scholarly journals Determinant of Mother’s Health Promotional Measures Practice of Infant with Age 6–12 Months in a Tertiary Hospital of Nepal

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Chet Kant Bhusal
Keyword(s):  
Logistic Regression ◽  
Goodness Of Fit ◽  
Good Practice ◽  
Medical Science ◽  
Outpatient Department ◽  
Bivariate Analysis ◽  
Monthly Income ◽  
Index Child ◽  
Multivariable Logistic Regression Model ◽  
Birth Space

Background. Promotion of health is vital for the optimal growth and development of every infant. Globally, many infants died due to common problems such as diarrhoea and respiratory infection; most of these problems are related to inadequate breast feeding, improper complimentary feeding, lack of immunization, and home accident. Infant and child health status depends upon mothers’ knowledge and practice regarding health promotional measures. This study aimed to determine practice and its determinants regarding health promotional measures of infant with 6–12 months age amongst the mothers attending Pediatrics Outpatient Department of Universal College of Medical Science and Teaching Hospital, Bhairahawa, Rupandehi, Nepal. Methods. Hospital-based cross-sectional study was conducted in Universal College of Medical Science, Bhairahawa, Rupandehi, Nepal, among 414 mothers attending pediatrics outpatient department from September 2019–March 2020. Purposive sampling technique was used to select mothers of infants aged 6–12 months. Bivariate analysis was used primarily to assess the association between dependent and independent variables. Variables which were associated in bivariate analysis with p < 0.05 were entered into a multivariable logistic regression model to identify associated factors of health promotional measures. The goodness of fit of multivariate logistic regression was checked by Nagelkerke R square and variation inflation factor. Results. The mean age and family size was 25.89 ± 4.81 years and 5.94 ± 2.48, respectively. A total of 71.5% mothers have good practice of health promotional measures. Mothers from Dalit caste (adjusted odds ratio = 0.04, confidence interval: 0.005–0.30), mothers with below school leaving certificate education (AOR = 0.08, CI: 0.02–0.27), fathers engaged in nonagricultural work (AOR = 7.21, CI: 2.59–20.11), birth space of index child greater than 2 years (AOR = 12.88, CI: 3.49–47.58), and family monthly income greater than 20000 Nepalese rupees (AOR = 3.29, CI: 1.16–13.32 were significantly associated with good practice of health promotional measures. Conclusions. More than one-fourth of the mothers have poor practice of health promotional measures. Ethnicity, mothers’ education, fathers’ occupation, birth space of index child, and family monthly income were found to be independent determinants of practice of health promotion measures. Thus, policy makers should provide specific education regarding health promotional measures to both parents.

Risk factors for incidence of trachomatous scarring in a cohort of women in low endemic district

2018 ◽  
Vol 102 (4) ◽  
pp. 419-423 ◽  
Author(s):  
Rabia Karani ◽  
Meraf Wolle ◽  
Harran Mkocha ◽  
Beatriz Muñoz ◽  
Sheila K West
Keyword(s):  
Socioeconomic Status ◽  
Logistic Regression ◽  
Demographic Factors ◽  
Bivariate Analysis ◽  
Fire Exposure ◽  
Lower Socioeconomic Status ◽  
Multivariable Logistic Regression Model ◽  
Lower Socioeconomic ◽  
Endemic District

Background/aimsTo determine the incidence of scarring in women in a trachoma low endemic district of rural Tanzania and to determine the effects of lifetime cooking fire exposure and markers of lower socioeconomic status on incidence of scarring in these women.MethodsA prospective cohort study was conducted over a 3.5-year period from 2013 to 2016 in 48 villages in Kongwa, Tanzania where trachoma at baseline was 5.2% in children. A random sample of 2966 women aged 15 and older who were at risk for incident scarring were eligible for follow-up. Data on demographic factors, cooking fire exposure and trachomatous scarring were gathered at baseline and follow-up. An index of lifetime exposure to cooking fire exposure was created and bivariate analysis, age-adjusted logistic regression and multivariable logistic models were used to look for associations of demographic factors and cooking fire exposure with incident trachomatous scarring.ResultsThe cumulative incidence of scarring was 7.1% or 2.0% per year. Incidence of scarring increased with age and exposure to markers of lower socioeconomic status. A multivariable logistic regression model adjusting for confounding factors did not find an association between lifetime cooking fire exposure and incidence of scarring (OR=0.92; 95% CI 0.68 to 1.24, P=0.58).ConclusionsThere was still incident scarring in women in Tanzania despite low rates of active trachoma. There was no association between exposure to cooking fires and incident scarring. More research is needed to understand the factors that contribute to new scarring in these women.

