Context Type 2 diabetes is a common manifestation of hemochromatosis, a disease
of iron overload. However, it is not clear whether higher iron stores predict
the development of type 2 diabetes in a healthy population.
Objective To examine plasma ferritin concentration and the ratio of the concentrations
of transferrin receptors to ferritin in relation to risk of type 2 diabetes.
Design, Setting, and Participants Prospective nested case-control study within the Nurses' Health Study
cohort. Of the 32 826 women who provided blood samples during 1989-1990
and were free of diagnosed diabetes, cardiovascular disease, and cancer, 698
developed diabetes during 10 years of follow-up. The controls (n = 716) were
matched to cases on age, race, and fasting status; and on body mass index
(BMI) for cases in the top BMI decile.
Main Outcome Measure Incident cases of type 2 diabetes.
Results Among cases, the mean (SD) concentration of ferritin was significantly
higher (109 [105] vs 71.5 [68.7] ng/mL for controls; P<.001
for difference) and the mean (SD) ratio of transferrin receptors to ferritin
was significantly lower (102 [205] vs 141 [340], respectively; P = .01). In conditional logistic regression stratified on the matching
factors and controlled for BMI and other diabetes risk factors, the multivariate
relative risks [RRs] of incident type 2 diabetes across increasing quintiles
of ferritin were 1.00, 1.09 (95% confidence interval [CI], 0.70-1.70), 1.26
(95% CI, 0.82-1.95), 1.30 (95% CI, 0.83-2.04), and 2.68 (95% CI, 1.75-4.11)
(P<.001 for trend). The RRs across increasing
quintiles of transferrin receptors to ferritin ratio were 2.44 (95% CI, 1.61-3.71),
1.00 (95% CI, 0.64-1.56), 1.13 (95% CI, 0.73-1.74), 0.99 (95% CI, 0.64-1.53),
and 1.00 (P = .01 for trend). Further adjustment
for an inflammatory marker (C-reactive protein) did not change the results
appreciably. The associations persisted within strata defined by levels of
BMI, menopausal status, alcohol consumption, and C-reactive protein.
Conclusion Higher iron stores (reflected by an elevated ferritin concentration
and a lower ratio of transferrin receptors to ferritin) are associated with
an increased risk of type 2 diabetes in healthy women independent of known
diabetes risk factors.
Excessive iron stores can cause type 2 diabetes among patients with
hemochromatosis.1 However, it is not clear
whether moderately elevated iron stores predict the risk of developing type
2 diabetes among healthy individuals. Iron is a catalyst in the formation
of hydroxyl radicals, which are powerful prooxidants that attack cellular
membrane lipids, proteins, and nucleic acids.2-4 It
has been hypothesized that formation of hydroxyl radicals catalyzed by iron
contributes initially to insulin resistance and subsequently to decreased
insulin secretion and then to the development of type 2 diabetes.5-7 Findings on the association
between serum ferritin concentration and insulin resistance or type 2 diabetes
risk from cross-sectional or case-control studies have been inconsistent.
Several of these studies observed positive associations7-12;
however, serum ferritin concentrations may reflect systemic inflammation coexisting
with diabetes rather than high iron stores because blood samples are collected
after the diagnosis of diabetes. Also, the directionality of the associations
cannot be established based on retrospective or cross-sectional data.
One small prospective nested case-control study from Finland (41 cases
and 82 controls, blood samples were collected prior to diabetes diagnosis)
has shown a direct association between iron stores, as measured by the ratio
of serum transferrin receptor concentration to serum ferritin concentration,
and the incidence of diabetes in men.13 To
our knowledge, there are no other prospective studies relating iron stores
to incident type 2 diabetes in a healthy population. To test the hypothesis
that higher iron stores might predict development of type 2 diabetes, we conducted
a large prospective nested case-control study to evaluate biomarkers reflecting
iron stores, including plasma ferritin concentration and the ratio of the
concentrations of transferrin receptors to ferritin in relation to the development
of type 2 diabetes in apparently healthy middle-aged women enrolled in the
Nurses' Health Study.
