scholarly journals Examine the Association between Metabolic Syndrome and Frailty in an Older Asian Population

2021 ◽  
Author(s):  
Hiep Huu Hoang Dao ◽  
Anh Trung Nguyen ◽  
Huyen Thi Thanh Vu ◽  
Tu Ngoc Nguyen
Keyword(s):  
Metabolic Syndrome ◽  
Logistic Regression ◽  
Sex Education ◽  
Regression Models ◽  
Asian Population ◽  
Frailty Phenotype ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Asian Populations ◽  
Definition Of

Background: There has been evidence that metabolic syndrome (MetS) may increase the risk of frailty. However, there is limited evidence on this association in Asian populations. Aims: This study aims to identify the association between MetS and frailty in older people in Vietnam. Methods: This is a cross-sectional analysis of a dataset obtained from an observational study on frailty and sarcopenia in patients aged ≥60 at a geriatric hospital in Vietnam. Frailty was defined by the frailty phenotype. Participants were defined as having MetS if they had ≥3 out of 5 criteria from the definition of the National Cholesterol Education Program (NCEP) Adults Treatment Panel (ATP) III. Multiple logistic regression models were performed to estimate the risk of having frailty in patients with MetS. Results: There were 669 participants (mean age 71, 60.2% female), 62.3% had MetS and 39.0% was frail. The prevalence of frailty was 42.2% in participants with MetS, 33.7% in participants without MetS (p=0.029). On logistic regression models, MetS was associated with increased likelihood of being frail (adjusted OR 1.52, 95%CI 1.01-2.28), allowing for age, sex, education, nutritional status, history of hospitalisation and chronic diseases. Conclusion: There was a significant association between MetS and frailty in this population. Further longitudinal studies are required to confirm this association.

scholarly journals Association between the HTR2C rs1414334 C/G gene polymorphism and the development of the metabolic syndrome in patients treated with atypical antipsychotics

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2163 ◽  
Author(s):  
José María Rico-Gomis ◽  
Antonio Palazón-Bru ◽  
Irene Triano-García ◽  
Luis Fabián Mahecha-García ◽  
Ana García-Monsalve ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Logistic Regression ◽  
Regression Models ◽  
Atypical Antipsychotics ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
The Metabolic Syndrome

Few studies have assessed the association between the rs1414334 C/G polymorphism in the HTR2C gene and the development of the metabolic syndrome in patients treated with atypical antipsychotics. To provide further evidence, a cross-sectional study was conducted in Spain between 2012 and 2013 in 166 patients with these characteristics. In these patients, the association between the polymorphism and the presence of the metabolic syndrome was determined by implementing binary logistic regression models adjusted for variables associated with the metabolic syndrome. We did not confirm previous claims that the C allele of the polymorphism was linked to the metabolic syndrome: the association was in the opposite direction and non-significant. This conclusion held after taking gender and lifestyle variables into account.

Physician Perceptions on Quality of Life and Resuscitation Preferences for Extremely Early Newborns

2021 ◽  
Author(s):  
Danielle LoRe ◽  
Christopher Mattson ◽  
Dalia M. Feltman ◽  
Jessica T. Fry ◽  
Kathleen G. Brennan ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Logistic Regression ◽  
Regression Models ◽  
Mixed Effects ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Comfort Care ◽  
Logistic Regression Models ◽  
Extremely Preterm

