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Prevalence and determinants of restless leg syndrome in type 2 diabetes mellitus (T2DM) in Pakistan

Nawaz MS, Nawaz MS, Shah KU, Mustafa ZU, Ahmed A, Sajjad Ahmed H, et al.

Diabetes Metab Syndr, 2021 Feb 13;15(2):525-528.
PMID: 33668002 DOI: 10.1016/j.dsx.2021.02.013

BACKGROUND AND AIMS: Restless legs syndromes (RLS) are intrinsic sleeping disorder and its prevalence rate is 10-15% in general population but it is observed that prevalence rate is different in diabetes patients. Current study aims to find prevalence and determinants of RLS in people living with type 2 diabetes mellitus in Pakistan.
METHOD: A multicenter cross-sectional observational study was conducted in 388 diabetes patients attending daily diabetes clinics and teaching hospitals in Pakistan's twin city between August 2019 and February 2020. The chi-square test and linear regression were used to detect RLS-related factors in type 2 diabetes mellitus.
RESULTS: The prevalence of RLS found was; 3.1% patients with diabetes were suffering from very severe RLS, 23.5% from severe RLS, 34% from moderate RLS, 21.1% from mild RLS and 18.3% from non-RLS. Gender, age, education, blood glucose fasting (BSF), blood glucose random (BSR) and HBA1c were found to be significant predictors of RLS in patients with diabetes.
CONCLUSION: Policy makers can develop local interventions to curb the growing RLS prevalence by keeping in control the risk factors of RLS in people living with type 2 diabetes.

Matched MeSH terms: Linear Models
Fulltext Predictors of intention to stay for employees of casual dining restaurant in Klang Valley area

Nasyira, M.N., Othman, M., Ghazali, H.

International Food Research Journal, 2014;21(3):863-871.
MyJurnal

Employees are an asset to an organisation where they could be the determinant behind organisational’s success or failure in an industry. In this study, the relationship between perceived organisational support (POS), perceived supervisor support (PSS), and organisational commitment (OC) with employee’s intention to stay with their current jobs were studied. For that purpose, 717 questionnaires were collected among casual dining restaurants employees in Klang Valley area and analyses Pearson correlation and multiple linear regression were run by using SPSS version 21. The results suggest that POS, PSS, and OC were positively correlated with employee’s intention to stay with their current job. Furthermore, OC was also found to be the most influential factor in affecting employees’ staying intention. The finding is hoped to have important implications where the management can formulate strategies to retain employees in restaurant industry in Malaysia.

Matched MeSH terms: Linear Models
Fulltext Television screen time, but not computer use and reading time, is associated with cardio-metabolic biomarkers in a multiethnic Asian population: a cross-sectional study

Nang EE, Salim A, Wu Y, Tai ES, Lee J, Van Dam RM

Int J Behav Nutr Phys Act, 2013;10:70.
PMID: 23718927 DOI: 10.1186/1479-5868-10-70

BACKGROUND: Recent evidence shows that sedentary behaviour may be an independent risk factor for cardiovascular diseases, diabetes, cancers and all-cause mortality. However, results are not consistent and different types of sedentary behaviour might have different effects on health. Thus the aim of this study was to evaluate the association between television screen time, computer/reading time and cardio-metabolic biomarkers in a multiethnic urban Asian population. We also sought to understand the potential mediators of this association.
METHODS: The Singapore Prospective Study Program (2004-2007), was a cross-sectional population-based study in a multiethnic population in Singapore. We studied 3305 Singaporean adults of Chinese, Malay and Indian ethnicity who did not have pre-existing diseases and conditions that could affect their physical activity. Multiple linear regression analysis was used to assess the association of television screen time and computer/reading time with cardio-metabolic biomarkers [blood pressure, lipids, glucose, adiponectin, C reactive protein and homeostasis model assessment of insulin resistance (HOMA-IR)]. Path analysis was used to examine the role of mediators of the observed association.
RESULTS: Longer television screen time was significantly associated with higher systolic blood pressure, total cholesterol, triglycerides, C reactive protein, HOMA-IR, and lower adiponectin after adjustment for potential socio-demographic and lifestyle confounders. Dietary factors and body mass index, but not physical activity, were potential mediators that explained most of these associations between television screen time and cardio-metabolic biomarkers. The associations of television screen time with triglycerides and HOMA-IR were only partly explained by dietary factors and body mass index. No association was observed between computer/ reading time and worse levels of cardio-metabolic biomarkers.
CONCLUSIONS: In this urban Asian population, television screen time was associated with worse levels of various cardio-metabolic risk factors. This may reflect detrimental effects of television screen time on dietary habits rather than replacement of physical activity.
MESH: screen time

