Elsevier

Preventive Medicine

Volume 67, October 2014, Pages 248-254
Preventive Medicine

The association of major patterns of physical activity, sedentary behavior and sleep with health-related quality of life: A cohort study

https://doi.org/10.1016/j.ypmed.2014.08.015Get rights and content

Highlights

  • Three patterns of physical activity, sedentary behavior, and sleep were derived.

  • A “vigorous activity-seated at the computer” pattern led to good physical health.

  • A “light activity-seated for reading” pattern was linked to good mental health.

  • A “seated watching TV-daytime sleep” pattern was linked to poor physical health.

  • The third pattern should be a priority target of preventive interventions.

Abstract

Objective

To examine the prospective association of patterns of physical activity, sedentary behavior and sleep with health-related quality of life (HRQL) in the general population of Spain.

Methods

A cohort study with 4271 individuals aged ≥ 18 years was recruited in 2008–2010 and followed-up prospectively through 2012. Activity patterns were derived from factor analysis. HRQL was assessed with the SF-12 questionnaire, and suboptimal HRQL was defined as a score below the sex-specific sample median.

Results

Three main activity patterns were identified. A higher adherence to the pattern named “vigorous activity-seated at the computer” was inversely associated with a suboptimal score in the physical-composite summary (PCS) of the SF-12 (multivariate adjusted odds ratio [aOR] for the highest vs. the lowest quartile 0.71; 95% confidence interval [IC] 0.55–0.90; p-trend = 0.003). The “light activity-seated for reading” pattern was inversely associated with a suboptimal score in the mental-composite summary (aOR = 0.73; 95% CI = 0.61–0.89; p-trend = 0.002). However, a higher adherence to the “seated for watching TV-daytime sleeping” pattern was directly associated with suboptimal PCS (aOR = 1.35; 95% CI = 1.10–1.66; p-trend = 0.008).

Conclusion

Patterns including any physical activity were associated with better physical or mental HRQL. However, a pattern defined by sedentary behavior with diurnal sleep showed worse HRQL and should be a priority target of preventive interventions.

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.

References (56)

  • S. Schmidt et al.

    Reference guidelines for the 12-Item Short-Form Health Survey version 2 based on the Catalan general population

    Med. Clin. (Barc.)

    (2012)
  • S. Sidney et al.

    Television viewing and cardiovascular risk factors in young adults: the CARDIA study

    Ann. Epidemiol.

    (1996)
  • A.A. Thorp et al.

    Sedentary behaviors and subsequent health outcomes in adults a systematic review of longitudinal studies, 1996–2011

    Am. J. Prev. Med.

    (2011)
  • P.Y. Yang et al.

    Exercise training improves sleep quality in middle-aged and older adults with sleep problems: a systematic review

    J. Physiother.

    (2012)
  • G.G. Alvarez et al.

    The impact of daily sleep duration on health: a review of the literature

    Prog. Cardiovasc. Nurs.

    (2004)
  • T. Balboa-Castillo et al.

    Longitudinal association of physical activity and sedentary behavior during leisure time with health-related quality of life in community-dwelling older adults

    Health Qual. Life Outcomes

    (2011)
  • M.P. Buman et al.

    Objective light-intensity physical activity associations with rated health in older adults

    Am. J. Epidemiol.

    (2010)
  • M.R. Carnethon et al.

    Cardiorespiratory fitness in young adulthood and the development of cardiovascular disease risk factors

    JAMA

    (2003)
  • C.A. Celis-Morales et al.

    Objective vs. self-reported physical activity and sedentary time: effects of measurement method on relationships with risk biomarkers

    PLoS One

    (2012)
  • Centers for Disease Control and Prevention

    Health-related quality of life

  • W.J. Chodzko-Zajko et al.

    American College of Sports Medicine position stand. Exercise and physical activity for older adults

    Med. Sci. Sports Exerc.

    (2009)
  • C. Dowrick et al.

    Get into reading as an intervention for common mental health problems: exploring catalysts for change

    Med. Humanit.

    (2012)
  • M.K. Eriksson et al.

    Quality of life and cost-effectiveness of a 3-year trial of lifestyle intervention in primary health care

    Arch. Intern. Med.

    (2010)
  • R. Faubel et al.

    Sleep duration and health-related quality of life among older adults: a population-based cohort in Spain

    Sleep

    (2009)
  • L. Gallicchio et al.

    Sleep duration and mortality: a systematic review and meta-analysis

    J. Sleep Res.

    (2009)
  • L.D. Gillespie et al.

    Interventions for preventing falls in older people living in the community

    Cochrane Database Syst. Rev.

    (2009)
  • J.L. Gutierrez-Fisac et al.

    Prevalence of general and abdominal obesity in the adult population of Spain, 2008–2010: the ENRICA study

    Obes. Rev.

    (2012)
  • G.N. Healy et al.

    Television time and continuous metabolic risk in physically active adults

    Med. Sci. Sports Exerc.

    (2008)
  • Cited by (46)

    • Components of Pittsburgh Sleep Quality Index in Iranian adult population: an item response theory model

      2021, Sleep Medicine: X
      Citation Excerpt :

      Sleep is the best form of rest and revitalization, and the quality of sleep and its related problems are among the factors which can impact health [1]. Extensive research has shown that sleep disorders are associated with various illnesses including depression and anxiety [1,2], physical problems [3], congestive heart failure [4,5], unwanted injuries [6], and decreased quality of life [7]. Since sleep quality is a multidimensional concept that includes satisfaction with sleep, sleep adequacy and sleep effect on daily functioning, self-administered questionnaires are useful for assessing sleep quality in the population of patients and the general population [8].

    • Associations of health-behavior patterns, mental health and self-rated health

      2019, Preventive Medicine
      Citation Excerpt :

      Poor diet quality, excess alcohol consumption, smoking, low physical activity, prolonged sitting, short or long sleep duration and poor sleep quality are all individually associated with increased risks of morbidity and mortality (Biddle et al., 2016; Wilmot et al., 2012; Khaw et al., 2008; Knutson, 2010; Cappuccio et al., 2010). Mortality risk and risk of poor health-related quality of life also increase in a dose-response manner as the number of poor behaviors increases (Loef and Walach, 2012; Ford et al., 2011; Kvaavik et al., 2010; Ding et al., 2015; Martinez-Gomez et al., 2013; Krokstad et al., 2017; Duncan et al., 2014; Guallar-Castillón et al., 2014; Ding et al., 2014; Bayan-Bravo et al., 2017). Combinations of poor lifestyle behaviors have been shown to pose greater morbidity risk than the sum of their individual effects, suggesting a synergistic relationship between risk factors (Ding et al., 2015; Krokstad et al., 2017).

    View all citing articles on Scopus

    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.

    View full text