DISSERTATIONS | JUUSO VÄISTÖ | PHYSICAL ACTIVITY, SEDENTARY BEHAVIOR, PHYSICAL FITNESS... | No 613
JUUSO VÄISTÖ
PHYSICAL ACTIVITY, SEDENTARY BEHAVIOR, PHYSICAL FITNESS AND CARDIOMETABOLIC RISK IN A POPULATION SAMPLE OF PRIMARY SCHOOL-AGED CHILDREN
Dissertations in Health Sciences
PUBLICATIONS OF
THE UNIVERSITY OF EASTERN FINLAND
uef.fi
PUBLICATIONS OF
THE UNIVERSITY OF EASTERN FINLAND Dissertations in Health Sciences
This study investigated the cross-sectional and prospective associations of physical
activity and sedentary behavior with cardiometabolic risk factors and the cross- sectional associations of cardiorespiratory
and neuromuscular fitness with adiposity in a population sample of primary school-
aged children. The results of this study provide evidence that increasing physical activity can be beneficial in the prevention of
cardiometabolic diseases since childhood.
JUUSO VÄISTÖ
PHYSICAL ACTIVITY, SEDENTARY BEHAVIOR, PHYSICAL FITNESS AND CARDIOMETABOLIC RISK
IN A POPULATION SAMPLE OF PRIMARY SCHOOL-AGED CHILDREN
THE PHYSICAL ACTIVITY AND NUTRITION IN CHILDREN (PANIC) STUDY
Juuso Väistö
PHYSICAL ACTIVITY, SEDENTARY BEHAVIOR, PHYSICAL FITNESS AND CARDIOMETABOLIC RISK
IN A POPULATION SAMPLE OF PRIMARY SCHOOL-AGED CHILDREN
THE PHYSICAL ACTIVITY AND NUTRITION IN CHILDREN (PANIC) STUDY
To be presented by permission of the Faculty of Health Sciences, University of Eastern Finland for public examination (remote)
on March 5th, 2021, at 12 o’clock noon
Publications of the University of Eastern Finland Dissertations in Health Sciences
No 613
Institute of Biomedicine, Physiology / School of Medicine University of Eastern Finland, Kuopio
2021
Series Editors
Professor Tomi Laitinen, M.D., Ph.D.
Institute of Clinical Medicine, Clinical Physiology and Nuclear Medicine Faculty of Health Sciences
Professor Tarja Kvist, Ph.D.
Department of Nursing Science Faculty of Health Sciences
Professor Ville Leinonen, M.D., Ph.D.
Institute of Clinical Medicine, Neurosurgery Faculty of Health Sciences
Professor Tarja Malm, Ph.D.
A.I. Virtanen Institute for Molecular Sciences Faculty of Health Sciences
Lecturer Veli-Pekka Ranta, Ph.D.
School of Pharmacy Faculty of Health Sciences
Distributor:
University of Eastern Finland Kuopio Campus Library
P.O.Box 1627 FI-70211 Kuopio, Finland
www.uef.fi/kirjasto
Grano Oy Jyväskylä, 2021
ISBN: 978-952-61-3730-8 (print/nid.) ISBN: 978-952-61-3731-5 (PDF)
ISSNL: 1798-5706 ISSN: 1798-5706 ISSN: 1798-5714 (PDF)
Author’s address: Physiology/Institute of Biomedicine/School of Medicine University of Eastern Finland
KUOPIO FINLAND
Doctoral programme: Doctoral Programme of Clinical Research
Supervisors: Professor Timo Lakka, M.D., Ph.D.
Physiology/Institute of Biomedicine/School of Medicine University of Eastern Finland
KUOPIO FINLAND
Docent Eero Haapala, Ph.D.
Sports and Exercise Medicine Faculty of Sport and Health Sciences University of Jyväskylä
JYVÄSKYLÄ FINLAND
Docent David Laaksonen, M.D., M.P.H., Ph.D.
Internal Medicine/Institute of Clinical Medicine University of Eastern Finland
KUOPIO FINLAND
Docent Hanna-Maaria Lakka, M.D., Ph.D.
Physiology/Institute of Biomedicine/School of Medicine University of Eastern Finland
KUOPIO FINLAND
Reviewers: Professor Tommi Vasankari, M.D., Ph.D.
UKK Institute for Health Promotion Research & Faculty of Medicine and Health Technology
Tampere University TAMPERE
FINLAND
Research Director Tuija Tammelin, Ph.D.
LIKES Research Centre for Physical Activity and Health JYVÄSKYLÄ
FINLAND
Opponent: Associate Professor Katja Pahkala, Ph.D.
Research Centre of Applied and Preventive Cardiovascular Medicine
Paavo Nurmi Centre University of Turku TURKU
FINLAND
Väistö, Juuso
Physical activity, sedentary behavior, physical fitness and cardiometabolic risk in a population sample of primary school-aged children, the Physical Activity and Nutrition in Children (PANIC) Study
Kuopio: University of Eastern Finland
Publications of the University of Eastern Finland Dissertations in Health Sciences 613. 2021, 182 p.
ISBN: 978-952-61-3730-8 (print) ISSNL: 1798-5706
ISSN: 1798-5706
ISBN: 978-952-61-3731-5 (PDF) ISSN: 1798-5714 (PDF)
ABSTRACT
The prevalence of childhood overweight and obesity has increased alarmingly in recent decades and this is a global phenomenon. It is largely a consequence of unhealthy lifestyles, such as lack of physical activity, excessive sedentary behavior, and unhealthy diet. Unhealthy lifestyles can lead to clustering of cardiometabolic risk factors, including excessive body fat, increased waist circumference, elevated fasting insulin and glucose concentrations, increased triglyceride levels, decreased high-density lipoprotein (HDL) cholesterol, and elevated blood pressure, already in childhood. Overweight and the associated accumulation of cardiometabolic risk factors in childhood predict an increased risk of developing type 2 diabetes and cardiovascular diseases in adulthood.
The purpose of this doctoral thesis was to study the associations of different types and intensities of physical activity and sedentary behavior as well as different components of physical fitness with overall cardiometabolic risk and individual cardiometabolic risk factors in a population sample of 506 Finnish children aged 6-8 years as a part of the Physical Activity and Nutrition in Children (PANIC) study. Physical activity and sedentary behavior were measured using the Actiheart® heart rate and body movement monitor and questionnaires which were filled out by the parents. Dietary factors were assessed by 4-day food
records. Cardiorespiratory fitness was assessed comprehensively i.e. by a maximal cycle ergometer exercise test and neuromuscular fitness by the 50-meter shuttle run, the 15-meter sprint run test, the hand grip test, the standing long jump test,
the sit-up test, the modified flamingo balance test, the box-and-block test, and the sit-and-reach test. Cardiometabolic risk factors included measurements of waist circumference, fasting levels of insulin and glucose, triglycerides, HDL cholesterol, blood pressure, VLDL triglycerides, VLDL cholesterol, LDL cholesterol, and HDL triglycerides.
