Prevalence of frailty indicators and association with socioeconomic status in middle-aged and older adults in a swiss region with universal health insurance coverage : a population-based cross-sectional study

Frailty prevalence in older adults has been reported but is largely unknown in middle-aged adults. We determined the prevalence of frailty indicators among middle-aged and older adults from a general Swiss population characterized by universal health insurance coverage and assessed the determinants of frailty with a special focus on socioeconomic status. Participants aged 50 and more from the population-based 2006-2010 Bus Santé study were included (N = 2,930). Four frailty indicators (weakness, shrinking, exhaustion, and low activity) were measured according to standard definitions. Multivariate logistic regressions were used to determine associations. Overall, 63.5%, 28.7%, and 7.8% participants presented no frailty indicators, one frailty indicator, and two or more frailty indicators, respectively. Among middle-aged participants (50-65 years), 75.1%, 22.2%, and 2.7% presented 0, 1, and 2 or more frailty indicators. The number of frailty indicators was positively associated with age, hypertension, and current smoking and negatively associated with male gender, body mass index, waist-to-hip ratio, and serum total cholesterol level. Lower income level but not education was associated with higher number of frailty indicators. Frailty indicators are frequently encountered in both older and middle-aged adults from the Swiss general population. Despite universal health insurance coverage, household income is independently associated with frailty.

Association of Lifecourse Socioeconomic Status with Chronic Inflammation and Type 2 Diabetes Risk: The Whitehall II Prospective Cohort Study.

BACKGROUND: Socioeconomic adversity in early life has been hypothesized to "program" a vulnerable phenotype with exaggerated inflammatory responses, so increasing the risk of developing type 2 diabetes in adulthood. The aim of this study is to test this hypothesis by assessing the extent to which the association between lifecourse socioeconomic status and type 2 diabetes incidence is explained by chronic inflammation. METHODS AND FINDINGS: We use data from the British Whitehall II study, a prospective occupational cohort of adults established in 1985. The inflammatory markers C-reactive protein and interleukin-6 were measured repeatedly and type 2 diabetes incidence (new cases) was monitored over an 18-year follow-up (from 1991-1993 until 2007-2009). Our analytical sample consisted of 6,387 non-diabetic participants (1,818 women), of whom 731 (207 women) developed type 2 diabetes over the follow-up. Cumulative exposure to low socioeconomic status from childhood to middle age was associated with an increased risk of developing type 2 diabetes in adulthood (hazard ratio [HR] = 1.96, 95% confidence interval: 1.48-2.58 for low cumulative lifecourse socioeconomic score and HR = 1.55, 95% confidence interval: 1.26-1.91 for low-low socioeconomic trajectory). 25% of the excess risk associated with cumulative socioeconomic adversity across the lifecourse and 32% of the excess risk associated with low-low socioeconomic trajectory was attributable to chronically elevated inflammation (95% confidence intervals 16%-58%). CONCLUSIONS: In the present study, chronic inflammation explained a substantial part of the association between lifecourse socioeconomic disadvantage and type 2 diabetes. Further studies should be performed to confirm these findings in population-based samples, as the Whitehall II cohort is not representative of the general population, and to examine the extent to which social inequalities attributable to chronic inflammation are reversible. Please see later in the article for the Editors' Summary.

Socioeconomic status, structural and functional measures of social support, and mortality: The British Whitehall II Cohort Study, 1985-2009.

The authors examined the associations of social support with socioeconomic status (SES) and with mortality, as well as how SES differences in social support might account for SES differences in mortality. Analyses were based on 9,333 participants from the British Whitehall II Study cohort, a longitudinal cohort established in 1985 among London-based civil servants who were 35-55 years of age at baseline. SES was assessed using participant's employment grades at baseline. Social support was assessed 3 times in the 24.4-year period during which participants were monitored for death. In men, marital status, and to a lesser extent network score (but not low perceived support or high negative aspects of close relationships), predicted both all-cause and cardiovascular mortality. Measures of social support were not associated with cancer mortality. Men in the lowest SES category had an increased risk of death compared with those in the highest category (for all-cause mortality, hazard ratio = 1.59, 95% confidence interval: 1.21, 2.08; for cardiovascular mortality, hazard ratio = 2.48, 95% confidence interval: 1.55, 3.92). Network score and marital status combined explained 27% (95% confidence interval: 14, 43) and 29% (95% confidence interval: 17, 52) of the associations between SES and all-cause and cardiovascular mortality, respectively. In women, there was no consistent association between social support indicators and mortality. The present study suggests that in men, social isolation is not only an important risk factor for mortality but is also likely to contribute to differences in mortality by SES.

