Quality of Life Research

, Volume 22, Issue 7, pp 1515–1523

Health-related quality of life, obesity, and fitness in schoolchildren: the Cuenca study

Authors

  • Pablo Franquelo Morales
    • Emergency DepartmentHospital Virgen de la Luz
  • Mairena Sánchez-López
    • Social and Health Care Research CenterUniversity of Castilla-La Mancha
    • School of EducationUniversity of Castilla-La Mancha
  • Pablo Moya-Martínez
    • Social and Health Care Research CenterUniversity of Castilla-La Mancha
  • Jorge Cañete García-Prieto
    • Social and Health Care Research CenterUniversity of Castilla-La Mancha
  • María Martínez-Andrés
    • Social and Health Care Research CenterUniversity of Castilla-La Mancha
  • Noelia Lahoz García
    • Social and Health Care Research CenterUniversity of Castilla-La Mancha
    • Social and Health Care Research CenterUniversity of Castilla-La Mancha
Article

DOI: 10.1007/s11136-012-0282-8

Cite this article as:
Morales, P.F., Sánchez-López, M., Moya-Martínez, P. et al. Qual Life Res (2013) 22: 1515. doi:10.1007/s11136-012-0282-8

Abstract

Purpose

The purpose of this study was to analyze the association of weight status and physical fitness with health-related quality of life (HRQoL) and to examine the independent association of body mass index (BMI), cardiorespiratory fitness (CRF) and musculoskeletal fitness (MF) with HRQoL in schoolchildren.

Methods

Cross-sectional study of 1,158 schoolchildren, 8–11 years, from 20 schools in the Cuenca province, Spain. We measured weight, height, and physical fitness, measured by CRF (20-m shuttle run test) and MF index by summing the age–sex z scores of handgrip strength test/weight + standing broad jump test. Self-reported HRQoL was measured by KIDSCREEN-52 questionnaire.

Results

Normal weight boys scored better in physical well-being, mood and emotions, autonomy, and social support and peers dimensions than overweight/obese boys. The mean in self-perception dimensions was lower in obese girls compared to normal weight or overweight girls. Higher levels of CRF and MF were associated with better physical well-being in both genders. Multiple linear regression models showed that the influence of MF in boys and CRF in girls on HRQoL was greater than that of overweight.

Conclusions

This is one of the first studies that assess the association of CRF and MF with HRQoL while controlling for BMI. CRF and MF are closely related to HRQoL, in particular to physical well-being. Improving fitness could be a strategy of particular interest for improving the HRQoL of schoolchildren.

Keywords

Health-related quality of lifeSchoolchildrenCardiorespiratory fitnessMusculoskeletal fitnessObesity

Abbreviations

BMI

Body mass index

CRF

Cardiorespiratory fitness

HRQoL

Health-related quality of life

MF

Musculoskeletal fitness

MFI

Musculoskeletal fitness index

Background

Childhood obesity is an important public health problem in Spain [1] and worldwide [2]. Overweight and obesity prevalence based on measured weights and heights in schoolchildren from Cuenca in 2004 (35 %) ranked among the highest worldwide [3]. Such prevalence is similar to that found in other areas of Spain [4] and the Mediterranean area [5]. Obesity in children and adolescents has been associated with high risk of hypertension, hyperinsulinemia, dyslipidemia, and type 2 diabetes [68]. Several studies have shown that obesity impairs health-related quality of life (HRQoL) in children [913]. However, the relationship between different aspects of psychosocial functioning and obesity is not very clear [11, 14, 15].

Physical fitness in children and adolescents is considered an important indicator of health [16]. Few studies have analyzed the relationship between physical fitness and HRQoL in children. A positive relationship between aspects of HRQoL and cardiorespiratory fitness (CRF) has been observed in children and adolescents [15, 17, 18]. To our knowledge, no study has examined the relationship between musculoskeletal fitness (MF) and HRQoL.

There is an inverse association between CRF and overweight in children and adolescents [16], and improvements in MF levels from childhood to adolescence are associated with a decrease in overall adiposity [19], but no study has jointly examined the association between overweight and CRF and MF with HRQoL.

