Sage Journals: Discover world-class research

Abstract

Background

Studies of gender difference in type 2 diabetes have been inconclusive. We investigated gender difference in type 2 diabetes and the contribution of body iron, as assessed by serum ferritin to this difference.

Methods

We performed cross-sectional (n = 1707) and prospective (n = 1506) analyses in males and females aged 53–73 years in 1998–2001. Type 2 diabetes diagnosis was determined by questionnaire, blood glucose measurements and record linkage to type 2 diabetes registers. Gender difference in type 2 diabetes and serum ferritin contribution to the difference was examined in multivariable logistic and Cox regression models. Gender difference in fasting plasma glucose and insulin and homeostasis model assessment of insulin resistance was examined in linear regression analysis.

Results

In the cross-sectional analysis, a total of 201 type 2 diabetes cases were observed (males = 111 [55.2%] vs. female = 90 [44.8%], P = 0.032), and in adjusted models, males had higher odds of type 2 diabetes (OR = 1.61, 95% CI 1.10 to 2.34); higher fasting plasma glucose (β = 0.28, 95% CI 0.15 to 0.41), fasting plasma insulin (β = 0.73, 95% CI 0.26 to 1.19) and homeostasis model assessment of insulin resistance (β = 0.11, 95% CI 0.04 to 0.17). In the prospective analysis, males had increased risk of type 2 diabetes (HR = 1.46, 95% CI 1.03 to 2.07). With serum ferritin introduction (100 µg/L, log-transformed) into the models, the type 2 diabetes prevalence (OR = 1.35, 95% CI 0.91 to 1.99) and incidence (HR = 1.38, 95% CI 0.96 to 1.97) were appreciably attenuated.

Conclusions

These data suggest a gender difference in type 2 diabetes, with a higher prevalence and increased type 2 diabetes risk in males. Body iron explains about two-fifths and one-fifth of the gender difference in type 2 diabetes prevalence and incidence, respectively.

Keywords

Gender type 2 diabetes body iron serum ferritin insulin resistance

Introduction

Some studies have suggested that there might be a gender difference in diabetes prevalence¹ and insulin sensitivity.² A recent study conducted in a Czech cohort suggests a male predominance in insulin resistance and type 2 diabetes (T2D) prevalence.³ Evidence in Finland has suggested an alarming increase in the incidence of T2D with male preponderance.^4,5 Recent studies in other population have also suggested that male sex is an independent risk factor of T2D.^6,7 Furthermore, it is known that T2D risk increases with aging as clearly demonstrated in a multicentre study across different European countries, which showed a consistently higher age-adjusted risk of T2D diabetes (T2D) in males compared to females.⁸

Body iron accumulation varies with age and gender.^9–11 The physiological loss of blood during menstrual cycle contributes to the marked sex difference in body iron stores between premenopausal females and males of similar age. This evidence is further supported by the striking reduction in the difference postmenopause.¹¹ Serum ferritin (sF) is a useful marker of body iron stores¹² that has been used to demonstrate the difference in iron accumulation by gender. sF is also an acute phase protein which responds to inflammatory states, and may in addition act as a marker of insulin resistance.¹³ However, it has been widely used to assess body iron stores in epidemiological studies, particularly after adjustments for inflammation.¹⁴ Higher sF concentrations are often observed in males compared with females across varying population samples.^9,12,15–17 Body iron as assessed by sF is a known independent risk factor of T2D.^14,18 As iron accumulation varies by gender, body iron could to some extent explain the possible gender disparity in T2D prevalence and incidence.

The explanation for the gender difference in the prevalence and incidence of T2D is unclear. To our knowledge, no study has investigated whether gender differences in body iron accumulation influence the gender differences in T2D prevalence and incidence. We aimed therefore to address two important study questions. Firstly, whether there is a gender difference in the prevalence and incidence of T2D and the prevalence of abnormalities in glucose metabolism as assessed by fasting plasma glucose (FPG), fasting plasma insulin (FPI) and the homeostasis model assessment of insulin resistance (HOMA-IR), secondly, whether body iron accumulation explains any gender difference in T2D prevalence and incidence, and the prevalence of abnormalities of glucose metabolism.

