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Application of loglinear models in estimating wet category in monthly rainfall

Wahidah Sanusi, Kamarulzaman Ibrahim

Sains Malaysiana, 2012;41:1345-1353.

Climate changes have become serious issues that have been widely discussed by researchers. One of the issues concerns with the study in changes of rainfall patterns. Changes in rainfall patterns affect the dryness and wetness conditions of a region. In this study, the three-dimensional loglinear model was used to fit the observed frequencies and to model the expected frequencies of wet class transition on eight rainfall stations in Peninsular Malaysia. The expected frequency values could be employed to determine the odds value of wet classes of each station. Further, the odds values were used to estimate the wet class of the following month if the wet class of the previous month and current month were identified. The wet classification based on SPI index (Standardized Precipitation Index). For station that was analyzed, there was no difference found were between estimated and observed wet classes. It was concluded that the loglinear models can be used to estimate the wetness classes through the estimates of odds values.

Matched MeSH terms: Linear Models
Application of multivariate membership function discrimination method for lithology identification

Jun Zhao, Feifei Wang, Yifan Lu

Sains Malaysiana, 2017;46:2223-2229.

Formation lithology identification is an indispensable link in oil and gas exploration. Precision of the traditional recognition method is difficult to guarantee when trying to identify lithology of particular formation with strong heterogeneity and complex structure. In order to remove this defect, multivariate membership function discrimination method is proposed, which regard to lithology identification as a linear model in the fuzzy domain and obtain aimed result with the multivariate membership function established. It is indicated by the test on lower carboniferous Bachu group bioclastic limestone section and Donghe sandstone section reservoir on T Field H area that satisfactory accuracy can be achieved in both clastic rock and carbonate formation and obvious advantages are unfold when dealing with complex formations, which shows a good application prospect and provides a new thought to solve complex problems on oilfield exploration and development with fuzzy theory.

Matched MeSH terms: Linear Models
Fulltext Application of pattern recognition tools for classifying acute coronary syndrome: an integrated medical modeling

Salari N, Shohaimi S, Najafi F, Nallappan M, Karishnarajah I

Theor Biol Med Model, 2013 Sep 18;10:57.
PMID: 24044669 DOI: 10.1186/1742-4682-10-57

OBJECTIVE: The classification of Acute Coronary Syndrome (ACS), using artificial intelligence (AI), has recently drawn the attention of the medical researchers. Using this approach, patients with myocardial infarction can be differentiated from those with unstable angina. The present study aims to develop an integrated model, based on the feature selection and classification, for the automatic classification of ACS.
METHODS: A dataset containing medical records of 809 patients suspected to suffer from ACS was used. For each subject, 266 clinical factors were collected. At first, a feature selection was performed based on interviews with 20 cardiologists; thereby 40 seminal features for classifying ACS were selected. Next, a feature selection algorithm was also applied to detect a subset of the features with the best classification accuracy. As a result, the feature numbers considerably reduced to only seven. Lastly, based on the seven selected features, eight various common pattern recognition tools for classification of ACS were used.
RESULTS: The performance of the aforementioned classifiers was compared based on their accuracy computed from their confusion matrices. Among these methods, the multi-layer perceptron showed the best performance with the 83.2% accuracy.
CONCLUSION: The results reveal that an integrated AI-based feature selection and classification approach is an effective method for the early and accurate classification of ACS and ultimately a timely diagnosis and treatment of this disease.

Matched MeSH terms: Linear Models
Application of regression and artificial neural network analysis of Red-Green-Blue image components in prediction of chlorophyll content in microalgae

Ying Ying Tang D, Wayne Chew K, Ting HY, Sia YH, Gentili FG, Park YK, et al.

Bioresour Technol, 2023 Feb;370:128503.
PMID: 36535615 DOI: 10.1016/j.biortech.2022.128503

This study presented a novel methodology to predict microalgae chlorophyll content from colour models using linear regression and artificial neural network. The analysis was performed using SPSS software. Type of extractant solvents and image indexes were used as the input data for the artificial neural network calculation. The findings revealed that the regression model was highly significant, with high R2 of 0.58 and RSME of 3.16, making it a useful tool for predicting the chlorophyll concentration. Simultaneously, artificial neural network model with R2 of 0.66 and low RMSE of 2.36 proved to be more accurate than regression model. The model which fitted to the experimental data indicated that acetone was a suitable extraction solvent. In comparison to the cyan-magenta-yellow-black model in image analysis, the red-greenblue model offered a better correlation. In short, the estimation of chlorophyll concentration using prediction models are rapid, more efficient, and less expensive.

