1,082 results on '"compositional data analysis"'
Search Results
2. Association between 24-hour movement behavior and depression in college students: A compositional data analysis.
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Huang, Zan, Chen, Baoxiang, Dong, Xuefen, He, Jiabei, Liu, Yanjie, Li, Jiayu, and Zhou, Yulan
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DEPRESSION in college students , *SLEEP duration , *SEDENTARY behavior , *SLEEP , *PHYSICAL activity - Abstract
Evidence strongly suggests that moderate-to-vigorous physical activity (MVPA) can help reduce symptoms of depression. However, the relationship between 24-h movement behaviors and depressive symptoms, as well as the potential substitution effects between different behaviors, remains unclear. Therefore, this study seeks to investigate how the time spent in one behavior relative to others is associated with depressive symptoms. The study recruited 366 participants, who had their levels of MVPA, light PA (LPA), and sedentary behavior (SB) recorded using tri-axial accelerometers over 7 consecutive days. Participants also self-reported their sleep duration (SLP). Depression scores were measured using the Center for Epidemiological Studies Depression Scale (CES D). Using compositional linear regression, the study explored the connections between different compositions of time spent in movement behaviors and depression symptom scores. Spending more time on LPA and MVPA relative to other behaviors were associated with lower depression scores, whereas a higher proportion of SB relative to other activities was linked to increased depression scores. Reallocating time spent on SB to LPA and MVPA was associated with decreased depression scores. This study is a cross-sectional research design, and causality cannot be inferred. In addition, the sampling method of this study may have imposed some limitations on the representativeness of the sample. Further longitudinal studies could be conducted by selecting a large, representative sample. Within the spectrum of 24-h movement behaviors, increasing the duration of LPA and MVPA emerges as advantageous for reducing depression scores, suggesting a potential benefit in reallocating SB to PA, especially MVPA. • Higher proportions of sedentary behavior are associated with increased depression. • Increased time in moderate-to-vigorous physical activity and light physical activity is linked to lower depression. • Reallocating time from sedentary behavior to physical activities can reduce depression symptoms. [ABSTRACT FROM AUTHOR] more...
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- 2025
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3. 24-hour movement behaviors and changes in quality of life over time among community-dwelling older adults: a compositional data analysis.
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Palmberg, Lotta, Suorsa, Kristin, Löppönen, Antti, Karavirta, Laura, Rantanen, Taina, and Rantalainen, Timo
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BEHAVIORAL assessment , *INDEPENDENT living , *RESEARCH funding , *SEDENTARY lifestyles , *INTERVIEWING , *QUESTIONNAIRES , *ACCELEROMETRY , *DESCRIPTIVE statistics , *LONGITUDINAL method , *QUALITY of life , *SLEEP , *HEALTH behavior , *BODY movement , *PHYSICAL activity , *ALGORITHMS , *REGRESSION analysis , *WELL-being , *OLD age - Abstract
Background: Favorable movement behavior patterns, comprising more physical activity, less sedentary behavior, and sufficient sleep, may promote the maintenance of good quality of life (QoL) with advancing age. The aim of the present study was to investigate whether movement behaviors predict future changes in QoL among community-dwelling older adults over a four-year follow-up. Methods: Participants were 75-, 80- and 85-year-old community-dwelling older adults (n = 203) followed up for 4 years. Participants wore thigh- and trunk-mounted accelerometers for 3–7 days at baseline. Proportion of time-use in physical activity, standing and sedentary behavior were assessed based on body posture and movement intensity. Time in bed was determined using an automated algorithm. QoL was assessed during a home interview using the short Older People's Quality of Life Questionnaire at baseline and follow-up (range 13–65, higher scores indicate higher QoL). Compositional linear regression analysis was used to study whether baseline time-use composition predicts changes in QoL. Results: Over the 4-year follow-up, QoL scores decreased by 5% on average. Higher physical activity in relation to the other movement behaviors was associated with increase in QoL over time (βilr 0.94, p = 0.013), but this association attenuated after adding baseline physical function into the model. Sedentary behavior, standing, and time in bed were not associated with changes in QoL. Theoretical reallocation of 30 min of physical activity into sedentary behavior, standing or time in bed was estimated to decrease QoL by 0.5 (CI 95% -0.6 to -0.4), 0.6 (-0.7 to -0.5) and 0.4 (-0.5 to -0.3) points, respectively. Conclusions: Theoretical reallocation of physical activity into sedentary behavior, standing, and time in bed was found to be associated with prospective decline in QoL among older adults. Engaging more in physical activity and less in more passive activities may promote better QoL with advancing age. [ABSTRACT FROM AUTHOR] more...
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- 2024
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4. Optimal levels of sleep, sedentary behaviour, and physical activity needed to support cognitive function in children of the early years.
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Zahran, Samah, Cliff, Dylan P., Antczak, Devan, Aadland, Eivind, Aadland, Katrine N., Burley, Jade, Carson, Valerie, Draper, Catherine E., Dumuid, Dorothea, Kuzik, Nicholas, Silva, Diego Augusto Santos, van Sluijs, Esther M. F., Tremblay, Mark S., Olds, Timothy S., Okely, Anthony D., Stanley, Rebecca, Santos, Rute, and Janssen, Ian more...
- Abstract
Background: Sleep, sedentary behaviour, physical activity, and the composition of these movement behaviours across the 24-h day are associated with cognitive function in early years children. This study used a Goldilocks day compositional data analysis approach to identify the optimal duration of sleep, sedentary behaviour, light physical activity, and moderate-to-vigorous physical activity associated with desired cognitive function outcomes in early years children. Methods: This cross-sectional study included 858 children aged 2.8–5.5 years from the Sleep and Activity Database for the Early Years. 24-h movement behaviours (sleep, sedentary behaviour, light physical activity, moderate-to-vigorous physical activity) were measured using ActiGraph accelerometers. Cognitive function was measured using three tasks from the Early Years Toolbox: visual-spatial working memory, response inhibition, and expressive vocabulary. A Goldilocks day compositional data analysis approach was used in R software to identify the optimal time-use compositions associated with the best 10% of the cognitive function scores. Results: The movement behaviour composition and the relative time spent in sleep and sedentary behaviour but not different intensities of physical activity were significantly associated with working memory (P ≤ 0.01). The movement behaviour composition and relative time spent in sleep, sedentary behaviour, and different intensities of physical activity were not significantly associated with response inhibition or expressive vocabulary (P > 0.2). Therefore, optimal time use was only determined for working memory. Optimal daily durations for working memory were observed with 11:00 (hr:min) of sleep, 5:42 of sedentary behaviour, 5:06 of light physical activity, and 2:12 of moderate-to-vigorous physical activity. Conclusion: Working memory was the only cognitive function outcome related to the 24-h movement behaviour composition. Optimal sleep for working memory was consistent with current recommended durations, while optimal moderate-to-vigorous physical activity greatly exceeded minimal recommended levels. Optimal sedentary behaviour was longer and light physical activity was shorter than the sample average. [ABSTRACT FROM AUTHOR] more...
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- 2024
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5. Forecasting age distribution of life-table death counts via <italic>α</italic>-transformation.
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Shang, Han Lin and Haberman, Steven
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PRINCIPAL components analysis , *AGE distribution , *TIME series analysis , *LIFE expectancy , *PRICES - Abstract
We introduce a compositional power transformation, known as an
α -transformation, to model and forecast a time series of life-table death counts, possibly with zero counts observed at older ages. As a generalisation of the isometric log-ratio transformation (i.e. $ \alpha =0 $ α=0), theα transformation relies on the tuning parameterα , which can be determined in a data-driven manner. Using the Australian age-specific period life-table death counts from 1921 to 2020, theα transformation can produce more accurate short-term point and interval forecasts than the log-ratio transformation. The improved forecast accuracy of life-table death counts is of great importance to demographers and government planners for estimating survival probabilities and life expectancy and actuaries for determining annuity prices and reserves for various initial ages and maturity terms. [ABSTRACT FROM AUTHOR] more...- Published
- 2024
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6. Associations Between Childcare Physical Activity and Sedentary Time and Early Childhood Developmental Outcomes: A Compositional and Isotemporal Substitution Analysis.
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Phillips, Sophie M., Bourke, Matthew, Bruijns, Brianne A., Vanderloo, Leigh, Loh, Aidan, Saravanamuttoo, Kendall, and Tucker, Patricia
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MOTOR ability , *COGNITIVE testing , *SEDENTARY lifestyles , *ACCELEROMETERS , *EXERCISE intensity , *INTERNALIZING behavior , *OBJECT manipulation , *BEHAVIOR disorders in children , *CHILD development , *SOCIAL skills , *CHILD care , *EXTERNALIZING behavior , *BODY movement , *PHYSICAL activity , *REGRESSION analysis , *CHILDREN - Abstract
Background: Physical activity and sedentary time are independently associated with health and developmental outcomes in preschool children. However, the integrated nature of these behaviours on early life outcomes, particularly during childcare hours, is currently understudied. As such, the aim of this study was to examine the association between preschool children's physical activity and sedentary time during childcare and various developmental outcomes (psychosocial, cognitive and fundamental movement skills). Methods: A total of 107 preschool children (Mage: 41 ± 6 months) recruited from London, Canada, wore ActiGraph wGT3X‐BT accelerometers during childcare hours to measure their sedentary time, light intensity physical activity (LPA) and moderate‐to‐vigorous intensity physical activity (MVPA). Developmental outcomes, including psychosocial health (internalising, externalising, prosocial behaviour), indicators of cognitive development (memory, inhibitory control) and fundamental movement skills (locomotor control, object control, total fundamental movement), were assessed using validated tools. Compositional regression and isotemporal substitution models were estimated to examine how movement compositions in childcare were associated with developmental outcomes. Results: Engaging in more MVPA relative to LPA and sedentary time was associated with fewer internalising symptoms and better total fundamental movement skills and object control skills, whilst spending more time in LPA relative to MVPA and sedentary time was associated with more internalising symptoms and worse object control skills. Isotemporal substitution models suggested that theoretically increasing sedentary time or engaging in MVPA at the expense of time engaging in LPA during childcare is associated with lower internalising symptoms. Conclusion: The findings of this study provide preliminary evidence that engaging in MVPA during childcare, at the expense of time in LPA or sedentary time, is associated with children's fundamental movement skills and psychosocial development. Further longitudinal research is required, with larger samples of young children, to assess the mechanisms through which childcare movement behaviour compositions may interact with developmental outcomes, including contextualising both sedentary time and LPA. Trial Registration: ClinicalTrials.gov identifier: NCT05359536 [ABSTRACT FROM AUTHOR] more...