Association of socioeconomic status with overall and cause specific mortality in the republic of seychelles : results from a cohort study in the african region

BACKGROUND: Low socioeconomic status (SES) is consistently associated with higher mortality in high income countries. Only few studies have assessed this association in low and middle income countries, mainly because of sparse reliable mortality data. This study explores SES differences in overall and cause-specific mortality in the Seychelles, a rapidly developing small island state in the African region. METHODS: All deaths have been medically certified over more than two decades. SES and other lifestyle-related risk factors were assessed in a total of 3246 participants from three independent population-based surveys conducted in 1989, 1994 and 2004. Vital status was ascertained using linkage with vital statistics. Occupational position was the indicator of SES used in this study and was assessed with the same questions in the three surveys. RESULTS: During a mean follow-up of 15.0 years (range 0-23 years), 523 participants died (overall mortality rate 10.8 per 1000 person-years). The main causes of death were cardiovascular disease (CVD) (219 deaths) and cancer (142 deaths). Participants in the low SES group had a higher mortality risk for overall (HR = 1.80; 95% CI: 1.24-2.62), CVD (HR = 1.95; 1.04-3.65) and non-cancer/non-CVD (HR = 2.14; 1.10-4.16) mortality compared to participants in the high SES group. Cancer mortality also tended to be patterned by SES (HR = 1.44; 0.76-2.75). Major lifestyle-related risk factors (smoking, heavy drinking, obesity, diabetes, hypertension, hypercholesterolemia) explained a small proportion of the associations between low SES and all-cause, CVD, and non-cancer/non-CVD mortality. CONCLUSIONS: In this population-based study assessing social inequalities in mortality in a country of the African region, low SES (as measured by occupational position) was strongly associated with overall, CVD and non-cancer/non-CVD mortality. Our findings support the view that the burden of non-communicable diseases may disproportionally affect people with low SES in low and middle income countries.

Health behaviours, socioeconomic status, and mortality: further analyses of the British Whitehall II and the French GAZEL prospective cohorts

BACKGROUND: Differences in morbidity and mortality between socioeconomic groups constitute one of the most consistent findings of epidemiologic research. However, research on social inequalities in health has yet to provide a comprehensive understanding of the mechanisms underlying this association. In recent analysis, we showed health behaviours, assessed longitudinally over the follow-up, to explain a major proportion of the association of socioeconomic status (SES) with mortality in the British Whitehall II study. However, whether health behaviours are equally important mediators of the SES-mortality association in different cultural settings remains unknown. In the present paper, we examine this issue in Whitehall II and another prospective European cohort, the French GAZEL study. METHODS AND FINDINGS: We included 9,771 participants from the Whitehall II study and 17,760 from the GAZEL study. Over the follow-up (mean 19.5 y in Whitehall II and 16.5 y in GAZEL), health behaviours (smoking, alcohol consumption, diet, and physical activity), were assessed longitudinally. Occupation (in the main analysis), education, and income (supplementary analysis) were the markers of SES. The socioeconomic gradient in smoking was greater (p<0.001) in Whitehall II (odds ratio [OR] = 3.68, 95% confidence interval [CI] 3.11-4.36) than in GAZEL (OR = 1.33, 95% CI 1.18-1.49); this was also true for unhealthy diet (OR = 7.42, 95% CI 5.19-10.60 in Whitehall II and OR = 1.31, 95% CI 1.15-1.49 in GAZEL, p<0.001). Socioeconomic differences in mortality were similar in the two cohorts, a hazard ratio of 1.62 (95% CI 1.28-2.05) in Whitehall II and 1.94 in GAZEL (95% CI 1.58-2.39) for lowest versus highest occupational position. Health behaviours attenuated the association of SES with mortality by 75% (95% CI 44%-149%) in Whitehall II but only by 19% (95% CI 13%-29%) in GAZEL. Analysis using education and income yielded similar results. CONCLUSIONS: Health behaviours were strong predictors of mortality in both cohorts but their association with SES was remarkably different. Thus, health behaviours are likely to be major contributors of socioeconomic differences in health only in contexts with a marked social characterisation of health behaviours. Please see later in the article for the Editors' Summary.

