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Currently available pain assessment scales focus on pain-related symptoms and limitations imposed by pain. Validated assessment tools that measure how pain is regulated by those who live well with pain are missing. This study seeks to fill this gap by describing the development and preliminary validation of the Biobehavior Life Regulation (BLR) scale. The BLR scale assesses engagement, social relatedness, and self-growth in the presence of chronic pain and the unpredictability of chronic pain. Sources for items included survivor strategies, patient experiences, existing scales, and unpredictable pain research. Review for suitability yielded 52 items. Validation measures were identified for engagement, social relatedness, self-growth, and unpredictability of pain. The study sample (n = 202) represented patients treated in the Phoenix VA Health Care System (n = 112) and two community clinics (n = 90). Demographic characteristics included average age of 52.5, heterogeneous in ethnicity and race at the VA, mainly Non-Hispanic White at the community clinics, 14 years of education, and pain duration of 18 years for the VA and 15.4 years for community clinics. Exploratory factor analysis using Oblimin rotation in the VA sample (n = 112) yielded a two-factor solution that accounted for 48.23% of the total variance. Confirmatory factor analysis (CFA) in the same sample showed high correlations among items in Factor 1, indicating redundancy and the need to further reduce items. The final CFA indicated a 2-factor solution with adequate fit to the data. The 2-factor CFA was replicated in Sample 2 from the community clinics ( n = 90) with similarly adequate fit to the data. Factor 1, Pain Regulation, covered 8 items of engagement, social relatedness, and self-growth while Factor 2, Pain Unpredictability, covered 6 items related to the experience of unpredictable pain. Construct validity showed moderate to higher Pearson correlations between BLR subscales and relevant well-established constructs that were consistent across VA and community samples. The BLR scale assesses adaptive regulation strategies in unpredictable pain as a potential tool for evaluating regulation resources and pain unpredictability.

Background Overweight, obesity, and associated comorbidities are a pressing global issue among children of all ages, particularly among low-income populations. Rapid weight gain (RWG) in the first 6 months of infancy contributes to childhood obesity. Suboptimal sleep-wake patterns and gut microbiota (GM) have also been associated with childhood obesity, but little is known about their influences on early infant RWG. Sleep may alter the GM and infant metabolism, and ultimately impact obesity; however, data on the interaction between sleep-wake patterns and GM development on infant growth are scarce. In this study, we aim to investigate associations of infant sleep-wake patterns and GM development with RWG at 6 months and weight gain at 12 months. We also aim to evaluate whether temporal interactions exist between infant sleep-wake patterns and GM, and if these relations influence RWG. Methods The Snuggle Bug/ Acurrucadito study is an observational, longitudinal study investigating whether 24-h, actigraphy-assessed, sleep-wake patterns and GM development are associated with RWG among infants in their first year. Based on the Ecological Model of Growth, we propose a novel conceptual framework to incorporate sleep-wake patterns and the GM as metabolic contributors for RWG in the context of maternal-infant interactions, and familial and socio-physical environments. In total, 192 mother-infant pairs will be recruited, and sleep-wake patterns and GM development assessed at 3 and 8 weeks, and 3, 6, 9, and 12 months postpartum. Covariates including maternal and child characteristics, family and environmental factors, feeding practices and dietary intake of infants and mothers, and stool-derived metabolome and exfoliome data will be assessed. The study will apply machine learning techniques combined with logistic time-varying effect models to capture infant growth and aid in elucidating the dynamic associations between study variables and RWG. Discussion Repeated, valid, and objective assessment at clinically and developmentally meaningful intervals will provide robust measures of longitudinal sleep, GM, and growth. Project findings will provide evidence for future interventions to prevent RWG in infancy and subsequent obesity. The work also may spur the development of evidence-based guidelines to address modifiable factors that influence sleep-wake and GM development and prevent childhood obesity.

This study examines how feeding, sleep, and growth during infancy impact the gut microbiome (GM) in toddlers. The research was conducted on toddlers (n = 36), born to Latina women of low-income with obesity. Their mothers completed retrospective feeding and sleeping questionnaires at 1, 6, and 12 months; at 36 months, fecal samples were collected. Sequencing of the 16S rRNA gene (V4 region) revealed that breastfeeding for at least 1 month and the introduction of solids before 6 months differentiated the GM in toddlerhood (Bray–Curtis, pseudo-F = 1.805, p = 0.018, and pseudo-F = 1.651, p = 0.044, respectively). Sleep had an effect across time; at 1 and 6 months of age, a lower proportion of nighttime sleep (relative to 24 h total sleep) was associated with a richer GM at three years of age (Shannon H = 4.395, p = 0.036 and OTU H = 5.559, p = 0.018, respectively). Toddlers experiencing rapid weight gain from birth to 6 months had lower phylogenetic diversity (Faith PD H = 3.633, p = 0.057). These findings suggest that early life nutrition, sleeping patterns, and growth rate in infancy may influence the GM composition. Further verification of these results with objective sleep data and a larger sample is needed.

