Abstract
Background and Objectives
Mechanism studies have indicated that magnesium (Mg) and calcium (Ca) have important biological functions in glucose regulation, but epidemiological data on their associations with glycosylated hemoglobin (HbA1c) are sparse. We aimed to explore the associations of Mg and Ca with abnormal HbA1c, and examine the mediating effects of inflammation in coronary artery disease (CAD) Chinese adults.
Methods and Study Design
A hospital–based cross–sectional study of 11934 patients with CAD was conducted. Serum Mg and Ca concentrations were measured.
Results
In multivariable analyses, Mg and Mg/Ca ratio were inversely associated with abnormal HbA1c (Q4 vs Q1: ORMg: 0.61, 95% CIMg: 0.53, 0.71; ORMg/Ca ratio: 0.67, 95% CIMg/Ca ratio: 0.54, 0.84). However, null association of Ca with abnormal HbA1c was shown (Q4 vs Q1: OR: 1.15, 95% CI: 0.92, 1.44). Serum Mg and Mg/Ca ratio were inversely associated with abnormal fasting blood glucose (FBG). In contrast, serum Ca was positively associated with abnormal FBG. Path analysis indicated that there were no mediating effects of hypersensitivity C reactive protein (hsCRP) on Mg and Mg/Ca-abnormal HbA1c associations.
Conclusions
Our study suggested that serum Mg and Mg/Ca ratio were inversely associated with abnormal HbA1c in Chinese adults with CAD. The Mg-abnormal HbA1c relationship might not be mediated by hsCRP.
Key Words: magnesium, calcium, abnormal glycosylated hemoglobin, coronary artery disease, cross–sectional study
Introduction
Glycated hemoglobin (HbA1c) is an index that reflects average blood glucose concentrations over the past 3-4 months.1 It plays an important role in the development of coronary artery disease (CAD).2 Elevated HbA1c level has been proven to be an independent risk factor for mortality in populations with CAD patients.3 Previous studies indicated that magnesium (Mg) and calcium (Ca) are established factors in the risk of CAD4, 5 and might modulate circulating HbA1c concentration in body.6, 7, 8, 9 Thus, it is possible that Mg and Ca might improve the risk and prognosis of CAD by regulating HbA1c concentration. However, the effects of Mg and Ca on HbA1c are less well known.
Ca and Mg have important biological functions in glucose regulation.10, 11 In vitro and animal experiments have revealed the potential role of Ca and Mg in modulating glucose concentrations.12, 13, 14 However, sparse data aimed at examining the associations between blood Ca and HbA1c were inconsistent, showing both inverse15 and positive associations.16, 17 Additionally, some epidemiological studies reported inverse associations of Mg with HbA1c.17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 However, a recent meta-analysis found that
Mg supplementation could not improve HbA1c concentrations.28 Other studies found null correlation between Mg and HbA1c.20, 22, 29 Liu et al. even reported a positive association between serum Mg and HbA1c in individuals with diabetes or central obesity.30 Therefore, the associations of Ca and Mg with HbA1c remained to be speculative. Moreover, CAD patients were more likely to have some degree of lipid and glucose metabolism dysfunction than the general populations. However, it is not clear whether the results from previous research can be generalized to CAD patients.
Additionally, previous evidence revealed that Mg and Ca could modulate inflammatory status,31, 32 which is considered an important regulatory factor of glucose metabolism. However, no study had yet examined whether the associations of Mg and Ca with HbA1c concentration might be mediated by inflammation.
This study aimed to examine the associations of Mg and Ca with abnormal HbA1c and the mediating role of inflammation on the Mg and Ca-abnormal HbA1c association in Chinese adults with CAD.
Methods
Study participants
A hospital–based cross–sectional study was conducted between November 2016 and December 2019 in Wuhan Asia Heart Hospital. 11934 patients (Age: 29 − 89 years; mean age: 61.7 years) with CAD were included in this study. CAD was defined as meeting one of the following criteria: a). history of angina pectoris, myocardial infarction or coronary intervention; b). coronary angiography implied vascular stenosis >50%; c). significant myocardial infarction was presented from electrocardiogram. The present study was conducted based on the Declaration of Helsinki and approved by the ethics committee of Wuhan Asia Heart Hospital (No. 2016–B008). Informed consents were obtained from all the participants.
