Background There is growing concern about associations between social media use and mental health and wellbeing amongst young people. We explored links between frequency of social media use and later mental health and wellbeing in early adolescents, including mediation of effects through cyberbullying and displacement of sleep and physical activity. Methods Secondary analyses of Our Futures, a nationally-representative longitudinal study of young people in England from age 13 to 16 years. Exposures: frequency of social media use at waves 1 (age 13/14 years) through 3 (age 15/16y). Outcomes: a) mental health: General Health Questionnaire (GHQ) at wave 2; b) wellbeing scores (life satisfaction, life is worthwhile, happiness and anxiety) at wave 3. Analyses adjusted for minimal sufficient confounding structure. Mediation: assessed using khb commands in Stata 15. Findings Very frequent social media use (habitually multiple times daily) increased from 42.6% (95% CI: 41.2, 44.2) in wave 1 to 68.5%(67.3, 69.7) by wave 3. Very frequent social media use in wave 1 predicted GHQ high score at wave 2 amongst girls (odds ratio (OR) 1.31 (95% CI: 1.06, 1.63) p=0.01) and boys (1.67 (1.24, 2.26) p=0.001). Persistent very frequent social media use across waves 1 and 2 predicted lower wellbeing amongst girls only (happiness 0.80 (0.70, 0.92) p=0.001; anxiety 1.28 (1.11, 1.48) p=0.001). Associations of social media use with GHQ high score and wellbeing scores for girls were attenuated when adjusted for cyberbullying, sleep and physical activity, although associations amongst boys remained significant. Interpretation Mental health harms related to very frequent social media use amongst girls and appeared very largely due to exposure to cyberbullying and or displacement of sleep and physical activity. Interventions to promote mental health should include efforts to prevent or increase resilience to cyberbullying and ensure adequate sleep and physical activity amongst young people.

This study examined the relationship between racial discrimination and use of dental services among American adults. We used data from the 2014 Behavioral Risk Factor Surveillance System, a health-related telephone cross-sectional survey of a nationally representative sample of adults in the United States. Racial discrimination was indicated by two items, namely perception of discrimination while seeking healthcare within the past 12 months and emotional impact of discrimination within the past 30 days. Their association with dental visits in the past year was tested in logistic regression models adjusting for predisposing (age, gender, race/ethnicity, income, education, smoking status), enabling (health insurance), and need (missing teeth) factors. Approximately 3% of participants reported being discriminated when seeking healthcare in the past year, whereas 5% of participants reported the emotional impact of discrimination in the past month. Participants who experienced emotional impact of discrimination were less likely to have visited the dentist during the past year (Odds Ratios (OR): 0.57; 95% CI 0.44–0.73) than those who reported no emotional impact in a crude model. The association was attenuated but remained significant after adjustments for confounders (OR: 0.76, 95% CI 0.58–0.99). There was no association between healthcare discrimination and last year dental visit in the fully adjusted model. Emotional impact of racial discrimination was an important predictor of use of dental services. The provision of dental health services should be carefully assessed after taking account of racial discrimination and its emotional impacts within the larger context of social inequalities.

Psychosocial stress plays an important role in periodontal disease through biological and behavioral pathways. In this paper we review studies that examine the relationship between stress and periodontal diseases, and discuss the different measures used to assess stress. Self-reported measures, such as the Perceived Stress Scale and the Stress Appraisal Measure, have traditionally been used to assess stress. Frequent and repeated exposure to stressor(s) leads to wear and tear of the body's systems, resulting in what is known as allostatic load. In recent years, few studies examining the relationship between stress and periodontal diseases have used an aggregate variable, including primary and secondary markers of allostatic load, as a biological marker of stress. While research on the relationship between allostatic load and periodontal disease is still developing, as most of the studies used cross-sectional data, this line of research presents a good opportunity for establishing a composite biological indicator as a risk factor for periodontal disease. Such an indicator is also potentially beneficial for personalized periodontics as it will help to target intervention to specific levels of risk and will help in integrating oral and general health promotion policies.

ObjectiveTo determine the modifiable factors influencing well-being in boys and girls by accounting for deprivation, ethnicity and clustering within local authorities.MethodsWe used data from a very large nationally representative survey, the What About Youth study involving 120 115 adolescents aged 15 years. Our outcome measure of mental well-being was the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS). Potential explanatory factors included substance abuse, screen time, eating habits, reading, bullying, sleeping pattern, physical activity and area-level deprivation. We ran unadjusted and adjusted multilevel models for each explanatory factor, after adjusting for ethnicity, deprivation and including a random effect for the local authority.ResultsBoys had a higher overall mean WEMWBS score than girls (p<0.0001). In the adjusted model, each of multiple risk behaviours, eating habits, sleep, bullying, physical activity, screen-time and reading were independently associated with mental well-being in both boy and girls (p<0.0001 for both). Sleep and eating behaviours had a stronger association in both sexes than bullying, physical activity and screen time. Young people from black ethnic groups had significantly higher well-being in both sexes. Deprivation was not associated with well-being among boys but was among girls.ConclusionThe largest contributors to adolescent well-being appear to be sleep, eating behaviours and bullying when considered in a multivariable framework. While adolescents from black ethnic groups had higher overall well-being scores, area deprivation did not affect male well-being but had a small effect on female well-being. Future longitudinal studies and health policies need to consider a range of behavioural factors to drive improvements in adolescent well-being.

