The Calcium-Magnesium Ratio and Macronutrient Intake in Master Athletes

Adequate nutrient intake is essential for athletic performance. Emphasis on macro-nutrient intake of athletes of various sport types, athlete levels, and sexes is emphasized; however, micronutrient intake plays important roles in athletic performance. Calcium is a vital mineral involved in several physiological processes, including skeletal muscle contractions, heart rate conductivity, blood pressure regulation, water balance, energy and fat metabolism, and transportation of nutrients across cell membranes (Kunstel, 2005). Magnesium is critical in processes such as skeletal muscle contraction, energy metabolism, immune system regulation, and muscle function/recovery (Carvil & Cronin, 2010; Hunt, Sukumar, & Volpe, 2021). Adequate magnesium consumption has previously been associated with lower body mass indexes in adolescents (Naseeb, Bruneau, Milliron, et al., 2021). Cooperatively, calcium and magnesium interact in the maintenance of the body’s homeostatic state. Calcium- magnesium ratios have recently been shown to predict the risk of various health conditions, including cardiovascular and metabolic diseases and some cancers (Dai, Shu, Deng, et al., 2013). While variations in the calcium-magnesium ratio appear across sexes and geographical regions, ratios between 1.7 to 2.6 are recommended to promote health in the general population (Costello, Rosanoff, Dai, et al., 2021; Morgan, Stampley, Zabik, et al., 1985). To date, calcium, magnesium, and calcium-magnesium ratios have been explored in nutrition science research (Costello, Rosanoff, Dai, et al., 2021; Kunstel, 2005; Zhang, Xun, Wang, et al., 2017); however, differences between sport type, athlete level (i.e., recreational or competitive), and sex are not fully understood. Previous researchers have identified the calcium-magnesium ratio as a predictor of long-term disease risk (Li, Chen, Zhang, et al., 2020; Sato, Takeuchi, Matsuda, et al., 2017; Shah, Dai, Zhu, et al., 2020); however, there is a limited body of evidence surrounding the calcium-magnesium ratio use in athletes and how the ratio impacts athletic performance. Therefore, discovering whether differences exist in the calcium-magnesium ratio across sport types, athlete levels, and sexes is needed to develop more appropriate sports nutrition guidelines for athletes. The United States Department of Agriculture (USDA) has defined Acceptable Macronutrient Distribution Ranges (AMDR) for carbohydrates (45% to 65%), fats (20% to 35%), and proteins (10% to 35%) for women and men between 19 and 70 years of age (Manore, 2005). The Recommended Dietary Allowance (RDA) includes 130 grams (g) of carbohydrates/ day, 67 to 83 g of fat/day, and 46 g of protein/day for women, and 56 g of protein/day for men (Trumbo, Schlicker, Yates, et al., 2002). Among athletes, the RDAs include a carbohydrate intake between 6 to 10 g/kilograms (kg) body weight (BW)/day, a protein intake between 1.2 to 1.7 g/kg BW/day, and fat intake of 1 g/kg BW/ day (Rodriguez, DiMarco, Langley, et al., 2009). However, athletes have differing needs based on sport- specific intensity, type, and frequency of their training (Benardot, Clark, & Manore, 2016). Accordingly, we aimed to evaluate whether differences in the calcium-magnesium ratio and dietary macronutrient intake existed between women and men who are recreational and competitive athletes who partake in different sport types.

Data were derived from a larger cross-sectional study conducted by the Metabolic Research Laboratory at Drexel University. The primary purpose of the study (referred to as “The Athletes Study”) was to compare nutrition and physical fitness characteristics of athletes across a wide range of sport and athletic engagement. The Athletes Study was approved by the Drexel University Institutional Review Board (#1304002037), and all participants provided written informed consent prior to enrollment.

Participants

Participants recruited from the Philadelphia area completed an online survey to determine inclusion or exclusion in the study. Participants considered for study inclusion were 18 years of age or older and exercised two or more times per week. Excluded participants were under 18 years of age; current smokers; persons with cardiovascular, metabolic, renal, and/or musculoskeletal disease; women who were pregnant or thought they may be pregnant; and/or individuals who exercised less than two times per week. Participants were classified by sport type (Table 1) athlete level, and whether they performed their sport for fun (recreational) or participated in competitions/organized leagues (competitive). All participants in the present study were Masters Athletes, operationally defined as anyone 26 years of age or older, which has been the consensus across studies and sport types with large and generalizable samples consistent with the current study.

