Influence of socioeconomic status on objective sleep measurement: A systematic review and meta-analysis of actigraphy studies

Sleep Health ◽  
2021 ◽  
Author(s):  
FA Etindele Sosso ◽  
Sari D. Holmes ◽  
Ali A. Weinstein
BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e042212
Author(s):  
Hamish Foster ◽  
Peter Polz ◽  
Frances Mair ◽  
Jason Gill ◽  
Catherine A O'Donnell

IntroductionCombinations of unhealthy lifestyle factors are strongly associated with mortality, cardiovascular disease (CVD) and cancer. It is unclear how socioeconomic status (SES) affects those associations. Lower SES groups may be disproportionately vulnerable to the effects of unhealthy lifestyle factors compared with higher SES groups via interactions with other factors associated with low SES (eg, stress) or via accelerated biological ageing. This systematic review aims to synthesise studies that examine how SES moderates the association between lifestyle factor combinations and adverse health outcomes. Greater understanding of how lifestyle risk varies across socioeconomic spectra could reduce adverse health by (1) identifying novel high-risk groups or targets for future interventions and (2) informing research, policy and interventions that aim to support healthy lifestyles in socioeconomically deprived communities.Methods and analysisThree databases will be searched (PubMed, EMBASE, CINAHL) from inception to March 2020. Reference lists, citations and grey literature will also be searched. Inclusion criteria are: (1) prospective cohort studies; (2) investigations of two key exposures: (a) lifestyle factor combinations of at least three lifestyle factors (eg, smoking, physical activity and diet) and (b) SES (eg, income, education or poverty index); (3) an assessment of the impact of SES on the association between combinations of unhealthy lifestyle factors and health outcomes; (4) at least one outcome from—mortality (all cause, CVD and cancer), CVD or cancer incidence. Two independent reviewers will screen titles, abstracts and full texts of included studies. Data extraction will focus on cohort characteristics, exposures, direction and magnitude of SES effects, methods and quality (via Newcastle-Ottawa Scale). If appropriate, a meta-analysis, pooling the effects of SES, will be performed. Alternatively, a synthesis without meta-analysis will be conducted.Ethics and disseminationEthical approval is not required. Results will be disseminated via peer-reviewed publication, professional networks, social media and conference presentations.PROSPERO registration numberCRD42020172588.


Author(s):  
Jessica K. Knorst ◽  
Camila S. Sfreddo ◽  
Gabriela F. Meira ◽  
Fabrício B. Zanatta ◽  
Mario V. Vettore ◽  
...  

BMJ Open ◽  
2017 ◽  
Vol 7 (9) ◽  
pp. e017567
Author(s):  
Shimels Hussien Mohammed ◽  
Mulugeta Molla Birhanu ◽  
Tesfamichael Awoke Sissay ◽  
Tesfa Dejenie Habtewold ◽  
Balewgizie Sileshi Tegegn ◽  
...  

IntroductionIndividuals living in poor neighbourhoods are at a higher risk of overweight/obesity. There is no systematic review and meta-analysis study on the association of neighbourhood socioeconomic status (NSES) with overweight/obesity. We aimed to systematically review and meta-analyse the existing evidence on the association of NSES with overweight/obesity.Methods and analysisCross-sectional, case–control and cohort studies published in English from inception to 15 May 2017 will be systematically searched using the following databases: PubMed, EMBASE, Web of Sciences and Google Scholar. Selection, screening, reviewing and data extraction will be done by two reviewers, independently and in duplicate. The Newcastle–Ottawa Scale (NOS) will be used to assess the quality of evidence. Publication bias will be checked by visual inspection of funnel plots and Egger’s regression test. Heterogeneity will be checked by Higgins’s method (I2statistics). Meta-analysis will be done to estimate the pooled OR. Narrative synthesis will be performed if meta-analysis is not feasible due to high heterogeneity of studies.Ethics and disseminationEthical clearance is not required as we will be using data from published articles. Findings will be communicated through a publication in a peer-reviewed journal and presentations at professional conferences.PROSPERO registration numberCRD42017063889.