scholarly journals Knowledge Regarding Health Promotional Measures of Infant among Mothers Attending Pediatric OPD of Universal College of Medical Sciences

2020 ◽  
Vol 8 (02) ◽  
pp. 57-62
Author(s):  
Chet Kant Bhusal ◽  
Sigma Bhattarai ◽  
Raju Kafle ◽  
Rubina Shrestha
Keyword(s):  
Rural Area ◽  
Family Size ◽  
Teaching Hospital ◽  
Associated Factors ◽  
Cross Sectional Study ◽  
Outpatient Department ◽  
Medical Sciences ◽  
Index Child ◽  
Cross Sectional ◽  
Birth Space

INTRODUCTION Infant and child health status depends upon knowledge of mothers regarding health promotional measures. This study aimed to determine knowledge and its associated factors regarding health promotional measures of infants amongst the mothers attending pediatrics outpatient department of Universal College of Medical Sciences Teaching Hospital, Bhairahawa, Rupandehi, Nepal. MATERIAL AND METHODS Hospital based cross-sectional study was conducted in Universal College of Medical Sciences Teaching Hospital, Bhairahawa, Rupandehi, Nepal among 414 mothers attending pediatrics outpatient department from June 2019 to March 2020. Bivariate and multivariate logistic regressions were used to explore associations between different factors with health promotional measures. RESULTS The mean age and family size was 25.89 ±4.81 and 5.94 ±2.48 respectively. A total of 73.2% mothers have good knowledge of health promotional measures. Mothers greater than 20 years (AOR =8.13, CI: 2.16-30.67), Dalit (AOR=0.02, CI: 0.003-0.16), living in rural area (AOR=0.27, CI: 0.08-0.61), family size greater than 5 (AOR =3.99, CI: 1.37-11.59), below SLC education (AOR=0.29, CI: (0.09-0.88) and fathers with SLC and above education (AOR=25.40, CI: 4.54-142.0), fathers engaged in non-agricultural work (AOR =4.78, CI: 1.80-12.68) and birth space of index child greater than two years (AOR =5.88, CI: 1.48-23.55) were significantly associated with knowledge of health promotional measures. CONCLUSIONS Mothers’ age, caste, residence, family size, education of parents, occupation of father and birth space of index child were found to be independent associated factors of knowledge. Thus policy makers should provide specific education regarding health promotional measures to both parents focusing rural area. Similarly, local Government needs to subsidize in reducing teenage marriage.  

ANALISIS HUBUNGAN SARANA, PENGETAHUAN, DAN SIKAP BIDAN PRAKTIK MANDIRI DENGAN KEPATUHAN MENJALANKAN STANDAR PELAYANAN ANTENATAL CARE DI KOTA PADANGSIDIMPUAN

2019 ◽  
Vol 2 (1) ◽  
pp. 27-33
Author(s):  
Megawati Sinambela ◽  
Evi Erianty Hasibuan
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Antenatal Care ◽  
Pregnant Women ◽  
Logistic Regression Analysis ◽  
Care Service ◽  
Multivariate Logistic Regression Analysis ◽  
Bivariate Analysis ◽  
Cross Sectional ◽  
The North

Antenatal care is a service provided to pregnant women to monitor, support maternal health and detect mothers whether normal or problematic pregnant women. According to the WHO, globally more than 70% of maternal deaths are caused by complications of pregnancy and childbirth such as hemorrhage, hypertension, sepsis, and abortion. Based on data obtained from the profile of the North Sumatra provincial health office in 2017, in the city of Padangsidimpuan in 2017 the coverage of ANC visits reached (76.58%) and had not reached the target in accordance with the 2017 Provincial Health Office strategy plan (95%). This type of research was an observational analytic study with a cross sectional design. The population in this study were independent practice midwives who were in the Padangsidimpuan, the sample in this study amounted to 102 respondents. The technique of collecting data used questionnaires and data analysis used univariate, bivariate and multivariate analysis with logistic regression analysis. Based on bivariate analysis showed that there was a relationship between facilities, knowledge and attitudes of independent midwives with compliance with the standards of antenatal care services with a value of p <0.05. The results of the study with multivariate logistic regression analysis showed that the factors associated with the compliance of independent midwives in carrying out antenatal care service standards were attitudes with values (p = 0.026).

