Background: Prostate cancer has a strong hereditary component, but it has been proposed that hormonal influences in utero may contribute to offspring risk. We investigated the associations between birth characteristics and the risk of prostate cancer in twins, and whether possible associations could be confounded by familial factors, such as shared environment and common genes.

Methods: All like-sexed male twins in the Swedish Twin Registry, born from 1926 to 1958 and alive in 1973, were eligible. Data were obtained from birth records, and 11,420 male twins with reliable birth weight data were included in the final study population. Hazard ratios with 95% confidence intervals (CI) from Cox regression models were used to estimate associations between birth characteristics and risk of prostate cancer. Paired analysis was done to account for potential confounding by familial factors.

Results: Compared with twins with a birth weight of 2,500 to 2,999 g, the hazard ratio (95% CI) for twins with a higher birth weight (≥3,000 g) corresponded to 1.22 (0.94-1.57). In analyses within twin pairs, in which both twins had a birth weight of ≥2,500 g, a 500 g increase in birth weight was associated with an increased risk of prostate cancer within dizygotic twin pairs (odds ratio, 1.41; 95% CI, 1.02-1.57), but not within monozygotic twin pairs (odds ratio, 1.06; 95% CI, 0.61-1.84).

Conclusions: High birth weight is associated with an increased risk of prostate cancer. The difference in risk within dizygotic and monozygotic twin pairs may be due to genetic factors playing an important role in this association. (Cancer Epidemiol Biomarkers Prev 2009;18(9):2422–6)

Prostate cancer has a strong genetic component (1), and a number of specific genetic factors associated with prostate cancer risk have recently been detected (2). In addition, prostate cancer is a hormone-dependent cancer, and it has been proposed that hormonal influences in utero may contribute to offspring risk (3). Birth weight can, especially when adjusted for gestational age, be considered a proxy for fetal growth. As such, birth weight may be used as an indirect marker for fetal exposure to growth-stimulating factors such as insulin-like growth factors (4-6) and estrogens (7-9), which may also be involved in the carcinogenesis of reproductive cancer diseases (10, 11). High birth weight is associated with breast cancer (12), whereas the association between birth weight and prostate cancer is less certain (13-18).

Fetal growth is, like prostate cancer, largely determined by genetic factors (19). If the same genes influence fetal growth and prostate cancer, a possible association between birth weight and prostate cancer may be confounded by genetic factors. Twin studies enable unique possibilities to study whether the association between exposure and disease is influenced by shared environment and common genes: all twin siblings share intrauterine and early environment, dizygotic twins share, on average, half of their segregating genes and monozygotic twins share all genes. We analyzed information on birth characteristics from birth records in like-sexed male twins with known zygosity to investigate the association between birth weight and risk of prostate cancer, and whether a possible association is confounded by genetic and/or shared environmental factors in early life.

Study Population

The Swedish Twin Registry is a population-based registry of twins born in Sweden since 1886 (20). In 1973, all like-sexed twins born from 1926 to 1958 were sent a paper-based questionnaire, including questions of degree of likeness, anthropometric measures, and lifestyle factors. The response rate was 81% (20-22). In this study, we restricted the cohort to male twins with known zygosity, as determined by questions on childhood resemblance. Self-reported zygosity has been validated with DNA markers in a subsample of 199 twin pairs, and was proven correct in 99% of the twin pairs (20). The person-unique national registration number, assigned to all Swedish citizens, permitted linkage between the Swedish Twin Registry, the Cancer and Cause of Death Registers, and also enabled us to retrieve information from birth records.

The study was approved by the research ethics committee of the Karolinska Institutet.

Outcome

Information about prostate cancer was retrieved from the population-based Swedish Cancer Register, which includes information from all primary incident cancers in Sweden since 1958. Reporting is mandatory for physicians as well as pathologists and cytologists separately, and 99% of the registered cancers in 2006 have been morphologically verified (23). The registry roughly covers 95% of all cancers reported in the Cause of Death Registry (23, 24), the deficit mainly represented by patients over 75 years of age. The cancers are classified according to the International Classification of Diseases (ICD). Prostate cancer cases were recorded during the time of follow-up (from 1973 to 2006) and identified from the Swedish Cancer Register (ICD-7 code 177, ICD-8 and ICD-9 code 185, and ICD-10 code C61). We found no cases whose underlying cause of death was reported to be prostate cancer in the Cause of Death Register that were not reported in the Swedish Cancer Register. Reports of death in the Cause of Death Register have been computerized since 1952, and are considered reliable from 1961 onwards (25).

