Activity and Health:
Epidemiological studies in older adults
Acknowledgments
The work conducted in this thesis was conducted within ErasmusAGE at the department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. All studies described in this manuscript were performed within the Rotterdam Study, which is supported by the Erasmus Medical Center, Rotterdam; Erasmus University, Rotterdam; the Netherlands Organisation for Scientific Research (NOW); and the Netherlands Organisation for Health Research and Development (ZonMw). ErasmusAGE is a research center investigating the role of lifestyle and nutrition on health across the life-course, funded by Nestlé Nutrition (Nested Ltd.) and Metagenics Inc. The funders were not involved in design or conduct of the studies; collection, management, analysis or interpretation of the data; or preparation, review or approval of the manuscripts described in this thesis.
Publication of this thesis was kindly supported by the Department of Epidemiology of the Erasmus Medical Center. Additional financial support by the Dutch Heart Foundation for the publication of this thesis is gratefully acknowledged. Further financial support was kindly provided by ChipSoft.
Cover design and printing: Optima Grafische Communicatie BV ISBN: 978-94-6361-064-3
© 2018 Chantal Koolhaas, Rotterdam, the Netherlands
The copyright is transferred to the respective publisher upon publication of the manuscript. No part of this thesis may be reproduced, stored in a retrieval system, or transmitted in any form or by any means without prior permission of the author or the publisher of the manuscript.
Activity and Health:
Epidemiological studies in older adults
Activiteit en gezondheid:
Epidemiologische studies in ouderen
Proefschrift
ter verkrijging van de graad van doctor aan de
Erasmus Universiteit Rotterdam
op gezag van de rector magnificus
Prof.dr. H.A.P. Pols
en volgens besluit van het College voor Promoties.
De openbare verdediging zal plaatsvinden op
woensdag 28 maart 2018 om 11.30 uur
door
Chantal M. Koolhaas
geboren te Enkhuizen
Acknowledgments
The work conducted in this thesis was conducted within ErasmusAGE at the department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. All studies described in this manuscript were performed within the Rotterdam Study, which is supported by the Erasmus Medical Center, Rotterdam; Erasmus University, Rotterdam; the Netherlands Organisation for Scientific Research (NOW); and the Netherlands Organisation for Health Research and Development (ZonMw). ErasmusAGE is a research center investigating the role of lifestyle and nutrition on health across the life-course, funded by Nestlé Nutrition (Nested Ltd.) and Metagenics Inc. The funders were not involved in design or conduct of the studies; collection, management, analysis or interpretation of the data; or preparation, review or approval of the manuscripts described in this thesis.
Publication of this thesis was kindly supported by the Department of Epidemiology of the Erasmus Medical Center. Additional financial support by the Dutch Heart Foundation for the publication of this thesis is gratefully acknowledged. Further financial support was kindly provided by ChipSoft.
Cover design and printing: Optima Grafische Communicatie BV ISBN: 978-94-6361-064-3
© 2018 Chantal Koolhaas, Rotterdam, the Netherlands
The copyright is transferred to the respective publisher upon publication of the manuscript. No part of this thesis may be reproduced, stored in a retrieval system, or transmitted in any form or by any means without prior permission of the author or the publisher of the manuscript.
Activity and Health:
Epidemiological studies in older adults
Activiteit en gezondheid:
Epidemiologische studies in ouderen
Proefschrift
ter verkrijging van de graad van doctor aan de
Erasmus Universiteit Rotterdam
op gezag van de rector magnificus
Prof.dr. H.A.P. Pols
en volgens besluit van het College voor Promoties.
De openbare verdediging zal plaatsvinden op
woensdag 28 maart 2018 om 11.30 uur
door
Chantal M. Koolhaas
geboren te Enkhuizen
Promotiecommissie
Promotoren: Prof.dr. O.H. Franco
Prof.dr. H. Tiemeier Overige leden: Prof.dr. F.J. van Lenthe
Prof.dr. J.W. Deckers Prof.dr. A.E. Kunst Copromotoren: Dr. J.D. Schoufour
Dr. K. Dhana
Promotiecommissie
Promotoren: Prof.dr. O.H. Franco
Prof.dr. H. Tiemeier Overige leden: Prof.dr. F.J. van Lenthe
Prof.dr. J.W. Deckers Prof.dr. A.E. Kunst Copromotoren: Dr. J.D. Schoufour
Dr. K. Dhana
Contents
Chapter 1 General introduction
13
Chapter 2 Activity in the elderly
23
2.1 Comparing physical activity derived from questionnaires and accelerometers 25 2.2 Distribution of objective activity measures and associations with demographic
and health factors
53
2.3 Seasonality of physical activity, sedentary behavior, and sleep 97
Chapter 3 Activity and mortality
125
3.1 Physical activity and cause-specific mortality 127
3.2 Sedentary time assessed by actigraphy and mortality 153
Chapter 4 Activity and cardiovascular health
173
4.1 Physical activity types and coronary heart disease risk 175
4.2 Physical activity types and atrial fibrillation risk 205
4.3 Physical activity types and life expectancy with and without cardiovascular disease
227 4.4 The impact of physical activity on the association of overweight and obesity with cardiovascular disease
251
Chapter 5 Activity and mental health and wellbeing
267
5.1 Physical activity types and health-related quality of life 269
5.2 Sedentary behavior measured by actigraphy and mental and cognitive health 299 5.3 The bidirectional association between objectively measured sleep and body mass index
325
Chapter 6 General discussion
349
Chapter 7 Appendices
371
Summary 372
Samenvatting 374
Authors’ affiliations 377
About the author 379
Word of thanks 380
Publications and manuscripts 382
Contents
Chapter 1 General introduction
13
Chapter 2 Activity in the elderly
23
2.1 Comparing physical activity derived from questionnaires and accelerometers 25 2.2 Distribution of objective activity measures and associations with demographic
and health factors
53
2.3 Seasonality of physical activity, sedentary behavior, and sleep 97
Chapter 3 Activity and mortality
125
3.1 Physical activity and cause-specific mortality 127
3.2 Sedentary time assessed by actigraphy and mortality 153
Chapter 4 Activity and cardiovascular health
173
4.1 Physical activity types and coronary heart disease risk 175
4.2 Physical activity types and atrial fibrillation risk 205
4.3 Physical activity types and life expectancy with and without cardiovascular disease
227 4.4 The impact of physical activity on the association of overweight and obesity with cardiovascular disease
251
Chapter 5 Activity and mental health and wellbeing
267
5.1 Physical activity types and health-related quality of life 269
5.2 Sedentary behavior measured by actigraphy and mental and cognitive health 299 5.3 The bidirectional association between objectively measured sleep and body mass index
325
Chapter 6 General discussion
349
Chapter 7 Appendices
371
Summary 372
Samenvatting 374
Authors’ affiliations 377
About the author 379
Word of thanks 380
Publications and manuscripts 382
Manuscripts based on the studies described in this thesis
Chapter 2 Activity in the elderly
Koolhaas CM, van Rooij FJA, Cepeda M, Tiemeier H, Franco OH, Schoufour JD. Physical activity derived from questionnaires and wrist-worn accelerometers: comparability and the role of demographic, lifestyle, and health factors among a population-based sample of older adults.