Objective The study aimed to explore physician views on whether extremely early newborns will have an acceptable quality of life (QOL), and if these views are associated with physician resuscitation preferences. Study Design We performed a cross-sectional survey of neonatologists and maternal fetal medicine (MFM) attendings, fellows, and residents at four U.S. medical centers exploring physician views on future QOL of extremely early newborns and physician resuscitation preferences. Mixed-effects logistic regression models examined association of perceived QOL and resuscitation preferences when adjusting for specialty, level of training, gender, and experience with ex-premature infants. Results A total of 254 of 544 (47%) physicians were responded. A minority of physicians had interacted with surviving extremely early newborns when they were ≥3 years old (23% of physicians in pediatrics/neonatology and 6% in obstetrics/MFM). The majority of physicians did not believe an extremely early newborn would have an acceptable QOL at the earliest gestational ages (11% at 22 and 23% at 23 weeks). The majority of physicians (73%) believed that having an extremely preterm infant would have negative effects on the family's QOL. Mixed-effects logistic regression models (odds ratio [OR], 95% confidence interval [CI]) revealed that physicians who believed infants would have an acceptable QOL were less likely to offer comfort care only at 22 (OR: 0.19, 95% CI: 0.05–0.65, p < 0.01) and 23 weeks (OR: 0.24, 95% CI: 0.07–0.78, p < 0.02). They were also more likely to offer active treatment only at 24 weeks (OR: 9.66, 95% CI: 2.56–38.87, p < 0.01) and 25 weeks (OR: 19.51, 95% CI: 3.33–126.72, p < 0.01). Conclusion Physician views of extremely early newborns' future QOL correlated with self-reported resuscitation preferences. Residents and obstetric physicians reported more pessimistic views on QOL. Key Points

Fall Worry Restricts Social Engagement in Older Adults

2019 ◽  
Vol 32 (5-6) ◽  
pp. 422-431 ◽  
Author(s):  
Namkee G. Choi ◽  
Martha L. Bruce ◽  
Diana M. DiNitto ◽  
C. Nathan Marti ◽  
Mark E. Kunik
Keyword(s):  
Older Adults ◽  
Logistic Regression ◽  
Social Engagement ◽  
Regression Models ◽  
Multinomial Logistic Regression ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Health Related ◽  
Reported Health ◽  
Longitudinal Associations

Objective: To examine cross-sectional and longitudinal associations between (a) activity-limiting fall worry (ALW) and (b) self-reported health-related restrictions and social engagement among older adults. Method: The National Health and Aging Trends Study Waves 5 (T1) and 6 (T2) provided data ( n = 6,279). Binary and multinomial logistic regression models were used to examine association of T2 social engagement restrictions with T2 fall worry and association of T1–T2 changes in social engagement restrictions with T1–T2 changes in fall worry. Results: ALW was significantly associated with both informal and formal social engagement restriction at T2. Onset of ALW and continued ALW between T1 and T2 were also significantly associated with newly reported restrictions in both informal and formal social engagement at T2 even controlling for falls incidents and changes in health status and other covariates. Discussion: The findings underscore the importance of reducing fall worry and preventing social disengagement in late life.

Association of Systemic Inflammation and Fatigue in Osteoarthritis: 2007−2010 National Health and Nutrition Examination Survey

2019 ◽  
Vol 21 (5) ◽  
pp. 532-543 ◽  
Author(s):  
Alisha J. Hackney ◽  
N. Jennifer Klinedinst ◽  
Barbara Resnick ◽  
Meg Johantgen
Keyword(s):  
Logistic Regression ◽  
Systemic Inflammation ◽  
National Health ◽  
Regression Models ◽  
Secondary Analysis ◽  
Nutrition Examination Survey ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Health And Nutrition ◽  
Wbc Count

