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  1. Osterrieder A, Cuman G, Pan-Ngum W, Cheah PK, Cheah PK, Peerawaranun P, et al.
    BMJ Open, 2021 Jul 20;11(7):e046863.
    PMID: 34285007 DOI: 10.1136/bmjopen-2020-046863
    OBJECTIVES: To understand the impact of COVID-19 and public health measures on different social groups, we conducted a mixed-methods study in five countries ('SEBCOV-social, ethical and behavioural aspects of COVID-19'). Here, we report the results of the online survey.

    STUDY DESIGN AND STATISTICAL ANALYSIS: Overall, 5058 respondents from Thailand, Malaysia, the UK, Italy and Slovenia completed the self-administered survey between May and June 2020. Poststratification weighting was applied, and associations between categorical variables assessed. Frequency counts and percentages were used to summarise categorical data. Associations between categorical variables were assessed using Pearson's χ2 test. Data were analysed in Stata 15.0 RESULTS: Among the five countries, Thai respondents reported having been most, and Slovenian respondents least, affected economically. The following factors were associated with greater negative economic impacts: being 18-24 years or 65 years or older; lower education levels; larger households; having children under 18 in the household and and having flexible/no income. Regarding social impact, respondents expressed most concern about their social life, physical health, mental health and well-being.There were large differences between countries in terms of voluntary behavioural change, and in compliance and agreement with COVID-19 restrictions. Overall, self-reported compliance was higher among respondents who self-reported a high understanding of COVID-19. UK respondents felt able to cope the longest and Thai respondents the shortest with only going out for essential needs or work. Many respondents reported seeing news perceived to be fake, the proportion varying between countries, with education level and self-reported levels of understanding of COVID-19.

    CONCLUSIONS: Our data showed that COVID-19 and public health measures have uneven economic and social impacts on people from different countries and social groups. Understanding the factors associated with these impacts can help to inform future public health interventions and mitigate their negative consequences.

    TRIAL REGISTRATION NUMBER: TCTR20200401002.

    Matched MeSH terms: Slovenia
  2. Reidpath DD, Ling ML, Wellington E, Al-Sadat N, Yasin S
    Nicotine Tob Res, 2013 Mar;15(3):729-33.
    PMID: 22990215 DOI: 10.1093/ntr/nts177
    INTRODUCTION: It is held that younger smoking initiates are more likely to become regular smokers. The definitions of smoking initiation (a puff, part of a cigarette, a whole cigarette) are inconsistent and raise questions about the robustness of the view. We sought to re-examine the relationship using adolescent smoking data from 3 European countries.
    METHODS: A stratified secondary, logistic regression analysis of Global Youth Tobacco Survey data was conducted using a design-based analysis. Subgroup analyses were conducted of 13- to 15-year olds from Latvia (high smoking prevalence), Slovenia (moderate prevalence), and Montenegro (low prevalence) who had initiated smoking. The outcome was current smoking--smoking everyday for the past 30 days, or smoking 10 or more days in the past 30 days. Smoking initiation was operationalized as a single puff of a cigarette, and age of smoking initiation was a derived continuous measure.
    RESULTS: In Latvia, there was a significant association between age of smoking initiation and current smoking for males (p < .05) and females (p < .001) when smoking was operationalized as smoking every day. It was only significant in female adolescents (p < .001) for smoking 10 or more days. In Slovenia and Montenegro, there was no significant relationship between age of smoking initiation and current smoking for either males or females.
    CONCLUSIONS: The evidence about the relationship between age of smoking initiation and current smoking is not clear. Explanations for the findings may relate to a lack of power, the specificity of the measure, or problems with the theory.
    Matched MeSH terms: Slovenia/epidemiology
  3. Pin Viso N, Redondo E, Díaz Carrasco JM, Redondo L, Sabio Y Garcia J, Fernández Miyakawa M, et al.
    PLoS One, 2021;16(1):e0244724.
    PMID: 33406150 DOI: 10.1371/journal.pone.0244724
    The gastrointestinal tract of chickens harbors a highly diverse microbiota contributing not only to nutrition, but also to the physiological development of the gastrointestinal tract. Microbiota composition depends on many factors such as the portion of the intestine as well as the diet, age, genotype, or geographical origin of birds. The aim of the present study was to demonstrate the influence of the geographical location over the cecal microbiota from broilers. We used metabarcoding sequencing datasets of the 16S rRNA gene publicly available to compare the composition of the Argentine microbiota against the microbiota of broilers from another seven countries (Germany, Australia, Croatia, Slovenia, United States of America, Hungary, and Malaysia). Geographical location played a dominant role in shaping chicken gut microbiota (Adonis R2 = 0.6325, P = 0.001; Mantel statistic r = 0.1524, P = 4e-04) over any other evaluated factor. The geographical origin particularly affected the relative abundance of the families Bacteroidaceae, Lactobacillaceae, Lachnospiraceae, Ruminococcaceae, and Clostridiaceae. Because of the evident divergence of microbiota among countries we coined the term "local microbiota" as convergent feature that conflates non-genetic factors, in the perspective of human-environmental geography. Local microbiota should be taken into consideration as a native overall threshold value for further appraisals when testing the production performance and performing correlation analysis of gut microbiota modulation against different kind of diet and/or management approaches. In this regard, we described the Argentine poultry cecal microbiota by means of samples both from experimental trials and commercial farms. Likewise, we were able to identify a core microbiota composed of 65 operational taxonomic units assigned to seven phyla and 38 families, with the four most abundant taxa belonging to Bacteroides genus, Rikenellaceae family, Clostridiales order, and Ruminococcaceae family.
    Matched MeSH terms: Slovenia
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