Clinical Epidemiology. 2018;10:1-16.
Koolhaas CM*, van Rooij FJA*, Schoufour JD, Cepeda M, Tiemeier H, Brage S, et al. Objective
Measures of activity in the elderly: distribution and associations with demographic and health factors. J Am Med Dir Assoc. 2017 Jun 08.
Cepeda M*, Koolhaas CM*, van Rooij FJA, Tiemeier H, Guxens M, Franco OH, Schoufour JD. Seasonality of physical activity, sedentary behavior, and sleep in a middle-aged and elderly population: The Rotterdam study. Maturitas. 2018;110:41-50.
Chapter 3 Activity and mortality
Koolhaas CM, Dhana K, Schoufour JD, Lahousse L, van Rooij FJA, Ikram MA, Brusselle G, Tiemeier H, Franco OH. Physical activity and cause-specific mortality: The Rotterdam Study.
Submitted for publication.
Koolhaas CM, Dhana K, van Rooij FJ, Kocevska D, Hofman A, Franco OH, Tiemeier H. Sedentary time assessed by actigraphy and mortality: The Rotterdam Study. Prev Med. 2017; 95: 59-65.
Chapter 4 Activity and cardiovascular disease
Koolhaas CM, Dhana K, Golubic R, Schoufour JD, Hofman A, van Rooij FJ, Franco OH. Physical activity types and coronary heart disease risk in middle-aged and elderly persons: The Rotterdam Study. Am J Epidemiol. 2016 Apr 15;183(8):729-738.
Albrecht M*, Koolhaas CM*, Schoufour JD, van Rooij FJ, Kavousi M, Ikram MA, Franco OH. Physical activity types and atrial fibrillation risk in the middle-aged and elderly: the Rotterdam Study. Submitted for publication.
Manuscripts based on the studies described in this thesis
Chapter 2 Activity in the elderly
Koolhaas CM, van Rooij FJA, Cepeda M, Tiemeier H, Franco OH, Schoufour JD. Physical activity derived from questionnaires and wrist-worn accelerometers: comparability and the role of demographic, lifestyle, and health factors among a population-based sample of older adults.
Clinical Epidemiology. 2018;10:1-16.
Koolhaas CM*, van Rooij FJA*, Schoufour JD, Cepeda M, Tiemeier H, Brage S, et al. Objective
Measures of activity in the elderly: distribution and associations with demographic and health factors. J Am Med Dir Assoc. 2017 Jun 08.
Cepeda M*, Koolhaas CM*, van Rooij FJA, Tiemeier H, Guxens M, Franco OH, Schoufour JD. Seasonality of physical activity, sedentary behavior, and sleep in a middle-aged and elderly population: The Rotterdam study. Maturitas. 2018;110:41-50.
Chapter 3 Activity and mortality
Koolhaas CM, Dhana K, Schoufour JD, Lahousse L, van Rooij FJA, Ikram MA, Brusselle G, Tiemeier H, Franco OH. Physical activity and cause-specific mortality: The Rotterdam Study.
Submitted for publication.
Koolhaas CM, Dhana K, van Rooij FJ, Kocevska D, Hofman A, Franco OH, Tiemeier H. Sedentary time assessed by actigraphy and mortality: The Rotterdam Study. Prev Med. 2017; 95: 59-65.
Chapter 4 Activity and cardiovascular disease
Koolhaas CM, Dhana K, Golubic R, Schoufour JD, Hofman A, van Rooij FJ, Franco OH. Physical activity types and coronary heart disease risk in middle-aged and elderly persons: The Rotterdam Study. Am J Epidemiol. 2016 Apr 15;183(8):729-738.
Albrecht M*, Koolhaas CM*, Schoufour JD, van Rooij FJ, Kavousi M, Ikram MA, Franco OH. Physical activity types and atrial fibrillation risk in the middle-aged and elderly: the Rotterdam Study. Submitted for publication.
Dhana K*, Koolhaas CM*, Berghout MA, Peeters A, Ikram MA, Tiemeier H, Hofman A, Nusselder W, Franco OH. Physical activity types and life expectancy with and without cardiovascular disease: The Rotterdam Study. J Public Health (Oxf). 2017;39(4):e209-e218. Koolhaas CM, Dhana K, Schoufour JD, Ikram MA, Kavousi M, Franco OH. Impact of physical activity on the association of overweight and obesity with cardiovascular disease: The Rotterdam Study. Eur J Prev Cardiol. 2017;24(9):934-941.
Chapter 5 Activity and mental health and wellbeing
Koolhaas CM, Dhana K, van Rooij FJA, Schoufour JD, Hofman A, Franco OH. Physical activity types and health-related quality of life among middle-aged and elderly adults: The Rotterdam Study. The journal of nutrition, health & aging. 2018;22(2):246-253.
Koolhaas CM. van Rooij FJA, Kocevska D, Luik AI, Franco OH, Tiemeier H. Objectively measured sedentary time and mental and cognitive health: cross-sectional and longitudinal associations in The Rotterdam Study. Submitted for publication.
Koolhaas CM*, Kocevska D*, te Lindert BHW, Erler, NS, Franco OH, Tiemeier H, Luik AI. The
bidirectional association between objectively measured sleep and body mass index: The Rotterdam Study. Submitted for publication.
Dhana K*, Koolhaas CM*, Berghout MA, Peeters A, Ikram MA, Tiemeier H, Hofman A, Nusselder W, Franco OH. Physical activity types and life expectancy with and without cardiovascular disease: The Rotterdam Study. J Public Health (Oxf). 2017;39(4):e209-e218. Koolhaas CM, Dhana K, Schoufour JD, Ikram MA, Kavousi M, Franco OH. Impact of physical activity on the association of overweight and obesity with cardiovascular disease: The Rotterdam Study. Eur J Prev Cardiol. 2017;24(9):934-941.
Chapter 5 Activity and mental health and wellbeing
Koolhaas CM, Dhana K, van Rooij FJA, Schoufour JD, Hofman A, Franco OH. Physical activity types and health-related quality of life among middle-aged and elderly adults: The Rotterdam Study. The journal of nutrition, health & aging. 2018;22(2):246-253.
Koolhaas CM. van Rooij FJA, Kocevska D, Luik AI, Franco OH, Tiemeier H. Objectively measured sedentary time and mental and cognitive health: cross-sectional and longitudinal associations in The Rotterdam Study. Submitted for publication.
Koolhaas CM*, Kocevska D*, te Lindert BHW, Erler, NS, Franco OH, Tiemeier H, Luik AI. The
bidirectional association between objectively measured sleep and body mass index: The Rotterdam Study. Submitted for publication.
