Cargando…
A technique to determine the fastest age-adjusted masters marathon world records
INTRODUCTION/PURPOSE: This study’s purpose was to develop and employ a technique to determine the fastest masters marathon world records (WR), ages 35–79 years, adjusted for age (WRadj). METHODS: From single-age WR data, a best-fit polynomial curve (WRpred1) was developed for the larger age range of...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016493/ https://www.ncbi.nlm.nih.gov/pubmed/27652089 http://dx.doi.org/10.1186/s40064-016-3190-5 |
_version_ | 1782452566798368768 |
---|---|
author | Vanderburgh, Paul M. |
author_facet | Vanderburgh, Paul M. |
author_sort | Vanderburgh, Paul M. |
collection | PubMed |
description | INTRODUCTION/PURPOSE: This study’s purpose was to develop and employ a technique to determine the fastest masters marathon world records (WR), ages 35–79 years, adjusted for age (WRadj). METHODS: From single-age WR data, a best-fit polynomial curve (WRpred1) was developed for the larger age range of 29–80 years for women and 30–80 years for men to improve curve stability in the 35–79 years range. Due to the relatively large degree of data scatter about the curve and the resultant age bias in favor of older runners, a subsample was constituted consisting of those with the lowest WR/WRpred1 ratio within each five-year age group (N = 11). A new polynomial best-fit curve (WRpred2) was developed from this subsample to become the standard against which WR would be compared across age. WRadj was computed from WR/WRpred2 for all runners, 35–79 years, from which the top ten fastest were then determined. RESULTS: The WRpred2 model reduced data scatter and eliminated the age bias. Tatyana Pozdniakova, 50 years, WR = 2:31:05, WRadj = 2:12:40; and Ed Whitlock, 73 years, WR = 2:54:48, WRadj = 1:59:57, had the fastest WRadj for women and men, respectively. CONCLUSIONS: This technique of iterative curve-fitting may be an optimal way of determining the fastest masters WRadj and may also be useful in better understanding the upper limits of human performance by age. |
format | Online Article Text |
id | pubmed-5016493 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-50164932016-09-20 A technique to determine the fastest age-adjusted masters marathon world records Vanderburgh, Paul M. Springerplus Methodology INTRODUCTION/PURPOSE: This study’s purpose was to develop and employ a technique to determine the fastest masters marathon world records (WR), ages 35–79 years, adjusted for age (WRadj). METHODS: From single-age WR data, a best-fit polynomial curve (WRpred1) was developed for the larger age range of 29–80 years for women and 30–80 years for men to improve curve stability in the 35–79 years range. Due to the relatively large degree of data scatter about the curve and the resultant age bias in favor of older runners, a subsample was constituted consisting of those with the lowest WR/WRpred1 ratio within each five-year age group (N = 11). A new polynomial best-fit curve (WRpred2) was developed from this subsample to become the standard against which WR would be compared across age. WRadj was computed from WR/WRpred2 for all runners, 35–79 years, from which the top ten fastest were then determined. RESULTS: The WRpred2 model reduced data scatter and eliminated the age bias. Tatyana Pozdniakova, 50 years, WR = 2:31:05, WRadj = 2:12:40; and Ed Whitlock, 73 years, WR = 2:54:48, WRadj = 1:59:57, had the fastest WRadj for women and men, respectively. CONCLUSIONS: This technique of iterative curve-fitting may be an optimal way of determining the fastest masters WRadj and may also be useful in better understanding the upper limits of human performance by age. Springer International Publishing 2016-09-08 /pmc/articles/PMC5016493/ /pubmed/27652089 http://dx.doi.org/10.1186/s40064-016-3190-5 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Methodology Vanderburgh, Paul M. A technique to determine the fastest age-adjusted masters marathon world records |
title | A technique to determine the fastest age-adjusted masters marathon world records |
title_full | A technique to determine the fastest age-adjusted masters marathon world records |
title_fullStr | A technique to determine the fastest age-adjusted masters marathon world records |
title_full_unstemmed | A technique to determine the fastest age-adjusted masters marathon world records |
title_short | A technique to determine the fastest age-adjusted masters marathon world records |
title_sort | technique to determine the fastest age-adjusted masters marathon world records |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016493/ https://www.ncbi.nlm.nih.gov/pubmed/27652089 http://dx.doi.org/10.1186/s40064-016-3190-5 |
work_keys_str_mv | AT vanderburghpaulm atechniquetodeterminethefastestageadjustedmastersmarathonworldrecords AT vanderburghpaulm techniquetodeterminethefastestageadjustedmastersmarathonworldrecords |