Differential associations of physical activity and exercise to physical fitness

doi:10.21203/rs.3.rs-4874512/v1

Physical activity (PA) and exercise behavior are important strategies and assessment indicators for health promotion. However, past studies have measured PA and exercise differently, leading to inconsistent and difficult-to-compare results regarding their association with health. To elucidate the relationship between the Global Physical Activity Questionnaire (GPAQ) and self-reported exercise behavior and their association with health outcomes, this study aims to determine which approach reflects more health benefits.

This study used the 2020 Changhua Community-Based Integrated Screening database and included individuals aged 40–64 who participated in both physical fitness tests and GPAQ surveys. A total of 1,631 individuals were included as analysis samples. Exercise behaviors are classified into never, irregular and regular based on the lifestyle records in the screening database. Furthermore, metabolic equivalents were computed using the GPAQ questionnaire, and PA was classified into two groups using a cut-off point of 600. Logistic regression was performed using SAS version 9.4.

Our findings revealed that individuals who did not engage in exercise demonstrated lower flexibility, while those who exercised regularly but had low PA-METs showed poor muscular endurance. Additionally, individuals who did not exercise and had low PA-METs exhibited poor cardiorespiratory endurance.

Our study revealed diverse connections between PA, exercise, and physical fitness. When promoting PA, it is suggested to exclude work-related PA and prioritize purposeful PA with adequate intensity, duration, and regularity to maximize the benefits for physical fitness.

Global Physical Activity Questionnaire

Self-reported exercise behavior

Physical fitness

Being physically active is becoming increasingly essential in this era. People of all ages can take measures to improve health to feel, function, and sleep better and prevent many chronic diseases (US Department of Health & Services, 2018). Regular physical activity (PA) also helps prevent and manage non-communicable diseases (WHO, 2018). Recently, the Global Physical Activity Questionnaire (GPAQ) is used to assess PA, which was developed by the World Health Organization (WHO). The instrument included domains such as occupation, transport, and leisure time (Armstrong & Bull, 2006). Exercise is a subcategory of PA whose objective is to increase physical fitness. Based on the notion that exercise possesses more positive characteristics than PA, many health promotion events recommend the term exercise more than physical activity (Dugdill, Graham, & McNair, 2005; Pascoe et al., 2021; Rodrigues & Macedo, 2021). The majority of surveys in Taiwan, including the National Health Survey conducted by the Health Promotion Administration, Ministry of Health and Welfare, and the Exercise City Survey conducted by the Sports Administration, Ministry of Education, use exercise in their questionnaires and publish official statistics (Sports Administration, 2023).

GPAQ is widely used to investigate PA and sedentary behavior. However, a few studies point out that a few discrepancies remain between the GPAQ and objective measures (Jakicic et al., 2015).

The Self-Report Exercise Behavior is another questionnaire on the focus of people on planned, structured, and repetitive exercise as leisure. PA and exercise behavior have become important strategies and assessment indicators of health promotion. The definitions of physical and exercise are different. In addition, the emphasis between the two is different, such that determining which approach reflects more health benefits is necessary.

This study aimed to elucidate the relationship between GPAQ and self-reported exercise behavior and their association with health fitness

Participants

Changhua Community-Based Integrated Screening (CHCIS), which is provided by the Changhua Health Bureau, has been offering health screening for a wide range of diseases for people aged > 30 years since 2005. Screening is conducted in two stages. The first stage consists of screening for four types of cancer (i.e., breast, colorectal, oral, and cervical), adult health screening items (chronic diseases, biochemical tests, and anthropometric measurements (Yeh et al., 2014), and a self-report questionnaire, which is a structured questionnaire and is used to understand the health-related lifestyles of participants (e.g., exercise, smoking, alcohol consumption, chewing betel nut, and dietary intake) and personal and family histories of the disease. In stage 2, an examination report was provided two weeks after the end of stage 1, and the interested parties were recruited for a physical fitness test and a survey using the GPAQ. Data were derived from the database of the CHCIS for 2020, which comprises 12,168 respondents. A total of 2,135 and 1,879 respondents participated in the physical fitness test and completed the GPAQ, respectively. 1,631 were participation in both stages and ages between 40–64 years. Each participant was provided with a declaration of consent before the questionnaire and data analysis were conducted. The study proceeded only after obtaining the participant's consent. Additionally, points 7 and 9 of the declaration address the use and publication of the data.

