Pregnant women face a heightened risk from foodborne illnesses, and a new study from Michigan State University aims to refine food safety guidance to better protect them. Researchers have developed more precise models for assessing the risk of listeriosis – an infection caused by the bacterium Listeria monocytogenes – during pregnancy, a condition that often goes unnoticed by expectant mothers but can lead to severe complications, including stillbirth. This research addresses a critical gap in current food safety policies, which have historically relied on models not specifically tailored to the unique vulnerabilities of pregnant individuals.
Each year, approximately 1,250 people in the United States contract listeriosis, according to the Centers for Disease Control and Prevention. The illness has a high hospitalization rate – 86 percent – and is fatal in about 14 percent of cases. However, the stakes are significantly higher for pregnant women, who account for roughly 14 percent of all listeriosis cases. When Listeria crosses the placental barrier, it can cause stillbirth in approximately 25 percent of those infections. The insidious nature of the illness, often presenting with mild, flu-like symptoms or no symptoms at all, allows the bacteria to progress undetected, making early intervention challenging.
Refining Risk Assessment with Biologically Informed Models
The study, soon to be published in the journal Risk Analysis, focuses on creating what researchers call “biologically informed, dose-response models.” These models move beyond generic population estimates and incorporate data from animal studies – specifically guinea pigs and gerbils, chosen for their biological similarities to humans in relation to Listeria pathogenesis – to better predict maternal infection and adverse fetal outcomes. Jade Mitchell, a professor in the Department of Biosystems and Agricultural Engineering at Michigan State University, explained that the goal was to determine how to better protect pregnant women from Listeria.
A key finding of the research is that fetal brain infection is a more reliable indicator of stillbirth risk than simply tracking stillbirth outcomes. Researchers consistently found Listeria infection in the brains of fetuses that resulted in stillbirth, but not in those that were carried to term. This consistent pattern allowed for a more accurate and precise model, strengthening the ability to assess risk.
The Urgency of Improved Food Safety Guidance
Recent outbreaks have underscored the require for more refined risk assessments. Outbreaks between 2021 and 2023, linked to contaminated ice cream, queso fresco, and enoki mushrooms, tragically resulted in five stillbirths in just three years. These incidents highlight the potential consequences of relying on outdated or insufficiently targeted food safety policies.
“Public health agencies should use population-specific models like these when developing food safety guidance rather than applying generic population estimates,” Mitchell said. “As listeria outbreaks continue to occur, having more precise risk assessment tools will support more informed and protective food safety policies.” The researchers emphasize that pregnancy involves a unique combination of physiological, behavioral, and clinical variables that are not adequately captured by models designed for the general population or those focused solely on immunocompromised individuals.
Foods to Avoid During Pregnancy
The Food and Drug Administration (FDA) currently recommends that pregnant individuals avoid certain high-risk foods to minimize their risk of listeriosis. These include unpasteurized cheeses, raw sprouts, deli meats, hot dogs, and smoked seafood unless they are thoroughly heated. Listeria is particularly concerning because it can grow even in refrigerated temperatures, making careful food handling practices essential. Symptoms of listeriosis, such as fever, muscle aches, nausea, and diarrhea, can appear anywhere from one to several weeks after exposure.
The study was led by Mitchell, with contributions from recent Michigan State University graduates Carly Gomez and Tyler Stump. Their work represents a significant step forward in precision public health, offering the potential to reduce the devastating impact of listeriosis on pregnant women and their babies.
Looking ahead, researchers hope their findings will be incorporated into updated food safety guidelines and risk assessments by public health agencies. The implementation of these population-specific models could lead to more targeted interventions and a reduction in the incidence of pregnancy-associated listeriosis.
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