scholarly journals Factors associated with anaemia among women of reproductive age in Ethiopia: Multilevel ordinal logistic regression analysis

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Lire Lemma Tirore ◽  
Afework Mulugeta ◽  
Abate Bekele Belachew ◽  
Menaseb Gebrehaweria ◽  
Abraham Sahilemichael ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Ordinal Logistic Regression ◽  
Reproductive Age ◽  
Women Of Reproductive Age ◽  
Factors Associated ◽  
Ordinal Logistic Regression Analysis

Decline of gustatory sensitivity with the progression of Alzheimer's disease

2015 ◽  
Vol 28 (3) ◽  
pp. 511-517 ◽  
Author(s):  
Mariko Sakai ◽  
Manabu Ikeda ◽  
Hiroaki Kazui ◽  
Kazue Shigenobu ◽  
Takashi Nishikawa
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Ordinal Logistic Regression ◽  
Threshold Values ◽  
Ordinal Logistic Regression Analysis ◽  
And Control ◽  
Detection And Recognition

ABSTRACTBackground:Patients with Alzheimer's disease (AD) manifest various impairments in eating behavior. However, few previous studies have directly investigated the gustatory function of AD patients, and results have been inconsistent.Methods:Thirty-two AD patients (Clinical Dementia Rating (CDR) 0.5/1/2, respectively 11/15/6 patients) and 22 normal control participants were examined to measure detection and recognition thresholds of the four elemental tastes (sweet, salty, sour, and bitter), and their ability to discriminate between tastes. Effects of demographic and clinical factors (age, sex, histories of alcohol and tobacco consumption, and CDR grade) on gustatory threshold were examined using ordinal logistic regression analysis. Performance was compared between AD and control groups.Results:Total threshold values (the sum of threshold grades for the four tastes) for detection and recognition of tastes were significantly higher in the AD group. Detection thresholds for sweet, salty, and bitter, and recognition thresholds for sweet and sour, were also significantly higher in the AD group. Ordinal logistic regression analysis revealed that CDR grade was the only factor that significantly affected both total threshold values. Regarding taste discrimination, there were no significant differences between the AD group and control group.Conclusions:These findings suggest that progression of dementia severity accompanies gustatory decline. Although it seemingly paradoxical, weight loss and preference for sweet tastes are frequently, often simultaneously, observed in AD. Gustatory dysfunction may be partially involved in these symptoms. Thus, the nutritional care of patients with AD could be improved by making the taste of meals stronger, while controlling calorie and mineral intake.

scholarly journals Total small vessel disease burden and functional outcome in patients with ischemic stroke

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242319
Author(s):  
Wi-Sun Ryu ◽  
Sang-Wuk Jeong ◽  
Dong-Eog Kim
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Functional Outcome ◽  
Logistic Regression Analysis ◽  
Small Vessel Disease ◽  
Ordinal Logistic Regression ◽  
Small Vessel ◽  
Vessel Disease ◽  
Ordinal Logistic Regression Analysis

Background Cerebral small vessel disease (SVD) is comprised of lacunes, cerebral microbleeds (CMBs), white matter hyperintensities (WMHs), and enlarged perivascular space (EPVS). We investigated the cumulative effect of SVD on 3-month functional outcome following ischemic stroke using the total SVD score. Methods The total SVD score of 477 acute ischemic stroke patients with adequate brain MRI was analyzed. We used multivariable ordinal logistic regression analysis to investigate the independent impact of total SVD score on ordinal modified Rankin Scale (mRS) score at 3-month after ischemic stroke. Results Mean age was 66±14 years, and 61% were men. The distribution of the total SVD score from 0 to 4 was 27%, 24%, 26%, 16%, and 7%, respectively. The proportion of mRS scores 2 or greater was 16% and 47% in total SVD score 0 and 4, respectively. Multivariable ordinal logistic regression analysis results showed that compared with the total SVD score of 0, total SVD scores of 2, 3, and 4 were independently associated with higher mRS scores with adjusted odds ratios (95% confidence intervals) of 1.68 (1.02–2.76), 2.24 (1.25–4.00), and 2.00 (1.02–4.29). Lacunes, CMBs, WMHs but not EPVS were associated with mRS scores at 3 months. However, the impact of each SVD marker on stroke outcome was smaller than that of the total SVD score. Conclusion We found an independent association between total SVD scores and functional outcome at 3 months following ischemic stroke. The total SVD score may be useful for stratification of patients who are at a high-risk of unfavorable outcomes.

scholarly journals Pola Spasial dan Keputusan Keluarga Bermukim di Permukiman Kumuh Pusat Kota dan Wilayah Pinggiran Kota Malang, Jawa Timur

2021 ◽  
Vol 35 (1) ◽  
pp. 64
Author(s):  
Irvan Ardiansyah ◽  
Satti Wagistina
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Low Income ◽  
Family Members ◽  
Ordinal Logistic Regression ◽  
Economic Conditions ◽  
River Bank ◽  
Ordinal Logistic Regression Analysis ◽  
Economic Needs

