Skip to main content
  • Research article
  • Open access
  • Published:

Associations of sleep duration with physical fitness performance and self-perception of health: a cross-sectional study of Taiwanese adults aged 23–45

Abstract

Background

The relationship between sleep duration and physical fitness is one aspect of sleep health. Potential factors associated with sleep duration interfere with physical fitness performance, but the impact trends on physical fitness indicators remain unclear.

Methods

This study examined associations between sleep duration and physical fitness among young to middle-aged adults in Taiwan. A total of 42,781 Taiwanese adults aged 23–45 participated in the National Physical Fitness Examination Survey 2013 (NPFES-2013) in Taiwan between October 2013 and March 2014. A standardized structural questionnaire was used to record participants’ sleep duration, which was stratified as short (< 6 h/day (h/d)), moderate (6–7 h/d; 7–8 h/d; 8-9 h), and long (≥ 9 h/d) sleep duration groups. Physical fitness was assessed based on four components: body composition (body mass index [BMI], waist-to-height ratio [WHtR], and waist-to-hip ratio [WHR]), muscle strength and endurance (1-min bent-leg sit-up test [BS]), flexibility (sit-and-reach test [SR]), and cardiorespiratory endurance index (3-min step test [CEI]).

Results

By using analysis of covariance (ANCOVA), after sex grouping and age adjustment, we observed that sleep duration was significantly associated with obesity, functional fitness, and self-perception of health. The sleep duration for low obesity-related values (BMI, WHtR, and WHR) for men was 7–9 h/d, and that for women was 7–8 h/d. Sleeping more than 8 h/d showed poor functional fitness performances (BS and SR). For both sexes, sleep duration of 8–9 h/d was the optimal sleep duration for self-perceptions of health.

Conclusions

Our research found that there were wide and different associations of sleep duration with physical fitness and self-perception of health among Taiwanese adults aged 23–45, and there were differences in these associated manifestations between men and women. This study could be of great importance in regional public health management in Taiwan, and provide inspirations for clinical research on physical fitness.

Peer Review reports

Background

In recent years, many studies have suggested associations between sleep duration and health status. Research on sleep and health has focused on many aspects, such as chronic disease, obesity, self-perception of health, etc. However, there were different opinions on the appropriate sleep duration. Several studies showed that, for adults aged 18–60, sleeping less than 7 h/day (h/d) was associated with increased risk for obesity, diabetes, hypertension, coronary heart disease, stroke, mental distress, and all-cause mortality [1,2,3]. Alvarez and Ayas [4] found that individuals who reported increased (> 8 h/d) and decreased (< 7 h/d) sleep durations had moderately increased risks of all-cause mortality, cardiovascular disease, and symptomatic diabetes. Gottlieb et al. [5, 6] revealed that sleep durations of ≤6 h/d and ≥ 9 h/d were associated with an increased prevalence of hypertension, diabetes and impaired glucose tolerance. Garaulet et al. [7] found that the optimal sleep duration was 8 h/d, and people with shorter sleep duration showed higher obesity risk, particularly in women. Cappuccio et al. [8] showed that the obesity risk consistently increased in adults who slept less than 5 h/d. Hsu et al. [9] found that 7 h/d of sleep duration was the recommended duration for good physical fitness performance. Steptoe et al. [10] found that self-rated health was poorer in respondents who slept < 7 h/d or > 8 h/d than in those who slept 7–8 h/d. Magee et al. [11] observed that short (< 6 h/d) and long (≥ 9 h/d) sleep durations were significantly associated with poor self-rated health and low quality of life. However, Watson et al. [12] explained that little empirical evidence existed to indicate that long sleep duration (≥ 9 h/d) causes adverse conditions among healthy adults exists. These results emphasized the importance of adequate sleep for physical and mental health.

