Seasonality of month of birth in children and adolescents with autoimmune thyroiditis: a continuing conundrum

2018 ◽  
Vol 31 (10) ◽  
pp. 1123-1131 ◽  
Author(s):  
Ioannis Kyrgios ◽  
Styliani Giza ◽  
Vasiliki Rengina Tsinopoulou ◽  
Ioanna Maggana ◽  
Anna-Bettina Haidich ◽  
...  

Abstract Background The aim of this study was to analyze the seasonal birth month pattern in young patients with autoimmune thyroiditis and compare it with youth controls. Methods Medical records of a total of 298 children and adolescents of Greek origin, with a diagnosis of Hashimoto thyroiditis (HT) before the age of 21 years that were born from 1987 to 2010 were retrospectively reviewed. In addition, 298 consecutive subjects that were born from 1988 to 2012 and evaluated in a tertiary unit for any reason, served as controls, provided that they had no personal or family history of thyroid or any other autoimmune disease. Results Significant differences were found between children and adolescents with HT and healthy controls in the yearly pattern of month of birth distribution (p=0.029). During month-by-month analysis, it was shown that the highest and lowest predispositions to HT were among those born in spring (March) (odds ratio [OR] 2.34, p=0.005), and autumn (November) (OR 0.49, p=0.035), respectively. A binary logistic regression model also revealed that season of birth and sex were the only factors that remained related to HT disease, even after adjustment for confounding factors such as year of birth and age (p<0.001, Nagelkerke r-square 0.151). Conclusions This study suggests that the effect of certain seasonal factors during fetal development, reflected by the seasonal differences in birth pattern, in children and adolescents with autoimmune thyroiditis could contribute to long-term programming of an autoimmune response against the thyroid gland. Further studies are needed to demonstrate a clear cause and effect relationship between month of birth and HT.

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Omid Mirmosayyeb ◽  
Mahdi Barzegar ◽  
Alireza Afshari-Safavi ◽  
Nasim Nehzat ◽  
Afshin Heidari ◽  
...  

Introduction. Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMO) are chronic immune-mediated diseases in the central nervous system (CNS). Environmental factors such as month of birth can be a trigger for these diseases. Therefore, we conducted this study to compare the months of birth in MS and NMOSD patients with the control group. Methods. In this cross-sectional study, 2345 patients with MS, 220 NMOSD patients, and 2174 healthy subjects were enrolled. Demographic information such as age, sex, month of birth, and education in three groups was extracted from the database. The associations between month of birth and MS were studied by binary logistic regression with adjusting for the year of birth. Results. There was a reduced birth rate in September-October in NMOSD ( OR = 0.309 , 95% CI: 0.150-0.636; p < 0.001 ) and MS patients ( OR = 0.470 , 95% CI: 0.374-0.591; p < 0.001 ) compared to the general population. The birth rate in March-April in MS was higher than the control group ( OR = 1.613 , 95% CI: 1.324-1.964; p < 0.001 ). There was no difference in the birth month distribution between the NMOSD and MS patients. No significant difference in MOB among different MS types was found. Conclusion. Our findings showed a decreasing risk of NMOSD and MS in individuals born in the autumn months and an increasing MS risk in spring. More studies are required to elucidate the association between the month of birth and risk of MS and NMOSD and the seasonality factors.


2018 ◽  
Vol 15 (3) ◽  
pp. 389-398
Author(s):  
Ruchi Singh

Rural economies in developing countries are often characterized by credit constraints. Although few attempts have been made to understand the trends and patterns of male out-migration from Uttar Pradesh (UP), there is dearth of literature on the linkage between credit accessibility and male migration in rural Uttar Pradesh. The present study tries to fill this gap. The objective of this study is to assess the role of credit accessibility in determining rural male migration. A primary survey of 370 households was conducted in six villages of Jaunpur district in Uttar Pradesh. Simple statistical tools and a binary logistic regression model were used for analyzing the data. The result of the empirical analysis shows that various sources of credit and accessibility to them play a very important role in male migration in rural Uttar Pradesh. The study also found that the relationship between credit constraints and migration varies across various social groups in UP.


