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Keywords:

  • physical activity;
  • sedentary activities;
  • waist circumference;
  • BMI

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Objective: To determine whether physical activity, sedentary activities, and/or cardiorespiratory fitness are related to waist circumference in adolescents, as previously reported in adults.

Research Methods and Procedures: The study subjects were a representative sample of Spanish adolescents (N = 2859; 1357 boys, 1502 girls; age, 13 to 18.5 years), all of whom were involved in the AVENA (Food and Assessment of the Nutritional Status of Adolescents) study. BMI, waist circumference, pubertal maturation status, and cardiorespiratory fitness were measured in all. Leisure-time physical activity, sedentary activities, active commuting to school, and socioeconomic status were assessed by self-reported questionnaires.

Results: No relationship was found between leisure-time physical activity and BMI or waist circumference. In contrast, and in both boys and girls and after adjustment for confounding variables, cardiorespiratory fitness was found to be inversely associated with waist circumference and BMI, independent of sedentary activities or physical activity (p ≤ 0.001). The maximum oxygen consumption explained 13% of the variance in waist circumference in boys and 16% in girls. Sedentary activities were independently and directly related to waist circumference in both boys and girls (p ≤ 0.05) and to BMI in boys (p ≤ 0.05). Sedentary activities explained 10% of the variance in waist circumference in boys and 18% in girls. The BMI-adjusted waist circumference was inversely correlated with cardiorespiratory fitness in overweight-obese boys (p ≤ 0.05) and showed a trend toward significance in girls (p ≤ 0.1).

Discussion: Both moderate to high levels of cardiorespiratory fitness and sedentary activities, but not physical activity, are associated with lower abdominal adiposity, as measured by waist circumference.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Childhood obesity has reached epidemic proportions worldwide and its prevalence is increasing (1)(2)(3). This increase has led to a significant growth in economic costs (4). In adults, it is well established that abdominal adiposity is a strong predictor of morbidity and mortality, independent of BMI (5)(6). In addition, waist circumference has been shown to be a powerful marker of abdominal fat accumulation (7) and a significant predictor of cardiovascular disease and type 2 diabetes after adjustment for BMI (8)(9)(10)(11)(12). It has also been reported (13) that, within a given BMI category, children and adolescents with a large waist circumference are more likely to have elevated coronary artery disease risk factors compared with those with a small waist circumference. Consequently, waist circumference could be a useful tool for studying obesity in adolescents (especially central obesity) and its relationship with daily activity patterns and cardiorespiratory fitness.

The association between sedentary activities and obesity seems to be clearly established (14)(15), but the results obtained so far on the relationship between physical activity and obesity in children and adolescents are inconsistent (16)(17)(18). In adults, for a given BMI, several studies have reported that individuals showing better cardiorespiratory fitness have less abdominal fat and/or smaller waist circumferences (19)(20)(21). The mechanism by which the cardiorespiratory fitness is linked to abdominal fat has not been completely clarified, but presumably this is because cardiorespiratory fitness is a marker for physical activity and its effect on energy balance. To our knowledge, this relationship has not been studied in adolescents. The aim of this study was to explore the relationships between waist circumference plus BMI and physical activity, sedentary activities, and cardiorespiratory fitness in a representative sample of Spanish adolescents.

Research Methods and Procedures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Study Sample and Design

The data presented in this paper were gathered as a part of the Food and Assessment of the Nutritional Status of Adolescents (AVENA)1 study, a population-based cross-sectional multicenter study on the etiology and pathogenesis of obesity and related metabolic disorders during adolescence. The complete methodology has been published elsewhere (22)(23). The subjects of this study were adolescents 13 to 18.5 years old. Given the heterogeneity of this population, subjects from public and private secondary schools and technical colleges were included. Sampling was multistaged, performed at random, and stratified by town of origin (five Spanish cities), socioeconomic status, sex, and age.

