Increase In Multimorbidity Research Articles

Antibiotic Resistance in the Elderly: Mechanisms, Risk Factors, and Solutions.

Antibiotic resistance presents a critical challenge in healthcare, particularly among the elderly, where multidrug-resistant organisms (MDROs) contribute to increased morbidity, mortality, and healthcare costs. This review focuses on the mechanisms underlying resistance in key bacterial pathogens and highlights how aging-related factors like immunosenescence, frailty, and multimorbidity increase the burden of infections from MDROs in this population. Novel strategies to mitigate resistance include the development of next-generation antibiotics like teixobactin and cefiderocol, innovative therapies such as bacteriophage therapy and antivirulence treatments, and the implementation of antimicrobial stewardship programs to optimize antibiotic use. Furthermore, advanced molecular diagnostic techniques, including nucleic acid amplification tests and next-generation sequencing, allow for faster and more precise identification of resistant pathogens. Vaccine development, particularly through innovative approaches like multi-epitope vaccines and nanoparticle-based platforms, holds promise in preventing MDRO infections among the elderly. The role of machine learning (ML) in predicting resistance patterns and aiding in vaccine and antibiotic development is also explored, offering promising solutions for personalized treatment and prevention strategies in the elderly. By integrating cutting-edge diagnostics, therapeutic innovations, and ML-based approaches, this review underscores the importance of multidisciplinary efforts to address the global challenge of antibiotic resistance in aging populations.

The Longitudinal Relationship between Edentulism and the Progress of Multimorbidity.

To examine the longitudinal relationship between edentulism, nutritional intake, and the progress of multimorbidity among older Americans. We used data from the Health and Retirement Study (2006-2018), a longitudinal survey of older Americans that has collected data biennially since 1992. Edentulism was assessed in 2006 while nutritional intake was assessed in 2013. Multimorbidity was indicated by five self-reported chronic conditions: diabetes, heart conditions, lung diseases, cancer, and stroke. Individuals with two or more conditions at baseline were excluded from the analysis. Nutritional intake was calculated by summing 10 nutrients (protein, vitamins C, D, B12 and E, calcium, zinc, polyunsaturated fatty acids, folate, and ß-carotene). Structural equation modelling (SEM) was used to examine the nutritional pathway between edentulism (2006) and the increase in multimorbidity from 2006 to 2018. The number of individuals included in the analysis was 3463. The incidence of multimorbidity between 2006 and 2018 was 24.07%, while the percentage of edentate participants in 2006 was 16.42%. The mean total nutrition in 2013 was 4.50 (4.43, 4.55). The SEM analysis showed that edentulism was negatively associated with nutritional intake {estimate -0.15 (95%CI: -0.30, -0.01)}. A negative association was found between total nutrition and multimorbidity {estimate -0.008 (95%CI: -0.01, -0.002)}. Age, wealth, and smoking were included in the analysis and had statistically significant associations with multimorbidity. The analysis demonstrated a longitudinal association between edentulism, nutritional intake, and the progress of multimorbidity.

P037 Rheum for more? A systematic literature review on undergraduate exposure to rheumatology

Abstract Background/Aims Since the introduction of Modernising Medical Careers by the General Medical Council in the United Kingdom (UK) in 2007, newly-qualified doctors are expected to choose their specialty much sooner than previously. A recent report published by the British Society of Rheumatology (BSR) in 2021 demonstrated a lack of exposure to the specialty for medical students. We conducted a systematic literature review on the quantity and quality of rheumatology teaching amongst undergraduate medical students. Methods Articles published until June 2023 were included. Eligible articles were: case reports and series, observational studies, qualitative studies and randomised control trials. Medline, Embase, PyscINFO, Cochrane library and WHO international clinical trial registry were searched, restricted to English language articles only. Articles including postgraduate trainees and those pertaining to a single intervention or single student cohort were excluded. Information was extracted on demographics, method of teaching, hours dedicated to rheumatology and students’ and educators’ feedback where mentioned. Results After deduplication, 1195 article were identified. After screening title and abstract, 1156 papers were excluded, with 39 proceeding to full text screening. Ultimately, seven articles (all cross-sectional surveys) were included. Publication year of included articles ranged from 1981 to 2018. The countries of included studies were UK (3), USA (2), Australian (1) and Pan-European (1). Year of rheumatology teaching at medical school was reported in four studies (3 UK and 1 USA). The three UK studies were all taught in the latter years (4-6), whereas in the USA study the students were taught at every single year. Where reported, data on the number of hours of exposure to rheumatology were variable, ranging from 15 to 96 hours per medical student. Reported method of teaching included lecture-based, rheumatology inpatient service and shadowing consultations. Student feedback was only provided in one (UK-based) study, from 49 students of whom two regarded rheumatology as “fascinating”, four felt that they had limited exposure and eight considered it as “a niche specialty of no interest”. No feedback from educators were collected in any of the included studies. Factors identified by the included studies for overall poor exposure to rheumatology included: lack of having full-time rheumatologists on the school’s faculty, lack of specialty training programme in their local teaching hospital and greater emphasis on general medical/ acute specialties (e.g. general practice and emergency medicine). Conclusion Overall, there are significant limitations in recording the amount and quality of rheumatology teaching amongst undergraduate medical students. Exposure to clinical rheumatology has markedly decreased over time, with variable student awareness of the speciality. Given the ageing UK population and increase in multimorbidity, there is a need to increase exposure and entry to the specialty, which may be partly facilitated by improved incorporation of rheumatology in the undergraduate curriculum. Disclosure K. Kouranloo: None. N. Myall: None. J. Christie: None.

