Obesity as a mediator between physical fitness and cardiometabolic risk in children

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(1)Department of Nursing, Physiotherapy and Occupational Therapy. Obesity  as  a  mediator  between   physical  fitness  and  cardiometabolic   risk  in  children.                         La obesidad como mediador entre la condición física y el riesgo cardiometabólico en niños.. DOCTORAL THESIS Supervised by Dra. Mairena Sánchez López and Dr. Vicente Martínez Vizcaíno. ANA DÍEZ FERNÁNDEZ Ciudad Real, Spain 2014.

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(3) Departamento de Enfermería, Fisioterapia y Terapia Ocupacional. La  obesidad  como  mediador  entre  la   condición  física  y  el  riesgo   cardiometabólico  en  niños.             Obesity as a mediator between physical fitness and cardiometabolic risk in children.. TESIS DOCTORAL. Dirigida por la Dra. Mairena Sánchez López y el Dr. Vicente Martínez Vizcaíno. ANA DÍEZ FERNÁNDEZ Ciudad Real, España 2014.

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(9) A María José y Enrique, los pilares de mi vida.

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(11) “También será posible que esa hermosa mañana, ni tú, ni yo ni el otro la lleguemos a ver, pero habrá que empujarla para que pueda ser.” Canto a la Libertad, José Antonio Labordeta.

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(13) Contents   TABLES  INDEX  .......................................................................................................................................  1   FIGURES  INDEX  .....................................................................................................................................  3   Abbreviations  ........................................................................................................................................  5   Presentation  ..........................................................................................................................................  9   1.  Introduction  ....................................................................................................................................  13   2.  Framework  for  the  question  ......................................................................................................  33   2.1  Framework  for  the  question  ........................................................................................................  35   2.2  Objectives  ...........................................................................................................................................  37   2.2  [Objetivos]  ..........................................................................................................................................  39  . 3.  Abstracts  ..........................................................................................................................................  41   3.1  Abstract  manuscript  1  ...................................................................................................................  43   3.2  Abstract  manuscript  2  ...................................................................................................................  45  . 3.  [Resúmenes]  ....................................................................................................................................  47   Resumen  manuscrito  1  .........................................................................................................................  49   Resumen  manuscrito  2  .........................................................................................................................  51  . 4.  Manuscript  I:  Obesity  as  a  mediator  of  the  influence  of  cardiorespiratory  fitness   on  cardiometabolic  risk:  a  mediation  analysis  .......................................................................  53   4.1  Background  .......................................................................................................................................  55   4.2  Research  design  and  methods  .....................................................................................................  56   4.2.1  Study  design  and  population  .....................................................................................................................................  56   4.2.2  Measurement  Anthropometrics  ..............................................................................................................................  56   4.2.3  Biochemical  assessments  ...........................................................................................................................................  57   4.2.4  MetS  Risk  Assessment  ..................................................................................................................................................  57   4.2.5  Evaluation  of  fitness  ......................................................................................................................................................  58   4.2.6  Statistical  analysis  ..........................................................................................................................................................  58  . 4.3  Results  .................................................................................................................................................  59   4.3.1  Mediation  analysis  in  boys  ...........................................................................................................................................  62   4.3.2  Mediation  analysis  in  girls  ...........................................................................................................................................  67  . 4.4  Conclusions  ........................................................................................................................................  69   4.4.1  Obesity  and  metabolic  syndrome  ............................................................................................................................  69   4.4.2  Cardiorespiratory  fitness  and  metabolic  syndrome  .......................................................................................  70   4.4.3  Body  mass  index  as  a  mediator  between  cardiorespiratory  fitness  and  cardiometabolic  risk   factors  .............................................................................................................................................................................................  70   4.4.4  Limitations  ........................................................................................................................................................................  71   4.4.5  Conclusion  .........................................................................................................................................................................  71  . 5.  Manuscript  II:  Body  mass  index  as  a  mediator  of  the  relationship  between   muscular  fitness  and  cardiometabolic  risk  in  children:  a  mediation  analysis  ............  73   5.1  Background  .......................................................................................................................................  75   5.2  Materials  and  methods  ..................................................................................................................  76   5.2.1  Study  design  and  population  .......................................................................................................................................  76   5.2.2  Measurement  Anthropometrics  .................................................................................................................................  76   5.2.3  Biochemical  assessments 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(14) 5.2.4  Cardiometabolic  risk  assessment  ..............................................................................................................................  77   5.2.5  Evaluation  of  fitness  .......................................................................................................................................................  78   5.2.6  Pubertal  development  ....................................................................................................................................................  79   5.2.7  Statistical  analysis  ...........................................................................................................................................................  79  . 5.3  Results  .................................................................................................................................................  80   5.3.1   Mediation  analysis  ....................................................................................................................................................  93  . 5.4  Discussion  ..........................................................................................................................................  98   5.3.2   Obesity  and  cardiometabolic  risk  .........................................................................................................................  98   5.3.3   Muscular  fitness  and  cardiometabolic  risk  .......................................................................................................  98   5.3.4   Body  mass  index  as  a  mediator  between  muscular  fitness  and  cardiometabolic  risk  factors  ......  99   5.3.5   Limitations  .................................................................................................................................................................  100   5.4.5  Conclusion  .......................................................................................................................................................................  101  . 6.  Conclusions  ...................................................................................................................................  103   6.  [Conclusiones]  .............................................................................................................................  109   7.  References  ....................................................................................................................................  113   8.  Scientific  contributions  ............................................................................................................  129   8.1  Obesity  as  a  mediator  of  the  influence  of  cardiorespiratory  fitness  on   cardiometabolic  risk:  a  mediation  analysis.  ...............................................................................  131   8.2.  Body  mass  index  as  a  mediator  of  the  relationship  between  muscular  fitness  and   cardiometabolic  risk  in  children:  a  mediation  analysis.  .........................................................  141  . 9.  Other  related  scientific  contributions  of  this  PhD  Thesis  ............................................  171   Communications  to  conferences.  .....................................................................................................................................  173   10.  Other  scientific  contributions  during  the  PhD  ..............................................................  179    .

