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10.1017/S1368980021000355 http://scihub22266oqcxt.onion/10.1017/S1368980021000355 33500018!8207551!33500018     free     free     free Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Public+Health+Nutr 2021 ; 24 (12): 3929-3936 Nephropedia Template TP {{tp|p=33500018|t=2021. Predictors of households at risk for food insecurity in the United States during the COVID-19 pandemic |pdf=|usr=}}{{33500018}} gab.com Text Predictors of households at risk for food insecurity in the United States during the COVID-19 pandemic JO: Public Health Nutr http://www.kidney.de/pget.php?&tw=1&pmid=33500018 #FOAvip OBJECTIVE: To examine associations between sociodemographic and mental health characteristics with household risk for food insecurity during the COVID-19 outbreak. DESIGN: Cross-sectional online survey analysed using univariable tests and a multivariable logistic regression model. SETTING: The United States during the week of 30 March 2020. PARTICIPANTS: A convenience sample of 1965 American adults using Amazon's Mechanical Turk platform. Participants reporting household food insecurity prior to the pandemic were excluded from analyses. RESULTS: One thousand two hundred and fifty participants reported household food security before the COVID-19 outbreak. Among this subset, 41 % were identified as at risk for food insecurity after COVID-19, 55 % were women and 73 % were white. On a multivariable analysis, race, income, relationship status, living situation, anxiety and depression were significantly associated with an incident risk for food insecurity. Black, Asian and Hispanic/Latino respondents, respondents with an annual income <$100 000 and those living with children or others were significantly more likely to be newly at risk for food insecurity. Individuals at risk for food insecurity were 2.60 (95 % CI 1.91, 3.55) times more likely to screen positively for anxiety and 1.71 (95 % CI 1.21, 2.42) times more likely to screen positively for depression. CONCLUSIONS: An increased risk for food insecurity during the COVID-19 pandemic is common, and certain populations are particularly vulnerable. There are strong associations between being at risk for food insecurity and anxiety/depression. Interventions to increase access to healthful foods, especially among minority and low-income individuals, and ease the socioemotional effects of the outbreak are crucial to relieving the economic stress of this pandemic. Twit Text FOAVip Predictors of households at risk for food insecurity in the United States during the COVID-19 pandemic ????Public Health Nutr http://www.kidney.de/pget.php?&tw=1&pmid=33500018 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33500018 #FOAvip English Wikipedia <ref>{{Cite pmid|33500018}}</ref> Predictors of households at risk for food insecurity in the United States during the COVID-19 pandemic #MMPMID33500018 Lauren BN; Silver ER; Faye AS; Rogers AM; Woo-Baidal JA; Ozanne EM; Hur C Public Health Nutr 2021[Aug]; 24 (12): 3929-3936 PMID33500018show ga OBJECTIVE: To examine associations between sociodemographic and mental health characteristics with household risk for food insecurity during the COVID-19 outbreak. DESIGN: Cross-sectional online survey analysed using univariable tests and a multivariable logistic regression model. SETTING: The United States during the week of 30 March 2020. PARTICIPANTS: A convenience sample of 1965 American adults using Amazon's Mechanical Turk platform. Participants reporting household food insecurity prior to the pandemic were excluded from analyses. RESULTS: One thousand two hundred and fifty participants reported household food security before the COVID-19 outbreak. Among this subset, 41 % were identified as at risk for food insecurity after COVID-19, 55 % were women and 73 % were white. On a multivariable analysis, race, income, relationship status, living situation, anxiety and depression were significantly associated with an incident risk for food insecurity. Black, Asian and Hispanic/Latino respondents, respondents with an annual income <$100 000 and those living with children or others were significantly more likely to be newly at risk for food insecurity. Individuals at risk for food insecurity were 2.60 (95 % CI 1.91, 3.55) times more likely to screen positively for anxiety and 1.71 (95 % CI 1.21, 2.42) times more likely to screen positively for depression. CONCLUSIONS: An increased risk for food insecurity during the COVID-19 pandemic is common, and certain populations are particularly vulnerable. There are strong associations between being at risk for food insecurity and anxiety/depression. Interventions to increase access to healthful foods, especially among minority and low-income individuals, and ease the socioemotional effects of the outbreak are crucial to relieving the economic stress of this pandemic. |*COVID-19/epidemiology[MESH] |*Food Insecurity[MESH] |*Pandemics[MESH] |Adolescent[MESH] |Adult[MESH] |Aged[MESH] |Cross-Sectional Studies[MESH] |Female[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Risk Factors[MESH] |Socioeconomic Factors[MESH] |United States/epidemiology[MESH]Predictors of households at risk for food insecurity in the United Sta(epmc).pdf DeepDyve Pubget Overpricing