Brief report: Effect of cardiac multi-morbidity on COVID hospitalization outcomes.

The COVID-19 pandemic has stretched healthcare resources thin and led to significant morbidity and mortality. There have been no studies utilizing national data to investigate the role of cardiac risk factors on outcomes of COVID hospitalizations. The aim of this study was to examine the effect of cardiac multimorbidity on healthcare utilization and outcomes among COVID hospitalizations during the first year of the pandemic. Using the national inpatient sample (NIS), we identified all adult hospital admissions with a primary diagnosis of COVID in 2020, using International Classification of Diseases, Tenth Revision, Clinical Modification codes (ICD010-CM). Coronary artery disease, diabetes mellitus, heart failure, peripheral vascular disease, previous stroke, and atrial fibrillation were then identified as cardiac comorbidities using ICD-10-CM codes. Multivariable logistic regression was used to evaluate the effect of cardiac multimorbidity on mortality and mechanical ventilation. We identified 1,005,040 primary COVID admissions in 2020. Of these admissions, 216,545 (20.6%) had CAD, 413,195 (39.4%) had DM, 176,780 (16.8%) had HF, 159,700 (15.2%) had AF, 30735 (2.9%) had PVD, and 25,155 (2.4%) had a previous stroke. When stratified by number of comorbidities, 428390 (40.8%) had 0 comorbidities, 354960 (33.8%) had 1, 161225 (15.4%) had 2, and 105465 (10.0%) had 3+ comorbidities. COVID hospitalizations with higher cardiac multimorbidity had higher mortality rates (p<0.001) higher MV rates (p<0.001). In our multivariable regression, these associations remained with increasing odds for mortality with each stepwise increase in cardiac multimorbidity (1: OR 1.48 (1.45-1.50); 2: OR 2.13 (2.09-2.17); 3+: OR 2.43 (2.38-2.48), p<0.001, all). Our study is the first national examination of the impact of cardiac comorbidities on COVID outcomes. A higher number of cardiac comorbidities was associated with significantly higher rates of MV and in-hospital mortality, independent of age. Future, more granular, and longitudinal studies are needed to further examine these associations.

Abstract 96: Temporal Trends in Vascular Risk Factor Burden Among Young Adults With Ischemic Stroke: The Florida Stroke Registry