Subjects with metabolic diseases, who were pregnant, or who were alcohol or drug abusers were excluded. The variable that showed the greatest variance in the population, BMI, was used to determine the sample size (23). A total of 2100 subjects were deemed necessary for the full study to be properly conducted. These subjects were distributed by cities and proportionally by sex and age (13, 14, 15, 16, and 17 to 18.5 years). In fact, a greater number of subjects were initially chosen to avoid problems of drop-out and consequent data loss. The final figure was adjusted by a weighting factor to balance the sample according to the age distribution of the Spanish population and to guarantee true representation of each of the stratified groups (Instituto Nacional de Estadística, http:www.ine.es). After eliminating those subjects who failed to meet the inclusion criteria, the final sample was composed of 2859 subjects (1357 boys and 1502 girls). Parents and school supervisors were informed by letter about the nature and purpose of the study, and written informed consent to be included was requested. The study protocol was performed in accordance with the ethical standards laid down in the 1975 Declaration of Helsinki (as revised in Hong Kong in 1989 and in Edinburgh in 2000) and approved by the Review Committee for Research Involving Human Subjects of the Hospital Universitario Marqués de Valdecilla (Santander, Spain).

Anthropometric Measurements

All anthropometric measurements were made with subjects barefoot and in their underwear. Weight was measured using a Seca scale (range, 0.05 to 130 kg; precision, 0.05 kg), and height was measured using a stadiometer incorporated into this same apparatus (range, 60 to 200 cm; precision, 1 mm). Waist and hip circumferences were measured using an inelastic tape (range, 0 to 150 cm; precision, 1 mm). The harmonization and standardization of anthropometric measurements used to assess body composition in the AVENA study were strictly controlled and have been published elsewhere (2)(23). The International Obesity Task Force-proposed gender- and age-adjusted cut-off points (24) were used to categorize the subjects as overweight-obese or normal weight. Trained interviewers asked the adolescents to classify themselves in one of the five stages of pubertal maturity defined by Tanner and Whitehouse (25). This standard staging describes breast and pubic hair development in girls and genital and pubic hair development in boys. The first Tanner stage corresponds to the prepubertal state; subjects classified in Tanner Stage 5 are completely mature.

Measurement of Cardiorespiratory Fitness

Maximum aerobic capacity was assessed by the 20-m shuttle run test (26). Running pace was determined by audio signals emitted from a prerecorded cassette tape; the initial velocity was 8.5 km/h, which was increased by 0.5 km/h per minute (i.e., per stage). Subjects were instructed to run in a straight line, to pivot on completing a shuttle, and to pace themselves in accordance with the audio signals. The test was finished when the subject failed to reach the end lines concurrent with the audio signals on two consecutive occasions. Scores were recorded as the number of stages completed. The equations of Léger et al. (27) were used to estimate the maximum oxygen consumption (Vo2max). The reliability and validity of this test for determining the Vo2max in children and adolescents has been widely documented (27)(28)(29). A constant level of encouragement was given to participants throughout the test. Subjects were instructed to abstain from strenuous exercise for 48 hours before the test.

Physical Activity Assessment

To assess physical activity levels, a leisure-time physical activity index (PAI) was developed. Subjects answered four questionnaires on physical activity, at least 2 days before the 20-m shuttle run test was performed, to measure the practice of physical/sporting activity outside school hours. Energy expenditure [in metabolic equivalents (METs)] was an overall estimation, calculated from the assessed energy expenditure of 1 school day, 2 weekend days, and an average day during summer holidays. The questionnaires were designed on the basis of the previous day's activity checklist (30); they were previously translated and validated (31) for the Spanish population. These questionnaires include a list of the most common activities undertaken by adolescents, and the subjects marked those in which they had been involved. MET values were assigned to each, according to the classification of energy expenditure for each activity (32)(33). The PAI was calculated from the sum of the MET values for each activity. After principal component analysis with varimax rotation identified, a single axis was obtained with an auto value of 2.23, which explained 55.9% of the variance regarding the practice of physical activity. The sensitivity and specificity for the PAI were determined, and a cut-off point was obtained from the receiver operating characteristic curve (34) to distinguish between active and non-active subjects; this was calculated using the highest value of the Youden index (35). The area under the curve was 0.766 with a standard error of 0.011, showing the PAI to have intermediate discriminating power. The optimum cut-off point discriminating between active and non-active adolescents was −0.44.

