scholarly journals Incisor Occlusion Affects Profile Shape Variation in Middle-Aged Adults

2021 ◽  
Vol 10 (4) ◽  
pp. 800
Author(s):  
Georgios Kanavakis ◽  
Anna-Sofia Silvola ◽  
Demetrios Halazonetis ◽  
Raija Lähdesmäki ◽  
Pertti Pirttiniemi
Keyword(s):  
Shape Variation ◽  
Middle Aged ◽  
Multivariate Regression Model ◽  
Factors Affecting ◽  
Profile Shape ◽  
Soft Tissue Profile ◽  
Study Population ◽  
Genetic And Environmental Factors ◽  
Middle Aged Adults ◽  
Procrustes Superimposition

Background: The aim of this study was to assess the effect of overjet and overbite on profile shape in middle–aged individuals. Methods: The study population comprised 1754 46-year-old individuals, members of the 1966 Northern Finland Birth Cohort. Their profile images were digitized using 48 landmarks and semi-landmarks. The subsequent landmark coordinates were then transformed to shape coordinates through Procrustes Superimposition, and final data were reduced into Principal Components (PCs) of shape. Overjet and overbite values were measured manually, during a clinical examination. A multivariate regression model was developed to evaluate the effect of overjet and overbite on profile shape. Results: The first nine PCs described more than 90% of profile shape variation in the sample and were used as the shape variables in all subsequent analyses. Overjet predicted 21.3% of profile shape in the entire sample (η2overjet = 0.213; p < 0.001), while the effect of overbite was weaker (η2overbite = 0.138; p < 0.001). In males, the equivalent effects were 22.6% for overjet and 14% for overbite, and in females, 25.5% and 13.5%, respectively. Conclusion: Incisor occlusion has a noteworthy effect on profile shape in middle-aged adults. Its impact becomes more significant taking into consideration the large variety of genetic and environmental factors affecting soft tissue profile.

scholarly journals Influencing Factors of Subjective Cognitive Impairment in Middle-Aged and Older Adults

2021 ◽  
Vol 18 (21) ◽  
pp. 11488
Author(s):  
Min Roh ◽  
Hyunju Dan ◽  
Oksoo Kim
Keyword(s):  
Older Adults ◽  
Cognitive Impairment ◽  
Depressive Symptoms ◽  
Multiple Logistic Regression Analysis ◽  
Middle Aged ◽  
Factors Affecting ◽  
Subjective Cognitive Impairment ◽  
Community Health Survey ◽  
Major Factors ◽  
Middle Aged Adults

The purpose of this study was to identify the factors affecting subjective cognitive impairment. We analyzed data from the 2019 Korea Community Health Survey and enrolled 68,546 middle-aged adults, aged 50 to 64 years, and 74,547 older adults, aged 65 years and older, in this study. Multiple logistic regression analysis was performed to identify factors influencing subjective cognitive impairment. Of the participants, 11,926 (17.4%) middle-aged and 21,880 (29.4%) older adults living in the community reported subjective cognitive impairment. Major factors that influenced subjective cognitive impairment in both middle-aged and older adults were gender, subjective stress, depressive symptoms, and alcohol drinking. In contrast to middle-aged adults, the marital status of older adults affected subjective cognitive impairment. Therefore, the factors affecting subjective cognitive impairment in middle-aged and older adults need to be considered for screening and management to prevent cognitive impairment and dementia. In particular, it is necessary to evaluate and manage stress and depressive symptoms from middle age to prevent subjective cognitive impairment.

scholarly journals Factors affecting adherence to asthma treatment in an international cohort of young and middle-aged adults

2007 ◽  
Vol 101 (6) ◽  
pp. 1363-1367 ◽  
Author(s):  
Angelo G. Corsico ◽  
Lucia Cazzoletti ◽  
Roberto de Marco ◽  
Christer Janson ◽  
Deborah Jarvis ◽  
...  
Keyword(s):  
Asthma Treatment ◽  
Middle Aged ◽  
Factors Affecting ◽  
Middle Aged Adults

scholarly journals Estimation of Heart Rate Using Regression Models and Artificial Neural Network in Middle-Aged Adults

2021 ◽  
Vol 12 ◽  
Author(s):  
Kuan Tao ◽  
Jiahao Li ◽  
Jiajin Li ◽  
Wei Shan ◽  
Huiping Yan ◽  
...  
Keyword(s):  
Neural Network ◽  
Heart Rate ◽  
Artificial Neural Network ◽  
Regression Model ◽  
Multivariate Regression ◽  
Maximal Heart Rate ◽  
Middle Aged ◽  
Multivariate Regression Model ◽  
Artificial Neural ◽  
Middle Aged Adults

Purpose: Heart rate is the most commonly used indicator in clinical medicine to assess the functionality of the cardiovascular system. Most studies have focused on age-based equations to estimate the maximal heart rate, neglecting multiple factors that affect the accuracy of the prediction.Methods: We studied 121 middle-aged adults at an average age of 57.2years with an average body mass index (BMI) of 25.9. The participants performed on a power bike with a starting wattage of 0W that was increased by 25W every 3min until the experiment terminated. Ambulatory blood pressure and electrocardiography were monitored through gas metabolic analyzers for safety concerns. Six descriptive characteristics of participants were observed, which were further analyzed using a multivariate regression model and an artificial neural network (ANN).Results: The input variables for the multivariate regression model and ANN were selected by correlation for the reduction of dimension. The accuracy of estimation by multivariate regression model and ANN was 9.74 and 9.42%, respectively, which outperformed the traditional age-based model (with an accuracy of 10.31%).Conclusion: This study provides comprehensive approaches to estimate the maximal heart rate using multiple indicators, revealing that both the multivariate regression model and ANN incorporated with age, resting heart rate (RHR), and second-order heart rate (SOHR) are more accurate than univariate models.

Sign in / Sign up

Export Citation Format

Share Document