Socioeconomic Inequalities in Frailty in Hong Kong, China: A 14-Year Longitudinal Cohort Study
Abstract
1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Exposure
2.3. Outcome
2.4. Covariate
2.4.1. Demographics
2.4.2. Objective Measures of SES
2.4.3. Medical History
2.4.4. Lifestyle
2.4.5. Health-Related Quality of Life (Mental Component)
2.4.6. Cognitive Function
2.5. Data Analysis
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Fried, L.P.; Tangen, C.M.; Walston, J.; Newman, A.B.; Hirsch, C.; Gottdiener, J.; Seeman, T.; Tracy, R.; Kop, W.J.; Burke, G.; et al. Frailty in older adults: Evidence for a phenotype. J. Gerontol. Ser. A Biol. Sci. Med. Sci. 2001, 56, M146–M156. [Google Scholar] [CrossRef] [PubMed]
- Clegg, A.; Young, J.; Iliffe, S.; Rikkert, M.O.; Rockwood, K. Frailty in elderly people. Lancet 2013, 381, 752–762. [Google Scholar] [CrossRef]
- World Health Organization. WHO Clinical Consortium on Healthy Ageing Topic Focus: Frailty and Intrinsic Capacity; Report of Consortium Meeting; WHO: Geneva, Switzerland, 2017. [Google Scholar]
- Moody, D.; Lyndon, H.; Stevens, G. Toolkit for General Practice in Supporting Older People Living with Frailty; NHS England: Leeds, UK, 2017. [Google Scholar]
- National Health Service. Supporting Routine Frailty Identification through the GP Contract 2017/2018; NHS England: Leeds, UK, 2018; Available online: https://www.england.nhs.uk/wp-content/uploads/2017/04/supporting-guidance-on-frailty-update-sept-2017.pdf (accessed on 12 March 2018).
- National Health Service. NHS England Standard General Medical Services Contract; NHS England: Leeds, UK, 2018; Available online: https://www.england.nhs.uk/wp-content/uploads/2018/01/17-18-gms-contract.pdf (accessed on 12 March 2018).
- Syddall, H.; Roberts, H.C.; Evandrou, M.; Cooper, C.; Bergman, H.; Sayer, A.A. Prevalence and correlates of frailty among community-dwelling older men and women: Findings from the Hertfordshire Cohort study. Age Ageing 2010, 39, 197–203. [Google Scholar] [CrossRef]
- Woo, J.; Chan, R.; Leung, J.; Wong, M. Relative contributions of geographic, socioeconomic, and lifestyle factors to quality of life, frailty, and mortality in elderly. PLoS ONE 2010, 5, e8775. [Google Scholar] [CrossRef]
- Marengoni, A.; Fratiglioni, L.; Bandinelli, S.; Ferrucci, L. Socioeconomic status during lifetime and cognitive impairment no-dementia in late life: The population-based aging in the Chianti area (InCHIANTI) study. J. Alzheimer’s Dis. 2011, 24, 559–568. [Google Scholar] [CrossRef] [PubMed]
- Puts, M.T.E.; Toubasi, S.; Andrew, M.K.; Ashe, M.C.; Ploeg, J.; Atkinson, E.; Ayala, A.P.; Roy, A.; Rodriguez Monforte, M.; Bergman, H.; et al. Interventions to prevent or reduce the level of frailty in community-dwelling older adults: A scoping review of the literature and international policies. Age Ageing 2017, 46, 383–392. [Google Scholar] [CrossRef] [PubMed]
- Mackenbach, J.P.; Stirbu, I.; Roskam, A.J.R.; Schaap, M.M.; Menvielle, G.; Leinsalu, M.; Kunst, A.E.; Socioec, E.U.W.G. Socioeconomic inequalities in health in 22 European countries. N. Engl. J. Med. 2008, 358, 2468–2481. [Google Scholar] [CrossRef] [PubMed]
- Stringhini, S.; Sabia, S.; Shipley, M.; Brunner, E.; Nabi, H.; Kivimaki, M.; Singh-Manoux, A. Association of socioeconomic position with health behaviors and mortality. JAMA J. Am. Med. Assoc. 2010, 303, 1159–1166. [Google Scholar] [CrossRef]
- Woo, J.; Goggins, W.; Sham, A.; Ho, S.C. Social determinants of frailty. Gerontology 2005, 51, 402–408. [Google Scholar] [CrossRef]
