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Background: Socioeconomic inequalities are well established across health, morbidity and mortality measures. Social class theory describes how social groups relate, interact and accrue advantages/disadvantages relative to one another, with different theorists emphasising different dimensions. In the context of health inequalities, different social class measures are used interchangeably to rank population groups in terms of health rather than directly exploring the role of social class in creating inequalities. We aim to better understand how four distinct social class mechanisms explain differences in a range of self-reported and biological health outcomes., Methods: We use data from the UK Household Longitudinal Study, a representative population survey of UK adults, to identify measures pertaining to Early years, Bourdieusian, Marxist, and Weberian social class mechanisms. Using logistic and least-squares regression we consider the relative extent to which these mechanisms explain differences in health (Self-reported health, SF12 Physical (PCS) and Mental (MCS) Component Scores, General Health Questionnaire; N = 21,446) and allostatic load, a biomarker-based measure of cumulative stress (N = 5003)., Results: Respondents with higher social position according to all social class measures had better self-rated, physical and mental health, and lower allostatic load. Associations with Marxist social class were among the strongest (e.g. Relative Index of Inequality for very good/excellent self-rated health comparing highest versus lowest Marxist social class: 4.96 (4.45, 5.52), with the Weberian measure also strongly associated with self-rated (4.35 (3.90, 4.85)) and physical health (Slope Index of Inequality for SF12-PCS: 7.94 (7.39, 8.48)). Health outcome associations with Bourdieusian and Marxist measures were generally stronger for women and older respondents, and physical health associations with all measures were stronger among those aged 50+ years., Conclusions: The impact of social class on health is multi-faceted. Policies to reduce health inequalities should focus more on unequal capital ownership, economic democracy and educational inequalities, reflecting Marxist and Weberian mechanisms., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Smoking contributes significantly to socioeconomic health inequalities. Vaping has captured much interest as a less harmful alternative to smoking, but may be harmful relative to non-smoking. Examining inequalities in vaping by smoking status, may offer insights into potential impacts of vaping on socioeconomic inequalities in health., Methods: Data were from 3291 youth (aged 10-15) and 35,367 adults (aged 16+) from wave 7 (2015-17) of the UK Household Longitudinal Study. In order to adjust for biases that could be introduced by stratifying on smoking status, marginal structural models were used to estimate controlled direct effects of an index of socioeconomic disadvantage (incorporating household education, occupation and income) on vaping by smoking status (among adults and youth), adjusting for relevant confounders and for selection into smoking states. We also estimated controlled direct effects of socioeconomic disadvantage on being an ex-smoker by vaping status (among adult ever-smokers; n = 18,128)., Results: Socioeconomic disadvantage was associated with vaping among never smoking youth (OR for a unit increase in the socioeconomic index: 1.17; 95%: 1.03-1.34), and among ex-smoking adults (OR: 1.17; 95% CI: 1.09-1.26), with little to no association among never smoking (OR: 0.98; 95% CI: 0.91-1.07) and current smoking (OR: 1.00; 95% CI: 0.93-1.07) adults. Socioeconomic disadvantage was also associated with reduced odds of being an ex-smoker among adult ever-smokers, but this association was moderately weaker among those who vaped (OR: 0.88; 95% CI: 0.82-0.95) than those who did not (OR: 0.82; 95% CI: 0.80-0.84; p-value for difference = 0.081)., Conclusions: Inequalities in vaping among never smoking youth and adult ex-smokers, suggest potential to widen health inequalities, while weaker inequalities in smoking cessation among adult vapers indicate e-cigarettes could help narrow inequalities. Further research is needed to understand the balance of these opposing potential impacts, and how any benefits can be maximised whilst protecting the vulnerable.

Background: Neighborhood deprivation has been consistently linked to poor individual health outcomes; however, studies exploring the mechanisms involved in this association are scarce. The objective of this study was to investigate whether objective measures of the physical environment mediate the association between neighborhood socioeconomic deprivation and biomarkers of health in Britain., Methods: We linked individual-level biomarker data from Understanding Society: The UK Household Longitudinal Survey (2010-2012) to neighborhood-level data from different governmental sources. Our outcome variables were forced expiratory volume in 1 s (FEV 1 %; n=16,347), systolic blood pressure (SBP; n=16,846), body mass index (BMI; n=19,417), and levels of C-reactive protein (CRP; n=11,825). Our measure of neighborhood socioeconomic deprivation was the Carstairs index, and the neighborhood-level mediators were levels of air pollutants (sulphur dioxide [SO 2 ], particulate matter [PM 10 ], nitrogen dioxide [NO 2 ], and carbon monoxide [CO]), green space, and proximity to waste and industrial facilities. We fitted a multilevel mediation model following a multilevel structural equation framework in MPlus v7.4, adjusting for age, gender, and income., Results: Residents of poor neighborhoods and those exposed to higher pollution and less green space had worse health outcomes. However, only SO 2 exposure significantly and partially mediated the association between neighborhood socioeconomic deprivation and SBP, BMI, and CRP., Conclusion: Reducing air pollution exposure and increasing access to green space may improve population health but may not decrease health inequalities in Britain.