Data collection
The information collected from all CAD patients included height, weight, smoking, alcohol intake, age, sex, antihypertensive and hypoglycemic agent use based on medical records. Body mass index (BMI) was calculated as weight (kg)/height (m2).
Serum Mg and Ca concentrations were measured by NexION 350X (PerkinElmer, USA). The pressurizing collision cell was used to eliminate polyatomic interferences in the kinetic energy discrimination mode.33 HbA1c concentrations in the red blood cells was measured using a Bole glycated hemoglobin D-10 kit with a Bole glycated hemoglobin analyzer D-10. Fasting blood glucose (FBG) was measured by a commercial kit (Roche Diagnostics GmbH, China). High-sensitivity C-reactive protein (hsCRP) was measured by a Cardiac CRP (Latex) High Sensitive kit. Abnormal HbA1c and abnormal FBG was defined as: HbA1c ≥ 6.5% and FBG ≥ 5.6 mmol/L.34
Statistical analysis
Continuous variables were presented as mean (standard deviation). Discrete variables were presented as frequencies (percentage). Comparisons of differences between groups were tested using the analysis of variance. All subjects were divided into sex-specific quartile groups according to the rank of serum Mg and Ca concentrations and Mg/Ca ratio. The higher the quartile levels, the higher the corresponding exposure levels. Quartile 1 (Q1) was the lowest concentration group and Q4 was the highest concentration group. Logistic regression models were performed to assess the associations of Mg and Ca with abnormal HbA1c. Multivariable adjusted models were performed as follows: Model 1 adjusted for age and sex; Model 2 was further adjusted for smoking status, alcohol consumption, BMI, hypoglycemic and antihypertensive agent use. The mediating effects of hsCRP on the associations of serum Mg, Ca and Mg/Ca ratio with abnormal HbA1c and abnormal FBG were examined by path analyses35 using SPSS AMOS v.24 (IBM, Armonk, NY). Two-tailed p≤ 0.05 was considered statistically significant.
Results
Characteristics of subjects
As shown in Table 1, all participants were divided into different quartiles according to serum Mg (n = 11934) and Ca (n = 4606) levels. A higher age and lower proportion of hypoglycemic drugs intake were observed in subjects with higher serum Mg concentrations. A lower age and hsCRP were observed in subjects with higher serum Ca concentrations. No significant correlations were found between serum Mg, Ca and other indices (e.g., BMI, alcohol drinker, smoking status, and hypotensor agent using, all p trend > 0.05).
Table 1.
Baseline characteristics of the study participants with coronary artery disease by quartiles of serum Mg and Ca†
| Variables | Quartiles by Mg and Ca |
p-trend | ||||