This study had a case-control design, and was nested in the Nurses'
Health Study, a prospective investigation initiated in 1976 that was designed
to study the etiological characteristics of heart disease, cancer, and other
major diseases in 121 700 female registered nurses aged 30 to 55 years
at baseline.14 During 1989-1990, 32 826
women free of diagnosed diabetes, cardiovascular disease, and cancer provided
blood samples. By 2000, 698 had developed definite type 2 diabetes. For each
woman who developed type 2 diabetes, a control individual was chosen at random
among women free of self-reported diabetes at the time the case individual
reported her event. The controls were matched to the cases on age (within
1 year), race, and fasting status at blood draw. Fasting was defined as 8
hours or longer since last meal prior to sample collection. For diabetic cases
in the top 10% of body mass index (BMI) (very obese cases), another control
individual was chosen who was further matched on BMI (if available) to better
control for obesity. Body mass index was calculated as weight in kilograms
divided by the square height in meters. The final study group included 698
cases and 716 controls. This study was approved by the human subjects committee
at Brigham and Women's Hospital, Boston, Mass.
Ascertainment of Diabetes
Diabetes incidence was identified by self-report on biennial follow-up
questionnaires and confirmed by a validated supplementary questionnaire regarding
diabetes symptoms, diagnostic tests, and treatments. Based on the diagnostic
criteria proposed by the National Diabetes Data Group,15 a
diagnosis of diabetes (prior to 1998) was established when at least 1 of following
criteria was reported on the supplementary questionnaire: (1) one or more
classic symptoms (excessive thirst, polyuria, weight loss, hunger, or coma)
plus a fasting plasma glucose concentration of 140 mg/dL (7.77 mmol/L) or
higher or a random plasma glucose concentration of 200 mg/dL (11.1 mmol/L)
or higher; or (2) at least 2 elevated plasma glucose concentrations on different
occasions (fasting ≥140 mg/dL [≥7.77 mmol/L] and/or random ≥200 mg/dL
[≥11.1 mmol/L] and/or ≥200 mg/dL [≥11.1 mmol/L] after ≥2 hours
with oral glucose tolerance testing) in the absence of symptoms; or (3) treatment
with hypoglycemic medication (insulin or oral hypoglycemic agents). These
criteria were changed in 199716; the fasting
glucose concentration of 126 mg/dL (6.99 mmol/L) or higher was considered
diagnostic for cases after 1998. We excluded women with type 1 diabetes and
women classified as having gestational diabetes only. A validation study in
a subsample of the Nurses' Health Study demonstrated that our supplementary
questionnaire is highly reliable in confirming diabetes diagnosis.17 Among a random sample of 84 women classified by our
criteria as having type 2 diabetes according to the information reported on
the supplementary questionnaire, medical records were available for 62. An
endocrinologist blinded to the information reported on the questionnaire reviewed
the records. The diagnosis of type 2 diabetes was confirmed in 61 (98%) of
the 62 women.
We sent a phlebotomy kit (including sodium heparin blood tubes, needles,
a tourniquet, etc) and instructions to women willing to provide blood specimens
in 1989-1990. Blood specimens were returned by overnight mail in a frozen
water bottle and on arrival were centrifuged and stored in liquid nitrogen
until laboratory analysis. Ninety-seven percent of samples arrived within
26 hours of phlebotomy. Quality-control samples were routinely frozen along
with study samples to monitor for plasma changes due to long-term storage
and to monitor for changes in assay variability. Previous work has documented
the long-term stability of plasma samples collected and stored under this
protocol.18 Frozen plasma aliquots from cases
and controls were selected for simultaneous analysis in 2002 and were analyzed
in randomly ordered case-control pairs to reduce systematic bias and interassay
variation.
Concentrations of ferritin and transferrin receptors were measured by
a particle-enhanced immunoturbidimetric assay using the Hitachi 911 analyzer
(Roche Diagnostics, Indianapolis, Ind). C-reactive protein (CRP) concentrations
were measured via a highly sensitive latex-enhanced immunonephelometric assay
on a BN II analyzer (Dade Behring, Newark, Del). Insulin concentrations were
measured using a double antibody system with less than 0.2% cross-reactivity
between insulin and its precursors (Linco Research, St Louis, Mo). Hemoglobin
A1c was measured by immunoassay (Hitachi 911 Analyzer). The coefficients
of variation for each analyte were: ferritin, 3.75%; transferrin receptors,
8.4%; CRP, 3.8%; fasting insulin, 9.5%, and hemoglobin A1c, 3.8%.
