Maturation of the Human Cerebral Cortex During Adolescence: Myelin or Dendritic Arbor?

Previous in vivo studies revealed robust age-related variations in structural properties of the human cerebral cortex during adolescence. Neurobiology underlying these maturational phenomena is largely unknown. Here we employ a virtual-histology approach to gain insights into processes associated with inter-regional variations in cortical microstructure and its maturation, as indexed by magnetization transfer ratio (MTR). Inter-regional variations in MTR correlate with inter-regional variations in expression of genes specific to pyramidal cells (CA1) and ependymal cells; enrichment analyses indicate involvement of these genes in dendritic growth. On the other hand, inter-regional variations in the change of MTR during adolescence correlate with inter-regional profiles of oligodendrocyte-specific gene expression. Complemented by a quantitative hypothetical model of the contribution of surfaces associated with dendritic arbor (1631 m2) and myelin (48 m2), these findings suggest that MTR signals are driven mainly by macromolecules associated with dendritic arbor while maturational changes in the MTR signal are associated with myelination.

0413 The Influence of Community Environment Exposure and Individual Health Behavior on Insufficient Sleep

Introduction

Short sleep duration is associated with the risk of various chronic diseases, and it has been hypothesized to influence health behaviors and environmental exposure such as green space and noise. However, little studies have explored this relationship, especially with the consideration of the integrated environment information. The purpose of this study is to examine the influence of environmental exposure and individuals’ health behavior on sleep duration.

Methods

We examined aggregate national-level datasets regarding health information, noise, and green space. Sleep, health behavior, and socio-demographic variables were derived from 500 cities data, and the unit of analysis was the prevalence of each variable in the census tract. The insufficient sleep was calculated by the percentage of the population who had less than 7 hours of sleep in the census block. Spatial analysis was performed for green space and noise measurement; both values were calculated within the community activity space, which is a combined area with the census urban area and census place to examine the potential activity space. Multiple linear regression analysis was performed to model the relationship.

Results

The final sample was 29,610 census tracts from 497 cities, and the average median age of each census tract was 36.02±7.085. 36.64% of insufficient sleep was reported from the entire sample. The model (R2=0.804) indicate that green space (β=-.053, p<.001) and natural noise (β=-.029, p<.001) has negatively associated with insufficient sleep; while, smoker (β=.374, p<.001), binge drinker (β=.105, p<.001), no leisure physical activity time (β=.111, p<.001), and artificial noise (β=.034, p<.001) has positive association with insufficient sleep.

Conclusion

The results indicate that a better environment source in the community mitigates the insufficient sleep population as well as individual health behavior. Further studies are needed, however, to fully disentangle the association between sleep duration and sleep quality associated with other environmental exposure.

Support

N/A

0379 Green Space Exposure and Sleep Duration Among Supplemental Nutrition Assistance Program Participants

Introduction

Emerging empirical evidence suggests green space exposure is protective against insufficient sleep. Limited studies exist, however, exploring the relationship between greenspace exposure and sleep among low income populations in the United States.

Methods

Using a sample of Supplemental Nutrition Assistance Program (SNAP) participants (n=104) recruited from Champaign County, Illinois, we examined the relationship between self-reported sleep duration and exposure to green space. Sleep duration was determined using the question, “On average, how many hours did you sleep each night during the past 4 weeks?” Green space exposure was determined using satellite imagery from the National Aeronautic Space Administration (NASA) normalized difference vegetation index (NDVI). An NDVI score was assigned to each participant based on residential geo-referenced data. Multiple linear regression was performed in SPSS to explore the relationship between self-reported sleep duration and green space.

Results

Higher number of hours of sleep within a 24-hour period was positively associated with higher scores for greenspace exposure (β=0.091, P=0.02), controlling for age, gender, smoking status, education, alcohol consumption, and sleep quality. Sleep duration was negatively associated with age (β=-0.03, P=0.007), but positively associated with sleep quality (β=0.856, P=0.008).