Definition of variables

Outcome variable: Physical fitness

Physical fitness is measured at the second stage of the screening process, and participation is voluntary. Trained testers conducted physical fitness testing, which included (1) the sit and reach test to measure flexibility, (2) a one-minute sit-up test and a grip strength test to measure muscular fitness; and (3) three-minute step test to test for cardiorespiratory endurance. After each component, the testers rated the results using a five-point scale (very poor, poor, fair, good, and excellent). The test results are divided into two groups: very poor and poor are regarded as "bad", and the rest of fair, good, and excellent are combined as "good".

Independent variable: self-report exercise and physical activity

1. Self-Report Exercise Behavior

Exercise behavior is self-reported, and the question was “Do you exercise currently?” followed by “On average, how many times per week do you exercise?” and “How long do you exercise?” The duration of exercise was calculated by multiplying the frequency of exercise per week by the length of exercise (in minutes). Accordingly, we classify exercise behaviors into three categories, namely, regular, irregular, and never. The regular exercise group was defined as participants who exercised more than three times per week and for more than 30 min each time. Those who reported that they exercised less than three times per week or less than 30 min per time were classified under the irregular exercise group. Lastly, those without exercise were categorized under the no-exercise group.

2. Physical Activity

PA was measured using the GPAQ of the WHO, which includes three domains, namely, activity at work (six items), travel to and from places (three items), and recreational activities (six items). Metabolic equivalents (METs) were calculated using the following formula: total PA MET-minutes/week (= sum of the total MET minutes of activity computed for each setting).

The WHO recommendations on PA for health are an equivalent combination of moderate- and vigorous-intensity PA that achieves approximately 600 MET-minutes. According to this principle, the level of PA is divided into two groups, ≧600 and < 600 METs.

Covariates

Sociodemographic variables: The sociodemographic covariates were age (40–50/50–64 years), education (junior high school or below, high school, or college and above), and area of residence (city, town, or village).
Personal history of three highs (hyperglycemia, hypertension, and hyperlipidemia) according to a self-reported response of yes or no.

Statistical analyses

Using logistic regression, the study constructed multivariate models using each model of activity as the predictor variable and each physical fitness as the dependent variable. The models were adjusted for possible confounders such as age, gender, and self-reported disease history. Model 1 was based on exercise behavior, and the reference group was regular exercisers; Model 2 was based on PA-METs, and the reference group with METs ≧ 600; lastly, Model 3 denoted the interaction between self-reported exercise behavior and PA, and the reference group was regular exercisers with METs ≧ 600. The odds ratio (OR) and 95% confidence intervals were obtained from the estimated regression coefficients of the model. All statistical tests were performed in SAS (version 9.4), and p < 0.05 was considered statistically significant.

Ethical review board

This experimental protocol was conducted with the approval of the Ethics Review Board of Chung Shan Medical University Hospital (approval number: CS2-20055).

Table 1 presents the distribution of sociodemographic and PA-related variables among the 1,631 participants. In terms of sociodemographic variables, male participants accounted for 61.6% of the sample, 68.4% were aged between 50 and 64 years, 39.1% obtained a high school education and 66.5% lived in village areas. In terms of self-reported exercise behavior, 39.3%, 29.6%, and 39.3% of the participants mentioned that they never exercised, exercised irregularly, and exercised regularly, respectively. In terms of PA as measured by METs, the percentage of physical inactivity (< 600 METs) was 55.5%. In terms of body composition, 56.2% of the participants were overweight or obese. For physical fitness-related variables, 55.7%, 27.4%, and 41.6% exhibited poor flexibility, poor muscular endurance, and poor cardiorespiratory endurance, respectively.

Table 1. Characteristics of the participants (n = 1,631)
Variable	n	%	Variable	n	%
Sociodemographic variables			Physical activity (PA)
Gender			Self-reported exercise behavior
Male	1004	61.56	Never	641	39.30
Female	627	38.44	Irregular	483	29.61
Age (years)			Regular	507	31.09
40–50	520	31.88	Metabolic equivalents (METs)
50–64	1111	68.12	<600	905	55.49
Level of education			≧600	726	44.51
Junior high school or below	535	32.80	Body composition
Senior high school	638	39.12	BMI overweight/obesity	916	56.16
College or above	458	28.08	Physical fitness
Area of residence			Bad flexibility	908	55.67
City	222	13.61	Bad muscular fitness	447	27.41
Town	324	19.87	Bad cardiorespiratory endurance	678	41.57
Village	1085	66.52

1. Relationship between self-reported exercise behavior and PA as measured by the GPAQ

In contrast to the GPAQ, in which self-reported exercise behavior is based on the self-reported exercise frequency and length (one question) of the participants, the GPAQ includes PA at work, during transport, and during leisure time (a total of 15 questions). Self-reported exercise behavior reflects the exercise behavior of an individual, while GPAQ measures PA-METs through intensity and frequency. The first objective of this study is to depict the correlation between self-reported exercise behavior and PA-METs as measured by the GPAQ.

