Simple Prediction Equation Research Articles

Investigation on the physical, mechanical and microstructural properties of epoxy polymer matrix with crumb rubber and short fibres for composite railway sleepers

Crumb rubber and short fibres are introduced into the epoxy polymer core of composite railway sleepers to reduce cost and improve mechanical performance. The study investigates the effects of increasing content of crumb rubber, chopped glass fibres and polypropylene fibres. The experimental results including the microstructure of the polymer mixes demonstrate that short fibres enhanced the flexural and shear performance while the crumb rubber improved flexibility of polymer mixes. A simplified prediction equation was proposed to predict critical properties using the compressive strength. Analytical Hierarchy Process was also implemented to determine the most suitable polymer mix for the railway sleeper application.

Point‐Counterpoint: Indirect Calorimetry Is not Necessary for Optimal Nutrition Therapy in Critical Illness

Clinicians have widely recognized that indirect calorimetry (IC) is the "gold standard" for measuring energy expenditure (EE) and thus would intuitively anticipate that its use would be needed to provide optimal nutrition support in critical illness. Recent studies in the literature as well as dramatic changes in clinical practice over the past decade, though, would suggest that such a precise measure by IC to set energy goals is not required to maximize clinical benefit from early feeding in the intensive care unit (ICU). Results from randomized controlled trials evaluating permissive underfeeding, use of supplemental parenteral nutrition to achieve tight calorie control, and caloric density of formulas to increase energy delivery have provided an important perspective on 3 pertinent issues. First, a simple weight-based predictive equation (25 kcal/kg/day) provides a clinically useful approximation of EE. Second, a precise measure of EE by IC does not appear to improve outcomes compared with use of this less accurate estimation of energy requirements. And third, providing some percentage of requirements (50%-80%), achieves similar clinical benefit to full feeding (100%) in the early phases of critical illness. The value from IC use lies in the determination of caloric requirements in conditions for which weight-based equations are rendered inaccurate (anasarca, amputation, severe obesity) or the clinical state is markedly altered (such as the prolonged hyperinflammatory state of coronavirus disease 2019 [COVID-19]). In most other circumstances, routine use of IC would not be expected to change clinical outcomes from early nutrition therapy in the ICU.

The evaluation of soil detachment capacity induced by vegetal species based on the comparison between natural and planted forests

Planted forests and management operation method can potentially alter the soil properties as a consequence of changes in the characteristics of tree and plant species. However, the effects of planted forest species with different root systems on the soil detachment capacity (Dc) have not well been quantified. This study investigates the effects of plantation practice on the soil detachment capacity of soil with six vegetal species (Quercus castaneifolia, Alnus glutinosa, and Zelkova carpinifolia, as planted forest species) and Carpinus betulus, Parrotia persica, and Pinus taeda (as natural forest species) based on a comparison between natural and planted forests in forestland of the Saqalaksar Park (Northern Iran). To this aim, the soil detachment capacity on samples collected under trees of the studied species was measured in an experimental flume at five slopes (0.26, 0.35, 0.46, 0.57 and 0.69 m m−1) and flow rates (0.037, 0.086, 0.185, 0.285 and 0.376 L m−1 s−1). Moreover, simple prediction equations are suggested to evaluate the soil detachment capacity and rill erodibility (Kr) for studied species. The soils of natural forestland showed the lower soil detachment capacity compared to soils of the planted forestland, due to the different influence of plant root systems. Moreover, the inappropriate management practices in planted forestland could have worsened the soil properties and thus increased the soil detachment rate. The unit stream power was better predictor of Dc compared to other hydraulic parameters in both natural and planted forestlands. The rill erodibility of soils was higher in planted forestland than in natural forestland. According to the results, the natural forestland is able to show higher resistance against soil erosion in comparison with the planted forestland. These findings indicate that for sustainable management of forest ecosystems, the maintenance of natural vegetal species can be an effective practice to reduce the soil erosion.