Matched MeSH terms: Linear Models
Application of the Kvaal method for adult dental age estimation using Cone Beam Computed Tomography (CBCT)

Marroquin Penaloza TY, Karkhanis S, Kvaal SI, Nurul F, Kanagasingam S, Franklin D, et al.

J Forensic Leg Med, 2016 Nov;44:178-182.
PMID: 27821308 DOI: 10.1016/j.jflm.2016.10.013

Different non-invasive methods have been proposed for dental age estimation in adults, with the Kvaal et al. method as one of the more frequently tested in different populations. The purpose of this study was to apply the Kvaal et al. method for dental age estimation on modern volumetric data from 3D digital systems. To this end, 101 CBCT images from a Malaysian population were used. Fifty-five per cent were female (n = 55), and forty-five percent were male (n = 46), with a median age of 31 years for both sexes. As tomographs allow the observer to obtain a sagittal and coronal view of the teeth, the Kvaal pulp/root width measurements and ratios were calculated in the bucco-lingual and mesio-distal aspects of the tooth. From these data different linear regression models and formulae were built. The most accurate models for estimating age were obtained from a diverse combination of measurements (SEE ±10.58 years), and for the mesio-distal measurements of the central incisor at level A (SEE ±12.84 years). This accuracy, however is outside an acceptable range in for forensic application (SEE ±10.00 years), and is also more time consuming than the original approach based on dental radiographs.

Matched MeSH terms: Linear Models
Application of the threshold model for modelling and forecasting of exchange rate in selected ASEAN countries

Behrooz Gharleghi, Abu Hassan Shaari Md Nor, Tamat Sarmidi

Sains Malaysiana, 2014;43:1609-1622.

Linear time series models are not able to capture the behaviour of many financial time series, as in the cases of exchange rates and stock market data. Some phenomena, such as volatility and structural breaks in time series data, cannot be modelled implicitly using linear time series models. Therefore, nonlinear time series models are typically designed to accommodate for such nonlinear features. In the present study, a nonlinearity test and a structural change test are used to detect the nonlinearity and the break date in three ASEAN currencies, namely the Indonesian Rupiah (IDR), the Malaysian Ringgit (MYR) and the Thai Baht (THB). The study finds that the null hypothesis of linearity is rejected and evidence of structural breaks exist in the exchange rates series. Therefore, the decision to use the self-exciting threshold autoregressive (SETAR) model in the present study is justified. The results showed that the SETAR model, as a regime switching model, can explain abrupt changes in a time series. To evaluate the prediction performance of SETAR model, an Autoregressive Integrated Moving Average (ARIMA) model used as a benchmark. In order to increase the accuracy of prediction, both models are combined with an exponential generalised autoregressive conditional heteroscedasticity (EGARCH) model. The prediction results showed that the construct model of SETAR-EGARCH performs better than that of the ARIMA model and the combined ARIMA and EGARCH model. The results indicated that nonlinear models give better fitting than linear models.

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
Applied chemometric approach in identification sources of air quality pattern in Selangor, Malaysia

Ang KH

Sains Malaysiana, 2018;47:471-479.

In recent years, Malaysia has experienced quite a few number of chronic air pollution problems and it has become a
major contributor to the deterioration of human health and ecosystems. This study aimed to assess the air quality data
and identify the pattern of air pollution sources using chemometric analysis through hierarchical cluster analysis (HCA),
discriminant analysis (DA), principal component analysis (PCA) and multiple linear regression analysis (MLR). The air
quality data from January 2016 until December 2016 was obtained from the Department of Environment Malaysia. Air
quality data from eight sampling stations in Selangor include the selected variables of nitrogen dioxide (NO2
), ozone (O3
),
sulfur dioxide (SO2
), carbon monoxide (CO) and particulate matter (PM10). The HCA resulted in three clusters, namely low
pollution source (LPS), moderate pollution source (MPS) and slightly high pollution source (SHPS). Meanwhile, DA resulted
in two and four variables for the forward stepwise mode and the backward stepwise mode, respectively. Through PCA,
it was identified that the main pollutants of LPS, MPS and SHPS came from industrial and vehicle emissions, agricultural
systems, residential factors and natural emission sources. Among the three models yielded from the MLR analysis, it was
found that SHPS is the most suitable model to be used for the prediction of Air Pollution Index. This study concluded that
a clearer review and practical design of air quality monitoring network would be beneficial for better management of
air pollution. The study also suggested that chemometric techniques have the ability to show significant information on
spatial variability for large and complex air quality data.

