scholarly journals Multiple health behaviours: overview and implications

2012 ◽  
Vol 34 (suppl 1) ◽  
pp. i3-i10 ◽  
Author(s):  
B. Spring ◽  
A. C. Moller ◽  
M. J. Coons
Keyword(s):  
Health Behaviours ◽  
Multiple Health Behaviours ◽  
Multiple Health

scholarly journals Multiple health behaviours among mothers and partners in England: Clustering, social patterning and intra-couple concordance

2016 ◽  
Vol 2 ◽  
pp. 824-833 ◽  
Author(s):  
Hilary Graham ◽  
Jayne Hutchinson ◽  
Catherine Law ◽  
Lucinda Platt ◽  
Heather Wardle
Keyword(s):  
Health Behaviours ◽  
Multiple Health Behaviours ◽  
Multiple Health

scholarly journals Clusters of health behaviours in Queensland adults are associated with different socio-demographic characteristics

2018 ◽  
Vol 41 (2) ◽  
pp. 268-277 ◽  
Author(s):  
M Hobbs ◽  
M J Duncan ◽  
P Collins ◽  
J Mckenna ◽  
S Schoeppe ◽  
...  
Keyword(s):  
Fast Food ◽  
Health Behaviours ◽  
Elevated Risk ◽  
Sitting Time ◽  
Moderate Risk ◽  
Cross Sectional Survey ◽  
Excessive Alcohol Consumption ◽  
Wide Range ◽  
Multiple Health Behaviours ◽  
Multiple Health

Abstract Background The co-occurrence of unhealthy lifestyles, calls for interventions that target multiple health behaviours. This study investigates the clustering of health behaviours and examines demographic differences between each cluster. Methods In total, 934 adults from Queensland, Australia completed a cross-sectional survey assessing multiple health behaviours. A two-step hierarchical cluster analysis using multiple iterations identified the optimal number of clusters and the subset of distinguishing health behaviour variables. Univariate analyses of variance and chi-squared tests assessed difference in health behaviours by socio-demographic factors and clusters. Results Three clusters were identified: the ‘lower risk’ cluster (n = 436) reported the healthiest profile and met all public health guidelines. The ‘elevated risk’ cluster (n = 105) reported a range of unhealthy behaviours such as excessive alcohol consumption, sitting time, fast-food consumption, smoking, inactivity and a lack of fruit and vegetables. The ‘moderate risk behaviour’ cluster (n = 393) demonstrated some unhealthy behaviours with low physical activity levels and poor dietary outcomes. The ‘elevated risk’ cluster were significantly younger and more socio-economically disadvantaged than both the ‘lower and moderate risk’ clusters. Discussion Younger people who live in more deprived areas were largely within the ‘elevated risk’ cluster and represent an important population for MHBC interventions given their wide range of unhealthy behaviours.

scholarly journals Clustering and Correlates of Multiple Health Behaviours in 9–10 Year Old Children

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e99498 ◽  
Author(s):  
Leonie K. Elsenburg ◽  
Eva Corpeleijn ◽  
Esther M. F. van Sluijs ◽  
Andrew J. Atkin
Keyword(s):  
Health Behaviours ◽  
Multiple Health Behaviours ◽  
Multiple Health

scholarly journals Adolescents Who Intend to Change Multiple Health Behaviours Choose Greater Exposure to an Internet-delivered Intervention

2008 ◽  
Vol 13 (7) ◽  
pp. 906-911 ◽  
Author(s):  
Rik Crutzen ◽  
Jascha de Nooijer ◽  
Math J.J.M. Candel ◽  
Nanne K. de Vries
Keyword(s):  
Health Behaviours ◽  
Multiple Health Behaviours ◽  
Multiple Health

scholarly journals Longitudinal Health Behaviour Patterns Among Chinese Adults Aged ≥ 50 Years and Their Associations With Trajectories of Depressive Symptoms Over Time: A Latent Class Analysis

2020 ◽  
Author(s):  
Zeyun Feng ◽  
Thijs van den Broek ◽  
Jane Cramm ◽  
Anna Nieboer
Keyword(s):  
Depressive Symptoms ◽  
Health Behaviour ◽  
Social Participation ◽  
Latent Class ◽  
Health Behaviours ◽  
Physically Active ◽  
Longitudinal Patterns ◽  
Multiple Health Behaviours ◽  
Multiple Health ◽  
Over Time

