Background. One of the stakeholders in tackling the rise and health consequences of overweight and obesity is the general practice physician (GP). GPs are in a good position to inform and give nutrition guidance to overweight patients. Objective. Assessment of working mechanism of determinants of the nutrition guidance practice: noticing patients’ overweight and guidance of treatment by GPs [linear analysis of structural relations (LISREL) path model] in a longitudinal study. Methods. This longitudinal study measured data in 1992, 1997 and 2007. The 1992 LISREL path model (Hiddink GJ, Hautvast J, vanWoerkumCMJ, Fieren CJ, vantHofMA. Nutrition guidance by primary-care physicians: LISREL analysis improves understanding. Prev Med 1997; 26: 29–36.) demonstrated that ‘noticing patients’ overweight and guidance of treatment’ was directly and indirectly influenced by predisposing factors, driving forces and perceived barriers. This article defines and discusses the path analysis of the 2007 data (compared with 1997). Results. This analysis shows both similarity and differences inworking mechanism of determinants of noticing patients’ overweight and guidance of treatment between 1997 and 2007. The backbone of themechanism with four predisposing factors is the similarity. The number of driving forces and of paths through intermediary factors to the dependent variable constitutes the difference. Conclusions. The backbone of the working mechanism of determinants of the nutrition guidance practice: noticing patients’ overweight and guidance of treatment by GPs was similar in 2007 and 1997. The influence of GPs task perception on noticing patients’ overweight and guidance of treatment considerably increased in 2007 compared to 1997. The longitudinal character of this article gives a strong practice-based evidence for weight management by GPs.
Two key air pollutants that affect asthma are ozone and particle pollution. Studies show a direct relationship between the number of deaths and hospitalizations for asthma and increases of particulate matter in the air, including dust, soot, fly ash, diesel exhaust particles, smoke, and sulfate aerosols. Cars are found to be a primary contributor to this problem. However, patient awareness of the link is limited. This chapter begins with a general discussion of vehicular dependency or ‘car culture’, and then focuses on the discussion of the effects of air pollution on asthma in the Netherlands. I argue that international organizations and patient organizations have not tended to put pressure on air-control, pollution-control or environmental standards agencies, or the actual polluters. While changes in air quality and the release of greenhouse gases are tied to practices like the massive corporate support for the ongoing use of motor vehicles and the increased prominence of ‘car culture’ globally, patient organizations seem more focused on treating the symptoms rather than addressing the ultimate causes of the disease. Consequently, I argue that to fully address the issue of asthma the international health organizations as well as national health ministries, patient organizations, and the general public must recognize the direct link between vehicular dependency and asthma. The chapter concludes with a recommendation for raising environmental health awareness by explicitly linking the vehicular dependency to the state of poor respiratory health. Strategic policy in the Netherlands then should explicitly link the present pattern of auto mobility to public health. https://onlinelibrary.wiley.com/doi/book/10.1002/9781118786949 LinkedIn: https://www.linkedin.com/in/helenkopnina/
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Digitalization is the core component of future development in the 4.0 industrial era. It represents a powerful mechanism for enhancing the sustainable competitiveness of economies worldwide. Diverse triggering effects shape future digitalization trends. Thus, the main research goal in this study is to use sustainable competitiveness pillars (such as social, economic, environmental and energy) to evaluate international digitalization development. The proposed empirical model generates comprehensive knowledge of the sustainable competitiveness-digitalization nexus. For that purpose, a nonlinear regression has been applied on gathered annual data that consist of 33 European countries, ranging from 2010 to 2016. The dataset has been deployed using Bernoulli’s binominal distribution to derive training and testing samples and the entire analysis has been adjusted in that context. The empirical findings of artificial neural networks (ANN) suggest strong effects of the economic and energy use indicators on the digitalization progress. Nonlinear regression and ANN model summary report valuable results with a high degree of coefficient of determination (R2>0.9 for all models). Research findings state that the digitalization process is multidimensional and cannot be evaluated as an isolated phenomenon without incorporating other relevant factors that emerge in the environment. Indicators report the consumption of electrical energy in industry and households and GDP per capita to achieve the strongest effect.
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