Multimorbidity patterns in older persons and their association with self-reported quality of life and limitations in activities of daily living.

BACKGROUND: As populations age, multimorbidity (the presence of two or more chronic morbidities) is increasingly more common. These evolving demographics demand further research into the identification of morbidity patterns in different settings as well as the longitudinal effects of these patterns. METHODS: Prospectively collected data on 12,755 older persons aged 65+ years were derived from The Older Persons and Informal Caregivers Survey Minimum DataSet (TOPICS-MDS, www.topics-mds.eu). Latent class analyses were performed to identify unobserved relationship patterns between morbidities in older persons. Using linear mixed models, the average difference in health-related quality of life (EQ-5D) and general quality of life scores (Cantril's Self Anchoring Ladder) as well as limitations in Activities of Daily Living and Instrumental Activities of Daily Living (ADL/IADL) were examined over a 12-month period. RESULTS: Five multimorbidity patterns were identified: sensory (n = 3882), cardio-metabolic (n = 2627), mental health (n = 920), osteo-articular (n = 4486), and system decline (n = 840). Relative to older persons in the sensory group, multimorbidity patterns did not have a strong effect on health-related quality of life, general quality of life or ADL/IADLs over a one-year period. CONCLUSIONS: The observed multimorbidity patterns are similar to others based on different methodologies and study populations. When examining the effect of such patterns on quality of life, the EQ-5D and Cantril's Ladder may be insufficient outcome measures. Further investigations into the prognostic value of morbidity patterns would be of benefit.

Impact of comorbidity on health-related quality of life among type 2 diabetic patients in primary care.

BACKGROUND: Health-related quality of life (HRQL) is an important outcome for chronic diseases such as diabetes mellitus that is associated with complications, comorbidities, and lifelong care. OBJECTIVES: The present study aims to explore the impact of comorbidities on the different dimensions of HRQL among type 2 diabetic patients attending primary care. METHODS: A total of 912 type 2 diabetic patients attending primary care centers in India were assessed using a predesigned and pretested questionnaire - Diabetes Comorbidity Evaluation Tool in Primary Care. The HRQL was measured by physical and mental health summary scores [physical component summary (PCS) and mental component summary (MCS)] of the Short Form Health Survey 12. The associations of sociodemographic variables and clinical variables with PCS and MCS were assessed, and a minimal difference of 5 in the scores (on a scale of 0-100) was kept as clinically relevant difference for this study. Mean differences in mental (MCS) and physical (PCS) scores of quality of life by number and type of comorbid conditions in type 2 diabetic patients were calculated. RESULT: The presence of comorbid conditions was associated with lower scores of PCS and MCS (P < 0.001). Significant reduction in HRQL was found with increase in number of comorbid conditions, and negative association was established between the number of comorbidities and the PCS (r = -0.25, P < 0.0001) and MCS scores (r = -0.21, P < 0.0001). Among comorbidities, acid peptic disease, chronic lung disease, visual impairment, depression, and stroke had significantly and clinically relevant reduced scores. Duration of diabetes, use of insulin, and obesity were also associated with poor HRQL. CONCLUSION: Comorbidities considerably impair the HRQL among type 2 diabetic patients. National programs designed for diabetes management should also take into account the challenges of coexisting chronic conditions and its substantial effect on HRQL.

Prevalence estimates of multimorbidity: a comparative study of two sources.

BACKGROUND: Published prevalence studies on multimorbidity present diverse data collection methods, sources of data, targeted age groups, diagnoses considered and study populations, making the comparability of prevalence estimates questionable. The objective of this study was to compare prevalence estimates of multimorbidity derived from two sources and to examine the impact of the number of diagnoses considered in the measurement of multimorbidity. METHODS: Prevalence of multimorbidity was estimated in adults over 25 years of age from two separate Canadian studies: a 2005 survey of 26,000 respondents randomly selected from the general population and a 2003 study of 980 patients from 21 family practices. We estimated the prevalence of multimorbidity based on the co-occurrence of >/= 2 and >/= 3 diseases of the seven diseases listed in the general population survey. For primary care patients, we also estimated multimorbidity prevalence using an open list of chronic diseases. RESULTS: Prevalence estimates were considerably higher for each age group in the primary care sample than in the general population. For primary care patients, the number of chronic diseases considered for estimates resulted in large differences, especially in younger age groups. The prevalence of multimorbidity increased with age in both study populations. CONCLUSIONS: The prevalence of multimorbidity was substantially lower when estimated in a general population than in a family practice-based sample and was higher when the number of conditions considered increased.