Association between weight perception and socioeconomic status among adults in the Seychelles.

BACKGROUND: Few studies have examined the association between weight perception and socioeconomic status (SES) in sub-Saharan Africa, and none made this association based on education, occupation and income simultaneously. METHODS: Based on a population-based survey (n = 1255) in the Seychelles, weight and height were measured and self-perception of one's own body weight, education, occupation, and income were assessed by a questionnaire. Individuals were considered to have appropriate weight perception when their self-perceived weight matched their actual body weight. RESULTS: The prevalence of overweight and obesity was 35% and 28%, respectively. Multivariate analysis among overweight/obese persons showed that appropriate weight perception was directly associated with actual weight, education, occupation and income, and that it was more frequent among women than among men. In a model using all three SES indicators together, only education (OR = 2.5; 95% CI: 1.3-4.8) and occupation (OR = 2.3; 95% CI: 1.2-4.5) were independently associated with appropriate perception of being overweight. The OR reached 6.9 [95% CI: 3.4-14.1] when comparing the highest vs. lowest categories of SES based on a score including all SES indicators and 6.1 [95% CI: 3.0-12.1] for a score based on education and occupation. CONCLUSIONS: Appropriately perceiving one's weight as too high was associated with different SES indicators, female sex and being actually overweight. These findings suggest means and targets for clinical and population-based interventions for weight control. Further studies should examine whether these differences in weight perception underlie differences in cognitive skills, healthy weight norms, or body size ideals.

Increasing prevalence of obesity in the Seychelles and association with socioeconomic status

Objective: We assessed the 15-year trends in the distribution of body mass index (BMI) categories in the Seychelles (Indian Ocean, African Region) and the relationship with sex, age and socio-economic status (SES). Methods: We conducted three population-based examination surveys in 1989 (n=1,081; participation rate: 86.4%), in 1994 (n=1,067; 87.0%), and in 2004 (n=1,255; 80.2%). Occupation was categorized as "laborer", "intermediate" or "professional". Results are adjusted to the population of 2002. Results: Between 1989 and 2004, mean BMI increased markedly in all sex and age categories (overall: ∼0.15 kg/m2/calendar year). The prevalence of overweight and obesity combined ("excess weight", BMI ≥25 kg/m2) increased from 29% to 52% in men and from 50% to 67% in women. The prevalence of obesity (BMI ≥30 kg/m2) increased from 4% to 15% in men and from 23% to 34% in women. Mean BMI - respectively the prevalence of excess weight- was lower in laborers than professionals in men but higher in laborers that professionals in women and this pattern was similar in the three surveys. Odds ratios for excess weight in professionals vs. laborers were 2.10 (95% CI: 1.94-2.17) in men and 0.51 (0.48-0.53) in women, adjusting for calendar year and participants' age and smoking habits. Conclusion: The prevalence of overweight/obesity increased markedly during a 15- year period. Similar increase of BMI over time in all age and sex categories suggests common environment obesogenic factors. The association between SES and excess weight was in opposite directions in men and women. The study emphasizes the need for prevention measures in all sex, age and SES groups, and suggests that they should be tailored according to sex and SES categories.

Association of socioeconomic status with inflammatory markers: a two cohort comparison.

OBJECTIVE: To assess the association between socioeconomic status (SES) and inflammatory markers using two different European population samples. METHODS: We used data from the CoLaus (N=6412, Lausanne, Switzerland) and EPIPorto (N=1205, Porto, Portugal) studies. Education and occupational position were used as indicators of socioeconomic status (SES). High-sensitivity C-reactive protein (hs-CRP) was available for both cohorts. Interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α) were available in CoLaus; leukocyte count and fibrinogen in EPIPorto. RESULTS: We showed that low SES was significantly associated with high inflammation in both studies. We also showed that behavioural factors contributed the most to SES differences in inflammation. In both studies the larger difference between the lowest and the highest SES was observed for hs-CRP. In the Swiss sample, a linear association between education and hs-CRP persisted after adjustment for all mediating factors and confounders considered (p for linear trend <0.001). CONCLUSION: Large social differences exist in inflammatory activity, in part independently from demographic and behavioural factors, chronic conditions and medication use. SES differences in inflammation are also similar in countries with different underlying socioeconomic conditions.