Matched MeSH terms: Linear Models
Applying a data duplication technique in linear regression analysis of waiting time to pregnancy

Awang H

J Biosoc Sci, 2005 Jul;37(4):471-9.
PMID: 16082858

This analysis demonstrates the application of a data duplication technique in linear regression with censored observations of the waiting time to third pregnancy ending in two outcome types, using data from Malaysia. The linear model not only confirmed the results obtained by the Cox proportional hazards model, but also identified two additional significant factors. The method provides a useful alternative when Cox proportionality assumption of the hazards is violated.

Matched MeSH terms: Linear Models*
Fulltext Aqueous Extract of Nypa fruticans Wurmb. Vinegar Alleviates Postprandial Hyperglycemia in Normoglycemic Rats

Yusoff NA, Ahmad M, Al-Hindi B, Widyawati T, Yam MF, Mahmud R, et al.

Nutrients, 2015 Aug;7(8):7012-26.
PMID: 26308046 DOI: 10.3390/nu7085320

Nypa fruticans Wurmb. vinegar, commonly known as nipa palm vinegar (NPV) has been used as a folklore medicine among the Malay community to treat diabetes. Early work has shown that aqueous extract (AE) of NPV exerts a potent antihyperglycemic effect. Thus, this study is conducted to evaluate the effect of AE on postprandial hyperglycemia in an attempt to understand its mechanism of antidiabetic action. AE were tested via in vitro intestinal glucose absorption, in vivo carbohydrate tolerance tests and spectrophotometric enzyme inhibition assays. One mg/mL of AE showed a comparable outcome to the use of phloridzin (1 mM) in vitro as it delayed glucose absorption through isolated rat jejunum more effectively than acarbose (1 mg/mL). Further in vivo confirmatory tests showed AE (500 mg/kg) to cause a significant suppression in postprandial hyperglycemia 30 min following respective glucose (2 g/kg), sucrose (4 g/kg) and starch (3 g/kg) loadings in normal rats, compared to the control group. Conversely, in spectrophotometric enzymatic assays, AE showed rather a weak inhibitory activity against both α-glucosidase and α-amylase when compared with acarbose. The findings suggested that NPV exerts its anti-diabetic effect by delaying carbohydrate absorption from the small intestine through selective inhibition of intestinal glucose transporters, therefore suppressing postprandial hyperglycemia.

Matched MeSH terms: Linear Models
Artificial Light at Night and Cancer: Global Study

Al-Naggar RA, Anil Sh

Asian Pac J Cancer Prev, 2016 10 01;17(10):4661-4664.
PMID: 27892680

Background: Artificial light at night (ALAN) has been linked to increased risk of cancers in body sites like the breast
and colorectum. However exposure of ALAN as an environmental risk factor and its relation to cancers in humans has
never been studied in detail. Objective: To explore the association of ALAN with all forms of cancers in 158 countries.
Materials and Methods: An ecological study encompassing global data was conducted from January to June 2015,
with age-standardized rates (ASR) of cancers as the outcome measure. ALAN, in the protected areas, as the exposure
variable, was measured with reference to the Protected Area Light Pollution Indicator (PALI) and the Protected Area
Human Influence Indicator (PAHI). Pearson’s correlations were calculated for PALI and PAHI with ASR of cancers for
158 countries, adjusted for country populations, electricity consumption, air pollution, and total area covered by forest.
Stratified analysis was conducted according to the country income levels. Linear regression was applied to measure the
variation in cancers explained by PALI and PAHI. Results: PALI and PAHI were positively associated with ASR of all
forms of cancer, and also the four most common cancers (p < 0.05). These positive correlations remained statistically
significant for PAHI with all forms of cancer, lung, breast, and colorectal cancer after adjusting for confounders. Positive
associations of PALI and PAHI with cancers varied with income level of the individual countries. Variation in all forms
of cancers, and the four most common cancers explained by PALI and PAHI, ranged from 3.3 – 35.5%. Conclusion:
Artificial light at night is significantly correlated for all forms of cancer as well as lung, breast, colorectal, and prostate
cancers individually. Immediate measures should be taken to limit artificial light at night in the main cities around the
world and also inside houses.