The time spent in sedentary activities, which included television viewing and computer/video games, was recorded by questionnaire (36) and divided into two classes (≤2 and >2 h/d). A further question concerned active commuting to school, which was divided into two classes (0 to 15 and >15 min/d).

Assessment of Socioeconomic Status

Socioeconomic status was assessed by examining paternal educational level and occupation. The subjects were accordingly classified into five categories: low, medium-low, medium, medium-high, and high socioeconomic status.

Statistical Analysis

Means and standard deviation values for the different variables were recorded. For comparisons of variables with respect to gender and pubertal maturation status (pubescent, Tanner Stages 2 to 4; postpubescent, Tanner Stage 5), the Student's t test (for parametric variables) or Mann Whitney U test (for non-parametric variables) were used. One-way ANOVA (parametric variables) and the Kruskal-Wallis test (non-parametric variables) were used in analyses involving age. The dichotomous variable (active vs. non-active) was only used as a descriptive indicator of participation in leisure-time physical activity (Table 1). The PAI (continuous variable) was used in the rest of the statistical analysis.

Table 1.  Characteristics (means ± standard deviation) of the study subjects by gender
CharacteristicBoys (n = 1445)Girls (n = 1403)
  • Vo2max, maximum oxygen consumption.

  • *

    p ≤ 0.05 boys vs. girls.

  • p ≤ 0.01 boys vs. girls.

  • p ≤ 0.001 boys vs. girls. Otherwise not significant.

  • §

    International gender- and age-specific BMI cut-off points (24).

Age (13 to 18.5 years)15.4 ± 1.415.4 ± 1.4
Tanner stage (%)  
 Stage 24.90.8*
 Stage 314.010.8*
 Stage 437.049.2*
 Stage 544.239.3*
Weight (kg)64.2 ± 13.256.4 ± 9.6
Height (m)1.71 ± 0.081.61 ± 0.06
BMI (kg/m2)21.8 ± 3.621.5 ± 3.3*
Overweight including obesity (%)§25.719.1
Waist circumference (cm)76.8 ± 9.571.1 ± 7.9
Waist-to-height ratio (cm/m)45.0 ± 5.344.0 ± 4.8
Vo2max (mL/kg per minute)50.9 ± 11.742.1 ± 8.0
 1st Quartilex < 43.5x < 36.8
 2nd Quartile43.5 ≤ x < 49.336.8 ≤ x < 40.7
 3rd Quartile49.3 ≤ x < 55.040.7 ≤ x < 45.4
 4th Quartilex ≥ 55.0x ≥ 45.4
Leisure-time physical activity: participation (%)71.046.7
Active commuting to school  
 Time (min/d)10.711.2
 >15 min/d (%)9.612.6
Sedentary activities  
 Time (h/d)2 h 58 min ± 1 h 56 min2 h 11 min ± 1 h 31 min
 > 2 h/d (%)65.346.4
Parental socioeconomic status (%)  
 Low6.77.4
 Medium-low26.323.7
 Medium33.338.8
 Medium-high25.624.2
 High8.15.8

The associations of BMI and waist circumference with physical activity patterns and cardiorespiratory fitness (Vo2max) were assessed by analysis of covariance, taking into account age and pubertal maturation status, and with the additional adjustment of waist circumference for height. General linear models with BMI and waist circumference as dependent variables were used to evaluate the independent association of leisure-time physical activity, sedentary activities, and cardiorespiratory fitness with adiposity. In this analysis, additional adjustment was made for potential confounders such as age, pubertal maturation status, height (only for waist circumference), active commuting to school, and socioeconomic status. To determine whether Vo2max was associated preferentially with abdominal fat, the relationship between waist circumference and Vo2max was further studied after additional adjustment for BMI. Because an interaction between BMI and Vo2max was noted, and given that physical activity patterns and lifestyle habits differ between overweight-obese and normal-overweight adolescents (37), this analysis was also performed separately for overweight-obese and normal-weight subjects according to the International Obesity Task Force cut-off points (24). Because physical activity patterns and cardiorespiratory fitness differed between boys and girls (38), all analyses were made separately for boys and girls. All calculations were performed using the SPSS/PC statistical program (version 12.0 for Windows; SPSS, Inc., Chicago, IL). For all analyses, the α error was fixed at 0.05.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Anthropometric Data, Cardiorespiratory Fitness, and Activity Patterns

