Low Birth Weight and High Birth Weight
Infants Are Both at an Increased Risk to
Have Type 2 Diabetes Among
Schoolchildren in Taiwan
JUNG-NANWEI,PHD1FUNG-CHANGSUNG,PHD1 CHUNG-YILI,PHD2
CHIA-HSUINCHANG,MD, MSC3
RUEY-SHIUNGLIN,MD, DRPH1 CHAU-CHINGLIN,MD4 CHUAN-CHICHIANG,PHD4 LEE-MINGCHUANG,MD, PHD1,3,5
OBJECTIVE — To study the effect of birth weight on risk of type 2 diabetes in the
school-children in Taiwan.
RESEARCH DESIGN AND METHODS — From 1992 to 1997, all schoolchildren aged
6 –18 years were screened for diabetes in Taiwan Province. This cohort consisted of 1,966 patients with diabetes and 1,780 randomly selected subjects with normal fasting glycemia (NFG). Questionnaire interviewing was designed to classify diabetes. The birth weight was obtained from the Taiwan’s Birth Registry. After merging the data, there were 978 subjects, including 429 with type 2 diabetes and 549 with of NFG enrolled in the present analyses.
RESULTS — The odds ratios (95% CI) for type 2 diabetes, after adjusting age, sex, BMI, family
history of diabetes, and socioeconomic status, were 2.91 (1.25– 6.76) for children with low birth weight (⬍2,500 g) and 1.78 (1.04–3.06) for those with high birth weight (ⱖ4,000 g) when compared with the referent group (birth weight 3,000 –3,499 g). The risk of diabetes was still 64% higher in the high birth weight group [odds ratio (OR) 1.64 (95% CI 0.91–2.96)], even after adjustment for gestational diabetes mellitus (GDM). Patients with type 2 diabetes who were born with high birth weight were more likely to have a higher BMI and diastolic blood pressure as well as a higher family history of diabetes compared with those with low birth weight.
CONCLUSIONS — A U-shaped relationship between birth weight and risk of type 2
diabe-tes was found in the schoolchildren aged 6 –18 years in Taiwan. Schoolchildren with type 2 diabetes who were born with low birth weight had different metabolic phenotypes compared with those born with high birth weight.
Diabetes Care 26:343–348, 2003
I
nteractions between fetal growth in utero and early postnatal environmen-tal exposures have been considered pivotal to the manifestation of diabetes in later life (1– 4). Such early adaptations toa nutritional environment might lead to a permanent change in the physiology of fuel metabolism and result in the expres-sion of metabolic disturbances in adults, a process termed “metabolic programming”
(5,6). Several epidemiological studies (7– 12) suggest that, for both men and women, those born with low birth weight were at an elevated risk for type 2 diabetes and other health outcomes during adult-hood. Initial observation was made from a follow-up study in Hertfordshire, U.K., to show the prevalence of impaired glucose tolerance or type 2 diabetes at age 64 years was inversely associated with birth weight (7). Despite the strength of associ-ation, currently all published studies have showed consistent results. Similar obser-vations were recently seen in children and young adolescents (13–16).
Interestingly, studies in Pima Indians revealed a U-shaped relationship between birth weight and risk of type 2 diabetes (11). However, this relationship has not been found in other ethnic populations. This discrepancy has been attributed to a very high frequency of diabetes in Pima Indians, and therefore, gestational diabe-tes mellitus (GDM) is relatively common. Evidence suggests that the offspring of di-abetic mothers are at higher risk for dia-betes, an effect probably stemming from the influence of maternal diabetes (17– 19). Because GDM is frequently compli-cated with macrosomia (20), a link between high birth weight and risk of di-abetes can be anticipated. However, in a large study, the Nurses’ Health Study, the risk of type 2 diabetes suggested a reverse J shape. These data stress the importance to elucidate pathophysiology of pre-natal nutrition and other intrauterine environmental factors and the risk for type 2 diabetes in each of the different populations.