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- 2024
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7. Review and revamp of compositional data transformation: A new framework combining proportion conversion and contrast transformation
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Yiqian Zhang, Jonas Schluter, Lijun Zhang, Xuan Cao, Robert R. Jenq, Hao Feng, Jonathan Haines, and Liangliang Zhang
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Compositional data analysis ,Contrast transformation ,Conversion ,Microbiome ,Relative abundance ,Zero inflation ,Biotechnology ,TP248.13-248.65 - Abstract
Due to the development of next-generation sequencing technology and an increased appreciation of their role in modulating host immunity and their potential as therapeutic agents, the human microbiome has emerged as a key area of interest in various biological investigations of human health and disease. However, microbiome data present a number of statistical challenges not addressed by existing methods, such as the varying sequencing depth, the compositionality, and zero inflation. Solutions like scaling and transformation methods help to mitigate heterogeneity and release constraints, but often introduce biases and yield inconsistent results on the same data. To address these issues, we conduct a systematic review of compositional data transformation, with a particular focus on the connection and distinction of existing techniques. Additionally, we create a new framework that enables the development of new transformations by combining proportion conversion with contrast transformations. This framework includes well-known methods such as Additive Log Ratio (ALR) and Centered Log Ratio (CLR) as special cases. Using this framework, we develop two novel transformations—Centered Arcsine Contrast (CAC) and Additive Arcsine Contrast (AAC)—which show enhanced performance in scenarios with high zero-inflation. Moreover, our findings suggest that ALR and CLR transformations are more effective when zero values are less prevalent. This comprehensive review and the innovative framework provide microbiome researchers with a significant direction to enhance data transformation procedures and improve analytical outcomes. more...
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- 2024
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8. Optimal levels of sleep, sedentary behaviour, and physical activity needed to support cognitive function in children of the early years
- Author
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Samah Zahran, Dylan P. Cliff, Devan Antczak, Eivind Aadland, Katrine N. Aadland, Jade Burley, Valerie Carson, Catherine E. Draper, Dorothea Dumuid, Nicholas Kuzik, Diego Augusto Santos Silva, Esther M. F. van Sluijs, Mark S. Tremblay, Timothy S. Olds, Anthony D. Okely, Rebecca Stanley, Rute Santos, and Ian Janssen more...
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Cognition ,Time use epidemiology ,Compositional data analysis ,Movement behaviours ,Early childhood ,Preschool ,Pediatrics ,RJ1-570 - Abstract
Abstract Background Sleep, sedentary behaviour, physical activity, and the composition of these movement behaviours across the 24-h day are associated with cognitive function in early years children. This study used a Goldilocks day compositional data analysis approach to identify the optimal duration of sleep, sedentary behaviour, light physical activity, and moderate-to-vigorous physical activity associated with desired cognitive function outcomes in early years children. Methods This cross-sectional study included 858 children aged 2.8–5.5 years from the Sleep and Activity Database for the Early Years. 24-h movement behaviours (sleep, sedentary behaviour, light physical activity, moderate-to-vigorous physical activity) were measured using ActiGraph accelerometers. Cognitive function was measured using three tasks from the Early Years Toolbox: visual-spatial working memory, response inhibition, and expressive vocabulary. A Goldilocks day compositional data analysis approach was used in R software to identify the optimal time-use compositions associated with the best 10% of the cognitive function scores. Results The movement behaviour composition and the relative time spent in sleep and sedentary behaviour but not different intensities of physical activity were significantly associated with working memory (P ≤ 0.01). The movement behaviour composition and relative time spent in sleep, sedentary behaviour, and different intensities of physical activity were not significantly associated with response inhibition or expressive vocabulary (P > 0.2). Therefore, optimal time use was only determined for working memory. Optimal daily durations for working memory were observed with 11:00 (hr:min) of sleep, 5:42 of sedentary behaviour, 5:06 of light physical activity, and 2:12 of moderate-to-vigorous physical activity. Conclusion Working memory was the only cognitive function outcome related to the 24-h movement behaviour composition. Optimal sleep for working memory was consistent with current recommended durations, while optimal moderate-to-vigorous physical activity greatly exceeded minimal recommended levels. Optimal sedentary behaviour was longer and light physical activity was shorter than the sample average. more...
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- 2024
- Full Text
- View/download PDF
9. 24-hour movement behaviors and changes in quality of life over time among community-dwelling older adults: a compositional data analysis
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Lotta Palmberg, Kristin Suorsa, Antti Löppönen, Laura Karavirta, Taina Rantanen, and Timo Rantalainen
- Subjects
Physical activity ,Sedentary behavior ,Sleep ,Wellbeing ,Compositional data analysis ,Nutritional diseases. Deficiency diseases ,RC620-627 ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background Favorable movement behavior patterns, comprising more physical activity, less sedentary behavior, and sufficient sleep, may promote the maintenance of good quality of life (QoL) with advancing age. The aim of the present study was to investigate whether movement behaviors predict future changes in QoL among community-dwelling older adults over a four-year follow-up. Methods Participants were 75-, 80- and 85-year-old community-dwelling older adults (n = 203) followed up for 4 years. Participants wore thigh- and trunk-mounted accelerometers for 3–7 days at baseline. Proportion of time-use in physical activity, standing and sedentary behavior were assessed based on body posture and movement intensity. Time in bed was determined using an automated algorithm. QoL was assessed during a home interview using the short Older People’s Quality of Life Questionnaire at baseline and follow-up (range 13–65, higher scores indicate higher QoL). Compositional linear regression analysis was used to study whether baseline time-use composition predicts changes in QoL. Results Over the 4-year follow-up, QoL scores decreased by 5% on average. Higher physical activity in relation to the other movement behaviors was associated with increase in QoL over time (βilr 0.94, p = 0.013), but this association attenuated after adding baseline physical function into the model. Sedentary behavior, standing, and time in bed were not associated with changes in QoL. Theoretical reallocation of 30 min of physical activity into sedentary behavior, standing or time in bed was estimated to decrease QoL by 0.5 (CI 95% -0.6 to -0.4), 0.6 (-0.7 to -0.5) and 0.4 (-0.5 to -0.3) points, respectively. Conclusions Theoretical reallocation of physical activity into sedentary behavior, standing, and time in bed was found to be associated with prospective decline in QoL among older adults. Engaging more in physical activity and less in more passive activities may promote better QoL with advancing age. more...
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- 2024
- Full Text
- View/download PDF
10. Reallocation of time to moderate-to-vigorous physical activity and estimated changes in physical fitness among preschoolers: a compositional data analysis
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Zhaoxu Lu, Jin Guo, Chuanhe Liu, Jian Wu, Chuo Zhao, Fang Wang, Yihua Bao, Haowen Zhang, Bing Qi, Xiuhe Li, Hongyan Guan, Jianxin Wu, and Ting Zhang
- Subjects
Preschoolers ,Compositional data analysis ,24-h movement behaviours ,Physical fitness ,MVPA ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background Previous research has examined the associations of preschoolers’ 24-h movement behaviours, including light and moderate-to-vigorous physical activity (LPA and MVPA), sedentary behaviour (SB), sleep, with physical fitness in isolation, ignoring intrinsically compositional nature of movement data while increasing the risk of collinearity. Thus, this study investigated the associations of preschoolers’ 24-h Movement behaviours composition with physical fitness, estimated changes in physical fitness when time was reallocated between movement behaviours composition, and determined whether associations differ between different genders, using compositional data analysis. Methods In the cross-sectional study, a total of 275 preschoolers (3 ~ 6 y) from China were included. SB, LPA and MVPA times were objectively monitored with an ActiGraph GT9X accelerometer for 7 consecutive days. Sleep duration was obtained using parental reports. Physical fitness parameters, including upper and lower limb strength, static balance, speed-agility, and cardiorespiratory fitness (CRF), were determined with the PREFIT battery. The associations of 24-h movement behaviours composition with each physical fitness parameter were examined employing compositional multivariable linear regression models. The changes following time reallocation among behaviours were estimated employing compositional isotemporal substitution analyses. Results Greater MVPA, but not LPA, was significantly related to better upper and lower limb strength, speed-agility, and CRF. Reallocating time from LPA or SB to MVPA was related to better physical fitness. The associations were non-symmetrical: the estimated detriments to physical fitness from replacing MVPA with LPA or SB were larger than the estimated benefits associated with adding MVPA of the same magnitude. The aforementioned associations with lower limb strength, CRF, and speed-agility were observed in boys, while associations with upper and lower limb strength were noted in girls. Conclusion Our findings reinforce the importance of physical activity (PA) intensity for the development of physical fitness in preschoolers. Replacing LPA or SB time with MVPA may be an appropriate strategy for enhancing preschoolers’ physical fitness. more...
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- 2024
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11. Organizational Culture and Business-IT Alignment: A Compositional Study.
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Sieber, Marcel R.