Background Evidence indicates that early life is critical for determining future obesity risk. A sharper policy focus on pregnancy and early childhood could help improve obesity prevention efforts. This study aimed to systematically identify and categorise policy levers used in England with potential to influence early life course (pregnancy, 0-5 years) and identify how these interface with energy balance behaviours. The objective is to identify gaps and where further policy actions could most effectively focus. Methods A behavioural science approach was taken using the Capability-Opportunity-Motivation-Behaviour (COM-B) model and Behaviour Change Wheel (BCW) framework. The key determinants of energy balance in the early years were identified from the Foresight Systems Map. Policy actions were scoped systematically from available literature, including any health or non-health policies which could impact on energy balance behaviours. Foresight variables and policy actions were considered in terms of COMB and the BCW to determine approaches likely to be effective for obesity prevention and treatment. Existing policies were overlaid across the map of key risk factors to identify gaps in obesity prevention and treatment provision. Results A wide range of policy actions were identified (n = 115) to address obesity-relevant risk factors. These were most commonly educational or guidelines relating to environmental restructuring (i.e. changing the physical or social context). Scope for strengthening policies relating to the food system (e.g. the market price of food) and psychological factors contributing to obesity were identified. Policies acted via all aspects of the COMB model, but there

Background The need for specific services for young people is being widely recognized to address their unique and complex health needs. Growing evidence in integrated health services shows promise in improving the efficiency of health systems. Although there is a broad agreement on the need for integrated care in young people, there has been no systematic effort to evaluate the provision of integrated out-of-hospital health services for this group. The proposed systematic review aims to assess the effectiveness, feasibility, and acceptability of young people-specific integrated out-of-hospital services. Methods We will search the following databases using a systematic search strategy: MEDLINE, EMBASE, CINAHL Plus, and CENTRAL for articles published in the English language without applying date filters. The search will be supplemented with article search from systematic reviews of relevant topics, reference lists, and citations of included studies. Eligible studies will include peer-reviewed publications reporting on the evaluation of integrated out-of-hospital health services for young people (10–24 years) regarding effectiveness, feasibility, and acceptability. Two reviewers (AP and AA) will independently carry out study selection, data extraction, and quality assessment. Study findings will be summarized in a narrative review. Wherever possible, evidence synthesis of quantitative data will be done using forest plots and pooled estimates. Discussion This review aims to provide comprehensive evidence regarding young people-specific integrated out-of-hospital health services. Such rigorously evaluated evidence will be useful for policy makers and health professionals to design and select health services for this group. This review will also identify any evidence gaps in young people-specific integrated health services evaluation. Systematic review registration PROSPERO CRD42017068836 Electronic supplementary material The online version of this article (10.1186/s13643-019-0993-9) contains supplementary material, which is available to authorized users.

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Background Evidence indicates that early life is a critical time for determining future risk of obesity. A sharper policy focus on pregnancy and early childhood would be useful to improve obesity prevention efforts. This study aimed to systematically identify and categorise the policy levers being used in England that have potential to influence early lifecourse (pregnancy and 0-5 years) and identify how these policies interface with energy balance behaviours. The objective is to identify gaps and where further policy actions could most effectively focus. Methods A behavioural science approach was taken using the Capability-Opportunity-Motivation-Behaviour (COM-B) model and Behaviour Change Wheel (BCW) framework. The key determinants of energy balance in the early years were identified from the Foresight Systems Map. Policy actions were scoped systematically from available literature, including any health or non-health policies which could impact on energy balance behaviours. The Foresight variables and policy actions were considered in terms of COM-B and the BCW to determine approaches that would be likely to be effective for obesity prevention and treatment. Existing policies were then overlaid across the map of key risk factors to identify gaps in obesity prevention and treatment provision. Results A wide range of policy actions were identified (n=115) to address obesity-relevant risk factors. The most common policy actions were educational and guidelines relating to environmental restructuring (i.e. changing the physical or social context). Scope for strengthening policies relating to the food system (e.g. the market price of food) and psychological factors contributing to obesity were identified. Policies acted via all aspects of the COM-B model, but there was scope forimproving policies to increase capability through skills acquisition and both reflective and automatic motivation. Conclusions There is substantial policy activity to address early years obesity but much is focused on education. Scope exists to strengthen actions relating to upstream policies which act on food systems and those targeting psychological factors contributing to obesity risk.