Methods

Subjects and study design

We performed both cross-sectional and prospective analyses within the Kuopio Ischemic Heart Disease Risk Factor (KIHD) study, which is an ongoing population-based study designed to investigate the risk factors for cardiovascular diseases and other common illnesses in Kuopio and its environs.¹⁹ At baseline examination rounds (1984–1989), a total of 2682 males (83% of the eligible study population) aged 42 to 60 years were recruited in two cohorts. In 1984–1986, the first cohort of 1166 males aged 54 years were recruited and the second cohort of 1516 males in four age categories, 42, 48, 54 or 60 years were enrolled in 1986–1989.¹⁹ During the 11-year follow-up examination round (1998–2001), males from the second cohort were invited of which 854 participated. At the same 11-year examination round, a random sample of 920 postmenopausal females aged 53–73 years from the same area as the males entered the study. Out of those eligible, 95% of males and 78.4% of females participated in the 11-year examination.²⁰ The non-eligible males for the 11-year follow-up examination round were those who had migrated or had died between the baseline and the 11-year examinations. The 11-year follow-up study served as the baseline for the current analysis. Subjects with missing data on sF (n = 9), FPG or FPI (n = 64) were excluded from the analyses, leaving a total of 1707 individuals for the cross-sectional analysis. After the exclusion of prevalent T2D cases (n = 201) at baseline, the prospective analysis was carried out in 1506 subjects. The KIHD study was approved by the Research Ethics Committee of the Kuopio University Hospital, and all participants gave their written informed consent.

Data collection

Data on body mass index (BMI) and other anthropometry measurements¹⁹ were obtained. In addition, data on dietary intakes of foods and nutrients using a four-day food recording,²¹ physical activity using the 12-month leisure-time physical activity Questionnaire of the KIHD study,²² alcohol consumption,²³ smoking status,²³ history of hypertension²⁴ and medication for dyslipidemia²⁴ were collected, and they all have been described earlier. A positive family history of diabetes was defined as the presence of diabetes history in a first-degree relative of the study participant. A history of hypertension was defined as systolic/diastolic blood pressure of ≥140/90 mmHg and/or the use of antihypertensive medication.

Diagnosis of T2D

The diagnosis of T2D was via a self-reporting of a previous diagnosis of T2D and/or FPG ≥ 7.0 mmol/L or 2-h oral-glucose-tolerance-test plasma glucose≥11.1 mmol/L at the study visit and by record linkage to the national hospital discharge registry and the Social Insurance Institution of Finland register for reimbursement of T2D medication expenses.¹⁸

Biomarker and biochemical measurements

After an overnight fast and abstinence from alcohol use for three days and tobacco smoking for 12 h, fasting blood samples were collected between 8:00 and 10:00. The 11-year follow-up sF measurement was assayed from the stored serum samples by radioimmunoassay (RIA) based on a double-antibody technique (RIA Amersham International, Amersham, UK) as described previously.²³ The measurements of serum C reactive protein,²⁵ serum low-density lipoprotein, high-density lipoprotein and triglycerides,²⁴ serum insulin and blood glucose measurements²⁶ were as described previously. HOMA computer algorithm was used to estimate insulin resistance.²⁷

Statistical analyses

The baseline characteristics of both male and female participants were presented as means ± SDs and median and interquartile range. The means between males and females were compared by independent sample t-tests or chi-square tests for categorical variables (Table 1). Skewed and higher sF values (100 µg/L) were normalized by logarithmic transformation (log₁₀) and treated as continuous variable in all the analyses. In the cross-sectional analysis, the association between gender and T2D prevalence was assessed by multivariable logistic regression analysis (Table 2). The association between gender and glucose homeostasis markers, FPG, FPI and HOMA-IR was examined by linear regression analysis. The positive value of regression coefficient represents an increase in the markers of glucose homeostasis for males (Table 3). In the prospective analysis, multivariable Cox regression models were used to investigate the association between gender and incidence of T2D.

Table 1.

Baseline characteristics of 1707 Eastern Finnish males and females in the Kuopio Ischemic Heart Disease Risk Factor study in 1989–1991.

