Incidence and predictors of multimorbidity among older adults in Korea: a 10-year cohort study

Incident multimorbidity and associated factors among middle-aged and older adults in Thailand

Assessing the longitudinal relationship between sociodemographic, lifestyle, and psychological characteristics and incident multimorbidity (IMM) in middle-aged and older persons in Thailand was the goal of this study. We examined prospective cohort data of individuals aged 45 and over from three successive waves of the Health, Aging and Retirement in Thailand (HART) research conducted in 2015, 2017, and 2020 (analytic sample N = 2442). IMM was assessed with 10 health care provider diagnosed medical conditions. To assess the longitudinal associations between measures of sociodemographic, lifestyle and psychosocial factors, and IMM between 2015 (baseline without MM), 2017 (first follow-up, IMM) and 2020 (second follow-up, IMM), we conducted Generalized Estimating Equations analysis (GEE). The 5-year cumulative IMM was 19.6% and the incidence rate was 39.1 per 1000 person-years. In the final GEE logistic regression model, sociodemographic factors (older age, urban residence, lower economic status, and central region), lifestyle factors (past alcohol use, overweight and obesity) and psychosocial factors (poor self-rated mental health, insomnia symptoms, loneliness, and low informal social engagement) were associated with IMM. We found that sociodemographic, factors and psychosocial factors were associated with IMM. Enhancing lifestyles related to reducing bodyweight, screening and treatment of poor mental health and improving social interaction may reduce MM in Thailand.

Regional Dietary Pattern Associated with the Risk of Hypertensive Dyslipidemia Multimorbidity in Chinese Elderly: Results from China Nutrition and Health Surveillance in 2015-2017

Objectives: This study investigated regional dietary patterns and their association with hypertensive dyslipidemia multimorbidity among older Chinese adults. Methods: Data from 13,809 individuals (aged ≥ 65 years) were extracted from the 2015-2017 China Nutrition and Health Surveillance. Hypertensive dyslipidemia multimorbidity was defined as concurrent hypertension and dyslipidemia. Four dietary patterns were identified via exploratory factor analysis using 3-day 24 h dietary records. Results: Four dietary patterns were extracted: traditional southern, diverse, high oil and salt, and animal oil-other animal meat-coarse grain pattern. The national prevalence of hypertensive dyslipidemia multimorbidity was 31.9%, with significant regional variation (highest in North China: 36.4%; lowest in Central China: 27.9%; p < 0.0001). Regional dietary dominance included: the traditional southern pattern in South China (75.9%); the traditional southern (35.8%) and diversified (28.8%) patterns in East China; animal oil-other animal meat-coarse grain (38.4%) and traditional southern (37.9%) patterns in Southwest China; high oil and salt (36.8%) and traditional southern (25.9%) in Central China; diversified (47.7%) and high oil and salt (26.3%) patterns in North China; high oil and salt (44.9%) and diversified (37.9%) patterns in Northwest China; and the diversified (46.9%) pattern in Northeast China. In the highest scoring group of the animal oil-other animal meat-coarse grain pattern, the risk of hypertensive dyslipidemia multimorbidity was 1.179 times greater compared with the lowest scoring group (Q4 vs. Q1, OR = 1.179, 95% CI: 1.032-1.316, p < 0.001). Region-specific analyses highlighted: increased risks with the traditional southern pattern in South/East China (Q4 vs. Q1, OR = 2.080, 95% CI: 1.036-4.175, p < 0.001) and (Q4 vs. Q1, OR = 1.734, 95% CI: 1.052-2.859, p < 0.001); protective effects of the diversified pattern in Northwest China (Q4 vs. Q1, OR = 0.377, 95% CI: 0.173-0.824, p < 0.001); elevated risks with the high oil and salt pattern in Central/North China (Q4 vs. Q1, OR = 2.343, 95% CI: 1.107-4.955, p < 0.001) and (Q4 vs. Q1, OR = 1.837, 95% CI: 1.019-3.312, p < 0.001); and higher risks with the animal oil-other animal meat-coarse grain pattern in Southwest China (Q4 vs. Q1, OR = 2.009, 95% CI: 1.004-4.021, p < 0.001). Conclusions: In conclusion, dietary patterns among elderly Chinese are diversified and should be optimized based on local food resources to control hypertensive dyslipidemia multimorbidity.

Association between ambient temperatures and cardiovascular disease: A time series analysis using emergency ambulance dispatches in Chongqing, China, 2019-2021

BACKGROUND

Cardiovascular disease (CVD) is one of the leading causes of death globally. Yet, further research is required into the relationship between CVD and extreme environmental temperatures. This study aims to explore the association between the incidence of CVD and extreme temperatures, and also to identify susceptible subgroups within the population.

METHODS

We collected cardiovascular emergency ambulance dispatch (CEAD) records from Chongqing Emergency Dispatch Center in the main urban areas of Chongqing from 2019 to 2021. Then, we used distributed lag nonlinear modeling (DLNM) with a quasi-Poisson distribution to evaluate the association between extreme temperatures and CEADs. Susceptibility subgroups were identified by stratified analysis according to gender, age and initial diagnosis. Finally, the attribution analysis was used to calculate the scores and counts of CEADs caused by low and high temperatures.