Development of an Algorithm for Chemically Dispersed Oil Spills

An algorithm utilizing four basic processes was described for chemical oil spill dispersion. Initial dispersion was calculated using a modified Delvigne equation adjusted to chemical dispersion, then the dispersion was distributed over the mixing depth, as predicted by the wave height. Then the droplets rise to the surface according to Stokes’ law. Oil on the surface, from the rising oil and that undispersed, is re-dispersed. The droplets in the water column are subject to coalescence as governed by the Smoluchowski equation. A loss is invoked to account for the production of small droplets that rise slowly and are not re-integrated with the main surface slick. The droplets become less dispersible as time proceeds because of increased viscosity through weathering, and by increased droplet size by coalescence. These droplets rise faster as time progresses because of the increased size. Closed form solutions were provided to allow practical limits of dispersibility given inputs of oil viscosity and wind speed. Discrete solutions were given to calculate the amount of oil in the water column at specified points of time. Regression equations were provided to estimate oil in the water column at a given time with the wind speed and oil viscosity. The models indicated that the most important factor related to the amount of dispersion, was the mixing depth of the sea as predicted from wind speed. The second most important factor was the viscosity of the starting oil. The algorithm predicted the maximum viscosity that would be dispersed given wind conditions. Simplified prediction equations were created using regression.

Development of an Easy-to-Use Prediction Equation for Body Fat Percentage Based on BMI in Overweight and Obese Lebanese Adults.

An accurate estimation of body fat percentage (BF%) in patients who are overweight or obese is of clinical importance. In this study, we aimed to develop an easy-to-use BF% predictive equation based on body mass index (BMI) suitable for individuals in this population. A simplified prediction equation was developed and evaluated for validity using anthropometric measurements from 375 adults of both genders who were overweight or obese. Measurements were taken in the outpatient clinic of the Department of Nutrition and Dietetics at Beirut Arab University (Lebanon). A total of 238 participants were used for model building (training sample) and another 137 participants were used for evaluating validity (validation sample). The final predicted model included BMI and sex, with non-significant prediction bias in BF% of −0.017 ± 3.86% (p = 0.946, Cohen’s d = 0.004). Moreover, a Pearson’s correlation between measured and predicted BF% was strongly significant (r = 0.84, p < 0.05). We are presenting a model that accurately predicted BF% in 61% of the validation sample with an absolute percent error less than 10% and non-significant prediction bias (−0.028 ± 4.67%). We suggest the following equations: BF% females = 0.624 × BMI + 21.835 and BF% males = 1.050 × BMI − 4.001 for accurate BF% estimation in patients who are overweight or obese in a clinical setting in Lebanon.

Ground Motion to Intensity Conversion Equations for Iran

New empirical relations between macroseismic intensity and ground motion parameters including peak ground acceleration and velocity are developed using strong ground motion data and Modified Mercalli Intensity (MMI) information from earthquakes within Iran plateau. The strong motion data consists of 116 three-component waveforms of 23 earthquakes with Mw 5.1–7.3 occurred from 1977 to 2017. The intensity values for each ground motion record were assigned considering the location of accelerograph stations on the isoseismal maps. Simple predictive equations are obtained by fitting a linear model to the mean peak ground motion values applying least squares regression. However, visual inspection of residuals shows magnitude and distance dependency for this set of equations. Improved relationships between ground motion and intensity are derived by comprising magnitude and distance terms as predictive variables. The refined ground motion to intensity conversion equations show smaller variability than simple linear equations in predicting MMI values. Both proposed models are compared with similar relationships in Iran and other regions of the world. The observed discrepancies in relationships may reflect the differences in input data, especially the macroseismic intensity assignments as well as regional variability. The proposed relations can be used for rapid hazard assessments and loss estimation in Iran and surrounding regions.

Derivation and validation of a simple anthropometric equation to predict fat-free mass in patients with chronic hepatitis C

Loss of skeletal muscle mass is very common in chronic liver diseases and affects 30.0-70.0% of the patients with cirrhosis. Given the relevance of muscle wasting in hepatic diseases, a practical screening tool for earlier detection of skeletal muscle mass loss is of utmost significance. To develop and validate a simple anthropometric prediction equation for fat-free mass estimation by using Bioelectrical Impedance Analysis (BIA) as a reference method in patients with chronic hepatitis C (CHC). We prospectively, included 209 CHC patients, randomly allocated into two groups, 158 patients in a development model (derivation sample) and 51 patients in a validation group (validation sample). Predictive equations were developed using backward stepwise multiple regression and the most adequate and simplest derived predictive equation was further explored for agreement and bias in the validation sample. The accuracy of the predictive equation was evaluated using the coefficient of determination (R2). The predictive equation with an optimal R2 was Fat-Free Mass (Kg)=Sex×0.17+Height (m)×16.83+Weight (Kg)×0.62+Waist Circumference (cm)×(-0.15)+Weight (Kg)×Sex×(-0.30)+Sex×Waist Circumference (cm)×0.14-6.23; where sex=1 for female and 0 for male. R2=0.93, standard error of the estimate=2.6Kg and coefficient of variation=20.0%, p<0.001. Our developed and cross-validated anthropometric prediction equation for fat-free mass estimation by using BIA attained a high coefficient of determination, a low standard error of the estimate, and lowermost coefficient of variation. This study indicates that predictive equations may be reliable and useful alternative methods for clinical evaluation of fat-free mass in patients with CHC.

