To What Extent Do Age, Period, and Cohort Patterns Account for Time Trends and Social Inequalities in Smoking?

2010 ◽  
Vol 56 (5) ◽  
pp. 361-371 ◽  
Author(s):  
Daniela Piontek ◽  
Ludwig Kraus ◽  
Stefanie Müller ◽  
Alexander Pabst
Keyword(s):  
Random Effects ◽  
Time Trends ◽  
Fixed Effects ◽  
Social Inequalities ◽  
Smoking Behavior ◽  
Epidemiological Survey ◽  
Control Measures ◽  
Cohort Effects ◽  
Social Disparities ◽  
Random Effects Models

Aims: This paper evaluates nonconfounded and independent age, period, and cohort effects on time trends and social disparities in smoking behavior. Methods: Data from nine waves of the German Epidemiological Survey of Substance Abuse (ESA) conducted between 1980 and 2009 were used. A total of N = 73,782 individuals aged 18 and older were included in the analyses. Using cross-classified random-effects models, fixed effects of age (level 1) as well as random effects of periods and cohorts (level 2) on 30-day smoking prevalence and average number of cigarettes per day were estimated. Analyses were stratified by socioeconomic status (SES). Results: Independent of SES, positive and curvilinear age effects emerged. Prevalence and amount of smoking declined sharply over time and revealed an inversion of the social gradient in 2003. This was due to a stronger decrease of smoking in the highest SES group compared to the other groups. Cohort effects were nonlinear and inconsistent. Conclusion: The emergence of increasing social disparities in smoking implies the need to specifically address the situation of low-SES groups when developing tobacco control measures.

scholarly journals An Estimate of Global Anthrax Prevalence in Livestock: A Meta-analysis

2021 ◽  
pp. 1263-1271
Author(s):  
Bylaiah Sushma ◽  
Seema Shedole ◽  
Kuralayanapalya Puttahonnappa Suresh ◽  
Gowda Leena ◽  
Sharanagouda S. Patil ◽  
...  
Keyword(s):  
High Risk ◽  
Random Effects ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Economic Loss ◽  
Control Measures ◽  
Fixed Effects Model ◽  
Random Effects Models ◽  
Online Databases ◽  
Pooled Prevalence

Background and Aim: Anthrax, caused by the soil-borne spore-forming bacteria called Bacillus anthracis, is a zoonotic disease that persists worldwide in livestock and wildlife and infects humans. It is a great hazard to livestock; henceforth, evaluating the global concerns about the disease occurrence in livestock is essential. This study was conducted to estimate the global prevalence of anthrax and predict high-risk regions, which could be an input to veterinarians to take necessary steps to control and avoid the disease. Materials and Methods: A literature review was performed using online databases, namely, PubMed, Google Scholar, Scopus, Biomed Central, and Science Direct, to extract relevant publications worldwide between 1992 and 2020. Initially, 174 articles were selected, and after scrutinizing, 24 articles reporting the prevalence of anthrax were found to be adequate for the final meta-analysis. The statistical study was accompanied by employing fixed effects and random effects models using R. Results: The pooled prevalence of anthrax globally was 28% (95% confidence interval, 26-30%) from 2452 samples through the fixed effects model. Continent-wise subgroup analysis through the random effects model revealed that the pooled prevalence of anthrax was highest in Africa (29%) and least in North America (21%). Conclusion: In these publications, anthrax causes economic loss to farmers and, thus, to the world. Hence, controlling anthrax infections in high-risk regions are essential by implementing appropriate control measures to decrease the effect of the disease, thereby reducing economic loss.

scholarly journals Association of bisphenol A with puberty timing: a meta-analysis

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Hui Meng ◽  
Yunping Zhou ◽  
Yunxia Jiang
Keyword(s):  
Bisphenol A ◽  
Confidence Intervals ◽  
Random Effects ◽  
Strong Correlation ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Random Effects Models ◽  
Study Heterogeneity ◽  
The Relationship ◽  
Prevalence Ratios

