies with varying participant follow-up. Meta-analysis techniques were then applied to these adjusted estimates.

Sub-group analyses were conducted subdividing studies by type (case–control and cohort) and including only studies with a low risk of bias (excluding case–control studies in which controls were not population-based or not randomly selected controls, and excluding any study with a response rate of less than 80% in the case group or control group). A separate analysis was conducted by age at onset of diabetes.

All statistical analyses were performed using STATA 9.0 (Stata, College Station, TX, USA).

Results

Search results

The searches identified 81 relevant articles. Of these, 35 were excluded because they contained duplicate or overlapping information; only the most comprehensive article was retained in the review. Ten articles were excluded because they contained information on fewer than 100 cases, six articles were excluded because they had family-based designs and a further article was excluded (after contact with the author) because birthweight was not recorded in sufficient detail [27]. A full list of the papers identified by the searches is available from the authors.

The remaining 29 articles [8, 9, 10, 11, 12, 13, 15, 16, 17, 18, 19, 21, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44] contained information from 34 independent studies, as information from five centres was taken from one article [15] and information from two centres was taken from another [19]. An investigator from each of the 34 studies was invited to provide raw data (or estimates from pre-specified analyses), but one author [40] could not be contacted. Individual patient data or pre-specified estimates were obtained from 29 studies (in one study [28], data were extracted directly from the published report). Characteristics of these predominantly European studies are shown in Table 1.
Table 1

Characteristics of included studies investigating the association between birthweight and type 1 diabetes, ordered by publication date

Study

Type 1 diabetes

Controls

Available confoundersd

First author [ref]

Design

Country

Source

Year of diag

Age at diag. (years) a

n (<5 years)b

Rc

Source (matching criteria)

nb

Rc

GA

MA

BO

CS

MDh

BFi

Patterson [16]

C-C

UK

Hosp. admission/childhood diabetes register

1976–1988

0–14

268 (73)

100

Maternal discharge records (age, sex, area)

1340

100

✓0.4

 

Lawler-Heavner [28]

C-C

USA

Colorado IDDM registry

1978–1988

<18

221

?

Newspapers/radio/postersf

197

?

      

Bock [10]

C-C

Denmark

Hosp. admission, National Patient Registry

1978–1989

<16

837

98

Birth registry (age, sex)

837

NA

      

Wadsworth [31]

C-C

UK

British Paediatric Association surveillance unit

1992

0–5

214 (214)

89

Health Authority Immunization Register

318

70

 

 

✓1.9

✓4

Gimeno [32]

C-C

Brazil

Diabetes Association\Hospital admission

1995

0–19

333 (105)

91

Unclear (neighbourhood, sex, age)f

333

100

 

 

✓0.3

✓3

McKinney [13]

C-C

UK

Yorkshire Childhood Diabetes Register

1993–1994

0–15

214 (43)

94

GPs’ records (age, sex)

423

82

✓0

✓any

Rami [34]

C-C

Austria

Vienna type 1 diabetes register

1989–1994

0–14

103 (14)

86

Schools (age, sex)

373

80

✓0.3d

✓any

Eurodiab [15]

C-C

Bulgaria

W. Bulgaria type 1 diabetes register

1991–1994

0–14

127 (34)

73

Schools, polyclinics (age)

440

79

✓0.5d

✓any

C-C

Latvia

Latvian type 1 diabetes register

1989–1994

0–14

133 (24)

99

Population register (age)

301

79

✓0.3d

✓any

C-C

Lithuania

Lithuanian type 1 diabetes register

1989–1994

0–14

115 (36)

94

Polyclinics (age)

266

73

✓0d

✓any

C-C

L’bourg

L’bourg type 1 diabetes register

1989–1995

0–14

57 (15)

100

Pre-schools and schools (age)

172

95

✓0d

✓any

C-C

Romania

Bucharest type 1 diabetes register

1989–1994

0–14

82 (14)

74

Pre-schools and schools (age)

