Journal of Physical Activity and Health, 2015, 12, 266 -272 http://dx.doi.org/10.1123/jpah.2013-0062 © 2015 Human Kinetics, Inc.
Official Journal of ISPAH www.JPAH-Journal.com ORIGINAL RESEARCH
High Levels of Physical Activity and Cardiorespiratory Fitness are Associated With Good Self-Rated Health in Adolescents Marko T. Kantomaa, Tuija Tammelin, Hanna Ebeling, Emmanuel Stamatakis, and Anja Taanila Background: Adolescent self-rated health is a strong predictor of future illness. In this study we investigated whether physical activity and cardiorespiratory fitness are associated with self-rated health among adolescents aged 16 years. Methods: The study sample comprised 7,063 adolescents from the Northern Finland Birth Cohort 1986 (NFBC 1986) who responded to a postal questionnaire in 2001 to 2002. Self-rated health was measured by a single-item question, while physical activity was evaluated by a set of questions concerning the intensity and volume of physical activity outside school hours. Cardiorespiratory fitness was measured with a submaximal cycle ergometer test. Odds ratios (OR) and their 95% confidence intervals (95% CI) for good self-rated health were obtained from multinomial logistic regression. Results: High levels of physical activity (boys: OR 5.50, 95% CI 3.16 to 9.58; girls: OR 4.25, 95% CI 2.37 to 7.61) and cardiorespiratory fitness (boys: OR 1.85, 95% CI 1.05 to 3.24; girls: OR 2.62, 95% CI 1.47 to 4.66) were associated with very good self-rated health in adolescents. Conclusions: High levels of physical activity and cardiorespiratory fitness are positively associated with adolescents’ self-rated health. Public health promotion activities that foster physical activity and cardiorespiratory fitness may benefit young people’s overall health and well-being. Keywords: exercise, well-being, youth One of the most commonly used measures of perceived health status consists of a single Likert scale question, querying about respondents’ overall health.1 This measure of self-rated health has consistently been found to be a valid measure of overall physical health status among adults.2 Self-rated health is, even in young populations, strongly linked to mortality3 and is a strong predictor of future illness, independently of clinical health status.4 Health-related behaviors such as physical activity may be important contributors to self-rated health among adolescents.5 There is some literature suggesting that physical activity is positively associated with adolescents’ self-rated health,3,6,7 and it has been suggested that health-related behaviors, such as physical activity, may play a central role for adolescents when determining their self-rated health status.8,9 However, the association between physical activity and self-rated health among adolescents may differ according to sex and a person’s overall level of physical activity, the association being stronger among boys and among more active adolescents.10 Even though much less is known about the association between cardiorespiratory fitness and self-rated health among young people, there is some evidence of a positive association between these factors.11 However, the number of studies on cardiorespiratory fitness Kantomaa ([email protected]) and Tammelin are with LIKES – Research Center for Sport and Health Sciences, Jyväskylä, Finland. Kantomaa is also with the Dept of Epidemiology and Biostatistics, Imperial College London, London, UK. Ebeling is with the Institute of Clinical Medicine, Dept of Child Psychiatry, University of Oulu, Oulu, Finland; and the Clinic of Child Psychiatry, Oulu University Hospital, Oulu, Finland. Stamatakis is with Charles Perkins Centre, University of Sydney, Australia; Exercise and Sport Sciences, Faculty of Health Sciences, University of Sydney, Sydney, Australia; and Physical Activity Research Group, Dept of Epidemiology and Public Health, University College London, London, UK. Taanila is with the Institute of Health Sciences, University of Oulu, Oulu, Finland. 266
and self-rated health among adolescents is very limited, especially with respect to those using objective measures of cardiorespiratory fitness. Furthermore, studies on the mutual associations of physical activity and cardiorespiratory fitness with self-rated health are rare. The existing literature looking at the associations of physical activity and cardiorespiratory fitness with self-rated health among adolescents lacks studies with large, unselected population samples and high-quality study designs. The purpose of this study was to investigate whether physical activity and cardiorespiratory fitness are associated with self-rated health among adolescents in a large, population-based birth cohort. We hypothesized that high levels of physical activity and cardiorespiratory fitness are associated with good self-rated health among adolescents.
Methods Participants The study population consisted of the Northern Finland Birth Cohort 1986 (NFBC 1986), which, at the baseline of this study, was composed of 9,432 infants whose expected date of birth was between July 1, 1985 and June 30, 1986 in the two northernmost provinces of Finland, Oulu, and Lapland.12 In 2001 to 2002, at the age of 15 to 16 years (hereafter referred to as “16 years”), the cohort members were sent a postal questionnaire including questions about health and well-being (response rate 80%, N = 7,344). Parents were also sent a postal inquiry including questions about family conditions (response rate 76%, N = 6,985). At the age of 16 years, cohort members also participated in individual health examinations (participation rate 74%, N = 6,798), including the measurement of cardiorespiratory fitness (N = 5,375). The present analyses included those 7,063 adolescents who reported their self-rated health at age 16 years. Informed consent was obtained from all participants and their parents, and the research protocol was approved by the Ethics Committee of Northern Ostrobotnia Hospital District.
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Physical Activity and Self-Rated Health 267
Physical Activity
Potential Confounders
The amount of physical activity outside school hours was evaluated separately for moderate-to-vigorous physical activity and light physical activity at age 16 years by asking participants, “How many hours a week all together do you participate in (a) brisk and (b) light physical activity outside school hours?” In the questionnaire, the term “brisk” was defined as physical activity causing at least some sweating and shortness of breath (here referred to as moderate-tovigorous intensity physical activity), while the term “light physical activity” was defined as causing no sweating or shortness of breath. In addition, the adolescents were asked about their daily time spent in physically active commutes to and from school. The response alternatives (not at all, less than 20 min, 20 to 39 min, 40 to 59 min, and at least 1 hour per day) were multiplied by 5 (5 school days a week) to correspond to 0, 1, 2.5, 3.75, and 5 hours per week.13 The physical activity level was converted into metabolic equivalent of task (MET) hours per week based on the intensity and the volume of physical activity engaged in outside school hours, including commuting to and from school. An MET intensity value of 3 METs was used for light physical activity, 5 METs for brisk physical activity, and 4 METs for all types of commuting physical activity in the calculations.14 MET hours were divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the middle tertile), and (3) low (the lowest tertile). The test-retest reliability of these physical activity questions among Finnish adolescents aged 15 to 16 years has been shown to be good.13 The intraclass correlation coefficient for physical activity levels described in terms of quintile categories of MET hours per week was 0.70 (95% confidence interval 0.58 to 0.80), and the proportion of subjects who were classified in the same or next (up or down) category between test and retest was 86%.