Table 1 shows the characteristics of the study population. Forty-four percent of the boys fell into Tanner Stage 5; 49% of the girls fell into Stage 4. The boys showed higher anthropometric measurements, BMI, and waist-to-height ratio than the girls. About one-quarter of the boys and one-fifth of the girls were overweight or obese (Table 1). Cardiorespiratory fitness performance, as measured by Vo2max, was higher (by ∼9 mL/kg per minute) among the boys. Boys were more physically active than girls (71% compared with 47%). Only 10% of subjects reported active commuting to school involving 15 min/d or more. Two thirds of the boys and one-half of the girls devoted >2 h/d to sedentary activities. In both boys and girls, waist circumference and Vo2max increased significantly with age, whereas participation in leisure-time physical activity and sedentary activities diminished. However, after post hoc analysis, a significant decline was seen (p ≤ 0.001) only in girls 15 years old and older and in boys 16 years old and older. Age-specific BMI values are shown in Table 2. Postpubescent (Tanner Stage 5) girls showed higher BMIs, waist circumferences, and leisure-time physical activity coefficients than pubescent girls (Tanner Stages 2 to 4) girls. A lower Vo2max was also noted in postpubescent girls. These differences were not observed in boys.

Table 2.  Age-specific BMI values (means ± standard deviation) of the study subjects by gender
Age (years)Boys (n = 1445)Girls (n = 1403)
  • Age is listed at the half-year point for the entire year; for example, 13.5 years represents 13.0 to 13.99 years old. Differences between age groups: in boys, p ≤ 0.001 between 13.5 and 15.5, 13.5 and 16.5, 13.5 and 17.5, 14.5 and 17.5, and 16.5 and 17.5, p ≤ 0.05 between 15.5 and 17.5. Otherwise not significant. In girls, no significant difference between age groups.

  • *

    p ≤ 0.05 boys vs. girls.

  • p ≤ 0.01 boys vs. girls.

  • p ≤ 0.001 boys vs. girls. Otherwise not significant.

  • §

    17.0 to 18.5 years old.

13.520.6 ± 3.821.5 ± 3.7
14.521.5 ± 3.621.3 ± 3.7
15.5*22.0 ± 3.621.4 ± 3.0
16.521.8 ± 3.221.6 ± 3.1
17.5§22.9 ± 3.621.7 ± 3.2
Total*21.8 ± 3.621.5 ± 3.3

Association of BMI and Waist Circumference with Activity Patterns and Vo2max

Table 3 shows the univariate associations of BMI and waist circumference with activity patterns and cardiorespiratory fitness. No difference was found in BMI or waist circumference between the adolescents who practiced leisure-time physical activity and those who did not. With respect to activity patterns (physical activity, sedentary activities, and active commuting to school), the strongest relationships were observed between sedentary activities and waist circumference for boys (p = 0.006) and between active commuting to school and waist circumference for girls (p = 0.002). Cardiorespiratory fitness (Vo2max) was inversely associated with both BMI and waist circumference in boys and girls (p ≤ 0.001). Multivariate general linear models were used to assess the independent associations of Vo2max and sedentary activities using BMI and waist circumference as dependent variables (Table 4). Adjustments for potential confounding factors (age, pubertal maturation status, socioeconomic status, practice of leisure-time physical activity, and active commuting to school) were made. Waist circumference was adjusted for height. In both boys and girls, sedentary activities were directly related to waist circumference, independent of Vo2max (p = 0.02 for both boys and girls). The association between sedentary activities and BMI, independent of Vo2max, was only significant in boys (p = 0.04). In both boys and girls, Vo2max was negatively associated with BMI, independent of leisure-time physical activity and sedentary activities (p = 0.006 for boys and 0.0001 for girls). Similarly, Vo2max was inversely related to waist circumference (p = 0.001 for boys and 0.005 for girls). The adjusted linear regression model showed that a strongly sedentary lifestyle (>2 h/d) was associated with a 2.5-cm waist circumference increase in boys and a 1.5-cm increase in girls. Up to 10% of waist circumference variance in boys and 18% in girls was explained by sedentary activities. Compared with 4th quartile results, the 1st quartile values for cardiorespiratory fitness (Vo2max < 43.5 in boys and <36.8 mL/kg per minute in girls) were associated with 5.6- and 2.9-cm increases in waist circumference in boys and girls, respectively. The Vo2max explained up to 13% of the variance in waist circumference in boys and 16% in girls. After paired analyses of the Vo2max quartiles, significant differences were found between Quartile 1 and Quartile 4 in boys but not between Quartiles 2 and 4 or 3 and 4. Significant differences were also found between Quartiles 1 and 4 and between Quartiles 2 and 4 in girls but not between Quartiles 3 and 4. Up to 15% of waist circumference variance in boys and 18% in girls was explained by sedentary activity and cardiorespiratory fitness combined.

