Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Intake of Vitamin and Mineral Supplements and Longitudinal Association with HbA1c Levels in the General Non-Diabetic Population—Results from the MONICA/KORA S3/F3 Study

  • Sigrid Schwab,

    Affiliation Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany

  • Astrid Zierer,

    Affiliation Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany

  • Margit Heier,

    Affiliations Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany, MONICA/KORA Myocardial Infarction Registry, Central Hospital of Augsburg, Augsburg, Germany

  • Beate Fischer,

    Affiliation Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany

  • Cornelia Huth,

    Affiliations Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany, German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany

  • Jens Baumert,

    Affiliations Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany, German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany

  • Christa Meisinger,

    Affiliations Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany, MONICA/KORA Myocardial Infarction Registry, Central Hospital of Augsburg, Augsburg, Germany

  • Annette Peters,

    Affiliations Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany, German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany

  • Barbara Thorand

    thorand@helmholtz-muenchen.de

    Affiliations Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany, German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany

Abstract

Background

Lower levels of hemoglobin A1c (HbA1c) are associated with a decreased risk of cardiovascular complications in diabetic and non-diabetic individuals. The aim of the study was to longitudinally investigate the association between the use of 11 vitamins and minerals (vitamins E, C, D, B1, folic acid, carotenoids, calcium, magnesium, zinc, iron, and selenium) and change in HbA1c levels over 10 years in non-diabetic individuals drawn from the general population.

Methods

Baseline data were available from 4447 subjects included in the population-based “Monitoring of Trends and Determinants in Cardiovascular Diseases” (MONICA) Augsburg S3 survey (1994/95). Follow-up data were derived from 2774 participants in the follow-up survey named “Cooperative Health Research in the Region of Augsburg” (KORA) F3 (2004/05). Vitamin/mineral intake from supplements and medications was assessed in a personal interview, where participants were asked to bring product packages of preparations that had been ingested during the last 7 days prior to the examination. Associations between regular vitamin/mineral intake amounts and HbA1c levels measured at baseline and follow-up were investigated using generalized estimating equation models. For carotenoids, analyses were stratified by smoking status.

Results

None of the investigated nutrients except for carotenoids was significantly associated with changes in HbA1c levels after 10 years. Regular intake of carotenoids from supplements and medications in amounts > 6.8mg/d (upper tertile) was associated with an absolute –0.26% (95% CI: –0.43 to –0.08) lower increase in HbA1c levels compared with no intake of carotenoids. An inverse association was observed in those who never smoked but not in (former) smokers.

Conclusion

Larger prospective and intervention studies in non-diabetic/non-smoking individuals are needed to confirm the results and to assess whether the observed associations between carotenoid intake and change in HbA1c levels are causal. If our results are confirmed, high carotenoid intake could be one strategy for the prevention of cardiovascular complications in non-diabetic people.

Introduction

Hemoglobin A1c (HbA1c) reflects the percentage of glycated hemoglobin, which results from non-enzymatic attachment of glucose to hemoglobin. Levels of HbA1c indicate the long-term average blood glucose level over the previous 8–12 weeks [1]. Values ≥ 6.5% can be used for the diagnosis of diabetes [2]. Besides its use as a diagnostic tool, HbA1c has been investigated as a marker for cardiovascular risk. An increase in HbA1c levels of 1% is associated with a 17% increase in risk of cardiovascular disease and a 15% increase in risk of all-cause mortality in subjects with type 2 diabetes [3]. The increased risk of cardiovascular complications with higher HbA1c levels is not only evident in those with established diabetes, but also in non-diabetic adults [47]. In the latter, HbA1c levels are more strongly associated with coronary heart disease risk than other glycemic measures [8], and all-cause mortality risk increases by 26% with a 1% increase in HbA1c concentration [9]. Therefore, HbA1c should be investigated continuously in the assessment of cardiovascular and mortality risk [9].

Previous studies on the association between vitamins/minerals and HbA1c levels investigated the effect of vitamin E, vitamin C, vitamin D, vitamin B1, folic acid, carotenoids (β-carotene), calcium, magnesium, zinc, iron, and selenium [1033]. For most nutrients, the results were not consistent between studies that investigated the same nutrients as exposure. Furthermore, all the above mentioned intervention studies were conducted in diabetic patients or high risk populations [1027]. However, supplementation of nutrients might be less effective if the disease has already developed [11,14]. Therefore, investigations in non-diabetic populations are warranted. Population-based studies conducted to date have been of cross-sectional design [28,29,32,33], which precludes conclusions regarding causal relationships. Considering that chronic diseases develop over a period of several years, it is particularly important to conduct long-term studies to investigate potential prevention strategies.

To our knowledge, there is currently no population-based longitudinal study of the association between the use of different vitamin or mineral supplements and change in HbA1c levels in the general healthy population. As the use of dietary supplements could be a promising and feasible strategy to prevent hyperglycemia related complications, the aim of the study was to investigate the longitudinal relationship between the intake of vitamins/minerals from supplements and medications with HbA1c concentrations over 10 years in a population-based sample of non-diabetic people.

