Metabolic effects of kidney donation: A Bayesian analysis of matched cohorts.

The kidney is a notable site of glycolysis, gluconeogenesis, and fatty acid oxidation. Loss of a kidney after kidney donation might, therefore, affect the glucose and lipid metabolism of the donors. This matched cohort study investigated the effect of nephrectomy on glucose and lipid metabolisms using Bayesian hypothesis testing. There were 77 pairs of matched donor-control pairs in the present study. Clinical and laboratory data of the participants, at baseline and 1-year, were extracted from electronic medical records. Comparisons between donor and control groups were performed using the Bayesian independent samples t-test or Bayesian Mann-Whitney test. The Bayes Factor for alternative hypothesis over null hypothesis (BF10 ) was used to compare the two competing hypotheses. The BF10 of 3 or more was considered evidence for the alternative hypothesis. Comparing changes from baseline to 1-year between donors and controls, the BF10 of triglycerides, high-density lipoprotein cholesterol (HDL-C), triglyceride-glucose (TyG) index of insulin resistance, and estimated glomerular filtration rate (eGFR) were 7.95, 3.96, 30.13, and 1.32 x 1041 , respectively signifying that the change of these variables in the donors differed from those in the controls (alternative hypothesis). Triglyceride, HDL-C, and TyG index of the donors increased more than those of the controls while eGFR of the donor decreased more than that of the controls. Our data suggest that triglycerides and insulin resistance increase after donor nephrectomy. Kidney donors should be informed about these metabolic changes and should adhere to lifestyle recommendations that may mitigate insulin resistance.

Shift Work and Leukocyte Count Changes among Workers in Bangkok.

OBJECTIVES: Previous epidemiological evidence for the association of shift work exposure and increased leukocyte count is cross-sectional in nature, thus limiting cause-effect inference. We therefore used a longitudinal design to: (i) compare leukocyte counts at baseline between shift and day workers and (ii) examine the time trend of leukocyte counts over the follow-up period for these workers. METHODS: A retrospective cohort study was conducted among 6737 workers aged <60 years at two large organizations (a humanitarian organization and a university) in Bangkok, Thailand who had participated in at least two annual health check-ups during the period 2005-2016. Shift work exposure history was assessed by a self-administered questionnaire and categorized into day, former, and current shift workers. Data on leukocyte count were collected annually as part of worksite health screening during the observation period. Association of shift work exposure and increased leukocyte count was then examined cross-sectionally and longitudinally by using multiple linear regression and multilevel analysis of repeated measures data, respectively. In addition, trends for leukocyte count over the follow-up period and work years were examined using LOWESS smooth curves. RESULTS: Compared to day work, the current shift work was associated with increased leukocyte counts. The magnitude of percentage increase was the highest for basophil counts, followed by eosinophil and lymphocyte counts. Both cross-sectional and longitudinal evidence revealed this association, although it was less pronounced longitudinally. For total leukocyte count, the magnitude of difference was constant across the 11-year follow-up period. However, for lymphocyte and basophil counts, these discrepancies tapered over the work years until they no longer differed (for lymphocyte count) or even differed in the opposite direction (for basophil count) in later work years. CONCLUSION: This study confirmed previous cross-sectional evidence that shift work exposure-increased leukocyte counts and that this was reversible. Whether this increase in immune cell count also results in an increased immune cell activity and serves as the intermediary in the association between shift work exposure and subsequent chronic disease development needs further investigation.

Increased Risk Of Type 2 Diabetes And Abnormal FPG Due To Shift Work Differs According To Gender: A Retrospective Cohort Study Among Thai Workers In Bangkok, Thailand.

PURPOSE: The gender differential evidence of the association between shift work and type 2 diabetes risk remains scarce. This longitudinal study determines whether the association between shift-work exposure and type 2 diabetes risk and abnormal fasting plasma glucose (FPG) differs according to gender; the study aims to find the association between shift work and changes in physiological, behavioral, and psychosocial stress. PATIENTS AND METHODS: This retrospective cohort study was conducted among 5947 workers (4647 female and 1300 male) aged ≤60 years old in Bangkok, Thailand. Participants required a normal FPG level (<100 mg/dL) at baseline and at least two health check-up results from 2009 to 2016. Shift-work exposure history was assessed using a self-administered questionnaire; FPG levels were measured annually. Cox proportional hazard models were used to assess the aforementioned association. RESULTS: During the follow-up period, 1470 new abnormal FPG and 154 new type 2 diabetes cases developed. Stratified analysis of male workers' data revealed an association was significant in the unadjusted model, which tended to be stronger after adjustment for demographic data and the baseline values of anthropometric and biochemical parameters. This was the case both for type 2 diabetes [Hazard Ratio (HR) (95% Confidence Interval (CI))=2.98 (1.58-5.62)] and abnormal FPG [HR (95% CI)=1.86 (1.43-2.41)]; this association was less obvious among women. CONCLUSION: Shift work is a risk factor for type 2 diabetes and abnormal FPG; this risk is gender differential, being more pronounced in men. Preventive measures aiming at ameliorating shift work induced type 2 diabetes risk should pay more attention to men.

