Sociodemographic and lifestyle determinants of multimorbidity among community-dwelling older adults: findings from 346,760 SHARE participants

Adverse childhood experiences and trajectories of chronic diseases: A population-base longitudinal study

OBJECTIVES

Adverse childhood experiences (ACEs) have far-reaching effects on health outcomes. This study aimed to evaluate the associations of ACEs with trajectories and number of chronic diseases.

STUDY DESIGN

Cohort study.

METHODS

Participants aged 45 years or older of China Health and Retirement Longitudinal Study were included. Ten kinds of ACEs encountered before 17 years old were calculated. Number of chronic diseases were assessed by 14 kinds of self-reported or proxy-reported diagnosed chronic diseases. The associations of specific types and number of ACEs with trajectories and number of chronic diseases were analyzed with latent class trajectory model, multinomial Logistic regression, and general estimating equation.

RESULTS

Four trajectories of chronic diseases were identified in 12157 participants. With the reference of low baseline and persistent growth trajectory, those encountered physical abuse, domestic violence, household mental illness, and parental death had higher risks of high baseline and transient growth trajectory, middle baseline and accelerated growth trajectory of chronic diseases (ORs = 1.18-1.65). Compared to those without ACEs, those with 1 and above kinds of ACEs had elevated risks of middle baseline and persistent growth, high baseline and transient growth trajectory, middle baseline and accelerated growth trajectory of chronic diseases (ORs = 1.15-2.71). Physical abuse, domestic violence, bullying, household mental illness, parental death, and exposure of 2 and above kinds of ACEs increased the number of chronic diseases (β = 0.09-0.62). Associations of ACEs with trajectories and number of chronic diseases were more salient in women than men.

CONCLUSIONS

Different types and number of ACEs were related to trajectories of chronic diseases, especially in women. Early, comprehensive, and joint actions should be taken to prevent chronic diseases from a life-course perspective.

Non-communicable diseases and their associations with outpatient services utilisation: insight from a population-based survey in Malaysia

OBJECTIVES

Multimorbidity has been recognised as a global public health issue, and individuals with multimorbidity have been found to have high healthcare utilisation. This study aims to estimate the prevalence of non-communicable diseases among adults in Malaysia, identify factors associated with multimorbidity, and assess the association between the number of non-communicable diseases and outpatient services utilisation.

DESIGN AND SETTING

A retrospective secondary data analysis using data from the National Health and Morbidity Survey 2019, a cross-sectional household survey among the population in Malaysia.

PARTICIPANTS

All adults aged 18 years and above.

OUTCOME MEASURES

The two outcome variables were multimorbidity and outpatient services utilisation. Characteristics of respondents and those having multimorbidity were described using complex sample descriptive statistics. We used multivariable logistic regression to determine the associated factors of having multimorbidity and the association between the number of non-communicable diseases and outpatient services utilisation.

RESULTS

Overall, 11 347 respondents were included in the analysis. This study found a prevalence of 11.4 (95% CI=10.43-12.39) for multimorbidity. Age, marital status and working status were the factors associated with multimorbidity. Adults with multimorbidity were high users of outpatient services (20.4%, 95% CI=17.5-23.7), approximately threefold of adults with no non-communicable diseases. In the final model, multimorbidity showed an adjusted OR of 3.28 (95% CI=2.48-4.32) for outpatient services utilisation.

CONCLUSION

Understanding factors associated with multimorbidity and the magnitude of the impact of having multimorbidity towards outpatient services utilisation could help in future planning for healthcare system transformation. The recently launched Health White Paper for Malaysia has emphasised primary healthcare as a critical component to achieve aspirations of the health system, which includes equity and responsiveness. Strengthening primary care services and improving patient navigation across healthcare levels are critical to supporting individuals with multimorbidity. Avenues for further research include exploring a wider range of conditions and assessing the longitudinal impact of multimorbidity on healthcare utilisation and health outcomes.