Assessment of Lifestyle Factors
The participants provided information on family history of diabetes
in first-degree relatives in 1982 and 1988. They provided information on their
body weight, cigarette smoking, and physical activity, menopausal status,
and use or nonuse of postmenopausal hormone therapy every 2 years since 1976.
The correlation coefficient between self-reported weight and measured weight
was 0.96.18 Physical activity (metabolic equivalent
hours per week) was based on the reported time spent on various activities,
weighting each activity by its intensity level.19
Diet was assessed in 1980, 1984, 1986, and 1990 by using semiquantitative
food frequency questionnaires (SFFQs). The SFFQ in 1980 included 61 food items
and was revised and expanded to about twice the number of foods in later years.
A full description of the SFFQ and the reproducibility and validity of the
dietary questionnaires have been previously published.20,21 We
used the cumulative average of dietary intake (from all available dietary
questionnaires up to the start of this study) because it reduces within-subject
variation and best represents long-term diet, and has been shown to be a stronger
predictor of type 2 diabetes than the baseline diet in a previous study of
our cohort.22 The calculation of cumulative
average of dietary intake was previously reported.23
We first calculated mean (SDs), medians, and proportions of potential
diabetes risk factors for the cases and the controls at baseline. t and χ2 Tests were used for comparisons of the means
and the proportions. We divided the distributions of the markers of iron stores
in the controls into quintiles; quintile-specific relative risks (RRs) of
diabetes were estimated from conditional logistic regression models stratified
on matching factors (age, race, and fasting status). In multivariate models,
we adjusted for conventional diabetes risk factors including BMI, family history
of diabetes, physical activity, smoking status, alcohol use, menopausal status,
and dietary variables.22 We also adjusted for
a sensitive biomarker of inflammation (CRP). Tests for trend were conducted
using the median values for each quintile of ferritin or the ratio of transferrin
receptors to ferritin as a continuous variable in the regression models. Tests
for interaction were performed using likelihood ratio tests by comparing 2
nested models, one with the main effects only and the other with both the
main effects and interaction terms. In addition, we used restricted cubic
spline regressions with 4 knots24 to model
the associations between ferritin and the ratio of transferrin receptors to
ferritin (as continuous variables) and risk of type 2 diabetes. All P values were 2-sided. P≤.05
was considered statistically significant. All analyses were performed using
SAS statistical software (Version 8.12, SAS Institute Inc, Cary, NC).
The distributions of potential risk factors for type 2 diabetes in cases
(n = 698) and healthy controls (n = 716) are presented in Table 1. Overall, women who subsequently developed diabetes during
follow-up were heavier, more likely to have a family history of diabetes,
less likely to exercise and consume alcohol, and had higher plasma concentrations
of CRP, fasting insulin, and hemoglobin A1c at baseline. In addition,
diabetic women tended to have higher baseline average intake of heme iron,
transfat, red and processed meats, total calories, and lower intake of cereal
fiber and magnesium. The correlation between ferritin and CRP was 0.14, and
the correlation between the ratio of transferrin receptors to ferritin and
CRP was −0.12.
At baseline, the mean (SD) ferritin concentration was significantly
higher (109 [105] vs 71.5 [68.7] ng/mL; P<.001
for the difference) and the mean (SD) ratio of transferrin receptors to ferritin
was significantly lower (102 [205] vs 141 [340]; P =
.01 for the difference) in the cases than in the healthy controls (Table 1). In conditional logistic regression
analyses stratified on matching factors (age, race, and fasting status), the
RRs across increasing quintiles of ferritin were 1.00, 1.19 (95% confidence
interval [CI], 0.81-1.75), 1.53 (95% CI, 1.06-2.23), 1.38 (95% CI, 0.94-2.03),
and 3.20 (95% CI, 2.22-4.62) (P≤.001 for linear
trend) (Table 2). The RRs across
increasing quintiles of the ratio of transferrin receptors to ferritin were
2.59 (95% CI, 1.82-3.68), 1.04 (95% CI, 0.72-1.52), 1.31 (95% CI, 0.91-1.88),
1.11 (95% CI, 0.76-1.61), and 1.00 (P<.001 for
linear trend). These RRs were modestly attenuated after adjusting for BMI,
but remained statistically significant. Additional adjustment for other diabetes
risk factors including family history of diabetes, physical activity, smoking
status, alcohol use, menopausal status, and diet did not change the results
appreciably. Because ferritin concentration reflects both the storage of iron
and acute-phase inflammation, we further adjusted for CRP to reduce potential
confounding by inflammation. The associations between ferritin concentration
and ratio of transferrin receptors to ferritin with diabetes risk remained
virtually unchanged (Table 2).