Table 1: Demographic and Anthropometric Information by Sport Type.

All values are represented as M ± SD, unless otherwise noted.

Anthropometrics

Body weight was measured with a Seca® 700 balance beam scale (Seca Hamburg, Germany) and recorded to the nearest 0.11 kg (0.25 pounds). Height was measured with a sliding vertical scale stadiometer and recorded to the nearest 0.5 centimeters (cm). Body mass index (BMI) was computed from the body weight and height measurements as the weight in kilograms divided by the height in meters squared. Waist circumference was measured with a Gulick tape measure 1 inch above the umbilicus and recorded to the nearest 0.1 cm. All anthropometric measurements were assessed in duplicate, except waist circumference, which was measured in triplicate. All duplicate and triplicate measures were averaged for each anthropometric assessment.

Block 2005 Food Frequency Questionnaire

The Block 2005 Food Frequency Questionnaire (FFQ) (NutritionQuest©, Berkeley, CA) was used to evaluate average dietary patterns over the past year. Calcium (measured in milligrams [mg]), magnesium (mg), calcium-magnesium ratio (derived from dividing the dietary intake of calcium by magnesium), carbohydrates (g), fat (g), and protein (g) were extracted from data collected in the Athletes Study. Foods listed within the Block 2005 FFQ estimated the micro- and macro-nutrients consumed from nutrient contents and food groups developed from the 1999 to 2002 National Health Assessment and Nutrition Examination Survey (NHANES). Dietary recall data and nutrient data developed from the USDA Food and Nutrient Database for Dietary Studies (FNDDS) version 1.0 were also integrated into our analyses. Pictures were provided to participants for quantifying portion size(s), and the FFQ was completed in approximately 30 to 40 minutes for each participant.

Procedures

Upon enrollment, participants arrived at the Metabolic Research Laboratory for session one, where written informed consent was obtained. Participant self-reported demographic information (age, date of birth, ethnicity, date of last menstrual cycle [for women], medications, and health conditions) preparticipation health screening as measured with the Physical Activity Readiness Questionnaire (PAR-Q+), and anthropometric measures were then taken. At session two, participants completed the Block 2005 FFQ, which were sent to NutritionQuest© for dietary analysis and determination of daily macro-nutrient and micro-nutrient intake over the previous year.

Data Analysis

Given the cross-sectional nature of the Athlete Study, independent group T-tests and univariate analyses of variance (ANOVA) were performed using least significant difference (LSD) correction procedures to identify differences in the calciummagnesium ratio between sport types, athlete levels, and sexes. If the basic assumption of normality was violated, a nonparametric Kruskal-Wallis test was performed. Preliminary data, including histograms and box and whisker plots, were created to test normality of the data. Extreme and outlying values were managed with Winsorizing procedures, which normalized the distribution for the calcium-magnesium ratio, but not for macronutrient distributions. Levene’s Test of Equality of Error Variances was performed to confirm homogeneity of variance, and descriptive statistics were reported as means ± standard deviations, unless otherwise noted. Alpha levels were set a priori to p < 0.05. All procedures were performed with the Statistical Package for Social Sciences (SPSS), version 28.0 (IBM SPSS, Chicago, IL).

Participant characteristics

A total of 235 athletes were included in the study sample. Demographic and anthropometric data for the total sample and by sport type can be found in Table 1. The sample included 158 recreational athletes, 75 competitive athletes, 1 professional athlete, and 1 athlete who did not provide an athlete level. Recreational athletes had a mean age of 37.50 years old (+/- 8.98 years) and a mean BMI of 24.74 (+/- 3.52). Competitive athletes had a mean age of 40.36 years old (+/- 12.61 years) and a mean BMI of 24.19 (+/- 3.20). The sample was made of 120 women and 115 men. Means and standard deviations for calcium-magnesium ratio by sport type, athlete level, and sex can be found in Tables 2, 3, and 4, respectively. Macronutrient means and standard deviations for each sport type can be found in Table 5.

