scholarly journals Impact of banning smoking in cars with children on exposure to second-hand smoke: a natural experiment in England and Scotland

2019 ◽  
Author(s):  
Anthony A Laverty ◽  
Thomas Hone ◽  
Philip E. Anyanwu ◽  
David Taylor Robinson ◽  
Frank de Vocht ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Survey Data ◽  
Tobacco Smoke ◽  
Natural Experiment ◽  
Second Hand Smoke ◽  
Regression Analyses ◽  
Difference In Difference ◽  
Difference In Differences ◽  
Survey Weighting ◽  
The Impact

ABSTRACTA ban on smoking in cars with children was implemented in April 2015 in England and December 2016 in Scotland. With survey data from both countries (NEngland=3,483-6,920 and NScotland=232-319), we used this natural experiment to assess the impact of the ban using a difference-in-differences approach. We conducted logistic regression analyses within a Difference-in-Difference framework and adjusted for age, sex, a marker of deprivation and survey weighting for non-response. Among children aged 13-15 years, self-reported levels of regular exposure to smoke in cars were 3.4% in 2012, 2.2% in 2014 and 1.3% in 2016 for Scotland and 6.3%, 5.9% and 1.6% in England. The ban was associated with a 73% reduction (95%CI -59%, -81%) in self-reported exposure to tobacco smoke among children.

scholarly journals Impact of banning smoking in cars with children on exposure to second-hand smoke: a natural experiment in England and Scotland

Thorax ◽  
2020 ◽  
Vol 75 (4) ◽  
pp. 345-347 ◽  
Author(s):  
Anthony A Laverty ◽  
Thomas Hone ◽  
Eszter P Vamos ◽  
Philip E Anyanwu ◽  
David Taylor-Robinson ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Survey Data ◽  
Tobacco Smoke ◽  
Natural Experiment ◽  
Second Hand Smoke ◽  
Relative Reduction ◽  
Difference In Differences ◽  
Absolute Reduction

England banned smoking in cars carrying children in 2015 and Scotland in 2016. We used survey data from 3 years for both countries (NEngland=3483–6920, NScotland=232–319) to assess effects of the English ban using logistic regression within a difference-in-differences framework. Among children aged 13–15 years, self-reported levels of regular exposure to smoke in cars for Scotland were 3.4% in 2012, 2.2% in 2014 and 1.3% in 2016 and for England 6.3%, 5.9% and 1.6%. The ban in England was associated with a −4.1% (95% CI −4.9% to −3.3%) absolute reduction (72% relative reduction) in exposure to tobacco smoke among children.

scholarly journals Regression analyses of questionnaires in bedside teaching

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Wolf Ramackers ◽  
Julia Victoria Stupak ◽  
Indra Louisa Marcheel ◽  
Annette Tuffs ◽  
Harald Schrem ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Linear Regression ◽  
Survey Data ◽  
Organizational Structures ◽  
Bedside Teaching ◽  
Regression Analyses ◽  
Negative Perception ◽  
Data Analyses ◽  
Main Target ◽  
Relevant Factors

Abstract Background Students’ ratings of bedside teaching courses are difficult to evaluate and to comprehend. Validated systematic analyses of influences on students’ perception and valuation of bedside teaching can serve as the basis for targeted improvements. Methods Six hundred seventy-two observations were conducted in different surgical departments. Survey items covered the categories teacher’s performance, student’s self-perception and organizational structures. Relevant factors for the student overall rating were identified by multivariable linear regression after exclusion of variable correlations > 0.500. The main target for intervention was identified by the 15% worst overall ratings via multivariable logistic regression. Results According to the students the success of bedside teaching depended on their active participation and the teacher’s explanations of pathophysiology. Further items are both relevant to the overall rating and a possible negative perception of the session. In comparison, negative perception of courses (worst 15%) is influenced by fewer variables than overall rating. Variables that appear in both calculations show slight differences in their weighing for their respective endpoints. Conclusion Relevant factors for overall rating and negative perception in bedside teaching can be identified by regression analyses of survey data. Analyses provide the basis for targeted improvement.

scholarly journals Relation between body composition and severe diarrhea in patients treated with preoperative chemoradiation with capecitabine for rectal cancer: a single-centre cohort study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
J. M. van Rees ◽  
W. Hartman ◽  
J. J. M. E. Nuyttens ◽  
E. Oomen-de Hoop ◽  
J. L. A. van Vugt ◽  
...  
Keyword(s):  
Risk Factors ◽  
Rectal Cancer ◽  
Body Composition ◽  
Logistic Regression ◽  
Cohort Study ◽  
Preoperative Chemoradiation ◽  
Regression Analyses ◽  
Single Centre ◽  
Severe Diarrhea ◽  
The Impact

