CriticalAppraisal of Research Article
The title is brief and captures the purpose of the study. Immediatelyafter the title is the credentials of the authors and theiraffiliations to enhance the credibility of findings.
The role of ethnicity or genetics in influencing insulin resistanceamong a sample of different groups of Chinese people.
This study sought to analyze the relationship between IR and a set ofvariables including glucose, lipid metabolism, and ethnicheterogeneity (Yan et al., 2016).
The study lacks an explicit hypothesis, which would suggest theexpected outcomes of the research. Such a suggestion works best inquantitative studies using the grounded theory approach. Where ahypothesis is used, the study should seek to validate or invalidateit.
Implicit hypothesis:obesity and IR have a causal relationship as the accumulation ofexcessive adipose tissue can induce IR.
IR is most closelyrelated to glucose metabolism and is a predictor of diabetes.
The study applied a baseline survey targeting residents of Yili,Kashi, Shihezi, Tacheng, and Changji prefectures in China between2009 and 2012. A total of 419 Uygur, 331 Kazak, and 220 Han cases(n=970) were randomly selected (Yan et al., 2016). Such a sample issufficiently large for a quantitative study. Researchers targeteddifferent groups in various prefectures to accommodate changes indiet, lifestyle, culture, and genetic make-up, which all affectmetabolism and IR. Data was collected by measuring vital indicatorsin the subjects. The vitals or variables targeted in this case areidentified as dyslipidemia, hyperglycemia, and abdominal obesity(waist size). Several tools and instruments were used to collect datain laboratory tests. A biochemical auto-analyzer recommended by theChinese Diabetes Society was used to assess insulin resistance whilea kit purchased from Beijing Atomic-Tech Co. Ltd. measured fastingserum insulin levels. The values obtained using the mentioned toolswere used to calculate IR using the homeostasis model assessment ofinsulin resistance (HOMA-IR) index. Data obtained was synthesizedfurther using SPSS (19.0), and statistical tests of variance andunivariate and multivariate logistic regression analysis. Such detailmakes the study replicable elsewhere.
The study presented data using both descriptive and analyticalstatistics. Much of the descriptive statistics of the study were usedexplain the sample and not the results. Gender and age are importantfactors in diabetes and IR cases. The study thus examined for anysignificant differences in the averages of age and gender and foundnone (P<0.05 for each). A univariate logistic regression analysisusing six dependent variables and IR as the independent variableshowed that the Uygur, Kazak, and Han populations were more prone todiabetes as indicated by higher IR. A multivariate logisticalanalysis was also conducted. Logistical regression analysis suits thecurrent study because the approach does not assume a directrelationship between the independent and dependent variables (Yan etal., 2016). However, the research did not provide the results in amanner that a layperson or a person not familiar with statisticsmight understand. This decision can be attributed to the targetedaudience of the study.
Summary of KeyPoints
There is significant variation in IR among different ethnic groups as predicted by the implicit hypothesis.
The Kazak have the highest risk of IR and diabetes while the Han have the lowest.
Abdominal obesity is linked to increased incidence of IR.
Some confounding factors and behaviors such as smoking affect the prevalence of IR across the different ethnicities.
The study was conducted in several Chinese villages. Although datawas collected for the duration of about four years, the study doesnot take a longitudinal approach with follow-ups and does not explainwhy it took that long.
The study informs health practitioners on the significance ofethnicity in determining IR. Personally, it cautions me about theneed to examine my ethnic predisposition to IR. However, the studyignores genetic distance between the various groups studied. Thus,the variation in IR might not be attributable to genetics alone byother factors such as culture.
The study employed tables to present essential data for enhancedunderstanding. The first table shows the distribution of thevariables across the various study groups while the other tables showthe univariate and multivariate logistical regression analysisresults.
Yan, Y., Ma, R.,Zhang, J. He, J., Ma, J., Pang, H………Guo, S. (2016). Associationof insulin
resistance with glucose and lipid metabolism: Ethnic heterogeneity infar western China. Mediators of Inflammation, 1-8. doi:10.1155/2016/3825037.