Calcium-magnesium ratio

Sport type

A univariate ANOVA employing the LSD correction procedure for all athletes produced a statistically significant difference in the calcium-magnesium ratio by sport type (p = 0.030). Post-hoc pairwise comparisons identified significant differences between: General Athletes vs Triathletes, General Athletes vs Powerlifters, General Athletes vs Swimmers, Runners vs Swimmers, Triathletes vs CrossFit Athletes, CrossFit Athletes vs Powerlifters, CrossFit Athletes vs Swimmers, Crew Athletes vs Swimmers, Cyclists vs Powerlifters, Cyclists vs Swimmers, Resistance Trained Athletes vs Powerlifters, Resistance Trained Athletes vs Swimmers, Powerlifters vs Ice Hockey Players (p < 0.05). All other post-hoc comparisons were not significant (p > 0.05).

Athlete level

A univariate ANOVA employing the LSD correction procedure for the total sample produced a non- significant difference in the calcium-magnesium ratio by athlete level (p = 0.245).

Sex

An independent groups T-test for the total sample produced non-significant differences in the calcium- magnesium ratio by sex (p = 0.802).

Carbohydrate Intake

A univariate ANOVA using the LSD correction procedure including all athletes produced statistically significant differences in dietary carbohydrate intake between sport types (p = 0.005). The Kruskal-Wallis test produced a statistically significant difference in dietary carbohydrate intake by sport type (p = 0.003). Post-hoc pairwise comparisons identified significant differences between: General Athletes vs Runners, Runners vs CrossFit Athletes, Runners vs Resistance Trained Athletes, Triathletes vs CrossFit Athletes, Triathletes vs Resistance Trained Athletes, CrossFit Athletes vs Crew Athletes, CrossFit Athletes vs Powerlifters, CrossFit Athletes vs Ice Hockey Players, Crew Athletes vs Resistance Trained Athletes, Resistance Trained Athletes vs Ice Hockey Players (p < 0.05). All other post-hoc comparisons were not significant (p > 0.05). No other statistically significant differences were found for dietary carbohydrate intake by athlete level and sex.

Fat Intake

A univariate ANOVA using the LSD correction procedure produced non-significant, but trending, differences in dietary fat intake among sport types (p = 0.056). Because the basic assumption of normality was violated, a nonparametric Kruskal-Wallis test was performed. No significant difference was found in dietary fat intake by sport type (p = 0.091). An interaction effect was found between sport type and sex; however, no statistically significant difference existed for athlete level or sex.

Protein intake

A univariate ANOVA using the LSD correction procedure produced significant differences in dietary protein intake among athlete sport types (p = 0.048). Because the basic assumption of normality was violated, a nonparametric Kruskal-Wallis test was performed. No significant differences were found in dietary protein intake by sport type (p = 0.062). An interaction effect was found between sport type and sex; however, a non-significant difference was found for both athlete level and sex in relation to dietary protein intake.

To our knowledge, our study is the first to evaluate the calciummagnesium ratio in athletes of different sport types, athlete levels, and sexes. We also examined whether differences in dietary macronutrient intake existed amongst these categories. We found a statistically significant difference in the calcium-magnesium ratio for the total sample across sport types and post-hoc pairwise comparison identified where significant differences occurred; however, these findings neglected to maintain significance when analyzed by level and sex. We also found statistically significant differences in dietary carbohydrate intake among sport types, and post-hoc pairwise comparisons revealed where these differences existed. No statistically significant differences in dietary fat or protein intake were observed among sport types. Non-significant differences were found for athlete level and sex in relation to dietary carbohydrate intake, dietary fat intake, and dietary protein intake.

Calcium-magnesium ratioFor athletes, the crucial role that calcium and magnesium play in sport performance demand a proper calcium-magnesium ratio. Previous researchers have identified an optimal calciummagnesium ratio to be between 1.70 to 2.60 (Costello, Rosanoff, Dai, et al., 2021; Rosanoff, Dai, & Shapses, 2016). Much of the population does not consume adequate amounts of calcium and magnesium to obtain an ideal ratio (Morgan, Stampley, Zabik, et al., 1985). In the U.S., the dietary intake of calcium has increased at a rate 2.0 to 2.5 times that of dietary magnesium, suggesting that the calciummagnesium ratio may be increasing (Rosanoff, Dai, and Shapses, 2016). Since 2000, the calcium-magnesium ratio in adults living in the U.S. has been greater than 3.0, well above recommended guidelines (Costello, Rosanoff, Dai, et al., 2021; Rosanoff, Dai, & Shapses, 2016). High calcium-magnesium ratios are associated with increased risk for cardiovascular diseases, metabolic syndrome, and certain cancers (Costello, Rosanoff, Dai, et al., 2021; Rosanoff, Dai, and Shapses, 2016). In those with low calcium-magnesium ratios (< 1.7), there is an increased risk of developing esophageal adenocarcinoma (Costello, Rosanoff, Dai, et al., 2021; Shah, Dai, Zhu, et al., 2020). Micronutrient deficiencies are often a problem for athletes; frequent loss of bodily fluids makes these deficiencies more common (Volpe, 2007). The cooperative interaction of calcium and magnesium in the body necessitates adequate intake of both micronutrients. While use of the calcium-magnesium ratio as an indicator for disease risk has been well-studied, its usefulness in athletic populations is novel.

