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Associations between physical activity and fat mass in adolescents: the Stockholm Weight Development Study^1,2,3

¹ From the Medical Research Council Epidemiology Unit, Cambridge, United Kingdom; the Department of Physical Education and Health, Örebro University, Sweden; and the Obesity Unit, Karolinska Institutet, Karolinska University Hospital, Stockholm

² Supported by grant no. QLK1-2000-00515 from the European Commission and by a grant from the Swedish National Center for Research in Sports (to UE).

³ Reprints not available. Address correspondence to U Ekelund, MRC Epidemiology Unit, Elsie Widdowson Laboratory, Fulbourn Road, CB1 9NL Cambridge, United Kingdom. E-mail: ue202{at}medschl.cam.ac.uk

See corresponding editorial on page 337.

	ABSTRACT

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Background: Obesity is multifactorial. However, the accumulation of fat mass (FM) is proposed to be due to a positive energy balance, which may be caused by reduced physical activity (PA).

Objective: The objectives of the study were to describe the independent associations between PA and FM in adolescents and to describe the intergenerational association of FM between mothers and their offspring.

Design: We conducted a cross-sectional study in 445 (190 M, 255 F) 17-y-old adolescents and their mothers. PA was assessed with a self-reported questionnaire and validated by comparison with accelerometric data in a subsample of the cohort. Body composition was measured by using air-displacement plethysmography.

Results: Males were significantly more active than were females (P < 0.01). PA was significantly and inversely associated with FM (ß = –3.63, P = 0.005) and percentage FM (ß = –3.117, P = 0.017) in males but not in females (ß = –0.576, P = 0.54; ß = –0.532, P = 0.59, respectively) after adjustment for birth weight and maternal FM and education level. However, FM and percentage FM in females were significantly associated with maternal FM (ß = 0.159, P < 0.0001; ß = 0.145, P = 0.002, respectively) and education level (ß = –1.048, P < 0.005; ß = –1.085, P = 0.006, respectively). No such associations were observed in males.

Conclusions: PA was independently associated with FM in males but not in females. The data also showed an intergenerational association of FM between mothers and their daughters but not between mothers and their sons.

Key Words: Adolescents • fat mass • physical activity • obesity • intergenerational association

	INTRODUCTION

TOP ABSTRACT INTRODUCTION SUBJECTS AND METHODS RESULTS DISCUSSION REFERENCES

 
Several studies consistently showed that the prevalence of overweight and obesity in young people is increasing dramatically (1-4). Obesity is multifactorial, and it involves genetic (5) and behavioral (6) components. The behavioral components include physical activity (PA) and food habits, which are influenced by the social, cultural, and environmental context (6, 7). The rise in the prevalence of excess body fat in young people is proposed to be mainly due to environmental changes such as easy access to large-sized portions of energy-dense foods and a reduced PA level (6-8).

The association between PA or sedentary behavior and obesity in children and adolescents has not been consistently shown (9-14). The difference in findings between studies is most likely due to the differences in study methods, the imprecision of the measurement of the exposure and outcome variables, and differences in adjustment for confounding variables. Objective methods are generally preferable in assessing dimensions of PA in young people. However, in many cases, self-reporting is the only feasible method of assessing PA in epidemiologic studies, and it may provide a valid overall estimate of the total amount of PA (15).

Although the respective contribution of shared genetic and environmental influences on obesity is unknown, parental body mass index (BMI; in kg/m²) is associated with that of the parents’ children (16-19). However, even if BMI is considered a reasonably valid marker of overweight and obesity in population-based epidemiologic studies, it does not provide a measure of the absolute body fat mass (FM) or distinguish FM from fat-free mass (FFM). Therefore, more precise methods are needed to assess the associations between PA and FM. For example, air-displacement plethysmography has been shown to be a valid method of measuring FM and FFM in children, adolescents, and adults, and thus it would be a preferred method for increasing the precision of the outcome measurement (20-23).

The primary purpose of the current cross-sectional study was to describe the independent associations between self-reported PA and absolute and percentage FM in 17-y-old adolescents; the secondary purpose was to describe the intergenerational association of FM between 17-y-old adolescents and their mothers.

