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Addressing young people’s health inequalities

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Presentation on theme: "Addressing young people’s health inequalities"— Presentation transcript:

1 Addressing young people’s health inequalities
Social determinants and Adolescent Mental Health Stephen Stansfeld Centre for Psychiatry, Wolfson Institute of Preventive Medicine, Barts & the London School of Medicine and Dentistry, London UK Addressing young people’s health inequalities Association for Young People’s Health and Young People’s Health Special Interest Group, Royal College of Paediatrics and Child Health Coin Street Conference Centre London October 17-18th 2013

2 Outline Pathways of influences on adolescent mental health
Effects of socioeconomic status Neighbourhood and cultural factors Parental and peer social support Exposure to adversity Conclusions

3 Hypothetical pathways linking income inequality and health
(Kondo, 2012)

4 Intermediate factors between social disadvantage and health
Material factors Low income Poor housing Psychosocial factors Stress levels Coping mechanisms Low social support Lifestyle Poor diet Smoking Obesity Environmental factors Noise Air pollution Poor water quality Exposure to toxic chemicals

5 Environment Physical Social Cultural Intervening variables Nervous system Psychiatric Physical Illness illness

6 Health inequalities begin before birth
Generation R Study: 9778 mothers from multi-ethnic sample in Rotterdam Low socioeconomic status associated with: Greater risk of eclampsia, raised maternal blood pressure slower foetal growth, lower birth weight, more pre-term births Infants had more respiratory infections (2 years) and more difficult temperaments (6 months) measured on a standard scale (Raat et al, 2011)

7 Cross-sectional associations between Father’s Social Class and childhood mental health: 1958 Birth Cohort Father’s SEP OR (95% CI) RGSC Internalising Externalising 7y Non-manual Manual 1.0 1.86 ( ) 1.58 ( ) 11y 2.01 ( ) 16y 1.46 ( ) 2.28 ( ) (adjusted for gender)

8 Association of childhood SEP (cumulative) and CIS-R diagnoses in adulthood: 1958 Birth Cohort
No of occasions in manual RGSC % with any Diagnosis OR (95% CI) 4.6 1.0 1 3.8 0.8 ( ) 2 7.2 1.57 ( ) 3 1.57 ( ) 4 6.4 1.39 ( )

9 Just to get a bit of a feel for the area – here are some images of East London…
- Old buildings, and towers blocks close together, London buses

10 RELACHS Study: Risk and Protective factors for mental health
2790 pupils from 29 schools, years at baseline 68% of all secondary school age children in ELCHA are non- White (64% Hackney; 70% Newham; 71% Tower Hamlets) (DfEE 1999) Main groups: Bangladeshi; Black African/Caribbean; Indian and Pakistani Questionnaire administered in English as most respondents are fluent in English Multilingual research workers recruited

11 Proportion with High Strengths and Difficulties score by age and sex compared with national data
% High SDQ score 11-12 years RELACHS HSE Female 11.3% 7% Male 10.5% 11% 13-15 years Female 11.4% 6% Male 8% 9%

12 Proportion of High scorers on the Strengths and Difficulties Questionnaire by socioeconomic status and sex SES Male Female % % Parental employment One/both working Neither working Car ownership Eligibility for Free School Meals No Yes (Stansfeld et al, 2004)

13 Odds ratios for poor mental health by socioeconomic status
Eligibility for SDQ SDQ Free School Adjusted for Sex Adjusted Meals and Year Groups for Ethnicity No 1 1 Yes 1.03 ( ) 1.10 ( )

14 Mean WEMWBS score by socioeconomic Indicator: ORIEL Study
Overcrowded housing Not overcrowded n 51.2 50.8 2688 [50.9, 51.6] [50.1, 51.5] Free school meals No free school meals 51.3 2887 [50.9, 51.7] [50.2, 51.3] Both unemployed Al least one parent employed Both parents employed 51.6 2569 [49.6, 51.8] [ ] [ ] Low FAS score Middle FAS score High FAS score 50.2 50.7 51.8 2819 [49.0, 51.3 [50.2, 51.2] [51.3, 52.4] Significantly different to low FAS (Smith et al, in preparation)