Table 3.  BMI and waist circumference according to activity pattern and cardiorespiratory fitness (Vo2max) by gender (means ± standard deviation)
 Boys (n = 1445)Girls (n = 1403)
  • Vo2max, maximum oxygen consumption.

  • *

    Adjustment for age.

  • Adjustment for height.

  • In these cases, the analysis was performed separately for pubescent (Tanner Stages 2 to 4) and postpubescent (Tanner Stage 5) subjects. The difference was significant only in pubescent subjects (p ≤ 0.05).

  • §

    In these cases, the same analysis was performed, and the difference remained significant for both groups (p ≤ 0.01 to ≤0.001). Comparisons were made by analysis of covariance.

 BMI (kg/m2)*Waist circumference (cm)*BMI (kg/m2)*Waist circumference (cm)*
Sedentary activities        
 0 to 2 h/d21.6 ± 3.1p = 0.02676.2 ± 8.1p = 0.00621.3 ± 3.1p = 0.02871.0 ± 7.8p = 0.082
 >2 h/d22.0 ± 3.9 77.6 ± 10.1 21.8 ± 3.6 71.8 ± 8.1 
Active commuting to school        
 0 to 15 min/d21.8 ± 3.6p = 0.14476.9 ± 9.3p = 0.34121.5 ± 3.4p = 0.14971.5 ± 8.1p = 0.002
 >15 min/d22.3 ± 3.8 78.1 ± 10.6 21.1 ± 2.6 69.6 ± 6.2 
Leisure-time physical activity        
 1st Quartile22.2 ± 4.1p for trend = 0.55777.8 ± 10.6p for trend = 0.23921.7 ± 3.4p for trend = 0.34071.9 ± 7.9p for trend = 0.068
 2nd Quartile22.0 ± 3.6 77.8 ± 9.2 21.4 ± 3.1 70.9 ± 7.4 
 3rd Quartile21.7 ± 3.2 76.3 ± 8.1 21.3 ± 3.0 70.5 ± 7.6 
 4th Quartile21.6 ± 3.5 76.3 ± 9.5 21.8 ± 3.8 71.3 ± 9.3 
Vo2max (mL/kg per minute)        
 1st Quartile23.1 ± 4.2p for trend ≤ 0.001§80.4 ± 11.3p for trend ≤ 0.001§22.5 ± 3.9p for trend ≤ 0.001§73.3 ± 9.4p for trend ≤ 0.001§
 2nd Quartile21.9 ± 3.4 77.1 ± 9.1 21.7 ± 3.4 71.4 ± 8.0 
 3rd Quartile21.0 ± 2.7 75.0 ± 7.2 20.8 ± 2.5 70.1 ± 6.5 
 4th Quartile21.1 ± 2.9 75.2 ± 7.3 20.9 ± 2.7 69.5 ± 6.7 
Table 4.  Multiple regression linear analyses with BMI and waist circumference as dependent variables and cardiorespiratory fitness (Vo2max) and sedentary activities as explanatory variables
 Vo2maxSedentary activities
  • Vo2max, maximum oxygen consumption; SE, standard error.

  • *

    1st Quartile against 4th Quartile, 2nd Quartile against 4th Quartile, 3rd Quartile against 4th Quartile.

  • Adolescents who devoted 0 to 2 h/d to sedentary activities compared with those who spent more than 2 h/d in sedentary activities.