For athletes, the crucial role that calcium and magnesium play in sport performance demand a proper calcium-magnesium ratio. Previous researchers have identified an optimal calciummagnesium ratio to be between 1.70 to 2.60 (Costello, Rosanoff, Dai, et al., 2021; Rosanoff, Dai, & Shapses, 2016). Much of the population does not consume adequate amounts of calcium and magnesium to obtain an ideal ratio (Morgan, Stampley, Zabik, et al., 1985). In the U.S., the dietary intake of calcium has increased at a rate 2.0 to 2.5 times that of dietary magnesium, suggesting that the calciummagnesium ratio may be increasing (Rosanoff, Dai, and Shapses, 2016). Since 2000, the calcium-magnesium ratio in adults living in the U.S. has been greater than 3.0, well above recommended guidelines (Costello, Rosanoff, Dai, et al., 2021; Rosanoff, Dai, & Shapses, 2016). High calcium-magnesium ratios are associated with increased risk for cardiovascular diseases, metabolic syndrome, and certain cancers (Costello, Rosanoff, Dai, et al., 2021; Rosanoff, Dai, and Shapses, 2016). In those with low calcium-magnesium ratios (< 1.7), there is an increased risk of developing esophageal adenocarcinoma (Costello, Rosanoff, Dai, et al., 2021; Shah, Dai, Zhu, et al., 2020). Micronutrient deficiencies are often a problem for athletes; frequent loss of bodily fluids makes these deficiencies more common (Volpe, 2007). The cooperative interaction of calcium and magnesium in the body necessitates adequate intake of both micronutrients. While use of the calcium-magnesium ratio as an indicator for disease risk has been well-studied, its usefulness in athletic populations is novel.

By sport type

We found significant differences in calcium-magnesium ratio across sport types. Participants across most sport types had a mean calcium-magnesium ratio of 1.70 to 2.60, with some notable exceptions. Powerlifters and swimmers had mean calciummagnesium ratios of 3.2 and 3.4, respectively. A possible explanation for these high ratio values may be the lack of research on magnesium intake for athletes, especially those engaging in powerlifting and swimming. Although dietary calcium plays an accepted role in muscle contraction, the importance of dietary magnesium has not been extensively investigated (Kunstel, 2005). Therefore, athletes are likely consuming above average amounts of calcium and below average levels of magnesium, leading to a high calciummagnesium ratio. Additionally, powerlifters typically consume more kilocalories than the average person and may consequently yield a higher calcium-magnesium ratio (Slater & Phillips, 2011). Furthermore, the abnormally high calcium-magnesium ratios observed for these two groups may be due to small sample sizes in each cluster, possibly skewing our mean findings.

We identified significant differences in calcium-magnesium ratios between sport types - most notably, between sport types classified as aerobic (e.g., runners, swimmers, etc.) and those classified as anaerobic (e.g., general athletes, powerlifters, etc.). We observed significant differences within groups of aerobic and anaerobic athletes; however, athletes of different sport types may have different calcium-magnesium ratios due to variations in volume, intensity, and continuity of training sessions. The crucial role magnesium plays for muscle contraction and nerve conduction suggests that magnesium is a more important micronutrient for anaerobic (strength-focused training) than aerobic (endurancefocused) exercise (Zhang, Xun, Wang, et al., 2017). If magnesium is a vital micronutrient for anaerobic training and consumed at higher rates among strength-focused athletes, differences in its consumption may be reflected in sport types with smaller calciummagnesium ratios.

