The burden of multimorbidity
TL;DR: Mark Greener summarises the latest research on how long-term conditions cluster together and suggests that the next generation of climate scientists will have to consider these relationships in more detail than ever before.
Abstract: Mark Greener summarises the latest research on how long-term conditions cluster together
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TL;DR: Patients with one or more chronic diseases including diabetes, dyslipidemia, hypertension, osteoporosis, chronic lung disease, chronic kidney disease and arthritis should be encouraged to develop effective self-management strategies to manage multiple chronic diseases.
Abstract: Self-management strategies are essential for improving prognosis in chronic illnesses. This study aimed to investigate the association between comorbidity and self-management strategies. A total of 700 patients with one or more chronic diseases including diabetes, dyslipidemia, hypertension, osteoporosis, chronic lung disease, chronic kidney disease and arthritis were enrolled. A questionnaire including the Smart Management Strategy for Health Assessment Tool Short Form (SAT), the Short Form-12, the McGill Quality of Life questionnaire, and the Patient Health Questionnaire-9 was administered to participants. The trend of each SAT according to number of comorbidities was evaluated, and the difference in quality of life and depression according to self-management strategies was examined in the model classified by the number of diseases. Self-management strategy scores tended to decrease as the number of comorbidities increased from one to four (p-value: 0.001 to 0.008). Regardless of the number of comorbidities, the MQOL score was higher in the good self-management strategy group (p: <0.001 to 0.016). The prevalence of mild depression was higher in patients with low self-management strategy, but the differences were not significant. Based on these findings, self-management strategies should be evaluated multidimensionally, and patients should be encouraged to develop effective self-management strategies to manage multiple chronic diseases.
18 citations
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Journal Article•
TL;DR: This review summarizes the available evidence supporting the existence of microbiota-GBA interactions, as well as the possible pathophysiological mechanisms involved, and describes the importance of gut microbiota in influencing these interactions.
Abstract: The gut-brain axis (GBA) consists of bidirectional communication between the central and the enteric nervous system, linking emotional and cognitive centers of the brain with peripheral intestinal functions. Recent advances in research have described the importance of gut microbiota in influencing these interactions. This interaction between microbiota and GBA appears to be bidirectional, namely through signaling from gut-microbiota to brain and from brain to gut-microbiota by means of neural, endocrine, immune, and humoral links. In this review we summarize the available evidence supporting the existence of these interactions, as well as the possible pathophysiological mechanisms involved. Most of the data have been acquired using technical strategies consisting in germ-free animal models, probiotics, antibiotics, and infection studies. In clinical practice, evidence of microbiota-GBA interactions comes from the association of dysbiosis with central nervous disorders (i.e. autism, anxiety-depressive behaviors) and functional gastrointestinal disorders. In particular, irritable bowel syndrome can be considered an example of the disruption of these complex relationships, and a better understanding of these alterations might provide new targeted therapies.
1,476 citations
02 Mar 2021
TL;DR: Mental health problems, pain, and at-risk behaviours leading to cardiovascular diseases are the important clusters identified in this young, urban population.
Abstract: Background Globally, there is increasing research on clusters of multimorbidity, but few studies have investigated multimorbidity in urban contexts characterised by a young, multi-ethnic, deprived populations. This study identified clusters of associative multimorbidity in an urban setting. Methods This is a population-based retrospective cross-sectional study using electronic health records of all adults aged 18 years and over, registered between April 2005 to May 2020 in general practices in one inner London borough. Multiple correspondence analysis and cluster analysis was used to identify groups of multimorbidity from 32 long-term conditions (LTCs). Results The population included 41 general practices with 826,936 patients registered between 2005 and 2020, with mean age 40 (SD15·6) years. The prevalence of multimorbidity was 21% (n = 174,881), with the median number of conditions being three and increasing with age. Analysis identified five consistent LTC clusters: 1) anxiety and depression (Ratio of within- to between- sum of squares (WSS/BSS Interpretation Mental health problems, pain, and at-risk behaviours leading to cardiovascular diseases are the important clusters identified in this young, urban population. Funding Impact on Urban Health, United Kingdom.
22 citations