Background/Purpose:Mechanistic insight into osteoarthritis fatigue is needed as clinical management of this condition is nonspecific. Systemic inflammation is associated with fatigue in other chronic diseases. The purpose of this study was to explore the relationship between systemic inflammation and fatigue in osteoarthritis, while controlling for covariates.Method:This secondary analysis with a cross-sectional, multiyear retrospective design used data from the 2007−2010 National Health and Nutrition Examination Survey. Adults with self-reported osteoarthritis who participated in an examination at a mobile center and had no comorbidities associated with fatigue or systemic inflammation were included ( n = 296). Complex sample analysis, independent samples t tests, and χ2tests of independence were used to explore differences between nonfatigued and fatigued adults with osteoarthritis. Adjusted hierarchical logistic regression models were used to calculate odds of fatigue as a function of two systemic inflammatory markers, C-reactive protein (CRP), and white blood cell (WBC) count.Results:Fatigued adults with osteoarthritis had significantly higher CRP levels and WBC counts compared to nonfatigued adults with osteoarthritis. In adjusted logistic regression models, increased CRP was associated with higher odds of fatigue when controlling for age, days affected by pain, depressive symptoms, sleep quantity, and body mass index (Odds ratio [ OR] = 3.38, 95% CI [1.18, 9.69]). WBC count was not associated with higher odds of fatigue when controlling for these variables ( OR = 1.10, 95% CI [0.92, 1.32]).Conclusion:Systemic inflammation may have a relationship with fatigue in osteoarthritis. Future work is necessary to replicate these findings in more robust studies.

scholarly journals Frail by different measures: a comparison of 8-year mortality in The Irish Longitudinal Study on Ageing (TILDA)

2021 ◽  
Author(s):  
Roman Romero-Ortuno ◽  
Peter Hartley ◽  
Rose Anne Kenny ◽  
Aisling M. O’Halloran
Keyword(s):  
Logistic Regression ◽  
Longitudinal Study ◽  
Regression Models ◽  
Frailty Index ◽  
Binary Logistic Regression ◽  
Clinical Frailty Scale ◽  
Frailty Phenotype ◽  
Logistic Regression Models

Abstract Purpose We compared the ability of four frailty identification tools (frailty phenotype: FP; FRAIL scale; 32-item Frailty Index: FI; and Clinical Frailty Scale: CFS) to predict 8-year mortality in TILDA. Methods We included wave 1 (2010) participants with data for all four tools. Mortality was ascertained at wave 5 (2018). Age, sex and education-adjusted binary logistic regression models were computed. Results At baseline, there were 5700 participants (mean age 63, range 50–98, 54% women). Frailty prevalences were 2.3% by FRAIL, 3.8% by FP, 10.9% by CFS, and 12.8% by FI. Mortality was 41.2%, 44.9%, 25.3% and 27.0%, respectively. The highest adjusted OR for mortality was for FRAIL (OR 4.48, 95% CI 2.93–6.85, P < 0.001), followed by FP (OR 3.55, 95% CI 2.52–5.00, P < 0.001), FI (OR 2.10, 95% CI 1.68–2.62, P < 0.001), and CFS (OR 1.88, 95% CI 1.48–2.38, P < 0.001). Conclusions All tools significantly predicted mortality, but FRAIL and FP seemed more specific.

scholarly journals Childhood maltreatment and suicidal ideation in Chinese children and adolescents: the mediation of resilience

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11758
Author(s):  
Xue Chen ◽  
Linling Jiang ◽  
Yi Liu ◽  
Hailiang Ran ◽  
Runxu Yang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Suicidal Ideation ◽  
Childhood Maltreatment ◽  
Emotional Abuse ◽  
Regression Models ◽  
Suicide Ideation ◽  
Chinese Adolescents ◽  
Path Model ◽  
Cross Sectional ◽  
Logistic Regression Models