At the age of 16 years, the adolescents self-reported their body weight and height in the postal questionnaire, and these were measured in the health examination. Self-reported body weight and height were used for those who failed to attend the health examination. Body mass index (BMI) was calculated as the individual’s weight divided by the square of the height (kg/m2). Obesity was defined using the International Obesity Task Force (IOTF) agespecific cut-off points for BMI.18 Information about parental socioeconomic position was obtained from the parents’ questionnaire at the age of 16 years. Socioeconomic position was based on the mother’s and father’s occupations. Parental socioeconomic position was classified into six groups: (1) upper-level employees, (2) lower-level employees, (3) farmers, (4) self-employed persons, (5) manual workers, and (6) others (students, pensioners, and others).19 Adolescent smoking at the age of 16 years was measured by asking, “Do you smoke now?” The response alternatives were: (1) not at all, (2) occasionally, (3) on one day a week, (4) on 2 to 4 days a week, (5) on 5 to 6 days a week, and (6) 7 days a week. Emotional and behavioral problems were measured using the Youth Self-Report (YSR), a widely used questionnaire designed to assess emotional and behavioral problems among adolescents aged 11 to 18 years.20 The YSR was scored for the following 8 syndrome scales: (1) anxious/depressed symptoms, (2) withdrawn/depressed symptoms, (3) somatic complaints, (4) social problems, (5) thought problems, (6) attention problems, (7) rule-breaking behavior, and (8) aggressive behavior. These 8 core syndrome scales were further combined into a Total Problem Scale.21 Information about adolescent long-term illness (other than heart defect or high blood pressure) and handicap and disability diagnosed by a doctor was obtained from the parents’ questionnaire at the age of 16 years.
Cardiorespiratory Fitness Cardiorespiratory fitness was measured during a health examination at age 16 (N = 5,375) with a submaximal cycle ergometer test, and was expressed as peak oxygen uptake (VO2peak) in ml·kg–1·min–1. Adolescents were categorized into sex-specific thirds of fitness: (1) high (the highest tertile), (2) average (the middle tertile), and (3) low (the lowest tertile). The exercise test protocol included 2 incremental work stages of 4 minutes each on a bicycle ergometer (model 818E, Monark, Sweden). Peak oxygen uptake (VO2peak in ml·kg–1·min–1) was calculated based on the heart-rate response during submaximal work stages. The method has been validated against directly measured VO2peak during the maximal exercise test, and has previously been described in detail.15
Self-Rated Health Self-rated overall health was measured by asking, “How would you describe your health at the moment?” The response alternatives were: (1) very poor, (2) poor, (3) fair, (4) good, and (5) very good. Because of low prevalence of very poor, poor, and fair self-rated health in the current study sample (altogether 16%) and, therefore, for the reasons of statistical power, the adolescents were grouped into three groups: (1) very good, (2) good, and (3) moderate/poor (fair, poor, or very poor self-rated health). This single-item measure of general health status has been used widely in previous research and has been consistently found to be an independent predictor of mortality, as well as a reasonable measure of objective health status in adults.2,16,17
Statistical Analyses The basic analyses included frequency counts and relative distributions. Bivariate associations were tested separately for boys and girls with cross-tabulation using chi-square tests and multinomial logistic regression. Multivariable analyses were also performed separately for boys and girls using multiple multinomial logistic regression. The results of the regression analyses are presented with odds ratios (OR) and 95% confidence intervals (95% CI). In the multivariable models, the variables were adjusted for obesity level, parental socioeconomic position, smoking, emotional and behavioral problems, long-term illness, handicap and disability, and mutually for cardiorespiratory fitness and physical activity. The data were analyzed using SPSS software, version 19 (IBM, Chicago, IL).22
Results Boys were physically more active (P < .001) and had higher cardiorespiratory fitness (P < .001) than girls at the age of 16 years. The mean MET hours per week were 32.9 (SD 17.9) among boys and 28.6 (SD 15.5) among girls. The mean peak oxygen consumption was 49.1 (SD 9.7) ml·kg–1·min–1 among boys and 35.4 (SD 6.3) ml·kg–1·min–1 among girls. The sex-specific distributions of the variables used in the current study are presented in Table 1.
Table 1 Characteristics of the Northern Finland Birth Cohort 1986 Study Sample
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Characteristic Self-rated health Very good Good Moderate/poor Physical activityb High Average Low Cardiorespiratory fitnessc High Average Low Obesity leveld Normal weight Overweight Obese Long-term illnesse Yes No Mother’s socioeconomic position Upper-level employees Lower-level employees Farmers Self-employed Manual workers Others Father’s socioeconomic position Upper-level employees Lower-level employees Farmers Self-employed Manual workers Others Smoking Not at all Occasionally On 1 day a week On 2–4 days a week On 5–6 days a week 7 days a week Emotional and behavioral problemsf Yes No
Boys N (total) (3,406) 1,002 1,902 502 (3,322) 1,162 1,090 1,070 (2,385) 799 786 800 (3,371) 2,804 425 142 (3,008) 602 2,406 (2,947) 497 1,558 118 81 529 164 (2,782) 720 518 207 197 1,063 77 (2,156) 1,181 401 37 67 77 393 (3,275) 291 2,984
% 29.4 55.8 14.7 35.0 32.8 32.2 33.5 33.0 33.5 83.2 12.6 4.2 20.0 80.0 16.9 52.9 4.0 2.7 18.0 5.6 25.9 18.6 7.4 7.1 38.2 2.8 54.8 18.6 1.7 3.1 3.6 18.2 8.9 91.1
Girls N (total) (3,657) 726 2,290 641 (3,582) 1,227 1,237 1,118 (2,167) 730 722 715 (3,632) 3,136 389 107 (3,197) 605 2,592 (3,094) 527 1,589 129 84 614 151 (2,931) 704 539 256 191 1,132 109 (2,459) 1,092 579 26 124 127 511 (3,563) 629 2,934
%
P-valuea < .001
19.9 62.6 17.5 N/A 34.3 34.5 31.2 N/A 33.7 33.3 33.0 < .001 86.3 10.7 2.9 .279 18.9 81.1 .414 17.0 51.4 4.2 2.7 19.8 4.9 .085 24.0 18.4 8.7 6.5 38.6 3.7 < .001 44.4 23.5 1.1 5.0 5.2 20.8 < .001 17.7 82.3
P-values for the sex differences (Pearson’s chi-squared test). Metabolic equivalent hours based on the intensity and volume of physical activity divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the middle tertile), and (3) low (the lowest tertile). c Peak oxygen uptake (VO peak) in ml·kg–1·min–1 divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the middle tertile), and 2 (3) low (the lowest tertile). d Obesity level was defined using the International Obesity Task Force (IOTF) age-specific cut-off points for body mass index (BMI). BMI was calculated as weight divided by the square of the height (kg/m2). e Includes long-term illness (other than heart defect or high blood pressure) and handicap and disability. f Includes anxious/depressed, withdrawn/depressed, social, thought and attention problems, somatic complaints, and rule-breaking and aggressive behavior. a
b
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Physical Activity and Self-Rated Health 269
According to the unadjusted results from cross-tabulation with linear-by-linear association test, physical activity and a high level of cardiorespiratory fitness were associated with good self-rated health (Table 2). When adjusted for obesity, parental socioeconomic position, smoking, emotional and behavioral problems, long-term illness, handicap and disability, and mutually for cardiorespiratory fitness and physical activity, physically active boys (OR 5.50, 95% CI 3.16, 9.58) and girls (OR 4.25, 95% CI 2.37, 7.61) were more likely to report very good self-rated health compared with moderate/ poor self-rated health than their physically inactive peers (Table 3). Physically active adolescents were also more likely to report good self-rated health compared with moderate/poor self-rated health than physically inactive adolescents (Table 3). Similarly, boys (OR 1.85, 95% CI 1.05, 3.24) and girls (OR 2.62, 95% CI 1.47, 4.66) with a high level of cardiorespiratory fitness were more likely to report very good self-rated health compared with moderate/poor self-rated health than their peers with low levels of cardiorespiratory fitness (Table 4). In addition, adolescents with high levels of cardiorespiratory fitness were more likely to report good self-rated health compared with moderate/poor self-rated health than adolescents with low levels of cardiorespiratory fitness (Table 4). We also fitted the regression models 1 and 2 for the restricted samples of 1,151 boys and 1,078 girls having information on all the variables included in the fully-adjusted models (Tables 3 and 4).
