Changes in ultra-processed food consumption during the first Italian lockdown following the COVID-19 pandemic and major correlates: results from two population-based cohorts

新冠疫情后意大利首次封城期间超加工食品消费的变化及其主要相关因素:来自两个基于人群队列的研究结果

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Abstract

OBJECTIVE: To evaluate changes in ultra-processed food (UPF) intake and its major correlates during the first Italian lockdown (9 March-3 May 2020). DESIGN: Retrospective observational study. SETTING: Italy. PARTICIPANTS: We analysed 2992 subjects (mean age 57·9 ± 15·3 years, 40·4 % men). Individual participant data were pooled from two retrospective cohorts: (1) The Moli-LOCK cohort consists of 1501 adults, a portion of the larger Moli-sani study (n 24 325; 2005-2010) who were administered a phone-based questionnaire to assess lifestyles and psychological factors during confinement and (2) the Analysis of Long Term Risk of Covid-19 Emergency is a web-based survey of 1491 individuals distributed throughout Italy who self-responded to the same questionnaire by using Google forms.UPF was defined according to NOVA classification based on degree of food processing. An UPF score was created by assigning 1 point to increased consumption, -1 to decreased and 0 point for unchanged intakes of nineteen food items, with higher values indicating an increase in UPF during confinement. RESULTS: Overall, 37·5 % of the population reported some increase in UPF (UPF score ≥1). Adults were more likely to decrease UPF (multivariable regression coefficient β = -1·94; 95 % CI -2·72, -1·17 for individuals aged >75 years as compared with 18-39 years) as did individuals from southern Italian regions as compared with Northern inhabitants (β = -1·32; 95 % CI -1·80, -0·84), while UPF lowering associated with increased exercise (β = -0·90; 95 % CI -1·46, -0·35) and weight loss (β = -1·05; 95 % CI -1·51, -0·59) during confinement. CONCLUSIONS: During the first Italian lockdown, about 40 % of our population switched to unfavourable eating as reflected by increased UPF intake and this may have long-term effects for health.

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