A scoping review of the toxicity and health impact of IQOS.

This work aims to summarize the current evidence on the toxicity and health impact of IQOS, taking into consideration the data source. On 1 June 2022, we searched PubMed, Web of Science, and Scopus databases using the terms: 'heated tobacco product', 'heat-not-burn', 'IQOS', and 'tobacco heating system'. The search was time-restricted to update a previous search conducted on 8 November 2021, on IQOS data from 2010-2021. The data source [independent, Philip Morris International (PMI), or other manufacturers] was retrieved from relevant sections of each publication. Publications were categorized into two general categories: 1) Toxicity assessments included in vitro, in vivo, and systems toxicology studies; and 2) The impact on human health included clinical studies assessing biomarkers of exposure and biomarkers of health effects. Generally, independent studies used classical in vitro and in vivo approaches, but PMI studies combined these with modeling of gene expression (i.e. systems toxicology). Toxicity assessment and health impact studies covered pulmonary, cardiovascular, and other systemic toxicity. PMI studies overall showed reduced toxicity and health risks of IQOS compared to cigarettes, but independent data did not always conform with this conclusion. This review highlights some discrepancies in IQOS risk assessment regarding methods, depth, and breadth of data collection, as well as conclusions based on the data source.

Prediction of dementia based on older adults' sleep disturbances using machine learning.

BACKGROUND: The most common degenerative condition in older adults is dementia, which can be predicted using a number of indicators and whose progression can be slowed down. One of the indicators of an increased risk of dementia is sleep disturbances. This study aims to examine if machine learning can predict dementia and which sleep disturbance factors impact dementia. METHODS: This study uses five machine learning algorithms (gradient boosting, logistic regression, gaussian naive Bayes, random forest and support vector machine) and data on the older population (60+) in Sweden from the Swedish National Study on Ageing and Care - Blekinge (n=4175). Each algorithm uses 10-fold stratified cross-validation to obtain the results, which consist of the Brier score for checking accuracy and the feature importance for examining the factors which impact dementia. The algorithms use 16 features which are on personal and sleep disturbance factors. RESULTS: Logistic regression found an association between dementia and sleep disturbances. However, it is slight for the features in the study. Gradient boosting was the most accurate algorithm with 92.9% accuracy, 0.926 f1-score, 0.974 ROC AUC and 0.056 Brier score. The significant factors were different in each machine learning algorithm. If the person sleeps more than two hours during the day, their sex, education level, age, waking up during the night and if the person snores are the variables that most consistently have the highest feature importance in all algorithms. CONCLUSION: There is an association between sleep disturbances and dementia, which machine learning algorithms can predict. Furthermore, the risk factors for dementia are different across the algorithms, but sleep disturbances can predict dementia.

The prevalence of eHealth literacy and its relationship with perceived health status and psychological distress during Covid-19: a cross-sectional study of older adults in Blekinge, Sweden.

BACKGROUND AND AIMS: eHealth literacy is important as it influences health-promoting behaviors and health. The ability to use eHealth resources is essential to maintaining health, especially during COVID-19 when both physical and psychological health were affected. This study aimed to assess the prevalence of eHealth literacy and its association with psychological distress and perceived health status among older adults in Blekinge, Sweden. Furthermore, this study aimed to assess if perceived health status influences the association between eHealth literacy and psychological distress. METHODS: This cross-sectional study (October 2021-December 2021) included 678 older adults' as participants of the Swedish National Study on Aging and Care, Blekinge (SNAC-B). These participants were sent questionnaires about their use of Information and Communications Technology (ICT) during the COVID-19 pandemic. In this study, we conducted the statistical analysis using the Kruskal-Wallis one-way analysis of variance, Kendall's tau-b rank correlation, and multiple linear regression. RESULTS: We found that 68.4% of the participants had moderate to high levels of eHealth literacy in the population. Being female, age [Formula: see text] years, and having a higher education are associated with high eHealth literacy ([Formula: see text]). eHealth literacy is significantly correlated ([Formula: see text]=0.12, p-value=0.002) and associated with perceived health status ([Formula: see text]=0.39, p-value=0.008). It is also significantly correlated ([Formula: see text]=-0.12, p-value=0.001) and associated with psychological distress ([Formula: see text]=-0.14, p-value=0.002). The interaction of eHealth literacy and good perceived health status reduced psychological distress ([Formula: see text]=-0.30, p-value=0.002). CONCLUSIONS: In our cross-sectional study, we found that the point prevalence of eHealth literacy among older adults living in Blekinge, Sweden is moderate to high, which is a positive finding. However, there are still differences among older adults based on factors such as being female, younger than 75 years, highly educated, in good health, and without psychological distress. The results indicated that psychological distress could be mitigated during the pandemic by increasing eHealth literacy and maintaining good health status.

Psychological Health and Digital Social Participation of the Older Adults during the COVID-19 Pandemic in Blekinge, Sweden-An Exploratory Study.

COVID-19 has affected the psychological health of older adults directly and indirectly through recommendations of social distancing and isolation. Using the internet or digital tools to participate in society, one might mitigate the effects of COVID-19 on psychological health. This study explores the social participation of older adults through internet use as a social platform during COVID-19 and its relationship with various psychological health aspects. In this study, we used the survey as a research method, and we collected data through telephonic interviews; and online and paper-based questionnaires. The results showed an association of digital social participation with age and feeling lack of company. Furthermore, in addition, to the increase in internet use in older adults in Sweden during COVID-19, we conclude that digital social participation is essential to maintain psychological health in older adults.