Leading determinants for multimorbidity in middle-aged Australian men and women: A nine-year follow-up cohort study

Prevalence of chronic conditions in masters games athletes: predictors and comparison to the general population

Background

Masters athletes (MA) are typically considered healthier than age-matched non-athletes. However, limited evidence exists on the prevalence of chronic conditions in MA.

Methods

Masters athletes competing at the 2017 Australian Masters Games (n = 4,848) and 2018 Pan Pacific Masters Games (n = 14,455) were invited to complete a survey collecting demographic and health information focused on chronic conditions. Age- and sex-adjusted prevalence of selected chronic conditions in MA was compared with Australian general population data.

Results

Overall, 817 MA (53.7 ± 10.6 y, 61% female) completed the survey with 48% reporting ≥1 chronic condition. Cardiovascular conditions were less prevalent in MA vs. the general population (11%, 95% CI [9-14%] vs. 30%), as were cardiovascular risk factors, anxiety, asthma, cancers, and depression. The prevalence of osteoarthritis in MA was, however, similar (11%, 95% CI [9-14%] vs. 14%). Older (>50 yr) vs. younger MA were more likely to report osteoarthritis (OR 2.17, 95% CI [1.35-3.48]) and heart conditions (OR 1.85, 95% CI [1.11-3.07]), while younger vs. older MA were more likely to report mental health conditions (OR 1.86, 95% CI [1.23-2.82]). Prevalence of mental health conditions was higher in female vs. male MA (17% 95% CI [13-20%] vs. 8% 95% CI [5-11%]) and younger vs. older MA (18% vs. 10%). Employed MA were less likely than MA who were not employed to report having one or more cancers (OR 0.33, 95% CI [0.16-0.69]), cardiovascular conditions (OR 0.47, 95% CI [0.29-0.79]) and hypertension (OR 0.36 95% CI [0.18-0.73]).

Conclusions

Cardiovascular and other chronic conditions prevalence was lower in MA compared to age-matched non-athletes, highlighting the value of promoting sport involvement in aging individuals as well as for continuation of participation in younger age groups into MA level. Greater participation of younger and female groups in masters sport to improve mental health, and inclusion of people who are not employed should be supported.

Lifestyle factors and incident multimorbidity related to chronic disease: a population-based cohort study

BACKGROUND

Multimorbidity is linked to poor quality of life, and increased healthcare costs, and multimorbidity risk is potentially mitigated by a healthy lifestyle. This study evaluated the individual and joint contributions of an extensive set of lifestyle factors to the development of multimorbidity.

METHODS

A prospective study of 133,719 adults (age 45.2 ± 12.9, range 18-93 years) from the Dutch Lifelines cohort assessed the influence of lifestyle factors on multimorbidity, defined as having at least two of four major chronic diseases, using Cox regression models and population attributable fractions (PAFs). Lifestyle-related factors included diet quality, physical activity, TV watching, substance use (alcohol, smoking), sleep (duration, medication), stress (acute, chronic) and social connectedness (social contacts, marital status).

RESULTS

Over a median follow-up of 3.4 years, 3687 (12.5%) of the 29,545 participants with a chronic disease at baseline developed multimorbidity, compared to 434 (0.4%) of the 104,174 without a chronic disease. Key lifestyle factors linked to multimorbidity included smoking, prolonged TV watching, and stress, with hazard ratios indicating a higher risk in both groups. Additionally, high alcohol consumption and inadequate sleep duration were found to increase multimorbidity risk specifically in those with a chronic disease. Lifestyle factors jointly accounted for 34.4% (PAF, 95%CI 28.8%-73.5%) (with baseline morbidity) and 55.6% (95%CI 17.2%-48.5%) (without) of multimorbidity cases, with smoking as the primary contributor.

CONCLUSIONS

Lifestyle factors, particularly smoking, alcohol consumption, TV watching, stress, and sleep, significantly contribute to the development of multimorbidity. The study underscores the importance of targeted prevention in public health and healthcare settings to manage and prevent multimorbidity.

