OBJECTIVE: To document the extent of polypharmacy or multiple medication use in the elderly. DESIGN: Cross-sectional examination of an age cohort of a community. SETTING: Community-based study in Dubbo, NSW, in 1988-1989. SUBJECTS: All non-institutionalised residents aged 60 years and over, numbering 1237 men and 1568 women. MAIN OUTCOME MEASURES: Assessment of use of prescription and non-prescription drugs, recent hospitalisation, years of education, psychosocial variables. RESULTS: 18% of men and 25% of women were currently using three or more classes of prescription drugs. The corresponding values for two or more classes of non-prescription drugs were 29% and 44%. Of those who were using multiple prescription drugs 56% of men and 76% of women were also using multiple non-prescription drugs. In a multiple logistic model, the following possible predictors of multiple drug use were included: hospitalisation in the last six months, age, sex, depression, life satisfaction and education. Multiple prescription drug use was significantly predicted by recent hospitalisation (odds ratio [OR] = 2.40; 95% confidence interval [CI], 1.63-3.56), increasing age (e.g. 70-79 years versus 60-69 years; OR = 2.54; CI, 1.97-3.25), female sex (OR = 1.59; CI, 1.25-2.01) and increasing depression (e.g. highest tertile of depression scale versus lowest; OR = 2.52; CI, 1.84-3.42). Multiple non-prescription drug use was significantly predicted by female sex (OR = 2.38; CI, 1.95-2.92) and increasing depression (OR = 2.77; CI, 2.16-3.56). For prescription items, non-prescription items, and both categories in combination levels of use 20% above the population average have been documented. CONCLUSIONS: Polypharmacy in the elderly population appears to be predicted by recent hospitalisation, increasing age, female sex and increasing depression. There is potential for drug-drug interaction to occur, but the findings suggest target areas for preventive action.
OBJECTIVE: To document the extent of polypharmacy or multiple medication use in the elderly. DESIGN: Cross-sectional examination of an age cohort of a community. SETTING: Community-based study in Dubbo, NSW, in 1988-1989. SUBJECTS: All non-institutionalised residents aged 60 years and over, numbering 1237 men and 1568 women. MAIN OUTCOME MEASURES: Assessment of use of prescription and non-prescription drugs, recent hospitalisation, years of education, psychosocial variables. RESULTS: 18% of men and 25% of women were currently using three or more classes of prescription drugs. The corresponding values for two or more classes of non-prescription drugs were 29% and 44%. Of those who were using multiple prescription drugs 56% of men and 76% of women were also using multiple non-prescription drugs. In a multiple logistic model, the following possible predictors of multiple drug use were included: hospitalisation in the last six months, age, sex, depression, life satisfaction and education. Multiple prescription drug use was significantly predicted by recent hospitalisation (odds ratio [OR] = 2.40; 95% confidence interval [CI], 1.63-3.56), increasing age (e.g. 70-79 years versus 60-69 years; OR = 2.54; CI, 1.97-3.25), female sex (OR = 1.59; CI, 1.25-2.01) and increasing depression (e.g. highest tertile of depression scale versus lowest; OR = 2.52; CI, 1.84-3.42). Multiple non-prescription drug use was significantly predicted by female sex (OR = 2.38; CI, 1.95-2.92) and increasing depression (OR = 2.77; CI, 2.16-3.56). For prescription items, non-prescription items, and both categories in combination levels of use 20% above the population average have been documented. CONCLUSIONS: Polypharmacy in the elderly population appears to be predicted by recent hospitalisation, increasing age, female sex and increasing depression. There is potential for drug-drug interaction to occur, but the findings suggest target areas for preventive action.
Authors: N Husson; G Watfa; M-C Laurain; C Perret-Guillaume; J-Y Niemier; P Miget; A Benetos Journal: J Nutr Health Aging Date: 2014-01 Impact factor: 4.075
Authors: Javier Jerez-Roig; Lucas F B Medeiros; Victor A B Silva; Camila L P A M Bezerra; Leandro A R Cavalcante; Grasiela Piuvezam; Dyego L B Souza Journal: Drugs Aging Date: 2014-12 Impact factor: 3.923