Abstract MP29: Factors Associated With Stability of Metabolically Healthy Obesity: The Coronary Artery Risk Development in Young Adults (CARDIA) Study

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Sarah M Camhi ◽  
Aviva Must ◽  
Philimon N Gona ◽  
Arlene Hankinson ◽  
Andrew Odegaard ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Alcohol Intake ◽  
Multinomial Logistic Regression ◽  
Multinomial Logistic Regression Analysis ◽  
Factors Associated ◽  
Lower Alcohol ◽  
Total Alcohol ◽  
Metabolically Healthy ◽  
Baseline Bmi ◽  
Metabolically Unhealthy Obesity

Background: The demographic, behavioral or lifestyle factors associated with transitioning from metabolically healthy (MHO) to metabolically unhealthy obesity (MUO) are unknown. Methods: CARDIA participants (n=735) were included if they were not obese (BMI <30 kg/m 2 ) at baseline and developed obesity at exams 7, 10, 15, 20, or 25 years. MHO was defined as the presence of obesity and 0-1 risk factor: SBP/DBP ≥130/85mmHg; glucose ≥100mg/dL; triglycerides (≥150mg/dL); and HDL-C (men <40, women <50mg/dL) or on relevant medication. MUO was defined as obesity and 2+ risk factors. Duration of MHO and obesity were estimated (yrs). Phenotypes were categorized by MHO duration (%; MHO duration÷obesity duration): stable MHO (100%); transient MHO (1-99%); MUO (0%). Factors were compared between phenotypes using linear or logistic regression (adjusted for sex, race, baseline BMI, age). Multinomial logistic regression analysis was used to determine which factors [obesity duration, BMI change (ΔBMI), obesity onset age, physical activity (PA), alcohol intake, smoking] associated with transient MHO and MUO, relative to stable MHO. Results: Participants were 55% black and 72% women. Relative to transient MHO (n=184, 25%), stable MHO (n=347, 47%) had 5.4±0.5 yrs later obesity onset, 3.4±0.4 kg/m 2 smaller ΔBMI, 5.6±0.5 yrs shorter obesity duration, and 2.4±0.5 yrs longer MHO duration (all p<0.0001), with no significant differences for PA (moderate, vigorous or total), alcohol or smoking. Relative to stable MHO, transient MHO were less likely to be female, but more likely to smoke, have increased obesity duration and ΔBMI. Relative to stable MHO, MUO (n=204, 28%) were less likely to be female or black, more likely to smoke, have lower total PA, lower alcohol, and increased ΔBMI (Table 1). Conclusion: Obesity duration, ΔBMI and smoking were the strongest correlates of transition from MHO to MUO. MUO were more likely to have adverse health factors. Additional research should explore the cardiovascular consequences of the transition of MHO to MUO.

scholarly journals Prevalence and Factors Associated to Persistent Anemia among Pregnant Women in the Buea Health District, Cameroon

2021 ◽  
pp. 20-27
Author(s):  
Simon Eyongabane Ako ◽  
Bimabam Josiah ◽  
Oscar Sakwe ◽  
Tembong Nerville ◽  
Vicky Tankeu Ndassi
Keyword(s):  
Logistic Regression ◽  
Pregnant Women ◽  
Multinomial Logistic Regression ◽  
Health District ◽  
Folate Intake ◽  
Cross Sectional ◽  
Multinomial Logistic Regression Analysis ◽  
Factors Associated ◽  
Intervention Measures ◽  
The Impact

