| Literature DB >> 28273128 |
Li Min Lim1, Megan McStea2,3, Wen Wei Chung4, Nuruljannah Nor Azmi3, Siti Azdiah Abdul Aziz3,5, Syireen Alwi1, Adeeba Kamarulzaman3,6, Shahrul Bahyah Kamaruzzaman2,6, Siew Siang Chua1, Reena Rajasuriar1,3,7.
Abstract
BACKGROUND: Polypharmacy has been associated with increased morbidity and mortality in the older population.Entities:
Mesh:
Year: 2017 PMID: 28273128 PMCID: PMC5342241 DOI: 10.1371/journal.pone.0173466
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Characteristics of all participants included in the study (n = 1256) as well as those with polypharmacy (n = 576) and dietary supplement users (n = 715).
| Total | 1256 (100.0) | 576 (45.9) | 715 (56.9) |
| Age (n = 1256) | 69 (63–74) | 71 (66–76) | 70 (64–75) |
| 55–59 | 124 (9.9) | 39 (31.5) | 76 (61.3) |
| 60–64 | 243 (19.4) | 79 (32.5) | 126 (51.9) |
| 65–69 | 279 (22.2) | 122(43.7) | 160 (57.3) |
| 70–74 | 300 (23.9) | 151 (50.3) | 178 (59.3) |
| 75–79 | 202 (16.1) | 118 (58.4) | 119 (58.9) |
| 80+ | 108 (8.6) | 67 (62.0) | 65 (60.2) |
| Gender (n = 1256) | |||
| Male | 532 (42.3) | 259 (48.7) | 269 (50.6) |
| Female | 724 (57.7) | 317 (43.8) | 446 (61.6) |
| Ethnic (n = 1255) | |||
| Malay | 383 (30.5) | 137 (35.8) | 133 (34.7) |
| Chinese | 418 (33.3) | 170 (40.7) | 294 (70.3) |
| Indian | 447 (35.6) | 265 (59.3) | 284 (63.5) |
| Others | 7 (0.6) | 4 (50.0) | 4 (50.0) |
| Highest education level (n = 1252) | |||
| Primary or No Formal | 326 (26.0) | 133 (40.8) | 121 (37.1) |
| Secondary | 538 (43.0) | 232 (43.1) | 317 (58.9) |
| Tertiary | 388 (31.0) | 210 (54.1) | 275 (70.9) |
| Employment status (n = 1255) | |||
| No | 1021 (81.4) | 483 (47.3) | 572 (56.0) |
| Yes | 234 (18.6) | 93 (39.7) | 142 (60.7) |
| Payment method for healthcare service in the last 12 months | |||
| Used free service | 56 (4.9) | 32 (57.1) | 34 (60.7) |
| Self/Out of pocket | 591 (51.6) | 252 (42.6) | 332 (56.2) |
| Employer | 292 (25.5) | 156 (52.7) | 156 (53.4) |
| Relatives | 127 (11.1) | 64 (50.4) | 67 (52.8) |
| Welfare | 112 (9.8) | 62 (55.4) | 67 (59.8) |
| Insurance | 13 (1.1) | 4 (30.8) | 10 (76.9) |
| Non-governmental/Religious organizations | 4 (0.4) | 3 (75.0) | 4 (100) |
| Chronic health problems | |||
| (n = 1256) | |||
| Cardiovascular disorders | 1002 (79.8) | 607 (50.6) | 519 (51.8) |
| Endocrine disorders | 472 (37.6) | 296 (62.7) | 229 (48. 5) |
| Bone and joint disorders | 359 (28.6) | 211 (58.8) | 246 (68.5) |
| Urologic disorders | 321 (25.6) | 170 (53.0) | 182 (56.7) |
| Ophthalmic disorders | 237 (18.9) | 130 (54.9) | 134 (56.5) |
| Respiratory disorders | 104 (8.3) | 58 (55.8) | 53 (51.0) |
| Oncologic disorders | 84 (6.7) | 47 (56.0) | 72 (85.7) |
| Gastrointestinal disorders | 64 (5.1) | 45 (70.3) | 43 (67.2) |
| Renal disorders | 39 (3.2) | 30 (76.9) | 21 (53.8) |