15 Al least one parent employed Both parents employed 25.8 22.5 0.84
Proportion with depressive symptoms by socioeconomic indicator: ORIEL Study % Odds of having depressive symptoms by socioeconomic indicators OR 95% CI Not overcrowded Overcrowded housing n 22.3 2546 [0.81, 1.27] 1 Free school meals No free school meals 21.6 2732 [0.92, 1.33] Both unemployed Al least one parent employed Both parents employed 25.8 2429 [0.61, 1.14] [0.56, 1.06] Low FAS score Middle FAS score High FAS score 25.4 2659 [0.64, 1.16] [0.58, 1.09] (Smith et al, in preparation)

16 Malaise symptoms (mean in past month) by social class at ages 11, 13 and 15 West of Scotland Study I II III-NM III-M IV Linear sig Malaise symptoms Males 11 1.5 13 1.4 15 Females 1.8 2.3 (West & Sweeting, 2004)

17 SHaW Study Questionnaire study of Grade 8 learners (14-15 yrs) in 7 schools from Cape Town Metro Central Educational District All co-educational schools from one administrative district stratified according to fees Total sample size for main study =1034 Response rate = 88% Coloured 60%, Black 25%, White 10%, Indian 2%

18 Risk of mental ill-health by financial difficulties
Depressive Symptoms OR (95% CI) Anxiety symptoms Most financial difficulties Receiving household grants

19 Neighbourhood Quality
Moving to higher quality neighbourhoods associated with less anxiety/depression for boys (Leventhal & Brooks Gunn, 2003) Ambient hazards related to conduct disorder, depression and anxiety (Aneshensel & Sucoff, 1996; Curtis et al, 2004)

20 Neighbourhood deprivation and adolescent mental health
8 Studies from North America and 2 from other parts of Europe show associations between neighbourhood deprivation and externalising and internalising problems controlling for individual and family risk factors Recent UK studies do not show significant associations (Curtis et al 2013) One longitudinal study of adults, 6 cross-sectional studies of children Violence – witnessing an arrest, mugging, shooting, stabbing, having possessions stolen, verbal/physical threats or attacks All North American studies Longitudinal evidence that being a victim of crime associated with poorer mental health, 15 months later. Victims of violent crime more symptomatic than victims of property crime All cross-sectional studies found an association between being a witness or victim of crime and poorer mental health for children Level of evidence: 3b for children 2b for adults: Caution over adult rating as is based on only one study Lack of longitudinal studies and studies of adults 20

21 East London is quite a deprived area, but it is still fairly close to the city – which you can see in the background there~~

22 Area characteristics and psychological distress
Social and economic conditions at level of ‘Middle Layer Super Output Areas’, (Census, 2001) linked with SDQ Lower SDQ among Asian, Black groups, families with social support and no financial stress High SDQ among those with special educational needs, long standing illness, reconstituted families Area differences associated with 6% of variation in SDQ score Material deprivation, social fragmentation, crime did not show effects on SDQ Better mental health for South Asians in medium rather than high or low ethnic density areas (Fagg et al, 2006)

23 Odds ratios for high SDQ scores by ethnic group and socioeconomic status
Adjusted* for + Adjusted for Ethnicity sex and year group SES OR (95%CI) OR (95%CI) White (UK) 1 1 White (Other) 1.39 ( ) 1.36 ( ) Bangladeshi 0.64 ( ) 0.63 ( ) Pakistani 0.92 ( ) 0.91 ( ) Indian 1.02 ( ) 1.03 ( ) Black 0.89 ( ) 0.89 ( ) Mixed 1.16 ( ) 1.15 ( ) Other 0.71 ( ) 0.71 ( ) *Adjusted for sex, year group, and interaction sex x year group (Stansfeld et al, 2004)