Introduction: Anemia in pregnancy represents a life-threatening but preventable reason for maternal and childhood morbidity and mortality. Although intervention measures are practiced in most affected countries like Cameroon, the impact of anemia on pregnant women is still apparent in most local communities. The relative contribution of sociodemographic related to anemia throughout gestation varies greatly and warrants investigation in urban and rural communities in developing countries, where the condition is most apparent. Methods: A cross-sectional study design was carried out from February to July 2019 at six sites, Regional Hospital Buea, Bokwango Integrated Health Center (IHC), Buea - Road IHC, Buea town IHC, Molyko IHC, and Great Soppo IHC. A total of 408 pregnant women were enrolled in the study. The sociodemographic characteristics identified through questionnaires filled by the participants included age, marital status, educational status, occupation, gravida status, alcohol intake, iron folate intake, knowledge on anemia and crave for non-food substance. The clinical factors of participants gathered included previous records of diarrhea within the last 6 months, diagnosis for worm infection for the last 6 months, diagnosis for Malaria for the last 6 months. A blood sample was collected and analyzed with a haemoglobinometer ( HemoCue  201+ system, Sweden). SPSS version 22 statistical package software was used to perform the data analysis. Factors related to anemia among participants unadjusted and adjusted odds ratios with their 95%CI were calculated using logistic regression models. Results: The prevalence of anemia was 50 %. Among the anemic study participants 0.74 %, 11.76 %, and 37.50 % recorded severe, moderate, and mild levels of anemia respectively. The majority of the anemic participants 195 (95.6%) and 126 (61.8) had recently been diagnosed for Malaria and worm infections respectively. Craving for non-food substances (Calabar clay) and poor adherence to iron folate intake had a prevalence of 120 (58.8%) and 117 (57.4%) respectively. Multinomial logistic regression analysis showed that, irregular adherence to iron folate intake and reduce intake of iron folate frequency 2-3 times/week was statistically significantly associated with anemia (p=0.0001 and p= 0.0001 respectively). We equally observed a statistically significant association of alcohol drink consumption and craving for non-food substances (Calabar clay) with anemia (p=0.004 and p=0.0001 respectively). Cases of worm infection for the last 6 months were statistically significantly related to anemia (p = 0.004). Conclusion: Anemia is high among pregnant women in the Buea health district. Factors associated with persistent anemia despite intervention measures in the community hospitals include malaria; no intake or reduced intake of iron folate; alcohol drinks consumption; craving for non-food substances (Calabar clay) and previously diagnosed worm infection within the last 6 months.

scholarly journals Factors associated with vaccination status among children age 12–23 months in Ethiopia, based on 2016 EDHS: logit based multinomial logistic regression analysis

2021 ◽  
Author(s):  
Ermias Bekele Enyew ◽  
Abiyu Abadi Tareke
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Relative Risk ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Vaccination Status ◽  
World Health ◽  
Effective Prevention ◽  
Multinomial Logistic Regression Analysis ◽  
Factors Associated

Abstract Background: Childhood immunization is one of the most cost-effective prevention measures for children's mortality and morbidity, saving 2–3 million lives per year. Therefore, the aim of this study was to identify factors associated with vaccination status among children 12–23 months of age in Ethiopia.Method: A secondary data analysis was done based on the 2016 Ethiopian Demographic and Health Survey (EDHS). A total weighted sample of 1911 children age 12–23 months of age were included in the study. Logit based Multinomial logistic regression analysis was computed to distinguish factors associated with routine vaccination of children aged 12-23 months. P-value less than 0.05 was used to declare statistical significance of each independent variables, and adjusted Relative risk ratio (RRR) with 95% confidence interval were used to present the result and STATA 14 was utilized for data management and analysis. Result: Overall the prevalence of full vaccinated children was 35%, while 49% of children were partially vaccinated and 16% were non-vaccinated. In multinomial analysis, having focused ANC (at least four visits) contrasted to no ANC visits at all had 9.7 higher relative risk of being fully vaccinated than not vaccinated [RRR= 9.74, 95% CI=3.52-26.94], and 5 times higher relative risk of being partially vaccinated than not vaccinated [RRR=4.97, 95% CI=2.00-12.33]. Conclusion: The present study found that childhood full vaccination status was low compared with the World Health Organization targets. Frequency of ANC visit and visited by field worker were significantly associated both partially and full vaccination whereas, visited health facility last 12 months and wealth status were significantly associated with childhood full vaccination.