Chapter 1
Introduction
14 BACKGROUND
Physical activity, defined as any bodily movement requiring energy expenditure above the resting state,1is an important factor associated with health. Worldwide, insufficient levels of physical
activity are estimated to cause 6% of the burden of disease, including coronary heart disease, colon cancer and breast cancer, and 9% of the premature mortality.2 Conversely, engaging in sufficient
physical activity can decrease the risk of bone fractures and is related to better cardiovascular health.3 For adults, it is therefore recommended to be physically active at moderate to vigorous
intensity for 30 minutes/day, on most days of the week.4 However, globally, many individuals do
not meet these guidelines5 and in the Netherlands, around 42% of older adults fail to meet these
recommendations.6 Gaining more insight in the levels of physical activity and the types of physical
activity that adults engage in can help to create targeted interventions and recommendations, with the aim to achieve health benefits. This is especially important in older adults, who more often have difficulties in engaging in exercise or sports. For these adults, knowing more about the benefits of other types of activity is of importance. The population of older adults is growing rapidly, which is accompanied by a rise in health care costs associated with diseases in later life.7 A
modifiable lifestyle factor like physical activity could contribute to enhance healthy aging.8
In addition to physical activity, the 24-hour cycle of activity consists of sedentary behavior and sleep (Figure 1.1). Sedentary behavior is defined as engaging in sitting, reclining or lying behaviors during the waking hours, which result in little energy expenditure above the basal metabolic rate.9Current trends of population ageing, urbanization and automatization of daily
activities have contributed to a predominantly sedentary lifestyle, with low levels of physical activity, high levels sedentary behavior and an unhealthy nighttime sleep duration.10 However,
whereas the activity guidelines specifically promote at least 30 minutes of physical activity per day4
and 7-8 hours of nighttime sleep per day,11 this leaves approximately 16 hours of unaccounted
time, with a vague and non-quantified recommendation to refrain from too much sedentary behavior.12 Moreover, still little is known about the health effects related to sedentary behavior in
older adults. Therefore, more information is required on the determinants associated with inactivity and the health effects associated with all activity domains.
Figure 1.1. 24-hour activity distribution
Sedentary behavior Sleep Physical activity Introduction 15 MEASUREMENT OF ACTIVITY
For practical reasons, physical activity is often measured by questionnaire.13 In addition,
accelerometers are increasingly being used to gain more objective measures of physical activity levels,13,14 and can provide information on the intensity and duration of physical activity levels.15
An accelerometer is a small device worn on the body that measures changes in gravitational acceleration. In most previous studies, accelerometers have been worn on the hip and had to be removed for sleeping.16,17 Wrist-worn devices have the advantage that they can be worn day and
night, thereby allowing for collection of 24-hour of activity data.
However, when comparing activity measures obtained by questionnaire with objective methods applied in large populations, major discrepancies emerge.18,19 The inconsistency might be
related to recall-bias, a phenomenon in which information on the variable of interest is reported differently across subgroups of the population.20 Population characteristics such as age, sex and
health status might be related to the extent that the information is reported correctly.13 In
addition, the inconsistency might be derived from the fact that accelerometers cannot measure all physical activity accurately.21 For example, weight lifting and cycling are generally underestimated
by wrist-worn accelerometers.21 Considering the increased use of accelerometers in current
research,13 it is important to understand and quantify how physical activity assessed using
questionnaires and accelerometers differ and how these differences might be related to population characteristics.22 This is especially relevant in older adults, because the higher likelihood of
cognitive impairment23 might lead to more recall bias and reporting errors.
FACTORS ASSOCIATED WITH ACTIVITY
With the information collected from wrist-worn accelerometers, we can shed more light on the daily distribution of physical activity, sedentary behavior and sleep in older adults, as well as the factors associated with these activities domains. To date, several studies have examined factors associated with objectively assessed physical activity in adults aged 60 years and over,16,17,24 and
showed that physical activity levels decrease with increasing age and across increasing levels of body mass index (BMI). However, it has not yet been investigated what factors are associated with activity in the very old (aged 77 and over), a population with generally lower activity levels and more disability. Moreover, the demographic and health factors associated with sleep and sedentary behavior have not been addressed jointly with physical activity in the elderly. Additionally, it is still unclear which environmental factors are associated with these different activity domains. Physical activity has a seasonal pattern, with higher levels of physical activity in the summer and less physical activity in the winter,25 but it is unclear whether this is at the
expense of sedentary behavior or sleep. It is also still unclear which meteorological factors are related to this seasonal pattern of activity in older adults, and it remains unknown whether the seasonality of activity might have an effect on health outcomes.
Introduction
14 BACKGROUND
Physical activity, defined as any bodily movement requiring energy expenditure above the resting state,1is an important factor associated with health. Worldwide, insufficient levels of physical
activity are estimated to cause 6% of the burden of disease, including coronary heart disease, colon cancer and breast cancer, and 9% of the premature mortality.2 Conversely, engaging in sufficient
physical activity can decrease the risk of bone fractures and is related to better cardiovascular health.3 For adults, it is therefore recommended to be physically active at moderate to vigorous
intensity for 30 minutes/day, on most days of the week.4 However, globally, many individuals do
not meet these guidelines5 and in the Netherlands, around 42% of older adults fail to meet these
recommendations.6 Gaining more insight in the levels of physical activity and the types of physical
activity that adults engage in can help to create targeted interventions and recommendations, with the aim to achieve health benefits. This is especially important in older adults, who more often have difficulties in engaging in exercise or sports. For these adults, knowing more about the benefits of other types of activity is of importance. The population of older adults is growing rapidly, which is accompanied by a rise in health care costs associated with diseases in later life.7 A
modifiable lifestyle factor like physical activity could contribute to enhance healthy aging.8
In addition to physical activity, the 24-hour cycle of activity consists of sedentary behavior and sleep (Figure 1.1). Sedentary behavior is defined as engaging in sitting, reclining or lying behaviors during the waking hours, which result in little energy expenditure above the basal metabolic rate.9Current trends of population ageing, urbanization and automatization of daily
activities have contributed to a predominantly sedentary lifestyle, with low levels of physical activity, high levels sedentary behavior and an unhealthy nighttime sleep duration.10 However,
whereas the activity guidelines specifically promote at least 30 minutes of physical activity per day4
and 7-8 hours of nighttime sleep per day,11 this leaves approximately 16 hours of unaccounted
time, with a vague and non-quantified recommendation to refrain from too much sedentary behavior.12 Moreover, still little is known about the health effects related to sedentary behavior in
older adults. Therefore, more information is required on the determinants associated with inactivity and the health effects associated with all activity domains.
Figure 1.1. 24-hour activity distribution
Sedentary behavior Sleep Physical activity Introduction 15 MEASUREMENT OF ACTIVITY
For practical reasons, physical activity is often measured by questionnaire.13 In addition,
accelerometers are increasingly being used to gain more objective measures of physical activity levels,13,14 and can provide information on the intensity and duration of physical activity levels.15
An accelerometer is a small device worn on the body that measures changes in gravitational acceleration. In most previous studies, accelerometers have been worn on the hip and had to be removed for sleeping.16,17 Wrist-worn devices have the advantage that they can be worn day and
night, thereby allowing for collection of 24-hour of activity data.
