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Objective Given the paucity of evidence-based research investigating different suicidal ideation profiles and trajectories, this project sought to investigate health and socio-economic factors associated with the presence of suicidal ideation and changes in ideation over time. Design Longitudinal cohort design, using logistic regression analysis. Setting A public health survey was administered at two timepoints in a community setting across the North West of England. In the 2015/2016 survey, participants were recruited from high (n=20) and low (n=8) deprivation neighbourhoods. In the 2018 survey, only the 20 high-deprivation neighbourhoods were included. Participants 4287 people were recruited in 2015/2016 and 3361 were recruited in 2018. The 2018 sample was subdivided into those who responded only in 2018 (n=2494: replication sample) and those who responded at both timepoints (n=867: longitudinal sample). Primary outcome measures Suicide ideation was the dependent variable which was assessed using item 9 of the Patient Health Questionnaire instrument. Results The prevalence of suicidal ideation was 11% (n=454/4319) at 2015/2016 and 16% (n=546/3361) at 2018. Replication study results highlighted: persistent debilitation from physical ill health and/or medication side effects; demographic factors (ie, middle-aged, single or never married); and personal coping strategies (ie, smoking) as risk factors for suicidal ideation. A static/improved financial position and high levels of empathy were protective factors. Longitudinal study results confirmed three suicidal ideation trajectories: ‘onset’, ‘remission’ and ‘persistence’. Similar findings to the replication study were evidenced for the onset and persistence trajectories. Persistent suicidal ideation was synonymous with higher levels of practical support which may correspond to the higher levels of debilitation and functional disability reported within this group. Remission was characterised by fewer debilitating fact

Objectives To examine the socioeconomic and demographic drivers associated with polypharmacy (5–9 medicines), extreme polypharmacy (9–20 medicines) and increased medication count. Design, setting and participants A total of 5509 participants, from two waves of the English North West Coast, Household Health Survey were analysed Outcome measures Logistic regression modelling was used to find associations with polypharmacy and extreme polypharmacy. A negative binomial regression identified associations with increased medication count. Descriptive statistics explored associations with medication management. Results Age and number of health conditions account for the greatest odds of polypharmacy. ORs (95% CI) were greatest for those aged 65+ (3.87, 2.45 to 6.13) and for those with ≥5 health conditions (10.87, 5.94 to 19.88). Smaller odds were seen, for example, in those prescribed cardiovascular medications (3.08, 2.36 to 4.03), or reporting >3 emergency attendances (1.97, 1.23 to 3.17). Extreme polypharmacy was associated with living in a deprived neighbourhood (1.54, 1.06 to 2.26). The greatest risk of increased medication count was associated with age, number of health conditions and use of primary care services. Relative risks (95% CI) were greatest for those aged 65+ (2.51, 2.23 to 2.82), those with ≥5 conditions (10.26, 8.86 to 11.88) or those reporting >18 primary care visits (2.53, 2.18 to 2.93). Smaller risks were seen in, for example, respondents with higher levels of income deprivation (1.35, 1.03 to 1.77). Polypharmic respondents were more likely to report medication management difficulties associated with taking more than one medicine at a time (p<0.001). Furthermore, individuals reporting a mental health condition, were significantly more likely to consistently report difficulties managing their medication (p<0.001). Conclusion Age and number of health conditions are most associated with polypharmacy. Thus, delaying or preventing the onset of long-term con

Objectives To address a gap in knowledge by simultaneously assessing a broad spectrum of individual socioeconomic and potential health determinants of suicidal ideation (SI) using validated measures in a large UK representative community sample. Design In this cross-sectional design, participants were recruited via random area probability sampling to participate in a comprehensive public health survey. The questionnaire examined demographic, health and socioeconomic factors. Logistic regression analysis was employed to identify predictors of SI. Setting Community setting from high (n=20) and low (n=8) deprivation neighbourhoods across the North West of England, UK. Participants 4319 people were recruited between August 2015 and January 2016. There were 809 participants from low-deprivation neighbourhoods and 3510 from high-deprivation neighbourhoods. The sample comprised 1854 (43%) men and 2465 (57%) women. Primary outcome measures SI was the dependent variable which was assessed using item 9 of the Patient Health Questionnaire-9 instrument. Results 454 (11%) participants reported having SI within the last 2 weeks. Model 1 (excluding mental health variables) identified younger age, black and minority ethnic (BME) background, lower housing quality and current smoker status as key predictors of SI. Higher self-esteem, empathy and neighbourhood belonging, alcohol abstinence and having arthritis were protective against SI. Model 2 (including mental health variables) found depression and having cancer as key health predictors for SI, while identifying as lesbian, gay, bisexual, transgender or queer (LGBTQ) and BME were significant demographic predictors. Alcohol abstinence, having arthritis and higher empathy levels were protective against SI. Conclusions This study suggests that it could be useful to increase community support and sense of belonging using a public health approach for vulnerable groups (e.g. those with cancer) and peer support for people who identify as