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BACKGROUND: In countries with high life expectancy, a growing share of the population is living with several diseases, a situation referred to as multi-morbidity. In addition to health data, cause-of-death data, based on the information reported on death certificates, can help monitor and characterize this situation. This requires going beyond the underlying cause of death and accounting for all causes on the death certificates which may have played various roles in the morbid process, depending on how they relate to each other. METHODS: Apart from the underlying cause, the cause-of death data available in vital registration systems do not differentiate all other causes. We developed an algorithm based on the WHO rules that assigns a role to each entry on the death certificate. We distinguish between the following roles: originating (o), when the condition has initiated a sequence of events leading directly to death; precipitating (p), when it was caused by an originating condition or one of its consequences; associated (a), when it contributed to death but was not part of the direct sequence leading to death; ill-defined (i), i.e., conditions such as symptoms or signs or poorly informative causes. We applied this algorithm to all death records in four countries (Italy, France, Spain and the US) in 2017. RESULTS: The average number of originating causes is similar in the four countries. The proportion of death certificates with more than one originating cause-a situation typical of multi-morbidity-ranges from 10% in the US to 18% in Spain. All ages combined, the proportion of deaths with at least one associated cause is higher in Italy (41%) and in the US (42%) than in France (29%) and in Spain (27%). It is especially high in the US at all adult ages. Variations in the average number of causes between the four countries are mainly due to precipitating and ill-defined causes. CONCLUSIONS: The output of our algorithm sheds light on cross-country differences in the average number of causes on death certificates. It also opens the door for improvements in the methods used for multiple cause-of-death analysis.

BACKGROUND: Older adults with multimorbidity are under-represented in clinical drug trials. Their inclusion will not increase unless they are willing and able to participate. Data on motivators and barriers to participation in trials of new medications of older adults with multimorbidity are needed. METHODS: Cross-sectional internet and telephone survey of a nationally representative sample of adults ≥65 years with ≥3 chronic conditions (NORC University of Chicago Amerispeak Panel) conducted from March-April, 2023 to determine motivators and barriers to drug trial participation, described graphically and using statistics. RESULTS: Surveyed 1318 (1142 Internet, 176 phone) with mean age 72.3 ± 6.3 (SD), 52% women; race: 83% White, 10% Black or African American, 5% Hispanic or Latino, 1.1% Asian; 4.4 ± 1.9 chronic conditions (of 16 queried), taking 7.5 ± 3.3 medications. Barriers included fear of side effects (48%), taking too many medications (44%), placebo (44%), mobility (33%), bathroom needs (25%), hearing (19%), eyesight (15%), video visits (33%; higher in women, Black or African-American respondents, and those ≥80 years). Sixty-five percent would join all in-person trials, 49% would join all-video trials. Travel >1 h was difficult for 66%, most difficult for women. Trust was a concern in 25% of Black respondents. Caregiving responsibilities or lack of time were not obstacles. Participants were most likely to consider a drug trial for a problem they have (63%) versus prevention (44%) and if invited by a physician (80%) or University healthcare system (58%). Getting better care was ranked very important (79%) followed by helping others (57%). CONCLUSIONS: Major concerns of older patients with multimorbidity about participation in drug trials are potential side effects, taking too many medicines, and video visits. Physicians have the greatest influence on decisions and in-person visits are preferred. Proposed changes in trial design to increase enrollment of under-represented older adults may not align with patient-reported preferences.

Purpose: The relationship between the number of chronic diseases and oral health problems is unclear. We sought to determine whether the number of chronic diseases and multimorbidity have an association with oral health problems in Korean adults. Materials and Methods: Data from 23,246 adults aged ≥ 19 years, who participated in the Korea National Health and Nutrition Examination Survey from 2016 to 2019, were considered for our analyses. Participants with either masticatory or speech problems were defined as the oral health problems group. Individuals who reported having had dental treatment in the last year were defined as the dental treatment group. We used multivariable logistic regression analyses to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Results: The proportions of oral health problems and dental treatment were higher in participants with multimorbidity than in those without multimorbidity (all p < 0.001). Moreover, ORs of oral health problems demonstrated a tendency to increase with the number of chronic diseases, even after adjustment (p for trend < 0.001). Compared to the participants without multimorbidity, the risk of having oral health problems increased by 25% (OR: 1.25, 95% CI: 1.12–1.39), and that of receiving dental treatment increased by 23% (OR: 1.23, 95% CI: 1.13–1.34) in patients with multimorbidity. Conclusion: The risk of oral health problems and dental treatment increased in association with the number of chronic diseases in Korean adults. The authors emphasise the risks and importance of oral health in a large population affected by multiple chronic diseases. [ABSTRACT FROM AUTHOR]