The objectives of this study were to examine in schoolchildren: (1) the differences in HRQoL among body mass index (BMI), CRF, and MF categories; and (2) the independent association of BMI, CRF, and MF with HRQoL.

Methods

Study design and population

This was a cross-sectional study of the 1,596 schoolchildren, aged 8–11, invited; of which, 1,158 (72.6 %) agreed to participate in the study, from 20 public primary schools in the Province of Cuenca, Spain, during the 2010–2011 academic year. The study protocol was approved by the Clinical Research Ethics Committee of the Virgen de la Luz Hospital, in Cuenca. After obtaining the approval of the Director and the Board of Governors (Consejo Escolar) of each school, a letter was sent to all parents of children in 4th and 5th grade, inviting them to a meeting at which the study objectives were outlined and written authorization for their children’s participation was requested. Informative talks, in which the schoolchildren were asked to collaborate, were then held class by class.

Measurements anthropometrics

Data collection was performed at the schools. Weight was measured twice, to the nearest 100 g, with a calibrated digital scale (SECA Model 861; Vogel & Halke, Hamburg, Germany) with the children lightly dressed and without shoes. Height was measured twice to the nearest millimeter with a wall-mounted stadiometer, with the children without shoes, standing straight against the wall to align the spine with the stadiometer. The head was positioned with the chin parallel to the floor. The mean of the two measurements of weight and height was used to calculate BMI as weight in kilograms divided by the square of the height in meters (kg m−2). Children were classified as normal weight, overweight, or obese according to gender-and age-specific cut-offs defined by Cole et al. [20].

Health-related quality of life

HRQoL was measured using the KIDSCREEN-52 questionnaire, a self-reported, generic measure of HRQoL for children and adolescents validated for people 8–18 years old [21]. The KIDSCREEN-52 measures HRQOL in 10 dimensions: physical well-being, psychological well-being, moods and emotions, self-perception, autonomy, parent relation and home life, social support and peers, school environment, social acceptance (bullying), and financial resources, and a summary index of HRQoL (KIDSCREEN-10 index) was also calculated. The KIDSCREEN items use a five-point Likert-type scale to assess either frequency (never–seldom–sometimes–often–always) or intensity (not at all–slightly–moderately–very–extremely). The recall period was 1-week. Scores for each dimension were calculated and then, according to the methods described by the authors of the original scale by using Rash analysis [22], transformed into t values with a mean of 50 and standard deviation of 10 [23]. Higher scores indicate better HRQoL. The Spanish version of the KIDSCREEN-52 has been shown to have acceptable levels of reliability and validity [24].

Physical fitness

CRF was assessed by the 20-m shuttle run test [25]. Participants are required to run between two lines 20 m apart, while keeping pace with audio signals emitted from a prerecorded CD. The initial speed is 8.5 km h−1, which is increased by 0.5 kmh−1 min−1 (1 min equals one stage). Schoolchildren were encouraged to keep running as long as possible throughout the course of the test. We recorded the last half-stage completed as an indicator of his or her CRF. MF was assessed using two tests: (1) handgrip test (maximum handgrip strength assessment) using a hand dynamometer with adjustable grip (TKK 5401 Grip D; Takey, Tokyo, Japan). The participant squeezes gradually and continuously for at least 2 s, performing the test with the right and left hands in turn, using the optimal grip span. Children made two trials (alternately with both hands) with a short resting time between them. The maximum score in kilograms for each hand was recorded. The average (in kilograms) of both hands was used in the analysis. (2) The standing broad jump test (lower limb explosive strength assessment): from a starting position immediately behind a line, standing with feet approximately shoulder width apart, the schoolchildren jump horizontally to achieve maximum distance. The result was recorded in centimeters [16].

We calculated an age- and sex-specific MF index (MFI) as the sum of the standardized scores of handgrip strength test/weight and standing broad jump test.

Sexual maturation was assessed with standardized procedure in which parents identified in some figures the pubertal status of their children according to Tanner stages.

Statistical analysis

We evaluated the fit of the different variables to a normal distribution both through graphical procedures and by the Kolmogorov–Smirnov test. All variables were normally distributed.

