OBJECTIVE: The primary aim was to assess associations between total steps per day and incident diabetes, whereas the secondary aim was to assess whether the intensity and/or cadence of steps is associated with incident diabetes. RESEARCH DESIGN AND METHODS: Women without physician-diagnosed diabetes (n = 4,838; mean [SD] age 78.9 [6.7] years) were followed up to 6.9 years; 395 developed diabetes. Hip-worn ActiGraph GT3X+ accelerometers worn for 1 week enabled measures of total, light-intensity, and moderate- to vigorous-intensity (MV-intensity) steps per day. Using Cox proportional hazards analysis we modeled adjusted change in the hazard rate for incident diabetes associated with total, light-intensity, and MV-intensity steps per day. We further estimated the proportion of the steps-diabetes association mediated by BMI. RESULTS: On average, participants took 3,729 (SD 2,114) steps/day, of which 1,875 (791) were light-intensity steps and 1,854 ± 1,762 were MV-intensity. More steps per day were associated with a lower hazard rate for incident diabetes. Confounder-adjusted models for a 2,000 steps/day increment yielded hazard ratio (HR) 0.88 (95% CI 0.78–1.00; P = 0.046). After further adjustment for BMI, HR was 0.90 (95% CI 0.80–1.02; P = 0.11). BMI did not significantly mediate the steps-diabetes association (proportion mediated = 17.7% [95% CI −55.0 to 142.0]; P = 0.09]). The relationship between MV-intensity steps per day (HR 0.86 [95% CI 0.74–1.00]; P = 0.04) and incident diabetes was stronger than for light-intensity steps per day (HR 0.97 [95% CI 0.73–1.29]; P = 0.84). CONCLUSIONS: These findings suggest that for older adults, more steps per day are associated with lower incident diabetes and MV-intensity steps are most strongly associated with a lower hazard of diabetes. This evidence supports that regular stepping is an important risk factor for type 2 diabetes prevention in older adults.

Inflammation is a ubiquitous factor accompanying normal aging and neurodegeneration, and recent studies indicate a major contribution of inducible cyclooxygenase (COX-2) and its downstream prostaglandin signaling pathways in modulating neuroinflammatory responses and neuronal function. We have previously shown that the prostaglandin PGE₂ receptor EP4 suppresses innate immune responses in models of systemic inflammation. Here we investigated the role of the EP4 receptor in models of Parkinson’s disease (PD). Systemic co-administration of the EP4 agonist ONO-AE1–329 with the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) prevented loss of dopaminergic (DA) neurons in the substantia nigra pars compacta (SNpc) without significant changes in glial activation, suggesting a potent neuroprotective effect of EP4 signaling in this acute model of DA neuronal loss. Cell-specific conditional ablation of EP4 in Cd11bCre;EP4^lox/lox mice exacerbated MPTP-associated glial activation and T-cell infiltration in SNpc, consistent with anti-inflammatory functions of microglial EP4 signaling. In vitro, in primary microglia stimulated with oligomeric α-synuclein, EP4 receptor activation suppressed generation of pro-inflammatory and oxidative stress factors. Taken together, these findings suggest a dual neuroprotective and anti-inflammatory mechanism of action by the EP4 receptor in models of PD.

Non-alcoholic fatty liver disease (NAFLD) is common among 30% of American adults. Former and current smokers are at higher risk for NAFLD compared to never smokers. The ratio of urine caffeine metabolites to caffeine intake—namely, urine caffeine metabolite indices—has previously been used as a proxy for CYP1A2 activity, which is one of the main liver metabolizing enzymes. CYP1A2 activity is associated with NAFLD progression. No studies to our knowledge have examined the associations of liver enzymes, smoking intensity, and secondhand smoke (SES) with CYP1A2 activity (using caffeine metabolite indices) across smoking status. We analyzed national representative samples from the 2009–2010 National Health and Nutrition Examination Survey (NHANES). Interestingly, even within a normal range, several liver enzymes were associated with caffeine metabolite indices, and patterns of many of these associations varied by smoking status. For instance, within a normal range, aspartate aminotransferase (AST) in never smokers and bilirubin in current smokers were inversely associated with 1-methyluric acid and 5-acetylamino-6-amino-3-methyluracil (URXAMU). Furthermore, we observed a common pattern: across all smoking statuses, higher AST/alanine aminotransferase (AST/ALT) was associated with 1-methyluric acid and URXAMU. Moreover, in current smokers, increased lifelong smoking intensity was associated with reduced caffeine metabolite indices, but acute cigarette exposure as measured by SES levels was associated with increased caffeine metabolite indices among never smokers. In summary, commonly used liver enzyme tests can reflect the CYP1A2 activity even within a normal range, but the selection of these enzymes depends on the smoking status; the associations between smoking and the CYP1A2 activity not only depend on the intensity but also the duration of tobacco exposure.

