scholarly journals Physical health and health risk factors in a population of long-stay psychiatric patients

2005 ◽  
Vol 29 (1) ◽  
pp. 18-20 ◽  
Author(s):  
Irene Cormac ◽  
Michael Ferriter ◽  
Ram Benning ◽  
Carol Saul
Keyword(s):  
Risk Factors ◽  
Health Risk ◽  
Physical Health ◽  
Psychiatric Patients ◽  
Cross Sectional Survey ◽  
Health Risk Factors ◽  
Cross Sectional ◽  
Case Register ◽  
Care Services ◽  
Waist Size

Aims and MethodTo evaluate the physical health and health risk factors in long-stay psychiatric patients in a high secure psychiatric hospital. A cross-sectional survey of consenting patients was undertaken using a semi-structured questionnaire, a brief physical examination and review of patient case notes. A comparison was made with data collected on admission and held on the Special Hospitals' Case Register.ResultsMain findings were: a mean increase in weight since admission, in men of 10.62 kg and in women of 12.74 kg; high rates of smoking, obesity and large waist size; 54% of patients had one or more health problems.Clinical ImplicationsThe study's profile of the physical health of psychiatric in-patients indicates the need for health promotion initiatives in such hospitals and the need for primary care services.

scholarly journals Beta Inflated Regression Models on the Physical and Mental Health of Nigerian Stroke Survivors

2021 ◽  
Vol 7 (3) ◽  
pp. 302-312
Author(s):  
KS Oritogun ◽  
OO Oyewole
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Blood Pressure ◽  
Health Risk ◽  
Physical Health ◽  
Regression Models ◽  
Outcome Variable ◽  
Stroke Survivors ◽  
Physical And Mental Health ◽  
Health Risk Factors

Background: Stroke is one of the major public health problems worldwide. Physical and mental health data of stroke survivors are often expressed in proportions. Therefore, the Beta Regression models family for data between zero and one will be appropriate. Objectives: To identify a suitable model and the likely risk factors of physical and mental health of stroke survivors. Method: Secondary data of stroke survivors from two tertiary health Institutions in Ogun State, Nigeria, were analysed. Inflated Beta (BEINF) and Inflated-at-one-Beta (BEINF1) models were compared using Deviance (DEV), Akaike Information Criterion (AIC) and Bayesian Information Criteria (BIC) for model selection. The model with minimum DEV, AIC and BIC was considered to be better. Results: The deviance (-86.0604,), AIC (-46.0604) and BIC (6.4391) values of the BEINF1 model for physical health and the deviance (-20.1217), AIC (19.8783) and BIC (72.3778) values of BEINF1 model for mental health were smaller than BEINF models. Therefore, BEINF1 was the better model to identify the health risk factors of stroke survivors. Age, marital status, diastolic blood pressure, disability duration and systolic blood pressure had a significant association with physical health, while BMI had a significant positive association with mental health.  Conclusion: The beta-inflated-at-one (BEINF1) model is suitable for identifying health risk factors of stroke survivors when the outcome variable is a proportion. Both demographic and clinical characteristics were significantly associated with the health of stroke survivors. This study would assist researchers in knowing the appropriate model for analysing proportion or percentage response variables.

scholarly journals Prison primary care and non-communicable diseases: a data-linkage survey of prevalence and associated risk factors

BJGP Open ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. bjgpopen19X101643 ◽  
Author(s):  
Nat MJ Wright ◽  
Philippa Hearty ◽  
Victoria Allgar
Keyword(s):  
Risk Factors ◽  
Physical Health ◽  
Respiratory Disease ◽  
Prison Population ◽  
Communicable Diseases ◽  
Self Report ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Non Communicable Diseases ◽  
Clinical Records

BackgroundThe size and mean age of the prison population has increased rapidly in recent years. Prisoners are a vulnerable group who, compared with the general population, experience poorer health outcomes. However, there is a dearth of research quantifying the prevalence of non-communicable diseases (NCDs) among prisoner populations.AimTo explore both the prevalence of NCDs and their risk factors.Design & settingA cross-sectional survey was undertaken that was compared with clinical records in two male prisons in the north of England.MethodSelf-report surveys were completed by 199 prisoners to assess sociodemographic characteristics, general health, NCD prevalence, and risk factor prevalence. Data were checked against that retrieved from prison clinical records.ResultsIt was found that 46% reported at least one NCD and 26% reported at least one physical health NCD. The most common self-reported NCD was 'anxiety and depression' (34%), followed by 'respiratory disease' (17%), and 'hypertension' (10%). Having a physical health NCD was independently associated with increasing age or drug dependence.The level of agreement between clinical records and self-report ranged from 'fair' for alcohol dependence (kappa 0.38; P<0.001) to 'very good' for diabetes (kappa 0.86; P<0.001).ConclusionCompared with mainstream populations and despite high prevalence of risk factors for NCDs physical illness NCDs, with the exception of respiratory disease, are less common. However, poor mental health is more common. These differences are possibly owing to the younger average age of prison populations, since prevalence of risk factors was reported as high.Secondary data analysis of clinical records is a more methodologically robust way of monitoring trends in prisoner population disease prevalence.