Both CRF and MFI were categorized by percentiles (poor < P25, satisfactory = P25–P75, and good > P75). Analysis of covariance (ANCOVA) was used to test differences in the mean scores of the KIDSCREEN-52 dimensions and KIDSCREEN-10 index among categories of CRF, MFI and BMI, by sex, and controlling for age. Multiple linear regression models were estimated using KIDSCREEN-52 dimensions and KIDSCREEN-10 index as dependent variables, alternately BMI, CRF, and MFI as independent variables, and controlling for age, by sex. Lastly, models including jointly BMI, CRF, and MFI were used to estimate the independent effect of each variable.

All statistical analysis was performed using IBM SPSS statistics 19 software. For statistical significance, a p ≤ 0.05 was considered as criterion.

Results

Table 1 shows descriptive characteristics by sex. There were no significant differences in age and sex among those who participated and those who did not. The mean scores for each of the dimensions of the KIDSCREEN-52 were similar in boys and girls except for physical well-being, a domain which was higher in boys, and parents’ relation and home and school environment which were higher in girls.
Table 1

Descriptive characteristics of the studied schoolchildren, by sex

 

Boys (n = 587)

Girls (n = 571)

p

Age (years)

9.51 (0.7)

9.48 (0.7)

0.479

Weight (kg)

37.67 (9.6)

37.02 (8.8)

0.220

Height (cm)

139.52 (6.9)

139.61 (7.1)

0.820

BMI (kg/m2)

19.16 (3.8)

18.84 (3.5)

0.142

Overweight/Obesity (%)

37.6

33.3

0.120

Cardiorespiratory fitness (20-m shuttle run, stage)

4.09 (1.8)

2.87 (1.2)

<0.001

Handgrip (kg)

15.38 (3.4)

13.77 (3.1)

<0.001

Standing broad jump (cm)

120.11 (18.7)

109.64 (17.4)

<0.001

Musculoskeletal fitness index

−0.001 (1.7)

−0.001(1.7)

0.990

Tanner stage

1.54 (0.6)

1.65 (0.7)

0.150

(I–II/III–V) (%)

(22.8/77.2)

(20.1/79.9)

0.266

KIDSCREEN-52 dimensions*

 Physical well-being

54.4 (9.5)

51.9 (9.8)

<0.001

 Psychological well-being

55.8 (8.5)

56.8 (7.8)

0.057

 Moods and emotions

48.4 (10.0)

48.4 (9.8)

0.893

 Self-perception

55.2 (9.6)

54.4 (9.6)

0.211

 Autonomy

53.2 (10.2)

52.4 (9.6)

0.179

 Parents relation and home

53.0 (8.6)

54.1 (8.7)

0.025

 Social support and peers

55.1 (10.5)

54.8 (10.2)

0.589

 School environment

52.8 (12.2)

58.3 (10.1)

<0.001

 Social acceptance

45.0 (11.3)

44.5 (11.3)

0.423

 Financial resources

49.7 (9.8)

49.8 (9.4)

0.864

 KIDSCREEN-10 index

54.2 (10.1)

54.3 (9.6)

0.889

Data are presented as mean (standard deviation), except for prevalence of overweight/obesity and Tanner stage

Musculoskeletal fitness index was calculated as the sum of the standardized z scores of the ratio dynamometry/weight and standing broad jump test

*Higher scores indicate better health-related quality of life

BMI body mass index as total body weight/height (kg/m2)

In bold type: sex differences (p ≤ 0.05)

Table 2 shows mean differences in HRQoL dimensions by BMI, CRF, and MFI categories, controlling for age, by sex. Overall, HRQoL was worse in children with excess of weight and better in children with higher levels of fitness. However, only in a few dimensions were the differences large enough to achieve statistical significance. In boys, significant differences by BMI categories were observed in physical well-being, mood and emotions, autonomy and social support and peers. In girls, no differences by BMI categories were found in any dimension except for self-perception.
Table 2

Mean differences in health-related quality of life KIDSCREEN-52 dimensions* by body mass index, cardiorespiratory fitness, and muscular strength index categories, by analysis of covariance (ANCOVA) controlling for age, by sex

