Matías Tomás Salvà

Background: Diabesity is a growing problem internationally. Taking into account the importance of physical activity and diet in its prevention and treatment, the objective of this study was to delve into the impact of healthy habits on diabesity. Methods: A descriptive, cross-sectional study was carried out in 386,924 Spanish adult workers. Obesity was determined according to eleven different formulas. Life habits were also valued; sociodemographic variables; and educational level; as well as analytical and clinical variables such as blood pressure and blood glucose levels. The association between the different variables was performed using the chi-square and the Student’s t-tests when the samples were independent. A multivariate analysis was performed using the multinomial logistic regression test by calculating the odds ratio and a 95% confidence interval. The Hosmer–Lemeshow goodness-of-fit test was also performed. Results: The overall prevalence of diabesity ranged between 0.3% (95% CI 0.3–0.4) when obesity was assessed according to the abdominal volume index and 8.3% (95% CI 8.2–8.4) when evaluated according to the CUN-BAE (Clínica Universitaria de Navarra Body Adiposity Estimator) formula. The prevalence of diabesity was also higher in workers with a non-heart-healthy diet and in those who did not exercise regularly. Conclusions: The most disadvantaged socioeconomic classes are those with the highest prevalence of diabesity. It is important to prioritise prevention in populations and communities with the most unfavourable social and environmental conditions to reduce the burden of diabesity.

Background: Dealing with suffering, grief, and death on a daily basis, together with the particular working conditions, may produce high levels of burnout in nurses, and hinder their well-being. The purpose of this research is to study the effect of self-care and self-compassion on nurses’ professional quality of life and well-being. Methods: The research had a cross-sectional design, used correlational methodology and a structural equation model was hypothesized. Along the study, 210 nurses from the Healthcare Public System of the Balearic Islands, participated. The study took place from June to September 2018. Results: The hypothesized model showed an overall adequate fit. Practice environment predicted both self-care and self-compassion, whereas nursing stress did not. Self-care and self-compassion predicted nurses’ professional quality of life, whereas the practice environment and nursing stress were not predictors. Finally, professional quality of life showed a positive relationship with life satisfaction. Conclusions: The study presents a comprehensive structural equation model in which self-care and self-compassion are the best predictors of nurses’ professional quality of life. A direct relation of professional quality of life and nurses’ well-being has also been found, while controlling for the effects of nurses’ practice environment and stress.

Early detection of people with undiagnosed type 2 diabetes (T2D) is an important public health concern. Several predictive equations for T2D have been proposed but most of them have not been externally validated and their performance could be compromised when clinical data is used. Clinical practice guidelines increasingly incorporate T2D risk prediction models as they support clinical decision making. The aims of this study were to systematically review prediction scores for T2D and to analyze the agreement between these risk scores in a large cross-sectional study of white western European workers. A systematic review of the PubMed, CINAHL, and EMBASE databases and a cross-sectional study in 59,042 Spanish workers was performed. Agreement between scores classifying participants as high risk was evaluated using the kappa statistic. The systematic review of 26 predictive models highlights a great heterogeneity in the risk predictors; there is a poor level of reporting, and most of them have not been externally validated. Regarding the agreement between risk scores, the DETECT-2 risk score scale classified 14.1% of subjects as high-risk, FINDRISC score 20.8%, Cambridge score 19.8%, the AUSDRISK score 26.4%, the EGAD study 30.3%, the Hisayama study 30.9%, the ARIC score 6.3%, and the ITD score 3.1%. The lowest agreement was observed between the ITD and the NUDS study derived score (κ = 0.067). Differences in diabetes incidence, prevalence, and weight of risk factors seem to account for the agreement differences between scores. A better agreement between the multi-ethnic derivate score (DETECT-2) and European derivate scores was observed. Risk models should be designed using more easily identifiable and reproducible health data in clinical practice.