High-Level Circulating Total Calcium and Low Phosphate as Predictors of Insulin Resistance among Non-Diabetic Taxi-Motorbike Drivers Living and Working in Cotonou, Benin ()
1. Introduction
Insulin resistance (IR) is defined as a decreased sensitivity of the body cells to normal insulin concentrations [1]. The pathogenesis of IR is complex and involves several etiological factors, such as hyperinsulinemia, hyperlipidemia and adipokines (i.e., hormone released from adipocytes), all of which crosstalk with insulin signaling pathways [2]. IR is recognized as the cornerstone of the metabolic syndrome (MetS), which is a clustering of metabolic risk factors including hyperglycemia, obesity, dyslipidemia, and hypertension. Insulin resistant patients had an increased risk of developing type 2 diabetes (T2D) and cardiovascular diseases (CVDs) [3]. Importantly, the burden of T2D is rising globally and even in Africa [4] [5]. Worldwide, diabetes is the ninth leading cause of mortality, with over 1 million deaths in 2017 [4]. Moreover, the estimated number of adults with diabetes in 2030 is projected to be 366 million, and that of hypertension will be 1.56 billion in 2025 [6]. Therefore, preventive strategies are needed to reduce the burden of non-communicable diseases (NCDs), including T2D. It is well known that IR precedes many years before the clinical diagnosis of diabetes in healthy patients [7] [8]. As such, IR may be considered as a critical target for primary prevention of cardiometabolic diseases. Screening for IR predictors would be valuable to reduce the likelihood of progression from early stage of IR to T2D or CVDs.
Previous studies have revealed that circulating total calcium (CTCa) levels (i.e., 1% of the total body calcium), are associated with increased fasting plasma glucose and IR [9] [10] [11], which are characteristic features of prediabetic states. Consistently, cross-sectional and longitudinal studies demonstrated that elevated CTCa levels were associated with increased risk of developing MetS, T2D, as well as CVDs mortality [12] [13] [14], similarly to reports on hyperparathyroidism, an endocrine disorder characterized by elevated calcium levels [15]. Conversely, epidemiologic studies have shown that phosphate concentrations were negatively correlated with both blood glucose and IR levels [11] [16]. However, the knowledge of IR predictors is lacking among populations of Benin, although hyperinsulinemia rate is very high (e.g., 82%, [17]) with an overall IR prevalence ranging between 17.7% and 25.5% [18] [19] [20]. To the best of our knowledge, the influence of CTCa and phosphate levels on IR has never been explored in populations of Benin.
We anticipated that imbalance in CTCa or phosphate levels may predict IR risk among normoglycemic patients. Therefore, we conducted this cross-sectional study to examine whether plasma CTCa and phosphate levels within the normal ranges are associated with the risk of developing IR in non-diabetic taxi-motorbike drivers (TMDs) living and working in Cotonou city [21] [22].
2. Patients and Methods
2.1. Data Source and Study Participants
We conducted several surveys (between 2004-2018) to investigate the health impacts of air pollution on exposed populations, including TMDs. However, surveillance and research on NCDs are still lacking in TMDs. In the current study, we selected the 2009 survey which offered comprehensive health checkups, including assessments of cardiometabolic markers among TMDs. This was a retrospective cross-sectional study that analyzed plasma biochemistry data from our 2009 survey. The study population has been described previously [21] [22].
Individuals fulfilling the following criteria were included in the study: male non-smokers without diabetes or CVDs, age ≥ 20 years, and having measurements of variables of interest. Participants having fasting glucose level > 7.0 mmol/L, or without insulin, calcium, phosphate, blood lipids, and uric acid records were excluded. A total of 147 TMDs were assessed for eligibility but 134 met predetermined criteria and were included in the analyses reported in this paper. Written informed consent was obtained from each participant prior to enrolment in the study. The study was evaluated and approved by the Benin Environmental Agency.