Exposures

Information about maternal and birth characteristics were documented at birth by the attending midwife, and recording and preservation of birth records is enforced by law. We retrieved information from original birth records by visiting delivery archives, located all over Sweden. Correct birth identification of each twin within a pair was ensured by restricting the data collection to twin pairs who were both baptized and named at birth, or who reported birth order with mutual within-pair agreement in a telephone interview, conducted in 1998 to 2002 (26). Information from birth records included anthropometric measures at birth, gestational age, maternal age, parity, and occupational status of both parents. Gestational age was based on the date of the first day of the last menstrual period. Socioeconomic status at birth was based on information of parental occupation, and was classified according to the recommendations by Statistics Sweden (27).

For this study, all like-sexed male twins with known zygosity born from 1926 to 1958, were considered. In the 15,418 males who were alive and without previous prostate cancer diagnosis at the start of follow-up in 1973, the birth record coverage was 74%. Restrictions were due to missing birth weight data in birth records (N = 2,809) and not certain correct identification of each twin within a twin pair at birth (N = 1,189), resulting in a final study population of 11,420 twins (including 5,622 intact twin pairs).

Statistical Analyses

Risk time (person-years) was accrued from the time of entry (January 1, 1973) until a first diagnosis of prostate cancer, or censored at the date of first emigration from Sweden, death, or end of follow-up (December 31, 2006). Cox proportional hazard models were used to estimate hazard ratios (HR) for prostate cancer, with age (measured in months) as the underlying time scale, and robust SE estimates to account for the dependence within twin pairs. The proportional hazards assumption was verified by plotting of scaled Schoenfeld residuals. Splines were used to investigate whether there is a linear relationship between birth weight and risk for prostate cancer.

We calculated age-adjusted incidence rates for prostate cancer for zygosity, birth weight, gestational age, mother's age at delivery, parity, and parental socioeconomic status at birth. Variables were categorized according to Table 1. In the cohort analyses, we first estimated age-adjusted HRs of prostate cancer. Thereafter, we adjusted for gestational age and zygosity (Table 2). Analyses were done in PROC PHREG in SAS 9.2 and R v2.80 survival pack.

Table 1.

Numbers and incidence rates of prostate cancer as a function of birth characteristics among like-sexed Swedish twins born from 1926 to 1958