An increasing prevalence of child-hood and adolescent type 2 diabetes has been identified during the past decades (21). One study (22) conducted in a large diabetes clinic in the midwestern U.S. demonstrated that type 2 diabetes ac-counted for 33% of all newly diagnosed diabetics aged 10 –19 years in 1994. Type 2 diabetes has also become an epidemic in
● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● From the1
College of Public Health, School of Medicine, National Taiwan University, Taipei, Taiwan;2 Fu-Jen Catholic University, Taipei Hsien, Taiwan; the3Department of Internal Medicine, National Taiwan Univer-sity Hospital, Taipei, Taiwan; the4
Chinese Foundation of Health, Taipei, Taiwan; and the5
Graduate Insti-tute of Clinical Medicine, School of Medicine, National Taiwan University, Taipei, Taiwan.
Address correspondence and reprint requests to Lee-Ming Chuang, MD, PhD, Department of Internal Medicine, National Taiwan University Hospital, 7 Chung-Shan South Rd., Taipei, Taiwan. E-mail: leeming@ha.mc.ntu.edu.tw.
Received for publication 15 July 2002 and accepted in revised form 9 October 2002.
Abbreviations: ADA, American Diabetes Association; CFH, Chinese Foundation of Health; DBP, diastolic blood pressure; FPG, fasting plasma glucose; GDM, gestational diabetes mellitus; HNF, hepatocyte nuclear factor; IFG, impaired fasting glycemia; NFG, normal fasting glycemia; OR, odds ratio; SBP, systolic blood pressure; SES, socioeconomic status.
A table elsewhere in this issue shows conventional and Syste`me International (SI) units and conversion factors for many substances.
Asian countries. In Japan, the incidence of type 2 diabetes is estimated to be⬃2.8– 4.6 per 100,000 children per year (23– 25). In Taiwan, with the advent of a nationwide mass urine screening pro-gram for diabetes in schoolchildren in the past decade, we recruited a cohort of 1,966 subjects with diabetes and 96,548 subjects with normal fasting glycemia (NFG). In this study, we attempted to ex-plore the relationship between birth weight and development of type 2 diabe-tes and other metabolic phenotypes among schoolchildren and adolescents aged 6 –18 years via a national registry of birth weight (Taiwan’s Birth Registry).
RESEARCH DESIGN AND METHODS — From 1992 to 1997, a
mass screening program for detecting di-abetes and renal disease had been con-ducted in Taiwan, including all 21 counties and cities except the city of Tai-pei. All schoolchildren (⬃3,000,000 for each semester) from grades 1 to 12, aged 6 –18 years, underwent urine screening each semester. This program was con-ducted by the Chinese Foundation of Health (CFH) with the support from the Taiwan Provincial Department of Health and the approval from the Provincial Ed-ucation Board of Taiwan.
With consent and assistance obtained from the parents, nearly all of the students (average response rate 97%) were
in-structed to collect a midstream sample of the first morning urine. After glucosuria was confirmed in two sequential urine samples within 2 weeks, a third appoint-ment was arranged for physical examina-tion and collecexamina-tion of a fasting blood sample for determination of glucose and cholesterol levels. All blood samples were transferred to the central laboratory at the CFH headquarters. Blood glucose levels were measured by an automatic analyzer (Technican RA 2000 Serum Autoana-lyzer; Bayer Diagnostic, Tarrytown, NY). For quality control, CFH participated in the College of American Pathologists quality assurance program and won a Good Performance award. According to 1997 American Diabetes Association (ADA) recommendations (26), subjects were classified into three categories, i.e., diabetes, impaired fasting glycemia (IFG), and NFG, based on fasting plasma glu-cose (FPG) levels. These students were re-ferred for further diagnosis and care.
During this period (1992–1997), a total of 1,966 cases of diabetes were iden-tified using the 1997 ADA criteria. For comparison, 1,780 control subjects were randomly selected from all students with NFG (n⫽ 96,548). All students with ab-normal FPG were referred for clinical di-agnosis; however, there was no evidence of the classification of diabetes by their physicians. To obtain further information to classify diabetes, we performed
tele-phone questionnaire interviews with the students’ parents regarding current weight and height, parental education years, age at diagnosis of diabetes, modal-ities of diabetes therapy (diet alone, an-tidiabetic oral medication, or insulin), interval between diagnosis (screening) and initiation of insulin treatment, and family history of diabetes and hyperten-sion in first-degree relatives. Subjects were considered to have type 2 diabetes if both of the following criteria were met: 1) FPG⭌126 mg/dl at screening; and 2) cur-rent treatment with an oral hypoglycemic drug or diet control. Subjects who had received insulin injection within 3 years after diagnosis of diabetes were excluded from the study due to a possible diagnosis of type 1 diabetes or slowly progressive type 1 diabetes.