In general, there were no significant differences in the estimates. However, in the restricted sample the association between average level of physical activity (compared with low level of physical activity) and good (model 1: boys OR 1.18, 95% CI 0.80, 1.76; girls OR 1.24, 95% CI 0.82, 1.86; model 2: boys OR 1.12, 95% CI 0.74, 1.70; girls OR 1.15, 95% CI 0.75, 1.76) and very good (model 1: boys OR 1.60, 95% CI 1.00, 2.56; girls OR 1.87, 95% CI 1.09, 3.21; model 2: boys OR 1.39, 95% CI 0.85, 2.28; girls OR 1.69, 95% CI 0.96, 3.01) self-rated health (compared with moderate/ poor self-rated health) was slightly attenuated compared with the larger samples (Table 3). There were no significant differences in the associations between cardiorespiratory fitness and self-rated health between different samples.
Discussion High levels of physical activity and cardiorespiratory fitness were associated with better self-rated health in this sample of Finnish adolescents. Our finding that physically active adolescents more often report good self-rated health than physically inactive adolescents is in line with previous studies.5,23,24 Recently, Breidablik et al reported that self-rated health deteriorated consistently with a decrease in sports and exercise over a 4-year observation period among adolescents.6
Table 2 Self-Rated Health by Physical Activity and Cardiorespiratory Fitness (%) Very Good Boys Physical activitya (N = 3,322) High Average Low P-trendb Cardiorespiratory fitnessc (N = 2,385) High Average Low P-trendb Girls Physical activitya (N = 3,582) High Average Low P-trendb Cardiorespiratory fitnessc (N = 2,167) High Average Low P-trendb
Self-Rated Health Good
Moderate/Poor
42.5 28.6 16.4 < .001
49.7 57.7 60.7
7.7 13.7 23.0
39.8 29.8 22.9 < .001
52.6 57.1 57.0
7.6 13.1 20.1
27.1 20.0 12.3 < .001
62.3 64.2 61.5
10.6 15.8 26.2
28.4 22.4 16.4 < .001
60.8 65.5 64.8
10.8 12.0 18.9
a Metabolic equivalent hours based on the intensity and volume of physical activity divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the middle tertile), and (3) low (the lowest tertile). b Linear-by-linear association test. c Peak oxygen uptake (VO peak) in ml·kg–1·min–1 divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the 2 middle tertile), and (3) low (the lowest tertile).
Table 3 Multinomial Regression of Physical Activitya on Self-Rated Health Self-Rated Health Good vs Moderate/Poor OR (95% CI) Very Good vs Moderate/Poor OR (95% CI)
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Boys Model 1b (N = 3,322) Average vs low High vs low Model 2c (N = 1,595) Average vs low High vs low Model 3d (N = 1,151) Average vs low High vs low Girls Model 1b (N = 3,582) Average vs low High vs low Model 2c (N = 1,775) Average vs low High vs low Model 3d (N = 1,078) Average vs low High vs low
1.60 (1.27, 2.02) 2.43 (1.87, 3.18)
2.94 (2.24, 3.88) 7.72 (5.74, 10.38)
1.35 (0.96, 1.89) 2.69 (1.80, 4.02)
1.96 (1.29, 2.96) 6.87 (4.36, 10.82)
1.08 (0.71, 1.64) 2.10 (1.27, 3.47)
1.33 (0.81, 2.18) 5.50 (3.16, 9.58)
1.73 (1.40, 2.12) 2.50 (1.99, 3.15)
2.70 (2.05, 3.55) 5.48 (4.11, 7.30)
1.38 (1.03, 1.86) 2.44 (1.74, 3.41)
1.92 (1.27, 2.91) 4.73 (3.06, 7.31)
1.14 (0.75, 1.75) 1.74 (1.10, 2.75)
1.70 (0.95, 3.02) 4.25 (2.37, 7.61)
Note. OR = odds ratio; CI = confidence interval. a Metabolic equivalent hours based on the intensity and volume of physical activity divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the middle tertile), and (3) low (the lowest tertile). b Unadjusted associations. c Adjusted for obesity level, mother’s and father’s socioeconomic position, smoking, emotional and behavioral problems, long-term illness, and handicap and disability. d Additional adjustment for cardiorespiratory fitness.
Table 4 Multinomial Regression of Cardiorespiratory Fitnessa on Self-Rated Health Self-Rated Health Good vs Moderate/Poor OR (95% CI) Very Good vs Moderate/Poor OR (95% CI) Boys Model 1b (N = 2,385) Average vs low High vs low Model 2c (N = 1,167) Average vs low High vs low Model 3d (N = 1,151) Average vs low High vs low Girls Model 1b (N = 2,167) Average vs low High vs low Model 2c (N = 1,097) Average vs low High vs low Model 3d (N = 1,078) Average vs low High vs low
1.54 (1.16, 2.04) 2.43 (1.76, 3.36)
2.00 (1.46, 2.74) 4.59 (3.24, 6.48)
1.37 (0.89, 2.11) 2.10 (1.27, 3.45)
1.30 (0.80, 2.12) 2.75 (1.60, 4.73)
1.34 (0.86, 2.08) 1.80 (1.08, 3.01)
1.09 (0.66, 1.81) 1.85 (1.05, 3.24)
1.59 (1.18, 2.14) 1.64 (1.21, 2.23)
2.15 (1.50, 3.08) 3.02 (2.11, 4.33)
1.27 (0.82, 1.96) 1.46 (0.93, 2.31)
1.69 (0.97, 2.95) 2.77 (1.58, 4.86)
1.25 (0.81, 1.94) 1.42 (0.89, 2.27)
1.74 (0.99, 3.06) 2.62 (1.47, 4.66)
Note. OR = odds ratio; CI = confidence interval. a Peak oxygen uptake (VO peak) in ml·kg–1·min–1 divided into sex-specific quintiles: (1) high (two highest quintiles), (2) average (third 2 and fourth quintiles), and (3) low (lowest quintile). b Unadjusted associations. c Adjusted for obesity level, mother’s and father’s socioeconomic position, smoking, emotional and behavioral problems, long-term illness, and handicap and disability. d Additional adjustment for physical activity.