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INFORMATION technology , *DIGITAL technology , *PERSONNEL management , *CORPORATE culture , *REGRESSION analysis , *INFORMATION technology management - Abstract
In the digital age, the role of information technology (IT) management in organizations is fundamentally changing, especially in aligning business and IT. This study examines the relationship between organizational culture and business-IT alignment. It juxtaposes two four-component models in a novel way and presents a sound methodology for dealing with multiplicative ipsative rating scales of a questionnaire. Such measures have in common that the items' alternatives relate to each other or the whole and need corresponding compositional data analysis. Linear regression and the resulting log-ratio coefficients reveal a culture/alignment combination of hierarchy with service- and adhocracy with investment orientation. This study claims to be one of the first papers to successfully employ the established compositional methodology on a composition-to-composition model in IT management research. Plain language summary: Purpose—This paper examines the relationship between organizational culture and business-IT alignment moderated by digitalization based on established models from IT and management research. Methodology—Ipsative data from 450 respondents of an online questionnaire were analyzed using compositional data analysis and linear regression. Findings—The results show that culture and alignment are interrelated. Hierarchy and adhocracy culture types in IT are paired with the alignment performance criteria of a service center and an investment center; digitalization moderates and amplifies the effects. Research limitations/implications—This study compares two four-component models in a novel way and applies compositional data analysis to explain the culture-alignment relationship. However, it represents only a general snapshot; sample or group differences remain to be explored. Practical implications—The findings indicate that a combined cultural mindset of stability and innovation can help IT management and staff better align IT and business and achieve strategic and operative goals. Originality/value—Comparing two established IT culture and alignment models, this paper presents a sound methodology for dealing with forced-choice questionnaire data. [ABSTRACT FROM AUTHOR] more...
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- 2024
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12. Comparative Analysis of Airborne Bacterial and Fungal Communities in South-Eastern Italy and in Albania Using the Compositional Analysis of 16S and ITS rRNA Gene Sequencing Datasets.
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Romano, Salvatore, Pepkolaj, Lekë, Fragola, Mattia, Peccarrisi, Dalila, Dhimitri, Jostina, Buccolieri, Alessandro, Talà, Adelfia, Alifano, Pietro, Quarta, Gianluca, and Calcagnile, Lucio
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MICROBIAL ecology , *SINGULAR value decomposition , *MICROBIAL communities , *AUREOBASIDIUM pullulans , *PRINCIPAL components analysis - Abstract
This study investigates airborne bacterial and fungal communities in south-eastern Italy and Albania using advanced DNA-based techniques and compositional data analysis (CoDa). We assess the significance of airborne microbial communities, detailing our methodologies for site selection, sample collection, DNA extraction, and data analysis. Our results reveal distinct differences in microbial composition between the two regions, driven by local environmental factors. Specifically, Albanian samples showed higher abundances of bacterial species such as Rubellimicrobium roseum and Sphingomonas cynarae, while Italian samples were characterized by a prevalence of Truepera radiovictrix and Rubrobacter radiotolerans. In terms of fungi, Albanian sites exhibited greater abundance of Mycosphaerella tassiana, Aureobasidium pullulans, and Ascochyta herbicola. Aitchison distance-based dendrograms and principal component analysis (PCA) biplots, utilizing singular value decomposition, clearly delineated a geographical separation of microbial communities, underscoring the impact of regional atmospheric conditions on microbial composition. In the discussion, we interpret these findings in the context of regional environmental factors, highlighting their implications for understanding regional differences in airborne microbial communities. The conclusion emphasizes the effectiveness of advanced DNA techniques and CoDa in environmental microbiology, offering insights into how local environmental conditions shape microbial communities and suggesting directions for future research and public health considerations. [ABSTRACT FROM AUTHOR] more...
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- 2024
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13. Associations of Reallocating Sedentary Time to Physical Activity and Sleep with Physical and Mental Health of Older Adults.
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WEI LIANG, YANPING WANG, NING SU, HUIQI SONG, RHODES, RYAN E., XIANG WANG, BORUI SHANG, LIN ZHOU, QIAN HUANG, DANRAN BU, BAKER, JULIEN S., and YANPING DUAN
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CROSS-sectional method , *HEALTH status indicators , *MENTAL health , *RESEARCH funding , *SEDENTARY lifestyles , *BODY composition , *QUESTIONNAIRES , *DESCRIPTIVE statistics , *CARDIOVASCULAR diseases risk factors , *SLEEP , *PHYSICAL fitness , *DATA analysis software , *CONFIDENCE intervals , *PHYSICAL activity , *OLD age - Abstract
Introduction: Twenty-four-hour movement behaviors: moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behavior (SB), and sleep are crucial factors affecting older adults’ health. Using a compositional data analysis approach, this study examined the associations of time spent in these four movement behaviors with cardiometabolic health, physical fitness, and mental health among older adults. Furthermore, this study identified the estimated changes in aforementioned health outcomes by reallocating SB time to other movement behaviors. Methods: A population-based cross-sectional study of 4562 participants (67.68 ± 5.03 yr; 55.8% female) were implemented in Hubei China between July 25 and November 19, 2020. Measures included demographics, movement behaviors, cardiometabolic indicators (body mass index, waist circumference, waist–hip ratio, percentage body fat, systolic and diastolic blood pressure), physical fitness, and mental health outcomes (depressive symptoms and loneliness). Compositional data analyses were implemented in R. Results: MVPA and sleep time were associated with greater health outcomes (all P < 0.001), except blood pressure (P = 0.13–0.83). LPA time was associated with waist circumference (B = 0.313, P = 0.009), waist–hip ratio (B = 0.003, P = 0.003), physical fitness (B = 0.36, P < 0.001), and mental health indicators (both P < 0.001). Reallocating 30-min SB to MVPA and sleep was associated with predicated improvements in all health outcomes, except blood pressure, whereas reallocating 30-min SB to LPA resulted in predicted improvements in physical fitness (0.187 units), depressive symptoms (−0.264 units), and loneliness (−0.395 units). For dose–effect relationships, reallocating 5–60 min of SB to MVPA showed greatest benefits for all health outcomes. Conclusions: This study provides timely empirical evidence for future interventions and policymaking on promoting healthy aging during the post–COVID-19 era. The findings underline the importance of including 24-h movement behaviors in future health promotion among older adults. [ABSTRACT FROM AUTHOR] more...
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- 2024
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14. Study of Ge‐Rich Ge–Sb–Te Device‐Dependent Segregation for Industrial Grade Embedded Phase‐Change Memory.
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Petroni, Elisa, Allegra, Mario, Baldo, Matteo, Laurin, Luca, Serafini, Andrea, Favennec, Laurent, Desvoivres, Latifa, Sandrini, Jury, Boccaccio, Christian, Le‐Friec, Yannick, Ostrovsky, Alain, Gouraud, Pascal, Bonnevialle, Aurore, Ranica, Rossella, and Redaelli, Andrea more...
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ELECTRON energy loss spectroscopy , *STATISTICAL reliability , *AUTOMOBILE industry , *RECORDS management , *MANUFACTURING processes - Abstract
Ge‐rich Ge–Sb–Te (GGST) alloys are the most promising materials for phase‐change memory in embedded applications, being able to fulfill the tough data retention requirements of automotive and consumer markets. GGST alloys are sensitive to thermal budgets and spatial confinement; thus, memory device process integration and architecture can strongly impact their final electrical properties and reliability. Herein, exploiting a statistical methodology capable to extract quantitative metrics for evaluating by‐process segregation, the inhomogeneity of out‐of‐fab GGST material in function of process parameters is studied such as architecture and alloy composition. The present results with the already known source of segregation, namely the back‐end‐of‐line thermal budget, are compared providing a comprehensive description of the main modulating factors of segregation among these different process parameters. [ABSTRACT FROM AUTHOR] more...
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- 2024
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15. A new approach for measuring and analysing residential segregation.
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De Falco, Antonio and Irpino, Antonio
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RESIDENTIAL segregation ,SOCIAL science research ,SOCIAL types ,FACTOR analysis ,GRID cells - Abstract
This work proposes a new approach for residential segregation analysis contributing to the methodological debate relating to the measurement of the phenomenon and its comparability between different urban contexts. The strategy of analysis involves the use of areal interpolation methods to create high-resolution population grids, a compositional data approach, and the implementation of factorial analysis to define a socio-economic class composition index based on categorical data, which is a common data type in social research. The latter, in combination with spatial autocorrelation tools and the adoption of a criterion based on temporal distances to define spatial relations between grid cells, enables the identification and mapping of segregated areas. To test our method, we rely on the latest UK census data (2021) for the metropolitan areas of Liverpool, Manchester, and Newcastle upon Tyne, employing social groups defined according to the National Statistics Socio-economic Classification provided by the Office for National Statistics as population data. Finally, the validity of the proposed methodology is demonstrated through case studies, and the results are interpreted within the broader theoretical framework on the topic. [ABSTRACT FROM AUTHOR] more...
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- 2024
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16. Generalized functional additive mixed models with (functional) compositional covariates for areal Covid-19 incidence curves.
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Eckardt, Matthias, Mateu, Jorge, and Greven, Sonja
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REGRESSION analysis ,HILBERT space ,FUNCTIONAL analysis ,ISOMORPHISM (Mathematics) ,COVID-19 - Abstract
We extend the generalized functional additive mixed model to include compositional and functional compositional (density) covariates carrying relative information of a whole. Relying on the isometric isomorphism of the Bayes Hilbert space of probability densities with a sub-space of the L 2 , we include functional compositions as transformed functional covariates with constrained yet interpretable effect function. The extended model allows for the estimation of linear, non-linear, and time-varying effects of scalar and functional covariates, as well as (correlated) functional random effects, in addition to the compositional effects. We use the model to estimate the effect of the age, sex, and smoking (functional) composition of the population on regional Covid-19 incidence data for Spain, while accounting for climatological and socio-demographic covariate effects and spatial correlation. [ABSTRACT FROM AUTHOR] more...