Exclusion of 7 individuals with exceptionally elevated ferritin concentrations
(≥500 ng/mL) or iron supplement users did not change the results.
In the subset of women who provided waist circumference measurements
(420 cases and 515 controls), we adjusted for both BMI and waist circumference
(as continuous variables) in the multivariate conditional logistic regression
models. The results did not change appreciably. The RR was 2.40 (95% CI, 1.34-4.28)
comparing the highest with the lowest quintile of ferritin (P<.001 for trend) and was 2.41 (95% CI, 1.37-4.26) comparing the
lowest with the highest quintiles of the ratio of transferrin receptors to
ferritin (P = .12 for trend).
To eliminate potential bias due to undiagnosed diabetes in the control
group, we excluded control women with hemoglobin A1c levels higher
than 6.5% and repeated the multivariate analysis. The RR was 2.63 (95% CI,
1.69-4.11) comparing women in the highest with the lowest quintile of ferritin
(P<.001 for trend) and was 2.43 (95% CI, 1.57-3.75)
comparing women in the lowest with the highest quintile of ratio of transferrin
receptors to ferritin (P = .02 for trend).
We also used restricted cubic spline regressions with 4 knots to model
the associations continuously. The regression splines demonstrated a linear
relationship between ferritin and the risk of type 2 diabetes (P = .29 for curvature; Figure 1).
However, there is a possible threshold effect for the ratio of transferrin
receptors to ferritin of approximately 50 on diabetes risk (P≤.001 for curvature).
To assess whether the associations between ferritin concentration and
ratio of transferrin receptors to ferritin and risk of diabetes were modified
by CRP concentrations, we examined the joint associations of ferritin and
CRP (Figure 2) and the ratio of
transferrin receptors to ferritin and CRP. In the joint analyses, the associations
of the markers of iron storage and CRP with diabetes risk tended to be independent
(P = .25 for interaction between ferritin and CRP; P = .35 for interaction between the ratio of transferrin
receptors to ferritin and CRP). Overall, women with the highest concentrations
of ferritin and CRP or with the lowest ratio of transferrin receptors to ferritin
and the highest concentrations of CRP had the highest diabetes risk (Figure 2).
Because menstruation causes iron loss and alcohol consumption can accelerate
the effects of iron overload, we further conducted multivariate analyses within
strata defined by levels of BMI (≤25, 25-29.9, and ≥30), menopausal
status (premenopausal and postmenopausal), and alcohol consumption (<5
g/d or ≥5 g/d). We observed that the associations between ferritin concentration
and ratio of transferrin receptors to ferritin and risk of type 2 diabetes
persisted in all subgroups (Table 3).
We found no apparent modification in the relationships with these factors
(P>.05 for all interaction tests).
In this prospective nested case-control study of middle-aged women,
body iron stores reflected by a higher ferritin concentration and a lower
ratio of transferrin receptors to ferritin were associated with a significantly
increased incidence of type 2 diabetes after adjustment for obesity and other
diabetes risk factors. A possible threshold effect of the ratio of transferrin
receptors to ferritin on diabetes risk was suggested by regression splines.
The associations persisted in all subgroup analyses according to BMI, menopausal
status, and alcohol consumption. These data provide evidence that increased
total body iron stores are an independent risk factor for type 2 diabetes
in this healthy population.
