Poor Cognitive Function Is Associated with Obstructive Lung Diseases in Taiwanese Adults

Multimorbidity, lifestyle, and cognitive function: A cross-cultural study on the role of diabetes, cardiovascular disease, cancer, and chronic respiratory diseases

BACKGROUND

The effect of lifestyle factors on cognitive function related to four major noncommunicable diseases (NCDs) including diabetes, cardiovascular disease, cancer, and chronic respiratory diseases, and the relationship between these NCDs and cognitive function have not been fully studied. We aimed to investigate the longitudinal associations between these NCDs and cognitive function in middle-aged and older people, and the combined effects of lifestyle factors.

METHODS

By employing the data from three large-scale cohort studies from the U.S. Health and Retirement Study (2010-2019), English Longitudinal Study of Aging (2014-2019), and China Health and Retirement Longitudinal Study (2011-2019), this study carried out a multi-cohort analysis to 77, 210 participants. Fixed-effects regression models were used to examine associations between NCD status and cognitive function. Margin plots were used to illustrate the effect of lifestyle factors.

RESULTS

Our findings revealed the dose-dependent association between mounting these NCDs and declining cognitive performance, ranging from one NCD (β = -0.05, 95 % CI: -0.08 to -0.02) to four NCDs (β = -0.51, 95 % CI: -0.75 to -0.28). Decline in cognitive function associated with NCDs was exacerbated with physical inactivity, current smoking status, and an increase in unhealthy lifestyle behaviors.

LIMITATIONS

The observational study design precludes causal interrogation of lifestyles and four NCDs on cognitive function.

CONCLUSIONS

An increasing number of these NCDs were dose-dependently associated with the decline in cognitive function score. Unhealthy lifestyle factors expedite decline in cognitive function linked to these NCDs.

Relationships between muscle strength, lung function, and cognitive function in Chinese middle-aged and older adults: A study based on the China health and retirement longitudinal study (CHARLS)

OBJECTIVE

As the population ages, concerns about cognitive decline have become increasingly relevant in medical consultations. This study aims to analyze the interaction between muscle strength, lung function, and cognitive function in Chinese middle-aged and older adults, providing a theoretical basis for better prevention of cognitive decline.

METHODS

This study used data from the China Health and Retirement Longitudinal Study (CHARLS) wave 3, including 13 716 participants aged 45 years or older. Cognitive function was assessed through two dimensions, resulting in a total score ranging from 0 to 31 points, with higher scores indicating better cognitive function. Muscle strength was measured using normalized grip strength and chair-standing time, while lung function was evaluated using peak expiratory flow (PEF).

RESULTS

Total cognitive function scores exhibited significant correlations with grip strength, chair-standing time, and PEF. Muscle strength and lung function demonstrated significant associations with cognitive function, with lung function emerging as a notable mediating factor. This relationship persisted even after adjusting for potential confounding variables. Specifically, PEF played a substantial mediating role in linking grip strength to cognitive function scores (estimated indirect effect = 0.0132, boot-strapped standard error = 0.0015, boot-strapped standard 95% confidence interval = 0.0104, 0.0162). Additionally, PEF served as a significant mediator in the association between chair-standing time and cognitive function scores (estimated indirect effect = -0.0204, boot-strapped standard error = 0.0023, boot-strapped standard 95% confidence interval = -0.0251, -0.0159).

CONCLUSION

The study highlights the importance of addressing declines in muscle strength and lung function to identify risk factors associated with cognitive function. Understanding these relationships can provide insights into potential pathways linking these variables and may aid in better prevention of cognitive decline. Further long-term longitudinal cohort studies are needed to explore the causality between these factors.

The impact of the synergistic effect of SO2 and PM2.5/PM10 on obstructive lung disease in subtropical Taiwan

Background

Chronic Obstructive lung diseases (COPD) are complex conditions influenced by various environmental, lifestyle, and genetic factors. Ambient air pollution has been identified as a potential risk factor, causing 4.2 million deaths worldwide in 2016, accounting for 25% of all COPD-related deaths and 26% of all respiratory infection-related deaths. This study aims to evaluate the associations among chronic lung diseases, air pollution, and meteorological factors.

Methods

This cross-sectional study obtained data from the Taiwan Biobank and Taiwan Air Quality Monitoring Database. We defined obstructive lung disease as patients with FEV1/FVC < 70%. Descriptive analysis between spirometry groups was performed using one-way ANOVA and the chi-square or Fisher's exact test. A generalized additive model (GAM) was used to evaluate the relationship between SO2 and PM2.5/PM10 through equations and splines fitting.

Results

A total of 2,635 participants were enrolled. Regarding environmental factors, higher temperature, higher relative humidity, and lower rainfall were risk factors for obstructive lung disease. SO2 was positively correlated with PM10 and PM2.5, with correlation coefficients of 0.53 (p < 0.0001) and 0.52 (p < 0.0001), respectively. Additionally, SO2 modified the relative risk of obstructive impairment for both PM10 [β coefficient (β) = 0.01, p = 0.0052] and PM2.5 (β = 0.01, p = 0.0155). Further analysis per standard deviation (per SD) increase revealed that SO2 also modified the relationship for both PM10 (β = 0.11, p = 0.0052) and PM2.5 (β = 0.09, p = 0.0155). Our GAM analysis showed a quadratic pattern for SO2 (per SD) and PM10 (per SD) in model 1, and a quadratic pattern for SO2 (per SD) in model 2. Moreover, our findings confirmed synergistic effects among temperature, SO2 and PM2.5/PM10, as demonstrated by the significant associations of bivariate (SO2 vs. PM10, SO2 vs. PM2.5) thin-plate smoothing splines in models 1 and 2 with obstructive impairment (p < 0.0001).

Conclusion

Our study showed high temperature, humidity, and low rainfall increased the risk of obstructive lung disease. Synergistic effects were observed among temperature, SO2, and PM2.5/PM10. The impact of air pollutants on obstructive lung disease should consider these interactions.

The Impact of the Synergistic Effect of Temperature and Air Pollutants on Chronic Lung Diseases in Subtropical Taiwan

Previous studies have suggested an association between air pollution and lung disease. However, few studies have explored the relationship between chronic lung diseases classified by lung function and environmental parameters. This study aimed to comprehensively investigate the relationship between chronic lung diseases, air pollution, meteorological factors, and anthropometric indices. We conducted a cross-sectional study using the Taiwan Biobank and the Taiwan Air Quality Monitoring Database. A total of 2889 participants were included. We found a V/U-shaped relationship between temperature and air pollutants, with significant effects at both high and low temperatures. In addition, at lower temperatures (<24.6 °C), air pollutants including carbon monoxide (CO) (adjusted OR (aOR):1.78/Log 1 ppb, 95% CI 0.98–3.25; aOR:5.35/Log 1 ppb, 95% CI 2.88–9.94), nitrogen monoxide (NO) (aOR:1.05/ppm, 95% CI 1.01–1.09; aOR:1.11/ppm, 95% CI 1.07–1.15), nitrogen oxides (NO_x) (aOR:1.02/ppm, 95% CI 1.00–1.05; aOR:1.06/ppm, 95% CI 1.04–1.08), and sulfur dioxide (SO₂) (aOR:1.29/ppm, 95% CI 1.01–1.65; aOR:1.77/ppm, 95% CI 1.36–2.30) were associated with restrictive and mixed lung diseases, respectively. Exposure to CO, NO, NO₂, NO_x and SO₂ significantly affected obstructive and mixed lung disease in southern Taiwan. In conclusion, temperature and air pollution should be considered together when evaluating the impact on chronic lung diseases.