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Physical Activity and Self-Rated Health 271
According to the authors, self-rated health is a relatively stable construct during adolescence, and is potentially influenced by health-compromising lifestyle factors, such as physical inactivity.6 In turn, Page and Suwanteerangkul concluded that Thai adolescents who rated themselves as “very healthy” were more likely to engage in vigorous physical and muscle-strengthening activities, play on sports teams, and score higher on the physical activity index compared with adolescents who rated themselves as “healthy” or “not healthy”.25 Previous studies have reported both direct and indirect (eg, through smoking, alcohol consumption, and mental health problems) influences of sport and physical activity on perceived health.26,27 Adolescents who engage in sports more frequently tend to experience fewer feelings of anxiety and depression, describe fewer psycho-physiological symptoms, and indicate higher perceived fitness.26,27 These results are consistent with studies that have analyzed the benefits of physical activity on healthy lifestyles and on psychological well-being.26 Pastor et al even suggested that one’s perceived fitness was a more important mediator for perceived health than one’s psychological state.26 However, the direct effect of sport on perceived health seems to be greater than the indirect effect.26 Our finding that high levels of cardiorespiratory fitness were associated with good self-rated health supports the recent findings of Mota et al, who concluded that physically unfit adolescents were more likely to report negative self-rated health compared with their physically fit peers.11 According to the authors, cardiorespiratory fitness also mediates the association between body mass index and self-rated health.11 Because of its association with a better metabolic profile and, therefore, good perceived health, cardiorespiratory fitness may improve psychological well-being, making it of great value to public health11 and an important objective for future research. In the current study, the association between self-reported physical activity and self-rated health remained stronger after the adjustment for obesity level, mother’s and father’s socioeconomic position, smoking, emotional and behavioral problems, long-term illness, and handicap and disability, compared with the association between objectively measured fitness and self-rated health. This might reflect the subjective nature of our measure of physical activity or some conceptual overlap between self-reported physical activity and self-rated general health, resulting in stronger associations between self-reported measures. It is also possible that adolescents with better self-rated health are more likely to report their physical activity, or it might reflect the healthier nature of our slightly smaller sample of adolescents who participated in objective measurement of cardiorespiratory fitness. To our knowledge, this is the first study to demonstrate positive, mutual associations of physical activity and cardiorespiratory fitness with adolescents’ self-rated health in a large birth cohort with objective measurement of cardiorespiratory fitness. The major strength of this study lies in the large, unselected population sample. Participation rates were high in both the postal questionnaire surveys and the clinical examination. In addition, cardiorespiratory fitness was measured objectively with a cycle ergometer test. Because of the cross-sectional design of this study, reverse causality is possible; that is, poor self-rated health could have an effect on physical activity and cardiorespiratory fitness. The current study relied on selfreporting of physical activity, which is more prone to measurement errors and social desirability bias than more objective measurements. Adjustment for various confounding variables resulted in substantial loss of participants in the fully adjusted models, which possibly attenuates the associations between average level physical activity and self-rated health. In addition, multinomial logistic regression,
the statistical method used in the current study, is less parsimonious than, for example, ordered logistic regression model. However, multinomial logistic model does not assume proportionality between the categories of outcome variable, like ordered logistic regression. The results can most likely be generalized to represent Finnish adolescents aged about 15 to 16 years. Some results, for instance, the levels of physical activity and cardiorespiratory fitness, and to some extent, the distribution of parental socioeconomic position, are typical for Northern Finland. Levels of physical activity and cardiorespiratory fitness may also have changed in Finnish adolescents since 2001 to 2002. Therefore, it would be useful to investigate physical activity and cardiorespiratory fitness in association with adolescent self-rated health in more contemporary cohorts and versatile sociocultural settings. A deeper understanding of the causal directions of these associations, the mechanisms behind them, as well as the interactions between physical activity, cardiorespiratory fitness, and self-rated health requires knowledge of both the direct and indirect influences of physical activity and cardiorespiratory fitness on adolescents’ self-rated health. A key to understanding these relations in the future will be the examination of how physical activity, cardiorespiratory fitness, and self-rated health change with respect to each other over time, or as the result of an intervention.
Conclusions High levels of physical activity and high levels of cardiorespiratory fitness were associated with good self-rated health in adolescents. Public health promotion activities to foster physical activity and cardiorespiratory fitness may benefit young people by improving their overall health and well-being. Acknowledgments Marko T. Kantomaa is supported by a grant (76/627/2011) from the Ministry of Education and Culture, Finland. Emmanuel Stamatakis is funded by the National Institute for Health Research UK through a Career Development Fellowship. The Northern Finland Birth Cohort 1986 is supported by grants from the Academy of Finland, European Union, National Institutes of Health, Wellcome Trust, Nordic Academy for Advanced Study, and Ministry of Education and Culture, Finland.
References 1. Wade TJ, Pevalin DJ, Vingilis E. Revisiting student self-rated physical health. J Adolesc. 2000;23(6):785–791. PubMed doi:10.1006/ jado.2000.0359 2. Idler EL, Benyamini Y. Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav. 1997;38(1):21– 37. PubMed doi:10.2307/2955359 3. Breidablik HJ, Meland E, Lydersen S. Self-rated health in adolescence: a multifactorial composite. Scand J Public Health. 2008;36(1):12–20. PubMed doi:10.1177/1403494807085306 4. Bjorner JB, Kristensen TS, Orth-Gomer K, Tibblin G, Sullivan M, Westerholm P. Self-rated Health: A Useful Concept in Research, Prevention, and Clinical Medicine. Stockholm: Swedish Council for Planning and Coordination of Research; 1996. 5. Tremblay S, Dahinten S, Kohen D. Factors related to adolescents’ self-perceived health. Health Rep. 2003;14(Suppl):7–16. PubMed 6. Breidablik HJ, Meland E, Lydersen S. Self-rated health during adolescence: stability and predictors of change (Young-HUNT study, Norway). Eur J Public Health. 2009;19(1):73–78. PubMed doi:10.1093/eurpub/ckn111