Conclusion

In a sample of SNAP participants, exposure to green space was associated with more hours of sleep per night. Additional studies with larger, and more geographically diverse samples of low income adults are needed to determine whether this relationship is robust.

Support

USDA UNC/DUKE BECR Center

P5298Influence of the changes in body fat on all-cause and cardiovascular mortality in a general population: a report from Ansan-Ansung cohort in the Korean genome environment study

Background

Paradoxical beneficial effects of obesity on all-cause and cardiovascular mortality have been reported in multiple cohort studies based on patients with cardiovascular disease as well as general populations. However, the association between the presence of obesity at baseline and the better survival rates could not be directly interpreted into the beneficial effect of gain in obesity or fatness on the mortality, which makes it difficult to provide any recommendation for the management of obesity. Therefore, we investigated the influence of the changes in body fat on all-cause and cardiovascular mortality in a general population.

Methods

A population-based cohort study has been conducted for 12 years (from 2001 to 2012). A total of 5,259 subjects in whom body compositions using a bio-impedance method were measured at least 2 times during the observational period were included. The causes of death was identified from the nation-wide database in KOSTAT. I20-I82 and R99 in the International Classification of Disease-10 codes were defined as a cardiovascular death. The subjects were evenly divided into 3 groups by the percentages of the changes in body fat (Δ%BF; decreased [Δ%BF <0.0%] vs. increased [Δ%BF 0.0–13.7%] vs. highly increased [Δ%BF ≥13.7%]). Inverse probability of treatment weighting was applied to balance the covariate differences among the groups.

Results

The age was 51.2±8.5 years and 51.6% was male. Median observation duration was 163 (the interquartile range: 157–168) months. The all-cause death and cardiovascular death occurred most frequently in the decreased Δ%BF group and least frequent in the highly increased Δ%BF group in both unweighted and weighted cohort. Multivariate Cox proportional hazard models showed that the risk of all-cause death was lower in the increased and highly increased Δ%BF groups (hazard ratio [HR] 0.61 [0.47–0.80] and 0.24 [0.17–0.34], respectively) and the risk of cardiovascular death was lower in the highly increased Δ%BF group (HR 0.20 [0.08–0.48]), compared to those in the decreased Δ%BF group after adjustment for all covariates including physical activities and the changes in muscle mass. The risk of all-cause death and cardiovascular death linearly decreased with increasing Δ%BF (HR 0.72 [0.67–0.77] and 0.70 [0.60–0.82], respectively).

Conclusion

The increase in body fat is associated with a lower risk of all-cause death and cardiovascular death in a middle-age general population, independently with physical activities and the changes in muscle mass.

P5665The independent effect of insulin resistance on incidence of atrial fibrillation in non-diabetics

Purpose

Patients with diabetes mellitus have an elevated risk of atrial fibrillation (AF). However, whether insulin resistance may elevate risk of AF incidence in non-diabetic is inconsistent. The aim of our study was to verify the association between insulin resistance and incidence of AF in non-diabetics.

Methods

We evaluated population-based cohorts embedded in the Korean Genome Epidemiology Study. Insulin resistance was expressed as Homeostasis Model Assessment for Insulin resistance (HOMA-IR). Baseline data including HOMA-IR and electrocardiography (ECG) were obtained at 2001. Subsequent biennial ECG was performed for identification of AF until 2016.

Results

Among the 8220 participants (46.8% male; median age 49 years), 25 participants had AF (0.3%) at baseline and 101 participants developed AF (1.2%) during follow up of 12 years. In multivariate Cox regression analysis, high HOMA-IR (≥1.4) was significantly associated with incident AF compared with low HOMA-IR (<1.40) (adjusted hazard ratio [HR] 1.9, 95% confidence interval [CI] 1.3–3.0). In subgroup analysis, these association was consistent regardless of obesity (BMI<25; adjust HR 1.8, 95% CI 1.1–3.0, BMI≥25; adjust HR 2.3, 95% CI 1.3–4.0)

Subgroup analysis

Conclusion

Based on prospective cohort study, insulin resistance (HOMA-IR) was associated with AF independently of obesity in non-diabetics.