However, when comparing activity measures obtained by questionnaire with objective methods applied in large populations, major discrepancies emerge.18,19 The inconsistency might be
related to recall-bias, a phenomenon in which information on the variable of interest is reported differently across subgroups of the population.20 Population characteristics such as age, sex and
health status might be related to the extent that the information is reported correctly.13 In
addition, the inconsistency might be derived from the fact that accelerometers cannot measure all physical activity accurately.21 For example, weight lifting and cycling are generally underestimated
by wrist-worn accelerometers.21 Considering the increased use of accelerometers in current
research,13 it is important to understand and quantify how physical activity assessed using
questionnaires and accelerometers differ and how these differences might be related to population characteristics.22 This is especially relevant in older adults, because the higher likelihood of
cognitive impairment23 might lead to more recall bias and reporting errors.
FACTORS ASSOCIATED WITH ACTIVITY
With the information collected from wrist-worn accelerometers, we can shed more light on the daily distribution of physical activity, sedentary behavior and sleep in older adults, as well as the factors associated with these activities domains. To date, several studies have examined factors associated with objectively assessed physical activity in adults aged 60 years and over,16,17,24 and
showed that physical activity levels decrease with increasing age and across increasing levels of body mass index (BMI). However, it has not yet been investigated what factors are associated with activity in the very old (aged 77 and over), a population with generally lower activity levels and more disability. Moreover, the demographic and health factors associated with sleep and sedentary behavior have not been addressed jointly with physical activity in the elderly. Additionally, it is still unclear which environmental factors are associated with these different activity domains. Physical activity has a seasonal pattern, with higher levels of physical activity in the summer and less physical activity in the winter,25 but it is unclear whether this is at the
expense of sedentary behavior or sleep. It is also still unclear which meteorological factors are related to this seasonal pattern of activity in older adults, and it remains unknown whether the seasonality of activity might have an effect on health outcomes.
Chapter 1
16
ACTIVITY AND MORTALITY
There is extensive literature on the association between physical activity and mortality.26 However,
there is limited information on what type of physical activities are beneficially associated with mortality after retirement in an elderly population, and more specifically if the association between physical activity and mortality differs by cause of death. In particular, information is currently lacking on whether physical activity is associated with reduced mortality related to dementia and chronic lung disease.27-29
Furthermore, information on the association between sedentary behavior and mortality currently mostly relies on studies using self-reported measures of sedentary behavior30 and studies
using accelerometers have only a limited follow-up time, up to an average of 4.5 years.31-33
Self-reported sedentary behavior might be influenced by information and recall bias34 and the limited
follow-up time in studies using accelerometers increases the likelihood of the results being influenced by reverse causation. An underlying disease or disability might be related to both sedentary behavior and a higher mortality risk. Therefore, it is important to examine the association between sedentary behavior and all-cause mortality with longer follow-up, by using objective measures of sedentary behavior.
ACTIVITY AND CARDIOVASCULAR HEALTH
The inverse association between higher physical activity levels and lower risk of cardiovascular diseases (CVDs) has been well documented in literature.3 According to recent meta-analyses,
regular physical activity of moderate to vigorous intensity may contribute to up to 27% reduced risk of coronary heart disease.35,36 However, it remains unclear whether all cardiovascular
conditions, including atrial fibrillation, benefit from physical activity. Atrial fibrillation is the most common chronic cardiac arrhythmia with significant morbidity and mortality.37 Since known risk
factors of atrial fibrillation, such as heart failure and myocardial infarction are directly influenced by the level of physical activity,38 high levels of physical activity might also reduce the risk of atrial
fibrillation.
Previous studies on the association between physical activity and CVDs have mainly focused on the effect of overall leisure time physical activity, whereas it remains unclear what specific physical activity types contribute most to the beneficial effects of physical activity. Only a few studies have addressed the impact of different types of physical activity on CVD39,40 or specifically
coronary heart disease41 or atrial fibrillation.42 Several studies documented a beneficial association
between walking and risk of coronary heart disease43 or atrial fibrillation,44 but evidence of the
influence of cycling and domestic work remains scarce among the elderly,39,45 whereas domestic
work is an important domain contributing to the daily physical activity of older adults.46
Additionally, in order to provide comprehensive information for public and individual health care planning, measures of the lifetime consequences of physical activity, including life expectancy estimates, are most informative. Since individuals with CVD have a lower quality of life,47
information on the life years with and without CVD is of relevance in this matter.
Introduction
17 Furthermore, it has been suggested that physical activity might counterbalance the CVD risk associated with overweight and obesity,48 but information among the elderly is scarce. In
older adults, it has been suggested that the risks of myocardial infarction and stroke associated with overweight and obesity are attenuated,49 possibly because in older adults BMI is a poor
indicator of body composition. Therefore, we examined the role of physical activity in the association of overweight and obesity with CVD in elderly adults.
ACTIVITY AND MENTAL HEALTH AND WELLBEING
Physical activity and sedentary behavior have been associated with health-related quality of life (HRQL) and mental health outcomes such as depression, anxiety and cognitive function. HRQL is defined as an individuals’ perspective of well-being in physical, mental and social domains of life.50 Recent studies have shown a consistent association between physical activity and HRQL.51,52
However, it remains unclear what specific physical activity types contribute most to the beneficial effects of physical activity in older adults.
Regarding mental health, higher levels of self-reported sedentary behavior have been associated with a higher risk to develop depression53 and anxiety disorders54 and with a lower risk
to decrease in cognitive functioning.55 However, most studies performed thus far were
cross-sectional, making it impossible to infer temporality. In addition, only a limited number of studies adjusted for disability status, which can be considered an important confounder influencing both the sedentary behavior and the mental health measures. Furthermore, the use of subjective measures of sedentary behavior, which are usually assessed by probing types of sitting behavior (e.g. television viewing, car driving), might have influenced the associations.56,57 In this regard, the
reported associations might be driven more by the social context of sitting than sedentary behavior. Therefore, using objective measures of sedentary behavior, while carefully adjusting the associations for important confounders such as disability, can provide additional information on the association between sedentary behavior and mental health measures.
Furthermore, sleep has received interest as a possible modifiable factor that might influence body weight.58,59 Short sleep duration has been associated with obesity,58 giving rise to the idea that
chronic sleep deprivation might contribute to the obesity epidemic.59 However, studies assessing
the association between sleep and obesity have mostly been cross-sectional, thus the temporality of the relation between sleep and adiposity could not be explored.58,60 Second, prospective studies
performed thus far have relied on self-reported measures, which are prone to information and recall bias.61 Moreover, adiposity most probably impacts sleep, but very few studies have examined
the hypothesis that the association between sleep and adiposity might be bidirectional.62-64
Chapter 1
16
ACTIVITY AND MORTALITY
There is extensive literature on the association between physical activity and mortality.26 However,
there is limited information on what type of physical activities are beneficially associated with mortality after retirement in an elderly population, and more specifically if the association between physical activity and mortality differs by cause of death. In particular, information is currently lacking on whether physical activity is associated with reduced mortality related to dementia and chronic lung disease.27-29
Furthermore, information on the association between sedentary behavior and mortality currently mostly relies on studies using self-reported measures of sedentary behavior30 and studies
using accelerometers have only a limited follow-up time, up to an average of 4.5 years.31-33
Self-reported sedentary behavior might be influenced by information and recall bias34 and the limited
follow-up time in studies using accelerometers increases the likelihood of the results being influenced by reverse causation. An underlying disease or disability might be related to both sedentary behavior and a higher mortality risk. Therefore, it is important to examine the association between sedentary behavior and all-cause mortality with longer follow-up, by using objective measures of sedentary behavior.