The Dietary Inflammatory Index and Its Associations with Biomarkers of Nutrients with Antioxidant Potential, a Biomarker of Inflammation and Multiple Long-Term Conditions

We aimed to validate the Dietary Inflammatory Index (DII®) and assess the cross-sectional associations between the DII® and multiple long-term conditions (MLTCs) and biomarker concentrations and MLTCs using data from the European Prospective Investigation into Cancer (EPIC-Norfolk) study (11,113 men and 13,408 women). The development of MLTCs is associated with low-grade chronic inflammation, and ten self-reported conditions were selected for our MLTC score. Data from a validated FFQ were used to calculate energy-adjusted DII® scores. High-sensitivity C-reactive protein (hs-CRP) and circulating vitamins A, C, E, β-carotene and magnesium were available. Micronutrient biomarker concentrations were significantly lower as the diet became more pro-inflammatory (p-trend < 0.001), and hs-CRP concentrations were significantly higher in men (p-trend = 0.006). A lower DII® (anti-inflammatory) score was associated with 12-40% higher odds of MLTCs. Lower concentrations of vitamin C and higher concentrations of hs-CRP were associated with higher odds of MLTCs. The majority of the associations in our study between MLTCs, nutritional biomarkers, hs-CRP and the DII® were as expected, indicating that the DII® score has criterion validity. Despite this, a more anti-inflammatory diet was associated with higher odds of MLTCs, which was unexpected. Future studies are required to better understand the associations between MLTCs and the DII®.

Risk factors for multimorbidity in adulthood: A systematic review

BACKGROUND

Multimorbidity, the coexistence of multiple chronic diseases in an individual, is highly prevalent and challenging for healthcare systems. However, its risk factors remain poorly understood.

OBJECTIVE

To systematically review studies reporting multimorbidity risk factors.

METHODS

A PRISMA-compliant systematic review was conducted, searching electronic databases (MEDLINE, EMBASE, Web of Science, Scopus). Inclusion criteria were studies addressing multimorbidity transitions, trajectories, continuous disease counts, and specific patterns. Non-human studies and participants under 18 were excluded. Associations between risk factors and multimorbidity onset were reported.

RESULTS

Of 20,806 identified studies, 68 were included, with participants aged 18-105 from 23 countries. Nine risk factor categories were identified, including demographic, socioeconomic, and behavioral factors. Older age, low education, obesity, hypertension, depression, low pysical function were generally positively associated with multimorbidity. Results for factors like smoking, alcohol consumption, and dietary patterns were inconsistent. Study quality was moderate, with 16.2% having low risk of bias.

CONCLUSIONS

Several risk factors seem to be consistently associated with an increased risk of accumulating chronic diseases over time. However, heterogeneity in settings, exposure and outcome, and baseline health of participants hampers robust conclusions.

A Multidimensional Assessment of Activities of Daily Living, Mental Status, Communication, and Social Abilities Among Older Adults in Shenzhen, China: Cross-Sectional Study

BACKGROUND

China is facing a rapidly expanding aging population. Insights into the health status of older adults are of great significance for health resource allocation and health care provision to this population.

OBJECTIVE

With the goal of providing a comprehensive understanding of the health status of older adults and to inform potential interventions, we investigated the level of disability and identified risk factors associated with disability among the older population (aged ≥60 years) living in China.

METHODS

A total of 8467 older adults living in the Chinese city of Shenzhen were enrolled in this cross-sectional study. We used a multidimensional ability assessment survey, which assessed their activities of daily living (ADL; including eating, bathing, grooming, dressing, defecation control, urination control, using a toilet unaided, transfer, flat-ground walking, stair activity), mental status (including cognitive function, aggressive behavior, depression symptoms), sensory and communication (including consciousness level, vision, hearing, communication), and social participation (including living, working, time/space orientation, distinguish persons, social communication) abilities. The impact of demographic risk factors on ability levels was analyzed using ordinal logistic regression. The correlations between the four dimensions of ability mentioned above were analyzed using Spearman correlation analysis.