- Alvarado, B.E.; Zunzunegui, M.V.; Beland, F.; Bamvita, J.M. Life course social and health conditions linked to frailty in Latin American older men and women. J. Gerontol. Ser. A Biol. Sci. Med. Sci. 2008, 63, 1399–1406. [Google Scholar] [CrossRef]
- Szanton, S.L.; Seplaki, C.L.; Thorpe, R.J.; Allen, J.K.; Fried, L.P. Socioeconomic status is associated with frailty: The women’s health and aging studies. J. Epidemiol. Commun. Health 2010, 64, 63–67. [Google Scholar] [CrossRef] [PubMed]
- Casale-Martinez, R.I.; Navarrete-Reyes, A.P.; Avila-Funes, J.A. Social determinants of frailty in elderly Mexican community-dwelling adults. J. Am. Geriatr. Soc. 2012, 60, 800–802. [Google Scholar] [CrossRef]
- Etman, A.; Burdorf, A.; Van der Cammen, T.J.M.; Mackenbach, J.P.; Van Lenthe, F.J. Socio-demographic determinants of worsening in frailty among community-dwelling older people in 11 European countries. J. Epidemiol. Commun. Health 2012, 66, 1116–1121. [Google Scholar] [CrossRef] [PubMed]
- Hoogendijk, E.O.; van Hout, H.P.J.; Heymans, M.W.; van der Horst, H.E.; Frijters, D.H.M.; van Groenou, M.I.B.; Deeg, D.J.H.; Huisman, M. Explaining the association between educational level and frailty in older adults: Results from a 13-year longitudinal study in the Netherlands. Ann. Epidemiol. 2014, 24, 538–544. [Google Scholar] [CrossRef] [PubMed]
- Gardiner, P.A.; Mishra, G.D.; Dobson, A.J. The effect of socioeconomic status across adulthood on trajectories of frailty in older women. J. Am. Med. Dir. Assoc. 2016, 17, e371–e373. [Google Scholar] [CrossRef]
- Stolz, E.; Mayerl, H.; Waxenegger, A.; Rasky, E.; Freidl, W. Impact of socioeconomic position on frailty trajectories in 10 European countries: Evidence from the survey of health, ageing and retirement in Europe (2004–2013). J. Epidemiol. Commun. Health 2017, 71, 73–80. [Google Scholar] [CrossRef]
- Hoogendijk, E.O.; Heymans, M.W.; Deeg, D.J.H.; Huisman, M. Socioeconomic inequalities in frailty among older adults: Results from a 10-year longitudinal study in the Netherlands. Gerontology 2018, 64, 157–164. [Google Scholar] [CrossRef]
- Singh-Manoux, A.; Adler, N.E.; Marmot, M.G. Subjective social status: Its determinants and its association with measures of ill-health in the Whitehall II study. Soc. Sci. Med. 2003, 56, 1321–1333. [Google Scholar] [CrossRef]
- Demakakos, P.; Nazroo, J.; Breeze, E.; Marmot, M. Socioeconomic status and health: The role of subjective social status. Soc. Sci. Med. 2008, 67, 330–340. [Google Scholar] [CrossRef]
- Marmot, M.; Wilkinson, R.G. Psychosocial and material pathways in the relation between income and health: A response to Lynch et al. BMJ 2001, 322, 1233–1236. [Google Scholar] [CrossRef]
- Singh-Manoux, A.; Marmot, M.G.; Adler, N.E. Does subjective social status predict health and change in health status better than objective status? Psychosom. Med. 2005, 67, 855–861. [Google Scholar] [CrossRef] [PubMed]
- Woo, J.; Lynn, H.; Leung, J.; Wong, S.Y. Self-perceived social status and health in older Hong Kong Chinese women compared with men. Women’s Health 2008, 48, 209–234. [Google Scholar] [CrossRef] [PubMed]
- Chen, B.; Covinsky, K.E.; Cenzer, I.S.; Adler, N.; Williams, B.A. Subjective social status and functional decline in older adults. J. Gen. Intern. Med. 2012, 27, 693–699. [Google Scholar] [CrossRef] [PubMed]
- Zhang, F.; Fung, H.; Kwok, T. Spouse’s subjective social status predicts older adults’ prospective cognitive functioning. Aging Mental Health 2019, 23, 277–285. [Google Scholar] [CrossRef] [PubMed]