Physical fitness, which can be more objectively measured than physical activity, is a powerful indicator of health status. Physical fitness included body composition and functional fitness, among which, functional fitness of coordination, endurance, power fitness, and cardiovascular systems were prioritized [13,14,15,16,17]. Crucial physical fitness indicators for adults include body mass index (BMI), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), 1-min bent-leg sit-up test (BS), sit-and-reach test (SR), and 3-min step test which reflects the cardiorespiratory endurance index (CEI). BMI, WHtR, and WHR indicate the probability of being overall obesity or central obesity; BS indicates lumbar and muscle endurance; SR indicates hamstring flexibility and tension of the movable range of the lower back joint or the toughness of the ligament; and CEI indicates cardiorespiratory endurance.

However, the link between physical fitness and sleep duration is still poorly understood, and there were few studies related to Taiwanese adults. In the current study, we discussed the distribution of short, moderate, and long sleep duration among young adults in Taiwan, and explored how long sleep duration was the optimal sleep duration for physical fitness and self-perception of health.

Methods

Data source

We reviewed the data from 42,781 Taiwanese adults aged between 23 and 45 years who participated in the National Physical Fitness Examination Survey 2013 (NPFES-2013) in Taiwan between October 2013 and March 2014. The National Physical Fitness Examination Survey (NPFES) was implemented by the Sports Administration, Ministry of Education (MOE-SA) in Taiwan, and the purpose was to investigate the annual physical fitness status of Taiwan residents. Participants in NPFES-2013 were recruited using convenience sampling at 46 test stations in 22 cities and counties in Taiwan. The research protocol comprised three phases: participating in a standardized interview, pretest health screening, and physical fitness tests. These data were recorded using a standardized structural questionnaire, which included items related to demographic characteristics, sleep behaviors, self-perceptions of health, anthropometric characteristics and physical fitness measurements. All tests and records were conducted by well-trained examiners, and informed consent was obtained from each participant after a full explanation of the survey. The data obtained comprised de-identified secondary data, which were released to the public for research purposes [18]. This study was approved by the Institutional Review Board of Fu Jen Catholic University (FJU-IRB C108006).

Anthropometric measurements

Anthropometric indicators included body weight, height, waist circumference (WC), and hip circumference (HC). Body weight and height were recorded to the nearest 0.1 kg and 0.1 cm with an electronic height-weight scale; WC was measured to the nearest 0.1 cm with a flexible steel tape measure placed midway between the lowest rib and iliac crest; and HC was measured to the nearest 0.1 cm at the widest part of the hip region. The above measurements required the participants to take off their shoes and thick clothes before measurements, and to be measured at the end of the exhalation in the standing position.

Physical fitness measurements

The following four physical fitness measurements were taken according to the governmental guideline of the MOE-SA in Taiwan [18]: body composition (body mass index [BMI], waist-to-height ratio [WHtR], and waist-to-hip ratio [WHR]), muscle strength and endurance (1-min bent-leg sit-up test [BS]), flexibility (sit-and-reach test [SR]) and cardiorespiratory endurance (3-min step test [CEI]).

Body composition

Body composition was assessed by BMI, WHtR, and WHR, where: BMI = body weight (kg)/height squared (m2), WHtR = WC (cm)/height (cm), and WHR = WC (cm)/HC (cm). The procedures and instruments for the anthropometric measures (i.e., body weight, height, WC and HC) have been previously described.

Muscle strength and endurance

Abdominal muscular strength and endurance were measured using a timed bent-leg sit-up test (BS). Participants laid down on a mat with knees bent at right angles and hands behind the head; the ankles were firmly held by a partner. The BS test result was measured as the repetitions within 1 min.

Flexibility

Flexibility was measured using a sit-and-reach test (SR), which was considered a useful field test to evaluate hamstring and low-back flexibility. Participants took off their shoes before the test and sat on an SR box with a measuring scale. The examiner instructed participants to bend body slowly and recorded the maximum distance reached by their fingertips in cm.

Cardiorespiratory endurance

Cardiorespiratory endurance index (CEI) was used as an evaluation indicator of cardiorespiratory fitness performance. In this test, it was measured using an adapted 3-min step test from the Harvard Step Test. Participants were assisted by the examiner and a metronome cadence for repeatedly stepping on and off a 35-cm step for 3 min. After stepping, the participants were immediately seated, and CEI was calculated using the post exercise recovery heartbeat counts in intervals of 1 to 1.5 min, 2 to 2.5 min, and 3 to 3.5 min. CEI was calculated by the formula: CEI = duration of step test (s) × 100/sum of heartbeat counts during the recovery period/2.