Study populationProstate cancer
Nn%Incidence rate*
Total 11,420 382 3.3 10.0 
Zygosity 
    Monozygous 4,313 147 3.4 10.6 
    Dizygous 7,107 235 3.3 9.7 
Birth year 
    1926-1936 2,038 195 9.6 7.6 
    1937-1943 2,438 101 4.1 6.9 
    1944-1950 3,416 68 2.0 5.7 
    1951-1958 3,528 18 0.5 2.6 
Birth weight (g) 
    <2,500 3,882 132 3.4 10.4 
    2,500-2,999 4,143 121 2.9 8.9 
    ≥3,000 3,395 129 3.8 10.9 
Gestational age (wk) 
    32-34 1,498 56 3.7 12.4 
    35-36 2,342 73 3.1 9.4 
    37-41 6,686 230 3.4 10.4 
    42-45 358 2.0 5.9 
    Missing 536 16 3.0 6.1 
Mother's age (y) 
    <20 285 10 3.5 11.4 
    20-24 1,830 54 3.0 9.7 
    25-29 3,493 98 2.8 8.3 
    30-34 3,138 125 4.0 12.1 
    >34 2,666 95 3.6 9.9 
    Missing 0.0 0.0 
Maternal parity 
    Primipara 3,427 111 3.2 9.4 
    Multipara 7,875 268 3.4 10.4 
    Missing 118 2.5 4.9 
Parental socioeconomic status at birth 
    Blue-collar worker     
    Unskilled 3,164 82 2.6 9.1 
    Skilled 1,768 59 3.3 13.0 
White-collar worker 
    Low level 935 19 2.0 8.8 
    Intermediate level 891 24 2.7 14.6 
    High level 418 17 4.1 26.8 
Self-employed 1,446 43 3.0 10.9 
Missing 2,798 138 4.9 8.4 
Study populationProstate cancer
Nn%Incidence rate*
Total 11,420 382 3.3 10.0 
Zygosity 
    Monozygous 4,313 147 3.4 10.6 
    Dizygous 7,107 235 3.3 9.7 
Birth year 
    1926-1936 2,038 195 9.6 7.6 
    1937-1943 2,438 101 4.1 6.9 
    1944-1950 3,416 68 2.0 5.7 
    1951-1958 3,528 18 0.5 2.6 
Birth weight (g) 
    <2,500 3,882 132 3.4 10.4 
    2,500-2,999 4,143 121 2.9 8.9 
    ≥3,000 3,395 129 3.8 10.9 
Gestational age (wk) 
    32-34 1,498 56 3.7 12.4 
    35-36 2,342 73 3.1 9.4 
    37-41 6,686 230 3.4 10.4 
    42-45 358 2.0 5.9 
    Missing 536 16 3.0 6.1 
Mother's age (y) 
    <20 285 10 3.5 11.4 
    20-24 1,830 54 3.0 9.7 
    25-29 3,493 98 2.8 8.3 
    30-34 3,138 125 4.0 12.1 
    >34 2,666 95 3.6 9.9 
    Missing 0.0 0.0 
Maternal parity 
    Primipara 3,427 111 3.2 9.4 
    Multipara 7,875 268 3.4 10.4 
    Missing 118 2.5 4.9 
Parental socioeconomic status at birth 
    Blue-collar worker     
    Unskilled 3,164 82 2.6 9.1 
    Skilled 1,768 59 3.3 13.0 
White-collar worker 
    Low level 935 19 2.0 8.8 
    Intermediate level 891 24 2.7 14.6 
    High level 418 17 4.1 26.8 
Self-employed 1,446 43 3.0 10.9 
Missing 2,798 138 4.9 8.4 

*Age-adjusted incidence rates per 10,000 person-years.

Table 2.

Unadjusted and adjusted HRs of prostate cancer in relation to birth weight in the cohort analyses of Swedish like-sexed twins born from 1926 to 1958

Study populationProstate cancerHR (95% confidence interval)
Crude*Adjusted for birth characteristics
Birth weight (g)Nn%(n = 11,420)(n = 10,884)
    <2,500 3,882 132 3.4 1.16 (0.91-1.48) 1.12 (0.86-1.46) 
    2,500-2,999 4,143 121 2.9 1.00 1.00 
    ≥3,000 3,395 129 3.8 1.22 (0.96-1.56) 1.22 (0.94-1.57) 
Study populationProstate cancerHR (95% confidence interval)
Crude*Adjusted for birth characteristics
Birth weight (g)Nn%(n = 11,420)(n = 10,884)
    <2,500 3,882 132 3.4 1.16 (0.91-1.48) 1.12 (0.86-1.46) 
    2,500-2,999 4,143 121 2.9 1.00 1.00 
    ≥3,000 3,395 129 3.8 1.22 (0.96-1.56) 1.22 (0.94-1.57) 

NOTE: All analyses accounted for the clustered data structure and between-cluster effect.

*Age-adjusted HRs.

Also adjusted for gestational age and zygosity.

Studies within twin pairs enable us to study associations between exposure and disease, controlling for familial (shared environmental and genetic) factors. In paired analyses (Table 3), the birth weight exposure is replaced by the twin pair mean birth weight (xij) and the individual deviance from the twin mean birth weight (xijxj; ref. 28). In twins, this latter “within-component” can be considered an approximation of growth that is independent of familial factors (shared by the twins). Thus, if the risk of prostate cancer is similar for the deviance from the twin mean birth weight as for the effect of birth weight in the cohort, this would lend support to the hypothesis that the association between birth weight and prostate cancer is independent of familial factors. A decrease in the estimated effect would indicate confounding by familial factors, the nature of which could be further elucidated by looking at zygotic groups separately. All twins share early environment, dizygotic twins share, on average, 50% of their segregating genes, whereas monozygotic twins share 100% of their segregating genes. If the effect of the within-component is smaller in monozygotic twins compared with dizygotic twins, this indicates that confounding is more related to genetic than to shared environmental factors.