Data on birth weight and gestational age in weeks were obtained by matching the citizenship identification numbers with Taiwan’s Birth Registry, Department of Internal Affairs, Executive Yuan, Re-public of China.
Statistical analysis
Descriptive data were shown as means and SDs for a continuous variable, and Student’s t test and2test were used for assessing the differences between type 2 diabetes and NFG (Table 1). Birth weight was classified into five categories: ⬍2,500, 2,500 –2,999, 3,000 –3,499,
Table 1—Demographic and anthropometric characteristics of the subjects with type 2 diabetes and NFG
Boys Girls T2D NFG T2D NFG n 198 213 231 336 Age (years) 13.5⫾ 2.4 13.5⫾ 2.8 13.3⫾ 2.5 13.1⫾ 2.6 Birth weight (g) 3,374⫾ 655 3,348⫾ 473 3,404⫾ 641 3,252⫾ 437* Gestation weeks 39.7⫾ 1.4 39.7⫾ 1.2 39.7⫾ 1.6 39.9⫾ 0.9 SBP (mmHg) 119⫾ 18 112⫾ 14* 117⫾ 17 106⫾ 12* DBP (mmHg) 73⫾ 12 69⫾ 10* 74⫾ 12 67⫾ 9* BMI (kg/m2) 24.5⫾ 7.4 19.3⫾ 3.2* 24.9⫾ 6.7 18.8⫾ 3.3* Obesity (%) 42.2 6.6* 49.3 3.6*
Positive family history of diabetes 58.2 36.3* 64.2 35.6*
Maternal age (years) 26.1⫾ 4.2 26.1⫾ 3.9 25.9⫾ 5.0 25.6⫾ 4.0
Paternal age (years) 29.9⫾ 5.6 29.0⫾ 5.1 29.5⫾ 5.6 28.9⫾ 4.7
Maternal BMI (kg/m2) 23.9⫾ 3.6 23.2⫾ 3.0* 24.7⫾ 4.0 23.0⫾ 3.3* Paternal BMI (kg/m2) 24.4⫾ 3.1 24.1⫾ 3.8 25.0⫾ 3.8 24.3⫾ 3.2* SES Low 88 (38.8) 72 (30.9) 102 (39.1) 113 (30.8) Middle 109 (48.0) 124 (53.2) 132 (50.6) 203 (55.3) High 30 (13.2) 37 (15.9) 27 (10.3) 51 (13.9)
3,500 –3,999, andⱖ4,000 g. Test for lin-ear trend based on linlin-ear regression with adjustment for age and sex (and height for blood pressure) was derived for compar-isons of selected variables in type 2 diabe-tes by birth weight categories. Linear regression and multivariate logistic re-gression adjusted age and sex (and height for blood pressure) were used for testing significance between the low birth weight (⬍2,500 g) and high birth weight (⭌4,000 g) subjects with type 2 diabetes as well. Odds ratio (OR) and 95% CI were calculated to estimate the relative risk of type 2 diabetes by birth weight category using those of 3,000 –3,499 g as the ref-erent group (OR⫽ 1) in the multivariate logistic regression model. Age, sex, BMI, family history of diabetes (in their first-degree relatives), socioeconomic status (SES), and GDM were potential covariates and were adjusted in different models of analyses. Parental education levels (⬉9, 10 –12, and⭌13 years of education) were used as the indicator of SES in our present study. Obesity was defined for students as BMI⭌95th percentile of the sex- and age-specific anthropometry of the children in Taiwan (27). All statistical analyses were performed with SPSS statistical software package (version 10.0; SPSS, Chicago, IL). A P value⬍0.05 was considered sta-tistically significant.
RESULTS — Among 1,966 subjects
with diabetes and 1,780 subjects of NFG, 825 of those with diabetes (42%) and 673 of those with NFG (38%) were success-fully traced by telephone interviews. Be-cause of incorrect or missing telephone
numbers and addresses, the actual re-sponse rates were 86.5% for subjects with diabetes and 87.5% for those with NFG. There was no significant difference in terms of response rates between partici-pants and nonparticipartici-pants with respect to age and sex at screening. After excluding subjects with type 1 diabetes (n⫽ 330) and those with missing data on birth weight (n⫽ 146), our analysis was con-fined to 978 participants (429 with type 2 diabetes and 549 with NFG).