Abstract Background Chemoradiation with capecitabine followed by surgery is standard care for locally advanced rectal cancer (LARC). Severe diarrhea is considered a dose-limiting toxicity of adding capecitabine to radiation therapy. The aim of this study was to describe the risk factors and the impact of body composition on severe diarrhea in patients with LARC during preoperative chemoradiation with capecitabine. Methods A single centre retrospective cohort study was conducted in a tertiary referral centre. All patients treated with preoperative chemoradiation with capecitabine for LARC from 2009 to 2015 were included. Patients with locally recurrent rectal cancer who received chemoradiation for the first time were included as well. Logistic regression analyses were performed to identify risk factors for severe diarrhea. Results A total of 746 patients were included. Median age was 64 years (interquartile range 57–71) and 477 patients (64%) were male. All patients received a radiation dosage of 25 × 2 Gy during a period of five weeks with either concomitant capecitabine administered on radiation days or continuously during radiotherapy. In this cohort 70 patients (9%) developed severe diarrhea. In multivariable logistic regression analyses female sex (OR: 4.42, 95% CI 2.54–7.91) and age ≥ 65 (OR: 3.25, 95% CI 1.85–5.87) were the only risk factors for severe diarrhea. Conclusions Female patients and patients aged sixty-five or older had an increased risk of developing severe diarrhea during preoperative chemoradiation therapy with capecitabine. No relation was found between body composition and severe diarrhea.

scholarly journals Association Between Diagnosis Code Expansion and Changes in 30‐Day Risk‐Adjusted Outcomes for Cardiovascular Diseases

2021 ◽  
Author(s):  
Lauren Gilstrap ◽  
Rishi K. Wadhera ◽  
Andrea M. Austin ◽  
Stephen Kearing ◽  
Karen E. Joynt Maddox ◽  
...  
Keyword(s):  
Logistic Regression ◽  
International Classification Of Diseases ◽  
Fee For Service ◽  
Readmission Rates ◽  
Difference In Differences ◽  
Diagnosis Codes ◽  
Classification Of Diseases ◽  
Changes In Risk ◽  
The Impact

BACKGROUND In January 2011, Centers for Medicare and Medicaid Services expanded the number of inpatient diagnosis codes from 9 to 25, which may influence comorbidity counts and risk‐adjusted outcome rates for studies spanning January 2011. This study examines the association between (1) limiting versus not limiting diagnosis codes after 2011, (2) using inpatient‐only versus inpatient and outpatient data, and (3) using logistic regression versus the Centers for Medicare and Medicaid Services risk‐standardized methodology and changes in risk‐adjusted outcomes. METHODS AND RESULTS Using 100% Medicare inpatient and outpatient files between January 2009 and December 2013, we created 2 cohorts of fee‐for‐service beneficiaries aged ≥65 years. The acute myocardial infarction cohort and the heart failure cohort had 578 728 and 1 595 069 hospitalizations, respectively. We calculate comorbidities using (1) inpatient‐only limited diagnoses, (2) inpatient‐only unlimited diagnoses, (3) inpatient and outpatient limited diagnoses, and (4) inpatient and outpatient unlimited diagnoses. Across both cohorts, International Classification of Diseases, Ninth Revision ( ICD‐9 ) diagnoses and hierarchical condition categories increased after 2011. When outpatient data were included, there were no significant differences in risk‐adjusted readmission rates using logistic regression or the Centers for Medicare and Medicaid Services risk standardization. A difference‐in‐differences analysis of risk‐adjusted readmission trends before versus after 2011 found that no significant differences between limited and unlimited models for either cohort. CONCLUSIONS For studies that span 2011, researchers should consider limiting the number of inpatient diagnosis codes to 9 and/or including outpatient data to minimize the impact of the code expansion on comorbidity counts. However, the 2011 code expansion does not appear to significantly affect risk‐adjusted readmission rate estimates using either logistic or risk‐standardization models or when using or excluding outpatient data.

scholarly journals Bismarck’s Health Insurance and the Mortality Decline

2019 ◽  
Vol 18 (5) ◽  
pp. 2561-2607 ◽  
Author(s):  
Stefan Bauernschuster ◽  
Anastasia Driva ◽  
Erik Hornung
Keyword(s):  
Health Insurance ◽  
Fixed Effects ◽  
Natural Experiment ◽  
Social Health Insurance ◽  
Insurance Fund ◽  
Difference In Differences ◽  
German Empire ◽  
Compulsory Health Insurance ◽  
The Impact ◽  
Significant Mortality