Sleep duration assessment

A standardized structural questionnaire was used to record participants’ self-reported daily average sleep duration. We selected nodes with < 6 h/day (h/d) and ≥ 9 h/d to divide the short and long sleep duration categories. For the sleep duration of middle interval, we took into account the definition differences in the literature [1,2,3,4,5,6,7,8,9,10,11,12], and divided it into the moderate sleep duration interval I (Moderate-I) when the sleep duration was greater than or equal to 6 h/d and less than 7 h/d; divided it into the moderate sleep duration interval II (Moderate-II) when it was greater than or equal to 7 h/d and less than 8 h/d; divided it into the moderate sleep duration interval III (Moderate-III) when it was greater than or equal to 8 h/d and less than 9 h/d.

Self-perception of health

The standardized structural questionnaire was also used to record participants’ self-perceptions of health status. The assessments included three questions, asking about self-rated health, subjective happiness, and life satisfaction. According to the feeling of self-health from bad to good, each question was filled in 1 point for feeling very bad, 2 points for feeling bad, 3 points for feeling normal, 4 points for feeling good, and 5 points for feeling very good. The self-reported health assessments of NPFES-2013 used the same 5 classification answers as in references [19,20,21,22].

Statistical analyses

All research data were processed using R software of version 3.6.3 (R core team, Vienna, Austria). T-test analysis was performed to analyze sex interference. For physical fitness performances and self-perceptions of health, age-adjusted analysis of covariance (ANCOVA) was used for determining the differences between short, moderate, and long sleep duration groups. Due to the sample imbalance for the groups, the Scheffe test was used for post-hoc tests [23]. Values were presented as means and standard deviations, or frequency percentages. Statistical results were significant at p <  0.05.

Results

After processing missing values and outliers for the self-reported variables (sleep duration, self-rated health, subjective happiness, and life satisfaction) of the applied data, 40,944 valid sample individuals were obtained. Table 1 showed the results of T-test analysis of the study subjects grouped by sex. All variables showed significant differences between sex groups, in which the performances of 1-min bent-leg sit-up (BS) and cardiorespiratory endurance index (CEI) of males were better than those of females, while the performance of sit-and-reach (SR) of females was better than that of males. Regarding the self-perceptions of health, men’s self-rated health feelings were better than women’s, while women’s subjective happiness and life satisfaction were better than men’s.

Table 1 T-test analysis grouped by sex

Table 2 presented the results of age-adjusted ANCOVA by sex. For males, the post-hoc test results showed that, compared with those who slept 7–9 h/day (h/d), the group with less than 7 h/d of sleep had higher body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and waist-to-hip ratio (WHR) values, which meant that less than 7 h/d of sleep might be associated with higher performances of obesity indicators. Regarding the functional fitness performances (BS, SR, and CEI), the group with more than 8 h/d of sleep showed poorer performances than that with less than 8 h/d of sleep. For self-perceptions of health, the moderate sleep duration of 8–9 h/d was the optimal sleep duration for presenting the best self-rated health, subjective happiness, and life satisfaction.

Table 2 Age-adjusted ANCOVA grouped by sex

For females, Table 2 showed that the group with less than 6 h/d of sleep had a higher BMI, while the sleep duration of 7–8 h/d was shown as the optimal sleep duration for central obesity indicators (WC, WHtR, WHR) and BS. Similar to men, women who slept for less than 8 h/d performed better in terms of SR. 8–9 h/d of sleep was also the optimal sleep duration for women to show the best self-rated health, subjective happiness and life satisfaction feelings. However, women’s CEI performance was not related to sleep duration.

Discussion

Numerous studies have demonstrated the health benefits of sufficient sleep, but few studies have examined the relationship between sleep duration and physical fitness indicators. The purpose of this research was to determine the associations of sleep duration with physical fitness performances and self-perceptions of health in Taiwanese adults aged 23–45. This young and middle-aged labor force group in Taiwan generally had the characteristics of regular sleep and mild sleep deprivation. We selected a more detailed sleep duration grouping based on literature comparison, and used ANCOVA method to perform an age-adjusted analysis under sex division. Since the body compositions and functional fitness performances between male and female groups showed universal differences, it was necessary to divide the applied data by sex grouping. The results revealed that sleep duration was significantly associated with obesity, functional fitness, and self-perception of health.

