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Abstract Background Due to the relatively low numbers of households in high income countries experiencing food insecurity most studies conflate the levels of severity, which masks between- and within-country differences. This study aims to describe the characteristics of individuals living in high income countries who were moderately or severely food insecure and investigates temporal trends in prevalence. It assesses these characteristics in comparison to those who were food secure. Methods This is a secondary analysis of data collected by the FAO Voices of the Hungry between 2014–2018. The data were collected during the annual Gallup World Polls of nationally representative samples using the Food Insecurity Experience Scale. Data from 34 highly developed, wealthy countries were analysed. The age, gender, income, education, area of residence and household structure of individuals experiencing moderate/severe food insecurity (FI), and severe FI, were compared using ANOVA, Welch’s F, Pearson’s Chi-square, and Linear-by-Linear Association, dependent on the variable of interest. Hierarchical cluster analysis was used to group countries according to their prevalence of moderate/severe FI, and severe FI. Results Overall, 6.5% of the weighted sample were moderately/severely food insecure (M-SFI), while 1.6% were severely food insecure. M-SFI individuals were present in all 34 countries, in all years and across all education levels and income quintiles. The proportion of individuals experiencing moderate/severe FI varied between years and countries. Fifteen countries showed a significant downward temporal trend in prevalence of moderate/severe FI (p

Background: Due to the relatively low numbers of households in high income countries experiencing food insecurity most studies conflate the levels of severity, which masks between- and within-country differences. This study aims to describe the characteristics of individuals living in high income countries who were moderately or severely food insecure and investigates temporal trends in prevalence. It assesses these characteristics in comparison to those who were food secure. Methods: This is a secondary analysis of data collected by the FAO Voices of the Hungry between 2014–2018. The data were collected during the annual Gallup World Polls of nationally representative samples using the Food Insecurity Experience Scale. Data from 34 highly developed, wealthy countries were analysed. The age, gender, income, education, area of residence and household structure of individuals experiencing moderate/severe food insecurity (FI), and severe FI, were compared using ANOVA, Welch's F, Pearson's Chi-square, and Linear-by-Linear Association, dependent on the variable of interest. Hierarchical cluster analysis was used to group countries according to their prevalence of moderate/severe FI, and severe FI. Results: Overall, 6.5% of the weighted sample were moderately/severely food insecure (M-SFI), while 1.6% were severely food insecure. M-SFI individuals were present in all 34 countries, in all years and across all education levels and income quintiles. The proportion of individuals experiencing moderate/severe FI varied between years and countries. Fifteen countries showed a significant downward temporal trend in prevalence of moderate/severe FI (p < 0.001), while three countries demonstrated an increasing temporal trend driven by increasing prevalence in those aged 65 years or less (p < 0.001). Comparing individuals experiencing moderate versus severe FI showed over-representation of males, single adult households and lower household income in the severe FI group. Conclusions: Individuals across all income, education and age categories living in high income countries are experiencing moderate/severe food insecurity, but with higher prevalence in those experiencing more disadvantage. Over the study period some countries experienced escalating while others demonstrated decreasing moderate/severe FI trends. This comparison of countries with similar economic and human development indices highlights an opportunity to investigate subtle variations in social, economic and education policy that could have profound impacts on food insecurity. [ABSTRACT FROM AUTHOR]

Background Excess intake of sugar sweetened beverages (SSBs) has been shown to result in weight gain. To address the growing epidemic of obesity, one option is to combine programmes that target individual behaviour change with a fiscal policy such as excise tax on SSBs. This study evaluates the literature on SSB taxes or price increases, and their potential impact on consumption levels, obesity, overweight and body mass index (BMI). The possibility of switching to alternative drinks is also considered. Methods The following databases were used: Pubmed/Medline, The Cochrane Database of Systematic Reviews, Google Scholar, Econlit, National Bureau of Economics Research (NBER), Research Papers in Economics (RePEc). Articles published between January 2000 and January 2013, which reported changes in diet or BMI, overweight and/or obesity due to a tax on, or price change of, SSBs were included. Results Nine articles met the criteria for the meta-analysis. Six were from the USA and one each from Mexico, Brazil and France.,. All showed negative own-price elasticity, which means that higher prices are associated with a lower demand for SSBs. Pooled own price-elasticity was -1.299 (95%CI: -1.089 - -1.509). Four articles reported cross-price elasticities, three from the USA and one from Mexico; higher prices for SSBs were associated with an increased demand for alternative beverages such as fruit juice (0.388, 95%CI: 0.009 - 0.767) and milk (0.129, 95%CI: -0.085 - 0.342), and a reduced demand for diet drinks (-0.423, 95%CI: -0.628 - -1.219). Six articles from the USA showed that a higher price could also lead to a decrease in BMI, and decrease the prevalence of overweight and obesity. Conclusions Taxing SSBs may reduce obesity. Future research should estimate price elasticities in low- and middle-income countries and identify potential health gains and the wider impact on jobs, monetary savings to the health sector, implementation costs and government revenue. Context-specific cost-effectiveness studies would allow policy makers to weigh these factors. [ABSTRACT FROM AUTHOR]