| Neurologic disorders | 22 (1.8) | 14 (63.6) | 12 (54.5) |
| Falls in the last 12 months (n = 1256) | 294 (23.4) | 146 (49.7) | 151 (51.4) |
| Functional disability | |||
| Katz ADL | 44 (3.5) | 25 (56.8) | 27 (61.4) |
| Lawton IADL | 388 (30.9) | 210 (54.1) | 192 (49.5) |
| PIMs use (n = 1256) | 400 (31.8) | 271 (67.8) | 177 (44.3) |
| PDDIs (n = 1256) | 281 (22.4) | 215 (76.5) | 141 (50.2) |
| Smoking status (n = 1236) | |||
| Never | 985 (79.7) | 446 (45.3) | 584 (59.3) |
| Current smoker | 96 (7.8) | 36 (37.5) | 40 (41.7) |
| Ex-smoker | 155 (12.5) | 87 (56.1) | 78 (50.3) |
| Alcohol consumption (n = 1250) | |||
| Never | 889 (71.1) | 388 (43.6) | 467 (52.5) |
| Yes | 280 (22.4) | 147 (52.5) | 204 (72.9) |
| Used to | 81 (6.5) | 37 (45.7) | 40 (49.4) |
| More than 1 comorbidity | 979 (78.0) | 521 (53.2) | 636 (65.0) |
| Using dietary supplements | 715 (56.9) | 401 (56.1) | - |
| Quality of life (QoL) (n = 124), CASP 12 score | 28 (24‒31) | 28 (24‒31) | 28 (25–31) |
| Number of visits to any healthcare facility in the last 12 months | 4 (2‒6) | 4 (2‒7) | 3 (1–6) |
| Number of comorbidities (n = 1256) | 3 (2‒4) | 3 (2–5) | 3 (1–4) |
| Number of prescribed and non-prescribed drugs (n = 1256) | 3 (1‒5) | 5 (3–6) | 2 (1–4) |
| Number of dietary supplements (n = 1256) | 1 (0‒2) | 2 (0–3) | 2 (1–3) |
| Total number of medications (n = 1256) | 4 (2–6) | 6 (5–8) | 5 (3–7) |
IQR: interquartile range; ADL: activities of daily living; IADL: instrumental activities of daily living; PIMs: potential inappropriate medications; PDDIs: potential drug-drug interactions
†More than one choice can be chosen.
Risk factors associated with polypharmacy among urban community-dwelling older adults.
| Crude IRR (95%CI) | Adjusted IRR (95%CI) | |||
|---|---|---|---|---|
| Number of dietary supplements | 1.13 (1.11–1.15) | 1.19 (1.15–1.23) | ||
| Number of comorbidities | 1.15 (1.13–1.16) | 1.14 (1.11‒1.17) | ||
| Ethnic | ||||
| Indian (reference) | 1.00 | 1.00 | ||
| Malay | 0.73 (0.67‒0.79) | 0.89 (0.30‒0.94) | ||
| Chinese | 0.77 (0.71‒0.83) | 0.83 (0.78‒0.88) | ||
| Age | ||||
| 55‒59 (reference) | 1.00 | 1.00 | ||
| 60‒64 | 1.05 (0.93–1.21) | 1.05 (0.95‒1.15) | ||
| 65‒69 | 1.27 (1.11‒1.44) | 1.11 (1.01‒1.22) | ||
| 70–74 | 1.47 (1.29‒1.67) | 1.23 (1.12‒1.34) | ||
| 75–79 | 1.55 (1.36–1.77) | 1.28 (1.15–1.41) | ||
| 80+ | 1.63 (1.40–1.90) | 1.29 (1.13–1.46) | ||
| Chronic health problems | ||||
| Cardiovascular disorders | 1.42 (1.28‒1.58) | 1.23 (1.14‒1.33) | ||
| Endocrine disorders | 1.48 (1.38‒1.58) | 1.47 (1.31–1.64) | ||
| Bone and joint disorders | 1.26 (1.17‒1.35) | _ | ||
| Urologic disorders | 1.12 (1.03‒1.21) | 0.91 (0.86–0.97) | ||
| Ophthalmic disorders | 1.15 (1.06‒1.25) | ‒ | ||
| Respiratory disorders | 1.13 (1.00‒1.28) | 0.051 | _ | |