Methods

Study description and population

Baseline data were available from the population-based Monitoring of Trends and Determinants in Cardiovascular Diseases (MONICA) Augsburg S3 survey conducted in the years 1994/95 as part of the international World Health Organization (WHO) MONICA project [34]. The study region comprised the city of Augsburg (Germany) and its two surrounding counties. A total of 6640 participants aged 25–74 years were randomly selected by a two-stage cluster sampling method, of whom 4856 participated (73.1%) [35]. Of these, 3006 participants took part in the subsequent Cooperative Health Research in the Region of Augsburg (KORA) F3 survey after 10 years of follow-up [36]. After exclusion of diabetic individuals at baseline, either clinically diagnosed (n = 241) or with baseline HbA1c levels ≥ 6.5% (n = 57), those who ingested antidiabetic medication at baseline or follow-up (n = 109), and participants with missing HbA1c values at baseline and follow-up (n = 2), the final study population comprised 4447 subjects at baseline and 2774 at follow-up.

The study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving human subjects were approved by the ethics committee of the Bavarian Chamber of Physicians (Munich, Germany). Written informed consent was obtained from all participants.

Data collection

Outcome.

The outcome HbA1c was assessed at baseline (1994/95) and at follow-up (2004/05). Non-fasting blood samples were collected according to a standardized procedure. HbA1c was measured with turbidimetric immunoassays (Tina-quant® Hämoglobin A1c, Boehringer Mannheim, Mannheim, Germany, and Dimension Rxl 5 Dade-Behring (TINA) with coefficients of variation (CVs) < 5%) at baseline and follow-up. HbA1c was treated as a continuous variable in all analyses.

Exposure.

Intake of vitamins/minerals from supplements and medications was assessed in a personal interview at baseline (1994/95) and follow-up (2004/05) and also in between after 3 years from baseline investigation through a self-administered postal questionnaire in 2998 individuals (1997/98). Data from the postal questionnaire were only used for descriptive purposes. In the baseline and follow-up surveys, participants were asked to bring all product packages of preparations that were ingested during the last 7 days prior to the examination to the study center. In MONICA S3 (1994/95), the information was recorded through a questionnaire. In KORA F3 (2004/05), database supported computer software (IDOM: Instrument for databased assessment of medication) [37] was used. Daily amounts of regularly ingested nutrients per person were calculated for each survey from a database established by staff at the Helmholtz Zentrum München, which has been updated regularly [38]. Both total carotenoids and β-carotene intakes were investigated, but we restricted our main analyses to carotenoids, as the number of missing values was lower here.

Regular intake of each nutrient was investigated by dividing average intake amount per day into tertiles. Additionally, intake was analyzed binarily (regular vs no intake). For all analyses, the reference group comprised those who did not take the specific nutrient of interest. Cut-off points for tertiles were built from the means of the cut-off points from daily intake amounts at baseline and follow-up (see S1 Table).

Potential confounders.

In both surveys, data regarding sex, age, physical activity, smoking status, alcohol intake, healthy diet, and medication intake were collected during a standardized face-to-face interview by trained medical staff [36]. For information on years of education and family history of diabetes, i.e., diabetes of the mother or father, only the baseline survey was considered. Participants who did not know whether their mother or father suffered or died from diabetes were added to the group that answered this question with “yes”. Education was defined through a combination of years of schooling and professional education and divided into a low (8–10 years) and high (11–17 years) level of education. Physical activity included frequency and duration of activity in summer and winter and was divided into four categories. Smoking status was divided into current (regular and irregular), former, and never smoking. Alcohol intake during the last week was assessed, and an average daily intake amount was calculated based on the alcohol intake during the last weekend and the last weekday prior to each examination. Sex-specific categories were created as follows: moderate intake (> 0 to < 20 g alcohol per day (g/d) (women) and > 0 to < 40 g/d (men)), high intake (≥ 20 g/d (women) and ≥ 40 g/d (men)), and no intake (0 g/d (men and women)). A food frequency questionnaire with 15 food items was used to build a healthy diet score according to the recommendations of the German Nutrition Society 1989 with higher values representing a healthier diet [39]. As food intake was only assessed through a short food frequency questionnaire in the total study sample which did not allow us to calculate intake levels for individual nutrients from diet, we restricted our analyses to intake of nutrients from dietary supplements. Medication that increased HbA1c levels included beta-blockers, diuretics, and regular intake of systemic corticoids.

Anthropometric data (body mass index (BMI), waist–hip ratio (WHR)), information on hypertension, and cholesterol levels were collected during health examinations by trained medical staff. To calculate the BMI, participants’ weight and height were measured, and categories were applied according to the WHO. The WHR was calculated as the ratio between waist and hip circumferences and categorized as low (men < 1, women < 0.85) and high (men ≥ 1, women ≥ 0.85). Hypertension was defined as a systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg or if the participant was taking antihypertensive medication and was aware of being hypertensive. Total and high density lipoprotein (HDL) cholesterol were measured using the CHOD-PAP method (Dade Behring) with CVs < 5% at baseline and follow-up.