Iron is a transitional metal that can catalyze the conversion of poorly
reactive free radicals into highly active free radicals. It has been suggested
that formation of hydroxyl radicals catalyzed by iron may play a role in the
development of diabetes because the highly active radicals can attack cell
membrane lipids, proteins, and DNA and cause tissue damage.3-6 Studies
have shown that iron deposition in muscle decreases glucose uptake because
of muscle damage,25 while iron accumulation
interferes with hepatic insulin extraction26 and
affects insulin synthesis and secretion in the pancreas.27 Iron
excess seems to contribute initially to insulin resistance and subsequently
to decreased insulin secretion.27
One concern of this study is that the ferritin concentration is not
an entirely specific marker for iron storage and may reflect other mechanisms,
especially subclinical systemic inflammation related to insulin resistance
and risk of type 2 diabetes.1 We tried to minimize
the potential confounding by inflammation in several ways. First, we conducted
a prospective nested case-control study in which all blood samples were collected
before the disease outcome developed; therefore, the incident cases of diabetes
that developed during the follow-up would be unlikely to affect the ferritin
concentrations at baseline. We also excluded women with diagnosed diabetes,
cardiovascular disease, and cancer at baseline. Second, we controlled for
CRP in the multivariate models, although the correlation between ferritin
and CRP was small (r = 0.14). This statistical control
did not attenuate associations of iron markers and risk of diabetes.
Another potential concern is residual confounding by obesity because
obesity is an important determinant of type 2 diabetes. In our study, along
with matching on BMI for the most obese cases, we controlled for BMI using
a continuous variable. In an additional analysis, we controlled for both BMI
and waist circumference among women who provided waist circumference measurements.
The associations for markers of iron stores did not substantially change.
Although we cannot rule out the possibility of residual confounding by other
diabetes risk factors, it is unlikely that they can explain the observed strong
associations. Because our controls were not uniformly screened for glucose
intolerance, some cases of diabetes may have been undiagnosed. However, when
the analyses were restricted to women with hemoglobin A1c levels
of less than 6.5%, the results did not change, suggesting that a bias due
to undiagnosed diabetes is unlikely. It also should be noted that the diagnostic
criteria for type 2 diabetes in this study were changed after 1998 (a lower
fasting glucose threshold of 126 mg/dL [6.99 mmol/L] was considered the diagnostic
cut point compared with that before 1998). If the new criteria were used for
diagnosing cases before 1998, some women classified as not having diabetes
would have been diagnosed as having diabetes. But, inclusion of those with
diabetes into the group without diabetes would tend to weaken the observed
association.
Our results are consistent with the findings from a small prospective
nested case-control study in Finland.13 In
that study (41 cases and 82 controls), men in the lowest quarter for the ratio
of transferrin receptors to ferritin were 2.4 times more likely to develop
diabetes than men in the highest quarter. To our knowledge, no other study
has evaluated the associations between biomarkers of iron stores and diabetes
incidence in a healthy population. Cross-sectional or case-control studies
have produced mixed findings about the difference in serum ferritin concentration
between diabetic patients and nondiabetic individuals. Several of these studies
observed positive associations between serum ferritin concentrations and insulin
resistance or risk of diabetes.7-12 However,
serum ferritin concentration in cross-sectional and case-control studies may
reflect systemic inflammation associated with diabetes rather than high iron
storage.
Type 2 diabetes is an established, common complication of hemochromatosis,
a genetic defect in the regulation of iron absorption. Individuals who have
homozygous hereditary hemochromatosis absorb more iron than normal. Excess
iron accumulation in patients with hemochromatosis often results in clinical
manifestation of type 2 diabetes (53%-82% of patients with hemochromatosis
develop diabetes1), which provides clinical
evidence that excess iron stores are strongly associated with development
of type 2 diabetes. Iron reduction therapy in individuals with hereditary
hemochromatosis and transfusional iron overload is associated with improved
glucose tolerance and reduced incidence of secondary diabetes.27 Trials
of iron reduction therapy in type 2 diabetes have shown some promising results
but are inconclusive.27-29
There has been considerable interest in the possibility that excess
iron stores may contribute to the pathogenesis of cardiovascular disease.