2.2. Blood Sample Collection and Laboratory Testing
Detailed information about the blood collection and processing has been previously described [20]. All biological analyses were performed by standardized methods within the research Unit NGERE: “Nutrition-Génétique-Exposition aux risques environnementaux”, Faculté de Médecine, Nancy, France.
2.3. Covariates
Covariates of IR were selected and controlled based on previously published studies [20]. Demographic and clinical information such as age, alcohol intake, height and weight, systolic (SBP) and diastolic blood pressure (DBP) were obtained from each participant through face-to-face interviews by trained doctors. The body mass index (BMI) was calculated by dividing weight in kilograms by the square of height in meters (kg/m2). Fasting plasma glucose, uric acid, phosphate, CTCa, blood lipids, such as total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) were obtained from laboratory analyses, which were performed on a clinical chemistry analyzer (Siemens, Germany). Plasma insulin was determined by radioimmunoassay using a commercial kit (BI INSULIN IRMA, Biorad, Mames la Coquette, France).
2.4. Definition of Variables
Fasting insulin level ≥ 15 µU/ml was considered elevated [23]. Hypertension was defined as SBP ≥ 140 mmHg or DBP ≥ 90 mmHg [24]. Alcohol intake was defined as the average consumption of one or more alcoholic drinks per day. The homeostatic model assessment-insulin resistance (HOMA-IR) was assessed using the formula described by Matthews et al. [25]. HOMA-IR = Fasting plasma insulin (µU/ml) × Fasting plasma glucose (mmol/L)/22.5. IR was defined as the 75th percentile of HOMA-IR value [25].
2.5. Statistical Analysis
Data are presented as percentage for categorical variables and as mean (± standard deviation, SD) for continuous variables. Survey participants were divided into three groups based on CTCa and phosphate levels: low, middle, and high groups. The cut-off points for CTCa and phosphate were <2.43, 2.44 - 2.50, >2.50 mmol/L and <1.09, 1.10 - 1.23, >1.23 mmol/L, respectively. Demographic and biological characteristics of survey participants were compared by tertiles of CTCa and phosphate using one-way analysis of variance (ANOVA) or chi-square tests as appropriate for the variable. The relationships between IR and CTCa and phosphate levels were examined in three multivariable-adjusted logistic regression models, using backward selection procedure. IR status was set as dependent variable and clinically relevant variables were modeled as predictors. The model 1 adjusted for age and BMI; model 2 additionally adjusted for blood pressure, TC, TG, HDL-C, and LDL-C; and model 3 adjusted for variables in model 2 plus uric acid levels. The low calcium or phosphate level groups were set as the reference groups to calculate the odds ratios (ORs) for IR with the corresponding 95% confidence intervals (CIs) in the middle and high-level groups. Additionally, we analyzed CTCa and phosphate as continuous variables (per SD change). P–values < 0.05 were considered to indicate a statistical significance. Data analysis was performed using IBM SPSS Statistics 20.0 software.
3. Results
3.1. Univariate Analysis of Demographic and Metabolic Parameters Related to Total Calcium and Phosphate Levels
The means (SD) age, CTCa, and phosphate levels of the survey participants were 39.4 (7.8) years, 2.4 (0.4) mmol/L, and 1.2 (0.2) mmol/L, respectively. Alcohol consumption, elevated fasting insulin (hyperinsulinemia), IR, and hypertension were prevalent in 38.1%, 67.2%, 24.6%, and 47.0% of survey participants, respectively (Table 1). The cut-off value for IR (i.e., 75th of HOMA-IR) was 5.9. We also compared demographic and biological characteristics by CTCa and phosphate levels (Table 1). Age was inversely associated with CTCa levels (p = 0.032). Participants with high phosphate levels had low concentrations of fasting insulin and the least HOMA-IR, in comparison with those in the low phosphate levels groups (p = 0.037, p = 0.123, respectively). Participants with high CTCa levels demonstrated marked hyperinsulinemia (p = 0.029), had the highest prevalence of IR (p = 0.014), and elevated TC (p = 0.032) and HDL-C (p = 0.037) levels than did those with low CTCa levels (Table 1).
