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10.1016/j.clnesp.2021.01.046 http://scihub22266oqcxt.onion/10.1016/j.clnesp.2021.01.046 33745572!7871880!33745572     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Clin+Nutr+ESPEN 2021 ; 42 (ä): 158-165 Nephropedia Template TP {{tp|p=33745572|t=2021. Trajectories of eating behavior during COVID-19 lockdown: Longitudinal analyses of 22,374 adults |pdf=|usr=}}{{33745572}} gab.com Text Trajectories of eating behavior during COVID-19 lockdown: Longitudinal analyses of 22,374 adults JO: Clin Nutr ESPEN http://www.kidney.de/pget.php?&tw=1&pmid=33745572 #FOAvip BACKGROUND & AIMS: The COVID-19 pandemic has led to the implementation of stay-at-home and lockdown measures. It is currently unknown if the experience of lockdown leads to long term changes in individual's eating behaviors. The objectives of this study were: i) to derive longitudinal trajectories of change in eating during UK lockdown, and ii) to identify risk factors associated with eating behavior trajectories. METHOD: Data from 22,374 UK adults from the UCL COVID-19 Social study (a panel study collecting weekly data during the pandemic) were analyzed from 28th March to 29th May 2020. Latent Class Growth Analysis was used to derive trajectories of change in eating. These were then associated with prior socio-economic, health-related and psychological factors using multinomial regression models. RESULTS: Analyses suggested five trajectories, with the majority (64%) showing no change in eating. In contrast, one trajectory was marked by persistently eating more, whereas another by persistently eating less. Overall, participants with greater depressive symptoms were more likely to report any change in eating. Loneliness was linked to persistently eating more (OR = 1.07), whereas being single or divorced, as well as stressful life events, were associated with consistently eating less (OR = 1.69). Overall, higher education status was linked to lower odds of changing eating behavior (OR = 0.54-0.77). Secondary exploratory analyses suggest that participants self-reported to have overweight were more commonly categorised into the group consistently eating more, whereas participants with underweigh persistently ate less. CONCLUSION: In this study, we found that one third of the sample report changes in quantities eaten throughout the first UK lockdown period. Findings highlight the importance of adjusting public health programs to support eating behaviors in future lockdowns both in this and potential future pandemics. This is particularly important as part of on-going preventive efforts to prevent nutrition-related chronic diseases. Twit Text FOAVip Trajectories of eating behavior during COVID-19 lockdown: Longitudinal analyses of 22,374 adults ????Clin Nutr ESPEN http://www.kidney.de/pget.php?&tw=1&pmid=33745572 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33745572 #FOAvip English Wikipedia <ref>{{Cite pmid|33745572}}</ref> Trajectories of eating behavior during COVID-19 lockdown: Longitudinal analyses of 22,374 adults #MMPMID33745572 Herle M; Smith AD; Bu F; Steptoe A; Fancourt D Clin Nutr ESPEN 2021[Apr]; 42 (ä): 158-165 PMID33745572show ga BACKGROUND & AIMS: The COVID-19 pandemic has led to the implementation of stay-at-home and lockdown measures. It is currently unknown if the experience of lockdown leads to long term changes in individual's eating behaviors. The objectives of this study were: i) to derive longitudinal trajectories of change in eating during UK lockdown, and ii) to identify risk factors associated with eating behavior trajectories. METHOD: Data from 22,374 UK adults from the UCL COVID-19 Social study (a panel study collecting weekly data during the pandemic) were analyzed from 28th March to 29th May 2020. Latent Class Growth Analysis was used to derive trajectories of change in eating. These were then associated with prior socio-economic, health-related and psychological factors using multinomial regression models. RESULTS: Analyses suggested five trajectories, with the majority (64%) showing no change in eating. In contrast, one trajectory was marked by persistently eating more, whereas another by persistently eating less. Overall, participants with greater depressive symptoms were more likely to report any change in eating. Loneliness was linked to persistently eating more (OR = 1.07), whereas being single or divorced, as well as stressful life events, were associated with consistently eating less (OR = 1.69). Overall, higher education status was linked to lower odds of changing eating behavior (OR = 0.54-0.77). Secondary exploratory analyses suggest that participants self-reported to have overweight were more commonly categorised into the group consistently eating more, whereas participants with underweigh persistently ate less. CONCLUSION: In this study, we found that one third of the sample report changes in quantities eaten throughout the first UK lockdown period. Findings highlight the importance of adjusting public health programs to support eating behaviors in future lockdowns both in this and potential future pandemics. This is particularly important as part of on-going preventive efforts to prevent nutrition-related chronic diseases. |*COVID-19[MESH] |Adolescent[MESH] |Adult[MESH] |Body Weight[MESH] |Eating[MESH] |Feeding Behavior/*psychology[MESH] |Female[MESH] |Humans[MESH] |Life Style[MESH] |Male[MESH] |Mental Health[MESH] |Middle Aged[MESH] |Overweight/prevention & control[MESH] |Pandemics[MESH] |Quarantine[MESH] |Risk Factors[MESH] |SARS-CoV-2[MESH] |Socioeconomic Factors[MESH] |United Kingdom[MESH]Trajectories of eating behavior during COVID-19 lockdown: Longitudinal(epmc).pdf DeepDyve Pubget Overpricing