The association of major patterns of physical activity, sedentary behavior and sleep with health-related quality of life: A cohort study☆
Introduction
Health-related quality of life (HRQL) represents the individuals' perception of physical, mental and social health status. There is evidence that HRQL is a stronger predictor of mortality than many objective measures of health. Given that HRQL is a global health indicator, using HRQL as study outcome can provide newer insights into the effect of risk factors as compared to using only disease-specific endpoints. Moreover, because HRQL is a subjective measure, it might be useful as motivational instrument to promote the adoption of health behaviors. Lastly, since HRQL is a broad multidimensional concept, it allows us to define public policy interventions addressing a variety of areas, including the social, mental and medical services. (Centers for Disease Control and Prevention).
There is evidence that physical activity (PA) is directly associated with HRQL (Luncheon and Zack, 2011, Bize et al., 2007, Martin et al., 2009, Sorensen et al., 2011, Eriksson et al., 2010, Balboa-Castillo et al., 2011, Davies et al., 2012, Heesch et al., 2012), while sedentary behavior (SB) is inversely associated (Balboa-Castillo et al., 2011, Davies et al., 2012, Rhodes et al., 2012). SB, in particular, has been associated with poor physical and mental health after adjusting for physical activity (Balboa-Castillo et al., 2011). However, most of the studies on SB were cross-sectional (Davies et al., 2012), primarily focused on watching TV, and were very heterogeneous (Rhodes et al., 2012). Moreover, sleep duration, particularly short and long sleep, has been linked to worse HRQL in some studies (Faubel et al., 2009, Furihata et al., 2012, Lima et al., 2012).
However, since the total number of hours in a day is fixed and finite for an individual, participating in one activity results in not participating in another. For instance, individuals who engage more in SB usually devote less time to PA; or persons who spend more time playing basketball usually spend less time playing tennis. Consequently, the health effects of PA, SB and sleep duration depend not only on the specific activity, but also on the activities it displaces (Mekary et al., 2009). However, most studies on the impact of these three types of activities on HRQL do not directly account for these substitutions.
One method to address this issue is to summarize all activities across the day as activity patterns derived from the data (a posteriori patterns). This method is frequently used in nutritional epidemiology (Hu, 2002) and has served, for instance, to show that certain dietary patterns, such as the Prudent or the Mediterranean pattern, are associated with a lower risk of cardiovascular disease, while a Westernized dietary pattern is associated with a higher cardiovascular risk (Hu et al., 2000, Guallar-Castillon et al., 2012). Instead of looking at individual types of activities, pattern analysis examines the effect of overall physical activity; in fact, this type of analysis can account for substitution and interaction between PA, SB and sleep, as occurs in actual daily living, and goes beyond the somewhat artificial assessment of the independent (adjusted) effect of each of them. Conceptually, pattern analysis represents a broader picture of the time spent in different types of activities, and may thus be more predictive of health risks than each of them separately.
To our knowledge, however, no study has yet reported data on activity patterns based on the amount of time devoted to them. Therefore, this work has estimated these patterns and examined their prospective association with HRQL in the general population of Spain.
Section snippets
Study design and participants
The data were taken from the ENRICA study, whose methods have been reported elsewhere (Rodriguez-Artalejo et al., 2011). In brief, this is a cross-sectional study conducted from June 2008 to October 2010 with 12,948 persons representative of the non-institutionalized Spanish population aged 18 years and older. Data were collected in three stages: first, a phone interview using a structured questionnaire on socio-demographic variables, heath status, lifestyle, morbidity and health services use;
Results
Three main patterns of PA/SB/sleep were identified. The first one was characterized by spending time sitting at the computer, doing vigorous PA and commuting to work; this pattern was also inversely associated with performing household chores and spending time seated watching TV (13% explained variance); this pattern was labeled as “vigorous PA-seated at the computer”. The second pattern was characterized by longer time spent in walking, being seated for reading, and in gardening or
Discussion
In this population-based cohort, we identified three patterns of PA, SB and sleep. Over the 3 year follow-up, greater adherence to the pattern “vigorous PA-seated at the computer” was associated with better physical health, and greater adherence to the pattern “light PA-seated for reading” was associated with better physical function and better mental health. In contrast, the pattern “seated for watching TV-daytime sleeping pattern” was associated with worse physical health.
Various analytic
Contributors
PG-C conceived the study. PG-C, AB-B and FR-A drafted the manuscript and are the guarantors. PG-C, AB-B and LML-M analyzed the data. All authors interpreted the results and contributed to writing the manuscript. PG-C and AB-B take responsibility for the integrity of the data and the accuracy of the data analysis.
Conflict of interest statement
The authors declare that there are no conflicts of interests.
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Funding: The data were taken from the ENRICA study, which was funded by Sanofi-Aventis. Funding specific for this analysis was obtained from FIS grants PI11-01379 and PI12/1166 (Ministry of Health of Spain), and from the “Cátedra UAM de Epidemiología y Control del Riesgo Cardiovascular”. The study funders had no role in study design or in the collection, analysis, and interpretation of data. The authors have sole responsibility for the manuscript content.