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Divisional Variations in Safe Maternal Delivery Practices in Bangladesh: A logistic regression Analysis

Asian Journal of Medical Sciences 2009年第1期1卷 15-18页

作者： Mah Fuzar Rahman Nazrul Islam Mondal Rafiqul Islam Department of Population Science and Human Resource. Development University of Rajshahi

The aim of this article is to determine the effectiveness of the existing safe-delivery facilities in six divisions of Bangladesh and also investigate the effects of some selected factors in taking assistance from medically-trained persons, such as doctors, trained nurses or midwives, or family welfare visitors during delivery, with a view to reducing maternal morbidity and mortality in Bangladesh so that the country would be able to reach the Millennium Development Goals (MDGs) by 2015. Data for the study were drawn from the Bangladesh Demographic and Health Survey (BDHS), 2004. The study was executed separately for six administrative divisions for the five-year period preceding the survey, having an eligible woman with one or more child(ren). Well-known statistical tools, such as Pearson chi-square test and logistic regression model, were used for analyzing data. It is apparent from the study that the overall performance of respondents of six divisions towards safe delivery practices was very low. The divisional variations were also clearly evident in the study. Respondents’ and their husbands’ education, place of residence, electrification, husbands’ occupational status, and respondents’ exposures to mass media were significantly (p<0.001) associated with the delivery assistance taken from medically-trained persons. The probability of safe maternal delivery practice increased with the increase in education for both respondents and their husbands. Finally, the paper provides some additional suggestive policy measures that the planners and implementers may consider for quality development of the inconsistent factors.

关键词： Delivery Maternal mortality Neonatal mortality Chi-square test logistic regression model

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A multi-level analysis of risk factors for Schistosoma japonicum infection in China

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INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES 2009年第6期13卷 E407-E412页

作者： Yang, Jianzhou Zhao, Zhengyuan Li, Yuesheng Krewski, Daniel Wen, Shi Wu Cent S Univ Sch Publ Hlth Changsha Hunan Peoples R China Changzhi Med Coll Dept Prevent Med Changzhi Shanxi Peoples R China Hunan Inst Parasit Dis Yueyang Hunan Peoples R China Queensland Inst Med Res Australian Ctr Int & Trop Hlth & Nutr Mol Parasitol Lab Brisbane Qld 4006 Australia Univ Ottawa McLaughlin Ctr Populat Hlth Risk Assessment Inst Populat Hlth Ottawa ON Canada Univ Ottawa Dept Epidemiol & Community Med Fac Med Ottawa ON Canada Univ Ottawa OMNI Res Grp Dept Obstet & Gynecol Fac Med Ottawa ON K1H 8L6 Canada Clin Epidemiol Program Ottawa Hlth Res Inst Ottawa ON Canada

Objective: The aim of this study was to explore the risk factors of schistosomiasis japonica in China, using a hierarchical multi-level model with individuals nested within villages. Methods: A cross-sectional survey of schistosomiasis japonica was conducted in 16 villages in the Chinese province of Hunan. A multi-level modeling technique (HLM version 6.04) was used to assess risk factors of schistosomiasis. The results from this multi-level model were compared with those from a conventional single-level logistic regression model. Results: A total of 10 245 individuals were enrolled in this study, of whom about 4.1% were infected with Schistosoma japonicum. In the multi-level model analysis, individual level variables such as gender, age, and occupation, and village level variables such as type of S. japonicum endemic area, drinking water source, sewage treatment, June temperature, and April rainfall were associated with schistosomiasis japonica infection. Conventional single-level logistic regression analysis selected more independent variables, and had narrower confidence intervals around the corresponding regression coefficients. In particular, per capita income, precipitation in October, and density of infected snails were statistically significant in the conventional single-level logistic regression analysis but not in the multi-level model. Conclusions: Multi-level modeling is a useful tool in the analysis of risk factors of schistosomiasis japonica. Because the multi-level model captures the hierarchical structure of the data, it may be considered a more appropriate analytical tool for data of this type. This technique may also be useful in the analysis of other infectious diseases with a similar hierarchical structure. (C) 2009 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

关键词： Schistosoma japonicum China Risk factors Multi-level model logistic regression model

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Identification of invasive vegetation using hyperspectral remote sensing in the California Delta ecosystem

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REMOTE SENSING OF ENVIRONMENT 2008年第11期112卷 4034-4047页