277

81

✓0d

✓any

Stene [8]

Co

Norway

Norwegian Childhood Diabetes Registry

1989–1998

0–14

1,810 (376)

100g

Norwegian medical birth registry

1,382,602

NA

✓0.4

 

Visalli [21]

C-C

Italy

Lazio type 1 diabetes register

1989–1995

0–14

141 (19)

100

Schools (age)

703

91

 

✓0.5

✓3

Stene [36]

C-C

Norway

Norwegian Childhood Diabetes Registry

1989–2000

0–14

346 (58)

73

Norwegian population registry

1,626

56

✓0.2d

✓3

Sadauskaite-Kuehne [19]

C-C

Sweden

S.E. Sweden type 1 diabetes register

1995–2000

0–15

492 (98)

100

Population register

1084

73

 

✓0.5d

✓3

 

C-C

Lithuania

Lithuanian type 1 diabetes register

1996–2000

0–15

284 (42)

100

Outpatient clinicf

807

95

 

✓0.3d

✓3

Marshall [17]

C-C

UK

Morecombe Bay\E. Lancashire diabetes clinics

1998

0–15

196 (78)

83

Health Authorities (sex, birth date)

381

53

 

✓0.5d

✓any

Cardwell [11]

Co

UK

N. Ireland type 1 diabetes register

1971–2001

0–14

984 (188)

92g

Northern Ireland Child Health Register

439,647

NA

✓0.2

✓any

Sipetic [37]

C-C

Serbia

Belgrade hospital admission

1994–1997

0–16

105 (19)

91

Hospital outpatients with skin diseasef (age, sex, area)

210

100

✓1.0d

✓4

Svensson [38]

C-C

Denmark

Danish register of childhood diabetes

1996–1999

0–14

474 (118)

81

Danish population register (age, sex)

674

48

✓1.5

✓4

Malcova [39]

C-C

Cz. Rep.

Czech Childhood Diabetes Register

1987–2000

0–14

850 (195)

76

School friendsf

1,458

73

✓0.8

✓4

Polanska [18]

C-C

Poland

Upper Silesia Diabetes Register

1986–1996

0–14

344 (49)

87

Central Bureau for Statistics

994,460

100

 

   

Wei [9]

C-C

Taiwan

School-based urine screening programme + questionnaire

1992–1997

0–18

277 (19)

87

Randomly selected negatives from screening programme

533

88

 

✓0.6

✓3

Haynes [41]

Co

Austr.

W. Australian Children’s Diabetes Register

1980–2002

0–14

926

99g

W. Australia Midwives’ Notification System

≈557,707

NA

 

✓0.1

 

Ievins [12]

Co

UK

Hosp. admission (ICD diabetes code)

1963–1999

0–14

408 (100)

?

Oxfordshire/W. Berkshire maternity records

266,665

NA

✓0.7

✓any

Borras Perez [42]

C-C

Spain

Catalonia type 1 diabetes register

1978–2008

0–14

607 (215)

72

Catalonia Public Health Birth Register

3,321

98

   

✓any

Rosenbauer [43]

C-C

Germany

Nationwide hosp.-based surveillance

1992–1995

0–4

746 (746)

71

Local registration offices (age, sex, area)

1,828

43

 

 

✓0.4d

✓4

Waldhoer [44]

Co

Austria

Austrian diabetes register

1989–2005

0–5

444 (444)

85g

Birth certificate registry

1,435,668

NA

   

aIn years; bnumber included in analysis of birthweight; cresponse rate (%); dtick denotes data recorded in study and available for analysis; ematernal type 1 diabetes used in analyses; fnot randomly selected or not population-based; gpercentage of cases identified in cohort shown in subscript; hproportion (%) of controls whose mothers have (type 1) diabetes; iduration (months) of breastfeeding used in adjusted analysis shown in subscript