- Demakakos, P.; Biddulph, J.P.; de Oliveira, C.; Tsakos, G.; Marmot, M.G. Subjective social status and mortality: The English longitudinal study of ageing. Eur. J. Epidemiol. 2018, 33, 729–739. [Google Scholar] [CrossRef] [PubMed]
- Wong, S.Y.S.; Kwok, T.; Woo, J.; Lynn, H.; Griffith, J.F.; Leung, J.; Tang, Y.Y.N.; Leung, P.C. Bone mineral density and the risk of peripheral arterial disease in men and women: Results from Mr. and Ms Os, Hong Kong. Osteoporos. Int. 2005, 16, 1933–1938. [Google Scholar] [CrossRef]
- Adler, N.E.; Epel, E.S.; Castellazzo, G.; Ickovics, J.R. Relationship of subjective and objective social status with psychological and physiological functioning: Preliminary data in healthy white women. Health Psychol. 2000, 19, 586–592. [Google Scholar] [CrossRef]
- Washburn, R.A.; Smith, K.W.; Jette, A.M.; Janney, C.A. The physical-activity scale for the elderly (pase)—Development and evaluation. J. Clin. Epidemiol. 1993, 46, 153–162. [Google Scholar] [CrossRef]
- Kim, S.; Haines, P.S.; Siega-Riz, A.M.; Popkin, B.M. The Diet Quality Index-International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States. J. Nutr. 2003, 133, 3476–3484. [Google Scholar] [CrossRef]
- Woo, J.; Cheung, B.; Ho, S.; Sham, A.; Lam, T.H. Influence of dietary pattern on the development of overweight in a Chinese population. Eur. J. Clin. Nutr. 2008, 62, 480–487. [Google Scholar] [CrossRef]
- Haywood, K.L.; Garratt, A.M.; Fitzpatrick, R. Quality of life in older people: A structured review of generic self-assessed health instruments. Qual. Life Res. 2005, 14, 1651–1668. [Google Scholar] [CrossRef] [PubMed]
- Lam, C.L.K.; Tse, E.Y.Y.; Gandek, B. Is the standard SF-12 health survey valid and equivalent for a Chinese population? Qual. Life Res. 2005, 14, 539–547. [Google Scholar] [CrossRef] [PubMed]
- Folstein, M.F.; Folstein, S.E.; McHugh, P.R. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 1975, 12, 189–198. [Google Scholar] [CrossRef]
- Chiu, H.F.; Lee, H.C.; Chung, W.S.; Kwong, P.K. Reliability and validity of the cantonese version of the mini-mental state examination—A preliminary study. J. Hong Kong Coll. Psychiatr. 1994, 4, 25–28. [Google Scholar]
- van Rossum, C.T.M.; Shipley, M.J.; van de Mheen, H.; Grobbee, D.E.; Marmot, M.G. Employment grade differences in cause specific mortality. A 25 year follow up of civil servants from the first Whitehall study. J. Epidemiol. Commun. Health 2000, 54, 178–184. [Google Scholar] [CrossRef]
- Dunn, J.R.; Veenstra, G.; Ross, N. Psychosocial and neo-material dimensions of SES and health revisited: Predictors of self-rated health in a Canadian national survey. Soc. Sci. Med. 2006, 62, 1465–1473. [Google Scholar] [CrossRef]
- Prentice, D.A.; Carranza, E. What women and men should be, shouldn’t be, are allowed to be, and don’t have to be: The contents of prescriptive gender stereotypes. Psychol. Women Q. 2002, 26, 269–281. [Google Scholar] [CrossRef]
- Canetto, S.S.; Kaminski, P.L.; Felicio, D.M. Typical and optimal aging in women and men: Is there a double standard? Int. J. Aging Hum. Dev. 1995, 40, 187–207. [Google Scholar] [CrossRef]
- Matthews, S.; Manor, O.; Power, C. Social inequalities in health: Are there gender differences? Soc. Sci. Med. 1999, 48, 49–60. [Google Scholar] [CrossRef]
- Wallerstein, N. What is the Evidence on Effectiveness of Empowerment to Improve Health? Health Evidence Network Report; WHO Regional Office for Europe: Copenhagen, Denmark, 2006; Available online: http://wwweurowhoint/Document/E88086pdf (accessed on 8 October 2019).
