Significant weight loss, co-morbidity improvement and reduced health risk-factors after treatment at a multidisciplinary weight management clinic in a university hospital in Sydney, Australia

2020 ◽  
Author(s):  
Zoe Rock ◽  
Juliana Chen ◽  
Joanna Jacques ◽  
Divya Namboodiri ◽  
Bernard Champion ◽  
...  
Keyword(s):  
Risk Factors ◽  
Weight Loss ◽  
Health Risk ◽  
Weight Management ◽  
University Hospital ◽  
Significant Weight Loss ◽  
Health Risk Factors ◽  
Co Morbidity ◽  
Sydney Australia

scholarly journals Consumption of a controlled low-fat diet containing olestra for 9 months improves health risk factors in conjunction with weight loss in obese men: the Ole' Study

2003 ◽  
Vol 27 (10) ◽  
pp. 1242-1249 ◽  
Author(s):  
J C Lovejoy ◽  
G A Bray ◽  
M Lefevre ◽  
S R Smith ◽  
M M Most ◽  
...  
Keyword(s):  
Risk Factors ◽  
Weight Loss ◽  
Health Risk ◽  
Low Fat ◽  
Health Risk Factors ◽  
Low Fat Diet

Abstract #615: Hispanic People Achieve Clinically Significant Weight loss with Liraglutide 3.0 Mg for Weight Management

2015 ◽  
Vol 21 ◽  
pp. 121
Author(s):  
Patrick O’Neil ◽  
W. Timothy Garvey ◽  
J. Michael Gonzalez-Campoy ◽  
Pablo Mora ◽  
Rafael Violante Ortiz ◽  
...  
Keyword(s):  
Weight Loss ◽  
Weight Management ◽  
Significant Weight Loss ◽  
Hispanic People ◽  
Clinically Significant

A Study of the Effects of Exercise on Stress, Depression Levels, and Health Risk Factors

2000 ◽  
Author(s):  
Paul A. Thomas ◽  
Jen Hanley ◽  
Christy Tomczak ◽  
Jennifer Wuchteil ◽  
Nathan Underwood ◽  
...  
Keyword(s):  
Risk Factors ◽  
Health Risk ◽  
Health Risk Factors

Behavioral Health Risk Factors for Nonmedical Use of Prescription Opioids in Adolescence

2020 ◽  
Author(s):  
Junhan Cho ◽  
Lorraine I. Kelley-Quon ◽  
Jessica L. Barrington-Trimis ◽  
Afton Kechter ◽  
Sarah Axeen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Health Risk ◽  
Behavioral Health ◽  
Prescription Opioids ◽  
Health Risk Factors ◽  
Nonmedical Use

Consumption of carbonated soft drinks among Ghanaian adolescents: associations with socio-demographic factors, health risk factors and psychological distress

2021 ◽  
pp. 026010602199693
Author(s):  
Prince Atorkey ◽  
Mariam Akwei ◽  
Winifred Asare-Doku
Keyword(s):  
Risk Factors ◽  
Psychological Distress ◽  
Health Risk ◽  
Soft Drink ◽  
Demographic Factors ◽  
Soft Drinks ◽  
Health Risk Factors ◽  
Soft Drink Consumption ◽  
Carbonated Soft Drinks ◽  
Socio Demographic Factors

Background: Carbonated soft drinks consumption is associated with weight gain and other chronic diseases. Aim: To examine whether socio-demographic factors, health risk factors and psychological distress are associated with carbonated soft drink consumption among adolescents in selected senior high schools in Ghana. Methods: Data were obtained from the 2012 Ghana Global School-based Student Health Survey (GSHS). Participants consisted of 1756 school-going adolescents sampled using a two-stage cluster sampling method. Binomial logistic regression was used to determine whether socio-demographic factors, health risk factors and psychological distress were associated with consumption of soft drinks. Results: The prevalence of carbonated soft drinks consumption was 34.9%. Males (odds ratio (OR) = 0.73 (95% confidence intervals (CI) 0.59–0.92); p = 0.007), and participants with high socio-economic status (OR = 0.76 (95% CI 0.48–0.97); p = 0.033) had smaller odds for consumption of soft drinks. Also, adolescents in Senior High School (SHS) 3 (OR = 0.72 (95% CI 0.53–0.97); p = 0.034) and SHS 4 (OR = 0.63 (95% CI 0.43–0.91); p = 0.014) had smaller odds for soft drinks intake compared to those in SHS 1. Health risk factors associated with greater odds of high soft drink consumption were tobacco use (OR = 1.68, (95% CI 1.07–2.65); p = 0.025), fast food consumption (OR = 1.88, (95% CI 1.47–2.41); p = 0.011) and alcohol consumption (OR = 1.43, (95% CI 1.02–1.99); p = 0.039). Consuming adequate fruit (OR = 0.19 (95% CI 0.15–0.24); p = 0.000) and adequate vegetable (OR = 0.55 (95% CI 0.34–0.87); p = 0.011) were associated with lower odds for soft drink consumption. Adolescents who reported feeling anxious had smaller odds for soft drink intake (OR = 0.65, (95% CI 0.47–0.91); p = 0.011). Conclusions: The findings from this study show that socio-demographic characteristics, health risk factors and psychological distress are associated with the soft drink consumption among adolescents in Ghana. Interventions aimed at reducing soft drink consumption and other health risk factors are needed.

Cannabis use among early adolescents and transdiagnostic mental health risk factors

2021 ◽  
pp. 135910452199463
Author(s):  
Sara Moreno-Mansilla ◽  
Jorge J Ricarte ◽  
David J Hallford
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Health Risk ◽  
Suicide Attempts ◽  
Intolerance Of Uncertainty ◽  
Cannabis Use ◽  
Health Risk Factors ◽  
Symptoms Of Depression ◽  
Modifiable Factors ◽  
Wide Range

Introduction: Cannabis is the most widely used psychoactive substance among adolescents worldwide, and the age at which consumption begins to decrease. Cannabis use in adolescents is associated with a wide range of adverse consequences in adulthood including increased vulnerability to psychosis and other mental disorders, as well as suicidal ideation and attempt. The aim of this study is to extend understanding of the link between cannabis use and mental illness by examining whether cannabis use at early ages predicts transdiagnostic variables that are precursors to severe clinical diagnoses. Methods: A descriptive cross-sectional study was conducted. The sample was made up of 605 adolescents from 7th to 9th grades, with a mean age of 13.2 years ( SD = 1.0, 47% girls). The variables evaluated were: anomalous perception of reality, intolerance of uncertainty, rumination, suicide attempt, hopelessness, and symptoms of depression and anxiety. The administration of the questionnaires was carried out in groups of 20 participants under the supervision of a researcher in a unique session of 1 hour. Results: Adolescent cannabis users scored higher on all variables assessed: anomalous perception of reality (Cohen’s d = .60), rumination ( d = .48), intolerance of uncertainty ( d = .11), suicidal attempt (affirmative answer: 25.9% of users vs 7.7% of non-users), hopelessness ( d = .85), symptoms of depression ( d = .80), and anxiety ( d = .39). A binary logistic regression showed that the only variable uniquely related to cannabis use was hopelessness (Wald = 4.560, OR: 1.159, p = .033). Conclusions: Among some mental health risk factors, hopelessness appears uniquely related to cannabis use. Adolescents may use cannabis as a coping strategy for negative thoughts and emotions, or it may be a consequence of cannabis use. Future prevention programs should focus on preventing/treating modifiable factors such as hopelessness, and delaying cannabis use in specific subgroups of adolescents who experience pathologies such as depression or suicide attempts.

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