The authors wish to acknowledge the following individuals for the guidance and support provided throughout the completion of this project:
Mrs. Peggy Larisch - Teacher, Silver High School, Advanced Computer Studies and Mathematical Models
Dr. Brian Robinson - Doctor of Orthopedics, Grant County Orthopedics and Associates, Orthopedics
Dr. Robert Schenks - Doctor of Orthopedics, University Hospital, Orthopedics
Dr. Thomas Gruska - Teacher, Western New Mexico University, Interpretation of Statistical Data

The purpose of this project is to determine whether Body Mass Index (BMI), age, and gender have an affect on what type of knee injury a person will receive. To determine this, research was done at a local orthopedic office, and statistics were collect ed from patients who had received certain types of knee injuries in the past two years. These statistics were entered into a database, which was read by a C++ program. This program not only has the ability to calculate the BMI of a user; it outputs the percentage of patients that received each of the various injuries based on age and BMI ranges entered by the user. To determine this, the program will count from the dat abase the number of patients that received an injury for each of the specified ranges, and divide that number by the total patient who received that particular injury. This solution is multiplied by one hundred to figure the percentile. This process is repeated many times to find the solutions of seven different knee injuries. Two solutions in each category will be given-- first for age and second for BMI. If the user enters the personal information accurately, and uses a range in which he or she is included, the results will show the user which injury they are most susceptible to as a result of their BMI and age. Based on the average BMI and age ranges of the patients located in the database, younger people with lower BMI tend to tear the anterior cruciate ligament of the knee and fracture the upper tibia. Older and heavier people seem to be more prone to injurie s involving the lateral collateral ligament. Male and female patients with similar age seem to receive similar injuries. It was surprising to observe that of a total of 303 patients, the female to male ratio of injuries was approximately one-to-one.

1.1 Purpose

The purpose of this project is to develop a statistical comparison and the associated computer program required to examine the affects of Body Mass Index (BMI), age, and gender have on a range of knee injuries. Following a personal experience involvin g a knee injury during an athletic event, the project was created to satisfy the desire of the team members to determine what factors, besides athletics, act as indicators to specific knee injuries.

1.2 Background Research

The knee is a very important part of life, and is used daily for activities such as walking, running, and jumping. There are many components in the knee, all of which have significantly different, but equally important responsibilities. The component s that are used in this project are the Anterior Cruciate Ligament (ACL), Lateral Collateral Ligament (LCL), Medial Collateral Ligament (MCL), Medial Meniscus, Lateral Meniscus, Patella, and Upper Tibia.

The ACL prevents the tibia from sliding forwards beneath the femur. The ACL can be injured by a rapid change in direction, deceleration when running, landing from a jump, or, though an ACL tear is usually a non-contact injury, by direct contact such a s a football tackle1. If the ACL is torn, reconstructive surgery is required to repair the damage.

The LCL and MCL work together to provide stability for the knee. The MCL connects the femur to the tibia and supplies stability to the inner side of the knee, while the LCL connects the femur to the fibula and stabilizes the outer side of the knee. I njuries to the MCL are caused by contact of the outer knee, and can be treated by rest if the tear is small1. Rest is needed to repair such partial tears, but if the fibers cannot heal by themselves, surgery is required. Treatment of LCL injuries is sim ilar to MCL treatment, but requires a longer resting period as the LCL takes longer to heal2.

The meniscus lies between the femur and the tibia functions as a shock absorber. The Medial Meniscus is located on the inner side of the knee, while the Lateral Meniscus is positioned on the outer side of the knee. Injuries to these menisci are commo n, the most frequent cause being a combined loading and twisting action, and are often associated with ligament tears. Treatment for this injury is rest and ice. However, surgery may be necessary if the menisci do not heal on their own3.

The Patella is a small bone in the front of the knee that glides up and down in the femoral groove in the femur as the knee bends and straightens. A dislocation of the patella occurs when the patella completely comes out of the femoral groove. Most c ommonly, patella are dislocated by a plant and twist movement, or after direct contact. Rest and special knee braces are used to treat this type of injury, and surgery is rarely needed4.

