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Background
Adolescent multiple risk behaviour (MRB) is associated with negative outcomes such as police arrests, unemployment and premature mortality and morbidity. What is unknown is whether MRB is associated with socioeconomic status (SES) in adulthood. We test whether adolescent MRB is associated with socioeconomic status (SES) in young adulthoo...
Context in source publication
Context 1
... File 1 contains the flow diagrams describing the derivation of the imputation sample and the complete case sample for both cohorts ( Supplementary Figures 3 and 4). Table 2 contains the descriptive statistics of both samples. The descriptive statistics for the enrolled cohort samples can be found in Supplementary File 1. ...Similar publications
Objectives: To examine the effect of smoking status, smoking intensity, duration of smoking cessation and age of smoking initiation on the risk of all-cause and cause-specific mortality among cardiovascular disease (CVD) patients.
Design: A population-based prospective cohort study.
Setting: The National Health Interview Survey (NHIS) in the U.S. t...
Background: Frail older adults have an increased risk of adverse health outcomes and premature death. They also exhibit altered gait characteristics in comparison with healthy individuals.
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Background:
A goal of 10,000 steps per day is widely advocated, but there is little evidence to support that goal. Our purpose was to examine the dose-response relationships between step count and mortality and cardiovascular disease risk.
Methods:
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The COVID-19 pandemic and measures aimed at its mitigation, such as physical distancing, have been discussed as risk factors for loneliness, which increases the risk of premature mortality and mental and physical health conditions. To ascertain whether loneliness has increased since the start of the pandemic, this study aimed to narratively and sta...
Citations
... inactive). Notwithstanding these exceptions, our findings support the idea that SNAP behaviours in older people are fairly stable and likely reflect lifelong habits [8], emphasising the importance of addressing risk behaviours early in the life course to prevent negative health outcomes [44]. Additionally, the finding that behavioural patterns are relatively stable over time suggests that clustering in older adults can be accurately captured by cross-sectional studies. ...
Background
Health-risk behaviours such as smoking, unhealthy nutrition, alcohol consumption, and physical inactivity (termed SNAP behaviours) are leading risk factors for multimorbidity and tend to cluster (i.e. occur in specific combinations within distinct subpopulations). However, little is known about how these clusters change with age in older adults, and whether and how cluster membership is associated with multimorbidity.
Methods
Repeated measures latent class analysis using data from Waves 4–8 of the English Longitudinal Study of Ageing (ELSA; n = 4759) identified clusters of respondents with common patterns of SNAP behaviours over time. Disease status (from Wave 9) was used to assess disorders of eight body systems, multimorbidity, and complex multimorbidity. Multinomial and binomial logistic regressions were used to examine how clusters were associated with socio-demographic characteristics and disease status.
Findings
Seven clusters were identified: Low-risk (13.4%), Low-risk yet inactive (16.8%), Low-risk yet heavy drinkers (11.4%), Abstainer yet inactive (20.0%), Poor diet and inactive (12.9%), Inactive, heavy drinkers (14.5%), and High-risk smokers (10.9%). There was little evidence that these clusters changed with age. People in the clusters characterised by physical inactivity (in combination with other risky behaviours) had lower levels of education and wealth. People in the heavy drinking clusters were predominantly male. Compared to other clusters, people in the Low-risk and Low-risk yet heavy drinkers had a lower prevalence of all health conditions studied. In contrast, the Abstainer but inactive cluster comprised mostly women and had the highest prevalence of multimorbidity, complex multimorbidity, and endocrine disorders. High-risk smokers were most likely to have respiratory disorders.
Conclusions
Health-risk behaviours tend to be stable as people age and so ought to be addressed early. We identified seven clusters of older adults with distinct patterns of behaviour, socio-demographic characteristics and multimorbidity prevalence. Intervention developers could use this information to identify high-risk subpopulations and tailor interventions to their behaviour patterns and socio-demographic profiles.
... inactive). Notwithstanding these exceptions, our findings support the idea that SNAP behaviours in older people are fairly stable and likely reflect lifelong habits [8], emphasising the importance of addressing risk behaviours early in the life course to prevent negative health outcomes [44]. Additionally, the finding that behavioural patterns are relatively stable over time suggests that clustering in older adults can be accurately captured by cross-sectional studies. ...
... Several factors have been shown to be associated with high-risk behaviors (e.g., Meeus et al., 2021;Murray et al., 2021;Tinner et al., 2021); these include behavioral, activity, and attention disorders, along with antisocial behavior (Song et al., 2021;Sultan et al., 2021). The underlying causes of behavioral disorders are complex; however, childhood abuse and neglect are important factors in the development of these disorders (García et al., 2021;Kobulsky et al., 2022). ...
Adolescents in aftercare services who are transitioning from out-of-home care, also called care leavers, face more challenges in their lives, and engage in more risk behaviors, than their peers. However, no previous reviews have comprehensively addressed this issue to identify future research needs. The aim of this systematic review was to gather, assess, and synthesize previous studies concerning care leavers’ high-risk behavior. The search was conducted in six databases, with sixteen articles included in the final review. The selected research highlighted five forms of high-risk behavior: substance abuse, delinquency, sexual behavior, irresponsible use of money, and self-destructive behavior. The incidence of high-risk behavior among care leavers varied noticeably between the studies. Some of the studies reported significant connections between high-risk behavior and gender, race, reason(s) for placement, and the form and number of placements. The synthesized findings revealed a fragmented, limited view of care leavers’ high-risk behavior that highlighted substance abuse and delinquency. The development of adolescents, particularly care leavers, includes multiple factors that have either a conducive or protecting effect for high-risk behavior. Comprehensive research regarding care leavers’ high-risk behavior, including the associated factors, is needed to better support healthy development and success in transitioning to independent living.
Schools play a significant role in promoting health and well-being and the reciprocal links between health and educational attainment are well-evidenced. Despite recognition of the beneficial impact of school-based health improvement programmes, significant barriers to improving health and well-being within schools remain. This study pilots a School Health Research Network in the South West of England (SW-SHRN), a systems-based health intervention bringing together schools, academic health researchers and public health and/or education teams in local authorities to share knowledge and expertise to improve the health and well-being of young people. A maximum of 20 secondary schools will be recruited to the pilot SW-SHRN. All students in Years 8 (age 12-13) and 10 (age 14-15) will be invited to complete a health and well-being questionnaire, generating a cohort of approximately 5000 adolescents. School environment questionnaires will also be completed with each school to build a regional picture of existing school health policies and programmes. Each school will be provided with a report summarising data for their students benchmarked against data for all schools in the network. Quantitative analysis will model associations between health risk behaviours and mental health outcomes and a qualitative process evaluation will explore the feasibility and sustainability of the network. This study will create adolescent health data to help provide schools and local authorities with timely and robust information on the health and well-being of their students and help them to identify areas in which public health interventions may be required. SW-SHRN will also help public health professionals focus their resources in the areas most at need.