The cumulative epidemiological evidence has been inconsistent, but most studies
do not support the iron and cardiovascular disease hypothesis.30,31 However,
most studies have important limitations including short follow-up time and
small numbers of cases and few have included women. Although diabetes and
cardiovascular disease share many risk factors and pathophysiological pathways,
the primary mechanisms for type 2 diabetes involve insulin resistance and
beta-cell dysfunction, both of which can be directly affected by high iron
storage. Excess iron is usually stored in the liver, muscle, and pancreas
and may cause organ-specific oxidative damage leading to insulin resistance
and eventually beta-cell failure. This may not be the case for cardiovascular
disease because cardiomyopathy due to iron deposition in the heart, but not
ischemic heart disease, is often seen in late-stage hemochromatosis patients.
The fact that type 2 diabetes is a common complication in patients with hemochromatosis
and iron reduction therapy can improve glucose tolerance provide clinical
evidence that excess iron storage may directly contribute to the development
of type 2 diabetes. Our study provides support for the hypothesis that higher
iron stores may also contribute to the origin of type 2 diabetes in a generally
healthy population.
In summary, an elevated ferritin concentration and a low ratio of transferrin
receptors to ferritin were associated with an increased incidence of type
2 diabetes in apparently healthy middle-aged women independent of known diabetes
risk factors. This finding may have important implications for the prevention
of type 2 diabetes because elevated ferritin concentration and lower concentration
in the ratio of tranferrin receptors to ferritin in healthy populations may
help to identify a high-risk population for type 2 diabetes who may benefit
from further evaluation and interventions (lifestyle or therapeutic).
1.Witte DL, Crosby WH, Edwards CQ, Fairbanks VF, Mitros FA. Practice guideline development task force of the College of American
Pathologists: hereditary hemochromatosis.
Clin Chim Acta.1996;245:139-200.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8867884&dopt=Abstract
Google Scholar 2.McCord JM. Effects of positive iron status at a cellular level.
Nutr Rev.1996;54:85-88.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8935218&dopt=Abstract
Google Scholar 3.Andrews NC. Disorders of iron metabolism.
N Engl J Med.1999;341:1986-1995.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10607817&dopt=Abstract
Google Scholar 4.Beard JL. Iron biology in immune function, muscle metabolism and neuronal functioning.
J Nutr.2001;131:568S-580S.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11160590&dopt=Abstract
Google Scholar 5.Oberley LW. Free radicals and diabetes.
Free Radic Biol Med.1988;5:113-124.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=3075947&dopt=Abstract
Google Scholar 6.Wolff SP. Diabetes mellitus and free radicals: free radicals, transition metals
and oxidative stress in the aetiology of diabetes mellitus and complications.
Br Med Bull.1993;49:642-652.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8221029&dopt=Abstract
Google Scholar 7.Ford ES, Cogswell ME. Diabetes and serum ferritin concentration among US adults.
Diabetes Care.1999;22:1978-1983.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10587829&dopt=Abstract
Google Scholar 8.Tuomainen TP, Nyyssonen K, Salonen R.
et al. Body iron stores are associated with serum insulin and blood glucose
concentrations: population study in 1,013 eastern Finnish men.
Diabetes Care.1997;20:426-428.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9051399&dopt=Abstract
Google Scholar 9.Fernandez-Real JM, Ricart-Engel W, Arroyo E.
et al. Serum ferritin as a component of the insulin resistance syndrome.
Diabetes Care.1998;21:62-68.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9580307&dopt=Abstract
Google Scholar 10.Hughes K, Choo M, Kuperan P, Ong CN, Aw TC. Cardiovascular risk factors in non–insulin-dependent diabetics
compared to non-diabetic controls: a population-based survey among Asians
in Singapore.
Atherosclerosis.1998;136:25-31.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9544728&dopt=Abstract
Google Scholar 11.Kim NH, Oh JH, Choi KM.
et al. Serum ferritin in healthy subjects and type 2 diabetic patients.
Yonsei Med J.2000;41:387-392.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10957894&dopt=Abstract
Google Scholar 12.Hernandez C, Genesca J, Ignasi Esteban J, Garcia L, Simo R. Relationship between iron stores and diabetes mellitus in patients
infected by hepatitis C virus: a case-control study.
Med Clin (Barc).2000;115:21-22.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10953832&dopt=Abstract
Google Scholar 13.Salonen JT, Tuomainen TP, Nyyssonen K, Lakka HM, Punnonen K. Relation between iron stores and non–insulin-dependent diabetes
in men: case-control study.
