Fall Risk factors in Chinese older people: Implications for falls prevention

Transcription

1 Fall Risk factors in Chinese older people: Implications for falls prevention Chinese Older Peoples Study of Injury: X cultural (CHOPSTIX) 1 st June 2012 NSW Falls Prevention Network Forum

2 Falls research in the elderly

3 Previous studies on Chinese older people Prevalence Falls incidence lower in Chinese population: 14.7% - 34% (median 18%) Risk factors Risk factors similar to those found in Caucasian-based populations Risk factor N Gender 10 Decline in ADL/IADL 9 Multiple medication use 8 Increasing age 7 Fear of falling 6 Use of walking aid 6 Self-perceived poor health 6 Marital status 6 Diabetes 6 Significant risk factor in univariate analysis in 4 or more studies Risk factor N Living alone 5 Gait abnormality/ instability 5 Chronic conditions 5 Falls in past 12/18 months 5 Antihypertensive Drugs 5 Eye problem (eg. cataract/ glaucoma) 4 Hypotension 4 Hypertension 4 Depression 4

4 Previous comparative studies Hawaii Osteoporosis Study (HOS) & Study of Osteoporotic Fracture (SOF) fall incidence rate in Japanese half of the Caucasian compared neuromuscular performance measures & functional disabilities Concord Health and Ageing g in Men Project (CHAMP) recurrent fall rate in Italian-born (11%) vs Australian born (22%) compared established fall risk factors: age, dementia, multiple medications, some physical tests The Osteoporotic Fractures in Men (MrOS): USA, Sweden and Hong Kong Fall prevalence: USA (21.2%), Sweden (16.5%) & Hong Kong (15.4%) compared physical function: handgrip, 5xSTS, 6-m walk & narrow walk

5 Study rationale Studies to date were not able to explain the discrepancy of fall rates between Chinese & Caucasian A different approach required cross-country and migrant study design epidemiologic studies of CHD in Japanese men living in Japan, Hawaii and California risk factors same as before emigrating social, cultural & genetic more oelike new host environmental e & soca social

6 Aim 1. To determine the physiological/ functional & lifestyle risk factors contributing to falls in Chinese older people 2. To compare risk factor profiles among Chinese and Caucasian samples in multiple countries

7 Methods Multi country Tainan, Taiwan Hong Kong Sydney Sydney Caucasian Selection criteria 65 years MMSE 19 community dwelling independent ambulation

8 Methods Measurements Physical (including Physiological Profile Assessment) Vision : depth, visual acuity, contrast sensitivity Strength: quadriceps, hamstrings Balance: sway, co-ordinated stability, maximal balance range Reaction time: hand, foot Functional single leg stance, near tandem stand timed-up & go, 6-m walking speed alternate stepping, sit-to-standto stand

9 Methods Details we asked Cognition (MMSE) & Depression (GDS-15) Quality of life Physical activity level (IPEQ) Nutritional status (Mini Nutritional Assessment) Falls efficacy (FES-I) Medical conditions & medications Mobility & functional limitationsit ti Monthly follow-up for 1 year on falls

10 Results Basic Characteristics Variable TW (n=280) HK (n=201) AU (n=211) Caucasian (n=764) Age (mean±sd)(yrs) 74.9± ± ± ±4.7 Female 120 (43) 155 (77) 136 (65) 431 (56) Maritalstatus (married) 197 (70) 153 (76) 131 (62) 140 (47) Education (nil) 44 (16) 61 (30) 24 (11) 0 (0) 4+ medical conditions 15 (5) 18 (9) 14 (7) 44 (6) 4+medications 72 (26) 44 (22) 99 (47) 510 (68) Fair/poor self rated health 205 (73) 88 (44) 107 (51) 57 (19) GDS 15>=6 61 (22) 22 (11) 14 (7) 26 (6) Values are numbers (percentage) unless specify

11 Results Physical & functional performance Variable TW (n=280) HK (n=201) AU (n=211) Caucasian (n=764) Edge contrast sensitivity (db) 18.6± ± ±2.41±2 19.9±2.39±2 Sway on foam eye open (mm) 220± ± ± ±90 Proprioception (degree) 2.1± ± ± ±1.5 Tactile sensation (log10 me pressure) 4.4± ± ± ±0.5 Knee extension strength (N) 229.6± ± ± ±119.2 Reaction time hand (ms) 308±85 292±97 238±53 242±49 Reaction time foot (ms) 360±89 342± ±60 297±54 Timed Up & Go (s) 10.9± ± ± ±3.0 Alternate Step time (s) 12.1± ± ± ±3.0 Values are mean±sd unless specify

12 Results Other responses Variable TW (n=280) HK (n=201) AU (n=211) Caucasian (n=764) FES I score (mean±sd) 34.0± ± ± ±6.4 Self perceived balance (fair/poor) 187 (67) 100 (50) 118 (58) 231 (30) Incidental activity (hours/week) (mean±sd) 16.9± ± ± ±15.6 Planned activity (hours/week) 6.2± ± ± ±3.8 (mean±sd) Values are numbers (%) unless specify

13 Results Falls Variable TW (n=280) HK (n=201) AU (n=211) Caucasian (n=764) Prospective single fall Number (%) Prosp. recurrent falls Number (%) 86 (31)^ 31 (15) 55 (26) 315 (41) 34 (12)^ 6 (3) 12 (6) 133 (17) Prospective fall rate (no. of falls per 100 person yrs) Incidence Rate Ratio (95% CI) Age & sex adjusted ( ) 0.28 ( ) 0.52 ( ) ^ 2-year follow-up

14 Results models Variable in model TW (n=280) HK (n=201) AU (n=211) Cohort (unadjusted) 0.39 ( ) 0.49) 0.28 ( ) 0.41) 0.50 ( ) 0.67) Cohort + age & sex 0.41 ( ) 0.28 ( ) 0.52 ( ) Cohort + age & sex + incontinence + PD + education 0.41 ( ) 0.32 ( ) 0.53 ( ) Cohort + age & sex + incontinence + PD + education + FES I 0.36 ( ) 0.27 ( ) 0.46 ( ) Age,sex, incontinence, PD, years ofeducation & interaction term cohort FES I score 0.98 ( ) 0.55 ( ) 0.60 ( )

15 Results

16 Discussion Falls incidence Risk factors Physical/ functional performances Concern about falling Physical activity patterns

17 Applications & Issues Application Fall prevention in Chinese older people? Cognitive-Behavioural Therapy? Current prevention programs Issues Language barrier Cultural difference Adaptation

18 Acknowledgements Supervisors: Prof. Stephen Lord & A/Prof. Jacqueline Close Collaborators & affiliated organisations Subjects, volunteers & helpers

19 Thank you!!