RESULTS

A total of 7766 participants were effectively assessed. The participants' average age was 70.64 (SD 8.46) years comprising 56.53% females. The overall ability level was classified as mildly, moderately, and severely impaired for 27.57% (n=2141), 2.83% (n=220), and 4.28% (n=332) of the 7766 participants, respectively. With increasing age, the proportion of impaired participants increased from 17.62% (365/2071) in the age group 60-64 years to 91.3% (253/277) in the age group above 90 years (P<.001), corresponding to an approximate 10% rise for every 5-year age increment. The odds of having more severe overall ability impairment in females was 1.15 times that in males (odds ratio [OR] 1.15, 95% CI 1.04-1.28). Participants who were divorced or widowed had a higher risk of more severe overall ability impairment than those currently married (OR 1.98, 95% CI 1.68-2.33). Participants living with nonrelatives had an increased risk of more severe overall ability impairment than those living alone (OR 2.38, 95% CI 1.46-3.91). Higher education level was a protective factor of overall ability impairment (college degree or above: OR 0.32, 95% CI 0.24-0.42). The four dimensions of ability assessed were significantly correlated; a low score for ADL was significantly correlated with poorer mental status, sensory and communication, and social participation (all P<.001).

CONCLUSIONS

The proportion of disability among Chinese older adults increases with age, being female, having lower education levels, being divorced or widowed, and living with nonrelatives. Impairment in ADL ability is significantly correlated with poor mental status, social participation, and sensory and communication abilities. A holistic approach to improving the health of the older population is recommended in China.

Overweight, obesity and risk of multimorbidity: A systematic review and meta-analysis of longitudinal studies

This study aimed to review and quantify the association between overweight and obesity in the risk of multimorbidity among the general population. We conducted a systematic review and meta-analysis in the databases of Pubmed, Lilacs, Web of Science, Scopus, and Embase. We included cohort studies that assessed the association between overweight and/or obesity with the risk of multimorbidity. The Newcastle-Ottawa assessed the studies' individual quality. A random-effect model meta-analysis was performed to evaluate the association between overweight and obesity with the relative risk (RR) of multimorbidity; the I² test evaluated heterogeneity. After excluding duplicates, we found 1.655 manuscripts, of which eight met the inclusion criteria. Of these, seven (87.5%) evidenced an increased risk of multimorbidity among subjects with overweight and/or obesity. Overall, we observed an increased risk of multimorbidity among subjects with overweight (RR: 1.26; CI95%: 1.12; 1.40, I²  = 98%) and obesity (RR: 1.99; CI95%: 1.45;2.72, I²  = 99%) compared to normal weight. According to the I² test, the heterogeneities of the meta-analyses were high. The Newcastle-Ottawa scale showed that all studies were classified as high quality. Further longitudinal studies are needed, including different populations and stratifications by sex, age, and other variables.

Multimorbidity

Multimorbidity (two or more coexisting conditions in an individual) is a growing global challenge with substantial effects on individuals, carers and society. Multimorbidity occurs a decade earlier in socioeconomically deprived communities and is associated with premature death, poorer function and quality of life and increased health-care utilization. Mechanisms underlying the development of multimorbidity are complex, interrelated and multilevel, but are related to ageing and underlying biological mechanisms and broader determinants of health such as socioeconomic deprivation. Little is known about prevention of multimorbidity, but focusing on psychosocial and behavioural factors, particularly population level interventions and structural changes, is likely to be beneficial. Most clinical practice guidelines and health-care training and delivery focus on single diseases, leading to care that is sometimes inadequate and potentially harmful. Multimorbidity requires person-centred care, prioritizing what matters most to the individual and the individual's carers, ensuring care that is effectively coordinated and minimally disruptive, and aligns with the patient's values. Interventions are likely to be complex and multifaceted. Although an increasing number of studies have examined multimorbidity interventions, there is still limited evidence to support any approach. Greater investment in multimorbidity research and training along with reconfiguration of health care supporting the management of multimorbidity is urgently needed.