Background: Grip strength in early adulthood and midlife is an important predictor of disability, morbidity and mortality in later life. Understanding social patterning in grip strength at different life stages could improve insight into inequalities in age-related decline and when in the life course interventions could prevent the emergence of inequalities., Methods: Using United Kingdom Household Longitudinal Study (UKHLS) data on 19,292 people aged 16 to 99, fractional polynomial models were fitted to identify which function of age best described its association with grip strength. Linear regressions were used to establish whether socio-economic position (SEP), as measured by maternal education, highest educational qualification and income, was associated with grip strength. To test whether the association between age and grip strength was modified by SEP, interactions between SEP and the age terms were added. Differentiation was used to identify the age at which grip strength was highest for men and women and predicted levels of grip strength at peak were compared., Results: SEP is significantly associated with grip strength on all SEP measures, except education for men. Grip strength is highest at a younger age, and less strong for all measures of disadvantage for women and most measures for men. Interaction terms were not statistically significant indicating that the association between age and grip strength was not modified by SEP. Grip strength peak was 29.3 kg at age 33 for women with disadvantaged childhood SEP compared with 30.2 kg at age 35 for women with advantaged childhood SEP., Conclusion: The SEP differences in age and level of peak grip strength could be indicative of decline in muscle strength beginning earlier and from a lower base for disadvantaged groups. This could impact on the capacity for healthy ageing for those with disadvantaged SEP.

Background: Evidence is inconsistent as to whether or not there are health inequalities in adolescence according to socio-economic position (SEP) and whether or when they emerge in early adulthood. Despite the large health inequalities literature, few studies have simultaneously compared the relative importance of 'health selection' versus 'social causation' at this life-stage. This study followed a cohort through the youth-adult transition to: (1) determine whether, and if so, when, health inequalities became evident according to both class of origin and current SEP; (2) compare the importance of health selection and social causation mechanisms; and (3) investigate whether these phenomena vary by gender., Methods: Data are from a West-of-Scotland cohort, surveyed five times between age 15 (in 1987, N=1,515, response=85%) and 36. Self-reported physical and mental health were obtained at each survey. SEP was based on parental occupational class at 15, a combination of own education or occupational status at 18 and own occupational class (with an additional non-employment category) at older ages. In respect of when inequalities emerged, we used the relative index of inequality to examine associations between both parental and own current SEP and health at each age. In respect of mechanisms, path models, including SEP and health at each age, investigated both inter and intra-generational paths from SEP to health ('causation') and from health to SEP ('selection'). Analyses were conducted separately for physical and mental health, and stratified by gender., Results: Associations between both physical and mental health and parental SEP were non-significant at every age. Inequalities according to own SEP emerged for physical health at 24 and for mental health at 30. There was no evidence of selection based on physical health, but some evidence of associations between mental health in early adulthood and later SEP (intra-generational selection). Paths indicated intra-generational (males) and inter-generational (females) social causation of physical health inequalities, and intra-generational (males and females) and inter-generational (females) social causation of mental health inequalities., Conclusions: The results suggest complex and reciprocal relationships between SEP and health and highlight adolescence and early adulthood as a sensitive period for this process, impacting on future life-chances and health.

Lower socioeconomic position (SEP), both accumulated across the life course and at different life-stages, has been found to be associated with higher cumulative physiological burden, as measured by allostatic load. This study aimed to identify what factors mediate the association between SEP and allostatic load, as measured through combining cardiovascular, metabolic and inflammatory markers. We explored the role of material, psychological and behavioral factors, accumulated across two periods in time, in mediating the association between SEP and allostatic load. Data are from the West of Scotland Twenty-07 Study, with respondents followed over five waves of data collection from ages 35 to 55 (n=999). Allostatic load was measured by summing nine binary biomarker scores ('1'=in the highest-risk quartile) measured when respondents were 55years old (wave 5). SEP was measured by a person's accumulated social class over two periods All mediators and SEP were measured at baseline in 1987 and 20years later and combined to form accumulated measures of risk. Material mediators included car and home ownership, and having low income. The General Health Questionnaire (GHQ-12) was used as the psychosocial mediator. Behavioral mediators included smoking, alcohol consumption, physical activity and diet. Path analysis using linear regressions adjusting for sex were performed for each of the potential mediators to assess evidence of attenuation in the association between lower SEP and higher allostatic load. Analyses by mediator type revealed that renting one's home (approximately 78% attenuation) and having low income (approx. 62% attenuation) largely attenuated the SEP-allostatic load association. GHQ did not attenuate the association. Smoking had the strongest attenuating effect of all health behaviors (by 33%) with no other health behaviors attenuating the association substantially. Material factors, namely home tenure and income status, and smoking have important roles in explaining socioeconomic disparities in allostatic load, particularly when accumulated over time., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Introduction: Nordic countries do not have the smallest health inequalities despite egalitarian social policies. A possible explanation for this is that drivers of class differences in health such as financial strain and labour force status remain socially patterned in Nordic countries., Methods: Our analyses used data for working age (25-59) men (n = 48,249) and women (n = 52,654) for 20 countries from five rounds (2002-2010) of the European Social Survey. The outcome was self-rated health in 5 categories. Stratified by gender we used fixed effects linear regression models and marginal standardisation to instigate how countries varied in the degree to which class inequalities were attenuated by financial strain and labour force status., Results and Discussion: Before adjustment, Nordic countries had large inequalities in self-rated health relative to other European countries. For example the regression coefficient for the difference in health between working class and professional men living in Norway was 0.34 (95% CI 0.26 to 0.42), while the comparable figure for Spain was 0.15 (95% CI 0.08 to 0.22). Adjusting for financial strain and labour force status led to attenuation of health inequalities in all countries. However, unlike some countries such as Spain, where after adjustment the regression coefficient for working class men was only 0.02 (95% CI -0.05 to 0.10), health inequalities persisted after adjustment for Nordic countries. For Norway the adjusted coefficient was 0.17 (95% CI 0.10 to 0.25). Results for women and men were similar. However, in comparison to men, class inequalities tended to be stronger for women and more persistent after adjustment., Conclusions: Adjusting for financial security and labour force status attenuates a high proportion of health inequalities in some counties, particularly Southern European countries, but attenuation in Nordic countries was modest and did not improve their relative position.

