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Article

The Relationship Between Arterial Stiffness and Circulating Lipids in Firefighters

by
Angelia M. Holland-Winkler
*,
Jonathan J. Ruiz Ramie
,
Andrew R. Moore
and
Austin A. Kohler
Department of Kinesiology, Augusta University, 3109 Wrightsboro Road, Augusta, GA 30909, USA
*
Author to whom correspondence should be addressed.
Lipidology 2025, 2(1), 2; https://doi.org/10.3390/lipidology2010002
Submission received: 27 November 2024 / Revised: 26 December 2024 / Accepted: 6 January 2025 / Published: 9 January 2025
Browse Figure
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Abstract

:
Background/Objectives: Firefighters have an elevated risk of developing cardiovascular disease (CVD). Thus, it is vital to determine areas of health associated with the development of CVD that need improvement in the firefighter population, such as circulating lipids and arterial stiffness. The purpose of this study was to assess the potential relationship of lipid and lipoprotein metrics with measures of arterial stiffness in full-time firefighters in the southeastern United States. Methods: Twenty male full-time firefighters underwent a fasted blood draw to assess circulating lipids. Resting arterial stiffness was then assessed via pulse wave velocity (PWV) using an aortic measure. To determine the linear relationships between arterial stiffness and lipid measures of interest, a series of bivariate correlations were conducted as appropriate. The outcome variable was PWV measured continuously in m/s. The predictor variables were total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), small dense LDL-C (sdLDL-C), and triglycerides (TG) measured in mg/dL. All analyses were carried out using SPSS version 29 (α = 0.05). Results: TG levels were positively and moderately correlated with PWV (rs = 0.497, p = 0.026). No other significant relationships were detected between PWV and the remaining variables TC (rs = 0.104, p = 0.664), HDL-C (rs = −0.328, p = 0.158), LDL-C (rs = 0.184, p = 0.436), or sdLDL-C (rs = 0.330, p = 0.155). Conclusion: Higher TG levels are associated with higher PWV and thus, arterial stiffness. Management of circulating TG may be an important consideration in maximizing arterial health and minimizing CVD risk.

1. Introduction

Cardiovascular disease (CVD) is the leading cause of on-duty deaths in firefighters, accounting for nearly half of all fatalities. More specifically, most of the CVD-related fatalities in firefighters (90%) are due to coronary heart disease (CHD), indicating major arterial compromise of the heart [1]. Furthermore, for every fatal CVD-related on-duty incident, estimates point to over 10 non-fatal cardiovascular events [2]. Thus, CVD imposes a major burden on this population, jeopardizing the health of the affected team members and potentially further affecting the team’s performance.
Recognizing these trends, increased attention and effort have been invested into supporting the cardiovascular health of firefighters, helping to foster better lifestyle decisions to reduce risk, encouraging earlier risk stratification, and earlier diagnoses and management of CVD. Many of the same risk factors the general population faces commonly correlate with CVD among firefighters. Hypercholesterolemia has long been considered a traditional risk factor for CVD, regularly adjusted for in statistical models to ascertain potential novel, independent CVD risk factors [3]. Bode et al. measured risk factors for CVD in a large sample of United States firefighters and found that male firefighters exhibited high levels of total cholesterol (TC) and triglycerides (TG). These elevations increased with age and BMI [4].
More recently, alternative measures, such as nuclear magnetic resonance imaging, have allowed for the quantification of the size and number of subclasses of lipoprotein particles. While low- and high-density cholesterol levels (LDL-C and HDL-C, respectively) may traditionally be associated with CVD risk and mortality, some studies point to small-dense LDL cholesterol (sdLDL-C) as an independent risk factor for CVD or preclinical CVD risk factors, above and beyond that of traditional measures such as LDL-C [5]. Furthermore, residual CVD risk in patients who have achieved a lowered LDL-C target value has been attributed to sdLDL-C.
In addition to lipid and lipoprotein measures, arterial stiffness represents a functional risk factor for clinical and preclinical CVD, independent of traditional risk factors such as blood pressure and blood lipids [6,7,8]. Arterial stiffness represents the arteries’ progressive loss of elasticity and ability to dilate or constrict in reaction to changes in pressure. It is considered a hallmark of vascular aging and can be a consequence of the progression of hypertension. In a sample of firefighters from Seoul City, Korea, subjective occupational stress was positively correlated with arterial stiffness [9]. Nagel et al. suggest factors associated with firefighting that may result in increased arterial stiffness, such as long hours and dangerous environments; however, more research is needed to determine the impact of these conditions on arterial stiffness in this population [10].
As lipid/lipoprotein and arterial stiffness measures are implicated in CVD, it is plausible that these two metrics are also related. Numerous studies have verified the relationship between arterial stiffness and TC [7,11,12,13,14], LDL-C [15,16], HDL-C [13,17], TG [12,13,17], and sdLDL-C [18,19]. Combined, these studies provide evidence on a largely heterogeneous sample of men and women ranging in age from 12–84 years, and from healthy adolescents to Cardiology department patients. Although the literature linking lipids/lipoproteins to arterial stiffness covers a broad population, no study to date has investigated these relationships in a targeted manner by occupation, and more specifically in tactical athletes such as firefighters. Thus, the present study aimed to evaluate the relationship of lipid and lipoprotein metrics with a measure of arterial stiffness in full-time firefighters in the southeastern United States. We hypothesized that there would be a significant relationship between arterial stiffness and at least one marker of dyslipidemia.

