Dataset Information

Associations between actigraphy-assessed sleep, inflammatory markers, and insulin resistance in the Midlife Development in the United States (MIDUS) study.

ABSTRACT: BACKGROUND:Disturbed sleep has been associated with increased insulin resistance and elevated inflammation. Although there is growing body of evidence that activation of inflammatory pathways plays a crucial role in the development of insulin resistance, the mediational model whereby sleep disturbances influence inflammation that drives insulin resistance has not been fully assessed in general population studies with objectively measured sleep. This study aimed to examine associations between objectively measured sleep, inflammatory markers, and insulin resistance simultaneously and in a mediational analysis, thereby offering insights into the possible causal model. METHODS:Cross-sectional data collected from 2004 to 2009 during the Midlife Development in the United States II biomarker project were used. The study population included 374 community-based participants (138 men and 236 women) who completed seven nights of wrist actigraphy. Multiple regressions controlling for age and statistically significant variables in univariate regressions were performed to evaluate the associations between actigraphy-assessed sleep measures, inflammatory cytokines, and insulin resistance. RESULTS:The regression models showed that in women, higher sleep onset latency (SOL) was associated with higher insulin resistance after controlling for age, smoking, obesity, diabetes, depression, and inflammatory cytokines. Higher SOL was also associated with higher interleukin (IL)-6 and C-reactive protein (CRP) levels in women, but no association was found in men. Using mediation models in women, the association between SOL and insulin resistance was partially explained by the indirect effect of inflammatory cytokines. CONCLUSION:A combination of inflammation and other unidentified pathways may contribute to the relationship between disturbed sleep and glucose homeostasis.

SUBMITTER: Kim TH

PROVIDER: S-EPMC5206915 | biostudies-literature | 2016 Nov - Dec

REPOSITORIES: biostudies-literature

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Associations between actigraphy-assessed sleep, inflammatory markers, and insulin resistance in the Midlife Development in the United States (MIDUS) study.

Kim Tae Ho TH Carroll Judith E JE An Suk Kyoon SK Seeman Teresa E TE Namkoong Kee K Lee Eun E

Sleep medicine 20161027

<h4>Background</h4>Disturbed sleep has been associated with increased insulin resistance and elevated inflammation. Although there is growing body of evidence that activation of inflammatory pathways plays a crucial role in the development of insulin resistance, the mediational model whereby sleep disturbances influence inflammation that drives insulin resistance has not been fully assessed in general population studies with objectively measured sleep. This study aimed to examine associations be ...[more]

PMID: 27938923

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Project description:BackgroundMeasures of financial hardship have been suggested to supplement traditional indicators of socioeconomic status (SES) to elucidate household economic well-being. This study formally tested the construct validity of financial hardship and examined its association with markers of inflammation.MethodsThis study utilized data from the Midlife Development in the United States Refresher Study (MIDUS-R; Age = 23-76, 53.7% female, 71% white). Participants were divided into exploratory factor analysis (EFA; completed SAQs only; N = 2,243) and confirmatory factor analysis sample (CFA; completed SAQs and biomarker assessment; N = 863). Analysis was divided into three steps. First, exploratory factor analysis (EFA) is used to examine if the three-domain factor (material, psychological, and behavioral) is the best fitting model for financial hardship measures. Second, we conducted CFA to test the hypothesized three-factor measurement model of financial hardship. Third, we tested the association between domains and the general latent factor of financial hardship and inflammation (interleukin 6/IL6, c-reactive protein/CRP, and fibrinogen).ResultsResults from EFA supported the three-domain model of financial hardship. The hypothesized three-domain measurement model fits well in a different sample within MIDUS-R. In the models adjusted for age and sex, higher material hardship was associated with elevated IL6, CRP, and fibrinogen, while higher behavioral hardship was associated with higher CRP. The association between the material domain and IL6 remained significant after adding body mass index, education, and race as additional covariates. The second-order financial hardship measurement model was associated with IL6, CRP, and fibrinogen, adjusted for age, sex, BMI, education, and race.ConclusionExplicating the socioeconomic environment to include indicators of financial hardship can help researchers better understand the pathway between SES and the inflammation process, which may help elucidate pathways between SES and age-related chronic diseases associated with inflammation.

Project description:BACKGROUND:There is a lack of empirical effort that systematically investigates the clustering of comorbidity among known risk factors (obesity, hypertension, diabetes, hypercholesterolemia, and elevated inflammation) of chronic kidney disease (CKD) and how different types of comorbidity may link differently to kidney function among healthy adult samples. This study modeled the clustering of comorbidity among risk factors, examined the association between the clustering of risk factors and kidney function, and tested whether the clustering of risk factors was associated with childhood SES. METHODS:The data were from 2118 participants (ages 25-84) in the Midlife in the United States (MIDUS) Study. Risk factors included obesity, elevated blood pressure (BP), high total cholesterol levels, poor glucose control, and increased inflammatory activity. Glomerular filtration rate (eGFR) was estimated from serum creatinine, calculated with the CKD-EPI formula. The clustering of comorbidity among risk factors and its association with kidney function and childhood SES were examined using latent class analysis (LCA). RESULTS:A five-class model was optimal: (1) Low Risk (class size?=?36.40%; low probability of all risk factors), (2) Obese (16.42%; high probability of large BMI and abdominally obese), (3) Obese and Elevated BP (13.37%; high probability of being obese and having elevated BP), (4) Non-Obese but Elevated BP (14.95%; high probability of having elevated BP, hypercholesterolemia, and elevated inflammation), and (5) High Risk (18.86%; high probability for all risk factors). Obesity was associated with kidney hyperfiltration, while comorbidity between obesity and hypertension was linked to compromised kidney filtration. As expected, the High Risk class showed the highest probability of having eGFR <?60?ml/min/1.73?m2 (P?=?.12; 95%CI?=?.09-.17). Finally, higher childhood SES was associated with reduced probability of being in the High Risk rather than Low Risk class (??=?-?0.20, SE?=?0.07, OR [95%CI]?=?0.82 [0.71-0.95]). CONCLUSION:These results highlight the importance of considering the impact of childhood SES on risk factors known to be associated with CKD.

Dataset Information

Associations between actigraphy-assessed sleep, inflammatory markers, and insulin resistance in the Midlife Development in the United States (MIDUS) study.

Publications

Associations between actigraphy-assessed sleep, inflammatory markers, and insulin resistance in the Midlife Development in the United States (MIDUS) study.

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