Abstrak. Perkembangan kawasan permukiman kumuh di Kota Malang disebabkan oleh faktor urbanisasi dan  penduduk asli yang penghasilan rendah sehingga berakibat pada rendahnya daya beli terhadap rumah layak huni dan berlokasi di zona permukiman ideal. Kedua golongan masyarakat ini mendorong  untuk memilih lokasi bermukim di wilayah yang tidak seharusnya dijadikan kawasan permukiman sehingga menyebakan kemunculan kawasan permukiman kumuh baru. Tujuan penelitian ini adalah; 1) mengetahui pola spasial permukiman kumuh pusat kota dan wilayah pinggiran; 2) mengetahui hubungan kondisi sosial ekonomi masyarakat terhadap permukiman kumuh pusat kota dan wilayah pinggiran. Wilayah kajian permukiman kumuh pusat Kota Malang berada di Kelurahan Kauman, sedangkan wilayah pinggiran berada di Kelurahan Tlogomas. Kedua wilayah tersebut berdasarkan SK Walikota Malang termasuk dalam kawasan permukiman kumuh yang terdapat di Kota Malang. Penelitian ini menggunakan pendekatan kuantitatif. Alat analisis yang digunakan yakni Sistem Informasi Geografis (SIG) dengan metode overlay untuk mengetahui pola spasial permukiman kumuh. Untuk mengetahui keputusan keluarga bermukim di permukiman kumuh digunakan uji regresi logistik ordinal. Hasil penelitian menunjukkan kawasan permukiman kumuh pusat kota memiliki pola linier sepanjang Sungai Kasin. Kawasan permukiman kumuh wilayah pinggiran memiliki pola linier dan memusat. Hasil analisis regresi logistik ordinal menunjukkan keputusan keluarga bermukim di permukiman kumuh secara signifikan dipengaruhi oleh kondisi sosial ekonomi yang meliputi tingkat pendidikan, jumlah anggota keluarga, dan kebutuhan ekonomi untuk permukiman kumah pusat Kota Malang. Keputusan keluarga untuk bermukim di permukiman kumuh wilayah pinggiran dipengaruhi oleh kebutuhan ekonomi, pendapatan, jumlah anggota keluarga, dan jenis pekerjaan.   Abstract. The emergent growing of slums in Malang City has been caused by urbanization and the locals with low income making it hard for them to afford proper housing located in ideal residential zones. These two groups of societies have triggered the choice to reside in the improper areas, and thus new slums emerge. This current study aimed at: 1) describing the spatial pattern of the slums in the down town and suburb area; and 2) investigating the correlation between socio-economic conditions of the societies and the slums in the down towan and suburb area. The slum in down town Malang City was Kauman Sub-district; while the slum in the suburb area was Tlogomas Sub-district. Both locations have been pronounced as the slums within the Decree Statement of the Mayor of Malang. This study was conducted by means of quantitative approach. Geographic Information System (GIS) was employed as the analysis. Overlay method was used to detect the spatial patterns of the slums and ordinal logistic regression was performed to investigate the correlation between socio-economic conditions of the societies and the slums. It has been revealed that the slum in the downtown portrayed a linear pattern along Kasin river bank. The slum in the suburb area showed linear and centered patterns. The ordinal logistic regression analysis resulted in the notion that the decision to reside in the slums has been significantly affected by the socio-economic conditions. The results of ordinal-logistic regression analysis showed that the family's decision to live in the slum was significantly influenced by socio-economic conditions including education level, number of family members, and economic needs for slum in the downtown.  The family's decision to live in the slum areas in surburb area was influenced by economic needs, income, number of family members, and their professions.     

scholarly journals Perbandingan Analisis Diskriminan dan Analisis Regresi Logistik Ordinal dalam Prediksi Klasifikasi Kondisi Kesehatan Bank

2017 ◽  
Vol 7 (2) ◽  
pp. 92
Author(s):  
Fajri Zufa ◽  
Sigit Nugroho ◽  
Mudin Simanihuruk
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Discriminant Analysis ◽  
Logistic Regression Analysis ◽  
Prediction Accuracy ◽  
Secondary Data ◽  
Ordinal Logistic Regression ◽  
Capital Adequacy ◽  
Ordinal Logistic Regression Analysis

The purpose of this research is to compare the accuracy of bank classification prediction based on Capital Adequacy Ratio (CAR), Earning Asset Quality (EAQ), Non Performing Loan (NPL), Return on Assets (ROA), Net Interest Margin (NIM), Short Term Mismatch (STM) and Loan to Deposit Ratio (LDR). Discriminant analysis and ordinal logistic regression analysis are compared in classifying the prediction. The data used are secondary data, namely data classification of bank conditions in Indonesia in 2014 obtained from research institute PT Infovesta Utama. Based on Apparent Error Rate (APER) score obtained, it can be said that discriminant analysis is better in predicting the classification of bank conditions in Indonesia than that of ordinal logistic regression analysis. Discriminant analysis has the average prediction accuracy of 80%, while ordinal logistic regression analysis has the average prediction accuracy of 74,38%.

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