Statistical analyses

Age- and sex-adjusted mean levels of HbA1c by categories of covariables and exposure variables were compared using analysis of covariance. To account for the intra-individual correlation, generalized estimating equation (GEE) models using the compound symmetry correlation structure were performed by the Statistical Analysis Systems (SAS) procedure GENMOD for investigation of the long-term association between vitamin/mineral intake from supplements/medications and HbA1c levels. As results, the beta estimates of the interaction terms of each nutrient tertile of interest with time (coded 0/1) are presented (βx). These reflect the difference in change in HbA1c levels between the nutrient tertile of interest and the reference group. Furthermore, beta estimates of time are displayed, which reflect the average change in HbA1c levels in the reference group (βt). Estimates for each nutrient tertile of interest show the difference in HbA1c levels at baseline compared with the reference group (β0).

Continuous covariates were investigated continuously if their association with the outcome was linear in cross-sectional analysis using univariable linear regression models; otherwise, they were categorized. The following variables were included in the models as potential confounders: sex, age (continuously), education (high/low), BMI (three groups), WHR (two groups), physical activity (four groups), smoking (three groups), alcohol intake (three sex-specific categories), healthy diet score (continuously), total/HDL cholesterol (continuously), actual hypertension (yes/no), diabetes of the father (yes/no), diabetes of the mother (yes/no), intake of HbA1c increasing medication (yes/no).

The level of statistical significance was Bonferroni corrected and set at p < 0.0045 (11 investigated nutrients). Statistical analyses were performed using SAS version 9.3 (SAS Institute Inc, Cary, NC, USA).

Sensitivity analyses

As sensitivity analyses, individuals were excluded who 1) developed diabetes during the 10-year follow-up period (n = 142); and 2) had baseline HbA1c levels > 5.7% (n = 354) [40], as supplementation of nutrients in those with impaired glucose regulation might already be too late to exert beneficial effects [14]. Furthermore, stratified analyses according to smoking status were conducted to investigate the association between carotenoid intake and HbA1c levels, because detrimental effects of β-carotene have been reported in smokers [41]. We also conducted longitudinal analyses only in those without any missing values in vitamin/mineral intake and HbA1c values at baseline and follow-up (n = 2630).

Results

Descriptive analyses

Unadjusted mean (standard error of the mean, SEM) HbA1c levels in the study population were 5.12 (0.01) at baseline (n = 4133) and 5.28 (0.01) at follow-up (n = 2774). Description of adjusted mean HbA1c levels by participant characteristics is provided in Table 1. Adjusted mean levels of HbA1c according to exposure categories are presented in Table 2. Regular intake of each investigated nutrient increased constantly from baseline over the 3-year to the 10-year follow-up (see S1 Fig). The proportion of individuals with constant regular intake of nutrients, i.e., regular intakes at baseline and follow-up, in relation to those with regular intake of that nutrient at baseline ranged between 10.0% (iron) and 31.0% (selenium).

thumbnail
Table 1. Characteristics of the study population with adjusted mean levels of HbA1c at baseline (1994/95) and follow-up (2004/05).

https://doi.org/10.1371/journal.pone.0139244.t001

thumbnail
Table 2. Adjusted mean levels of HbA1c by categories of exposure variables at baseline (1994/95) and follow-up (2004/05).

https://doi.org/10.1371/journal.pone.0139244.t002

Main analysis

After 10 years, the HbA1c levels of participants who comprised the reference group (no intake) for each investigated nutrient increased by about 0.1% from baseline (see βt in Table 3). Participants with carotenoid intakes in the upper tertile had a 0.26% lower increase in HbA1c values after 10 years than those with no intake of carotenoids (see βx in Table 3). It is noteworthy that participants with carotenoid intakes in the upper tertile had 0.22% higher HbA1c levels at baseline compared with the reference group (see β0 in Table 3), even though this difference was marginally not statistically significant after Bonferroni correction (p = 0.005). The intake of none of the other investigated nutrient tertiles was significantly associated with concentrations of HbA1c after correction for multiple testing (see Table 3). Treating the exposure to regular intake of each nutrient as binary variables (regular intake vs no intake) yielded analogous findings, whereas the association of regular carotenoid intake with HbA1c levels was not statistically significant (data not shown).

thumbnail
Table 3. Longitudinal association between regular supplement intake and HbA1c (1994/95–2004/05); results from generalized estimating equations (GEE).

https://doi.org/10.1371/journal.pone.0139244.t003

Sensitivity analyses

Excluding 142 participants who developed diabetes during the 10-year follow-up resulted in similar findings to the main analysis, apart from the fact that the inverse association between the upper carotenoid tertile and change in HbA1c levels was not statistically significant (data not shown). Like in the main analysis, after exclusion of 354 participants with baseline HbA1c levels > 5.7%, the increase in HbA1c levels in individuals with intakes of carotenoids in the upper tertile was significantly lower (βx = –0.29% (95% CI: –0.45 to –0.12)) compared with individuals with no intake of carotenoids (p = 0.0006). Unlike in the main analysis, the difference in baseline HbA1c levels of 0.25% (95% CI: 0.11 to 0.39) between those with the highest intakes of carotenoids compared with those with no intake was statistically significant.