Austr., Australia; BF, breastfeeding; BO, birth order; C-C, case–control; Co, cohort; CS, Caesarean section; Cz. Rep., Czech Republic; GA, gestational age; L’bourg , Luxembourg; MA, maternal age; MD, maternal diabetes; ref, reference

Birthweight and type 1 diabetes

The association between birthweight and type 1 diabetes from these 29 included studies (with a total of 12,087 cases of type 1 diabetes) is shown in Fig. 1. Overall, children with higher birthweights had small increases in their risk of type 1 diabetes. Specifically, children weighing 3.5 to 4.0 kg at birth had on average a 6% increase and children born heavier than 4.0 kg had on average a 10% increase in their risk of diabetes (p = 0.02 and p = 0.003, respectively); there was little heterogeneity in these increases between studies (I2 = 0, p = 0.70 for heterogeneity and I2 = 0, p = 0.94 for heterogeneity, respectively). No difference in the risk of diabetes was found in children weighing 2.5 to 3.0 kg at birth (combined OR 1.01, p = 0.82) compared with children of 3.0 to 3.5 kg birthweight. There was also no difference in the risk of diabetes in children born lighter than 2.5 kg (combined OR 0.98, p = 0.75); however, we did find evidence of marked heterogeneity between studies for this association (p = 0.01 for heterogeneity, I2 = 42). Figure 1 shows that this heterogeneity was partly due to the study designs. Cohort studies consistently (p = 0.64 for heterogeneity, I2 = 0) demonstrated a reduced risk of diabetes in children born lighter than 2.5 kg (combined OR 0.79, p = 0.002), while case–control studies were less consistent (p = 0.03 for heterogeneity, I2 = 38) and found no evidence of reduced risk of diabetes in children born lighter than 2.5 kg (combined OR 1.07, p = 0.45). Finally, funnel plots of the association between birthweight in categories and risk of type 1 diabetes (Electronic supplementary material [ESM] Fig. 1) roughly conformed to the expected funnel shape, providing little evidence of asymmetry and therefore little evidence of publication bias. Further analysis comparing children weighing over 4 kg at birth with children weighing under 4 kg revealed a combined OR of 1.09 (95% CI 1.02–1.15; p = 0.006); for children weighing under 2.5 kg at birth vs those weighing over 2.5 kg, the combined OR was 0.93 (95% CI 0.80–1.08; p = 0.32).
Fig. 1

Meta-analyses of the unadjusted association between birthweight in categories (compared with reference category 3–3.5 kg) and type 1 diabetes including 12,087 cases) using the random effects model, studies ordered by publication date. L’bourg, Luxembourg

A linear trend in the risk of type 1 diabetes per category increase in birthweight (corresponding to approximately 500 g) was also investigated (Table 2). Although we found evidence (p = 0.03) of a linear increase in the risk of diabetes by on average 3% per 500 g, this was subject to heterogeneity (I2 = 35%, p = 0.03); moreover, Fig. 1 revealed a number of studies [9, 18, 31, 43] which did not seem to conform to a linear trend.
Table 2

Meta-analyses of 29 studies investigating the association between birthweight and type 1 diabetes (including 12,087 cases) before and after adjustments for recorded confounders and in studies with low risk of bias

Analysis per birthweight categories (kg)

Cases (n)

Combined OR (95% CI)

p value

Heterogeneity

χ2 (p)

I2

Unadjusteda

     

 <2.5

554

0.98 (0.84–1.13)

0.75

46.71 (0.01)

42

 2.5–3.0

1,713

1.01 (0.94–1.08)

0.82

30.60 (0.29)

12

 3.0–3.5

4,399

1.00 (Ref. cat.)

   

 3.5–4.0

3,849

1.06 (1.01–1.11)

0.02

23.66 (0.70)

0

 ≥4

1,572

1.10 (1.03–1.18)

0.003

17.41 (0.94)

0

 Trend

 

1.03 (1.00–1.06)

0.03

43.29 (0.03)

35

Adjusted for gestational age, maternal age and birth order (where available)b

     

 <2.5

528

0.87 (0.73–1.04)

0.13

54.62 (0.001)

51

 2.5–3.0

1,643

0.98 (0.91–1.07)

0.68

33.76 (0.17)

20

 3.0–3.5

4,212

1.00 (Ref. cat.)