Matched MeSH terms: Linear Models
Fulltext Ascariasis, trichuriasis, and growth of schoolchildren in Northeastern Peninsular Malaysia

Raj SM, Naing NN

Southeast Asian J. Trop. Med. Public Health, 1998 Dec;29(4):729-34.
PMID: 10772554

A study to determine the effect of antihelminthic treatment on growth and nutritional status was undertaken on 103 children in the second grade of primary school, 71 of whom were found to be infected with Ascaris lumbricoides or Trichuris trichiura. The median Ascaris and Trichuris intensities in the infected group were 19,600 (range; 0-488,000) and 2,800 (range; 0-84,600) eggs per gram of feces respectively. Forty-three children harbored both types of worm. Fourteen weeks after two 400 mg doses of albendazole were administered to infected children, the increases in weight, height, weight for age, height for age and weight for height were significantly higher among infected children than controls who were uninfected at baseline. The observed gains were independent of sex and socioeconomic status. Decrease in log transformed Trichuris intensity correlated with increases in weight (r=0.24; p=0.02) and weight for age (r=0.20; p=0.06) but decrease in Ascaris intensity did not correlate with increases in any of the anthropometric parameters. The results suggest that antihelminthic treatment has beneficial short-term effects on growth and nutritional status of a modest magnitude among early primary schoolchildren in the area.

Matched MeSH terms: Linear Models
Assessing bilingual Chinese-English young children in Malaysia using language sample measures

Ooi CC, Wong AM

Int J Speech Lang Pathol, 2012 Dec;14(6):499-508.
PMID: 23039126 DOI: 10.3109/17549507.2012.712159

One reason why specific language impairment (SLI) is grossly under-identified in Malaysia is the absence of locally- developed norm-referenced language assessment tools for its multilingual and multicultural population. Spontaneous language samples provide quantitative information for language assessment, and useful descriptive information on child language development in complex language and cultural environments. This research consisted of two studies and investigated the use of measures obtained from English conversational samples among bilingual Chinese-English Malaysian preschoolers. The research found that the language sample measures were sensitive to developmental changes in this population and could identify SLI. The first study examined the relationship between age and mean length of utterance (MLU(w)), lexical diversity (D), and the index of productive syntax (IPSyn) among 52 typically-developing (TD) children aged between 3;4-6;9. Analyses showed a significant linear relationship between age and D (r = .450), the IPsyn (r = .441), and MLU(w) (r = .318). The second study compared the same measures obtained from 10 children with SLI, aged between 3;8-5;11, and their age-matched controls. The children with SLI had significantly shorter MLU(w) and lower IPSyn scores than the TD children. These findings suggest that utterance length and syntax production can be potential clinical markers of SLI in Chinese-English Malaysian children.

Matched MeSH terms: Linear Models
Fulltext Assessment of predictive models for chlorophyll-a concentration of a tropical lake

Malek S, Syed Ahmad SM, Singh SK, Milow P, Salleh A

BMC Bioinformatics, 2011;12 Suppl 13:S12.
PMID: 22372859 DOI: 10.1186/1471-2105-12-S13-S12

This study assesses four predictive ecological models; Fuzzy Logic (FL), Recurrent Artificial Neural Network (RANN), Hybrid Evolutionary Algorithm (HEA) and multiple linear regressions (MLR) to forecast chlorophyll- a concentration using limnological data from 2001 through 2004 of unstratified shallow, oligotrophic to mesotrophic tropical Putrajaya Lake (Malaysia). Performances of the models are assessed using Root Mean Square Error (RMSE), correlation coefficient (r), and Area under the Receiving Operating Characteristic (ROC) curve (AUC). Chlorophyll-a have been used to estimate algal biomass in aquatic ecosystem as it is common in most algae. Algal biomass indicates of the trophic status of a water body. Chlorophyll- a therefore, is an effective indicator for monitoring eutrophication which is a common problem of lakes and reservoirs all over the world. Assessments of these predictive models are necessary towards developing a reliable algorithm to estimate chlorophyll- a concentration for eutrophication management of tropical lakes.