(15) TABLES  INDEX   Table  1.  Complications  associated  with  childhood  obesity  .................................................  17   Table  2.  Definitions  of  metabolic  syndrome  in  children  ......................................................  18   Table  3.  Age-­‐specific  mean  and  range  prevalence  of  metabolic  syndrome  in  children.  ..................................................................................................................................................................  19   Table  4.  Muscular  fitness  tests  ......................................................................................................  24   Table  5.  Descriptive  characteristics  for  participants  in  the  study  (manuscript  I)  .....  60   Table  6.  Pearson  correlation  coefficients  between  body  mass  index  and   cardiorespiratory  fitness  with  cardiometabolic  risk  factors  controlling  for  age.  .....  61   Table  7.  Mean  differences  in  cardiometabolic  risk  factors  by  body  composition  and   cardiorespiratory  fitness  categories  in  boys.  ..........................................................................  63   Table  8.  Mean  differences  in  cardiometabolic  risk  factors  by  body  composition  and   cardiorespiratory  fitness  categories  in  girls  ...........................................................................  64   Table  9.  Mean  differences  in  cardiometabolic  risk  factors  by  categories  of   cardiorespiratory  fitness,  controlling  for  age,  by  sex  and  weight  status.  .....................  65   Table  10.  Mean  differences  in  cardiometabolic  risk  factors  by  categories  of  weight   status,  controlling  for  age,  by  sex  and  cardiorespiratory  fitness  levels.  ........................  66   Table  11.  Characteristics  of  the  study  sample  (manuscript  II)  .........................................  82   Table  12.  Pearson  correlation  coefficients  between  body  mass  index  and  muscular   fitness  with  cardiometabolic  risk  factors  controlling  for  age.  ..........................................  83   Table  13.  Mean  differences  in  cardiometabolic  risk  factors  by  body  mass  index  and   muscular  fitness  categories  in  boys.  ...........................................................................................  84   Table  14.  Mean  differences  in  cardiometabolic  risk  factors  by  body  mass  index  and   muscular  fitness  categories  in  girls.  ...........................................................................................  85   Table  15.  ANCOVA  model  testing  mean  differences  in  cardiometabolic  risk  factors  by   body  mass  index  and  dynamometry/weight  categories  in  boys.  ......................................  86   Table  16.  ANCOVA  model  testing  mean  differences  in  cardiometabolic  risk  factors  by   body  mass  index  and  dynamometry/weight  categories  in  girls.  ......................................  87   Table  17.  ANCOVA  model  testing  mean  differences  in  cardiometabolic  risk  factors  by   body  mass  index  and  standing  long  jump  categories  in  boys.  ...........................................  88   Table  18.  ANCOVA  models  testing  mean  differences  in  cardiometabolic  risk  factors   by  body  mass  index  and  standing  long  jump  categories  in  girls.  .....................................  89   Table  19.  ANCOVA  model  testing  mean  differences  in  cardiometabolic  risk  factors  by   body  mass  index  and  adjusted  standing  long  jump  categories.  .......................................  90   Table  20.  ANCOVA  model  testing  mean  differences  in  cardiometabolic  risk  factors  by   body  mass  index  and  adjusted  dynamometry  categories.  ..................................................  91   Table  21.  ANCOVA  model  testing  mean  differences  in  cardiometabolic  risk  factors  by   body  mass  index  and  adjusted  muscular  fitness  categories.  .............................................  92  . Ana Díez Fernández. 1.

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(17) FIGURES  INDEX   Figure  1.  Prevalence  of  childhood  obesity.  ………………………………………………………………16   Figure  2.    Aerobic  fitness  tests  classification.  …………………………………………………….……23   Figure  3.  Graphical  definitions  of  mediator,  confounder  and  moderator  variables..27     Figure  4.  Simple  mediation  analysis  graphical  definition.    …………………..………………...28   Figure  5.  Path  model  depicting  the  relationships  among  the  variables  included  in   this  doctoral  thesis.  ...........................................................................................................................  30   Figure  6.  Conceptual  diagram  of  a  serial  multiple  mediator  model.  ……………………....31   Figure  7.  Body  mass  index  mediation  models  of  the  relationship  between   cardiorespiratory  fitness  and  cardiometabolic  risk  variables,  controlling  for  age,  by   sex.  ..........................................................................................................................................................  68   Figure  8.  Body  mass  index  mediation  models  of  the  relationship  between  muscular   fitness  and  cardiometabolic  risk  variables,  controlling  for  age,  by  sex.  ........................  95   Figure  9.  Body  mass  index  mediation  models  of  the  relationship  between   dynamometry/weight  and  cardiometabolic  risk  factors  controlling  for  age,  by  sex.  ..................................................................................................................................................................  96   Figure  10.  Body  mass  index  mediation  models  of  the  relationship  between  standing   long  jump  and  cardiometabolic  risk  factors  controlling  for  age,  by  sex.  ......................  97    . Ana Díez Fernández. 3.

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(19) Abbreviations  .

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(21) ALADINO: Nutrition, Physical Activity, Childhood Development and Obesity ALPHA: Assessing Levels of Physical Activity ANCOVA: Analysis of covariance ATP-III: National Cholesterol Education Program’s Adult Treatment Panel III BMI [IMC]: Body mass index [Índice de masa corporal] CMRI: Cardiometabolic risk index CRF: Cardiorespiratory fitness CVR: Cardiovascular risk DBP: Diastolic blood pressure EGIR: European Group for the Study of Insulin Resistance HDL-c [HDL]: High density lipoprotein-cholesterol [Lipoproteína de alta densidad] IDF: International diabetes federation LDL: Low density lipoprotein Log: Logarithm [Logaritmo] MAP: Mean arterial pressure MetS: Metabolic Syndrome MF: Muscular fitness MS: Muscular strength NCDs: Non-Communicable Diseases SBP: Systolic blood pressure SLJ: Standing long jump TG: Triglycerides [Triglicéridos] WC: Waist circumference WHO: World Health Organization. Ana Díez Fernández. 7.

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(23) Presentation  .

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(25) Presentation  . Childhood obesity is considered one of the most serious public health challenges of the 21st century. The tracking of this condition to adulthood is related to several complications. Obesity has been located in the core of metabolic syndrome, a cluster of cardiometabolic risk factors that has a special relevance in children due to the current prevalence rates, associated morbidity, and lifelong consequences (e.g. type 2 diabetes mellitus). Cardiorespiratory and muscular fitness are positively associated to metabolic syndrome, and have evidenced to be a useful tool to prevent cardiometabolic risk and to improve individual general health status. However, the prevention of overweight and obesity maintaining an appropriate body mass seems to be a crucial factor for obtaining real benefits of physical fitness and therefore, to prevent metabolic syndrome, but this fact remains unclear in children. Two original articles addressing this question are included in this doctoral thesis. Data from both studies are from a cluster randomized trial (Clinicaltrials.gov, NCT01277224) aimed to assess the effectiveness of an intervention that included the MOVI2 program, a strategy of physical activity promotion in the school environment in order to reduce the cardiovascular risk factors levels and the prevalence of overweight and obesity in children. This study was designed by the Social Health Care and Research Center (CESS) from the University of Castilla-La Mancha (UCLM), where the PhD student belongs, and was conducted in 20 public primary schools from the province of Cuenca, Spain, from September 2010 to June 2011.. Ana Díez Fernández. 11.