Wave Hydrodynamic Characteristics of Vertical and Sloped Seawalls

The hydrodynamic performance of vertical and sloped plane, rectangular serrated, and triangular serrated seawalls were investigated experimentally in terms of wave reflection coefficient, kr, relative wave run-up, Rup/Hi, and relative wave run-down, Rdown/Hi, using physical model studies. Regular waves of wide rang of heights, and periods were used. Tests were carried out for different inclinations of seawall (i.e. ), relative dissipater blocks spacing (s/w =1.0, 2.0, 3.0), and a constant water depth of 0.4 m. It was observed that the rectangular serrated seawall was superior to the triangular serrated and plane seawall in reducing the hydrodynamic parameters mentioned above. As well it was found that the relative spacing of dissipater blocks, s/w, wave steepness, Hi/Li, and the relative water depth, d/Li were better influencing parameters compared to the surf similarity parameter (Iribarren N0), in predicting the wave hydrodynamic parameters. Both rectangular and triangular serrated seawalls gives a good results for all hydrodynamic parameters when, s/w=2.0 compared to s/w equal to1.0 and 3.0. A total performance evaluation was done in terms of a single parameter called hydrodynamic performance parameter, and it was found that for s/w=2.0, both rectangular and triangular serrations reduces this parameter by about 37% and 28% respectively compared with the plane seawall. The worst results for performance parameter were observed when , while the optimum values occur when, s/w equal to (2.21-2.27), and (2.34-2.41) for the rectangular and triangular serrated seawalls respectively. Simple predictive equations were developed for estimating the wave reflection coefficients, relative run-up, and relative run-down by using non-linear regression analysis by SPSS.16 (SPSS Inc, 2006) software.

A Simple and Sustainable Prediction Method of Liquefaction-Induced Settlement at Pohang Using an Artificial Neural Network

Conventionally, liquefaction-induced settlements have been predicted through numerical or analytical methods. In this study, a machine learning approach for predicting the liquefaction-induced settlement at Pohang was investigated. In particular, we examined the potential of an artificial neural network (ANN) algorithm to predict the earthquake-induced settlement at Pohang on the basis of standard penetration test (SPT) data. The performance of two ANN models for settlement prediction was studied and compared in terms of the R2 correlation. Model 1 (input parameters: unit weight, corrected SPT blow count, and cyclic stress ratio (CSR)) showed higher prediction accuracy than model 2 (input parameters: depth of the soil layer, corrected SPT blow count, and the CSR), and the difference in the R2 correlation between the models was about 0.12. Subsequently, an optimal ANN model was used to develop a simple predictive model equation, which was implemented using a matrix formulation. Finally, the liquefaction-induced settlement chart based on the predictive model equation was proposed, and the applicability of the chart was verified by comparing it with the interferometric synthetic aperture radar (InSAR) image.

A Multi-Axial Fatigue Limit Prediction Equation for Metallic Materials

Abstract Based on the multi-axial fatigue life prediction model presented recently by the authors, in this note, a fatigue limit prediction equation for metallic materials under multi-axial loading is proposed. In the multi-axial fatigue life prediction model, the wildly used von Mises equivalent stress is taken as an equivalent fatigue mechanical quantity, and the multi-axial fatigue life prediction equation has the invariance of mathematical equation form. By applying the multi-axial fatigue life prediction equation without mean stress effect to fatigue limit case, a simple fatigue limit prediction equation can be obtained. By using a large number of experimental data of metallic materials reported in literature, it has been proven that the fatigue limit prediction equation is not only simple in computation but also high in accuracy.