Characteristics	Males (n = 817)	Females (n = 890)	P
Clinical variables
Age (years)	62.6 ± 6.5	63.3 ± 6.5	0.024
Body mass index (kg/m²)	27.4 ± 3.6	28.5 ± 5.1	<0.001
Waist circumference (cm)	97.5 ± 10.3	88.5 ± 12.3	<0.001
History of hypertension (%)	6.4	6.7	0.197
Family history of diabetes (yes, %)	3.3	3.5	0.302
Alcohol intake (grams/week)	79.2 ± 130	19.1 ± 37.9	<0.001
Smoking (pack years)	4.6 ± 12.5	1.4 ± 6.0	<0.001
Total energy intake (kcal/day)	2082.4 ± 558.3	1557.1 ± 424.2	<0.001
Physical activity (sessions/week)	3.09 ± 2.92	3.73 ± 3.19	<0.001
Biochemical variables
Serum glucose (mmol/L)	5.2 ± 1.3	5.0 ± 1.1	<0.001
Serum insulin (mU/L)	8.7 ± 5.1	8.4 ± 5.3	0.192
Serum ferritin (µg/L)^a	103 (55.0–173.6)	53 (29.0–94.3)	<0.001
Serum C-reactive protein (mg/L)^a	1.4 (0.7–2.9)	1.7 (0.8–3.3)	0.012
Plasma fibrinogen (g/L)	3.14 ± 0.61	3.19 ± 0.59	0.051
Soluble leptin receptor (U/L)	31.8 ± 23.6	26.2 ± 10.5	<0.001
Serum LDL cholesterol (mmol/L)	3.49 ± 0.92	3.70 ± 0.92	<0.001
Serum HDL cholesterol (mmol/L)	1.14 ± 0.27	1.35 ± 0.31	<0.001
Serum triglyceride (mmol/L)	1.33 ± 0.70	1.26 ± 0.66	0.039

Note: Values are means ± SD. P-values were calculated by independent sample t-tests, Mann-Whitney U test and chi-square tests for categorical variables.

LDL: low-density lipoprotein; HDL: high-density lipoprotein.

median (interquartile range).

Table 2.

Association between gender and type 2 diabetes prevalence and incidence.

	T2D prevalence			T2D incidence
Models	Odds ratios	95% CI	P-value	Hazards ratios	95% CI	P
Model 1	1.44	1.07 to 1.94	0.016	1.11	0.85 to 1.46	0.439
Model 1 + serum ferritin	1.16	0.85 to 1.58	0.361	0.96	0.72 to 1.28	0.958
Model 2	1.64	1.15 to 2.35	0.007	1.43	1.03 to 1.99	0.034
Model 2 + serum ferritin	1.36	0.94 to 1.97	0.104	1.32	0.94 to 1.86	0.113
Model 3	1.61	1.10 to 2.34	0.014	1.46	1.03 to 2.07	0.035
Model 3 + serum ferritin	1.35	0.91 to 1.99	0.136	1.38	0.96 to 1.97	0.081

Note: Model 1 is adjusted for age and baseline examination year. Model 2 is adjusted for Model 1 plus body mass index, smoking, alcohol intake, leisure time physical activity and total energy intake. Model 3 is adjusted for Model 2 plus serum C-reactive protein, plasma fibrinogen, serum soluble leptin receptor, serum LDL/HDL-cholesterol ratio, serum triglyceride, hypertension, family history of diabetes and drug for dyslipidemia. Serum ferritin (100 µg/L) was log-transformed and treated as continuous variable.

CI: confidence interval.

Table 3.

Association between gender and fasting plasma glucose, fasting plasma insulin and homeostasis model assessment of insulin resistance.

Models	Fasting plasma glucose (mmol/L)	Fasting plasma insulin (mU/L)	HOMA-IR
Model 1	β = 0.24, 95% CI 0.13 to 0.35, P < 0.001	β = 0.38, 95% CI−0.11 to 0.87, P = 0.130	β = 0.06, 95% CI −0.01 to 0.13, P = 0.084
Model 1 + serumferritin	β = 0.14, 95% CI 0.02 to 0.26, P = 0.021	β = −0.10, 95% CI −0.61 to 0.42, P = 0.709	β = −0.01, 95% CI −0.08 to 0.06, P = 0.793
Model 2	β = 0.28, 95% CI 0.15 to 0.41, P < 0.001	β = 0.89, 95% CI 0.40 to 1.37, P < 0.001	β = 0.13, 95% CI 0.06 to 0.20, P < 0.001
Model 2 + serum ferritin	β = 0.20, 95% CI 0.06 to 0.34, P = 0.004	β = 0.67, 95% CI 0.16 to 1.17, P = 0.009	β = 0.10, 95% CI 0.03 to 0.17, P = 0.007
Model 3	β = 0.28, 95% CI 0.15 to 0.41, P < 0.001	β = 0.73, 95% CI 0.26 to 1.19, P = 0.002	β = 0.11, 95% CI 0.04 to 0.17, P = 0.001
Model 3 + serum ferritin	β = 0.20, 95% CI 0.07 to 0.34, P = 0.003	β = 0.62, 95% CI 0.14 to 1.11, P = 0.012	β = 0.09, 95% CI 0.02 to 0.16, P = 0.008

: regression coefficients; CI: confidence interval; HOMA-IR: homeostasis model assessment of insulin resistance.