scholarly journals Prediction Algorithm of Young Students’ Physical Health Risk Factors Based on Deep Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xianping Yin
Keyword(s):  
Risk Factors ◽  
Health Risk ◽  
Physical Health ◽  
Human Body ◽  
Vascular System ◽  
Overweight And Obesity ◽  
Prediction Algorithm ◽  
Fundus Images ◽  
Physical And Mental Health ◽  
Health Risk Factors

Young people’s physical and mental health is the foundation of society’s overall development and the key to improving people’s health quality. Middle school students’ physical examinations and monitoring work are a surefire way to ensure their healthy development. Poor vision, dental caries, overweight and obesity, and high blood pressure are the most common adverse health outcomes of students caused by adolescent health risk behavior factors. Researchers have been concerned about the retinal fundus vascular system, which is the only internal vascular system that can be observed in a noninvasive state of the human body. Fundus images contain a wealth of disease-related information. Fundus images have been widely used in the field of medical auxiliary diagnosis because many important systemic diseases of the human body cause specific reactions in the fundus. Aiming to solve the problem of inseparable tiny blood vessels, this paper proposes a model of retinal vessel segmentation based on attention mechanisms. In light of the retinal arteriovenous division of discontinuous challenges, the topological structure of the constraint system along with overcoming the network and topology restrictions is monitored. Finally, simulation experiments were conducted on two publicly available datasets. The findings show that the proposed method is reliable, effective, and accurate in predicting physical health risk factors in adolescent students.

scholarly journals COVID-19 mortality with regard to healthcare services availability, health risks, and socio-spatial factors at department level in France: A spatial cross-sectional analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256857
Author(s):  
Anastase Tchicaya ◽  
Nathalie Lorentz ◽  
Kristell Leduc ◽  
Gaetan de Lanchy
Keyword(s):  
Risk Factors ◽  
Mortality Rate ◽  
Health Services ◽  
Health Risk ◽  
Negative Binomial ◽  
Healthcare Services ◽  
Mortality Data ◽  
Health Risk Factors ◽  
Cross Sectional ◽  
Spatial Factors

Background The 2019 coronavirus (COVID-19) epidemic began in Wuhan, China in December 2019 and quickly spread to the rest of the world. This study aimed to analyse the associations between the COVID-19 mortality rate in hospitals, the availability of health services, and socio-spatial and health risk factors at department level. Methods and findings This spatial cross-sectional study used cumulative mortality data due to the COVID-19 pandemic in hospitals until 30 November 2020 as a main outcome, across 96 departments of mainland France. Data concerning health services, health risk factors, and socio-spatial factors were used as independent variables. Independently, we performed negative binomial, spatial and geographically weighted regression models. Our results revealed substantial geographic disparities. The spatial exploratory analysis showed a global positive spatial autocorrelation in each wave indicating a spatial dependence of the COVID-19 deaths across departments. In first wave about 75% of COVID-19 deaths were concentrated in departments of five regions compared to a total of 13 regions. The COVID-19 mortality rate was associated with the physicians density, and not the number of resuscitation beds. Socio-spatial factors were only associated with the COVID-19 mortality rate in first wave compared to wave 2. For example, the COVID-19 mortality rate increased by 35.69% for departments densely populated. Health risk factors were associated with the COVID-19 mortality rate depending on each wave. This study had inherent limitations to the ecological analysis as ecological bias risks and lack of individual data. Conclusions Our results suggest that the COVID-19 pandemic has spread more rapidly and takes more severe forms in environments where there is already a high level of vulnerability due to social and health factors. This study showed a different dissemination pattern of COVID-19 mortality between the two waves: a spatial non-stationarity followed by a spatial stationarity in the relationships between the COVID-19 mortality rate and its potential drivers.

scholarly journals Back pain, mental health and substance use are associated in adolescents

2019 ◽  
Vol 41 (3) ◽  
pp. 487-493
Author(s):  
S J Kamper ◽  
Z A Michaleff ◽  
P Campbell ◽  
K M Dunn ◽  
T P Yamato ◽  
...  
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Back Pain ◽  
Health Risk ◽  
Poor Mental Health ◽  
Anxiety And Depression ◽  
Health Risk Factors ◽  
Cross Sectional ◽  
Pain Frequency ◽  
Healthy Schools

Abstract Background During adolescence, prevalence of pain and health risk factors such as smoking, alcohol use and poor mental health all rise sharply. The aim of this study was to describe the relationship between back pain and health risk factors in adolescents. Methods Cross-sectional data from the Healthy Schools Healthy Futures study, and the Australian Child Wellbeing Project was used, mean age: 14–15 years. Children were stratified according to back pain frequency. Within each strata, the proportion of children that reported drinking alcohol or smoking or that experienced feelings of anxiety or depression was reported. Test-for-trend analyses assessed whether increasing frequency of pain was associated with health risk factors. Results Data was collected from ~2500 and 3900 children. Larger proportions of children smoked or drank alcohol within each strata of increasing pain frequency. The trend with anxiety and depression was less clear, although there was a marked difference between the children that reported no pain, and pain more frequently. Conclusion Two large, independent samples show adolescents that experience back pain more frequently are also more likely to smoke, drink alcohol and report feelings of anxiety and depression. Pain appears to be part of the picture of general health risk in adolescents.

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