Introduction: While ischemic stroke (IS) in the young (18-55) is thought to have different etiologies than in older patients, a rise in vascular risk factors (VRFs) among young adults may translate to an IS risk profile similar to the older population. We aimed to examine the prevalence of VRFs and temporal trends in VRF burden among young patients presenting with IS. Methods: Data was prospectively collected by Get With the Guidelines-Stroke® hospitals participating in the Florida Stroke Registry between January 2010 and December 2022. Patients aged 18-55 with a diagnosis of IS were included and separated into two age groups: 18-35 and 36-55. VRFs included hypertension, dyslipidemia, obesity, smoking, atrial fibrillation, coronary artery disease, heart failure, diabetes, and sleep apnea. Multimorbidity was defined as having ≥4 VRFs. Results: 47,792 patients with IS were included (43% female, median age 49, 51% white), comprising 4,275 patients aged 18-35 (8.9%) and 43,517 aged 36-55 (91.1%). The prevalence of each VRF was higher among patients aged 36-55 vs 18-35 (all p values &lt;0.001), and only 15.3% of patients aged 36-55 and 40.0% of patients aged 18-35 had 0 VRFs. African American patients with IS had a significantly higher prevalence of multimorbidity than white or non-white Hispanic patients; specifically in those aged 18-35 (6.1% vs 3.5% vs 3.5%, p &lt;0.001), while those aged 36-55 demonstrated a smaller difference (17.6% vs 17.2% vs 15.4% p &lt;0.001).VRF burden worsened across the study period, with an increase in multimorbidity from 11.2% to 21.7% in patients 36-55 (p&lt;0.0001) and from 1.3% to 6.6% in patients 18-35 (p= 0.0006). Conclusions: Increasingly, young stroke patients have traditional VRFs. The prevalence of multimorbidity disproportionately affects African American patients and has significantly increased over the past 12 years. Efforts targeting VRFs reduction must start as early as possible in light of the rise in VRF burden amongst young IS patients.

Prognostication of co-morbidity clusters on hospitalisation and mortality in advanced COPD

RationaleAs the prevalence of multimorbidity increases, understanding the impact of isolated comorbidities in people COPD becomes increasingly challenging. A simplified model of common comorbidity patterns may improve outcome prediction and allow targeted therapy. ObjectivesTo assess whether comorbidity phenotypes derived from routinely collected clinical data in people with COPD show differences in risk of hospitalisation and mortality. MethodsTwelve clinical measures related to common comorbidities were collected during annual reviews for people with advanced COPD and k-means cluster analysis performed. Cox proportional hazards with adjustment for covariates was used to determine hospitalisation and mortality risk between clusters. Measurements and main resultsIn 203 participants (age 66 ± 9 years, 60 % male, FEV1%predicted 31 ± 10 %) no comorbidity in isolation was predictive of worse admission or mortality risk. Four clusters were described: cluster A (cardiometabolic and anaemia), cluster B (malnourished and low mood), cluster C (obese, metabolic and mood disturbance) and cluster D (less comorbid). FEV1%predicted did not significantly differ between clusters. Mortality risk was higher in cluster A (HR 3.73 [95%CI 1.09–12.82] p = 0.036) and B (HR 3.91 [95%CI 1.17–13.14] p = 0.027) compared to cluster D. Time to admission was highest in cluster A (HR 2.01 [95%CI 1.11–3.63] p = 0.020). Cluster C was not associated with increased risk of mortality or hospitalisation. ConclusionsDespite presence of advanced COPD, we report striking differences in prognosis for both mortality and hospital admissions for different co-morbidity phenotypes. Objectively assessing the multi-system nature of COPD could lead to improved prognostication and targeted therapy for patients.

The Prevalence of Frailty and Associated Factors, Including Food Security in Community Dwelling Older Adults with Multimorbidity: A Cross-Sectional Analysis from the Longitudinal Aging Study in India.

The global increase in multimorbidity among older adults is a result of ongoing epidemiological and demographic transitions. This study focuses on the prevalence and determinants of frailty in this demographic in India, accounting for the potential mediating role of food insecurity. To determine the prevalence and determinants of frailty among older Indian adults with multimorbidity, and to ascertain the mediating effect of food insecurity on frailty. Cross-sectional analysis of cohort study data. Analysis of data from the Longitudinal Aging Study in India (LASI) Wave 1 (2017-2018). 31,902 individuals aged 60 and above of whom 7900 were categorized as having multimorbidity. Frailty was assessed using a modified Fried scale. Details on sociodemographic factors, lifestyle choices, and health-related variables were collected through face-to-face participant interviews. Multimorbidity was defined as the presence of two or more chronic conditions such as hypertension, diabetes, cancer, chronic lung disease, chronic heart disease, stroke, bone disease, neurological or psychiatric problems, and high cholesterol. Statistical analysis was conducted using Stata 15.1. The weighted prevalence of frailty in individuals with multimorbidity was 30.31% (95% CI: 28.17, 32.54), significantly higher than those without multimorbidity (23.81%, 95% CI: 22.90, 24.74) (P<0.001). Frailty prevalence was higher in women (33.27%) than in men (26.56%) among those with multimorbidity. In the group with multimorbidity, age ≥75 (years), middle MPCE quintile, lower educational attainment, unemployment, and low body mass index was associated with higher odds of frailty. Mediation analysis showed that 3.47% of the association between multimorbidity and frailty was mediated by food insecurity. Frailty is prevalent among older adults with multimorbidity in India, with significant disparities based on gender, age, socioeconomic status, and body mass index. Food insecurity partially mediates the relationship between multimorbidity and frailty, highlighting the need for targeted interventions addressing both health and nutritional insecurities in this population.