The associations were adjusted for known risk factors of T2D. Model 1 included age (years) and baseline examination years. Model 2 included variables in model 1 and modifiable clinical variables, i.e. BMI (kg/m²); smoking (pack years); alcohol intake (grams of absolute ethanol per week); total daily energy intake (kcal/day) and leisure-time physical activity (conditioning leisure-time sessions per week). Model 3 included variables in model 2 and other clinical variables as well as biochemical variables, i.e. history of hypertension (≥140/90 mmHg and/or use of hypertension medication [%]); medication for dyslipidaemia (%); family history of diabetes (%); serum C-reactive protein concentration (mg/L, high sensitivity method); plasma fibrinogen (g/L); serum soluble leptin receptor (U/L) serum low-density lipoprotein/high-density lipoprotein ratio and serum triglyceride concentrations (mmol/L). Missing values in covariates were less than 3% and were replaced with the cohort mean. Statistical analyses were performed with SPSS version 21 for Windows (Armonk, NY: IBM corporation), and all tests of statistical significance (P < 0.05) were two sided.

Results

The characteristics of the study participants by gender are as shown (Table 1). The mean age was 62.6 years (SD = 6.4), and the median sF concentration was 103.0 µg/L (IQR = 55.0–173.6) in males and 63.3 years (SD = 6.5) and 53.0 µg/L (IQR = 29.0–94.3) in females, respectively. Although baseline clinical and biochemical characteristics were similar between the genders, males had a higher total daily energy intake, less leisure-time physical activity, higher alcohol intake and they smoked more cigarettes (Table 1).

At baseline, a total of 201 participants had prevalent T2D, with a significantly higher T2D prevalence in males (111 cases [55.2%] vs. 90 cases [44.8%] in males and females, respectively; P = 0.032). The cross-sectional analysis showed a statistically significant association between gender and T2D in model 3, with a 61% higher odds of having T2D in males (Odds ratio [OR] = 1.61, 95% CI 1.10 to 2.34, P = 0.014). Introduction of body iron stores as assessed by sF into the model, significantly attenuated the association (OR = 1.35, 95% CI 0.91 to 1.99, P = 0.136, in model 3) (Table 2). Factors that remained statistically significant in association with T2D in the model 3 were age (OR per 1 year = 1.05, 95% CI 1.02 to 1.07, P = 0.001), BMI (OR per 1 kg/m²= 1.07, 95% CI 1.03 to 1.11, P = 0.001), serum triglyceride concentration (mmol/L, OR = 1.76, 95% CI 1.41 to 2.20, P < 0.001), serum LDL/HDL ratio (OR = 0.83, 95% CI 0.70 to 0.98, P = 0.030), medication for dyslipidaemia (OR = 2.00, 95% CI 1.12 to 3.61, P = 0.020), family history of diabetes (OR = 2.41, 95% CI 1.76 to 3.29, P < 0.001), hypertension (OR = 1.77, 95% CI 1.19 to 2.64, P = 0.005) and log sF (OR per 100 µg/L = 2.17, 95% CI 1.42 to 3.30, P < 0.001).

In linear regression analysis with markers of glucose homeostasis, a statistically significant association was observed between gender and FPG after multivariable adjustments in model 3 (β = 0.28, 95% CI 0.15 to 0.41, P < 0.001). The association was again attenuated after the introduction of sF into the model (Table 3). Introduction of sF into the models with FPI and HOMA-IR showed a similar impact on the associations between gender and FPI and HOMA-IR (Table 3).

