Displaying publications 21 - 40 of 389 in total

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  1. Faust O, Hagiwara Y, Hong TJ, Lih OS, Acharya UR
    Comput Methods Programs Biomed, 2018 Jul;161:1-13.
    PMID: 29852952 DOI: 10.1016/j.cmpb.2018.04.005
    BACKGROUND AND OBJECTIVE: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.2017.

    METHODS: An initial bibliometric analysis shows that the reviewed papers focused on Electromyogram(EMG), Electroencephalogram(EEG), Electrocardiogram(ECG), and Electrooculogram(EOG). These four categories were used to structure the subsequent content review.

    RESULTS: During the content review, we understood that deep learning performs better for big and varied datasets than classic analysis and machine classification methods. Deep learning algorithms try to develop the model by using all the available input.

    CONCLUSIONS: This review paper depicts the application of various deep learning algorithms used till recently, but in future it will be used for more healthcare areas to improve the quality of diagnosis.

    Matched MeSH terms: Linear Models
  2. Zin CS, Taufek NH, Ahmad MM
    Front Pharmacol, 2019;10:1286.
    PMID: 31736760 DOI: 10.3389/fphar.2019.01286
    Limited data are available on the adherence to opioid therapy and the influence of different patient groups on adherence. This study examined the patterns of adherence in opioid naïve and opioid existing patients with varying age and gender. This retrospective cohort study was conducted using the prescription databases in tertiary hospital settings in Malaysia from 2010 to 2016. Adult patients aged ≥18 years, receiving at least two opioid prescriptions, were included and stratified into the opioid naïve and existing patient groups. Adherence to opioid therapy was measured using the proportion of days covered (PDC), which was derived by dividing the total number of days covered with any opioids by the number of days in the follow-up period. Generalized linear modeling was used to assess factors associated with PDC. A total of 10,569 patients with 36,650 prescription episodes were included in the study. Of these, 91.7% (n = 9,696) were opioid naïve patients and 8.3% (n = 873) were opioid existing patients. The median PDC was 35.5% (interquartile range (IQR) 10.3-78.7%) and 26.8% (IQR 8.8-69.5%) for opioid naïve and opioid existing patients, respectively. A higher opioid daily dose (coefficient 0.010, confidence interval (CI) 0.009, 0.012 p < 0.0001) and increasing age (coefficient 0.002, CI 0.001, 0.003 p < 0.0001) were associated with higher levels of PDC, while lower PDC values were associated with male subjects (coefficient -0.0041, CI -0.072, -0.010 p = 0.009) and existing opioid patients (coefficient -0.134, CI -0.191, -0.077 p < 0.0001). The suboptimal adherence to opioid medications was commonly observed among patients with non-cancer pain, and the opioid existing patients were less adherent compared to opioid naïve patients. Increasing age and a higher daily opioid dose were factors associated with higher levels of adherence, while male and opioid existing patients were potential determinants for lower levels of adherence to opioid medications.
    Matched MeSH terms: Linear Models
  3. Intan Syafinaz Mat Shafie, Yuslina Liza Mohammad Yunus, Nur Izzah Jamil, Aini Hayati Musa
    MyJurnal
    Television (TV) advertisements have become one of the most powerful marketing tools in attracting their audience to become potential customers. They are widely used among food industry locally and also internationally. This study is conducted to identify the factors that contribute to an effective TV advertisement in food industry among centennials using predictive analysis. The aims of this study are to; 1) Identify significant factors; Attractive Visual, Persuasive Message and Repetition of Advertisement to the Effectiveness of TV advertisements in food industry. 2) Identify the most contribute significant factors; Attractive Visual, Persuasive Message and Repetition of Advertisement to the Effectiveness of TV advertisements in food industry. Thus, it was tested to 300 respondents in Shah Alam area using convenient sampling technique. Preliminary analysis included reliability analysis, checking for the correlation, multiple linear regression requirement and R-Square score. Correlation analysis shows that there was a significant positive linear relationship between attractive visuals, persuasive message and repetition of advertisements towards Effectiveness of TV advertisements in food industry. Among independent variables entered into the model, persuasive message (t=7.474, p-value=0.000
    Matched MeSH terms: Linear Models
  4. Ghazali NA, Ramli NA, Yahaya AS, Yusof NF, Sansuddin N, Al Madhoun WA
    Environ Monit Assess, 2010 Jun;165(1-4):475-89.