   

 3.5–4.0

3,697

1.07 (1.02–1.13)

0.01

25.92 (0.58)

0

 ≥4

1,531

1.13 (1.05–1.22)

0.001

30.13 (0.36)

70

 Trend

 

1.05 (1.01–1.08)

0.01

53.76 (0.002)

48

Adjusted for all available confounders as shown in Table 1c

     

 <2.5

517

0.87 (0.73–1.04)

0.13

50.60 (0.004)

47

 2.5–3.0

1,600

0.98 (0.90–1.07)

0.67

35.37 (0.13)

24

 3.0–3.5

4,127

1.00 (Ref. cat.)

   

 3.5–4.0

3,617

1.07 (1.02–1.13)

0.009

24.24 (0.67)

0

 ≥4

1,506

1.11 (1.03–1.20)

0.01

32.02 (0.27)

13

 Trend

 

1.04 (1.01–1.08)

0.01

53.09 (0.003)

47

Unadjusted, including only studies with a low risk of bias (n = 12 studies)d

     

 <2.5

284

0.92 (0.75–1.11)

0.37

18.95 (0.06)

42

 2.5–3.0

906

1.01 (0.91–1.12)

0.90

14.96 (0.18)

26

 3.0–3.5

2,286

1.00 (Ref. cat.)

   

 3.5–4.0

2,057

1.09 (1.02–1.16)

0.01

8.86 (0.63)

0

 ≥4

872

1.16 (1.07–1.26)

0.001

6.55 (0.83)

0

 Trend

 

1.07 (1.04–1.10)

<0.001

12.56 (0.32)

12

aOne study [28] unavailable for the categories <2.5 kg and 2.5–3.0 kg

bAdjusted for gestational age in categories (≤37, 38–41, ≥42 weeks), maternal age in categories (<20, 20–24, 25–29, 30–34, ≥35 years) and birth order in categories (1st, 2nd or 3rd born) except for four studies [18, 31, 32, 43] that were not adjusted for gestational age, two studies [21, 42] not adjusted for birth order and two unadjusted studies [10, 28]

cAdjusted for maternal age in categories as above, gestational age in categories (as above), birth order in categories (as above), maternal diabetes (see Table 1), Caesarean section (yes or no) and breastfeeding (see Table 1 for details)

dExcluding case–control studies with controls not randomly selected or population-based or studies in which the response rate in either the case group or control group was less than 80% (or unknown) as shown in Table 1

Ref cat., reference category

Adjustments for potential confounders

Table 2 shows the overall results for birthweight before and after adjustments for potential confounders. The results after adjustment for maternal age, gestational age and birth order are largely consistent with the unadjusted results, except that the overall OR in the under 2.5 kg category is slightly reduced (adjusted OR 0.87); consequently the OR per 500 g increase is slightly increased (adjusted OR 1.05). The fully adjusted results, which were additionally adjusted for breastfeeding, Caesarean section and maternal diabetes (information on available confounders, see Table 1), are also shown and differed only slightly (Table 2). Repeating the analysis after removal of children born to mothers with diabetes in the 20 studies with available data had little impact on the association between birthweight and type 1 diabetes (data not shown).

Analysis by study quality

Table 2 also contains an analysis in 12 studies with a low risk of bias (excluding case–control studies with non-population based or not randomly selected controls, and excluding any study with a response rate of less than 80% in the case or control group, as shown in Table 1). In these 12 studies, a slightly more marked association between birthweight and type 1 diabetes was seen. Thus compared with the 3.0 to 3.5 kg birthweight category, the increase in diabetes risk in children of 3.5 to 4.0 kg birthweight was 9%, while that in children born heavier than 4.0 kg was 16%. These studies also showed a more marked increase in diabetes risk per 500 g increase in birthweight, namely 7%, with considerably less heterogeneity in their estimates (I2 = 12%, p = 0.32).