Lower levels of physical activity, particularly unstructured physical activity, as assessed by the questionnaire, were independently associated with higher levels of cardiometabolic risk factors in children independent of possible confounding factors. The excessive use of electronic media, particularly excessive television and video viewing, was also independently associated with higher levels of
cardiometabolic risk factors in children. The cardiometabolic risk was highest in those children who were physically least active and spent most time looking at electronic media. A change in vigorous physical activity, assessed by the
Actiheart® monitor, was inversely associated and a change in sedentary time was directly associated with changes in the overall cardiometabolic risk and individual cardiometabolic risk factors over two years and these changes were independent of possible confounding factors. Higher body fat percentage and lower levels of physical activity were associated with poorer results in the 50-meter shuttle run test. Moreover, a higher body fat percentage was associated with poorer results in the standing long jump test, the sit-up test, the box-and-block test, and the
modified flamingo balance test. The associations of body fat percentage and physical activity with neuromuscular fitness were independent of each other. In addition, children with a higher body fat percentage and lower levels of physical activity had poorer results in the 50-meter shuttle run test, the 15-meter sprint run test, and the standing long jump test than other children.
Physical activity was inversely associated with body fat percentage and truncal adiposity. These relationships strengthened with increasing intensity of physical activity. Children who participated in as little as 10 minutes of vigorous physical activity had 26–30 percent less total and truncal adipose tissue than children who did not have any vigorous physical activity. Even light physical activity was inversely related to body fat percentage, but only at least moderate-to-vigorous physical activity was directly associated with cardiorespiratory fitness. By using isotemporal substitution models, it was observed that switching from 10 minutes spent in sedentary behaviors to an equivalent amount of vigorous physical activity would reduce the amount of total and truncal adipose tissue by 13 percent, a statistically significant change.
This doctoral thesis provides new insights into the associations between different levels of physical activity and physical fitness and risk factors for future cardiometabolic disorders in a general population of primary school-aged children. It observed that there is a direct association of sedentary behavior with elevated levels of cardiometabolic risk factors.
National Library of Medicine Classification: WK 880, QT 256, WS440, WA 105, WS 130
Medical Subject Headings: Adiposity; Cardiometabolic Risk Factors;
Cardiorespiratory Fitness; Child; Cholesterol, HDL; Cholesterol, LDL; Cholesterol VLDL; Exercise; Exercise Test; Finland; Insulin; Insulin Resistance; Longitudinal Studies; Pediatric Obesity; Population; Sedentary Behavior; Screen Time;
Triglycerides
Väistö, Juuso
Fyysinen aktiivisuus, kunto ja kardiometaboliset riskitekijät alakouluikäisten lasten väestöotoksessa, Lasten liikunta ja ravitsemus (PANIC)-tutkimus
Kuopio: Itä-Suomen yliopisto
Publications of the University of Eastern Finland Dissertations in Health Sciences 613. 2021, 182 s.
ISBN: 978-952-61-3730-8 (nid.) ISSNL: 1798-5706
ISSN: 1798-5706
ISBN: 978-952-61-3731-5 (PDF) ISSN: 1798-5714 (PDF)
TIIVISTELMÄ
Lasten ylipaino ja lihavuus ovat lisääntyneet huolestuttavasti viime vuosikymmeninä maailmanlaajuisesti. Tämä on seurausta erityisesti
epäterveellisistä elämäntavoista, kuten liian vähäisestä fyysisestä aktiivisuudesta, liiallisesta paikallaanolosta ja epäterveellisestä ravitsemuksesta. Epäterveelliset elämäntavat voivat johtaa kardiometabolisten riskitekijöiden eli kehon liiallisen rasvapitoisuuden, suurentuneen vyötärönympäryksen, kohonneen paastoveren insuliinin ja glukoosin, suurentuneiden triglyseridien, pienentyneen HDL-
kolesterolin ja kohonneen verenpaineen kasaantumiseen jo lapsuudessa. Ylipaino ja siihen liittyvä kardiometabolisten riskitekijöiden kasautuminen lapsuudessa ennustaa kohonnutta riskiä sairastua tyypin 2 diabetekseen ja valtimotauteihin aikuisiässä.
Tässä väitöskirjatyössä tutkittiin fyysisen aktiivisuuden kunnon eri osatekijöiden ja paikallaanolon yhteyksiä kardiometaboliseen kokonaisriskiin sekä yksittäisiin riskitekijöihin 506 iältään 6-8-vuotiaan suomalaisen lapsen väestöotoksessa osana Lasten liikunta ja ravitsemus (PANIC) -tutkimusta. Liikuntaa ja paikallaanoloa mitattiin sykettä ja kehon liikkeitä mittaavalla Actiheart®-monitorilla ja kyselylomakkeilla. Lasten ravitsemusta mitattiin neljän vuorokauden
ruokapäiväkirjalla. Kardiorespiratorista kuntoa mitattiin polkupyöräergometrillä tehtyllä maksimaalisella kuormituskokeella ja neuromuskulaarista kuntoa 10 x 5 metrin sukkulajuoksu-, 15 metrin juoksu-, puristusvoima-, vauhditon pituushyppy-, vatsalihasten voima-, tasapaino-, käden hienomotoriikka- ja eteentaivutustestillä.
Kardiometaboliset riskitekijät määritettiin laboratoriokokein ja -mittauksin, joista
tärkeimmät olivat vyötärönympärysmitta, paastoveren insuliini ja glukoosi, paastoveren triglyseridit ja HDL-kolesteroli sekä systolinen- ja diastolinen verenpaine, VLDL:n triglyseridit, VLDL- ja LDL-kolesteroli sekä HDL:n triglyseridit.
Tutkimus osoitti poikkileikkausasetelmassa, että itseraportoitu liikunta ja erityisesti omatoiminen liikunta olivat käänteisesti yhteydessä tyypin 2 diabeteksen ja valtimotautien riskitekijöihin lapsilla. Myös itseraportoidulla viihdemedian käytöllä ja erityisesti television ja videoiden katselulla oli suora yhteys näihin riskitekijöihin lapsilla. Riskitekijöiden tasot olivat korkeimmat lapsilla, jotka liikkuivat vähiten ja käyttivät eniten aikaa viihdemediaan. Itseraportoidulla runsaalla viihdemedian käytöllä oli suorat yhteydet riskitekijöihin paitsi vähän itseraportuidusti liikkuvilla niin myös paljon itseraportoidusti liikkuvilla lapsilla.
Reippaan fyysisen aktiivisuuden muutoksella oli käänteinen yhteys ja paikkallaanolon muutoksella oli suora yhteys tyypin 2 diabeteksen ja
valtimotautien kokonaisriskin ja yksittäisten riskitekijöiden muutoksiin kahden vuoden seurannan aikana riippumatta mahdollisista sekoittavista tekijöistä.
Korkeampi rasvaprosentti ja vähäisempi liikunta olivat yhteydessä huonompiin tuloksiin 10 x 5 metrin sukkulajuoksutestissä. Korkeampi rasvaprosentti oli lisäksi yhteydessä huonompiin tuloksiin vauhdittomassa pituushypyssä,
vatsalihastestissä, käden hienomotoriikkatestissä ja tasapainotestissä.
