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Created: Sep 3, 2016
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Bone Density Measurements
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Introduction

Bone Density test can provide useful information in determining an individual’s risk for fractures based on their bone mineral content. This information could be useful for physicians in knowing if individuals with bone fractures, were due to a low bone density and/or accident. Results of bone density test could also aid in preventative care in those with known lower densities. 

Method

A sample of 18 individuals with femoral neck stress fractures were collected. Data included the individuals age, gender, and bone density (mg/ml). This data was compared to the University of California San-Francisco database (UCSF) consisting bone density measurements of several thousand health individuals. We looked at Bone Density tests to compare men and women.

Statistical Analysis

Below are the Boxplots for the Bone Density in males and females from our study versus the UCSF measurements of healthy individuals (male and female).

Result 1: Bone density 1   [Info]
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Result 5: Boxplot123   [Info]
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Using a one sample T-test the data was grouped by gender (male and female) with a 95% confidence interval. This is also compared to the UCSF measurements in healthy individuals with a 95% confidence interval. 

Result 2: One Sample T Bone Density   [Info]
One sample T hypothesis test:
Group by: gender
μ : Mean of bonedensity
H0 : μ = 0
HA : μ ≠ 0

Hypothesis test results:
genderSample MeanStd. Err.DFT-StatP-value
female148.966679.1178092216.3379890.0037
male155.273336.61911711423.458315<0.0001

 

Result 3: One Sample Tourtest   [Info]
One sample T confidence interval:
Group by: gender
μ : Mean of bonedensity

95% confidence interval results:
genderSample MeanStd. Err.DFL. LimitU. Limit
female148.966679.11780922109.7359188.19743
male155.273336.619117114141.07674169.46993

Result 4: One Sample T12345   [Info]
One sample T confidence interval:
Group by: gender
μ : Mean of UCSF norm

95% confidence interval results:
genderSample MeanStd. Err.DFL. LimitU. Limit
female184.666672.02758752175.94266193.39067
male2192.622249114213.37583224.62417

Discussion/Conclusion

 

While comparing the bone density in males and females with femoral neck stress fractures it shows that the males in the sample have a higher mean than woman in both our study and the study done by UCSF. It is interesting that in healthy individuals the average bone densities in male vs. females is much more wide spread. In the current conducted study, it may prove valuable to look at other medical conditions the individuals study may have had, possibly income levels, education, and so on. It may be helpful to get a better 'whole' picture of the individuals from our group to see if anything else contributed to the lower bone densities.  These may be considered confounders that may have skewed the data. 


 



 

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Comments
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By nku.katie.waters
Sep 7, 2016

Hi Jessica,
Nice work on your report! A few comments:
1. Your hypothesis test results are not really useful as you are testing whether the mean bone density differs from 0. We would expect such results to be significant.

2. Your confidence interval results are correct. Keep in mind that confidence intervals allow us to generalize about the entire population. When interpreting them you should focus on the lower and upper limits. For example: With 95% confidence we estimate average bone density for young men who have femoral stress fractures to be somewhere between 141 and 169 mg/ml, and for young women the average bone density is somewhere between 110 and 188 mg/ml.

3. We can use the empirical rule to give consideration to individuals which can be useful in clinical application. We use the sample mean and standard deviation to calculate two standard deviations above and below the sample mean. This tells us that the typical bone density for a female is between 117.4 mg/ml and 180.6 mg/ml and the typical bone density for a male is between 104.0 mg/ml and 206.5 mg/ml.

4. Because of the small sample sizes, the confidence intervals are very wide. The lack of statistical power makes it too difficult to make comparisons between men and women using this data.

Please take a look at the solutions and let me know if you have any questions.
By debbie.hagedorn1
Sep 5, 2016

Jessica,
You did a great job displaying the data in your report. Very simple and clear to understand. The box plot displaying the difference in the male and female in the UCSF group is impressive. Great point that future work in the area of other demographics such as income levels would be intriguing.
Debbie
By karissa.neidig
Sep 5, 2016

Jessica,
It was very easy for me to follow your report and figure out the results on my own. The box plots were easy to read for this scenario. I agree with what you said in your conclusion about looking at other medical conditions that the patient has, but I also think it may benefit to see what medications/vitamins a patient takes that may affect the results. Nice job!
Karissa
By teri.corbin24
Sep 4, 2016

Good conclusion, I agree with you. There seems more surrounding information is needed that could impact the outcomes if done in different areas.

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