2023 CiteScore: 0.8
pISSN: 2383-4196
eISSN: 2383-420X
Editor-in-Chief:
Hojjat Zeraati, PhD.
Vol 10 No 3 (2024)
Articles
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Background: Hybrid of the high-dimensional sparse data and multicollinearity problems can cause instabilities in classification models when applying them to new datasets. The Lasso, or Least Absolute Shrinkage and Selection Operator, is popularly used in machine-learning algorithm. Despite its computational feasibility for high-dimensional data, this method has certain drawbacks. Consequently, the adaptive Lasso was developed to solve these problems. Power of adaptive weight for this estimator is one of the important parameters. Therefore, we concentrate on the power of adaptive weight for the penalty functions. This study aimed to compare the impact of the power of adaptive weight on penalized logistic regression under high-dimensional sparse data with multicollinearity.
Methods: A penalized approaches were used to apply the variable selection and parameter estimates. The Monte Carlo simulation was performed using 50 and 1000 independent variables and sample size equal to 30/40. Degree of correlation was set to 0.1, 0.3, 0.5, 0.75, 0.85, and 0.95. Performance of the power of adaptive weight on penalized approaches was evaluated in term of the mean of the predicted mean squared error for simulation study and the classification accuracy of machine-learning model for real-data applications.
Results: The results presented that the higher-order of the adaptive Lasso approach performed best under very high-dimensional sparse data with multicollinearity when the initial weight was determined using a ridge estimator. However, in the case of high-dimensional sparse data with multicollinearity, the square root of the adaptive Lasso together with the initial weight using Lasso was the best option.
Conclusion: Our finding showed that the power of adaptive weight on penalty function and the initial weight can affect certain the classification accuracy of machine-learning model. In practice, if choosing these parameters are appropriate, it produces models that have good performance.
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Introduction: Congenital endocrine disorders have a global impact on the morbidity and mortality of children and are a public health problem that heavily affects society and the daily lives of affected children and their families. The severity and consequences of congenital hypothyroidism (CH) on physical and especially cerebral maturation combined with lifetime mental retardation make CH neonatal screening one of the costliest preventive health programs. Thus, early diagnosis can improve the prognosis of the disease. The objective of the study is to examine CH’s risk factors reported in previous studies.
Methods: Meta-analysis was performed according to the PRISMA checklist. PUBMED, Google Scholar, Scopus, MEDLINE, Web of Science, and Springer were analyzed using R version 4.0.3. For further review, we assessed eligibility analysis to identify influential studies.
Results: Of 63 studies, 22 studies were suitable for synthesis. Based on this review, risk factors related to CH were birth weight, age of pregnancy, female sex, home environment, notion of inbreeding, seasonality, multiple pregnancy, gestational diabetes, parity, advanced maternal age, parental thyroid disease, gestational diabetes, ethnicity, maternal body mass index (BMI), and socio-economic status.
Conclusion: This systematic review and meta-analysis indicates that the risk factors related to CH vary by country and even by inter-region according to geographical, genetic, and socioeconomic specificities.
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Introduction: Limited studies have been conducted on the effect of oral contraceptive pills on the subgroups of ovarian cancer, so we decided that conduct a systematic review and meta-analysis to investigate the effect of preventive pills on ovarian cancer subgroups.
methods: Scopus, PubMed, Web of Science and EMBASE were searched to identify studies on the association between OCPs and subtypes of ovarian cancer from January 1, 2000, through February 5, 2023. The pooled relative risk (RR) and odds ratio (OR) were used to measure this relationship.
Results: A total of 48 studies were included. In the association between ever-use compared with never-use of OCPs and ovarian cancer risk, the pooled RR in cohort studies was 0.69 [95% CI: 0.61, 0.78], and the pooled OR of the case-control studies was 0.64 [95% CI: 0.59, 0.69]. For the relationship between OCPs and subtypes of ovarian cancer, there is a significant inverse relationship between OCPs and serous 0.72 [95% CI: 0.23, 0.82] and endometrioid 0.74 [95% CI: 0.64, 0.86], but no association between OCPs and clear cell 0.84 [95% CI: 0.60, 1.16] and mucinous 0.80 [95% CI: 0.63, 1.01].