In the smoking status-stratified analyses of carotenoid intake and HbA1c levels, the results for current and former smokers were pooled together, as they did not differ substantially (data not shown). A longitudinal inverse association of the upper carotenoid tertile with HbA1c level was significant in participants who never smoked (βx = –0.43% (95% CI: –0.63 to –0.24), p < 0.0001), but not in current or former smokers (βx = –0.11% (95% CI: –0.39 to 0.17), p = 0.451) (see Fig 1). Never smokers with carotenoid intakes in the upper tertile had higher baseline HbA1c values than never smokers with no intake of carotenoids (β0 = 0.33 (95% CI: 0.18 to 0.48), p < 0.0001).

thumbnail
Fig 1. Longitudinal association between regular carotenoid intake amount from supplements and medications in tertiles and levels of HbA1c over 10 years (1994/95 to 2004/05).

nTotal population = 4447, nnever smokers = 1959, n(former) smokers = 2498; 10 people who stated they were never smokers at baseline but smokers at follow-up were partly used for both strata for the appropriate time point; HbA1c beta estimates (βx) result from fully adjusted generalized estimating equation models and refer to interaction terms with time (represents the difference in change in HbA1c levels compared with those with no intake of carotenoids, see βx in Table 3 for total population); cut-off point for tertiles 1 and 2: 1.9 mg/d; for tertiles 2 and 3: 6.8 mg/d.

https://doi.org/10.1371/journal.pone.0139244.g001

The results when restricting the study population to participants without any missing values in exposure and outcome at baseline and follow-up were similar to the main analysis (data not shown).

Discussion

We investigated the longitudinal association of regular intake of vitamin E, vitamin C, vitamin D, vitamin B1, folic acid, carotenoids, calcium, magnesium, zinc, iron, and selenium from supplements and medications with levels of HbA1c in the general non-diabetic population. The results indicate that there is an inverse association of regular carotenoid intakes above 6.8 mg/d with concentrations of HbA1c after 10 years and no significant association of intake of the other investigated vitamins and minerals with HbA1c levels. The observed reduction of 0.3 absolute percentage points in HbA1c levels in the upper carotenoid tertile can be regarded as clinically relevant, as a reduction of 0.1% in the general non-diabetic population could lead to a reduction in mortality of up to 6% over a period of 6 years [9].

Comparison with the literature

Previous intervention studies examining the effect of use of vitamins/minerals on HbA1c levels have mostly been conducted in diabetic or prediabetic subjects and found inconsistent results. Significant inverse associations with HbA1c levels were reported for vitamins E, C, D, B1, folic acid, calcium, magnesium, zinc, iron, and selenium supplemented either alone or in combination [12,19,21,22,24,26,42]. Other intervention studies found no significant associations for vitamins E, C, D, B1, folic acid, carotenoids, calcium, magnesium, and zinc [10,11,1315,17,18,20,23,25]. In contrast, significant positive associations were also observed for vitamin D, folic acid, and selenium [16,27,43].

Inadequacy of baseline nutrient status might influence the efficacy of supplementation, as single studies that reported a protective role for supplemented nutrients (iron, vitamin D with calcium) were conducted in those with inadequate baseline status [21,26]. Furthermore, a recently published meta-analysis on vitamin E supplementation found that HbA1c lowering effects might rather be present in people with low baseline vitamin E status [10]. The same study reported that vitamin E dosages above 400 mg/d might be necessary to result in decreased HbA1c levels. In the present study, two thirds of all subjects who regularly supplemented vitamin E ingested daily amounts of less than 66 mg.

One explanation for the null findings in some of the above mentioned studies is that all were conducted in (pre-)diabetic or high risk populations. The state of dysglycemia might already be too advanced to facilitate beneficial effects of vitamin supplementation [11,14]. Therefore, further intervention studies are warranted in non-diabetic and also in non-prediabetic individuals to investigate the relationship between vitamin/mineral intake and HbA1c levels.

Carotenoids

In the present study, regular intake of > 6.8 mg of carotenoids per day from supplements and medications, which corresponds to the upper tertile, was associated with an about 0.3% lower increase in HbA1c concentrations after 10 years. Similar dose–effect results were presented by Akbaraly et al. from the Epidemiology of Vascular Ageing (EVA) study; however, they investigated plasma carotenoid levels as exposure with regard to other diabetes related outcomes in elderly volunteers [44]. They found that the risk of dysglycemia was significantly lower in the highest plasma carotenoid quartile after 9 years of follow-up.