(26) Presentation  . Acknowledgements. This study has been financed by the PII1I09-0259-9898 y POII10-0208-5325 grants from the Education and Sciences Department of the Regional government of Castilla-La Mancha and another grant from Carlos III Health Institute, Health and Social Welfare Ministery (FIS PI081297). Additional funding was obtained from the Primary Care Prevention and Health Promotion Network (RD06/0018/0038). We gratefully acknowledge the contribution of children, parents and teacher from the schools involved in the study.. This doctoral thesis is focused on analysing the relationship between cardiometabolic risk with physical fitness and weight status, and also on examining whether the association between physical fitness and cardiometabolic risk is mediated by body mass index in 8-11 years schoolchildren. PhD student involvement: ü Collaboration in the study design. ü Data analysis and results interpretation. ü Writing of the papers included in the present thesis.. 12. Doctoral Thesis UCLM - CESS.

(27)                   1.  Introduction.

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(29) Introduction  . 1.1  Childhood  obesity.     Childhood obesity: one of the most serious public health challenges of the 21st century. Overweight and obesity in adults are defined as an abnormal or excessive fat accumulation that signifies a risk for health. A crude population measure of obesity is the body mass index (BMI), a person’s weight (in kilograms) divided by the square of his or her height (in meters). A person with a BMI of 30 or more is generally considered obese and a person with a BMI equal to or more than 25 is considered overweight (1). Childhood obesity is increasing in Spain and most countries around the world at alarming rates, such that has been declared by the World Health Organization (WHO) as one of the most serious public health challenges of the 21st century (2). Physical inactivity, food intake, urban planning and some others barriers for active commuting have been identified are, among others, as responsible of the current children obesity epidemic. Several definitions of obesity in children have been proposed in the last two decades, but nowadays only two are internationally recognized: the WHO sex-and-age cut-offs (3, 4) and the most used, the International Obesity Task Force (IOTF) cut-offs (5). Both of them are based on the BMI, since they rely on the assumption that it is a reliable indirect appropriated index value for measuring overweight and obesity in children in both clinical and community settings (6, 7). In Spain, the overweight/obesity prevalence in 6-11 years old children was 35.2% in 2011 according to the ALADINO (Nutrition, Physical Activity, Childhood Development and Obesity) study (8), and the prevalence has increased in the province of Cuenca from 31.5% in 2004 to 35.4% in 2010 (9), situating Spain between countries with higher overweight/obesity childhood prevalence, like other southern Europe countries, where prevalence is around 40% in Greece (10), 37% in Portugal (11), and 34% in Italy (12). In northern Europe countries the prevalence decreases up to a 20.5% in Germany (13) and a 18.6% in France (14).. Ana Díez Fernández. 15.

(30) Introduction  . Figure  1.  Prevalence  of  childhood  obesity. Extracted from: <http://www.worldobesity.org/aboutobesity/world-map-obesity/?map=children> [Consulted 02/10/2014]. Consequences of childhood obesity Childhood obesity is associated with a higher probability of premature death and disability in adulthood (15, 16), and many other consequences reported to date (17, 18) are summarized in Table 1. Obese children also experience breathing difficulties, increased risk of fractures, hypertension, and early markers of cardiovascular disease, insulin resistance and psychological effects (1, 2, 19). Besides, overweight and obese children that maintain this excess of weight into youth and adulthood have more probabilities of develop noncommunicable diseases (NCDs) like diabetes and cardiovascular diseases at a younger age (2, 20).. 16. Doctoral Thesis UCLM - CESS.

(31) Introduction  . Table  1.  Complications  associated  with  childhood  obesity   System Psychosocial Neurological Pulmonary. Complications Poor self-esteem Depression Eating disorders Pseudotumor cerebri Sleep apnea Asthma Exercise intolerance. Dyslipidemia Hypertension Coagulopathy Chronic inflammation Endothelial dysfunction Metabolic syndrome Adapted from Ebbeling CB et al. (17). Cardiovascular. 1.2. System Gastrointestinal. Complications Gallstones Steatohepatitis. Renal Endocrine. Glomerulosclerosis Type 2 diabetes Precocious puberty Polycystic ovary syndrome (girls) Hypogonadism (boys) Slipped capital femoral epiphysis Blount’s disease Forearm fracture Flat feet. Musculoskeletal. Metabolic  Syndrome  . What is metabolic syndrome in children? Metabolic syndrome (MetS) is defined as a cluster of cardiometabolic disorders including insulin resistance or glucose intolerance, hypertension, dyslipidemia and central obesity. MetS is a predictor of cardiovascular disease, type 2 diabetes and overall mortality (26-30). The first MetS reference comes from about 250 years ago, when the Italian physician and anatomist Morgagni identified the association between visceral obesity, hypertension, atherosclerosis and high levels of uric acid in the blood. Subsequently, at the end of the 80’s, Reaven defined the clustering of disorders in glucose and insulin metabolism, obesity, dyslipidemia and hypertension as ‘syndrome X’ (31). From the first working definition of MetS by the WHO in 1999 (32), several alternative consensus regarding how to diagnose MetS have appeared, and two of them are very well known: the National Cholesterol Education Program’s Adult Treatment Panel III (ATP-III) (33) and the European Group for the Study of Insulin resistance (EGIR) (34). Although the concept of MetS in adults has been largely studied, it is still a debatable issue, since there is not consensus about which disorders should or should not be included. Ana Díez Fernández. 17.

(32) Introduction   in this cluster of cardiovascular risk (CVR) factors in children. Modifications of the adult WHO and ATP-III definitions have been used in pediatric research, and most of them include the same risk factors as in adults, but there is not consensus on the appropriate cutoff for each MetS component in children (35). Different MetS definitions in children are summarized in Table 2. Table  2.  Definitions  of  metabolic  syndrome  in  children  .  . Definition. Adiposity. TG. HDL-c. Blood pressure. Blood glucose/insulin. Cook et al.(36)2,3. WC≥90th percentile1. ≥110mg/dl. ≥40 mg/dl. ≥90th percentile1. Fasting glucose ≥110mg/dl. Ford et al.(37)2. WC≥90th percentile1. ≥110mg/dl. ≥40 mg/dl. ≥90th percentile1. Fasting glucose ≥110mg/l. Weiss et al.(38)2. BMI zscore≥2.01. ≥95th percentile1. <5th percentile1. >95th percentile1. Impaired glucose tolerance (ADA criterion). IDEFICS (39). WC≥90th percentile1. ≥90th percentile1. ≥10th percentile1. SBP≥90th percentile1 DBP≥90th percentile1. WHO (40)4. >95th or 97th percentile1 for WC or BMI WC≥90th percentile1. >95th percentile1. <5th percentile1. HOMA-insulin resistance ≥90th percentile1 or fasting glucose ≥90th percentile1. >95th percentile1. Fasting glucose ≥110mg/l. ≥150mg/dl. ≥40 mg/dl. SBP ≥130mg/dl DBP ≥85mg/dl. Impaired fasting glucose ≥100mg/dl or known T2DM TG= Triglycerides; HDL-c= High density lipoprotein-cholesterol; WC= Waist circumference; SBP= Systolic blood pressure; DBP= Diastolic blood pressure. 1 Age/sex/height specific. 2 The definition includes three or more of the CVR factors. 3 National Cholesterol Education Program (ATP-III) definition modified for age. 4 Impaired glucose tolerance or impaired fasting glucose or insulin resistance + 2 others. 5 The definition requires the presence of central obesity + any two others. IDF(41)5. Pathogenesis of the MetS Two closely related cardiovascular risk factors seem to play a crucial role in the development of MetS: obesity and insulin resistance. Both of them are included in all MetS definitions in children (30). Visceral fat has been positively correlated with glucose-stimulated insulin levels and also a negatively with insulin sensitivity and glucose intake rates (42). Also the deposits of fat in the liver and muscles are related to insulin resistance in obese children (43). Not only obesity and insulin resistance but also genetically influenced factors such as maternal obesity, gestational diabetes, ethnicity, birth weight, and family history of diabetes (44) should be considered in the pathogenesis of this syndrome.. 18. Doctoral Thesis UCLM - CESS.