|---|---|---|---|---|---|---|
| Q1 | Q2 | Q3 | Q4 | |||
| Mg, n | 2829 | 3312 | 2729 | 3064 | ||
| Age, years | 61.1 ± 9.81 | 61.6 ± 10.1 | 61.7 ± 10.0 | 62.4 ± 10.1 | <0.001 | |
| Sex | 0.196 | |||||
| Male, n (%) | 1777 (62.8) | 2083 (62.9) | 1594 (58.4) | 2023 (66.0) | ||
| Female, n (%) | 1052 (37.2) | 1229 (37.1) | 1135 (41.6) | 1041 (34.0) | ||
| BMI, kg/m2 | 25.7 ± 16.1 | 26.0 ± 17.4 | 25.4 ± 13.1 | 25.9 ± 19.2 | 0.923 | |
| Alcohol drinker, n (%) | 253 (8.9) | 308 (9.3) | 237 (8.7) | 279 (9.1) | 0.969 | |
| Smoker, n (%) | 424 (15.0) | 452 (13.6) | 367 (13.4) | 442 (14.4) | 0.511 | |
| Hypotensor agents user, n (%) | 1357 (48.0) | 1576 (47.6) | 1307 (47.9) | 1518 (49.5) | 0.204 | |
| Hypoglycemic agents user, n (%) | 676 (23.9) | 573 (17.3) | 404 (14.8) | 461 (15.0) | <0.001 | |
| hsCRP, mg/L (n=5208) | 6.20 ± 0.35 | 5.14 ± 0.37 | 5.05 ± 0.35 | 5.71 ± 0.39 | 0.327 | |
| Ca, n | 1146 | 1183 | 1171 | 1106 | ||
| Age, years | 64.2 ± 9.92 | 62.1 ± 9.73 | 61.0 ± 9.97 | 59.5 ± 10.7 | <0.001 | |
| Sex | 0.461 | |||||
| Male, n (%) | 730 (63.7) | 788 (66.6) | 757 (64.6) | 729 (65.9) | ||
| Female, n (%) | 416 (36.3) | 395 (33.4) | 414 (35.4) | 377 (34.1) | ||
| BMI, kg/m2 | 25.3 ± 21.1 | 25.1 ± 12.3 | 26.1 ± 18.5 | 25.6 ± 13.2 | 0.432 | |
| Alcohol drinker, n (%) | 87 (7.6) | 107 (9.0) | 109 (9.3) | 94 (8.5) | 0.415 | |
| Smoker, n (%) | 150 (13.1) | 179 (15.1) | 149 (12.7) | 153 (13.8) | 0.985 | |
| Hypotensor agents user, n (%) | 547 (47.7) | 536 (45.3) | 551 (47.1) | 516 (46.7) | 0.858 | |
| Hypoglycemic agents user, n (%) | 236 (20.6) | 207 (17.5) | 203 (17.3) | 206 (18.6) | 0.249 | |
| hsCRP, mg/L (n=1911) | 12.8 ± 0.78 | 7.34 ± 0.78 | 6.55 ± 0.84 | 7.29 ± 0.78 | <0.001 | |
BMI, body mass index. Ca, calcium; hsCRP, hypersensitivity C reactive protein; Mg, Magnesium; Q, quartile.
Values were means ± standard deviations or n (%).
p values were calculated using analyses of covariance.
Associations of Mg, Ca, Mg/Ca ratio and abnormal HbA1c
In general, serum Mg and Mg/Ca ratio showed inverse associations with abnormal HbA1c, while Ca exhibited null association with abnormal HbA1c (Table 2). Adjusting for sex and age in Model 1, inverse associations for serum Mg and Mg/Ca ratio [Q4 vs Q1: ORs (95% CI): 0.53 (0.47, 0.60), 0.64 (0.53, 0.77) respectively]. Ca was not associated with abnormal HbA1c (OR: 1.06, 95% CI: 0.88, 1.28). After further adjusting for the other potential covariates in Model 2, Mg and Mg/Ca ratio were inversely associated with abnormal HbA1c (Q4 vs Q1: ORMg: 0.61, 95% CIMg: 0.53, 0.71; ORMg/Ca ratio: 0.67, 95% CIMg/Ca ratio: 0.54, 0.84). However, null association of Ca concentrations with abnormal HbA1c were showed (Q4 vs Q1: OR: 1.15, 95% CI: 0.92, 1.44).
Table 2.