Matched MeSH terms: Linear Models
Fulltext Development of HPLC Method for Quantification of Sinigrin from Raphanus sativus Roots and Evaluation of Its Anticancer Potential

Nair AB, Gandhi D, Patel SS, Morsy MA, Gorain B, Attimarad M, et al.

Molecules, 2020 Oct 26;25(21).
PMID: 33114598 DOI: 10.3390/molecules25214947

Sinigrin, a precursor of allyl isothiocyanate, present in the Raphanus sativus exhibits diverse biological activities, and has an immense role against cancer proliferation. Therefore, the objective of this study was to quantify the sinigrin in the R. sativus roots using developed and validated RP-HPLC method and further evaluated its' anticancer activity. To achieve the objective, the roots of R. sativus were lyophilized to obtain a stable powder, which were extracted and passed through an ion-exchange column to obtain sinigrin-rich fraction. The RP-HPLC method using C18 analytical column was used for chromatographic separation and quantification of sinigrin in the prepared fraction, which was attained using the mobile phase consisting of 20 mM tetrabutylammonium: acetonitrile (80:20%, v/v at pH 7.0) at a flow rate of 0.5 mL/min. The chromatographic peak for sinigrin was showed at 3.592 min for pure sinigrin, where a good linearity was achieved within the concentration range of 50 to 800 µg/mL (R2 > 0.99), with an excellent accuracy (-1.37% and -1.29%) and precision (1.43% and 0.94%), for intra and inter-day, respectively. Finally, the MTT assay was performed for the sinigrin-rich fraction using three different human cancer cell lines, viz. prostate cancer (DU-145), colon adenocarcinoma (HCT-15), and melanoma (A-375). The cell-based assays were extended to conduct apoptotic and caspase-3 activities, to determine the mechanism of action of sinigrin in the treatment of cancer. MTT assay showed IC50 values of 15.88, 21.42, and 24.58 µg/mL for DU-145, HCT-15, and A-375 cell lines, respectively. Increased cellular apoptosis and caspase-3 expression were observed with sinigrin-rich fraction, indicating significant increase in overexpression of caspase-3 in DU-145 cells. In conclusion, a simple, sensitive, fast, and accurate RP-HPLC method was developed for the estimation of sinigrin in the prepared fraction. The data observed here indicate that sinigrin can be beneficial in treating prostate cancer possibly by inducing apoptosis.

Matched MeSH terms: Linear Models
Fulltext The change of Barthel Index scores from the time of discharge until 3-month post-discharge among acute stroke patients in Malaysia: A random intercept model