Examining the predictability and prognostication of multimorbidity among older Delayed-Discharge Patients: A Machine learning analytics

BACKGROUND

Patient complexity among older delayed-discharge patients complicates discharge planning, resulting in a higher rate of adverse outcomes, such as readmission and mortality. Early prediction of multimorbidity, as a common indicator of patient complexity, can support proactive discharge planning by prioritizing complex patients and reducing healthcare inefficiencies.

OBJECTIVE

We set out to accomplish the following two objectives: 1) to examine the predictability of three common multimorbidity indices, including Charlson-Deyo Comorbidity Index (CDCI), the Elixhauser Comorbidity Index (ECI), and the Functional Comorbidity Index (FCI) using machine learning (ML), and 2) to assess the prognostic power of these indices in predicting 30-day readmission and mortality.

MATERIALS AND METHODS

We used data including 163,983 observations of patients aged 65 and older who experienced discharge delay in Ontario, Canada, during 2004 - 2017. First, we utilized various classification ML algorithms, including classification and regression trees, random forests, bagging trees, extreme gradient boosting, and logistic regression, to predict the multimorbidity status based on CDCI, ECI, and FCI. Second, we used adjusted multinomial logistic regression to assess the association between multimorbidity indices and the patient-important outcomes, including 30-day mortality and readmission.

RESULTS

For all ML algorithms and regardless of the predictive performance criteria, better predictions were established for the CDCI compared with the ECI and FCI. Remarkably, the most predictable multimorbidity index (i.e., CDCI with Area Under the Receiver Operating Characteristic Curve = 0.80, 95% CI = 0.79 - 0.81) also offered the highest prognostications regarding adverse events (RRR_mortality = 3.44, 95% CI = 3.21 - 3.68 and RRR_readmission = 1.36, 95% CI = 1.31 - 1.40).

CONCLUSIONS

Our findings highlight the feasibility and utility of predicting multimorbidity status using ML algorithms, resulting in the early detection of patients at risk of mortality and readmission. This can support proactive triage and decision-making about staffing and resource allocation, with the goal of optimizing patient outcomes and facilitating an upstream and informed discharge process through prioritizing complex patients for discharge and providing patient-centered care.

Marriage contributes to higher obesity risk in China: findings from the China Health and Nutrition Survey

Background

To investigate the association between marriage and the prevalence of overweight and obesity in China.

Methods

We conducted cross-sectional and retrospective cohort analyses using a nationwide sample of 36,310 individuals from the China Health and Nutrition Survey [2004-2015].

Results

The prevalence of overweight and obesity increased from 28.7% to 36.7% and from 8.0% to 14.5% between 2004 and 2015, respectively. The cross-sectional analysis showed that married individuals were at a higher risk of being overweight (OR =2.18; 95% CI, 1.90-2.51) or obese (OR =1.95; 1.57-2.43) than never-married individuals. Divorced/widowed individuals were also at a greater risk of being overweight (OR =1.80; 1.51-2.13) or obese (OR =1.67; 1.28-2.17) than never-married individuals. Retrospective cohort analysis showed that individuals who married during the study were 1.55 (1.13-2.11) times more likely to be overweight than those who remained never-married. Compared to those who remained never-married, individuals who remained married were 1.71 (1.42-2.07) and 1.45 (1.11-1.89) times more likely to be overweight and obese. Individuals who became divorced or widowed were more likely to be overweight (RR =1.59; 1.18-2.15) or obese (RR =1.63; 1.08-2.46) than those who remained never-married. However, the risk of being overweight or obese among those who became divorced or widowed did not differ significantly from the risk among those who remained married.

Conclusions

Marriage contributes to an increased risk of overweight and obesity in China; however, this risk is not significantly reduced by exiting a marriage.