    PMID: 19440846 DOI: 10.1007/s10661-009-0960-3
    Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. This study examines transformation of nitrogen dioxide (NO(2)) into ozone (O(3)) at urban environment using time series plot. Data on the concentration of environmental pollutants and meteorological variables were employed to predict the concentration of O(3) in the atmosphere. Possibility of employing multiple linear regression models as a tool for prediction of O(3) concentration was tested. Results indicated that the presence of NO(2) and sunshine influence the concentration of O(3) in Malaysia. The influence of the previous hour ozone on the next hour concentrations was also demonstrated.
    Matched MeSH terms: Linear Models*
  5. 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
  6. Ganasegeran K, Renganathan P, Manaf RA, Al-Dubai SA
    BMJ Open, 2014;4(4):e004794.
    PMID: 24760351 DOI: 10.1136/bmjopen-2014-004794
    OBJECTIVE: To determine the prevalence and factors associated with anxiety and depression among type 2 diabetes outpatients in Malaysia.
    DESIGN: Descriptive, cross-sectional single-centre study with universal sampling of all patients with type 2 diabetes.
    SETTING: Endocrinology clinic of medical outpatient department in a Malaysian public hospital.
    PARTICIPANTS: All 169 patients with type 2 diabetes (men, n=99; women, n=70) aged between 18 and 90 years who acquired follow-up treatment from the endocrinology clinic in the month of September 2013.
    MAIN OUTCOME MEASURES: The validated Hospital Anxiety and Depression Scale (HADS), sociodemographic characteristics and clinical health information from patient records.
    RESULTS: Of the total 169 patients surveyed, anxiety and depression were found in 53 (31.4%) and 68 (40.3%), respectively. In multivariate analysis, age, ethnicity and ischaemic heart disease were significantly associated with anxiety, while age, ethnicity and monthly household income were significantly associated with depression.
    CONCLUSIONS: Sociodemographics and clinical health factors were important correlates of anxiety and depression among patients with diabetes. Integrated psychological and medical care to boost self-determination and confidence in the management of diabetes would catalyse optimal health outcomes among patients with diabetes.
    Study site: Endocrinology Clinic, Hospital Tengku Ampuan Rahimah Hospital (HTAR), Selangor, Malaysia
    Matched MeSH terms: Linear Models
  7. Al-Mansoob MAK, Al-Mazzah MM
    Med J Malaysia, 2005 Aug;60(3):349-57.
    PMID: 16379191
    The aim of study was to investigate the role of climate on the Malaria Incidence Rates (MIR) in some regions in of Yemen. For such purpose, the monthly (MIR) were calculated from the records of the hospitals' laboratories and centers of the Malaria Rollback centers in the main cities of the governorates Hudeidah, Taiz, Sana'a and Hadramout for the period 1989-1998. The readings of the climatic factors (CF) particularly the average monthly temperature (T), relative humidity (RH), volume of rain fall (RF) and wind speed (WS) for the same period of time were also collected from different weather and climatic information resources. Descriptive statistics, simple linear regression and multiple linear regression techniques were used to analyse the relationship between MIR and CF. The analysis shows highly significant relationship between MIR and the CF in these regions of Yemen (p-value 0.001).
    Matched MeSH terms: Linear Models
  8. Al-Naggar, Redhwan Ahmed
    MyJurnal
    Objective: The objective of this study was to determine the prevalence of the most common phobias and associated factors among university students. Methods: This cross-sectional study was carried out at Management and Science University (MSU). Random sampling was performed throughout all faculties. The questionnaires were distributed randomly at classes, library and university cafe within MSU. Diagnosis of anxiety disorders were established according to DSM-IV criteria. These criteria are included in Liebowitz Social Anxiety Scale (LSAS). The questionnaire consists of two sections. The first section consists of socio-demographic characteristics such as (age, sex, race, type of faculty and income); the second section is LSAS standard questionnaire. Multiple linear regression using backward analysis was performed to obtain the associated factors. Results: A total number of four hundred sixty eight (468) students participated in this study. The majority of them were older than 20
