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最大摄氧量的规模指数在超过 6500 名人类中的应用:系统回顾和荟萃分析。

Size Exponents for Scaling Maximal Oxygen Uptake in Over 6500 Humans: A Systematic Review and Meta-Analysis.

机构信息

Health and Social Care Institute, School of Health and Social Care, Teesside University, Constantine Building, Middlesbrough, TS1 3BA, UK.

出版信息

Sports Med. 2017 Jul;47(7):1405-1419. doi: 10.1007/s40279-016-0655-1.

DOI:10.1007/s40279-016-0655-1
PMID:28058696
Abstract

BACKGROUND

Maximal oxygen uptake ([Formula: see text] ) is conventionally normalized to body size as a simple ratio or using an allometric exponent < 1. Nevertheless, the most appropriate body size variable to use for scaling and the value of the exponent are still enigmatic. Studies tend to be based on small samples and can, therefore, lack precision.

OBJECTIVE

The objective of this systematic review was to provide a quantitative synthesis of reported static allometric exponents used for scaling [Formula: see text] to whole body mass and fat-free mass.

METHODS

Eight electronic databases (CINAHL, Cochrane Central Register of Controlled Trials, EMBASE, MEDLINE, PubMed, Scopus, SPORTDiscus and Web of Science) were searched for relevant studies published up to January 2016. Search terms included 'oxygen uptake', 'cardiorespiratory fitness', '[Formula: see text] ', '[Formula: see text] ', 'scaling' and all interchangeable terms. Inclusion criteria included human cardiorespiratory fitness data; cross-sectional study designs; an empirical derivation of the exponent; reported precision statistics; and reported information regarding participant sex, age and sports background, [Formula: see text] protocol, whole body composition protocol and line-fitting methods. A random-effects model was used to quantify weighted pooled exponents and 95% confidence limits (Cls). Heterogeneity was quantified with the tau-statistic (τ). Meta-regression was used to quantify the impact of selected moderator variables on the exponent effect size. A 95% prediction interval was calculated to quantify the likely range of true fat-free mass exponents in similar future studies, with this distribution used to estimate the probability that an exponent would be above theorised universal values of [Formula: see text].

RESULTS

Thirty-six studies, involving 6514 participants, met the eligibility criteria. Whole body mass and fat-free mass were used as the scaling denominator in 27 and 15 studies, respectively. The pooled allometric exponent (95% Cls) was found to be 0.70 (0.64 to 0.76) for whole body mass and 0.90 (0.83 to 0.96) for fat-free mass. The between-study heterogeneity was greater for whole body mass (τ = ±0.15) than for fat-free mass (τ = ±0.11). Participant sex explained 30% of the between-study variability in the whole body mass exponent, but the influence on the fat-free mass exponent was trivial. The whole body mass exponent of 0.52 (0.40 to 0.64) for females was substantially lower than the 0.76 (0.70 to 0.83) for males, whereas the fat-free mass exponent was similar for both sexes. The effects of all other moderators were trivial. The 95% PI for fat-free mass ranged from 0.68 to 1.12. The estimated probability of a true fat-free mass exponent in a future study being greater than [Formula: see text] power scaling is 0.98 (very likely) and 0.92 (likely), respectively.

CONCLUSIONS

In this quantitative synthesis of published studies involving over 6500 humans, the whole body mass exponent was found to be spuriously low and prone to substantial heterogeneity. We conclude that the scaling of [Formula: see text] in humans is consistent with the allometric cascade model with an estimated prediction interval for the fat-free mass exponent not likely to be consistent with the [Formula: see text] power laws.

摘要

背景

最大摄氧量([Formula: see text])通常通过将其与身体大小进行归一化来表示为简单的比值或使用小于 1 的幂指数。然而,用于缩放的最合适的身体大小变量以及指数的值仍然是神秘的。研究往往基于小样本,因此可能缺乏准确性。

目的

本系统评价的目的是提供对用于将[Formula: see text] 与总体质量和去脂体重进行缩放的报告静态幂指数的定量综合。

方法

检索了截至 2016 年 1 月的 8 个电子数据库(CINAHL、Cochrane 对照试验中心注册、EMBASE、MEDLINE、PubMed、Scopus、SPORTDiscus 和 Web of Science),以查找相关研究。搜索词包括“氧气摄取”、“心肺适应能力”、“[Formula: see text]”、“[Formula: see text]”、“缩放”和所有可互换的术语。纳入标准包括人类心肺适应能力数据;横断面研究设计;经验推导的指数;报告的精度统计数据;以及有关参与者性别、年龄和运动背景、[Formula: see text] 方案、全身成分方案和线拟合方法的报告信息。使用随机效应模型量化加权汇总指数和 95%置信区间(Cls)。使用τ-统计量(τ)量化异质性。Meta 回归用于量化选定的调节变量对指数效应大小的影响。计算了 95%预测区间,以量化类似未来研究中真实去脂体重指数的可能范围,使用该分布估计指数大于理论通用值[Formula: see text]的概率。

结果

36 项研究,涉及 6514 名参与者,符合入选标准。27 项研究和 15 项研究分别将总体质量和去脂体重用作缩放分母。发现整体幂指数(95%Cls)为 0.70(0.64 至 0.76),用于总体质量,0.90(0.83 至 0.96)用于去脂体重。整体身体质量的异质性(τ=±0.15)大于去脂体重(τ=±0.11)。参与者的性别解释了整体身体质量指数变异性的 30%,但对去脂体重指数的影响微不足道。女性的整体身体质量指数为 0.52(0.40 至 0.64),明显低于男性的 0.76(0.70 至 0.83),而男女的去脂体重指数相似。所有其他调节因素的影响都微不足道。去脂体重的 95%PI 范围为 0.68 至 1.12。估计未来研究中去脂体重指数大于[Formula: see text]幂律缩放的真实可能性分别为 0.98(极有可能)和 0.92(很有可能)。

结论

在这项涉及超过 6500 名人类的已发表研究的定量综合研究中,我们发现整体身体质量指数被人为地低估,且容易产生很大的异质性。我们得出结论,人类[Formula: see text]的缩放符合幂次级联模型,其去脂体重指数的估计预测区间不太可能与[Formula: see text]幂律一致。

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