Another proposed explanation for the observed differences in the calcium-magnesium ratio between aerobic and anaerobic athletes is the utilization of calcium in slow-twitch versus fasttwitch muscles. Slow-twitch and fast-twitch muscle fibres differ in the duration of twitch, amount of muscle charge movement, and concentration of several receptors playing a role in skeletal muscle contraction (Baylor & Hollingworth, 2003). Fast-twitch muscle fibres had a three-fold greater total concentration of released calcium in response to an action potential compared to slow- twitch muscle fibres in mice; this suggests that aerobic and anaerobic athletes use calcium at different rates (Baylor & Hollingworth, 2003). If aerobic training uses greater concentrations of calcium, athletes engaging in endurance sports may require more calcium, reflected in higher calcium-magnesium ratios.

Table 2: Calcium-Magnesium Ratio (mg/mg)/day by Sport Type.

All values are represented as M ± SD, unless otherwise noted.

By athlete level

We found no significant differences in calcium-magnesium ratios by athlete level. Our recreational and competitive athletes had calcium-magnesium ratios within the recommended range of 1.70 to 2.60, with values between 2.3 to 2.4 common. The lack of differences between our cohorts of recreational and competitive athletes may be due to the lack of available data on recommended micronutrient intake in athletes. Although recommended calcium and magnesium intakes exist for athletes in general, there are not specific recommendations based on athlete level, suggesting that significant differences in calcium-magnesium ratios across athlete levels may not occur. Additionally, the measure of athlete level used in our investigation may not be the most effective for identifying significant differences.

Table 3: Calcium-Magnesium Ratio (mg/mg)/day by Athlete Level.

All values are represented as M ± SD, unless otherwise noted.

By sex

We found no significant difference in the calcium-magnesium ratio based on sex, though we did observe differences in calcium and magnesium intake independently. Female athletes had an average calcium intake of 781.8 mg/day and an average magnesium intake of 354.8 mg/day, while male athletes had an average calcium intake of 941.5 mg/day, and an average magnesium intake of 399.5 mg/day. The adequate intake (AI) for calcium is 1000 mg/day for women and men, 31 to 50 years of age (Bailey, Dodd, Goldman, et al., 2010). The RDA for magnesium for women and men, 31 to 50 years of age, is 320 mg/day and 420 mg/day, respectively (Durlach, 1989). Prior research has identified women to consume calcium below the RDA, which is consistent with the underconsumption of calcium and magnesium reported for most of the U.S. population (Morgan, Stampley, Zabik, et al., 1985). Many population samples were not consuming calcium and magnesium in appropriate concentrations to obtain an optimal calcium-magnesium ratio; however, women were found to have more appropriate ratios than men (Morgan, Stampley, Zabik, et al., 1985). In our study, women had an average calcium intake considerably lower than the 1,000 mg/day AI, and an average magnesium intake slightly greater than the 320 mg/day RDA. The male athletes in our study had an average calcium intake that neared the AI of 1000 mg/day and consumed average magnesium intakes close to the RDA of 420 mg/day. Future research building upon these findings should include larger sample sizes, which may reveal a minimally effective intake of calcium, magnesium, and calcium-magnesium ratios for women and men.

Table 4: Calcium-Magnesium Ratio (mg/mg)/day by Sex.

All values are represented as M ± SD, unless otherwise noted.

Carbohydrate intake

In our study, mean values of carbohydrate intake by sport type varied, ranging from 125.3 g/day to 397.6 g/day. Many of the sport types exhibited dietary carbohydrate intakes that were larger than the AMDR for the general population (130 g/day). Due to carbohydrates’ role in providing energy, athletes require more carbohydrates than the general population (Economos, Bortz, & Nelson, 1993). Moreover, the ranges observed for carbohydrate intake across sport types in our study could be attributed to the fact that the RDAs for carbohydrates for athletes have a wide range and are largely dependent on body weight. We identified significant differences in carbohydrate intake between a variety of sport types (Table 5); most notably, sport types that were endurancefocused (e.g., running) compared to those that were strengthfocused (e.g., resistance training). Previous literature has identified that carbohydrate intake needs for general training is 5 to 7 g/kg body weight/day, while carbohydrate intake needs for endurance athletes is 7 to 10 g/kg body weight/day (Burke, Cox, Cummings, et al., 2001). Athletes in our study exhibited different carbohydrate intakes corresponding to differences in the energy demand of their respective sports. Our lack of identifying a statistically significant difference for dietary carbohydrate intake by athlete level nor sex may be due to a lack of nutritional guidelines based on these two categories, or simply because athletes of the same sport tend to have similar carbohydrate needs, regardless of their level or sex.

