About this Journal Submit a Manuscript Table of Contents
Journal of Aging Research
Volume 2013 (2013), Article ID 302163, 12 pages
http://dx.doi.org/10.1155/2013/302163
Research Article

The Use of Multiple Correspondence Analysis to Explore Associations between Categories of Qualitative Variables in Healthy Ageing

1Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, 4710-057 Braga, Portugal
2ICVS/3B’s, PT Government Associate Laboratory, Guimarães, 4710-057 Braga, Portugal
3Centro Hospital Alto Ave, EPE, 4810-055 Guimarães, Portugal

Received 30 June 2013; Revised 23 August 2013; Accepted 30 August 2013

Academic Editor: F. Richard Ferraro

Copyright © 2013 Patrício Soares Costa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. E. J. Beh, “Simple correspondence analysis: a bibliographic review,” International Statistical Review, vol. 72, no. 2, pp. 257–284, 2004. View at Scopus
  2. R. A. Johnson and D. W. Wichern, Applied Multivariate Correspondence Analysis, Prentice-Hall, Upper Saddle River, NJ, USA, 6th edition, 2007.
  3. J. F. Hair, R. L. Tatham, R. E. Anderson, and W. Black, Multivariate Data Analysis, Prentice-Hall, Upper Saddle River, NJ, USA, 5th edition, 1998.
  4. B. G. Tabachnick and L. S. Fidell, Using Multivariate Statistics, Allyn and Bacon, Boston, Mass, USA, 4th edition, 1996.
  5. S. E. Clausen, Applied Correspondence Analysis: An Introduction, Quantitative applications in the social science, Sage, Thousand Oaks, Calif, USA, 1998.
  6. M. Greenacre and T. Hastie, “The geometric interpretation of correspondence analysis,” Journal of the American Statistical Association, vol. 82, no. 398, pp. 437–447, 1987.
  7. K. M. van Meter, M. A. Schiltz, P. Cibois, and L. Mounier, “Correspondence analysis: a history and French sociological perspective,” in Correspondence Analysis in the Social Sciences: Recent Developments and Applications, M. Greenacre and J. Blasius, Eds., Academic Press, San Diego, Calif, USA, 1994.
  8. D. Aktürk, S. Gün, and T. Kumuk, “Multiple correspondence analysis technique used in analyzing the categorical data in social sciences,” Journal of Applied Sciences, vol. 7, no. 4, pp. 585–588, 2007. View at Scopus
  9. N. Sourial, C. Wolfson, B. Zhu et al., “Correspondence analysis is a useful tool to uncover the relationships among categorical variables,” Journal of Clinical Epidemiology, vol. 63, no. 6, pp. 638–646, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. P. Loslever, “Using multiple correspondence analysis with membership values when the system study yields miscellaneous datasets,” Cybernetics and Systems, vol. 40, no. 7, pp. 633–652, 2009. View at Publisher · View at Google Scholar · View at Scopus
  11. N. C. Santos, P. S. Costa, P. Cunha et al., “Mood is a key determinant of cognitive performance in community-dwelling older adults: a cross-sectional analysis,” Age, 2012. View at Publisher · View at Google Scholar
  12. A. C. Paulo, A. Sampaio, N. C. Santos et al., “Patterns of cognitive performance in healthy ageing in northern portugal: a cross-sectional analysis,” PLoS One, vol. 6, no. 9, Article ID e24553, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. K. Anstey and H. Christensen, “Education, activity, health, blood pressure and apolipoprotein E as predictors of cognitive change in old age: a review,” Gerontology, vol. 46, no. 3, pp. 163–177, 2000. View at Scopus