    years old, female, Malay and from non-medical and heath faculties (59.6%, 69.6%, 77.8%, 68.8%; respectively). Regarding history of abuse during childhood, the majority of the university students reported that there was no sexual, physical and emotional abuse during childhood (98.5%, 97.4%, 82.1%; respectively). The majority of the students (53.85%) reported that they have phobia. The highest type of phobia reported among university students was phobia from snake (11.5%), followed by speaking in front of crowd (9.2%) and the lowest were phobia of speed, dolls phobia, ropes phobia. Types of faculty, smoking status and history of physical abuse during childhood were the factors that significantly influence the social anxiety among university students in univariate and multivariate analysis. Conclusion: The prevalence of phobic symptoms among university students was
    high types of faculty; smoking status and history of physical abuse during childhood significantly influenced social anxiety among university students. Education and counseling university students is necessary to educate the students who suffer from phobia to cope with different situations during study period.
    Matched MeSH terms: Linear Models
  9. Teng KH, Kot P, Muradov M, Shaw A, Hashim K, Gkantou M, et al.
    Sensors (Basel), 2019 Jan 28;19(3).
    PMID: 30696110 DOI: 10.3390/s19030547
    : Concrete failure will lead to serious safety concerns in the performance of a building structure. It is one of the biggest challenges for engineers to inspect and maintain the quality of concrete throughout the service years in order to prevent structural deterioration. To date, a lot of research is ongoing to develop different instruments to inspect concrete quality. Detection of moisture ingress is important in the structural monitoring of concrete. This paper presents a novel sensing technique using a smart antenna for the non-destructive evaluation of moisture content and deterioration inspection in concrete blocks. Two different standard concrete samples (United Kingdom and Malaysia) were investigated in this research. An electromagnetic (EM) sensor was designed and embedded inside the concrete to detect the moisture content within the structure. In addition, CST microwave studio was used to validate the theoretical model of the EM sensor against the test data. The results demonstrated that the EM sensor at 2.45 GHz is capable of detecting the moisture content in the concrete with linear regression of R² = 0.9752. Furthermore, identification of different mix ratios of concrete were successfully demonstrated in this paper. In conclusion, the EM sensor is capable of detecting moisture content non-destructively and could be a potential technique for maintenance and quality control of the building performance.
    Matched MeSH terms: Linear Models
  10. Altowayti WAH, Othman N, Al-Gheethi A, Dzahir NHBM, Asharuddin SM, Alshalif AF, et al.
    Molecules, 2021 Oct 13;26(20).
    PMID: 34684757 DOI: 10.3390/molecules26206176
    Sustainable wastewater treatment is one of the biggest issues of the 21st century. Metals such as Zn2+ have been released into the environment due to rapid industrial development. In this study, dried watermelon rind (D-WMR) is used as a low-cost adsorption material to assess natural adsorbents' ability to remove Zn2+ from synthetic wastewater. D-WMR was characterized using scanning electron microscope (SEM) and X-ray fluorescence (XRF). According to the results of the analysis, the D-WMR has two colours, white and black, and a significant concentration of mesoporous silica (83.70%). Moreover, after three hours of contact time in a synthetic solution with 400 mg/L Zn2+ concentration at pH 8 and 30 to 40 °C, the highest adsorption capacity of Zn2+ onto 1.5 g D-WMR adsorbent dose with 150 μm particle size was 25 mg/g. The experimental equilibrium data of Zn2+ onto D-WMR was utilized to compare nonlinear and linear isotherm and kinetics models for parameter determination. The best models for fitting equilibrium data were nonlinear Langmuir and pseudo-second models with lower error functions. Consequently, the potential use of D-WMR as a natural adsorbent for Zn2+ removal was highlighted, and error analysis indicated that nonlinear models best explain the adsorption data.
    Matched MeSH terms: Linear Models
  11. Ahmad WMAW, Yaqoob MA, Noor NFM, Ghazali FMM, Rahman NA, Tang L, et al.
    Biomed Res Int, 2021;2021:5436894.
    PMID: 34904115 DOI: 10.1155/2021/5436894
    Background: Cancer is primarily caused by smoking, alcohol, betel quit, a series of genetic alterations, and epigenetic abnormalities in signaling pathways, which result in a variety of phenotypes that favor the development of OSCC. Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer, accounting for 80-90% of all oral malignant neoplasms. Oral cancer is relatively common, and it is frequently curable when detected and treated early enough. The tumor-node-metastasis (TNM) staging system is used to determine patient prognosis; however, geographical inaccuracies frequently occur, affecting management.