  • Adjustment for age, pubertal maturation status (Tanner stages), socioeconomic status, practice of leisure time physical activity, and active commuting to school.

  • §

    Additional adjustment for height.

     ≤2 Hours 
 Quarter 1* [β-coefficient (SE)]Quarter 2* [β-coefficient (SE)]Quarter 3* [β-coefficient (SE)]pβ-coefficient (SE)p% Total variance explained (R2)
BMI       
Boys2.37 (0.64)1.22 (0.64)−0.51 (0.66)0.006−0.72 (0.90)0.04311
Girls2.17 (0.67)1.57 (0.65)0.23 (0.68)<0.0010.33 (0.65)NS14
Waist circumference§       
Boys5.61 (1.54)2.06 (1.53)−1.36 (1.57)0.001−2.46 (2.15)0.02415
Girls2.93 (1.52)2.97 (1.48)0.77 (1.54)0.005−1.47 (1.47)0.02818

To determine whether Vo2max was related to the amount of abdominal fat, the correlation between the former and waist circumference was examined after adjustment for BMI; age was taken into account as a covariable. Figure 1 shows the association between BMI-adjusted waist circumference and Vo2max in adolescents with a BMI above (Fig. 1a) and below (Fig. 1b) the International Task Force cut-off point (24). In this adjusted model, no significant association was observed in normal-weight subjects. However, BMI-adjusted waist circumference was inversely correlated with Vo2max in overweight-obese boys (p ≤ 0.05). A similar trend was seen in girls (p ≤ 0.1). The same model was performed for sedentary activity, and no significant association was found for either normal-weight or overweight-obese subjects.

image

Figure 1. BMI-adjusted waist circumference (means ± standard error) according to cardiorespiratory fitness (Vo2max) quartiles in adolescents with a BMI above (A) and below (B) the International Task Force cut-off point (24). Adjustment for age: * p ≤ 0.05 and † p ≤ 0.1.

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

The relationships among physical activity, sedentary activities, and/or cardiorespiratory fitness and abdominal adiposity has been studied in adults (18)(19)(20)(39)(40). The present study is the first to evaluate these associations in a large cohort of adolescents.

The most interesting finding was that moderate to high levels of cardiorespiratory fitness are associated with lower abdominal adiposity (as measured by waist circumference) in both boys and girls. This association remained after adjustment for age, pubertal maturation status, and confounding factors (height, socioeconomic status, leisure-time physical activity, and active commuting to school). This suggests a mechanism exists by which cardiorespiratory fitness attenuates the health risk of obesity. Cardiorespiratory fitness in the prevention and treatment of obesity-related disease should, therefore, be encouraged. Moreover, in overweight or obese adolescents, a beneficial connection between waist circumference and cardiorespiratory fitness was observed after adjusting for BMI (p ≤ 0.05 in boys, p ≤ 0.1 in girls). Similar observations have been reported in adults (19)(20)(21) but, to the best of our knowledge, never before in children or adolescents. The fact that sedentary activity was not associated with BMI-adjusted waist circumference suggests that, at least in overweight-obese adolescents, cardiorespiratory fitness might be specifically related to abdominal adiposity, rather than sedentary habits. Because waist circumference is recognized as a good indicator of cardiovascular risk in adolescents (41) and later in life (8)(9)(10)(11), cardiorespiratory fitness may have a beneficial impact on cardiovascular risk in young people. A number of important longitudinal studies have shown that the level of physical fitness during infancy and adolescence largely determines one's physical fitness during adulthood (42)(43). In addition, poor physical fitness during these stages of life is associated with later cardiovascular risk factors such as hyperlipidemia, hypertension, and obesity (44)(45)(46). Finally, several longitudinal studies (47)(48) have shown that, rather than the level of physical activity, the level of physical fitness in childhood and adolescence (especially aerobic capacity and muscular strength) determines the future risk of cardiovascular disease. This highlights the importance of routine measurements of waist circumference and cardiorespiratory fitness in clinical practice, especially in the overweight-obese adolescent population.

