Self-Reported Sleep Duration and Pattern in Old Order Amish and Non-Amish Adults

High Body Roundness Index Is Associated With Unhealthy Sleep Patterns: Insights From NHANES (2007-2014)

BACKGROUND

Substantial evidence suggests an association between obesity and sleep. However, research investigating sleep patterns in relation to novel anthropometric indices is limited. Therefore, we conducted a cross-sectional analysis of data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2014 to examine the relationship between the body roundness index (BRI) and unhealthy sleep patterns.

OBJECTIVE

This study aimed to investigate the association between the BRI and unhealthy sleep patterns among US adults.

METHODS

Data were sourced from NHANES (2007-2014), including respondents aged 20 years and older. Participants were categorized into two groups based on the healthiness of their sleep patterns. The data were weighted, and multiple potential covariates were included in the analysis to provide national estimates and account for the comprehensive sampling design. A multivariable weighted logistic regression model was used, employing restricted cubic spline (RCS) curves to examine potential associations, and subgroup analyses were conducted to determine the stability of the results. Receiver operating characteristic (ROC) analysis was used to compare the diagnostic performance of BRI and body mass index (BMI) in identifying unhealthy sleep patterns.

RESULTS

In the fully adjusted multivariable logistic regression model, the prevalence odds ratio (POR) for the association between BRI and unhealthy sleep patterns was 1.09, with a 95% confidence interval (CI) of 1.07-1.10. The RCS analysis found that the nonlinear association between BRI and unhealthy sleep patterns was not significant. Subgroup and sensitivity analyses indicated a consistently positive association between high BRI and unhealthy sleep patterns across most subgroups. ROC diagnostic tests showed that BRI's effectiveness in diagnosing unhealthy sleep patterns was comparable to that of BMI, and it was not inferior to BMI in assessing certain components of sleep patterns.

CONCLUSION

High BRI is positively associated with unhealthy sleep patterns significantly, indicating that BRI could be a promising metric for evaluating sleep health.

Frontal white matter association with sleep quality and the role of stress

An important measure of brain health is the integrity of white matter connectivity structures that link brain regions. Studies have found an association between poorer sleep quality and decreased white matter integrity. Stress is among the strongest predictors of sleep quality. This study aimed to evaluate the association between sleep quality and white matter and to test if the relationship persisted after accounting for stress. White matter microstructures were measured by diffusion tensor imaging in a population of Old Order Amish/Mennonite (N = 240). Sleep quality was determined by the Pittsburgh Sleep Quality Index. Current stress levels were measured by the perceived stress scale. Exposure to lifetime stress was measured by the lifetime stressor inventory. Microstructures of four white matter tracts: left and right anterior limbs of internal capsule, left anterior corona radiata, and genu of corpus callosum were significantly correlated with sleep quality (all p ≤ 0.001). The current stress level was a significant predictor of sleep quality (p ≤ 0.001) while lifetime stress was not. PSQI remained significantly associated with white matter integrity in these frontal tracts (all p < 0.01) after accounting for current stress and lifetime stress, while current and lifetime stress were not significant predictors of white matter in any of the four models. Sleep quality did not have any substantial mediation role between stress and white matter integrity. Sleep quality was significantly associated with several frontal white matter tracts that connect brain structures important for sleep regulation regardless of current or past stress levels.

Physical health conditions of the Amish and intervening social mechanisms: an exhaustive narrative review

As an ethnic religion, the Amish are of interest to population health researchers due to a distinctive health profile arising from ethnic attributes, including a closed genetic pool and shared culture that shapes lifestyle practices. Amish-focused health research both furthers our knowledge of health conditions by comparing Amish with non-Amish and assists health practitioners in serving this rapidly growing population. Amish health research, now representing approximately a quarter of all Amish-focused publications, is in need of review, to the end of strengthening this knowledge body's coherence, clarifying research directions, and identifying knowledge gaps, lapses, and stagnations. Herein, we synthesize and discuss Amish physical health conditions research, both the population's distinctive health profile and mechanisms shaping this profile. Specifically, we summarize research addressing BMI, physical activity, and body image; diet and supplements; cancer; cardiovascular conditions; communicable diseases; immunity; sleep; genetic disorders; tobacco and alcohol use; periodontal conditions; traumatic injuries; natural treatments for burns; fertility; and sexually transmitted diseases. In reflection, we raise questions about the nature of intervening mechanisms shaping the Amish health profile, the strange omission of several common independent variables commonly used when studying other ethnic groups' health, several recurring methodological complications, and public health policy considerations.