ACTIVITY AND CARDIOVASCULAR HEALTH
The inverse association between higher physical activity levels and lower risk of cardiovascular diseases (CVDs) has been well documented in literature.3 According to recent meta-analyses,
regular physical activity of moderate to vigorous intensity may contribute to up to 27% reduced risk of coronary heart disease.35,36 However, it remains unclear whether all cardiovascular
conditions, including atrial fibrillation, benefit from physical activity. Atrial fibrillation is the most common chronic cardiac arrhythmia with significant morbidity and mortality.37 Since known risk
factors of atrial fibrillation, such as heart failure and myocardial infarction are directly influenced by the level of physical activity,38 high levels of physical activity might also reduce the risk of atrial
fibrillation.
Previous studies on the association between physical activity and CVDs have mainly focused on the effect of overall leisure time physical activity, whereas it remains unclear what specific physical activity types contribute most to the beneficial effects of physical activity. Only a few studies have addressed the impact of different types of physical activity on CVD39,40 or specifically
coronary heart disease41 or atrial fibrillation.42 Several studies documented a beneficial association
between walking and risk of coronary heart disease43 or atrial fibrillation,44 but evidence of the
influence of cycling and domestic work remains scarce among the elderly,39,45 whereas domestic
work is an important domain contributing to the daily physical activity of older adults.46
Additionally, in order to provide comprehensive information for public and individual health care planning, measures of the lifetime consequences of physical activity, including life expectancy estimates, are most informative. Since individuals with CVD have a lower quality of life,47
information on the life years with and without CVD is of relevance in this matter.
Introduction
17 Furthermore, it has been suggested that physical activity might counterbalance the CVD risk associated with overweight and obesity,48 but information among the elderly is scarce. In
older adults, it has been suggested that the risks of myocardial infarction and stroke associated with overweight and obesity are attenuated,49 possibly because in older adults BMI is a poor
indicator of body composition. Therefore, we examined the role of physical activity in the association of overweight and obesity with CVD in elderly adults.
ACTIVITY AND MENTAL HEALTH AND WELLBEING
Physical activity and sedentary behavior have been associated with health-related quality of life (HRQL) and mental health outcomes such as depression, anxiety and cognitive function. HRQL is defined as an individuals’ perspective of well-being in physical, mental and social domains of life.50 Recent studies have shown a consistent association between physical activity and HRQL.51,52
However, it remains unclear what specific physical activity types contribute most to the beneficial effects of physical activity in older adults.
Regarding mental health, higher levels of self-reported sedentary behavior have been associated with a higher risk to develop depression53 and anxiety disorders54 and with a lower risk
to decrease in cognitive functioning.55 However, most studies performed thus far were
cross-sectional, making it impossible to infer temporality. In addition, only a limited number of studies adjusted for disability status, which can be considered an important confounder influencing both the sedentary behavior and the mental health measures. Furthermore, the use of subjective measures of sedentary behavior, which are usually assessed by probing types of sitting behavior (e.g. television viewing, car driving), might have influenced the associations.56,57 In this regard, the
reported associations might be driven more by the social context of sitting than sedentary behavior. Therefore, using objective measures of sedentary behavior, while carefully adjusting the associations for important confounders such as disability, can provide additional information on the association between sedentary behavior and mental health measures.
Furthermore, sleep has received interest as a possible modifiable factor that might influence body weight.58,59 Short sleep duration has been associated with obesity,58 giving rise to the idea that
chronic sleep deprivation might contribute to the obesity epidemic.59 However, studies assessing
the association between sleep and obesity have mostly been cross-sectional, thus the temporality of the relation between sleep and adiposity could not be explored.58,60 Second, prospective studies
performed thus far have relied on self-reported measures, which are prone to information and recall bias.61 Moreover, adiposity most probably impacts sleep, but very few studies have examined
the hypothesis that the association between sleep and adiposity might be bidirectional.62-64
Chapter 1
18
STUDY DESIGN: THE ROTTERDAM STUDY
The Rotterdam Study (RS) is a prospective population-based cohort, among subjects aged 55 years or older in the well-defined Ommoord neighborhood, in the municipality of Rotterdam, the Netherlands.65 The Rotterdam Study started in 1990 and was set up to study risk factors of
cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, oncological, and respiratory diseases. In the original study cohort, 7,983 participants aged 55 years and older were enrolled, which constituted 78% of all 10,215 invitees. In 2000-2001, the Rotterdam Study was extended with 3,011 participants out of 4,472 invitees who were ≥55 years old or had moved into the study district. In 2006 a third study cohort was initiated, in which 3,932 adults aged 45 years and older were included.65 Physical activity was assessed for the first time by
questionnaire during the third examination of the original cohort (RS-I-3, between 1997 and 1999) and during the baseline examination of the extended cohort (RS-II-1, between 2000 and 2001). Objective measures of activity were obtained for the first time between 2002 and 2008, in a subset of participants from each of the cohorts. From 2012 on forwards, objective data on physical activity has been collected in all participants who agreed to wear a wrist-worn accelerometer.
Data on clinical outcomes, including cardiovascular disease, depression and dementia, were collected through a follow-up system involving digital linkage of the study database to medical records maintained by general practitioners working in the research area. Trained research assistants collected notes, outpatient clinic reports, hospital discharge letters, electrocardiograms, and imaging results from general practitioner records and hospital records. Other health-related measurements were obtained during the home-interview or at the research center.
OVERALL AIM OF THIS THESIS
The overall aim of this thesis was to study the factors associated with activity in older age and to examine the association of activity domains with mortality, cardiovascular disorders and mental health outcomes. In Chapter 2, we discuss differences between objectively and subjectively measured physical activity, as well as provide an overview of the 24-hour activity distribution in an elderly population and report which factors are associated with physical activity, sedentary behavior and sleep. In Chapter 3, we discuss the association between physical activity and sedentary behavior with all-cause and cause-specific mortality. In Chapter 4, we discuss the association of overall physical activity and specific physical activity types with several cardiovascular health outcomes. In Chapter 5, we study the association of physical activity and sedentary behavior with mental health and wellbeing, including health-related quality of life, depression, anxiety and cognition. Last, in the general discussion in Chapter 6, we address methodological considerations, practical implications of our findings and suggestions for future research.
