{"title":"The path less traveled: Using structural equation modeling to investigate factors influencing bone functional morphology","authors":"Rob'yn A. Johnston, Libby W. Cowgill","doi":"10.1002/ajpa.24999","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Objectives</h3>\n \n <p>The relationship between an organism's mechanical environment and its bone strength has been long established by experimental research. Multiple intrinsic and extrinsic factors, including body mass, muscle strength, genetic background, and nutritional and/or hormonal status, are likely to influence bone deposition and resorption throughout the lifespan, complicating this relationship. Structural equation modeling (SEM) is uniquely positioned to parse this complex set of influences.</p>\n </section>\n \n <section>\n \n <h3> Materials and Methods</h3>\n \n <p>Data from the Third National Health and Nutrition Examination Survey, including sex, total body mass, lean body mass, exercise frequency, peak body mass, and age, were analyzed using SEM to determine how they affect bone strength both individually and combined.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Body mass is typically the driver of cross-sectional area, but body mass and lean mass have similar effects on the polar moment of area (J). Peak body mass had a strong direct effect on J, despite decreasing strongly with increases in lean mass. Exercise also did not confer a large direct effect on cross-sectional area or J but did modify body mass and lean mass. In females, intentional weight loss was associated with decreased exercise levels.</p>\n </section>\n \n <section>\n \n <h3> Discussion</h3>\n \n <p>SEM is a useful tool for parsing complex systems in bone functional morphology and has the potential to uncover causal links in the study of skeletal remodeling, including factors like weight loss or exercise that may have secondary effects.</p>\n </section>\n </div>","PeriodicalId":29759,"journal":{"name":"American Journal of Biological Anthropology","volume":"185 2","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Biological Anthropology","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ajpa.24999","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ANTHROPOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives
The relationship between an organism's mechanical environment and its bone strength has been long established by experimental research. Multiple intrinsic and extrinsic factors, including body mass, muscle strength, genetic background, and nutritional and/or hormonal status, are likely to influence bone deposition and resorption throughout the lifespan, complicating this relationship. Structural equation modeling (SEM) is uniquely positioned to parse this complex set of influences.
Materials and Methods
Data from the Third National Health and Nutrition Examination Survey, including sex, total body mass, lean body mass, exercise frequency, peak body mass, and age, were analyzed using SEM to determine how they affect bone strength both individually and combined.
Results
Body mass is typically the driver of cross-sectional area, but body mass and lean mass have similar effects on the polar moment of area (J). Peak body mass had a strong direct effect on J, despite decreasing strongly with increases in lean mass. Exercise also did not confer a large direct effect on cross-sectional area or J but did modify body mass and lean mass. In females, intentional weight loss was associated with decreased exercise levels.
Discussion
SEM is a useful tool for parsing complex systems in bone functional morphology and has the potential to uncover causal links in the study of skeletal remodeling, including factors like weight loss or exercise that may have secondary effects.
目的:生物体的机械环境与骨强度之间的关系早已被实验研究证实。多种内在和外在因素(包括体重、肌肉力量、遗传背景以及营养和/或激素状况)可能会影响人一生中的骨沉积和吸收,从而使这种关系变得更加复杂。结构方程建模(SEM)在解析这一系列复杂的影响因素方面具有独特的优势:使用 SEM 分析了第三次全国健康与营养调查的数据,包括性别、总体重、瘦体重、运动频率、峰值体重和年龄,以确定它们如何单独或合并影响骨强度:体重通常是横截面积的驱动因素,但体重和瘦体重对面积极矩(J)的影响相似。峰值体重对J有很强的直接影响,尽管随着瘦体重的增加,峰值体重会大幅下降。运动也不会对横截面积或 J 产生很大的直接影响,但会改变体重和瘦体重。在女性中,有意减轻体重与运动量减少有关:SEM是解析骨骼功能形态复杂系统的有用工具,并有可能在骨骼重塑研究中发现因果联系,包括可能产生次生效应的减肥或运动等因素。