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Abstract
Purpose:
Forests have positive effects on health due to phytoncide, thus increasing physical activity and stress relief. However, research has not been conducted on the daily health benefits of existing forests. Therefore, this study attempts to compare the health status and behaviors of residents in urban and forested areas. Methods: This cross-sectional study used anthropometric measures, blood tests, heart rate variability, depression, stress, and health behavior self-reports for adults between 35 and 79 years from two regions. Results: Adults living in a forested region had better health consequences-including lower prevalence of osteoarthritis (6.4%) and mean bone mineral density (-0.84) -than those in an urban region (osteoarthritis: 13.7%; bone mineral density: -1.55). The percentage of ‘physically active’ participants (measured in MET-minutes) differed significantly different between the forested (49.1%) and urban (7.3%) areas. However, health behaviors such as smoking, alcohol consumption, and regular heath check-up rates were worse among residents from the forested, than the urban area. Conclusion: We concluded that more proactive forest therapy programs are needed to prove the health differences.
REFERENCES
1.Lee SY., Kim SW., Park JW. Health behavior patterns of Korean. Korean J Prev Med. 1997. 30(1):181–94.
2.Korea Centers for Disease Control and Prevention. The Fifth Korea National Health and Nutrition Examination Survey (KNHANES V-2). 2011.
3.Korea Centers for Disease Control and Prevention. Community Health Survey. 2012.
4.Breslow L., Enstrom JE. Persistence of health habits and their relationship to mortality. Prev Med. 1980 July. 9(4):469–83. http://dx.doi.org/10.1016/0091-7435(80)90042-0.
5.Rubinstein RL. The home environments of older people: a description of the psychosocial processes linking person to place. J Gerontol. 1989 Mar. 44(2):S45–53.
6.Morita E., Naito M., Hishida A., Wakai K., Mori A., Asai Y, et al. No association between the frequency of forest walking and blood pressure levels or the prevalence of hypertension in a cross-sectional study of a Japanese population. Environ health and Prev Med. 2011 Sep. 16(5):299–306. http://dx.doi.org/10.1007/s12199-010-0197-3.
7.Morita E., Weigl M., Schuh A., Stucki G. Identification of relevant ICF categories for indication, intervention planning and evaluation of health resort programs: a Delphi exercise. Int J Biometeorol. 2006 Jan. 50(3):183–91. http://dx.doi.org/10.1007/s00484-005-0008-5.
8.Fisheries Global Information System (FAO-FIGIS) - Web site. Web services. FI Institutional Websites. In: FAO Fisheries and Aquaculture Department [online]. Rome. Updated 10 June 2010. [Cited 24 April 2015]. Available from:. http://www.fao.org/docrep/017/i3110e/i3110e.pdf.
9.Cha J., Kim S. Healing effects of the forest experience on alcoholics. J Korean Acad Nurs. 2009 Jun. 39(3):338–48. http://dx.doi.org/10.4040/jkan.2009.39.3.338.
10.Lee JH. Characteristics of nature based recreation in Germany-a view from the historical background and laws. J Korean Ins Recreation. 2010. 14(4):81–91.
11.Takano T., Nakamura K., Watanabe M. Urban residential environments and senior citizens' longevity in megacity areas: the importance of walkable green spaces. J Epidemiol Community Health. 2002. 56(12):913–18. http://dx.doi.org/10.1136/jech.56.12.913.
12.Choi KM., Shin WS., Yeoun PS., Cho YM. Effect of Forest Walking Exercise on University Student, Stress and Fatigue. A Joint Conf of forest Sci. 2011. 1222–5.
13.Lim HJ., Choi YH., Kim BY K., Kim SH., Park BJ. The stress reduction effects of healing forest on university students. A Jt Conf Forest Sci. 2012. 649–52.
14.Park BJ., Miyazaki Y. Physiological effects of viewing forest landscapes-results of field tests in Atsugi city, Japan. J Korean Forest Soc. 2008. 97(6):634–40. http://dx.doi.org/10.5322/JES.2012.21.5.605.
15.Korea Forest Servic. A basic statistics of forest in Korea. 2010.