作者： Hestir, Erin L. Khanna, Shruti Andrew, Margaret E. Santos, Maria J. Viers, Joshua H. Greenberg, Jonathan A. Rajapakse, Sepalika S. Ustin, Susan L. Univ Calif Davis Dept Land Air & Water Resources Davis CA 95616 USA Univ Calif Davis Dept Environm Sci & Policy Davis CA 95616 USA

Estuaries are among the most invaded ecosystems on the planet. Such invasions have led in part, to the formation of a massive $1 billion restoration effort in California's Sacramento-San Joaquin River Delta. However, invasions of weeds into riparian, floodplain, and aquatic habitats threaten the success of restoration efforts within the watershed and jeopardize economic activities. The doctrine of early detection and rapid response to invasions has been adopted by land and water resource managers, and remote sensing is the logical tool of choice for identification and detection. However meteorological, physical, and biological heterogeneity in this large system present unique challenges to successfully detecting invasive weeds. We present three hyperspectral case studies which illustrate the challenges, and potential solutions, to mapping invasive weeds in wetland systems: 1) Perennial pepperweed was mapped over one portion of the Delta using a logistic regression model to predict weed occurrence. 2) Water hyacinth and 3) submerged aquatic vegetation (SAV). primarily composed of Brazilian waterweed, were mapped over the entire Delta using a binary decision tree that incorporated spectral mixture analysis (SMA), spectral angle mapping (SAM), band indexes, and continuum removal products. Perennial pepperweed detection was moderately successful;phenological stage influenced detection rates. Water hyacinth was mapped with modest accuracies, and SAV was mapped with high accuracies. Perennial pepperweed and water hyacinth both exhibited significant spectral variation related to plant phenology. Such variation must be accounted for in order to optimally map these species, and this was done for the water hyacinth case study. Submerged aquatic vegetation was not mapped to the species level due to complex non-linear mixing problems between the water column and its constituents, which was beyond the scope of the current study. We discuss our study in the context of providing g

关键词： Aquatic and wetland weeds logistic regression model Spectral mixture analysis Spectral Angle Mapper Hyperspectral HyMap Phenology

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Efficient experimental designs for sigmoidal growth models

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JOURNAL OF STATISTICAL PLANNING AND INFERENCE 2008年第1期138卷 2-17页

作者： Dette, Holger Pepelyshev, Andrey Ruhr Univ Bochum Fak Math D-44780 Bochum Germany St Petersburg State Univ Dept Math St Petersburg Russia

For the Weibull- and Richards-regression model robust designs are determined by maximizing a minimum of D- or D-1-efficiencies, taken over a certain range of the non-linear parameters. It is demonstrated that the derived designs yield a satisfactory solution of the optimal design problem for this type of model in the sense that these designs are efficient and robust with respect to misspecification of the unknown parameters. Moreover, the designs can also be used for testing the postulated form of the regression model against a simplified sub-model. (c) 2007 Elsevier B.V. All rights reserved.

关键词： sigmoidal growth Weibull regression model exponential regression model Richards-regression model logistic regression model robust optimal design goodness-of-fit test

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The hazard of being an English football league manager: empirical estimates for three recent league seasons

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2008年第7期59卷 884-891页

作者： Bachan, R. Reilly, B. Witt, R. Univ Surrey Dept Econ Guildford GU2 7XH Surrey England Univ Sussex Brighton E Sussex England Univ Brighton Brighton E Sussex England

This paper uses data drawn from the English Football League to model separate hazard rates for club managers for the 2001/2, 2002/3 and 2003/4 seasons. On average over the three seasons, approximately one-third of managers involuntarily exited employment status with their club. We model the hazard using a standard logistic model exploiting information on the spell at risk rather than the individual. The role of neglected heterogeneity is also examined using random and fixed effects logistic models within a discrete-time setting. League position at the start of the spell at risk is found to be the most important determinant of a manager's involuntary exit. A variety of individual specific human capital and other covariates are found to be unimportant in determining the hazard and no role for unobservable heterogeneity as captured by random effects is detected.