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- 2024
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17. A Stepwise Cosimulation Framework for Modeling Critical Elements in Copper Porphyry Deposits.
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Nasretdinova, Milena, Madani, Nasser, and Maleki, Mohammad
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METALS ,PORPHYRY ,COPPER ,MOLYBDENUM ,LITHIUM-ion batteries ,MACHINE learning - Abstract
The increased attention given to batteries has given rise to apprehensions regarding their availability; they have thus been categorized as essential commodities. Cobalt (Co), copper (Cu), lithium (Li), nickel (Ni), and molybdenum (Mo) are frequently selected as the primary metallic elements in lithium-ion batteries. The principal aim of this study was to develop a computational algorithm that integrates geostatistical methods and machine learning techniques to assess the resources of critical battery elements within a copper porphyry deposit. By employing a hierarchical/stepwise cosimulation methodology, the algorithm detailed in this research paper successfully represents both soft and hard boundaries in the simulation results. The methodology is evaluated using several global and local statistical studies. The findings indicate that the proposed algorithm outperforms the conventional approach in estimating these five elements, specifically when utilizing a stepwise estimation strategy known as cascade modeling. The proposed algorithm is also validated against true values by using a jackknife method, and it is shown that the method is precise and unbiased in the prediction of critical battery elements. [ABSTRACT FROM AUTHOR] more...
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- 2024
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18. Life Activities Time Allocation and Subjective Well-Being of the Old Adults in China: a Compositional Perspective: Life Activities Time Allocation and Subjective Well-being of the Old Adults in China: a Compositional Perspective
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Chen, Xuan, Zhang, Peng, Peng, Kaiping, and Wang, Yifan
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- 2025
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19. Reallocating just 10 min to moderate-to-vigorous physical activity from other components of 24-hour movement behaviors improves cardiovascular health in adults
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Yemeng Ji, Muhammed M. Atakan, Xu Yan, Jinlong Wu, Jujiao Kuang, and Li Peng
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Cardiovascular health ,Compositional data analysis ,Isotemporal substitution ,Moderate-to-vigorous physical activity ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background As components of a 24-hour day, sedentary behavior (SB), physical activity (PA), and sleep are all independently linked to cardiovascular health (CVH). However, insufficient understanding of components’ mutual exclusion limits the exploration of the associations between all movement behaviors and health outcomes. The aim of this study was to employ compositional data analysis (CoDA) approach to investigate the associations between 24-hour movement behaviors and overall CVH. Methods Data from 581 participants, including 230 women, were collected from the 2005–2006 wave of the US National Health and Nutrition Examination Survey (NHANES). This dataset included information on the duration of SB and PA, derived from ActiGraph accelerometers, as well as self-reported sleep duration. The assessment of CVH was conducted in accordance with the criteria outlined in Life’s Simple 7, encompassing the evaluation of both health behaviors and health factors. Compositional linear regression was utilized to examine the cross-sectional associations of 24-hour movement behaviors and each component with CVH score. Furthermore, the study predicted the potential differences in CVH score that would occur by reallocating 10 to 60 min among different movement behaviors. Results A significant association was observed between 24-hour movement behaviors and overall CVH (p 0.05). Conclusions MVPA seems to be as a pivotal determinant for enhancing CVH among general adult population, relative to other movement behaviors. Consequently, optimization of MVPA duration is an essential element in promoting overall health and well-being. more...
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- 2024
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20. The 'sweet- and sour-spot' of occupational physical activity for back pain: a prospective accelerometer study among eldercare workers
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Stavros Kyriakidis, Charlotte Lund Rasmussen, Karen Søgaard, Andreas Holtermann, Charlotte Diana Nørregaard Rasmussen, and Nidhi Gupta
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back pain ,occupational health ,physical activity ,occupational physical activity ,musculoskeletal health ,eldercare worker ,compositional data analysis ,sweet- and sour-spot ,accelerometer study ,time-use epidemiology ,physical behavior ,Public aspects of medicine ,RA1-1270 - Abstract
OBJECTIVES: Both high and low levels of occupational physical activity are associated with back pain. Thus, there might be a “sweet- and sour-spot” of occupational physical activity for back pain. Our aim was to investigate if there exists an occupational physical activity “sweet- (lowest risk) and sour-spot” (highest risk) for back pain. METHODS: A total of 396 eldercare workers from 20 Danish nursing homes participated. Occupational physical activity was measured between 1–4 working days using thigh-worn accelerometry. Back pain intensity was reported monthly on a scale from 0–10 over 1-year. A zero-inflated mixed-effects model was developed regressing occupational physical activity against back pain, adjusted for confounders. The “sweet- and sour-spot” were defined as the occupational physical activity compositions (sitting, standing, light, and moderate-to-vigorous) associated with the 5% lowest and highest risk for back pain, respectively. RESULTS: The composition associated with the lowest risk of back pain – the “sweet-spot”– consisted of 71% worktime spent sitting, 18% spent standing, 5% spent on light physical activity and 6% spent on moderate-to-vigorous physical activity. The composition associated with highest risk for back pain –the “sour-spot”– consisted of 8% worktime spent sitting, 66% spent standing, 4% spent on light physical activity, and 21% spent on moderate-to-vigorous physical activity. CONCLUSIONS: The “sweet-spot” of occupational physical activity for back pain among eldercare workers involves more sitting and light physical activity time, while the “sour-spot” involves more standing and moderate-to-vigorous physical activity time. Research on the occupational physical activity “sweet- and sour-spot” is needed. more...
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- 2024
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21. Is patients’ activities of daily living self-care score in Norwegian home care a proxy for workers standing at work?
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Fredrik Klæboe Lohne, Marius Steiro Fimland, Charlotte Lund Rasmussen, Ingeborg Frostad Liaset, Heike Fischer, and Skender Redzovic
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Occupational health ,Constrained standing ,Health care services ,Compositional data analysis ,Musculoskeletal pain ,Norway ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background Prolonged standing at work may contribute to increased risk of musculoskeletal pain in home care workers. Patients’ activities of daily living (ADL) score may be a proxy for home care workers’ standing time at work. The objective of the present study was to investigate the association between patients’ ADL self-care score, and workers standing time. Methods This cross-sectional study measured time spent standing, sitting and in physical activity for seven days using thigh-worn accelerometers, among 14 home care workers. Patients’ ADL self-care scores are routinely adjusted by home care nurses, and time intervals of home care visits are stored in home care services electronic patient journal. We collected ADL self-care scores and start and end time points of visits, and categorized ADL self-care scores as low (ADL ≤ 2.0), medium (ADL > 2.0 to 3.0) or high (ADL > 3.0). Physical behavior data were transformed to isometric log-ratios and a mixed-effect model was used to investigate differences in physical behavior between the three ADL self-care score categories. Results We analyzed 931 patient visits and found that high ADL self-care scores were associated with longer standing times relative to sitting and physical activity, compared to low ADL score (0.457, p = 0.001). However, no significant differences in time spent standing were found between high and medium ADL patient visits (0.259, p = 0.260), nor medium and low (0.204, p = 0.288). High ADL score patients made up 33.4% of the total care time, despite only making up 7.8% of the number of patients. Conclusion Our findings suggest that caring for patients with high ADL self-care score requires workers to stand for longer durations and that this group of patients constitute a significant proportion of home care workers’ total work time. The findings of this study can inform interventions to improve musculoskeletal health among home care workers by appropriate planning of patient visits. more...
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- 2024
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22. Research progress of 24-hour movement behaviors in chronic non-communicable disease.
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Rong-Xuan Li, Qing-Qing Fan, and Di Cui
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NON-communicable diseases , *CHRONIC diseases , *SEDENTARY behavior , *MENTAL illness , *CARDIOVASCULAR diseases , *COMMUNICABLE diseases , *PSYCHIATRIC epidemiology - Abstract
Chronic non-communicable diseases (NCDs) represent a significant impediment to improve life expectancy and remain a focal point in global public health and disease prevention efforts. 24-hour movement behaviors, which include sleep, sedentary behavior (SED), and physical activity, underscore the inherent connections between different daily activities and the comprehensive impact of overall movement patterns on health. Evidence suggested that modifying patterns of 24-hour movement behaviors can aid in preventing and attenuating the progression of NCDs. This study systematically delineated the concept, evolution, analytical methods, and intrinsic associations of 24-hour movement behaviors, emphasizing their pivotal role in the prevention and management of NCDs such as obesity, mental disorders, cardiovascular diseases, diabetes, and renal diseases. Future research endeavors should focus on refining methodologies, broadening study populations, developing research tools, and exploring precise intervention strategies and interdisciplinary approaches to comprehensively enhance the effectiveness of NCDs prevention and management from a temporal perspective. Such efforts are poised to provide substantive guidance and support for public health practices. [ABSTRACT FROM AUTHOR] more...
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- 2024
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23. Longitudinal Associations between 24-h Movement Behaviors and Cardiometabolic Biomarkers: A Natural Experiment over Retirement.