Socioeconomic Status Plays a Moderating Role in the Association Between Multimorbidity and Health-Related Quality of Life Among Cancer Patients.

This study aimed to explore the moderating role of socioeconomic status (SES) in the association between multimorbidity and health-related quality of life (HRQOL) among cancer patients in Anhui China. A total of 560 cancer patients were recruited for the cross-section study. Socio-demographic and clinical characteristics were analyzed using descriptive statistics. Tobit regression analysis was employed to investigate the relationship between multimorbidity and HRQOL as well as to assess the moderating effect of SES. The research findings indicated that 76.61% of cancer patients experienced multimorbidity, with psychological multimorbidity being the most prevalent (45.54%), followed by physical-psychological multimorbidity (20.89%). Moreover, physical-psychological multimorbidity had the most substantial adverse effect on HRQOL (P < .001). The presence of multimorbidity was correlated with a significant decline in HRQOL, with a 17.5% (P < .001) decrease in HRQOL for each additional multimorbidity. Additionally, SES played a significant role in moderating the impact of multimorbidity on HRQOL in cancer patients. (Marginal effect = -0.022, P < .01). The high SES group exhibited a higher overall HRQOL than the low SES group (Marginal effect = 0.068, P < .001). And with the increase of multimorbidity, HRQOL in the higher SES showed a more pronounced downward trend, compared with the lower SES (β = -.270 vs β = -.201, P < .001). Our findings underscore the importance of preventing and managing multimorbidity in cancer patients, particularly those with low SES. Furthermore, it is essential to consider the impact of the rapid decline in HRQOL as the number of multimorbidity increases in individuals with higher SES. It is imperative to explore interdisciplinary and continuous collaborative management models.

Goal-oriented care through the eyes of people with chronic conditions

Background: The healthcare system is faced by an increase in chronic conditions and multimorbidity. People with chronic conditions (i.e., ‘patients’) are often confronted with an overload of tasks (e.g., medication management, control visits) prescribed by multiple providers to manage their conditions. As a result, they are at risk of fragmented care. A strategy to integrate the different processes might be to explicitly focus on the patients’ personal goals. Goal-oriented care (GOC) reorients care from ‘what is the matter with the patient’ to ‘what matters to the patient’ and specifically addresses patients’ personal goals. However, little is known about GOC. Especially about whether and how patients experience GOC during their primary care visits. The aim of this study is to understand the concept of GOC through the patients’ experiences. &#x0D; Method: Interviews with people with chronic conditions (n=50) were analyzed in two ways. A deductive approach based on the GOC attributes generated in a concept analysis on GOC: goal-elicitation, goal-setting, goal-evaluation, patients’ context, and patients’ needs and preferences. An inductive approach based on a thematic analysis using descriptive phenomenology to identify additional aspects of GOC.&#x0D; Results: The phase of goal-elicitation was recognized by participants, whereas goal-setting and goal-evaluation were experienced in lesser extent. Regarding the underpinning attributes, mixed feelings were reported concerning the integration of the patients’ context and the presence of their needs and preferences throughout the care process. The inductive analysis revealed specific attention to informing patients about their condition and treatment options and discussing goals in interprofessional collaboration. &#x0D; Conclusion: Goal-elicitation was already present and seems to be a good foundation for GOC. More attention should be given to goal-setting and goal-evaluation. Developing guidance by means of a workflow, tools, or questions might support people with chronic conditions and providers to underpin the entire care process with the patients’ personal goals. &#x0D; &#x0D; &#x0D;

Association of Benign Prostatic Hyperplasia With Multimorbidity Among Older Adults: Insights From the Longitudinal Ageing Study in India (LASI), First Wave.