Rasvaprosentin ja liikunnan yhteydet fyysiseen kuntoon olivat toisistaan
riippumattomia. Lisäksi lapsilla, joilla oli korkea rasvaprosentti ja jotka liikkuivat vähän, oli muita lapsia huonommat tulokset 10 x 5 metrin sukkulajuoksutestissä, 15 metrin juoksutestissä ja vauhdittomassa pituushypyssä.
Fyysisellä aktiivisuudella oli käänteinen yhteys koko kehon ja keskivartalon rasvan määrään lapsilla. Nämä yhteydet olivat sitä voimakkaampia mitä
kuormittavampaa liikkuminen oli. Jo 10 minuuttia rasittavaa liikkumista päivittäin harrastavilla lapsilla oli 26–30 prosenttia vähemmän rasvakudosta koko kehossaan ja keskivartalossaan kuin rasittavaa liikkumista harrastamattomilla lapsilla.
Kevyelläkin liikkumisella oli käänteinen yhteys kehon rasvapitoisuuteen, mutta vasta vähintään kohtuullisesti kuormittavalla liikkumisella oli suora yhteys
kardiorespiratoriseen kuntoon. Tutkimusaineistosta laskettiin tilastollisesti, että 10 minuutin paikallaanolon vaihtaminen vastaavaan määrään rasittavaa liikkumista pienentäisi koko kehon ja keskivartalon rasvakudoksen määrää 13 prosenttia.
Tämä väitöskirja toi uutta tietoa fyysisen aktiivisuuden ja kunnon käänteisistä yhteyksistä ja paikallaanolon suorista yhteyksistä tyypin 2 diabeteksen ja
valtimotautien riskitekijöihin alakouluikäisillä lapsilla.
Luokitus: WK 880, QT 256, WS440, WA 105, WS 130
Yleinen suomalainen ontologia: fyysinen aktiivisuus; fyysinen kunto;
interventiotutkimus; kolesteroli; kouluikäiset; lapsuus; lihavuus; liikunta;
metabolinen oireyhtymä; rasvaprosentti; riskitekijät; sydän- ja verisuonitaudit;
terveyskäyttäytyminen; ylipaino
“Those who think they have no time for bodily exercise will sooner or later have to find time for illness.”
Edward Stanley, 15th Earl of Derby, British statesman.
(The Conduct of Life, address at Liverpool College, 20th of December 1873)
ACKNOWLEDGEMENTS
This study was carried out in the Institutes of Biomedicine at the University of Eastern Finland as a part of the Physical Activity and Nutrition in Children (PANIC) Study.
First of all, I want to owe my deepest gratitude to my principal supervisor, Professor Timo Lakka, for his expertise in this research area, excellent guidance and advice. Even despite the fact that he sometimes thinks that almost everything was better before, in “the good old days”. I greatly admire his ability to think big and see things far into the future, although this sometimes extends too far and can put pressure not only on himself but also others in the team. As a research group leader, he leads the team from the front; he also excels through his crucial ability to know what matters and what doesn't. Referring to Lieutenant Koskela's famous statement in Väinö Linna’s the Unknown Soldier ”When duty calls, we react, when bunk calls, we relax.” This describes best his attitude to life and work.
One more time, a big thanks to “Tiger” for providing me with the opportunity to undertake these PhD studies as part of the PANIC Study, encouraging me and challenging me to do my best. I have learned so much from you about scientific research, physiology, and epidemiology and working under your guidance has developed me a lot as a researcher.
Secondly, I would like to express my gratitude to my second supervisor Docent Eero Haapala from the University of Jyväskylä. Without Eero’s clear guidance throughout this work, I would have been in trouble. Trust me, we do not all have the same 24 hours in a day. Eero is one of those people who has more than 24 hours in a day. On top of all that, he has an insatiable thirst for knowledge as well as a desire and ability to do excellent science. Thank you Eero - the best research paper is yet to come!
I wish to thank also my other supervisors Docent David Laaksonen and Docent Hanna-Maaria Lakka. Their comments were very valuable and helped to see this thesis through to completion.
Publications are the bedrock of this dissertation. Therefore, I want to thank all my collaborators and co-authors. Your comments and ideas were invaluable.
Docent Aino-Maija Eloranta, Docent Anna Viitasalo, Tuomo Tompuri, M.D. M.Sc., Niina Lintu, Ph.D., Panu Karjalainen M.Sc., Eeva-Kaarina Lampinen, M.Sc., Docent Jyrki Ågren, Docent Virpi Lindi, Theresia M. Schnurr, Ph.D., Associate Professor
Professor Søren Brage, Docent Arja Sääkslahti, Paul J. Collings, Ph.D., Katrien Wijndaele, Ph.D., Andrew J. Atkin, Ph.D., and Professor Tomi Laitinen.
The greatest thanks go to the present and former members of the PANIC research team. A great workplace is like a family, so I am happy that even though I will not see all of you every day, we’ll still be part of each other’s lives through our research work. You have been invaluable workmates; many of you have been also invaluable co-authors in our publications. In addition to the co-authors mentioned earlier, I was lucky to be able to work with the world’s most diligent research secretary Merja Atalay, the elite team of research nurses Kirsi Saastamoinen and Tuula-Riitta Mutanen, three geniuses of nutrition Sanna Kiiskinen, M.Sc., Taisa Sallinen, Ph.D., and Henna Jalkanen, M.Sc., two wonderful social pediatricians Aino Mäntyselkä, M.D., Ph.D., and Saija Savinainen, M.D., a stellar star in general
medicine and bone research Sonja Soininen, M.D., Ph.D., a great physiologist, researcher and teacher Docent Mustafa Atalay, and finally the grand old man of dentistry and oral physiology and the best fisherman in Kitkajoki, Professor Matti Närhi.
I sincerely express my thanks to this thesis preliminary examiners Professor Tommi Vasankari and Research Director Tuija Tammelin, Ph.D., for the valuable comments which improved this thesis.
The staff in the Institute of Biomedicine are warmly acknowledged for their advice, support, and collaboration. I want to also thank the children and their families who volunteered to participate in the PANIC Study. I would also like to take this opportunity to extend my sincere gratitude to the MRC Epidemiology Unit at the University of Cambridge for your efforts in the objective physical activity data processing.
Furthermore, I am happy that I had the opportunity to work as a part of DigiCenter North Savo team. It has been a great pleasure and privilege to work with the entire DigiCenter team.
I would like to give warm thanks to emeritus lecturer Ewen MacDonald, Ph.D., for the proof-reading and language revision of this thesis.
Big thanks to the Julkula boys (also those who did not live in Julkula) for a lifelong friendship. You have been prepared me well for the thesis’ public defence.
You have been an important part of my life, and I am very grateful to all of you that our friendship has lasted for decades despite the distance.
My deepest thanks goes to my family. To the greatest love of my life Lissu, I express my deepest gratitude for your endless love and support and for reminding me of the most important things in life every day. You and our dog Papu bring so
much joy and happiness to my life. Thank you, my dear parents Sirpa and Jukka, and brother Panu, for your endless support and encouragement throughout my life. Without your love and support, this would not have been possible. For my passed away grandparents Meeri and Pentti for your love and caring during my childhood. In addition, I want to express my deepest thanks to my 93-year-old grandmother Kaisu, who is living proof of the health benefits of regular exercise, for her love, caring and encouragement during my life. To my passed away mother-in-law Kaija and Erkki, you were an important part of my life for many years, especially I want to thank you as parents for bringing Lissu into this world and raising her to be the perfect woman that she is. Also warm thanks to my sister-in-law Kati and brother-in-law Tipi and their families for their support and friendship. Thank to all my godchildren that I can be a part of their lives. I would also like to thank all my relatives, aunts, uncles, and cousins for their
encouragement.
