Comparison of the physical activity levels between shift workers and non-shift workers in a large-scale cross-sectional study in Iran

Association between Sleep Duration, Social Jetlag, and the Metabolic Syndrome by Shift Works

Lifestyle factors, including sleep characteristics, have been implicated in the development of metabolic syndrome, particularly among shift workers. This study aimed to explore the relationship between shift work, sleep duration, social jetlag, and the risk of metabolic syndrome among U.S. workers and the moderating effect of sleep duration and social jetlag on this relationship. Data from the National Health and Nutrition Examination Survey (NHANES) in 2017-2020 March were analyzed. Poisson regression models were employed to examine associations. Among 4136 U.S. workers, 53.3% had metabolic syndrome, with a higher proportion of shift workers (63.8% vs. 56.7%, p = 0.001) and those sleeping less than 6 h or more than 9 h per week (22.3% vs. 19.1%, p = 0.044) in the affected group. Shift workers were initially found to have an increased risk of metabolic syndrome (Coef. = 0.03, 95% CI: 0.02, 0.16); however, this association was mitigated when accounting for the interaction with social jetlag. Specifically, 1 to <2 h of social jetlag interacted significantly, increasing metabolic risk (Coef. = 0.15, 95% CI: 0.09, 0.22), whereas 1 to <2 h alone showed a protective effect (Coef. = -0.11, 95% CI: -0.17, -0.06). These findings suggest that optimizing sleep schedules and addressing social jetlag may be crucial in mitigating metabolic syndrome risks among shift workers.

Prevalence and associated factors for asymptomatic microscopic hematuria in adults in the PERSIAN Guilan cohort study (PGCS)

Although hematuria is not life-threatening, some could be the result of a more severe condition. Our objectives are to report on the prevalence and risk factors of asymptomatic microscopic hematuria (AMH) in the prospective epidemiological research studies of the Iranian adults (PERSIAN) Guilan cohort study (PGCS) population. This cross-sectional study was conducted from 2014 to 2017 and consisted of 10,520 individuals aged 35-70. Data collection was conducted using a questionnaire during a face-to-face interview. The urine analyses (UA) were done up to 2 h after sample collection. Based on a urine microscopy evaluation, AMH is defined as 3 or more red blood cells per high power field (HPF). Simple and multiple logistic regression analysis was conducted to explore factors associated with AMH. The prevalence of AMH in this study was 34.1% and was more prevalent in participants of older ages and female gender as well as those with low educational level, underweight-body mass index (BMI), high physical activity, smoking, alcohol consumption, and kidney stone disease. On the other hand, obesity, opium, and diabetes decreased the likelihood of AMH. The results of the present study shed light on the prevalence and risk factors of AMH and suggested that a significant portion of the study population is affected by AMH. Considering the lack of consensus on a definite clinical guideline for AMH in our country, the results of the present study could be used to design a unit algorithm for screening and therapy of AMH.