Financial responsibility, financial context, and ambulatory blood pressure in early middle-aged African-American women.

BACKGROUND: African-American women have excess rates of elevated blood pressure (BP) and hypertension compared to women of all other racial/ethnic backgrounds. Several researchers have speculated that race and gender-related socioeconomic status (SES) stressors might play a role. OBJECTIVE: To examine the association between a novel SES-related stressor highly salient among African-American women, financial responsibility for one's household, and 48-h ambulatory BP. We further examined whether aspects related to African-American women's financial context (e.g., single parenthood, household income, marital status) played a role. METHODS: Participants were N = 345 employed, healthy African-American women aged 30-46 from diverse SES backgrounds who underwent 48-h ambulatory BP monitoring. Linear regression analyses were conducted to examine associations between self-reported financial responsibility and daytime and nighttime BP, adjusting for age, SES and other sociodemographics, cardiovascular risk factors, financial strain and depressive symptoms. Interactions between financial responsibility and single parenthood, household income, and marital/partnered status were tested. RESULTS: In age-adjusted analyses, reporting financial responsibility was associated with higher daytime systolic (ß = 4.42, S.E. = 1.36, p = 0.0013), and diastolic (ß = 2.82, S.E. = 0.98, p = 0.004) BP. Associations persisted in fully adjusted models. Significant associations were also observed for nighttime systolic and diastolic BP. There were no significant interactions with single parenthood, household income, nor marital/partnered status. CONCLUSION: Having primary responsibility for one's household may be an important driver of BP in early middle-aged African-American women, independent of SES, financial strain, and across a range of financial contexts. Future studies examining prospective associations are needed, and policy interventions targeting structural factors contributing to financial responsibility in African-American women may be warranted.

The association between Superwoman schema and subjective sleep quality among Black women.

OBJECTIVES: Similar to women overall, Black women are socialized to be communal and "self-sacrificing," but unlike women from other racial/ethnic backgrounds, Black women are also socialized to be "strong" and "invulnerable." This phenomenon is labeled Superwoman schema. This study examined associations between Superwoman schema endorsement and subjective sleep quality. METHODS: Participants included 405 Black women (ages 30-46). Superwoman schema was measured using a 35-item scale capturing five dimensions: obligation to present strength, suppress emotions, resistance to vulnerability, motivation to succeed, and obligation to help others. Superwoman schema overall and the five dimensions/subscales were analyzed. The Pittsburgh Sleep Quality Index (PSQI) was used to investigate overall subjective sleep quality (range: 0-19), poor sleep quality (PSQI >5), and specific sleep domains (eg, sleep duration, sleep disturbances). We fit linear and binary logistic regression models, adjusting for health-related and sociodemographic factors. RESULTS: Superwoman schema dimension obligation to help others was associated with lower overall subjective sleep quality (ß: .81, 95%CI=0.29, 1.32) and poor sleep quality (OR: 1.55, 95%CI=1.10, 2.19), as well as bad subjective sleep quality (OR: 1.76, 95%CI=1.18, 2.66), sleep disturbances (ß: .73, 95%CI =0.07, 1.41), and daytime sleepiness (OR: 2.01, 95%CI=1.25, 3.26). Suppress emotions (OR: 1.41, 95%CI=1.01, 1.99) was associated with poor subjective sleep quality. Superwoman schema overall was associated with daytime sleepiness (OR: 2.01, 95%CI=1.06, 3.82). CONCLUSION: Superwoman schema endorsement, especially obligation to help others and suppress emotions, may be important psychosocial risk factors for Black women's sleep health.

Extreme racism-related events and poor sleep in African-American women.

RATIONALE: Much of the research linking racism-related stressors to poor health has focused on fairly non-violent forms of racism that directly impact individuals under study. Exposure to particularly extreme and/or violent racist events are increasingly visible via smartphone recordings and social media, with consistent anecdotal reports of the effects of seeing and hearing about these events on sleep among minorities who racially identify with the victims. OBJECTIVE: This study examines whether exposure to direct and vicarious racism-related events (RREs), including more extreme events, are associated with sleep quality. Additionally, we examine effects of less and more violent direct RREs and vicarious RREs witnessed in person and via social media. METHODS: Among 422 African-American women, we assessed exposure to RREs using a modified version of the Race-Related Events Scale and assessed sleep quality using the Pittsburgh Sleep Quality Index (PSQI). Linear regression analyses were used to model continuous global sleep. RESULTS: Direct (ß = 0.24 [95% CI: 0.13, 0.35]) RREs were associated with worse continuous global sleep quality scores in analyses adjusted for sociodemographics and risk factors for poor sleep. More violent direct RREs (ß = 0.59 [95% CI: 0.30, 0.89]) had stronger associations with poor sleep quality than less violent direct RREs (ß = 0.25 [95% CI: 0.11, 0.40]). Vicarious RREs overall (ß = 0.04 [95% CI: 0.14, 0.21]) and those witnessed via social media (ß = -0.07 [95% CI: 0.29, 0.14]) were not associated with global sleep quality; conversely, vicarious RREs witnessed in person were (ß = 0.52 [95% CI: 0.21, 0.83]). CONCLUSION: Extreme, direct experiences of racism, particularly those that are violent in nature, are associated with poor sleep quality. However, extreme vicarious experiences are not-- unless witnessed in person.

Gendered Racial Microaggressions and Black Women's Sleep Health.