Introduction
19 REFERENCES
1. Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Effect of physical inactivity on major
non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. The Lancet.380(9838):219-229.
2. Li J, Siegrist J. Physical activity and risk of cardiovascular disease--a meta-analysis of prospective cohort studies.
International journal of environmental research and public health. 2012;9(2):391-407.
3. Organization WH. Health Topics: Physical Activity. 2017; http://www.who.int/topics/physical_activity/en/.
4. Physical Activity Guidelines Advisory Committee. Physical Activity Guidelines Advisory Committee Report, 2008.
Washington, DC: U.S: Department of Health and Human Services;2008.
5. Clarke TC, Norris T, Schiller JS. Early Release of Selected Estimates Based on Data From the 2016 National Health
Interview Survey. National Center for Health Statistics;2017.
6. Organization WH. Global Health Observatory (GHO) data: Life Expectancy. 2017;
http://www.who.int/gho/mortality_burden_disease/life_tables/situation_trends_text/en/.
7. He W, Goodkind D, Kowal PR. An aging world: 2015. United States Census Bureau; 2016.
8. Hamer M, Lavoie KL, Bacon SL. Taking up physical activity in later life and healthy ageing: the English longitudinal
study of ageing. British Journal of Sports Medicine. 2013.
9. Alvarez GG, Ayas NT. The impact of daily sleep duration on health: a review of the literature. Progress in
cardiovascular nursing. 2004;19(2):56-59.
10. Wu Y, Zhai L, Zhang D. Sleep duration and obesity among adults: a meta-analysis of prospective studies. Sleep Med.
2014;15(12):1456-1462.
11. Tremblay MS, Aubert S, Barnes JD, et al. Sedentary Behavior Research Network (SBRN) – Terminology Consensus
Project process and outcome. International Journal of Behavioral Nutrition and Physical Activity. 2017;14(1):75.
12. Rosenberger ME, Buman MP, Haskell WL, McConnell MV, Carstensen LL. 24 Hours of Sleep, Sedentary Behavior,
and Physical Activity with Nine Wearable Devices. Medicine and science in sports and exercise. 2016;48(3):457-465.
13. Skender S, Ose J, Chang-Claude J, et al. Accelerometry and physical activity questionnaires - a systematic review. BMC
Public Health. 2016;16:515.
14. Westerterp KR. Physical activity assessment with accelerometers. Int J Obes Relat Metab Disord. 1999;23 Suppl
3:S45-49.
15. Hills AP, Mokhtar N, Byrne NM. Assessment of Physical Activity and Energy Expenditure: An Overview of Objective
Measures. Frontiers in Nutrition. 2014;1:5.
16. Berkemeyer K, Wijndaele K, White T, et al. The descriptive epidemiology of accelerometer-measured physical activity
in older adults. Int J Behav Nutr Phys Act. 2016;13(1):2.
17. Davis MG, Fox KR, Hillsdon M, Sharp DJ, Coulson JC, Thompson JL. Objectively measured physical activity in a
diverse sample of older urban UK adults. Med Sci Sports Exerc. 2011;43(4):647-654.
18. Scheers T, Philippaerts R, Lefevre J. Assessment of physical activity and inactivity in multiple domains of daily life: a
comparison between a computerized questionnaire and the SenseWear Armband complemented with an electronic diary. Int J Behav Nutr Phys Act. 2012;9:71.
19. Prince SA, Adamo KB, Hamel ME, Hardt J, Connor Gorber S, Tremblay M. A comparison of direct versus self-report
measures for assessing physical activity in adults: a systematic review. Int J Behav Nutr Phys Act. 2008;5:56.
20. Coughlin SS. Recall bias in epidemiologic studies. Journal of clinical epidemiology. 1990;43(1):87-91.
21. Chen KY, Bassett DR, Jr. The technology of accelerometry-based activity monitors: current and future. Med Sci Sports
Exerc. 2005;37(11 Suppl):S490-500.
22. Shiroma EJ, Cook NR, Manson JE, Buring JE, Rimm EB, Lee IM. Comparison of Self-Reported and
Accelerometer-Assessed Physical Activity in Older Women. PLoS One. 2015;10(12):e0145950.
23. Rait G, Fletcher A, Smeeth L, et al. Prevalence of cognitive impairment: results from the MRC trial of assessment and
management of older people in the community. Age Ageing. 2005;34(3):242-248.
24. Arnardottir NY, Koster A, Van Domelen DR, et al. Objective measurements of daily physical activity patterns and
sedentary behaviour in older adults: Age, Gene/Environment Susceptibility-Reykjavik Study. Age Ageing. 2013;42(2):222-229.
25. Matthews CE, Freedson PS, Hebert JR, et al. Seasonal variation in household, occupational, and leisure time physical
activity: longitudinal analyses from the seasonal variation of blood cholesterol study. Am J Epidemiol. 2001;153(2):172-183.
26. Nocon M, Hiemann T, Muller-Riemenschneider F, Thalau F, Roll S, Willich SN. Association of physical activity with
all-cause and cardiovascular mortality: a systematic review and meta-analysis. Eur J Cardiovasc Prev Rehabil. 2008;15(3):239-246.
27. Rosness TA, Strand BH, Bergem AL, Engedal K, Bjertness E. Associations between Physical Activity in Old Age and
Chapter 1
18
STUDY DESIGN: THE ROTTERDAM STUDY
The Rotterdam Study (RS) is a prospective population-based cohort, among subjects aged 55 years or older in the well-defined Ommoord neighborhood, in the municipality of Rotterdam, the Netherlands.65 The Rotterdam Study started in 1990 and was set up to study risk factors of
cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, oncological, and respiratory diseases. In the original study cohort, 7,983 participants aged 55 years and older were enrolled, which constituted 78% of all 10,215 invitees. In 2000-2001, the Rotterdam Study was extended with 3,011 participants out of 4,472 invitees who were ≥55 years old or had moved into the study district. In 2006 a third study cohort was initiated, in which 3,932 adults aged 45 years and older were included.65 Physical activity was assessed for the first time by
questionnaire during the third examination of the original cohort (RS-I-3, between 1997 and 1999) and during the baseline examination of the extended cohort (RS-II-1, between 2000 and 2001). Objective measures of activity were obtained for the first time between 2002 and 2008, in a subset of participants from each of the cohorts. From 2012 on forwards, objective data on physical activity has been collected in all participants who agreed to wear a wrist-worn accelerometer.
Data on clinical outcomes, including cardiovascular disease, depression and dementia, were collected through a follow-up system involving digital linkage of the study database to medical records maintained by general practitioners working in the research area. Trained research assistants collected notes, outpatient clinic reports, hospital discharge letters, electrocardiograms, and imaging results from general practitioner records and hospital records. Other health-related measurements were obtained during the home-interview or at the research center.
