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Vigorously Cited: A Bibliometric Analysis of the 500 Most Cited Physical Activity Articles

Aamir R. Memon, Quyen G. To, and Corneel Vandelanotte

Background: To date, no citation analysis has been conducted in the physical activity field, which can contribute to assess the impact of this research field and identify knowledge gaps. Therefore, this study aimed to identify the 500 most cited physical activity publications and report their bibliometric characteristics. Methods: The Web of Science database (all database indexes) was searched, and bibliometric characteristics were imported and calculated. Results: A total of 520 publications were ranked as the top 500. The sum of the citations was 326,258, and the average citation density was 41.0 (45.1) citations per year. Original research articles constituted the major portion of included publications (53.7%; 170,774 citations). Papers reporting relationship of physical activity with health were the most prevalent type of publication included (43.7%; 141,027 citations). Journal impact factor had a weak but significant positive correlation with citation density (r = .12; P = .006). The United States was ranked first in terms of the contributions from institutions and authors contributing to the most cited physical activity papers. Conclusions: Top physical activity publications are well cited compared with other health behavior fields. Original research reporting on the associations between physical activity and health has a higher citation impact compared with other types of original research within the physical activity field. The physical activity research field continues to expand rapidly as newer publications attract more citations in a shorter time span compared with older publications.

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Reliability and Validity of a Computerized and Dutch Version of the International Physical Activity Questionnaire (IPAQ)

Corneel Vandelanotte, Ilse De Bourdeaudhuij, Renaat Philippaerts, Michael Sjöström, and James Sallis


The purpose of this study was to examine the reliability and validity of a newly developed computerized Dutch version of the International Physical Activity Questionnaire (IPAQ).


Subjects (N = 53) completed the computerized IPAQ at three specified times. Subjects wore a CSA activity monitor during seven full days and simultaneously completed a 7-d physical activity diary. Finally, respondents filled out a paper and pencil IPAQ.


Intraclass correlation coefficient ranged from 0.60 to 0.83. Correlations for “total physical activity” between the computerized IPAQ and the CSA activity counts were moderate (min: r = 0.38; kcal: r = 0.43). Correlations with the physical activity diary were also moderate (min: r = 0.39; kcal: r = 0.46). Correlations between the computerized and the paper and pencil IPAQ were high (min: r = 0.80; kcal: r = 0.84).


The computerized Dutch IPAQ is a reliable and reasonably valid physical activity measurement tool for the general adult population.

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Do Birds of a Feather Flock Together Within a Team-Based Physical Activity Intervention? A Social Network Analysis

Sarah Edney, Tim Olds, Jillian Ryan, Ronald Plotnikoff, Corneel Vandelanotte, Rachel Curtis, and Carol Maher

Background: Homophily is the tendency to associate with friends similar to ourselves. This study explored the effects of homophily on team formation in a physical activity challenge in which “captains” signed up their Facebook friends to form teams. Methods: This study assessed whether participants (n = 430) were more similar to their teammates than to nonteammates with regard to age, sex, education level, body mass index, self-reported and objectively measured physical activity, and negative emotional states; and whether captains were more similar to their own teammates than to nonteammates. Variability indices were calculated for each team, and a hypothetical variability index, representing that which would result from randomly assembled teams, was also calculated. Results: Within-team variability was less than that for random teams for all outcomes except education level and depression, with differences (SDs) ranging from +0.15 (self-reported physical activity) to +0.47 (age) (P < .001 to P = .001). Captains were similar to their teammates except in regard to age, with captains being 2.6 years younger (P = .003). Conclusions: Results support hypotheses that self-selected teams are likely to contain individuals with similar characteristics, highlighting potential to leverage team-based health interventions to target specific populations by instructing individuals with risk characteristics to form teams to help change behavior.

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The Association Between Time-Use Behaviors and Physical and Mental Well-Being in Adults: A Compositional Isotemporal Substitution Analysis

Rachel G. Curtis, Dorothea Dumuid, Timothy Olds, Ronald Plotnikoff, Corneel Vandelanotte, Jillian Ryan, Sarah Edney, and Carol Maher

