16 research outputs found

    ‘Fish out of water’: a cross-sectional study on the interaction between social and neighbourhood effects on weight management behaviours

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    Objective: To analyse whether an individual’s neighbourhood influences the uptake of weight management strategies and whether there is an interaction between individual socio-economic status and neighbourhood deprivation. Methodology: Data were collected from the Yorkshire Health Study (2010–2012) for 27 806 individuals on the use of the following weight management strategies: ‘slimming clubs’, ‘healthy eating’, ‘increasing exercise’ and ‘controlling portion size’. A multi-level logistic regression was fit to analyse the use of these strategies, controlling for age, sex, body mass index, education, neighbourhood deprivation and neighbourhood population turnover (a proxy for neighbourhood social capital). A cross-level interaction term was included for education and neighbourhood deprivation. Lower Super Output Area was used as the geographical scale for the areal unit of analysis. Results: Significant neighbourhood effects were observed for use of ‘slimming clubs’, ‘healthy eating’ and ‘increasing exercise’ as weight management strategies, independent of individual- and area-level covariates. A significant interaction between education and neighbourhood deprivation was observed across all strategies, suggesting that as an area becomes more deprived, individuals of the lowest education are more likely not to use any strategy compared with those of the highest education. Conclusions: Neighbourhoods modify/amplify individual disadvantage and social inequalities, with individuals of low education disproportionally affected by deprivation. It is important to include neighbourhood-based explanations in the development of community-based policy interventions to help tackle obesit

    Is Social Network Diversity Associated with Tooth Loss among Older Japanese Adults?

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    Background: We sought to examine social network diversity as a potential determinant of oral health, considering size and contact frequency of the social network and oral health behaviors. Methods: Our cross-sectional study was based on data from the 2010 Japan Gerontological Evaluation Study. Data from 19,756 community-dwelling individuals aged 65 years or older were analyzed. We inquired about diversity of friendships based on seven types of friends. Ordered logistic regression models were developed to determine the association between the diversity of social networks and number of teeth (categorized as ≥20, 10–19, 1–9, and 0). Results: Of the participants, 54.1% were women (mean age, 73.9 years; standard deviation, 6.2). The proportion of respondents with ≥20 teeth was 34.1%. After adjusting for age, sex, socioeconomic status (income, education, and occupation), marital status, health status (diabetes and mental health), and size and contact frequency of the social network, an increase in the diversity of social networks was significantly associated with having more teeth (odds ratio = 1.08; 95% confidence interval, 1.04–1.11). Even adjusted for oral health behaviors (smoking, curative/preventive dental care access, use of dental floss/fluoride toothpaste), significant association was still observed (odds ratio = 1.05 (95% confidence interval, 1.02–1.08)). Conclusion: Social connectedness among people from diverse backgrounds may increase information channels and promote the diffusion of oral health behaviors and prevent tooth loss
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