Prospective studies on the association of carotenoids (intake or plasma/serum levels) with HbA1c levels as an outcome have not, to our knowledge, been published so far. Cross-sectional studies in healthy subjects reported an inverse association [31,32], or no association [30]. A randomized controlled trial (RCT) detected no significant effect with regard to lowering of HbA1c levels [13]. However, the trial was conducted in people with type 2 diabetes [13]. To our knowledge, there is currently no RCT that investigated the effect of carotenoids on HbA1c levels in healthy individuals. Also, the safety of carotenoid supplementation in higher dosages has to be confirmed in future studies, as detrimental effects have been found for β-carotene not only in smokers with dosages above 20 mg/d [41], but also in a pooled analysis of diverse populations with dosages ranging from 15 to 50 mg/d [45]. The main carotenoid ingested in the present study population was β-carotene. Some 98.0% and 68.1%, respectively, of all those who regularly ingested carotenoids at baseline and follow-up took β-carotene. Mean (SD) intake amount in the upper tertile of carotenoids was 15.4 (9.2) mg with a maximum value of 50 mg.

Mechanism.

A potential mechanism for a HbA1c lowering effect of carotenoids might be their antioxidant activity [46], which is closely related to protein glycosylation [47]. However, controlling for several antioxidative markers in the EVA study mentioned above did not change the result of a lower risk of dysglycemia with higher plasma carotenoids [44]. Furthermore, intake of the other investigated antioxidants (vitamin E, vitamin C, zinc, and selenium) from supplements or medications was not significantly associated with lower HbA1c values in the present investigation. Recently, Bumke-Vogt et al. [48] reported that, apart from carotenoids, another subgroup of phytochemicals resulted in down-regulation of gluconeogenic gene expression in human hepatoma cells, an effect not attributed to their antioxidant activity [48]. This suggests that phytochemicals might exert other effects than hitherto known.

Smoking status.

Stratified analyses according to smoking status showed that an inverse association of carotenoids and HbA1c levels is only present in those who have never smoked. These results support previous findings by Hozawa et al., who investigated serum carotenoid levels as exposure and diabetes incidence and insulin concentrations as outcomes in the Coronary Artery Risk Development in Young Adults (CARDIA) study [49]. The authors concluded that higher serum carotenoid levels are significantly associated with a lower risk of diabetes and insulin resistance after 15 years only in non-smokers, but not in smokers.

Strengths and limitations

A limitation of the present study is that measurements of HbA1c and covariables were only available for two time points. Intake of supplements was assessed at three time points. Furthermore, there were no detailed data available on nutrient intakes from diet, and we only adjusted for a diet score that represents a healthy or an unhealthy eating pattern. However, we believe that dietary habits remained rather constant during the study period, as the categorized healthy diet score remained the same in 56% of the participants with available information at baseline and follow-up. An important limitation is the small (and also unequal) number of participants in some nutrient tertiles, which might have underpowered the present analyses. Furthermore, variation in baseline HbA1c levels was high in specific tertile groups, and the results might be driven by outliers. Moreover, plasma levels were not measured, although these do not always represent intake of nutrients, especially if a high turnover is present, such as with antioxidant levels in smokers [50]. Inadequacy of baseline status of nutrients was not considered in the present analysis, but might influence the efficacy of supplementation [10,21,26]. With respect to vitamin E, ingested dosages might have been too low. Another important point to consider is that participants with the highest intakes of carotenoids at baseline had relatively high baseline levels of HbA1c. Therefore, regression to the mean might be present and might lead to biased results with regard to the inverse longitudinal association. We also cannot exclude the possibility that the results are due to residual confounding, as this is an observational study, even if the beta estimates did not differ greatly between the raw and fully adjusted models.

The strengths of the present study include the long follow-up duration of 10 years, the availability of important covariables not only at baseline but also at follow-up, and the thorough assessment of vitamin/mineral intake from supplements and medications. The availability of average daily intake amounts of nutrients allowed the conduct of dose–effect analyses, which are crucial in the investigation of physiological nutrient effects. Furthermore, this represents a population-based study of healthy non-diabetic individuals. Therefore, the results can be transferred to the general population. Finally, HbA1c exhibits a lower biological variability compared with other glycemic outcomes [51] and is strongly associated with cardiovascular disease risk in non-diabetic people [8].

Future perspectives

Larger prospective studies on vitamin/mineral intake or blood levels and HbA1c concentrations are needed to confirm the results of the present analyses. If the results regarding a significant inverse association of higher carotenoid intakes with HbA1c levels are replicated, RCTs can be conducted, especially in non-smokers and those without diabetes, to investigate the causal effect of carotenoid dosages > 6.8 mg/d in lowering HbA1c concentrations. If these studies confirm the present findings, supplementation of carotenoids might be a useful strategy in preventing the development of type 2 diabetes as well as cardiovascular complications and mortality in the general or non-smoking population.

Supporting Information

S1 Fig. Regular intake of dietary supplements over 10 years.

Data are derived from the MONICA (Monitoring of Trends and Determinants in Cardiovascular Diseases) S3 survey in 1994/95 (n = 4447), from a postal questionnaire in 1997/98 (n = 2998), and from the KORA (Cooperative Health Research in the Region of Augsburg) F3 survey in 2004/05 (n = 2774); all surveys longitudinally investigated the same individuals.

https://doi.org/10.1371/journal.pone.0139244.s001

(TIF)

S1 Table. Cut-off points of daily intake amounts for building tertiles in baseline and follow-up surveys and their mean values.

