Dataset Information

The contribution of sleep to social inequalities in cardiovascular disorders: a multi-cohort study.

ABSTRACT:

Aims

Sleep disturbances exhibit a strong social patterning, and inadequate sleep has been associated with adverse health outcomes, including cardiovascular disorders (CVD). However, the contribution of sleep to socioeconomic inequalities in CVD is unclear. This study pools data from eight European cohorts to investigate the role of sleep duration in the association between life-course socioeconomic status (SES) and CVD.

Methods and results

We used cross-sectional data from eight European cohorts, totalling 111 205 participants. Life-course SES was assessed using father's and adult occupational position. Self-reported sleep duration was categorized into recommended (6-8.5 h/night), long (>8.5 h/night), and short (<6 h/night). We examined two cardiovascular outcomes: coronary heart disease (CHD) and stroke. Main analyses were conducted using pooled data and examined the association between life-course SES and CVD, and the contribution of sleep duration to this gradient using counterfactual mediation. Low father's occupational position was associated with an increased risk of CHD (men: OR = 1.19, 95% CI [1.04; 1.37]; women: OR = 1.25, 95% CI [1.02; 1.54]), with marginal decrease of the gradient after accounting for adult occupational position (men: OR = 1.17, 95% CI [1.02; 1.35]; women: OR = 1.22, 95% CI [0.99; 1.52]), and no mediating effect by short sleep duration. Low adult occupational position was associated with an increased risk of CHD in both men and women (men: OR = 1.48, 95% CI [1.14; 1.92]; women: OR = 1.53, 95% CI [1.04; 2.21]). Short sleep duration meaningfully contributed to the association between adult occupational position and CHD in men, with 13.4% mediation. Stroke did not exhibit a social patterning with any of the variables examined.

Conclusion

This study suggests that inadequate sleep accounts to a meaningful proportion of the association between adult occupational position and CHD, at least in men. With sleep increasingly being considered an important cardiovascular risk factor in its own terms, our study additionally points to its potential role in social inequalities in cardiovascular disease.

SUBMITTER: Petrovic D

PROVIDER: S-EPMC7425783 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveTo assess the contribution of modifiable risk factors to social inequalities in the incidence of type 2 diabetes when these factors are measured at study baseline or repeatedly over follow-up and when long term exposure is accounted for.DesignProspective cohort study with risk factors (health behaviours (smoking, alcohol consumption, diet, and physical activity), body mass index, and biological risk markers (systolic blood pressure, triglycerides and high density lipoprotein cholesterol)) measured four times and diabetes status assessed seven times between 1991-93 and 2007-09.SettingCivil service departments in London (Whitehall II study).Participants7237 adults without diabetes (mean age 49.4 years; 2196 women).Main outcome measuresIncidence of type 2 diabetes and contribution of risk factors to its association with socioeconomic status.ResultsOver a mean follow-up of 14.2 years, 818 incident cases of diabetes were identified. Participants in the lowest occupational category had a 1.86-fold (hazard ratio 1.86, 95% confidence interval 1.48 to 2.32) greater risk of developing diabetes relative to those in the highest occupational category. Health behaviours and body mass index explained 33% (-1% to 78%) of this socioeconomic differential when risk factors were assessed at study baseline (attenuation of hazard ratio from 1.86 to 1.51), 36% (22% to 66%) when they were assessed repeatedly over the follow-up (attenuated hazard ratio 1.48), and 45% (28% to 75%) when long term exposure over the follow-up was accounted for (attenuated hazard ratio 1.41). With additional adjustment for biological risk markers, a total of 53% (29% to 88%) of the socioeconomic differential was explained (attenuated hazard ratio 1.35, 1.05 to 1.72).ConclusionsModifiable risk factors such as health behaviours and obesity, when measured repeatedly over time, explain almost half of the social inequalities in incidence of type 2 diabetes. This is more than was seen in previous studies based on single measurement of risk factors.

Project description:ObjectivesTo investigate if socioeconomic status (SES) is predictive of cardiovascular risk factors among Swedish adolescents. Identify the most important SES variable for the development of each cardiovascular risk factor. Investigate at what age SES inequality in overweight and obesity occurs.DesignLongitudinal follow-up of a prospective birth cohort.SettingAll Babies in Southeast Sweden (ABIS) study includes data from children born between October 1997 and October 1999 in five counties of south east Sweden.ParticipantsA regional ABIS-study subsample from three major cities of the region n=298 adolescents aged 16-18 years, and prospective data from the whole ABIS cohort for overweight and obesity status at the ages 2, 5, 8 and 12 years (n=2998-7925).Outcome measuresBlood pressure above the hypertension limit, overweight/obesity according to the International Obesity Task Force definition, low high-density lipoproteins (HDL) or borderline-high low-density lipoproteins according to National Cholesterol Education Program expert panel on cholesterol levels in children.ResultsFor three out of four cardiovascular risk outcomes (elevated blood pressure, low HDL and overweight/obesity), there were increased risk in one or more of the low SES groups (p<0.05). The best predictor was parental occupational class (Swedish socioeconomic classification index) for elevated blood pressure (area under the receiver operating characteristic (ROC) curve 0.623), maternal educational level for overweight (area under the ROC curve 0.641) and blue-collar city of residence for low HDL (area under the ROC curve 0.641). SES-related differences in overweight/obesity were found at age 2, 5 and 12 and for obesity at age 2, 5, 8 and 12 years (all p<0.05).ConclusionsEven in a welfare state like Sweden, SES inequalities in cardiovascular risks are evident already in childhood and adolescence. Intervention programmes to reduce cardiovascular risk based on social inequality should start early in life.

Project description:ObjectiveSleep plays an important role in the health and well-being of middle aged and elderly people, and social capital may be one of the important factors for sleep disorders. This study aimed to understand the relationship between social capital and sleep disorders in a unique region of China -Tibet that generally has the disadvantaged economic status compared to other parts of China.MethodsThe study was based on Tibetan data from The China Multi-Ethnic Cohort (CMEC) and was conducted from May 2018 to September 2019. A total of 3194 Tibetans aged > 50 were selected from the community population by multi-stage stratified cluster sampling. Social capital was measured using two validated health-related social capital scales, family/community and society.. Sleep disorders were measured as the presence of disorders of initiating and maintaining sleep, early morning awakening, or daytime dysfunction. Logistic regression models were applied to examine the association between social capital and sleep disorders.Results39.9% (1271/3194) of the participants had sleep disorders. In addition, after controlling for all potential variables, family social capital was significantly negatively associated with sleep disorders (OR = 0.95, P < 0.05), while community and society social capital was not associated with sleep disorders. Then, when we did all the sex-stratified analyses, the significant association between social capital and sleep disorders was found only in women (OR = 0.94, P < 0.05), while no association was found in males; neither males nor females showed any association with community and society social capital.ConclusionOur study would help to better understand the extent of health inequality in China, and guide future interventions, strategies and policies to promote sleep quality in low-income areas, taking into account both the role of Tibetan specific cultural traditions, lifestyles and religious beliefs in social capital and the gender differences in social capital.