Musa KI, Keegan TJ

PLoS One, 2018;13(12):e0208594.
PMID: 30571691 DOI: 10.1371/journal.pone.0208594

BACKGROUND: Acute stroke results in functional disability measurable using the well-known Barthel Index. The objectives of the study are to describe the change in the Barthel Index score and to model the prognostic factors for Barthel Index change from discharge up to 3 months post-discharge using the random intercept model among patients with acute first ever stroke in Kelantan, Malaysia.
METHODS: A total 98 in-hospital first ever acute stroke patients were recruited, and their Barthel Index scores were measured at the time of discharge, at 1 month and 3 months post-discharge. The Barthel Index was scored through telephone interviews. We employed the random intercept model from linear mixed effect regression to model the change of Barthel Index scores during the three months intervals. The prognostic factors included in the model were acute stroke subtypes, age, sex and time of measurement (at discharge, at 1 month and at 3 month post-discharge).
RESULTS: The crude mean Barthel Index scores showed an increased trend. The crude mean Barthel Index at the time of discharge, at 1-month post-discharge and 3 months post-discharge were 35.1 (SD = 39.4), 64.4 (SD = 39.5) and 68.8 (SD = 38.9) respectively. Over the same period, the adjusted mean Barthel Index scores estimated from the linear mixed effect model increased from 39.6 to 66.9 to 73.2. The adjusted mean Barthel Index scores decreased as the age increased, and haemorrhagic stroke patients had lower adjusted mean Barthel Index scores compared to the ischaemic stroke patients.
CONCLUSION: Overall, the crude and adjusted mean Barthel Index scores increase from the time of discharge up to 3-month post-discharge among acute stroke patients. Time after discharge, age and stroke subtypes are the significant prognostic factors for Barthel Index score changes over the period of 3 months.

Matched MeSH terms: Linear Models
Fulltext Gender-based market constraints to informal fish retailing: Evidence from analysis of variance and linear regression

Murphy S, Arora D, Kruijssen F, McDougall C, Kantor P

PLoS One, 2020;15(3):e0229286.
PMID: 32231375 DOI: 10.1371/journal.pone.0229286

Over the last decade, Egypt's aquaculture sector has expanded rapidly, which has contributed substantially to per capita fish supply, and the growth of domestic fish markets and employment across the aquaculture value chain. Despite the growing importance of aquaculture sector in Egyptian labour force, only a few studies have explored the livelihoods of Egypt's women and men fish retailers. Even fewer studies have examined gender-based market constraints experienced by these informal fish retailers. This study uses sex-disaggregated data collected in 2013 in three governorates of Lower Egypt to examine the economic and social constraints to scale of enterprises between women (n = 162) and men informal fish retailers (n = 183). Specifically, we employ linear regression method to determine the correlates of enterprise performance. We found that both women and men retailers in the informal fish market earn low profits and face livelihood insecurities. However, women's enterprise performance is significantly lower than that of men even after controlling for individual socio-economic and retailing characteristics. Specifically, the burden of unpaid household work and lack of support therein impedes women's ability to generate higher revenues. These findings strengthen the argument for investing in understanding how gender norms and attitudes affect livelihood options and outcomes. This leads to recommendations on gender-responsive interventions that engage with both men and women and enhance the bargaining power and collective voice of fish retailers.

Matched MeSH terms: Linear Models
Fulltext Simple and effective HPLC method development and its validation for Clindipine in human drug free plasma

Muralidharan S, Kumar Jr, Dhanaraj SA

Pak J Pharm Sci, 2015 Jan;28(1):135-8.
PMID: 25553676

Simple and effective high performance liquid chromatographic (HPLC) method was developed for estimation of Clindipine in drug free human drug free blank plasma. The internal standard used as Nifidipine (IS). The current method was used protein precipitating extraction of Clindipine from blank plasma. Separation was achieved on reversed-phase c18 column (25cm × 4.6mm, 5μ) and the detection was monitored by UV detector at 260 nm. The optimized mobile phase was used acetonitrile: 5mM potassium dihydrogen orthophosphate (pH 4.5), in the ratio of 60:40% v/v at a flow rate of 1.0 ml/min. This linearity was achieved in this method range of 10.0-125.0 ng/ml with regression coefficient range is 0.99. The present method is suitable in terms of precise, accurate and specific during the study. The simplicity of the method allows for application in laboratories that lack sophisticated analytical instruments such as LC-MS/MS or GC-MS/MS that are complicated, costly and time consuming rather than a simple HPLC-UV method. The present method was successfully applied for pharmacokinetic studies.