Boys

 

NW (n = 366)

BMI OV (n = 159)

OB (n = 62)

p

Poor (n = 146)

CRF Satisfactory (n = 272)

Good (n = 148)

p

Poor (n = 145)

MFI Satisfactory (n = 292)

Good (n = 145)

p

PH

55.5 (9.3)OV/OB

53.1 (9.6)

50.6 (9.0)

<0.001

51.2 (9.9)S/G

54.8 (8.6)G

57.0 (9.8)

<0.001

51.1 (8.2)S/G

54.8 (9.7)

56.8 (9.3)

<0.001

PW

55.6 (8.6)

55.9 (8.3)

57.1 (8.4)

0.438

55.2 (9.6)

56.3 (7.8)

55.7 (8.7)

0.437

55.2 (8.3)

56.0 (8.8)

56.0 (8.2)

0.644

ME

48.5 (10.0)

49.5 (10.3)OB

45.5 (8.0)

0.036

48.1 (10.9)

47.9 (9.4)

49.8 (10.3)

0.171

48.0 (9.0)

48.0 (10.0)

49.8 (10.6)

0.176

SP

55.5 (9.7)

54.7 (9.2)

54.4 (10.2)

0.573

54.3 (10.1)

55.3 (9.3)

56.1 (9.6)

0.209

54.1 (9.7)

55.2 (9.3)

56.3 (10.1)

0.146

AU

52.9 (10.2)

54.6 (10.5)

50.9 (9.2)

0.050

51.6 (10.7)

53.6 (10.1)

54.2 (10.1)

0.093

52.7 (10.1)

52.6 (10.7)

54.8 (9.4)

0.111

PA

53.1 (8.6)

53.0 (8.6)

52.4 (8.7)

0.840

52.5 (8.8)

52.9 (8.5)

53.8 (8.6)

0.372

52.2 (8.8)

52.9 (8.8)

53.8 (8.4)

0.283

PE

55.9 (10.4)

54.2 (10.7)

52.6 (10.2)

0.037

52.4 (11.2)S/G

55.2 (9.6)G

57.6 (10.8)

<0.001

52.1 (10.7)S/G

55.0 (9.9)G

58.1 (10.6)

<0.001

SC

52.5 (12.5)

53.3 (11.2)

53.3 (12.6)

0.726

52.5 (11.8)

53.6 (12.3)

52.0 (11.9)

0.425

52.6 (10.8)

52.7 (12.3)

53.4 (13.1)

0.798

BU

45.7 (11.2)

44.4 (11.4)

42.6 (11.9)

0.105

43.6 (11.7)

45.3 (11.5)

45.9 (10.8)

0.149

43.5 (11.3)G

44.8 (11.4)

46.9 (11.0)

0.032

FI

49.8 (10.0)

49.8 (9.8)

48.3 (9.0)

0.576

48.7 (10.3)

49.6 (9.9)

50.9 (9.3)

0.286

48.5 (9.8)

49.5 (9.8)

51.1 (9.8)

0.102

KIDSCREEN 10 index

54.3 (10.1)

55.0 (10.7)

51.8 (8.4)

0.100

53.3 (11.6)

54.3 (9.5)

55.4 (9.8)

0.198

53.5 (9.8)

53.9 (10.4)

55.7 (9.7)

0.125

Girls

 

NW (n = 381)

BMI OV (n = 136)

OB (n = 54)

p

Poor (n = 96)

CRF Satisfactory (n = 340)

Good (n = 120)

p

Poor (n = 141)

MFI Satisfactory (n = 284)

Good (n = 142)

p

PH

52.4 (10.0)

51.4 (8.9)

50.2 (11.1)

0.179

49.7 (9.2)G

51.6 (9.8)G

55.0 (9.8)

<0.001

49.3 (9.1)S/G

51.9 (9.7)G

54.7 (10.1)

<0.001

PW

56.4 (7.7)

57.6 (8.2)

57.3 (7.8)

0.287

56.3 (7.5)

56.6 (8.1)

57.4 (7.6)

0.494

56.3 (7.9)