The high prevalence of sedentariness in the adolescent population observed in other countries can also be seen in Spain, where 46% of girls and 65% of boys spend 2 or more h/d watching television or playing computer/video games. In fact, these figures are much higher than the 33% to 40% seen in European data (18)(49)(50). They are lower, however, than in the U.S., where figures of 75% are seen (51). In the present study, 47% of the girls and 71% of the boys practiced physical activity in their leisure time; this is similar to recent U.S. observations where the prevalence of participation was 53% for girls and 70% for boys (52). However, they are slightly lower than in France, where the prevalence of participation is 58% among girls and 75% among boys (18).

A strong point of the present study is that no association was observed between activity and BMI, or between the former and waist circumference, after adjustment for age and pubertal maturation status and even after controlling for sedentary activities. This contrasts with a recent study conducted on adolescents 12 years old (18) in which an inverse relationship between both BMI and waist circumference with physical activity was noted. The fact that the influence of age and pubertal maturation status were not taken into account in this other study might explain these differences. Paradoxically, in a recent study of French adolescents (53), physical activity was not associated with adiposity indicators in either sex at baseline. However, after adjustment for baseline values, all adiposity indicators (waist circumference included) were higher in girls who decreased their relative level of moderate physical activity during the 2 years of follow-up. No such association was found, however, in adolescent boys. On the other hand, cardiorespiratory fitness seems stronger than self-reported physical activity as a predictor of health outcomes because fitness assessment is less prone to misclassification (54) and because factors other than physical activity may influence fitness levels and health status through related biological pathways. This fact needs to be considered when comparing the results between self-reported physical activity and those of cardiorespiratory fitness or objectively measured physical activity and when comparing self-reported physical activity results with those of others papers. Anyway, the relationship between physical activity and total or central adiposity in children and adolescents is now controversial (16)(17). Given that cardiorespiratory fitness is presumably a marker for physical activity, the disassociation between both variables seen in this study seems paradoxical. However, it is necessary to highlight that only vigorous, but not light or moderate, physical activity could be strongly related to cardiovascular fitness, as Gutin et al. (55) have recently reported.

In the present study, sedentary activities were significantly and inversely associated with BMI, as previously reported by several authors (56)(57)(58)(59)(60). Even after adjustment for confounding variables, the associations between sedentary activities and BMI or waist circumference were significant and independent of leisure-time physical activity (except for that between sedentary activities and BMI in girls). This suggests that sedentary activities not only represent a lack of physical activity but probably also reflect other unfavorable factors such as an increased energy intake during television watching and the negative effects of food advertising (61). In agreement with this, active commuting to school was negatively associated with waist circumference in girls, indicating that active commuting to school might be representative of a lifestyle or act as a consistent contribution to total daily physical activity by which a reduction in abdominal adiposity may occur. In contrast, other authors have found a positive relationship between physical activity and waist circumference in adolescents (18). It is noted that findings for BMI and waist circumference were very similar, and this is probably because a strong association was found between BMI and waist circumference in the present sample (R = 0.88 and 0.81 in boys and girls, respectively; adjustment for age).

Multiple regression analysis explained the characteristics of the association between cardiorespiratory fitness and waist circumference in the present study subjects. Very low cardiorespiratory fitness levels (Vo2max <43.5 in boys and <36.8 mL/kg per minute in girls) were associated with 5.6- and 2.9-cm increases in male and female waist circumference, respectively, compared with the results seen in subjects with a Vo2max ≥ 55.0 (boys) and ≥45.4 mL/kg per minute (girls). The significant differences between Vo2max quartiles suggests that achieving a Quartile 2 Vo2max level (43.5 mL/kg per minute or more) in boys and a Quartile 3 level in girls (40.7 mL/kg per minute or more) might be enough to maintain waist circumference. Curiously, the minimum Vo2max level associated with a significantly lower waist circumference in boys (43.5 mL/kg per minute) was similar to the lower limit for a low risk of cardiovascular disease (42 mL/kg per minute) proposed by the Cooper Institute for Aerobics Research (62).