The results showed that men who sleep less than 7 h/day (h/d) might face higher values of overall obesity and central obesity indicators, while women who sleep less than 6 h/d might face a higher value of overall obesity indicator. 7–8 h/d of sleep was the optimal sleep duration for women to stay away from central obesity. From the results, we cannot completely determine that there was no association of more than 9 h/d of sleep with men’s overall obesity and central obesity, because the self-reported sleep durations of more than 9 h/d were very few in the study sample. As mentioned, there was a general lack of sleep in Taiwanese adults aged 23–45, such sample imbalance might affect the statistical results of the long sleep duration group. Previous research mainly explored the association between short sleep duration and obesity, but there were different conclusions on the cut-off point of short sleep duration. Garaulet et al. [7] concluded that the cut-off point of short sleep duration for obesity risk was 8 h/d. Grandner et al. [3] indicated the short sleep cut-off point for obesity risk was 7 h/d. Bjorkelund et al. [24] indicated the cutoff was 6 h/d. Cappuccio et al. [8] and Stranges et al. [25] found the cutoff was 5 h/d, etc. Our findings supported that among Taiwanese adults aged 23–45, the cut-off point of obesity risk for men was 7 h/d of sleep, and the cutoff of overall obesity for women was 6 h/d of sleep. Women’s central obesity had a low-risk sleep duration interval of 7–8 h/d.

The present study found that men who slept for more than 8 h/d showed poorer functional fitness (BS, SR, and CEI) performances. Women who slept for less than 6 h/d or especially more than 7 h/d had poorer performances in BS, while similar to men, women who slept more than 8 h/d performed poorer in SR. The associations might indicate that prolonged sleep makes the muscles slack for a long time, which is not conducive to the development of the muscle strength and endurance and the flexibility. Or on the contrary, people with better functional fitness may be more energetic, more resistant to fatigue, and don’t need too much sleep [26]. Previous studies [27,28,29,30] have found that people with poor sleep quality were more likely to have lower performances of functional fitness and athletic ability. But few researchers have studied the relationship between sleep duration and functional fitness. Our results were unique and applicable to Taiwanese adults aged 23–45, and could provide inspirations for clinical research on functional fitness such as functional degeneration of articular capsule or ligament, and stiffness of muscle-tendon or connective tissue [31, 32].

In our results, for both sexes, sleep duration of 8–9 h/d was the optimal sleep duration for presenting the best self-rated health, subjective happiness, and life satisfaction. Shankar et al. [33] found that compared to 7 h/d of sleep, those with shorter or longer sleep duration were more likely to report poor self-rated health. Steptoe et al. [10] found that sleep duration of 7–8 h/d was the optimal for presenting the best self-rated health. Magee et al. [11] observed that short (< 6 h/d) and long (≥ 9 h/d) sleep durations were significantly associated with poor self-rated health and low quality of life. It can be speculated that our results were more representative of sleep wellbeing self-efficacy in Taiwanese adults aged 23–45.

The present study has several advantages. First, the sample size was large, and the data were representative of Taiwanese adults aged 23–45. Second, according to the review of relevant literature, this study was the first to investigate the association between sleep duration and functional fitness among young to middle-aged adults in Taiwan. Meanwhile, we divided the sleep duration interval into five categories in more detail for comparison. However, this study has some limitations. First, the sample lacked individuals who reported more than 9 h of sleep. Such sample imbalance might lead to poor robustness to the statistical results of the long sleep duration group. Second, a causal relationship cannot be demonstrated because of the cross-sectional study design. But longitudinal study design was relatively difficult to practice in this research direction. Sleep duration is an experimental condition or goal which is difficult to control, since it is usually related to one’s habits and schedule. This research is an apt opportunity to clarify how sleep might be a cause of and a consequence of adiposity and fitness-enhancing physical activity. More in-depth exploration should require the coordination of clinical research and detailed sleep data monitoring, and correlate that with phased adiposity or fitness conditions to establish a temporal order. Third, the survey data eliminated the functionally disabled and physically unfit population. Fourth, the data on sleeping and self-perception of health was self-reported data which could be biased.