Table 3.

Odds ratios of prostate cancer related to a 500 g increase in birth weight within twin pairs

Effect of 500 g increase in birth weightNOdds ratio (95% confidence interval)
Within dizygous pairs 7,107 1.25 (0.96-1.62) 
Within monozygous pairs 4,313 1.12 (0.79-1.59) 
Within pairs >2,500 g   
    Within dizygous pairs 4,819 1.41 (1.02-1.95) 
    Within monozygous pairs 2,456 1.06 (0.61-1.84) 
Effect of 500 g increase in birth weightNOdds ratio (95% confidence interval)
Within dizygous pairs 7,107 1.25 (0.96-1.62) 
Within monozygous pairs 4,313 1.12 (0.79-1.59) 
Within pairs >2,500 g   
    Within dizygous pairs 4,819 1.41 (1.02-1.95) 
    Within monozygous pairs 2,456 1.06 (0.61-1.84) 

NOTE: The analysis has accounted for the clustered data structure and between-cluster effect.

The paired analysis assumes a linear effect of the exposure. Finding a not strictly linear relationship between birth weight and prostate cancer between twins, we proceeded with the paired analyses in the subgroup of twins born above 2,500 g.

In the cohort of 11,420 male twins, 382 developed prostate cancer during the time of follow-up. Table 1 shows the distribution of birth characteristics in relation to age-adjusted incidence rates of prostate cancer. The incidence rate was higher in older compared with younger birth cohorts. The incidence rate of prostate cancer was lower among men with a birth weight between 2,500 and 2,999 g than among men with higher or lower birth weight.

The nonlinear relationship between birth weight and risk of prostate cancer is illustrated in Fig. 1. In the spline model, the association between birth weight and risk of prostate cancer started to increase from ∼3,000 g.

Figure 1.

Splines showing the relationship between birth weight and prostate cancer risk.

Figure 1.

Splines showing the relationship between birth weight and prostate cancer risk.

Close modal

Table 2 show birth weight categories and HRs of prostate cancer. Compared with males with birth weights of 2,500 to 2,999 g, males with lower but especially higher birth weight had slightly increased risks of prostate cancer in the age-adjusted model. The association between birth weight and risk of prostate cancer remained essentially unchanged when we also adjusted for gestational age and zygosity.

Next, we wanted to investigate whether familial (genetic or shared environmental) factors influenced the association between birth weight and prostate cancer risk. Table 3 shows the effect of a 500 g increase in birth weight on prostate cancer risk within twin pairs. Within dizygotic twin pairs, the risk of prostate cancer increased with birth weight: a 500 g increase in birth weight was associated with a 25% increased risk of prostate cancer, whereas corresponding increase within monozygotic twins was 12%. Given that the risk of prostate cancer started to increase from ∼3,000 g (Fig. 1), we also restricted the analyses to twin pairs, in which both twins had a birth weight of ≥2,500 g. We found that a 500 g increase in birth weight was associated with a 41% increased risk within dizygotic twins. These results were in contrast with the results within monozygotic twins, in which corresponding risk was not increased (Table 3). When we formally tested for an interaction between birth weight and zygosity with regard to the risk of prostate cancer, the interaction was not significant (P = 0.61).

We found that an increase in birth weight was associated with a modestly increased risk of prostate cancer within dizygotic (fraternal) but not within monozygotic (genetically identical) twin pairs. These findings suggest a genetic background for the association between birth weight and prostate cancer risk.

In the cohort analysis, we found evidence of a nonlinear relationship between birth weight and prostate cancer, with increasing risks especially among offspring with birth weights from ∼3,000 g. Given the generally reduced birth weight in twins, we had limited possibilities to study the effects of high birth weight on prostate cancer risk. We also observed a modest nonsignificant risk increase related to low birth weight (odds ratio, 1.12; Table 2), which does not agree with the observation that prenatal exposure to preeclampsia (which reduces fetal growth) is, if anything, associated with a reduced risk of prostate cancer in offspring (14, 15).