The process by which excess body weight develops is complex and involves both lifestyle and genetic determinants. As in most other cross-sectional studies, even after adjustment for confounding factors, a substantial amount of BMI and waist circumference variance remained unexplained in the present multivariable models. It is also noteworthy that the present cross-sectional study only provides suggestive evidence concerning causal relations between cardiorespiratory fitness and abdominal adiposity; in addition, the direction of the cause can be suggested but never stated. Quantitative data on food intake and genetic aspects were not collected, and the use of self-reported activity data means some error is inherent. Moreover, recent studies have shown that vigorous physical activity, but not light or moderate, are inversely associated with adiposity (55). Therefore, given that the questionnaire used in the present study provides neither the intensity level of physical activity, nor the frequency or accurate duration of physical activity, it is necessary to be cautious with the physical activity-related conclusions. Further research with objective methods for measuring physical activity, such as accelerometry, will provide accurate information about physical activity patterns (intensity, frequency, and duration), helping to clarify this issue.

In conclusion, the results of this study suggest that moderate to high levels of cardiorespiratory fitness, but not physical activity, are associated with lower abdominal adiposity (as measured by BMI and waist circumference). In adolescents, a Vo2max of 43.5 mL/kg per minute for boys and 40.7 mL/kg per minute for girls might be considered the minimum level for limiting abdominal fat accumulation.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

The AVENA study was funded by the Spanish Ministry of Health (Facultad de CC Fisicas 00/0015); National Sports Agency (CSD) Grants 05/UPB32/01, 109/UPB31/03, and 13/UPB20/04; by the Spanish Ministry of Education (Grants AP2002-2920, AP2003-2128, and AP-2004-2745), and by grants from Panrico S.A., Madaus S.A., and Procter and Gamble S.A. We gratefully acknowledge the help of all of the adolescents who took part in the study, and we thank the parents and teachers for collaboration.

The Alimentación y Valoración del Estado Nutricional en Adolescentes (AVENA) Study Group: Coordinator: A. Marcos, Madrid, Spain. Principal researchers: M.J. Castillo, Granada; A. Marcos, Madrid; S. Zamora, Murcia; M. García Fuentes, Santander; and M. Bueno, Zaragoza. Granada: M.J. Castillo, M.D. Cano, and R. Sola (biochemistry); A. Gutiérrez, J.L. Mesa, and J. Ruiz (physical fitness); M. Delgado, P. Tercedor, and P. Chillón (physical activity); F.B. Ortega, M. Martín, F. Carreño, G.V. Rodríguez, R. Castillo, and F. Arellano (collaborators), Universidad de Granada, Granada. Madrid: A. Marcos, M. González-Gross, J. Wärnberg, S. Medina, F. Sánchez Muniz, E. Nova, A. Montero, B. de la Rosa, S. Gómez, S. Samartín, J. Romeo, and R. Álvarez (coordination, immunology), A. Álvarez (cytometric analysis), L. Barrios (statistical analysis), A. Leyva and B. Payá (psychological assessment), L. Martínez, E. Ramos, R. Ortiz, and A. Urzanqui (collaborators), Instituto de Nutrición y Bromatología, Consejo Superior de Investigaciones Científicas, Madrid. Murcia: S. Zamora, M. Garaulet, F. Pérez-Llamas, J.C. Baraza, J.F. Marín, F. Pérez de Heredia, M.A. Fernández, C. González, R. García, C. Torralba, E. Donat, E. Morales, M.D. García, J.A. Martínez, J.J. Hernández, A. Asensio, F.J. Plaza, and M.J. López (diet analysis), Departamento De Fisiología, Universidad de Murcia, Murcia. Santander: M. García Fuentes, D. González-Lamuño, P. de Rufino, R. Pérez-Prieto, D. Fernández, and T. Amigo (genetic study), Departamento Pediatría, Universidad de Cantabria, Santander. Zaragoza: M. Bueno, L.A. Moreno, A. Sarriá, J. Fleta, G. Rodríguez, C.M. Gil, M.I. Mesana, J.A. Casajús, V. Blay, and M.G. Blay (anthropometric assessment), Escuela Universitaria de Ciencias de la Salud, Universidad de Zaragoza, Zaragoza.

Footnotes
  • 1

    Nonstandard abbreviations: AVENA, Food and Assessment of the Nutritional Status of Adolescents; Vo2max, maximum oxygen consumption; PAI, physical activity index; MET, metabolic equivalent.

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References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
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