Association of socioeconomic status with sleep disturbances in the Swiss population-based CoLaus study.

OBJECTIVE: To examine the association of socioeconomic status (SES) with subjective and objective sleep disturbances and the role of socio-demographic, behavioural and psychological factors in explaining this association. METHODS: Analyses are based on 3391 participants (53% female, aged 40-81 years) of the follow-up of the CoLaus study (2009-2012), a population-based sample of the city of Lausanne, Switzerland. All participants completed a sleep questionnaire and a sub-sample (N = 1569) underwent polysomnography. RESULTS: Compared with men with a high SES, men with a low SES were more likely to suffer from poor sleep quality [prevalence ratio (PR) for occupational position = 1.68, 95% Confidence Interval (CI): 1.30-2.17], and to have long sleep latency (PR = 4.90, 95%CI: 2.14-11.17), insomnia (PR = 1.47, 95% CI: 1.12-1.93) and short sleep duration (PR = 3.03, 95% CI: 1.78-5.18). The same pattern was observed among women (PR = 1.29 for sleep quality, 2.34 for sleep latency, 2.01 for daytime sleepiness, 3.16 for sleep duration, 95%CIs ranging from 1.00 to 7.51). Use of sleep medications was not patterned by SES. SES differences in sleep disturbances were only marginally attenuated by adjustment for other socio-demographic, behavioural and psychological factors. Results from polysomnography confirmed poorer sleep patterns among participants with low SES (p <0.05 for sleep efficiency/stage shifts), but no SES differences were found for sleep duration. CONCLUSIONS: In this population-based sample, low SES was strongly associated with sleep disturbances, independently of socio-demographic, behavioural, and psychological factors. Further research should establish the extent to which social differences in sleep contribute to socioeconomic differences in health outcomes.

Life-course socioeconomic status and DNA methylation of genes regulating inflammation

BACKGROUND: In humans, low socioeconomic status (SES) across the life course is associated with greater diurnal cortisol production, increased inflammatory activity and higher circulating antibodies for several pathogens, all suggesting a dampened immune response. Recent evidence suggests that DNA methylation of pro-inflammatory genes may be implicated in the biological embedding of the social environment. METHODS: The present study examines the association between life-course SES and DNA methylation of candidate genes, selected on the basis of their involvement in SES-related inflammation, in the context of a genome-wide methylation study. Participants were 857 healthy individuals sampled from the EPIC Italy prospective cohort study. RESULTS: Indicators of SES were associated with DNA methylation of genes involved in inflammation. NFATC1, in particular, was consistently found to be less methylated in individuals with low vs high SES, in a dose-dependent manner. IL1A, GPR132 and genes belonging to the MAPK family were also less methylated among individuals with low SES. In addition, associations were found between SES and CXCL2 and PTGS2, but these genes were consistently more methylated among low SES individuals. CONCLUSIONS: Our findings support the hypothesis that the social environment leaves an epigenetic signature in cells. Although the functional significance of SES-related DNA methylation is still unclear, we hypothesize that it may link SES to chronic disease risk.

Lifecourse socioeconomic status and type 2 diabetes : the role of chronic inflammation in the English Longitudinal Study of Ageing.