Conclusions: This study shows a statistically significant inverse relationship between ever-use compared to never-use of OCPs and ovarian cancer risk. Also shows a statistically significant inverse relationship between serous and endometrioid cancer and OCPs, but no association between OCPs and clear cell and mucinous.
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Introduction: Attitudes about COVID-19 relate to cognitions, feelings, and behaviors regarding the pandemic and vaccination, as well as other factors, such as demographic characteristics, and health-related information. This research uses the Causal Attitude Network (CAN) model to measure attitudes and acceptance of COVID-19 vaccination among 1385 Indonesian people from 15 cities.
Methods: Data was obtained from instruments that made in the Netherlands and adapted to Indonesian language and culture. This research integrates psychometrics with network analysis which is an advanced implementation of the field of Statistics to reveal the interaction between psychological factors that shape people's attitudes towards COVID-19 and vaccination in Indonesia. Data analysis used JASP, an open source statistical analysis software.
Results: From this research, it was found that attitude elements regarding trust in vaccine development and awareness of the importance of vaccines in Indonesian society have a high influence on other attitude elements. Attitude elements regarding the habit of wearing masks and awareness about the importance of the COVID-19 vaccine are the attitude elements that have the highest impact on changing other attitude elements,
Conclusion: Two attitude elements, namely trust and awareness, are the attitude elements that most influence other attitude elements. Trust in the development of the COVID-19 vaccine is related to trust in the experts in developing the COVID-19 vaccine. In other words, increasing public confidence in the development of a science-appropriate COVID-19 vaccine will be in line with increasing public trust in COVID-19 vaccine developers, and vice versa.
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Background: Parkinson’s disease (PD) is a complex, progressive neurodegenerative disorder known to negatively impair patient gait. Therefore, with gait and vertical ground reaction force (VGRF) data, an association can be made between the data and Parkinson’s disease.
Methods: Data from 146 participants; 93 with Parkinson’s disease and 73 without Parkinson’s disease was obtained from a PhysioNet database for use in this article. A Fourier Analysis and several support vector machine learning models were computed in MATLAB to classify whether an individual had Parkinson’s disease.
Results: From the Fourier analysis, it was determined that a statistically significant difference was present between the VGRF data of individuals with and without Parkinson’s disease. Additionally, it was found that a Minimum Classification Error Optimized SVM machine learning model using Bayesian statistics was able to classify individuals with Parkinson’s disease using VGRF data at an accuracy of 67.1%, and sensitivity of 80.43%.
Conclusion: Therefore, it can be determined that vertical ground reaction force can predict Parkinson’s Disease with considerable accuracy which could be improved with an increased number of participants.
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Background: Prostate cancer is an emerging health problem in Sub-Saharan Africa and it is often diagnosed at an advanced stage due to the lack of access to screening and diagnostic facilities.
Method: This study therefore aimed at modelling the effects of risk factors on the outcome of prostate cancer screening using Generalized Bayesian ordinal logistic regression with random effects then compare the results obtained with the model without random effects. The study further used Mean Squared Errors and established that the estimates for the two models were different
Results: The findings in this study indicate that aged individuals have high chances of having prostate cancer at the early, late or advanced stage. The individual with traces of family history and hereditary breast & ovarian cancer syndrome are also most likely to be in late or advanced stage of prostate cancer.
Conclusion: From the findings aged individuals, having traces of family history and individuals with hereditary breast & ovarian cancer history, should be on alert and understand all symptoms of prostate cancer. For any signs or appearance of prostate cancer symptoms, they are supposed seek for screening services at earliest time possible. In addition, the Ministry of Health should create awareness training and increase screening facilities, this will also encourage for early screening and detection of prostate cancer. The different estimates led to identifying the best model, whereby models with presence of random effects had lowest Widely Applicable Information Criterion values hence they were considered to be the best models in each category.
