Association of Physical Activity, Fitness, and Race: NHANES 1999-2004
Association of Physical Activity, Fitness, and Race: NHANES 1999-2004
复制标题
DOI：
10.1249/mss.0b013e318271689e
复制
发表时间：
2013-02-01
影响因子：
4.1
通讯作者：
Bassett, David R., Jr.
中科院分区：
文献类型：
--
作者：
Ceaser, Tyrone G.;Fitzhugh, Eugene C.;Bassett, David R., Jr.
CEASER、T. G.、E. C. FITZHUGH、D. L. THOMPSON 和 D. R. BASSETT JR。体育活动、健身和种族协会：NHANES 1999-2004。医学。科学。体育锻炼，卷。 45，第 2 期，第 286-293 页，2013 年。目的：定期体力活动 (PA) 可用于改善心肺健康 (CRF)。先前的研究已经表明不同种族群体之间 CRF（(V) 与 dotO(2max)）存在差异，但尚不清楚这些差异在多大程度上可以通过 PA 来解释。因此，我们试图研究不同种族群体中 PA 和 CRF 之间的关联。方法：作为国家健康和营养检查调查（1999-2004）的一部分，3115 名成年人（18-49 岁）完成了次最大分级跑步机运动测试，以估计 (V) 超过 dotO(2max)。自变量是人口统计数据（种族、教育程度、性别、伴侣状况和腰围）、行为测量（吸烟和饮酒）、来自三个领域（休闲时间、家庭和交通 PA (MET.min.wk(-1))）的自我报告 PA 以及高强度 PA 比例 (VMET)。 CRF 是因变量。使用SUDAAN统计软件进行多元线性回归。结果：结果表明，与非西班牙裔黑人 (37.9 +/- 0.6 mL.kg(-1).min(-1)) 相比，墨西哥裔美国人 (40.9 +/- 0.5 mL.kg(-1).min(-1)) 和非西班牙裔白人 (40.2 +/- 0.3 mL.kg(-1).min(-1)) 的 (V) 显着高于 dotO(2max)。 （P = 0.01）。包括种族在内的人口统计解释了 (V) 相对于 dotO(2max) 的 18.5% 方差，其中种族在模型中具有显着性 (P G 0.01)。当 PA 添加到模型中时，(V) 相对于 dotO(2max) 的解释方差增加到 19.3% (P = 0.001)。 VMET 比 dotO(2max) 比总 PA 更能预测 (V)，并且包含 VMET 的模型解释了 (V) 相对 dotO(2max) 的 20.4% 的方差。将 VMET 和总体 PA 添加到模型后，种族仍然是 (V) 相对于 dotO(2max) 的重要独立预测因子。结论：种族、PA 和运动强度是解释 CRF 差异的重要因素。在考虑了人口统计、PA 和 VMET 后，CRF 的很大一部分方差仍然无法解释。因此，在检查 CRF 的种族/民族差异时还应考虑其他因素。
CEASER, T. G., E. C. FITZHUGH, D. L. THOMPSON, and D. R. BASSETT JR. Association of Physical Activity, Fitness, and Race: NHANES 1999-2004. Med. Sci. Sports Exerc., Vol. 45, No. 2, pp. 286-293, 2013. Purpose: Regular physical activity (PA) can be used to improve cardiorespiratory fitness (CRF). Previous research has shown differences in CRF ((V) over dotO(2max)) among racial groups, but it is unclear how much of these differences can be explained by PA. Thus, we sought to examine the association between PA and CRF in different racial groups. Methods: As a part of the National Health and Nutrition Examination Survey (1999-2004), 3115 adults (18-49 yr) completed a submaximal graded treadmill exercise test to estimate (V) over dotO(2max). Independent variables were demographics (race, education, sex, partner status, and waist circumference), behavioral measures (smoking and alcohol consumption), self-reported PA from three domains (leisure-time, domestic, and transportational PA (MET.min.wk(-1))), and the proportion of PA at a vigorous intensity (VMET). CRF was the dependent variable. Multiple linear regression was performed using SUDAAN statistical software. Results: Results indicated that (V) over dotO(2max) was significantly higher for Mexican Americans (40.9 +/- 0.5 mL.kg(-1).min(-1)) and non-Hispanic Whites (40.2 +/- 0.3 mL.kg(-1).min(-1)) compared with non-Hispanic Blacks (37.9 +/- 0.6 mL.kg(-1).min(-1)) (P = 0.01). Demographics including race explained 18.5% of the variance in (V) over dotO(2max), with race being significant (P G 0.01) in the model. When PA was added to the model, the explained variance in (V) over dotO(2max) increased to 19.3% (P = 0.001). VMET was more predictive of (V) over dotO(2max) than total PA, and the model including VMET explained 20.4% of the variance in (V) over dotO(2max). Race remained a significant, independent predictor of (V) over dotO(2max) after VMET and overall PA were added to the model. Conclusion: Race, PA, and exercise intensity are important factors in explaining differences in CRF. After accounting for demographics, PA, and VMET, a large proportion of the variance in CRF remains unexplained. Thus, other factors should also be considered when examining racial/ethnic differences in CRF.