Introduction Population ageing is expected to be accompanied by an increase in multi-morbidity, i.e. the co-occurrence of multiple chronic conditions simultaneously. Benign prostatic hyperplasia (BPH) is a non-malignant disease prevalent in ageing men. Both BPH and multi-morbidity are known to have a significant impact on quality of life. The objective of this study was to determine the association between BPH and multimorbidity amongolder adults and the elderlypopulation in India. Methods This is an analytical cross-sectional study involving secondary data from the nationally representative Longitudinal Ageing Study in India (LASI) Wave I 2017-18. Multivariable logistic regression analysis was conducted to study the association between BPH and multimorbidity while accounting for other associated factors. Results Compared to those having no co-morbidities, the odds of having BPH increased with the increasing number of co-morbidities. Those with at least two co-morbidities were twice as likely (aOR=2.19; 95%CI 1.78-2.72), and those with at least four co-morbidities were almost six times as likely (aOR=5.78; 95%CI 2-16.72) to have BPH as compared to those with no co-morbidities. The association was stronger among males >60 years. Conclusion Self-reported benign prostatic hyperplasia was found to be strongly associated with multi-morbidity. The need of the hour is the inclusion of BPH within the framework of a national health programme. Health technology assessment of high-risk screening strategies for BPH may be conducted among patients with multimorbidity. Research into the impact on the quality of life of those affected by both BPH and multimorbidity will help highlight this as a priority problem for decision-makers.

Polypharmacy in patients with dementia

The number of patients with dementia is expected to grow in the coming years due to an aging population and an increasing life-expectancy. At the same time, in an aging society there will be an increase in multimorbidity and therefore polypharmacy. This combination presents numerous challenges particularly for people with dementia, as the correct administration of the drugs can frequently no longer be guaranteed. The drug treatment of neuropsychiatric symptoms of dementia are often treated with antipsychotics with potentially severe side effects and with limited efficacy. Moreover, many drugs have an anticholinergic potential, which may worsen the cognitive function even further in patients with dementia. The use of anticholinergic drugs should be handled with care and when possible be avoided in patients with dementia.

Development and validation of predictive models for unplanned hospitalization in the Basque Country: analyzing the variability of non-deterministic algorithms

BackgroundThe progressive ageing in developed countries entails an increase in multimorbidity. Population-wide predictive models for adverse health outcomes are crucial to address these growing healthcare needs. The main objective of this study is to develop and validate a population-based prognostic model to predict the probability of unplanned hospitalization in the Basque Country, through comparing the performance of a logistic regression model and three families of machine learning models.MethodsUsing age, sex, diagnoses and drug prescriptions previously transformed by the Johns Hopkins Adjusted Clinical Groups (ACG) System, we predict the probability of unplanned hospitalization in the Basque Country (2.2 million inhabitants) using several techniques. When dealing with non-deterministic algorithms, comparing a single model per technique is not enough to choose the best approach. Thus, we conduct 40 experiments per family of models - Random Forest, Gradient Boosting Decision Trees and Multilayer Perceptrons - and compare them to Logistic Regression. Models’ performance are compared both population-wide and for the 20,000 patients with the highest predicted probabilities, as a hypothetical high-risk group to intervene on.ResultsThe best-performing technique is Multilayer Perceptron, followed by Gradient Boosting Decision Trees, Logistic Regression and Random Forest. Multilayer Perceptrons also have the lowest variability, around an order of magnitude less than Random Forests. Median area under the ROC curve, average precision and positive predictive value range from 0.789 to 0.802, 0.237 to 0.257 and 0.485 to 0.511, respectively. For Brier Score the median values are 0.048 for all techniques. There is some overlap between the algorithms. For instance, Gradient Boosting Decision Trees perform better than Logistic Regression more than 75% of the time, but not always.ConclusionsAll models have good global performance. The only family that is consistently superior to Logistic Regression is Multilayer Perceptron, showing a very reliable performance with the lowest variability.