Our finding, that high birth weight may be associated with a modestly increased risk of prostate cancer in the twin cohort, has previously been reported. A strong positive association between birth weight and prostate cancer was initially reported by a Swedish cohort study, only including 21 cases of prostate cancer (18). Later, a Swedish study found nonsignificant positive associations between high birth weight and risk of prostate cancer (14) and a Norwegian study found a positive association between increasing birth length and risk of metastatic prostate cancer (16). However, in two studies from the United States and in one Swedish study, there was no overall support for an association (13, 15, 17), although one of the studies could not rule out a modest positive association between birth weight and high stage/grade prostate cancer (17). Differences in study size and designs may account for these discrepant results.

Given that both fetal growth (19) and prostate cancer (1) have strong genetic components, we did a twin study, which allowed us to investigate whether a possible association between birth weight and prostate cancer may be confounded by genetic factors. Our findings of a positive association within dizygotic (fraternal) twins and a lack of association within monozygotic twins support the hypothesis of genetic confounding. We acknowledge that our results were hampered by statistical power and need to be confirmed. Still, because genetic confounding was our a priori hypothesis, we feel entitled to speculate about possible underlying reasons.

Genetic factors could be important for the association between high birth weight and prostate cancer in several ways. A locus in the HNF1B gene in chromosome 17 has repeatedly been associated with increased risk of prostate cancer (29, 30). This gene is also associated with reduced risk of type 2 diabetes (29), and we recently reported that the association between low birth weight and risk of type 2 diabetes may be explained by genetic factors (31). Type 2 diabetes has also been reported to reduce the risk of prostate cancer (32). Thus, it is plausible that the same set of genetic factors contribute to the association between high birth weight and increased prostate cancer risk and to the association between low birth weight and increased risk of type 2 diabetes. As far as we know, it has not been studied whether the locus in the HNF1B gene in chromosome 17 is connected to the regulation of fetal growth. In addition, genotypes related to reduced insulin secretion or insulin resistance has been associated with both low birth weight and glucose intolerance (33), whereas corresponding associations with prostate cancer are less certain (11).

Our study of twins offers a major advantage as the associations in the within-pair analyses were not confounded by unmeasured shared environmental or socioeconomic influences and, in monozygotic twins, they were also independent of genetic factors. Furthermore, differences in birth weight within twin pairs reflect differences in fetal growth. Information on perinatal and parental sociodemographic characteristics was retrieved from original birth records, which precludes recall bias on the exposures.

Our cohort analysis was limited in number of prostate cancer cases, and a hampered statistical power was obvious from the wide confidence intervals. We also acknowledge that we cannot exclude the possibility that the association between birth weight and risk of prostate cancer within dizygotic, but not within monozygotic twin pairs, is due to chance. However, the lack of a significant interaction between birth weight and zygosity could also be explained by the small sample size.

The generalizability of results from twin studies may be questionable because twins are, in general, more growth-restricted than singletons, have shorter gestational age, and because they may differ in prenatal environment and upbringing. However, the incidence of prostate cancer does not seem to be different in twins compared with singletons (34). An important question is also whether results within dizygotic and monozygotic twin pairs can be compared. Dizygotic twin pairs have two placentas, whereas 70% of monozygotic twins are monochorionotic, i.e., they share one placenta. Unequal sharing of the placenta is also a primary contributor of birth weight discordance within monochorionotic (monozygotic) twin pairs (35). This suggests that the etiology behind birth weight discordance is similar and due to placental constraint in both dizygotic and monozygotic twin pairs.

To our knowledge, no previous study has investigated the association between birth weight and prostate cancer in a genetically informative population, such as like-sexed twins with known zygosity. We found a positive association between birth weight and prostate cancer within dizygotic but not within monozygotic twins, suggesting that this association may be confounded by genetic factors. Together with recent progress in genetic cancer research, our findings lend support to the hypothesis of an interaction between prostate cancer–regulating genes and the intrauterine environment with respect to prostate cancer development.