| Oncologic disorders | 1.12 (1.03‒1.32) | _ | ||
| Gastrointestinal disorders | 1.48 (1.29‒1.68) | 1.13 (1.03–1.24) | ||
| Renal disorders | 1.59 (1.36‒1.85) | ‒ | ||
| Neurologic disorders | 1.31 (0.97‒1.77) | 0.077 | ‒ | |
| Psychiatric disorders | 1.08 (0.71‒1.64) | 0.714 | ‒ | |
| Smoke cigarettes | ||||
| No (reference) | 1.00 | ‒ | _ | |
| Current smoker | 0.86 (0.76‒0.97) | 0.013 | _ | |
| Ex-smoker | 1.125 (1.01‒1.23) | 0.031 | _ | |
| Payment method for healthcare service in last 12 months | ||||
| Used Free Service | 1.14 1.01–1.28) | ‒ | ||
| Self/Out of pocket | 0.90 (0.84‒0.97) | ‒ | ||
| Employer | 1.14 (1.05‒1.23) | ‒ | ||
| Relative | 1.09(0.98‒1.23) | 0.123 | ‒ | |
| Welfare | 1.14 (1.02‒1.28) | _ | ||
| Insurance | 0.73 (0.55‒0.97) | _ | ||
| Non-governmental/ religious organization | 3.59 (0.37‒34.56 | 0.270 | _ | |
| Alcohol consumption history | ||||
| No (reference) | 1.00 | ‒ | ||
| Yes | 1.10 (1.02‒1.19) | 0.013 | - | |
| Used to | 1.17 (1.01‒1.35) | 0.037 | ||
| Employment | 0.88 (0.81‒0.97) | ‒ | ||
| Highest education level | ||||
| Primary or below | 1.00 | _ | _ | |
| Secondary | 1.06(0.98–1.15) | 0.170 | _ | |
| Tertiary | 1.22 (1.12–1.33) | <0.001 | _ | |
| Gender | ||||
| Male | 1.06 (0.99‒1.14) | 0.085 | 1.09 (1.03–1.14) | |
IRR:incidence rate ratio; CI: confidence interval
†”No” is the reference group
Multicollinearity Overdispersion and interaction terms were checked and not found.
Interactions were between the number of supplements and the number of comorbidities and the presence of endocrine disorders and number of comorbidities
Area under the receiver operating characteristic (ROC) curve (79.9%) were applied to check the goodness of qfit
Health outcomes associated with polypharmacy among urban-community dwelling older adults.
| PIMs* | 1.31 (1.25‒1.37) | <0.001 | 1.27 (1.20‒1.34) | <0.001 |
| PDDIs* | 1.38 (1.31‒1.46) | <0.001 | 1.34 (1.26‒1.42) | <0.001 |
| Fall in last 12 months | 1.04 (0.99‒1.09) | 0.060 | ‒ | ‒ |
| Katz ADL | 1.04 (0.94‒1.14) | 0.473 | ‒ | ‒ |
| Lawton IADL | 1.09 (1.05‒1.14) | <0.001 | ‒ | ‒ |
| Healthcare utilisation | 0.46 (0.32–0.60) | <0.001 | 0.44 (0.30–0.59) | <0.001 |
| CASP 12 QoL | -0.11 (-2.08 -,0.01) | 0.040 | - | - |
OR: odd ratio; CI: confidence interval; PIMs: potential inappropriate medications; PDDIs: potential drug-drug interactions; ADL: activities of daily living; IADL: instrumental activities of daily living
†Adjusted for age, gender, number of comorbidities and ethnicity
Healthcare utilisation unadjusted model:, R2 = 0.003; adjusted model: R2 = 0.038
CASP 12 QoL unadjusted model:, R2 = 0.003;
β: regression coefficient; CI: confidence interval; R2: coefficient of determination; CASP 12 QoL: control, autonomy, self realisation and pleasure measure of quality of life