ABSTRACT
Background: Diabetes mellitus is a chronic metabolic disorder with substantial implications for public health. Understanding the factors influencing blood sugar fluctuations is crucial for effective diabetes management and prevention. This study aimed to evaluate factors associated with blood sugar changes in diabetic patients and healthy individuals attending the Sabzevar Persian Cohort Center, employing the growth curve model. Materials and Methods: Data related to 589 diabetic patients and 589 non-diabetic patients participating in the Persian cohort study of Sabzevar were used. Due to the repetition of blood sugar measurements for each individual over time, we use the conditional latent growth curve model to examine intra-individual changes and variables that affect these changes over time. Results: The linear latent growth curve model, fitted with independent variables, exhibited a superior fit. The slope of the line for the diabetic group was measured at 1.78, while for the non-diabetic group, it was estimated to be -0.29. Within the diabetic group, the influence of age, the presence of fatty liver, and history of congenital heart disease (CHD) had a significant impact on the baseline (the intercept), and the effect of body mass index (BMI) on the changing trend of the response variable (slope) was also significant. In the non-diabetic group, significant effects were observed for age variables, BMI, family history of diabetes, and history of stroke in the family. Conclusion: Overall, the linear latent growth curve model showed good performance in the evaluation of the factors related to blood sugar changes in diabetic patients and healthy people.
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Background: Environmental exposures and genetic predisposition interactions may result in autoimmune rheumatic diseases. This study aimed to determine the effect of outdoor air pollutants on the activity of rheumatoid arthritis (RA) in a longitudinal follow-up. Methods: We longitudinally studied 50 patients with RA bimonthly over 6 months in Mashhad, one of the most polluted cities in Iran. Disease activity and health-related quality of life (HRQoL) were examined according to the disease activity score (DAS28ESR), health assessment questionnaires (HAQ), physical health component summary (PCS), and visual analogue scale (VAS) criteria. The outdoor air pollutant was measured by monitoring the average concentration of nitrogen oxide (NO), carbon monoxide (CO), O2 level, Sulfur dioxide (SO2), and some particles less than 10 and 2.5 micrometers in diameter (PM <10 µm, PM <2.5 µm). The temperature and humidity levels were also measured. The univariate and multivariate statistical analyses were used for data analysis and the role of confounding factors was determined using the generalized estimation equation method. Results: Statistical analysis indicated a significant increase of the DAS28ESR (B = 0.04 [0.08]; P = 0.01) and VAS (B = 4.48 [1.73]; P = 0.01) by CO concentration. Moreover, a number of polluted days increased the VAS in patients. In addition, other air pollutants, temperature, and humidity were not affected significantly by the DAS28ESR and quality of life indexes by considering confounders such as medications, age, and job. Conclusion: Based on our findings, CO concentration was the only effective outdoor air pollutant that could increase RA disease activity. In addition, CO concentration and the number of polluted days make patients feel more ill. As the role of indoor air pollutants is highly important, further research on this critical topic is required to establish the role of air pollution on RA disease activity.
ABSTRACT
INTRODUCTION: Air pollution is one of the environmental factors that influences the pathogenesis of systemic autoimmune diseases, followed by the development and spread of inflammation and increased oxidative damage. Only a few studies have been conducted on the impact of air pollution on disease activity in patients with lupus, which mostly have focused on PM2.5 particles. MATERIALS AND METHODS: We longitudinally studied 50 patients with lupus bimonthly in a 6-month period in Mashhad, one of the polluted cities of Iran. Disease activity and quality of life were examined considering SLEDAI2K, SLEQOL, and VAS criteria. The outdoor air pollutant was measured by monitoring the average concentration of nitrogen dioxide (NO2), carbon monoxide (CO), some particles less than 10 and 2.5 micrometers in diameter (PM <10, PM <2.5) and the level of temperature and humidity which were taken from the Meteorological Organization of Mashhad. Confounding factors such as medications were investigated by univariate and multivariate statistical analysis, specifically by GEE method. RESULTS: The possible relation among various factors to SLEDAI, SLEQOL and VAS by two different univariate and multivariate analyses were studied. Our analysis indicated that spring season, decreased temperature, increased air pollutants including (PM2.5, and NO2) and increased humidity increase SLEDAI2K. Furthermore, the percent of polluted days directly correlates with Anti-dsDNA and NO2 significantly increases SLEQOL. CONCLUSION: Based on our findings, air pollution (particularly NO2 and PM2.5) has affected at least some aspects of the disease and the health-related quality of life (HRQL) of lupus patients. Further research is needed to confirm these findings.