No potential conflicts of interest were disclosed.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1
Lichtenstein
P
,
Holm
NV
,
Verkasalo
PK
, et al
. 
Environmental and heritable factors in the causation of cancer—analyses of cohorts of twins from Sweden, Denmark, and Finland
.
N Engl J Med
2000
;
343
:
78
85
.
2
Sun
J
,
Turner
A
,
Xu
J
,
Gronberg
H
,
Isaacs
W
. 
Genetic variability in inflammation pathways and prostate cancer risk
.
Urol Oncol
2007
;
25
:
250
9
.
3
Ross
RK
,
Henderson
BE
. 
Do diet and androgens alter prostate cancer risk via a common etiologic pathway?
J Natl Cancer Inst
1994
;
86
:
252
4
.
4
Osorio
M
,
Torres
J
,
Moya
F
, et al
. 
Insulin-like growth factors (IGFs) and IGF binding proteins-1, -2, and -3 in newborn serum: relationships to fetoplacental growth at term
.
Early Hum Dev
1996
;
46
:
15
26
.
5
Ong
K
,
Kratzsch
J
,
Kiess
W
,
Costello
M
,
Scott
C
,
Dunger
D
. 
Size at birth and cord blood levels of insulin, insulin-like growth factor I (IGF-I), IGF-II, IGF-binding protein-1 (IGFBP-1), IGFBP-3, and the soluble IGF-II/mannose-6-phosphate receptor in term human infants. The ALSPAC Study Team. Avon Longitudinal Study of Pregnancy and Childhood
.
J Clin Endocrinol Metab
2000
;
85
:
4266
9
.
6
Christou
H
,
Connors
JM
,
Ziotopoulou
M
, et al
. 
Cord blood leptin and insulin-like growth factor levels are independent predictors of fetal growth
.
J Clin Endocrinol Metab
2001
;
86
:
935
8
.
7
Kaijser
M
,
Granath
F
,
Jacobsen
G
,
Cnattingius
S
,
Ekbom
A
. 
Maternal pregnancy estriol levels in relation to anamnestic and fetal anthropometric data
.
Epidemiology
2000
;
11
:
315
9
.
8
Petridou
E
,
Panagiotopoulou
K
,
Katsouyanni
K
,
Spanos
E
,
Trichopoulos
D
. 
Tobacco smoking, pregnancy estrogens, and birth weight
.
Epidemiology
1990
;
1
:
247
50
.
9
Mucci
LA
,
Lagiou
P
,
Tamimi
RM
,
Hsieh
CC
,
Adami
HO
,
Trichopoulos
D
. 
Pregnancy estriol, estradiol, progesterone and prolactin in relation to birth weight and other birth size variables (United States)
.
Cancer Causes Control
2003
;
14
:
311
8
.
10
Hankinson
S
,
Tamini
R
,
Hunter
D
. 
Breast cancer
. In:
Adami
H-O
,
Hunter
D
,
Trichopoulos
D
, editors.
Textbook of cancer epidemiology
. 2nd ed.:
Oxford University Press
; 
2008
, p.
403
45
.
11
Mucci
L
,
Signorello
LB
,
Adami
H-O
. 
Prostate cancer
. In:
Adami
HO
,
Hunter
D
,
Trichopoulos
D
, editors.
Textbook of cancer epidemiology
. 2nd ed.:
Oxford University Press
; 
2008
, p.
517
54
.
12
Silva Idos
S
,
De Stavola
B
,
McCormack
V
. 
Birth size and breast cancer risk: re-analysis of individual participant data from 32 studies
.
PLoS Med
2008
;
5
:
e193
.
13
Boland
LL
,
Mink
PJ
,
Bushhouse
SA
,
Folsom
AR
. 
Weight and length at birth and risk of early-onset prostate cancer (United States)
.
Cancer Causes Control
2003
;
14
:
335
8
.
14
Ekbom
A
,
Hsieh
CC
,
Lipworth
L
, et al
. 
Perinatal characteristics in relation to incidence of and mortality from prostate cancer
.
Br Med J
1996
;
313
:
337
41
.
15
Ekbom
A
,
Wuu
J
,
Adami
HO
, et al
. 
Duration of gestation and prostate cancer risk in offspring
.
Cancer Epidemiol Biomarkers Prev
2000
;
9
:
221
3
.
16
Nilsen
TI
,
Romundstad
PR
,
Troisi
R
,
Vatten
LJ
. 
Birth size and subsequent risk for prostate cancer: a prospective population-based study in Norway
.
Int J Cancer
2005
;
113
:
1002
4
.
17
Platz
EA
,
Giovannucci
E
,
Rimm
EB
, et al
. 