Table 2 indicates that the overall METs varied according to the frequency of self-reported exercise behavior: METs were significantly lower for individuals without exercise than those who exercised irregularly, and METs was also significantly lower for those who exercised irregularly than in those who exercised regularly. When the three dimensions of METs were analyzed with self-reported exercise behavior, the study found that transport and leisure METs were associated with exercise behavior in the same manner as the overall METs. However, work METs displayed the opposite association: work METs were higher for individuals without exercise than for those who exercised irregularly and significantly higher for those who exercised irregularly than for those who exercised regularly. According to the recommendation of the WHO, PA is classified into two categories based on total METs: insufficient (METs < 600) and sufficient (METs ≥ 600). The results of the stratified analysis (Table 2) demonstrated that the association with exercise behavior was the same as the overall result, regardless of whether or not PA was adequate.

The GPAQ measures PA by asking respondents how long they engage in vigorous or moderate PA at work or leisure. Therefore, the GPAQ can be used to classify the intensity of PA into four categories: vigorous and moderate; vigorous only; moderate only; and neither vigorous nor moderate. Table 3 presents the results of the examination of the association between self-reported exercise behavior and PA intensity (measured using the GPAQ) at work and at leisure, respectively. For those whose work was physically vigorous, the percentages of regular exercise were only 14.81% (vigorous, moderate) and 12.00% (vigorous) regardless of whether or not it included moderate PA. In contrast, 30.58% and 28.65% of those working at moderate PA reported irregular and regular exercise, respectively. In terms of PA intensity during leisure time, approximately 10% of individuals with vigorous or moderate PA reported that they never exercised (12.35% - vigorous, moderate, 5.56% - vigorous, and 9.16% - moderate respectively). Alternatively, 21.82% and 11.20% of individuals with neither vigorous nor moderate leisure PA reported irregular or regular exercise behavior respectively.

Table 2. Correlation between exercise behavior and physical activity metabolic equivalents (n = 1,631)
Metabolic equivalents (METs)	Total		Self-reported exercise behavior
	Total		Never n = 641 (39.30%)		Irregular n = 483 (29.61%)		Regular n = 507 (31.09%)		Kruskal–Wallis test
	Mean	SD	Mean	SD	Mean	SD	Mean	SD	p	post hoc test
Total (n = 1,631)	1421	2934.8	1249.4	3453.3	1350.5	2784.5	1705.2	2270.4	<.0001	N < IR < R
Work	889	2797.5	1162.8	3444.3	846.4	2567.1	583.5	1933.4	<.0001	N > IR > R
Travel to and from places	62.2	306.6	22.4	133.5	56.9	239.9	117.5	469.3	<.0001	N < IR < R
Recreational activities	469.8	839.7	64.1	282.2	447.2	746.2	1004.3	1070	<.0001	N < IR < R

MET < 600 (n = 905; 55.49%)			n = 489		n = 275		n = 141
Total	117.7	173.2	68.4	136.9	162.1	182.8	202	208.3	<.0001	N < IR,R
Work	26.6	87	35.8	102.7	20.2	66.7	7	52.2	<.0002	N > IR,R; IR > R
Travel to and from places	15.4	64.8	15	67.7	14.5	59.1	18.4	65.3	0.2497
Recreational activities	75.7	149	17.6	68.6	127.3	173.6	176.6	201.7	<.0001	N < IR, R

MET≧600 (n = 726; 44.51%)			n = 152		n = 208		n = 366
Total	3045.7	3816.3	5048.6	5606.9	2921.6	3695	2284.4	2433.1	<.0001	N > IR, R
Work	1964.1	3937	4788.4	5736	1938.8	3637.8	805.6	2236.8	<.0001	N > IR > R
Travel to and from places	120.5	447.1	46.3	244.9	112.8	352	155.7	546.3	0.0002	N < IR, R
Recreational activities	961.1	1059.2	213.8	541.2	870.1	970.1	1323.1	1097.7	<.0001	N < IR < R