Matched MeSH terms: Linear Models
Fulltext Costs of fogging activities and its contributing factors at Hulu Langat District Health Office, Selangor, Malaysia

Muhammad Syazni, Aidalina Mahmud, Suhainizam Muhamad Saliluddin

Malaysian Journal of Medicine and Health Sciences, 2019;15(104):107-107.
MyJurnal

Introduction: Dengue fever currently remains as one of the major public health issues in Malaysia. Dengue inci-dence in Malaysia has been increasing in the last 20 years. Dengue fever has been causing an economic burden to the country each year. Vector control is one of the preventions and control activities to reduce its incidence. Vector control activities, especially fogging is a resource-intensive activity. It uses most of the allocated budget of a district health office (33%). The major cost components of the prevention and control activities were human resources and pesticides with 60.7% were for human resources and 13.6% of the costs were for pesticides. Therefore, it is important to know, cost of each fogging activity and the factors that contribute to that cost. The objective of this study was to determine the costs of fogging activities carried out by Hulu Langat Health District Office, Selangor, Malaysia. Meth-ods: This study was a retrospective descriptive and analytical study using data from the Hulu Langat District Health Office for the year 2018. Cost analysis of fogging activities was carried out using the activity-based costing method-ology. The factors associated with, and predictors of, the costs of fogging activities were determined using chi-square and multiple linear regression. Results: In 2018, Hulu Langat District Health Office carried out total of 2,063 fogging activities. The average cost of each fogging activity was estimated as RM 1,579. Types of insecticides was statistically significant associated and predictive factor of the cost of fogging activity. Conclusion: The present study showed that the estimated average cost per fogging activity is RM 1,579 and water-based insecticide was found to be the cheaper option compared to oil-based insecticide. However, as this study did not determine the effectiveness of these insec-ticides, recommendations cannot be made as to which insecticide should be used.

Matched MeSH terms: Linear Models
Fulltext Development of a composite pavement performance index to monitor the pavement condition in UPNM

Muhammad Nur Arsyad Azman, Ng, Choy Peng, Faridah Hanim Khairuddin, Neza Ismail, Wan Mohamed Syafuan Wan Sabri

ZULFAQAR International Journal of Defence Science, Engineering & Technology, 2020;3(1):23-31.
MyJurnal

Road surface condition of a pavement is one of the most important features as it affect driving comfort and safety. A good road surface condition could reduce the risk of traffic accidents and injuries. Pavement Condition Index (PCI) is one of the important tools to measure the pavement performance. By conducting pavement evaluation, civil engineers could prioritize the maintenance and rehabilitation which usually incurred a huge cost. In University Pertahanan Nasional Malaysia (UPNM), there was no proper maintenance and rehabilitation scheduled for the roads as no performance evaluation tool available to measure the pavement condition. Thus, the objective of this study was to develop a Composite Pavement Performance Index (CPPI) to monitor the pavement condition and to rank the roads in UPNM. To develop the CPPI, road defects data were collected from 6 internal roads in UPNM. From the data collected, 4 major distresses were identified: longitudinal cracking, crocodile cracking, potholes and ravelling were found more likely to affect the pavement’s condition in UPNM. By measuring the growth of the distresses over a period of 6 months, modelling was conducted using simple linear regression. The growth of the distresses were compared, and odds ratios were computed to calculate the weightage of each distress for the determination of the CPPI value. The CPPI value developed could be used to rank the roads in UPNM. This study demonstrated that the road connecting to the library building in UPNM experienced the worst pavement deterioration with a PCI of 24 or a CPPI value of 1.1915. The level of severity was classified as “SERIOUS” in accordance to ASTM D6433. This road was recommended for reconstruction to increase the comfort and safety for road users

Matched MeSH terms: Linear Models
Fulltext A machine learning approach of predicting high potential archers by means of physical fitness indicators