Matched MeSH terms: Linear Models*
Fulltext Association between dietary folate intake and blood status of folate and homocysteine in Malaysian adults

Chew SC, Khor GL, Loh SP

J Nutr Sci Vitaminol (Tokyo), 2011;57(2):150-5.
PMID: 21697634 DOI: 10.3177/jnsv.57.150

Folate is of prime interest among investigators in nutrition due to its multiple roles in maintaining health, especially in preventing neural tube defects and reducing the risk of cardiovascular diseases. We investigated the effect of dietary folate intake on blood folate, vitamin B(12), vitamin B(6), and homocysteine status. One hundred subjects consisting of Chinese and Malay subjects volunteered to participate in this cross-sectional study. Dietary folate intake was assessed by 24-h dietary recall and a food-frequency questionnaire (FFQ). Serum and red blood cell folate were analyzed using a microbiological assay, while serum vitamin B(12) was determined by electrochemiluminescence immunoassay (ECLIA), and high-performance liquid chromatography (HPLC) was used for the determination of serum vitamin B(6) and homocysteine. The mean folate intake, serum folate, RBC folate, serum vitamin B(12), and B(6), were higher in female subjects, with the exception of serum homocysteine. The Chinese tended to have higher folate intake, serum folate, RBC folate, and vitamin B(12). A positive association was found between folate intake and serum folate while a negative association was found between folate intake and serum homocysteine. Stepwise linear regression of serum folate showed a significant positive coefficient for folate intake whilst a significant negative coefficient was found for serum homocysteine when controlling for age, gender, and ethnicity. In conclusion, high dietary folate intake helps to increase serum folate and to lower the homocysteine levels.

Matched MeSH terms: Linear Models
Fulltext Association between eating behaviour and weight gain among primary school children in Bandar Baru Bangi, Selangor

Norliza Ahmad, Munn-Sann Lye, Zalilah Mohd Shariff, Firdaus Mukhtar, Lim Poh Ying

Malaysian Journal of Medicine and Health Sciences, 2019;15(104):86-86.
MyJurnal

Introduction: Childhood obesity is increasing in prevalence in Malaysia. Excess in dietary intake and inadequate physical activity contribute to the development of obesity among children. The objective of this study was to de-termine the association between eating behaviour and excess weight among primary school children in an urban community in Malaysia. Methods: This is a baseline data of a randomized control field trial of a family-based inter-vention to reduce adiposity in overweight and obese children. It involved five primary government schools in Bandar Baru Bangi, Selangor. The inclusion criteria include parent-child dyad; children aged 7 to 10 years with body mass index (BMI) z-score of +1 standard deviation or more. Parents completed the validated self-administered Children Eating Behaviour Questionnaire (CEBQ). This questionnaire assessed children’s eating behaviour that includes food responsiveness, enjoyment of food, emotional overeating, desire to drink, slowness in eating, satiety responsiveness, emotional undereating and food fussiness. The children’s weight and height were measured and the BMI z-score was calculated. The association between CEBQ subscales and obesity was assessed using multiple linear regression, adjusted for sex and family income. Results: One hundred and thirty-four parent-child dyads had participated in this study. The food responsiveness was found to be significant with excess weight (β = 0.094, 95% CI: 0.02-0.17, p= 0.014). Conclusion: The food responsiveness subscale was associated with excess weight. This eating behaviour need to be taken into consideration in the development and implementation of health campaign targeted at the re-duction of childhood obesity.

Matched MeSH terms: Linear Models
Fulltext Association between long-term exposure to ambient air pollution and prevalence of diabetes mellitus among Malaysian adults

Wong SF, Yap PS, Mak JW, Chan WLE, Khor GL, Ambu S, et al.

Environ Health, 2020 04 03;19(1):37.
PMID: 32245482 DOI: 10.1186/s12940-020-00579-w