56.9 (8.1)

56.9 (7.3)

0.738

ME

48.6 (9.8)

48.9 (10.2)

45.0 (8.4)

0.071

46.2 (9.2)

48.5 (10.0)

50.0 (10.0)

0.053

47.1 (9.0)

48.9 (9.6)

48.6 (11.0)

0.212

SP

55.3 (9.6)OB

54.0 (9.3)OB

49.7 (9.1)

0.001

52.4 (9.9)G

54.6 (9.4)

55.8 (9.8)

0.050

53.2 (10.1)

54.7 (9.1)

55.3 (10.0)

0.194

AU

51.8 (9.4)

53.8 (10.4)

52.5 (9.2)

0.102

53.3 (10.2)

51.8 (9.6)

53.1 (9.6)

0.266

51.9 (10.3)

52.1 (9.0)

53.4 (10.3)

0.395

PA

54.3 (8.8)

54.1 (8.2)

53.2 (8.9)

0.863

53.4 (8.7)

53 (8.9)

54.9 (8.1)

0.584

52.9 (9.1)

54.3 (8.6)

55.0 (8.4)

0.122

PE

54.9 (10.6)

54.5 (8.8)

54.9 (10.4)

0.932

53.4 (10.5)

54.5 (9.8)

56.8 (11.0)

0.044

53.4 (9.4)

55.1 (10.1)

55.6 (11.1)

0.161

SC

58.0 (10.1)

59.8 (9.6)

56.6 (10.4)

0.097

57.1 (10.5)

58.3 (9.8)

59.3 (10.4)

0.334

57.1 (10.1)

58.9 (9.9)

58.3 (10.3)

0.207

BU

45.0 (11.6)

43.9 (10.7)

42.1 (10.9)

0.237

42.3 (11.1)G

44.3 (11.2)

47.2 (11.6)

0.013

43.8 (10.9)

44.4 (11.1)

45.4 (12.2)

0.480

FI

49.6 (9.3)

50.1 (9.9)

50.0 (9.1)

0.723

49.1 (9.5)

49.5 (9.4)

50.7 (9.4)

0.592

49.3 (8.9)

50.3 (9.2)

49.3 (10.3)

0.430

KIDSCREEN 10 index

54.5 (9.8)

54.6 (9.2)

52.3 (8.8)

0.371

52.4 (9.2)G

54.1 (9.5)

56.4 (10.2)

0.017

51.7 (8.6)S/G

54.8 (8.8)

55.8 (11.2)

0.001

Categories of body mass index (BMI) are normal weight (NW), overweight (OV), and obesity (OB) according to gender-and age-specific cut-offs defined by Cole et al. (2000). Categories of cardiorespiratory fitness (CRF) are poor (P), satisfactory (S), and good (G), representing the 1st, 2nd and 3rd, and 4th quartiles. Musculoskeletal fitness index (MFI) was calculated as the sum of the standardized z scores of the ratio dynamometry/weight and standing broad jump test. Musculoskeletal fitness index are poor (P), satisfactory (S), and good (G), representing the 1st, 2nd and 3rd, and 4th quartiles

PH physical well-being, PW psychological well-being, ME moods and emotions, SP self-perception, AU autonomy, PA parents relation and home life, PE social support and peers, SC school environment, BU social acceptance, FI financial resources

*Higher scores indicate better health-related quality of life

In bold type: p value ≤ 0.05

Superscript letter indicates statistical significance (p ≤ 0.05) for post hoc hypothesis tests determined with the Bonferroni correction for multiple comparisons

In both girls and boys, mean scores in physical well-being and social support and peers dimensions were higher in children with higher levels of CRF. In addition, girls with higher levels of CRF scored higher in self-perception, social acceptance and in the KIDSCREEN-10 index (Table 2). Lastly, no significant differences in mean scores of most of the KIDSCREEN-52 dimensions by MFI categories were observed, except for physical well-being, social support and peers, and social acceptance, in which boys with better MFI scored higher; and except for physical well-being and KIDSCREEN-10 index, in which girls with better MFI scored higher.