    Objective: To determine the additional relationship between factors discovered by searching for sociodemographic and metastasis factors, as well as treatment outcomes, which could help improve the prediction of the survival rate in cancer patients. Material and Methods. A total of 56 patients were recruited from the ambulatory clinic at the Hospital Universiti Sains Malaysia (USM). In this retrospective study, advanced computational statistical modeling techniques were used to evaluate data descriptions of several variables such as treatment, age, and distant metastasis. The R-Studio software and syntax were used to implement and test the hazard ratio. The statistics for each sample were calculated using a combination model that included methods such as bootstrap and multiple linear regression (MLR).

    Results: The statistical strategy showed R demonstrates that regression modeling outperforms an R-squared. It demonstrated that when data is partitioned into a training and testing dataset, the hybrid model technique performs better at predicting the outcome. The variable validation was determined using the well-established bootstrap-integrated MLR technique. In this case, three variables are considered: age, treatment, and distant metastases. It is important to note that three things affect the hazard ratio: age (β 1: -0.006423; p < 2e - 16), treatment (β 2: -0.355389; p < 2e - 16), and distant metastasis (β 3: -0.355389; p < 2e - 16). There is a 0.003469102 MSE for the linear model in this scenario.

    Conclusion: In this study, a hybrid approach combining bootstrapping and multiple linear regression will be developed and extensively tested. The R syntax for this methodology was designed to ensure that the researcher completely understood the illustration. In this case, a hybrid model demonstrates how this critical conclusion enables us to better understand the utility and relative contribution of the hybrid method to the outcome. The statistical technique used in this study, R, demonstrates that regression modeling outperforms R-squared values of 0.9014 and 0.00882 for the predicted mean squared error, respectively. The conclusion of the study establishes the superiority of the hybrid model technique used in the study.