Future research may include several aspects. First, we suggest that the subsequent National Physical Fitness Examination Survey (NPFES) should consider a more informative questionnaire covering issues about profession, self-reported sleep quality, alcohol use, diet, psychological stress, and depression which can be used as new independent variables as well as confounders. Secondly, a suitable longitudinal study design can be developed for clinical research on functional fitness and sleep monitoring. Furthermore, the research may link sleep, physical fitness, and chronic diseases to conduct a more systematic study. Previous studies have linked physical fitness to diabetes, hypertension, and heart disease [34,35,36,37]. Hence, future study may explore the effects of sleep status on chronic diseases through the mediating role of physical health.

Conclusions

This study analyzed the associations of sleep duration with physical fitness performances and self-perceptions of health among Taiwanese adults aged 23–45. According to the results, sleep duration was significantly associated with obesity, functional fitness, and self-perception of health. The appropriate sleep duration for men with low obesity-related values was 7–9 h/day (h/d), and that for women was 7–8 h/d. Sleeping less than 8 h/d showed better functional fitness (BS, SR, and CEI) performances in males, and better SR performance in females, while 7–8 h/d was the optimal sleep duration for BS for women. For both sexes, sleep duration of 8–9 h/d was the optimal sleep duration for self-perceptions of health. We infer that sleep duration may be a potential factor regarding the effects on physical fitness and self-perception of health.

Availability of data and materials

The computerized data sets of the National Physical Fitness Examination Survey (NPFES) were comprised of de-identified data, which were released by the Sports and Health Information Application Research Center of the MOE-SA for public research purposes. The data set analyzed during the current study was publicly available at https://isports.sa.gov.tw/Apps/EssayList.aspx? SYS = TIS&MENU_CD = M04&ITEM_CD = T06&MENU_PRG_CD = 4&ITEM_PRG_CD = 5, based on the research project application and IRB.

Abbreviations

ANCOVA:

Analysis of covariance

BS:

1-munite bent-leg sit-up test

BMI:

Body mass index

CEI:

Cardiorespiratory endurance index

HC:

Hip circumference

SR:

Sit-and-reach test

WC:

Waist circumference

WHR:

Waist-to-hip ratio

WHtR:

Waist-to-height ratio

References

  1. Gallicchio L, Kalesan B. Sleep duration and mortality: a systematic review and meta-analysis. J Sleep Res. 2009;18(2):148–58. https://doi.org/10.1111/j.1365-2869.2008.00732.x.

    Article  PubMed  Google Scholar 

  2. Liu Y, Wheaton AG, Chapman DP, Croft JB. Sleep duration and chronic diseases among U.S. adults age 45 years and older: evidence from the 2010 behavioral risk factor surveillance system. Sleep. 2013;36(10):1421–7. https://doi.org/10.5665/sleep.3028.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Grandner MA, Chakravorty S, Perlis ML, Oliver L, Gurubhagavatula I. Habitual sleep duration associated with self-reported and objectively determined cardiometabolic risk factors. Sleep Med. 2014;15(1):42–50. https://doi.org/10.1016/j.sleep.2013.09.012.

    Article  PubMed  Google Scholar 

  4. Alvarez GG, Ayas NT. The impact of daily sleep duration on health: a review of the literature. Prog Cardiovasc Nurs. 2004;19(2):56–9. https://doi.org/10.1111/j.0889-7204.2004.02422.x.

    Article  PubMed  Google Scholar 

  5. Gottlieb DJ, Punjabi NM, Newman AB, Resnick HE, Redline S, Baldwin CM, Nieto FJ. Association of sleep time with diabetes mellitus and impaired glucose tolerance. Arch Intern Med. 2005;165(8):863–7. https://doi.org/10.1001/archinte.165.8.863.