As shown in the Table 1, there were no significant differences in the distribu-tion of age, gestadistribu-tion weeks, and SES be-tween the subjects with type 2 diabetes and NFG. However, subjects with type 2 diabetes were associated with a signifi-cantly higher level of BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP), and family history of diabetes in first-degree relatives (all the P values were ⬍0.05 for both boys and girls). Using BMI ⭌95th percentile for age- and sex-matched values of the anthropometry in Taiwan (27) to define obesity, the rate of obesity was much higher for students with type 2 diabetes than students with NFG: 42.2 vs. 6.6% for boys and 49.3 vs. 3.6% for girls. Interestingly, maternal BMI consistently showed a significant dif-ference between the subjects with type 2 diabetes and NFG. There was no signifi-cant difference in SES between type 2 di-abetes and NFG.
To assess the relation of birth weight and the risk of type 2 diabetes in our co-hort, multivariate logistic regression was applied in different models (Table 2). A U-shaped relationship was initially
ob-served for the crude risk of developing type 2 diabetes across different birth weight categories (Table 2 and Fig. 1). Af-ter adjusting for age, sex, BMI, family his-tory of diabetes, and SES in different models, the risk of type 2 diabetes re-mained significantly high for the low birth weight (⬍2,500 g) and high birth weight groups (⭌4,000 g) as compared with the referent group (Table 2). In contrast to the low birth weight group, the odds for type 2 diabetes were reduced when adjusted with the confounding factors and to a nonsignificant level after adjustment with GDM in the high birth weight group (Fig. 1).
To compare clinical characteristics among the subjects with type 2 diabetes born with low or high birth weight, a lin-ear regression was applied to test the P for trends across five different birth weight categories and multivariate logistic re-gression adjusted with age and sex were used for testing significance between type 2 diabetes subjects with low birth weight (⬍2,500 g) and high birth weight (⭌4,000 g) (Table 3). As can be seen, type 2 diabetic subjects born with high birth weight had higher BMI and DBP as well as a higher incidence of family history of di-abetes compared with type 2 diabetic sub-jects born with low birth weight.
CONCLUSIONS — In the present
study, we analyzed the impact of birth weight on various metabolic phenotypes in a young cohort aged 6 –18 years based on a nationwide screening program from 1992 to 1997. We first confirmed a
U-Table 2—OR for type 2 diabetes by birth weight category in the schoolchildren in Taiwan
Variable
Birth weight (g) category
⬍2,500 2,500–2,999 3,000–3,499 3,500–3,999 ⱖ4,000 n (case/control) 23/17 71/90 153/262 115/137 67/43 Crude OR 2.32 (1.20–4.47) 1.35 (0.93–1.96) 1.00 1.43 (1.05–1.98) 2.67 (1.73–4.11) OR (95% CI of diabetes) after adjustment for: Age 2.30 (1.19–4.44) 1.34 (0.93–1.95) 1.00 1.42 (1.04–1.96) 2.67 (1.73–4.11)
Age and sex 2.27 (1.17–4.39) 1.35 (0.93–1.95) 1.00 1.42 (1.03–1.96) 2.61 (1.69–4.02)
Age, sex, and BMI 2.38 (1.12–5.06) 1.47 (0.94–2.29) 1.00 1.30 (0.89–1.90) 2.06 (1.25–3.40) Age, sex, BMI, and family
history of diabetes
2.17 (1.00–4.75) 1.41 (0.89–2.22) 1.00 1.15 (0.77–1.72) 1.79 (1.06–3.02) Age, sex, BMI, family history
of diabetes, and SES
2.91 (1.25–6.76) 1.41 (0.89–2.25) 1.00 1.19 (0.79–1.78) 1.78 (1.04–3.06) Age, sex, BMI, family history
of diabetes, SES, and GDM
shaped relation between birth weight and the risk of type 2 diabetes, which was originally demonstrated in children and young adults in a study of Pima Indians (28). In the type 2 diabetic subjects born with high birth weight, blood pressure was higher, BMI was greater, and the in-cidence of positive family history of dia-betes was higher than in those born with low birth weight, indicating a possibility of a different pathogenesis of type 2 dia-betes in subjects with low and high birth weight. The constellation of diabetes, obesity, and high blood pressure, collec-tively termed metabolic syndrome, was
more frequently observed in the subjects born with high birth weight.