India is a large middle-income country and has surpassed China in overall population, comprising 20% of the global population (over 1.43 billion people). India is experiencing a major demographic shift in its aging population. Chronic diseases are common among older adults and can be persistent over the life course, lead to the onset of disability, and be costly. Among older adults in India, the existence of multiple comorbid chronic conditions (i.e., multimorbidity) is rapidly growing and represents a burgeoning public health burden. Prior research identified greater rates of multimorbidity (e.g., overweight/obesity diabetes, hypertension, cardiovascular disease, stroke, and malignancies) in minority populations in the United States (U.S.); however, limited studies have attempted to characterize multimorbidity among older adult sub-populations residing in India. To address this gap, we conducted a narrative review of studies on multimorbidity using the data from the Longitudinal Aging Study of India (LASI), the largest nationally representative longitudinal survey study of adults in India. Our definition of multimorbidity was the presence of more than two conditions in the same person. Our findings, based on 15 reviewed studies, aim to (1) characterize the definition and measurement of multimorbidity and to ascertain its prevalence in ethnically and culturally diverse sub-populations in India; (2) identify adverse outcomes associated with multimorbidity in the Indian adult population; and (3) identify gaps, opportunities, and future directions.

Purpose: The symptom representations (i.e., beliefs and attitudes) that people with cancer hold about their symptom experience can impact how they self-manage their symptoms. Having two or more chronic conditions (multimorbidity) can complicate illness representations. Little is known about symptom representations in people with cancer and multimorbidity. Methods: This qualitative descriptive study was conducted with a sample of adults with a diagnosis of cancer and at least one additional chronic condition. Semi-structured interviews were conducted to understand their symptom representations. Leventhal’s Common-Sense Model of Illness Representations (i.e., identity, consequences, cure/control, timeline, and cause) provided the guiding framework. A qualitative thematic analysis was used to identify codes, themes, and subthemes. Results: The mean age of the participants (n = 17) was 62.1 years and primary cancer sites were gastrointestinal, thoracic, or head/neck. Five themes were identified: (1) perceiving and living with symptoms, (2) being unable to do things, (3) self-management behaviors, (4) domino theory, and (5) a side effect of conditions. These themes aligned with Leventhal’s Common-Sense Model dimensions. The interaction among diagnoses and multimorbidity was identified by a minority of participants. Conclusion: People with cancer and multimorbidity described symptom representations primarily in the context of cancer. Consistent with previous research, symptoms negatively impacted their lives, and their representations include an understanding of how symptoms interact. Few participants described their symptoms within the larger context of multimorbidity. Future research is needed to determine how symptom representations impact their communication patterns with providers and coping behaviors. [ABSTRACT FROM AUTHOR]