This thesis is part of the results of Digiteknologian TKI-ympäristö project A74338 (funded by the European Regional Development Fund and the Regional Council of Pohjois-Savo). I was fortunate to receive financial support for this work from the Doctoral Programme of Clinical Research in the University of Eastern Finland, the Finnish Cultural Foundation, and the Juho Vainio Foundation. I am grateful to the above institutions for believing in my research work.
Kuopio, January 2021
Juuso Väistö
LIST OF ORIGINAL PUBLICATIONS
This dissertation is based on the following original publications:
I Väistö J, Eloranta A-M, Viitasalo A, Tompuri T, Lintu N, Karjalainen P, Lampinen E-K, Ågren J, Laaksonen DE, Lakka H-M, Lindi V†, Lakka TA. Physical activity and sedentary behaviour in relation to cardiometabolic risk in children: cross- sectional findings from the Physical Activity and Nutrition in Children (PANIC) Study. International Journal of Behavioral Nutrition and Physical Activity. 2014;
11: 55.
II Väistö J, Haapala EA, Viitasalo A, Schnurr TM, Kilpeläinen TO, Karjalainen P, Westgate K, Lakka H-M, Laaksonen DE, Ekelund U, Brage S, Lakka TA.
Longitudinal associations of physical activity and sedentary time with cardiometabolic risk factors in children. Scandinavian Journal of Medicine &
Science in Sports. 2019; 29: 113–123.
III Haapala EA, Väistö J, Lintu N, Tompuri T, Brage S, Westgate K, Ekelund U, Lampinen E-K, Sääkslahti A, Lindi V†, Lakka TA. Adiposity, physical activity and neuromuscular performance in children. Journal of Sports Sciences. 2016; 34:
1699–1706.
IV Collings PJ, Westgate K, Väistö J, Wijndaele K, Atkin AJ, Haapala EA, Lintu N, Laitinen T, Ekelund U, Brage S, Lakka TA. Cross-Sectional Associations of Objectively-Measured Physical Activity and Sedentary Time with Body Composition and Cardiorespiratory Fitness in Mid-Childhood: The PANIC Study. Sports Medicine. 2017; 47: 769-780.
The publications were adapted with the permission of the copyright owners.
CONTENTS
ABSTRACT ... 7 TIIVISTELMÄ ... 11 ACKNOWLEDGEMENTS ... 17 1 INTRODUCTION ... 29 2 REVIEW OF THE LITERATURE ... 33 2.1 Metabolic syndrome ... 33 2.1.1 A brief history of metabolic syndrome in adults and children ... 33 2.1.2 Definitions of pediatric metabolic syndrome ... 35 2.1.3 Prevalence of metabolic syndrome ... 37 2.1.4 Pathogenesis of pediatric metabolic syndrome ... 38 2.2 Independent cardiometabolic risk factors in children ... 39 2.2.1 Overweight and obesity ... 39 2.2.2 Insulin resistance and impaired glucose metabolism ... 40 2.2.3 Dyslipidemia ... 41 2.2.4 Elevated blood pressure ... 41 2.2.5 Other cardiometabolic risk factors ... 42 2.3 Physical activity ... 43 2.3.1 Definition of physical activity among children ... 43 2.3.2 Assessment of physical activity among children ... 43 2.3.3 Status and trends of physical activity levels among school-aged
children and adolescents ... 44 2.3.4 Associations of physical activity with cardiometabolic risk
factors ... 45 2.4 Sedentary behavior ... 49 2.4.1 Definition of sedentary behavior among children ... 49 2.4.2 Assessment of sedentary behavior among children ... 49 2.4.3 Associations of sedentary behavior with cardiometabolic risk
factors ... 50 2.5 Cardiorespiratory and neuromuscular fitness ... 53 2.5.1 Definition of cardiorespiratory and neuromuscular fitness ... 53 2.5.2 Assessment of cardiorespiratory and neuromuscular fitness ... 53 2.5.3 Associations of cardiorespiratory and neuromuscular fitness with
cardiometabolic risk factors ... 53
3 AIMS OF THE STUDY ... 57 4 PHYSICAL ACTIVITY AND SEDENTARY BEHAVIOUR IN RELATION TO
CARDIOMETABOLIC RISK IN CHILDREN ... 59 4.1 Abstract ... 59 4.2 Background ... 60 4.3 Methods... 61 4.3.1 Study design and study population ... 61 4.3.2 Assessment of physical activity and sedentary behaviour ... 61 4.3.3 Assessment of dietary factors ... 62 4.3.4 Assessment of cardiometabolic risk factors ... 62 4.3.5 Statistical analyses... 63 4.4 Results ... 64 4.4.1 Basic characteristics ... 64 4.4.2 Independent associations of different types of PA with
cardiometabolic risk factors ... 65 4.4.3 Independent associations of different types of SB with
cardiometabolic risk factors ... 66 4.4.4 Combined associations of total PA and EMT with the
cardiometabolic risk score ... 70 4.5 Discussion ... 74 4.6 Conclusions ... 76 4.7 Acknowledgements ... 76 4.8 Additional information ... 76 4.8.1 Competing interests ... 76 4.8.2 Authors’ contributions ... 77 5 LONGITUDINAL ASSOCIATIONS OF PHYSICAL ACTIVITY AND SEDENTARY
TIME WITH CARDIOMETABOLIC RISK FACTORS IN CHILDREN ... 79 5.1 Abstract ... 79 5.2 Introduction ... 80 5.3 Methods... 81 5.3.1 Study design and study population ... 81 5.3.2 Assessment of PA and ST ... 81 5.3.3 Assessment of cardiometabolic risk factors and calculation of
cardiometabolic risk score ... 82 5.3.4 Assessment of pubertal status ... 83 5.3.5 Statistical analysis ... 83 5.4 Results ... 84 5.4.1 Basic characteristics ... 84
5.4.2 Cross-sectional associations at baseline ... 86 5.4.3 Longitudinal associations during 2-year follow-up ... 88 5.5 Discussion ... 92 5.6 Conclusion ... 94 5.7 Perspectives ... 94 5.8 Research ethics ... 95 5.9 Acknowledgments ... 95 5.10 Ethical approval ... 95 6 ADIPOSITY, PHYSICAL ACTIVITY, AND NEUROMUSCULAR PERFORMANCE
IN CHILDREN ... 97 6.1 Abstract ... 97 6.2 Introduction ... 97 6.3 Methods... 98 6.3.1 Study design and study population ... 98 6.3.2 Assessment of body size and composition ... 99 6.3.3 Assessment of physical activity ... 99 6.3.4 Neuromuscular performance ... 100 6.3.5 Other assessments ... 101 6.3.6 Statistical methods ... 102 6.4 Results ... 103 6.4.1 Characteristics of children ... 103 6.4.2 Independent associations of body fat percentage and physical
activity with neuromuscular performance ... 105 6.4.3 Combined associations of body fat percentage and objectively
assessed physical activity with neuromuscular performance ... 107 6.5 Discussion ... 109 6.6 Acknowledgement ... 111 6.7 Footnotes ... 111 7 CROSS-SECTIONAL ASSOCIATIONS OF OBJECTIVELY-MEASURED PHYSICAL
ACTIVITY AND SEDENTARY TIME WITH BODY COMPOSITION AND
CARDIORESPIRATORY FITNESS IN MID-CHILDHOOD ... 113 7.1 Abstract ... 113 7.2 Key points ... 114 7.3 Introduction ... 115 7.4 Subjects and methods ... 116 7.4.1 Sample ... 116 7.4.2 Assessment of body size and composition ... 116
