ACE2-containing defensosomes serve as decoys to inhibit SARS-CoV-2 infection.

Extracellular vesicles of endosomal origin, exosomes, mediate intercellular communication by transporting substrates with a variety of functions related to tissue homeostasis and disease. Their diagnostic and therapeutic potential has been recognized for diseases such as cancer in which signaling defects are prominent. However, it is unclear to what extent exosomes and their cargo inform the progression of infectious diseases. We recently defined a subset of exosomes termed defensosomes that are mobilized during bacterial infection in a manner dependent on autophagy proteins. Through incorporating protein receptors on their surface, defensosomes mediated host defense by binding and inhibiting pore-forming toxins secreted by bacterial pathogens. Given this capacity to serve as decoys that interfere with surface protein interactions, we investigated the role of defensosomes during infection by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of Coronavirus Disease 2019 (COVID-19). Consistent with a protective function, exosomes containing high levels of the viral receptor ACE2 in bronchoalveolar lavage fluid (BALF) from critically ill COVID-19 patients was associated with reduced intensive care unit (ICU) and hospitalization times. We found ACE2+ exosomes were induced by SARS-CoV-2 infection and activation of viral sensors in cell culture, which required the autophagy protein ATG16L1, defining these as defensosomes. We further demonstrate that ACE2+ defensosomes directly bind and block viral entry. These findings suggest that defensosomes may contribute to the antiviral response against SARS-CoV-2 and expand our knowledge on the regulation and effects of extracellular vesicles during infection.

Patterns and drivers of disparities in pediatric asthma outcomes among Medicaid-enrolled children living in subsidized housing in NYC.

OBJECTIVE: There are persistent disparities in pediatric asthma morbidity in the U.S. We linked claims data with information on neighborhood-level risk factors to explore drivers of asthma disparities among Medicaid-enrolled children in New York City subsidized housing. METHODS: We constructed a cohort of Medicaid-enrolled children living in public or other subsidized housing, based on residential address, in NYC between 2016 and 2019 (n = 108,969). We examined claims-derived asthma prevalence across age and racial and ethnic groups, integrating census tract-level information and using the Bayesian Improved Surname Geocoding (BISG) algorithm to address high rates of missing data in self-reported race and ethnicity. We used inverse probability weighting (IPW) to explore the extent to which disparities persisted when exposure to asthma risk factors - related to the built environment, neighborhood poverty, and air quality - were balanced across groups. This analysis was conducted in 2022-2023. RESULTS: Claims-derived asthma prevalence was highest among children <7 years at baseline and among non-Hispanic Black and Hispanic children. For example, among children aged 3-6 years at baseline, claims-derived prevalence was 17.3% and 18.1% among non-Hispanic Black and Hispanic children, respectively, compared to 9.3% and 9.0% among non-Hispanic White and non-Hispanic Asian American/Pacific Islander children. Using IPW to balance exposure to asthma risk factors across racial and ethnic groups attenuated, but did not eliminate, disparities in asthma prevalence. CONCLUSIONS: We found high asthma burden among children living in subsidized housing. Modifiable place-based characteristics may be important contributors to pediatric asthma disparities.

State-Level Firearm Laws and Firearm Homicide in US Cities: Heterogenous Associations by City Characteristics.

Despite well-studied associations of state firearm laws with lower state- and county-level firearm homicide, there is a shortage of studies investigating differences in the effects of distinct state firearm law categories on various cities within the same state using identical methods. We examined associations of 5 categories of state firearm laws-pertaining to buyers, dealers, domestic violence, gun type/trafficking, and possession-with city-level firearm homicide, and then tested differential associations by city characteristics. City-level panel data on firearm homicide cases of 78 major cities from 2010 to 2020 was assessed from the Centers for Disease Control and Prevention's National Vital Statistics System. We modeled log-transformed firearm homicide rates as a function of firearm law scores, city, state, and year fixed effects, along with time-varying city-level confounders. We considered effect measure modification by poverty, unemployment, vacant housing, and income inequality. A one z-score increase in state gun type/trafficking, possession, and dealer law scores was associated with 25% (95% confidence interval [CI]:-0.37,-0.1), 19% (95% CI:-0.29,-0.07), and 17% (95% CI:-0.28, -0.4) lower firearm homicide rates, respectively. Protective associations were less pronounced in cities with high unemployment and high housing vacancy, but more pronounced in cities with high income inequality. In large US cities, state-level gun type/trafficking, possession, and dealer laws were associated with lower firearm homicide rates, but buyers and domestic violence laws were not. State firearm laws may have differential effects on firearm homicides based on city characteristics, and city-wide policies to enhance socioeconomic drivers may add benefits of firearm laws.