Muazu Musa R, P P Abdul Majeed A, Taha Z, Chang SW, Ab Nasir AF, Abdullah MR

PLoS One, 2019;14(1):e0209638.
PMID: 30605456 DOI: 10.1371/journal.pone.0209638

k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. The present study classified and predicted high and low potential archers from a set of physical fitness variables trained on a variation of k-NN algorithms and logistic regression. 50 youth archers with the mean age and standard deviation of (17.0 ± 0.56) years drawn from various archery programmes completed a one end archery shooting score test. Standard fitness measurements of the handgrip, vertical jump, standing broad jump, static balance, upper muscle strength and the core muscle strength were conducted. Multiple linear regression was utilised to ascertain the significant variables that affect the shooting score. It was demonstrated from the analysis that core muscle strength and vertical jump were statistically significant. Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the significant variables identified. k-NN model variations, i.e., fine, medium, coarse, cosine, cubic and weighted functions as well as logistic regression, were trained based on the significant performance variables. The HACA clustered the archers into high potential archers (HPA) and low potential archers (LPA). The weighted k-NN outperformed all the tested models at itdemonstrated reasonably good classification on the evaluated indicators with an accuracy of 82.5 ± 4.75% for the prediction of the HPA and the LPA. Moreover, the performance of the classifiers was further investigated against fresh data, which also indicates the efficacy of the weighted k-NN model. These findings could be valuable to coaches and sports managers to recognise high potential archers from a combination of the selected few physical fitness performance indicators identified which would subsequently save cost, time and energy for a talent identification programme.

Matched MeSH terms: Linear Models
Predictors of handgrip strength among adults of a rural community in Malaysia

Moy FM, Darus A, Hairi NN

Asia Pac J Public Health, 2015 Mar;27(2):176-84.
PMID: 24285778 DOI: 10.1177/1010539513510555

Handgrip strength is useful for screening the nutritional status of adult population as it is strongly associated with physical disabilities and mortality. Therefore, we aimed to determine the predictors of handgrip strength among adults of a rural community in Malaysia using a cross-sectional study design with multistage sampling. All adults aged 30 years and older from 1250 households were invited to our study. Structured questionnaire on sociodemographic characteristics, medical history, occupation history, lifestyle practices, and measurements, including anthropometry and handgrip strength were taken. There were 2199 respondents with 55.2% females and majority were of Malay ethnicity. Their mean (standard deviation) age was 53.4 (13.2) years. The response rate for handgrip strength was 94.2%. Females had significantly lower handgrip strength than males (P < .05). In the multiple linear regression models, significant predictors of handgrip strength for males were age, height, job groups, and diabetes, while for females, the significant predictors were age, weight, height, and diabetes.

Matched MeSH terms: Linear Models
Fulltext Association of carcinogenic polycyclic aromatic hydrocarbon emissions and smoking with lung cancer mortality rates on a global scale

Motorykin O, Matzke MM, Waters KM, Massey Simonich SL

Environ Sci Technol, 2013 Apr 2;47(7):3410-6.
PMID: 23472838 DOI: 10.1021/es305295d

The objective of this research was to investigate the relationship between lung cancer mortality rates, carcinogenic polycyclic aromatic hydrocarbon (PAH) emissions, and smoking on a global scale, as well as for different socioeconomic country groups. The estimated lung cancer deaths per 100,000 people (ED100000) and age standardized lung cancer death rate per 100,000 people (ASDR100000) in 2004 were regressed on PAH emissions in benzo[a]pyrene equivalence (BaPeq), smoking prevalence, cigarette price, gross domestic product per capita, percentage of people with diabetes, and average body mass index using simple and multiple linear regression for 136 countries. Using stepwise multiple linear regression, a statistically significant positive linear relationship was found between loge(ED100000) and loge(BaPeq) emissions for high (p-value <0.01) and for the combination of upper-middle and high (p-value <0.05) socioeconomic country groups. A similar relationship was found between loge(ASDR100000) and loge(BaPeq) emissions for the combination of upper-middle and high (p-value <0.01) socioeconomic country groups. Conversely, for loge(ED100000) and loge(ASDR100000), smoking prevalence was the only significant independent variable in the low socioeconomic country group (p-value <0.001). These results suggest that reducing BaPeq emissions in the U.S., Canada, Australia, France, Germany, Brazil, South Africa, Poland, Mexico, and Malaysia could reduce ED100000, while reducing smoking prevalence in Democratic People's Republic of Korea, Nepal, Mongolia, Cambodia, and Bangladesh could significantly reduce the ED100000 and ASDR100000.