Abstract We study the impact of social health insurance on mortality. Using the introduction of compulsory health insurance in the German Empire in 1884 as a natural experiment, we estimate difference-in-differences and regional fixed effects models exploiting variation in eligibility for insurance across occupations. Our findings suggest that Bismarck’s health insurance generated a significant mortality reduction. Despite the absence of antibiotics and most vaccines, we find the results to be largely driven by a decline of deaths from infectious diseases. Further evidence suggests that statutory access to well-trained doctors was an elementary channel. This finding may be explained by insurance fund physicians transmitting new knowledge on infectious disease prevention.

scholarly journals Adolescent motherhood in Bangladesh: Evidence from 2007 BDHS data

2012 ◽  
Vol 39 (1-2) ◽  
pp. 63 ◽  
Author(s):  
S.M. Mostafa Kamal
Keyword(s):  
Logistic Regression ◽  
Survey Data ◽  
Contraceptive Method ◽  
Married Women ◽  
Multiple Logistic Regression ◽  
Regression Analyses ◽  
Factors Affecting ◽  
Adolescent Motherhood ◽  
Health Survey Data ◽  
First Time

This paper examines the factors affecting adolescent motherhood in Bangladesh using the 2007 Bangladesh Demographic and Health Survey data. Overall, 69.3 per cent of the married adolescents began childbearing. Among them 56.4 per cent were already mothers and 12.9per cent were pregnant for the first time. Of the adult married women age 20–49, 62.1 per cent initiated childbearing before age 19. The multiple logistic regression analyses revealed that women’s education, husband’s education, place of residence, ever use of contraceptive method, religion, wealth and region are important determinants of adolescent motherhood in Bangladesh.

Extent of lymph node resection and effect on pancreatic cancer overall survival.

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 682-682
Author(s):  
Brian Cox ◽  
Nicholas Manguso ◽  
Humair Quadri ◽  
Jessica Crystal ◽  
Katelyn Mae Atkins ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Logistic Regression ◽  
Lymph Node ◽  
Cox Regression ◽  
Survival Curve ◽  
Regression Analyses ◽  
Kaplan Meier ◽  
The Impact ◽  
Meier Survival Curve

682 Background: Lymph node (LN) metastases affect overall survival (OS) in pancreatic cancer (PC). However, a LN sampling threshold does not exist. We examined the impact of nodal sampling on overall survival (OS). Methods: Patients with Stage I-III PC ≥55 years old who underwent curative resection from 2004-2016 were identified from the National Cancer Database (NCDB). After adjusting for age, gender, grade, stage, and Charlson-Deyo score, multiple binomial logistic regression analyses assessed the impact of the LN ratio (LNR) on OS. LNR was defined as the number of positive LN over the number of LN examined. Regression analyses, a Cox-Regression, and a Kaplan-Meier survival curve assessed how many LN should be sampled. Results: A total of 13,673 patients, median age 69 years (55-90), were included. Most were Caucasian (86.6%) males with Charlson-Deyo scores ≤ 1 (90.3%) and moderately to poorly differentiated PC (90.1%). Median number of LN examined was 15 (1-75) with a median of 1 positive LN (0-35). As expected, increased number of positive LNs was associated with reduced OS, p < 0.001. After data normalization, an increasing LNR was associated with a 12-fold likelihood of death [OR: 11.9, p < 0.001 (CI 6.0, 23.7)]. Subsequent regression models established evaluation of ≥ 16 LNs as the greatest predictor of OS. A regression model evaluating < or ≥ 16 lymph nodes was performed to ascertain the effects of age, gender, ethnicity, grade, stage, and LN examined on OS. The logistic regression model correctly classified 74.5% of cases with a specificity of 99.6% (p < 0.001). Examination of < 16 LN, Caucasian race, grade, stage, and higher Charlson-Deyo scores were significantly associated with decreased OS. If ≥ 16 LNs were examined, patients had a 1.5-fold likelihood of better OS, p < 0.001 (CI 1.4, 1.6). An adjusted Cox Regression showed increased HR of 1.2, p < 0.001 (CI 1.1, 1.2) and an unadjusted Kaplan Meier survival curve predicted ≥ 16 LN examined are associated with an increase in OS of 2.8 months [log-rank: 32.0, p < 0.001]. Conclusions: Patients undergoing curative intent resection for PC should have adequate nodal sampling. Stratification of patients by LNR may provide useful information of OS. Examination of ≥ 16 LNs impacts OS in patients with Stage I-III PC.