Prevalence of Facebook Addiction and Related Factors Among Thai High School Students.

OBJECTIVE: To determine the prevalence ofFacebook (FB) addiction and its related factors among Thai high school students. MATERIAL AND METHOD: This cross-sectional study was performed among 972 high school students in four provinces associated with high economic prosperity in Thailand: Bangkok, Ubon Ratchathani, Chiang Mai and Songkhla, utilizing a multistage cluster sampling technique. A self-administrative questionnaire was produced composing of three parts; demographic data, a Thai version of the Bergen Facebook Addiction Scale (Thai-BFAS) and the Thai version of the General Health Questionnaire-28 items. Multivariate analysis was employed to analyze thefactors associated with FB addiction. RESULTS: The prevalence ofFB addiction amongst Thai adolescents was 41.8% (95% CI; 38.6, 45.2). Related factors included gender school location, sufficiency ofpersonalfinance, devices ofFB access, duration ofstaying online via FB, andFB usage during holidays. In addition, every 1-hour increase in usage enhanced the risk for FB addiction (OR = 1.12, 95% CI; 1.05, 1.19). CONCLUSION: The prevalence of FB addiction in Thai high school students was found to be higher than in many other countries. Relatedfactors should be controlled in order to reduce FB addiction and its detrimental impacts, such as behavior modification and the promotion of healthier free-time activities. Further studies are recommended to understand why FB addiction is so high in Thailand.

Facebook Addiction and Its Relationship with Mental Health among Thai High School Students.

OBJECTIVE: To investigate the relationship between Facebook addiction and mental health among high school students. MATERIAL AND METHOD: This cross-sectional analytic study was performed among 972 high school students from four provinces associated with high economic prosperity in Thailand: Bangkok, ChiangMai, Ubon Ratchathani and Songkhla, utilizing a multistage cluster sampling technique. Facebook addiction was assessed using the Thai version of the Bergen-Facebook Addiction Scale (Thai-BFAS), while a Thai version ofthe General Health Questionnaire (Thai GHQ-28) was used for mental health evaluation. The relationship between Facebook addiction and mental health was analyzed through multiple logistic regressions. RESULTS: The prevalence of Facebook addiction and abnormal mental health were 41.9% (95% CI; 38.6, 45.2), and 21.9% (95% CI; 19.2, 24.8), respectively. After adjustment for confounding factors (sufficiency of household income, school location, level of education, GPAX learning deficits and attention deficit hyperactivity disorder), the individuals identified as having Facebook addiction were discovered to be at a high risk of developing abnormal general mental health (ORadj = 1.7, 95% CI: 1.1, 2.4), somatic symptoms (OR = 1.2, 95% CI: 0.9, 1.7), anxiety and insomnia (ORadj = 1.3, 95% CI: 0.9, 1.8), social dysfunction (OR = 1.5, 95% CI: 1.1, 2.1) and severe depression (ORadj = 1.5, 95% CI: 1.0, 2.2). Moreover; there were pronounced trends of increasing risk according to the level of Facebook addiction (Ptrend < 0.05). CONCLUSION: It was found that Facebook addiction among high school students could be associated with abnormal, general mental health status, somatic symptoms, anxiety & insomnia, social dysfunction, and severe depression. Therefore, it is essential that the relevant authorities educate young people about the mental health impacts linked with Facebook addictive usage and impose appropriate public health policies by screening Facebook addiction and mental health issues in risk groups.

Validation of the Thai version of Bergen Facebook addiction scale (Thai-BFAS). .

OBJECTIVE: To determine the validity ofthe Thai version ofthe Bergen FacebookAddiction Scale (Thai-BFAS) using Facebook addiction screening in Thai high school students. MATERIAL AND METHOD: The original BFAS was authorized for translation and validation in Thai. After content validity and usability were approved by three Thai psychiatrists, the Thai-BFAS was adjusted again by the authors and back translated by an English expert. Thisfinal version was investigated using the internal consistency method among 874 high schools students in Bangkok, Chiang Mai, Ubon Ratchathani and Songkhla, and confirmatoy factor analysis (CFA) was employed to prove that the six-component model could be representative of addiction behaviors. In addition, test-retest reliability was performed separately among 30 pilot high school students in Bangkok. RESULTS: The Thai-BFAS has six items, which are each scored on a 5-point scale with total score ranges from 0 to 24; the cutoff score for Facebook addition stands at least 12 points. The Cronbach s alpha coefficient was 0.91 (95% CI; 0.90, 0.92) and the inter-class correlation coefficient was 0.80 (95% CI; 0.49, 0.92). The CFA showed that the six items accurately represent the six-component model of addiction such as salience, mood modification, tolerance, withdrawal, relapse and conflict. CONCLUSION: The Thai-BFAS is consistent as a screening testfor Facebook addiction among high school students due to good reliability and validity. It also conforms well to the original version. The six items in the Thai-BFAS are a good representation of the addiction behaviors. Further studies should be undertaken in cases of sensitivity and specificity when compared with other similar tests of addiction as well as in various additional populations and circumstances.