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272 Kantomaa et al 7. Piko BF, Keresztes N. Self-perceived health among early adolescents: role of psychosocial factors. Pediatr Int. 2007;49(5):577–583. PubMed doi:10.1111/j.1442-200X.2007.02430.x 8. Dowdell EB, Santucci ME. Health risk behavior assessment: nutrition, weight, and tobacco use in one urban seventh-grade class. Public Health Nurs. 2004;21(2):128–136. PubMed doi:10.1111/j.07371209.2004.021206.x 9. Goodwin DK, Knol LL, Eddy JM, Fitzhugh EC, Kendrick OW, Donahue RE. The relationship between self-rated health status and the overall quality of dietary intake of US adolescents. J Am Diet Assoc. 2006;106(9):1450–1453. PubMed doi:10.1016/j.jada.2006.06.011 10. Piko B. Health-related predictors of self-perceived health in a student population: the importance of physical activity. J Community Health. 2000;25(2):125–137. PubMed doi:10.1023/A:1005129707550 11. Mota J, Santos RM, Silva P, Aires L, Martins C, Vale S. Associations between self-rated health with cardiorespiratory fitness and obesity status among adolescent girls. J Phys Act Health. 2012;9(3):378–381. PubMed 12. Jarvelin MR, Hartikainen-Sorri AL, Rantakallio P. Labour induction policy in hospitals of different levels of specialisation. Br J Obstet Gynaecol. 1993;100(4):310–315. PubMed doi:10.1111/j.1471-0528.1993. tb12971.x 13. Tammelin T, Ekelund U, Remes J, Nayha S. Physical activity and sedentary behaviors among Finnish youth. Med Sci Sports Exerc. 2007;39(7):1067–1074. PubMed doi:10.1249/mss.0b13e318058a603 14. Ainsworth BE, Haskell WL, Whitt MC, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32(9 Suppl):S498–S504. PubMed doi:10.1097/00005768-200009001-00009 15. Tammelin T, Remes J, Kujala V, et al. Cardiorespiratory fitness of Finnish adolescents. Int J Sports Med. 2007;28(10):853–859. PubMed doi:10.1055/s-2007-964911 16. Singh-Manoux A, Gueguen A, Martikainen P, Ferrie J, Marmot M, Shipley M. Self-rated health and mortality: short- and long-term associations in the Whitehall II study. Psychosom Med. 2007;69(2):138–143. PubMed doi:10.1097/PSY.0b013e318030483a
17. Singh-Manoux A, Martikainen P, Ferrie J, Zins M, Marmot M, Goldberg M. What does self rated health measure? Results from the British Whitehall II and French Gazel cohort studies. J Epidemiol Community Health. 2006;60(4):364–372. PubMed doi:10.1136/jech.2005.039883 18. Cole TJ, Bellizzi M, Flegal K, Dietz W. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000;320(7244):1240–1243. PubMed doi:10.1136/ bmj.320.7244.1240 19. Statistics Finland. Classification of Socio-economic Groups 1989. Helsinki: Statistics Finland; 1989. 20. Achenbach TM, Rescorla LA. Manual for the ASEBA School Age Forms & Profiles. Burlington: University of Vermont, Research Center for Children, Youth, & Families; 2001. 21. Kantomaa MT, Tammelin TH, Ebeling HE, Taanila AM. Emotional and behavioral problems in relation to physical activity in youth. Med Sci Sports Exerc. 2008;40(10):1749–1756. PubMed doi:10.1249/ MSS.0b013e31817b8e82 22. SPSS. IBM SPSS Statistics 19 Core System User’s Guide. Chicago: SPSS Inc; 2010. 23. Heard HE, Gorman BK, Kapinus CA. Family structure and self-rated health in adolescence and young adulthood. Popul Res Policy Rev. 2008;27(6):773–797. doi:10.1007/s11113-008-9090-9 24. Boardman JD. Self-rated health among U.S. adolescents. J Adolesc Health. 2006;38(4):401–408. PubMed doi:10.1016/j.jadohealth.2005.01.006 25. Page RM, Suwanteerangkul J. Self-rated health, psychosocial functioning, and health-related behavior among Thai adolescents. Pediatr Int. 2009;51(1):120–125. PubMed doi:10.1111/j.1442200X.2008.02660.x 26. Pastor Y, Balaguer I, Pons D, Garcia-Merita M. Testing direct and indirect effects of sports participation on perceived health in Spanish adolescents between 15 and 18 years of age. J Adolesc. 2003;26(6):717–730. PubMed doi:10.1016/j.adolescence.2003.07.001 27. Thorlindsson T, Vilhjalmsson R, Valgeirsson G. Sport participation and perceived health status: a study of adolescents. Soc Sci Med. 1990;31(5):551–556. PubMed doi:10.1016/0277-9536(90)90090-F
Official Journal of ISPAH www.JPAH-Journal.com ORIGINAL RESEARCH
High Levels of Physical Activity and Cardiorespiratory Fitness are Associated With Good Self-Rated Health in Adolescents Marko T. Kantomaa, Tuija Tammelin, Hanna Ebeling, Emmanuel Stamatakis, and Anja Taanila Background: Adolescent self-rated health is a strong predictor of future illness. In this study we investigated whether physical activity and cardiorespiratory fitness are associated with self-rated health among adolescents aged 16 years. Methods: The study sample comprised 7,063 adolescents from the Northern Finland Birth Cohort 1986 (NFBC 1986) who responded to a postal questionnaire in 2001 to 2002. Self-rated health was measured by a single-item question, while physical activity was evaluated by a set of questions concerning the intensity and volume of physical activity outside school hours. Cardiorespiratory fitness was measured with a submaximal cycle ergometer test. Odds ratios (OR) and their 95% confidence intervals (95% CI) for good self-rated health were obtained from multinomial logistic regression. Results: High levels of physical activity (boys: OR 5.50, 95% CI 3.16 to 9.58; girls: OR 4.25, 95% CI 2.37 to 7.61) and cardiorespiratory fitness (boys: OR 1.85, 95% CI 1.05 to 3.24; girls: OR 2.62, 95% CI 1.47 to 4.66) were associated with very good self-rated health in adolescents. Conclusions: High levels of physical activity and cardiorespiratory fitness are positively associated with adolescents’ self-rated health. Public health promotion activities that foster physical activity and cardiorespiratory fitness may benefit young people’s overall health and well-being. Keywords: exercise, well-being, youth One of the most commonly used measures of perceived health status consists of a single Likert scale question, querying about respondents’ overall health.1 This measure of self-rated health has consistently been found to be a valid measure of overall physical health status among adults.2 Self-rated health is, even in young populations, strongly linked to mortality3 and is a strong predictor of future illness, independently of clinical health status.4 Health-related behaviors such as physical activity may be important contributors to self-rated health among adolescents.5 There is some literature suggesting that physical activity is positively associated with adolescents’ self-rated health,3,6,7 and it has been suggested that health-related behaviors, such as physical activity, may play a central role for adolescents when determining their self-rated health status.8,9 However, the association between physical activity and self-rated health among adolescents may differ according to sex and a person’s overall level of physical activity, the association being stronger among boys and among more active adolescents.10 Even though much less is known about the association between cardiorespiratory fitness and self-rated health among young people, there is some evidence of a positive association between these factors.11 However, the number of studies on cardiorespiratory fitness Kantomaa ([email protected]) and Tammelin are with LIKES – Research Center for Sport and Health Sciences, Jyväskylä, Finland. Kantomaa is also with the Dept of Epidemiology and Biostatistics, Imperial College London, London, UK. Ebeling is with the Institute of Clinical Medicine, Dept of Child Psychiatry, University of Oulu, Oulu, Finland; and the Clinic of Child Psychiatry, Oulu University Hospital, Oulu, Finland. Stamatakis is with Charles Perkins Centre, University of Sydney, Australia; Exercise and Sport Sciences, Faculty of Health Sciences, University of Sydney, Sydney, Australia; and Physical Activity Research Group, Dept of Epidemiology and Public Health, University College London, London, UK. Taanila is with the Institute of Health Sciences, University of Oulu, Oulu, Finland. 266
and self-rated health among adolescents is very limited, especially with respect to those using objective measures of cardiorespiratory fitness. Furthermore, studies on the mutual associations of physical activity and cardiorespiratory fitness with self-rated health are rare. The existing literature looking at the associations of physical activity and cardiorespiratory fitness with self-rated health among adolescents lacks studies with large, unselected population samples and high-quality study designs. The purpose of this study was to investigate whether physical activity and cardiorespiratory fitness are associated with self-rated health among adolescents in a large, population-based birth cohort. We hypothesized that high levels of physical activity and cardiorespiratory fitness are associated with good self-rated health among adolescents.