    Matched MeSH terms: Linear Models
  12. 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
  13. Adeyi AA, Jamil SNAM, Abdullah LC, Choong TSY, Lau KL, Alias NH
    Molecules, 2020 Jun 07;25(11).
    PMID: 32517324 DOI: 10.3390/molecules25112650
    Proper remediation of aquatic environments contaminated by toxic organic dyes has become a research focus globally for environmental and chemical engineers. This study evaluates the adsorption potential of a polymer-based adsorbent, thiourea-modified poly(acrylonitrile-co-acrylic acid) (T-PAA) adsorbent, for the simultaneous uptake of malachite green (MG) and methylene blue (MB) dye ions from binary system in a continuous flow adsorption column. The influence of inlet dye concentrations, pH, flow rate, and adsorbent bed depth on adsorption process were investigated, and the breakthrough curves obtained experimentally. Results revealed that the sorption capacity of the T-PAA for MG and MB increase at high pH, concentration and bed-depth. Thomas, Bohart-Adams, and Yoon-Nelson models constants were calculated to describe MG and MB adsorption. It was found that the three dynamic models perfectly simulate the adsorption rate and behavior of cationic dyes entrapment. Finally, T-PAA adsorbent demonstrated good cyclic stability. It can be regenerated seven times (or cycles) with no significant loss in adsorption potential. Overall, the excellent sorption capacity and multiple usage make T-PAA polymer an attractive adsorbent materials for treatment of multicomponent dye bearing effluent in a fixed-bed column system.
    Matched MeSH terms: Linear Models
  14. Ganasegeran K, Al-Dubai SA, Qureshi AM, Al-abed AA, Am R, Aljunid SM
    Nutr J, 2012;11:48.
    PMID: 22809556 DOI: 10.1186/1475-2891-11-48
    BACKGROUND: Eating habits have been a major concern among university students as a determinant of health status. The aim of this study was to assess the pattern of eating habits and its associated social and psychological factors among medical students.
    METHODS: A cross sectional study was conducted among 132 medical students of pre-clinical phase at a Malaysian university. A self-administered questionnaire was used which included questions on socio-demography, anthropometry, eating habits and psychosocial factors.
    RESULTS: Mean (± SD) age of the respondents was 22.7 (± 2.4) years and (the age) ranged from 18 to 30 years. More than half had regular meals and breakfast (57.6% &, 56.1% respectively). Majority (73.5%) consumed fruits less than three times per week, 51.5% had fried food twice or more a week and 59.8% drank water less than 2 liters daily. Eating habits score was significantly low among younger students (18-22 years), smokers, alcohol drinkers and those who did not exercise. (p<0.05). Four psychological factors out of six, were significantly associated with eating habits (p<0.05). In multivariate analysis, age and 'eating because of feeling happy' were significantly associated with eating habits score (p<0.05).
    CONCLUSION: Most of the students in this study had healthy eating habits. Social and psychological factors were important determinants of eating habits among medical students.
    Study site: Management and Science University, Selangor, Malaysia
    Scales & Questionnaires: Compulsive Eating Scale
    Matched MeSH terms: Linear Models
  15. Akhabue E, Perak AM, Chan C, Greenland P, Allen NB
    J Pediatr, 2018 Nov;202:98-105.e6.
    PMID: 30177351 DOI: 10.1016/j.jpeds.2018.07.023
    OBJECTIVE: To assess whether racial differences in rates of change in body mass index (BMI) and blood pressure (BP) percentiles emerge during distinct periods of childhood.

    STUDY DESIGN: In this retrospective cohort study, we included children aged 5-20 years who received regular outpatient care at a large academic medical center between January 1996 and April 2016. BMI was expressed as age- and sex-specific percentiles and BP as age-, sex-, and height-specific percentiles. Linear mixed models incorporating linear spline functions with 2 breakpoints at 9 and 12 years of age were used to estimate the changes in BMI and BP percentiles over time during age periods: <9, 9-<12, and >12 years of age.

    RESULTS: Among 5703 children (24.8% black, 10.1% Hispanic), Hispanic females had an increased rate of change in BMI percentile per year relative to white females during ages 5-9 years (+2.94%; 95% CI, 0.24-5.64; P = .033). Black and Hispanic males also had an increased rate of change in BMI percentile per year relative to white males that occurred from ages 5-9 (+2.35% [95% CI, 0.76-3.94; P = .004]; +2.63% [95% CI, 0.31-4.95; P = .026], respectively). There were no significant racial differences in the rate of change of BP percentiles, although black females had higher hypertension rates compared with white females (10.0% vs 5.7%; P 

    Matched MeSH terms: Linear Models
  16. Esa R, Razak IA, Allister JH
    Community Dent Health, 2001 Mar;18(1):31-6.
    PMID: 11421403
    Data on malocclusion and orthodontic treatment need in Malaysia are limited. The purpose of this study was to evaluate malocclusion and orthodontic treatment need in a sample of 12-13-year-old schoolchildren using the Dental Aesthetic Index (DAI), and to assess the relationship between malocclusion and socio-demographic variables, perceptions of need for orthodontic treatment, aesthetic perception and social functioning.
    Matched MeSH terms: Linear Models
  17. Azbel L, Polonsky M, Wegman M, Shumskaya N, Kurmanalieva A, Asanov A, et al.
    Int J Drug Policy, 2016 Nov;37:9-20.
    PMID: 27455177 DOI: 10.1016/j.drugpo.2016.06.007
    BACKGROUND: Central Asia is afflicted with increasing HIV incidence, low antiretroviral therapy (ART) coverage and increasing AIDS mortality, driven primarily by people who inject drugs (PWID). Reliable data about HIV, other infectious diseases, and substance use disorders in prisoners in this region is lacking and could provide important insights into how to improve HIV prevention and treatment efforts in the region.