	SUBJECTS AND METHODS

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Design
The Stockholm Weight Development Study, known as SWEDES, is a longitudinal study of weight development in the offspring of mothers participating in the Stockholm Pregnancy and Weight Development Study (24, 25). Briefly, 2342 pregnant women were recruited in 1984 and 1985 and followed during and after their pregnancies. Of this group, 1423 completed the study at 1-y follow-up, and 481 of those mothers and their 481 children participated in the follow-up study at 17 y. Anthropometric, metabolic, psychological, and lifestyle variables (including PA) were measured at follow-up. We report here the cross-sectional associations between PA and body fatness in the offspring.

Subjects
Data on the body composition and socioeconomic status of the mothers and complete data on adolescents’ birth weight, self-reported PA, and body composition were available for 455 (255 females and 190 males) of the 481 adolescent subjects at follow-up. There were no significant differences in height, weight, or BMI between participants and those who did not provide complete data (P > 0.5).

The ethics committee of Huddinge University Hospital approved the study. Written informed consent was obtained from both the mothers and the adolescents.

Measurements
Anthropometric measures
Standing height was measured to the nearest 0.5 cm while the subjects stood in bare feet against a wall-mounted stadiometer, and body weight was measured to the nearest 0.1 kg by using the BodPod scale (Life Measurement Instruments, Concord, CA) while they wore light clothing. BMI was calculated, and the adolescent subjects were classified as normal-weight, overweight, or obese according to the age- and sex-adjusted cutoffs described by Cole et al (26). The absolute values for overweight in 17-y-old males and females are a BMI of 24.46 and 24.70, respectively (26), and those for obesity are a BMI of 29.41 and 29.69 (26). In the mothers, overweight and obesity were determined by BMIs > 25 and > 30, respectively. Body volume was measured by using air-displacement plethysmography and the BodPod scale after adjustment for predicted thoracic lung volume and estimated surface area artifact. FM, percentage FM, and FFM were calculated by using the software provided by the manufacturer and the equation of Siri (27). Body volume was measured in duplicate, and a third measurement was taken when the first 2 measurements differed by >150 mL. All subjects were measured while wearing tight underwear or swimwear and a swim cap. The same procedures were adopted for the mothers and the offspring, and they were examined on the same day.

Maturity
Sexual maturity was assessed by using the 5-stage Tanner scale for breast development in females and for pubic hair in males (28). A dichotomous variable, puberty passed (Tanner stage 5) or puberty not passed (Tanner stage < 5) was created.

Physical activity
A self-administered PA questionnaire was developed for use in Swedish adolescents. The questionnaire was designed to collect information on the frequency, duration, and intensity of PA in 3 different domains—ie, school, transportation, and leisure time—during the previous 7 d. These 3 domains were selected to encompass most of the possible physical activities performed by adolescents. The first domain comprised PA and sedentary behavior (ie, sitting) at school, including PA during physical education classes and ordinary classes and during breaks. The second domain related to transportation-related PA, eg, PA during transit to and from school and that during other types of transportation. The third domain included all PAs during leisure time, including PA during paid and unpaid work, exercise, sports, and other recreation. Questions regarding participation in moderate and vigorous PA during leisure time were supplemented by concrete examples of activities. Two questions about the type of moderate and vigorous PA performed during leisure time were also asked. The last part of the questionnaire comprised 2 questions about the duration of sitting during leisure time on weekends and weekdays. Data from the questionnaire were manually checked for out-of-range values (ie, >3 SD) within each PA domain, and these values were deleted. However, including all out-of-range values within each activity domain affected only the mean of total PA [metabolic equivalents (METs)-min/wk] and not the ranking of individuals. Data were summed within each domain to estimate the total amount of time spent in PA per week. Total weekly PA was estimated by weighting the reported time within each activity domain by a specific MET energy expenditure estimate assigned to each category of PA (29, 30). The weighted minutes of METs per week were calculated as duration x frequency x MET intensity across activity domains to produce a total estimate of PA (MET-min/wk).

We assessed the validity of the questionnaire in a subsample (n = 49; 18 males) of study participants against PA measured objectively by using accelerometry (MTI Actigraph, Fort Walton Beach, FL). The accelerometer was worn for 7 consecutive days, and the questionnaire for the previous 7 d was filled in on day 8. Self-reported PA was significantly and inversely associated with time spent being sedentary (r = –0.45, P < 0.001) and significantly and positively associated with time spent in PA (r = 0.51, P < 0.001) and with the total amount of PA (r = 0.49, P < 0.001). These findings indicated a reasonable degree of validity of our instrument (U Ekelund, M Neovius, Y Linné, S Rössner, unpublished observations, 2004).