    Article  PubMed  Google Scholar 

  6. Gottlieb DJ, Redline S, Nieto FJ, Baldwin CM, Newman AB, Resnick HE, Punjabi NM. Association of usual sleep duration with hypertension: the sleep heart health study. Sleep. 2006;29(8):1009–14. https://doi.org/10.1093/sleep/29.8.1009.

    Article  PubMed  Google Scholar 

  7. Garaulet M, Ortega FB, Ruiz JR, Rey-López JP, Béghin L, Manios Y, Cuenca-García M, Plada M, Diethelm K, Kafatos A, Molnár D, Al-Tahan J, Moreno LA. Short sleep duration is associated with increased obesity markers in European adolescents: effect of physical activity and dietary habits. The HELENA study. Int J Obes (Lond). 2011;35(10):1308–17.

    Article  CAS  Google Scholar 

  8. Cappuccio FP, Taggart FM, Kandala NB, Currie A, Peile E, Stranges S, Miller MA. Meta-analysis of short sleep duration and obesity in children and adults. Sleep. 2008;31(5):619–26. https://doi.org/10.1093/sleep/31.5.619.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Hsu CC, Gu M, Lee TS, Lu CJ. The effects of daily sleep condition on performances of physical fitness among Taiwanese adults: a cross-sectional study. Int J Environ Res Public Health. 2020;17(6):1907. https://doi.org/10.3390/ijerph17061907.

    Article  PubMed Central  Google Scholar 

  10. Steptoe A, Peacey V, Wardle J. Sleep duration and health in young adults. Arch Intern Med. 2006;166(16):1689–92. https://doi.org/10.1001/archinte.166.16.1689.

    Article  PubMed  Google Scholar 

  11. Magee CA, Caputi P, Iverson DC. Relationships between self-rated health, quality of life and sleep duration in middle aged and elderly Australians. Sleep Med. 2011;12(4):346–50. https://doi.org/10.1016/j.sleep.2010.09.013.

    Article  PubMed  Google Scholar 

  12. Consensus Conference Panel, Watson NF, Badr MS, Belenky G, Bliwise DL, Buxton OM, Buysse D, Dinges DF, Gangwisch J, Grandner MA, Kushida C, Malhotra RK, Martin JL, Patel SR, Quan SF, Tasali E. Joint consensus statement of the American Academy of sleep medicine and Sleep Research Society on the recommended amount of sleep for a healthy adult: methodology and discussion. Sleep. 2015;38(8):1161–83.

    Article  Google Scholar 

  13. Cattuzzo MT, Dos Santos HR, Ré AH, de Oliveira IS, Melo BM, de Sousa MM, de Araújo RC, Stodden D. Motor competence and health related physical fitness in youth: a systematic review. J Sci Med Sport. 2016;19(2):123–9. https://doi.org/10.1016/j.jsams.2014.12.004.

    Article  PubMed  Google Scholar 

  14. Tremblay MS, Carson V, Chaput JP, Connor Gorber S, Dinh T, Duggan M, Faulkner G, Gray CE, Gruber R, Janson K, Janssen I, Katzmarzyk PT, Kho ME, Latimer-Cheung AE, LeBlanc C, Okely AD, Olds T, Pate RR, Phillips A, Poitras VJ, Rodenburg S, Sampson M, Saunders TJ, Stone JA, Stratton G, Weiss SK, Zehr L. Canadian 24-hour movement guidelines for children and youth: an integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab. 2016;41(6 Suppl 3):S311–27. https://doi.org/10.1139/apnm-2016-0151.

    Article  PubMed  Google Scholar 

  15. Miñarro PA, Andújar PS, García PL, Toro EO. A comparison of the spine posture among several sit-and-reach test protocols. J Sci Med Sport. 2007;10(6):456–62. https://doi.org/10.1016/j.jsams.2006.10.003.

    Article  PubMed  Google Scholar 

  16. Esco MR, Olson MS, Williford H. Relationship of push-ups and sit-ups tests to selected anthropometric variables and performance results: a multiple regression study. J Strength Cond Res. 2008;22(6):1862–8. https://doi.org/10.1519/JSC.0b013e318181fd03.