Methods Participants The study population consisted of the Northern Finland Birth Cohort 1986 (NFBC 1986), which, at the baseline of this study, was composed of 9,432 infants whose expected date of birth was between July 1, 1985 and June 30, 1986 in the two northernmost provinces of Finland, Oulu, and Lapland.12 In 2001 to 2002, at the age of 15 to 16 years (hereafter referred to as “16 years”), the cohort members were sent a postal questionnaire including questions about health and well-being (response rate 80%, N = 7,344). Parents were also sent a postal inquiry including questions about family conditions (response rate 76%, N = 6,985). At the age of 16 years, cohort members also participated in individual health examinations (participation rate 74%, N = 6,798), including the measurement of cardiorespiratory fitness (N = 5,375). The present analyses included those 7,063 adolescents who reported their self-rated health at age 16 years. Informed consent was obtained from all participants and their parents, and the research protocol was approved by the Ethics Committee of Northern Ostrobotnia Hospital District.
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Physical Activity and Self-Rated Health 267
Physical Activity
Potential Confounders
The amount of physical activity outside school hours was evaluated separately for moderate-to-vigorous physical activity and light physical activity at age 16 years by asking participants, “How many hours a week all together do you participate in (a) brisk and (b) light physical activity outside school hours?” In the questionnaire, the term “brisk” was defined as physical activity causing at least some sweating and shortness of breath (here referred to as moderate-tovigorous intensity physical activity), while the term “light physical activity” was defined as causing no sweating or shortness of breath. In addition, the adolescents were asked about their daily time spent in physically active commutes to and from school. The response alternatives (not at all, less than 20 min, 20 to 39 min, 40 to 59 min, and at least 1 hour per day) were multiplied by 5 (5 school days a week) to correspond to 0, 1, 2.5, 3.75, and 5 hours per week.13 The physical activity level was converted into metabolic equivalent of task (MET) hours per week based on the intensity and the volume of physical activity engaged in outside school hours, including commuting to and from school. An MET intensity value of 3 METs was used for light physical activity, 5 METs for brisk physical activity, and 4 METs for all types of commuting physical activity in the calculations.14 MET hours were divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the middle tertile), and (3) low (the lowest tertile). The test-retest reliability of these physical activity questions among Finnish adolescents aged 15 to 16 years has been shown to be good.13 The intraclass correlation coefficient for physical activity levels described in terms of quintile categories of MET hours per week was 0.70 (95% confidence interval 0.58 to 0.80), and the proportion of subjects who were classified in the same or next (up or down) category between test and retest was 86%.
At the age of 16 years, the adolescents self-reported their body weight and height in the postal questionnaire, and these were measured in the health examination. Self-reported body weight and height were used for those who failed to attend the health examination. Body mass index (BMI) was calculated as the individual’s weight divided by the square of the height (kg/m2). Obesity was defined using the International Obesity Task Force (IOTF) agespecific cut-off points for BMI.18 Information about parental socioeconomic position was obtained from the parents’ questionnaire at the age of 16 years. Socioeconomic position was based on the mother’s and father’s occupations. Parental socioeconomic position was classified into six groups: (1) upper-level employees, (2) lower-level employees, (3) farmers, (4) self-employed persons, (5) manual workers, and (6) others (students, pensioners, and others).19 Adolescent smoking at the age of 16 years was measured by asking, “Do you smoke now?” The response alternatives were: (1) not at all, (2) occasionally, (3) on one day a week, (4) on 2 to 4 days a week, (5) on 5 to 6 days a week, and (6) 7 days a week. Emotional and behavioral problems were measured using the Youth Self-Report (YSR), a widely used questionnaire designed to assess emotional and behavioral problems among adolescents aged 11 to 18 years.20 The YSR was scored for the following 8 syndrome scales: (1) anxious/depressed symptoms, (2) withdrawn/depressed symptoms, (3) somatic complaints, (4) social problems, (5) thought problems, (6) attention problems, (7) rule-breaking behavior, and (8) aggressive behavior. These 8 core syndrome scales were further combined into a Total Problem Scale.21 Information about adolescent long-term illness (other than heart defect or high blood pressure) and handicap and disability diagnosed by a doctor was obtained from the parents’ questionnaire at the age of 16 years.
Cardiorespiratory Fitness Cardiorespiratory fitness was measured during a health examination at age 16 (N = 5,375) with a submaximal cycle ergometer test, and was expressed as peak oxygen uptake (VO2peak) in ml·kg–1·min–1. Adolescents were categorized into sex-specific thirds of fitness: (1) high (the highest tertile), (2) average (the middle tertile), and (3) low (the lowest tertile). The exercise test protocol included 2 incremental work stages of 4 minutes each on a bicycle ergometer (model 818E, Monark, Sweden). Peak oxygen uptake (VO2peak in ml·kg–1·min–1) was calculated based on the heart-rate response during submaximal work stages. The method has been validated against directly measured VO2peak during the maximal exercise test, and has previously been described in detail.15
Self-Rated Health Self-rated overall health was measured by asking, “How would you describe your health at the moment?” The response alternatives were: (1) very poor, (2) poor, (3) fair, (4) good, and (5) very good. Because of low prevalence of very poor, poor, and fair self-rated health in the current study sample (altogether 16%) and, therefore, for the reasons of statistical power, the adolescents were grouped into three groups: (1) very good, (2) good, and (3) moderate/poor (fair, poor, or very poor self-rated health). This single-item measure of general health status has been used widely in previous research and has been consistently found to be an independent predictor of mortality, as well as a reasonable measure of objective health status in adults.2,16,17
Statistical Analyses The basic analyses included frequency counts and relative distributions. Bivariate associations were tested separately for boys and girls with cross-tabulation using chi-square tests and multinomial logistic regression. Multivariable analyses were also performed separately for boys and girls using multiple multinomial logistic regression. The results of the regression analyses are presented with odds ratios (OR) and 95% confidence intervals (95% CI). In the multivariable models, the variables were adjusted for obesity level, parental socioeconomic position, smoking, emotional and behavioral problems, long-term illness, handicap and disability, and mutually for cardiorespiratory fitness and physical activity. The data were analyzed using SPSS software, version 19 (IBM, Chicago, IL).22
Results Boys were physically more active (P < .001) and had higher cardiorespiratory fitness (P < .001) than girls at the age of 16 years. The mean MET hours per week were 32.9 (SD 17.9) among boys and 28.6 (SD 15.5) among girls. The mean peak oxygen consumption was 49.1 (SD 9.7) ml·kg–1·min–1 among boys and 35.4 (SD 6.3) ml·kg–1·min–1 among girls. The sex-specific distributions of the variables used in the current study are presented in Table 1.