16.Poortinga W. The prevalence and clustering of four major lifestyle risk factors in an English adult population. Prev Med. 2007. 44(2):124–8. http://dx.doi.org/10.1016/j.ypmed.2006.10.006.
17.Chiolero A., Wietlisbach V., Ruffieux C., Paccaud F., Cornuz J. Clustering of risk behaviors with cigarette consumption: a population-based survey. Prev Med. 2006. 42(5):348–53. http://dx.doi.org/10.1016/j.ypmed.2006.01.011.
18.Ainsworth BE., Haskell WL., Whitt MC., Iriwn ML., Swartz AM., Strath SJ, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000. 32(9 Suppl):S498–504.
19.Oh JY., Yang YJ., Kim BS., Kang JH. Validity and reliability of Korean version of International Physical Activity Questionnaire (IPAQ) short form. Korean J Fam Med. 2007. 28(7):532–41.
20.Hagstromer M., Oja P., Sjostrom M. The International Physical Activity Questionnaire(IPAQ): a study of concurrent and construct validity. Public Health Nutr. 2006. 9(6):755–62. http://dx.doi.org/10.1079/PHN2005898.
21.Cho MJ., Kim KH. Use of the center for epidemiologic studies depression (CES-D) scale in Korea. J Nerv Ment Dis. 1998. 186(5):304–10.
22.Radloff LS. The CES-D scale a self-report depression scale for research in the general population. Applied psychological Meas. 1977. 1(3):385–401. http://dx.doi.org/10.1177/014662167700100306.
23.Koh KB., Park JK., Kim CH. Development of the stress response inventory. J Korean Neuropsychiatric Assoc. 2000. 39(4):707–19.
24.Koh KB., Park JK., Kim CH., Cho S. Development of the stress response inventory and its application in clinical practice. Psychosom Med. 2001. 63(4):668–78.
25.Korea Forest Service. Forest welfare master Plan. 2013.
26.Lee J., Lee Y. Comparison of healthy life style and chronic disease management between urban and rural older adults. Korean J Rehabil Nurs. 2012. 15(2):100–8. http://dx.doi.org/10.7587/kjrehn.2012.100.
27.Miyazaki Y., Ikei H., Song C. Forest medicine research in Japan. Nihon Eiseigaku Zasshi. 2014. 69(2):122–35. http://dx.doi.org/10.1265/jjh.69.122.
28.Park BJ., Tsunetsugu Y., Morikawa T., Kagawa T., Lee J., Ikei H, et al. Physiological and psychological effects of walking in stay-in forest therapy. Nihon Eiseigaku Zasshi. 2014. 69(2):98–103. http://dx.doi.org/10.1265/jjh.69.98.
29.Lee J., Park B., Tsunetsugu Y., Kagawa T., Miyazaki Y. Physiological benefits of forest environment: based on field research at 4 sites. Nihon Eiseigaku Zasshi. 2011. 66(4):663–9. http://dx.doi.org/10.1265/jjh.66.663.
Table 1.