2020 ◽  
Author(s):  
Gobi Hariyanayagam ◽  
Sera Selvanthan Sundram Gunasekaran ◽  
Shargunan Selvanthan Gunasekaran ◽  
Nur Syafina Insyirah Zaimi ◽  
Nor Amirah Abdul Halim

BACKGROUND In late December 2019, an outbreak of a novel coronavirus disease (COVID-19; previously known as 2019-nCoV) was epidemiologically linked to seafood and wet animal market in Wuhan, Hubei, China. This event has instigated negative stigma among the general population to view the wet market as a high-risk location for potential transmission of coronavirus. OBJECTIVE This study investigated the prevalence of facemask use among general population visiting the wet market as well as factors contributing to unacceptable facemask practice. Setting The visitors to a district wet market selling range of live or freshly slaughtered animals during COVID-19 pandemic outbreak was observed for facemask practice. METHODS All Individuals visiting the market were observed for the type, category and practice of wearing facemas. Subjects were categorized into two groups of acceptable and unacceptable facemask practice. The Pearson chi-square was used to test for differences in investigated variables in the univariate setting and Binary Logistic regression model was used in the multivariate setting. Main outcome measure Prevalence, acceptance practice and odds ratio of unacceptance of facemask use. RESULTS Among 1697 individuals included in the final analysis, 1687 (99.7%) was observed wearing facemask with 1338 (78.8%) using medical-grade facemask. Among them, 1615 (95.7%) individuals facemask practice was acceptable while the reaming 72 (4.3%) individuals were observed with unacceptable facemask practice. Individuals using medical-grade facemask and high-risk age group are 6.4 times (OR=6.40; 95% CI, 2.00-20.43; p=.002) and 2.06 times practice (OR=2.06; 95% CI, 1.08-3.94; p=.028) more likely to have unacceptable facemask practice respectively. CONCLUSIONS High saturation of facemask among the general population is an adequate indicator of public hygiene measures strategy which can help to mitigate the COVID-19 epidemic impact. Alarmingly, the unacceptable facemask practice among high-risk population raises the need for a targeted approach by healthcare authorities to ensure satisfactory facemask use.


Author(s):  
Jeremy Freese

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.


2021 ◽  
Author(s):  
Matthew Briggs ◽  
Christine Ulses ◽  
Lucas VanEtten ◽  
Cody Mansfield ◽  
Anthony Ganim ◽  
...  

Abstract Objective The objective of this study was to xamine primary factors which may predict patients’ failure to show at initial physical therapist evaluation in an orthopedic and sports outpatient setting. Methods A retrospective analysis of patients’ demographic data for physical therapist evaluations between January 2013 and April 2015 was performed. A binary logistic regression model was used to evaluate the odds of a no-show at evaluation. Demographic variables of age, employment status, days waited for the appointment, payer source, and distance traveled to clinic were analyzed. Independent variables were considered significant if the 95% Cis of the odds ratios did not include 1.0. Results A total of 6971 patients were included in the final analysis with 10% (n = 698) of the scheduled patients having a no-show event for their initial evaluation. The following factors increased the odds of patients having a no-show event: days to appointment (OR = 1.058; 95% CI = 1.042 to 1.074), unemployment status (OR = 1.96; 95% CI = 1.41 to 2.73), unknown employment status (OR = 3.22; 95% CI = 1.12 to 8.69), Medicaid insurance (OR = 4.87; 95% CI = 3.43 to 6.93), Medicare insurance (OR = 2.22; 95% CI = 1.10 to 4.49), unknown payer source (OR = 262.84; 95% CI = 188.72 to 366.08), and distance traveled ≥5 miles (OR = 1.31; 95% CI = 1.01 to 1.70). Female sex [OR = 0.73; 95% CI = 0.57 to 0.95) and age ≥ 40 years (OR = 0.44; 95% CI = 0.33 to 0.60) decreased the odds of a no-show event. Conclusion Results from this study indicate there may be some demographic factors that are predictive of patients failing to attend their first physical therapist visit. Impact Understanding the predictive factors and identifying potential opportunities for improvements in scheduling processes might help decrease the number of patients failing to show for their initial physical therapy appointment, with the ultimate goal of positively influencing patient outcomes.


2021 ◽  
Vol 9 (4) ◽  
pp. 42
Author(s):  
Hilja Viitaniemi ◽  
Auli Suominen ◽  
Linnea Karlsson ◽  
Paula Mustonen ◽  
Susanna Kortesluoma ◽  
...  