The Cross-Sectional Association Between Multimorbidity and Sleep Quality and Duration Among the Elderly Community Dwellers in Northwest China

Background

Multimorbidity, defined as the coexistence of two or more chronic diseases, is highly prevalent among the elderly population and is associated with adverse outcomes. However, little is known about its relationship with sleep issues, particularly in this demographic. Therefore, this study aimed to investigate its association with sleep quality and duration among the elderly.

Methods

This cross-sectional study was conducted in Emin County, Xinjiang, China, which included a population aged 60 years and above. We employed the Pittsburgh Sleep Quality Index (PSQI) score to assess sleep quality and duration. Multimorbidity was determined through self-reports, physical examination, blood tests, and imaging. Logistic regression analyses were used to explore the association between multimorbidity and sleep patterns, adjusting for confounders.

Results

A total of 8205 elderly participants were included, of whom 66.8% suffered from multimorbidity. Participants with multimorbidity exhibited higher total PSQI scores [6 (3,9)], and a higher percentage of poor sleep quality (50.6%), compared to those without multimorbidity. Multimorbidity was significantly associated with the presence of poor sleep quality (OR = 1.27, 95% CI: 1.14-1.41, P < 0.001) before and after adjusting for confounders. The risk of having poor sleep quality significantly increased as the number of multimorbidities increased. The OR (95% CI) values were 1.16 (1.02,1.32) for two diseases, 1.54 (1.26,1.90) for ≥5 diseases. In the adjusted model for total participants, having four diseases (OR = 1.26, 95% CI: 1.05-1.51, p = 0.013) and five or more diseases (OR = 1.29, 95% CI: 1.03-1.61, p = 0.029) were associated with shorter sleep duration. Furthermore, those with five or more diseases associated with longer sleep duration (OR = 1.40, 95% CI: 1.00-1.95, p = 0.057).

Conclusion

There is a significant association between multimorbidity and poor sleep quality in older community dwellers, which may provide clues for disease prevention.

Associations of Low-density Lipoprotein Cholesterol With All-cause and Cause-specific Mortality in Older Adults in China

CONTEXT

Limited information was available on detailed associations of low-density lipoprotein cholesterol (LDL-C) with all-cause and cause-specific mortality in older adults.

METHODS

This prospective cohort study included a representative sample of 211 290 adults aged 65 or older who participated in Shenzhen Healthy Aging Research 2018-2019. The vital status of the participants by December 31, 2021, was determined. We estimated the hazard ratios (HR) with 95% confidence intervals for all-cause or cause-specific mortality using multivariable Cox proportional hazards models and Cox models with restricted cubic spline (RCS).

RESULTS

The median follow-up time was 3.08 years. A total of 5333 participants were confirmed to have died. Among them, 2037 cardiovascular disease (CVD) deaths and 1881 cancer deaths occurred. Compared to those with LDL-C of 100 to 129 mg/dL, the all-cause mortality risk was significantly higher for individuals with LDL-C levels that were very low (<70 mg/dL) or low (70-99 mg/dL). Compared with individuals with the reference LDL-C level, the multivariable-adjusted HR for CVD-specific mortality was 1.338 for those with very low LDL-C levels (< 70 mg/dL), 1.437 for those with high LDL-C levels (160 mg/dL ≤ LDL-C < 190 mg/dL), and 1.489 for those with very high LDL-C levels (≥190 mg/dL). Low LDL-C levels (70-99 mg/dL) and very low LDL-C levels (<70 mg/dL) were also associated with increased cancer mortality and other-cause mortality, respectively. The results from an RCS curve showed similar results.

CONCLUSION

Considering the risk of all-cause mortality and cause-specific mortality, we recommended 100 to 159 mg/dL as the optimal range of LDL-C among older adults in China.

