scholarly journals Reconsideration of cohort study and case-control study

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Ma Junling
PLoS ONE ◽  
2015 ◽  
Vol 10 (3) ◽  
pp. e0119349 ◽  
Author(s):  
Ester M. M. Klaassen ◽  
John Penders ◽  
Quirijn Jöbsis ◽  
Kim D. G. van de Kant ◽  
Carel Thijs ◽  
...  

2014 ◽  
Vol 143 (3) ◽  
pp. 515-521 ◽  
Author(s):  
J. H. PARK ◽  
H. S. JEONG ◽  
J. S. LEE ◽  
S. W. LEE ◽  
Y. H. CHOI ◽  
...  

SUMMARYIn February 2012, an outbreak of gastroenteritis was reported in school A; a successive outbreak was reported at school B. A retrospective cohort study conducted in school A showed that seasoned green seaweed with radishes (relative risk 7·9, 95% confidence interval 1·1–56·2) was significantly associated with illness. Similarly, a case-control study of students at school B showed that cases were 5·1 (95% confidence interval 1·1–24·8) times more likely to have eaten seasoned green seaweed with pears. Multiple norovirus genotypes were detected in samples from students in schools A and B. Norovirus GII.6 isolated from schools A and B were phylogenetically indistinguishable. Green seaweed was supplied by company X, and norovirus GII.4 was isolated from samples of green seaweed. Green seaweed was assumed to be linked to these outbreaks. To our knowledge, this is the first reported norovirus outbreak associated with green seaweed.


1996 ◽  
Vol 17 (4) ◽  
pp. 249-255
Author(s):  
Jonathan Freeman

AbstractWe provide guidance for new practitioners in the vocabulary of modern epidemiology and the application of quantitative methods. Most hospital epidemiology involves surveillance (observational) data that were not part of a planned experiment, so the rubric and logic of controlled experimental studies cannot be applied. Forms of incidence and prevalence often are confused. The names “cohort study” and “case-control study” are unfortunate, as cohort studies rarely involve cohorts and case-control studies allow no active control by the investigator. Either type of study can be prospective or retrospective. Results of studies with discrete outcomes (infected or not, lived or died) often are represented best by a form of the risk ratio with 95% confidence intervals. The potential distorting effects of selection bias, misclassification, and confounding need to be considered.


2021 ◽  
Author(s):  
Bahman Cheraghian ◽  
Nader Saki ◽  
Zahra Rahimi ◽  
Sara Sarvandian ◽  
Seyed Jalal Hashemi ◽  
...  

Abstract Background: Age at menarche (AAM) affects women's health outcomes and could be a risk factor for some diseases such as Metabolic Syndrome (MetS). We assessed the association between age at menarche and metabolic syndrome components (obesity, hypertension, type 2 diabetes and cardiovascular disease) in women aged 35 to 70 years in Hoveyzeh, southwest Iran.Methods: This is a case-control study conducted on 5830 women 35 to 70 years in Hoveyzeh cohort study (HCS), a part of the PERSIAN cohort study, between 2016 to 2018. The case group were women with MetS while the controls were women without MetS. Metabolic syndrome is determined based on standard NCEP-ATP III criteria. Demographic, socioeconomic and reproductive history data were gathered face to face by trained interviews. Also, lab, anthropometrics and blood pressure measurements were assayed for participants. Multiple Logistic Regression was used to estimate the association between age at menarche and metabolic syndrome, with adjustment for potential confounding variables.Results: The overall mean age at menarche was 12.60 ± 1.76 years old. Urban and rural women differed in their age at menarche (at age 12.58±1.71 and 12.63±1.83 years, respectively). Comparison of the four menarche age groups (≤10, 11-12, 13-14, 15-16 years) was statistically different showed between age at menarche and MetS. The odds of having metabolic syndrome for groups with menarche age of 13-14 years and 16-15 years, compared to women with a menstrual age ≤10 years, decreased by 21% and 20%, respectively. Conclusion: The present study showed the effect of age at menarche on odds of having MetS in women 35-70 years.


2021 ◽  
Author(s):  
Balachandran Kumarendran ◽  
Michael W O'Reilly ◽  
Anuradhaa Subramanian ◽  
Dana Šumilo ◽  
Konstantinos Toulis ◽  
...  

<b>Objectives: </b>Irregular menstrual cycles are associated with increased cardiovascular mortality. Polycystic ovary syndrome (PCOS) is characterized by androgen excess and irregular menses; androgens are drivers of increased metabolic risk in women with PCOS. Combined oral contraceptives (COCPs) are used in PCOS both for cycle regulation and to reduce the biologically active androgen fraction. We examined COCP use and risk of dysglycemia (pre-diabetes and type 2 diabetes) in women with PCOS. <p><b>Research Design and Methods: </b>Utilizing a large UK primary care database (The Health Improvement Network, THIN; 3.7 million patients from 787 practices), we carried out a retrospective population-based cohort study to determine dysglycemia risk (64,051 women with PCOS, 123,545 matched controls), as well as a nested pharmaco-epidemiological case-control study to investigate COCP use in relation to dysglycemia risk (2407 women with PCOS with [=cases] and without [=controls] a diagnosis of dysglycemia during follow-up).<b> </b>Cox models were used to estimate the unadjusted and adjusted hazard ratio and conditional logistic regression was used to obtain adjusted odds ratios (aORs). </p> <p><b>Results: </b>The adjusted hazard ratio for dysglycemia in women with PCOS was 1.87 (95% CI 1.78-1.97, p<0.001; adjustment for age, social deprivation, BMI, ethnicity, and smoking), with increased rates of dysglycemia in all BMI subgroups. Women with PCOS and COCP use had a reduced dysglycemia risk (aOR 0.72, 95% CI 0.59 to 0.87).</p> <p><b>Conclusions: </b>In this study limited by its retrospective nature and the use of routinely collected electronic general practice record data, which does not allow to exclude the impact of prescription-by-indication bias, women<b> </b>with PCOS exposed to COCPs had a reduced risk of dysglycemia across all BMI subgroups. Future prospective studies should be considered to further understand these observations and potential causality. </p>


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