Fat intake

The mean values for dietary fat intake by sport type ranged from 43.4 to 87.2 g/day, with one outlier. A powerlifter had an average dietary fat intake of 145.4 g/day, which was determined to be an outlier as evidenced of its value +/- 3 standard deviations above the mean value. This outlier can be attributed to the higher energy demand for powerlifting. The range of values for our other athletes was similar to the RDA for the general population (67 to 83 g/ day). We found no statistically significant differences in dietary fat across sport types. Previous researchers have identified differences in recommended total fat intake for women and men in aerobic sports versus anaerobic sports (Economos, Bortz, & Nelson, 1993). Although recommendations exist, only 40% of female athletes and 17% of male athletes followed recommended guidelines (Economos, Bortz, & Nelson, 1993). Therefore, it is possible that athletes stick more to the RDA for the general population, as evidenced by the fat intake range found in this study, which could explain why a significant difference in fat intake by sport type was not observed in our study. Additionally, no statistically significant difference was found for fat intake in relation to athlete level nor sex, which may be due to a lack of nutritional guidelines or simply because athletes of the same sport tend to have similar dietary fat needs.

Protein intake

The mean values for dietary protein intake by sport type ranged from 41.9 to 92.3 g/day, with one prominent outlier. One powerlifter had an average dietary protein intake of 133.7 g/day. Again, this outlier can be attributed to the greater muscle mass for this athlete, and the increased nutritional demands for powerlifting. Most athletes in other sport types exhibited a mean dietary protein intake value larger than the RDA for the general population (46 to 56 g/day). Protein intake is typically 150% to 200% greater in athletes compared to the general population because of the role of protein in the maintenance and gain of skeletal muscle (Lemon & Proctor, 1991; Taylor, 2019). While the RDA of protein in the general population is 0.8 g/kg body weight, the RDA for athletes ranges from 1.2 to 1.7 g/kg body weight depending on the sport type (Benardot, Clark, & Manore, 2016). We found no statistically significant differences in dietary protein intake across sport types. Based on previous studies, we expected to see a difference in protein intake between endurance and strength trained athletes (Lemon & Proctor, 1991). Previous researchers have identified that endurance athletes have a recommended protein intake of 1.2 to 1.4 g/kg body weight, while strength trained athletes have a recommended intake of 1.2 to 1.7 g/kg body weight (Benardot, Clark, & Manore, 2016).

However, athletes not following these guidelines could infringe on our detection of statistically significant differences by sport type. Another possible explanation for our nonsignificant finding is the individual analysis of sport types. If sport types had been grouped and analyzed based on endurance versus strength, we may have observed a significant difference between groups. Furthermore, a non-significant difference was found for both athlete level and sex in relation to dietary protein intake. This may be due to a lack of nutritional guidelines based on athlete level and sex, or simply because athletes of the same sport tend to have similar protein needs.

Table 5: Macronutrient Intake (g)/day by Sport Type.

All values are represented as M ± SD, unless otherwise noted.

We found significant differences in the calcium-magnesium ratios by sport type but neglected to find differences by athlete level or sex. We found significant differences in dietary carbohydrate intake across sport types, but not in dietary fat or protein intake. We did not find significant differences in dietary carbohydrate, fat, or protein intake by athlete level nor sex. Researchers should consider the calcium, magnesium, and macronutrient needs of athletes by sport type, athlete level, and sex, which would allow for more individualized and prescriptive approaches to nourishing athletes. Additionally, future research efforts should focus on illustrating how dietary intake can affect performance in athletes and employ samples larger in number and varied by athletic or sport type and level.

Ethics approval and consent to participate

All ethical guidelines for research involving human participants were followed. The study protocol and supporting materials were reviewed by the institutional review board prior to data collection and was approved (Protocol #1304002037). All participants provided written informed consent prior to enrolment. All study protocols align with the Declaration of Helinski.

Consent for publication

Not applicable.

Availability of data and material

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

No external financial support was awarded for this project; support was fully internal.

The author declares that he has no competing interests

Authors’ contributions

SLV and MB contributed to research design. JRS and RR collected data. MB and AGG conducted statistical analysis. MB prepared the manuscript with support from AGG. All authors read and approved the final manuscript.

Acknowledgements

The authors thank Ms. Janvi Patel, Ms. Danielle Nehring and Drexel University for providing internal support to this project.

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