Background Childhood maltreatment could increase the risk of suicidal ideation (SI) in adolescents. However, the mediation of resilience in this association remains unclear. Methods A population-based cross-sectional study has been done among 3,146 Chinese adolescents. We collected relevant information from the study participants by using self-administered questionnaire. Chinese version of the Childhood Trauma Questionnaire (CTQ), the Resilience Scale for Chinese Adolescents (RSCA), and the Beck Scale for Suicide Ideation (BSSI) were used to measure childhood maltreatment, resilience, and SI, respectively. Univariate and multivariate binary Logistic regression models were employed to estimate crude and adjusted associations between childhood maltreatment, resilience, and SI. Path analysis has subsequently been performed to measure the mediation of resilience in this association. Results Multivariate Logistic regression models revealed that compared to non-abused counterparts, adolescents who had ever experienced any type of childhood maltreatment was 1.74 times likely to report SI. Among the specific types of childhood maltreatment, emotional abuse showed the strongest association with SI (adjusted OR = 3.01, 95% CI [2.37–3.82]). Path model suggested that over one-third (39.8%) of the total association between childhood maltreatment and SI was mediated via resilience. Emotion regulation and interpersonal assistance were the most prominent mediators among all dimensions of resilience. Conclusions Resilience played as a significant mediator in the association between childhood maltreatment and SI. Resilience-oriented intervention measures could be considered for suicidal risk prevention among abused Chinese adolescents.

scholarly journals Effects of food items and related nutrients on metabolic syndrome using Bayesian multilevel modelling using the Tehran Lipid and Glucose Study (TLGS): a cohort study

BMJ Open ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. e020642 ◽  
Author(s):  
Zahra Cheraghi ◽  
Saharnaz Nedjat ◽  
Parvin Mirmiran ◽  
Nazanin Moslehi ◽  
Nasrin Mansournia ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Logistic Regression ◽  
Cohort Study ◽  
Regression Models ◽  
Multilevel Modelling ◽  
Confidence Limits ◽  
Logistic Regression Models ◽  
Food Items ◽  
Highly Correlated ◽  
Sparse Data Bias

ObjectivesDiet and nutrition might play an important role in the aetiology of metabolic syndrome (MetS). Most studies that examine the effects of food intake on MetS have used conventional statistical analyses which usually investigate only a limited number of food items and are subject to sparse data bias. This study was undertaken with the goal of investigating the concurrent effect of numerous food items and related nutrients on the incidence of MetS using Bayesian multilevel modelling which can control for sparse data bias.DesignProspective cohort study.SettingThis prospective study was a subcohort of the Tehran Lipid and Glucose Study. We analysed dietary intake as well as pertinent covariates for cohort members in the fourth (2008–2011) and fifth (2011–2014) follow-up examinations. We fitted Bayesian multilevel model and compared the results with two logistic regression models: (1) full model which included all variables and (2) reduced model through backward selection of dietary variables.Participants3616 healthy Iranian adults, aged ≥20 years.Primary and secondary outcome measuresIncident cases of MetS.ResultsBayesian multilevel approach produced results that were more precise and biologically plausible compared with conventional logistic regression models. The OR and 95% confidence limits for the effects of the four foods comparing the Bayesian multilevel with the full conventional model were as follows: (1) noodle soup (1.20 (0.67 to 2.14) vs 1.91 (0.65 to 5.64)), (2) beans (0.96 (0.5 to 1.85) vs 0.55 (0.03 to 11.41)), (3) turnip (1.23 (0.68 to 2.23) vs 2.48 (0.82 to 7.52)) and (4) eggplant (1.01 (0.51 to 2.00) vs 1 09 396 (0.152×10–6to 768×1012)). For most food items, the Bayesian multilevel analysis gave narrower confidence limits than both logistic regression models, and hence provided the highest precision.ConclusionsThis study demonstrates that conventional regression methods do not perform well and might even be biased when assessing highly correlated exposures such as food items in dietary epidemiological studies. Despite the complexity of the Bayesian multilevel models and their inherent assumptions, this approach performs superior to conventional statistical models in studies that examine multiple nutritional exposures that are highly correlated.

scholarly journals Characteristics of Pica Behavior among Mothers around Lake Victoria, Kenya: A Cross-Sectional Study

2019 ◽  
Vol 16 (14) ◽  
pp. 2510
Author(s):  
Esther O. Chung ◽  
Brian Mattah ◽  
Matthew D. Hickey ◽  
Charles R. Salmen ◽  
Erin M. Milner ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Lake Victoria ◽  
Soft Rock ◽  
Cross Sectional Study ◽  
Postpartum Women ◽  
Soil N ◽  
Sectional Study ◽  
Cross Sectional ◽  
Logistic Regression Models