(33) Introduction   Prevalence of the Mets There is no doubt that the children’s prevalence of MetS should be increasing, since childhood obesity prevalence is growing and adiposity variables are included in all definitions of MetS, but the variability of reported MetS prevalence in children is quite large, mainly due to the several diagnosis criteria applied. A systematic review in 2013 estimated the prevalence of MetS in children at 3.3% (range 0%-19.2%); in overweight children was 11.9% (range 2.8%-29.3%) and in obese children was 29.2% (range 10%-66%) (45). Prevalence was lower in non-obese and non-overweight children compared with overweight or obese. Using three different definitions (ATP-III, WHO and IDF), the mean and range prevalence of MetS in Europe compared to worldwide is shown in Table 3. Table  3.  Age-­‐specific  mean  and  range  prevalence  of  metabolic  syndrome  in   children.  . Total Overweight Obesity. ATP-III1 4.2% (1%-19.2%) 10.7% (2.8%-37%) 30.2% (2.1%-50%). ATP-III1 2.1% (0.3%-13.9%) Total 35.3% (16.9%-45.5%) Overweight and obesity Extracted and converted from Friend A et al. (45). 1 Adult definition modified for age.. WORLDWIDE WHO1 6% 26.1% (23.3-42.3) EUROPE WHO1 6% 28.2% (23.3%-39%). IDF 3.1% (1-14%) 6.7% 23.2% (16.4%-44.2%) IDF 2.2% (0.3%-5%) 21.0% (8.9-50%).   MetS in epidemiological research: continuous score or dichotomous variable? A WHO Expert Consultation Group, the American Diabetes Association and the European Association for the Study of Diabetes have highlighted the importance of defining a continuous score for MetS instead of a categorical dichotomous classification (46, 47). Quantitative measures capture the essence of the components variables and in both the clinical practice and the epidemiologic research constitutes an advantage to the extent that an individual with none of the risk factors that include the syndrome, who therefore does not reach the established cut-off points, could achieve a score above the cutoff defined for the multifactorial index for measuring MetS. For the same reason, multifactorial interventions (changes in lifestyle, multiple drug therapy) that are not effective against a. Ana Díez Fernández. 19.

(34) Introduction   dichotomously defined metabolic syndrome could be beneficial in a metabolic syndrome defined using a quantitative scoring system (48). Different structured models using confirmatory factor analysis in children (56) and adults (57-59), including the key components of MetS (obesity, lipid profile, blood pressure and glucose homeostasis) underlying patterns among variables have shown high intercorrelation degrees, which help to understand which risk factors should be included to diagnose MetS and if the risk factors included in children models showed stability in the track to adolescence (60). A definitive quantitative index should be agreed between the international scientific societies and health agencies to ensure comparability of scores of different studies and to allow international comparisons of cardiometabolic risk in children.. Consequences of MetS in children The effects of being diagnosed with MetS during childhood and adolescence have important consequences in terms of morbidity and mortality into adulthood (30, 61). It has been reported that adults with MetS when they were children had higher levels of BMI, blood pressure and triglycerides (62). Also is known that, compared with children free of MetS, children with MetS have higher incidence of type 2 diabetes 25 to 30 years later (63) and their risk of having MetS and increased intima media thickness during adulthood is three times higher (64).. How to prevent and treat MetS during childhood? Prevalence of MetS is particularly high among obese children, so the prevention strategies should be mainly targeted to this population in order to avoid insulin resistance and to diminish the excess of weight (65), both of them considered the precursors of MetS. Different anthropometric variables including not only BMI but also skinfolds, waist circumference and body fat percentage by electric bioimpedance analysis should be evaluated, as well as blood pressure, lipid profile and insulin resistance indexes (66). Other risk factors like family history of diabetes, gestational diabetes or birth weight must be taken into account in order to identify potential population at risk (30).. 20. Doctoral Thesis UCLM - CESS.

(35) Introduction   There is not an specific treatment for MetS in children, but changes in lifestyle focused on increasing physical activity, reducing adiposity and maintaining a balanced diet (20, 67, 68) should always be the first treatment step because they will help to reduce insulin sensitivity and improve cardiovascular profile even in the absence of weight loss (65). If necessary, each risk factor can be treated independently, but further studies must be conducted to assure safety of drugs like metformin or orlistat in pediatric population (30).. 1.3. Physical  fitness  in  children  . Definition of physical fitness Physical fitness is defined as a set of attributes that people have or achieve that relates to the ability to perform physical activity (69). This concept must be distinguished from “physical activity” which is defined as any bodily movement produced by skeletal muscles that results in energy expenditure and “exercise” that is a planned, structured, and repetitive bodily movement done to improve or maintain one or more components of physical fitness (69). Although the development of physical fitness is the result of many parameters, optimal physical fitness is not possible without regular exercise (70). Higher levels of physical activity result in higher physical fitness and a better physiologic response in skeletomuscular, cardiorespiratory, hematocirculatory, psychoneurological and endocrine–metabolic systems (71, 72).. Health-related physical fitness in children Health-related physical fitness refers to four components of fitness that are affected favorably or unfavorably by habitual physical activity and are related to health status (73). It involves two characteristics: 1) the ability to perform daily activities with vigor, and 2) the demonstration of traits and capacities that are associated with a low risk of premature development of cardiovascular risk, chronic diseases, and general health status (73, 74).. Ana Díez Fernández. 21.