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SUORSA, KRISTIN, LESKINEN, TUIJA, GUPTA, NIDHI, ANDERSEN, LARS L., PASANEN, JESSE, HETTIARACHCHI, PASAN, JOHANSSON, PETER J., PENTTI, JAANA, VAHTERA, JUSSI, and STENHOLM, SARI
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METABOLIC disorders , *HDL cholesterol , *CARDIOVASCULAR diseases , *RESEARCH funding , *RETIREMENT , *PUBLIC sector , *ACCELEROMETERS , *SEDENTARY lifestyles , *LDL cholesterol , *EXERCISE intensity , *HEALTH behavior , *SLEEP , *BODY movement , *BIOMARKERS , *PHYSICAL activity , *REGRESSION analysis - Abstract
Introduction: Physical activity, sedentary behavior, and sleep, that is, 24-h movement behaviors, often change in the transition from work to retirement, which may affect cardiometabolic health. This study investigates the longitudinal associations between changes in 24-h movement behaviors and cardiometabolic biomarkers during the retirement transition. Methods: Retiring public sector workers (n = 212; mean (SD) age, 63.5 (1.1) yr) from the Finnish Retirement and Aging study used a thigh-worn Axivity accelerometer and filled out a diary to obtain data on daily time spent in sedentary behavior (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), and sleep before and after retirement (1 yr in-between). Cardiometabolic biomarkers, including LDL-cholesterol, HDL-cholesterol, total/HDL-cholesterol ratio, triglycerides, C-reactive protein, fasting glucose, and insulin, were measured. Associations between changes in 24-h movement behaviors and cardiometabolic biomarkers were analyzed using compositional robust regression and isotemporal substitution analysis. Results: Increasing LPA in relation to remaining behaviors was associated with an increase in HDL-cholesterol and decrease in total/HDL-cholesterol ratio ( P < 0.05 for both). For instance, reallocation of 30 min from sleep/SED to LPA was associated with an increase in HDL-cholesterol by 0.02 mmol⋅L-1. Moreover, increasing MVPA in relation to remaining behaviors was associated with a decrease in triglycerides ( P = 0.02). Reallocation of 30 min from SED/sleep to MVPA was associated with 0.07-0.08 mmol⋅L-1 decrease in triglycerides. Findings related to LDL-cholesterol, C-reactive protein, fasting glucose, and insulin were less conclusive. Conclusions: During the transition from work to retirement, increasing physical activity at the expense of passive behaviors was associated with a better lipid profile. Our findings suggest that life transitions like retirement could be utilized more as an optimal time window for promoting physical activity and health. [ABSTRACT FROM AUTHOR] more...
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- 2024
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24. A New Methodological Proposal for Classifying Firms According to the Similarity of Their Financial Structures Based on Combining Compositional Data with Fuzzy Clustering.
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MOLAS-COLOMER, XAVIER, LINARES-MUSTARÓS, SALVADOR, ÀNGELS FARRERAS-NOGUER, MARIA, and CARLES FERRER-COMALAT, JOAN
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FINANCIAL ratios ,BUSINESS enterprises ,FUZZY clustering technique - Abstract
The main aim of this paper is to show that the methodology of classifying firms of the same sector according to the similarity of their classical financial ratios results in serious problems of incoherence and, consequently, it is necessary to find a viable alternative. With this objective in mind, simple examples are used to show that the appearance of multiple unsolvable problems make it impossible to accept the validity of grouping firms according to homogeneous groups based on these ratios using the usual clustering techniques. Once this fundamental fact has been verified, the proposal of classifying firms based on the ratios created in compositional data methodology and fuzzy clustering is shown to offer a viable alternative for this purpose. The paper ends with a complete analysis using real data. [ABSTRACT FROM AUTHOR] more...
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- 2024
25. Evaluation of normalization methods for predicting quantitative phenotypes in metagenomic data analysis.
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Beibei Wang and Yihui Luan
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METAGENOMICS ,PHENOTYPES ,STANDARD deviations ,EVALUATION methodology ,DATA analysis ,FORECASTING - Abstract
Genotype-to-phenotype mapping is an essential problem in the current genomic era. While qualitative case-control predictions have received significant attention, less emphasis has been placed on predicting quantitative phenotypes. This emerging field holds great promise in revealing intricate connections between microbial communities and host health. However, the presence of heterogeneity in microbiome datasets poses a substantial challenge to the accuracy of predictions and undermines the reproducibility of models. To tackle this challenge, we investigated 22 normalization methods that aimed at removing heterogeneity across multiple datasets, conducted a comprehensive review of them, and evaluated their effectiveness in predicting quantitative phenotypes in three simulation scenarios and 31 real datasets. The results indicate that none of these methods demonstrate significant superiority in predicting quantitative phenotypes or attain a noteworthy reduction in Root Mean Squared Error (RMSE) of the predictions. Given the frequent occurrence of batch effects and the satisfactory performance of batch correction methods in predicting datasets affected by these effects, we strongly recommend utilizing batch correction methods as the initial step in predicting quantitative phenotypes. In summary, the performance of normalization methods in predicting metagenomic data remains a dynamic and ongoing research area. Our study contributes to this field by undertaking a comprehensive evaluation of diverse methods and offering valuable insights into their effectiveness in predicting quantitative phenotypes. [ABSTRACT FROM AUTHOR] more...
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- 2024
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26. Hypothesis-driven mediation analysis for compositional data: an application to gut microbiome.
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Kartiosuo, Noora, Nevalainen, Jaakko, Raitakari, Olli, Pahkala, Katja, and Auranen, Kari
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GUT microbiome , *CAUSAL inference , *GRAPH theory , *PARAMETRIC modeling , *DATA analysis , *MEDIATION (Statistics) - Abstract
Sequencing read-count data often exhibit sparsity (zero-count inflation) and overdispersion. As most sequencing techniques provide an arbitrary total count, taxon-specific counts should be treated under the compositional data-analytic framework. There is increasing interest in the role of gut microbiome composition in mediating the effects of exposures on health. Previous compositional mediation approaches have focused on identifying mediating taxa among a number of candidates. We here consider compositional causal mediation when a priori knowledge is available about the hierarchy for a restricted number of taxa, building on a single hypothesis structured as contrasts between appropriate sub-compositions. Based on the assumed causal graph and the theory of multiple contemporaneous mediators, we define non-parametric estimands for overall and coordinate-wise mediation effects and show how they are estimated based on parametric linear models. The mediators have straightforward and coherent interpretations, related to causal questions about interrelationships between the sub-compositions. We perform a simulation study focusing on the impact of sparsity on estimation. While unbiased, the estimators' precision depends on sparsity and the relative magnitudes of exposure-to-mediator and mediator-to-outcome effects in a complex manner. In the empirical application we find an inverse association of fibre intake on insulin level, mainly attributable to the direct effects. [ABSTRACT FROM AUTHOR] more...
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- 2024
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27. Compositional data analysis by the square-root transformation: Application to NBA USG% data.
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Jeseok Lee and Byungwon Kim
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DATA analysis ,SQUARE root - Abstract
Compositional data refers to data where the sum of the values of the components is a constant, hence the sample space is defined as a simplex making it impossible to apply statistical methods developed in the usual Euclidean vector space. A natural approach to overcome this restriction is to consider an appropriate transformation which moves the sample space onto the Euclidean space, and log-ratio typed transformations, such as the additive log-ratio (ALR), the centered log-ratio (CLR) and the isometric log-ratio (ILR) transformations, have been mostly conducted. However, in scenarios with sparsity, where certain components take on exact zero values, these log-ratio type transformations may not be effective. In this work, we mainly suggest an alternative transformation, that is the square-root transformation which moves the original sample space onto the directional space. We compare the square-root transformation with the log-ratio typed transformation by the simulation study and the real data example. In the real data example, we applied both types of transformations to the USG% data obtained from NBA, and used a density based clustering method, DBSCAN (density-based spatial clustering of applications with noise), to show the result. [ABSTRACT FROM AUTHOR] more...
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- 2024
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28. Online or Face-to-Face: A Data-Analytics Approach to Understanding First-Year Students' Learning Preferences and Academic Achievements
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Moeketsi Mosia
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compositional data analysis ,face-to-face learning ,first-year students ,online learning ,post-pandemic education ,Education (General) ,L7-991 - Abstract
This research explored the predictive power of individual and contextual factors on first-year students' preferences for online versus face-to-face learning environments, examined through a Bayesian framework for analyzing compositional data. Purposefully, it delves into how students' academic performance and geographic location influence their educational modality choices in a post-pandemic context. As quantitative research, the paper employs Bayesian statistical methods, the research analyzed student preferences across varied South African provinces, juxtaposing these with academic performance to uncover patterns and predictors of learning modality preferences. The student learning modalities preferences were collected through questionnaire as a compositional data. The findings revealed a significant correlation analysis which is, that students with higher academic performance and those residing in remote areas show a preference for face-to-face learning modality, challenging the notion that online learning preferences are primarily driven by academic outcomes alone. Adding a novel dimension, this investigation enriches the current understanding of educational preferences by applying a Bayesian approach, revealing that predictive analyses must account for a blend of personal and situational factors. This insight is pivotal for formulating educational policies that are both inclusive and responsive to the diverse needs of the student populace in a dynamically evolving educational terrain. more...
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- 2024
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29. Reallocation of time to moderate-to-vigorous physical activity and estimated changes in physical fitness among preschoolers: a compositional data analysis
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Lu, Zhaoxu, Guo, Jin, Liu, Chuanhe, Wu, Jian, Zhao, Chuo, Wang, Fang, Bao, Yihua, Zhang, Haowen, Qi, Bing, Li, Xiuhe, Guan, Hongyan, Wu, Jianxin, and Zhang, Ting
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- 2024
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30. Reallocating just 10 min to moderate-to-vigorous physical activity from other components of 24-hour movement behaviors improves cardiovascular health in adults
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Ji, Yemeng, Atakan, Muhammed M., Yan, Xu, Wu, Jinlong, Kuang, Jujiao, and Peng, Li
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- 2024
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31. Compositional PLS biplot based on pivoting balances: an application to explore the association between 24-h movement behaviours and adiposity.