- Zimmerman, M.A. Empowerment theory: Psychological, organizational and community levels of analysis. In Handbook of Community Psychology; Rappaport, J., Seidman, E., Eds.; Kluwer Academic/Plenum: New York, NY, USA, 2000; pp. 43–63. [Google Scholar]
- Barnett, R.C.; Hyde, J.S. Women, men, work, and family—An expansionist theory. Am. Psychol. 2001, 56, 781–796. [Google Scholar] [CrossRef]
- Gordon, E.H.; Peel, N.M.; Samanta, M.; Theou, O.; Howlett, S.E.; Hubbard, R.E. Sex differences in frailty: A systematic review and meta-analysis. Exp. Gerontol. 2017, 89, 30–40. [Google Scholar] [CrossRef] [PubMed]
- Poulton, R.; Caspi, A.; Milne, B.J.; Thomson, W.M.; Taylor, A.; Sears, M.R.; Moffitt, T.E. Association between children’s experience of socioeconomic disadvantage and adult health: A life-course study. Lancet 2002, 360, 1640–1645. [Google Scholar] [CrossRef]
Subjective Social Status | Frailty Status at Year 14 | |||||||
---|---|---|---|---|---|---|---|---|
High (n = 414) | Middle (n = 228) | Low (n = 52) | Robust (n = 64) | Pre-Frail (n = 419) | Frail (n = 211) | |||
Variables | Mean ± SD/n (%) | Mean ± SD/n (%) | Mean ± SD/n (%) | P | Mean ± SD/n (%) | Mean ± SD/n (%) | Mean ± SD/n (%) | P |
Demographics | ||||||||
Age, years | 69.7 ± 3.5 | 69.7 ± 3.7 | 69.2 ± 3.3 | 0.551 | 67.2 ± 2.2 | 69.3 ± 3.2 | 71.2 ± 3.9 | <0.001 |
Sex | ||||||||
Men | 182 (44.0) | 127 (55.7) | 37 (71.2) | <0.001 | 38 (59.4) | 230 (54.9) | 78 (37.0) | <0.001 |
Women | 232 (56.0) | 101 (44.3) | 15 (28.8) | 26 (40.6) | 189 (45.1) | 133 (63.0) | ||
Marital status | ||||||||
Married | 322 (77.8) | 186 (81.6) | 47 (90.4) | 0.077 | 58 (90.6) | 343 (81.9) | 154 (73.0) | 0.003 |
Non-married (single, divorced, separated) | 92 (22.2) | 42 (18.4) | 5 (9.6) | 6 (9.4) | 76 (18.1) | 57 (27.0) | ||
Objective socioeconomic status | ||||||||
Educational level | ||||||||
At least completed primary | 232 (56.0) | 120 (52.6) | 26 (50.0) | 0.119 | 40 (62.5) | 248 (59.2) | 90 (42.7) | 0.001 |
Some primary education | 112 (27.1) | 78 (34.2) | 21 (40.4) | 16 (25.0) | 120 (28.6) | 75 (35.5) | ||
No education | 70 (16.9) | 30 (13.2) | 5 (9.6) | 8 (12.5) | 51 (12.2) | 46 (21.8) | ||
Maximum life-time income | ||||||||
Quartile 4 ≥HKD$14,000 | 97 (29.0) | 40 (21.5) | 12 (26.7) | 0.328 | 19 (35.2) | 101 (29.3) | 29 (17.4) | <0.001 |
Quartile 3 HKD$8000–13,999 | 79 (23.6) | 61 (32.8) | 13 (28.9) | 20 (37.0) | 95 (27.5) | 38 (22.8) | ||
Quartile 2 HKD$2500–7900 | 77 (23.0) | 45 (24.2) | 10 (22.2) | 11 (20.4) | 72 (20.9) | 49 (29.3) | ||
Quartile 1 HKD$0–2499 | 82 (24.5) | 40 (21.5) | 10 (22.2) | 4 (7.4) | 77 (22.3) | 51 (30.5) | ||
Medical history | ||||||||
Hypertension | ||||||||
No | 251 (60.6) | 137 (60.1) | 31 (59.6) | 0.984 | 48 (75.0) | 267 (63.7) | 104 (49.3) | <0.001 |
