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1.
J Clin Epidemiol ; 62(2): 177-87, 2009 Feb.
Article in English | MEDLINE | ID: mdl-18722090

ABSTRACT

OBJECTIVE: To examine the impact of changes in comorbidity--as measured by the Charlson comorbidity index--on self-rated health in a large sample of community-dwelling elderly over a 1-year period, and to examine the differential effects of changes in specific Charlson diagnostic categories. STUDY DESIGN AND SETTING: Longitudinal survey data on self-rated health were linked with Medicare inpatient, outpatient, and physician visit data for 30,535 U.S. elderly residing in Pennsylvania. Multivariate logistic regression with fractional polynomials was used to model relationships involving baseline and changing Charlson comorbidity with self-rated health decline, and to evaluate covariate interactions. RESULTS: Comorbidity change was associated with greater likelihood of worsened self-rated health, but the relationship was nonlinear and was moderated by age and baseline comorbidity. The impact of comorbidity change appeared to be less among older individuals and those with higher baseline comorbidity. Declines in self-rated health were most likely following new diagnoses for metastatic tumors, paralysis, and dementia. CONCLUSION: Self-rated health is responsive to changes in Charlson comorbidity, but nonlinearity and interactions suggest complexity in how elderly respond to comorbidity change. Younger individuals and those with initially low comorbidity are more likely to reduce self-ratings of health following new diagnoses for chronic conditions.


Subject(s)
Chronic Disease/epidemiology , Comorbidity , Health Status , Activities of Daily Living , Age Factors , Aged , Aged, 80 and over , Chronic Disease/psychology , Female , Geriatric Assessment , Health Status Indicators , Humans , Longitudinal Studies , Male , Pennsylvania/epidemiology , Quality of Life , Residence Characteristics
2.
J Aging Health ; 18(6): 837-51, 2006 Dec.
Article in English | MEDLINE | ID: mdl-17099136

ABSTRACT

OBJECTIVE: To determine the extent to which changes in medication use and health influence the decision to quit drinking among older adults. METHOD: The sample consisted of 8,883 elderly enrolled in Pennsylvania's Pharmaceutical Assistance Contract for the Elderly (PA-PACE) program who completed surveys in 2000 and 2002. Survey data were linked with prescription claims to examine medication and health factors associated with drinking cessation between baseline and follow-up. RESULTS: Overall, 3.9% of those using alcohol at baseline quit drinking during the study period. Logistic regression results showed that individuals who initiated antipsychotic (OR = 2.92) and antineoplastic therapies (OR = 2.67) were the most likely to quit drinking. DISCUSSION: These findings support the hypothesis that elderly quit drinking in response to ill health. Results have implications for alcohol interventions in older adults and underscore the importance of separating former drinkers from lifetime abstainers in the study of alcohol-health relationships.


Subject(s)
Alcohol Drinking , Drinking Behavior/drug effects , Drug Prescriptions , Drug Therapy , Health Status , Aged , Aged, 80 and over , Drug-Related Side Effects and Adverse Reactions , Female , Humans , Male , United States
3.
J Am Geriatr Soc ; 53(11): 1930-6, 2005 Nov.
Article in English | MEDLINE | ID: mdl-16274374

ABSTRACT

OBJECTIVES: To examine the patterns and prevalence of concomitant alcohol and alcohol-interactive (AI) drug use in older people. DESIGN: Cross-sectional analysis of survey and prescription claims data. SETTING: The Pennsylvania Pharmaceutical Assistance Contract for the Elderly (PA-PACE) program, a state-funded program providing prescription benefits to older people with low to moderate incomes. PARTICIPANTS: A total of 83,321 PA-PACE cardholders (age range 65-106) who were using any prescription medications at the time of survey completion. MEASUREMENTS: All AI drugs were identified using a database of medication warning labels obtained from First DataBank. Prescription drug claims were used to characterize AI drug exposure according to therapeutic class of prescription drug use. A mail survey of PA-PACE cardholders was used to examine alcohol use, as well as sociodemographic and health factors associated with concomitant use of alcohol and AI drugs. RESULTS: Seventy-seven percent of all prescription drug users were exposed to AI medications, with significant variation in exposure and concomitant alcohol use according to therapeutic class. Overall, 19% of AI drug users reported concomitant alcohol use, compared with 26% of non-AI drug users (P<.001). Multinomial logistic regression analyses showed that certain groups of older people, including younger older people, men, and those with higher educational levels, were at greater risk for concomitant exposure to alcohol and AI drugs. CONCLUSION: Many older people use alcohol in combination with AI prescription drugs. Clinicians should warn every patient who is prescribed an AI drug about alcohol-drug interactions, especially those at high risk for concomitant exposure.


Subject(s)
Alcohol Drinking/adverse effects , Drug Prescriptions , Drug-Related Side Effects and Adverse Reactions , Ethanol/adverse effects , Aged , Aged, 80 and over , Alcohol Drinking/epidemiology , Cross-Sectional Studies , Drug Interactions , Female , Health Surveys , Humans , Insurance, Pharmaceutical Services , Male , Mass Screening , Pennsylvania , Risk Assessment , Risk Factors , State Health Plans , United States
4.
BMC Womens Health ; 5: 7, 2005 May 16.
Article in English | MEDLINE | ID: mdl-15904516

ABSTRACT

BACKGROUND: Many women have discontinued hormone replacement therapy (HRT) in view of recent findings. The goal of this study was to determine if HRT discontinuation is associated with changes in health-related quality of life (HRQOL) in elderly women. METHODS: We studied women enrolled in Pennsylvania's Pharmaceutical Assistance Contract for the Elderly (PACE) program, linking prescription claims with data from a longitudinal mail survey. HRQOL measures included the number of days out of the last 30 that physical health was not good and analogous measures for mental health, pain, and interference with activities, as well as a composite "healthy days" measure developed by CDC. Longitudinal analyses focused on 2,357 women who completed surveys in both 2002 and 2003, and who used HRT at baseline (mean age = 75.5, range = 65-102). Propensity scores were used to match HRT continuers and discontinuers according to HRT type, demographics, and baseline HRQOL. Analysis of covariance was used to compare HRQOL change in continuers and discontinuers. RESULTS: Between 2002 and 2003, 43% of HRT users discontinued therapy. Analysis of covariance to examine HRQOL change revealed complex interactions with age. Discontinuers aged 65-74 reported greater increases in days in which mental health was not good (p < .05), fewer "healthy days" (p < .05), more days in which health interfered with activities (p < .01), and more days with pain (p < .01). Among women aged 75-84, HRT discontinuers reported more days in which physical health was not good (p < .01); no other significant effects were observed in this group. Relative to HRT continuers, discontinuers aged 85 and older experienced apparent HRQOL improvements following cessation, with fewer days in which physical health was not good (p < .01), fewer days of poor mental health (p < .05), and more "healthy days" (p < .01). CONCLUSIONS: These results suggest that there are substantial age differences in response to HRT discontinuation. While women aged 65-74 experienced apparent declines in HRQOL following HRT cessation, women aged 85 and older experienced relative improvements. The HRQOL declines observed among younger women underscore the importance of communication between clinicians and patients throughout the discontinuation process. These results also demonstrate the value of HRQOL surveillance as a component of health program administration.

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