RESULTS

Compared with the optimal temperature (23 °C), the cumulative lagged risk of total CEADs was increased under extreme low-temperature conditions (CRR: 1.732, 95% CI: [1.157, 2.593]), with the lagged effect lasting for 8 days. Under extreme high-temperature conditions, it decreased (CRR: 0.752, 95% CI: [0.611, 0.926]) and a protective effect was observed. Compared to the group under 60, those over 60 were more sensitive to temperature changes, showing a higher risk of disease with cold exposure (RR: 1.087, 95% CI: [1.021, 1.157]). In addition, a reduction in risk of disease was observed just one day after heat exposure. There were also gender differences in the elderly group: males showed longer lagged effects after cold exposure, while females had higher dispatch risk in cold weather and less heat adaptation in hot weather than males.

CONCLUSION

Ambient temperature is significantly associated with the risk of CVD, with elderly patients, especially females, being a high-risk subgroup. Governments need to formulate localized health policies that address regional climate patterns and population vulnerabilities. As one of the famous "Furnace Cities", Chongqing's measures for coping with hot environments can serve as a reference. Nonetheless, improving our understanding and preparation for cold weather is also crucial. Public warning systems should be improved, and local heating strategies for vulnerable groups should be developed to minimize the negative risk of extreme cold temperatures to the public.

Body mass index and multimorbidity risk: A systematic review and dose-response meta-analysis

OBJECTIVE

To verify the dose-response relationship between body mass index (BMI) and multimorbidity risk.

METHODS

PubMed, CINAHL, and Embase were systematically studied until January 25, 2023. Original articles on BMI and multimorbidity risk were included. Random effects model and dose-response meta-analysis were used to estimate the pooled odds ratio (OR) with 95 % confidence interval (CI). Subgroup analysis was performed to explore potential heterogeneity.

RESULTS

A total of 43 studies involving 969,130 patients (94,978 with multimorbidity) were involved in the meta-analysis. In the longitudinal studies, the pooled results showed that, compared to being a normal BMI, being overweight was much similar with 1.32 times possibility of getting multimorbidity; in persons with obesity the risk was 1.93 times higher; and the risk decreased 0.80 times among underweight persons. Additionally, obesity was 1.75 times as likely to be multimorbidity than those non-obese persons. In the cross-sectional studies, the pooled results demonstrated that persons with overweight and obesity had a 1.38-fold and 2.38-fold risk for multimorbidity, respectively; and the risk decreased 0.90 times among underweight persons compared to those with normal BMI. Besides, obese people are 1.89 times more likely to have multimorbidity than non-obese people. Dose response analysis found the linear connection between BMI and multimorbidity risk (Pnon-linearity=0.762), that for each 1 kg/m2 and 5 kg/m2 increase in BMI, the multimorbidity risk increased by 6 % and 35 %, respectively.

CONCLUSIONS

Multimorbidity increased linearly with an increase in BMI. Clinicians should pay attention to persons with abnormal weight, to help them achieve normal BMI.

Prevalence and predictors of multimorbidity in older adults, a community-based cross-sectional study

Background

Multimorbidity is a condition that refers to the coexistence of two or more chronic diseases or long-term medical conditions in an individual. It has become one of the key issues in the public health sector, particularly among older adults. So, this study aimed to estimate the prevalence of multimorbidity and its associated factors among older adults.

Methodology

The present study was a community-based cross-sectional study carried out on the elderly population (≥60 years) in a rural area of the study district, Gujarat. The estimated sample size was 384, and the final sample size was taken as 420, considering the multistage sampling procedure for fair distribution. The eligibility criteria included elderly people ≥60 years old, who were permanent residents (living for ≥6 months) of the study district and willing to participate in the study. Elderly people who were not willing to participate in the study for their reasons were excluded. A multistage sampling procedure was used to choose the study participants. The data collection tools included a pretested, predesigned, semi-structured questionnaire. The questionnaire consisted of two parts: sociodemographic details and morbidity details. Categorical variables were described by frequency and percentage, and numerical variables were described by mean ± SD. Logistic regression analyses were applied to test the relationship of categorized independent and dependent variables, and all tests were two-tailed with statistical significance set at the probability value (P < 0.05).

Results

Out of the 420 study participants, 52.1% were male and 47.9% were female, with a mean age of 70.70 years (SD ± 8.18 years). The prevalence of multimorbidity was 50%, with males having a mean number of morbidities of 1.38 ± 1.06 and females having a mean number of morbidities of 1.44 ± 0.99. As the age increased, the strength of association of multimorbidity also increased. Literacy level, marital status, occupation (business, farmer, housewife), and family history were statistically associated with multimorbidity in the study participants in both bivariate and multivariate analyses (P < 0.05).