For building of tertiles, cut-off values were included in the lower category.

https://doi.org/10.1371/journal.pone.0139244.s002

(DOC)

Acknowledgments

We would like to thank the participants in and the staff of the MONICA/KORA studies for their efforts and contribution. We thank Andrea Schneider for her contribution to data management.

Author Contributions

Conceived and designed the experiments: SS BT. Performed the experiments: SS MH BF CH CM AP BT. Analyzed the data: SS. Wrote the paper: SS. Gave advice for statistical analyses: AZ JB. Read and approved the final manuscript: AZ MH BF CH JB CM AP BT.

References

  1. 1. Nathan DM, Turgeon H, Regan S. Relationship between glycated haemoglobin levels and mean glucose levels over time. Diabetologia. 2007 50: 2239–2244. pmid:17851648
  2. 2. World Health Organization. Use of Glycated Haemoglobin (HbA1c) in the Diagnosis of Diabetes Mellitus. 2011.
  3. 3. Zhang Y, Hu G, Yuan Z, Chen L. Glycosylated hemoglobin in relationship to cardiovascular outcomes and death in patients with type 2 diabetes: a systematic review and meta-analysis. PLoS One. 2012 7: e42551. pmid:22912709
  4. 4. Verdoia M, Schaffer A, Cassetti E, Barbieri L, Di Ruocco MV, Perrone-Filardi P, et al. Glycosylated hemoglobin and coronary artery disease in patients without diabetes mellitus. Am J Prev Med. 2014 47: 9–16. pmid:24750972
  5. 5. Haring R, Baumeister SE, Lieb W, von Sarnowski B, Volzke H, Felix SB, et al. Glycated hemoglobin as a marker of subclinical atherosclerosis and cardiac remodeling among non-diabetic adults from the general population. Diabetes Res Clin Pract. 2014 105: 416–423. pmid:24972524
  6. 6. Ikeda F, Doi Y, Ninomiya T, Hirakawa Y, Mukai N, Hata J, et al. Haemoglobin A1c even within non-diabetic level is a predictor of cardiovascular disease in a general Japanese population: the Hisayama Study. Cardiovasc Diabetol. 2013 12: 164. pmid:24195452
  7. 7. Ashraf H, Boroumand MA, Amirzadegan A, Talesh SA, Davoodi G. Hemoglobin A1C in non-diabetic patients: an independent predictor of coronary artery disease and its severity. Diabetes Res Clin Pract. 2013 102: 225–232. pmid:24176244
  8. 8. Sarwar N, Aspelund T, Eiriksdottir G, Gobin R, Seshasai SR, Forouhi NG, et al. Markers of dysglycaemia and risk of coronary heart disease in people without diabetes: Reykjavik prospective study and systematic review. PLoS Med. 2010 7: e1000278. pmid:20520805
  9. 9. Khaw KT, Wareham N, Bingham S, Luben R, Welch A, Day N. Association of hemoglobin A1c with cardiovascular disease and mortality in adults: the European prospective investigation into cancer in Norfolk. Ann Intern Med. 2004 141: 413–420. pmid:15381514
  10. 10. Xu R, Zhang S, Tao A, Chen G, Zhang M. Influence of vitamin E supplementation on glycaemic control: a meta-analysis of randomised controlled trials. PLoS One. 2014 9: e95008. pmid:24740143
  11. 11. Lonn E, Yusuf S, Hoogwerf B, Pogue J, Yi Q, Zinman B, et al. Effects of vitamin E on cardiovascular and microvascular outcomes in high-risk patients with diabetes: results of the HOPE study and MICRO-HOPE substudy. Diabetes Care. 2002 25: 1919–1927. pmid:12401733
  12. 12. Shargorodsky M, Debby O, Matas Z, Zimlichman R. Effect of long-term treatment with antioxidants (vitamin C, vitamin E, coenzyme Q10 and selenium) on arterial compliance, humoral factors and inflammatory markers in patients with multiple cardiovascular risk factors. Nutr Metab (Lond). 2010 7: 55.
  13. 13. Rytter E, Vessby B, Asgard R, Ersson C, Moussavian S, Sjodin A, et al. Supplementation with a combination of antioxidants does not affect glycaemic control, oxidative stress or inflammation in type 2 diabetes subjects. Free Radic Res. 2010 44: 1445–1453. pmid:20942575
  14. 14. Sollid ST, Hutchinson MY, Fuskevag OM, Figenschau Y, Joakimsen RM, Schirmer H, et al. No effect of high-dose vitamin D supplementation on glycemic status or cardiovascular risk factors in subjects with prediabetes. Diabetes Care. 2014 37: 2123–2131. pmid:24947792
  15. 15. Oosterwerff MM, Eekhoff EM, Van Schoor NM, Boeke AJ, Nanayakkara P, Meijnen R, et al. Effect of moderate-dose vitamin D supplementation on insulin sensitivity in vitamin D-deficient non-Western immigrants in the Netherlands: a randomized placebo-controlled trial. Am J Clin Nutr. 2014 100: 152–160. pmid:24898240