scholarly journals Association between Social Integration and Face Mask Use Behavior during the SARS-CoV-2 Pandemic in Japan: Results from U-CORONA Study

2021 ◽  
Vol 18 (9) ◽  
pp. 4717
Author(s):  
Nobutoshi Nawa ◽  
Yui Yamaoka ◽  
Yuna Koyama ◽  
Hisaaki Nishimura ◽  
Shiro Sonoda ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Social Network ◽  
Social Integration ◽  
Response Bias ◽  
Multinomial Logistic Regression ◽  
Face Mask ◽  
Neighborhood Association ◽  
Multinomial Logistic Regression Analysis ◽  
Use Behavior

Face mask use is a critical behavior to prevent the spread of SARS-CoV-2. We aimed to evaluate the association between social integration and face mask use during the COVID-19 pandemic in a random sample of households in Utsunomiya City, Greater Tokyo, Japan. Data included 645 adults in the Utsunomiya COVID-19 seROprevalence Neighborhood Association (U-CORONA) study, which was conducted after the first wave of the pandemic, between 14 June 2020 and 5 July 2020, in Utsunomiya City. Social integration before the pandemic was assessed by counting the number of social roles, based on the Cohen’s social network index. Face mask use before and during the pandemic was assessed by questionnaire, and participants were categorized into consistent mask users, new users, and current non-users. Multinomial logistic regression analysis was used to examine the association between lower social integration score and face mask use. To account for possible differential non-response bias, non-response weights were used. Of the 645 participants, 172 (26.7%) were consistent mask users and 460 (71.3%) were new users, while 13 (2.0%) were current non-users. Lower social integration level was positively associated with non-users (RRR: 1.76, 95% CI: 1.10, 2.82). Social integration may be important to promote face mask use.

scholarly journals A Statistical Study of Crime in Ghana

2020 ◽  
pp. 6-16
Author(s):  
Bosson-Amedenu Senyefia ◽  
Eyiah-Bediako Francis ◽  
Kusi Prince
Keyword(s):  
Logistic Regression ◽  
Educational Level ◽  
Multinomial Logistic Regression ◽  
Religious Affiliation ◽  
Secondary Data ◽  
Age Group ◽  
Multinomial Logistic Regression Analysis ◽  
Equality Of Means ◽  
Homogeneity Of Variance ◽  
The Mean

Understanding the dynamics, patterns, and probabilities associated with the correlates of crime is a promising way to managing crime. In this study, a multinomial logistic regression was used to predict the propensity of individuals for committing particular crimes. The secondary data of 6702 prisoners was collated from Ghana Prisons Service for the purpose of the study. ANOVA and Brown-Forsythe robust tests of equality of means were employed, where the assumptions for homogeneity of variance were sustained and violated respectively. Pearson’s correlation matrix was also used in the analysis. Our findings showed that religious affiliation and educational level of convicts significantly affected the odds that they would commit a particular crime. Multinomial logistic regression analysis indicated that illiteracy significantly affected the odds that one would commit the crimes of manslaughter, rape, theft, causing harm, and issuing death threats. On the other hand, religious affiliation of an offender significantly affected the odds to commit the crime of murder. Educational level (r= -0.25; p< 0.05) and religious affiliation (r= -0.26; p<0.05) correlated negatively with crime. There were no significant differences in the mean score of crime across educational and religious levels. However, there were significant differences in the mean score of crime across age and gender. The mean difference from the post-hoc analysis showed a pattern of an initial rise in crime among the younger age group (8-25 years), a subsequent decline in the age group of 26-35, and a final surge in individuals beyond 35 years that did not surpass the initial peak. Females (M: 6.89, SD: 1.253) were found to have lower crime incidence than males (M: 7.43, SD: 3.008) for all crimes considered in this study. We recommend that Ghana’s Prison Service consider incorporating further demographic information of inmates in order to support research; which could help identify avenues for the amelioration of crime locally.