Currently available pain assessment scales focus on pain-related symptoms and limitations imposed by pain. Validated assessment tools that measure how pain is regulated by those who live well with pain are missing. This study seeks to fill this gap by describing the development and preliminary validation of the Biobehavior Life Regulation (BLR) scale. The BLR scale assesses engagement, social relatedness, and self-growth in the presence of chronic pain and the unpredictability of chronic pain. Sources for items included survivor strategies, patient experiences, existing scales, and unpredictable pain research. Review for suitability yielded 52 items. Validation measures were identified for engagement, social relatedness, self-growth, and unpredictability of pain. The study sample (n = 202) represented patients treated in the Phoenix VA Health Care System (n = 112) and two community clinics (n = 90). Demographic characteristics included average age of 52.5, heterogeneous in ethnicity and race at the VA, mainly Non-Hispanic White at the community clinics, 14 years of education, and pain duration of 18 years for the VA and 15.4 years for community clinics. Exploratory factor analysis using Oblimin rotation in the VA sample (n = 112) yielded a two-factor solution that accounted for 48.23% of the total variance. Confirmatory factor analysis (CFA) in the same sample showed high correlations among items in Factor 1, indicating redundancy and the need to further reduce items. The final CFA indicated a 2-factor solution with adequate fit to the data. The 2-factor CFA was replicated in Sample 2 from the community clinics (n = 90) with similarly adequate fit to the data. Factor 1, Pain Regulation, covered 8 items of engagement, social relatedness, and self-growth while Factor 2, Pain Unpredictability, covered 6 items related to the experience of unpredictable pain. Construct validity showed moderate to higher Pearson correlations between BLR subscales and relevant well-established constructs that were consistent across VA and community samples. The BLR scale assesses adaptive regulation strategies in unpredictable pain as a potential tool for evaluating regulation resources and pain unpredictability.

ABSTRACT Study Objectives We examined the association of sociocultural stress severity (i.e. acculturation stress, ethnic discrimination) and chronic stress burden with multiple dimensions of sleep in a population-based sample of US Hispanics/Latinos. We also explored whether employment status modified stress-sleep associations. Methods We conducted survey linear regressions to test the cross-sectional association of sociocultural stress severity and stress burden with sleep dimensions using data collected between 2010 and 2013 from individuals who participated in both the Hispanic Community Health Study/Study of Latinos Sueño and Sociocultural Ancillary studies (N = 1192). Results Greater acculturation stress (B = 0.75, standard error [SE] = 0.26, p < .01) and chronic psychosocial stress burden (B = 1.04, SE = 0.18, p < .001) were associated with greater insomnia symptoms but were not associated with actigraphic measures of sleep. Ethnic discrimination was not associated with any of the sleep dimensions. The association of acculturation stress with insomnia severity was greater in unemployed (B = 2.06, SE = 0.34) compared to employed (B = 1.01, SE = 0.31) participants (p-interaction = .08). Conclusions Acculturation stress severity and chronic stress burden are important and consistent correlates of insomnia, but not actigraphically measured sleep dimensions. If replicated, future research should test whether interventions targeting the resolution of sociocultural stress improve sleep quality in Hispanics/Latinos.

The coronavirus disease 2019 (COVID-19) pandemic impact on infant sleep (IS) is understudied. The purpose of this study was to examine the relationships between family impact and distress from COVID-19 pandemic stressors, parental insomnia symptoms, infant temperamental negative affectivity, and parent-reported IS. Parents from the Phoenix metropolitan area with a full-term healthy infant (<1 year) were recruited from February 27, 2021, to August 7, 2021. A sample of 70 parents (baby age 5.5 ± 3.5 months; parental age: 31.7 ± 5.0 years) completed the COVID-19 Exposure and Family Impact Survey (CEFIS) Impact and Distress scales, the Insomnia Severity Index (ISI), the Infant Behavioral Questionnaire-Revised Negative Affectivity subscale (IBQ-R-NA), and the Brief Infant Sleep Questionnaire-Revised (BISQ-R). Based on the transactional model of IS, path analyses were conducted to identify the direct effect of CEFIS scores and the indirect effects of parental ISI and infant IBQ-R-NA scores on BISQ-R scores. The parent sample was predominantly female (94.3%), white (72.9%), and married or in a domestic partnership (98.6%). Although COVID-19 pandemic impact and distress were not directly related to parent-reported IS, pandemic distress was negatively related to parent-reported IS indirectly through infant negative affectivity, including BISQ-R total score (β = -0.14, 95% CI [-0.32, -0.01]) and IS subscale score (β = -0.12, 95% CI [-0.27, -0.01]). Heightened COVID-19 pandemic family distress was related to poorer parent-reported IS through greater parent-reported infant negative affectivity, suggesting the importance of addressing family stress and emotional regulation during crises.