Demographic Characteristics of the Study Participants
| Characteristics | Categories | Total | A forest area | A metropolitan area | p |
|---|---|---|---|---|---|
| n(%) | n(%) | n(%) | |||
| Number of participants | 141(50.4) | 139(49.6) | |||
| Gender (n=280) | Male | 132 (47.1) | 66 (46.8) | 66 (47.5) | .91 |
| Female | 148 (52.9) | 75 (53.2) | 73 (52.5) | ||
| Age (year) (n=280) | ＜45 | 26 (9.3) | 14 (9.9) | 12 (8.6) | .93 |
| 45~64 | 144 (51.4) | 72 (51.1) | 72 (51.8) | ||
| ≥65 | 110 (39.3) | 55(39.0) | 55(39.6) | ||
| Marital status (n=279) | Married | 207 (74.2) | 108 (76.6) | 99 (71.7) | .35 |
| Others | 72 (25.8) | 33 (23.4) | 39 (28.3) | ||
| Education Level (n=280) | ≤Elementary school | 76 (27.1) | 40 (28.4) | 36 (25.9) | .96 |
| Middle school | 42 (15.0) | 20 (14.2) | 22 (15.8) | ||
| High school | 75 (26.8) | 38 (27.0) | 37 (26.6) | ||
| ≥University | 87 (31.1) | 43 (30.5) | 44 (31.7) | ||
| Occupation (n=278) | Yes | 117 (41.9) | 32 (22.7) | 85 (61.6) | ＜.001 |
| No | 161 (57.7) | 108 (76.6) | 53 (38.4) | ||
| Household income-level∗ (n=255) | 1Q (the lowest) | 62 (24.3) | 23 (19.0) | 39 (29.1) | .22 |
| 2Q | 65 (25.5) | 30 (24.8) | 35 (26.1) | ||
| 3Q | 65 (25.5) | 34 (28.1) | 31 (23.1) | ||
| 4Q (the highest) | 63 (24.7) | 34 (28.1) | 29 (21.6) | ||
| Health insurance (n=279) | Yes | 253 (90.7) | 127 (90.1) | 126 (91.3) | .06 |
| Medicaid | 13 (4.7) | 4 (2.8) | 9 (6.5) | ||
| Others | 13 (4.7) | 10 (7.1) | 3 (2.2) | ||
| Medical conditions | Hypertension | 93 (33.3) | 42 (30.0) | 51 (36.7) | .22 |
| Diabetes mellitus | 33 (11.8) | 12 (8.6) | 21 (15.1) | .22 | |
| Dyslipidemia | 30 (10.8) | 6 (4.3) | 24 (17.3) | .00 | |
| Stroke | 15 (5.4) | 4 (2.9) | 11 (7.9) | .16 | |
| Arthritis | 28 (10.0) | 9 (6.4) | 19 (13.7) | .02 | |
| Cancer | 19 (6.8) | 9 (6.4) | 10 (7.2) | .95 | |
| Depression | 14 (5.0) | 5 (3.6) | 9 (6.5) | .49 | |
| Urinary incontinence | 23 (8.2) | 11 (7.9) | 12 (8.6) | .74 | |
| Checkup (n=280) | Yes | 147 (52.5) | 46 (32.6) | 101 (72.7) | ＜.001 |
| No | 133 (47.5) | 95 (67.4) | 38 (27.3) | ||
| Types of household (n=278) | 1 generation | 158 (56.8) | 86 (61.4) | 72 (52.2) | ＜.001 |
| 2 generation | 91 (32.7) | 31 (22.1) | 60 (43.5) | ||
| 3 generation | 11 (4.0) | 8 (5.7) | 3 (2.2) | ||
| Others | 18 (6.5) | 15 (10.7) | 3 (2.2) |
Table 2.
Mean Value and Difference of the Health Indicators Two Areas
Table 3.
Difference in Health Indicators of the Health Behaviors between Two Areas
Table 4.
Mean Value and Difference of the Physical Activity
| Variables | Total | A forest area | A metropolitan area | p |
|---|---|---|---|---|
| M±SD | M±SD | M±SD | ||
| Physical activity (n=110)∗ | ||||
| Vigorous (day/week) | 0.90±1.90 | 1.20±2.24 | 0.60±1.45 | .10 |
| Vigorous (minute/day) | 30.69±93.66 | 50.00±127.30 | 11.73±30.11 | .03 |
| Moderate (day/week) | 1.75±2.47 | 2.81±2.86 | 0.70±1.37 | ＜.001 |
| Moderate (minute/day) | 51.36±91.08 | 86.64±114.60 | 16.09±32.77 | ＜.001 |
| Walking (day/week) | 4.75±2.58 | 4.61±2.74 | 4.90±2.43 | .56 |
| Walking (minute/day) | 62.11±65.37 | 73.98±85.25 | 50.45±33.67 | ＜.001 |
| Total Physical Activity (MET-min) | 3,976.40±5,016.70 | 5,303.50±7,016.50 | 1,327.10±1,050.20 | ＜.001 |
| Total physical activity (MET-min) | ＜.001 | |||
| Inactive | 29±26.36 | 16±29.09 | 13±23.64 | |
| Minimally active | 50±45.45 | 12±21.82 | 38±69.09 | |
| Physically active | 31±28.18 | 27±49.09 | 4±7.27 |
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