人体测量变量和PEFR

Q4 Health Professions
Rashmi Chandel, Garima Shivhare, A. Bhagat
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引用次数: 0

摘要

不同地区的呼气峰流量(PEFR)随年龄、身高、体重、体表面积等人体测量变量的变化而变化。本研究旨在分析PEFR与人体测量变量的关系,以了解该地区的参考值。我们对在印度帕蒂亚拉从事未接触污染物工作的18至45岁的健康成年男性进行了本研究。对每个人体测量变量类别进行分组。PEFR记录使用Mini Wright峰值流量计完成。结果以平均PEFR±标准差(mean±S.D.)表示,采用学生t检验确定均值之间的差异。我们观察到PEFR与所有人体测量变量呈线性增加。确定PEFR与人体测量变量的相关性。PEFR与身高、体表面积呈正相关(r = +0.20),与年龄(r = - 0.24)、体重(r = - 0.02)呈负相关。PEFR与身高相关性最好(r = +0.48),且结果极显著(p < 0.01)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Anthropometric Variables and PEFR
Peak expiratory flow rate (PEFR) varies with anthropometric variables like calendar age, body height, body weight, and body surface area in different regions. The present study aims at analyzing the relationship of PEFR with anthropometric variables to know a reference value in this region. We conducted the present study on healthy adult males aged eighteen to forty-five years engaged in works where they were un-exposed to pollutants in Patiala, India. Subgroups were made in each anthropometric variable category. PEFR recording was done using Mini Wright Peak Flow Meter. Results are expressed as mean PEFR ± standard deviation (mean ±S.D.), while the students’ t-test was used to determine the differences between the means. We observed a linear increase in PEFR with all anthropometric variables. The correlation of PEFR with anthropometric variables was determined. PEFR is positively correlated with body height and body surface area (r = +0.20) and negatively correlated with calendar age (r = – 0.24) and body weight (r = – 0.02). We conclude that PEFR correlates best with body height (r = +0.48), and the result is highly significant (p < 0.01).
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来源期刊
Central European Journal of Sport Sciences and Medicine
Central European Journal of Sport Sciences and Medicine Business, Management and Accounting-Tourism, Leisure and Hospitality Management
CiteScore
0.60
自引率
0.00%
发文量
9
审稿时长
12 weeks
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