Elsevier

Preventive Medicine

Volume 47, Issue 3, September 2008, Pages 319-323
Preventive Medicine

Relation of leisure time, occupational, domestic, and commuting physical activity to health indicators in Europe

https://doi.org/10.1016/j.ypmed.2008.03.012Get rights and content

Abstract

Objectives

To investigate relationships between physical activities in different domains (leisure time, occupational, domestic, commuting) and health indicators (self-rated health, body mass index).

Methods

The short version of the International Physical Activity Questionnaire (IPAQ) and additional questions on domain specific physical activity were submitted face-to-face to 29,193 individual's age 15 years and older in the 27 member states of the Europe Union, 2 affiliated nations (Croatia, Turkey), and Cyprus North in 2005 as part of Eurobarometer 64.3.

Results

Leisure time physical activity (compared to no leisure time physical activity) was positively associated with self-rated health (males: Odds Ratio (OR) = 2.85, 95% Confidence Interval (CI): 2.27, 3.58; females: OR = 2.77, 95% C.I. 2.16, 3.56) and inversely with obesity (males: OR = 0.65, 95% C.I. 0.50, 0.83; females: OR = 0.46, 95% C.I. 0.34, 0.63). Being in the highest quartile of the total volume of physical activity expressed using metabolic equivalents (in MET-min/week) (compared to being in the lowest quartile) was not related to self-rated health (males: OR = 0.99, 95% C.I. 0.81, 1.21; females: OR = 1.19, 95% C.I 0.98, 1.43) or obesity (males: OR = 1.25, 95% C.I., 0.99, 1.59; females: OR = 1.26, 95% C.I. 1.02, 1.57). Gender-specific effects were observed for other domains of physical activity. Analysis on national levels showed pronounced relationships of leisure time physical activity to health indicators.

Conclusions

Domains of physical activity being related to health indicators, they may pertain to surveillance.

Introduction

The surveillance of physical activity levels has received increased attention in recent years. As of today, a number of cross-national data sets are available that allow (for the first time) a comparison of population physical activity levels worldwide (e.g. STEPwise programme of the World Health Organisation, Eurobarometer of the European Union, International Prevalence Study of the IPAQ Group). International surveillance systems for monitoring trends in physical activity are being developed. Currently, two physical activity questionnaires are used for the purpose of physical activity surveillance. These instruments are the “International Physical Activity Questionnaire (IPAQ)” (Craig et al., 2003) and the “Global Physical Activity Questionnaire (GPAQ)” (Armstrong and Bull, 2006).

The IPAQ is available in a long and short form. The long form assesses domain specific physical activity (leisure time, commuting, domestic, occupation) of vigorous, moderate intensities and walking in the last 7 days. The short form assesses moderate, vigorous physical activities and walking across domains in the last 7 days. The IPAQ short form does not allow distinguishing physical activities by the domain they take place in. From both IPAQ forms, information on metabolic equivalents (METs) as an estimate for physical activity related energy expenditure can be drawn (Ainsworth et al., 2000). The GPAQ assesses occupational, commuting, and leisure time physical activities of vigorous and moderate intensity and walking in a typical week. With the GPAQ, domain specific METs can be calculated.

From a perspective of public health, it is important to consider if the assessment of different domains of physical activity within surveillance systems is necessary. Usually, surveillance systems require assessment instruments to be as short and concise as possible, providing little room for additional items needed to assess domain specific physical activity. Also, based on actual physical activity recommendations (Haskell et al., 2007) moderate or vigorous-intensity aerobic physical activities are important to promote and maintain health, independent of the domain they take place in (Blair and Connelly, 1996). Within this view, surveillance systems would not need to address domain specific physical activities.

In contrast, study results suggest that differences in the health effects of physical activity in different domains might exist. For example, cohort studies identified domain specific effects of physical activity on mortality (Andersen et al., 2000, Kristel-Boneh et al., 2000), and total stroke incidence (Hu et al., 2005). Also cross-sectional studies identified domain specific effects of physical activity on health outcomes such as HDL cholesterol levels (Greendale et al., 1996), total cholesterol levels (Hu et al., 2001), hypertension (Fransson et al., 2003), body mass index (Barengo et al., 2006, Oppert et al., 2006), and self-rated health (Kaleta et al., 2006). Considering these results, receiving information on the domain of physical activity within surveillance systems might be important to identify domains of physical activity that might yield greater health benefits.

The article investigates potential relationships between domains of physical activity and two common and relevant health indicators of surveillance systems (self-rated health, body mass index) in a large cross-sectional dataset of the European Union.

Section snippets

Methods

Data were collected by face-to-face interviews between October and December 2005 as part of the Eurobarometer 64.3. The Eurobarometer contained questions on health status, food habits, and physical activity. Fieldwork was carried out in the 27 Member States of the European Union, 2 affiliated nations (Croatia, Turkey), and Cyprus North by a consortium of market and public opinion research agencies. Sample sizes were about 1000 respondents per nation (Luxembourg, Malta 500 respondents each), the

Results

Table 1 presents an overview of the total sample. By nation, lowest median MET-minutes/week are reported in Malta (480 MET-minutes/week), highest are reported in Slovakia (5.901 MET-minutes/week). For domain specific physical activity, e.g. the proportion of those reporting a lot of physical activity at work ranged from 8% in Malta to 27% in Cyprus (North). The percentage of those reporting good or very good self-rated health ranged from 45% in Lithuania to 87% in Ireland. The rate of those

Discussion

The study investigated differences in the effects of MET-minutes/week and domain specific physical activity on self-rated health and the risk of being obese in adults in the European Union. Results indicated domain specific effects of physical activity on self-rated health, and BMI. Surprisingly, MET-minutes/week (as generated by the IPAQ short form) and physical activity in the domain of transport could only marginally be associated to health indicators applied in this study. Also, domestic

Conclusion

Using data from a large European health survey, our analysis suggests that domain specific relationships between physical activity levels and health indicators might exist. Such effects might support assessing domain specific physical activity levels in surveillance systems.

Acknowledgment

Data collection was funded by DG Sanco of the European Commission.

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