(36) Introduction   a). Body composition: Is the relative percentage of muscle, fat, bone and other tissues of which the body is composed (70).. b). Cardiorespiratory fitness (CRF): Reflects the overall capacity of the cardiovascular and respiratory systems and the ability to carry out prolonged exercise (75).. c). Muscular fitness: It comprises three different factors: muscular strength, muscular power and muscular endurance (73). 1). Muscular power: Is strictly the maximum rate of working of a. muscle (73). 2). Muscular strength (MS): Is related to the amount of external. force that a muscle can exert with a single maximal effort (70). 3). Muscular endurance: Is the ability of muscles groups to. repeatedly exert external force (70). d). Motor components: Is composed by four skill-related components that have a relationship with enhanced performance in sports (73): 1). Agility: Is described as a high score on a test that requires agile. movements. 2). Balance: Scored of various tests of whole body equilibrium.. 3). Speed of movements and. 4). Motor coordination: Both characterized by fast responses to. simple and complex reaction tasks.. Measuring physical fitness in children Over the last two decades, more than 15 battery tests for the assessment of physical fitness in children and adolescents have been developed (76, 77). These batteries consist in a number of field tests and their criterion-related validity have been proved so they can be performed in children and adolescents to measure their physical fitness (76). Most fitness batteries like EUROFIT, developed by the Council of Europe Committee for the Development of sport (78), FITNESSGRAM, developed by The Cooper Institute (79) or ALPHA-FIT (80) include aerobic capacity, maximal isometric strength, endurance strength, explosive strength, flexibility, speed, agility, balance and anthropometric field tests (76, 77).. 22. Doctoral Thesis UCLM - CESS.

(37) Introduction   Cardiorespiratory fitness Maximal oxygen uptake (VO2max) is one of the parameters of aerobic function and is commonly measured in exercise physiology. The VO2max achieved during a graded maximal exercise test is an objective measure of CRF level (75). The aerobic fitness tests can be divided into maximal (stress the body by exercising to exhaustion) and submaximal, and several protocols to measure them have been described (Figure 2). Direct determination by indirect calorimetry (where the oxygen expired [O2] and carbon dioxide [CO2] fractions are measured during exercise and pulmonary ventilation) is the most reliable test to determine VO2max, but it requires sophisticated and expensive equipment, a long time to evaluate each individual and high motivation of the participants. Indirect determinations by treadmill, cycle-ergometer or field tests performed during submaximal or maximal exertion are a feasible, safer and cost-effective alternative for predicting VO2max. These tests, specially field tests, can be performed in large population samples (76). From all these tests, the 20 meters shuttle run test, also known as CourseNavette, is considered one the most appropriate field test for measuring cardiorespiratory fitness in children (76).. Aerobic fitness. Maximal Direct determination Indirect calorimetry. Submaximal Indirect determination. Field test. Treadmill test. Multistages shuttle run. Bruce. Cooper. Balke. Cycle test. Cycle test. AstrandRhyming. Cycleergometer. Run/walk. Figure  2.  Aerobic  fitness  tests  classification. (Self-source, 2014). Ana Díez Fernández. 23.

(38) Introduction   Muscular fitness Due to the complexity and different characteristics of each muscular group, there is no a single test for measuring muscular fitness, thus specific muscular group tests must be carried out when measuring muscular fitness. Most important muscular strength, muscular power and muscular endurance tests are summarized in Table 4.. Table  4.  Muscular  fitness  tests   Muscular strength. Muscular power. Muscular endurance. 1-RM (Repetition maximum). Vertical Jump. Bench press. Isokinetic strength. Standing long jump. Push ups. Handgrip strength. Medicine ball throw. Bent arm hang. Isometric back strength Isometric leg strength (Self-source, 2014). Finally, is important to consider body size when analyzing muscular fitness tests, especially in those tests that do not require propulsion or lifting of the body mass (71). Different methods have been used for this purpose, like to adjust for body weight or other adiposity parameters, to stratify by BMI/adiposity categories in the analysis (81), to use allometric exponents (82), or to regress body mass on the fitness phenotypes and perform the analysis with its standardized residuals (83). Due to the lack of consensus about the best approach, all of them are widely used in epidemiological and clinical studies.. 1.4  Physical  fitness,  fatness  and  metabolic  syndrome   The analysis of the association between these three variables is quite complex due to the close relationship among them, and the several confounders that should be controlled for.. 24. Doctoral Thesis UCLM - CESS.

(39) Introduction   Physical fitness and metabolic syndrome Cardiorespiratory and muscular fitness are considered, at all stages of life powerful predictors of cardiovascular risk and general health status, as have been evidenced in several studies, systematic reviews and meta-analysis (51, 52, 61, 71, 74, 84-88) a negative association with cardiometabolic risk, such that as physical fitness increases, the risk of an unfavourable metabolic risk profile is reduced. Children with higher levels of fitness have shown lower values of all components of MetS and also in MetS indexes compared with children who have lower fitness levels (50, 51, 61). The benefits of higher levels of physical fitness on cardiometabolic health highlight the importance of maintaining a physically active lifestyle that, in fact, is one of the key strategies for preventing obesity and MetS since childhood (19, 21, 23, 47, 72). Obesity and metabolic syndrome On the other hand, it is well-known that obesity appears to be one of the primary causes of developing MetS in children (19, 64, 89-91), and combined with insulin resistance, are the most important predictors of cardiovascular disease and type 2 diabetes in adulthood (20, 29, 68). Obese children are at higher risk of become obese adults (16) and also of develop MetS into adulthood (19, 20, 63, 67, 68). Strategies for preventing both obesity and MetS (described previously in subsections 1.1 and 1.2 of this document) are similar, and therefore we can conclude that useful strategies for preventing obesity are effective for preventing MetS as well.. Fitness-fatness-metabolic syndrome Both fitness and fatness influence MetS in completely opposite ways, but which has a stronger influence? Is fitness influencing the relationship between obesity and MetS? Or perhaps obesity attenuates the positive association of physical fitness and MetS? Are there other variables influencing this relationships? A commonly used approach to answer these questions is the categorization of subjects into subgroups (normal weight – overweight – obesity cut-offs for fatness; low – medium – high levels for physical fitness). Obese children present higher MetS risk than their normal weight. Ana Díez Fernández. 25.