Yes | 163 (39.4) | 91 (39.9) | 21 (40.4) | 16 (25.0) | 152 (36.3) | 107 (50.7) | ||
Diabetes | ||||||||
No | 357 (86.2) | 200 (87.7) | 42 (80.8) | 0.420 | 59 (92.2) | 370 (88.3) | 170 (80.6) | 0.01 |
Yes | 57 (13.8) | 28 (12.3) | 10 (19.2) | 5 (7.8) | 49 (11.7) | 41 (19.4) | ||
Stroke | ||||||||
No | 399 (96.4) | 226 (99.1) | 49 (94.2) | 0.060 | 63 (98.4) | 411 (98.1) | 200 (94.8) | 0.052 |
Yes | 15 (3.6) | 2 (0.9) | 3 (5.8) | 1 (1.6) | 8 (1.9) | 11 (5.2) | ||
Lifestyle | ||||||||
Current smoker | ||||||||
No | 397 (95.9) | 222 (97.4) | 50 (96.2) | 0.628 | 61 (95.3) | 403 (96.2) | 205 (97.2) | 0.732 |
Yes | 17 (4.1) | 6 (2.6) | 2 (3.8) | 3 (4.7) | 16 (3.8) | 6 (2.8) | ||
Current drinker | ||||||||
No | 199 (48.1) | 91 (39.9) | 18 (34.6) | 0.047 | 23 (35.9) | 184 (43.9) | 101 (47.9) | 0.232 |
Yes | 215 (51.9) | 137 (60.1) | 34 (65.4) | 41 (64.1) | 235 (56.1) | 110 (52.1) | ||
Physical activity, PASE score | 106.7 ± 39.8 | 114.6 ± 47.7 | 115.7 ± 47.9 | 0.052 | 116.1 ± 42.0 | 112.0 ± 44.3 | 104.2 ± 41.3 | 0.052 |
Diet quality, DQI | 66.0 ± 9.2 | 65.9 ± 9.0 | 66.5 ± 10.0 | 0.904 | 66.2 ± 8.7 | 65.7 ± 9.3 | 66.5 ± 9.1 | 0.651 |
BMI, kg/m2 | 24.0 ± 2.8 | 23.8 ± 2.8 | 24.0 ± 2.7 | 0.746 | 23.9 ± 2.4 | 23.6 ± 2.5 | 24.6 ± 3.3 | <0.001 |
Mental health | ||||||||
SF-12 MCS score | 56.7 ± 5.8 | 56.9 ± 5.8 | 55.5 ± 5.8 | 0.286 | 56.1 ± 6.0 | 56.7 ± 5.9 | 56.7 ± 5.6 | 0.744 |
cognitive function | ||||||||
MMSE score | 26.8 ± 3.0 | 26.9 ± 2.8 | 27.7 ± 2.2 | 0.130 | 27.2 ± 2.9 | 27.1 ± 2.8 | 26.4 ± 3.1 | 0.010 |
Variables | Men (n = 346) | Women (n = 348) | |||||
---|---|---|---|---|---|---|---|
Subjective Social Status | Subjective Social Status | ||||||
High (n = 182) | Middle (n = 127) | Low (n = 37) | High (n = 232) | Low to Middle (n = 116) | |||
n (%) | P | n (%) | P | ||||
Educational level | |||||||
At least completed primary | 139 (76.4) | 90 (70.9) | 20 (54.1) | 0.064 | 93 (40.1) | 30 (25.9) | 0.132 |
Some primary | 36 (19.8) | 34 (26.8) | 15 (40.5) | 76 (32.8) | 50 (43.1) | ||
No education | 7 (3.8) | 3 (2.4) | 2 (5.4) | 63 (27.2) | 36 (31.0) | ||
Maximum life-time income | |||||||
Quartile 4 ≥HKD$14,000 | 78 (47.6) | 39 (34.2) | 12 (37.5) | 0.240 | 44 (25.7) | 16 (18.8) | 0.405 |
Quartile 3 HKD$8000–13,999 | 54 (32.9) | 47 (41.2) | 12 (37.5) | ||||
Quartile 2 HKD$2500–7900 | 25 (15.2) | 20 (17.5) | 4 (12.5) | 52 (30.4) | 31 (36.5) | ||
Quartile 1 HKD$0–2499 | 7 (4.3) | 8 (7.0) | 4 (12.5) | 75 (43.9) | 38 (44.7) |
Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | |
---|---|---|---|---|---|---|---|
Variables | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) |
Socioeconomic status | |||||||
Subjective social status (ref = High) | |||||||
Middle | 1.69 (1.21–2.38) | 1.69 (1.21–2.38) | 1.83 (1.24–2.68) | 1.97 (1.33–2.92) | 2.03 (1.36–3.02) | 2.03 (1.36–3.01) | 2.03 (1.36–3.02) |
