Does neighbourhood identification buffer against the effects of socioeconomic disadvantage on self-harm?
Section snippets
Participants
A total of 3,412 participants completed the survey; 1,490 identified as male and 1,922 identified as female. Ten per cent of the sample were from Black and Minority Ethnic (BME) backgrounds and the remaining 90% were from White ethnic backgrounds. The mean age of the sample was 49.37 years (SD = 18.91). Participants were compensated with a £10 voucher for their participation.
Design and sampling
The study is a secondary analysis of the NIHR ARC North West Coast Household Health Survey. This is a two-wave survey, although only the second wave of data (2018) is included in the present study because self-harm and neighbourhood identity were not measured in wave 1 (2015). In-person surveys were conducted with members of the public living in 19 disadvantaged neighbourhoods of North West England between August and December 2018. Neighbourhoods map approximately onto electoral ward boundaries
Patient and public involvement
A public advisory panel was involved in the development of the survey design and materials. Public advisors with lived experience of mental distress also sat on the Household Health Survey Implementation Group, which oversaw the survey administration and consulted on survey modifications between waves 1 and 2. A public advisor with experience of self-harm contributed to the present research questions and preparation of the manuscript and is therefore named as a co-author.
Neighbourhood identification
Neighbourhood identification was measured with the Four Item Social Identity Scale (FISIS; Postmes et al., 2013). The scale taps key components of social identity such as commitment (“I feel committed to my local neighbourhood”) and centrality (“Being part of my local neighbourhood is an important part of how I see myself”). The scale has good reliability and correlates highly with more comprehensive measures of social identification (Postmes, Haslam, & Jans, 2013). Response options range from
Socioeconomic disadvantage
Socioeconomic disadvantage was measured at the individual level and neighbourhood level. Subjective person-level disadvantage was based on a single-item inquiring about people's current financial situation, which they could describe as "doing well", "getting by", or "struggling". For the purposes of the present study, and to aid in the interpretation of the predicted interactive effects, this variable was dichotomised by collapsing the "getting by" and "struggling" categories (1 = struggling or
Self-harm behaviours and thoughts
For self-harm behaviour, participants indicated if they had “deliberately hurt yourself in the past 12 months” (0 = no, 1 = yes). Self-harm thoughts were assessed with item nine of the Patient Health Questionnaire (PHQ9; Kroenke et al., 2001). Participants indicated the extent to which they had been bothered by “Thoughts that you would be better off dead, or of hurting yourself in some way” over the past two weeks. Due to the extremely high level of skewness (S-W = .92, p < .00001) and to
Demographics
Age was recorded in years, ethnicity was coded as 0 = White background, 1 = BME background, and gender was coded as 1 = male, 2 = female.
Analysis plan
The study hypotheses and analysis plan were pre-registered prior to being undertaken (https://osf.io/amkuv). Analyses were undertaken using STATA version 12 (StataCorp, 2011). Unadjusted bivariate relationships were examined with point-biserial correlations. Logistic regression was used to estimate the relationship between self-harm behaviours and thoughts (in both cases, 1 = present, 0 = absent) and the variables of interest with strengths of association reported as odds ratios. Clustering by
Missing data analysis
Missing data analysis indicated very low levels of missing data at the variable and participant level. For the multi-item scale (neighbourhood identity), missing values analysis indicated that eleven participants (< .01%) had missing data for more than 20% of the items. As such, these participants were excluded from subsequent analyses in-line with the pre-registration plan. This resulted in a final sample size of N = 3401. Following this step, we conducted variable level missing values
Preliminary analyses and descriptive statistics
Four hundred and ninety-one participants (14.7%) reported thoughts of self-harm in the previous two weeks and 91 participants (2.8%) reported self-harm behaviours. Mean levels of neighbourhood identification were above the mid-point of the five-point scale (M = 3.60, SD = .94) and 719 participants (21.2%) indicated that they were “doing well” financially, relative to “struggling” or “getting by”. Eighty-one per cent of participants were in the most disadvantaged quintile based on IMD scores (M
Logistic regression analyses
A series of weight- and cluster-adjusted logistic regressions were conducted to examine the predictors of self-harm thoughts and behaviours. All coefficients and confidence intervals are reported in Tables 1, 2, 3, 4, 5 to 6. Predictors were entered in separate steps for every model, with socioeconomic status (SES) entered at Step 1 (Model A), neighbourhood identity at Step 2 (Model B) the interaction between neighbourhood identity and SES at Step 3 (Model C), and the demographic covariates
Self-harm thoughts (Tables 1 to 3)
Model 1, which assessed neighbourhood identity and IMD as predictors, found that at Step 1, IMD was a significant predictor of self-harm thoughts. Specifically, each one-point increase in IMD was associated with 2% higher odds of reporting self-harm thoughts. At Step 2, neighbourhood identity was also a significant predictor of self-harm thoughts. Each one-point increase in neighbourhood identity was associated with 24% lower odds of reporting self-harm thoughts. The interaction term did not
Self-harm behaviours (Tables 4 to 6)
In Model 4, IMD was a significant predictor of self-harm behaviours at Step 1. Each one-point increase in IMD was associated with 3% higher odds of self-harming. Neighbourhood identity was also a significant predictor of self-harm behaviours at Step 2. Each one-point increase in identification was associated with 41% lower odds of reporting self-harm behaviours. The interaction term was not significant at Step 3, but was significant at Step 4 when adjusting for demographic covariates. The
Discussion
The aim of this study was to investigate the association between neighbourhood identification, socioeconomic disadvantage and self-harm thoughts and behaviour. The study benefits from a large, locally representative sample, and pre-registered hypotheses and analysis plan. Lower neighbourhood identification and greater socioeconomic disadvantage were associated with self-harm across the analyses. The hypothesised interaction between identity and disadvantage was not evident in any analyses.
The
Declaration of competing interests
None
The role of funding source
This research is part funded by the National Institute for Health Research Applied Research Collaboration North West Coast (ARC NWC). The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care. The funding body had no role in any aspect of this study, including the design, data collection, analysis, interpretation, and write up.
Acknowledgement
Nothing to report
Ethical Statement
Ethical approval: Ethical approval was obtained from the University of Liverpool (Ref: RETH000836). Participants provided written informed consent prior to taking part in the study.
Availability of data and materials Users can obtain access to the ARC NWC HHS data files after submitting a brief proposal (including agreement to HHS’ conditions of use) at [[email protected]]. Users will also be required to outline which version of the survey dataset they wish to access, data security arrangements in
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