7.4.3 Assessment of cardiorespiratory fitness ... 117 7.4.4 Assessment of physical activity and sedentary time ... 117 7.4.5 Other assessments ... 118 7.4.6 Statistics ... 119 7.5 Results ... 120 7.5.1 Sample description ... 120 7.5.2 Cumulative intensity analyses ... 125 7.5.3 Categorical analyses and isotemporal substitution models ... 128 7.6 Discussion ... 130 7.7 Conclusion ... 133 7.8 Notes ... 133 7.8.1 Acknowledgments ... 133 7.8.2 Authors contributions ... 134 7.8.3 Compliance with ethical standards ... 134 7.8.4 Ethical approval ... 134 7.8.5 Informed consent ... 134 8 GENERAL DISCUSSION ... 135 8.1 Summary ... 135 8.1.1 Study design and population ... 135 8.1.2 Cross-sectional findings ... 138 8.1.3 Longitudinal findings ... 139 8.2 Strengths and limitations of the study ... 139 8.3 Perspectives ... 140 9 CONCLUSIONS ... 143 REFERENCES ... 144
ABBREVIATIONS
BMI Body mass index
CRF Cardiorespiratory fitness
DXA Dual-energy X-ray absorptiometry
EMT Electronic media time
FFM Fat-free mass
FFMI Fat-free mass index
FMI Fat mass index
HDL High-density lipoprotein
HOMA Homeostatic Model Assessment
IDF International Diabetes Federation
LDL Low-density lipoprotein
LPA Light physical activity MET Metabolic equivalent of task
MetS Metabolic syndrome
MPA Moderate physical activity
MVPA Moderate-to-vigorous physical activity
NAFLD Non-alcoholic fatty liver disease
NMF Neuromuscular fitness
PA Physical activity
PAEE Physical activity energy expenditure
SB Sedentary behavior
ST Sedentary time
TFMI Trunk fat mass index
TG Triglycerides
VPA Vigorous physical activity
WHO World Health Organization
1 INTRODUCTION
Childhood obesity has reached epidemic proportions on a global scale and has emerged as one of the leading public health problems since it increases the risk of chronic cardiometabolic diseases (1–3). The prevalence of overweight and obesity has steadily increased in recent decades among children of all ages and young people also in Finland. Over 15% of Finnish pre-school age girls and 7.5% of boys of the same age are overweight or obese (4,5). In the United States and many other high-income countries, the growth rate of childhood obesity has become decelerated during the past few years and the prevalence of obesity has
plateaued, but nonetheless the number of children with overweight and obesity has remained alarmingly high (6–9).
Children and adolescents with overweight and obesity are prone to develop many chronic diseases or disorders later in life such as metabolic syndrome (MetS), non-alcoholic fatty liver disease, type 2 diabetes (T2D), and cardiovascular diseases (10–13). Independent factors that increase the risk of these metabolic and cardiovascular diseases are called cardiometabolic risk factors. These risk factors include the accumulation of excessive fat tissue, especially in the central body area, insulin resistance, impaired glucose tolerance, dyslipidemia, and elevated blood pressure (Figure 1). The simultaneous occurrence of cardiometabolic risk factors in an individual can be described with the term MetS (14). It is noteworthy that childhood obesity also causes adverse metabolic changes and clustering of independent cardiometabolic risk factors that meet the characteristics of MetS.
There have been numerous diagnostic criteria proposed for children's MetS (15–
19) but there was no consensus on the preferred criteria until 2007 (20). There are also dissenting opinions about whether the diagnosis of MetS is in general
necessary among children because of their drastic changes in body size and composition with age and development. Therefore, the International Diabetes Federation (IDF) recommends that the MetS should not be diagnosed in children younger than 10 years (20).
There is a high probability that overweight and cardiometabolic risk factors in childhood and adolescence will remain in adulthood, and therefore effective interventions addressing these risk factors should be implemented as early as possible (21–23). The most important reasons for an individual becoming overweight, obesity and other cardiometabolic risk factors are an unhealthy diet
and physical inactivity, in other words, too much unhealthy food, too little physical activity (PA), and excessive time spent doing sedentary activities (Figure 1).
The role of PA in preventing and treating obesity and other cardiometabolic risk factors has been increasingly clarified in the past few years (23). PA has been identified as one of the major protective factors for cardiometabolic diseases, and physical activity interventions have been found to be effective in reducing the cardiometabolic risk (24). In addition, PA can improve the overall health and life quality of people of all ages and can be used in the primary and secondary prevention not only of cardiometabolic diseases but also of many other chronic diseases and conditions (25).
According to the Finnish PA recommendations, children and adolescents aged 7-18 years should have at least 60 minutes of moderate-to-vigorous PA (MVPA) daily (26). The international recommendations are essentially parallel and, likewise the World Health Organization (WHO) recommends 60 minutes of MVPA daily for children and adolescents (27), but there are also some country-specific differences in PA recommendations. Worryingly, it has been estimated that only about every third child meets the current recommendations for PA. In addition, there is a lack of evidence on the required volume, intensity, and type of PA needed to achieve the optimal beneficial effect on cardiometabolic risk factors among children.
The objectives of this doctoral thesis were to investigate both cross-sectional and prospective associations of PA, sedentary time (ST), cardiorespiratory fitness (CRF), and neuromuscular fitness (NMF) with adiposity and other cardiometabolic risk factors among Finnish primary-school children. This doctoral thesis provides novel information on these associations in a population sample of children 6–8 years of age who participated in the baseline examinations of the Physical Activity and Nutrition in Children (PANIC) study; they were followed-up for two years and underwent comprehensive and objective assessments of PA, ST, CRF, NMF, cardiometabolic risk factors, and possible confounding factors.
Figure 1. Causes and consequences of cardiometabolic risk factors and their clustering.
