The Metabolic Cost of Walking in healthy young and older adults – A Systematic Review and Meta Analysis

The Metabolic Cost of Walking (MCoW) is an important variable of daily life that has been studied extensively. Several studies suggest that MCoW is higher in Older Adults (OA) than in Young Adults (YA). However, it is difficult to compare values across studies due to differences in the way MCoW was expressed, the units in which it was reported and the walking speed at which it was measured. To provide an overview of MCoW in OA and YA and to investigate the quantitative effect of age on MCoW, we have conducted a literature review and performed two meta-analyses. We extracted data on MCoW in healthy YA (18–41 years old) and healthy OA (≥59 years old) and calculated, if not already reported, the Gross (GCoW) and Net MCoW (NCoW) in J/kg/m. If studies reported MCoW measured at multiple speeds, we selected those values for YA and OA at which MCoW was minimal. All studies directly comparing YA and OA were selected for meta-analyses. From all studies reviewed, the average GCoW in YA was 3.4 ± 0.4 J/kg/m and 3.8 ± 0.4 J/kg/m in OA (~12% more in OA), and the average NCoW in YA was 2.4 ± 0.4 J/kg/m and 2.8 ± 0.5 J/kg/m in OA (~17% more in OA). Our meta-analyses indicated a statistically significant elevation of both GCoW and NCoW (p < 0.001) for OA. In terms of GCoW, OA expended about 0.3 J/kg/m more metabolic energy than YA and about 0.4 J/kg/m more metabolic energy than YA in terms of NCoW. Our study showed a statistically significant elevation in MCoW of OA over YA. However, from the literature it is unclear if this elevation is directly caused by age or due to an interaction between age and methodology. We recommend further research comparing MCoW in healthy OA and YA during “natural” over-ground walking and treadmill walking, after sufficient familiarization time.


Calculation of MCoW from oxygen consumption
For those studies that did not report MCoW, but did report the oxygen consumption rate and RER, we used the Lusk Equation (Lusk, J. Biol. Chem. 1924) For the studies that reported the oxygen consumption rate but not RER, we estimated the mean RER to be equal to the average of the mean RERs from all the other studies that did report it. In that case we estimated the standard deviation of RER ( RER   ) using: for all n studies that reported RER. Then, we calculated GCoW in units of J/kg/m using: and, similarly NCoW using : The estimated standard deviation of GCoW was calculated by: The estimated standard deviation of NCoW was then calculated by:

Calculation of GCoW/NCoW
For those studies that did report MCoW, but only reported either GCoW or NCoW (and RMR), NCoW or GCoW was calculated. GCoW was calculated using: NCoW was calculated using: In case RMR was not reported, only the reported values of GCoW and NCoW were used, since RMR is needed to calculate one from the other. The standard deviation of either GCoW or NCoW was estimated by:

Appendix B -Risk of Bias Assessment
The risk of bias assessment (table B1) is shown for all the studies included in the two meta-analysis on GCoW and NCoW. Specific comments about all or particular studies are mentioned in the rightmost column of the table.

Appendix C -Funnel Plots
For potential publication bias assessment, funnel plots were plotted for the meta-analyses on GCoW and NCoW ( Figure C1). These plots are simple scatterplots of the mean differences of the included studies in the horizontal axis against the standard errors of the same studies in the vertical axis. A regression test for funnel plot asymmetry was also carried out because the pooled effect sizes for our meta-analyses were computed as mean differences (see: https://handbook-5-1.cochrane.org/chapter_10/10_4_3_1_recommendations_on_testing_for_funnel_plot_asymmetry.htm). In the absence of publication bias and heterogeneity, most of the studies will fall in the region within the "pseudo" 95% CI of the funnel, with an expected symmetric distribution of the studies about the vertical straight black line of MD (see Figure C1). Additionally we also note the results of the regression test for funnel plot asymmetry. For the meta-analysis on GCoW, the p-value of the test was statistically insignificant at an alpha level of 0.05 (p=0.250). However for the meta-analysis on NCoW, the p-value of the test is statistically significant at an alpha level of 0.05 (p=0.006), suggesting an asymmetry in the funnel plot. Funnel plot asymmetry can arise from many potential sources like publication bias, differences in methodologies of studies performed, heterogeneity across and/or within studies. Currently it is not possible to disentangle the reasons for the asymmetry in the plot for NCoW. Figure C1. Funnel plot for all the studies included in the meta-analysis for GCoW (above left) and NCoW (above right). The standard errors of all the individual studies are plotted against their MD. The vertical black line in the center of the funnels represents the overall pooled MD and the two sides of the funnels represent the "pseudo" 95% CI of the overall pooled MD. The outliers are plotted automatically outside the funnels and in absence of any publication bias and/or heterogeneity, the number of studies should look symmetrical on both sides of the vertical black line. The black cross in the above figures denote the study by Gaesser et al., 8 . That study has the lowest standard error and the highest relative weight among all the studies in our meta-analyses and is arguably the most precise on an individual level.

Appendix D -Search Strategy
The full search strategy with the query terms used for each of the four databases are detailed below.