Research Trends in Amish Population Health, a Growing Literature about a Growing Rural Population

The Amish are an endogamous rural population experiencing rapid growth; consequently, they have attracted the attention of population health researchers and service providers. With approximately one quarter of all Amish studies publications now devoted to population health (n=246), the time is ripe to review research trends. Using bibliometric measures, we map the genealogy, influence, and configuration of Amish health publications. Amish population health research has (1) a health culture-focused core with clusters representing social science and health practice, (2) peripheral clusters addressing health conditions-mental, physical, and injury/safety-and (3) several clusters straddling both. We identify fruitful interdisciplinary studies and recommend researchers investigating health culture and conditions seek ways to integrate their research agendas. This article represents a pivot-point for Amish population health research, for it provides a first-ever bibliometric mapping, allowing researchers to more easily locate their work within the literature and identify opportunities for interdisciplinary collaborations.

Genetic versus stress and mood determinants of sleep in the Amish

Sleep is essential to the human brain and is regulated by genetics with many features conserved across species. Sleep is also influenced by health and environmental factors; identifying replicable genetic variants contributing to sleep may require accounting for these factors. We examined how stress and mood disorder contribute to sleep and impact its heritability. Our sample included 326 Amish/Mennonite individuals with a lifestyle with limited technological interferences with sleep. Sleep measures included Pittsburgh Sleep Quality Index (PSQI), bedtime, wake time, and time to sleep onset. Current stress level, cumulative life stressors, and mood disorder were also evaluated. We estimated the heritability of sleep features and examined the impact of current stress, lifetime stress, mood diagnosis on sleep quality. The results showed current stress, lifetime stress, and mood disorder were independently associated with PSQI score (p < .05). Heritability of PSQI was low (0-0.23) before and after accounting for stress and mood. Bedtime, wake time, and minutes to sleep time did show significant heritability at 0.44, 0.42, and 0.29. However, after adjusting for shared environment, only heritability of wake time remained significant. Sleep is affected by environmental stress and mental health factors even in a society with limited technological interference with sleep. Wake time may be a more biological marker of sleep as compared to the evening measures which are more influenced by other household members. Accounting for nongenetic and partially genetic determinants of sleep particularly stress and mood disorder is likely important for improving the precision of genetic studies of sleep.

Daily and Seasonal Variation in Light Exposure among the Old Order Amish

Exposure to artificial bright light in the late evening and early night, common in modern society, triggers phase delay of circadian rhythms, contributing to delayed sleep phase syndrome and seasonal affective disorder. Studying a unique population like the Old Order Amish (OOA), whose lifestyles resemble pre-industrial societies, may increase understanding of light’s relationship with health. Thirty-three participants (aged 25–74, mean age 53.5; without physical or psychiatric illnesses) from an OOA community in Lancaster, PA, were assessed with wrist-worn actimeters/light loggers for at least 2 consecutive days during winter/spring (15 January–16 April) and spring/summer (14 May–10 September). Daily activity, sleep–wake cycles, and their relationship with light exposure were analyzed. Overall activity levels and light exposure increased with longer photoperiod length. While seasonal variations in the amount and spectral content of light exposure were equivalent to those reported previously for non-Amish groups, the OOA experienced a substantially (~10-fold) higher amplitude of diurnal variation in light exposure (darker nights and brighter days) throughout the year than reported for the general population. This pattern may be contributing to lower rates of SAD, short sleep, delayed sleep phase, eveningness, and metabolic dysregulation, previously reported among the OOA population.