Influence of alternative lifestyles on health status and health risk factors in pregnancy and maternity

Interpretation of changes in health and health care utilization patterns across the life span depends on an understanding of the effects of age, period, and cohort. The purpose of this article is to illustrate differences among three generations of women in demographic factors, health risk factors, and health status indicators from 1996 to 2008. The article examines data from the Australian Longitudinal Study on Women’s Health, a broad-ranging project funded by the Australian Government Department of Health and Ageing (DoHA) and involving three age groups of women (born in the periods 1973—1978, 1946—1951, and 1921—1926) who were first surveyed in 1996 and will be surveyed every 3 years until at least 2015. Patterns in selected demographic factors (marital status and level of educational qualification), health risk factors (smoking, alcohol consumption, physical activity, and body mass index [BMI]), and health status indicators (asthma, hypertension, diabetes and depression; physical functioning and mental health scores from the SF-36) were examined to illustrate examples of biological age, generational differences, or period effects that affect all age groups and generations simultaneously. The results can be used to inform the development of responsive and effective models for both prevention and management of chronic disease, including health and aged-care systems that will meet the needs of different generations of women across their life span.

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Fact Sheet: Differences Between Men and Women in Health Risk Factors, 1996 and 1997

PsycEXTRA Dataset ◽

10.1037/e371572004-001 ◽

2013 ◽

Author(s):

Keyword(s):

Risk Factors ◽

Health Risk ◽

Health Risk Factors ◽

Men And Women ◽

Fact Sheet

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

PsycEXTRA Dataset ◽

10.1037/e413792005-758 ◽

2000 ◽

Author(s):

Paul A. Thomas ◽

Jen Hanley ◽

Christy Tomczak ◽

Jennifer Wuchteil ◽

Nathan Underwood ◽

...

Keyword(s):

Risk Factors ◽

Health Risk ◽

Health Risk Factors

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Minority Health Profile: Health Risk Factors by Race and Ethnicity

PsycEXTRA Dataset ◽

10.1037/e550482009-001 ◽

2004 ◽

Keyword(s):

Risk Factors ◽

Health Risk ◽

Race And Ethnicity ◽

Minority Health ◽

Health Profile ◽

Health Risk Factors

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

SSRN Electronic Journal ◽

10.2139/ssrn.3529461 ◽

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

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Mental Health, Risk Factors and Access to Care for Primary School Children in the Island of Mauritius

Adolescent Psychiatry ◽

10.2174/221067660404150115163000 ◽

2015 ◽

Vol 4 (4) ◽

pp. 293-304

Author(s):

Sobharani Sungum-Paliwal

Keyword(s):

Mental Health ◽

Risk Factors ◽

Health Risk ◽

Primary School ◽

Access To Care ◽

School Children ◽

Primary School Children ◽

Health Risk Factors

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

Nutrition and Health ◽

10.1177/0260106021996933 ◽

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.

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Cannabis use among early adolescents and transdiagnostic mental health risk factors

Clinical Child Psychology and Psychiatry ◽

10.1177/1359104521994637 ◽

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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