The discovery that childhood type 2 diabetes is associated with obesity in the present study was consistent with previ-ous reports (12,29,30). It is well known that obesity is an important risk factor for type 2 diabetes (31–33). However, a sig-nificant linear and positive trend for BMI across different birth weight categories was found in type 2 diabetes. After adjust-ment with age, sex, and current BMI, sub-jects born with the lowest (⬍2,500 g) and highest (⭌4,000 g) birth weight were still at significant risk for type 2 diabetes when
compared with the referent group (birth weight 3,000 –3,500 g). These results suggest that both current BMI and birth weight are independent risk factors for development of type 2 diabetes. Indeed, adults born with low birth weight and having a high current BMI were shown to be more insulin resistant (34,35) and at the highest risk for type 2 diabetes (7). These observations might also be true in childhood (16). In contrast to the obser-vation in other reports, including a recent study (36) showing that the U-shaped re-lation was converted to a reverse J shape after adjustment for history of maternal diabetes, the U-shaped curve persisted, with a 64% excess risk in those with high birth weight in our study population. Al-though the significance was slightly re-duced after adjustment for GDM, it is anticipated due to a tight correlation be-tween GDM and macrosomia. This sug-gests that, at least in this population, factors other than maternal diabetes con-tribute to the high risk of diabetes among babies with high birth weight.
Previous studies suggested that a de-fect in insulin sensitivity (37) and defi-cient pancreatic-cell function (4) might be associated with subjects with low birth weight, independent of current BMI. Whether these defects are inherited or ac-quired in utero or postnatally remain to be answered. There are some debates on the argument that genetic influences on birth weight (38) or an interaction be-tween genetic and environmental effect might lead to development of type 2 dia-betes for subjects with low birth weight (39). A recent search for candidate genes involved in fetal growth identified that glucokinase gene mutation resulted in
re-Figure 1—ORs for type 2 diabetes in schoolchildren by birth weight categories. ORs were calcu-lated to estimate the relative risk of type 2 diabetes by birth weight category using subjects with birth weight of 3,000 –3,499 g as the referent group (OR⫽ 1) in different multivariate logistic regression models, i.e., crude OR without adjustment (model 1), and adjusted for age, sex, and BMI (model 2), further adjusted for family history of diabetes and SES (model 3), and together with GDM (model 4). Different birth weight categories are shown in vertical bars with a 500-g incre-ment in birth weight from⬍2,500 (white bar) to ⬎4,000 g (black bar).
Table 3—Clinical characteristics of type 2 diabetes in schoolchildren by birth weight categories
Variable
Birth weight (g) category
⬍2,500 2,500–2,999 3,000–3,499 3,500–3,999 ⱖ4,000 n (male/female) 11/12 33/38 77/76 47/68 30/37 Gestation weeks 36.8⫾ 3.7 39.6⫾ 1.4 39.9⫾ 1.0 39.9⫾ 0.7 39.8⫾ 1.1* BMI (kg/m2) 23.9⫾ 5.8 23.6⫾ 7.1 24.8⫾ 7.8 24.9⫾ 6.7 25.6⫾ 5.9* SBP (mmHg) 113⫾ 14 118⫾ 19 119⫾ 19 118⫾ 18 119⫾ 15 DBP (mmHg) 70⫾ 12 72⫾ 12 73⫾ 12 76⫾ 11 75⫾ 12† Obesity rates (%) 38.1 35.9 51.4 43.1 51.6
Family history of diabetes (%) 59.1 58.8 51.0 65.4 84.8‡
Data are means⫾ SD unless otherwise indicated. *P ⬍ 0.05 for trend derived by linear regression adjusted with age and sex by birth weight categories; †P ⬍ 0.05 for trend derived by linear regression adjusted with age, sex, and height by birth weight categories; ‡P valueⱕ0.05 between low and high birth weight was derived by linear regression adjusted for age and sex.
duced birth weight (40,41). Other genes, such as insulin receptor substrate-1, he-patocyte nuclear factor-1␣ (HNF-1␣), HNF-4␣, and HNF-6 had been excluded as major genes for controlling birth weight (42). In our present analysis, even after adjusting for age, sex, BMI, family history of diabetes, and SES, both low and high birth weight remained a significant risk factor for type 2 diabetes. However, the risk was reduced to a nonsignificant level in the subjects with high birth weight after adjustment for maternal his-tory of GDM. Our findings strongly sup-port an independent effect of reduced fetal growth (more environmental effect) on the outcome of diabetes, but it might be linked to some genetic factors inher-ited in those with high birth weight, be-cause the percentage of maternal GDM and the positive family history of diabetes in their first-degree relatives was higher in subjects with type 2 diabetes born with high birth weight.