2 REVIEW OF THE LITERATURE
2.1 METABOLIC SYNDROME
2.1.1 A brief history of metabolic syndrome in adults and children
In the 18th century, an Italian anatomist Giovanni Battista Morgagni (25 Feb 1682 – 6 Dec 1771) discovered a link between abdominal obesity, hypertension,
hyperuricemia, atherosclerosis, and obstructive sleep apnea (28). Later in the 20th century during the First World War, two Austrian physicians Karl Hitzenberger and Martin Richter-Quittnerr made an observation dealing with metabolic
abnormalities among their patients but could not publish their results until the end of the war. At about the same time, a Swedish physician Eskil Kylin and a Spaniard physician Gregorio Marañon published papers about the common coexistence of hypertension and diabetes mellitus in adults. During the next decades, many researchers reported observations on the clustering of cardiovascular and metabolic disorders. (29)
In the late 20th century in 1988, Gerald M. Reaven made MetS generally known and named it as “syndrome X”. According to his findings, Professor Reaven formed a hypothesis on a cluster of metabolic abnormalities that was associated with a greatly increased risk of cardiovascular diseases (30). One year later Doctor Norman Kaplan added an important factor, central adiposity, into the cluster of metabolic abnormalities proposed by Reaven. Kaplan summarized four typical characteristics, i.e. central adiposity, impaired glucose tolerance,
hypertriglyceridemia, and hypertension, in his formula of the MetS and named it
“the deadly quartet” (31). The identification of “the deadly quartet” led to the appreciation that the accumulation of these cardiometabolic risk factors could significantly increase the risk of developing several different cardiometabolic diseases (32,33). Therefore, early prevention and identification of these cardiometabolic risk factors were also understood to be of great clinical significance.
There was no unified definition for MetS until the end of the 20th century when WHO published a report on the definition and classification of diabetes mellitus and its complications. The definition of MetS by WHO includes impaired glucose regulation or diabetes and/or insulin resistance together with two or more of the following risk factors: raised arterial pressure (≥ 140/90 mmHg), increased plasma
triglycerides (≥ 1.7 mmol l-1) and/or low plasma high-density lipoprotein (HDL) cholesterol (men: ≤ 0.9 mmol l-1; women: ≤ 1.0 mmol l-1), central obesity (men:
waist to hip ratio > 0.90; women > 0.85; and/or BMI > 30 kg/m-2), and microalbuminuria (urinary albumin excretion rate > 20 μg min-1 or
albumin:creatinine ratio ≥ 30 mg g-1) (34,35). About one year later, the European Group for the study of Insulin Resistance (EGIR) published their own definition for MetS. The definition issued by EGIR was similar to that of WHO and included insulin resistance plus two or more of central obesity, dyslipidemia, hypertension, and increased fasting plasma glucose, but this was never widely used
internationally (36). Many other organizations also published their definitions of MetS after WHO and EGIR.
The IDF finally released a universal consensus workshop-based definition for MetS in 2005. The purpose was to harmonize several existing MetS criteria, and the IDF largely succeeded in achieving that goal. One other major reason for publishing the IDF definition was that the earlier definitions never provided exact and clear clinical criteria for MetS and the comparison between data used in earlier definitions was difficult because of the different characteristics used to identify MetS (14,37). IDF defined MetS in adults as a cluster of the most
dangerous risk factors for type 2 diabetes and cardiovascular disease, including abdominal obesity, increased plasma cholesterol, elevated blood pressure, increased fasting plasma glucose level, and diabetes if not already diagnosed (38).
After IDF published its definition of adult MetS, the next step was a demand for children’s definitions due to the growing epidemic of pediatric obesity (20). Similar to adults, there was no unified definition to assess the risk or existence for MetS in youngsters, and the existing adults’ definitions were not felt appropriate for children and adolescents. In 2007, IDF published a definition of MetS for children and adolescents that was based on data from previous studies using modified adult criteria. In the definition of pediatric MetS, IDF suggested that the syndrome should not be diagnosed among children under 10 years of age. For children 10-16 years of age, the definition included abdominal obesity and two or more of
increased plasma triglycerides, decreased plasma HDL cholesterol, raised blood pressure, and elevated plasma glucose. For adolescents older than 16 years, IDF recommended the use of adult criteria but mentioned that more research would be needed to find an optimum definition. (20) Despite the IDF definition, there is still no international consensus for children’s and adolescents’ MetS. For example, the American Heart Association refused to define pediatric MetS (39). However,
the IDF definition for pediatric MetS is still most widely used and is the closest to having gained an international consensus.
2.1.2 Definitions of pediatric metabolic syndrome
According to IDF’s criteria for MetS, obesity and insulin resistance are the essential components of MetS among children (20). As mentioned earlier, notwithstanding several attempts to define pediatric MetS, researchers have not succeeded in devising a clear unanimous definition or diagnostic criteria that would have been accepted all over the world (Table 1). The challenge among children and
adolescents is that it is complicated to establish the definitions for MetS due to the many physiological and methodological confounding factors. For example,
pubertal status and development, age, sex, and race have an effect on each component of the MetS among children and adolescents. Therefore, it seems to be more appropriate to use a continuous risk score for MetS among children and adolescents than to apply criteria that are based on artificial cut-offs for the individual features of MetS used in adults (40–44). None of the definitions for children’s and adolescents’ MetS has been fully validated among children and adolescents. Therefore, it has been stated that it would be better to focus on the prevention and treatment of the individual cardiometabolic risk factors to avoid clustering of these risk factors rather than the diagnostics of MetS (45,46).
36 Table 1. Definitions for children’s and adolescents’ MetS. Definition Criteria Age (ys) GlucoseBMI Waist circumference Triglycerides HDL cholesterol Blood pressure Cook et al. 2003 (15)≥3 of following 12-19 ≥6.1 mmol/l ≥90th percentile ≥1.2 mmol/l ≤1.03 mmol/l ≥90th percentile of SBP or DBP De Ferranti et al. 2004 (16) ≥3 of following 12-19 ≥6.1 mmol/l ≥75th percentile ≥1.1 mmol/l <1.3 mmol/l (for boys 15-19 years <1.17 mmol/l)
≥90th percentile of SBP or DBP Cruz et al. 2004 (17)≥3 of following 8-13 IGT (ADA criterion)≥90th percentile ≥90th percentile ≤10th percentile ≥90th percentile of SBP or DBP) Weiss et al. 2004 (18)≥3 of following 4-20 IGT (ADA criterion)BMI-Z score ≥2.0≥95th percentile ≤5th percentile≥95th percentile of SBP or DBP) Ford et al. 2005 (19)≥3 of following 12-17 ≥6.1 mmol/l ≥90th percentile ≥1.2 mmol/l ≤1.03 mmol/l ≥90th percentile of SBP or DBP Viner et al. 2005 (47)≥3 of following 2-18≥6.1 mmol/l ≥95th percentile≥1.7 mmol/l ≤0.9 mmol/l ≥95th percentile of SBP IDF definition 2007 (20)Obesity and ≥2 of following
10-15 ≥5.6 mmol/l or family history of MetS or T2D or a related disorder.
≥90th percentile or adult cut-off if lower
≥1.7 mmol/l <1.03 mmol/l SBP ≥130 or DBP ≥85 mm Hg IDF definition 2007 (20)Obesity and 2 of following
≥16 (Use IDF criteria for adults MetS)
≥5.6 mmol/l or family history of MetS or T2D or a related disorder.