Table 1 Characteristics of the Northern Finland Birth Cohort 1986 Study Sample
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Characteristic Self-rated health Very good Good Moderate/poor Physical activityb High Average Low Cardiorespiratory fitnessc High Average Low Obesity leveld Normal weight Overweight Obese Long-term illnesse Yes No Mother’s socioeconomic position Upper-level employees Lower-level employees Farmers Self-employed Manual workers Others Father’s socioeconomic position Upper-level employees Lower-level employees Farmers Self-employed Manual workers Others Smoking Not at all Occasionally On 1 day a week On 2–4 days a week On 5–6 days a week 7 days a week Emotional and behavioral problemsf Yes No
Boys N (total) (3,406) 1,002 1,902 502 (3,322) 1,162 1,090 1,070 (2,385) 799 786 800 (3,371) 2,804 425 142 (3,008) 602 2,406 (2,947) 497 1,558 118 81 529 164 (2,782) 720 518 207 197 1,063 77 (2,156) 1,181 401 37 67 77 393 (3,275) 291 2,984
% 29.4 55.8 14.7 35.0 32.8 32.2 33.5 33.0 33.5 83.2 12.6 4.2 20.0 80.0 16.9 52.9 4.0 2.7 18.0 5.6 25.9 18.6 7.4 7.1 38.2 2.8 54.8 18.6 1.7 3.1 3.6 18.2 8.9 91.1
Girls N (total) (3,657) 726 2,290 641 (3,582) 1,227 1,237 1,118 (2,167) 730 722 715 (3,632) 3,136 389 107 (3,197) 605 2,592 (3,094) 527 1,589 129 84 614 151 (2,931) 704 539 256 191 1,132 109 (2,459) 1,092 579 26 124 127 511 (3,563) 629 2,934
%
P-valuea < .001
19.9 62.6 17.5 N/A 34.3 34.5 31.2 N/A 33.7 33.3 33.0 < .001 86.3 10.7 2.9 .279 18.9 81.1 .414 17.0 51.4 4.2 2.7 19.8 4.9 .085 24.0 18.4 8.7 6.5 38.6 3.7 < .001 44.4 23.5 1.1 5.0 5.2 20.8 < .001 17.7 82.3
P-values for the sex differences (Pearson’s chi-squared test). Metabolic equivalent hours based on the intensity and volume of physical activity divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the middle tertile), and (3) low (the lowest tertile). c Peak oxygen uptake (VO peak) in ml·kg–1·min–1 divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the middle tertile), and 2 (3) low (the lowest tertile). d Obesity level was defined using the International Obesity Task Force (IOTF) age-specific cut-off points for body mass index (BMI). BMI was calculated as weight divided by the square of the height (kg/m2). e Includes long-term illness (other than heart defect or high blood pressure) and handicap and disability. f Includes anxious/depressed, withdrawn/depressed, social, thought and attention problems, somatic complaints, and rule-breaking and aggressive behavior. a
b
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According to the unadjusted results from cross-tabulation with linear-by-linear association test, physical activity and a high level of cardiorespiratory fitness were associated with good self-rated health (Table 2). When adjusted for obesity, parental socioeconomic position, smoking, emotional and behavioral problems, long-term illness, handicap and disability, and mutually for cardiorespiratory fitness and physical activity, physically active boys (OR 5.50, 95% CI 3.16, 9.58) and girls (OR 4.25, 95% CI 2.37, 7.61) were more likely to report very good self-rated health compared with moderate/ poor self-rated health than their physically inactive peers (Table 3). Physically active adolescents were also more likely to report good self-rated health compared with moderate/poor self-rated health than physically inactive adolescents (Table 3). Similarly, boys (OR 1.85, 95% CI 1.05, 3.24) and girls (OR 2.62, 95% CI 1.47, 4.66) with a high level of cardiorespiratory fitness were more likely to report very good self-rated health compared with moderate/poor self-rated health than their peers with low levels of cardiorespiratory fitness (Table 4). In addition, adolescents with high levels of cardiorespiratory fitness were more likely to report good self-rated health compared with moderate/poor self-rated health than adolescents with low levels of cardiorespiratory fitness (Table 4). We also fitted the regression models 1 and 2 for the restricted samples of 1,151 boys and 1,078 girls having information on all the variables included in the fully-adjusted models (Tables 3 and 4).
In general, there were no significant differences in the estimates. However, in the restricted sample the association between average level of physical activity (compared with low level of physical activity) and good (model 1: boys OR 1.18, 95% CI 0.80, 1.76; girls OR 1.24, 95% CI 0.82, 1.86; model 2: boys OR 1.12, 95% CI 0.74, 1.70; girls OR 1.15, 95% CI 0.75, 1.76) and very good (model 1: boys OR 1.60, 95% CI 1.00, 2.56; girls OR 1.87, 95% CI 1.09, 3.21; model 2: boys OR 1.39, 95% CI 0.85, 2.28; girls OR 1.69, 95% CI 0.96, 3.01) self-rated health (compared with moderate/ poor self-rated health) was slightly attenuated compared with the larger samples (Table 3). There were no significant differences in the associations between cardiorespiratory fitness and self-rated health between different samples.
Discussion High levels of physical activity and cardiorespiratory fitness were associated with better self-rated health in this sample of Finnish adolescents. Our finding that physically active adolescents more often report good self-rated health than physically inactive adolescents is in line with previous studies.5,23,24 Recently, Breidablik et al reported that self-rated health deteriorated consistently with a decrease in sports and exercise over a 4-year observation period among adolescents.6
Table 2 Self-Rated Health by Physical Activity and Cardiorespiratory Fitness (%) Very Good Boys Physical activitya (N = 3,322) High Average Low P-trendb Cardiorespiratory fitnessc (N = 2,385) High Average Low P-trendb Girls Physical activitya (N = 3,582) High Average Low P-trendb Cardiorespiratory fitnessc (N = 2,167) High Average Low P-trendb
Self-Rated Health Good
Moderate/Poor
42.5 28.6 16.4 < .001
49.7 57.7 60.7
7.7 13.7 23.0
39.8 29.8 22.9 < .001
52.6 57.1 57.0
7.6 13.1 20.1
27.1 20.0 12.3 < .001
62.3 64.2 61.5
10.6 15.8 26.2
28.4 22.4 16.4 < .001
60.8 65.5 64.8
10.8 12.0 18.9
a Metabolic equivalent hours based on the intensity and volume of physical activity divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the middle tertile), and (3) low (the lowest tertile). b Linear-by-linear association test. c Peak oxygen uptake (VO peak) in ml·kg–1·min–1 divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the 2 middle tertile), and (3) low (the lowest tertile).
Table 3 Multinomial Regression of Physical Activitya on Self-Rated Health Self-Rated Health Good vs Moderate/Poor OR (95% CI) Very Good vs Moderate/Poor OR (95% CI)
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Boys Model 1b (N = 3,322) Average vs low High vs low Model 2c (N = 1,595) Average vs low High vs low Model 3d (N = 1,151) Average vs low High vs low Girls Model 1b (N = 3,582) Average vs low High vs low Model 2c (N = 1,775) Average vs low High vs low Model 3d (N = 1,078) Average vs low High vs low
1.60 (1.27, 2.02) 2.43 (1.87, 3.18)
2.94 (2.24, 3.88) 7.72 (5.74, 10.38)
1.35 (0.96, 1.89) 2.69 (1.80, 4.02)
1.96 (1.29, 2.96) 6.87 (4.36, 10.82)
1.08 (0.71, 1.64) 2.10 (1.27, 3.47)
1.33 (0.81, 2.18) 5.50 (3.16, 9.58)
1.73 (1.40, 2.12) 2.50 (1.99, 3.15)
2.70 (2.05, 3.55) 5.48 (4.11, 7.30)
1.38 (1.03, 1.86) 2.44 (1.74, 3.41)
1.92 (1.27, 2.91) 4.73 (3.06, 7.31)
1.14 (0.75, 1.75) 1.74 (1.10, 2.75)
1.70 (0.95, 3.02) 4.25 (2.37, 7.61)
Note. OR = odds ratio; CI = confidence interval. a Metabolic equivalent hours based on the intensity and volume of physical activity divided into sex-specific thirds: (1) high (the highest tertile), (2) average (the middle tertile), and (3) low (the lowest tertile). b Unadjusted associations. c Adjusted for obesity level, mother’s and father’s socioeconomic position, smoking, emotional and behavioral problems, long-term illness, and handicap and disability. d Additional adjustment for cardiorespiratory fitness.