20-year trends in multimorbidity by race/ethnicity among hospitalized patient populations in the United States

BackgroundThe challenges presented by multimorbidity continue to rise in the United States. Little is known about how the relative contribution of individual chronic conditions to multimorbidity has changed over time, and how this varies by race/ethnicity. The objective of this study was to describe trends in multimorbidity by race/ethnicity, as well as to determine the differential contribution of individual chronic conditions to multimorbidity in hospitalized populations over a 20-year period within the United States.MethodsThis is a serial cross-sectional study using the Nationwide Inpatient Sample (NIS) from 1993 to 2012. We identified all hospitalized patients aged ≥ 18 years old with available data on race/ethnicity. Multimorbidity was defined as the presence of 3 or more conditions based on the Elixhauser comorbidity index. The relative change in the proportion of hospitalized patients with multimorbidity, overall and by race/ethnicity (Black, White, Hispanic, Asian/Pacific Islander, Native American) were tabulated and presented graphically. Population attributable fractions were estimated from modified Poisson regression models adjusted for sex, age, and insurance type. These fractions were used to describe the relative contribution of individual chronic conditions to multimorbidity over time and across racial/ethnic groups.ResultsThere were 123,613,970 hospitalizations captured within the NIS between 1993 and 2012. The prevalence of multimorbidity increased in all race/ethnic groups over the 20-year period, most notably among White, Black, and Native American populations (+ 29.4%, + 29.7%, and + 32.0%, respectively). In both 1993 and 2012, Black hospitalized patients had a higher prevalence of multimorbidity (25.1% and 54.8%, respectively) compared to all other race/ethnic groups. Native American populations exhibited the largest overall increase in multimorbidity (+ 32.0%). Furthermore, the contribution of metabolic diseases to multimorbidity increased, particularly among Hispanic patients who had the highest population attributable fraction values for diabetes without complications (15.0%), diabetes with complications (5.1%), and obesity (5.8%).ConclusionsFrom 1993 to 2012, the secular increases in the prevalence of multimorbidity as well as changes in the differential contribution of individual chronic conditions has varied substantially by race/ethnicity. These findings further elucidate the racial/ethnic gaps prevalent in multimorbidity within the United States.Prior presentationsPreliminary finding of this study were presented at the Society of General Internal Medicine (SGIM) Annual Conference, Washington, DC, April 21, 2017.

Rural-Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45.

Chronic conditions and multimorbidity are increasing worldwide. Yet, understanding the relationship between climate change, air pollution, and longitudinal changes in multimorbidity is limited. Here, we examined the effects of sociodemographic and environmental risk factors in multimorbidity among adults aged 45+ and compared the rural-urban disparities in multimorbidity. Data on the number of chronic conditions (up to 14), sociodemographic, and environmental factors were collected in 4 waves of the China Health and Retirement Longitudinal Study (2011-2018), linked with the full-coverage particulate matter 2.5 (PM2.5) concentration data set (2000-2018) and temperature records (2000-2018). Air pollution was assessed by the moving average of PM2.5 concentrations in 1, 2, 3, 4, and 5 years; temperature was measured by 1-, 2-, 3-, 4-, and 5-year moving average and their corresponding coefficients of variation. We used the growth curve modeling approach to examine the relationship between climate change, air pollution, and multimorbidity, and conducted a set of stratified analyses to study the rural-urban disparities in multimorbidity related to temperature and PM2.5 exposure. We found the higher PM2.5 concentrations and rising temperature were associated with higher multimorbidity, especially in the longer period. Stratified analyses further show the rural-urban disparity in multimorbidity: Rural respondents have a higher prevalence of multimorbidity related to rising temperature, whereas PM2.5-related multimorbidity is more severe among urban ones. We also found temperature is more harmful to multimorbidity than PM2.5 exposure, but PM2.5 exposure or temperature is not associated with the rate of multimorbidity increase with age. Our findings indicate that there is a significant relationship between climate change, air pollution, and multimorbidity, but this relationship is not equally distributed in the rural-urban settings in China. The findings highlight the importance of planning interventions and policies to deal with rising temperature and air pollution, especially for rural individuals.

Temporal Trend of Multimorbidity of Noncommunicable Diseases among Brazilian Adults, 2006–2021

We aimed to identify the temporal trend of multimorbidity of noncommunicable disease (NCDs) among Brazilian adults (n = 784,479) over a 16-year period of time. This is a time series of cross-sectional studies based on data from the Surveillance System of Risk and Protective Factors for Chronic Diseases by Telephone Survey (Vigitel) from 2006 to 2021. The presence of multimorbidity was assessed from the co-occurrence of (1) obesity and diabetes; (2) obesity and hypertension; and (3) obesity and diabetes and/or hypertension. Linear regression models (Prais–Winsten) were used to identify significant trends for the complete period (2006–2021) and the most recent quinquennium (2017–2021). Multimorbidity of obesity and diabetes and/or hypertension increased in the complete period (5.5% to 9.6%; 0.22 pp/year) and the most recent period (8.3% to 9.6%; 0.40 pp/year) studied. The highest increase occurred especially among men, older adults, and those with fewer years of education. Additionally, there was a high prevalence and an intense increase in multimorbidity among adults with poor self-rated health. These results reinforce the need for expanding and strengthening public health actions focused on individuals with multimorbidity especially with obesity.