    METHODS: A randomly sampled, nationwide biobehavioural health survey was conducted in 8 prisons in Kyrgyzstan among all soon-to-be-released prisoners; women were oversampled. Consented participants underwent computer-assisted, standardized behavioural health assessment surveys and testing for HIV, HCV, HBV, and syphilis. Prevalence and means were computed, and generalized linear modelling was conducted, with all analyses using weights to account for disproportionate sampling by strata.

    RESULTS: Among 381 prisoners who underwent consent procedures, 368 (96.6%) were enrolled in the study. Women were significantly older than men (40.6 vs. 36.5; p=0.004). Weighted prevalence (%), with confidence interval (CI), for each infection was high: HCV (49.7%; CI: 44.8-54.6%), syphilis (19.2%; CI: 15.1-23.5%), HIV (10.3%; CI: 6.9-13.8%), and HBV (6.2%; CI: 3.6-8.9%). Among the 31 people with HIV, 46.5% were aware of being HIV-infected. Men, compared to women, were significantly more likely to have injected drugs (38.3% vs.16.0%; p=0.001). Pre-incarceration and within-prison drug injection, primarily of opioids, was 35.4% and 30.8%, respectively. Independent correlates of HIV infection included lifetime drug injection (adjusted odds ratio [AOR]=38.75; p=0.001), mean number of years injecting (AOR=0.93; p=0.018), mean number of days experiencing drug problems (AOR=1.09; p=0.025), increasing duration of imprisonment (AOR=1.08; p=0.02 for each year) and having syphilis (AOR=3.51; p=0.003), while being female (AOR=3.06; p=0.004) and being a recidivist offender (AOR=2.67; p=0.008) were independently correlated with syphilis infection.

    CONCLUSION: Drug injection, syphilis co-infection, and exposure to increased risk during incarceration are likely to be important contributors to HIV transmission among prisoners in Kyrgyzstan. Compared to the community, HIV is concentrated 34-fold higher in prisoners. A high proportion of undiagnosed syphilis and HIV infections presents a significant gap in the HIV care continuum. Findings highlight the critical importance of evidence-based responses within prison, including enhanced testing for HIV and sexually transmitted infections, to stem the evolving HIV epidemic in the region.

    Matched MeSH terms: Linear Models
  18. Hasyima Ismail N, Amin Safwan A, Fairuz Fozi N, Megat FH, Muhd Farouk H, Kamaruddin SA, et al.
    Pak J Biol Sci, 2017;20(3):140-146.
    PMID: 29023005 DOI: 10.3923/pjbs.2017.140.146
    BACKGROUND: Orange mud crab Scylla olivacea is one of the most important fisheries resources. A new development in ageing technique of crustaceans has been introduced. The detection of growth band deposited in hard structure of gastric mill in the cardiac stomach are found retained after moulting process can be used as age indicator and growth estimation.

    OBJECTIVE: This study was carried out to determine the comparison between carapace width and growth band count of S. olivacea in Malaysia.

    MATERIALS AND METHODS: Samples were collected from Setiu Wetlands, Terengganu, Malaysia from February until August, 2016. Samples were categorized based on their morphological measurements. The mesocardiac and zygocardiac ossicles in the gastric mill of S. olivacea was dissected out and preserved in solutions and underwent a cross sectioning process. A total of 76 of wild S. olivacea ranging from 6.56 to 12.84 cm in carapace width were analysed. The growth band counts were examined for each individual and ranging from 1 to 3 band counts.

    RESULTS: A positive linear relation was observed between CW and GBC with r2 = 0.5178, p<0.01. Overall, there was a strong, positive correlation between CW and GBC. Increase in CW were correlated with increases in GBC respectively for this species.