BMI, CRF, and MFI were included as predictors of KIDSCREEN-10 index but also of each dimension of KIDSCREEN-52 in multiple regression models, controlling for age, by sex (Table 3). In boys, MFI was significantly associated with physical well-being, self-perception, autonomy, social support and peers, financial resources, and KIDSCREEN-10 index; CRF was only associated with social support and peers; no dimension was associated with BMI. In girls, CRF was associated with physical well-being, moods and emotions, self-perception, social support and peers, school environment, social acceptance, financial resources, and KIDSCREEN-10 index; BMI was only associated with self-perception, and MFI with physical well-being and KIDSCREEN-10 index.
Table 3

Associations of body mass index, cardiorespiratory fitness, and musculoskeletal fitness index with KIDSCREEN-52 dimensions, controlling for age, by sex

 

Model 1

Model 2

Boys

Girls

Boys

Girls

β

p value

β

p value

β

p value

β

p value

BMI

 PH

−0.173

<0.001

−0.094

0.028

−0.014

0.796

0.077

0.136

 PW

0.027

0.520

0.024

0.572

0.080

0.156

0.071

0.174

 ME

−0.034

0.431

−0.068

0.118

0.027

0.645

−0.010

0.857

 SP

−0.062

0.147

−0.178

<0.001

0.035

0.532

−0.170

0.001

 AU

0.001

0.995

0.024

0.573

0.089

0.113

0.052

0.319

 PA

−0.017

0.696

−0.060

0.161

0.025

0.659

0.008

0.880

 PE

−0.119

0.005

−0.042

0.329

0.044

0.422

0.013

0.800

 SC

−0.031

0.473

0.005

0.914

0.056

0.325

0.056

0.325

 BU

−0.111

0.008

−0.074

0.074

−0.041

0.464

−0.024

0.642

 FI

−0.013

0.761

−0.013

0.760

0.109

0.051

0.014

0.792

 KIDSCREEN 10 index

−0.023

0.607

−0.070

0.110

0.043

0.467

0.051

0.342

CRF

 PH

0.208

0.001

0.231

0.001

0.086

0.117

0.163

0.001

 PW

0.018

0.669

0.081

0.063

0.013

0.823

0.113

0.032

 ME

0.070

0.114

0.140

0.002

0.045

0.434

0.142

0.009

 SP

0.089

0.039

0.157

<0.001

0.036

0.528

0.131

0.014

 AU

0.070

0.108

0.002

0.971

0.045

0.418

0.045

0.418

 PA

0.076

0.082

0.079

0.072

0.049

0.392

0.042

0.432

 PE

0.211

<0.001

0.116

0.005

0.108

0.050

0.136

0.010

 SC

−0.007

0.876

0.098

0.025

−0.020

0.728

0.112

0.031

 BU

0.120

0.005

0.164

0.001

0.043

0.437

0.171

0.001

 FI

0.092

0.033

0.086

0.048

0.077

0.169

0.115

0.028

 KIDSCREEN 10 index

0.061

0.171

0.172

0.001

0.016

0.786

0.138

0.010

MFI

 PH

0.244

<0.001

0.226

<0.001

0.191

0.001

0.194

<0.001

 PW

0.047

0.259

0.016

0.700

0.090

0.114

0.001

0.991

 ME

0.070

0.104

0.065

0.138

0.065

0.266

−0.011

0.842

 SP

0.117

0.005

0.059

0.175

0.124

0.031

−0.094

0.088

 AU

0.093

0.028

0.009

0.832

0.131

0.021

0.039

0.475

 PA

0.062

0.144

0.082

0.056

0.076

0.184

0.077

0.164

 PE

0.233

<0.001

0.056

0.193

0.217

<0.001

−0.009

0.878

 SC

0.025

0.551

0.054

0.200

0.076

0.181

0.038

0.481

 BU

0.135

0.001

0.062

0.141

0.093

0.097

−0.034

0.531

 FI

0.103

0.014

0.005

0.910

0.129

0.023

−0.043

0.434

 KIDSCREEN 10 index

0.089

0.041

0.147

0.001

0.118

0.046

0.109

0.050

PH physical well-being, PW psychological well-being, ME moods and emotions, SP self-perception, AU autonomy, PA parents relation and home life, PE social support and peers, SC school environment, BU social acceptance, FI financial resources