Dental anxiety (DA) and hair cortisol concentrations (HCC) are associated with psychological symptoms and vary during pregnancy. We aimed to examine the association between HCC and DA at two points of pregnancy. Participants were pregnant mothers (n = 533) drawn from the FinnBrain Birth Cohort Study donating a hair sample at gestational week (gwk) 24 (n = 442) and/or at delivery (n = 176) and completed questionnaires on DA. Two groups, HCC1 and HCC2, treated as separate in the analyses, were formed according to the hair sample donation time i.e., gwk24 and delivery. 85 subjects were included in both groups. MDAS, EPDS, and SCL-90 were used to measure DA, depressive and anxiety symptoms, respectively, at gwk14 for the HCC1 group and gwk34 for the HCC2 group. The association between DA and HCC was studied with a binary logistic regression model, adjusted for anxiety and depressive symptoms, age, BMI, and smoking status. Individuals with high DA had lower HCC levels at gwk24 (OR = 0.548; 95% CI = 0.35–0.86; p = 0.009), but the association was not statistically significant at the delivery (OR = 0.611; 95% CI = 0.28–1.33; p = 0.216). The independent association between HCC and DA in pregnant women suggests that long-term cortisol levels could play a role in the endogenous etiology of DA. Further studies are however, needed.


2019 ◽  
Vol 5 (1) ◽  
Author(s):  
David Varillas Delgado ◽  
Juan José Tellería Orriols ◽  
Carlos Martín Saborido

Abstract Background The genetic profile that is needed to define an endurance athlete has been studied during recent years. The main objective of this work is to approach for the first time the study of genetic variants in liver-metabolizing genes and their role in endurance performance by comparing the allelic and genotypic frequencies in elite endurance athletes to the non-athlete population. Methods Genotypic and allelic frequencies were determined in 123 elite endurance athletes (75 professional road cyclists and 48 endurance elite runners) and 122 male non-athlete subjects (sedentary). Genotyping of cytochrome P450 family 2 subfamily D member 6 (CYP2D6 rs3892097), glutathione-S transferase mu isoform 1 (GSTM1), glutathione S-transferase pi (GSTP rs1695) and glutathione S-transferase theta (GSTT) genes was performed by polymerase chain reaction (PCR). The combination of the polymorphisms for the “optimal” polygenic profile has been quantified using the genotype score (GS). Results Statistical differences were found in the genetic distributions between elite endurance athletes and non-athletes in CYP2D6 (p < 0.001) and GSTT (p = 0.014) genes. The binary logistic regression model showed a favourable OR (odds ratio) of being an elite endurance runner against a professional road cyclist (OR: 2.403, 95% CI: 1.213–4.760 (p = 0.002)) in the polymorphisms studied. Conclusions Genotypic distribution of liver-metabolizing genes in elite endurance athletes is different to non-athlete subjects, with a favourable gene profile in elite endurance athletes in terms of detoxification capacity.


2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Yi Yang ◽  
Jingjuan Yang ◽  
Xiner Yao ◽  
Yu Cui ◽  
Xiabing Lang ◽  
...  

Background. The aim of this study was to identify the blood potassium level beneficial to the postoperative recovery of gastrointestinal motility during continuous renal replacement therapy (CRRT) in patient undergoing open abdominal surgery. Materials and Methods. 538 critically ill patients after open abdominal surgery and receiving CRRT were retrospectively recruited as the study cohort. Demographic and clinical data were recorded along with an evaluation of the postoperative gastrointestinal motility. Results. Correlation analysis was used to assess the correlation coefficient, and then the variables with correlation coefficient value less than 0.5 were included in the binary logistic regression model. Binary logistic regression model indicated that the postoperative blood potassium level was independently associated with the recovery of gastrointestinal motility (OR=0.109, 95% CI= 0.063 to 0.190, p<0.001). Based on the normal range of blood potassium level, we selected the cut-off point of blood potassium level via Weight of Evidence analysis, which was 4.00 mmol/L. Compared with the patients with insufficient blood potassium levels (plasma potassium concentration < 4.00 mmol/L), those with sufficient blood potassium levels (plasma potassium concentration≥ 4.00 mmol/L) conferred an increase in the rate of 4-day postoperative recovery of gastrointestinal motility (OR= 4.425, 95% CI = 2.933 to 6.667, p<0.001). Conclusions. Maintaining the blood potassium concentrations at a relatively high level of the normal blood potassium range during CRRT would be beneficial to postoperative recovery of gastrointestinal motility.


Sign in / Sign up

Export Citation Format

Share Document