Journal List > Korean J Health Promot > v.17(4) > 1089920

Oh, Moon, Kong, Oh, and Kim: The Association between Sitting Time and Health-Related Quality of Life According to Body Mass Index in Elderly Korean

Abstract

Background

Although obesity and health-related quality of life (HRQOL) in elderly are well known to be associated with obesity and sitting time, it is unclear whether effect of sedentary lifestyle on HRQOL is affected by body mass index (BMI) or not. So we analyzed the relationship between sitting time and HRQOL according to BMI groups in elderly Korean.

Methods

Participants aged over 60 from the 6th Korea National Health and Nutrition Examination Survey (2014 and 2015) were included. Participants were classified as normal weight and overweight/obese groups. Mean sitting times were compared between groups according to the EuroQol 5 dimension (EQ-5D) And logistic regression analyses were performed.

Results

Men with mobility, usual activity, or pain/discomfort domain problem had longer sitting time. Women with a problem in every domain had longer sitting time. Overweight/obese women with problem showed longer sitting time. Odds ratios (ORs) of mobility, usual activity, pain or discomfort, and low EQ-5D score domain were increased regardless of BMI groups in men. But, ORs of all domains were increased only in overweight/obese group in women.

Conclusions

In elderly Korean, prolonged sitting time associated with decreased HRQOL. Impaired HRQOL is associated with increased sitting time regardless of BMI in men. But only overweight/obese group showed association between prolonged sitting time and impaired HRQOL in women. These results represents that decrease in quality of life according to the increase of the sitting time differs according to the BMI in elderly Korean women.

Figures and Tables

Figure 1

Mean sitting time according to EQ-5D domain problem by sex. Shown are comparisons of adjusted mean sitting times between subjects with or without problem within each EQ-5D domain. P-values were calculated by t-test. Sitting time were adjusted for age, alcohol, smoking, physical activity, residential area, income, education, marital status, and comorbidities (hypertension, hypercholesterolemia, diabetes, coronary heart disease, stroke, COPD, arthritis, and cancer).

Abbreviations: EQ-5D, EuroQol comprising five dimensions; COPD, chronic obstructive pulmonary disease.
aP<0.01.
kjhp-17-209-g001
Figure 2

Mean sitting time according to EQ-5D domain problem by sex and BMI categories. Shown are comparisons of adjusted mean sitting times between subjects with or without problem within each EQ-5D domain. P-values were calculated by t-test. Sitting time were adjusted for age, alcohol, smoking, physical activity, residential area, income, education, marital status, comorbidities (hypertension, hypercholesterolemia, diabetes, coronary heart disease, stroke, COPD, arthritis, cancer).

Abbreviations: EQ-5D, EuroQol comprising five dimensions; BMI, body mass index; COPD, chronic obstructive pulmonary disease.
aP<0.01.
bP<0.05.
kjhp-17-209-g002
Table 1

Baseline characteristic according to sex and BMI categoriesa

kjhp-17-209-i001

Abbreviations: BMI, body mass index; LPA, low physical activity; MPA, moderate physical activity; HPA, high physical activity; COPD. chronic obstructive pulmonary disease; EQ-5D, EuroQol comprising five dimensions.

aValues are represented as number (%) or mean±standard error unless otherwise indicated.

bP-value by independent t-test (conticuous variables) or χ2 test (categorical variavles).

cDefined as consuming more than 7/5 (man/woman) standard alcoholic drinks at one time more than twice a week.

Table 2

ORs and 95% CI for impaired status of health related quality of lifea per hour increase in sitting time by sex and BMI categories

kjhp-17-209-i002

Abbreviations: OR, odds ratio; CI, confidence interval; BMI, body mass index; EQ-5D, EuroQol comprising five dimensions; COPD, chronic obstructive pulmonary disease.

Values are presented as OR (95% CI); OR (95% CI) by logistic regression analyses.

aImpaired status of health related quality of life: some or extreme problems in EQ-5D domains and the lowest 20% in EQ-5D index score.

bModel 1: adjusted for age

cP<0.05.

dP<0.01.

eModel 2: adjusted for age, alcohol, smoking, physical activity, residential area, income, education, and marital status.

fModel 3: adjusted for age, alcohol, smoking, physical activity, residential area, income, education, marital status, and comorbidities (hypertension, hypercholesterolemia, diabetes, coronary heart disease, stroke, COPD, arthritis, and cancer).