  14. R. A. Parslow, V. J. Lewis, and R. Nay, “Successful aging: development and testing of a multidimensional model using data from a large sample of older Australians,” Journal of the American Geriatrics Society, vol. 59, no. 11, pp. 2077–2083, 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. T. Archer, A. Fredriksson, E. Schütz, and R. M. Kostrzewa, “Influence of physical exercise on neuroimmunological functioning and health: aging and stress,” Neurotoxicity Research, vol. 20, no. 1, pp. 69–83, 2011. View at Publisher · View at Google Scholar · View at Scopus
  16. F. Marcellini, C. Giuli, R. Papa, C. Gagliardi, M. Malavolta, and E. Mocchegiani, “BMI, life-style and psychological conditions in a sample of elderly Italian men and women,” Journal of Nutrition, Health and Aging, vol. 14, no. 7, pp. 515–522, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. P. A. Reuter-Lorenz and C. Lustig, “Brain aging: reorganizing discoveries about the aging mind,” Current Opinion in Neurobiology, vol. 15, no. 2, pp. 245–251, 2005. View at Publisher · View at Google Scholar · View at Scopus
  18. T. A. Salthouse, “Selective review of cognitive aging,” Journal of the International Neuropsychological Society, vol. 16, no. 5, pp. 754–760, 2010. View at Publisher · View at Google Scholar · View at Scopus
  19. N. Sourial, C. Wolfson, H. Bergman et al., “A correspondence analysis revealed frailty deficits aggregate and are multidimensional,” Journal of Clinical Epidemiology, vol. 63, no. 6, pp. 647–654, 2010. View at Publisher · View at Google Scholar · View at Scopus
  20. P. S. Costa, N. C. Santos, P. Cunha, J. A. Palha, and N. Sousa, “The use of Bayesian latent class cluster models to classify patterns of cognitive performance in healthy ageing,” PLoS One, 2013. View at Publisher · View at Google Scholar
  21. OECD, “Country statistical profile—Portugal,” 2011, http://dx.doi.org/10.1787/csp-prt-Table-2011-1-en.
  22. M. Graffar, “Une methode de classification sociale d'echantillon des populations,” Courrier, vol. 6, pp. 455–459, 1956.
  23. M. F. Folstein, S. E. Folstein, and P. R. McHugh, “'Mini mental state'. a practical method for grading the cognitive state of patients for the clinician,” Journal of Psychiatric Research, vol. 12, no. 3, pp. 189–198, 1975. View at Publisher · View at Google Scholar · View at Scopus
  24. D. Wechsler, Wechsler Adult Intelligence Scale (WAIS-III), Harcourt Assessment, San Antonio, Tex, USA, 1997.
  25. H. Buschke, M. Sliwinski, G. Kuslansky, and R. B. Lipton, “Aging, encoding specificity, and memory change in the Double Memory Test,” Journal of the International Neuropsychological Society, vol. 1, no. 5, pp. 483–493, 1995. View at Scopus
  26. E. Strauss, E. M. S. Sherman, and O. Spreen, A Compendium of Neuropsychological Tests: Administration, Norms and Commentary, Oxford University Press, New York, N, USA, 2006.
  27. M. Lezak, D. Howieson, and D. Loring, Neuropsychological Assessment, Oxford University Press, New York, NY, USA, 2004.
  28. World Health Organization, “Waist circumference and waist-hip ratio,” Report of a WHO Expert Consultation, WHO Library Cataloguing-in-Publication Data, Geneva, Switzerland, 2008.
  29. H. Kim, “Measures of influence in correspondence analysis,” Journal of Statistical Computation and Simulation, vol. 40, pp. 3201–4217, 1992.
  30. H. Kim, “Influence functions in multiple correspondence analysis,” Korean Journal of Applied Statistics, vol. 7, no. 1, pp. 69–74, 1994.
  31. W. J. Krzanowski, “Attribute selection in correspondence analysis of incidence matrices,” Applied Statistics, vol. 42, no. 3, pp. 529–541, 1993.
  32. J. C. Gower, “Discussion of ”a combined approach to contingency table analysis using correspondence analysis and log-linear analysis”,” Applied Statistics, vol. 38, no. 1, pp. 249–292, 1989.