Exposure density and neighborhood disparities in COVID-19 infection risk.

Although there is increasing awareness of disparities in COVID-19 infection risk among vulnerable communities, the effect of behavioral interventions at the scale of individual neighborhoods has not been fully studied. We develop a method to quantify neighborhood activity behaviors at high spatial and temporal resolutions and test whether, and to what extent, behavioral responses to social-distancing policies vary with socioeconomic and demographic characteristics. We define exposure density ([Formula: see text]) as a measure of both the localized volume of activity in a defined area and the proportion of activity occurring in distinct land-use types. Using detailed neighborhood data for New York City, we quantify neighborhood exposure density using anonymized smartphone geolocation data over a 3-mo period covering more than 12 million unique devices and rasterize granular land-use information to contextualize observed activity. Next, we analyze disparities in community social distancing by estimating variations in neighborhood activity by land-use type before and after a mandated stay-at-home order. Finally, we evaluate the effects of localized demographic, socioeconomic, and built-environment density characteristics on infection rates and deaths in order to identify disparities in health outcomes related to exposure risk. Our findings demonstrate distinct behavioral patterns across neighborhoods after the stay-at-home order and that these variations in exposure density had a direct and measurable impact on the risk of infection. Notably, we find that an additional 10% reduction in exposure density city-wide could have saved between 1,849 and 4,068 lives during the study period, predominantly in lower-income and minority communities.

A Matched Analysis of the Association Between Federally Mandated Smoke-Free Housing Policies and Health Outcomes Among Medicaid-Enrolled Children in Subsidized Housing, New York City, 2015-2019.

Smoke-free housing policies are intended to reduce the deleterious health effects of secondhand smoke exposure, but there is limited evidence regarding their health impacts. We examined associations between implementation of a federal smoke-free housing rule by the New York City Housing Authority (NYCHA) and pediatric Medicaid claims for asthma, lower respiratory tract infections, and upper respiratory tract infections in the early post-policy intervention period. We used geocoded address data to match children living in tax lots with NYCHA buildings (exposed to the policy) to children living in lots with other subsidized housing (unexposed to the policy). We constructed longitudinal difference-in-differences models to assess relative changes in monthly rates of claims between November 1, 2015, and December 31, 2019 (the policy was introduced on July 30, 2018). We also examined effect modification by baseline age group (≤2, 3-6, or 7-15 years). In New York City, introduction of a smoke-free policy was not associated with lower rates of Medicaid claims for any outcomes in the early postpolicy period. Exposure to the smoke-free policy was associated with slightly higher than expected rates of outpatient upper respiratory tract infection claims (incidence rate ratio = 1.05, 95% confidence interval: 1.01, 1.08), a result most pronounced among children aged 3-6 years. Ongoing monitoring is essential to understanding long-term health impacts of smoke-free housing policies.

Associations between a Novel Measure of Census Tract-Level Credit Insecurity and Frequent Mental Distress in US Urban Areas, 2020.

Access to and utilization of consumer credit remains an understudied social determinant of health. We examined associations between a novel, small-area, multidimensional credit insecurity index (CII), and the prevalence of self-reported frequent mental distress across US cities in 2020. The census tract-level CII was developed by the Federal Reserve Bank of New York using Census population information and a nationally representative sample of anonymized Equifax credit report data. The CII was calculated for tracts in 766 cities displayed on the City Health Dashboard at the time of analysis, predominantly representing cities with over 50,000 residents. The CII combined data on tract-level participation in the formal credit economy with information on the percent of individuals without revolving credit, percent with high credit utilization, and percent with deep subprime credit scores. Tracts were classified as credit-assured, credit-likely, mid-tier, at-risk, or credit-insecure. We used linear regression to examine associations between the CII and a modeled tract-level measure of frequent mental distress, obtained from the CDC PLACES project. Regression models were adjusted for neighborhood economic and demographic characteristics. We examined effect modification by US region by including two-way interaction terms in regression models. In adjusted models, credit-insecure tracts had a modestly higher prevalence of frequent mental distress (prevalence difference = 0.38 percentage points; 95% CI = 0.32, 0.44), compared to credit-assured tracts. Associations were most pronounced in the Midwest. Local factors impacting credit access and utilization are often modifiable. The CII, a novel indicator of community financial well-being, may be an independent predictor of neighborhood health in US cities and could illuminate policy targets to improve access to desirable credit products and downstream health outcomes.