References

1. World Health Organization. Good health adds life to years: global brief for World Health Day 2012. In Good health adds life to years: Global brief for World Health Day 2012 [Internet]. Geneva: World Health Organization;2012. Accessed Sept 26, 2017. Available from: http://www.who.int/ageing/publications/hd2012_global_brief/en/.
2. Oldridge NB. Economic burden of physical inactivity: healthcare costs associated with cardiovascular disease. Eur J Cardiovasc Prev Rehabil. 2008; 15(2):130–139.
crossref
3. Martínez-Gómez D, Guallar-Castillón P, León-Muñoz LM, López-García E, Rodríguez-Artalejo F. Combined impact of traditional and non-traditional health behaviors on mortality: a national prospective cohort study in Spanish older adults. BMC Med. 2013; 11:47.
crossref
4. Scarborough P, Bhatnagar P, Wickramasinghe KK, Allender S, Foster C, Rayner M. The economic burden of ill health due to diet, physical inactivity, smoking, alcohol and obesity in the UK: an update to 2006–07 NHS costs. J Public Health (Oxf). 2011; 33(4):527–535.
crossref
5. Health UDo. Services H. 2008 Physical Activity Guidelines for Americans. Be Active, Healthy and Happy! [Internet]. Washington: US Department of Health and Human Services;2008. Accessed Sept 26, 2017. Available from: https://health.gov/paguidelines/df/paguide.pdf.
6. Owen N, Healy GN, Matthews CE, Dunstan DW. Too much sitting: the population health science of sedentary behavior. Exerc Sport Sci Rev. 2010; 38(3):105–113.
7. Katzmarzyk PT, Church TS, Craig CL, Bouchard C. Sitting time and mortality from all causes, cardiovascular disease, and cancer. Med Sci Sports Exerc. 2009; 41(5):998–1005.
crossref
8. Rowe JW, Kahn RL. Successful aging. Gerontologist. 1997; 37:433–440.
crossref
9. Spilker B. Quality of life and pharmacoeconomics in clinical rials. 2nd ed. Philadelphia Pennsylvania: Lippincott-Raven Publishers;1996. p. 11–24.
10. Goulart AC, Rexrode KM. Health consequences of obesity in the elderly: a review. Curr Cardiovasc Risk Rep. 2007; 1(4):340–347.
crossref
11. Banegas JR, López-García E, Graciani A, Guallar-Castillón P, Gutierrez-Fisac JL, Alonso J, et al. Relationship between obesity, hypertension and diabetes, and health-related quality of life among the elderly. Eur J Cardiovasc Prev Rehabil. 2007; 14(3):456–462.
crossref
12. Pedisic Z, Grunseit A, Ding D, Chau JY, Banks E, Stamatakis E, et al. High sitting time or obesity which came first? Bidirectional association in a longitudinal study of 31,787 Australian adults. Obesity (Silver Spring). 2014; 22(10):2126–2130.
crossref
13. van Uffelen JG, Watson MJ, Dobson AJ, Brown WJ. Sitting time is associated with weight, but not with weight gain in mid-aged Australian women. Obesity (Silver Spring). 2010; 18(9):1788–1794.
crossref
14. Vallance JK, Eurich D, Marshall AL, Lavallee CM, Johnson ST. Associations between sitting time and health-related quality of life among older men. Ment Health Phys Act. 2013; 6(1):49–54.
crossref
15. Lim JW, Gonzalez P, Wang-Letzkus MF, Ashing-Giwa KT. Understanding the cultural health belief model influencing health behaviors and health-related quality of life between Latina and Asian-American breast cancer survivors. Support Care Cancer. 2009; 17(9):1137–1147.
crossref
16. World Health Organization. Global physical activity questionnaire (GPAQ) analysis guide [Internet]. Geneva: World Health Organization;2012. Accessed Sept 26, 2017. Available from: http://www.who.int/ageing/publications/whd2012_global_rief/en/.
17. Weisell RC. Body mass index as an indicator of obesity. Asia Pac J Clin Nutr. 2002; 11:Suppl 8. S667–S751.
crossref
