Abstract
Food safety is an important component of global public health, particularly in low- and middle-income countries (LMICs). This study aimed to identify factors associated with microbiological non-compliance in ready-to-eat (RTE) foods using seven years of official surveillance data from the Colombian Orinoquía region. RTE foods were defined as foods intended for immediate consumption without additional cooking or thermal processing. A retrospective analysis was conducted on 1,868 samples collected between 2017 and 2023, of which 1,846 were included in inferential analyses. Microbiological non-compliance, defined as failure to meet at least one regulatory microbiological criterion, was the primary outcome. Associations were assessed using multivariable logistic regression, complemented by descriptive and exploratory analyses, including heatmaps and principal component analysis. Microbiological non-compliance was identified in 39.5% of the evaluated samples. Hygiene indicators predominated, particularly total coliforms (29.0%), aerobic mesophilic bacteria (12.7%), and
Escherichia coli
(12.3%), whereas foodborne pathogens were infrequently detected. Raw or highly handled foods had higher odds of microbiological non-compliance than thermally processed foods (OR = 8.40; 95% CI: 6.59–10.72). Higher odds were also observed for samples from rural or dispersed municipalities (OR = 1.31; 95% CI: 1.01–1.70) and samples collected in 2020 (OR = 1.78; 95% CI: 1.16–2.74). Exploratory analyses revealed heterogeneous microbiological profiles across temporal, territorial, operational, and food-related dimensions, with a consistent predominance of hygiene indicators. Overall, microbiological non-compliance was mainly associated with food matrix type, territorial characteristics, and sampling year. The predominance of hygiene indicators supports incorporating hygienic quality and process control alongside pathogen detection into microbiological surveillance. These findings provide evidence to support risk-based food safety surveillance and targeted prioritization strategies in tropical low- and middle-income settings.