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Štefelová, Nikola, Palarea-Albaladejo, Javier, Hron, Karel, Gába, Aleš, and Dygrýn, Jan
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OBESITY , *PREVENTION of obesity , *LEAST squares , *PARTIAL least squares regression , *DATA reduction , *PHYSICAL activity , *UNIFIED modeling language - Abstract
Movement behaviour data are compositional in nature, therefore the logratio methodology has been demonstrated appropriate for their statistical analysis. Compositional data can be mapped into the ordinary real space through new sets of variables (orthonormal logratio coordinates) representing balances between the original compositional parts. Geometric rotation between orthonormal logratio coordinates systems can be used to extract relevant information from any of them. We exploit this idea to introduce the concept of pivoting balances, which facilitates the construction and use of interpretable balances according to the purpose of the data analysis. Moreover, graphical representation through ternary diagrams has been ordinarily used to explore time-use compositions consisting of, or being amalgamated into, three parts. Data dimension reduction techniques can however serve well for visualisation and facilitate understanding in the case of larger compositions. We here develop suitable pivoting balance coordinates that in combination with an adapted formulation of compositional partial least squares regression biplots enable meaningful visualisation of more complex time-use patterns and their relationships with an outcome variable. The use and features of the proposed method are illustrated in a study examining the association between movement behaviours and adiposity from a sample of Czech school-aged girls. The results suggest that an adequate strategy for obesity prevention in this group would be to focus on achieving a positive balance of vigorous physical activity in combination with sleep against the other daily behaviours. [ABSTRACT FROM AUTHOR] more...
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- 2024
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32. Kent feature embedding for classification of compositional data with zeros.
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Lu, Shan, Wang, Wenjing, and Guan, Rong
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Compositional data have posed challenges to current classification methods owing to the non-negative and unit-sum constraints, especially when a certain of the components are zeros. In this paper, we develop an effective classification method for multivariate compositional data with certain of the components equal to zero. Specifically, a Kent feature embedding technique is first proposed to transform compositional data and improve data quality. We then use support vector machine as the state-of-the-art machine learning model to build the classifier. The proposed method is proved to be effective through numerical simulations. Results on multiple real datasets, including species classification, day-night image classification and household’s consumption pattern recognition, further verify that the proposed method can achieve good classification performance and outperform the other competitors. This method would help to broaden the practical usage of compositional data with zeros in the task of classification. [ABSTRACT FROM AUTHOR] more...
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- 2024
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33. Dietary Amino Acid Composition and Glycemic Biomarkers in Japanese Adolescents.
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Okuda, Masayuki and Sasaki, Satoshi
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Protein intake reportedly increases the risk of diabetes; however, the results have been inconsistent. Diabetes in adulthood may be attributed to early life dietary amino acid composition. This study aimed to investigate the association between amino acid composition and glycemic biomarkers in adolescents. Dietary intake was assessed using a food frequency questionnaire, and fasting glucose and insulin levels were measured in 1238 eighth graders. The homeostatic model assessment (HOMA) indices (insulin resistance and β-cell function) were calculated. Anthropometrics were measured and other covariates were obtained from a questionnaire. Amino acid composition was isometric log transformed according to the compositional data analysis, which was used as explanatory variables in multivariate linear regression models for glucose, insulin, and HOMA indices. Only the association between glucose and leucine was significant. In replacement of other amino acids with leucine, an increase of 0.1% of total amino acids correlated with a lower glucose level (−1.02 mg/dL). One-to-one substitution of leucine for isoleucine or methionine decreased glucose (−2.98 and −2.28 mg/dL, respectively). Associations with other biomarkers were not observed. In conclusion, compositional data analysis of amino acids revealed an association only with glucose in adolescents; however, the results of this study should be verified in other populations. [ABSTRACT FROM AUTHOR] more...
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- 2024
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34. Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium.
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Blodgett, Joanna M, Ahmadi, Matthew N, Atkin, Andrew J, Chastin, Sebastien, Chan, Hsiu-Wen, Suorsa, Kristin, Bakker, Esmee A, Hettiarcachchi, Pasan, Johansson, Peter J, Sherar, Lauren B, Rangul, Vegar, Pulsford, Richard M, Mishra, Gita, Eijsvogels, Thijs M H, Stenholm, Sari, Hughes, Alun D, Teixeira-Pinto, Armando M, Ekelund, Ulf, Lee, I-Min, and Holtermann, Andreas more...
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PHYSICAL activity ,SEDENTARY behavior ,WAIST-hip ratio ,DISEASE risk factors ,HDL cholesterol ,SLEEP - Abstract
Background and Aims Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers. Methods Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours. Results The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with −0.63 (95% confidence interval −0.48, −0.79), −0.43 (−0.25, −0.59), −0.40 (−0.25, −0.56), and −0.15 (0.05, −0.34) kg/m
2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day. Conclusions Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity. [ABSTRACT FROM AUTHOR] more...- Published
- 2024
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35. Utilizing co-abundances of antimicrobial resistance genes to identify potential co-selection in the resistome
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Hannah-Marie Martiny, Patrick Munk, Christian Brinch, Frank M. Aarestrup, M. Luz Calle, and Thomas N. Petersen
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metagenomics ,correlation ,network analysis ,compositional data analysis ,co-abundances ,antimicrobial resistance ,Microbiology ,QR1-502 - Abstract
ABSTRACT The rapid spread of antimicrobial resistance (AMR) is a threat to global health, and the nature of co-occurring antimicrobial resistance genes (ARGs) may cause collateral AMR effects once antimicrobial agents are used. Therefore, it is essential to identify which pairs of ARGs co-occur. Given the wealth of next-generation sequencing data available in public repositories, we have investigated the correlation between ARG abundances in a collection of 214,095 metagenomic data sets. Using more than 6.76∙108 read fragments aligned to acquired ARGs to infer pairwise correlation coefficients, we found that more ARGs correlated with each other in human and animal sampling origins than in soil and water environments. Furthermore, we argued that the correlations could serve as risk profiles of resistance co-occurring to critically important antimicrobials (CIAs). Using these profiles, we found evidence of several ARGs conferring resistance for CIAs being co-abundant, such as tetracycline ARGs correlating with most other forms of resistance. In conclusion, this study highlights the important ARG players indirectly involved in shaping the resistomes of various environments that can serve as monitoring targets in AMR surveillance programs.IMPORTANCEUnderstanding the collateral effects happening in a resistome can reveal previously unknown links between antimicrobial resistance genes (ARGs). Through the analysis of pairwise ARG abundances in 214K metagenomic samples, we observed that the co-abundance is highly dependent on the environmental context and argue that these correlations can be used to show the risk of co-selection occurring in different settings. more...
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- 2024
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36. GeoCoDA: Recognizing and validating structural processes in geochemical data. A workflow on compositional data analysis in lithogeochemistry
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Eric Grunsky, Michael Greenacre, and Bruce Kjarsgaard
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Geochemistry ,Logratio analysis ,Classification ,Lithologic prediction ,Compositional data analysis ,Machine learning ,Geography. Anthropology. Recreation ,Geology ,QE1-996.5 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Geochemical data are compositional in nature and are subject to the problems typically associated with data that are restricted to the real non-negative number space with constant-sum constraint, that is, the simplex. Geochemistry can be considered a proxy for mineralogy, comprised of atomically ordered structures that define the placement and abundance of elements in the mineral lattice structure. Based on the innovative contributions of John Aitchison, who introduced the logratio transformation into compositional data analysis, this contribution provides a systematic workflow for assessing geochemical data in a simple and efficient way, such that significant geochemical (mineralogical) processes can be recognized and validated. This workflow, called GeoCoDA and presented here in the form of a tutorial, enables the recognition of processes from which models can be constructed based on the associations of elements that reflect mineralogy. Both the original compositional values and their transformation to logratios are considered. These models can reflect rock-forming processes, metamorphism, alteration and ore mineralization. Moreover, machine learning methods, both unsupervised and supervised, applied to an optimized set of subcompositions of the data, provide a systematic, accurate, efficient and defensible approach to geochemical data analysis. The workflow is illustrated on lithogeochemical data from exploration of the Star kimberlite, consisting of a series of eruptions with five recognized phases. more...
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- 2024
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37. Compositionally Aware Phylogenetic Beta-Diversity Measures Better Resolve Microbiomes Associated with Phenotype
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Martino, Cameron, McDonald, Daniel, Cantrell, Kalen, Dilmore, Amanda Hazel, Vázquez-Baeza, Yoshiki, Shenhav, Liat, Shaffer, Justin P, Rahman, Gibraan, Armstrong, George, Allaband, Celeste, Song, Jin, and Knight, Rob more...
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Information and Computing Sciences ,Computer Vision and Multimedia Computation ,Microbiome ,Humans ,Phylogeny ,Microbiota ,Sequence Analysis ,DNA ,Research Design ,Phenotype ,beta-diversity ,phylogenetics ,compositional data analysis - Abstract
Microbiome data have several specific characteristics (sparsity and compositionality) that introduce challenges in data analysis. The integration of prior information regarding the data structure, such as phylogenetic structure and repeated-measure study designs, into analysis, is an effective approach for revealing robust patterns in microbiome data. Past methods have addressed some but not all of these challenges and features: for example, robust principal-component analysis (RPCA) addresses sparsity and compositionality; compositional tensor factorization (CTF) addresses sparsity, compositionality, and repeated measure study designs; and UniFrac incorporates phylogenetic information. Here we introduce a strategy of incorporating phylogenetic information into RPCA and CTF. The resulting methods, phylo-RPCA, and phylo-CTF, provide substantial improvements over state-of-the-art methods in terms of discriminatory power of underlying clustering ranging from the mode of delivery to adult human lifestyle. We demonstrate quantitatively that the addition of phylogenetic information improves effect size and classification accuracy in both data-driven simulated data and real microbiome data. IMPORTANCE Microbiome data analysis can be difficult because of particular data features, some unavoidable and some due to technical limitations of DNA sequencing instruments. The first step in many analyses that ultimately reveals patterns of similarities and differences among sets of samples (e.g., separating samples from sick and healthy people or samples from seawater versus soil) is calculating the difference between each pair of samples. We introduce two new methods to calculate these differences that combine features of past methods, specifically being able to take into account the principles that most types of microbes are not in most samples (sparsity), that abundances are relative rather than absolute (compositionality), and that all microbes have a shared evolutionary history (phylogeny). We show using simulated and real data that our new methods provide improved classification accuracy of ordinal sample clusters and increased effect size between sample groups on beta-diversity distances. more...