  33. D. B. Rubin, “Inference and missing data,” Biometrika, vol. 63, no. 3, pp. 581–592, 1976. View at Scopus
  34. P. Kline, An Easy Guide to Factor Analysis, Routledge, London, UK, 2002.
  35. R. J. A. Little and D. B. Rubin, Statistical Analysis with Missing Data, Wiley, Hoboken, NJ, USA, 2nd edition, 2002.
  36. R. B. Cattell, “The meaning and strategic use of factor analysis,” in Handbook of Multivariate Experimental Psychology, R. B. Cattell, Ed., Rand McNally, Chicago, Ill, USA, 1996.
  37. A. Gifi, Non-Linear Multivariate Analysis,, John Willey & Sons, Chichester, UK, 1996.
  38. L. Lebart, A. Morineau, and K. M. Warwick, Multivariate Descriptive Statistical Analysis, Wiley, New York, NY, USA, 1984.
  39. J. Beddington, C. L. Cooper, J. Field et al., “The mental wealth of nations,” Nature, vol. 455, no. 7216, pp. 1057–1060, 2008. View at Publisher · View at Google Scholar · View at Scopus
  40. L. Ferrucci, F. Giallauria, and J. M. Guralnik, “Epidemiology of Aging,” Radiologic Clinics of North America, vol. 46, no. 4, pp. 643–652, 2008. View at Publisher · View at Google Scholar · View at Scopus
  41. N. Yamamoto, G. Yamanaka, E. Takasugi et al., “Lifestyle intervention reversed cognitive function in aged people with diabetes mellitus: two-year follow up,” Diabetes Research and Clinical Practice, vol. 85, no. 3, pp. 343–346, 2009. View at Publisher · View at Google Scholar · View at Scopus
  42. K. G. M. M. Alberti and P. Zimmet, “The metabolic syndrome—a new worldwide definition,” The Lancet, vol. 366, no. 9491, pp. 1059–1062, 2005. View at Publisher · View at Google Scholar · View at Scopus
  43. T. N. Akbaraly, M. Kivimaki, M. J. Shipley et al., “Metabolic syndrome over 10 years and cognitive functioning in late midlife: the Whitehall II study,” Diabetes Care, vol. 33, no. 1, pp. 84–89, 2010. View at Publisher · View at Google Scholar · View at Scopus
  44. M. Kivipelto, E.-L. Helkala, T. Hänninen et al., “Midlife vascular risk factors and late-life mild cognitive impairment: a population-based study,” Neurology, vol. 56, no. 12, pp. 1683–1689, 2001. View at Scopus
  45. I. Skoog, B. Lernfelt, S. Landahl et al., “15-year longitudinal study of blood pressure and dementia,” Lancet, vol. 347, no. 9009, pp. 1141–1145, 1996. View at Scopus
  46. M. F. Elias, P. K. Elias, L. M. Sullivan, P. A. Wolf, and R. B. D'Agostino, “Obesity, diabetes and cognitive deficit: the Framingham Heart Study,” Neurobiology of Aging, vol. 26, supplement 1, pp. S11–S16, 2005. View at Publisher · View at Google Scholar · View at Scopus
  47. W. Dai, O. L. Lopez, O. T. Carmichael, J. T. Becker, L. H. Kuller, and H. M. Gach, “Abnormal regional cerebral blood flow in cognitively normal elderly subjects with hypertension,” Stroke, vol. 39, no. 2, pp. 349–354, 2008. View at Publisher · View at Google Scholar · View at Scopus
  48. G. A. Dore, M. F. Elias, M. A. Robbins, M. M. Budge, and P. K. Elias, “Relation between central adiposity and cognitive function in the Maine-Syracuse study: attenuation by physical activity,” Annals of Behavioral Medicine, vol. 35, no. 3, pp. 341–350, 2008. View at Publisher · View at Google Scholar · View at Scopus
  49. J. Gunstad, A. Lhotsky, C. R. Wendell, L. Ferrucci, and A. B. Zonderman, “Longitudinal examination of obesity and cognitive function: results from the baltimore longitudinal study of aging,” Neuroepidemiology, vol. 34, no. 4, pp. 222–229, 2010. View at Publisher · View at Google Scholar · View at Scopus