Association of Mg and Ca concentrations with abnormal HbA1c for all participants
| Variables | Quartiles by Mg and Ca |
|||
|---|---|---|---|---|
| Q1 | Q2 | Q3 | Q4 | |
| Mg | ||||
| Mean (SD) | 0.77 ± 0.04 | 0.83 ± 0.01 | 0.88 ± 0.01 | 0.97 ± 0.12 |
| Case/N | 911/2829 | 776/3312 | 570/2729 | 632/3064 |
| OR (95%CI) | ||||
| Model 1† | 1 | 0.64 (0.57, 0.71)** | 0.55 (0.48, 0.62)** | 0.53 (0.47, 0.60)** |
| Model 2‡ | 1 | 0.70 (0.61, 0.81)** | 0.65 (0.56, 0.75)** | 0.61 (0.53, 0.71)** |
| Ca | ||||
| Mean (SD) | 2.13 ± 0.08 | 2.24 ± 0.02 | 2.31 ± 0.02 | 2.41 ± 0.07 |
| Case/N | 325/1146 | 288/1183 | 286/1171 | 312/1106 |
| OR (95%CI) | ||||
| Model 1† | 1 | 0.84 (0.70, 1.01) | 0.85 (0.71, 1.03) | 1.06 (0.88, 1.28) |
| Model 2‡ | 1 | 0.88 (0.70, 1.10) | 0.90 (0.72, 1.13) | 1.15 (0.92, 1.44) |
| Mg/Ca ratio | ||||
| Mean (SD) | 0.33 ± 0.02 | 0.37 ± 0.01 | 0.39 ± 0.01 | 0.44 ± 0.07 |
| Case/N | 378/1150 | 281/1152 | 264/1152 | 288/1152 |
| OR (95%CI) | ||||
| Model 1† | 1 | 0.64 (0.53, 0.77)** | 0.59 (0.49, 0.71)** | 0.64 (0.53, 0.77)** |
| Model 2‡ | 1 | 0.71 (0.57, 0.89)* | 0.63 (0.50, 0.78)** | 0.67 (0.54, 0.84)** |
Ca, calcium; Mg, Magnesium; OR, odd ratio; 95% CI, 95% confidence interval; Q, quartile; SD, standard deviation; HbA1c, glycosylated hemoglobin.
Model 1 adjusted for age and sex.
Model 2 further adjusted for smoking status, BMI, alcohol consumption, hypotensor and hypoglycemic drug use.
p< 0.05
p< 0.001.
Table 3 showed the stratified analyses by sex. In multivariable analysis, serum Mg and Mg/Ca ratio were inversely associated with abnormal HbA1c (ORMg: 0.67, 95% CIMg: 0.56, 0.80; ORMg/Ca ratio: 0.69, 95% CIMg/Ca ratio: 0.52, 0.91) in the fourth quartile compared to the first quartile in men. Inverse associations between serum Mg and Mg/Ca ratio and abnormal HbA1c were also observed in women (ORMg: 0.51, 95% CIMg: 0.40, 0.64; ORMg/Ca ratio: 0.65, 95% CIMg/Ca ratio: 0.45, 0.94). There was no significant association between Ca and abnormal HbA1c in both men and women. Additionally, multivariable analysis found that Mg and Ca were also inversely associated with abnormal HbA1c in subjects without using hypoglycemic medications. The corresponding OR (95% CI) were 0.66 (0.56, 0.78) for Mg and 0.71 (0.56, 0.92) for Ca in the fourth quartile compared to the first quartile (Supplementary Table 1).
Table 3.
Association of Mg and Ca concentrations with abnormal HbA1c by sex (OR 95% CI)
| Variables | Quartiles by Mg and Ca |
|||
|---|---|---|---|---|
| Q1 | Q2 | Q3 | Q4 | |
| Mg | ||||
| Men | ||||
| Model 1† | 1 | 0.71 (0.61, 0.82)** | 0.70 (0.60, 0.82)** | 0.63 (0.54, 0.73)** |
| Model 2‡ | 1 | 0.73 (0.62, 0.87)** | 0.77 (0.64, 0.93)* | 0.67 (0.56, 0.80)** |