Analysis by age at onset

There was little evidence of a difference in the association between birthweight and type 1 diabetes in early-onset (age under 5 years) cases and later onset (age over 5 years) cases in the 23 studies in which these data were available. For instance, per 500 g increase in birthweight, there was a 4% (OR 1.04 [95% CI 0.99–1.09]) increase in early-onset and a 4% (OR 1.04 [95% CI 1.01–1.08]) increase in later onset disease.

Other studies

In five of the studies identified by our searches [29, 30, 33, 35, 40] the required data could not be obtained from authors (or extracted from the published reports). In a Swedish study [30] (with 4,584 cases of type 1 diabetes) we were able to estimate results from a figure, but only using a different reference category (of 3.0 to 4.0 kg). Recalculating estimates using this reference category in 28 of the studies included (and for which data were available) generated an increased risk of diabetes in children born heavier than 4.0 kg of 8% (combined OR 1.08 [95% CI 1.02–1.15]; p = 0.01) compared with children weighing 3.0 to 4.0 kg at birth. After adding this Swedish study, this increase in risk was little altered (combined OR 1.07 [95% CI 1.02–1.12]; p = 0.01).

A study from Finland [35] (662 cases) reported an increase in mean birthweight in cases compared with controls in males (3.7 vs 3.6 kg, respectively; p = 0.04) and in females (3.6 vs 3.5 kg, respectively; p = 0.49). A study from Denmark (with 839 cases) reported no significant difference in birthweight between cases and controls. Finally, two other studies, one from Hungary [29] and one from USA [40], reported little evidence of a difference, but contained relatively few cases (163 and 103, respectively).

Discussion

This meta-analysis demonstrates a consistent, but relatively small increase in the risk of type 1 diabetes in children who are heavier at birth. This increase in diabetes risk was more marked in studies with a low risk of bias. The association could not be explained by the confounding influence of gestational age, maternal age, birth order, Caesarean section, maternal diabetes or breastfeeding.

The main strength of this meta-analysis is that it used individual patient data (or estimates from pre-specified analyses) from 28 studies, allowing a unified approach to the investigation of birthweight and type 1 diabetes. It also included 12,058 cases, thus providing high power to identify associations of relatively small magnitude and allowing reliable subgroup analyses.

Although data were not available from five of the 34 studies identified, in the largest of these [30], approximate results could be extracted from a figure and were consistent with our main finding (as demonstrated by sensitivity analysis). Our search strategy was comprehensive, but it is nevertheless possible that other studies containing relevant data were not identified. Such studies, moreover, would have to be large and to have observed markedly different associations to influence our overall findings. Another potential weakness is that the birthweight association could only be adjusted uniformly for gestational age using the categories less than 38 weeks, 38 to 41 weeks and greater than 41 weeks; however, in 11 studies with available and complete gestational age information, the association with birthweight was little altered after adjustments based upon much finer categories (≤36, 37–38, 39, 40, ≥41 weeks).

A previous meta-analysis of birthweight and type 1 diabetes [45] included fewer studies than ours (and based its estimate for high birthweight upon ten studies only, whereas ours was based on 29 studies). Compared with our analysis, that previous work observed a slightly more marked 17% increase in diabetes risk in children weighing over 4.0 kg at birth, relative to children weighing under 4.0 kg (prior to adjustment for confounders). Although reported for ‘orientating purposes only’ [45, 46], the less comprehensive approach of that previous study to adjustment for various confounders produced a much more marked effect of birthweight, suggesting a 43% increase in diabetes risk (based on six studies). In contrast, our analysis, using individual patient data from 29 studies with no duplicated data [47], demonstrates that confounding by various perinatal factors (such as gestational age, maternal age, birth order, Caesarean section, maternal diabetes or breastfeeding) has little influence on the birthweight association.