Table 3. Distribution of exercise behavior and METs (n = 1,631)
Variables	n	%	Self-reported exercise behavior
			Never		Irregular		Regular		χ²	p
			n	%	n	%	n	%	χ²	p
Participant	1631		641	39.30	483	29.61	507	31.09
Work
Vigorous, moderate intensity	54	3.31	29	53.70	17	31.48	8	14.81	26.1365	0.0002
Vigorous, no moderate intensity	50	3.07	32	64.00	12	24.00	6	12.00
No vigorous, moderate intensity	363	22.26	148	40.77	111	30.58	104	28.65
No vigorous, no moderate intensity	1164	71.37	432	37.11	343	29.47	389	33.42

Recreational activities
Vigorous, moderate intensity	81	4.97	10	12.35	32	39.51	39	48.15	606.4168	<.0001
Vigorous, no moderate intensity	36	2.21	2	5.56	15	41.67	19	52.78
No vigorous, moderate intensity	666	40.83	61	9.16	251	37.69	354	53.15
No vigorous, no moderate intensity	848	51.99	568	66.98	185	21.82	95	11.20

Recreational activities				Colon%		Colon%		Colon%
Vigorous and moderate intensity	81	4.97	10	1.56	32	6.63	39	7.69	606.4168	<.0001
Vigorous intensity only	36	2.21	2	0.31	15	3.11	19	3.75
Moderate intensity only	666	40.83	61	9.52	251	51.97	354	69.82
No vigorous, no moderate intensity	848	51.99	568	88.61	185	38.30	95	18.74

Table 4. Multivariate analysis of physical fitness, exercise behavior, and METs (n = 1,631)
Variables		Body composition			Physical fitness
		BMI Overweight/obese			Bad flexibility			Bad muscular fitness			Bad cardiorespiratory endurance
		n = 916			n = 908			n = 447			n = 678
		OR	95 CI%		OR	95 CI%		OR	95 CI%		OR	95 CI%
Model 1: Exercise behavior (ref = regular exercise)
No exercise	n = 641	1.20	0.93	1.54	1.54	1.21	1.97	0.83	0.63	1.09	1.34	1.05	1.72
Irregular exercise	n = 483	1.05	0.80	1.37	1.23	0.95	1.59	0.71	0.53	0.95	1.13	0.86	1.47

Model 2: METs (ref = METs ≧ 600)
MET < 600	n = 905	1.20	0.97	1.48	1.13	0.93	1.39	1.04	0.83	1.30	1.37	1.11	1.68

Model 3: Exercise behavior ⁎ physical activity (ref = regular exercise and METs ≧ 600, n = 366)
No exercise, METs < 600	n = 489	1.28	0.95	1.71	1.50	1.13	1.99	0.98	0.72	1.35	1.58	1.18	2.11
Irregular exercise, METs < 600	n = 275	1.25	0.89	1.76	1.22	0.88	1.68	0.73	0.50	1.07	1.18	0.84	1.65
Regular exercise, METs < 600	n = 141	1.30	0.86	1.97	0.90	0.61	1.33	1.63	1.08	2.48	1.07	0.71	1.60
No exercise, METs ≧ 600	n = 152	1.34	0.89	2.03	1.50	1.01	2.23	0.88	0.56	1.38	0.84	0.55	1.26
Irregular exercise, METs ≧ 600	n = 208	0.99	0.69	1.42	1.16	0.82	1.65	0.95	0.64	1.42	1.11	0.78	1.59
All models were adjusted for gender, age, level of education, area of residence, and disease history (hyperglycemia, hypertension, and hyperlipidemia).

2. Associations among self-reported exercise behavior, PA measured by the GPAQ, and physical fitness

After adjusting for personal sociodemographic variables and disease history, the study conducted multivariate logistic regression analysis with self-reported exercise behavior and physical inactivity as the independent variables and physical fitness indicators as the dependent variables. Table 4 presents the results. Model 1 was based on the analysis of self-reported exercise behavior as the dependent variable only. Compared with individuals who exercised regularly, those who reported no exercise displayed higher rates of poor flexibility and cardiorespiratory endurance (OR: 1.54 and 1.34 times, respectively). Model 2, which uses physical inactivity as the independent variable, illustrated that physical inactivity was 1.37 times more likely than PA to lead to poor cardiorespiratory endurance (95% confidence interval (CI): 1.11–1.68). Model 3 combines self-reported exercise behavior and physical inactivity into a six-category composite with regular exerciser and physically active as the reference group. The results are as follows. (1) Those who reported not exercising and being physically inactive were significantly more likely to exhibit poor flexibility and cardiorespiratory endurance (OR: 1.50 and 1.58, respectively). (2) Those who exercised regularly but were physically inactive obtained significantly poor muscular endurance (OR: 1.63). (3) Those who reported not exercising but being physically active were significantly more likely to be less flexible (OR: 1.50).