Gendered racial microaggressions reflect historical and contemporary gendered racism that Black women encounter. Although gendered racial microaggressions are related to psychological outcomes, it is unclear if such experiences are related to sleep health. Moreover, the health effects of gendered racial microaggressions dimensions are rarely investigated. Using a cohort of Black women (N = 400), this study employs an intracategorical intersectional approach to (1) investigate the association between gendered racial microaggressions and sleep health, (2) assess whether gendered racial microaggressions dimensions are related to sleep health, and (3) examine whether the gendered racial microaggressions-sleep health association persists after accounting for depressive symptoms and worry. Gendered racial microaggressions were associated with poor sleep quality overall and four specific domains: subjective sleep quality, latency, disturbance, and daytime sleepiness. Two gendered racial microaggressions dimensions were especially detrimental for sleep: assumptions of beauty/sexual objectification and feeling silenced and marginalized. After accounting for mental health, the effect of gendered racial microaggressions on sleep was reduced by 47 percent. Future research implications are discussed.

Interpretive JIVE: Connections with CCA and an application to brain connectivity.

Joint and Individual Variation Explained (JIVE) is a model that decomposes multiple datasets obtained on the same subjects into shared structure, structure unique to each dataset, and noise. JIVE is an important tool for multimodal data integration in neuroimaging. The two most common algorithms are R.JIVE, an iterative approach, and AJIVE, which uses principal angle analysis. The joint structure in JIVE is defined by shared subspaces, but interpreting these subspaces can be challenging. In this paper, we reinterpret AJIVE as a canonical correlation analysis of principal component scores. This reformulation, which we call CJIVE, (1) provides an intuitive view of AJIVE; (2) uses a permutation test for the number of joint components; (3) can be used to predict subject scores for out-of-sample observations; and (4) is computationally fast. We conduct simulation studies that show CJIVE and AJIVE are accurate when the total signal ranks are correctly specified but, generally inaccurate when the total ranks are too large. CJIVE and AJIVE can still extract joint signal even when the joint signal variance is relatively small. JIVE methods are applied to integrate functional connectivity (resting-state fMRI) and structural connectivity (diffusion MRI) from the Human Connectome Project. Surprisingly, the edges with largest loadings in the joint component in functional connectivity do not coincide with the same edges in the structural connectivity, indicating more complex patterns than assumed in spatial priors. Using these loadings, we accurately predict joint subject scores in new participants. We also find joint scores are associated with fluid intelligence, highlighting the potential for JIVE to reveal important shared structure.

Extreme racism-related events and poor sleep in African-American women.

RATIONALE: Much of the research linking racism-related stressors to poor health has focused on fairly non-violent forms of racism that directly impact individuals under study. Exposure to particularly extreme and/or violent racist events are increasingly visible via smartphone recordings and social media, with consistent anecdotal reports of the effects of seeing and hearing about these events on sleep among minorities who racially identify with the victims. OBJECTIVE: This study examines whether exposure to direct and vicarious racism-related events (RREs), including more extreme events, are associated with sleep quality. Additionally, we examine effects of less and more violent direct RREs and vicarious RREs witnessed in person and via social media. METHODS: Among 422 African-American women, we assessed exposure to RREs using a modified version of the Race-Related Events Scale and assessed sleep quality using the Pittsburgh Sleep Quality Index (PSQI). Linear regression analyses were used to model continuous global sleep. RESULTS: Direct (ß = 0.24 [95% CI: 0.13, 0.35]) RREs were associated with worse continuous global sleep quality scores in analyses adjusted for sociodemographics and risk factors for poor sleep. More violent direct RREs (ß = 0.59 [95% CI: 0.30, 0.89]) had stronger associations with poor sleep quality than less violent direct RREs (ß = 0.25 [95% CI: 0.11, 0.40]). Vicarious RREs overall (ß = 0.04 [95% CI: 0.14, 0.21]) and those witnessed via social media (ß = -0.07 [95% CI: 0.29, 0.14]) were not associated with global sleep quality; conversely, vicarious RREs witnessed in person were (ß = 0.52 [95% CI: 0.21, 0.83]). CONCLUSION: Extreme, direct experiences of racism, particularly those that are violent in nature, are associated with poor sleep quality. However, extreme vicarious experiences are not-- unless witnessed in person.

Which multiband factor should you choose for your resting-state fMRI study?

Multiband acquisition, also called simultaneous multislice, has become a popular technique in resting-state functional connectivity studies. Multiband (MB) acceleration leads to a higher temporal resolution but also leads to spatially heterogeneous noise amplification, suggesting the costs may be greater in areas such as the subcortex. We evaluate MB factors of 2, 3, 4, 6, 8, 9, and 12 with 2 mm isotropic voxels, and additionally 2 mm and 3.3 mm single-band acquisitions, on a 32-channel head coil. Noise amplification was greater in deeper brain regions, including subcortical regions. Correlations were attenuated by noise amplification, which resulted in spatially varying biases that were more severe at higher MB factors. Temporal filtering decreased spatial biases in correlations due to noise amplification, but also tended to decrease effect sizes. In seed-based correlation maps, left-right putamen connectivity and thalamo-motor connectivity were highest in the single-band 3.3 mm protocol. In correlation matrices, MB 4, 6, and 8 had a greater number of significant correlations than the other acquisitions (both with and without temporal filtering). We recommend single-band 3.3 mm for seed-based subcortical analyses, and MB 4 provides a reasonable balance for studies analyzing both seed-based correlation maps and connectivity matrices. In multiband studies including secondary analyses of large-scale datasets, we recommend reporting effect sizes or test statistics instead of correlations. If correlations are reported, temporal filtering (or another method for thermal noise removal) should be used. The Emory Multiband Dataset is available on OpenNeuro.