Low | 2.43 (1.33–4.42) | 2.44 (1.34–4.44) | 2.43 (1.26–4.68) | 2.29 (1.17–4.47) | 2.30 (1.17–4.49) | 2.35 (1.20–4.61) | 2.34 (1.19–4.60) |
Socio-demographics | |||||||
Age | 1.22 (1.17–1.28) | 1.22 (1.16–1.28) | 1.22 (1.15–1.29) | 1.22 (1.15–1.29) | 1.22 (1.15–1.29) | 1.22 (1.15–1.29) | 1.22 (1.15–1.29) |
Female (ref = Male) | 2.15 (1.56–2.96) | 2.08 (1.48–2.92) | 2.04 (1.29–3.24) | 2.01 (1.25–3.21) | 2.15 (1.29–3.57) | 2.16 (1.30–3.60) | 2.17 (1.30–3.62) |
Non-married (single, divorced, separated) (ref = Married) | 1.12 (0.74–1.70) | 0.95 (0.58–1.56) | 0.88 (0.53–1.46) | 0.89 (0.54–1.48) | 0.90 (0.54–1.50) | 0.90 (0.54–1.50) | |
Educational level (ref = At least completed primary) | |||||||
Some primary | 1.08 (0.71–1.64) | 1.06 (0.69–1.61) | 1.02 (0.66–1.56) | 1.00 (0.65–1.54) | 1.01 (0.65–1.56) | ||
No education | 1.25 (0.70–2.25) | 1.48 (0.81–2.71) | 1.31 (0.71–2.43) | 1.30 (0.70–2.41) | 1.34 (0.68–2.62) | ||
Maximum life-time income (ref = Quartile 4 ≥HKD$14,000) | |||||||
Quartile 3 HKD$8000–13,999 | 0.82 (0.50–1.34) | 0.82 (0.50–1.35) | 0.83 (0.50–1.37) | 0.82 (0.50–1.36) | 0.82 (0.50–1.36) | ||
Quartile 2 HKD$2500–7900 | 1.17 (0.67–2.04) | 1.25 (0.71–2.19) | 1.30 (0.74–2.30) | 1.32 (0.75–2.33) | 1.33 (0.75–2.35) | ||
Quartile 1 HKD$0–2499 | 1.12 (0.61–2.05) | 1.15 (0.62–2.12) | 1.19 (0.64–2.20) | 1.18 (0.64–2.19) | 1.19 (0.64–2.21) | ||
Medical history | |||||||
Hypertension (ref = No hypertension) | 1.93 (1.31–2.84) | 1.83 (1.23–2.72) | 1.83 (1.23–2.73) | 1.84 (1.23–2.74) | |||
Diabetes (ref = No diabetes) | 1.86 (1.10–3.14) | 1.78 (1.05–3.03) | 1.78 (1.05–3.03) | 1.78 (1.05–3.03) | |||
Stroke (ref = No stroke) | 3.57 (1.27–10.05) | 3.79 (1.32–10.84) | 3.74 (1.31–10.68) | 3.75 (1.31–10.69) | |||
Lifestyle | |||||||
Current smoker (ref = Non-current smoker) | 1.19 (0.47–3.03) | 1.18 (0.47–3.01) | 1.18 (0.46–3.01) | ||||
Current drinker (ref = Non-current drinker) | 1.11 (0.74–1.64) | 1.10 (0.74–1.64) | 1.10 (0.74–1.64) | ||||
Physical activity, PASE score | 1.00 (1.00–1.00) | 1.00 (1.00–1.00) | 1.00 (1.00–1.00) | ||||
Diet quality, DQI | 1.00 (0.98–1.01) | 0.99 (0.98–1.01) | 0.99 (0.98–1.01) | ||||
BMI, kg/m2 | 1.07 (1.01–1.15) | 1.07 (1.00–1.15) | 1.07 (1.00–1.15) | ||||
Mental health | |||||||
SF-12 MCS score | 1.01 (0.98–1.05) | 1.01 (0.98–1.05) | |||||
Cognitive function | |||||||
MMSE score | 1.01 (0.94–1.08) |
Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | |
---|---|---|---|---|---|---|---|
Variables | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) |
Socioeconomic status | |||||||
Subjective social status (ref = High) | |||||||
Middle | 2.15 (1.31–3.53) | 2.14 (1.31–3.52) | 2.06 (1.22–3.49) | 2.21 (1.29–3.78) | 2.23 (1.30–3.83) | 2.22 (1.29–3.82) | 2.21 (1.28–3.81) |