(40) Introduction   peers across fitness level categories and conversely, those who are at the highest fitness levels present a better cardiometabolic profile across BMI categories (61, 85, 92). This evidence seemingly supports the protective role of physical fitness across levels of fatness, but other studies have also concluded that the effects of fitness do not completely counteract the harmful consequences of fatness or adiposity (51, 53, 54, 85, 93). Finally, the idea of “fat but fit” also suggests that overweight or obese children but with high level of fitness have a similar cardiovascular profile than their normal weight but unfit peers. This “metabolically healthy” children concept has been questioned in different studies and meta-analysis, concluding that among overweight and obese youth, high cardiorespiratory fitness is not associated with a “metabolically healthy” profile but other factors like lower BMI z-score and lower hepatic triglyceride are (94), and that compared with metabolically healthy normal weight individuals, obese people are at increased risk for all-cause mortality and cardiovascular events, suggesting that there is no healthy pattern of increased weight (95).. 1.5  Mediation  analysis  . Mediation analysis. Definition Mediation analysis is a statistical procedure useful to answer questions as whether a causal agent X (independent variable) transmits its effect on Y (outcome variable) through a third variable (96). Historically, mediation models have been used in psychology for about 90 years, where the concern for mediating variables in the design of a study is a pivotal issue to evaluate the effectiveness of interventions aimed to influence behavior (97, 98). The first psychological research on mediation can be traced back to Woodworth’s S-O-R model (99). In 1928 Woodworth found that the active organism that intervenes between the stimulus and response is responsible for the effects of stimuli on behavior (100). Most recently, Baron and Kenny gave the most influential discussion of mediation models in 1986 (101) and other authors, like Hayes, Preacher or MacKinnon have developed macros and other tools for mediation analysis (96, 97).. 26. Doctoral Thesis UCLM - CESS.

(41) Introduction   Differences between mediator, moderator and confounder variables Is important to understand and distinguish between related variables that affect the association between a predictor and an outcome variable. A graphical definition of each variable is presented in Figure 3.. Figure   3.   Graphical   definitions   of   mediator,   confounder   and   moderator   variables. [Extracted and adapted from Bauman AE et al (102).]. 1. Mediator: Is an intervening variable that is necessary to complete a cause-effect link, and is on the causal pathway between a predictor and an outcome (102). 2. Confounder: A confounding variable is associated with the outcome, but is also associated with the exposure or predictor variable, and influences the strength of the association between the predictor and the outcome (102), but unlike the mediator it is not included in a causal sequence. 3. Moderator: Is defined as an interaction or effect modifier variable that affects the direction, strength, or both of the relationship between an intervention and mediator or moderator and the outcome (102). The variable does not mediate the relationship between the predictor and the outcome, so that is not in the causal sequence.. Ana Díez Fernández. 27.

(42) Introduction   Procedures for mediation analysis Most research focuses on the relation between an independent variable (predictor) X and an outcome variable Y. With two variables, there are a limited number of potential causal relationships between them: X causes Y, Y causes X, both X and Y are reciprocally related. Sometimes it can be found that the relation between two variables is completely due to the existence of a third variable [M]. If the third variable M is intermediate in a causal sequence such that X causes M and M causes Y, then M is a mediating variable (98, 99); thus, a mediator is a third variable that conveys the association between an independent variable and an outcome variable (101). The simple mediation analysis procedure described by Baron and Kenny consists of a series of linear regression models where the following criteria must be used to establish mediation (101): 1. The independent variable X must be significantly related to the mediator M (path a); 2. The independent variable X must be significantly related to the outcome variable Y (path c, also called total effect); 3. The mediator M must be significantly related to the outcome variable Y (path b); and 4. The association between the independent and outcome variable X-Y must be attenuated when the mediator M is included in the regression model (path c´, also called direct effect). The scheme that best represents this widely used analysis is shown in Figure 4:. Figure  4.  Simple  mediation  analysis  graphical  definition.    (Self-source, 2014) Finally, a method for testing the significance of a mediator effect must be conducted to determine whether, after including the mediator in the model (indirect effect), the. 28. Doctoral Thesis UCLM - CESS.

(43) Introduction   decreasing in the effect of the independent variable on the outcome is statistically significant (103, 104). Sobel test or bootstrapping resampling methods can be performed for this purpose, and choose the most appropriate test depends on the sample size and the normal distribution of the sample.. Application and advantages of mediation analysis The study of the relationship between physical fitness, metabolic syndrome and or adiposity has usually been performed using multivariate methods like ANCOVA, multiple linear regression or logistic regression in order to control confounders or mediators variables, as well as using stratified analysis or other similar procedures, depending on the characteristics of the study and the variables included. Therefore, mediation analysis supposes the use of a novel statistical method in health sciences that help us to get a better understanding of the relationships between potentially related variables, and particularly to disentangle how these relationships works and how a third variable can exert its influence between two others. In the context of the statistical analysis of this doctoral thesis, this procedure helps us to clarify the causal pathway linking physical fitness and childhood obesity with metabolic syndrome. The path model overview of this study is depicted in Figure 5.. Ana Díez Fernández. 29.

(44) Introduction  . Figure  5.  Path  model  depicting  the  relationships  among  the  variables  included  in   this  doctoral  thesis.     Future research with mediation analysis procedures in the relationship between fitness and MetS Mediation processes involving simultaneous mediation by multiple variables can be considerably more complex than investigating simple mediation. Assessing multiple mediation involves not only deciding whether or not an indirect effect exists, but also how to disentangle the role of individual mediators that may overlap in content (105). This opens the door to more interesting analytical opportunities and test to continue studying the relationship between physical fitness and metabolic syndrome in the future, trying to reveal and understand how all the variables affect this relationship. Different variables of adiposity, other parameters of physical fitness, physical activity, inflammatory markers, as well as other cardiovascular risk factors may be in the causal pathway between physical fitness and metabolic syndrome. Figure 6 represents the conceptual diagram of the future research of the binomial “physical fitness-cardiometabolic risk”.. 30. Doctoral Thesis UCLM - CESS.

(45) Introduction  .   Figure   6.   Conceptual   diagram   of   a   serial   multiple   mediator   model. (Self-source, 2014). It can be also interesting to address in the future the issue of “metabolically healthy” children, and also to evaluate the influence of the dichotomous variable fit/unfit in the “fat but fit” paradigm (94, 95)..  .     Ana Díez Fernández. 31.

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(47) 2.  Framework  for  the  question  .

(48)                        .

(49) Framework  for  the  question  . 2.1  Framework  for  the  question   This doctoral thesis starts from the following assumptions or proposals:. 1. Childhood obesity is one of the most serious public health challenges of the 21st century. Spain has one of the highest children prevalence of overweight and obesity in Europe (8, 106), thus several health consequences in childhood are expected, but also in adulthood if this severe public health problem it is not reversed (17). 2. One of the consequences of obesity is the metabolic syndrome. Defined as a cluster of cardiometabolic risk factors, the MetS is a predictor for cardiovascular disease and mortality, as well as other chronic conditions (26). This disorder should be studied not only in adults but also in children due to its magnitude, morbidity and consequences. 3. Obesity and MetS are preventable conditions closely related to cardiometabolic risk. Relationship of excess of weight and other adiposity parameters with cardiometabolic risk is well known (89). Obesity is a essential predictor for the development of an unfavorable cardiometabolic profile (90) but in most cases both conditions can be prevented or reversed achieving and maintaining an energy balance and complying physical activity recommendations of experts and organizations (2). 4. Physical fitness is considered a powerful marker for health. To get and maintain good levels of cardiorespiratory and muscular fitness help to decline cardiometabolic risk factors levels in children, thus decrease the risk of developing metabolic syndrome (84).. Ana Díez Fernández. 35.