COHORT EFFECTS IN MULTIMORBIDITY AMONG OLDER US ADULTS: DIFFERENCES BY RACE/ETHNICITY AND NATIVITY

Abstract Multimorbidity (≥ 2 co-occurring chronic health conditions) affects &amp;gt; 50% of US adults aged 65 and older. Building on emerging work suggesting greater risk of multimorbidity in more recent cohorts of aging Americans, we examine heterogeneity in cohort-patterns of multimorbidity by race/ethnicity and nativity. Observations were drawn from the Health and Retirement Study (1998–2018) including adults aged 51 and older across 7 birth cohorts (born &amp;lt; 1924, 1924–1930, 1931–1941, 1942–1947, 1948–1953, 1954–1959, and 1960–1965). Multimorbidity was measured using a sum of 9 possible chronic conditions (heart disease, hypertension, stroke, diabetes, arthritis, lung disease, cancer, high depressive symptomatology, and cognitive impairment). Linear mixed models adjusting for age, period, and cohort effects tested whether cohort-specific multimorbidity risk varied for US-born White, US-born Black/African American, US-born Hispanic/Latino, and foreign-born Hispanic/Latino older adults. 30,607 adults contributed 158,727 total observations, grand mean age was 65.40 (SD=10.07), and mean multimorbidity was 2.18 (SD=1.60). US-born Black/African Americans had the greatest multimorbidity burden regardless of cohort. US-born Hispanic/Latinos experienced the highest cohort-related increases in multimorbidity, followed by US-born Black/African Americans. For example, compared to US-born Hispanic/Latinos born 1931–1941, US-born Hispanic/Latinos born 1954–1959 had 1.03 (CI: 0.78;1.28) more expected chronic conditions. Foreign-born Hispanic/Latinos had the smallest cohort-related increases in multimorbidity. Our results document heterogeneity in rising rates of multimorbidity across cohorts, suggest that US-born minority adults in Baby Boom cohorts may be at especially high risk of multimorbidity, and confirm protective effects of immigrant status among Hispanic/Latino older adults.

The role of age, sex, and multimorbidity in 7-year change in prevalence of limitations in adults 60–94 years

Recent data suggest a temporal trend in decline in functional limitations in older adults but whether this trend extends to the period after the 8th decade of life remains unclear. We examined change in prevalence of limitations in activities and instrumental activities of daily living (ADL and IADL) between 2008 and 2015 among adults of 60–94 years and the role of age, sex, multimorbidity; we also examined changes in severity of limitations. Data were drawn from two nationally representative surveys in 2008 (n = 13,593) and 2015 (n = 13,267). The 6-item scales of ADL and IADL were each categorized first as ≥ 1 limitations, and then to examine severity as 0, 1–2, and ≥ 3 limitations. Weighted logistic and multinomial regressions were used to estimate prevalence of limitations; the difference between surveys were extracted every 5 years between 60 and 90 years. The prevalence of ≥ 1 ADL declined between 2008 and 2015, from age 75 (− 1.2%; 95%CI = − 2.0, − 0.4%) to age 90 (− 8.8%; 95%CI = − 12.7, − 5.0%). This decline was more pronounced in men than women (p-value for interaction = 0.05) and observed primarily in those with multimorbidity (p-value for interaction = 0.06). Up to 2 ADL limitations declined from age 75 (− 1.0; 95%CI = − 1.7, − 0.3) to 90 (− 6.7; 95%CI = − 9.9, − 3.6) and from age 80 (− 0.6; 95%CI = − 1.1, 0.1) to 85 (− 1.2; 95%CI = − 2.2, − 0.1) for ≥ 3 ADL limitations. There was no substantial change in IADL limitations. These data from a high-income country with universal health care show improvement in ADL even after the 8th decade of life despite increase in multimorbidity.