Low birth weight has been linked to development of hypertension in adult life (43). On the contrary, the present study demonstrates an increase in DBP with in-creasing birth weight in children with type 2 diabetes. Therefore, it is specula-tive that a heterogeneity of pathogenesis exists among the subjects with type 2 di-abetes born with a low or high birth weight; namely, those born with a high birth weight are more similar to subjects with adult metabolic syndrome. How-ever, we cannot exclude the possibility of an age-dependent effect on clinical man-ifestations or mechanisms other than in-sulin resistance in the pathogenesis of type 2 diabetes, obesity, and essential hypertension.
Differentiating between type 1 diabe-tes or type 2 diabediabe-tes in childhood is very difficult, even in a clinical setting. In this study, there was a limitation in classifica-tion of type 1 diabetes and type 2 diabetes because the ascertainment of type 2 dia-betes was based on questionnaire inter-views. Although misclassifications may occur, the validity of self-reported type 2 diabetes has been documented in the Nurses’ Study (44), in which 98% of the cases could be confirmed by reviewing medical records. Because all students with the disease were under medical care with a clinical diagnosis (either type 1 di-abetes or type 2 didi-abetes) and the lack of information in disease type was not in-cluded in this study, the classification of
type 1 diabetes and type 2 diabetes should be acceptable in this nationwide epidemi-ological study.
In summary, a U-shaped relationship between birth weight and risk of type 2 diabetes was confirmed in our popula-tion, as demonstrated by the Pima Indi-a n s . O u r fi n d i n g s s u p p o r t Indi-a n independent role of birth weight on de-velopment of type 2 diabetes in addition to sex, age, BMI, positive family history of diabetes, and SES. Subjects with type 2 diabetes born with high birth weight tended to have higher BMI and DBP than those with low birth weight.
Acknowledgments — This work was
sup-ported by the Chinese Foundation of Health and Grant DOH90-TD1028 from the Depart-ment of Health, Executive Yuan, Republic of China.
We thank Chia-Ling Chao for technical as-sistance.
References
1. Ozanne SE, Osmond C, Hales CN: The role of the intrauterine environment in the later development of type 2 diabetes and the metabolic syndrome. Curr Opin Endo-crinol Diabetes 8:175–179, 2001 2. Forsen T, Eriksson J, Tuomilehto J,
Reu-nanen A, Osmond C, Barker D: The fetal and childhood growth of persons who de-velop type 2 diabetes. Ann Intern Med 133: 176 –182, 2000
3. Fall CH, Osmond C, Barker DJ, Clark PM, Hales CN, Stirling Y, Meade TW: Fetal and infant growth and cardiovascular risk factors in women. BMJ 310:428 – 432, 1995
4. Ravelli AC, van der Meulen JH, Michels RP, Osmond C, Barker DJ, Hales CN, Ble-ker OP: Glucose tolerance in adults after prenatal exposure to famine. Lancet 351: 173–177, 1998
5. Holness MJ, Langdown ML, Sugden MC: Early-life programming of susceptibility to dysregulation of glucose metabolism and the development of type 2 diabetes mellitus. Biochem J 349:657– 665, 2000 6. Patel MS, Srinivasan M: Metabolic
pro-gramming: causes and consequences. J Biol Chem 277:1629 –1632, 2002 7. Hales CN, Barker DJ, Clark PM, Cox LJ,
Fall C, Osmond C: Fetal and infant growth and impaired glucose tolerance at age 64. BMJ 303:1019 –1022, 1991 8. Phipps K, Barker DJ, Hales CN, Fall CH,