≥94 cm for males and ≥80 cm for women
≥1.7 mmol/l <1.03 mmol/l for males and <1.29 mmol/l for women
SBP ≥130 or DBP ≥85 mm Hg (or hypertension treatment) Ahrens et al. 2014 (48)≥3 of following 2-<11 ≥90th percentile (or ≥90th percentile of HOMA-insulin resistance)
≥90th percentile ≥90th percentile (or HDL cholesterol ≤10th percentile)
≤10th percentile (or triglycerides cholesterol ≥90th percentile)
≥90th percentile of SBP or DBP BMI, body mass index; HDL, high-density lipoprotein; IGT, impaired glucose tolerance; SBP, systolic blood pressure; DBP, diastolic blood pressure
2.1.3 Prevalence of metabolic syndrome
It is difficult to estimate the prevalence of children’s and adolescents’ MetS because there are no established criteria for its diagnosis. Nonetheless, several study groups have reported the prevalence of MetS especially among obese children or adolescents when applying their own definitions, commonly used pediatric definitions (Table 1), or modified definitions utilized for adults.
Regardless of the inconsistent definitions, some high-quality studies have provided an indication of the prevalence of children’s and adolescents’ MetS. The prevalence of MetS is highest in overweight and obese children and increases with the degree of adiposity. (49–51) In a North American cohort of 3385 adolescents aged 12-19 years, the prevalence of MetS was 19-35% among obese youngsters compared to less than 2% in their normal-weight peers (50). A systematic review from 85 studies examining children and adolescents aged 7-19 years showed that the median prevalence of MetS in the whole study population was 3.3%; this value for the prevalence of MetS among overweight children was higher i.e. 11.9%; and in obese children it was even higher, 29.2% (49). The prevalence of MetS was higher in boys (5.1%) than in girls (3.0%) and in older children (5.6%) than in younger children (2.9%) (49).
In a large Identification and prevention of Dietary- and lifestyle-induced health EFfects In Children and infantS (IDEFICS) study among 18 745 European children aged 2-11 years, the researchers estimated the prevalence of pediatric MetS by using reference standards obtained in the study and devised their own definition of MetS and compared it with three commonly used definitions of MetS among children (15,20,47). The prevalence of pediatric MetS varied in the IDEFICS cohort between 0.3% and 1.5% among girls and between 0.4% and 1.3% among boys using these three commonly used definitions (15,20). The researchers also proposed two decision levels for the definition of children’s MetS. The first level was considered to require a close observation and was called as a monitoring level and the second level was considered to require an intervention and was termed as an action level. They observed that the prevalence of MetS was 2.1% in girls and 1.5% in boys based on the action level and 5.9% in girls and 5.1% in boys based on the monitoring level (48).
The prevalence of pediatric MetS is increasing in parallel with the increasing rates of obesity, MetS is relatively uncommon among non-obese children, and the existence of pediatric MetS has often been even questioned regardless of the different definitions (49,52–55). The prevalence of overweight and obesity has
the National Institute for Health and Welfare of Finland initiated a research project with the aim of investigating, monitoring, and reporting the prevalence of
overweight and obesity among children between 2 and 16 years of age. In this project, researchers collect real-time data from the register of Primary Health Care Visits (Avohilmo) (57). According to the latest report of 96 341 Finnish children, about 25% of boys and about 16% of girls were overweight or obese according to the Finnish ISO-BMI criteria (58). Seven percent of the boys and 3% of the girls were classified as obese by applying these criteria. Using the International Obesity Task Force (IOTF) criteria for overweight and obesity (59) about 19% of the girls and the boys were classified as overweight, and 4% of the girls and 5% of the boys were defined as being obese (60).
2.1.4 Pathogenesis of pediatric metabolic syndrome
Understanding some progress has been made in clarifying the pathogenesis of pediatric MetS (Figure 2). According to the current knowledge, insulin resistance, excessive body adiposity, and inflammation are the core factors underlying the pathogenesis of pediatric MetS. Insulin is secreted by the pancreatic β cells from where it is transported via the portal system to the liver and suppresses glucose production in the liver. In a situation of insulin resistance, the suppression of glucose production is impaired which leads to abnormal glucose homeostasis and this manifests as a decreased tissue response to many insulin mediated cellular actions. (61) For example, in the insulin resistant state, not all insulin mediated cellular actions are impaired (62), because hepatic lipogenesis is not impaired resulting in the release of free fatty acids and triglycerides into the circulation, leading to dyslipidemia and ectopic fat accumulation (63). Excessive fat
accumulation promotes the productions of pro-inflammatory cytokines, such as plasminogen activator inhibitor-1, tumor necrosis factor α, and interleukin 6, and acute phase reactants, such as high-sensitivity C-reactive protein and fibrinogen in adults (64). Subsequently, the excessive fat accumulation evokes a systemic low- grade inflammation. Insulin resistance becomes manifest in several organs, including skeletal muscles, the liver, and the intestine, and is thereby associated with several systemic abnormalities, including impaired glucose metabolism, dyslipidemia, and hypertension. Insulin resistance has also been related to endothelial dysfunction and hypertension but the possible causal relationships have remained unclear (64). In addition, there are many determinants of metabolic risk factor clustering. Behavioral factors, such as lack of PA, excessive ST,
insufficient sleep, and an unhealthy diet, have been associated with the clustering
of cardiometabolic risk factors among children and adolescents (65–68). These associations are modified by genetic, epigenetic and environmental factors (Figure 2). The pathogenesis of pediatric MetS is complex and characterized by a cluster of individual risk factors (Figure 2), and it is the interplay of these risk factors that strongly predicts the future risk of type 2 diabetes and cardiovascular disease (Figure 1).
Figure 2. Determinants and mechanism for the clustering of cardiometabolic risk factors.
2.2 INDEPENDENT CARDIOMETABOLIC RISK FACTORS IN CHILDREN
2.2.1 Overweight and obesity
Overweight and obesity have been considered as key factors in the pathogenesis of MetS (16,18,69,70). While the primary function of adipose tissue is to act as an energy storage, it is also an active endocrine organ (71). MetS is encountered almost exclusively among overweight and obese children and adolescents, and the
has been independently related to all components of MetS (18,74). An excessive amount of fat in the body not only evokes harmful changes in sugar and fat metabolism but it also elevates blood pressure (18). Visceral fat around the internal organs is believed to be particularly harmful for health (75–77), but there is still not unambiguous evidence of the independent significance of visceral fat in health and the effects of visceral fat on health among children (78). However, there is some evidence suggesting that increased visceral fat content could be a stronger predictor for cardiometabolic risk factors in children than in adults (78).
Obesity is indisputably a significant part of the clustering of cardiometabolic risk factors and the development of MetS already among children.
Intramyocellular and intra–abdominal fat accumulation is strongly associated with post-glucose hyperglycaemia in obese prediabetic youth (79). Adverse metabolic changes can be detected already among very young children, soon after the onset of overweight or obesity. Children aged 2-6 years who had become overweight within the last year exhibited metabolic abnormalities, including signs of non- alcoholic fatty liver disease (NAFLD) (80). Visceral fat accumulation may also increase hepatic insulin resistance (77). However, it is important to note that although obesity is one of the most important etiological factors in the
development of MetS, this does not mean that obesity inevitably leads to MetS (81). Nevertheless, many prospective studies have revealed that childhood obesity is associated with cardiovascular disease and its risk factors later in life (22,82–86).
