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oai:figshare.com:article/34072151 2026-10-05T17:33:15Z category_272 category_39 category_45 category_734 category_64 category_106 category_135 portal_5 item_type_3 month_year_10_2026

<p>Multivariable logistic regression model for factors associated with microbiological non-compliance in ready-to-eat foods (n = 1,846). Regression coefficients (B), standard errors, Wald statistics, p-values, odds ratios [OR], and 95% confidence intervals (95% CI) are presented. The model was adjusted for temporal variables (year 2020), territorial variables (rural/dispersed municipalities and Villavicencio), type of establishment (food service, food operator, and institutional), and food matrix type (raw or highly handled foods, liquid preparations, and dairy/sweet products), using thermally processed foods as the reference category. Odds ratios >1 indicate higher odds of microbiological non-compliance, whereas odds ratios <1 indicate lower odds of microbiological non-compliance. Statistical significance was defined as p < 0.05.</p> L. Marcela Montilla Rodríguez (25316918) Jorge Alejandro Obando Bastidas (25316921) Hugo Andrés Rodríguez Fajardo (25316924) Astrid Magaly Mora López (25316927) Shirley Viviana Tique Aragón (25316930) Dora Patricia Rozo Cruz (25316933) Edgar Calderón Vega (25316936) Norma Cristina Pavas Escobar (25111413) Laura Nathalia Obando Vargas (25316939) Jean Paul Farfán (25316942) Marina Sthella Gonzalez Robayo (25111422) Environmental Sciences not elsewhere classified Ecology Sociology Biological Sciences not elsewhere classified Cancer Science Policy Computational Biology targeted prioritization strategies global public health findings provide evidence escherichia coli </ colombian orinoquía region 59 – 10 16 – 2 official surveillance data thermally processed foods highly handled foods particularly total coliforms hygiene indicators predominated food matrix type div >< p principal component analysis identify factors associated 868 samples collected 01 – 1 hygiene indicators factors associated samples collected microbiological surveillance important component foods intended year analysis retrospective analysis mainly associated thermal processing support risk study aimed sampling year related dimensions primary outcome microbiological non lmics ). infrequently detected inferential analyses income countries including heatmaps higher odds food safety exploratory analyses evaluated samples dispersed municipalities <p>Multivariable logistic regression model for factors associated with microbiological non-compliance in ready-to-eat foods (n = 1,846). Regression coefficients (B), standard errors, Wald statistics, p-values, odds ratios [OR], and 95% confidence intervals (95% CI) are presented. The model was adjusted for temporal variables (year 2020), territorial variables (rural/dispersed municipalities and Villavicencio), type of establishment (food service, food operator, and institutional), and food matrix type (raw or highly handled foods, liquid preparations, and dairy/sweet products), using thermally processed foods as the reference category. Odds ratios >1 indicate higher odds of microbiological non-compliance, whereas odds ratios <1 indicate lower odds of microbiological non-compliance. Statistical significance was defined as p < 0.05.</p> 2026-10-05T17:33:00Z Dataset Dataset 10.1371/journal.pgph.0006492.t003 https://figshare.com/articles/dataset/_p_Multivariable_logistic_regression_model_for_factors_associated_with_microbiological_non-compliance_in_ready-to-eat_foods_n_1_846_Regression_coefficients_B_standard_errors_Wald_statistics_p-values_odds_ratios_OR_and_95_confidence_interval/34072151 CC BY 4.0