  16. 16. Jorde R, Strand Hutchinson M, Kjaergaard M, Sneve M, Grimnes G. Supplementation with High Doses of Vitamin D to Subjects without Vitamin D Deficiency May Have Negative Effects: Pooled Data from Four Intervention Trials in Tromso. ISRN Endocrinol. 2013 2013: 348705. pmid:23577264
  17. 17. George PS, Pearson ER, Witham MD. Effect of vitamin D supplementation on glycaemic control and insulin resistance: a systematic review and meta-analysis. Diabet Med. 2012 29: e142–150. pmid:22486204
  18. 18. Gonzalez-Ortiz M, Martinez-Abundis E, Robles-Cervantes JA, Ramirez-Ramirez V, Ramos-Zavala MG. Effect of thiamine administration on metabolic profile, cytokines and inflammatory markers in drug-naive patients with type 2 diabetes. Eur J Nutr. 2011 50: 145–149. pmid:20652275
  19. 19. Rabbani N, Alam SS, Riaz S, Larkin JR, Akhtar MW, Shafi T, et al. High-dose thiamine therapy for patients with type 2 diabetes and microalbuminuria: a randomised, double-blind placebo-controlled pilot study. Diabetologia. 2009 52: 208–212. pmid:19057893
  20. 20. Sudchada P, Saokaew S, Sridetch S, Incampa S, Jaiyen S, Khaithong W. Effect of folic acid supplementation on plasma total homocysteine levels and glycemic control in patients with type 2 diabetes: a systematic review and meta-analysis. Diabetes Res Clin Pract. 2012 98: 151–158. pmid:22727498
  21. 21. Sabherwal S, Bravis V, Devendra D. Effect of oral vitamin D and calcium replacement on glycaemic control in South Asian patients with type 2 diabetes. Int J Clin Pract. 2010 64: 1084–1089. pmid:20642708
  22. 22. Eriksson J, Kohvakka A. Magnesium and ascorbic acid supplementation in diabetes mellitus. Ann Nutr Metab. 1995 39: 217–223. pmid:8546437
  23. 23. Song Y, He K, Levitan EB, Manson JE, Liu S. Effects of oral magnesium supplementation on glycaemic control in Type 2 diabetes: a meta-analysis of randomized double-blind controlled trials. Diabet Med. 2006 23: 1050–1056. pmid:16978367
  24. 24. Khan MI, Siddique KU, Ashfaq F, Ali W, Reddy HD, Mishra A. Effect of high-dose zinc supplementation with oral hypoglycemic agents on glycemic control and inflammation in type-2 diabetic nephropathy patients. J Nat Sci Biol Med. 2013 4: 336–340. pmid:24082728
  25. 25. Roussel AM, Kerkeni A, Zouari N, Mahjoub S, Matheau JM, Anderson RA. Antioxidant effects of zinc supplementation in Tunisians with type 2 diabetes mellitus. J Am Coll Nutr. 2003 22: 316–321. pmid:12897047
  26. 26. Rafat D, Rabbani TK, Ahmad J, Ansari MA. Influence of iron metabolism indices on HbA1c in non-diabetic pregnant women with and without iron-deficiency anemia: effect of iron supplementation. Diabetes Metab Syndr. 2012 6: 102–105. pmid:23153978
  27. 27. Faghihi T, Radfar M, Barmal M, Amini P, Qorbani M, Abdollahi M, et al. A randomized, placebo-controlled trial of selenium supplementation in patients with type 2 diabetes: effects on glucose homeostasis, oxidative stress, and lipid profile. Am J Ther. 2014 21: 491–495. pmid:23633679
  28. 28. Boeing H, Weisgerber UM, Jeckel A, Rose HJ, Kroke A. Association between glycated hemoglobin and diet and other lifestyle factors in a nondiabetic population: cross-sectional evaluation of data from the Potsdam cohort of the European Prospective Investigation into Cancer and Nutrition Study. Am J Clin Nutr. 2000 71: 1115–1122. pmid:10799373
  29. 29. Sargeant LA, Wareham NJ, Bingham S, Day NE, Luben RN, Oakes S, et al. Vitamin C and hyperglycemia in the European Prospective Investigation into Cancer—Norfolk (EPIC-Norfolk) study: a population-based study. Diabetes Care. 2000 23: 726–732. pmid:10840986
  30. 30. Shoff SM, Mares-Perlman JA, Cruickshanks KJ, Klein R, Klein BE, Ritter LL. Glycosylated hemoglobin concentrations and vitamin E, vitamin C, and beta-carotene intake in diabetic and nondiabetic older adults. Am J Clin Nutr. 1993 58: 412–416. pmid:8237854
  31. 31. Wang L, Gaziano JM, Norkus EP, Buring JE, Sesso HD. Associations of plasma carotenoids with risk factors and biomarkers related to cardiovascular disease in middle-aged and older women. Am J Clin Nutr. 2008 88: 747–754. pmid:18779292