3.2. Predictors of Insulin Resistance in the Study Participants
Table 2 summarizes factors associated with IR in the study participants. Participants in the second and the third tertiles of phosphate levels had a reduced risk
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Table 1. Univariate analysis of cardiometabolic factors by plasma calcium and phosphate levels.
Values are expressed as mean (standard deviation) or n (%). BMI, body mass index, SBP, systolic blood pressure, DBP, diastolic blood pressure, HOMA-IR, homeostatic model assessment-insulin resistance, TC, total cholesterol, TG, triglycerides, HDL-C, high density lipoprotein cholesterol, LDL-C, low-density lipoprotein cholesterol.
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Table 2. Factors independently associated with insulin resistance in the study population.
Insulin resistance was considered as dependent variable and other biological parameters were set as independent variables. BMI, body index mass, CI, confidence interval, OR, odd ratio, SD, standard deviation. aAdjusted for age and BMI. bAdjusted for age, BMI, blood pressure, total cholesterol, triglycerides, high density lipoprotein, and low–density lipoprotein. cAdjusted for all variables in model 2, plus uric acid levels.
of IR compared to those in the first tertile. In contrast, an increase in the CTCa levels (> 2.50 mmol/L) was related to an increased risk of IR in TMDs.
In the fully adjusted model (i.e., model 3), the OR for developing IR comparing the middle and high phosphate levels to the lowest levels were 0.27 (95% CI: 0.10 - 0.93, p = 0.038) and 0.28 (95% CI: 0.10 - 0.92, p = 0.037), respectively. This inverse association between plasma phosphate levels and IR remained robust when phosphate was analyzed as a continuous variable (per SD increase). The OR for IR comparing the middle and high CTCa levels to the lowest CTCa levels were 2.10 (95% CI: 0.63 - 6.98, p = 0.229) and 6.62 (95% CI: 1.94 - 22.58, p = 0.003), respectively. Additionally, elevated BMI (> 24.28 Kg/m2) was independently associated with an increased IR risk in our study population (OR = 5.45, 95% CI: 1.66 - 17.93, p = 0.005, Table 2). Age, blood pressure or blood lipids indicated no significant associations with IR.
4. Discussion
In the current study, we examined whether CTCa and phosphate levels within the normal ranges associate with IR risk among non-diabetic TMDs living and working in Cotonou. Our results showed that fasting insulin, glucose levels as well as IR level were higher in patients with elevated CTCa than those with low calcium levels. We applied three multivariable-adjusted logistic regression models and checked whether this association ascribed to CTCa was not driven by potential confounders, such as age, BMI, blood lipids or uric acid levels. Interestingly, logistic regression models indicated that CTCa concentrations > 2.50 mmol/L (10.0 mg/dL) were associated with elevated IR risk in TMDs. For example, in the fully adjusted analysis (i.e., model 3), we found that the OR decreased by 10% when comparing the highest versus the lowest CTCa levels, but the association remains statistically significant (OR = 6.62, p = 0.003). This suggests that none of the confounders assessed in this study impacted the link between IR and CTCa levels. This result strengthened findings of previous studies that investigated the association between IR and circulating calcium levels [10] [11]. A cross-sectional study on 1182 healthy subjects from Canada found that subjects with high serum calcium levels had the highest concentration of glucose and IR [10]. Similarly, Yamaguchi et al. examined 480 T2D patients and reported that elevated serum calcium level was strongly associated with fasting glucose and HOMA-IR levels [26].
Furthermore, prospective studies demonstrated that elevated total calcium levels and albumin-corrected calcium were associated with increased risk of incident MetS and diabetes [12] [27] [28]. Consistently, a prospective study by Lorenzo et al. demonstrated that individuals with calcium level ≥ 2.38 mmol/l (9.5 mg/dl) were at increased risk of developing T2D [13].