Conclusion

The study provides valuable insights into the health status of the elderly population in the rural area and can be used to inform healthcare policies and interventions aimed at improving the health outcomes of this population.

Clinical Manifestations and Outcomes of Older Patients with COVID-19: A Comprehensive Review

The consequences of coronavirus disease 2019 (COVID-19) are particularly severe in older adults with a disproportionate number of severe and fatal outcomes. Therefore, this integrative review aimed to provide a comprehensive overview of the clinical characteristics, management approaches, and prognosis of older patients diagnosed with COVID-19. Common clinical presentations in older patients include fever, cough, and dyspnea. Additionally, preexisting comorbidities, especially diabetes and pulmonary and cardiovascular diseases, were frequently observed and associated with adverse outcomes. Management strategies varied, however, early diagnosis, vigilant monitoring, and multidisciplinary care were identified as key factors for enhancing patient outcomes. Nonetheless, the prognosis remains guarded for older patients, with increased rates of hospitalization, mechanical ventilation, and mortality. However, timely therapeutic interventions, especially antiviral and supportive treatments, have demonstrated some efficacy in mitigating the severe consequences in this age group. In conclusion, while older adults remain highly susceptible to severe outcomes from COVID-19, early intervention, rigorous monitoring, and comprehensive care can play a pivotal role in improving their clinical outcomes.

Findings from the Indonesian family life survey on patterns and factors associated with multimorbidity

The prevalence of multimorbidity tends to increase with age, but it is now also reported in the middle-aged population, which has a negative impact on healthcare systems and health outcomes. This study aims to analyze the patterns and factors associated with multimorbidity in Indonesia. This national cross-sectional population-based survey used publicly available data from the Indonesian Family Life Survey (IFLS-5) for 2014 among middle-aged (40-59 years old) and elderly (≥ 60 years old) respondents. Information on all chronic diseases was assessed using a self-reported questionnaire. Sociodemographic and health-related behavioral factors were obtained from self-reported data. Binary logistic regression analysis was used to identify the factors associated with multimorbidity. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported. The study recruited 11,867 respondents. The prevalence of multimorbidity was 18.6% (95% CI 17.9-19.3) with which 15.6% among middle age (95% CI 14.95-16.25) and 24.9% among the elderly (95% CI 24.12-25.68). Hypertension was the most commonly reported disease (23.2%) in all combinations of multimorbidity and among all age groups. Socio-demographic factors: elderly (AOR: 1.66; 95% CI 1.46-1.89), female (AOR: 1.42; 95% CI 1.20-1.69), living in the urban area (AOR: 1.22; 95% CI 1.09-1.38), higher educational level (AOR: 2.49; 95% CI 1.91-3.26), unemployed (AOR: 1.63; 95% CI 1.44-1.84), and higher economic level (AOR: 1.41; 95% CI 1.18-1.68) were associated with multimorbidity. Poor health behavior factors: being former smokers (AOR: 2.03; 95% CI 1.65-2.51) and obesity (AOR: 1.53; 95% CI 1.35-1.75) were also associated with multimorbidity. The prevalence of multimorbidity in the middle-aged and elderly population in Indonesia is relatively high, particularly in populations with poor health behaviors. Therefore, healthcare professionals should integrate more patient-specific factors when designing and implementing tailored interventions to manage multimorbidity in Indonesia.

Effects of multimorbidity coexistence on the risk of mortality in the older adult population in China

Background

Multimorbidity coexistence is a serious public health issue affecting a significant number of older adults worldwide. However, associations between multimorbidity and mortality are rarely studied in China. We assessed the effects of multimorbidity coexistence on mortality among a nationwide sample of older adults from China.

Objective

We analyzed 10-year (2008-2018) longitudinal data of 12,337 individuals who took part in China, a nationwide survey of people aged 65 years and above. We used the Cox proportional hazard model to determine the effects of multimorbidity on the all-cause mortality risk. We also examined mortality risk between sex and age obtained through differential analysis.

Results

At baseline, 30.2, 29.9, and 39.9% of participants had 0, 1, and 2 or more diseases, respectively. The cumulative follow-up of this study was 27,428 person-years (median follow-up = 2.7 years; range, 0.01-11.3 years), with 8297 deaths. The HRs (95% CIs) for all-cause mortality in participants with 1, and 2 or more conditions compared with those with none were 1.04 (0.98, 1.10) and 1.12 (1.06, 1.18), respectively. The heterogeneity analysis indicated that, the mortality risk for 80-94 years and 95-104 years group with multimorbidity coexistence is 1.12 (1.05-1.21) and 1.11 (1.01-1.23), respectively, but the mortality risk for 65-79 years group with multimorbidity coexistence was not statistically significant. The heterogeneity analysis indicated that, the mortality risk for men and women in older adults with multimorbidity coexistence is 1.15 (1.06, 1.25) and 1.08 (1.01, 1.17), respectively.

Conclusion

Multimorbidity coexistence is associated with an increase in an increased risk of death in older individuals, with the effect being relatively significant in those aged 80-94 years.