Table 4 Multinomial Regression of Cardiorespiratory Fitnessa on Self-Rated Health Self-Rated Health Good vs Moderate/Poor OR (95% CI) Very Good vs Moderate/Poor OR (95% CI) Boys Model 1b (N = 2,385) Average vs low High vs low Model 2c (N = 1,167) Average vs low High vs low Model 3d (N = 1,151) Average vs low High vs low Girls Model 1b (N = 2,167) Average vs low High vs low Model 2c (N = 1,097) Average vs low High vs low Model 3d (N = 1,078) Average vs low High vs low
1.54 (1.16, 2.04) 2.43 (1.76, 3.36)
2.00 (1.46, 2.74) 4.59 (3.24, 6.48)
1.37 (0.89, 2.11) 2.10 (1.27, 3.45)
1.30 (0.80, 2.12) 2.75 (1.60, 4.73)
1.34 (0.86, 2.08) 1.80 (1.08, 3.01)
1.09 (0.66, 1.81) 1.85 (1.05, 3.24)
1.59 (1.18, 2.14) 1.64 (1.21, 2.23)
2.15 (1.50, 3.08) 3.02 (2.11, 4.33)
1.27 (0.82, 1.96) 1.46 (0.93, 2.31)
1.69 (0.97, 2.95) 2.77 (1.58, 4.86)
1.25 (0.81, 1.94) 1.42 (0.89, 2.27)
1.74 (0.99, 3.06) 2.62 (1.47, 4.66)
Note. OR = odds ratio; CI = confidence interval. a Peak oxygen uptake (VO peak) in ml·kg–1·min–1 divided into sex-specific quintiles: (1) high (two highest quintiles), (2) average (third 2 and fourth quintiles), and (3) low (lowest quintile). b Unadjusted associations. c Adjusted for obesity level, mother’s and father’s socioeconomic position, smoking, emotional and behavioral problems, long-term illness, and handicap and disability. d Additional adjustment for physical activity.
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Physical Activity and Self-Rated Health 271
According to the authors, self-rated health is a relatively stable construct during adolescence, and is potentially influenced by health-compromising lifestyle factors, such as physical inactivity.6 In turn, Page and Suwanteerangkul concluded that Thai adolescents who rated themselves as “very healthy” were more likely to engage in vigorous physical and muscle-strengthening activities, play on sports teams, and score higher on the physical activity index compared with adolescents who rated themselves as “healthy” or “not healthy”.25 Previous studies have reported both direct and indirect (eg, through smoking, alcohol consumption, and mental health problems) influences of sport and physical activity on perceived health.26,27 Adolescents who engage in sports more frequently tend to experience fewer feelings of anxiety and depression, describe fewer psycho-physiological symptoms, and indicate higher perceived fitness.26,27 These results are consistent with studies that have analyzed the benefits of physical activity on healthy lifestyles and on psychological well-being.26 Pastor et al even suggested that one’s perceived fitness was a more important mediator for perceived health than one’s psychological state.26 However, the direct effect of sport on perceived health seems to be greater than the indirect effect.26 Our finding that high levels of cardiorespiratory fitness were associated with good self-rated health supports the recent findings of Mota et al, who concluded that physically unfit adolescents were more likely to report negative self-rated health compared with their physically fit peers.11 According to the authors, cardiorespiratory fitness also mediates the association between body mass index and self-rated health.11 Because of its association with a better metabolic profile and, therefore, good perceived health, cardiorespiratory fitness may improve psychological well-being, making it of great value to public health11 and an important objective for future research. In the current study, the association between self-reported physical activity and self-rated health remained stronger after the adjustment for obesity level, mother’s and father’s socioeconomic position, smoking, emotional and behavioral problems, long-term illness, and handicap and disability, compared with the association between objectively measured fitness and self-rated health. This might reflect the subjective nature of our measure of physical activity or some conceptual overlap between self-reported physical activity and self-rated general health, resulting in stronger associations between self-reported measures. It is also possible that adolescents with better self-rated health are more likely to report their physical activity, or it might reflect the healthier nature of our slightly smaller sample of adolescents who participated in objective measurement of cardiorespiratory fitness. To our knowledge, this is the first study to demonstrate positive, mutual associations of physical activity and cardiorespiratory fitness with adolescents’ self-rated health in a large birth cohort with objective measurement of cardiorespiratory fitness. The major strength of this study lies in the large, unselected population sample. Participation rates were high in both the postal questionnaire surveys and the clinical examination. In addition, cardiorespiratory fitness was measured objectively with a cycle ergometer test. Because of the cross-sectional design of this study, reverse causality is possible; that is, poor self-rated health could have an effect on physical activity and cardiorespiratory fitness. The current study relied on selfreporting of physical activity, which is more prone to measurement errors and social desirability bias than more objective measurements. Adjustment for various confounding variables resulted in substantial loss of participants in the fully adjusted models, which possibly attenuates the associations between average level physical activity and self-rated health. In addition, multinomial logistic regression,
the statistical method used in the current study, is less parsimonious than, for example, ordered logistic regression model. However, multinomial logistic model does not assume proportionality between the categories of outcome variable, like ordered logistic regression. The results can most likely be generalized to represent Finnish adolescents aged about 15 to 16 years. Some results, for instance, the levels of physical activity and cardiorespiratory fitness, and to some extent, the distribution of parental socioeconomic position, are typical for Northern Finland. Levels of physical activity and cardiorespiratory fitness may also have changed in Finnish adolescents since 2001 to 2002. Therefore, it would be useful to investigate physical activity and cardiorespiratory fitness in association with adolescent self-rated health in more contemporary cohorts and versatile sociocultural settings. A deeper understanding of the causal directions of these associations, the mechanisms behind them, as well as the interactions between physical activity, cardiorespiratory fitness, and self-rated health requires knowledge of both the direct and indirect influences of physical activity and cardiorespiratory fitness on adolescents’ self-rated health. A key to understanding these relations in the future will be the examination of how physical activity, cardiorespiratory fitness, and self-rated health change with respect to each other over time, or as the result of an intervention.
Conclusions High levels of physical activity and high levels of cardiorespiratory fitness were associated with good self-rated health in adolescents. Public health promotion activities to foster physical activity and cardiorespiratory fitness may benefit young people by improving their overall health and well-being. Acknowledgments Marko T. Kantomaa is supported by a grant (76/627/2011) from the Ministry of Education and Culture, Finland. Emmanuel Stamatakis is funded by the National Institute for Health Research UK through a Career Development Fellowship. The Northern Finland Birth Cohort 1986 is supported by grants from the Academy of Finland, European Union, National Institutes of Health, Wellcome Trust, Nordic Academy for Advanced Study, and Ministry of Education and Culture, Finland.
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