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Critical Appraisal Assignment

   

Added on  2020-05-16

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Running head: CRITICAL APPRAISALCritical Appraisal of 2 articles using the CASP toolName of the StudentName of the UniversityAuthor Note

1CRITICAL APPRAISALIntroductionCritical appraisal refers to the systematic process that identifies strengths and weaknessesof an article for evaluating its validity and usefulness of the research findings (12). This reportwill critically analyse two articles, using the CASP tool for appraisal. Questions in the CASPtool will facilitate determination of the relevance and trustworthiness of the aforementionedarticles.Article 1Juntarawijit C, Juntarawijit Y. Association between diabetes and pesticides: a case-control study among Thai farmers. Environmental Health and Preventive Medicine. 2018January; 23:3.The issue addressed in the study was quite relevant to the context of the research.Diabetes is a chronic health disorder prevalent globally with an incidence of 1 in 3 adults (5).According to research studies, a dramatic increase has been observed in the number of diabeticpatients in Thailand from 2009 to 2014 (17). Furthermore, there are several evidences thatsuggest correlation between exposure to pesticides and incidence of type 2 and gestationaldiabetes (8). Moreover, the sudden increase in the application of pesticides in Thailandestablishes selection of the issue as a correct procedure (19).An appropriate method was used to address the research question that can be validatedby the fact that the outcomes were beneficial for the target population. The research methodapplied to address the question suggested that an overexposure to pesticides is responsible forincreasing the susceptibility to diabetes among farmers. Consistency with previous findingssuggests that the method was correct (3).

2CRITICAL APPRAISALLack of adequate information on association between diabetes and pesticide in Thailandmight create negative impacts on both the case and the control by providing inaccurate resultsduring analysis of the responses. Apart from mentioning that the cases were diagnosed withdiabetes, they were not defined in a precise way. The time frame of pesticide exposure andnumber of cases were not sufficient. Reliable system for selecting the cases was based ondiagnosis of diabetes. There was no specialty of the sample and no power calculation. However,the sample represented a defined population of diabetic rice farmers in Thailand. However, theselection of participants for the study was based on prevalence of diabetes and pesticideexposure, collected from hospital data and structured questionnaire respectively,and a reliablesystem was used (randomisation). Thus, the cases not recruited in an acceptable way.Although the controls represented rice farmers without diabetes, which represented thepopulation, their specialty was that they belonged to same gender and age that increasedlikelihood of pesticide exposure, due to similar environmental factors. They were matched butmore in number than the sample. The authors failed to provide information on the response rate.Thus, the controls were not selected in an acceptable way.Structured questionnaires, in addition to similar measurement in the sample and controlwere used. Temporal relation was correct as pesticide exposure preceded diabetes. However,there was recall bias due to collection of information based on questionnaire that might affect theresponses owing to differences in recall ability of the participants.Moreover, the researchers didnot blind the participants to the study, which might affect their responses and give misleadingresults (6).Construct validity was also not measured. Thus, the measures did not reflect true towhat was claimed.

3CRITICAL APPRAISALThe confounding factors that were taken into account include gender, BMI, cigarettesmoking, alcohol consumption, occupation, family history and age. The researchers had used logistic regression to analyse the adjusted odds ratio showingassociation between exposure to pesticide and its outcome (diabetes). Thus, use of regressionanalysis help in estimating the correlation between the independent variable and outcome,while holding other variables as constant (10).Statistically significant association between rodenticide exposure and diabetes prevalencewas established by the findings (OR = 1.35; 95%CI 1.04-1.76). Presence of odds ratio > 1 for theuse of fungicides (OR = 2.08; 95%CI 1.03–4.20), organophosphate (OR = 2.22; 95%CI 1.17–4.19), carbamate (OR = 1.50; 95%CI 1.02–2.19), and organoclorine (OR = 1.40; 95%CI 1.01–1.95) establishes strong correlation of exposure to outcome. Thus, adjustment of the resultsusing regression has made a big difference.Low p-values for BMI, occupation, smoking, alcohol consumption, and family history ofdiabetes signifies strong evidence against for the association between pesticide exposure anddiabetes incidence (16).Presence of 95% CI for all findings suggests that sampling the samepopulation numerous times will result in similar results and sound statistical findings. Although high odds ratio suggest positive association between exposure and the outcome,it is essential to remove selection bias and recall bias and use a larger sample size forconfirming and believing the results.The findings can be applied in local population based on the fact that about 2 milliontones of pesticides are used every year, worldwide (15). Owing to the high exposure to pesticides

4CRITICAL APPRAISALby people and the high prevalence of diabetes patients, worldwide, the results can prove effectivein the local population.Results show consistency with previous findings that correlated type 2 and gestationaldiabetes with pesticide exposure. Article 2Kuo SH, Hung WT, Tang PL, Huang WC, Yang JS, Lin HC, Mar GY, Chang HT, LiuCP. Impact of hepatitis C virus infection on long-term mortality after acute myocardialinfarction: a nationwide population-based, propensity-matched cohort study in Taiwan. BMJopen. 2018 January; 8:e017412.The issue addressed by the authors was relevant owing to the high mortality rates due toacute myocardial infarction (AMI) in Taiwan. Moreover, presence of previously conductedcohort studies and systematic review that correlated risks of myocardial infarction with chronicinfection of hepatitis C also establishes the fact that the authors addressed a clearly focused issue(4) (13).The cohort was recruited in an appropriate way owing to the fact that of the 186112patients diagnosed with AMI, 4666 patients were identified with HCV infection. Moreover, theresearchers displayed. Thus, the cohort represented the defined population. The authors used appropriate methodsto classify the subjects into particular groups.One-to-one matching among all participants regarding some factor such as, hypertension, age,sex, diabetes mellitus, peripheral vascular disease and heart failure demonstrates correct

5CRITICAL APPRAISALmethodology in minimizing bias. Moreover, the NHIRD data on AMI had been validated byprevious studies (2).The subjects and the assessors were not blinded to the study, which might contribute tobias in the outcomes. Although the measures reflected the expected outcomes, lack of adequateinformation on minimizing bias makes it difficult to tell if all the outcomes were accuratelymeasured.Although the database did not include information on potential confounding factors, theresearchers used a propensity score matching procedure for controlling the essential confoundingvariables such as, age, sex, hypertension, previous stroke, peripheral vascular disease, anddyslipidemia, which might affect the outcomes among AMI patients. Thus, all importantconfounding factors were identified.The authors had accurately analysed the results using a Cox proportional hazardregression method. This helped in adjusting the confounding factors that were taken into account(14). Furthermore, use of a propensity score matching method also helped in minimizing thefactors or variables. Thus, all confounding factors were taken into account in the researchdesign.The follow-up of the subjects was complete owing to the fact that all patients werefollowed for a time period of 12 years, until the outcomes of the disease was accuratelyobserved. The fact that the authors did not mention loss of patients from the groups, it can beconsidered that the study began and ended with similar number of patients. The fact that the study evaluated impacts of Hepatitis C infection on the mortality rate ofpatients with AMI in Taiwan for 12 years, establishes on the follow-up being long enough.

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