Low | 3.70 (1.74–7.88) | 3.67 (1.73–7.82) | 3.75 (1.66–8.47) | 3.44 (1.48–7.97) | 3.42 (1.47–7.97) | 3.45 (1.48–8.07) | 3.60 (1.54–8.41) |
Socio–demographics | |||||||
Age | 1.23 (1.15–1.32) | 1.23 (1.15–1.32) | 1.18 (1.09–1.28) | 1.19 (1.10–1.29) | 1.20 (1.11–1.30) | 1.20 (1.11–1.30) | 1.20 (1.11–1.30) |
Non–married (single, divorced, separated) (ref = Married) | 0.73 (0.28–1.95) | 0.70 (0.24–2.01) | 0.58 (0.20–1.70) | 0.60 (0.20–1.77) | 0.61 (0.21–1.81) | 0.62 (0.21–1.86) | |
Educational level (ref = At least completed primary) | |||||||
Some primary | 1.01 (0.57–1.79) | 0.95 (0.53–1.71) | 0.93 (0.51–1.68) | 0.89 (0.49–1.62) | 0.81 (0.44–1.51) | ||
No education | 2.11 (0.54–8.16) | 3.05 (0.75–12.43) | 2.80 (0.66–11.93) | 2.89 (0.68–12.36) | 2.30 (0.52–10.09) | ||
Maximum life–time income (ref = Quartile 4 ≥HKD$14,000) | |||||||
Quartile 3 HKD$8000–13,999 | 1.21 (0.69–2.14) | 1.21 (0.68–2.16) | 1.23 (0.69–2.20) | 1.22 (0.68–2.19) | 1.24 (0.69–2.22) | ||
Quartile 2 HKD$2500–7900 | 1.37 (0.66–2.84) | 1.39 (0.66–2.92) | 1.45 (0.68–3.08) | 1.47 (0.69–3.11) | 1.37 (0.64–2.93) | ||
Quartile 1 HKD$0–2499 | 1.43 (0.51–4.05) | 1.50 (0.52–4.30) | 1.43 (0.50–4.15) | 1.48 (0.51–4.29) | 1.35 (0.46–3.97) | ||
Medical history | |||||||
Hypertension (ref = No hypertension) | 1.93 (1.12–3.33) | 1.80 (1.02–3.18) | 1.82 (1.03–3.21) | 1.74 (0.98–3.09) | |||
Diabetes (ref = No diabetes) | 2.02 (0.97–4.24) | 1.95 (0.93–4.12) | 2.01 (0.95–4.27) | 1.99 (0.93–4.23) | |||
Stroke (ref = No stroke) | 3.07 (0.86–10.99) | 3.12 (0.86–11.40) | 3.15 (0.87–11.48) | 3.28 (0.90–12.00) | |||
Lifestyle | |||||||
Current smoker (ref = Non–current smoker) | 1.18 (0.42–3.30) | 1.15 (0.41–3.24) | 1.13 (0.40–3.19) | ||||
Current drinker (ref = Non–current drinker) | 1.00 (0.56–1.79) | 1.02 (0.57–1.83) | 1.03 (0.57–1.86) | ||||
Physical activity, PASE score | 1.00 (1.00–1.01) | 1.00 (1.00–1.01) | 1.00 (1.00–1.01) | ||||
Diet quality, DQI | 1.00 (0.97–1.03) | 1.00 (0.97–1.02) | 1.00 (0.97–1.02) | ||||
BMI, kg/m2 | 1.07 (0.97–1.18) | 1.07 (0.97–1.18) | 1.07 (0.97–1.18) | ||||
Mental health | |||||||
SF–12 MCS score | 1.02 (0.97–1.07) | 1.02 (0.98–1.07) | |||||
Cognitive function | |||||||
MMSE score | 0.92 (0.81–1.05) |
Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | |
---|---|---|---|---|---|---|---|
Variables | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) |
Socioeconomic status | |||||||
Subjective social status (ref = High) | |||||||
Low to middle * | 1.37 (0.87–2.16) | 1.37 (0.87–2.16) | 1.45 (0.84–2.51) | 1.56 (0.89–2.72) | 1.60 (0.91–2.82) | 1.61 (0.91–2.83) | 1.61 (0.91–2.84) |
Socio–demographics | |||||||
Age | 1.22 (1.14–1.29) | 1.21 (1.13–1.29) | 1.26 (1.16–1.36) | 1.25 (1.15–1.35) | 1.24 (1.14–1.35) | 1.24 (1.14–1.35) | 1.25 (1.14–1.36) |
Non–married (single, divorced, separated) (ref = Married) | 1.22 (0.77–1.93) | 1.01 (0.57–1.79) | 0.96 (0.54–1.71) | 0.98 (0.55–1.75) | 0.98 (0.55–1.75) | 0.97 (0.54–1.74) | |
