A MAIL SURVEY OF PHYSICAL-ACTIVITY HABITS AS RELATED TO MEASURED PHYSICAL-FITNESS
A MAIL SURVEY OF PHYSICAL-ACTIVITY HABITS AS RELATED TO MEASURED PHYSICAL-FITNESS
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DOI：
10.1093/oxfordjournals.aje.a114915
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发表时间：
1988-06-01
影响因子：
5
通讯作者：
KRONENFELD, JJ
中科院分区：
文献类型：
--
作者：
KOHL, HW;BLAIR, SN;KRONENFELD, JJ
研究人员对邮件调查中自我报告的身体活动测量值与客观身体健康测量值之间的关联进行了调查。德克萨斯州达拉斯健美操研究所于 1982 年进行了一项健康状况调查（n = 12,225），调查对象为受访者。在该组中，在问卷返回后 60 天内也进行过临床检查的男性作为受试者。研究对象（n = 375，平均年龄 = 4.71 岁）使用修改后的 Balke 方案完成了最大体能评估。调查问卷包括有关休闲时间体育活动参与的询问部分，其中要求受试者定量回忆不同时间段的锻炼参与情况。报告的运动参与值被转换为能量消耗的估计值，并合并为身体活动参与的总体指数。使用多元回归分析来确定体力活动指数在预测跑步机最大表现（体能）方面的个体贡献。身体健康的重要预测因素是年龄（β = -0.34）、跑步、步行和慢跑参与指数（β = -0.31）以及对出汗频率问题的回答（β = 0.35）。这些变量预测身体健康的多重相关系数为 0.65。这些结果表明，通过使用邮件调查中的简单问题，可以准确估计大量人群的运动行为。
The associations of self-reported measures of physical activity from a mail survey with an objective measure of physical fitness were investigated. Respondents to a health status survey (n = 12,225), conducted in 1982 by the Institute for Aerobics Reasearch in Dallas, TX formed the population. From this group, males who also had a clinical examination within 60 days of the return of their questionaire served as subjects. The study subjects (n = 375, mean age = 4.71 years) completed a maximal physical fitness assessment using a modified Balke protocol. The questionnaire included a section of inquiries concerning lesiure time physical activity participation in which subjects were asked to quantitatively recall exercise participation for varying periods of time. Reported exercise participation values were converted to estimates of energy expenditure and combined into overall indices of physical activity participation. Multiple regression analyses were used to determine the individual contributions of the physical activity indices in predictin maximal treadmill performance (physical fitness). Significant predictors of physical fitness were age (.beta. = -0.34), an index of running, walking, and jogging participation (.beta. = -0.31), and the response to a question on frequency of sweating (.beta. = 0.35). The multiple correlation coefficient for these variables in predicting physical fitness was 0.65. These results indicate that exercise behavior can be accurately estimated in large populations by using simple questions in a mail survey.