Introduction: Regression modeling is a statistical method commonly used in health research, especially by observational studies. Objective: The objectives of this paper were to 1) determine the frequency of reporting of regression modeling in original biomedical and public health articles that were published in Biomédica between 2000 and 2017; 2) describe the parameters used in the statistical models, and 3) describe the quality of the information reported by the studies to explain the statistical analyses. Materials and methods: We conducted a critical assessment review of all original articles published in Biomédica between 2000 and 2017 that used regression models for the statistical analysis of the studies main objectives. We generated a 20-item checklist based on four good practice guidelines for the presentation of statistical methods. Results: Most of the studies were observational studies related to public health sciences (65.7%). Less than half (37.2%) of them reported using a combination of conceptual frameworks and statistical criteria for the selection of variables to be included in the regression model. Less than one quarter (22.1%) reported the verification of the assumptions of the model. The most frequently used uncertainty measure was the p-value (73.5%). Conclusion: There are significant limitations in the quality of the reports of statistical regression models, which reviewers and readers need in order to correctly assess and interpret the statistical models. The results, herein, are provided as an invitation to researchers, reviewers, and editors of biomedical journals to develop, promote, and control an appropriate culture for statistical analysis and reporting in Colombia.
Introduction. Suicide has shown an international and national trend to increase, mainly in young people, together with seasonal behavior associated with high temperatures. Although Chihuahua saw the highest number of suicides and suicide attempts in 2016, there are no studies documenting their seasonal and trend behavior. Objective. This study sought to analyze the trend and seasonality of completed suicides in the state of Chihuahua from 2008 to 2018. Method. The number of deaths from intentionally self-inflicted injuries was obtained from INEGI. The absolute suicide rate was estimated, and a time series model applied to identify its trend and seasonality. In addition, environmental temperature was used as a predictor variable for the number of suicides through a Poisson model. Results. A trend was found in the completed suicide rate from 2008 to 2018 in men and women, both separately and together (stationary R2 .73, .66 and .69, respectively), together with seasonality in both sexes (p < .002), with the highest figures being recorded in June and July. An increase of 1,028 suicides was found for every 1°C rise in temperature. In the 10-24 and 25-34 age groups, a linear increase in the suicide rate was observed during the period studied (R² > .7, p = .001). Discussion and conclusion. Between 2008 and 2018, the suicide rate increased in the state of Chihuahua, mainly among those aged between 10 and 34. Moreover, suicide rates tend to increase during the months of June and July because of temperature.
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