Retrospective analysis of birth weight and prostate cancer in the Health Professionals Follow-up Study
.
Am J Epidemiol
1998
;
147
:
1140
4
.
18
Tibblin
G
,
Eriksson
M
,
Cnattingius
S
,
Ekbom
A
. 
High birthweight as a predictor of prostate cancer risk
.
Epidemiology
1995
;
6
:
423
4
.
19
Svensson
AC
,
Pawitan
Y
,
Cnattingius
S
,
Reilly
M
,
Lichtenstein
P
. 
Familial aggregation of small-for-gestational-age births: the importance of fetal genetic effects
.
Am J Obstet Gynecol
2006
;
194
:
475
9
.
20
Lichtenstein
P
,
de Faire
U
,
Floderus
B
,
Svartengren
M
,
Svedberg
P
,
Pedersen
NL
. 
The Swedish Twin Registry: a unique resource for clinical, epidemiological and genetic studies
.
J Intern Med
2002
;
252
:
184
205
.
21
Cederlof
R
,
Friberg
L
,
Jonsson
E
,
Kaij
L
. 
Studies on similarity diagnosis in twins with the aid of mailed questionnaires
.
Acta Genet Stat Med
1961
;
11
:
338
62
.
22
Crumpacker
DW
,
Cederlof
R
,
Friberg
L
, et al
. 
A twin methodology for the study of genetic and environmental control of variation in human smoking behavior
.
Acta Genet Med Gemellol (Roma)
1979
;
28
:
173
95
.
23
Cancer incidence in Sweden 2006
.
The National Board of Health and Welfare, Stockholm
:
Centre for Epidemiology
; 
2007
.
24
Mattsson
B
,
Wallgren
A
. 
Completeness of the Swedish Cancer Register. Non-notified cancer cases recorded on death certificates in 1978
.
Acta Radiol Oncol
1984
;
23
:
305
13
.
25
The Swedish Cause of Death Registry [in Swedish]
.
National Board of Health and Welfare, Stockholm
:
Centre for Epidemiology
; 
2008
.
26
Bergvall
N
,
Iliadou
A
,
Johansson
S
, et al
. 
Genetic and shared environmental factors do not confound the association between birth weight and hypertension: a study among Swedish twins
.
Circulation
2007
;
115
:
2931
8
.
27
Swedish Socioeconomic Classification
.
Stockholm, Sweden
:
Statistics Sweden
; 
1983
.
28
Carlin
JB
,
Gurrin
LC
,
Sterne
JA
,
Morley
R
,
Dwyer
T
. 
Regression models for twin studies: a critical review
.
Int J Epidemiol
2005
;
34
:
1089
99
.
29
Gudmundsson
J
,
Sulem
P
,
Steinthorsdottir
V
, et al
. 
Two variants on chromosome 17 confer prostate cancer risk, and the one in TCF2 protects against type 2 diabetes
.
Nat Genet
2007
;
39
:
977
83
.
30
Sun
J
,
Zheng
SL
,
Wiklund
F
, et al
. 
Evidence for two independent prostate cancer risk-associated loci in the HNF1B gene at 17q12
.
Nat Genet
2008
;
40
:
1153
5
.
31
Johansson
S
,
Iliadou
A
,
Bergvall
N
, et al
. 
The association between low birth weight and type 2 diabetes: contribution of genetic factors
.
Epidemiology
2008
;
19
:
659
65
.
32
Gong
Z
,
Neuhouser
ML
,
Goodman
PJ
, et al
. 
Obesity, diabetes, and risk of prostate cancer: results from the prostate cancer prevention trial
.
Cancer Epidemiol Biomarkers Prev
2006
;
15
:
1977
83
.
33
Hattersley
AT
,
Tooke
JE
. 
The fetal insulin hypothesis: an alternative explanation of the association of low birthweight with diabetes and vascular disease
.
Lancet
1999
;
353
:
1789
92
.
34
Verkasalo
PK
,
Kaprio
J
,
Koskenvuo
M
,
Pukkala
E
. 
Genetic predisposition, environment and cancer incidence: a nationwide twin study in Finland, 1976-1995
.
Int J Cancer
1999
;
83
:
743
9
.
35
Fick
AL
,
Feldstein
VA
,
Norton
ME
,
Wassel Fyr
C
,
Caughey
AB
,
Machin
GA
. 
Unequal placental sharing and birth weight discordance in monochorionic diamniotic twins
.
Am J Obstet Gynecol
2006
;
195
:
178
83
.