2. Materials and Methods

2.1. Research Design

A cross-sectional design was used to determine if circulating lipids were associated with arterial stiffness in full-time firefighters in the southeastern part of the United States. All participants had a blood draw during the same week in July to assess circulating lipids. They also visited the laboratory within two weeks of their blood draw for the arterial stiffness assessment. This study was approved by the University’s Institutional Review Board (IRBNet ID# 2095651), and all procedures performed followed institutional guidelines.

2.2. Participants

Twenty male full-time firefighters from the local fire department, aged 24–60, participated in this study. Inclusionary criteria included full-time male and female firefighters. Exclusionary criteria included pregnancy and/or taking vasoactive medication such as catecholamines, phosphodiesterase inhibitors, calcium sensitizers, and vasopressors. This study included only male volunteers, likely because the local fire department is composed of just 1.1% females. Participant characteristics are provided in Table 1.
The program G * Power version 3.1 [20] was used to perform an a priori power analysis for a point biserial correlation model analysis to estimate the required sample size. Assuming α = 0.05, power = 0.95, a two-tail analysis, and an effect size of 0.747 (observed for a large-scale study on the relationship between TG and PWV [21]), it was estimated that a sample size of 13 participants would be needed to detect a significant relationship. To account for dropout and missing data, 27 participants were initially recruited.

2.3. Protocol

During the first meeting, participants brought a list of their medications to ensure exclusionary criteria were not met and then signed the informed consent to participate. They were given preparation instructions for the blood draw and arterial stiffness assessment, which occurred one month after signing the informed consent document. The blood draw and arterial stiffness assessment occurred within two weeks of each other.

2.3.1. Lipid Panel

Preparatory instructions for the blood draw included fasting with only drinking water 8 h before the blood draw. A lipid panel was assessed from the blood draw, which included TG, TC, HDL-C, direct LDL-C, and sdLDL-C.
Blood samples were collected from participants via venipuncture using serum-separating tubes. After collection, the tubes were allowed to clot for 30 min at room temperature and then centrifuged at 1500× g for 10 min to separate the serum. The resulting serum was carefully aliquoted to avoid contamination from cellular material or the gel separator. Serum samples were stored at 4 °C until analysis and processed within 24 h to maintain sample integrity.
Each serum sample was pipetted directly into standardized cuvettes for the IR1200 colorimetric analysis, ensuring consistent sample volumes across all measurements. The Synermed IR1200 colorimetric analyzer (Infrared Laboratory Systems, LLC, Westfield, IN, USA) was calibrated before sample analysis. Calibration was performed using a series of known standards, covering the range of expected absorbance values. The calibration procedure involved measuring absorbance at specific wavelengths relevant to the target analyte, as the IR1200 operating manual specified. Calibration curves were constructed by plotting the absorbance against concentration, and a regression analysis was performed to confirm the linearity of the response across the working range.
Following calibration, each sample was introduced into the IR1200 instrument. The system parameters, including wavelength settings, temperature control, and sample path length, were set in accordance with the manufacturer’s recommendations. For the quantitative determination of TG, TC, LDL-C, sdLDL-C, and HDL-C, enzymatic assays were utilized, which included the Synermed Triglycerides IR 140, Synermed Cholesterol IR060 (Infrared Laboratory Systems, LLC, Westfield, IN, USA), Diazyme LDL-Cholesterol Assay, Diazyme sdLDL Assay, and Diazyme HDL-Cholesterol Assay (Diazyme Laboratories, Poway, CA, USA), respectively. The IR1200 software automatically calculated the concentration of the analyte based on the calibration curve.