Background: Pica, the craving and purposeful consumption of nonfoods, is poorly understood. We described the prevalence of pica among women on Mfangano Island, Kenya, and examined sociodemographic and health correlates. Methods: Our cross-sectional study included 299 pregnant or postpartum women in 2012. We used a 24-h recall to assess pica, defined as consumption of earth (geophagy), charcoal/ash, or raw starches (amylophagy) and built multivariable logistic regression models to examine sociodemographic and health correlates of pica. Results: Eighty-one women (27.1%) engaged in pica in the previous 24 h, with 59.3% reporting amylophagy and 56.8% reporting geophagy, charcoal, and/or ash consumption. The most common substances consumed were raw cassava (n = 30, 36.6%), odowa, a chalky, soft rock-like earth (n = 21, 25.6%), and soil (n = 17, 20.7%). Geophagy, charcoal, and/or ash consumption was negatively associated with breastfeeding (OR = 0.38, 95% CI: 0.18–0.81), and amylophagy was associated with pregnancy (OR = 4.31, 95% CI: 1.24–14.96). Pica was more common within one of six study regions (OR = 3.64, 95% CI: 1.39–9.51). We found no evidence of an association between food insecurity and pica. Conclusion: Pica was a common behavior among women, and the prevalence underscores the need to uncover its dietary, environmental, and cultural etiologies.

scholarly journals Internalized HIV stigma, bullying, major depressive disorder, and high-risk suicidality among HIV-positive adolescents in rural Uganda

2018 ◽  
Vol 5 ◽  
Author(s):  
S. Ashaba ◽  
C. Cooper-Vince ◽  
S. Maling ◽  
G. Z. Rukundo ◽  
D. Akena ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Major Depressive Disorder ◽  
High Risk ◽  
Depressive Disorder ◽  
Regression Models ◽  
Internalized Stigma ◽  
Major Depressive ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Related Stigma

Background.Studies conducted in sub-Saharan Africa suggest a high prevalence of depression and suicidality among adolescents living with HIV (ALWH). This is an important public health issue because depression is known to compromise HIV treatment adherence. However, the drivers of depression and suicidality in this population are unclear. We conducted a cross-sectional study to estimate the associations between internalized stigma, bullying, major depressive disorder, and suicidality.Methods.We conducted a cross-sectional survey between November 2016 and March 2017, enrolling a consecutive sample of 224 ALWH aged 13–17 years. We collected information on demographic characteristics, internalized HIV-related stigma (using the six-item Internalized AIDS-Related Stigma Scale), bullying victimization (using the nine-item Social and Health Assessment Peer Victimization Scale), major depressive disorder [using the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID)], and suicidality (also using the MINI-KID). We fitted multivariable logistic regression models to estimate the associations between stigma, bullying, major depressive disorder, and suicidality.Results.Thirty-seven participants (16%) had major depressive disorder, 30 (13%) had suicidality, and nine (4%) had high-risk suicidality. Ninety-one participants (41%) had high levels of internalized stigma, while 97 (43%) reported two or more bullying events in the past year. In multivariable logistic regression models, major depressive disorder had a statistically significant association with bullying (AOR = 1.09; 95% CI 1.00–1.20;p= 0.04); while suicidality (low, moderate, high risk) had statistically significant associations with both bullying (AOR = 1.09; 95% CI 1.01–1.17;p= 0.02) and stigma (AOR = 1.30; 95% CI 1.03–1.30;p= 0.02).Conclusions.Among ALWH in rural Uganda, stigma and bullying are strongly associated with major depressive disorder and suicidality. There is a need to incorporate psychological interventions in the mainstream HIV care to address these challenges for optimal management of HIV among ALWH.

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