Adherence to Physical Activity Among Older Adults Using a Geographic Information System: Korean National Health and Nutrition Examinations Survey IV

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      The purpose of this study was to examine the adherence to physical activity (PA) among older adults in Korea using data from the Fourth Korean National Health and Nutrition Examination Survey (KNHANESIV), and to illustrate geographic variations in PA using Geographic Information Systems (GIS).


      A secondary analysis of the KNHANES IV data from 2007 to 2008 was used for this study. Participants of the study included 2,241 older adults over the age of 65. Estimates on adherence to PA were obtained for vigorous, moderate, walking, strengthening, and stretching activities. All estimates were weighted to represent Korean population. The association between participants' characteristics and PA was analyzed using Wald chi-square test. Maps depicting regional variations in PA were created using GIS software.


      Adherence to PA among Korean older adults who met national recommendations during the period of year 2007–2008 was about 9% in vigorous activity, 10% in moderate activity, and 48% in walking. The most common type of PA was walking. A higher level of PA was associated with male gender, younger age, high level of income and education, and living with family.


      The majority of older adults did not meet the national PA recommendations, suggesting that consistent surveillance and intervention for PA in the geriatric population are needed in the future. Maps generated using GIS visually showed regional differences in PA among the study participants.

      Key Words


        • Ahmed N.U.
        • Smith G.L.
        • Flores A.M.
        • Pamies R.I.
        • Mason H.R.
        • Woods K.F.
        • et al.
        Racial/ethnic disparity and predictors of leisure-time physical activity among US men.
        Ethnicity & Disease. 2005; 15: 40-52
      1. ArcGIS (Version 9.2) [Computer software].

        • Braith R.W.
        • Stewart K.J.
        Resistance exercise training: its role in the prevention of cardiovascular disease.
        Circulation. 2006; 113: 2642-2650
        • Brownson R.C.
        • Hoehner C.M.
        • Day K.
        • Forsyth A.
        • Sallis J.F.
        Measuring the built environment for physical activity: state of the science.
        American Journal of Preventive Medicine. 2009; 36 (ell2.): S99-S123
        • Choi M.
        • Afzal B.
        • Sattler B.
        Geographic Information Systems (GIS): a new tool for environmental health assessment.
        Public Health Nursing. 2006; 23: 381-391
        • Crespo C.I.
        • Smit E.
        • Anderson R.E.
        • Carter-Pokras O.
        • Ainsworth B.E.
        Race/ethnicity, social class and their relation to physical inactivity during leisure time: results from the third national health and nutrition examination survey, 1988-1994.
        American Journal of Preventive Medicine. 2000; 18: 46-53
        • Cromley E.K.
        • McLafferty S.
        Mapping health information.
        in: Cromley E.K. McLafferty S. GIS and public health. Guilford, New York2002: 98-129
        • Croner C.M.
        • Sperling J.
        • Broome F.R.
        Geographic information systems (GIS): new perspectives in understanding human health and environmental relationships.
        Statistics in Medicine. 1996; 15: 1961-1977
        • Hughes J.P.
        • McDowell M.A.
        • Brody D.J.
        Leisure-time physical activity among US adults 60 or more years of age: results from NHANES 1999-2004.
        Journal of Physical Activity and Health. 2008; 5: 347-358
        • Kim J.
        • Yoo T.
        Comparison of health inequalities in small area with using the standardized mortality ratios in Korea.
        Journal of Preventive Medicine and Public Health. 2008; 41: 300-306
        • Kim W.
        Health-enhancing physical activity guidelines for Koreans: the status and directions for revision.
        Journal of Korean Society for Health Education and Promotion. 2009; 26: 103-117
      2. Korea Centers for Disease Control and Prevention. (2007). Data use manual of Korea National Health and Nutrition Examination Survey III (2005).

      3. Korea Centers for Disease Control and Prevention. (2009a). The Fourth Korea National Health and Nutrition Examination Survey (KNHANES IV-2) (2008).

      4. Korea Centers for Disease Control and Prevention. (2009b). Data use manual of Korea National Health and Nutrition Examination Survey IV (2007).

        • Korea Ministry of Health and Welfare
        Guidelines for healthy life projects.
        • Korea National Statistical Office
        Population projection.
        • Korea National Statistical Office
        Statistics for older adults.
        • Laaksonen D.E.
        • Lakka H.M.
        • Salonen J.T.
        • Niskanen L.K.
        • Rauramaa R.
        • Lakka T.A.
        Low levels of leisure-time physical activity and cardiorespiratory fitness predict development of the metabolic syndrome.
        Diabetes Care. 2002; 25: 1612-1618
        • Laaksonen D.E.
        • Lindstrom J.
        • Lakka T.A.
        • Eriksson J.G.
        • Niskanen L.
        • Wikstrom K.
        • et al.
        Physical activity in the prevention of type 2 diabetes: the Finnish diabetes prevention study.
        Diabetes. 2005; 54: 158-165
        • Lam T.H.
        • Ho S.Y.
        • Hedley A.J.
        • Mak K.H.
        • Leung G.M.
        Leisure time physical activity and mortality in Hong Kong: case-control study of all adult deaths in 1998.
        Annals of Epidemiology. 2004; 14: 391-398
        • Lasker R.D.
        • Humphreys B.L.
        • Braithwaite W.R.
        Making a powerful connection: the health of the public and the national information infrastructure.
        • Lehtonen R.
        • Pahkinen E.
        Practical methods for design and analysis of complex surveys. 2nd ed. John Wiley & Sons, Chichester, England2004
        • Melnick A.L.
        • Fleming D.W.
        Modern geographic information systems: promise and pitfalls.
        Journal of Public Health Management and Practice. 1999; 5: viii-x
        • Matthews S.A.
        • Moudon A.V.
        • Daniel M.
        Work group II: using Geographic Information Systems for enhancing research relevant to policy on diet, physical activity, and weight.
        American Journal of Preventive Medicine. 2009; 36: S171-S176
        • Park C.
        Physical activity programming for older adults: a way to improve quality of life.
        Journal of Sport and Leisure Studies. 2009; 38: 653-662
        • Park Y.
        • Kim I.
        • Kim H.
        Factors influencing regular exercise of the elderly.
        Journal of Korean Academy of Adult Nursing. 2002; 14: 348-358
        • Pettee K.K.
        • Brach J.S.
        • Kriska A.M.
        • Boudreau R.
        • Richardson C.R.
        • Colbert L.H.
        • et al.
        Influence of marital status on physical activity levels among older adults.
        Medicine & Science in Sports & Exercise. 2006; 38: 541-546
        • Statistical Geographic Information Service
        (n.d.). Census spatial statistics data.
        • United States Department of Health and Human Services
        Healthy People 2010. Author, Washington, DC2000
        • United States Department of Health and Human Services
        Health, United States: Health and aging chart-book. Author, Washington, D.C2006
        • United States Department of Health and Human Services
        Physical activity guidelines for Americans.