The tibia and the fibula form part of the knee and the ankle. The tibia has very little soft tissue in front of it. Due to this fact, open fractures of the upper tibia are more common than fractures of the femur or fibula. These fractures rarely occ ur in children, but are usually treated with casts. In adults, fractures of the upper tibia is usually broken into many pieces, and need surgery to fix the bone with screws, a plate, and sometimes a bone graft. There is a higher risk of infection in fra ctures of the tibia, as the skin is broken surrounding the fracture5.

1.3 Scope

It is the intention of this project is classify the common knee injury of specific body types and age, based on statistical information collected from a local orthopedic office. The data, consisting of recent information from injured patients, will be used to calculate the percentage of patients that fall within a specified range. This will assist in the interpretation of the data to determine the Body Mass Index and age most prone to receiving a specific knee injury.

1.4 Computer Program

A C++ computer program will be developed by the team members to be used for this project. It is believed that this programming language will satisfy the objective of the project. Teamwork, as well as some individual work, will be needed to successful ly create a program that will obtain the desired results (Appendix #6).

2.1 Problem Statement

Many knee injuries occur each year, though the causes of these knee injuries remain a mystery. People receive knee injuries regardless of their BMI, age, and gender; however, these factors may have an affect on what type of knee injury is received.

The purpose of this project is to determine, based on data trends, if people of a specific BMI, age, and gender receive the same injury. In order to complete this project, research will be done at a local orthopedic office and the statistics will be u sed to create a computer program that will calculate the percentage of people with injuries in user specified BMI and age ranges.

3.1 Mathematical Model

This computer program was completely developed by the team and is used to determine which knee injury is most likely to occur based on a user's age, BMI, and the statistical information located in the database. The user is prompted to enter his or her weight (in pounds), height (in feet and inches), age, and gender. This information is necessary for the program to distinguish between male and female, and for the calculation of BMI to occur.

In order for this calculation to take place, the program converts the user's weight in pounds into kilograms, while the entered height, in feet and inches, is converted to meters.

The correct BMI of the input information will be calculated and output along with a BMI chart. This chart will show the user the different categories of BMI and the range in which he or she is classified. (Refer to Appendix #2 to see BMI chart)

The user, now understanding BMI classification, will be prompted to enter a range for the BMI portion of their search, as well as an age range in order to configure the percent of patients, similar in BMI and age, that received a knee injury. The prog ram, reading statistics (Appendix #1) from the data file injury.dat, will separate data, compiling only information from patients of the same gender as previously entered by the user. The program then further separates data by injury, and counts the tota l number of patients in each injury while counting the number of patients that fall within the BMI and age ranges entered by the user. To calculate the percentage of a certain injury, the total number of patients within the range is divided the total num ber of patients the received the specific injury and multiplied by one hundred.

The computer program outputs the seven types of injuries and the percentages associated with each injury. From these outputs, the user can visualize which injury they are most prone to receive if a knee injury were to occur. A higher percentage means a higher risk, while a lower percentage indicates a lower risk.

3.2 Computational Methods

In summary, the computer program will:

• Input user's height, weight, age, and gender
• Calculate BMI and print out BMI chart
• Input user's range for BMI and age
• Reads data from database, injury.dat (Appendix #1) using a "for" loop
• Filters and saves information matching the gender and range input by user
• Counts total patients of an injury, while counting number of patients within user-specified range of the same injury using a "for" loop
• Repeats this cycle for each separate injury (using a "for" loop)
• Calculates the percentage of patients within both BMI and age ranges for each separate injury
• Outputs types of injuries using "if" statements
• Outputs percentages for each separate injury for both ranges

4.1 Calculations

The computer program calculates the percentage of patients with specific knee injuries within a range entered by the user. Refer to Appendix #7 to see an example of an operating program.

4.2 Graphs, Tables, and Figures

The charts two below separate the results by gender and type of injury, and show the final calculations of the project (Also available in Appendix #3).