The retirement (food)-consumption puzzle revisited - A panel data study from Denmark

The world population is ageing, and as lifestyle related illnesses and multi-morbidity increase with ageing, prevention with modifiable factors is becoming an increasingly important issue. In the current paper, we revisit the retirement (food) consumption puzzle in a welfare state context and examine how retirement affects food expenditure and energy intake as well as the dietary healthiness of elderly individuals with different marital and labor market status. We use a unique household panel data set covering the period from 2007–2017 with monthly food purchases from a sample of households above 55 years of age. We supplement the purchase data with official register data on income, health-contact days, unemployment, early voluntary and old age retirement at the individual level. The structure of the data set facilitates the identification of any associations between retirement and dietary behavior while controlling for important confounding factors such as the number of health-contact days as a proxy for health shocks and income as a proxy for wealth shocks. We compare the results with the results from estimations using instruments for the retirement decision. We do not find any evidence to support a retirement (food) consumption puzzle. Generally, the healthiness of diets increases at the point of retirement, and even more so for those who had the most unhealthy diets before retirement. Since the diets of individuals outside the labor market are less healthy both before and after retirement compared to other groups, the focus of dietary policy should be directed at this group.

Social inequalities in all-cause mortality among adults with multimorbidity: a 10-year prospective study of 0.5 million Chinese adults.

Chinese individuals face an increase in multimorbidity, but little is known about the mortality gradients of multimorbid people in different socio-economic groups. This study measures relative and absolute socio-economic inequality in mortality among multimorbid Chinese. For this study, the prospective China Kadoorie Biobank (CKB) enrolled 512712 participants ages 30-79y from 10 areas of China between 25 June 2004 and 15 July 2008. All-cause mortality was accessed with a mean follow-up period of 10y (to 31 December 2016). Associations between multimorbidity and mortality were assessed using Cox proportional hazards models, with the relative index of inequality (RII) and slope index of inequality (SII) in mortality calculated to measure disparities. Mortality risk was highest for those who had not attended formal school and with four or more long-term conditions (LTCs) (hazard ratio 3.11 [95% confidence interval {CI} 2.75 to 3.51]). Relative educational inequality was lower in participants with four or more LTCs (RII 1.92 [95% CI 1.60 to 2.30]), especially in rural areas. Absolute disparities were greater in adults with more LTCs (SII 0.18 [95% CI 0.14 to 0.21] for rural participants with three LTCs). Whereas the relative inequality in all-cause mortality was lower among multimorbid people, absolute inequality was greater among multimorbid men, especially in rural areas.

Conceptualisation of a measurement framework for Needs-based Quality of Life among patients with multimorbidity

BackgroundMultimorbidity is both an individual and societal problem. For society, patients with multimorbidity increase healthcare costs. For the individual, living with multimorbidity is complex, and there is an inverse relationship between a patient's Quality of Life (QoL) and their number of chronic conditions. Numerous intervention studies target these problems, yet there is no multimorbidity-specific patient-reported outcome measure (PROM) developed specifically for this group with adequate measurement properties to assess QoL. This study explores what overall needs regarding QoL are affected by living with multimorbidity through qualitative interviews. With this, we conceptualise Needs-based QoL specifically for this group, ensuring high content validity (regarding relevance and comprehensiveness) of using the Needs-based approach to measure their QoL. This is essential as this preliminary study leads to the development of the MultiMorbidity Questionnaire (MMQ), a PROM measuring QoL among patients with multimorbidity.MethodsThis study draws upon qualitative interviews with fifteen patients with multimorbidity based on a semi-structured interview guide following the Needs-based approach. This approach allowed the patients to cover needs relevant for their QoL in relation to the complexities of living with multimorbidity. The transcribed interviews were thematically analysed, inspired by Braun and Clarke’s reflexive approach.ResultsAnalysis of the interviews resulted in the construction of six intertwined domains relevant to patients with multimorbidity, covering their Needs-based QoL; “Physical ability”, “Self-determination”, “Security”, “Partner and social life”, “Self-image”, and “Personal finances”. “Physical limitations” and “Personal finances” were stated as core needs implicating the other domains.ConclusionThis study shows six intertwined overall domains relevant for patients with multimorbidity regarding their Needs-based QoL; “Physical ability”, “Self-determination”, “Security”, “Partner and social life”, “Self-image”, and “Personal finances”. These needs are relevant in a Danish context, with a generally high standard of living. Based on this conceptual framework of Need-based QoL for patients with multimorbidity, we will develop items for a new patient-reported outcome measure called the MMQ.