(50) Framework  for  the  question  . 5. The mediation role of obesity between physical fitness and metabolic syndrome still remains unclear. Despite all the epidemiological studies conducted so far, there are still doubts about how obesity can influence the benefits of physical fitness on cardiometabolic risk, and whether it is possible to improve significantly cardiometabolic risk without any changes in body composition variables. Elucidating this question allows us to establish which one is the priority target to improve children’s health status: to achieve good levels of physical fitness or to maintain normal weight. This question has never been answered by using mediation analysis techniques, thus it seems a relevant issue disentangle how weight status influence on the relationship between physical fitness and cardiometabolic health, in order to be more effective when designing prevention strategies against cardiovascular and metabolic risk in childhood..  . 36. Doctoral Thesis UCLM - CESS.

(51) Framework  for  the  question  . 2.2  Objectives  . 1) To assess, in schoolchildren, the relationship between body mass index and cardiorespiratory fitness with cardiometabolic risk factors. 2) To examine whether the association between cardiorespiratory fitness and cardiometabolic risk factors was mediated by body mass index in schoolchildren. 3) To analyze the relationship between cardiometabolic risk factors and weight status and muscular fitness in schoolchildren. 4). To. examine. whether. the. association. between. muscular. fitness. and. cardiometabolic risk factors was mediated by body mass index. The objectives of this PhD thesis will be addressed in the following subsections: ü Objectives 1 and 2, subsection 4, manuscript 1: Obesity as a mediator of the influence of cardiorespiratory fitness on cardiometabolic risk: a mediation analysis. ü Objectives 3 and 4, subsection 5, manuscript 2: Body mass index as a mediator of the relationship between muscular fitness and cardiometabolic risk in children: a mediation analysis.. Ana Díez Fernández. 37.

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(53) Framework  for  the  question  . 2.2  [Objetivos]  . 1) Evaluar la relación entre el índice de masa corporal y la condición física cardiorrespiratoria con los factores de riesgo cardiometabólicos en escolares. 2) Examinar si la asociación entre la condición física cardiorrespiratoria y los factores de riesgo cardiometabólicos estaba mediada por el índice de masa corporal. 3) Analizar la relación entre los factores de riesgo cardiometabólico con el estatus ponderal y la condición física muscular en escolares. 4) Examinar si la asociación entre la condición física muscular y los factores de riesgo cardiometabólicos está mediada por el índice de masa corporal.. Los objetivos de esta tesis doctoral se abordarán en los siguientes apartados: ü Objetivos 1 y 2, apartado 4, manuscrito 1: Obesity as a mediator of the influence of cardiorespiratory fitness on cardiometabolic risk: a mediation analysis. ü Objetivos 3 y 4, apartado 5, manuscrito 2: Body mass index as a mediator of the relationship between muscular fitness and cardiometabolic risk in children: a mediation analysis.. Ana Díez Fernández. 39.

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(55)  .     3.  Abstracts  .

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(57) Abstracts  . 3.1  Abstract  manuscript  1  . OBJECTIVE The relationship between cardiorespiratory fitness (CRF) and metabolic syndrome (MetS) is well known, although the extent to which body weight may act as a confounder or mediator in this relationship is uncertain. The aim of this study was examine whether the association between CRF and cardiometabolic risk factors is mediated by body mass index (BMI). RESEARCH DESIGN AND METHODS A cross-sectional study including 1158 schoolchildren aged 8-11 years from the province of Cuenca, Spain was undertaken. We measured height, weight, waist circumference, blood pressure, fasting plasma lipid profile and insulin, and CRF (20-m shuttle run test). A validated cardiometabolic risk index was estimated by summing standardized Z scores of waist circumference, logarithm of triglycerides/HDL-cholesterol (TG/HDL-c) ratio, mean arterial pressure (MAP), and log fasting insulin. To assess whether the association between CRF and cardiometabolic risk was mediated by BMI, linear regression models were fitted according to Baron and Kenny procedures for mediation analysis. RESULTS In girls, BMI acts as a full mediator in the relationship between CRF and cardiometabolic risk factors, with the exception of log TG/HDL-c ratio. In boys, BMI acts as a full mediator in the relationship between CRF and both log TG/HDL-c ratio and MAP, and as a partial mediator in the relationship between CRF and cardiometabolic risk factors. CONCLUSIONS BMI mediates the association between CRF and MetS in schoolchildren. Overall, good levels of CRF are associated with lower cardiometabolic risk, particularly when accompanied by weight reduction.. Ana Díez Fernández. 43.

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(59) Abstracts  . 3.2  Abstract  manuscript  2   OBJECTIVE Muscular fitness levels have been associated with cardiometabolic risk in children, although whether body weight acts as a confounder or as an intermediate variable in this relationship remains controversial. The aim of this study was to examine whether the association between muscular fitness and cardiometabolic risk factors is mediated by body mass index (BMI). RESEARCH DESIGN AND METHODS: Cross-sectional study using a sample of 1158 schoolchildren aged 8-11 years from the province of Cuenca, Spain. We measured anthropometrics and biochemical variables and we calculated a muscular fitness index as the sum of z-scores of handgrip dynamometry/weight and standing long jump, and we estimated a previously validated cardiometabolic risk index (CMRI). Linear regression models were fitted for mediation analysis to assess whether the association between muscular fitness and cardiometabolic risk was mediated by BMI. RESULTS Children with normal weight (N) had a better cardiometabolic risk profile than their overweight (OW) or obese (OB) peers after controlling for muscular fitness. Marginal estimated mean±SE values for N, OW and OB categories of CMRI were -0.75±0.06 < 0.84±0.10 < 2.18±0.16 in boys and -0.73±0.06 < 0.96±0.10 < 2.71±0.17 in girls, both p<0.001. Children with higher levels of muscular fitness had a better cardiometabolic risk profile (CMRI marginal estimated mean±SE 1.04±0.13 > 0.05±0.09 > -1.16±0.13 for poor, medium and good levels of muscular fitness in boys and 1.01±0.16 > 0.10±0.09 > -1.02±0.15 in girls, both p<0.001), but differences disappeared when controlling for BMI. BMI acted as a full mediator between muscular fitness and most cardiometabolic risk factors (Sobel test z=11.44 for boys; z=-11.83 for girls; p<0.001 in CMRI mediation model) and as a partial mediator in the case of waist circumference (Sobel test z=-14.86 for boys; z=-14.51 for girls; p<0.001). CONCLUSIONS BMI mediates the association between muscular fitness and cardiometabolic risk in schoolchildren. Overall, good muscular fitness is associated with lower cardiometabolic risk, but particularly when accompanied by normal weight.. Ana Díez Fernández. 45.

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(61)        . 3.  [Resúmenes]  .