18. Rabin R, de Charro F. EQ-SD: a measure of health status from the EuroQol Group. Ann Med. 2001; 33(5):337–343.
crossref
19. Kim MH, Cho YS, Uhm WS, Kim S, Bae SC. Cross-cultural adaptation and validation of the Korean version of the EQ-5D in patients with rheumatic diseases. Qual Life Res. 2005; 14(5):1401–1406.
crossref
20. Lee YK, Nam HS, Chuang LH, Kim KY, Yang HK, Kwon IS, et al. South Korean time trade-off values for EQ-5D health states: modeling with observed values for 101 health states. Value Health. 2009; 12(8):1187–1193.
crossref
21. World Health Organization. International guide for monitoring alcohol consumption and related harm [Internet]. Geneva: World Health Organization;2000. Accessed Sept 26, 2017. Available from: http://apps.who.int/iris/bitstream/10665/66529//WHO_MSD_MSB_00.4.pdf.
22. Herrmann SD, Heumann KJ, Der Ananian CA, Ainsworth BE. Validity and reliability of the global physical activity questionnaire (GPAQ). Meas Phys Educ Exerc Sci. 2013; 17(3):221–235.
crossref
23. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005; 112(17):2735–2752.
24. Rosenkranz RR, Duncan MJ, Rosenkranz SK, Kolt GS. Active lifestyles related to excellent self-rated health and quality of life: cross sectional findings from 194,545 participants in The 45 and Up Study. BMC Public Health. 2013; 13:1071.
crossref
25. Jia H, Lubetkin EI. The impact of obesity on health-related quality-of-life in the general adult US population. J Public Health (Oxf). 2005; 27(2):156–164.
crossref
26. Hu F, Kim D, Kawachi I. Obesity epidemiology. 1th ed. New York: Oxford University Press;2008. p. 234–226.
27. Olivares PR, Gusi N, Prieto J, Hernandez-Mocholi MA. Fitness and health-related quality of life dimensions in community-dwelling middle aged and older adults. Health Qual Life Outcomes. 2011; 9:117.
crossref
28. Salmon J, Owen N, Crawford D, Bauman A, Sallis JF. Physical activity and sedentary behavior: a population-based study of barriers, enjoyment, and preference. Health Psychol. 2003; 22(2):178–188.
crossref
29. Hamer M, Stamatakis E. Prospective study of sedentary behavior, risk of depression, and cognitive impairment. Med Sci Sports Exerc. 2014; 46(4):718–723.
crossref
30. de Wit L, van Straten A, Lamers F, Cuijpers P, Penninx B. Are sedentary television watching and computer use behaviors associated with anxiety and depressive disorders? Psychiatry Res. 2011; 186(2-3):239–243.
crossref
31. Kulinski JP, Khera A, Ayers CR, Das SR, De Lemos JA, Blair SN, et al. Association between cardiorespiratory fitness and accelerometer-derived physical activity and sedentary time in the general population. Mayo Clin Proc. 2014; 89(8):1063–1071.
crossref
32. Murtagh KN, Hubert HB. Gender differences in physical disability among an elderly cohort. Am J Public Health. 2004; 94(8):1406–1411.
crossref
33. Nolen-Hoeksema S. Gender differences in depression. Curr Dir Psychol Sci. 2001; 10(5):173–176.
crossref
34. Vasan RS. Cardiac function and obesity. Heart. 2003; 89(10):1127–1129.
crossref
35. Lang IA, Llewellyn DJ, Alexander K, Melzer D. Obesity, physical function, and mortality in older adults. J Am Geriatr Soc. 2008; 56(8):1474–1478.
crossref
36. Storch EA, Milsom VA, Debraganza N, Lewin AB, Geffken GR, Silverstein JH. Peer victimization, psychosocial adjustment, and physical activity in overweight and at-risk-for-overweight youth. J Pediatr Psychol. 2006; 32(1):80–89.
crossref
37. Strine TW, Mokdad AH, Dube SR, Balluz LS, Gonzalez O, Berry JT, et al. The association of depression and anxiety with obesity and unhealthy behaviors among community-dwelling US adults. Gen Hosp Psychiatry. 2008; 30(2):127–137.
crossref
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