Cardiovascular Risk Prediction using JBS3 Tool: A Kerala based Study

2020 ◽  
Vol 16 ◽  
Author(s):  
Paulin Paul ◽  
Noel George ◽  
B. Priestly Shan
Keyword(s):  
Logistic Regression ◽  
Cardiovascular Risk ◽  
Risk Prediction ◽  
Goodness Of Fit ◽  
Significant Risk ◽  
Lifetime Risk ◽  
British Society ◽  
Cvd Risk ◽  
South Indian ◽  
Cardiovascular Risk Prediction

Background: The accuracy of Joint British Society calculator3 (JBS3) cardiovascular risk prediction may vary within Indian population, and is not yet studied using south Indian Kerala based population data. Objectives: To evaluate the cardiovascular disease (CV) risk estimation using the traditional CVD risk factors (TRF) in Kerala based population. Methods: This cross sectional study has 977 subjects aged between 30 and 80 years. The traditional CVD risk markers are recorded from the medical archives of clinical locations at Ernakulum district, in Kerala The 10 year risk categories used are low (<7.5%), intermediate (≥7.5% and <20%), and high (≥20%). The lifetime classifications low lifetime (≤39%) and high lifetime (≥40%) are used. The study was evaluated using statistical analysis. Chi-square test was done for dependent and categorical CVD risk variable comparison. Multivariate ordinal logistic regression for 10-year risk model and odds logistic regression analysis for lifetime model was used to identify significant risk variables. Results: The mean age of the study population is 52.56±11.43 years. The risk predictions has 39.1% in low, 25.0% in intermediate, and 35.9% had high 10-year risk. The low lifetime risk had 41.1% and 58.9% is high lifetime risk. Reclassifications to high lifetime are higher from intermediate 10-year risk category. The Hosmer-Lemeshow goodness-of-fit statistics indicates a good model fit. Conclusion: The risk prediction and timely intervention with appropriate therapeutic and lifestyle modification is useful in primary prevention. Avoiding short-term incidences and reclassifications to high lifetime can reduce the CVD mortality rates.

scholarly journals Risk factors for peripheral venous catheter failure: A prospective cohort study of 5345 patients

2021 ◽  
pp. 112972982110150
Author(s):  
Ya-mei Chen ◽  
Xiao-wen Fan ◽  
Ming-hong Liu ◽  
Jie Wang ◽  
Yi-qun Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Cohort Study ◽  
Goodness Of Fit ◽  
Insertion Site ◽  
Healthcare Providers ◽  
Venous Catheter ◽  
Goodness Of Fit Test ◽  
Peripheral Venous Catheter ◽  
Independent Risk Factors

Purpose: The objective of this study was to determine the independent risk factors associated with peripheral venous catheter (PVC) failure and develop a model that can predict PVC failure. Methods: This prospective, multicenter cohort study was carried out in nine tertiary hospitals in Suzhou, China between December 2017 and February 2018. Adult patients undergoing first-time insertion of a PVC were observed from catheter insertion to removal. Logistic regression was used to identify the independent risk factors predicting PVC failure. Results: This study included 5345 patients. The PVC failure rate was 54.05% ( n = 2889/5345), and the most common causes of PVC failure were phlebitis (16.3%) and infiltration/extravasation (13.8%). On multivariate analysis, age (45–59 years: OR, 1.295; 95% CI, 1.074–1.561; 60–74 years: OR, 1.375; 95% CI, 1.143–1.654; ⩾75 years: OR, 1.676; 95% CI, 1.355–2.073); department (surgery OR, 1.229; 95% CI, 1.062–1.423; emergency internal/surgical ward OR, 1.451; 95% CI, 1.082–1.945); history of venous puncture in the last week (OR, 1.298, 95% CI 1.130–1.491); insertion site, number of puncture attempts, irritant fluid infusion, daily infusion time, daily infusion volume, and type of sealing liquid were independent predictors of PVC failure. Receiver operating characteristic curve analysis indicated that a logistic regression model constructed using these variables had moderate accuracy for the prediction of PVC failure (area under the curve, 0.781). The Hosmer-Lemeshow goodness of fit test demonstrated that the model was correctly specified (χ2 = 2.514, p = 0.961). Conclusion: This study should raise awareness among healthcare providers of the risk factors for PVC failure. We recommend that healthcare providers use vascular access device selection tools to select a clinically appropriate device and for the timely detection of complications, and have a list of drugs classified as irritants or vesicants so they can monitor patients receiving fluid infusions containing these drugs more frequently.