24 RELACHS Study: Odds ratios for Mood and Feelings Questionnaire caseness by ethnic group and socioeconomic status Adjusted* for + Adjusted for Ethnicity sex and year group SES OR (95%CI) OR (95%CI) White (UK) 1 White (Other) 1.53 ( ) 1.54 ( ) Bangladeshi 0.92 ( ) 0.92 ( ) Pakistani 0.97 ( ) 0.97 ( ) Indian 1.01 ( ) 1.01 ( ) Black 0.94 ( ) 0.94 ( ) Mixed 1.25 ( ) 1.25 ( ) Other 1.26 ( ) 1.27 ( ) *Adjusted for sex, year group, and interaction sex x year group (Stansfeld et al, 2004)

25 Risk for psychological distress and depressive symptoms: adjustment for recent migration

26 Cultural Identity and Psychological Distress
Integrated friendship choices (OR= 0.6, 95% CI ) boys (OR= 0.5, 95% CI ) and Bangladeshi pupils (OR= 0.15, 95% CI ) protective of psychological distress relative to marginalised identity (Bhui et al, 2005) In longitudinal analysis traditional identity based on clothing choice was protective for Bangladeshi girls (Bhui et al, 2008)

27 Area social fragmentation, social support and mental health
High levels of social cohesion are beneficial for mental health (Aneshesel & Sucoff, 1996) Health Survey for England 2002 – 5,777, years old Social fragmentation in geographical areas was a risk factor for mental ill-health Family social support for the individual was independently protective for mental health The benefits of social support did not vary by area (Fagg et al 2008) One longitudinal study of adults, 6 cross-sectional studies of children Violence – witnessing an arrest, mugging, shooting, stabbing, having possessions stolen, verbal/physical threats or attacks All North American studies Longitudinal evidence that being a victim of crime associated with poorer mental health, 15 months later. Victims of violent crime more symptomatic than victims of property crime All cross-sectional studies found an association between being a witness or victim of crime and poorer mental health for children Level of evidence: 3b for children 2b for adults: Caution over adult rating as is based on only one study Lack of longitudinal studies and studies of adults 27

28 Low Medium High Social support and odds of distress in HSE respondents
from areas of low, medium, high area fragmentation This slide shows the outcome of a further analysis which divided the young adults in the study into three groups according to the level of social fragmentation in their neighbourhood. There are some statistical limitations to comparisons across analyses like this, but they confirm the interaction model in the previous slide. Social support at the individual level has a clear association with reduced odds of distress (better health). People with very high social support have odds of reporting distress which are around a third of those with very low levels of social support, and there is a graded relationship. The differences in odds of distress associated with level of social support are similar in all three types of setting.

29 Prospective Associations between Social Support and Mental Health Outcomes
Low family social support at baseline was associated with a higher risk of depressive symptoms at follow-up in adjusted models* (OR=2.33, 95% CI: ) A decrease in family social support over time was associated with a higher risk of depressive symptoms at follow-up in adjusted models* (OR=2.14, 95% CI ) (Khatib et al, 2013) *Adjusted for age, gender, an interaction between age and gender, socio-economic status (eligibility for free school meals, parental employment status, parental ownership of vehicle), ethnicity, and country of birth, length of time in the UK ****Read from Slide****

30 Key Findings: Can Social Support Account for Ethnic Variations in Mental Health Outcomes?
Ethnicity OR (95% CI) for Overall Psychological Distress (SDQ Caseness) OR (95% CI) for Depressive Symptoms (MFQ Caseness) Unadjusted White UK Bangladeshi Black 1 0.68 (0.40,1.17) 0.26 (0.11,0.59) 1.59 (1.04,2.43) 0.69 (0.40,1.17) Adjusted* 0.29 (0.09,0.97) 0.16 (0.04,0.62) 1.12 (0.58,2.16) 0.66 (0.29,1.50) *****Describe Table***** PLUS Bangladeshi pupils displayed a significantly lower association with SDQ Caseness once socio-economic indicators were entered into the regression model. Although Bangladeshi pupils show higher rates of depressive symptoms (measured by the MFQ) at follow-up compared with White UK pupils in the unadjusted model, this association was not apparent when country of birth and length of time in the UK were entered into the model. *Adjusted for age, gender, an interaction between age and gender, socio-economic status (eligibility for free school meals, parental employment status, parental ownership of vehicle), ethnicity and country of birth, length of time in the UK and SOCIAL SUPPORT