This study findings also revealed an inverse association between plasma phosphate levels and IR. We found that low plasma phosphate levels were associated with elevated fasting insulin levels and a higher prevalence of IR, similarly to reports of previous studies [16]. Accordingly, logistic regression models indicated that individuals with plasma phosphate > 1.10 mmol/L had a reduced risk of having IR than those in the low phosphate level group. This association remains robust after adjustment for relevant confounders. This finding was consistent with reports by Haap et al. who demonstrated that low serum phosphate levels were associated with elevated blood glucose and a decreased insulin sensitivity [16]. Similarly, a cross-sectional study on 1701 healthy patients reported an inverse association between serum phosphate and HOMA-IR [11]. Furthermore, a growing body of evidence suggests an inverse association between phosphate levels and risk of MetS [29] [30].
The molecular mechanisms explaining the association of elevated CTCa and low phosphate levels with IR are not fully understood. However, it is speculated that elevated calcium levels could decrease glucose uptake by reducing insulin receptor activity or the number of glucose transporters in adipocytes and muscles cells [28] [31]. It is also suggested that glucose-mediated insulin secretion from pancreatic β-cells requires calcium-dependent enzymes and calcium channels [10] [32] [33]. Furthermore, compelling evidences revealed that disturbed calcium homeostasis could lead to functional deterioration of pancreatic β-cells (i.e., production and secretion of insulin) [10] [34]. Additionally, phosphate is required for ATP generation, and it is postulated that low phosphate levels could compromise the phosphorylation of carbohydrate intermediates in the glucose metabolism pathway [35]. This subsequently leads to development of IR.
Our study findings also demonstrated that higher BMI (>24.3 kg/m2) was associated with an increased IR risk, similarly to what was reported in previous studies [36]. Epidemiologic studies associated higher CTCa with overweight/obesity, high blood pressure, and higher TC [37] [38]. In our study, patients with elevated CTCa levels had higher TC and HDL-C levels. However, TC and HDL-C together with blood pressure, TG and LDL-C did not predict IR on logistic regression analyses, probably because of our study design, which included only normoglycemic patients.
Our study had several limitations. This was a cross-sectional study and longitudinal changes in total plasma calcium or phosphate levels are unavailable. Therefore, causality cannot be directly established. Additionally, the sample size was relatively small and participants could only be divided into three groups. This limits generalizability of our findings. Moreover, calcium homeostasis is regulated by vitamin D levels, parathyroid hormone, and ionized calcium. However, no information was available, and we could not evaluate the influence of vitamin D, parathyroid hormone, and ionized calcium on the relationship between plasma calcium and IR risk. Despite its limitations, this study strengthened data of previous studies conducted in other countries. Additionally, TMDs that have been the focus of this study was an understudied and at-risk population. Further, this study adds additional flows to existing literature on IR predictors within Benin. Plasma calcium and phosphate concentrations are easy to measure and cost effective. As such they could be used as potential screening markers to detect IR in the pre-clinical phase. In this regard, reported data may help policy makers when planning and implementing preventive interventions.
5. Conclusion
Our current study demonstrates that higher CTCa (>2.50 mmol/L) and low phosphate levels (<1.10 mmol/L) are strong predictors of IR, in non-diabetic TMDs. Continuous monitoring for these markers may help identify individuals at greatest risk for IR. However, whether elevated CTCa and low phosphate levels are precursors or consequences of IR requires further studies.
Acknowledgements
We gratefully acknowledge taxi-moto drivers whose cooperation made this study possible. We also express our gratefulness to Professors Rosa-Maria Guéant-Rodriguez and Jean-Louis Guéant for their invaluable assistance toward the success of this work.
Source of Funding
The Ministry of Higher Education and Scientific Research in Benin partially covered costs related to sample collection. Laboratory analyses performed in Nancy were fully funded by the Research Unit INSERM UMRS 1256 NGERE: “Nutrition-Génétique-Exposition aux Risques Environnementaux”, Faculté de Médecine, Nancy, France.
Author’s Contribution
All authors contributed to the study design, participated to data acquisition. PHA performed laboratory work, analyzed data, and wrote the manuscript. All authors read and approved the final manuscript.