Main findings

This study found that PA, whether measured as METs of PA or exercise behavior, was significantly correlated with physical fitness. Specifically, both are positively correlated with cardiorespiratory endurance performance, while exercise behavior are additionally positively correlated with flexibility and muscular fitness. However, neither is related to body composition. Furthermore, PA-METs and exercise behavior exert an interacting effect on physical fitness. In addition, this study found that work-related PA may exert a negative effect on physical fitness.

1. PA-METs and exercise behavior with health-related physical fitness

This study measured PA using METs and exercise behavior and investigated the relationship between PA and physical fitness. Individuals with sufficient PA-METs displayed significantly better cardiorespiratory endurance performance than those with inadequate METs. In terms of exercise behavior, the flexibility and cardiorespiratory endurance of regular exercisers are better than those without exercise. Therefore, PA-METs and exercise behavior clearly positively influenced cardiorespiratory endurance. This result is consistent with those of many studies (e.g., Anton, Duncan, Limacher, Martin, & Perri, 2011; Franklin, Eijsvogels, Pandey, Quindry, & Toth, 2022; Myers, Kokkinos, Arena, & LaMonte, 2021). The mechanisms of the effects of exercise and PA on cardiovascular health include changes that improve maximum output per beat, which, in turn, provides greater oxygen delivery and enhances vasodilatation (Hellsten & Nyberg, 2011). In terms of flexibility, the study found that it was related to exercise behavior but not to the PA-METs. Flexibility is a comprehensive expression of joints and muscle groups; thus, it can be improved through body movement and muscle extension.

1. Regular exercisers may display a more significant positive effect on flexibility due to the higher frequency of body movements over a larger range of motion (Cornelius, 1990).

In addition, this study combined different categories of exercise behavior and PA-METs to examine the interaction effects of exercise behavior and PA-METs on physical fitness. We found that (1) regular exercise is beneficial to cardiorespiratory endurance even if the PA-METs is insufficient; (2) even with regular exercise if the PA-METs are insufficient, the muscular fitness is significantly worse than that of those who with a sufficient amount; (3) those without exercise exhibited significantly poor flexibility regardless of whether or not their PA-METs are sufficient; (4) BMI is not correlated with exercise behavior and PA-METs.

2. Regular exercise is beneficial to cardiorespiratory endurance even if the PA-METs are insufficient.

The study found that for individuals with insufficient PA-METs, those without exercised displayed the worst cardiorespiratory endurance; however, their cardiorespiratory endurance performance did not differ significantly from the reference group as long as they observed exercise behavior (whether or not such behavior are regular). A possible reason for this result is that people with insufficient PA-METs tend to have a sedentary lifestyle (Ekelund et al., 2016), as the WHO (2023) recognizes physical inactivity as an important risk factor of non-communicable diseases. Therefore, as long as people engage in exercise, it is beneficial for cardiorespiratory fitness (Piercy et al., 2018).

3. Even with regular exercise, if the PA-METs are insufficient, then muscular fitness is significantly worse than those with sufficient PA-METs.

In terms of muscular fitness, PA intensity is more important. Muscular strength training is based on the does–response effect. In other words, the number of neurons activated at the site of movement to produce the number of contracted muscle fibers determines muscle strength. Therefore, the intensity of weight training becomes a necessary condition for resistance training: by loading the muscle groups with high-intensity exercise, more motor neurons are activated, and the corresponding stimulated muscle fibers are activated. Clearly, PA intensity is the key factor in the production of muscle strength, and if it does not reach the threshold of response, then muscular strength will not improve (Faigenbaum et al., 1999). For this reason, the results of the current study demonstrated that muscular fitness among individuals with insufficient PA-METs is significantly worse than those with sufficient PA-METs even with regular exercise.

Those without exercise displayed significantly poor flexibility regardless of whether or not their PA-METs are sufficient.

