2015 6 213 POPULATION & ECONOMICS No. 6 2015 Tot. No. 213 CLHLS 100871 CLHLS C92-05 DOI 10. 3969 /j. issn. 1000-4149. 2015. 06. 001 A 1000-4149 2015 06-0001 - 11 The Effect of Health Changes on Self-reported Quality of Life of the Elderly in China Fixed Effects Model Analysis Based on CLHLS Data LI Jianxin LIU Baozhong Department of Sociology Peking University Beijing 100871 China Abstract The previous studies have found that the health status of the elderly was closely related to self-reported quality of life. But these studies generally used the cross-section data and also tended to choose the single dimensional index to measure the health status. Using Chinese Longitudinal Healthy Longevity Survey CLHLS data from multi dimensions of health including body health mental health and self-rated health this paper tested the effect of health changes on the self-reported quality of life of the elderly in China with the fixed effects model. Our study showed that the improvements of body health mental health and self-rated health among the elderly could improve 2015-04 - 26 2015-07 - 20 71110107025 71233001 1
2015 6 their levels of quality of life. However three dimensional indexes exerted different influences. The mental health and self-rated health played a mediating effect between body health and self-reported quality of life. Keywords elderly health self-reported quality of life fixed effects model 1 - HRQOL 3 4-5 Smith 6 7-8 OLS CLHLS 4 9-10 11 Gill Feinstein 12 Diener Suh 13 14 2
15-16 17 18 Gayman 19 Livneh Antonak 20 Schieman Turner 15 4 21 Jylh 22 23 24-25 26 27 28 Saeedian 29 1 3
2015 6 1 1. CLHLS 2008 2011 22 85% 30 7093 14186 6869 13738 4012 2857 5714 ADL CLHLS Katz 31 1 = 2 = 3 = 4
1-5 Cronbach s Alpha 2008 0. 615 2011 0. 637 2008 2011 ADL 1 % 2008 2011 = 1 50. 00 49. 53 50. 47 = 0 50. 00 50. 47 49. 53 ADL 2. 92 2. 96 2. 86 0. 27 0. 17 0. 34 3. 68 3. 64 3. 71 60 0. 56 0. 53 0. 58 = 1 44. 29 48. 27 40. 32 = 0 55. 71 51. 73 59. 68 82. 16 80. 64 83. 68 10. 46 10. 37 10. 34 = 1 53. 27 53. 27 53. 27 = 0 46. 77 46. 73 46. 73 = 1 36. 86 36. 86 36. 86 = 0 63. 14 63. 14 63. 14 = 1 41. 64 44. 31 38. 92 = 0 58. 36 55. 69 61. 08 = 1 44. 87 44. 87 44. 87 = 0 55. 13 55. 13 55. 13 60 = 1 29. 37 29. 37 29. 37 = 0 70. 63 70. 63 70. 63 = 1 77. 06 77. 49 76. 62 = 0 22. 94 22. 51 23. 38 2. 94 2. 93 2. 95 0. 63 0. 60 0. 65 = 1 93. 91 93. 73 94. 08 = 0 6. 09 6. 27 5. 92 5714 2857 2857 1-5 1 2. Logit 5
2015 6 32 Hausman Ln p i1 / 1 - p i1 = u i1 + β 1 health i1 + β 2 control A i1 + β 3 control B i + v i + ε i1 1 Ln p i2 / 1 - p i2 = u i2 + β 1 health i2 + β 2 control A i2 + β 3 control B i + v i + ε i2 2 2 1 Ln Pr y i1 = 0 y i2 = 1 /Pr y i1 = 1 y i2 = 0 = u i2 - u i1 + β 1 health i2 - health i1 + β 2 control A i2 - control A i1 + ε i2 - ε i1 3 1 2008 t = 1 2 2011 t = 2 y it i y 0 1 P it y it = 1 u it health it control A it control B i 60 v i ε it β 1 β 2 β 3 3 2008 2011 1 ADL 2 1 3 2 Baron Kenny 33 1. 2 2 1 1 62% e 0. 480-1 = 0. 62 sig < 0. 001 2 1 0. 480 0. 231 sig < 0. 001 2008 2011 3 2 0. 886 0. 639 6
sig < 0. 001 2011 2008 4. 43 e 1. 490 2008 2011 3. 43 e 1. 490-1 ADL 2 1 2 3 1 + 2 + ADL 0. 480 *** 0. 127 0. 231 0. 133 0. 009 0. 141 0. 886 *** 0. 064 0. 639 *** 0. 070 1. 490 *** 0. 078 0. 015 0. 014-0. 009 0. 014 0. 032 * 0. 016-0. 202 0. 126-0. 292 * 0. 131-0. 347 * 0. 143 0. 572 *** 0. 080 0. 433 *** 0. 084 0. 439 *** 0. 091 0. 743 *** 0. 061 0. 668 *** 0. 063 0. 571 *** 0. 068 0. 547 *** 0. 143 0. 494 *** 0. 149 0. 363 * 0. 159 LR Chi2 417. 56 629. 23 1084. 38 Df 6 7 8 LR Chi2 211. 67 455. 15 % 50. 69 72. 33 Sig 0. 000 0. 000 0. 000 5714 5714 5714 1. *** sig < 0. 001 ** sig < 0. 01 * sig < 0. 05 2. with-group variance 2 3. 2 LR Chi2 = 2 LR Chi2-1 LR Chi2 3 LR Chi2 = 3 LR Chi2-2LR Chi2 4. 2 = 2 LR Chi2 / 1 LR Chi2 3 = 3 LR Chi2 / 1 LR Chi2 2008 2011 2. 2 2 3 LR Chi2 211. 67 455. 15 50. 69% 72. 33% 33 2 1 3 4 5 2 2 3 7
2015 6 3 4 5 2 3 ADL 0. 255 *** 0. 025 0. 838 *** 0. 161 1. 038 *** 0. 065 Sig 0. 000 0. 000 13738 5922 1. *** sig < 0. 001 ** sig < 0. 01 * sig < 0. 05 2. 4 5 2 2 3. 4 2 3 2 ADL 1. ADL B = 0. 480 *** B = - 0. 009 2. 34 Logit 3 6 7 CLHLS 2008 2011 8
4 6 7 8 ADL - 0. 184 * 0. 079-0. 186 * 0. 082-0. 132 0. 112 0. 660 *** 0. 041 0. 690 *** 0. 044 0. 537 *** 0. 059 1. 323 *** 0. 042 1. 386 *** 0. 049 1. 260 *** 0. 060 Sig 0. 000 0. 000 0. 000 13738 13738 5714 1. *** sig < 0. 001 ** sig < 0. 01 * sig < 0. 05 2. 6 7 2 35 36 Bishop 7 37 38 39 1 TORRANCE G W. 6 593-600. Utility approach to measuring health-related quality of life J. Journal of Chronic Diseases 1987 40 2 PATRICK D L ERICKSON P. Assessing health-related quality of life for clinical decision-making M / / WALKER S R ROESER R M. Quality of Life Assessment Key Issues in the 1990s. Netherlands Kluwer Academic Publishers 1993 11-63. 3 GUATT G H FEENY D H PATRICK D L. Measuring health-related quality of life J. Annals of Internal Medicine 1993 118 8 622-629. 4. J. 2007 3 50-60. 9
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