  32. 32. Suzuki K, Ito Y, Nakamura S, Ochiai J, Aoki K. Relationship between serum carotenoids and hyperglycemia: a population-based cross-sectional study. J Epidemiol. 2002 12: 357–366. pmid:12395879
  33. 33. Hypponen E, Power C. Vitamin D status and glucose homeostasis in the 1958 British birth cohort: the role of obesity. Diabetes Care. 2006 29: 2244–2246. pmid:17003300
  34. 34. The World Health Organization MONICA Project (monitoring trends and determinants in cardiovascular disease): a major international collaboration. WHO MONICA Project Principal Investigators. J Clin Epidemiol. 1988 41: 105–114. pmid:3335877
  35. 35. Lowel H, Doring A, Schneider A, Heier M, Thorand B, Meisinger C, et al. The MONICA Augsburg surveys—basis for prospective cohort studies. Gesundheitswesen. 2005 67 Suppl 1: S13–18. pmid:16032512
  36. 36. Holle R, Happich M, Lowel H, Wichmann HE, Group MKS. KORA—a research platform for population based health research. Gesundheitswesen. 2005 67 Suppl 1: S19–25. pmid:16032513
  37. 37. Mühlberger N, Behrend C, Stark R, Holle R. [Database-supported identification and entry of drug data in health studies—experience with the IDOM software]. Informatik, Biometrie und Epidemiologie in Medizin und Biologie. 2003 34: 601–611.
  38. 38. Schwab S, Heier M, Schneider A, Fischer B, Huth C, Peters A, et al. The use of dietary supplements among older persons in southern Germany—results from the KORA-age study. J Nutr Health Aging. 2014 18: 510–519. pmid:24886738
  39. 39. Winkler G, Döring A, Keil U. [Mealtime patterns in a southern German population. Results from the WHO MONICA 1984/1985 Augsburg nutritional survey project]. Z Ernährungswiss. 1995 34: 2–9. pmid:7785293
  40. 40. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010 33 Suppl 1: S62–69. pmid:20042775
  41. 41. The effect of vitamin E and beta carotene on the incidence of lung cancer and other cancers in male smokers. The Alpha-Tocopherol, Beta Carotene Cancer Prevention Study Group. N Engl J Med. 1994 330: 1029–1035. pmid:8127329
  42. 42. Gargari BP, Aghamohammadi V, Aliasgharzadeh A. Effect of folic acid supplementation on biochemical indices in overweight and obese men with type 2 diabetes. Diabetes Res Clin Pract. 2011 94: 33–38. pmid:21802161
  43. 43. Child DF, Hudson PR, Jones H, Davies GK, De P, Mukherjee S, et al. The effect of oral folic acid on glutathione, glycaemia and lipids in Type 2 diabetes. Diabetes Nutr Metab. 2004 17: 95–102. pmid:15244101
  44. 44. Akbaraly TN, Fontbonne A, Favier A, Berr C. Plasma carotenoids and onset of dysglycemia in an elderly population: results of the Epidemiology of Vascular Ageing Study. Diabetes Care. 2008 31: 1355–1359. pmid:18390802
  45. 45. Vivekananthan DP, Penn MS, Sapp SK, Hsu A, Topol EJ. Use of antioxidant vitamins for the prevention of cardiovascular disease: meta-analysis of randomised trials. Lancet. 2003 361: 2017–2023. pmid:12814711
  46. 46. Kaulmann A, Bohn T. Carotenoids, inflammation, and oxidative stress—implications of cellular signaling pathways and relation to chronic disease prevention. Nutr Res. 2014 34: 907–929. pmid:25134454
  47. 47. Aruna RV, Ramesh B, Kartha VN. Effect of betacarotene on protein glycosylation in alloxan induced diabetic rats. Ind J Exp Biol. 1999 37: 399–401.
  48. 48. Bumke-Vogt C, Osterhoff MA, Borchert A, Guzman-Perez V, Sarem Z, Birkenfeld AL, et al. The flavones apigenin and luteolin induce FOXO1 translocation but inhibit gluconeogenic and lipogenic gene expression in human cells. PLoS One. 2014 9: e104321. pmid:25136826
  49. 49. Hozawa A, Jacobs DR Jr, Steffes MW, Gross MD, Steffen LM, Lee DH. Associations of serum carotenoid concentrations with the development of diabetes and with insulin concentration: interaction with smoking: the Coronary Artery Risk Development in Young Adults (CARDIA) Study. Am J Epidemiol. 2006 163: 929–937. pmid:16597706
  50. 50. Dietrich M, Block G, Norkus EP, Hudes M, Traber MG, Cross CE, et al. Smoking and exposure to environmental tobacco smoke decrease some plasma antioxidants and increase gamma-tocopherol in vivo after adjustment for dietary antioxidant intakes. Am J Clin Nutr. 2003 77: 160–166. pmid:12499336
  51. 51. Bilous R, Donnelly R. Handbook of Diabetes: Wiley-Blackwell; 2010.