BMI body mass index as total body weight/height (kg/m2), CRF cardiorespiratory fitness, and MFI musculoskeletal fitness index was calculated as the sum of the standardized z scores of ratio dynamometry/weight and standing broad jump test

In bold type: p value ≤ 0.05

Model 1 controlling for age

Model 2 further adjustment for CRF and MFI to BMI; for BMI and MFI to CRF; and for BMI and CRF to MFI

Discussion

The present study is, to our knowledge, the first that analyzes the independent effects of overweight and two components of physical fitness, MF and CRF, on the HRQoL of schoolchildren. Overall, our data reveal lower levels of HRQoL in overweight/obesity children and higher levels of HRQoL in children with satisfactory/good physical fitness, but differences were not statistically significant in most of the dimensions of KIDSCREEN-52. In multivariate analysis, higher levels of CRF in girls and MF in boys were more closely associated with HRQoL than overweight; after controlling for physical fitness variables, self-perception in girls was the only variable that remained associated with BMI.

Overweight and obesity

Several studies provide evidence that overweight/obesity impairs HRQoL in children and adolescents, mainly in physical dimensions of HRQoL [1113, 26, 27]. Moreover, overweight and obesity during childhood and adolescence have been negatively associated with several aspects of adult HRQoL [28]. In accordance with those findings, our study shows that, in bivariate analysis, overweight and obese boys score worse in physical well-being, moods and emotions, autonomy and social support and peers, and overweight and obese girls score worse in self-perception, but no other dimensions of HRQoL are influenced significantly by excess of weight. Our data are also partially consistent with those of a European study [10] that also used the KIDSCREEN-52 instrument, in a sample of children and adolescents from 14 countries. This study concluded that overweight significantly impaired HRQoL, in particular in the physical well-being and self-perception dimensions, although other dimensions were affected in samples from some countries. However, comparisons between BMI categories were not similar, because in the European study, overweight and obesity were combined in a single category. This may be the explanation for the differences in the results of both studies.

Cardiorespiratory fitness

CRF has been associated with both mental and physical components of HRQoL in adult males [29, 30]. Evidence suggests that improvements in CRF have a positive effect on the psychological well-being of children and adolescents [16, 18]. To our knowledge, no studies have examined the relationship between aerobic capacity and HRQoL in population-based samples of children; in our study, higher levels of CRF fitness are associated with better scores in the dimensions physical well-being and social support and peers in boys; in girls, the CRF was associated with better scores in physical well-being, self-perception, social acceptance, and KIDSCREEN-10 index. The lack of studies correlating CRF and HRQoL hampers comparisons, but a study examining the associations between CRF and fatness with a similar construct, positive health, has been recently published [15]. In this study, CRF was associated with life satisfaction, though life satisfaction is a construct quite different to physical well-being.

Musculoskeletal fitness

Several studies have shown the beneficial impact of MF and resistance training on cardiometabolic risk (thus including obesity) in adults [31, 32] and in children and adolescents [16, 19, 33]. A study in Finnish young men indicates that a composite score of CRF and MF was associated with both mental and physical components of HRQoL, and also obesity and other cardiometabolic risk factors have been associated with HRQoL in adults [34] and children [13, 35], but this association may be confounded by physical fitness [15, 17, 36]. To our knowledge, no study has examined the independent association between MF and HRQoL. In our study, MF was associated with physical well-being in children in a similar way to CRF. Furthermore, in boys, MF was also associated with social acceptance and social support and peers. In girls, MF was also associated with KIDSCREEN-10 index; therefore, MF is a component of physical fitness that has a greater impact on the HRQoL of boys than on that of girls.

Gender differences in the impact of the components of physical fitness on quality of life could be attributed to differences in needs of strength or aerobic capacity that require playground games and sports in which boys and girls participate. Our data also reveal gender differences in HRQoL dimensions that are associated with physical fitness, probably because of the greater importance of psychological and emotional dimensions in girls [37]. Finally, the KIDSCREEN includes dimensions as autonomy (examines the autonomy and opportunity to shape one’s social and leisure time) and parents relation and home (explores the quality of the interaction with parents or guardians), which were not related to neither physical fitness nor BMI.