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(63) Resúmenes  . Resumen  manuscrito  1  . OBJETIVO La relación entre la condición física cardiorrespiratoria y el síndrome metabólico está bien establecida, aunque el grado en el que el peso corporal puede actuar como un factor confusor o mediador en esta relación es incierto. El objetivo de este estudio fue examinar si la asociación entre la condición física cardiorrespiratoria y los factores de riesgo cardiometabólicos está mediada por el índice de masa corporal (IMC). DISEÑO Y METODOLOGÍA Se llevó a cabo un estudio transversal que incluyó a 1158 escolares entre 8 y 11 años de la provincia de Cuenca, España. Se midieron peso, talla, circunferencia de cintura, presión arterial, perfil lipídico, insulina en ayunas en plasma y la condición física cardiorrespiratoria (Shuttle Run test de 20 metros). Se estimó un índice de riesgo cardiometabólico validado con la suma de las puntuaciones z estandarizadas de la circunferencia de cintura, ratio del logaritmo triglicéridos/colesterol HDL (log TG/HDL-c), presión arterial media y logaritmo de insulina en ayunas. Para calcular si la asociación entre la condición física cardiorrespiratoria y el riesgo cardiometabólico estaba mediada por el IMC, se utilizaron modelos de regresión lineal según el procedimiento descrito por Baron y Kenny para análisis de mediación. RESULTADOS En niñas, el IMC actúa como mediador total entre la capacidad cardiorrespiratoria y los factores de riesgo cardiometabólico, excepto el ratio log TG/HDL-c. En niños, el IMC es un mediador total entre la capacidad cardiorrespiratoria y el ratio log TG/HDL-c y la presión arterial media, y mediador parcial con el resto de factores de riesgo cardiometabólicos. CONCLUSIONES El IMC media la asociación entre la condición física cardiorrespiratoria y el síndrome metabólico en escolares. En general, buenos niveles de condición física cardiorrespiratoria se asocian con un menor riesgo cardiometabólico, especialmente cuando se acompaña de una reducción del peso corporal.. Ana Díez Fernández. 49.

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(65) Resúmenes  . Resumen  manuscrito  2   OBJETIVO La condición física muscular se ha relacionado con el perfil cardiometabólico en niños, pero si el peso corporal actúa como un factor mediador o confusor en esta relación sigue siendo objeto de controversia. El objetivo de este estudio fue examinar si la asociación entre la condición física muscular y los factores de riesgo cardiometabólicos está mediada por el índice de masa corporal (IMC). DISEÑO Y METODOLOGÍA Se llevó a cabo un estudio transversal que incluyó a 1158 escolares entre 8 y 11 años de la provincia de Cuenca, España. Se midieron variables antropométricas y bioquímicas y se calculó un índice de fuerza muscular con las puntuaciones z de la dinamometría/peso y el salto horizontal, y un índice de riesgo cardiometabólico validado previamente Se usaron modelos de regresión lineal para el análisis de mediación para calcular si la asociación entre la fuerza muscular y el riesgo cardiometabólico estaba mediada por el IMC. RESULTADOS Tanto niños como niñas con normopeso tuvieron un mejor perfil cardiometabólico que sus compañeros con sobrepeso u obesidad después de controlar por la condición física muscular. Las medias marginales estimadas ± error estándar para el índice de riesgo cardiometabólico en las categorías normopeso, sobrepeso y obesidad fueron 0.75±0.06 < 0.84±0.10 < 2.18±0.16 en niños y -0.73±0.06 < 0.96±0.10 < 2.71±0.17 en niñas, ambas p<0.001. Los escolares que tenían mejor condición física muscular tenían un mejor perfil cardiometabólico (medias marginales estimadas ± error estándar para el índice de riesgo cardiometabólico fueron 1.04±0.13 > 0.05±0.09 > -1.16±0.13 para cuartil bajo, medio y alto condición física muscular en niños y 1.01±0.16 > 0.10±0.09 > -1.02±0.15 en niñas, ambas p<0.001), pero las diferencias desaparecieron cuando se controló por el IMC. En escolares, el índice de masa corporal actuó como mediador total de la asociación entre condición física muscular y la mayoría de factores de riesgo cardiovascular (test de Sobel z=-11.44 en niños; z=-11.83 en niñas; p<0.001 en el modelo de mediación con índice de riesgo cardiometabólico), excepto para la circunferencia de cintura, que actuó como mediador parcial (test de Sobel z=-14.86 en niños; z=-14.51 en niñas; p<0.001).. Ana Díez Fernández. 51.

(66) Resúmenes   CONCLUSIONES El IMC media la asociación entre la condición física muscular y el riesgo cardiometabólico en escolares. En general, buenos niveles de fuerza muscular se asocian con un menor riesgo cardiometabólico, especialmente cuando se acompaña de una reducción del peso corporal.. 52. Doctoral Thesis UCLM - CESS.

(67)  . 4.  Manuscript  I:  Obesity  as  a  mediator  of   the  influence  of  cardiorespiratory  fitness   on  cardiometabolic  risk:  a  mediation   analysis    .    .  .

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(69) Manuscript  I  . 4.1  Background  . Metabolic syndrome (MetS) is a cluster of cardiometabolic disorders that is considered to be a predictor of cardiovascular disease, type 2 diabetes, and overall mortality (27-29). The definition of MetS is controversial, although all currently accepted definitions include insulin resistance or glucose intolerance, hypertension, dyslipidemia and central obesity (26, 30). The clustering of elevated levels of these risk factors track from childhood to adolescence and adulthood (20, 67, 68). Both physical activity and cardiorespiratory fitness (CRF) have evidenced a strong association with the clustering of cardiometabolic risk factors in children and youth (85, 86). It has been described that physical activity and CRF are independently and inversely associated with MetS, and better levels of CRF in children have shown lower cardiometabolic risk (61, 86, 88). On the other hand, several studies have observed an association between fatness and MetS in youth, such that as fatness increases, the risk of an unfavorable metabolic risk profile is raised (52, 89). But the extent to which adjustment for adiposity attenuates or modifies the association between CRF and metabolic risk is uncertain. In most of the studies reported to date, CRF appears to be independently associated with cardiometabolic risk even after adjusting for adiposity, although the magnitude of the association appears to be small to moderate when adiposity is included in the models (85, 107). Likewise, CRF levels do not completely account for the association between BMI and cardiometabolic risk (51, 107). Usually, confounding or mediator variables in health studies are controlled by multivariate methods such as ANCOVA, multiple linear regression or logistic regression, depending on the objectives of the study and/or whether the dependent variable is dichotomous or not. Mediation analysis is a statistical procedure which can be used to clarify the process underlying the relationship between two variables, and the extent to which this relationship can be modified, mediated or confounded by a third variable (101). A mediation effect occurs when the third variable (mediator) carries the influence of a given independent variable on a given dependent variable.. Ana Díez Fernández. 55.

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