AbstractObjectivesThe results of existing studies on bisphenol A (BPA) and puberty timing did not reach a consensus. Thereby we performed this meta-analytic study to explore the association between BPA exposure in urine and puberty timing.MethodsMeta-analysis of the pooled odds ratios (OR), prevalence ratios (PR) or hazards ratios (HR) with 95% confidence intervals (CI) were calculated and estimated using fixed-effects or random-effects models based on between-study heterogeneity.ResultsA total of 10 studies involving 5621 subjects were finally included. The meta-analysis showed that BPA exposure was weakly associated with thelarche (PR: 0.96, 95% CI: 0.93–0.99), while no association was found between BPA exposure and menarche (HR: 0.99, 95% CI: 0.89–1.12; OR: 1.02, 95% CI: 0.73–1.43), and pubarche (OR: 1.00, 95% CI: 0.79–1.26; PR: 1.00, 95% CI: 0.95–1.05).ConclusionsThere was no strong correlation between BPA exposure and puberty timing. Further studies with large sample sizes are needed to verify the relationship between BPA and puberty timing.

scholarly journals Metaanalysis of the relationship between violent video game play and physical aggression over time

2018 ◽  
Vol 115 (40) ◽  
pp. 9882-9888 ◽  
Author(s):  
Anna T. Prescott ◽  
James D. Sargent ◽  
Jay G. Hull
Keyword(s):  
Random Effects ◽  
Video Game ◽  
Physical Aggression ◽  
Fixed Effects ◽  
Time Lags ◽  
Random Effects Models ◽  
Video Game Play ◽  
Game Violence ◽  
The Relationship ◽  
Significant Moderator

To clarify and quantify the influence of video game violence (VGV) on aggressive behavior, we conducted a metaanalysis of all prospective studies to date that assessed the relation between exposure to VGV and subsequent overt physical aggression. The search strategy identified 24 studies with over 17,000 participants and time lags ranging from 3 months to 4 years. The samples comprised various nationalities and ethnicities with mean ages from 9 to 19 years. For each study we obtained the standardized regression coefficient for the prospective effect of VGV on subsequent aggression, controlling for baseline aggression. VGV was related to aggression using both fixed [β = 0.113, 95% CI = (0.098, 0.128)] and random effects models [β = 0.106 (0.078, 0.134)]. When all available covariates were included, the size of the effect remained significant for both models [β = 0.080 (0.065, 0.094) and β = 0.078 (0.053, 0.102), respectively]. No evidence of publication bias was found. Ethnicity was a statistically significant moderator for the fixed-effects models (P≤ 0.011) but not for the random-effects models. Stratified analyses indicated the effect was largest among Whites, intermediate among Asians, and nonsignificant among Hispanics. Discussion focuses on the implications of such findings for current debates regarding the effects of violent video games on physical aggression.

scholarly journals Prognostic Role of Matrix Metalloproteinases in Cervical Cancer: A Meta-Analysis

2021 ◽  
Vol 28 ◽  
pp. 107327482110337
Author(s):  
Weiwei Chen ◽  
Shenjiao Huang ◽  
Kun Shi ◽  
Lisha Yi ◽  
Yaqiong Liu ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Matrix Metalloproteinases ◽  
Random Effects ◽  
Fixed Effects ◽  
Prognostic Value ◽  
Meta Analysis ◽  
Free Survival ◽  
Random Effects Models ◽  
Registration Number ◽  
Meta Analyses

Objective Studies have published the association between the expression of matrix metalloproteinases (MMPs) and the outcome of cervical cancer. However, the prognostic value in cervical cancer remains controversial. This meta-analysis was conducted to evaluate the prognostic functions of MMP expression in cervical cancer. Methods A comprehensive search of PubMed, Embase, and Web of Science databases was conducted to identify the eligible studies according to defined selection and excluding criteria and analyzed according to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Fixed and random effects models were evaluated through the hazard ratios (HRs) and 95% confidence intervals (CIs) to estimate the overall survival (OS), recurrence-free survival (RFS), and progress-free survival (PFS). Results A total of 18 eligible studies including 1967 patients were analyzed for prognostic value. Totally 16 selected studies including 21 tests were relevant to the cervical cancer OS, 4 studies focused on RFS, and 1 study on PFS. The combined pooled HRs and 95% CIs of OS were calculated with random-effects models (HR = 1.64, 95% CI = 1.01–2.65, P = .000). In the subgroup analysis for OS, there was no heterogeneity in MMP-2 (I2 = .0%, P = .880), MMP-1 (I2 = .0%, P = .587), and MMP-14 (I2 = 28.3%, P = .248). In MMP-7 and MMP-9, the heterogeneities were obvious (I2 = 99.2% ( P = .000) and I2 = 77.9% ( P = .000), respectively). The pooled HRs and 95% CIs of RFS were calculated with fixed-effects models (HR = 2.22, 95% CI = 1.38–3.58, P = .001) and PFS (HR = 2.29, 95% CI = 1.14–4.58, P = .035). Conclusions The results indicated that MMP overexpression was associated with shorter OS and RFS in cervical cancer patients. It suggested that MMP overexpression might be a poor prognostic marker in cervical cancer. Research Registry Registration Number: reviewregistry 1159.