| Women | ||||
| Model 1† | 1 | 0.53 (0.44, 0.63)** | 0.37 (0.30, 0.45)** | 0.39 (0.32, 0.48)** |
| Model 2‡ | 1 | 0.64 (0.52, 0.80)** | 0.48 (0.38, 0.61)** | 0.51 (0.40, 0.64)** |
| Ca | ||||
| Men | ||||
| Model 1† | 1 | 0.86 (0.68, 1.09) | 0.95 (0.75, 1.20) | 1.18 (0.93, 1.50) |
| Model 2‡ | 1 | 0.89 (0.67, 1.18) | 0.93 (0.70, 1.24) | 1.22 (0.92, 1.62) |
| Women | ||||
| Model 1† | 1 | 0.82 (0.61, 1.11) | 0.72 (0.53, 0.97)* | 0.88 (0.65, 1.19) |
| Model 2‡ | 1 | 0.87 (0.60, 1.27) | 0.83 (0.57, 1.20) | 0.97 (0.66, 1.41) |
| Mg/Ca ratio | ||||
| Men | ||||
| Model 1† | 1 | 0.74 (0.59, 0.94)* | 0.74 (0.59, 0.94)* | 0.69 (0.55, 0.87)* |
| Model 2‡ | 1 | 0.74 (0.56, 0.98)* | 0.75 (0.57, 0.99)* | 0.69 (0.52, 0.91)* |
| Women | ||||
| Model 1† | 1 | 0.49 (0.36, 0.67)** | 0.38 (0.28, 0.52)** | 0.55 (0.41, 0.75)** |
| Model 2‡ | 1 | 0.67 (0.46, 0.97)* | 0.44 (0.30, 0.65)** | 0.65 (0.45, 0.94)* |
Ca, calcium; Mg, Magnesium; OR, odd ratio; 95% CI, 95% confidence interval; Q, quartile; HbA1c, glycosylated hemoglobin.
Model 1 adjusted for age.
Model 2 further adjusted for smoking status, BMI, alcohol consumption, hypotensor and hypoglycemic drug use.
p< 0.05
p< 0.001.
Associations of Mg, Ca and Mg/Ca ratio with abnormal fasting blood glucose
As shown in Supplementary Table 2, serum Mg and Mg/Ca ratio were inversely associated with abnormal FBG in both Model 1 and 2. In contrast, serum Ca was positively associated with abnormal FBG.
Path analysis
Path analysis was conducted to evaluate whether hsCRP had effects on the Mg and Mg/Ca-abnormal HbA1c associations. Figure 1 indicated that serum Mg and Mg/Ca ratio did not have direct effects on hsCRP. Mediating effects of hsCRP on serum Mg and Mg/Ca-abnormal HbA1c associations were not found. Similarly, no mediating effects of hsCRP on serum Mg and Mg/Ca-abnormal FBG associations were observed (Supplementary Figure 1).
Figure 1.
The mediating effects of hsCRP on the Mg and Mg/Ca-abnormal HbA1c associations among subjects with CAD in path analyses. CAD, coronary artery disease; Ca, calcium; hsCRP, hypersensitivity C reactive protein; Mg, magnesium; HbA1c, glycosylated hemoglobin.
Discussion
In this hospital–based cross–sectional study of patients with CAD, we observed graded and inverse associations of serum Mg and Mg/Ca ratio with abnormal HbA1c. These associations might not be mediated by hsCRP. Additionally, there was no significant association between serum Ca and abnormal HbA1c. To our knowledge, our study was the first to examine the associations of serum Mg, Ca and Mg/Ca ratio with abnormal HbA1c in Chinese adults with CAD. Our results indicated that serum Mg might influence HbA1c concentrations.