Osmond C, Clark PM: Fetal growth and impaired glucose tolerance in men and women. Diabetologia 36:225–228, 1993 9. Barker DJ, Hales CN, Fall CH, Osmond C,
Phipps K, Clark PM: Type 2 (non-insulin-dependent) diabetes mellitus, hyperten-sion and hyperlipidaemia (syndrome X): relation to reduced fetal growth. Diabeto-logia 36:62– 67, 1993
10. Valdez R, Athens MA, Thompson GH, Bradshaw BS, Stern MP: Birth weight and adult health outcomes in a biethnic pop-ulation in the USA. Diabetologia 37:624 – 631, 1994
11. McCance DR, Pettitt DJ, Hanson RL, Ja-cobsson LT, Knowler WC, Bennett PH: Birth weight and non-insulin dependent diabetes: thrifty genotype, thrifty pheno-type, or surviving small baby genotype? BMJ 308:942–945, 1994
12. Rich-Edwards JW, Colditz GA, Stampfer MJ, Willett WC, Gillman MW, Hennek-ens CH, Speizer FE, Manson JE: Birth-weight and the risk for type 2 diabetes mellitus in adult women. Ann Intern Med 130:278 –284, 1999
13. Law CM, Gordon GS, Shiell AW, Barker DJ, Hales CN: Thinness at birth and glu-cose tolerance in seven-year-old children. Diabet Med 12:24 –29, 1995
14. Yajnik CS, Fall CH, Vaidya U, Pandit AN, Bavdekar A, Bhat DS, Osmond C, Hales CN, Barker DJ: Fetal growth and glucose and insulin metabolism in four-year-old Indian children. Diabet Med 12:330 –336, 1995
15. Whincup PH, Cook DG, Adshead F, Tay-lor SJ, Walker M, Papacosta O, Alberti KG: Childhood size is more strongly related than size at birth to glucose and insulin level in 10- and 11-year-old chil-dren. Diabetologia 40:319 –326, 1997 16. Crowther NJ, Cameron N, Trusler J, Gray
IP: Association between poor glucose tol-erance and rapid post natal weight gain in seven-year-old children. Diabetologia 41: 1163–1167, 1998
17. Pettitt DJ, Aleck KA, Baird HR, Carraher MJ, Bennett PH, Knowler WC: Congenital susceptibility to NIDDM: role of intra-uterine environment. Diabetes 37:622– 628, 1988
18. Mohamed N, Dooley J: Gestational dia-betes and subsequent development of NIDDM in aboriginal women of north-western Ontario. Int J Circumpolar Health 57 (Suppl. 1):355–358, 1998
19. Silverman B, Metzger BE, Cho NH, Loeb CA: Impaired glucose tolerance in adoles-cent offspring of diabetic mothers: rela-tionship to fetal hyperinsulinism. Diabetes Care 18:611– 617, 1995
20. Breschi MC, Seghieri G, Bartolomei G, Gi-roni A, Baldi S, Ferrannini E: Relation of birthweight to maternal plasma glucose and insulin concentrations during normal pregnancy. Diabetologia 36:1315–1321, 1993
21. Dabelea D, Hanson RL, Bennett PH, Rou-main J, Knowler WC, Pettitt DJ:
Increas-ing prevalence of type II diabetes in American Indian children. Diabetologia 41:904 –910, 1998
22. Pinhas-Hamiel O, Dolan LM, Daniels SR, Standiford D, Khoury PR, Zeitler P: Increased incidence of non-insulin-de-pendent diabetes mellitus among adoles-cents. J Pediatr 128:608 – 615, 1996 23. Akazawa Y: Prevalence and incidence of
diabetes mellitus by WHO criteria. Diabe-tes Res Clin Pract 24 (Suppl.):23–27, 1994 24. Kitagawa T, Owada M, Urakami T, Tajima N: Epidemiology of type 1 (insulin-de-pendent) and type 2 (non-insulin-depen-dent) diabetes mellitus in Japanese children. Diabetes Res Clin Pract 24 (Suppl.):7–13, 1994
25. Owada M, Hanaoka Y, Tanimoto Y, Kita-gawa T: Descriptive epidemiology of non-insulin dependent diabetes mellitus detected by urine glucose screening in school children in Japan. Acta Paediatr Jpn 32:716 –724, 1990
26. Expert Committee on the Diagnosis and Classification of Diabetes Mellitus: Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 20:1183–1197, 1997 27. National Health Research Institutes