In the prospective analysis of 1506 people free of prevalent diabetes at baseline, a total of 207 incident T2D cases were observed during the mean follow-up of 7.3 years. In adjusted model 3, a statistically significant association was observed between gender and incident T2D (HR = 1.46, 95% CI 1.03 to 2.07, P = 0.035). The risk of developing T2D was attenuated with the introduction of sF into the models (Table 2). When males and females were examined separately, a statistically significant increased risk of developing T2D was observed in males in model 3 (HR = 1.52, 95% CI 1.19 to 1.95, P = 0.001), whereas an inverse association was observed among the females (HR = 0.66 95% CI 0.51 to 0.84, P = 0.001). We also examined the impact of excluding subjects with chronic liver/pancreatic disease and chronic kidney disease (n = 10) from the analysis which did not significantly attenuate the associations (Data not shown).

Discussion

This population-based cross-sectional and prospective study showed that there is a gender difference in T2D prevalence and incidence. Males had higher prevalence and increased risk of developing T2D. Body iron, as assessed by sF, explains about two-fifths and one-fifth of the gender difference observed in the prevalence and incidence of T2D, respectively (Table 2). In addition, gender difference was observed in glucose homeostasis with males having higher FPG, FPI and HOMA-IR. sF explains about one-fourth and one-fifth of the difference in FPG and markers of insulin resistance (FPI and HOMA-IR), respectively (Table 3).

In agreement with relatively recent studies^6,7,28 that demonstrated gender difference in T2D prevalence with more cases among males, we also observed more cases of T2D in males (55.2%) than in females (44.8%). This male predominance was not only limited to T2D prevalence but was also observed in T2D incidence, in which we found a 46% increased risk of T2D in males in models adjusted for age and other factors. The development of T2D has been suggested to increase linearly with age, with more cases observed in the middle-aged and ageing periods,^7,8 even in age-dependent T2D risk, the role of gender is clearly evident as demonstrated in our study. The influence of gender was particularly highlighted in the relatively large Inter Act Consortium study that cut across many European nations and which reported a 51% excess risk of T2D in males as compared with females in an age-adjusted model.⁸ Likewise, in Lin et al.⁷, which investigated the annual trends of incidence of T2D among adults in Taiwan, a 20% increased risk of T2D in males compared with females was observed, thus, providing more evidence base for the male preponderance in the incidence of T2D.

The direction of the gender bias in T2D prevalence and incidence as suggested in our study, as with other previous studies,^6–8,28 appeared to be in keeping with the known direction of gender influence on body iron stores.^9,12,15–17 Body iron accumulation follows a divergent pattern between males and females, so that body iron stores increase in males and decrease in females from teenage years up till the age of menopause in females and the comparable age in males.^9,15 During the middle-aged periods and particularly after menopause, iron accumulation slightly plateaus in males but increases markedly in females till the elderly aged periods, after which iron accumulation drops in both genders.^9,15 Despite the steep rise in iron accumulation in females in postmenopausal ages, it is still below the total iron accumulation in males throughout life,^16,17 which further strengthens the role of gender in iron accumulation. The similarities in the direction of gender influence on body iron accumulation and prevalence and incidence of T2D suggest that body iron stores may well explain to some extent the gender bias in T2D prevalence and incidence. We observed in our study, a significant attenuation in the association between gender and T2D when body iron, as assessed by sF, was introduced into the models (Table 2), which suggests that body iron to some extent explains the gender–T2D association. Of the previous studies that found a gender difference in the prevalence^6,7,28 and incidence of T2D,^7,8 none either investigated or reported iron as a possible explanation for the gender difference in T2D prevalence and incidence.

A study conducted in Glasgow, United Kingdom²⁹ suggested some explanations for the gender difference in insulin sensitivity – hallmark of T2D, but again, body iron was not reported. However, some of the factors identified in the study have being linked to body iron stores. A limited capacity for subcutaneous fat expansion in males as compared with females,³⁰ causing males to accumulate more fat in the viscera – liver, spleen and pancreas³¹ and in the skeletal muscles was one of the factors reported. Likewise, these organs are known sites for body iron stores, which implies more oxidation of the accumulated fats leading to an increase in insulin resistance in males as compared with females.³¹ Furthermore, a few studies^2,3,32,33 had reported the effect of gender on insulin sensitivity among the adolescents in which difference in body iron accumulation by gender is known to be relatively marked. However, none of these studies attributed the gender difference in insulin sensitivity to the difference in body iron accumulation. Aldhoon-Hainerova et al.³ in their study among the Czech adolescents suggested that there might be gender difference in insulin resistance. They found that obese boys had significantly higher insulin resistance as assessed by HOMA-IR than obese girls.³ In keeping with their results, we also found a higher HOMA-IR in males after multivariable adjustments (Table 3). Our analysis on the gender difference in insulin resistance adds to the existing knowledge³¹ by demonstrating that gender difference in insulin resistance is not restricted to the adolescents but also exists in the middle-aged and ageing population. Another factor identified in the Glasgow report was the differential circulating adiponectin concentrations by gender that is suggested to be lower in males.²⁹ Molecular studies have shown that iron supresses the transcription of adiponectin mRNA,³⁴ which leads to a reduction in adiponectin production and subsequent disturbance in insulin sensitivity. Hence, this further suggests that body iron perhaps could be the main determinant for a lower insulin sensitivity observed in middle-aged and ageing males as compared with females.