Estimating permeability and porosity of plant tissues: Evolution from raw to the processed states of potato

During the processing of water containing food materials, water transport can be driven by pressure from gas, capillarity, swelling, or gravity. To describe these various modes of pressure-driven transport using Darcy's law, permeability is a critical parameter for which few data are available, primarily as a result of measurement difficulties. Permeability in the flow of liquid water through potato tissue was estimated by approximating the plant cellular structure, measured directly using flow-through and indirectly using nuclear magnetic resonance. The data from the three approaches show the same order of magnitude 10−18 m2, and thus are in agreement with each other and results reported in the literature. The dynamics of porosity and permeability changes in fresh, water-saturated, and cooked samples were described using cellular structure changes as observed in microscopy images. Simple mechanistic equations for predicting permeability and porosity, which can include swelling and shrinkage, are proposed based on approximating the geometry of the cellular tissue. Data corroborated in three ways will provide permeability values with confidence, while the simple prediction equation will make a reasonable estimation of permeability possible for a large class of food products.

Incorporating ground motion effects into Sasaki and Tamura prediction equations of liquefaction-induced uplift of underground structures

In metropolitan areas, the quantity and density of the underground structure increase rapidly in recent years. Even though most damage incidents of the underground structure were minor, there were still few incidents causing a great loss in lives and economy. Therefore, the safety evaluation of the underground structure becomes an important issue in the disaster prevention plan. Liquefaction induced uplift is one important factor damaging the underground structure. In order to perform a preliminary evaluation on the safety of the underground structure, simplified prediction equations were introduced to provide a first order estimation of the liquefaction induced uplift. From previous studies, the input motion is a major factor affecting the magnitude of the uplift. However, effects of the input motion were not studied and included in these equations in an appropriate and rational manner. In this article, a numerical simulation approach (FLAC program with UBCSAND model) is adopted to study effects of the input motion on the uplift. Numerical results show that the uplift and the Arias Intensity (Ia) are closely related. A simple modification procedure to include the input motion effects in the Sasaki and Tamura prediction equation is proposed in this article for engineering practices.

Percent Body Fat Prediction from Body Mass Index and Waist Circumference: New Cross-validated Equations for Young Adults

Background: A simple prediction equation that accurately predicts an individual’s percent body fat (PBF) with easy to obtain inputs could benefit health and exercise science professionals. The purpose of this study was to develop and cross-validate a set of regression equations predicting PBF in young adults. Methods: A subset of N=684 participants from a national health survey between the ages of 18 and 24 years was used in this study. Criterion values of PBF (PBF.DXA) were obtained using dual energy X-ray absorptiometry (DXA). Predictor variables included age, sex, body mass index (BMI), and waist circumference (WC). The sample was split equally and randomly into training and validation samples. Two sets of equations were evaluated in the training sample, one set using BMI and the other using WC. Both sets were tested to determine if age was a useful predictor of PBF.DXA. Cross-validation of selected model coefficients using the validation sample was evaluated using Pearson correlation coefficients, Bland and Altman limits of agreement (LOA) plots and Kappa statistics for obesity classification. Results: The selected models were both two-predictor equations: PBF.BMI2 = 10.47827 + BMI*0.98342 – 12.50670; R2 = .872 and PBF.WC2 = 2.51020 + WC*0.38914 – 13.34843; R2 = .866. Cross-validation correlation coefficients were large for both PBF.BMI2 (r = .91) and PBF.WC2 (r = .92) equations. LOA plots indicated small bias of -0.49 ± 7.5% and -0.25 ± 6.8% in PBF.BMI2 and PBF.WC2 analyses, respectively. Kappa coefficients for agreement between the two obesity classification methods were considered “substantial” for PBF.BMI2 (κ = .64) and PBF.WC2 (κ = .70) models. Conclusion: This study provides validation evidence supporting the use of BMI- and WC-based PBF prediction equations in young adult populations.

Effect of elevated in-service temperature on the mechanical properties and microstructure of particulate-filled epoxy polymers