2.3.2. Pulse Wave Velocity

Preparatory instructions for the arterial stiffness assessment included fasting with only drinking water and not having nicotine or antioxidant vitamins for 12 h, no alcohol for 24 h, and not participating in moderate-to-vigorous intensity exercise 8 h before the visit. During the laboratory visit, height was assessed using a wall stadiometer, and weight was measured without shoes using a floor scale (InBody 580 Body Composition Analyzer, Cerritos, CA, USA).
Resting arterial stiffness was then assessed via pulse wave velocity (PWV; Vicorder, 80 Beats Medical GmbH, Kantstrasse, Berlin, Germany) using an aortic measure. For the measure, the participant rested in a supine position with their head and shoulders raised by 30 degrees. A neck pad was placed around the participant’s neck with a pressure pad over the right carotid area, secured with Velcro, and not too tight. A pressure cuff was placed around the participant’s right thigh and connected to the Vicorder. PWV was recorded in meters per second (m/s).

2.4. Statistical Analysis

To determine the linear relationships between arterial stiffness and the lipid measures of interest, a series of bivariate correlations were conducted. The outcome variable was PWV measured continuously in m/s. The predictor variables were TC, HDL-C, LDL-C, sdLDL-C, and TG. An alpha level of 0.05 was used for all analyses, which were carried out using SPSS version 29. All sets of scores were screened for missing data points, data entry errors, and outliers (values with SD > 3.0 from the group mean). The Shapiro–Wilk test was used to assess whether the assumption of normality was met in each of the variables. If a set of scores for a variable violated the assumption of normality, non-parametric Spearman’s rank-order correlation was performed instead to assess the relationship(s) of interest. Visual inspection of scatterplots was conducted to verify monotonic relationships between variables in this case. Both Pearson’s r and Spearman’s rs range from −1.0 to 1.0 and are interpreted according to their direction (i.e., positive = direct relationship between variables; negative = indirect relationship between variables) and their magnitude (0–0.3 = weak relationship; 0.31–0.5 = moderate relationship; 0.51–1.0 = strong relationship).

3. Results

The outcome variable PWV violated the assumption of normality. Therefore, all planned bivariate correlation analyses were completed as Spearman’s rank-order correlations. There was one outlier for the TG data (3.48 SD from the group mean). Although this score was substantially higher than the other participants’ scores in this sample, the observed value of 423 mg/dL was verified as a fasted measure and included in the correlational analysis. Additionally, a Winsorization approach was utilized [22], whereby the outlier’s score was converted to the next highest score in the sample that was not an outlier (229 mg/dL in this case). This approach was selected to reduce the impact of the extreme value while maintaining an already small dataset. When the outlier was included in the analysis, the relationship was positive, moderate, and significant (rs = 0.497, p = 0.026). Following Winsorization, the relationship between PWV and TG remained positive, moderate, and significant (rs = 0.498, p = 0.026). In this instance, an increase in TG was associated with an increase in PWV.
All other variables were analyzed with a complete data set and no outliers. There were no significant relationships detected between PWV and the remaining variables TC (rs = 0.104, p = 0.664), HDL-C (rs = −0.328, p = 0.158), LDL-C (rs = 0.184, p = 0.436), or sdLDL-C (rs = 0.330, p = 0.155). The averages for each variable are provided in Table 2. The linear relationships between variables are presented visually in Figure 1.