The transition from a comorbidity-based to a multimorbidity-focused to ultimately a network medicine approach in people with rheumatic diseases might mark a significant shift in how we understand and manage these complex conditions. Multimorbidity expands on the concept of comorbidity by encompassing the presence of multiple diseases, which results in further individual and societal impacts. This approach, while valuable, often leads to fragmented care focused on individual diseases rather than the patient as a whole. Network medicine, on the other hand, offers a more integrated perspective. It is an emerging concept that leverages the understanding of biologic networks and their interactions within the human body to gain insights into disease mechanisms. In the context of rheumatic diseases, network medicine involves examining how different diseases interconnect and influence each other through shared pathways, genetic factors, and molecular mechanisms. This paradigm shift allows for a more holistic understanding in how we manage rheumatic diseases. For instance, rheumatic diseases such as rheumatoid arthritis and systemic lupus erythematosus are not just a collection of symptoms affecting various organs but are also interconnected through underlying systemic inflammatory processes, immune system dysregulation, and genetic predispositions. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity has emerged as a significant challenge for healthcare systems globally. This study aims to examine the associations between key determinants of lifestyle behavior and various multimorbidity patterns. Methods: In a cross-sectional sample of older adults (aged 60–79) from the Fifth National Physical Fitness Surveillance in Shanghai, latent class analysis (LCA) was used to identify multimorbidity patterns among 9 chronic diseases. Multinomial logistic regression was performed to analyze the associations between sedentary time, sleep duration, physical exercise, and the different multimorbidity patterns. Weighted analysis was performed to appropriately account for complex sampling designs and provide more robust results. Results: Among 13,465 study participants (unweighted mean age 69.3 years; weighted mean age 67.4 years, 50.7% female), the overall prevalence of multimorbidity was 40.9%–42.3%. Four latent classes among the older adults were identified, with the relatively healthy class (63.6%–64.6%) had an average of less than 1 chronic disease. The other 3 classes, namely the metabolic-cardiovascular-joint-digestive-respiratory disease class (2.9%–3.0%), the metabolic-cardiovascular disease class (14.5%–15.5%), and the joint-digestive-respiratory disease class (17.9%–18.0%), each had an average of more than 2 chronic diseases, representing different multimorbidity patterns. Prolonged sedentary time (> 3 h/day) increased the odds of belonging to the metabolic-cardiovascular-joint-digestive-respiratory disease class by 56%–57% (unweighted odds ratio [OR] 1.57, 95% confidence interval [CI] 1.27–1.94; weighted OR 1.56, 95% CI 1.36–1.80), the metabolic-cardiovascular disease class by 38% (unweighted OR 1.38, 95% CI 1.25–1.53; weighted OR 1.38, 95% CI 1.29–1.48), and the joint-digestive-respiratory disease class by 30%–32% (unweighted OR 1.32, 95% CI 1.19–1.45; weighted OR 1.30, 95% CI 1.22–1.38). Shorter sleep duration (< 7 h/day) also increased the odds of membership in the metabolic-cardiovascular disease class by 48%–49% (unweighted OR 1.49, 95% CI 1.35–1.65; weighted OR 1.48, 95% CI 1.38–1.58), the metabolic-cardiovascular-joint-digestive-respiratory disease class by 37%–47% (unweighted OR 1.47, 95% CI 1.19–1.80; weighted OR 1.37, 95% CI 1.19–1.58), and the joint-digestive-respiratory disease class by 41%–42% (unweighted OR 1.42, 95% CI 1.29–1.56; weighted OR 1.41, 95% CI 1.32–1.50). Each additional daily hour of low-intensity physical exercise (LIPE) reduced the odds of membership in the metabolic-cardiovascular-joint-digestive-respiratory disease class by 24%–25% (unweighted OR 0.76, 95% CI 0.64–0.90; weighted OR 0.75, 95% CI 0.66–0.84), the joint-digestive-respiratory disease class by 20%–21% (unweighted OR 0.79, 95% CI 0.73–0.86; weighted OR 0.80, 95% CI 0.76–0.85), and the metabolic-cardiovascular disease class by 11%–12% (unweighted OR 0.88, 95% CI 0.81–0.95; weighted OR 0.89, 95% CI 0.85–0.94). Compared to LIPE, high-intensity physical exercise (HIPE) showed a significant advantage only in reducing the odds of the metabolic-cardiovascular disease class by 18%–23% (unweighted OR 0.77, 95% CI 0.62–0.97; weighted OR 0.82, 95% CI 0.71–0.95). Conclusions: Over 40% of older adults in Shanghai, China, suffer from multimorbidity. Prolonged sedentary behavior and shorter sleep duration were associated with membership in the metabolic-cardiovascular-joint-digestive-respiratory disease class, the metabolic-cardiovascular disease class, and the joint-digestive-respiratory disease class. Physical exercise showed varying degrees of protection against these 3 multimorbidity patterns, with special attention warranted for LIPE. Identifying the relationship between determinants of lifestyle behavior and patterns of multimorbidity can help develop more targeted prevention and management strategies. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity is a growing global concern, affecting patient outcomes and healthcare costs. In low- and middle-income countries, data on multimorbidity in primary care beyond prevalence is limited. Our study explored the demographic and clinical characteristics of multimorbidity among older people attending primary health care in Malawi. Methods: We conducted a cross-sectional analysis on medical records from 15,009 older patients aged ≥50 years across three hospitals in Malawi (one tertiary, two district). Data from 2019-2021 was analyzed using R statistical software to examine patterns of multimorbidity (two or more chronic conditions). Outcome estimates were adjusted for sex, age, location, and year of clinic visit. Results: The overall prevalence of multimorbidity, defined across 17 recorded chronic conditions, was 19.6%. Among the 2,941 cases of multimorbidity, 2,708 (92.0%) involved two chronic conditions, while 233 (8.0%) involved three. While most conditions increased steadily in prevalence with age, diabetes followed a different pattern, with higher prevalence among individuals aged 50–59 years (53.9%) and 60–69 years (52.4%) compared to those 70 years and older (40.3%). After adjusting for clinic visit year, gender, and study location, individuals aged 70 years and older were significantly less likely to have multimorbidity compared to those aged 50–59 years (AOR = 0.57, 95% CI: 0.52–0.62, p < 0.001). Conclusion: The study revealed a wide range of multimorbidity combinations among older people attending primary health care. Strategies to address multimorbidity in older people should include efforts to identify other, less common clusters of chronic conditions. [ABSTRACT FROM AUTHOR]