The mechanism behind the observed association between birthweight and type 1 diabetes remains unknown. Although our finding for birthweight remained after adjustment for various potential confounders (such as gestational age, maternal age, birth order, breastfeeding, Caesarean section delivery and maternal diabetes), it is impossible, as with all observational studies, to rule out residual confounding and it seems unlikely that birthweight plays a direct causal role. It is more probable that birthweight is a marker for some unknown exposure or exposures that influence type 1 diabetes risk such as maternal nutrition, maternal body weight or maternal diseases [5]. Ethnicity is also a possible confounder, as children born to Asian mothers, who are likely to be lighter at birth [48], also have a lower risk of type 1 diabetes [1]. It seems unlikely, however, that in these predominantly European populations this could explain the entirety of the observed association.

The observed association between type 1 diabetes and birthweight is supported by two animal studies. A recent experimental study in NOD mice demonstrated that calorific restriction during pregnancy resulted in reduced birthweight, leading to reduced risk of diabetes by 24 weeks [49]. Also an observational study in BioBreeding rats demonstrated a higher risk of diabetes with increased birthweight [50]. However, care should be taken when extrapolating animal results for aetiological factors to humans.

As fetal insulin is an important growth factor, children with greater intrauterine growth and consequently higher birthweight have pancreatic beta cells which secrete insulin more actively [51]. In vitro and other evidence shows that actively insulin-secreting beta cells are more prone to destruction via various mechanisms such as susceptibility to interleukin 1-beta and increased levels of islet antigens [52]. Further experimental animal data have been reviewed and potential mechanisms previously discussed [53]. A number of studies have found postnatal body size or growth to be associated with risk of type 1 diabetes [54, 55]. Consequently, it is possible, and worth further investigation, that the observed association between birthweight and type 1 diabetes may somehow be mediated via postnatal growth. It is also possible that some unknown genetic factor predisposes to high birthweight and increased risk of type 1 diabetes. Although one study [56] has demonstrated that established type 1 diabetes high-risk HLA genotypes are associated with higher birthweight in the general population, another [57], which recorded established HLA and insulin gene polymorphisms, demonstrated that the observed association between type 1 diabetes and birthweight was independent of these genetic factors.

Our study suggests that the association between type 1 diabetes and birthweight is similar in children diagnosed under 5 years and in those diagnosed between 5 and 15 years of age. However, the observed association between childhood-onset type 1 diabetes and birthweight may not hold for adult-onset type 1 diabetes, as two large studies [58, 59] investigating type 1 diabetes diagnosed in young adults have shown little evidence of association with birthweight.

In conclusion, children who are heavier at birth have a significant and consistent increase in their risk of type 1 diabetes. However this increase is relatively small in magnitude and suggests that increasing trends in birthweight explain little of the rise in type 1 diabetes incidence currently being observed in many countries [3].

Notes

Acknowledgements

The authors acknowledge support for the conduct of the original studies from the following: the Czech Republic Ministry of Education (grant MSM 0021620814), the Department of Health in Taiwan (grant DOH 92-TD1052), Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (grant 94/0943-0), the Centro Internazionale Studi Diabete (Italy, Rome), The Swedish Child Diabetes Foundation, the NHS National Coordinating Centre for Research Capacity Development UK, the Research Council of Norway, the German Research Foundation (grant HE 234/1-1), the Ministry for Science and Technological Development of Serbia (number 145084, 2006-2010), EUBIROD (funded by the European Commission Health Information Strand, DG-SANCO 2005, contract number 2007115), Diabetes UK and the Northern Ireland Department of Health and Social Services. Thanks also to G. Soltész (University of Pecs, Pecs, Hungary) and G. Dahlquist (Umeå University, Umeå, Sweden), the co-ordinators of the EURODIAB Substudy 2. We also thank M. Jané (Department of Health, Barcelona, Spain).