4. Discussion

The present pilot study aimed to assess the potential relationships of lipid and lipoprotein metrics with a measure of arterial stiffness in full-time firefighters in the southeastern United States. Arterial stiffness is a functional risk factor for CVD, the leading cause of death worldwide in the general population and in firefighters, specifically. Identifying lipid measures that could contribute to arterial stiffness is an important step in diagnosing and proactively treating arterial stiffness and CVD. Non-parametric correlation analyses were used to determine the linear relationships between PWV and a series of plasma lipid measurements. The main finding was a significant, moderate, and positive relationship between PWV and TG, suggesting that as TG increases in this population, arterial stiffness increases as well. The relationships between PWV and all other lipid metrics were non-significant and weak. The context and relevance of these results are discussed below.
While no studies to our knowledge have investigated the relationship between TG and PWV, specifically in firefighters, our findings are supported by multiple previous studies linking higher TG to elevated PWV in other populations [12,13,14,17,21,23]. Notably, Zhao et al. (2014) found a rather weak positive correlation between TG and arterial stiffness (r = 0.104) in a cohort of middle-aged and elderly Chinese individuals (50–90 years old) after adjusting for age and sex [14]. Further, when stratifying by sex, the relationship between TG and PWV was eliminated in men. This contrasts with our findings and may point to the relationship between TG and PWV changing with age as our population was considerably younger on average (39.4 ± 12.5 in our study vs 64.0 ± 8.6 yrs of age). Conversely, in a study of young men aged 18 to 44 years, the prevalence of high PWV (defined as the highest quartile of PWV) was significantly different between tertiles of TG, with higher TG being related to higher PWV [12]. A similar relationship was also found in adolescents aged 12–18, with higher TG being an independent predictor of increased PWV even after adjusting for traditional CVD risk factors [13]. Thus, while the strength of the relationship between TG and PWV may vary by age, there is a lasting relationship across a wide age range. Along these lines, baseline TG levels were found to have a stronger association with PWV in a longitudinal cohort of individuals older than 65 yrs relative to those younger than 65 [21].
Sang et al. (2021) found that log-transformed TG levels independently predicted elevated PWV in a retrospective analysis of 659 apparently healthy men (mean age 47.4 ± 10.7) [24]. TG was also found to be associated with PWV even when LDL-C was below 70 [23] and 79 [25] mg/dL, respectively, in two separate studies. Together, these studies, along with the results of our current study, support early TG-level screening for populations such as firefighters, especially those who are apparently healthy, as TG may represent residual risk not captured by other factors such as achieved target LDL-C levels.
Although the relationship between TG and PWV has been uncovered, the physiological basis behind the relationship has not been fully elucidated. One potential pathway links high levels of TGs to dysregulation of lipoprotein lipase activity, a key regulatory enzyme in TG breakdown. Reduced lipoprotein lipase activity leads to the accumulation of TGs, which may lead to larger, TG-rich, very low-density lipoprotein particles and smaller, more dense LDL particles [26]. These small LDL particles are susceptible to oxidation within the vasculature, which is considered an initial step in the atherogenic process, plaque formation, and ultimately increased arterial stiffness [27,28].
Diet-induced hyperlipidemia may also contribute to arterial stiffness via dietary carbohydrates and hyperglycemia [29]. Excess carbohydrate intake may activate de novo lipogenesis in the liver, leading to the accumulation of TG. Furthermore, simultaneous consumption of carbohydrates and lipids alters lipid clearance, results in higher postprandial VLDL, and, in hyperglycemia, leads to the spontaneous binding of glucose to lipoproteins [30]. These glucose-bound lipoproteins are modified, resulting in glycated lipoproteins associated with reduced lipoprotein lipase activity. Furthermore, glycated LDL is associated with endothelial dysfunction via the expression of adhesion molecules [31], decreased nitric oxide production [32], and decreased vascular anti-thrombotic activity [33]. Additionally, glycated LDL-C is associated with decreases in hepatic uptake and breakdown of low-density lipoproteins via the LDL-C receptors and increased scavenger receptor uptake by inflammatory cells, further encouraging the formation of atherogenic plaques [29]. As such, dietary intervention may be targeted in managing blood lipids and arterial health.