Health-related quality of life, obesity, and fitness

As far as we know, only one study has jointly analyzed the effects of overweight/obesity, CRF, and MF on HRQoL, but in a small sample of older people [38]. The multivariate analysis allows us to examine the association between overweight, CRF, and MF with the HRQoL. In boys, with BMI, CRF, and MFI in the model, and controlling for age, the association of MF with the HRQoL was stronger than that of CRF or overweight. On the contrary, in girls, CRF was the physical fitness dimension more closely associated with HRQoL. From the data of the Aerobics Center Longitudinal Study, in recent years, has emerged the hypothesis “fat but fit” for which the excess of cardiometabolic risk in people who are overweight is greatly mitigated if they have good physical fitness [39]. As for cardiometabolic risk, the “fat but fit” hypothesis seems also useful for the understanding of the relationships between excess of weight, physical fitness, and HRQoL in children, as has been shown in adults [40, 41]; actually, even in the case of HRQoL, when we control for fitness, the association between excess of weight and HRQoL almost disappears.

Limitations and strengths

The primary limitation of our study was the cross-sectional design, which prevents us from making cause–effect inferences. Generalizations based on our results could be limited because the HRQoL construct in children depends on several factors more than those examined in our study, such as family’s socioeconomic levels [42] or comorbidities (i.e., attention-deficit/hyperactivity disorder that has been associated with both overweight and HRQoL) [43, 44]. Moreover, although population-based studies have some advantages, we are conscious that in our sample, very few children showed extremely high BMI levels; therefore, the effect of morbid obesity on HRQoL may have been “diluted”; thus, in clinical samples of children, the association between overweight and HRQoL may be stronger. On the other hand, we did not control the influence of sexual maturation, although in our opinion the homogeneity of the sample in this variable (see Table 1) presumably has unnecessary control of this variable; in addition, not all the parents answered the items related to the Tanner stage; thus, the control of these variable diminishes in an important way the statistical power of our study. Furthermore, because there are several interrelated factors influencing the jump ability [45, 46], we are conscious about the weakness of whatever summative index for muscular strength. In fact, there is not a validated index like BMI for weight status. For this reason, we have used an index that we have proved to have a moderate relationship with cardiometabolic risk factors in children [47], but obviously there is not evidence that this index works in the same way when analyzing the relationship between MF with HRQoL.

Finally, we are conscious of the importance of genetics determinants of both obesity and physical fitness [48, 49], but also about the importance of epigenetics influences, but in our study, these influences were not controlled.

Among the strengths of our study, it should be noted that CRF, MF, and BMI were objectively measured. We used a population-based sample including children from 20 public schools spread throughout Cuenca, a Spanish province where over 90 % of children attend public school; therefore, our sample could be considered representative of the Cuenca’s schoolchildren population. Finally, our data support that the instrument used to evaluate the HRQoL in our sample, the KIDSCREEN-52 in its Spanish version, might be a sensitive instrument to assess the impact of overweight and fitness on HRQoL of schoolchildren.

Conclusions

Our findings are important from a clinical and public health point of view because they show that controlling for physical fitness mitigates ostensibly the impact of overweight on HRQoL in schoolchildren; conversely, CRF in girls and MF in boys are variables closely associated with most of the dimensions of HRQoL. Therefore, our findings suggest that promoting physical activity in children, and thus improving fitness [50], could be a strategy of particular interest for improving the HRQoL of schoolchildren.

Acknowledgments

We thank the schools, families, and children for their enthusiastic participation in the study. This study was funded by the Ministry of Education and Science-Junta de Comunidades de Castilla-La Mancha (PII1I09-0259-9898 and POII10-0208-5325), and Ministry of Health (FIS PI081297). Additional funding was obtained from the Research Network on Preventative Activities and Health Promotion (Ref.—RD06/0018/0038).

Conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Copyright information

© Springer Science+Business Media Dordrecht 2012