    Article  PubMed  Google Scholar 

  17. Vaara JP, Santtila M, Vasankari T, Fogelholm M, Mäntysaari M, Pihlainen K, Vaara E, Kyröläinen H. Cardiorespiratory and muscular fitness in young adult Finnish men between 2003 and 2015. Scand J Med Sci Sports. 2020;30(4):716–24. https://doi.org/10.1111/sms.13619.

    Article  PubMed  Google Scholar 

  18. Liao Y, Tsai HH, Wang HS, Lin CP, Wu MC, Chen JF. Traveling by private motorized vehicle and physical fitness in Taiwanese adults. Int J Behav Med. 2016;23(4):395–401. https://doi.org/10.1007/s12529-015-9489-8.

    Article  PubMed  Google Scholar 

  19. Salinero-Fort MÁ, del Otero-Sanz L, Martín-Madrazo C, de Burgos-Lunar C, Chico-Moraleja RM, Rodés-Soldevila B, Jiménez-García R, Gómez-Campelo P, HEALTH & MIGRATION Group. The relationship between social support and self-reported health status in immigrants: an adjusted analysis in the Madrid Cross Sectional Study. BMC family practice. 2011;12(1):46.

    Article  Google Scholar 

  20. Bodde AE, Seo DC, Frey G. Correlation between physical activity and self-rated health status of non-elderly adults with disabilities. Prev Med. 2009;49(6):511–4. https://doi.org/10.1016/j.ypmed.2009.10.004.

    Article  PubMed  Google Scholar 

  21. White AM, Philogene GS, Fine L, Sinha S. Social support and self-reported health status of older adults in the United States. Am J Public Health. 2009;99(10):1872–8. https://doi.org/10.2105/AJPH.2008.146894.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Chen HL, Lee PF, Chang YC, Hsu FS, Tseng CY, Hsieh XY, Ho CC. The association between physical fitness performance and subjective happiness among Taiwanese adults. Int J Environ Res Public Health. 2020;17(11):3774. https://doi.org/10.3390/ijerph17113774.

    Article  PubMed Central  Google Scholar 

  23. Scheffé H. A method for judging all contrasts in the analysis of variance. Biometrika. 1953;40(1–2):87–110.

    Google Scholar 

  24. Björkelund C, Bondyr-Carlsson D, Lapidus L, Lissner L, Månsson J, Skoog I, Bengtsson C. Sleep disturbances in midlife unrelated to 32-year diabetes incidence: the prospective population study of women in Gothenburg. Diabetes Care. 2005;28(11):2739–44. https://doi.org/10.2337/diacare.28.11.2739.

    Article  PubMed  Google Scholar 

  25. Stranges S, Cappuccio FP, Kandala NB, Miller MA, Taggart FM, Kumari M, Ferrie JE, Shipley MJ, Brunner EJ, Marmot MG. Cross-sectional versus prospective associations of sleep duration with changes in relative weight and body fat distribution: the Whitehall II study. Am J Epidemiol. 2008;167(3):321–9. https://doi.org/10.1093/aje/kwm302.

    Article  PubMed  Google Scholar 

  26. Kredlow MA, Capozzoli MC, Hearon BA, Calkins AW, Otto MW. The effects of physical activity on sleep: a meta-analytic review. J Behav Med. 2015;38(3):427–49. https://doi.org/10.1007/s10865-015-9617-6.

    Article  PubMed  Google Scholar 

  27. Lee AJ, Lin WH. Association between sleep quality and physical fitness in female young adults. J Sports Med Phys Fitness. 2007;47(4):462–7.

    CAS  PubMed  Google Scholar 

  28. Chang SP, Chen YH. Relationships between sleep quality, physical fitness and body mass index in college freshmen. J Sports Med Phys Fitness. 2015;55(10):1234–41.

    CAS  PubMed  Google Scholar 

  29. Evangelou C, Kartakoullis N, Hadjicharalambous M, Aphamis G, Hadjimarkou M, Sakkas GK, Giannaki CD. Depressive symptoms, sleep quality, physical fitness, and fatigue among adult women with different obesity status. Sport Sci Health. 2019;15(3):605–14. https://doi.org/10.1007/s11332-019-00559-9.