scholarly journals The impact of COVID-19 pandemic on rheumatology practice and rheumatologists: a cross-sectional multinational study

2020 ◽  
Author(s):  
Nelly Ziade ◽  
Ihsane Hmamouchi ◽  
Lina el Kibbi ◽  
Nizar Abdulateef ◽  
Hussein Halabi ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Unmet Needs ◽  
Web Survey ◽  
Multinational Study ◽  
Regression Analyses ◽  
Cross Sectional ◽  
Arab League ◽  
The Impact ◽  
E Mail ◽  
Rheumatology Practice

Abstract ObjectiveTo evaluate the impact of the COVID-19 pandemic on rheumatology practice and on the rheumatologists themselves, and to develop suggestions to improve the practice.MethodsA cross-sectional web survey was designed by members of the Arab League of Associations for Rheumatology (ArLAR), validated by its scientific committee and disseminated through e-mail and social media. It included close-ended questions about the impact of the pandemic on the activities (in percentage, where 100% corresponds to complete suspension), and open-ended questions about unmet needs. Univariate and multivariable logistic regression analyses were used to evaluate the predictors of impact. Suggestions were developed to improve practice.ResultsA total of 858 rheumatologists were included in the analysis (27.3% of registered), 37% were 35-44 years-old, 60% were females and 48% worked in the private sector. The impact of COVID-19 was a decrease of 69% in hospitalizations, 65% in outpatient clinic, 56% in infusion centers and 43% in income. It was associated with the region (highest in the Gulf), the use of telemedicine, the impact on income and the practice sector (lowest in private). Telemedicine was mostly based on traditional telephone contacts and e-mails and reimbursed in 12%. Fifteen rheumatologists (1.8%) were infected and 156 cases of COVID-19 among patients were reported, of whom 22% died. The top-cited unmet needs were: access to drugs and a telemedicine platform.Conclusion The negative COVID-19 pandemic on rheumatology practice may compromise rheumatic diseases control. Better access to drugs and providing telemedicine platforms are recommended to improve the practice.

scholarly journals Stillbirth Risk during the 1918 Influenza Pandemic in Arizona, USA

Epidemiologia ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 23-30
Author(s):  
Smriti Khare ◽  
Sushma Dahal ◽  
Ruiyan Luo ◽  
Richard Rothenberg ◽  
Kenji Mizumoto ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Retrospective Study ◽  
Pandemic Influenza ◽  
Influenza Pandemic ◽  
Regression Analyses ◽  
Maricopa County ◽  
Mother’S Age ◽  
1918 Influenza ◽  
Birth Records ◽  
The Impact

The 1918 influenza pandemic, the deadliest pandemic on record, affected approximately 1/3rd of the population worldwide. The impact of this pandemic on stillbirth risk has not been studied in depth. In this study, we assessed the stillbirth risk during the 1918 influenza pandemic in Arizona, USA. We carried out a retrospective study using 21,334 birth records for Maricopa County, Arizona, for the period 1915–1925. We conducted logistic regression analyses to assess the effect of that pandemic on stillbirth risk. Though we did not find a statistically significant impact on stillbirth risk during the pandemic, there was a higher risk of stillbirth in July 1919 (42 stillbirths/1000 births), 9 months after the peak pandemic mortality, and a stillbirth risk of 1.42 (95% CI: 1.17, 1.72) in women ≥35 years compared to the women aged <35 years. The risk of stillbirth was lowest if the mother’s age was approximately 26 years at the time of birth. We also report peaks in stillbirth risk 9–10 months after the peak pandemic mortality. Our findings add to our current understanding of the link between pandemic influenza and stillbirth risk.

scholarly journals Do minimum wages improve self-rated health? Evidence from a natural experiment

2021 ◽  
Author(s):  
Lucas Hafner ◽  
Benjamin Lochner
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Minimum Wage ◽  
Survey Data ◽  
Natural Experiment ◽  
Time Pressure ◽  
Working Hours ◽  
Difference In Differences ◽  
Self Rated Health ◽  
Confounding Variables

AbstractWe analyze whether the introduction of the general minimum wage in Germany in 2015 had an effect on workers’ self-rated health. To this end, we use survey data linked to administrative employment records and apply difference-in-differences regressions combined with propensity score matching. This approach enables us to control for a vast set of potential confounding variables. We find a health improving effect among the individuals who were most likely to be affected by the reform. Our results indicate that workers’ improved satisfaction with pay, their reduced working hours, and a reduction in time pressure at work may drive this result.

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