Background: We examined how socioeconomic position (SEP) across the lifecourse (three critical periods, social mobility and accumulated over time) is associated with allostatic load (a measure of cumulative physiological burden)., Methods: Data are from the West of Scotland Twenty-07 Study, with respondents aged 35 (n = 740), 55 (n = 817) and 75 (n = 483). SEP measures representing childhood, the transition to adulthood and adulthood SEP were used. Allostatic load was produced by summing nine binary biomarker scores (1 = in the highest-risk quartile). Linear regressions were used for each of the lifecourse models; with model fits compared using partial F-tests., Results: For those aged 35 and 55, higher SEP was associated with lower allostatic load (no association in the 75-year-olds). The accumulation model (more time spent with higher SEP) had the best model fit in those aged 35 (b = -0.50, 95%CI = -0.68, -0.32, P = 0.002) and 55 (b = -0.31, 95%CI = -0.49, -0.12, P < 0.001). However, the relative contributions of each life-stage differed, with adulthood SEP less strongly associated with allostatic load., Conclusions: Long-term, accumulated higher SEP has been shown to be associated with lower allostatic load (less physiological burden). However, the transition to adulthood may represent a particularly sensitive period for SEP to impact on allostatic load.

Purpose: Socioeconomic inequalities in anxiety and depression widen with increasing age. This may be due to differences in the incidence or persistence of symptoms. This paper investigates the widening of inequalities in anxiety and depression over the lifecourse., Methods: Data were from the West of Scotland Twenty-07 Study, constituting three cohorts aged approximately 16, 36 and 56 years at baseline and re-visited at 5-yearly intervals for 20 years. Symptoms were measured using the Hospital Anxiety and Depression Scale. Adjusting for age and sex, multilevel models with pairs of interviews (n = 6,878) nested within individuals (n = 3,165) were used for each cohort to estimate associations between current symptoms and education or household social class for both those with and without earlier symptoms, approximating socioeconomic differences in incidence and persistence., Results: Inequalities in current symptom levels were present for both those with and without earlier symptoms. In the youngest cohort, those with less education were more likely to experience persistent depression and to progress from anxiety to depression. At older ages there were educational and social class differences in both the persistence and incidence of symptoms, though there was more evidence of differential persistence than incidence in the middle cohort and more evidence of differential incidence than persistence in the oldest cohort., Conclusions: Differential persistence and symptom progression indicate that intervening to prevent or treat symptoms earlier in life is likely to reduce socioeconomic inequalities later, but attention also needs to be given to late adulthood where differential incidence emerges more strongly than differential persistence.

Deprived and declining areas in Scotland have poorer health than other areas in the rest of Scotland. Using data from the Scottish Longitudinal Study, this paper examines whether differential migration over a one year period can explain these differences. Compared with migrants to and from deprived and declining areas, stable residents in those areas were generally older, less well educated and less affluent. Continued disproportionate loss of more affluent and better educated individuals could result in deprived and declining areas becoming even more deprived over time. Migrants appeared to be in better health; however, this finding was reversed on adjustment for age. It may be that while the relationship between migration and socio-economic status is immediately apparent, the relationship between migration and health could take longer to develop., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Data from the longitudinal West of Scotland Twenty-07 STUDY: Health in the Community was used to examine whether, over a 20 year period, the self-reported health of people living in deprived areas became poorer faster compared to those living in more affluent areas. Three cohorts (born in the early 1930s, 1950s and 1970s) are included, covering 60 years of the life span. Using multilevel growth curve models, a 40% probability of reporting poor health was predicted among residents of more deprived areas at an earlier age (66) compared to those living in more affluent areas (83). Wider area differences were seen for men than for women. Our findings indicate that attempts to reduce area differences in health should start young but also continue throughout the lifespan., (Copyright © 2011 Elsevier Ltd. All rights reserved.)