New research indicates that shift work, particularly night shifts, could have a stronger negative impact on men’s health than women’s.
This conclusion comes from a combination of lab experiments on mice and data analysis of more than 90,000 UK shift workers.
The study, published in Science Translational Medicine, found that male mice showed several adverse effects when exposed to abnormal day-night cycles.
Changes were observed in their gene activity, gut bacteria, and blood pressure. In contrast, female mice seemed largely unaffected.
When analyzing the human data, researchers noted that men working night shifts were more likely than those working regular hours to have metabolic syndrome – a cluster of conditions that increase the risk of heart disease and diabetes.
This syndrome includes elevated blood pressure, cholesterol and blood sugar levels, and excess abdominal fat.
Although female shift workers were also at a greater risk of metabolic syndrome compared to those working regular hours, this risk diminished when researchers factored in job type.
The Role of Estrogen
The lab experiments revealed that estrogen might play a role in mitigating the adverse effects of abnormal day-night cycles.
Female mice without ovaries (and therefore not producing estrogen) were less shielded from the impact of disrupted cycles than those with normal estrogen production.
However, this hormonal influence wasn’t the complete answer. Despite the protective effects of estrogen, male mice were still more adversely affected.
Need for Further Research
Although the human findings align with the lab results, the jump from lab mice to humans working shifts is significant. More research is needed to confirm why shift work might be less harmful for women.
The study underlines the potential health impacts of shift work and emphasizes the importance of good sleep hygiene for everyone.
This involves getting sunlight during the day and minimizing exposure to artificial light at night.
However, linking disease risks to shift work definitively is complex due to the numerous variables, including differences in education, income, and daily exposures between people with different types of work.
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