Emerging evidence focused on the health benefits of Mg in patients with cardiovascular diseases. Previous studies demonstrated that higher circulating Mg concentrations were associated with lower risk of cardiovascular diseases.36 Mg appears to play an important role in protecting against cardiovascular diseases37 by regulating glycometabolism.10 Some studies evaluated the associations between Mg and HbA1c.17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 However, these findings were contradictory. Bertinato et al. pointed out that serum Mg was negatively correlated with HbA1c (r = − 0.02).26 Ozcaliskan et al. observed a negative relationship between serum Mg and HbA1c values in patients with diabetes mellitus (r = − 0.309).20 This negative association was also observed in other studies involving patients with diabetes mellitus17, 18, 19, 23, 24, 25, 27 or pre-diabetes.21 An animal study also demonstrated that Mg might improve HbA1C concentrations via regulating lipid profiles, energy metabolism and oxidative state as well as activating glucose transporter-4 in skeletal muscle.6 Consistent with these previous studies, we found an inverse association between Mg and abnormal HbA1c in patients with CAD. Nevertheless, a recent meta-analysis of randomized controlled trials revealed Mg supplementation had no significant effect on plasma concentrations of HbA1c.28 It is possible that HbA1c may not accurately reflect the effects of short-term clinical trials on glucose concentrations, as HbA1c is an index of overall glycemia over the past 3-4 months.1 Other studies also found null association between Mg and HbA1c in patients with diabetes mellitus.20, 22, 29 A positive association between serum Mg and HbA1c was observed in individuals with diabetes or central obesity (HbA1c: 5.7% in high Mg ≥ 0.95 mmol/L group vs 5.3% in low Mg ≤ 0.65 mmol/L).30 Small sample (n=57) and the presence of long-duration diabetes might attenuate the relationship between serum Mg concentrations and HbA1c.20
Targeting Ca modulation is an emerging area for innovative heart failure treatments, which could significantly enhance cardiac function and improve disease outcomes.38 Previous studies also demonstrated that Ca played an important role in CAD.5 However, there is limited data on the association between Ca and HbA1c.15, 16, 17 A cross-sectional study observed that serum Ca had a negative correlation with HbA1c concentrations in patients with diabetes mellitus (r = − 0.56).15 Nevertheless, Akter et al. found that serum Ca was positively associated with HbA1c in healthy populations (HbA1c Q4 vs Q1: 5.29% vs 5.24%).16 Wang et al. observed that serum Ca concentrations were positively correlated with HbA1c (Standardization β = 0.17) in patients with diabetes mellitus.17 Our study found null association between serum Ca and HbA1c. Lower Ca concentrations in patients with CAD (2.27 mmol/L [this study]) than those with diabetes mellitus (2.29 mmol/dL15 and 2.34 mmol/L17) might provide a potential explanation for the null results of our study. Different statistical method (person correlation,15 analyses of covariance16 [this study], linear regression analysis17), and subjects (patients with diabetes mellitus,15, 17 healthy populations,16 patients with CAD [this study]) might also explain the inconsistent results among studies.
Strengths and limitations
This study has several strengths. To our knowledge, this was the first study that investigated the associations of Mg and Ca with abnormal HbA1C concentrations and also examined the mediating effects of hsCRP in these relationships in Chinese adults with CAD. Moreover, both abnormal HbA1c and FBG were used as glycaemic indicators for correlation analysis, which strengthens the stability and reliability of our results. Additionally, the relative large sample size and adjustment of potential confounders in our study provided good insights into the associations of Mg and Ca with abnormal HbA1C. Nevertheless, this study also had several limitations. First, no causal associations of Mg and Ca with abnormal HbA1C were established due to the cross-sectional design of the study. Subjects were adults with CAD in this study, thus the generalization of the results is limited. Also, although hypotensor and hypoglycemic agents were considered in multivariable analysis, the use of other cardiovascular drugs was not considered. The associations of Mg and Ca with abnormal HbA1C may be overestimated in our study. Further prospective studies will be needed to validate our findings. Finally, although some potential confounding factors were adjusted in our study, the possibility of bias was not ruled out because of residual confounding.
Conclusion
Generally, our study suggested that serum Mg and Mg/Ca ratio were inversely associated with abnormal HbA1c in Chinese adults with CAD. The glucose regulation of Mg and Mg/Ca ratio reported here might lead to new intervention approaches in abnormal glucose metabolism related diseases among patients with CAD such as diabetes, hypertension and dyslipidemia. Replication of these findings is warranted in experimental settings and in different population.
Acknowledgements
We thank other staff who contributed to this study.
Conflict of Interest and Funding Disclosures
The authors declare no conflict of interest.
This work was partly supported by the Talent Project of Nantong Maternal and Child Health Hospital (No. YYR202005). The funders had no role in the design, analysis or writing of this article.
Supplementary Material
Supplementary data
Funding Statement
This work was partly supported by the Talent Project of Nantong Maternal and Child Health Hospital (No. YYR202005). The funders had no role in the design, analysis or writing of this article.
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