Duality of interest

The authors declare that there is no duality of interest associated with this manuscript.

Supplementary material

125_2009_1648_MOESM1_ESM.pdf (42 kb)
ESM Fig. 1(PDF 41 kb)

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • C. R. Cardwell
    • 1
  • L. C. Stene
    • 2
    • 3
  • G. Joner
    • 3
    • 4
  • E. A. Davis
    • 5
  • O. Cinek
    • 6
  • J. Rosenbauer
    • 7
  • J. Ludvigsson
    • 8
  • C. Castell
    • 9
  • J. Svensson
    • 10
  • M. J. Goldacre
    • 11
  • T. Waldhoer
    • 12
  • J. Polanska
    • 13
  • S. G. A. Gimeno
    • 14
  • L.-M. Chuang
    • 15
  • R. C. Parslow
    • 16
  • E. J. K. Wadsworth
    • 17
  • A. Chetwynd
    • 18
  • P. Pozzilli
    • 19
  • G. Brigis
    • 20
  • B. Urbonaitė
    • 21
  • S. Šipetić
    • 22
  • E. Schober
    • 23
  • C. Ionescu-Tirgoviste
    • 24
  • C. E. de Beaufort
    • 25
  • D. Stoyanov
    • 26
  • K. Buschard
    • 27
  • C. C. Patterson
    • 1
  1. 1.Centre for Public Health, School of Medicine, Dentistry and Biomedical SciencesQueen’s University BelfastBelfastUK
  2. 2.Division of EpidemiologyNorwegian Institute of Public HealthOsloNorway
  3. 3.Oslo Diabetes Research CentreOslo University HospitalOsloNorway
  4. 4.Faculty of MedicineUniversity of OsloOsloNorway
  5. 5.Telethon Institute for Child Health Research, Centre for Child Health ResearchThe University of Western AustraliaPerthAustralia
  6. 6.The 2nd Medical SchoolCharles UniversityPragueCzech Republic
  7. 7.Institute of Biometrics and Epidemiology, German Diabetes CentreLeibniz Institute at Duesseldorf UniversityDuesseldorfGermany
  8. 8.Department of Paediatrics and Diabetes Research CentreLinkoping UniversityLinkopingSweden
  9. 9.Department of HealthAdvisory Committee on Diabetes in CataloniaBarcelonaSpain
  10. 10.Pediatric DepartmentGlostrup University HospitalGlostrupDenmark
  11. 11.Department of Public HealthOxford UniversityOxfordUK
  12. 12.Department of EpidemiologyMedical University of ViennaViennaAustria
  13. 13.Faculty of Automatic Control, Electronics and Computer ScienceSilesian University of TechnologyGliwicePoland
  14. 14.Preventive Medicine DepartmentFederal University of São PauloSão PauloBrazil
  15. 15.Department of Internal MedicineNational Taiwan University HospitalTaipeiTaiwan
  16. 16.Paediatric Epidemiology GroupUniversity of LeedsLeedsUK
  17. 17.Centre for Occupational and Health PsychologyCardiff UniversityCardiffUK
  18. 18.Mathematics and Statistics DepartmentLancaster UniversityLancasterUK
  19. 19.University Campus Bio-MedicoRomeItaly
  20. 20.Department of Public Health and EpidemiologyRiga Stradins UniversityRigaLatvia
  21. 21.Institute of EndocrinologyKaunas University of MedicineKaunasLithuania
  22. 22.Institute of Epidemiology, School of MedicineBelgrade UniversityBelgradeSerbia
  23. 23.Department of PaediatricsMedical University of ViennaViennaAustria
  24. 24.Nutrition and Metabolic Diseases ClinicN. Paulescu Institute of DiabetesBucharestRomania
  25. 25.Clinique PédiatriqueLuxembourgLuxembourg
  26. 26.Children’s Diabetic CentreSofiaBulgaria
  27. 27.Bartholin InstituttetRigshospitaletCopenhagenDenmark

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