Guillermo Soriano Tarin, Juan C Francisco-García, José M Alonso-Bosque, Marisa Valle-Robles, Alba Bernabeu-Atanasio
{"title":"[Concordance between the Work Capability Index and the Years of Surviving Disability Estimated using the PoRT-9LSQ methodology].","authors":"Guillermo Soriano Tarin, Juan C Francisco-García, José M Alonso-Bosque, Marisa Valle-Robles, Alba Bernabeu-Atanasio","doi":"10.12961/aprl.2023.26.04.02","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To analyze the association between lifestyles and health risk factors that can lead to prematurely leaving work, with the expected Years Lived with Disability (AYLD) in a working population, and to calculate the correlation between the Work Ability Index (WAI) and the Work Ability Score (WAS), and then both of these with the AYLD and its economic cost.</p><p><strong>Methods: </strong>A cross-sectional study in a sample of workers who underwent a health examination. The information was collected using the ICL and WAS questionnaires, applying the PoRT-9LSQ methodology. Linear regression and analysis of variance (ANOVA) were used to analyze the association between the risk factors and AYLD. The correlation between WAI and WAS was analyzed using the intraclass correlation coefficient (ICC), and then between each of these the AYLD and its economic cost using adjusted linear regression. Results: A total of 590 workers were included. Factors that most influenced the average AYLD were a sedentary lifestyle, poor diet, and overweight/obesity, with statistically significant differences according to sex, shift, and occupation (p<0.05). An ICC of 93.0% was found between ICL and WAS, a good/excellent rating. The adjusted linear regression between ICL and ADSE was 7.982-0.136xICL (p<0.05), and was similar for WAS. Conclusions: The WAI is useful for predicting AYLD in the working population. This can facilitate decisionmaking by health personnel to identify vulnerable people, encouraging changes in lifestyle and self-care.</p>","PeriodicalId":101300,"journal":{"name":"Archivos de prevencion de riesgos laborales","volume":"26 4","pages":"259-274"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archivos de prevencion de riesgos laborales","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12961/aprl.2023.26.04.02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: To analyze the association between lifestyles and health risk factors that can lead to prematurely leaving work, with the expected Years Lived with Disability (AYLD) in a working population, and to calculate the correlation between the Work Ability Index (WAI) and the Work Ability Score (WAS), and then both of these with the AYLD and its economic cost.
Methods: A cross-sectional study in a sample of workers who underwent a health examination. The information was collected using the ICL and WAS questionnaires, applying the PoRT-9LSQ methodology. Linear regression and analysis of variance (ANOVA) were used to analyze the association between the risk factors and AYLD. The correlation between WAI and WAS was analyzed using the intraclass correlation coefficient (ICC), and then between each of these the AYLD and its economic cost using adjusted linear regression. Results: A total of 590 workers were included. Factors that most influenced the average AYLD were a sedentary lifestyle, poor diet, and overweight/obesity, with statistically significant differences according to sex, shift, and occupation (p<0.05). An ICC of 93.0% was found between ICL and WAS, a good/excellent rating. The adjusted linear regression between ICL and ADSE was 7.982-0.136xICL (p<0.05), and was similar for WAS. Conclusions: The WAI is useful for predicting AYLD in the working population. This can facilitate decisionmaking by health personnel to identify vulnerable people, encouraging changes in lifestyle and self-care.