关键词： hazard rate logistic regression model sports

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Habitat suitability assessment for the endangered Nilgiri Laughingthrush: A multiple logistic regression approach

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CURRENT SCIENCE 2008年第11期94卷 1487-1494页

作者： Zarri, Ashfaq A. Rahmani, Asad R. Singh, A. Kushwaha, S. P. S. Univ Florida Dept Wildlife Ecol & Conservat Gainesville FL USA Govt India Indian Inst Remote Sensing Dept Space Dehra Dun 248001 Uttar Pradesh India Bombay Nat Hist Soc Mumbai 400023 Maharashtra India

Application of remote sensing and Geographic Information System (GIS) tools has assumed an increasingly important role in conservation biology and wildlife management by providing means for modelling potential distributions of species and their habitats, unlike the conventional ground surveys. We present here a predictive model of habitat suitability for the Nilgiri Laughingthrush, Garrulax cachinnans based on a synergistic use of field surveys and digitally processed satellite imagery combined with features mapped using GIS data layers. Collateral data were created in a GIS framework based on ground surveys comprising layers such as land-use, measures of proximity to likely features of disturbance and a digital terrain model. Multiple binomial logistic regression approach was used for modelling, and the model performance was assessed by the area under the receiver operating characteristics (ROC) curve. About 320 km(2), 25.12% of the area of the Nilgiris considered for modelling was predicted to be suitable for the Nilgiri Laughingthrush. The area under the ROC curve was found to be 0.984 +/- 0.003 (R-2: 0.93 at P < 0.0001), implying, a highly effective model. The assessed suitable habitat was highly fragmented and comprised of 1352 patches (natural as well as man-made) distributed all over the study area. The smallest suitable patch identified by the model was 400 m(2) and the largest patch 17.65 km(2). Also, ca. 92% of all patches were smaller than 0.5 km(2). We presume that some suitable habitat patches may be unoccupied due to strong fidelity of the species to shola (montane wet temperate forest) patches, low colonization rates, or large inter-fragment distances. Also, larger fragments might serve as source or 'exporters' of surplus individuals to maintain sink populations throughout the rest of the range. We discuss the implication of habitat fragmentation and narrow geographical range and anthropogenic pressure for the conservation of the Nilgiri Laughingthrus

关键词： field surveys habitat suitability logistic regression model Nilgiri Laughingthrush

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Technology scoring model for reflecting evaluator's perception within confidence limits

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2008年第3期184卷 981-989页

作者： Moon, Tae Hee Sohn, So Young Yonsei Univ Dept Informat & Ind Engn Seoul 120749 South Korea

The main purpose of this study is to propose a new technology scoring model for reflecting the total perception scoring phenomenon which happens often in many evaluation settings. A base model used is a logistic regression for non-default prediction of a firm. The point estimator used to predict the probability for non-default based on this model does not consider the risk involved in the estimation error. We propose to update the point estimator within its confidence interval using the evaluator's perception. The proposed approach takes into account not only the risk involved in the estimation error of the point estimator but also the total perception scoring phenomenon. Empirical evidence of a better prediction ability of the proposed model is displayed in terms of the area under the ROC curves. Additionally, we showed that the proposed model can take advantage when it is applied to smaller data size. It is expected that the proposed approach can be applied to various technology related decision-makings such as R&D investment, alliance, transfer, and loan. (C) 2006 Elsevier B.V. All rights reserved.

关键词： technology scoring perception scoring phenomenon logistic regression model confidence interval ROC curve

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Non-Cognitive Psychopathological Symptoms Associated with Incident Mild Cognitive Impairment and Dementia, Alzheimer's Type

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NEUROTOXICITY RESEARCH 2008年第2-3期14卷 263-272页

作者： Lobo, Antonio Lopez-Anton, Raul De-La-Camara, Concepcion Quintanilla, Miguel Angel Campayo, Antonio Saz, Pedro Univ Zaragoza Inst Aragones Ciencias Salud Dept Psychiat Zaragoza Spain Hosp Clin Univ Zaragoza Spain

