An adequate forecasting model of mortality that allows an analysis of different population changes is a topic of interest for countries in demographic transition. Phenomena such as the reduction of mortality, ageing, and the increase in life expectancy are extremely useful in the planning of public policies that seek to promote the economic and social development of countries. To our knowledge, this paper is one of the first to evaluate the performance of mortality forecasting models applied to abridged life tables. Select a mortality model that best describes and forecasts the characteristics of mortality in Colombia when only abridged life tables are available. We used Colombian abridged life tables for the period 1973–2005 with data from the Latin American Human Mortality Database. Different mortality models to deal with modeling and forecasting probability of death are presented in this study. For the comparison of mortality models, two criteria were analyzed: graphical residuals analysis and the hold-out method to evaluate the predictive performance of the models, applying different goodness of fit measures. Only three models did not have convergence problems: Lee-Carter (LC), Lee-Carter with two terms (LC2), and Age-Period-Cohort (APC) models. All models fit better for women, the improvement of LC2 on LC is mostly for central ages for men, and the APC model’s fit is worse than the other two. The analysis of the standardized deviance residuals allows us to deduce that the models that reasonably fit the Colombian mortality data are LC and LC2. The major residuals correspond to children’s ages and later ages for both sexes. The LC and LC2 models present better goodness of fit, identifying the principal characteristics of mortality for Colombia. Mortality forecasting from abridged life tables by sex has clear added value for studying differences between developing countries and convergence/divergence of demographic changes.

The mortality structure of a population usually reflects the economic and social development of the country. The purpose of this study was to identify moments in time and age intervals at which the observed probability of death is substantially different from the pattern of mortality for a studied period. Therefore, a mortality model was fitted to decompose the historical pattern of mortality. The model residuals were monitored by the $T^2$ multivariate control chart to detect substantial changes in mortality that were not identified by the model. The abridged life tables for Colombia in the period 1973–2005 were used as a case study. The Lee–Carter model collects information regarding violence in Colombia. Therefore, the years identified as out-of-control in the charts are associated with very early or quite advanced ages of death and are inversely related to the violence that did not claim as many victims at those ages. The mortality changes identified in the control charts pertain to changes in the population’s health conditions or new causes of death such as COVID-19 in the coming years. The proposed methodology is generalizable to other countries, especially developing countries.

El presente estudio tuvo como objetivo el diseño, construcción y validación de un instrumento de medición de los factores de riesgo intralaboral en docentes universitarios. Se partió del reconocimiento de la importancia de abordar los factores de riesgo psicosociales intralaborales en el ámbito académico. Este enfoque no solo contribuye a la vigilancia de la salud individual y colectiva de los colaboradores, previniendo accidentes laborales, sino que también promueve su bienestar mental y emocional, fortaleciendo así el sentido de pertenencia y la cultura organizacional. Para el diseño y construcción del instrumento se tuvieron en cuenta las condiciones psicosociales intralaborales en cuatro dominios de análisis: demandas de trabajo, control sobre el trabajo, liderazgo y relaciones sociales en el trabajo y recompensa. El cuestionario fue validado mediante tres métodos estadísticos: el coeficiente Alpha de Cronbach, matrices de correlaciones y análisis factorial para comprobar las dimensiones y dominios. Es de resaltar que de manera general se obtuvo un valor de 0,92 en el Alpha de Cronbach, lo que indicó un alto nivel de precisión en la información recolectada y garantizó la calidad de las preguntas formuladas.