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Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis
Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis
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Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis
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Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis
Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis

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Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis
Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis
Journal Article

Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis

2026
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Overview
It is well known that the fastest elite marathon runners come from East African countries such as Ethiopia and Kenya. However, to date, there is no information available on the origin of the fastest age group (master) marathoners. This study aimed to determine the countries of origin of the fastest age group marathoners who have participated in the ‘New York City Marathon’ over the past several decades. Race data from 1,009,839 runners (626,183 male and 383,656 female finishers) who completed the ‘New York City Marathon’ between 1999 and 2024 were analyzed. Participants were categorized into five-year age groups: <20, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49, 50–54, 55–59, 60–64, 65–69, 70–74, and 75 + years. The data were stratified by sex (male and female) and country of origin. The dataset was organized into five performance-based subgroups: (i) the entire dataset, including all finishers by age group and nationality; (ii) the top 100 finishers per age group; (iii) the top 30 finishers per age group; (iv) the top 10 finishers per age group; and (v) the top individual from each country within each age group. Regression analyses were conducted to explore demographic predictors of marathon performance. Participation generally increased over the study period, with temporary declines during the COVID-19 pandemic; male participation consistently outnumbered female participation, the 40–44 years age group was the most represented for both sexes, and participation was lowest in the youngest (< 20 years) and oldest (75 + years) age groups. Crucially, analyses focusing on the fastest age-group marathoners revealed clear nationality-based performance patterns. In younger adult age groups (20–39 years), the fastest average race times were predominantly achieved by female and male runners from Kenya and Ethiopia. The < 20 years age category showed comparatively stronger performances from European runners, including those from Poland, Switzerland and Italy. In the 50 years and older age groups, the best average times were increasingly recorded by runners from the United States of America, Japan, Germany and Switzerland. This shift highlights a regional transition in peak marathon performance with increasing age, from East African to European, North American, and East Asian dominance.