Matched MeSH terms: Linear Models
Fulltext Factors affecting the HIV/AIDS epidemic: an ecological analysis of global data

Mondal MN, Shitan M

Afr Health Sci, 2013 Jun;13(2):301-10.
PMID: 24235928 DOI: 10.4314/ahs.v13i2.15

All over the world the prevalence of Human Immunodeficiency Virus (HIV)/Acquired Immune Deficiency Syndrome (AIDS) has became a stumbling stone in progress of human civilization and is a huge concern for people worldwide.

Matched MeSH terms: Linear Models
Fulltext The Association Between Diabetes and Cognitive Function in Later Life

Momtaz YA, Hamid TA, Bagat MF, Hazrati M

Curr Aging Sci, 2019;12(1):62-66.
PMID: 31589113 DOI: 10.2174/1874609812666190614104328

INTRODUCTION: Although diabetes through several possible mechanisms such as increased microvascular pathology and inefficiency of glucose utilization during cognitive tasks can be associated with cognitive impairment, there is inconclusive evidence that shows elderly diabetic patients under therapy have higher cognitive function compared to their non-diabetics counterparts. The present study was conducted to elucidate the association between diabetes and cognitive function in later life.
METHODS: Data for this study, consisting of 2202 older adults aged 60 years and above, were taken from a population-based survey entitled "Identifying Psychosocial and Identifying Economic Risk Factor of Cognitive Impairment among Elderly. Data analysis was conducted using the IBM SPSS Version 23.0.
RESULTS: The mean of MMSE was found to be 22.67 (SD = 4.93). The overall prevalence of selfreported diabetes was found to be 23.6% (CI95%: 21.8% - 25.4%). The result of independent t-test showed diabetic subjects had a higher mean score of MMSE (M = 23.05, SD =4 .55) than their counterparts without diabetes (M = 22.55, SD = 5.04) (t = -2.13 plinear regression analysis showed that diabetes was not significantly associated with cognitive function, after controlling the possible confounding factors.
CONCLUSIONS: The findings from the current study revealed that diabetes is not associated with cognitive decline. This study supports the findings that long-term treatment of diabetes may reduce the risk of cognitive decline. This finding may provide new opportunities for the prevention and management of cognitive decline.

Matched MeSH terms: Linear Models
Prediction of tuberculosis cases based on sociodemographic and environmental factors in gombak, Selangor, Malaysia: A comparative assessment of multiple linear regression and artificial neural network models

Mohidem NA, Osman M, Muharam FM, Elias SM, Shaharudin R, Hashim Z

Int J Mycobacteriol, 2021 12 18;10(4):442-456.
PMID: 34916466 DOI: 10.4103/ijmy.ijmy_182_21

Background: Early prediction of tuberculosis (TB) cases is very crucial for its prevention and control. This study aims to predict the number of TB cases in Gombak based on sociodemographic and environmental factors.
Methods: The sociodemographic data of 3325 TB cases from January 2013 to December 2017 in Gombak district were collected from the MyTB web and TB Information System database. Environmental data were obtained from the Department of Environment, Malaysia; Department of Irrigation and Drainage, Malaysia; and Malaysian Metrological Department from July 2012 to December 2017. Multiple linear regression (MLR) and artificial neural network (ANN) were used to develop the prediction model of TB cases. The models that used sociodemographic variables as the input datasets were referred as MLR1 and ANN1, whereas environmental variables were represented as MLR2 and ANN2 and both sociodemographic and environmental variables together were indicated as MLR3 and ANN3.
Results: The ANN was found to be superior to MLR with higher adjusted coefficient of determination (R2) values in predicting TB cases; the ranges were from 0.35 to 0.47 compared to 0.07 to 0.14, respectively. The best TB prediction model, that is, ANN3 was derived from nationality, residency, income status, CO, NO2, SO2, PM10, rainfall, temperature, and atmospheric pressure, with the highest adjusted R2 value of 0.47, errors below 6, and accuracies above 96%.
Conclusions: It is envisaged that the application of the ANN algorithm based on both sociodemographic and environmental factors may enable a more accurate modeling for predicting TB cases.