In civil engineering applications, epoxy-based polymers are subject to different environmental conditions including in-service temperature, which might accelerate their degradation and limit their application ranges. Recently, different particulate fillers were introduced to enhance the mechanical properties and reduce the cost of epoxy-based polymers. This paper addresses the effect of in-service elevated temperature (from room temperature to 80 °C) in particulate-filled epoxy based resin containing up to 60% by volume of fire retardant and fly ash fillers through a deep understanding of the microstructure and analysis of their mechanistic response. An improvement in the retention of mechanical properties at in-service elevated temperature was achieved by increasing the percentages of fillers. The retention of compressive and split tensile strength at 80 °C for the mix containing 60% fillers was 72% and 52%, respectively, which was significantly higher than the neat epoxy. Thermo-dynamic analysis showed an increase in glass transition temperature with the inclusion of fillers, while these mixes also experienced less weight loss compared to neat epoxy, indicating better thermal stability. Scanning electron microscopy images showed the formation of dense microstructures for particulate-filled epoxy based resin at elevated temperatures. This indicates that the particulate filled epoxy resin exhibits better engineering properties at in-service elevated temperatures, increasing their durability and therefore their suitability for civil engineering applications. A simplified prediction equation based on power function was proposed and showed a strong correlation to the experimental compressive and splitting tensile strength at different levels of in-service elevated temperature.

Estimating the Service Life of Activated Carbon Filters for Air Purification

It is very important to be able to predict the breakthrough time of gas mask filters under real life circumstances. This article describes the use of a very simple predictive equation, the Wheeler-Jonas equation, that yields excellent predictions but only within a very restrictive set of boundary conditions. In order to make this model work in a more realistic environment, it has been gradually adapted to take into account a number of parameters related to this environment: a non-constant inlet concentration, a breather flow, new physical forms of activated carbon, the relative humidity and temperature of the ambient air, chemisorbed gases and mixtures of organic vapours. As (nearly) all of these parameters can be calculated independently of each other, based on data that are either readily available or that can be measured, their influence on the complexity of the model stays low. This makes this combined model both easy to use and powerful in predicting breakthrough times of gas mask filters under real-life conditions.

A New and Simple Prediction Equation For Health-Related Fitness: Use of Honest Assessment Predictive Modeling

A New and Simple Prediction Equation For Health-Related Fitness: Use of Honest Assessment Predictive Modeling

Simple GMPE for underground mines

A simple ground motion prediction equation (GMPE) is developed for peak ground velocity, PGV, and for cumulative absolute displacement, CAD, for underground mines. Assuming the ground velocity at source, $$\text{PGV}_{0}=0.63 v_{S} \Delta \epsilon$$ where $$v_{S}$$ is S-wave velocity and $$\Delta \epsilon$$ is the average strain change at seismic sources (Brune in J Geophys Res 75(26):4997–5009, 1970; Kanamori in Phys Earth Planet Inter 5:426–434, 1972), is independent of seismic potency, P, then $$\overline{\text{PGV}}\left( P,R\right) = \text{PGV}_{0} \cdot B$$ , where $$B = \left[ c_{L}P^{1/3}/\left( R+c_{L}P^{1/3}\right) \right] ^{c_{R}}$$ and R is distance. Assuming after Eshelby that at source $$\text{CAD}_{0} = q_{0}$$ $$\Delta \epsilon ^{2/3} P^{1/3}$$ , then $$\overline{\text{CAD}}\left( P,R\right) = \text{CAD}_{0} \cdot B$$ , where $$q_{0}=0.828494$$ . The S-wave velocity and the strain drop are strongly constrained by the type of rock and can be assumed, therefore both GMPE have only two parameters to be inverted from ground motion data: $$c_{L}$$ and $$c_{R}$$ . There is no provision made for site effect since in mines almost all sensors are placed in boreholes away from excavations. The basic outcome of ground motion hazard analysis for a given site is a seismic hazard curve that shows the annual rate, or probability, at which a specific ground motion level will be exceeded. It is expected that CAD that includes both the peak and the duration of ground motion may be a better indicator of damage potential than PGV alone, being a single measurement over the whole waveform. Two simple applications are presented. (1) A graphical trigger for damage inspection when the PGV predicted for an event at selected sites exceeds a predetermined level. (2) The cumulative CAD plot that may be a useful tool to monitor the consumption of the deformation capacity of the support due to seismicity.

