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- Halkjaer, J., et al.
(författare)
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Intake of total, animal and plant proteins, and their food sources in 10 countries in the European Prospective Investigation into Cancer and Nutrition
- 2009
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Ingår i: European Journal of Clinical Nutrition. - : Springer Science and Business Media LLC. - 1476-5640 .- 0954-3007. ; 63:4s, s. 16-36
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To describe dietary protein intakes and their food sources among 27 redefined centres in 10 countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC). Methods: Between 1995 and 2000, 36 034 persons, aged between 35 and 74 years, were administered a standardized 24-h dietary recall (24-HDR) using a computerized interview software programme (EPIC-SOFT). Intakes (g/day) of total, animal and plant proteins were estimated using the standardized EPIC Nutrient Database (ENDB). Mean intakes were adjusted for age, and weighted by season and day of recall. Results: Mean total and animal protein intakes were highest in the Spanish centres among men, and in the Spanish and French centres among women; the lowest mean intakes were observed in the UK health-conscious group, in Greek men and women, and in women in Potsdam. Intake of plant protein was highest among the UK health-conscious group, followed by some of the Italian centres and Murcia, whereas Sweden and Potsdam had the lowest intake. Cereals contributed to the highest proportion of plant protein in all centres. The combined intake of legumes, vegetables and fruit contributed to a greater proportion of plant protein in the southern than in the northern centres. Total meat intake (with some heterogeneity across subtypes of meat) was, with few exceptions, the most important contributor to animal protein in all centres, followed by dairy and fish products. Conclusions: This study shows that intake of protein, especially of animal origin, differs across the 10 European countries, and also shows some differences in food sources of protein across Europe. European Journal of Clinical Nutrition (2009) 63, S16-S36; doi: 10.1038/ejcn.2009.73
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| 2. |
- Menvielle, Gwenn, et al.
(författare)
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The role of smoking and diet in explaining educational inequalities in lung cancer incidence.
- 2009
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 1460-2105 .- 0027-8874. ; 101:5, s. 321-330
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Studies in many countries have reported higher lung cancer incidence and mortality in individuals with lower socioeconomic status. METHODS: To investigate the role of smoking in these inequalities, we used data from 391,251 participants in the European Prospective Investigation into Cancer and Nutrition study, a cohort of individuals in 10 European countries. We collected information on smoking (history and quantity), fruit and vegetable consumption, and education through questionnaires at study entry and gathered data on lung cancer incidence for a mean of 8.4 years. Socioeconomic status was defined as the highest attained level of education, and participants were grouped by sex and region of residence (Northern Europe, Germany, or Southern Europe). Relative indices of inequality (RIIs) of lung cancer risk unadjusted and adjusted for smoking were estimated using Cox regression models. Additional analyses were performed by histological type. RESULTS: During the study period, 939 men and 692 women developed lung cancer. Inequalities in lung cancer risk (RII(men) = 3.62, 95% confidence interval [CI] = 2.77 to 4.73, 117 vs 52 per 100,000 person-years for lowest vs highest education level; RII(women) = 2.39, 95% CI = 1.77 to 3.21, 46 vs 25 per 100,000 person-years) decreased after adjustment for smoking but remained statistically significant (RII(men) = 2.29, 95% CI = 1.75 to 3.01; RII(women) = 1.59, 95% CI = 1.18 to 2.13). Large RIIs were observed among men and women in Northern European countries and among men in Germany, but inequalities in lung cancer risk were reverse (RIIs < 1) among women in Southern European countries. Inequalities differed by histological type. Adjustment for smoking reduced inequalities similarly for all histological types and among men and women in all regions. In all analysis, further adjustment for fruit and vegetable consumption did not change the estimates. CONCLUSION: Self-reported smoking consistently explains approximately 50% of the inequalities in lung cancer risk due to differences in education.
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| 3. |
- Kosti, M. V., et al.
(författare)
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Archetypal personalities of software engineers and their work preferences: a new perspective for empirical studies
- 2016
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Ingår i: Empirical Software Engineering. - : Springer Science and Business Media LLC. - 1573-7616 .- 1382-3256. ; 21:4, s. 1509-1532
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Tidskriftsartikel (refereegranskat)abstract
- As the area of Software Engineering (SE) matures the role of human factors in software development is commonly recognized as important. Increasingly we see empirical studies that investigate the connection between, for example, personalities and preferences, attitudes or performances of software engineers. Statistical analysis holds a key role by providing the means for uncovering associations between various facets of human factors and behavioral effects on projects and outcomes. Traditional statistical techniques tend to explore and interpret the multidimensional personality and behavioral data from an "average-point" perspective, targeting central trends. This paper introduces a methodology with statistical tools that can provide a new and different perspective for this type of SE data. It seeks the boundaries of a psychometric dataset and discovers reference or "benchmark" personalities, the archetypal personalities. Then, the method examines the placement of all individuals in the dataset in relation to the archetypes. Furthermore, the SE preference characteristics, or generally, any other types of behavioral SE data, are analyzed with respect to the archetypes. As a case to exemplify the methodology we analyze personality and project preference data from 276 master level SE students and compare to previous "average-point" statistical analysis of the same data. We also discuss how Archetypal Analysis, the heart of the proposed methodology, combined with multi-correspondence analysis might be of general use in empirical SE.
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| 4. |
- Kosti, M. V., et al.
(författare)
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Personality, emotional intelligence and work preferences in software engineering: An empirical study
- 2014
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Ingår i: Information and Software Technology. - : Elsevier BV. - 0950-5849 .- 1873-6025. ; 56:8, s. 973-990
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Tidskriftsartikel (refereegranskat)abstract
- Context: There is an increasing awareness among Software Engineering (SE) researchers and practitioners that more focus is needed on understanding the engineers developing software. Previous studies show significant associations between the personalities of software engineers and their work preferences. Objective: Various studies on personality in SE have found large, small or no effects and there is no consensus on the importance of psychometric measurements in SE. There is also a lack of studies employing other psychometric instruments or using larger datasets. We aim to evaluate our results in a larger sample, with software engineers in an earlier state of their career, using advanced statistics. Method: An operational replication study where extensive psychometric data from 279 master level students have been collected in a SE program at a Swedish University. Personality data based on the Five-Factor Model, Trait Emotional Intelligence Questionnaire and Self-compassion have been collected. Statistical analysis investigated associations between psychometrics and work preferences and the results were compared to our previous findings from 47 SE professionals. Results: Analysis confirms existence of two main clusters of software engineers; one with more "intense" personalities than the other. This corroborates our earlier results on SE professionals. The student data also show similar associations between personalities and work preferences. However, for other associations there are differences due to the different population of subjects. We also found connections between the emotional intelligence and work preferences, while no associations were found for self-compassion. Conclusion: The associations can help managers to predict and adapt projects and tasks to available staff. The results also show that the Emotional Intelligence instrument can be predictive. The research methods and analytical tools we employ can detect subtle associations and reflect differences between different groups and populations and thus can be important tools for future research as well as industrial practice.
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