The disparity in body iron accumulation between males and females which may underlie the gender difference in T2D and glucose homeostasis in our study is supported by several suggested mechanisms. Higher body iron accumulation in males may cause more impairment to peripheral glucose uptake due to oxidative muscle damage.³⁵ Also body iron accumulation may cause greater derangement of glucose homeostasis in males than in females due to gender-related differences in visceral and subcutaneous fat distribution. Increased visceral white adipose tissue has been found to be associated with altered glucose homeostasis and it is reported that males store more lipids in it than in the subcutaneous white adipose tissue as is the case in females.³⁶ Thus, males may oxidize dietary fatty acids more readily than females.³⁶ This further suggests that a more accelerated production of free radicals may occur in males than in females since iron is a pro-oxidant catalyst. The end result is the decreased glucose uptake in the muscles which stimulates gluconeogenesis in the liver and increases insulin resistance.^37,38 Other authors have suggested a mechanism mediated through an effect on sex hormone concentrations which might warrant further consideration.³⁹

Among the strengths of our study is the use of a randomly selected sample in a genetically and culturally homogenous ethnicity. It is known that body iron stores vary with ethnicity¹⁵ and previous multiethnic studies have showed how ethnicity could impact on gender difference observed in insulin resistance² and T2D prevalence.⁴⁰ Some of the previous studies adjusted for ethnicity in their analysis, but the findings were still contradictory.^2,33 Our study had no confounding due to ethnicity in the analyses of gender difference in HOMA-IR and T2D prevalence and incidence. The inclusion of only postmenopausal females from the same area as the males in our study provided to some extent an unbiased comparison in body iron accumulation between males and females. It also reduced the influence of hormonal differences between males and females on the analyses. The T2D cases in our cohort were not restricted to only self-report reporting of a previous T2D diagnosis and/or blood glucose measurements, but were further confirmed with record linkage to the hospital discharge register and reimbursement register of those people on medication for T2D, which further increased the sensitivity of T2D diagnosis in our study.

One of the limitations of this study is the relatively narrow age range of the study subjects. The difference in body iron accumulation between males and females is known to be marked during the premenopausal period in females and the comparable age in males.¹⁵ The inclusion of this younger age group could have increased the contribution of body iron to the gender difference observed in our analysis. The parallel increase in body iron and low-density lipoprotein in postmenopausal period may confound gender–T2D association in females;⁴¹ however, we extensively adjusted our analysis for the serum lipids, i.e. low-density lipoprotein, high-density lipoprotein and triglycerides. We are also aware that there could be a selection bias in the prevalence of T2D observed in the cross-sectional analysis; however, we performed a prospective analysis to further strengthen the gender difference observed in T2D prevalence. Also, our primary claim is not to reiterate the gender difference in T2D prevalence and incidence as it has been reported earlier,^6–8,28 but, that in such a difference, body iron accumulation has a role. The use of sF as a marker of iron accumulation has been questioned by some authors because of its variation with inflammation and for its role as a marker of insulin resistance; hence reverse causality cannot be completely ruled out.¹³

In conclusion, our data suggest that there is a gender difference in the prevalence and incidence of T2D, with a higher prevalence, and increased risk of T2D observed in males. Body iron accumulation, as assessed by sF, explains about two-fifths and one-fifth of the gender difference observed in T2D prevalence and incidence, respectively. Larger prospective cohort studies are needed to further confirm the extent of contribution of body iron to the gender dimorphism in T2D.