  50. C. H. van Gool, G. I. J. M. Kempen, B. W. J. H. Penninx, D. J. H. Deeg, A. T. F. Beekman, and J. T. M. van Eijk, “Relationship between changes in depressive symptoms and unhealthy lifestyles in late middle aged and older persons: results from the longitudinal aging study Amsterdam,” Age and Ageing, vol. 32, no. 1, pp. 81–87, 2003. View at Publisher · View at Google Scholar · View at Scopus
  51. A. Dregan, R. Stewart, and M. C. Gulliford, “Cardiovascular risk factors and cognitive decline in adults aged 50 and over: a population-based cohort study,” Age Ageing, vol. 42, no. 3, pp. 338–345, 2013. View at Publisher · View at Google Scholar
  52. I. Lang, R. B. Wallace, F. A. Huppert, and D. Melzer, “Moderate alcohol consumption in older adults is associated with better cognition and well-being than abstinence,” Age and Ageing, vol. 36, no. 3, pp. 256–261, 2007. View at Publisher · View at Google Scholar · View at Scopus
  53. A. L. Gross, G. W. Rebok, D. E. Ford et al., “Alcohol consumption and domain-specific cognitive function in older adults: Longitudinal data from the johns hopkins precursors study,” Journals of Gerontology B, vol. 66, no. 1, pp. 39–47, 2011. View at Publisher · View at Google Scholar · View at Scopus
  54. G. A. Greendale, C. A. Derby, and P. M. Maki, “Perimenopause and cognition,” Obstetrics & Gynecology Clinics of North America, vol. 38, no. 3, pp. 519–535, 2011. View at Publisher · View at Google Scholar · View at Scopus
  55. B. F. M. Bakker, “A new measure of social status for men and women: the social distance scale,” Netherlands Journal of Social Sciences, vol. 29, no. 2, pp. 113–129, 1993.
  56. C. Guinot, J. Latreille, D. Malvy et al., “Use of multiple correspondence analysis and cluster analysis to study dietary behaviour: food consumption questionnaire in the SU.VI.MAX. cohort,” European Journal of Epidemiology, vol. 17, no. 6, pp. 505–516, 2001. View at Publisher · View at Google Scholar · View at Scopus
  57. M. L. Burton, E. Greenberger, and C. Hayward, “Mapping the ethnic landscape: personal beliefs about own group's and other groups' traits,” Cross-Cultural Research, vol. 39, no. 4, pp. 351–379, 2005. View at Publisher · View at Google Scholar · View at Scopus
  58. S. M. Cavalcante, L. R. Kerr, S. M. Brignol et al., “Sociodemographic factors and health in a population of children living in families infected with HIV in Fortaleza and Salvador, Brazil,” AIDS Care, vol. 25, no. 5, pp. 550–558, 2012.
  59. D. B. Panagiotakos and C. Pitsavos, “Interpretation of epidemiological data using multiple correspondence analysis and log-linear models,” Journal of Data Science, vol. 2, pp. 75–86, 2004.
  60. L. D. Howe, B. Galobardes, A. Matijasevich et al., “Measuring socio-economic position for epidemiological studies in low- and middle-income countries: a methods of measurement in epidemiology paper,” International Journal of Epidemiology, vol. 41, no. 3, pp. 871–886, 2012.
  61. P. Traissac and Y. Martin-Prevel, “Alternatives to principal components analysis to derive asset-based indices to measure socio-economic position in low- and middle-income countries: the case for multiple correspondence analysis,” International Journal of Epidemiology, vol. 41, no. 4, pp. 1207–1208, 2012.
  62. P. G. M. Van der Heijden, “Correspondence Analysis of Longitudinal Data,” in Encyclopedia of Biostatistics, P. Armitage and T. Colton, Eds., John Wiley & Sons, Chichester, UK, 2005.