OVERALL AIM OF THIS THESIS
The overall aim of this thesis was to study the factors associated with activity in older age and to examine the association of activity domains with mortality, cardiovascular disorders and mental health outcomes. In Chapter 2, we discuss differences between objectively and subjectively measured physical activity, as well as provide an overview of the 24-hour activity distribution in an elderly population and report which factors are associated with physical activity, sedentary behavior and sleep. In Chapter 3, we discuss the association between physical activity and sedentary behavior with all-cause and cause-specific mortality. In Chapter 4, we discuss the association of overall physical activity and specific physical activity types with several cardiovascular health outcomes. In Chapter 5, we study the association of physical activity and sedentary behavior with mental health and wellbeing, including health-related quality of life, depression, anxiety and cognition. Last, in the general discussion in Chapter 6, we address methodological considerations, practical implications of our findings and suggestions for future research.
Introduction
19 REFERENCES
1. Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Effect of physical inactivity on major
non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. The Lancet.380(9838):219-229.
2. Li J, Siegrist J. Physical activity and risk of cardiovascular disease--a meta-analysis of prospective cohort studies.
International journal of environmental research and public health. 2012;9(2):391-407.
3. Organization WH. Health Topics: Physical Activity. 2017; http://www.who.int/topics/physical_activity/en/.
4. Physical Activity Guidelines Advisory Committee. Physical Activity Guidelines Advisory Committee Report, 2008.
Washington, DC: U.S: Department of Health and Human Services;2008.
5. Clarke TC, Norris T, Schiller JS. Early Release of Selected Estimates Based on Data From the 2016 National Health
Interview Survey. National Center for Health Statistics;2017.
6. Organization WH. Global Health Observatory (GHO) data: Life Expectancy. 2017;
http://www.who.int/gho/mortality_burden_disease/life_tables/situation_trends_text/en/.
7. He W, Goodkind D, Kowal PR. An aging world: 2015. United States Census Bureau; 2016.
8. Hamer M, Lavoie KL, Bacon SL. Taking up physical activity in later life and healthy ageing: the English longitudinal
study of ageing. British Journal of Sports Medicine. 2013.
9. Alvarez GG, Ayas NT. The impact of daily sleep duration on health: a review of the literature. Progress in
cardiovascular nursing. 2004;19(2):56-59.
10. Wu Y, Zhai L, Zhang D. Sleep duration and obesity among adults: a meta-analysis of prospective studies. Sleep Med.
2014;15(12):1456-1462.
11. Tremblay MS, Aubert S, Barnes JD, et al. Sedentary Behavior Research Network (SBRN) – Terminology Consensus
Project process and outcome. International Journal of Behavioral Nutrition and Physical Activity. 2017;14(1):75.
12. Rosenberger ME, Buman MP, Haskell WL, McConnell MV, Carstensen LL. 24 Hours of Sleep, Sedentary Behavior,
and Physical Activity with Nine Wearable Devices. Medicine and science in sports and exercise. 2016;48(3):457-465.
13. Skender S, Ose J, Chang-Claude J, et al. Accelerometry and physical activity questionnaires - a systematic review. BMC
Public Health. 2016;16:515.
14. Westerterp KR. Physical activity assessment with accelerometers. Int J Obes Relat Metab Disord. 1999;23 Suppl
3:S45-49.
15. Hills AP, Mokhtar N, Byrne NM. Assessment of Physical Activity and Energy Expenditure: An Overview of Objective
Measures. Frontiers in Nutrition. 2014;1:5.
16. Berkemeyer K, Wijndaele K, White T, et al. The descriptive epidemiology of accelerometer-measured physical activity
in older adults. Int J Behav Nutr Phys Act. 2016;13(1):2.
17. Davis MG, Fox KR, Hillsdon M, Sharp DJ, Coulson JC, Thompson JL. Objectively measured physical activity in a
diverse sample of older urban UK adults. Med Sci Sports Exerc. 2011;43(4):647-654.
18. Scheers T, Philippaerts R, Lefevre J. Assessment of physical activity and inactivity in multiple domains of daily life: a
comparison between a computerized questionnaire and the SenseWear Armband complemented with an electronic diary. Int J Behav Nutr Phys Act. 2012;9:71.
19. Prince SA, Adamo KB, Hamel ME, Hardt J, Connor Gorber S, Tremblay M. A comparison of direct versus self-report
measures for assessing physical activity in adults: a systematic review. Int J Behav Nutr Phys Act. 2008;5:56.
20. Coughlin SS. Recall bias in epidemiologic studies. Journal of clinical epidemiology. 1990;43(1):87-91.
21. Chen KY, Bassett DR, Jr. The technology of accelerometry-based activity monitors: current and future. Med Sci Sports
Exerc. 2005;37(11 Suppl):S490-500.
22. Shiroma EJ, Cook NR, Manson JE, Buring JE, Rimm EB, Lee IM. Comparison of Self-Reported and
Accelerometer-Assessed Physical Activity in Older Women. PLoS One. 2015;10(12):e0145950.
23. Rait G, Fletcher A, Smeeth L, et al. Prevalence of cognitive impairment: results from the MRC trial of assessment and
management of older people in the community. Age Ageing. 2005;34(3):242-248.
24. Arnardottir NY, Koster A, Van Domelen DR, et al. Objective measurements of daily physical activity patterns and
sedentary behaviour in older adults: Age, Gene/Environment Susceptibility-Reykjavik Study. Age Ageing. 2013;42(2):222-229.
25. Matthews CE, Freedson PS, Hebert JR, et al. Seasonal variation in household, occupational, and leisure time physical
activity: longitudinal analyses from the seasonal variation of blood cholesterol study. Am J Epidemiol. 2001;153(2):172-183.
26. Nocon M, Hiemann T, Muller-Riemenschneider F, Thalau F, Roll S, Willich SN. Association of physical activity with
all-cause and cardiovascular mortality: a systematic review and meta-analysis. Eur J Cardiovasc Prev Rehabil. 2008;15(3):239-246.
27. Rosness TA, Strand BH, Bergem AL, Engedal K, Bjertness E. Associations between Physical Activity in Old Age and
Chapter 1
20
28. Garcia‐Aymerich J, Lange P, Benet M, Schnohr P, Antó JM. Regular physical activity reduces hospital admission and
mortality in chronic obstructive pulmonary disease: a population based cohort study. Thorax. 2006;61(9):772-778.
29. Kopperstad O, Skogen JC, Sivertsen B, Tell GS, Saether SM. Physical activity is independently associated with reduced
mortality: 15-years follow-up of the Hordaland Health Study (HUSK). PLoS One. 2017;12(3):e0172932.
30. Biswas A, Oh PI, Faulkner GE, et al. Sedentary time and its association with risk for disease incidence, mortality, and
hospitalization in adults: a systematic review and meta-analysis. Ann Intern Med. 2015;162(2):123-132.
31. Koster A, Caserotti P, Patel KV, et al. Association of sedentary time with mortality independent of moderate to
vigorous physical activity. PLoS One. 2012;7(6):e37696.
32. Ensrud KE, Blackwell TL, Cauley JA, et al. Objective measures of activity level and mortality in older men. J Am
Geriatr Soc. 2014;62(11):2079-2087.