Cholesterol-reducing dietary modifications should serve as a first step non-pharmacological treatment of dyslipidemia for firefighters [34]. The National Cholesterol Education Program (NCEP) reported in 1994 that dietary therapy to reduce cholesterol has two phases. The first phase, Step I, consists of a diet with 8–10% of total calories from saturated fatty acids, 30% or less total calories from total fat, and cholesterol less than 300 mg/day. If Step I does not improve dyslipidemia, Step II is recommended, which consists of further reducing saturated fatty acids to less than 7% of total calories and cholesterol to less than 200 mg/day [33,34,35]. Furthermore, a meta-analysis demonstrated that combining the NCEP Step II diet with the Portfolio Diet significantly increased the improvements in dyslipidemia compared to the NCEP Step II diet alone in seven controlled trials lasting at least three weeks [36]. The Portfolio Diet is a plant-based diet that adds four cholesterol-reducing foods: nuts, soy or pulse protein, soluble fiber, and plant sterols [36,37]. The NCEP Step II and Portfolio Diet combination demonstrated significant improvements in LDL-C, TC, TG, and 10-year CHD risk.
In addition to improving dyslipidemia, dietary modifications have also demonstrated improvements in arterial stiffness, especially when individuals are overweight or obese [38]. Diets that restrict calories replace saturated fatty acids with monounsaturated fatty acids from seafood and plants, include vegetables and fruits, and/or replace simple sugar carbohydrates with low-glycemic complex carbohydrates have been shown to improve pulse wave velocity estimates of arterial stiffness [39,40,41,42,43,44]. A diet that includes all these components is the Mediterranean diet [45,46]. Thus, firefighters may choose to alter single components of their diet to improve circulating lipids and/or arterial stiffness, or for more significant improvements, choose to restructure their entire diet to include the components of the NCEP Step II diet, Portfolio diet, and Mediterranean diet, which have similar properties and could be cohesively combined. Other lifestyle modifications that may improve circulating lipids and/or arterial stiffness include smoking cessation and physical activity engagement [47,48].
Arterial stiffness is an early marker for the development of future atherosclerotic cardiovascular disease. Since firefighters are at high risk for cardiovascular disease, it may be beneficial to monitor their arterial stiffness and encourage healthy habits that may attenuate it. Our study demonstrated that circulating TGs are associated with arterial stiffness. Thus, the practical implications of our study for firefighters involve evaluating blood lipids and arterial stiffness annually, along with adopting and sustaining healthy lifestyle habits that have been shown to improve those factors.
Several issues present in this study constitute limitations of the study results. The use of a non-parametric correlational analysis prohibited the use of techniques to statistically control for variables that may have impacted arterial stiffness, such as age, blood pressure, and smoking status. The linear relationships between lipid variables and PWV may be different if the effects of these variables were statistically removed. Despite this potential limitation, we found that post hoc correlation analyses between blood lipid variables and the variables age and systolic blood pressure revealed only small/negligible non-significant linear relationships, suggesting that these variables had little confounding effect on the results. Furthermore, a large-scale study (N = 909) found that even after adjusting for age, body mass, smoking status, blood glucose levels, and glomerular filtration rate (i.e., kidney function), the linear relationship between TG and PWV was significant [16]. Taken together, these findings support the idea that the findings we present (a significant linear relationship between TG and PWV in firefighters) are valid and generalizable. A second limitation of this study is the low sample size for a correlational analysis. Findings from studies using this methodology are more generalizable and ecologically valid when drawing on results from a larger sample of the population of interest. Ideally, the results presented here will guide robust future research in this population.