scholarly journals Comparison of Competing Approaches to Analyzing Cross-Classified Data: Random Effects Models, Ordinary Least Squares, or Fixed Effects with Cluster Robust Standard Errors

2021 ◽  
Author(s):  
Young Ri Lee ◽  
James E Pustejovsky
Keyword(s):  
Least Squares ◽  
Random Effects ◽  
Fixed Effects ◽  
Good Alternative ◽  
Ordinary Least Squares ◽  
Alternative Methods ◽  
Least Squares Regression ◽  
Monte Carlo Simulation Study ◽  
Random Effects Models ◽  
Fixed Effects Regression

Cross-classified random effects modeling (CCREM) is a common approach for analyzing cross-classified data in education. However, when the focus of a study is on the regression coefficients at level one rather than on the random effects, ordinary least squares regression with cluster robust variance estimators (OLS-CRVE) or fixed effects regression with CRVE (FE-CRVE) could be appropriate approaches. These alternative methods may be advantageous because they rely on weaker assumptions than what is required by CCREM. We conducted a Monte Carlo Simulation study to compare the performance of CCREM, OLS-CRVE, and FE-CRVE in models with crossed random effects, including conditions where homoscedasticity assumptions and exogeneity assumptions held and conditions where they were violated. We found that CCREM performed the best when its assumptions are all met. However, when homoscedasticity assumptions are violated, OLS-CRVE and FE-CRVE provided similar or better performance than CCREM. FE-CRVE showed the best performance when the exogeneity assumption is violated. Thus, we recommend two-way FE-CRVE as a good alternative to CCREM, particularly if the homoscedasticity or exogeneity assumptions of the CCREM might be in doubt.

Age, Period, and Cohort Effects on Time Trends in Alcohol Consumption in the German Adult Population

2010 ◽  
Vol 56 (5) ◽  
pp. 349-359 ◽  
Author(s):  
Alexander Pabst ◽  
Ludwig Kraus ◽  
Daniela Piontek ◽  
Stefanie Mueller
Keyword(s):  
Alcohol Consumption ◽  
Time Trends ◽  
Adult Population ◽  
Heavy Drinking ◽  
Epidemiological Survey ◽  
Alcohol Policy ◽  
Cohort Effects ◽  
Drinking Patterns ◽  
Age Variations ◽  
Cohort Groups

Aims: To estimate independent age, period, and cohort effects on time trends in alcohol volume and episodic heavy drinking in Germany. Method: Data from six waves of the German Epidemiological Survey of Substance Abuse (ESA) between 1995 and 2009 were used. The analytical sample comprised n = 34,542 individuals aged 18 to 64 years with at least one drinking occasion in the last 30 days. Alcohol volume was derived from beverage-specific quantity frequency questions. Episodic heavy drinking was specified as the number of days with five or more alcoholic drinks at a single occasion. Results: On average across age and cohort groups, alcohol consumption has considerably declined over the last 15 years. Cohort effects indicate a decline in alcohol volume from the 1940s to the 1970s birth cohort groups and a steep increase in younger cohorts. Moreover, cohorts born after 1980 were found to drink more often to intoxication than older cohorts. Age variations in trends were rather small compared to period and cohort effects. Conclusions: Despite the steady declining trend in alcohol consumption in the German general population, there is a tendency toward riskier drinking patterns among the youngest cohorts. This underlines the need for alcohol policy measures.

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