Fo-rum: Assessment of Children Anthropometry and its Affecting Factors. 1st ed. Taipei, Re-public of China, National Health Research Institutes, 2000
28. Dabelea D, Pettitt DJ, Hanson RL, Impera-tore G, Bennett PH, Knowler WC: Birth weight, type 2 diabetes, and insulin resis-tance in Pima Indian children and young adults. Diabetes Care 22:944 –950, 1999 29. Bavdekar A, Yajnik CS, Fall CH, Bapat S,
Pandit AN, Deshpande V, Bhave S, Kellingray SD, Joglekar C: Insulin
resis-tance syndrome in 8-year-old Indian chil-dren: small at birth, big at 8 years, or both? Diabetes 48:2422–2429, 1999 30. Curhan GC, Willett WC, Rimm EB,
Spiegelman D, Ascherio AL, Stampfer MJ: Birth weight and adult hypertension, dia-betes mellitus, and obesity in US men. Circulation 94:3246 –3250, 1996 31. Dean H: NIDDM-Y in first nation children
in Canada. Clin Pediatr 37:89 –96, 1998 32. Scott CR, Smith JM, Cradock MM,
Pihoker C: Characteristics of youth-onset noninsulin-dependent diabetes mellitus and insulin-dependent diabetes mellitus at diagnosis. Pediatrics 100:84 –91, 1997 33. Bloomgarden ZT: Obesity and diabetes.
Diabetes Care 23:1584 –1590, 2000 34. Phillips DIW, Barker DJP, Hales CN, Hirst
S, Osmond C: Thinness at birth and insu-lin resistance in adult life. Diabetologia 37: 150 –154, 1994
35. Lithell HO, McKeigue PM, Berglund L, Mohsen R, Lithell U, Leon DA: Relation-ship of birthweight and ponderal index to non-insuldependent diabetes and in-sulin response to glucose challenge in men aged 50 – 60 years. BMJ 312:406 – 410, 1996
36. Innes KE, Byers TE, Marshall JA, Baro´n A, Orleans M, Hamman RF: Association of a woman’s own birth weight with subse-quent risk for gestational diabetes. JAMA 287:2534 –2541, 2002
37. Choi CS, Kim C, Lee WJ, Park JY, Hong SK, Lee MG, Park SW, Lee KU: Associa-tion between birth weight and insulin sensitivity in healthy young men in Korea: role of visceral adiposity. Diabetes Res Clin Pract 49:53–59, 2000
38. Wang X, Zuckerman B, Coffman CG, Corwin MJ: Familial aggregation of low
birth weight among white and blacks in the United States. N Engl J Med 333: 1744 –1749, 1995
39. Poulsen P, Vaag AA, Kyvik KO, Moller JD, Beck-Nielsen H: Low birth weight is asso-ciated with NIDDM in discordant monozygotic and dizygotic twin pairs. Diabetologia 40:439 – 446, 1997 40. Hattersley AT, Beards F, Ballantyne E,
Appleton M, Harvey R, Ellard S: Muta-tions in the glucokinase gene of the fetus result in reduced birth weight. Nat Genet 19:268 –270, 1998
41. Velho G, Hattersley AT, Froguel P: Mater-nal diabetes alters birth weight in glucoki-nase-deficient (MODY2) kindred but has no influence on adult weight, height, in-sulin secretion or inin-sulin sensitivity. Dia-betologia 43:1060 –1063, 2000
42. Rasmussen SK, Urhammer SA, Hansen T, Almind K, Moller AM, Borch-Johnsen K, Pedersen O: Variability of the insulin re-ceptor substrate-1, hepatocyte nuclear factor-1alpha (HNF-1alpha), HNF-4al-pha, and HNF-6 genes and size at birth in a population-based sample of young Dan-ish subjects. J Clin Endocrinol Metab 85: 2951–2953, 2000
43. Phillips DI, Walker BR, Reynolds RM, Flanagan DE, Wood PJ, Osmond C, Barker DJ, Whorwood CB: Low birth weight predicts elevated plasma corti-sol concentrations in adults from 3 pop-ulations. Hypertension 35:1301–1306, 2000
44. Colditz GA, Willett WC, Stampfer MJ, Manson JE, Hennekens CH, Arky RA, Speizer FE: Weight as a risk factor for clinical diabetes in women. Am J Epidemiol 132:501–513, 1990