Abstract Background Whether different longitudinal patterns of multiple health behaviours are associated with different trajectories of depressive symptoms is not well understood.Purpose To identify distinct longitudinal patterns of multiple health behaviours and their associations with trajectories of depressive symptoms among people aged ≥ 50 years in China.Methods We used longitudinal data from the Harmonized China Health and Retirement Longitudinal Study (three waves, 2010–2015; n = 8439). We performed latent class analyses to identify distinct patterns of multiple health behaviours at three timepoints. We estimated longitudinal random-effects models to predict differences in depressive symptoms trajectories by health behaviour class.Results The best-fitting model had five latent classes, all of which showed strong behavioural stability over time: 1) socially active, moderately physically active non-smokers (29.4%); 2) socially inactive, physically active non-smokers (22.3%); 3) socially and physically inactive non-smokers (17.9%); 4) socially inactive, moderately physically active smokers (14.6%); and (5) socially active, moderately physically active smokers (14.2%). All classes characterized by low social participation (classes 2–4) were associated with significantly higher predicted depressive symptom scores compared with the other classes (1 and 5). Conclusions Longitudinal behavioural patterns involving low probabilities of social participation were associated with more depressive symptoms. This overshadowing effect suggests that the damage caused by socially inactivity may render the effects of co-existing (un)healthy behaviours meaningless. The stability of the patterns of multiple health behaviours across survey waves suggests that interventions are needed earlier in life.

scholarly journals The importance of relationships in adolescent risk behaviour prevention

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
C Cooper ◽  
M Lhussier
Keyword(s):  
Health Risk ◽  
Focal Point ◽  
Contextual Factors ◽  
Health Behaviours ◽  
Risk Behaviour ◽  
Current Evidence ◽  
Risk Behaviours ◽  
Adolescent Risk ◽  
Health Risk Behaviours ◽  
Multiple Health

Abstract Health risk behaviours are a key contributing factor to adolescent morbidity and mortality. Furthermore, evidence shows that health behaviours begun in adolescence can impact on wellbeing across the lifespan. Current evidence suggests it is advantageous to target multiple health risk behaviours simultaneously, however efficacy testing remains the key focal point for research, with few studies exploring common underlying causal and contextual factors which may contribute to the success or failure of a programme. Methods This review used a customised realist approach, to explore how, why, for whom, and in what circumstances programmes are most successful in preventing multiple health risk behaviours in adolescents. The review synthesised evidence from published literature, along with qualitative data from stakeholders collected through focus groups with young people (n = 28) and school nurses (n = 22), and interviews with adolescent health and wellbeing practitioners (n = 8). Findings: Across all the realist programme theories developed, the role of relationships was the most commonly occurring theme. This theme goes beyond the expected impact of the relationship between programme deliverers and recipients, and familial and peer attachments, also taking in to consideration the relationships between programme and school leaders and staff, support networks and collaborative relationships between staff, and wider social connectedness within the community. These in turn were impacted upon by wider contextual factors, such as family, community, culture, socioeconomic status, intersectionality, and health inequalities. Conclusions These findings provide important insight in to understanding how, why, for whom, and in what circumstances multiple risk behaviour prevention programmes succeed or fail. Further to this they highlight key areas for consideration in the development of future adolescent public health interventions. Key messages Relationships built on trust and genuine care can improve adolescent risk behaviour prevention outcomes. Broader sociocultural context provide key explanations for variations in programme outcomes.

scholarly journals Compliance with Multiple Health Behaviour Recommendations: A Cross-Sectional Comparison between Female Cancer Survivors and Those with no Cancer History

2019 ◽  
Vol 16 (8) ◽  
pp. 1345 ◽  
Author(s):  
Daniel N Tollosa ◽  
Meredith Tavener ◽  
Alexis Hure ◽  
Erica L James
Keyword(s):  
Cancer Research ◽  
Cancer Survivors ◽  
Health Behaviour ◽  
Vegetable Intake ◽  
Health Behaviours ◽  
Cross Sectional ◽  
Cancer History ◽  
Lifestyle Behaviours ◽  
Cancer Group ◽  
Multiple Health

Lifestyle behaviours have an important role in preventing cancer, reducing treatment side effects, and improving survival and quality of life for cancer survivors. This study investigated adherence to multiple lifestyle behaviours among women with and without a cancer history. From the Australian Longitudinal Study on Women’s Health (ALSWH) surveys, 2407 cancer survivors and 3896 controls (cancer free population) were identified. Based on the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) recommendations, adherence to six health behaviours (smoking, physical activity, fruit and vegetable intake, alcohol consumption, sugary drink intake, and Body Mass Index [BMI]) were assessed. Overall adherence was low, and there were no differences between survivors and controls on adherence to any of the six individual health behaviours. However, both recent and long-term cancer survivors were more likely than controls to adhere to multiple health behaviours (p < 0.05). When participants with melanoma or non-melanoma skin cancer were excluded, adherence was less likely (but not significant) in the cancer group than controls. Higher education (p < 0.01), being married (p < 0.01), and lower comorbidity of chronic illnesses (p < 0.01) were significantly associated with adherence to multiple lifestyle behaviours. Overall, the findings suggest that a cancer diagnosis may result in increased compliance with multiple health behaviour guidelines.

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