Socioeconomic status
Data on variables of socioeconomic status (SES) were collected by questionnaire. The education level of the mothers was used as the indicator of SES because preliminary analyses suggested this variable was the strongest proxy for SES. Education level was assessed on a 5-point scale, in which level 1 indicated completion of compulsory school (ie, 9 y) and level 5 indicated a university degree.

Statistical methods
Data in tables and text are expressed as means ± SDs. Nonnormally distributed variables were log transformed before analysis and are presented as geometric means and 95% CI. Differences between the sexes were tested by using one-way analysis of variance. Associations between variables were assessed by using Pearson’s correlation coefficient. The independent associations between PA and FM, percentage FM, and BMI were tested by using analysis of covariance (general linear models). All analyses were adjusted for birth weight and maternal FM and education level. The interaction term PA x sex was introduced to examine whether sex modified the associations between PA and each of the outcomes (ie, FM, percentage FM, and BMI). We observed significant (P < 0.05) interactions in 2 of our 3 models (FM and BMI) and therefore reanalyzed our data with stratification by sex. In preliminary analyses, we also adjusted for smoking status (smoker or nonsmoker) and sexual maturity (puberty passed or puberty not passed). However, because these variables neither influenced the direction of the association nor contributed to the explained variations in FM, percentage FM, and BMI, they were excluded from the final models. All analyses were performed by using SPSS for WINDOWS software (version 11.0; SPSS Inc, Chicago), and the level of significance was set at P < 0.05.

	RESULTS

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Characteristics of the participants are shown in Table 1. The males were significantly (P < 0.001) heavier and taller, had a significantly (P < 0.001) higher FFM, and reported a significantly (P < 0.01) greater amount of PA than did the females. The females had significantly higher FM and percentage FM (both: P < 0.001) than did the males. According to BMI, 89.6% of the females and 85.1% of the males were classified as normal-weight, 7.5% of the females and 11.9% of the males were classified as overweight, and 2.9% and 3.0% of the females and the males, respectively, were obese. Of the mothers, 25.2% were classified as overweight, and an additional 8.9% were obese.

The correlation between obesity indicators (ie, FM, percentage FM, and BMI) and adolescent and maternal characteristics with stratification by sex is shown in Table 2. FFM was positively associated with FM and BMI in both males and females (P < 0.001). Birth weight was significantly and positively associated with FM in both sexes (P < 0.05) and with BMI in the males (P < 0.05). The total amount of PA (MET-min/wk) was significantly and inversely associated with FM (P < 0.01), percentage FM, and BMI in the males (P < 0.05) but not in the females. Maternal education level was significantly and inversely associated with FM, percentage FM, and BMI in the females (P < 0.01) but not in the males. Furthermore, maternal percentage FM was significantly and positively associated with FM (P < 0.01) and percentage FM (P < 0.001) in the females but not in the males.

Table 3

	DISCUSSION

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A sex difference in the relation of PA and body fatness was previously reported in young people and adults (31-34). In a meta-analysis, which used data on total energy expenditure obtained with the use of the doubly labeled water method in combination with data on resting energy expenditure, it was concluded that there is a significant and inverse cross-sectional relation between PA-related energy expenditure (PAEE) and percentage FM in males but not in females (32). Similarly, it was recently shown that percentage FM is significantly and inversely associated with PAEE in men. However, in women, dietary fat intake but not PAEE was associated with percentage FM (33).

The explained variation in body fatness due to PA was < 4% in all models. The small amount of explained variation due to PA may at least partly result from our imprecise measure of activity. However, studies adopting the doubly labeled water method for examination of the associations between PAEE and body composition in young people have had disparate findings (12, 13, 31, 34). In a case-control study comparing obese and normal-weight adolescents, it was shown that obese adolescents spent less time in activity as measured by accelerometry than do nonobese adolescents, whereas there was no difference in PAEE between the groups (12). This finding indicated lower levels of activity in obese adolescents, independent of sex.

Our current observations, which indicate that PA explains only a small amount of the variation in body fatness, are in agreement with findings of a recent, large, cross-sectional observational study in 9- to 10-y-old children from 4 countries in Europe (35). In that study, PA explained <1% of the variation in body fatness. Taken together, the results of that study and of ours suggest that factors such as food intake and especially the consumption of energy-dense food and sugar-sweetened drinks may play an important role in the development of overweight and obesity (36-38). In support of this hypothesis, a recent prospective study showed that energy intake but not PAEE was related to body weight gain in adult Pima Indians (39). However, current methods make it difficult to ascertain whether food intake or PAEE is the major contributor to a positive energy balance and thereby to the development of overweight and obesity (39).