BACKGROUND: Malaysia has the highest rate of diabetes mellitus (DM) in the Southeast Asian region, and has ongoing air pollution and periodic haze exposure.
METHODS: Diabetes data were derived from the Malaysian National Health and Morbidity Surveys conducted in 2006, 2011 and 2015. The air pollution data (NOx, NO2, SO2, O3 and PM10) were obtained from the Department of Environment Malaysia. Using multiple logistic and linear regression models, the association between long-term exposure to these pollutants and prevalence of diabetes among Malaysian adults was evaluated.
RESULTS: The PM10 concentration decreased from 2006 to 2014, followed by an increase in 2015. Levels of NOx decreased while O3 increased annually. The air pollutant levels based on individual modelled air pollution exposure as measured by the nearest monitoring station were higher than the annual averages of the five pollutants present in the ambient air. The prevalence of overall diabetes increased from 11.4% in 2006 to 21.2% in 2015. The prevalence of known diabetes, underdiagnosed diabetes, overweight and obesity also increased over these years. There were significant positive effect estimates of known diabetes at 1.125 (95% CI, 1.042, 1.213) for PM10, 1.553 (95% CI, 1.328, 1.816) for O3, 1.271 (95% CI, 1.088, 1.486) for SO2, 1.124 (95% CI, 1.048, 1.207) for NO2, and 1.087 (95% CI, 1.024, 1.153) for NOx for NHMS 2006. The adjusted annual average levels of PM10 [1.187 (95% CI, 1.088, 1.294)], O3 [1.701 (95% CI, 1.387, 2.086)], NO2 [1.120 (95% CI, 1.026, 1.222)] and NOx [1.110 (95% CI, 1.028, 1.199)] increased significantly from NHMS 2006 to NHMS 2011 for overall diabetes. This was followed by a significant decreasing trend from NHMS 2011 to 2015 [0.911 for NO2, and 0.910 for NOx].
CONCLUSION: The findings of this study suggest that long-term exposure to O3 is an important associated factor of underdiagnosed DM risk in Malaysia. PM10, NO2 and NOx may have mixed effect estimates towards the risk of DM, and their roles should be further investigated with other interaction models. Policy and intervention measures should be taken to reduce air pollution in Malaysia.

Matched MeSH terms: Linear Models
Fulltext Association between maternal food group intake and birth size

LOY S, MARHAZLINA M, HAMID JAN J

Sains Malaysiana, 2013;42(11):1633-1640.

Maternal nutrition is one of the dominant factors in determining fetal growth and subsequent developmental health for both mother and child. This study aimed to explore the association between maternal consumption of food groups and birth size among singleton, termed newborns. One hundred and eight healthy pregnant women in their third trimester, aged 19 to 40 years who visited the Obstetrics and Gynecology Clinic of Hospital Universiti Sains Malaysia completed an interviewed-administered, validated semi-quantitative food frequency questionnaire. The maternal socio-demographic, medical and obstetric histories and anthropometry measurements were recorded accordingly. The pregnancy outcomes, birth weight, birth length and head circumference were obtained from the medical records. The data were analyzed using multiple linear regression by controlling for possible confounders. Among all food groups, fruits intake was associated with higher birth weight (p=0.018). None of the food intake showed evident association with respect to birth length while only fruits intake was associated positively with head circumference (p=0.019). In contrast, confectioneries and condiments were associated with lower birth weight (p=0.013 and p=0.001, respectively). Also, condiments appeared to associate inversely with ponderal index (p=0.015). These findings suggest the potential beneficial effects of micronutrient rich food but detrimental effects of high sugar and sodium food on fetal growth. Such an effect may have long term health consequences to the lives of children.

Matched MeSH terms: Linear Models
Association of Eating Behavior With Nutritional Status and Body Composition in Primary School-Aged Children

Tay CW, Chin YS, Lee ST, Khouw I, Poh BK, SEANUTS Malaysia Study Group

Asia Pac J Public Health, 2016 07;28(5 Suppl):47S-58S.
PMID: 27252248 DOI: 10.1177/1010539516651475

Problematic eating behaviors during childhood may lead to positive energy balance and obesity. Therefore, this study aims to investigate the association of eating behaviors with nutritional status and body composition in Malaysian children aged 7 to 12 years. A total of 1782 primary schoolchildren were randomly recruited from 6 regions in Malaysia. The multidimensional Children's Eating Behaviour Questionnaire (CEBQ) was reported by parents to determine the 8 different dimensions of eating styles among children. Body mass index (BMI), BMI-for-age Z-score, waist circumference, and body fat percentage were assessed. Linear regression analyses revealed that both food responsiveness and desire to drink subscales were positively associated with a child's body adiposity, whereas satiety responsiveness, slowness in eating, and emotional undereating subscales were negatively associated with adiposity (all P < .05). A multidimensional eating style approach based on the CEBQ is needed to promote healthy eating behaviors in order to prevent excessive weight gain and obesity problems among Malaysian children.

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

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