BMJ.1998;317:727.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9732340&dopt=Abstract
Google Scholar 14.Colditz GA, Manson JE, Hankinson SE. The Nurses' Health Study: 20-year contribution to the understanding
of health among women.
J Womens Health.1997;6:49-62.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9065374&dopt=Abstract
Google Scholar 15.National Diabetes Data Group. Classification and diagnosis of diabetes mellitus and other categories
of glucose intolerance.
Diabetes.1979;28:1039-1057.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=510803&dopt=Abstract
Google Scholar 16.American Diabetes Association. Report of the expert committee on the diagnosis and classification
of diabetes mellitus.
Diabetes Care.1997;20:1183-1197.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9203460&dopt=Abstract
Google Scholar 17.Manson JE, Rimm EB, Stampfer MJ.
et al. Physical activity and incidence of non–insulin-dependent diabetes
mellitus in women.
Lancet.1991;338:774-778.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=1681160&dopt=Abstract
Google Scholar 18.Rimm EB, Stampfer MJ, Colditz GA, Chute CG, Litin LB, Willett WC. Validity of self-reported waist and hip circumferences in men and women.
Epidemiology.1990;1:466-473.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=2090285&dopt=Abstract
Google Scholar 19.Chasan-Taber S, Rimm EB, Stampfer MJ.
et al. Reproducibility and validity of a self-administered physical activity
questionnaire for male health professionals.
Epidemiology.1996;7:81-86.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8664406&dopt=Abstract
Google Scholar 20.Willett WC, Sampson L, Stampfer MJ.
et al. Reproducibility and validity of a semiquantitative food frequency questionnaire.
Am J Epidemiol.1985;122:51-65.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=4014201&dopt=Abstract
Google Scholar 21.Willett WC. Nutritional epidemiology. In: Rothman KJ, Greenland S, eds. Modern Epidemiology. 2nd ed. Philadelphia, Pa: Lippincott-Raven Publishers; 1998:623-642.
22.Hu FB, Manson JE, Stampfer MJ.
et al. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women.
N Engl J Med.2001;345:790-797.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11556298&dopt=Abstract
Google Scholar 23.Hu FB, Stampfer MJ, Rimm E.
et al. Dietary fat and coronary heart disease: a comparison of approaches
for adjusting total energy intake and modeling repeated dietary measurements.
Am J Epidemiol.1999;149:531-540.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10084242&dopt=Abstract
Google Scholar 24.Durrleman S, Simon R. Flexible regression models with cubic splines.
Stat Med.1989;8:551-561.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=2657958&dopt=Abstract
Google Scholar 25.Merkel PA, Simonson DC, Amiel SA.
et al. Insulin resistance and hyperinsulinemia in patients with thalassemia
major treated by hypertransfusion.
N Engl J Med.1988;318:809-814.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=3281000&dopt=Abstract
Google Scholar 26.Niederau C, Berger M, Stremmel W.
et al. Hyperinsulinaemia in non-cirrhotic haemochromatosis: impaired hepatic
insulin degradation?
Diabetologia.1984;26:441-444.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=6381191&dopt=Abstract
Google Scholar 27.Wilson JG, Lindquist JH, Grambow SC.
et al. Potential role of increased iron stores in diabetes.
Am J Med Sci.2003;325:332-339.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12811229
Google Scholar 28.Cutler P. Deferoxamine therapy in high-ferritin diabetes.
Diabetes.1989;38:1207-1210.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=2792574&dopt=Abstract
Google Scholar 29.Kaye TB, Guay AT, Simonson DC. Non–insulin-dependent diabetes mellitus and elevated serum ferritin
level.
J Diabetes Complications.1993;7:246-249.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8219368&dopt=Abstract
Google Scholar 30.Ma J, Stampfer MJ. Body iron stores and coronary heart disease.
Clin Chem.2002;48:601-603.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11901057&dopt=Abstract
Google Scholar 31.Knuiman MW, Divitini ML, Olynyk JK, Cullen DJ, Bartholomew HC. Serum ferritin and cardiovascular disease: a 17-year follow-up study
in Busselton, Western Australia.
Am J Epidemiol.2003;158:144-149.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12851227&dopt=Abstract
Google Scholar