Educational level (ref = At least completed primary) | |||||||
Some primary | 0.97 (0.52–1.82) | 1.01 (0.53–1.91) | 0.95 (0.50–1.83) | 0.95 (0.50–1.83) | 1.00 (0.52–1.94) | ||
No education | 0.95 (0.47–1.91) | 1.15 (0.56–2.37) | 1.03 (0.49–2.15) | 1.02 (0.49–2.15) | 1.26 (0.55–2.89) | ||
Maximum life–time income (ref = Quartile 3 and 4 (HKD$8000–13,999 and ≥HKD$14,000 ^)) | |||||||
Quartile 2 HKD$2500–7900 | 1.64 (0.79–3.41) | 1.90 (0.90–3.99) | 1.89 (0.88–4.06) | 1.91 (0.89–4.13) | 1.98 (0.91–4.29) | ||
Quartile 1 HKD$0–2499 | 1.46 (0.73–2.92) | 1.56 (0.77–3.15) | 1.57 (0.76–3.25) | 1.57 (0.76–3.25) | 1.58 (0.77–3.28) | ||
Medical history | |||||||
Hypertension (ref = No hypertension) | 2.08 (1.19–3.65) | 2.00 (1.12–3.58) | 1.99 (1.11–3.57) | 2.03 (1.13–3.64) | |||
Diabetes (ref = No diabetes) | 1.60 (0.73–3.48) | 1.50 (0.68–3.30) | 1.49 (0.67–3.27) | 1.45 (0.66–3.21) | |||
Stroke (ref = No stroke) | 5.70 (0.81–40.04) | 6.67 (0.93–47.74) | 6.44 (0.89–46.55) | 6.72 (0.93–48.44) | |||
Lifestyle | |||||||
Current smoker (ref = Non–current smoker) | 0.62 (0.05–8.10) | 0.62 (0.05–8.07) | 0.52 (0.04–6.64) | ||||
Current drinker (ref = Non–current drinker) | 1.22 (0.70–2.15) | 1.21 (0.69–2.13) | 1.24 (0.70–2.19) | ||||
Physical activity, PASE score | 1.00 (0.99–1.01) | 1.00 (0.99–1.01) | 1.00 (0.99–1.01) | ||||
Diet quality, DQI | 0.99 (0.97–1.02) | 0.99 (0.97–1.02) | 0.99 (0.96–1.02) | ||||
BMI, kg/m2 | 1.08 (0.98–1.19) | 1.08 (0.98–1.18) | 1.08 (0.98–1.19) | ||||
Mental health | |||||||
SF–12 MCS score | 1.01 (0.97–1.05) | 1.01 (0.97–1.06) | |||||
Cognitive function | |||||||
MMSE score | 1.06 (0.96–1.16) |
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Yu, R.; Tong, C.; Leung, J.; Woo, J. Socioeconomic Inequalities in Frailty in Hong Kong, China: A 14-Year Longitudinal Cohort Study. Int. J. Environ. Res. Public Health 2020, 17, 1301. https://doi.org/10.3390/ijerph17041301
Yu R, Tong C, Leung J, Woo J. Socioeconomic Inequalities in Frailty in Hong Kong, China: A 14-Year Longitudinal Cohort Study. International Journal of Environmental Research and Public Health. 2020; 17(4):1301. https://doi.org/10.3390/ijerph17041301
Chicago/Turabian StyleYu, Ruby, Cecilia Tong, Jason Leung, and Jean Woo. 2020. "Socioeconomic Inequalities in Frailty in Hong Kong, China: A 14-Year Longitudinal Cohort Study" International Journal of Environmental Research and Public Health 17, no. 4: 1301. https://doi.org/10.3390/ijerph17041301
APA StyleYu, R., Tong, C., Leung, J., & Woo, J. (2020). Socioeconomic Inequalities in Frailty in Hong Kong, China: A 14-Year Longitudinal Cohort Study. International Journal of Environmental Research and Public Health, 17(4), 1301. https://doi.org/10.3390/ijerph17041301