    CONCLUSION: Therefore, the carapace width, growth band counts and body weight can be used to improve data on growth, recruitment, maturation and mortality. Thus, this study would able to improve new ageing technique and contribute greatly to improve the conservation and management of S. olivacea in Setiu Wetlands, Terengganu, Malaysia.

    Matched MeSH terms: Linear Models
  19. Kassim MSA, Manaf MRA, Nor NSM, Ambak R
    Malays J Med Sci, 2017 Dec;24(6):83-91.
    PMID: 29379390 DOI: 10.21315/mjms2017.24.6.10
    Background: The obesity rate in Malaysia is the highest in Asia. Half its population is obese or overweight. The present study aims to determine the effects of lifestyle intervention on weight loss and blood pressure among Malaysian overweight and obese housewives in Klang Valley.

    Methods: A quasi-experimental study with 328 obese and overweight low socio- economic status housewives aged 18-59 years old who met the screening criteria participated in the study. They were recruited into an intervention group (N = 169) or control group (N = 159). The intervention group received a lifestyle intervention consisting of a diet, physical activity and self-monitoring behavior package. The control group (delayed intervention group) received a women's health seminar package. Both groups were followed up for six months. Weight, body mass index (BMI), and blood pressure were evaluated both pre- and post-intervention.

    Results: A total of 124 participants from the intervention group and 93 participants from the control group completed the study. Mean weight loss was 1.13 ± 2.70 kg (P < 0.05) in the intervention group and 0.97 ± 2.60 kg (P < 0.05) in the control group. Systolic blood pressure (SBP) reductions in the intervention group were 5.84 ± 18.10 mmHg (P < 0.05). The control group showed reduction in SBP 6.04 ± 14.52 mmHg (P < 0.05). Both group had non-significant DBP reduction. Multivariate analysis via General Linear Model Repeated Measures observed no significant differences in terms of parameter changes with time in both groups for all parameters.

    Conclusions: The results indicate that the lifestyle interventions in this study resulted in modest weight loss and thus decreased BMI and blood pressure (SBP) within six months of intervention.

    Matched MeSH terms: Linear Models
  20. Ahmad Mahir Razali, Khairiah Jusoh, Nor Asyikin A, Siti Adyani S, Wardatun Aathirah M, Maimon Abdullah, et al.
    Kajian yang dijalankan adalah berkaitan dengan penentuan model yang sesuai serta analisis data penyerapan logam berat oleh sayuran berdaun yang terpilih iaitu kangkung (Ipomea aquatica), sawi bunga (Brassica chinensis var parachinensis), bayam (Amaranthus oleraceus L) dan sawi putih (Brassica chinensis L.). Kajian ini bertujuan untuk menentukan dan membandingkan kandungan serta corak pengambilan logam berat yang diserap oleh sayuran dan juga bahagian-bahagiannya yang meliputi daun, batang dan akar. Penentuan model yang dibuat bertujuan bagi melihat corak penyerapan logam berat oleh sayuran atau bahagian sayuran tertentu. Logam berat yang dikaji terdiri daripada kadmium , kromium, kuprum, ferum , mangan, plumbum dan zink. Plot serakan digunakan bagi menentukan corak pengambilan logam berat dalam sayuran dan bahagian-bahagiannya. Selain itu ujian Kruskal-Wallis digunakan bagi membuat perbandingan median di antara logam berat yang diserap oleh sayuran yang dikaji. Nilai khi-kuasa dua dan juga nilai-p digunakan bagi menentukan sama ada sesuatu logam berat yang diserap itu berkait rapat dengan jenis sayuran secara signifikan. Secara umum bolehlah dikatakan bahawa logam Fe, Mn dan Zn adalah dominan dalam semua bahagian sayuran yang dikaji. Selain itu, melalui ujian Kruskal-Wallis didapati penyerapan kesemua logam berat pada setiap bahagian sayuran adalah berbeza secara signifikan. Penyuaian model regresi linear, kuadratik, kubik atau eksponen telah dilakukan terhadap data ini dan didapati kebanyakan data dapat disuaikan dengan baik oleh model kuadratik dan kubik berdasarkan nilai pekali penentuan (R2).
    Matched MeSH terms: Linear Models
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