    Article  Google Scholar 

  30. Peng X, Liu N, Zhang X, Bao X, Xie Y, Huang J, Wang P, Du Q. Associations between objectively assessed physical fitness levels and sleep quality in community-dwelling elderly people in South China. Sleep Breath. 2019;23(2):679–85. https://doi.org/10.1007/s11325-018-1749-9.

    Article  PubMed  Google Scholar 

  31. Mathew M, Dhollander A, Getgood A. Anterolateral ligament reconstruction or extra-articular tenodesis: why and when. Clin Sports Med. 2018;37(1):75–86. https://doi.org/10.1016/j.csm.2017.07.011.

    Article  PubMed  Google Scholar 

  32. Kannus P. Structure of the tendon connective tissue. Scand J Med Sci Sports. 2000;10(6):312–20. https://doi.org/10.1034/j.1600-0838.2000.010006312.x.

    Article  CAS  PubMed  Google Scholar 

  33. Shankar A, Charumathi S, Kalidindi S. Sleep duration and self-rated health: the National Health Interview Survey. Sleep. 2008;34(9):1173–7.

    Article  Google Scholar 

  34. Sargeant LA, Wareham NJ, Khaw KT. Family history of diabetes identifies a group at increased risk for the metabolic consequences of obesity and physical inactivity in EPIC-Norfolk: a population-based study. The European prospective investigation into cancer. Int J Obes Relat Metab Disord. 2000;24(10):1333–9. https://doi.org/10.1038/sj.ijo.0801383.

    Article  CAS  PubMed  Google Scholar 

  35. Healy GN, Winkler EAH, Brakenridge CL, Reeves MM, Eakin EG. Accelerometer-derived sedentary and physical activity time in overweight/obese adults with type 2 diabetes: cross-sectional associations with cardiometabolic biomarkers. PLoS One. 2015;10(3):e0119140. https://doi.org/10.1371/journal.pone.0119140.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Barth S, Zacher M, Reinecke H, Hautmann MB, Kerber S, Gietzen F, Halbfass H, Schade A, Deneke T, Schieffer B, Hamm K. Decreasing incidence of coronary heart disease in extreme obesity (BMI ≥ 40)-a single Centre experience. Obes Res Clin Pract. 2017;11(4):435–44. https://doi.org/10.1016/j.orcp.2016.08.007.

    Article  PubMed  Google Scholar 

  37. Antonopoulos AS, Oikonomou EK, Antoniades C, Tousoulis D. From the BMI paradox to the obesity paradox: the obesity-mortality association in coronary heart disease. Obes Rev. 2016;17(10):989–1000. https://doi.org/10.1111/obr.12440.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This study is based in part on data from the NPFES provided by the Sports Cloud: Information and Application Research Center of Sports for All, MOE-SA in Taiwan. The interpretation and conclusions contained herein do not represent those of MOE-SA. This manuscript was edited by Wallace Academic Editing.

Funding

This research received no external funding.

Author information

Authors and Affiliations

Authors

Contributions

CL1 and MG participated in the design, conducted the statistical analyses, interpreted the data, and drafted the manuscript. CH1 and CL2 supervised the study, and assisted in data interpretation. TL, MC and CH2 helped to manage, and critically reviewed the manuscript. All authors read and approved the final manuscript. Notes: CL1 ~ Chia-Chen Liu, CL2 ~ Chi-Jie Lu; CH1 ~ Chi-Chieh Hsu, CH2 ~ Chien-Chang Ho.

Corresponding author

Correspondence to Chia-Chen Liu.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Institutional Review Board of Fu Jen Catholic University (FJU-IRB C108006). The survey was approved by the Sports Administration, Ministry of Education (MOE-SA) in Taiwan, and written informed consent was obtained from each participant.

Consent for publication

Not applicable.

Competing interests

The authors declare no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gu, M., Liu, CC., Hsu, CC. et al. Associations of sleep duration with physical fitness performance and self-perception of health: a cross-sectional study of Taiwanese adults aged 23–45. BMC Public Health 21, 594 (2021). https://doi.org/10.1186/s12889-021-10636-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-021-10636-9

Keywords