Diabetes multimorbidity combinations and disability in the Mexican Health and Aging Study, 2012–2015

PurposeThe aim of this study was to investigate the relationship between specific combinations of chronic conditions and disability in Mexican older adults with diabetes.MethodsThis was a prospective cohort study of Mexican adults (n = 2558) with diabetes and aged 51 or older that used data from the 2012 and 2015 waves of the Mexican Health and Aging Study. The main outcome was an index that measured ability to perform activities of daily living and instrumental activities of daily living. The main independent variables were diabetes multimorbidity combinations, defined as diabetes and at least one other chronic condition. The authors calculated the prevalence of each multimorbidity combination present in the sample in 2012 and used negative binomial regression models to estimate the association of the most prevalent of these combinations with disability incidence in 2015.ResultsThe three most prevalent combinations were: 1) diabetes-hypertension (n = 637, 31.9%) 2) diabetes-hypertension-depression (n = 388, 19.4%) and 3) diabetes-depression (n = 211, 10.6%). In fully adjusted models comparing participants with specific multimorbidity combinations to participants with diabetes alone, the combinations that had an increased association with disability were diabetes-hypertension-depression, diabetes-depression and diabetes-hypertension-arthritis-depression. In nested models, the addition of arthritis to combinations including depression increased this association.ConclusionsConsistent with prior studies, multimorbidity combinations including depression were associated with increased risk of disability. However, the effect size of this relationship was lower than what had been previously been reported internationally. This highlights the need for globally oriented multimorbidity research.     

Symptom Burden and Palliative Care Needs Among High-Risk Veterans With Multimorbidity

Context

Palliative care research has focused on patients with disease-specific conditions. However, older patients with multimorbidity may have unmet palliative care needs.

锦州市老年人群共病疾病负担研究

目的 了解锦州市65岁及以上人群共病及疾病负担现状,为完善老年人群共病的管理提供理论依据。方法 采用分层整群随机抽样方法,抽取锦州市65岁及以上老年人群为研究对象,描述老年人群共病的流行病学分布特征,采用疾病负担分析指标——伤残调整寿命年（disability adjusted of life years, DALY）,伤残损失寿命年（years lived with disability, YLD）和早逝损失寿命年（years of life lost due to premature death, YLL）计算共病的疾病负担。结果 锦州市65岁及以上的老年人群共病患病率为19.66%,死亡率为14.12%;DALY为3 970.779人年,YLD为1 680.120人年,YLL为2290.695人年;其最主要的共病模式为高血压+冠心病,DALY为968.200人年;各年龄组间共病模式与DALY的差异均具有统计学意义（F = 90.498,P＜0.001）,男性和女性的DALY差异无统计学意义（t = 0.817,P = 0.414）。结论 锦州市老年人群共病模式为冠心病、高血压、脑卒中、糖尿病和肿瘤等疾病中某两种组合;老年人群共病疾病负担以死亡所造成的生命损失为主;共病的疾病负担在85岁及以上的年龄段最高。     

Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis

ObjectivesTo investigate the use of latent class growth analysis (LCGA) in understanding onset and changes in multimorbidity over time in older adults.Study Design and SettingThis study used primary care consultations for 42 consensus-defined chronic morbidities over 3 years (2003–2005) by 24,615 people aged >50 years at 10 UK general practices, which contribute to the Consultations in Primary Care Archive database. Distinct groups of people who had similar progression of multimorbidity over time were identified using LCGA. These derived trajectories were tested in another primary care consultation data set with linked self-reported health status.ResultsFive clusters of people representing different trajectories were identified: those who had no recorded chronic problems (40%), those who developed a first chronic morbidity over 3 years (10%), a developing multimorbidity group (37%), a group with increasing number of chronic morbidities (12%), and a multi-chronic group with many chronic morbidities (1%). These trajectories were also identified using another consultation database and associated with self-reported physical and mental health.ConclusionThere are distinct trajectories in the development of multimorbidity in primary care populations, which are associated with poor health. Future research needs to incorporate such trajectories when assessing progression of disease and deterioration of health.