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Epidemiology, clustering and spatial distribution of animal bites in Algeria Animal bites in Algeria
Introduction: Animals can transmit many viral and bacterial diseases through bites and saliva that can be potentially fatal to human. Rabies, one of these diseases, is rife in two-thirds of the world’s countries. Algeria is not spared. This study was scoped to provide insight into the demography and epidemiology, spatial distribution and clustering patterns of animal bites in Algeria.
Methods: The global and local Moran's I were used to investigate geographic clustering patterns of animal bites in Algeria. The animal bites data provided by North West Health Region (NWHR) Observatory was analyzed to glean useful information.
Results: Over the past five decades, 1201 human rabies fatalities have been recorded in Algeria with a yearly average of 20 cases and a male predominance. As for 2017, a total of 116403 animal attacks were recorded. Dog bites accounted for 64.1% followed by cat bites for 30.5%. The rabies vaccine was practiced in 74% of cases and vaccine with rabies immune globulin in 26% cases. The incidence was estimated at 279 per 100000 inhabitants. The incidence of animal bites, dog and cat bites exhibited spatial autocorrelation globally; the Moran index values were 0.41, 0.43 and 0.60 respectively. Significant hot spots were located in Tell, and significant cold spots were located on Sahara and High-Plateaus. The analysis of the 21314 animal attacks reported in NWHR in 2019, showed that young children and men are the most-at-risk. Indeed, 71.3% were male and 58.7% occurred outdoors. Among the 8275 bites that occurred in children under 15 years, 66.8% were boys and 29.3% were children under 5 years. Most of the bites were Category II(45.7%) followed by Category III(38.6%).
Conclusion: The current strategy needs to be reviewed, reformed and strengthened while promoting cross-sectoral work with a collaborative approach of all relevant sectors for a One Health initiative.
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Background: In Iran, evidence regarding the impact of socioeconomic (SES) inequality on the progression and complications of type 2 diabetes mellitus (T2DM) are sparse and needs growing body of research. SES is a complex construct and its impact on the health outcomes should be evaluated in an efficient and flexible way. The purpose of this study is to examine SES inequality in chronic complications among T2DM patients using methods of decomposing inequality.
Methods: This cross-sectional study included patients with T2DM receiving care at the diabetes clinic in Hamadan City, Iran, between April and September 2023. Demographic, SES, diabetic related factors were obtained from medical records and face-to-face interviews. A binary logistic regression model was utilized to investigate the relationship between diabetes complications and independent variables. The concentration index (CI) and decomposition approach were used to evaluate SES inequality and determine the contribution of each factor to inequality.
Results: A total of 530 patients (61.6% females and 54.9% less than 60 years) were included. In the study population, 22.3%, 9.5%, and 4.7% had retinopathy, kidney failure, and diabetic foot ulcers, respectively. The CI for retinopathy, kidney failure, and foot ulcers were [(CI: -0.273, p<0.001), (CI: -0.089, p<0.001), (CI: -0.122, p<0.001), respectively]. Factors with the greatest contribution to SES inequality for retinopathy were economic status (44.6%), duration of T2DM (24.5%), age (18.7%), and healthy lifestyle (12.5%), for kidney failure were economic status (33.8%), hypertension (22.5%), education level (21.3%), and HbA1c value (13.5%), and for foot ulcers were economic status (78.7%), duration of T2DM (33.6%), HbA1c value (17.2%) hypertension (7.4%).
Conclusion: This study demonstrated that SES inequality in chronic complications of T2DM with greatest contribution for economic status. It is recommended that policymakers and health professionals consider the main causes of SES inequality in the chronic complications of T2DM when developing health strategies.