2.2.2 Insulin resistance and impaired glucose metabolism
Insulin is a key factor in glucose metabolism and energy homeostasis in the human body. Normally after a glucose-containing meal, the plasma glucose level rises, and that triggers insulin release from the pancreatic β cells into the
circulation. The presence of insulin increases glucose uptake mainly in skeletal muscle and it also suppresses endogenous hepatic glucose production (87,88).
Insulin resistance refers to the situation where the pancreatic β cells still release insulin in response to glucose ingestion, but glucose uptake by skeletal muscle and other tissues of the human body is nonetheless inadequate (88).
Glucose and insulin metabolism disturbances, including impaired glucose tolerance and insulin resistance, are considered to be the major cardiometabolic risk factors and key components for the development of MetS among children and youth (81,89,90). It has been postulated that insulin resistance could be the most important trigger for the clustering of cardiometabolic risk factors (81,89–92), as well as being an independent predictor of MetS and its components (81,93).
The gold standard assessments of insulin resistance and impaired glucose metabolism are intravenous glucose and insulin tolerance tests. However, these invasive tests are complex and expensive to perform in large population-based studies. It is therefore common to assess insulin resistance and glucose
metabolism in such studies, particularly among children, by less invasive and less expensive surrogate measurements. The most common surrogate measurements are fasting plasma insulin and the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). HOMA-IR is a mathematical method to quantify insulin resistance that was first described by Matthews and coworkers (94).
2.2.3 Dyslipidemia
Dyslipidemia is associated with overweight and obesity in children and
adolescents (95–97). The Centers for Disease Control and Prevention in the United States analyzed the data from the National Health and Nutrition Examination Survey in 2010 and reported that 14.2% of normal weight, 22.3% of overweight and 42.9% of obese 12-19-year-old adolescents had at least one abnormal lipid level (98). Dyslipidemia is a disorder of blood lipoprotein metabolism where plasma or serum lipid concentrations or their relative proportions are abnormal (99). In essence, this means that the levels of low-density lipoprotein (LDL) cholesterol or triglycerides are elevated or the high-density lipoprotein (HDL) cholesterol concentration is too low in plasma or serum (100). Dyslipidemia is an independent risk factor for atherosclerosis and many studies have demonstrated its significant tracking from childhood into adulthood (23,101). Atherogenic
changes caused by dyslipidemia are already evident in the arterial walls of children and young adults (102). These changes rarely lead to illness during childhood, but their long-term effects on cardiovascular health in adulthood are significant (103).
Dyslipidemia could also lead to NAFLD in children (104). In this case, liver cells have accumulated an abundance of fat, especially triglycerides, and this interferes with normal liver function. NAFLD may, at worst, result in steatohepatitis, i.e., hepatic inflammation and hepatic cirrhosis (103).
2.2.4 Elevated blood pressure
Elevated blood pressure is relatively uncommon in general populations of children (105); in fact elevated blood pressure in children is usually associated with a secondary pathological factor for hypertension (106). Nonetheless, there is a clear
(107). Hypertension is twice as common in obese children, and even as many as every second hypertensive child is obese (108). The presence of elevated systolic blood pressure in childhood predicts hypertension and MetS later in life (109).
Therefore it is important to identify those children who are most at risk for the development of future hypertensive (110).
2.2.5 Other cardiometabolic risk factors
Circulating levels of biomarkers for low-grade inflammation, such as low
adiponectin concentrations, high high-sensitivity C-reactive protein concentrations, and elevated interleukin 6 (IL-6) concentrations, have been associated with
clustering of cardiometabolic risk factors and an increased risk of MetS in children and adolescents (18). C-reactive protein is an acute-phase protein whose
concentration reflects the inflammatory state of the body. Chronic low-grade inflammation is known to predict type 2 diabetes and cardiovascular diseases (111–113) and is believed to be an important factor in the pathogenesis of these diseases, particularly in the atheromatous process of arteriosclerosis and in the onset of diabetes and insulin resistance (111). Even a slightly elevated high- sensitivity C-reactive protein level has been associated with all components of MetS in adults (111) and children (18,111,114).
Adipose tissue, more specifically adipocytes, secrete many hormones, called adipokines, which have important roles in whole-body metabolism and in maintaining physiological homeostasis (115). Adiponectin is one of these
adipokines that has been found to be inversely associated with adiposity, insulin resistance, and the risk of MetS; this protein has both anti-atherogenic and anti- inflammatory properties (116,117). Leptin is another adipokine that affects many metabolic processes, including body fat mass regulation, and higher serum levels of leptin have been related to insulin resistance (118). Low serum levels of
adiponectin and high serum levels of leptin have also been associated with insulin resistance and other cardiometabolic risk factors in overweight and obese children (118). Ghrelin is a somatotropic and orexigenic hormone that increases before eating a meal and declines afterwards. Lower serum levels of ghrelin have been associated with insulin resistance among overweight children (119).
Microalbuminuria has also been associated with overall and abdominal adiposity, insulin resistance, impaired fasting glucose, increased serum LDL cholesterol and triglycerides, elevated blood pressure and an increased prevalence of MetS, and a decreased serum HDL cholesterol concentration in obese children (120).
2.3 PHYSICAL ACTIVITY
2.3.1 Definition of physical activity among children
PA means any bodily movement caused by skeletal muscles increasing energy expenditure, and it can be categorized as exercise and non-exercise PA. Exercise can involve a planned and structured activity like sports, or alternatively, it can be non-exercise PA which includes activities related to daily life without an exercise goal, such as commuting to school or work and stair climbing (121). The total PA volume is a sum of the intensity and frequency of PA and the duration of a single session of PA (122).
PA is typically divided according to its intensity energy demand into light PA (LPA), moderate PA (MPA), and vigorous PA (VPA). The energy demand of PA is usually expressed in metabolic equivalents of task (METs). (123) One MET refers to the energy cost of an average adult when he or she is sitting at rest and
corresponds to an oxygen uptake of approximately 3.5 ml O2·kg−1·min−1 (124).
The MET value of each PA denotes the energy expenditure of the activity multiplied by resting energy expenditure. In adults, LPA, MPA, and VPA are
typically defined as the time spent at intensities >1.5 and ≤3.0 METs, >3.0 and ≤6.0 METs, and >6.0 METs, respectively (123).
In pediatric populations, age-specific MET values for PA are recommended because the basal metabolic rate per body mass is higher in children than in adults, mainly because of their growth and maturation (125). Moreover, PA is usually not as planned and structured in children as in adults, and children’s PA is typically intermittent and includes spontaneous bouts of PA of varying intensity (126,127).
2.3.2 Assessment of physical activity among children
The measures of PA can be divided into device-based and self-reported measurements (122). Self-reported questionnaires, interviews, and diaries as subjective assessments are appropriate choices when the quality of PA or PA as a behavior in large study populations need to be assessed (128). Device-based measures, such as heart rate monitors and accelerometers, are good methods with which to assess the amount, intensity, and energy expenditure of PA (129).
Questionnaires are commonly used methods to assess PA because they allow the assessment of large study populations easily and at low cost (130). While