scholarly journals Development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ehab Nooh ◽  
Colin Griesbach ◽  
Johannes Rösch ◽  
Michael Weyand ◽  
Frank Harig
Keyword(s):  
Logistic Regression ◽  
Risk Score ◽  
Characteristic Curve ◽  
Multivariable Analysis ◽  
Individual Risk ◽  
Dependent Diabetes Mellitus ◽  
Analysis Model ◽  
Multivariable Logistic Regression Model ◽  
Sternal Dehiscence ◽  
Multivariable Logistic Regression

Abstract Background After sternotomy, the spectrum for sternal osteosynthesis comprises standard wiring and more complex techniques, like titanium plating. The aim of this study is to develop a predictive risk score that evaluates the risk of sternum instability individually. The surgeon may then choose an appropriate sternal osteosynthesis technique that is risk- adjusted as well as cost-effective. Methods Data from 7.173 patients operated via sternotomy for all cardiovascular indications from 2008 until 2017 were retrospectively analyzed. Sternal dehiscence occurred in 2.5% of patients (n = 176). A multivariable analysis model examined pre- and intraoperative factors. A multivariable logistic regression model and a backward elimination based on the Akaike Information Criterion (AIC) a logistic model were selected. Results The model showed good sensitivity and specificity (area under the receiver-operating characteristic curve, AUC: 0.76) and several predictors of sternal instability could be evaluated. Multivariable logistic regression showed the highest Odds Ratios (OR) for reexploration (OR 6.6, confidence interval, CI [4.5–9.5], p < 0.001), obesity (body mass index, BMI > 35 kg/m2) (OR 4.23, [CI 2.4–7.3], p < 0.001), insulin-dependent diabetes mellitus (IDDM) (OR 2.2, CI [1.5–3.2], p = 0.01), smoking (OR 2.03, [CI 1.3–3.08], p = 0.001). After weighting the probability of sternum dehiscence with each factor, a risk score model was proposed scaling from − 1 to 5 points. This resulted in a risk score ranging up to 18 points, with an estimated risk for sternum complication up to 74%. Conclusions A weighted scoring system based on individual risk factors was specifically created to predict sternal dehiscence. High-scoring patients should receive additive closure techniques.

scholarly journals Prediction of successful de-cannulation of tracheostomised patients in medical intensive care units

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Chul Park ◽  
Ryoung-Eun Ko ◽  
Jinhee Jung ◽  
Soo Jin Na ◽  
Kyeongman Jeon
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Goodness Of Fit ◽  
Characteristic Curve ◽  
Multivariable Logistic Regression Analysis ◽  
Limited Data ◽  
Underlying Malignancy ◽  
Medical Intensive Care ◽  
Good Calibration

Abstract Background Limited data are available on practical predictors of successful de-cannulation among the patients who undergo tracheostomies. We evaluated factors associated with failed de-cannulations to develop a prediction model that could be easily be used at the time of weaning from MV. Methods In a retrospective cohort of 346 tracheostomised patients managed by a standardized de-cannulation program, multivariable logistic regression analysis identified variables that were independently associated with failed de-cannulation. Based on the logistic regression analysis, the new predictive scoring system for successful de-cannulation, referred to as the DECAN score, was developed and then internally validated. Results The model included age > 67 years, body mass index < 22 kg/m2, underlying malignancy, non-respiratory causes of mechanical ventilation (MV), presence of neurologic disease, vasopressor requirement, and presence of post-tracheostomy pneumonia, presence of delirium. The DECAN score was associated with good calibration (goodness-of-fit, 0.6477) and discrimination outcomes (area under the receiver operating characteristic curve 0.890, 95% CI 0.853–0.921). The optimal cut-off point for the DECAN score for the prediction of the successful de-cannulation was ≤ 5 points, and was associated with the specificities of 84.6% (95% CI 77.7–90.0) and sensitivities of 80.2% (95% CI 73.9–85.5). Conclusions The DECAN score for tracheostomised patients who are successfully weaned from prolonged MV can be computed at the time of weaning to assess the probability of de-cannulation based on readily available variables.