Integrating multi-task and cost-sensitive learning for predicting mortality risk of chronic diseases in the elderly using real-world data

BACKGROUND AND OBJECTIVE

Real-world data encompass population diversity, enabling insights into chronic disease mortality risk among the elderly. Deep learning excels on large datasets, offering promise for real-world data. However, current models focus on single diseases, neglecting comorbidities prevalent in patients. Moreover, mortality is infrequent compared to illness, causing extreme class imbalance that impedes reliable prediction. We aim to develop a deep learning framework that accurately forecasts mortality risk from real-world data by addressing comorbidities and class imbalance.

METHODS

We integrated multi-task and cost-sensitive learning, developing an enhanced deep neural network architecture that extends multi-task learning to predict mortality risk across multiple chronic diseases. Each patient cohort with a chronic disease was assigned to a separate task, with shared lower-level parameters capturing inter-disease complexities through distinct top-level networks. Cost-sensitive functions were incorporated to ensure learning of positive class characteristics for each task and achieve accurate prediction of the risk of death from multiple chronic diseases.

RESULTS

Our study covers 15 prevalent chronic diseases and is experimented with real-world data from 482,145 patients (including 9,516 deaths) in Shenzhen, China. The proposed model is compared with six models including three machine learning models: logistic regression, XGBoost, and CatBoost, and three state-of-the-art deep learning models: 1D-CNN, TabNet, and Saint. The experimental results show that, compared with the other compared algorithms, MTL-CSDNN has better prediction results on the test set (ACC=0.99, REC=0.99, PRAUC=0.97, MCC=0.98, G-means = 0.98).

CONCLUSIONS

Our method provides valuable insights into leveraging real-world data for precise multi-disease mortality risk prediction, offering potential applications in optimizing chronic disease management, enhancing well-being, and reducing healthcare costs for the elderly population.

A study on the development of a fitness age prediction model: the national fitness award cohort study 2017-2021

BACKGROUND

Physical fitness is considered an important indicator of the health of the general public. In particular, the physical fitness of the older adults is an important requirement for determining the possibility of independent living. Therefore, the purpose of this study was to examine the association between chronological age and physical fitness variables in the National Fitness Award Cohort study data and to develop multiple linear regression analyses to predict fitness age using dependent variables.

METHODS

Data from 501,774 (359,303 adults, 142,471 older adults) individuals who participated in the Korea National Fitness Award Cohort Study from 2017 to 2021 were used. The physical fitness tests consisted of 5 candidate markers for adults and 6 candidate markers for the older adults to measure muscle strength, muscle endurance, cardiopulmonary endurance, flexibility, balance, and agility. Pearson's correlation and stepwise regression analyses were used to analyze the data.

RESULTS

We obtained a predicted individual fitness age values from physical fitness indicators for adults and older adults individuals, and the mean explanatory power of the fitness age for adults was [100.882 - (0.029 × VO2max) - (1.171 × Relative Grip Strength) - (0.032 × Sit-up) + (0.032 × Sit and reach) + (0.769 × Sex male = 1; female = 2)] was 93.6% (adjusted R2); additionally, the fitness age for older adults individuals was [79.807 - (0.017 × 2-min step test) - (0.203 × Grip Strength) - (0.031 × 30-s chair stand) - (0.052 × Sit and reach) + (0.985 × TUG) - (3.468 × Sex male = 1; female = 2) was 24.3% (adjusted R2).

CONCLUSIONS

We suggest the use of fitness age as a valid indicator of fitness in adults and older adults as well as a useful motivational tool for undertaking exercise prescription programs along with exercise recommendations at the national level.

Resilience among older adults with multimorbidity using the Connor-Davidson scale in the Canadian Longitudinal Study on Aging: health behaviour, socio-economic, and social support predictors

OBJECTIVE

Multimorbidity is recognized as a serious health condition faced by a majority of older adults. Research investigating adaptive responses to multimorbidity, termed multimorbidity resilience, has been growing. This paper examines protective and risk factors, with a focus on health behaviours, socio-economic resources, and social support using an established measure of resilience (Connor-Davidson Resilience Scale) among older adults, focusing on older persons with two or more concurrent chronic conditions.