Footnotes

Acknowledgements

The authors express their gratitude to the staff of Research Unit of Public Health for data collection.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

This study was funded by the University of Eastern Finland and Juho Vainio Foundation Research Grant #201510337 to AA.

Ethical approval

The KIHD study was approved by the Research Ethics Committee of the Kuopio University Hospital with approval number 143/97.

Guarantor

T-PT.

Contributorship

AA and T-PT were involved in conception and design of this study. T-PT, SV and JKV were involved in the acquisition of data. AA, T-PT and JKV performed the statistical analysis and interpretations. All authors contributed to and edited the final version of the manuscript.

References

Gale

Gillespie

. Diabetes and gender. Diabetologia 2001; 44: 3–15.

Moran

Jacobs

Jr Steinberger

. Insulin resistance during puberty: results from clamp studies in 357 children. Diabetes 1999; 48: 2039–2044.

Aldhoon-Hainerova

Zamrazilova

Dusatkova

. Glucose homeostasis and insulin resistance: prevalence, gender differences and predictors in adolescents. Diabetol Metab Syndr 2014; 6: 100–5996-6-100.

Lammi

Taskinen

Moltchanova

. A high incidence of type 1 diabetes and an alarming increase in the incidence of type 2 diabetes among young adults in Finland between 1992 and 1996. Diabetologia 2007; 50: 1393–1400.

Lammi

Blomstedt

Moltchanova

. Marked temporal increase in the incidence of type 1 and type 2 diabetes among young adults in Finland. Diabetologia 2008; 51: 897–899.

Kaiser

Vollenweider

Waeber

. Prevalence, awareness and treatment of type 2 diabetes mellitus in Switzerland: the CoLaus study. Diabet Med 2012; 29: 190–197.

Lin

Hsiao

. Time trend analysis of the prevalence and incidence of diagnosed type 2 diabetes among adults in Taiwan from 2000 to 2007: a population-based study. BMC Public Health 2013; 13: 318–2458-13-318.

Langenberg

Sharp

. InterAct Consortium. Design and cohort description of the InterAct Project: an examination of the interaction of genetic and lifestyle factors on the incidence of type 2 diabetes in the EPIC Study. Diabetologia 2011; 54: 2272–2282.

Cook

Finch

Smith

. Evaluation of the iron status of a population. Blood 1976; 48: 449–455.

10.

Leggett

Brown

Bryant

. Factors affecting the concentrations of ferritin in serum in a healthy Australian population. Clin Chem 1990; 36: 1350–1355.

11.

Milman

. Serum ferritin in Danes: studies of iron status from infancy to old age, during blood donation and pregnancy. Int J Hematol 1996; 63: 103–135.

12.

Skikne

Flowers

Cook

. Serum transferrin receptor: a quantitative measure of tissue iron deficiency. Blood 1990; 75: 1870–1876.

13.

Chen

Wildman

Hamm

. Association between inflammation and insulin resistance in U.S. nondiabetic adults: results from the Third National Health and Nutrition Examination Survey. Diabetes Care 2004; 27: 2960–2965.

14.

Forouhi

Harding

Allison

. Elevated serum ferritin levels predict new-onset type 2 diabetes: results from the EPIC-Norfolk prospective study. Diabetologia 2007; 50: 949–956.

15.

Zacharski

Ornstein

Woloshin

. Association of age, sex, and race with body iron stores in adults: analysis of NHANES III data. Am Heart J 2000; 140: 98–104.

16.

Lahti-Koski

Valsta

Alfthan

. Iron status of adults in the capital area of Finland. Eur J Nutr 2003; 42: 287–292.

17.

Cooper

Greene-Finestone

Lowell

. Iron sufficiency of Canadians. Health Rep 2012; 23: 41–48.

18.

Aregbesola

Voutilainen

Virtanen

. Body iron stores and the risk of type 2 diabetes in middle-aged men. Eur J Endocrinol 2013; 169: 247–253.

19.

Salonen

. Is there a continuing need for longitudinal epidemiologic research? The Kuopio Ischaemic Heart Disease Risk Factor Study. Ann Clin Res 1988; 20: 46–50.

20.

Aregbesola

Voutilainen

Nurmi

. Serum 25-hydroxyvitamin D3 and the risk of pneumonia in an ageing general population. J Epidemiol Community Health 2013; 67: 533–536.