The Victim–Offender Overlap in Prison: Examining the Factors Associated With Group Membership

2020 ◽  
pp. 088626051989842
Author(s):  
Jane C. Daquin ◽  
Leah E. Daigle
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Small Proportion ◽  
Group Membership ◽  
Multinomial Logistic Regression ◽  
Future Research ◽  
Correctional Facilities ◽  
Regression Analyses ◽  
Prison Literature ◽  
Factors Associated

Historically, criminologists have examined offending and victimization in the community as separate outcomes. Recently, however, researchers have begun to explore the shared commonalities of being an offender and a victim. The victim–offender overlap literature shows that victimization and offending are not different and distinct outcomes, but rather these outcomes share numerous risk factors. A close examination of the victim–offender overlap has not been done within the prison literature. Thus, it remains unclear whether there are commonalities among prisoners who offend while incarcerated and those who experience victimization. The focus of the current study is to (a) identify the proportion of the prisoners who were victims-only, offenders-only, victim–offenders, or neither victim nor offender and (b) identify the factors that predict membership into the four categories of the overlap. The current study used the 2004 Survey of Inmates in State and Federal Correctional Facilities with multinomial logistic regression analyses to examine which factors are associated with group membership into the victim–only, offender–only, or victim–offender groups in prison. Findings show that although the victim–offender overlap exists among prisoners, the majority of prisoners were neither a victim nor an offender. Victim–offenders and victims-only comprise only a small proportion of the sample. Findings also indicate that there are few unique factors across the groups. Results of the study have implications policy and future research.

scholarly journals Sociodemographic and Clinical Risk Factors Associated With Tuberculosis Mortality in the United States, 2009-2013

2017 ◽  
Vol 132 (3) ◽  
pp. 366-375 ◽  
Author(s):  
Haylea A. Hannah ◽  
Roque Miramontes ◽  
Neel R. Gandhi
Keyword(s):  
United States ◽  
Risk Factors ◽  
Multinomial Logistic Regression ◽  
The United States ◽  
Multidrug Resistant ◽  
Multinomial Logistic Regression Analysis ◽  
Factors Associated ◽  
Specific Mortality ◽  
Stage Renal Disease ◽  
End Stage

Objectives: The objectives of our study were (1) to determine risk factors associated with tuberculosis (TB)–specific and non–TB-specific mortality among patients with TB and (2) to examine whether risk factors for TB-specific mortality differed from those for non–TB-specific mortality. Methods: We obtained data from the National Tuberculosis Surveillance System and included all patients who had TB between 2009 and 2013 in the United States and its territories. We used multinomial logistic regression analysis to determine the adjusted odds ratio (aOR) of each risk factor for TB-specific and non–TB-specific mortality. Results: Of 52 175 eligible patients with TB, 1404 died from TB, and 2413 died from other causes. Some of the risk factors associated with the highest odds of TB-specific mortality were multidrug-resistant TB diagnosis (aOR = 3.42; 95% CI, 1.95-5.99), end-stage renal disease (aOR = 3.02; 95% CI, 2.23-4.08), human immunodeficiency virus infection (aOR = 2.63; 95% CI, 2.02-3.42), age 45-64 years (aOR = 2.57; 95% CI, 2.01-3.30) or age ≥65 years (aOR = 5.76; 95% CI, 4.37-7.61), and immunosuppression (aOR = 2.20; 95% CI, 1.71-2.83). All of these risk factors except multidrug-resistant TB were also associated with increased odds of non–TB-specific mortality. Conclusion: TB patients with certain risk factors have an elevated risk of TB-specific mortality and should be monitored before, during, and after treatment. Identifying the predictors of TB-specific mortality may help public health authorities determine which subpopulations to target and where to allocate resources.

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