METHODS

Using Baseline (2011-2015), Follow-up One (2015-2018), and Follow-up Two (2018-2021) data from the Comprehensive Cohort of the Canadian Longitudinal Study on Aging, we tested hypotheses using 13,064 participants aged 65 years and older, who completed all waves and reported two or more of 27 chronic conditions, for the full sample of multimorbid individuals and three multimorbidity clusters: Cardiovascular/Metabolic, Musculoskeletal, and Mental Health. Associations between protective and risk factors and resilience were examined using linear regression to model the Connor-Davidson resilience scale, adjusting for illness context and social determinants of health.

RESULTS

Among all multimorbid individuals, the strongest associations with resilience were found for higher self-rated health, greater sleep satisfaction, better appetite, higher household income, more relatives and friends, being overweight (compared to normal weight), fewer housing problems, and fewer skipped meals. Weaker associations were found for non-smokers, less alcohol consumption, less pain, sedentary behaviour, being non-married (compared to married), and among Canadian born (compared to foreign). The analyses for the three multimorbidity clusters were largely replicated for the three multimorbidity clusters, but with some nuances depending on the cluster.

DISCUSSION

This research provides confirmatory evidence for several protective and risk factors affecting the ability to cope and recover from multimorbidity adversity among older adults. There are consistent patterns for the multimorbidity disease clusters, but some distinct relationships arise that are worthy of attention. The implications of the findings for modifiable health behaviours and socio-economic factors are discussed for their public health and clinical relevance.

Community screening for dementia among older adults in China: a machine learning-based strategy

BACKGROUND

Dementia is a leading cause of disability in people older than 65 years worldwide. However, diagnosing dementia in its earliest symptomatic stages remains challenging. This study combined specific questions from the AD8 scale with comprehensive health-related characteristics, and used machine learning (ML) to construct diagnostic models of cognitive impairment (CI).

METHODS

The study was based on the Shenzhen Healthy Ageing Research (SHARE) project, and we recruited 823 participants aged 65 years and older, who completed a comprehensive health assessment and cognitive function assessments. Permutation importance was used to select features. Five ML models using BalanceCascade were applied to predict CI: a support vector machine (SVM), multilayer perceptron (MLP), AdaBoost, gradient boosting decision tree (GBDT), and logistic regression (LR). An AD8 score ≥ 2 was used to define CI as a baseline. SHapley Additive exPlanations (SHAP) values were used to interpret the results of ML models.

RESULTS

The first and sixth items of AD8, platelets, waist circumference, body mass index, carcinoembryonic antigens, age, serum uric acid, white blood cells, abnormal electrocardiogram, heart rate, and sex were selected as predictive features. Compared to the baseline (AUC = 0.65), the MLP showed the highest performance (AUC: 0.83 ± 0.04), followed by AdaBoost (AUC: 0.80 ± 0.04), SVM (AUC: 0.78 ± 0.04), GBDT (0.76 ± 0.04). Furthermore, the accuracy, sensitivity and specificity of four ML models were higher than the baseline. SHAP summary plots based on MLP showed the most influential feature on model decision for positive CI prediction was female sex, followed by older age and lower waist circumference.

CONCLUSIONS

The diagnostic models of CI applying ML, especially the MLP, were substantially more effective than the traditional AD8 scale with a score of ≥ 2 points. Our findings may provide new ideas for community dementia screening and to promote such screening while minimizing medical and health resources.

Stage 5 Chronic Kidney Disease: Epidemiological Analysis in a NorthEastern District of Italy Focusing on Access to Nephrological Care

BACKGROUND

We conducted a retrospective epidemiological study about the prevalence of stage 5 chronic kidney disease (CKD) in a high-income district, comparing some demographic characteristics and outcomes of those patients who had nephrological consultations and those who had not.