Matched MeSH terms: Linear Models
Fulltext A study of occupational stress and coping strategies among correctional officers in Kedah, Malaysia

Mohd Zukri, I., Noor Hassim, I.

Malaysian Journal of Community Health, 2010;16(2):66-74.
MyJurnal

Introduction: The effect of stress among correctional officers at the workplace can contribute to various health problems and this also affect their work performance and motivation.
Methodology: Study was done at a prison located at the rural district in Kedah. The study was conducted by using randomized stratified sampling method. A total of 418 self administrated questionnaires were distributed. These questionnaires included socio demographic factor, family and marriage factor, Personal Stress Inventory (using Stress Symptom Scale with 52 items), work related stressors (Job Stress Survey) and Brief COPE (Coping Orientation for Problems Experienced with 28 items).
Result: Response rate was 90.9%. Stress prevalence for correctional officers was 45.8%. Socio demographic factors which have significant relation with stress status were marital status, promotion factor, age, monthly salary, duration of service and number of children (p< 0.05). Family and marriage factor which have significant relation with stress status among married officer were pressure from relatives, clean up house, sexual frustration, conflict with spouse, conflict with children, conflict due to household work and no babysitter (p< 0.05).
Discussion: The study showed that work related stressors that have influence with stress were excessive workload, working after work hours, not enough staff, disgraced words from fellow workers, competition in carrier development and excessive work stress (p< 0.05). Multiple linear regression model was done in this study and revealed factors that explained 52% of variation in stress score distributions were behavioural disengagement, no babysitter, denial, conflict with children, replace other worker’s duty, not enough time with family, competition in carrier development, venting of emotion, positive reframing and emotional support. Coping strategies that have significant effect in reducing stress symptoms are positive reframing and emotional support.
Conclusion: Stress management programs should be implemented and emphasizing on specific stressors and coping mechanism are important to reduce the risk of occupational stress among correctional officers.

Matched MeSH terms: Linear Models
Application of third molar development and eruption models in estimating dental age in Malay sub-adults

Mohd Yusof MY, Cauwels R, Deschepper E, Martens L

J Forensic Leg Med, 2015 Aug;34:40-4.
PMID: 26165657 DOI: 10.1016/j.jflm.2015.05.004

The third molar development (TMD) has been widely utilized as one of the radiographic method for dental age estimation. By using the same radiograph of the same individual, third molar eruption (TME) information can be incorporated to the TMD regression model. This study aims to evaluate the performance of dental age estimation in individual method models and the combined model (TMD and TME) based on the classic regressions of multiple linear and principal component analysis. A sample of 705 digital panoramic radiographs of Malay sub-adults aged between 14.1 and 23.8 years was collected. The techniques described by Gleiser and Hunt (modified by Kohler) and Olze were employed to stage the TMD and TME, respectively. The data was divided to develop three respective models based on the two regressions of multiple linear and principal component analysis. The trained models were then validated on the test sample and the accuracy of age prediction was compared between each model. The coefficient of determination (R²) and root mean square error (RMSE) were calculated. In both genders, adjusted R² yielded an increment in the linear regressions of combined model as compared to the individual models. The overall decrease in RMSE was detected in combined model as compared to TMD (0.03-0.06) and TME (0.2-0.8). In principal component regression, low value of adjusted R(2) and high RMSE except in male were exhibited in combined model. Dental age estimation is better predicted using combined model in multiple linear regression models.

Matched MeSH terms: Linear Models
Modelling exchange rates using regime switching models

Mohd Tahir Ismail, Zaidi Isa

Sains Malaysiana, 2006;35:55-62.