We examined the association between lifecourse socioeconomic status (SES) and the risk of type 2 diabetes at older ages, ascertaining the extent to which adult lifestyle factors and systemic inflammation explain this relationship. Data were drawn from the English Longitudinal Study of Ageing (ELSA) which, established in 2002, is a representative cohort study of ≥50-year olds individuals living in England. SES indicators were paternal social class, participants' education, participants' wealth, and a lifecourse socioeconomic index. Inflammatory markers (C-reactive protein and fibrinogen) and lifestyle factors were measured repeatedly; diabetes incidence (new cases) was monitored over 7.5 years of follow-up. Of the 6218 individuals free from diabetes at baseline (44% women, mean aged 66 years), 423 developed diabetes during follow-up. Relative to the most advantaged people, those in the lowest lifecourse SES group experienced more than double the risk of diabetes (hazard ratio 2.59; 95% Confidence Interval (CI) = 1.81-3.71). Lifestyle factors explained 52% (95%CI:30-85) and inflammatory markers 22% (95%CI:13-37) of this gradient. Similar results were apparent with the separate SES indicators. In a general population sample, socioeconomic inequalities in the risk of type 2 diabetes extend to older ages and appear to partially originate from socioeconomic variations in modifiable factors which include lifestyle and inflammation.

Ideal Body Size as a Mediator for the Gender-Specific Association Between Socioeconomic Status and Body Mass Index: Evidence From an Upper-Middle-Income Country in the African Region.

While obesity continues to rise globally, the associations between body size, gender, and socioeconomic status (SES) seem to vary in different populations, and little is known on the contribution of perceived ideal body size in the social disparity of obesity in African countries. We examined the gender and socioeconomic patterns of body mass index (BMI) and perceived ideal body size in the Seychelles, a middle-income small island state in the African region. We also assessed the potential role of perceived ideal body size as a mediator for the gender-specific association between SES and BMI. A population-based survey of 1,240 adults aged 25 to 64 years conducted in December 2013. Participants' BMI was calculated based on measured weight and height; ideal body size was assessed using a nine-silhouette instrument. Three SES indicators were considered: income, education, and occupation. BMI and perceived ideal body size were both higher among men of higher versus lower SES (p< .001) but lower among women of higher versus lower SES (p< .001), irrespective of the SES indicator used. Multivariate analysis showed a strong and direct association between perceived ideal body size and BMI in both men and women (p< .001) and was consistent with a potential mediating role of perceived ideal body size in the gender-specific associations between SES and BMI. Our study emphasizes the importance of gender and socioeconomic differences in BMI and ideal body size and suggests that public health interventions that promote perception of healthy weight could help mitigate SES-related disparities in BMI.

Essays on the measurement of school efficiency

Measuring school efficiency is a challenging task. First, a performance measurement technique has to be selected. Within Data Envelopment Analysis (DEA), one such technique, alternative models have been developed in order to deal with environmental variables. The majority of these models lead to diverging results. Second, the choice of input and output variables to be included in the efficiency analysis is often dictated by data availability. The choice of the variables remains an issue even when data is available. As a result, the choice of technique, model and variables is probably, and ultimately, a political judgement. Multi-criteria decision analysis methods can help the decision makers to select the most suitable model. The number of selection criteria should remain parsimonious and not be oriented towards the results of the models in order to avoid opportunistic behaviour. The selection criteria should also be backed by the literature or by an expert group. Once the most suitable model is identified, the principle of permanence of methods should be applied in order to avoid a change of practices over time. Within DEA, the two-stage model developed by Ray (1991) is the most convincing model which allows for an environmental adjustment. In this model, an efficiency analysis is conducted with DEA followed by an econometric analysis to explain the efficiency scores. An environmental variable of particular interest, tested in this thesis, consists of the fact that operations are held, for certain schools, on multiple sites. Results show that the fact of being located on more than one site has a negative influence on efficiency. A likely way to solve this negative influence would consist of improving the use of ICT in school management and teaching. Planning new schools should also consider the advantages of being located on a unique site, which allows reaching a critical size in terms of pupils and teachers. The fact that underprivileged pupils perform worse than privileged pupils has been public knowledge since Coleman et al. (1966). As a result, underprivileged pupils have a negative influence on school efficiency. This is confirmed by this thesis for the first time in Switzerland. Several countries have developed priority education policies in order to compensate for the negative impact of disadvantaged socioeconomic status on school performance. These policies have failed. As a result, other actions need to be taken. In order to define these actions, one has to identify the social-class differences which explain why disadvantaged children underperform. Childrearing and literary practices, health characteristics, housing stability and economic security influence pupil achievement. Rather than allocating more resources to schools, policymakers should therefore focus on related social policies. For instance, they could define pre-school, family, health, housing and benefits policies in order to improve the conditions for disadvantaged children.