The results illustrated that individuals with sufficient PA-METs but without exercise exhibited poor flexibility, which is similar to the result of Lin et al. (2022). The possible reasons for this result are that people who are physically active but do not exercise are likely to be manual laborers, who frequently undergo brief periods of repetitive resistance PA. As such, they are vulnerable to fatigue, stiffness, and pain, which may affect flexibility (Balaguier et al., 2017), or to the lack of sufficient rest and recovery time (Fleck, 1999).

PA-METs and exercise behavior were not significantly correlated with BMI.

The study found no significant correlation among exercise behaviors, PA-METs, and BMI, regardless of whether or not the independent or combined variables were considered. This finding suggests that PA alone may be ineffective for long-term weight control and that it should be combined with dietary and lifestyle modification. (Annesi & Eberly, 2022). In fact, including psychological factors in weight management strategies may be beneficial (Lambert et al., 2019).

Comparison of the GPAQ and a single question to measure exercise behaviors

GPAQ is a tool that measures PM by and considers work, transportation, and leisure. It has good reliability and validity (Adiguzel et al., 2021; Doyle et al., 2019; Rudolf et al., 2020) and is applicable to different ethnic groups. Along with gender, age group, and occupational type (Adiguzel et al., 2021), data can be collected through a self-report or interview (Rudolf et al., 2020). The GPAQ seemingly implies the assumption that “the benefits (positive or negative) of PA during work, transportation and leisure time are the same.” However, exercise has a psychologically active and positive meaning due to its planned, structured, and repetitive nature (Caspersen et al., 1985), which makes it different from ordinary physical activities (e.g., PA-METs as measured by the GPAQ). On the basis of the findings, the study identifies three distinctions between PA-METs measured by the GPAQ and exercise behaviors measured by the single question as follows.

First, using the GPAQ as a measurement instrument for PA will simultaneously underestimate the health benefits of exercise and overestimate the benefits of PA at work, especially for high-intensity laborers (Holtermann, Schnohr, Nordestgaard, & Marott, 2021). Therefore, when using the GPAQ to evaluate PA-METs, consideration should be given to whether or not the proportion of PA at work is excessive.

Second, when PA-METs use the total METs of PA as the index, it does not adequately reflect the concept that “PA should have the appropriate frequency, intensity, and duration to be health-beneficial.” For example, weekend warriors (Lee, Sesso, Oguma, & Paffenbarger Jr, 2004) are busy during the week and do not maintain a regular exercise routine. Therefore, they can only demonstrate that they spend time diligently for their health by exercising for longer durations on holidays. Nonetheless, excessively concentrated exercise time and intensity can easily result in acute sports injuries, which is unhealthy (Delimaris, 2014). Therefore, although the PA-METs measured by the GPAQ are a simplified PA index, cautious discussions should be held regarding the obtained results (Keating et al., 2019).

Finally, the “single question to measure exercise behavior” only asks about the presence and regularity of exercise behavior. Although it focuses on exercise and saves time in answering, it ignores non-exercise physical activities and exercise intensity. Furthermore, as revealed by the finding, even regular exercise produces very limited health benefits if it lacks sufficient intensity.

In summary, although the choice of the multiple-question GPAQ or the single question for measuring exercise behavior can be determined according to the objective of the study and the needs of research implementation, scholars should focus on integrating the advantages of the two aspects as the measurement of PA in the future to better understand the relationship between PA and health.

Although PA is known to be beneficial to healthy fitness, it is still influenced by PA type, metabolic equivalent, and exercise behavior. In the three dimensions of the GPAQ, leisure-time PA provided more health benefits than did work PA and is related to the cumulative amount of PA (300 METs) per week. Nevertheless, even individuals who are sufficiently physically active are still advised to exercise regularly. Finally, the use of the single question to measure exercise behavior posed two advantages, namely, filling out takes less time and using more correlates of physical fitness factors than the GPAQ on PA.

Acknowledgments
The authors acknowledge the contributions and support of the Changhua Health Bureau.

Funding source

This work was supported by the Ministry of Science and Technology, Taiwan (MOST 109-2410-H-040-001)

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No competing interests reported.

Differential associations of physical activity and exercise to physical fitness

Status:

Version 1

Abstract

Figures

Introduction

Methods

Participants

Definition of variables

Outcome variable: Physical fitness

Independent variable: self-report exercise and physical activity

Covariates

Statistical analyses

Ethical review board

Results

Discussion

Conclusion

Declarations

References

Additional Declarations

Status:

Version 1