Related Experiment Video
Updated: Feb 10, 2026
Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts
Published on: January 29, 2018
Factors Affecting Bone Mineral Density Among Snowy Region Residents in Japan: Analysis Using Multiple Linear
Teppei Suzuki1, Tomoko Shimoda1, Noriko Takahashi1
1Faculty of Health Sciences, Hokkaido University, Sapporo, Japan.
Background:
As the onset of osteoporosis leads to reduced activities of daily living and may result in patients being bedridden, efforts to prevent decreased bone density are necessary. Various studies on the relationship between sex, age, nutrients, and exercise habits and bone mineral density have been conducted to date. However, for snowy region residents, the magnitude of influence of various factors affecting bone mineral density and the influence level have not been clarified.
Objective:
This study aimed to clarify the degree of influence and factors influencing bone mineral density based on survey results on health conditions and lifestyle habits in heavy snow areas.
Methods:
A total of 354 citizens who visited a drugstore in the target area were included in a study that included using the brief-type self-administered diet history questionnaire on lifestyle and exercise habits. Height, weight, body composition, and bone densitometer values were analyzed using multiple regression to calculate their association with bone mineral density. In addition, a Bayesian network model was used to determine the influence level of each factor as a conditional probability.
Results:
Multiple regression analysis revealed that age, sex, fracture, and calcium intake significantly influenced bone mineral density. In addition, the result of Bayesian network analysis suggested that age and sex affected bone mineral density, whereas nutrients and exercise habits might not have a direct impact. However, calcium intake and the T-score were significant factors affecting the presence or absence of fracture experiences, suggesting that adequate calcium intake is essential for preventing fractures.
Conclusions:
In the multiple regression analysis, age, sex, fracture, and calcium intake were selected as factors; however, in the Bayesian analysis, only age and sex affected bone mineral density while nutrients did not. In addition, the fact that calcium intake and the T-score were shown to affect bone fracture history suggests that calcium intake is an important measure that can prevent bone fractures. Overall, these results suggest that measures such as ensuring a bone fracture-free environment and providing nutritional advice for calcium intake can be effective in preventing bone loss.
Related Concept Videos
01:25Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
01:11Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
01:52Regression Toward the Mean
01:18Microsoft Excel: Regression Analysis
To perform regression...
01:31Essential Minerals for Bone Health
Calcium and Phosphorus
Calcium is a critical component of bones, especially in the form of calcium phosphate and calcium carbonate. Since the body cannot make calcium, it must be obtained from the diet. However, calcium cannot be absorbed from the small intestine without...
01:05Noncompartmental Analysis: Mean Residence Time
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...