33. Schmid D, Ricci C, Leitzmann MF. Associations of Objectively Assessed Physical Activity and Sedentary Time with
All-Cause Mortality in US Adults: The NHANES Study. PLoS One. 2015;10(3):e0119591.
34. Ainsworth BE, Leon AS, Richardson MT, Jacobs DR, Paffenbarger RS, Jr. Accuracy of the College Alumnus Physical
Activity Questionnaire. J Clin Epidemiol. 1993;46(12):1403-1411.
35. Sofi F, Capalbo A, Cesari F, Abbate R, Gensini GF. Physical activity during leisure time and primary prevention of
coronary heart disease: an updated meta-analysis of cohort studies. Eur J Cardiovasc Prev Rehabil. 2008;15(3):247-257.
36. Sattelmair J, Pertman J, Ding EL, Kohl HW, 3rd, Haskell W, Lee IM. Dose response between physical activity and risk
of coronary heart disease: a meta-analysis. Circulation. 2011;124(7):789-795.
37. Wang TJ, Larson MG, Levy D, et al. Temporal relations of atrial fibrillation and congestive heart failure and their joint
influence on mortality: the Framingham Heart Study. Circulation. 2003;107(23):2920-2925.
38. Williams PT. Dose-response relationship of physical activity to premature and total all-cause and cardiovascular
disease mortality in walkers. PLoS One. 2013;8(11):e78777.
39. Hoevenaar-Blom MP, Wendel-Vos GC, Spijkerman AM, Kromhout D, Verschuren WM. Cycling and sports, but not
walking, are associated with 10-year cardiovascular disease incidence: the MORGEN Study. Eur J Cardiovasc Prev Rehabil. 2011;18(1):41-47.
40. Sabia S, Dugravot A, Kivimaki M, Brunner E, Shipley MJ, Singh-Manoux A. Effect of intensity and type of physical
activity on mortality: results from the Whitehall II cohort study. Am J Public Health. 2012;102(4):698-704.
41. Hu G, Jousilahti P, Borodulin K, et al. Occupational, commuting and leisure-time physical activity in relation to
coronary heart disease among middle-aged Finnish men and women. Atherosclerosis. 2007;194(2):490-497.
42. Mozaffarian D, Furberg CD, Psaty BM, Siscovick D. Physical activity and incidence of atrial fibrillation in older adults:
the cardiovascular health study. Circulation. 2008;118(8):800-807.
43. Zheng H, Orsini N, Amin J, Wolk A, Nguyen VT, Ehrlich F. Quantifying the dose-response of walking in reducing
coronary heart disease risk: meta-analysis. Eur J Epidemiol. 2009;24(4):181-192.
44. Ridley K, Ainsworth BE, Olds TS. Development of a compendium of energy expenditures for youth. Int J Behav Nutr
Phys Act. 2008;5.
45. Tanasescu M, Leitzmann MF, Rimm EB, Willett WC, Stampfer MJ, Hu FB. Exercise type and intensity in relation to
coronary heart disease in men. JAMA. 2002;288(16):1994-2000.
46. Dong L, Block G, Mandel S. Activities Contributing to Total Energy Expenditure in the United States: Results from the
NHAPS Study. Int J Behav Nutr Phys Act. 2004;1(1):4.
47. De Smedt D, Clays E, Annemans L, et al. Health related quality of life in coronary patients and its association with
their cardiovascular risk profile: results from the EUROASPIRE III survey. Int J Cardiol. 2013;168(2):898-903.
48. Fogelholm M. Physical activity, fitness and fatness: relations to mortality, morbidity and disease risk factors. A
systematic review. Obes Rev. 2010;11(3):202-221.
49. Janssen I. Morbidity and mortality risk associated with an overweight BMI in older men and women. Obesity (Silver
Spring). 2007;15(7):1827-1840.
50. Berzon R, Hays RD, Shumaker SA. International use, application and performance of health-related quality of life
instruments. Qual Life Res. 1993;2(6):367-368.
51. Vagetti GC, Barbosa Filho VC, Moreira NB, Oliveira V, Mazzardo O, Campos W. Association between physical
activity and quality of life in the elderly: a systematic review, 2000-2012. Rev Bras Psiquiatr. 2014;36(1):76-88.
52. Bize R, Johnson JA, Plotnikoff RC. Physical activity level and health-related quality of life in the general adult
population: a systematic review. Prev Med. 2007;45(6):401-415.
53. Zhai L, Zhang Y, Zhang D. Sedentary behaviour and the risk of depression: a meta-analysis. Br J Sports Med.
2015;49(11):705-709.
54. Teychenne M, Costigan SA, Parker K. The association between sedentary behaviour and risk of anxiety: a systematic
review. BMC Public Health. 2015;15(1):513.
55. Falck RS, Davis JC, Liu-Ambrose T. What is the association between sedentary behaviour and cognitive function? A
systematic review. Br J Sports Med. 2017;51(10):800-811.
56. Sui X, Brown WJ, Lavie CJ, et al. Associations between television watching and car riding behaviors and development
of depressive symptoms: a prospective study. Paper presented at: Mayo Clinic Proceedings2015.
Introduction
21
57. Picavet HS, Pas LW, van Oostrom SH, van der Ploeg HP, Verschuren WM, Proper KI. The Relation between
Occupational Sitting and Mental, Cardiometabolic, and Musculoskeletal Health over a Period of 15 Years--The Doetinchem Cohort Study. PLoS One. 2016;11(1):e0146639.
58. Pesola AJ, Laukkanen A, Tikkanen O, Finni T. Heterogeneity of muscle activity during sedentary behavior. Appl
Physiol Nutr Metab. 2016;41.
59. Ayas NT. If You Weigh Too Much, Maybe You Should Try Sleeping More. Sleep. 2010;33(2):143-144.
60. Sperry SD, Scully ID, Gramzow RH, Jorgensen RS. Sleep Duration and Waist Circumference in Adults: A
Meta-Analysis. Sleep. 2015;38(8):1269-1276.
61. Van Den Berg JF, Van Rooij FJ, Vos H, et al. Disagreement between subjective and actigraphic measures of sleep
duration in a population-based study of elderly persons. J Sleep Res. 2008;17(3):295-302.
62. Alfaris N, Wadden TA, Sarwer DB, et al. Effects of a 2-year behavioral weight loss intervention on sleep and mood in
obese individuals treated in primary care practice. Obesity (Silver Spring). 2015;23(3):558-564.
63. Chaput JP, Drapeau V, Hetherington M, Lemieux S, Provencher V, Tremblay A. Psychobiological impact of a
progressive weight loss program in obese men. Physiol Behav. 2005;86(1-2):224-232.
64. Verhoef SP, Camps SG, Gonnissen HK, Westerterp KR, Westerterp-Plantenga MS. Concomitant changes in sleep
duration and body weight and body composition during weight loss and 3-mo weight maintenance. Am J Clin Nutr. 2013;98(1):25-31.
65. Hofman A, Brusselle GG, Darwish Murad S, et al. The Rotterdam Study: 2016 objectives and design update. Eur J
