Effect of Covid-19 pandemic on gender associated with risk factors: a retrospective data analysis, Thailand.

Background: The COVID-19 pandemic is having a serious impact around the world. Many countries have experienced a two or three wave pattern in reported cases. The virus's spread in Thailand was a cluster event distributed over multiple locations, multi-spender, and multiple waves of outbreaks. Objective: This study aims to study gender associated with age, risk factors, and nationality during coronavirus pandemic in Thailand. Material and methods: A retrospective cohort study was conducted from January 2020 to May 2021 (17 months) to determine the number of confirmed cases and identify gender associated with, age, various risk factors and nationality were analyzed by chi square test and binary logistic regression analyses. Results: The results show that the number of cases increased by over 100,000 over the course of three waves of outbreaks. The logistic regression analysis revealed that genders were significantly related with age, various risk factors, and nationality across different waves (p < 0.01). Across the primary risk factors were community risk, community cluster and close contact with a previously confirmed patient on confirmed cases during COVID-19 pandemic. Conclusion: Significant differences between genders were significantly associated with age, various risk factors, and nationality may be due to weak social distancing policies and the lack of public health interventions. A COVID-19 vaccination plan is needed for people who are at risk of suffering severe symptoms as well as the general population in outbreak areas to increase immunity.

Active smoking in urban households: An association between urinary cotinine metabolite level and serum eGFR concentration.

INTRODUCTION: Smoking stands as a primary contributor to preventable deaths globally and is linked to an increased risk of developing kidney failure and other diseases. A few studies have focused on the negative correlation between serum cotinine and estimated glomerular filtration rate (eGFR), indicating decreased kidney function. This study investigated the associations between urinary cotinine metabolite concentration and serum eGFR among active smokers in urban households. METHODS: This was a cross-sectional study of active smokers in urban households' community Bangkok, Thailand from January to April 2023. The study involved 85 participants aged ≥18 years who were active smokers. Both urinary cotinine and serum eGFR concentrations were used as biomarkers. Independent sample t-tests were used to compare the urinary cotinine metabolite based on differences in the characteristic variable. We used multiple linear regression to test the association between cotinine metabolite and characteristics variables. Spearman's analysis was used to test the correlation between cotinine metabolite and eGFR concentration. RESULTS: The association between urinary cotinine metabolite and serum eGFR concentration decreased with increasing cotinine concentrations (r= -0.223, p=0.041), suggesting a decline in kidney function. However, this study found no significant difference between urinary cotinine metabolite and characteristic variables (p>0.05). Additionally, those who smoked for ≥10 years (117.40 ± 89.80 ng/mL), smoked ≥10 cigarettes per day (117.40 ± 89.80 ng/mL) and used conventional cigarettes (124.53 ± 115.10 ng/mL). The results of the multiple linear regression models analysis indicated that those who were smokers for ≥10 years (ß=0.076; 95% CI: -31.575-59.715) and those who were smoked ≥10 cigarettes/day (ß=0.126; 95% CI: -65.636-18.150) were not associated with urinary cotinine metabolite level. CONCLUSIONS: This study shows that the urinary cotinine metabolite level is associated with serum eGFR concentration among active smokers in urban households. The current study suggests that clinical identification and a prospective cohort study are needed before robust conclusions about how tobacco affects kidney efficiency.

Effect of children secondhand smoke exposure associated with GABA concentration: Influence from parents who are extremely heavy smokers in urban households.

BACKGROUND: Secondhand smoke (SHS) poses the most considerable health risk to children in urban households. However, limited evidence exists regarding the impact of children exposure to SHS on gamma-aminobutyric acid (GABA) levels. This study aimed to investigate the level of cotinine and GABA and their association with variables related to children exposed to SHS. METHODS: A cross-sectional analysis was conducted to assess urinary cotinine and GABA levels in respondents. The study involved 85 participants aged 2-4 years who resided with parents exhibiting heavy smoking habits in urban households in Bangkok, Thailand. Urinary cotinine and GABA concentrations were utilized as biomarkers and measured using an enzyme-linked immunosorbent assay kit. An independent t-test was employed to compare contributing factors with urinary cotinine metabolites. Spearman's correlation test was utilized to assess the relationship between cotinine metabolites and GABA concentration. RESULTS: The study found a correlation between urinary cotinine metabolites and GABA concentration among children's (r = 0.260, p-value = 0.016), particularly influenced by parents exhibiting extreme heavy smoking in urban households. Male children exhibited significantly higher urinary cotinine metabolite concentrations than females (p-value = 0.040). Moreover, significantly elevated levels of cotinine metabolites (57.37 ± 10.27 ng/ml) were observed in households where parents engaged in extreme heavy smoking. CONCLUSIONS: This research establishes a link between urinary cotinine metabolite levels and GABA concentration among children exposed to extreme heavy smoking by their parents in urban households. Consequently, smoking might impact neurobehavioral effects, potentially leading to insomnia. The study emphasizes the importance of promoting and safeguarding non-smokers from exposure to SHS in indoor workplaces, public spaces, and households, advocating for the implementation of smoke-free public health regulations.

Comparison of Different Waves during the COVID-19 Pandemic: Retrospective Descriptive Study in Thailand.

BACKGROUND: Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. An outbreak is called an epidemic when there is a sudden increase in cases. Many countries have experienced a two-wave pattern in the reported cases of COVID-19. The spread of COVID-19 in Thailand was a cluster event distributed over multiple locations. This study aims to compare the characteristics of different waves during the COVID-19 pandemic in Thailand. METHODS: A retrospective cohort study was conducted from January 2020 to May 2021 (17 months) to determine the number of COVID-19 screenings and confirmed cases and deaths as well as sociodemographic characteristics such as gender, age, nationality, and source population at risk factors. The categorical data were compared using a chi-square test. RESULTS: Three waves of the COVID-19 pandemic occurred within 17 months in Thailand, and the number of cases increased by over 100,000 due to source population at risk factors such as close contact with a previously confirmed patient, community risk, cluster communities, and active and community surveillance. The chi-square test revealed significant differences between the three waves (p < 0.01). CONCLUSION: Significant differences between pandemic phases or waves may be due to weak social distancing policies and the lack of public health interventions. A COVID-19 vaccination plan is needed for people at risk of suffering severe symptoms and the general population in outbreak areas to increase immunity.