5. Conclusions

The increased risk of CVD in firefighters indicates a vital need to determine common underlying causes of CVD in this population to develop appropriate strategies to reduce this risk. Our study analyzed circulating lipids and arterial stiffness, two variables associated with CVD, and found that circulating triglycerides were positively associated with arterial stiffness. Future explorations should assess this relationship in a larger sample of firefighters, as our pilot study only included 20. In addition, studies should implement applicable lifestyle interventions, such as dietary modifications, to reduce circulating TG and analyze their impact on arterial stiffness. Also, a similar study examining female firefighters would be valuable in assessing sex differences to identify specific health concerns in fire departments further.

Author Contributions

Conceptualization, A.M.H.-W.; methodology, A.M.H.-W.; formal analysis, A.R.M.; investigation, A.A.K.; data curation, A.R.M.; writing—original draft preparation, A.M.H.-W., J.J.R.R. and A.R.M.; writing—review and editing, A.M.H.-W., J.J.R.R., A.R.M. and A.A.K.; supervision, A.M.H.-W.; funding acquisition, A.M.H.-W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Augusta University (IRBnet# 2095651 approved on 29 September 2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data collected and analyzed for this study are freely available at the online data repository Open Science Framework via the following link: https://osf.io/zhce6/ (last updated 27 November 2024).

Conflicts of Interest

The authors declare no conflicts of interest.

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Lipidology 02 00002 g001
Figure 1. Linear relationships between pulse wave velocity and plasma levels of (A) total cholesterol, (B) high-density lipoprotein cholesterol (HDL-C), (C) low-density lipoprotein cholesterol (LDL-C), (D) small-dense low-density lipoprotein cholesterol (sdLDL-C), and (E) triglycerides. The orange data point in each graph indicates the score of a single participant who displayed an extreme value for triglycerides only. The blue data point in (E) represents the triglycerides value for this participant following Winsorization (to the next highest value). Trend lines are depicted for all relationships of the original data (black and orange data points) and the Winsorized triglycerides data (black and blue data points). Each relationship is described by Spearman’s rho (rs) and a corresponding p-value. Significant linear relationships are indicated in bold font.
Figure 1. Linear relationships between pulse wave velocity and plasma levels of (A) total cholesterol, (B) high-density lipoprotein cholesterol (HDL-C), (C) low-density lipoprotein cholesterol (LDL-C), (D) small-dense low-density lipoprotein cholesterol (sdLDL-C), and (E) triglycerides. The orange data point in each graph indicates the score of a single participant who displayed an extreme value for triglycerides only. The blue data point in (E) represents the triglycerides value for this participant following Winsorization (to the next highest value). Trend lines are depicted for all relationships of the original data (black and orange data points) and the Winsorized triglycerides data (black and blue data points). Each relationship is described by Spearman’s rho (rs) and a corresponding p-value. Significant linear relationships are indicated in bold font.
Lipidology 02 00002 g001
Table 1. Characteristics of the 20 male firefighters.
Table 1. Characteristics of the 20 male firefighters.
CharacteristicAverage ± Standard Deviation
Age (yrs)39.4 ± 12.5
Weight (kg)100.2 ± 18.0
Height (cm)179.8 ± 7.1
BMI (kg/m2)31.0 ± 5.2
Table 2. Average PWV and circulating lipid values.
Table 2. Average PWV and circulating lipid values.
VariableMean ± Standard Deviation
Pulse wave velocity (m/s)6.5 ± 0.9
Total cholesterol (mg/dL)187.0 ± 36.3
Low-density lipoprotein cholesterol (mg/dL)117.5 ± 29.0
Small dense low-density lipoprotein cholesterol (mg/dL)35.3 ± 11.0
High-density lipoprotein cholesterol (mg/dL)55.0 ± 11.4
Triglycerides
outlier included (mg/dL)148 ± 79.1
outlier Winsorized (mg/dL)138.0 ± 50.2
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MDPI and ACS Style

Holland-Winkler, A.M.; Ruiz Ramie, J.J.; Moore, A.R.; Kohler, A.A. The Relationship Between Arterial Stiffness and Circulating Lipids in Firefighters. Lipidology 2025, 2, 2. https://doi.org/10.3390/lipidology2010002

AMA Style

Holland-Winkler AM, Ruiz Ramie JJ, Moore AR, Kohler AA. The Relationship Between Arterial Stiffness and Circulating Lipids in Firefighters. Lipidology. 2025; 2(1):2. https://doi.org/10.3390/lipidology2010002

Chicago/Turabian Style

Holland-Winkler, Angelia M., Jonathan J. Ruiz Ramie, Andrew R. Moore, and Austin A. Kohler. 2025. "The Relationship Between Arterial Stiffness and Circulating Lipids in Firefighters" Lipidology 2, no. 1: 2. https://doi.org/10.3390/lipidology2010002

APA Style

Holland-Winkler, A. M., Ruiz Ramie, J. J., Moore, A. R., & Kohler, A. A. (2025). The Relationship Between Arterial Stiffness and Circulating Lipids in Firefighters. Lipidology, 2(1), 2. https://doi.org/10.3390/lipidology2010002

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