This study aimed to investigate the role of sleep and circadian health on disparities in overall disease burden among individuals of Hispanic/Latino heritage with differing nativity backgrounds. This study evaluated associations between self-reported sleep (from HCHS/SOL baseline, 2008-2011) and actigraphy-derived sleep/circadian measures (from Sueño, 2010-2013) with multimorbidity at follow-up (2011-2017). Zero-inflated Poisson regression modeled associations between categorical sleep metrics (e.g. standard cut-off values or tertiles) with a modified Charlson Comorbidity Index (CCI) after accounting for the complex sampling design. This study explored effect modification of sleep-CCI associations to understand potential health disparities by age group, gender, and nativity (non-US-born <10 yrs. 10-20 yrs. +20 yrs. and US-born). Actigraphy-assessed short (short-sleep, IRR:1.48 (95%CI:0.99-2.20)) and long sleep duration (long-sleep, IRR:1.52 (95%CI:0.95-2.43)), and sleep regularity index (T3vs.T1, IRR: 1.43 (95%CI:1.14-1.79)) were individually associated with higher overall multimorbidity 5-6 years later; similar associations were seen utilizing self-reported insomnia symptoms (WHI insomnia score ≥ 9 vs. < 9, IRR:1.23 (95%CI:1.13-1.34)) and excessive daytime sleepiness (ESS score ≥ 11 vs. < 11, IRR:1.10 (0.99-1.21). Tests for the interaction showed differences by nativity (two-sided, p < 0.05). Lower sleep satisfaction, daytime alertness, extreme sleep durations, and fragmented RARs were associated with greater chronic disease burden.STATEMENT OF SIGNIFICANCELower sleep satisfaction, extreme sleep durations, and decreased sleep regularity were associated with greater chronic disease burden. Our study expands on previous work in HCHS/SOL and Sueño by investigating a composite measure of disease burden in association with sleep, whereas prior studies in this cohort focused on individual associations between sleep and these chronic diseases.

Background: The purpose of this study was to develop an equation for estimating gestational age using fetal ultrasound measurements specific to women living in the villages of Santiago Atitlán (SA) and San Lucas Tolimán (SLT), which sit in the Guatemalan highlands. Methods: This study was a prospective observational study of a Guatemalan obstetric population. Cross-sectional design was used to collect baseline maternal characteristics, whereas fetal ultrasound measurements were collected longitudinally. Guatemalan women were continuously enrolled in this study from January 2010 to May 2013 from four clinics based in SA and SLT. Forward selection and mixed-effect modeling techniques were used. Guatemalan data were extrapolated to the Skupski linear mixed effect model, which was developed using ultrasounds obtained in the United States. Results: 894 Guatemalan women enrolled in this study, with 460 of these women had known ultrasound biometrics. In the final model, 285 women contributed 376 ultrasound measurements, where the average number of ultrasound visits was slightly more than one visit. Conclusions: The intrauterine growth curve generated from these two Mayan populations had notable divergence at later gestation from Skupski curve. This difference may be related to a genetic predisposition, selection bias, environmental factor, or other confounding unidentified variable. Application of this formula longitudinally would help to verify these findings and provide further clarification to the etiology of this possible difference.

Background: Poor sleep is a suspected risk factor for lower physical functioning and frequent falling at older ages. We evaluated the relationship of multiple sleep and rest-activity rhythm (RAR) metrics with fall risk and physical functioning. Methods: Older women (N = 4543) wore hip-worn accelerometers, recording their falls daily for 13 months following accelerometry. Uniform manifold approximation projection identified sleep-circadian clusters; K-means clustering further distinguished healthy and unhealthy sleep patterns. After cross-validation, we examined associations between sleep clusters and fall risk using adjusted, negative binomial models. Linear regression models estimated associations of sleep clusters with short physical performance battery (SPPB) score and its sub-scores. We evaluated whether SPPB status modified associations of sleep and RAR with fall risk. Results: Five sleep clusters were identified including C1 (“sleep disturbed,” n = 1051), C2 (“healthy,” n = 1043), C3 (“mild RAR, active,” n = 1446), C4 (“earlier sleepers, n = 105), and C5 (“shorter, mildly disrupted, later sleeper,” n = 898). Unhealthy sleep clusters C1 and C4 were associated with a higher fall risk compared to healthy cluster C2 after adjustment (C4, IRR: 1.76 (95% CI: 1.15-2.69)). These same clusters were also associated with lower balance scores (score: 0-4) after adjustment (C1, beta: −0.11 (95% CI: −0.21 to −0.01); C4, beta: −0.30 (95% CI: −0.55 to −0.05)). Conclusions: Older women with unhealthier sleep-RAR patterns are more at risk for falling, which may be partially explained by the role of sleep on balance and physical functioning.