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- 2022
38. Comparative Analysis of Airborne Bacterial and Fungal Communities in South-Eastern Italy and in Albania Using the Compositional Analysis of 16S and ITS rRNA Gene Sequencing Datasets
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Salvatore Romano, Lekë Pepkolaj, Mattia Fragola, Dalila Peccarrisi, Jostina Dhimitri, Alessandro Buccolieri, Adelfia Talà, Pietro Alifano, Gianluca Quarta, and Lucio Calcagnile
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airborne microbiome ,bioaerosol ,metagenomics ,16S rRNA sequencing ,ITS rRNA sequencing ,compositional data analysis ,Meteorology. Climatology ,QC851-999 - Abstract
This study investigates airborne bacterial and fungal communities in south-eastern Italy and Albania using advanced DNA-based techniques and compositional data analysis (CoDa). We assess the significance of airborne microbial communities, detailing our methodologies for site selection, sample collection, DNA extraction, and data analysis. Our results reveal distinct differences in microbial composition between the two regions, driven by local environmental factors. Specifically, Albanian samples showed higher abundances of bacterial species such as Rubellimicrobium roseum and Sphingomonas cynarae, while Italian samples were characterized by a prevalence of Truepera radiovictrix and Rubrobacter radiotolerans. In terms of fungi, Albanian sites exhibited greater abundance of Mycosphaerella tassiana, Aureobasidium pullulans, and Ascochyta herbicola. Aitchison distance-based dendrograms and principal component analysis (PCA) biplots, utilizing singular value decomposition, clearly delineated a geographical separation of microbial communities, underscoring the impact of regional atmospheric conditions on microbial composition. In the discussion, we interpret these findings in the context of regional environmental factors, highlighting their implications for understanding regional differences in airborne microbial communities. The conclusion emphasizes the effectiveness of advanced DNA techniques and CoDa in environmental microbiology, offering insights into how local environmental conditions shape microbial communities and suggesting directions for future research and public health considerations. more...
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- 2024
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39. The association between reallocations of time and health using compositional data analysis: a systematic scoping review with an interactive data exploration interface
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Aaron Miatke, Tim Olds, Carol Maher, Francois Fraysse, Maddison L Mellow, Ashleigh E Smith, Zeljko Pedisic, Jozo Grgic, and Dorothea Dumuid
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Physical activity ,Moderate-to-vigorous physical activity ,Sedentary behaviour ,Sleep ,Compositional data analysis ,Nutritional diseases. Deficiency diseases ,RC620-627 ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background How time is allocated influences health. However, any increase in time allocated to one behaviour must be offset by a decrease in others. Recently, studies have used compositional data analysis (CoDA) to estimate the associations with health when reallocating time between different behaviours. The aim of this scoping review was to provide an overview of studies that have used CoDA to model how reallocating time between different time-use components is associated with health. Methods A systematic search of four electronic databases (MEDLINE, Embase, Scopus, SPORTDiscus) was conducted in October 2022. Studies were eligible if they used CoDA to examine the associations of time reallocations and health. Reallocations were considered between movement behaviours (sedentary behaviour (SB), light physical activity (LPA), moderate-to-vigorous physical activity (MVPA)) or various activities of daily living (screen time, work, household chores etc.). The review considered all populations, including clinical populations, as well as all health-related outcomes. Results One hundred and three studies were included. Adiposity was the most commonly studied health outcome (n = 41). Most studies (n = 75) reported reallocations amongst daily sleep, SB, LPA and MVPA. While other studies reported reallocations amongst sub-compositions of these (work MVPA vs. leisure MVPA), activity types determined by recall (screen time, household chores, passive transport etc.) or bouted behaviours (short vs. long bouts of SB). In general, when considering cross-sectional results, reallocating time to MVPA from any behaviour(s) was favourably associated with health and reallocating time away from MVPA to any behaviour(s) was unfavourably associated with health. Some beneficial associations were seen when reallocating time from SB to both LPA and sleep; however, the strength of the association was much lower than for any reallocations involving MVPA. However, there were many null findings. Notably, most of the longitudinal studies found no associations between reallocations of time and health. Some evidence also suggested the context of behaviours was important, with reallocations of leisure time toward MVPA having a stronger favourable association for health than reallocating work time towards MVPA. Conclusions Evidence suggests that reallocating time towards MVPA from any behaviour(s) has the strongest favourable association with health, and reallocating time away from MVPA toward any behaviour(s) has the strongest unfavourable association with health. Future studies should use longitudinal and experimental study designs, and for a wider range of outcomes. more...
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- 2023
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40. COVID-19 PANDEMİ SÜRECİNDE E-TİCARET VE DİJİTAL PAZARLAMANIN TÜRKİYE'DEKİ ÖNEMİ.
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DURUCASU, Remzi Reha
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INTERNET marketing , *DATA analysis , *ELECTRONIC commerce - Abstract
Digital marketing, which emerged with the digital transformation, offers indispensable channels for businesses. Today, people spend a lot of time online with internet-based devices such as smartphones and tablets. This has created the ability for businesses to interact with consumers regardless of time and place. Covid-19, whose impact is still ongoing, has brought about major changes in the way society lives. It is possible to claim that businesses that manage digital marketing and related electronic commerce activities correctly have managed to survive and even grow in this process. In this study, in the light of the data obtained from the Turkish Statistical Institute such as the purpose of individuals using the internet and the rate of online shopping of individuals, descriptive statistics were firstly included. Then, compositional data analysis was conducted and as a result of the analysis, the importance of digital marketing for existing and new businesses was revealed according to the technological habits of the society. [ABSTRACT FROM AUTHOR] more...
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- 2024
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41. CoDA-Based Geo-Electrochemical Prospecting Prediction of Uranium Orebodies in Changjiang Area, Guangdong Province, China.
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Tang, Rui, Sun, Li, Ouyang, Fei, Xiao, Keyan, Li, Cheng, Kong, Yunhui, Xie, Miao, Wu, Yixiao, and Gao, Yaxin
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URANIUM mining , *MINES & mineral resources , *PROSPECTING , *PRINCIPAL components analysis , *GAUSSIAN distribution , *FORECASTING , *PROVINCES , *URANIUM - Abstract
In order to achieve a breakthrough in the exploration of uranium orebodies in the Changjiang area of Guangdong province in China, the geo-electrochemical exploration method is used for mineral resource prediction. The logarithmically and isometric log-ratio (ilr) transformations are applied to the geo-electrochemical data in this study area to extract geochemical anomalies. The relationship between element associations and mineralization is revealed through descriptive statistical analysis and further biplot analysis. Then, the energy spectrum density–area fractal model (S-A model) is used to identify geochemical backgrounds and anomalies. The results show that: (i) the logarithmically and ilr-transformed data are more uniform, and they more or less obey the rules of normal distribution; (ii) the biplot shows that the ilr-transformed data eliminates the closure effect, and the robust principal component analysis (RPCA) has a better indicative significance for element associations—PC1 reveals the mineralization element association dominated by U and the multiple periods of hydrothermal activity; (iii) the S-A method could extract the local anomalies from different geochemical backgrounds, which indicates mineralization is more reliable. Finally, four favorable prospecting targets are delineated based on the geological and geochemical indicators. [ABSTRACT FROM AUTHOR] more...
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- 2024
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42. Advancing forensic research: An examination of compositional data analysis with an application on petrol fraud detection.
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Templ, M. and Gonzalez-Rodriguez, J.
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FRAUD investigation ,GASOLINE ,PRINCIPAL components analysis ,RATIO analysis ,VECTOR spaces - Abstract
• Classical forensic compound analysis can lead to erroneous conclusions. • Compositional approaches yield unbiased and better interpretable results. • Compositional methods boost performance, reducing misclassification rates. • For the analysis of petrol compounds, the log-ratio approach should be used. In recent years, numerous studies have examined the chemical compounds of petrol and petrol data for forensic research. Standard quantitative methods often assume that the variables or compounds do not have compositional constraints or are not part of a constrained whole, operating within an Euclidean vector space. However, chemical compounds are typically part of a whole, and the appropriate vector space for their analysis is the simplex. Biased and arbitrary results result when statistical analysis are applied on such data without proper pre-processing of such data. Compositional analysis of data has not yet been considered in forensic science. Therefore, we compare classical statistical analysis as applied in forensic research and the new proposed paradigm of compositional data analysis (CoDa). It is demonstrated how such analysis improves the analysis in petrol and forensic science. Our study shows how principal component analysis (PCA) and classification results are affected by the preprocessing steps performed on the raw data. Our results indicate that results from a log ratio analysis provides a better separation between subgroups of the data and leads to an easier interpretation of the results. In addition, with a compositional analysis a higher classification accuracy is obtained. Even a non-linear classification method - in our case a random forest - was shown to perform poorly when applied without using compositional methods. Moreover, normalization of samples due to laboratory/unit-of-measurement effects is no longer necessary, since the composition of an observation is in compositional thinking equivalent to a multiple of it, because the used (log) ratios on raw and log ratio transformed data are equal. Petrol data from different petrol stations in Brazil are used for the demonstration. This data is highly susceptible to counterfeit petrol. Forensic analysis of its chemical elements requires non-biased statistical analysis designed for compositional data to detect fraud. Based on these results, we recommend the use of compositional data methods for gasoline and petrol chemical element analysis and gasoline product characterization, authentication and fraud detection in forensic sciences. [ABSTRACT FROM AUTHOR] more...
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- 2024
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43. Working at the office or from home during the COVID-19 pandemic: a cross-sectional study of temporal patterns of sitting and non-sitting among normal-weight and overweight Brazilian office workers.