The behaviour of many financial time series cannot be modeled solely by linear time series model. Phenomena such as mean reversion, volatility of stock markets and structural breaks cannot be modelled implicitly using simple linear time series model. Thus, to overcome this problem, nonlinear time series models are typically designed to accommodate these nonlinear features in the data. In this paper, we use portmanteau test and structural change test to detect nonlinear feature in three ASEAN countries exchange rates (Malaysia, Singapore and Thailand). It is found that the null hypothesis of linearity is rejected and there is evidence of structural breaks in the exchange rates series. Therefore, the decision of using regime switching model in this study is justified. Using model selection criteria (AIC, SBC, HQC), we compare the in-sample fitting between two types of regime switching model. The two regime switching models we considered were the Self-Exciting Threshold Autoregressive (SETAR) model and the Markov switching Autoregressive (MS-AR) model where these models can explain the abrupt changes in a time series but differ as how they model the movement between regimes. From the AIC, SBC and HQC values, it is found that the MS -AR model is the best fitted model for all the return series. In addition, the regime switching model also found to perform better than simple autoregressive model in in-sample fitting. This result justified that nonlinear model give better in-sample fitting than linear model.

Matched MeSH terms: Linear Models
Fulltext Prediction of damage cost of bronchitis due to haze in Malaysia

Mohd Khairul Amri Kamarudin, Noorjima Abd Wahab, Khalid Abdul Rahim

Malaysian Journal of Applied Sciences, 2018;1(2):1-8.
MyJurnal

Awareness of haze pollution and management increased in Southeast Asia since 1990. However, the
focus on environmental management is decreasing especially in Malaysia due to the abundant
resources and increased development pressure. The total health damage cost because of haze in the
country became significantly high due to the long duration of haze events year by year. This paper
discusses the health damage caused by bronchitis due to the haze events in Malaysia. The analysis
shows positive coefficient of independent variables which indicates the positive relationship between
dependent variable and independent variables. Multiple linear regression analysis shows that 45.3%
variation in damage cost of bronchitis could be explained by FAI, GDPPC, and CO2.

Matched MeSH terms: Linear Models
Fulltext A Multi-Sensor Comparative Analysis on the Suitability of Generated DEM from Sentinel-1 SAR Interferometry Using Statistical and Hydrological Models

Mohammadi A, Karimzadeh S, Jalal SJ, Kamran KV, Shahabi H, Homayouni S, et al.

Sensors (Basel), 2020 Dec 16;20(24).
PMID: 33339435 DOI: 10.3390/s20247214

Digital elevation model (DEM) plays a vital role in hydrological modelling and environmental studies. Many essential layers can be extracted from this land surface information, including slope, aspect, rivers, and curvature. Therefore, DEM quality and accuracy will affect the extracted features and the whole process of modeling. Despite freely available DEMs from various sources, many researchers generate this information for their areas from various observations. Sentinal-1 synthetic aperture radar (SAR) images are among the best Earth observations for DEM generation thanks to their availabilities, high-resolution, and C-band sensitivity to surface structure. This paper presents a comparative study, from a hydrological point of view, on the quality and reliability of the DEMs generated from Sentinel-1 data and DEMs from other sources such as AIRSAR, ALOS-PALSAR, TanDEM-X, and SRTM. To this end, pair of Sentinel-1 data were acquired and processed using the SAR interferometry technique to produce a DEM for two different study areas of a part of the Cameron Highlands, Pahang, Malaysia, a part of Sanandaj, Iran. Based on the estimated linear regression and standard errors, generating DEM from Sentinel-1 did not yield promising results. The river streams for all DEMs were extracted using geospatial analysis tool in a geographic information system (GIS) environment. The results indicated that because of the higher spatial resolution (compared to SRTM and TanDEM-X), more stream orders were delineated from AIRSAR and Sentinel-1 DEMs. Due to the shorter perpendicular baseline, the phase decorrelation in the created DEM resulted in a lot of noise. At the same time, results from ground control points (GCPs) showed that the created DEM from Sentinel-1 is not promising. Therefore, other DEMs' performance, such as 90-meters' TanDEM-X and 30-meters' SRTM, are better than Sentinel-1 DEM (with a better spatial resolution).

Matched MeSH terms: Linear Models

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