21.

Voutilainen

Rissanen

Virtanen

Kuopio Ischemic Heart Disease Risk Factor Study . Low dietary folate intake is associated with an excess incidence of acute coronary events: the Kuopio Ischemic Heart Disease Risk Factor Study. Circulation 2001; 103: 2674–2680.

22.

Lakka

Venalainen

Rauramaa

. Relation of leisure-time physical activity and cardiorespiratory fitness to the risk of acute myocardial infarction. N Engl J Med 1994; 330: 1549–1554.

23.

Tuomainen

Punnonen

Nyyssonen

. Association between body iron stores and the risk of acute myocardial infarction in men. Circulation 1998; 97: 1461–1466.

24.

Salonen

Nyyssonen

Korpela

. High stored iron levels are associated with excess risk of myocardial infarction in eastern Finnish men. Circulation 1992; 86: 803–811.

25.

Virtanen

Nurmi

Voutilainen

. Association of serum 25-hydroxyvitamin D with the risk of death in a general older population in Finland. Eur J Nutr 2011; 50: 305–312.

26.

Tuomainen

Nyyssonen

Salonen

. 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.

27.

Matthews

Hosker

Rudenski

. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412–419.

28.

Leahy

O’Halloran

O’Leary

. Prevalence and correlates of diagnosed and undiagnosed type 2 diabetes mellitus and pre-diabetes in older adults: findings from the Irish Longitudinal Study on Ageing (TILDA). Diabetes Res Clin Pract 2015; 110: 241–249.

29.

Sattar

. Gender aspects in type 2 diabetes mellitus and cardiometabolic risk. Best Pract Res Clin Endocrinol Metab 2013; 27: 501–507.

30.

Koster

Stenholm

Alley

. Body fat distribution and inflammation among obese older adults with and without metabolic syndrome. Obesity (Silver Spring) 2010; 18: 2354–2361.

31.

Geer

Shen

. Gender differences in insulin resistance, body composition, and energy balance. Gend Med 2009; 6: 60–75.

32.

Travers

Jeffers

Bloch

. Gender and Tanner stage differences in body composition and insulin sensitivity in early pubertal children. J Clin Endocrinol Metab 1995; 80: 172–178.

33.

Lee

Okumura

Davis

. Prevalence and determinants of insulin resistance among U.S. adolescents: a population-based study. Diabetes Care 2006; 29: 2427–2432.

34.

Gabrielsen

Gao

Simcox

. Adipocyte iron regulates adiponectin and insulin sensitivity. J Clin Invest 2012; 122: 3529–3540.

35.

Merkel

Simonson

Amiel

. Insulin resistance and hyperinsulinemia in patients with thalassemia major treated by hypertransfusion. N Engl J Med 1988; 318: 809–814.

36.

Varlamov

Bethea

Roberts

Jr . Sex-specific differences in lipid and glucose metabolism. Front Endocrinol (Lausanne) 2015; 5: 241–241.

37.

Felber

Ferrannini

Golay

. Role of lipid oxidation in pathogenesis of insulin resistance of obesity and type II diabetes. Diabetes 1987; 36: 1341–1350.

38.

DeFronzo

. Lilly lecture 1987. The triumvirate: beta-cell, muscle, liver. A collusion responsible for NIDDM. Diabetes 1988; 37: 667–687.

39.

Sheu

Chen

Lee

. A relationship between serum ferritin and the insulin resistance syndrome is present in non-diabetic women but not in non-diabetic men. Clin Endocrinol (Oxf) 2003; 58: 380–385.

40.

King

Rewers

. Global estimates for prevalence of diabetes mellitus and impaired glucose tolerance in adults. WHO Ad Hoc Diabetes Reporting Group. Diabetes Care 1993; 16: 157–177.

41.

Berge

Bonaa

Nordoy

. Serum ferritin, sex hormones, and cardiovascular risk factors in healthy women. Arterioscler Thromb 1994; 14: 857–861.

Gender difference in type 2 diabetes and the role of body iron stores

Abstract

Background

Methods

Results

Conclusions

Keywords

Introduction

Methods

Subjects and study design

Data collection

Diagnosis of T2D

Biomarker and biochemical measurements

Statistical analyses

Results

Discussion

Footnotes

Acknowledgements

Declaration of conflicting interests

Funding

Ethical approval

Guarantor

Contributorship

References