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OBJECTIVE: The aim of this study was to examine the impact of coronary heart disease (CHD) on health-related quality of life (HRQoL) among individuals taking aspirin, as well as to explore the potential association between stroke and CHD on HRQoL. METHOD: A total of 17,106 respondents aged 50 years and above who reported using aspirin on "some days" or "daily" were included in the analysis. Among them, 4,036 individuals had a history of coronary heart disease. We utilized the Chi-square test to assess the proportion of individuals with CHD who reported poor self-rated health and experienced poor HRQoL in four domains: physical health, mental health, physical and mental health combined, and the number of days limited by poor health. Logistic regression was employed to investigate the interaction between stroke and CHD concerning the quality of life. RESULT: Among adults aged 50 years and above using aspirin, those with CHD tended to be older (68.7 years ± 0.37 vs 66.6 ± 0.24), had a higher proportion of male respondents (60.0% vs 45.1%), and were mostly of white ethnicity (77.4% vs 76.2%). The group with CHD reported significantly poorer self-rated health compared to those without CHD (52.1% vs 25.6%, p<0.001), along with a higher prevalence of poor physical health (55.3% vs 42.7%, p<0.001) and poor mental health (50.2% vs 40.4%, p = 0.033) in comparison to aspirin users without CHD. However, there was no statistically significant association between stroke and CHD concerning the impact on all domains of quality of life (p>0.05). CONCLUSION: Our findings indicate that individuals aged 50 years and above with CHD who are using aspirin experience a lower quality of life in both the physical and mental health domains when compared to their counterparts without CHD. Furthermore, there was no significant interaction between stroke and CHD in relation to the impact on HRQoL in this study.
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BACKGROUND: Individuals with different mental disorders tend to experience higher rates of colorectal cancer (CRC)-related mortality compared to the general population. Discrepancies in CRC screening behaviors have been suggested as a potential contributing factor to this difference in mortality. However, existing evidence on this topic has been inconclusive and conflicting. OBJECTIVE: This study aims to explore the relationship between mental health status (specifically, depression and/or anxiety) and the uptake of CRC screening. To achieve this, a larger and nationally representative sample from the adult population of the United States was utilized. METHODS: We employed a cross-sectional approach using data from the 2019-2020 edition of the Health Information National Trends Survey (HINTS). The study examined disparities in CRC screening between individuals with self-reported history of depression diagnosis and the general population. Chi-square tests were used for analysis. Multivariable logistic regression models were applied to adjust for variables such as gender, age, education level, race, comorbidities, healthcare access, smoking status, household income, geographical residence, and insurance status. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported. RESULTS: The findings of the study indicated that out of 5,398 eligible individuals, approximately 1,220 (weighted percentage: 22.8%) reported experiencing depression and/or anxiety, and approximately 4,154 (weighted percentage: 68.9%) reported adherence to colorectal cancer screening. In the bivariate analysis, there was no significant difference in participation in colorectal cancer screening between individuals with and without depression and/or anxiety (72.0% vs. 68.0%). Similarly, after adjusting for sociodemographic and health-related factors, the study found that the odds of participating in colorectal cancer screening did not vary based on an individual's depression status (OR 1.34, 95% CI 0.94-1.91, P = 0.05). CONCLUSION: Individuals with depression participate in colorectal cancer screening at comparable rates to the general population. The findings of this study suggest that factors beyond CRC screening may play significant roles in the higher CRC-associated mortality rate. Therefore, further research is needed to uncover the various mechanisms contributing to the increased cancer-related mortality rates among susceptible populations.
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Objective To examine the relationship between electronic wearable device (WD) use and physical activity (PA) levels among older adults in the US. Methods Data were pooled from 3310 older adults from the 2019 and 2020 Health Information National Trends Survey. The explanatory variable was WD use, and the outcomes were weekly PA levels, resistance training, and sedentary time. Logistic regression was conducted to investigate the association between WD use and the reported outcome variables. Separate logistic models were also fitted to explore the relationship between WD use and physical activity outcomes among a subgroup of older adults with chronic conditions. Results A total of 14.4% of older adults reported WD use. Older adults who use WD were more likely to meet national guidelines for weekly levels of PA (odds ratio (OR) 1.60, 95% confidence intervals (CI) (1.10, 2.32); p = 0.015) and resistance strength training (OR 1.54, 95% CI (1.14, 2.09); p = 0.005) when compared with their counterparts not using WD. After restricting the analysis to those with chronic conditions only, WD use was only associated with a higher level of weekly strength training (OR 1.68, 95% CI 1.19, 2.38; p = 0.004). Conclusion WD use may be associated with increased physical activity among older adults, including those with chronic health conditions. Further studies are needed to examine the factors influencing the adoption and sustained use of WD in older adults.
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Athletes risk injury every day during practice sessions and actual games, with the majority of the affected population being young males. The Centers for Disease Control and Prevention 2011-2014 report on sport and recreation-related injuries in the United States has consistently shown the average annual estimate of the millions of dollars spent on sport and recreation injuries. These injuries translate to a significant financial implication for the athlete, the team, the health system, and the public health. We composed a review protocol. We enumerated our inclusion and exclusion criteria, injury definition, and search strategy. We searched PubMed and SPORTDiscus. Then we used Forrest plots for the meta-analysis of the relevant selected studies. We used various keywords in our search strategy. These included "injury," "sports," "exercise," "prevention," "techniques," and every possible combination of them. Search results showed 2516 hits with our keywords, and we included 20 of those results. Twenty trials, including 19712 individuals with 2855 injuries, were analyzed. Eccentric Training relative risk (RR) of 0.54 (95% CI 0.395 to 0.739 with X2 of p < 0.05) showed that the risk of the injury was decreased by 54% in the intervention group compared to the control group. In the neuromuscular training group, a RR of 0.682 (95% CI 0.621 to 0.749 with X2 of p < 0.001) showed that the risk of the injury was decreased by 68.2% in its intervention group subgroup compared to its control group. Also, the "11" International Federation of Association Football (FIFA) program had a RR of 0.771, indicating that there was a 77.1% decrease in injury by this set of exercises (95% CI 0.728 to 0.816 with X2 of p < 0.05), and this "11" FIFA program also had the most preventative effects. Warm-up had a RR of 0.843 (95% CI 0.749 to 0.949 with X2 of p < 0.05) and showed small prevention. Strength Training RR of 0.97 (95% CI 0.57 to 1.63 with X2 of p > 0.05) had no preventive effect. Our analysis showed that different exercises have preventive roles in sports injuries. The warm-up FIFA, neuromuscular training, and eccentric training reduced the risk of injury in the intervention group compared to the control group by a high percentage. At the same time, neuromuscular warm-up and FIFA 11 dynamic warm-up also decreased the relative risk of injury in the intervention group. These effects varied among exercise type, injury type, and sport.