31 Multivariate associations with self harm
Factor Adjusted Odds Ratio 95% C.I. Support from family Moderate Low 1.0 3.92 3.53 ( ) ( ) Bullying (lifetime) Never been bullied Ever been bullied 2.37 ( ) Adverse life events 1 2 3+ 1.76 2.49 4.41 ( ) ( ) ( ) The variables with significant univariate associations were built into a multivariate model, adjusting for each other, predicting self-harm. This slide shows the significant associations, adjusted for the other factors, and also adjusted for ethnicity and SES. The odds for self harm for those who reported depressive symptoms at Phase 2 and Phase 3 remained significant, even adjusting for each other, implying that in this sample, both previous and current mental health are associated with self harm. Religious observance was not significantly associated with self harm in this adjusted analyses. However, in the Cultural identity assessment of clothing choices worn with family, the assimilated and marginalised groups had increased odds of self harm. Now, these groups are quite small, and that has widened the confidence intervals… but this result remained significant after adjustment for mental health and gender. The Traditional group did not have increased odds of self harm in this model. - Although there were no significant differences by ethnic group, there were higher (but non-significantly higher) rates in the Asian British group compared with other ethnicities… so these results may imply that there is some element intergenerational or cultural conflict associated with self harm in these East London adolescents. ~~

32 Peer relationships Broadly positive impact of peer support on depressive symptoms Association with delinquent peer group may have particularly negative effects Unsupervised peer contact associated with behavioural problems Peer rejection associated with depression but not always with behavioural difficulties (Stansfeld et al unpublished)

33 Early lack of care, abuse, neglect and depression
Parental indifference, physical, sexual abuse predict depression (Brown et al, 1993; Bifulco et al, 1994) Relationship between childhood neglect and abuse and adult depression ‘explained by’ depression before the age of 20y (Bifulco et al, 1998) Experience of childhood abuse and neglect may predict subsequent poor parenting – intergenerational transmission risk (Andrews et al, 1990)

34 Neighbourhood Violence and Mental Health
“Exposure” to violence includes: living in a neighbourhood with a high crime rate: witnessing violence: perceptions of the neighbourhood as risky: direct experience of victimisation: Strong relationships with post-traumatic stress disorder, psychological distress, internalizing and externalising behaviours, low self esteem, suicidal cognition, depression, anger, sadness, anxiety , aggression, conduct disorders and anti-social behaviour. Energy expended in coping with community violence may be at the cost of school, work and personal relationships (Cooley-Quille et al, 2001) Had expected to find qualitative and quantitative studies emerging: but they were very largely quantitative Almost all the studies were actually about ‘community violence’ rather than other sorts of crime (- home violence excluded, other than where it related to community violence) So now look at relationships with mental health 34

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37 Exposure to violence and risk of depressive symptoms: SHaW Study
Unadjusted Fully adjusted Harvard Trauma OR 95% CI OR 95% CI Questionnaire Quartile (1.05, 2.99) 1.74 (0.98, 3.11) (1.99, 5.41) 2.69 (1.49, 4.84) (3.34, 9.00) 4.72 (2.52, 8.84) *Adjusted for sex, ethnicity, social position, physical health, risk behaviours and social support

38 Multivariable analysis: odds of PTSD
Case on PTSD OR (95% CI) Levels of exposure to violence adjusting for sex Adjusting for sex, ethnicity adjusting for sex, ethnicity, social support 1 lowest 1 2 2.14 (0.38, 12.16) 2.04 (0.36, 11.50) 2.08 (0.39, 10.93) 3 2.68 (0.56, 12.81) 2.41 (0.50, 11.55) 2.41 (0.53, 10.88) 4 highest 10.26 (3.01, 35.00) 9.10 (2.70, 30.69) 8.93 (2.93, 27.24)

39 Conclusions Less advantaged socioeconomic status is associated with poorer mental health in some but not all studies Adverse neighbourhoods and exposure to violence tend to be associated with poorer mental health Cultural influences and social support can be important protective factors Interventions are needed that span areas, generations and the lifecourse 39


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