Background: Substantial evidence links activity domains with health and well-being; however, research has typically examined time-use behaviors independently, rather than considering daily activity as a 24-hour time-use composition. This study used compositional data analysis to estimate the difference in physical and mental well-being associated with reallocating time between behaviors. Methods: Participants (n = 430; 74% female; 41 [12] y) wore an accelerometer for 7 days and reported their body mass index; health-related quality of life (QoL); and symptoms of depression, anxiety, and stress. Regression models determined whether time-use composition, comprising sleep, sedentary behavior, light physical activity (LPA), and moderate to vigorous physical activity (MVPA), was associated with well-being. Compositional isotemporal substitution models estimated the difference in well-being associated with reallocating time between behaviors. Results: Time-use composition was associated with body mass index and physical health-related QoL. Reallocating time to MVPA from sleep, sedentary behavior, and LPA showed favorable associations with body mass index and physical health-related QoL, whereas reallocations from MVPA to other behaviors showed unfavorable associations. Reallocations from LPA to sedentary behavior were associated with better physical health–related QoL and vice versa. Conclusion: Results reinforce the importance of MVPA for physical health but do not suggest that replacing sedentary behavior with LPA is beneficial for health and well-being.

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Physical Activity Attitudes, Preferences, and Experiences of Regionally-Based Australia Adults Aged 65 Years and Older

Pamela K. Samra, Amanda L. Rebar, Lynne Parkinson, Jannique G.Z. van Uffelen, Stephanie Schoeppe, Deborah Power, Anthony Schneiders, Corneel Vandelanotte, and Stephanie Alley

An understanding of physical activity attitudes, preferences, and experiences in older adults is important for informing interventions. Focus groups were conducted with 46 regionally-based Australian adults aged 65 years and older, who were not currently meeting activity recommendations. Content analysis revealed that participants mainly engaged in incidental activities such as gardening and household chores rather than planned exercise; however, leisure-time walking was also mentioned frequently. Although participants valued the physical and mental health benefits of physical activity, they reported being restricted by poor physical health, extreme weather, and fear of injury. Participants were interested in exercise groups and physical activity programs tailored to their existing physical health. The majority of participants reported preferring to be active with others. The findings from this study are useful in for informing future interventions specifically tailored to the needs of older adults in Australia.

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Sitting Time in Adults 65 Years and Over: Behavior, Knowledge, and Intentions to Change

Stephanie Alley, Jannique G.Z. van Uffelen, Mitch J. Duncan, Katrien De Cocker, Stephanie Schoeppe, Amanda L. Rebar, and Corneel Vandelanotte

This study examined sitting time, knowledge, and intentions to change sitting time in older adults. An online survey was completed by 494 Australians aged 65+. Average daily sitting was high (9.0 hr). Daily sitting time was the highest during TV (3.3 hr), computer (2.1 hr), and leisure (1.7 hr). A regression analysis demonstrated that women were more knowledgeable about the health risks of sitting compared to men. The percentage of older adults intending to sit less were the highest for TV (24%), leisure (24%), and computer (19%) sitting time. Regression analyses demonstrated that intentions varied by gender (for TV sitting), education (leisure and work sitting), body mass index (computer, leisure, and transport sitting), and physical activity (TV, computer, and leisure sitting). Interventions should target older adults’ TV, computer, and leisure time sitting, with a focus on intentions in older males and older adults with low education, those who are active, and those with a normal weight.

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How Do Different Occupational Factors Influence Total, Occupational, and Leisure-Time Physical Activity?

Corneel Vandelanotte, Camille Short, Matthew Rockloff, Lee Di Millia, Kevin Ronan, Brenda Happell, and Mitch J. Duncan


A better understanding of how occupational indicators influence physical activity levels will aid the design of workplace interventions.


Cross-sectional data were collected from 1194 participants through a telephone interview in Queensland, Australia. The IPAQ-long was used to measure physical activity. Multiple logistic regression was applied to examine associations.


Of participants, 77.9% were employed full-time, 32.3% had professional jobs, 35.7% were engaged in shift work, 39.5% had physically-demanding jobs, and 66.1% had high physical activity levels. Participants with a physicallydemanding job were less likely to have low total (OR = 0.25, 95% CI = 0.17 to 0.38) and occupational (OR = 0.17, 95% CI = 0.12 to 0.25) physical activity. Technical and trade workers were less likely to report low total physical activity (OR = 0.44, 95% CI = 0.20 to 0.97) compared with white-collar workers. Part-time (OR = 1.74, 95% CI = 1.15 to 2.64) and shift workers (OR = 1.86, 95% CI = 1.21 to 2.88) were more likely to report low leisure-time activity.


Overall, the impact of different occupational indicators on physical activity was not strong. As expected, the greatest proportion of total physical activity was derived from occupational physical activity. No evidence was found for compensation effects whereby physically-demanding occupations lead to less leisure-time physical activity or vice versa. This study demonstrates that workplaces are important settings to intervene, and that there is scope to increase leisure-time physical activity irrespective of occupational background.