Many trends of information existed in the comparison of data. Of the 303 patients in the database, 52% are female while 48% are male. The most common injury for each gender is the tear of the Medial Meniscus. This injury is credited for 45% of all f emale injuries and 40% of al male injuries. The least common injury for each group is a sprain of the Lateral Collateral Ligament. Approximately 3% of females and 1% of the males obtained this injury. (Refer to Appendix #5 to view this information)

Using the average BMI information of each gender and injury:

• Two female injuries occurred within a normal BMI range. These injuries include the tear of the ACL, and an upper tibia fracture. No average male information contained normal BMI classifications.
• The dislocation of the patella and lateral meniscus tears most commonly occurred in women classified as overweight. All male injuries except for the one, the dislocation of the patella, occurred in the overweight category.
• Obese women obtained medial meniscus, lateral collateral ligament and medial collateral injuries, while men in this classification group received a dislocation of the patella.

Using the average age information of each gender and injury:

• Twenty-eight years old was the most common age for both man and female ACL patients.
• Thirty-one years old was the most common age for both male and female tibia fracture patients.
• A tear of the medial meniscus contained the oldest average age for each gender.

5.1 Mathematical Models

The mathematical models used in this project were very adequate in obtaining correct and acceptable solutions, as the results came strictly from the statistics. The program used these models and tested each individual statistic to check if it satisfie d the specified ranges of BMI and age. The program counted the statistics that suited these ranges, and also the total number of statistics it checked. This enabled the program to calculate a percentage that is used to show the user which injury occurre d most often in the ranges they entered. The solutions satisfied the problem, as it proved that certain knee injuries are received by groups of people containing similar BMI and/or age.

5.2 Computer Program

The computer program successfully completed the intended task, though some adjustments had to be made to the code throughout the duration of this project. The separation of data was difficult to code; however, with the use of "for" loops and "if" stat ements, the program accomplished the task at hand. The ability of C++ and JAVA to read data files helped with simplifying the program code (Appendix #6).

5.3 Results

There is enough deviation between the average age and BMI of each individual injury to categorize a person based on his or her BMI, age, and gender. For females this deviation is greater because of the large difference in BMI ranges pertaining to each injury type. It can be concluded that it is more common for younger people, with lower BMI, to tear the anterior cruciate ligament or fracture the upper tibia. This is most likely due to the involvement with athletics. Heavier and older people tend to injure the lateral collateral ligament. The fact that most of the older people in the research were also overweight may explain the cause of such injuries. Older bodies are more prone to getting hurt unless they are kept healthy and active. If a perso n is also considered to be overweight, this increases the chance of receiving an injury.

The results of the computer program vary as different BMI and age ranges are entered by a user. Because a smaller range is more specific, it demonstrates the largest difference between injuries and the percentile in which the user was classified. Lar ger ranges, though calculating higher percentages within each category, seem to balance the results of the differing knee injury calculations. For example, if an age range between 5 years and 60 years is entered, and the majority of the patients listed i n the data file are classified between these ages, each injury will relate the user to ninety to one hundred percent of the patients involved in the study.

5.4 Recommendations

The only recommendation the members of the team can suggest to increase the accuracy of this project is an increase in statistical information, and improve the method of collecting it. More information, especially from outside sources, would make the project more accurate for a person living anywhere, not just in the scope of the local orthopedic office where all information used for this project was collected.

1. "Knee ligament injuries." AAOS Online Service Fact Sheet. http://orthoinfo.aaos.org/fact/thr_report.cfm?Thread_ID=157&topcategory=Knee (3 Dec. 2001). Pg. 1-4.
   
   
2. Miller, Mark D. Review of Orthopaedics. Ed. Bohlman, Henry H., Corley, Fred G, Jr., Deffer, Philip A., et al. Mexico: W.B. Saunders, 1992. Pg. 94-96.
   
   
3. "Meniscal (Cartilage) Injuries." Knee Pain Info . Com. http://www.kneepaininfo.com/kneemeniscus.html (10 March 02). Pg 1-2.
   
   
4. "Patellar Dislocation." Knee Pain Info . Com. http://www.kneepaininfo.com/kneepatellardislocation.html (10 March 02). Pg. 1-2.
   
   
5. "Tibia fractures." http://www.liverpoolortho.com/fractures_of_the_tibia.htm (12 March 02). Pg. 1-3.