2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Caberry W. Yu ◽  
S. Mohammad Alavinia ◽  
David A. Alter

2017 ◽  
Vol 87 (2) ◽  
pp. 243-282 ◽  
Author(s):  
Jens Dietrichson ◽  
Martin Bøg ◽  
Trine Filges ◽  
Anne-Marie Klint Jørgensen

Socioeconomic status is a major predictor of educational achievement. This systematic review and meta-analysis seeks to identify effective academic interventions for elementary and middle school students with low socioeconomic status. Included studies have used a treatment-control group design, were performed in OECD and EU countries, and measured achievement by standardized tests in mathematics or reading. The analysis included 101 studies performed during 2000 to 2014, 76% of which were randomized controlled trials. The effect sizes (ES) of many interventions indicate that it is possible to substantially improve educational achievement for the target group. Intervention components such as tutoring (ES = 0.36), feedback and progress monitoring (ES = 0.32), and cooperative learning (ES = 0.22) have average ES that are educationally important, statistically significant, and robust. There is also substantial variation in effect sizes, within and between components, which cannot be fully explained by observable study characteristics.


BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e028238 ◽  
Author(s):  
Shimels Hussien Mohammed ◽  
Tesfa Dejenie Habtewold ◽  
Mulugeta Molla Birhanu ◽  
Tesfamichael Awoke Sissay ◽  
Balewgizie Sileshi Tegegne ◽  
...  

ObjectiveLow neighbourhood socioeconomic status (NSES) has been linked to a higher risk of overweight/obesity, irrespective of the individual’s own socioeconomic status. No meta-analysis study has been done on the association. Thus, this study was done to synthesise the existing evidence on the association of NSES with overweight, obesity and body mass index (BMI).DesignSystematic review and meta-analysis.Data sourcesPubMed, Embase, Scopus, Cochrane Library, Web of Sciences and Google Scholar databases were searched for articles published until 25 September 2019.Eligibility criteriaEpidemiological studies, both longitudinal and cross-sectional ones, which examined the link of NSES to overweight, obesity or BMI, were included.Data extraction and synthesisData extraction was done by two reviewers, working independently. The methodological quality of included studies was assessed using the Newcastle-Ottawa Scale for the observational studies. The summary estimates of the relationships of NSES with overweight, obesity and BMI statuses were calculated with random-effects meta-analysis models. Heterogeneity was assessed by Cochran’s Q and I2 statistics. Subgroup analyses were done by age categories, continents, study designs and NSES measures. Publication bias was assessed by visual inspection of funnel plots and Egger’s regression test.ResultA total of 21 observational studies, covering 1 244 438 individuals, were included in this meta-analysis. Low NSES, compared with high NSES, was found to be associated with a 31% higher odds of overweight (pooled OR 1.31, 95% CI 1.16 to 1.47, p<0.001), a 45% higher odds of obesity (pooled OR 1.45, 95% CI 1.21 to 1.74, p<0.001) and a 1.09 kg/m2 increase in mean BMI (pooled beta=1.09, 95% CI 0.67 to 1.50, p<0.001).ConclusionNSES disparity might be contributing to the burden of overweight/obesity. Further studies are warranted, including whether addressing NSES disparity could reduce the risk of overweight/obesity.PROSPERO registration numberCRD42017063889


2020 ◽  
Vol 19 ◽  
pp. 101124 ◽  
Author(s):  
Siping Wang ◽  
Huiying Zhai ◽  
Lin Wei ◽  
Binyan Shen ◽  
Juan Wang

2015 ◽  
Vol 38 ◽  
pp. 65-78 ◽  
Author(s):  
Antonio Rojas-García ◽  
Isabel Ruiz-Perez ◽  
Miguel Rodríguez-Barranco ◽  
Daniela C. Gonçalves Bradley ◽  
Guadalupe Pastor-Moreno ◽  
...  

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