The indirect association of childhood abuse with prevalent hypertension in adulthood through sleep disturbance and pro-inflammatory biomarkers was investigated in 589 community-dwelling, middle-aged adults. Participants completed the Childhood Trauma Questionnaire and self-reported current sleep disturbance and medical diagnoses including hypertension. Blood pressure was taken and blood samples were analyzed for C-reactive protein, interleukin-6, and fibrinogen. Hypertension was present in 41.3 % of the sample. In the full multiple mediation model, tested using structural equation modeling, all hypothesized pathways were significant ( p ’s < 0.05). Childhood abuse was significantly related to both body mass index and sleep disturbance, which, both in turn, were significantly associated with inflammation, which was subsequently associated with hypertension status. The model demonstrated good fit [χ 2 (122) = 352.0, p  < 0.001, CFI = 0.918, RMSEA = 0.057] and the indirect effect of all mediators was significant (indirect effect: 0.02, 95 % CI 0.005–0.03, p  = 0.001). Sleep disturbance, body mass, and inflammation may be independent, intermediate steps between childhood abuse and subsequent hypertension that may be amenable to biobehavioral interventions.

To identify weekly sleep trajectories (sleep pattern changing by day over a course of week) of specific characteristics and examine the associations between trajectory classes and obesity and hypertension. A total of 2043 participants (mean age 46.9, 65.5% female) completed at least 7 days of actigraphy aged 18-64 from the Sueño ancillary study of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Weekly sleep trajectories for three daily level measures (wake after sleep onset [WASO], daytime napping duration, and intranight instability index) were identified using latent class growth models. The outcomes were obesity and hypertension. Using the trajectory with low-stable WASO as reference, the trajectory classes with increasing and high-concave patterns had significantly higher odds for obesity (OR 3.64 [1.23-10.84]) and hypertension (OR 5.25 [1.33, 20.82]), respectively. Compared with individuals with a low-stable napping duration trajectory, those with the high-concave pattern class were associated with hypertension (OR 2.27 [1.10-4.67]), and the association was mediated in part by obesity (OR 1.11 [1.00-1.22]). Individuals in the high intranight instability index trajectory had significantly larger likelihood for both obesity (OR 1.90 [1.26-2.86]) and hypertension (OR 1.86 [1.13-3.06]) compared with those in the low intranight instability index trajectory. Weekly trajectories varied for WASO, daytime napping duration, and intranight instability index. The trajectories with relatively larger values for these three measures were associated with greater risk for obesity and hypertension. These findings suggest that a stable pattern with relatively small weekly and nightly variability may be beneficial for cardiovascular health.

Background Racial differences in endogenous pain facilitatory processes have been previously reported. Evidence suggests that psychological and behavioral factors, including depressive symptoms and sleep, can alter endogenous pain facilitatory processes. Whether depressive symptoms and sleep might help explain racial differences in endogenous pain facilitatory processes has yet to be determined. Purpose This observational, microlongitudinal study examined whether depressive symptoms and sleep were sequential mediators of racial differences in endogenous pain facilitatory processes. Methods A total of 50 (26 African American and 24 non-Hispanic white) community-dwelling adults without chronic pain (mean 49.04 years; range 21–77) completed the Center for Epidemiological Studies Depression Scale prior to seven consecutive nights of sleep monitoring with actigraphy in the home environment. Participants subsequently returned to the laboratory for assessment of endogenous pain facilitation using a mechanical temporal summation protocol. Results Findings revealed greater depressive symptoms, poorer sleep efficiency, and greater temporal summation of mechanical pain in African Americans compared to non-Hispanic whites. In a sequential mediation model, greater depressive symptoms predicted poorer sleep efficiency ( t  = −2.55, p  = .014), and poorer sleep efficiency predicted enhanced temporal summation of mechanical pain ( t  = −4.11, p  < .001), particularly for African Americans. Conclusions This study underscores the importance of examining the contribution of psychological and behavioral factors when addressing racial differences in pain processing. Additionally, it lends support for the deleterious impact of depressive symptoms on sleep efficiency, suggesting that both sequentially mediate racial differences in endogenous pain facilitation.