Factors Associated with Intention to Vaccinate against COVID-19 in Puerto Rico: An Online Survey of Adults (Preprint)

2021 ◽  
Author(s):  
Kyle Melin ◽  
Cheyu Zhang ◽  
Juan Pablo Zapata ◽  
Yonaira M. Rivera ◽  
Katie Fernandez ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Puerto Rico ◽  
Online Survey ◽  
Multivariate Logistic Regression Analysis ◽  
International Health ◽  
Bivariate Analysis ◽  
Sources Of Information ◽  
Multivariate Logistic Regression ◽  
Factors Associated ◽  
Bisexual Identity

UNSTRUCTURED COVID-19 has been particularly devastating to Black and Latinx communities in the U.S. However, data on acceptability of the COVID-19 vaccines among minority populations are limited. We conducted an online survey among adults in Puerto Rico to identify factors associated with intention to vaccinate against COVID-19. Sociodemographic variables were analyzed independently for association with intention to vaccinate. Significant associations were included in the multivariate logistic regression analysis. A total of 1016 responses were available for analysis. In the bivariate analysis, younger age, higher education, pre-covid employment, male sex, gay/bisexual identity, and single marital status were associated with increased intention to vaccinate. In the multivariate logistic regression, younger, male respondents who had higher educational attainment reported higher intention to vaccinate. Lower-income and living outside the San Juan metro region were associated with lower intention to vaccinate. National and international health organizations were identified as the most reliable sources of information, followed by healthcare professionals. These findings highlight the importance of considering sociodemographic characteristics identified with low intention to vaccinate as well as using trusted sources of information when designing public messaging related to increasing COVID-19 vaccinations.

scholarly journals A Comparison Study of Goodness of Fit Tests of Logistic Regression in R: Simulation and Application to Breast Cancer Data

2020 ◽  
pp. 50-59
Author(s):  
El-Housainy A. Rady ◽  
Mohamed R. Abonazel ◽  
Mariam H. Metawe’e
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Sample Size ◽  
Null Hypothesis ◽  
Goodness Of Fit ◽  
Quadratic Term ◽  
Breast Cancer Dataset ◽  
Cancer Data ◽  
Interaction Term ◽  
Test Package

Goodness of fit (GOF) tests of logistic regression attempt to find out the suitability of the model to the data. The null hypothesis of all GOF tests is the model fit. R as a free software package has many GOF tests in different packages. A Monte Carlo simulation has been conducted to study two situations; the first, studying the ability of each test, under its default settings, to accept the null hypothesis when the model truly fitted. The second, studying the power of these tests when assumptions of sufficient linear combination of the explanatory variables are violated (by omitting linear covariate term, quadratic term, or interaction term). Moreover, checking whether the same test in different R packages had the same results or not. As the sample size supposed to affect simulation results, so the pattern of change of GOF tests results under different sample sizes as well as different model settings was estimated. All tests accept the null hypothesis (more than 95% of simulation trials) when the model truly fitted except modified Hosmer-Lemeshow test in "LogisticDx" package under all different model settings and Osius and Rojek’s (OsRo) test when the true model had an interaction term between binary and categorical covariates. In addition, le Cessie-van Houwelingen-Copas-Hosmer unweighted sum of squares (CHCH) test gave unexpected different results under different packages. Concerning the power study, all tests had a very low power when a departure of missing covariate existed. Generally, stukel’s test (package ’LogisticDX) and CHCH test (package "RMS") reached a power in detecting a missing quadratic term greater than 80% under lower sample size while OsRo test (package ’LogisticDX’) was better in detecting missing interaction term. Beside the simulation study, we evaluated the performance of GOF tests using the breast cancer dataset.

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