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Brusaca, Luiz Augusto, Hallman, David M., Januario, Leticia Bergamin, Gupta, Nidhi, Oliveira, Ana Beatriz, and Mathiassen, Svend Erik
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COVID-19 pandemic , *WHITE collar workers , *OBESITY , *CROSS-sectional method , *BODY mass index - Abstract
Background: This study documents and compares temporal patterns of physical behaviours, assessed using accelerometry, on working and non-working days among normal-weight (body mass index [BMI] < 25 kg/m2) and overweight (BMI ≥ 25 kg/m2) office workers who were either working exclusively at the office (WAO) or exclusively from home (WFH) during the COVID-19 pandemic. Methods: In this cross-sectional study, behaviours were measured over 7 days using a thigh-worn accelerometer in 43 workers WAO (21 normal-weight and 22 overweight) and 73 workers WFH (33 normal-weight and 40 overweight). 24-h behaviours were completely described in terms of sitting in short (≤ 5 min), moderate (> 5 and ≤ 30 min) and long bouts (> 30 min), non-sitting in short (≤ 5 min) and long bouts (> 5 min), and time-in-bed. These behaviour compositions were transformed into five isometric log-ratios (ilr) coordinates according to compositional data analysis procedures. Differences between workplace (WAO vs. WFH) and BMI groups (normal-weight vs. overweight) were tested using ANCOVA with adjustment for age and gender. Results: Compared to workers WAO, workers WFH spent more time-in-bed relative to time awake during working days, more time sitting relative to non-sitting, less time in short bouts of sitting relative to moderate and long bouts, less time in moderate bouts of sitting relative to long bouts, and more time non-sitting in short bouts relative to long bouts. Effect sizes [ η p 2 ] were between 0.05 and 0.21 and p-values between < 0.001 and 0.04. Irrespective of workplace, overweight workers spent less time sitting in short relative to moderate and long bouts ( η p 2 = 0.06, p = 0.01) than normal-weight workers, while differences in the other ilr coordinates were insignificant. During non-working days, behaviours did not differ significantly by workplace, while overweight workers spent more time sitting relative to non-sitting ( η p 2 = 0.10, p < 0.001), less time sitting in short relative to moderate and long bouts ( η p 2 = 0.13, p < 0.001), and less time sitting in moderate relative to long bouts ( η p 2 = 0.04, p = 0.03) than normal-weight workers. We found no interactions between workplace and BMI. Conclusions: Our findings suggest that WFH and being overweight predispose to more time sitting and less temporal variation in behaviours, thus reinforcing that these workers could likely benefit from interventions to reduce prolonged sitting time and increase variation. [ABSTRACT FROM AUTHOR] more...
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- 2023
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44. Improving geological logging of drill holes using geochemical data and data analytics for mineral exploration in the Gawler Ranges, South Australia.
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Hill, E. J., Fabris, A., Uvarova, Y., and Tiddy, C.
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PROSPECTING , *GEOLOGICAL modeling , *DATA logging , *BIG data , *STATISTICAL learning , *ANALYTICAL geochemistry , *MACHINE learning - Abstract
Geochemical data are frequently collected from mineral exploration drill-hole samples to more accurately define and characterise the geological units intersected by the drill hole. However, large multi-element data sets are slow and challenging to interpret without using some form of automated analysis, such as mathematical, statistical or machine learning techniques. Automated analysis techniques also have the advantage in that they are repeatable and can provide consistent results, even for very large data sets. In this paper, an automated litho-geochemical interpretation workflow is demonstrated, which includes data exploration and data preparation using appropriate compositional data-analysis techniques. Multiscale analysis using a modified wavelet tessellation has been applied to the data to provide coherent geological domains. Unsupervised machine learning (clustering) has been used to provide a first-pass classification. The results are compared with the detailed geologist's logs. The comparison shows how the integration of automated analysis of geochemical data can be used to enhance traditional geological logging and demonstrates the identification of new geological units from the automated litho-geochemical logging that were not apparent from visual logging but are geochemically distinct. [ABSTRACT FROM AUTHOR] more...
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- 2023
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45. Analysing time-use composition as dependent variables in physical activity and sedentary behaviour research: different compositional data analysis approaches.
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von Rosen, Philip
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PHYSICAL activity , *DEPENDENT variables , *DATA analysis , *SEDENTARY behavior , *RESEARCH personnel , *CODEPENDENCY - Abstract
Recently, there has been a paradigm shift from considering physical activity and sedentary behaviour as "independent" risk factors of health to acknowledging their co-dependency and compositional nature. The focus is now on how these behaviours relate to each other rather than viewing them in isolation. Compositional data analysis (CoDA) is a methodology that has been developed specifically for compositional data and the number of publications using CoDA in physical activity and sedentary behaviour research has increased rapidly in the past years. Yet, only a small proportion of the published studies in physical activity and sedentary behaviour research have investigated the time-use composition as dependent variables. This could be related to challenges regarding the interpretation of the results and the lack of guidelines for deciding which statistical approach to use. Therefore, in this paper, four different approaches for analysing the time-use composition as dependent variables are presented and discussed. This paper advocates that the aim of research should guide how the dependent variable is defined and which data analysis approach is selected, and it encourages researchers to consider analysing time-use components as dependent variables in physical activity and sedentary behaviour research. [ABSTRACT FROM AUTHOR] more...
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- 2023
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46. Analysis of Psychological Well-Being from a Compositional Data Analysis Perspective: A New Approach.
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Cortés-Rodríguez, María, Galindo-Villardón, Purificación, Sánchez-Barba, Mercedes, Jarauta-Bragulat, Eusebi, and Urchaga-Litago, José David
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SELF-acceptance , *PSYCHOLOGICAL well-being , *PSYCHOMETRICS , *PSYCHOLOGICAL tests , *DATA analysis , *WELL-being - Abstract
Well-being is a widely studied construct in psychology. In 1989, Carol Ryff proposed the "Scale of Psychological Well-Being (SPWB)", which has been validated in multiple languages. The instrument assesses six dimensions of psychological well-being: Self-acceptance, Positive Relationships with Others, Autonomy, Environmental Mastery, Purpose in Life, and Personal Growth. In this article, we propose to enrich the traditional approach of directly interpreting the raw scores in each dimension by incorporating Compositional Data Analysis. This new approach aims to identify "what proportion" of each dimension constitutes well-being, which will allow us to analyze the interactions between the different dimensions of well-being and balance among them. To achieve this, we introduce two position ratios (PR1 and PR2) and a general adjustment indicator called the General Indicator of Subjective Psychological Well-Being (GISPW), which characterizes individuals in a compositional manner, providing a fresh perspective in the interpretation of psychological test results, specifically those related to PWB. The proposal is illustrated with three cases taken from a study involving 628 university students who completed the psychological well-being scale questionnaire. The results show that the GISPW, PR1, and PR2 obtained offer relevant information about the overall balance of each case in the different dimensions. [ABSTRACT FROM AUTHOR] more...
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- 2023
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47. Hybrid office work in women and men: do directly measured physical behaviors differ between days working from home and days working at the office?
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Wahlström, Viktoria, Januario, Leticia Bergamin, Mathiassen, Svend Erik, Heiden, Marina, and Hallman, David M
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WORK environment , *SEDENTARY lifestyles , *ACCELEROMETERS , *SEX distribution , *PHYSICAL activity , *COMPARATIVE studies , *HEALTH behavior , *RESEARCH funding , *DECISION making , *TELECOMMUTING , *MANAGEMENT , *COVID-19 pandemic - Abstract
Objective We investigated and compared temporal sitting patterns among male and female hybrid office workers when working at the office (WAO), working from home (WFH), and for non-working days (NWD). Methods We analyzed data collected in 2020 among 165 hybrid office workers, carrying thigh-worn accelerometers for 938 days in total. Day type (WAO, WFH, or NWD) and time in bed were identified using diaries. Time awake was exhaustively classified as non-sitting time and time sitting in short, moderate, and long bouts. Effects of day type and gender on the 24-h compositions of physical behaviors were analyzed using multilevel linear mixed models. Results During workdays (both WAO and WFH), workers spent less time in bed and more time sitting, particularly in moderate and long bouts, than during NWD. Time in bed was longer when working from home than when working at the office, and more of the awake time was spent sitting. Differences between WAO and WFH in ratios between short, moderate, and long bouts of sitting were small and inconsistent. Men spent more time sitting than women, and more time in moderate and long sitting bouts relative to short bouts. Conclusions When working from home, hybrid office workers sat more during their hours awake compared to when working at the office. Sitting time was larger during working days than during non-working days and was higher in men than in women. These results may contribute to support organizational policies for hybrid work. [ABSTRACT FROM AUTHOR] more...
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- 2023
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48. Analysis and Interpretation of Sedentary Behaviour Data
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Zhu, Weimo, Ahrens, Wolfgang, Series Editor, Pigeot, Iris, Series Editor, Leitzmann, Michael F., editor, Jochem, Carmen, editor, and Schmid, Daniela, editor
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- 2023
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49. Bioinformatics and Biostatistical Models for Analysis and Prognosis of Antimicrobial Resistance
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Zhelyazkova, Maya, Yordanova, Roumyana, Mihaylov, Iliyan, Tsonev, Stefan, Vassilev, Dimitar, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Sotirov, Sotir, editor, Pencheva, Tania, editor, Atanassov, Krassimir T., editor, Sotirova, Evdokia, editor, and Ribagin, Simeon, editor more...
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- 2023
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50. Where You Sleep Tells What You Care About
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Marine-Roig, Estela, Daries, Natalia, Martin-Fuentes, Eva, Ferrer-Rosell, Berta, Ferrer-Rosell, Berta, editor, Massimo, David, editor, and Berezina, Katerina, editor
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- 2023
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