We also observed an association between obesity and low SES, defined as maternal education level, in the mothers and body fat in their daughters. Data on the maternal education level was obtained by self-report, and there was no difference in maternal education level between male and female offspring. Although it did not contribute to the explained variation in body fat in males, the direction of the association was similar to that observed in females, and the correlation was significant in both genders combined (data not shown). Thus, our observations agree with previous studies suggesting an association between low SES and obesity in adolescents (6, 40, 41).

A novel finding from this study was the observation of the association between maternal FM (measured by air-displacement plethysmography) and that of their daughters. Maternal FM was significantly and consistently associated with FM and percentage FM in their female offspring but not in their male offspring. These associations persisted when maternal percentage FM was replaced by absolute FM in our analyses (data not shown). This clear sex difference is most likely due to a shared environmental component between mothers and their daughters that is stronger than that between mothers and their sons. Unfortunately, we do not have any paternal body-composition data from which to test whether the intergenerational association of FM is stronger between fathers and their sons than it is between fathers and their daughters. Although it is unlikely, a shared genetic component for the independent intergenerational association of FM between mothers and their daughters cannot be excluded.

Several limitations should be considered in interpreting the findings from the present study. First, it is not possible to infer a causal relation from cross-sectional data such as those in the current study. Although we controlled for several potential confounders such as birth weight and maternal obesity and education level, we cannot be certain that other, unmeasured confounders, such as diet, genetic variation, and paternal body composition, do not explain our observations. Second, our subjects may not be representative of Swedish adolescents in general. However, they were drawn from a population-based sample of the offspring of women who gave birth in 1984 or 1985 (21, 22). The prevalence of overweight and obesity in our cohort is similar to that reported in Swedish adolescents and young adults, although the definition of overweight and obesity differed slightly between the current study and previously reported studies (41, 42). The BMIs in our cohort were slightly lower in the males (0.2 units) and slightly higher in the females (0.4 units) than the Swedish reference data (43). Overall, these minimal differences seem to indicate that the body composition of our cohort is fairly representative of that in 17-y-old Swedes. Third, self-reported PA is associated with recall bias. Thus, one possible explanation for our findings may be due to a selective misreporting of activity by females. However, the questionnaire used in the current study was validated against accelerometry-measured PA in a subsample of our cohort, and this test showed a reasonable agreement between methods. Furthermore, the correlation coefficient between self-reported and objectively measured PA was of similar magnitude in females and in males (r = 0.60 and r = 0.45, respectively; both: P < 0.05), which indicates that sex does not bias self-reported PA in our study (U Ekelund, M Neovius, Y Linné, S Rössner, unpublished observations, 2004). We cannot, however, exclude the possibility that overweight and obese females substantially overreport their levels of activity, which would mask a true association between activity and body fat in females.

In conclusion, a clear sex difference was observed for the association between PA and FM in adolescents. PA was independently associated with FM in males but not in females. Our data also suggest a behavioral intergenerational association of FM between mothers and their daughters. Future studies, incorporating precise measures of exposures and outcome variables in parents and their offspring, are needed to test whether such an association also exists between fathers and their sons.

	ACKNOWLEDGMENTS

 
UE conceived the hypothesis for this manuscript, performed the data analyses, and drafted the manuscript. MN provided critical input for the conception of this study and assisted with editing of the manuscript. YL was the lead epidemiologist on the project and was primarily responsible for developing the study design for the Stockholm Pregnancy and Women’s Nutrition Study (1999) and the follow-up Stockholm Weight Development Study (2002). YL also supervised data collection and helped with editing of the manuscript. SB and NJW provided critical input on the data analyses and on the early versions of the manuscript. SR was the principal investigator, conceived the idea of the Stockholm Pregnancy and Women’s Nutrition Study (1999) and the follow-up Stockholm Weight Development Study (2002), and assisted with the study design and manuscript revision. All authors took part in the discussion of the results and approved the final version of the manuscript. None of the authors had any conflicts of interest.

We are grateful to Prevnut at NOVUM (Stockholm) for the BodPod equipment support. We also thank Manjinder Sandhu, Institute of Public Health, University of Cambridge, for critical comments with regard to the manuscript.

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