RESULTS

In a district of 400,000 adult subjects in 2020, 925 patients had an estimated glomerular filtration rate (eGFR) under 15 mL/min and CKD. In the same period, 747 (80.4%) patients were assessed by nephrologists, while 178 (19.6%) were not. Age (88 vs. 75, p < 0.0001), female gender (66.3% vs. 47%, p < 0.001), and eGFR (12 vs. 9 mL/min, p < 0.001) were significantly different in the patients assessed by a nephrologist as compared those who did not have nephrological care. Furthermore, unfollowed CKD patients had a significantly higher death rate, 83.1% versus 14.3% (p < 0.0001).

CONCLUSIONS

About 20% of ESKD patients did not receive a nephrologist consultation. Older people and women were more likely not to be referred to nephrology clinics. Unfollowed patients with stage 5 CKD had a significantly higher death rate.

Associations of urinary metal concentrations with anemia: A cross-sectional study of Chinese community-dwelling elderly

BACKGROUND

Anemia seriously affects the health and quality of life of the older adult population and may be influenced by various types of environmental metal exposure. Current studies on metals and anemia are mainly limited to single metals, and the association between polymetals and their mixtures and anemia remains unclear.

METHODS

We determined 11 urinary metal concentrations and hemoglobin levels in 3781 participants. Binary logistic regression and restricted cubic spline (RCS) model were used to estimate the association of individual metals with anemia. We used Bayesian kernel machine regression (BKMR) and Quantile g-computation (Q-g) regression to assess the overall association between metal mixtures and anemia and identify the major contributing elements. Stratified analyses were used to explore the association of different metals with anemia in different populations.

RESULTS

In a single-metal model, nine urinary metals significantly associated with anemia. RCS analysis further showed that the association of arsenic (As) and copper (Cu) with anemia was linear, while cobalt, molybdenum, thallium, and zinc were non-linear. The BKMR model revealed a significant positive association between the concentration of metal mixtures and anemia. Combined Q-g regression analysis suggested that metals such as Cu, As, and tellurium (Te) were positively associated with anemia, with Te as the most significant contributor. Stratified analyses showed that the association of different metals with anemia varied among people of different sexes, obesity levels, lifestyle habits, and blood pressure levels.

CONCLUSIONS

Multiple metals are associated with anemia in the older adult population. A significant positive association was observed between metal mixture concentrations and anemia, with Te being the most important factor. The association between urinary metal concentrations and anemia is more sensitive in the non-hypertensive populations.

Why Treat Patients with a Major Orthopaedic Surgery Only to Send Them Back to the Vulnerable Conditions That Made Them Sick in the First Place? A Conceptual Scenario to Improve Patient's Journey

Individuals with severe cartilage degeneration of the hip or knee or collapsed vertebrae that cause spine deformities can suffer from joint and neuropathic pain in the back, disuse of the affected limb, and restriction of movements. Surgical intervention is the most widespread and successful solution to date. There is a general belief that eating healthy and staying physically and mentally active might have a preventive role against musculoskeletal disease occurrence, while instead, we are more certain of the benefits deriving from a healthy diet and exercise therapy after major orthopaedic procedures. These aspects are in fact vital components in enhanced recovery after surgery programmes. However, they are applied in hospital settings, are often centre-dependent, and lack primary and tertiary preventive efficacy since end once the patient is discharged. There is the lack of initiatives at the territorial level that ensure a continuum in the patient's journey towards orthopaedic surgery, home transition, and a healthy and long-lasting life. The expert panel advocates the integration of an intermediate lifestyle clinic that promotes healthy eating, physical activity, and sleep hygiene. In this facility directed by professionals in enhancing recovery after surgery, patients can be referred after the surgical indication and before home discharge. Surgery is in fact a moment when individuals are more curious to do their best to heal and stay healthy, representing a timepoint and opportunity for educating patients on how lifestyle changes may optimise not only their surgical recovery but also long-term future health state.