Objective: To test the hypothesis that specific psychopathological non-cognitive symptoms are associated with incident mild cognitive impairment (MCI), while different symptoms are associated with incident dementia of Alzheimer's type (DAT). Methods: A representative community sample of 4,803 individuals aged 55+ years was interviewed in a two-phase screening, in Wave I or ZARADEMP I. This is the baseline, cross-sectional study of the ZARADEMP Project, a longitudinal study to document incidence and risk factors of dementia. The main instrument for assessment of participants was the ZARADEMP Interview, which includes standardized Spanish versions of instruments such as the Mini-Mental Status Examination and the Geriatric Mental State GMS-AGECAT. Two years later, in Wave II or ZARADEMP II, the cognitively non-deteriorated elderly were reassessed in a similar, two-phase procedure. "Incident cases" of both dementia and DAT (DSM-IV-TR criteria), as well as MCI (operationally defined Petersen's criteria) were diagnosed by a panel of psychiatrists. Statistical, logistic regression models, adjusted by age, sex and education were used to test the hypothesized association. Results: "Irritability", "neurovegetative symptoms", "sleep problems", "concentration difficulties", "loneliness" and "subjective slowing" documented at baseline were associated with incident MCI (odds ratio, OR range 1.71-2.67). A different profile of non-cognitive symptoms was associated with incident DAT, specifically "tension" (OR= 2.45), "sleep problems" (OR= 2.81), and "observed slowing" (OR= 4.35). On the contrary, "subjective restriction of activities" seemed to be negatively associated with DAT (OR= 0.12). Conclusions: To our knowledge, this is the first report about some specific psychopathological, non-cognitive symptoms associated with incident MCI and/or incident DAT, when controlling by each other. The psychopathological profile associated with MCI is different from the profile preceding DAT.

关键词： Dementia Dementia of Alzheimer's Type Community study Non-Cognitive symptoms logistic regression model

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A topography-based model of forest cover at the alpine tree line in the tropical Andes

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JOURNAL OF BIOGEOGRAPHY 2008年第4期35卷 711-723页

作者： Bader, Maaike Y. Ruijten, Johan J. A. Univ Wageningen & Res Ctr Ctr Geoinformat NL-6700 AA Wageningen Netherlands

Aim To present a method that assesses the influence of environmental variables, including climate, substrate, topography, and anthropogenic disturbances, on the distribution of Andean forest at the tree line, and to compare this forest distribution between areas. Location Sangay National Park, on the eastern slopes of the Andes in central Ecuador. Methods A logistic regression model was built using topographical variables and environmental indices, derived from a digital elevation model, to explain forest cover, derived from a Landsat ETM image, in a zone around the average tree line altitude. Results The model shows that after altitude, which can explain about 80% of forest cover, wetness has the next strongest effect (areas accumulating water, but also cold air, were devoid of forest, resulting in inverted tree lines), followed by eastness (western slopes had forest to higher altitudes). Application of the model in two nearby areas showed that the real tree line was lower than the predicted tree line in both areas, probably owing mainly to macroclimatic differences in one area, and partly also to human land use in the other. The locations with the largest deviations could be the focus of further research concerning human impacts on tree line vegetation. Main conclusions The tree line is located at lower altitudes on east-facing slopes, which may be because high levels of radiation are received by east-facing slopes in the clear mornings, resulting in the photoinhibition of tree seedlings in the paramo. In spite of the limitations of the quality and resolution of the remote sensing data, the presented method provides indications for important ecological factors at the tree line. The method also allows the detection of differences in tree line position between areas, which may reflect climatic differences or the location of anthropogenic disturbances.

关键词： Andes cloud forest digital elevation model Ecuador logistic regression model paramo remote sensing Sangay National Park topography

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Estimation of the determinants of bicycle mode share for the journey to work using census data

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TRANSPORTATION 2008年第1期35卷 93-109页

作者： Parkin, John Wardman, Mark Page, Matthew Univ Bolton Bolton BL3 5AB England Univ Leeds Inst Transport Studies Leeds LS2 9JT W Yorkshire England

A model is presented that relates the proportion of bicycle journeys to work for English and Welsh electoral wards to relevant socio-economic, transport and physical variables. A number of previous studies have exploited existing disaggregate data sets. This study uses UK 2001 census data, is based on a logistic regression model and provides complementary evidence based on aggregate data for the determinants of cycle choice. It suggests a saturation level for bicycle use of 43%. Smaller proportions cycle in wards with more females and higher car ownership. The physical condition of the highway, rainfall and temperature each have an effect on the proportion that cycles to work, but the most significant physical variable is hilliness. The proportion of bicycle route that is off-road is shown to be significant, although it displays a low elasticity (+0.049) and this contrasts with more significant changes usually forecast by models constructed from stated preference based data. Forecasting shows the trend in car ownership has a significant effect on cycle use and offsets the positive effect of the provision of off-road routes for cycle traffic but only in districts that are moderately hilly or hilly. The provision of infrastructure alone appears insufficient to engender higher levels of cycling.

关键词： bicycle journey to work logistic regression model census travel demand modelling

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