Development of an Easy-to-Use Visual Aid for the Prediction of Body Fat Based on Waist Circumference and Height in Asian Chinese Adults

BackgroundAdiposity is a major risk factor for metabolic and cardiovascular diseases. Initial prediction equations to estimate adiposity are complex, requiring skinfold measurements that cannot be obtained conveniently by the general population. ObjectiveTo develop simplified prediction equations to estimate body fat percentage (%BF) in Asian Chinese adults, evaluate the validity of the simplified %BF prediction equations, compare the simplified %BF prediction equations with an existing equation, and create visual charts to enable easy assessment of adiposity by the general public. DesignSimplified prediction equations were developed and evaluated for validity using anthropometric measurements obtained from a cross-sectional study. Participants and settingHealthy participants with no major diseases and not taking long-term medications were recruited in a cross-sectional study conducted at Clinical Nutrition Research Centre, Singapore, between June 2014 and October 2017. A total of 439 participants were used for model building (269 women and 170 men) and another 107 participants were used for evaluating validity (62 women and 45 men). Main outcome measuresSimplified but acceptable prediction models and generation of user-friendly charts. Statistical analyses performedSimplified sex-specific %BF prediction equations were developed using stepwise regression and the model-building dataset. The best models were selected using the Akaike information criterion. The models were further simplified and their performance was compared using the validation dataset before choosing the final prediction equations. ResultsThe final selected models for women and men included waist circumference and height with nonsignificant prediction bias in %BF of 0.84%±3.94% (P=0.098, Cohen’s dz=0.21) and –0.98%±3.65% (P=0.079, Cohen’s dz=0.27), respectively. The final equations were split into three height categories from which the sex-specific prediction charts were generated. ConclusionsThe sex-specific prediction charts provide a good visual guide for estimating %BF using height and waist circumference values that are easy to obtain by the general public.

Investigation of residual stresses of hybrid normal and high strength steel (HNHSS) welded box sections

In order to obtain high bearing capacity and good ductility simultaneously, a structural column with hybrid normal and high strength steel (HNHSS) welded box section has been developed. Residual stress is an important factor that can influence the behaviour of a structural member in steel structures. Accordingly, the magnitudes and distributions of residual stresses in HNHSS welded box sections were investigated experimentally using the sectioning method. In this study, the following four box sections were tested: one normal strength steel (NSS) section, one high strength steel (HSS) section, and two HNHSS sections. Based on the experimental data from previous studies and the test results of this study, the effects of the width-to-thickness ratio of plate, yield strength of plate, and the plate thickness of the residual stresses of welded box sections were investigated in detail. A unified residual stress model for NSS, HSS and HNHSS welded box sections was proposed, and the corresponding simplified prediction equations for the maximum tensile residual stress ratio (σrt/fy) and average compressive residual stress ratio (σrc/fy) in the model were quantitatively established. The predicted magnitudes and distributions of residual stresses for four tested sections in this study by using the proposed residual stress model were compared with the experimental results, and the feasibility of this proposed model was shown to be in good agreement.

A New and Simple Prediction Equation for Health-Related Fitness: Use of Honest Assessment Predictive Modeling

Background: The five components of health-related fitness are cardiorespiratory endurance, muscular strength, muscular endurance, body composition, and flexibility. To assess an individual on all five components can be time consuming. Thus, it would be useful to fitness specialists if a simpler and valid fitness assessment was available to measure overall health-related fitness. The purpose of this study was to employ honest assessment predictive modeling to find a parsimonious set of variables that can predict overall health-related fitness. Methods: Data used for this study came from college students who completed a fitness test battery. An overall health-related fitness score (T-score) was constructed using maximal oxygen consumption (VO2, ml/kg/min), 1RM bench press (BP, lb), maximal push-up repetition (PU, #), and percent body fat (PBF, %). The set of possible predictor variables consisted of participant age (yr), sex (male/female), body mass index (BMI, kg/m2), waist circumference (WC, cm), 1RM leg press (LP, lb), countermovement vertical jump (VJ, in), flexed arm hang (FAH, sec), physical activity rating (PAR, 0 thru 10), and sit-and-reach (SNR, cm). The honest assessment predictive modeling procedure comprised three steps: 1) development of competing models using a TRAINING dataset, 2) selecting an optimal model using a separate VALIDATION dataset, and 3) assessing fitness score construct validity using a final SCORING dataset. Results: Stepwise model selection with Schwarz Bayesian criterion (SBC) on the TRAINING data resulted in five possible models including sex, VJ, PAR, and WC. Results on the VALIDATION data indicated a three-variable model had the lowest average squared error (ASE) and consisted of sex, VJ, and PAR (F=107.8, pR2=.82, SEE=3.09). Finally, predicted values from the SCORING data showed that athletes (Mean=54.9, SD=5.1) had a significantly (p.001) greater mean fitness score than non-athletes (Mean=39.8, SD=4.8). Conclusion: This study presents a valid equation that can simply predict overall health-related fitness in college students.