Long-Term Trends in Secondhand Smoke Exposure in High-Rise Housing Serving Low-Income Residents in New York City: Three-Year Evaluation of a Federal Smoking Ban in Public Housing, 2018-2021.

INTRODUCTION: In July 2018, the U.S. Department of Housing and Urban Development passed a rule requiring public housing authorities to implement smoke-free housing (SFH) policies. We measured secondhand smoke (SHS) exposure immediately before, and repeatedly up to 36 months post-SFH policy implementation in a purposeful sample of 21 New York City (NYC) high-rise buildings (>15 floors): 10 NYC Housing Authority (NYCHA) buildings subject to the policy and 11 privately managed buildings in which most residents received housing vouchers (herein "Section 8"). AIMS AND METHODS: We invited participants from nonsmoking households (NYCHA n = 157, Section-8 n = 118) to enroll in a longitudinal air monitoring study, measuring (1) nicotine concentration with passive, bisulfate-coated filters, and (2) particulate matter (PM2.5) with low-cost particle sensors. We also measured nicotine concentrations and counted cigarette butts in common areas (n = 91 stairwells and hallways). We repeated air monitoring sessions in households and common areas every 6 months, totaling six post-policy sessions. RESULTS: After 3 years, we observed larger declines in nicotine concentration in NYCHA hallways than in Section-8, [difference-in-difference (DID) = -1.92 µg/m3 (95% CI -2.98, -0.87), p = .001]. In stairwells, nicotine concentration declines were larger in NYCHA buildings, but the differences were not statistically significant [DID= -1.10 µg/m3 (95% CI -2.40, 0.18), p = .089]. In households, there was no differential change in nicotine concentration (p = .093) or in PM2.5 levels (p = .385). CONCLUSIONS: Nicotine concentration reductions in NYCHA common areas over 3 years may be attributable to the SFH policy, reflecting its gradual implementation over this time. IMPLICATIONS: Continued air monitoring over multiple years has demonstrated that SHS exposure may be declining more rapidly in NYCHA common areas as a result of SFH policy adherence. This may have positive implications for improved health outcomes among those living in public housing, but additional tracking of air quality and studies of health outcomes are needed. Ongoing efforts by NYCHA to integrate the SFH policy into wider healthier-homes initiatives may increase policy compliance.

Assessing the association between food environment and dietary inflammation by community type: a cross-sectional REGARDS study.

BACKGROUND: Communities in the United States (US) exist on a continuum of urbanicity, which may inform how individuals interact with their food environment, and thus modify the relationship between food access and dietary behaviors. OBJECTIVE: This cross-sectional study aims to examine the modifying effect of community type in the association between the relative availability of food outlets and dietary inflammation across the US. METHODS: Using baseline data from the REasons for Geographic and Racial Differences in Stroke study (2003-2007), we calculated participants' dietary inflammation score (DIS). Higher DIS indicates greater pro-inflammatory exposure. We defined our exposures as the relative availability of supermarkets and fast-food restaurants (percentage of food outlet type out of all food stores or restaurants, respectively) using street-network buffers around the population-weighted centroid of each participant's census tract. We used 1-, 2-, 6-, and 10-mile (~ 2-, 3-, 10-, and 16 km) buffer sizes for higher density urban, lower density urban, suburban/small town, and rural community types, respectively. Using generalized estimating equations, we estimated the association between relative food outlet availability and DIS, controlling for individual and neighborhood socio-demographics and total food outlets. The percentage of supermarkets and fast-food restaurants were modeled together. RESULTS: Participants (n = 20,322) were distributed across all community types: higher density urban (16.7%), lower density urban (39.8%), suburban/small town (19.3%), and rural (24.2%). Across all community types, mean DIS was - 0.004 (SD = 2.5; min = - 14.2, max = 9.9). DIS was associated with relative availability of fast-food restaurants, but not supermarkets. Association between fast-food restaurants and DIS varied by community type (P for interaction = 0.02). Increases in the relative availability of fast-food restaurants were associated with higher DIS in suburban/small towns and lower density urban areas (p-values < 0.01); no significant associations were present in higher density urban or rural areas. CONCLUSIONS: The relative availability of fast-food restaurants was associated with higher DIS among participants residing in suburban/small town and lower density urban community types, suggesting that these communities might benefit most from interventions and policies that either promote restaurant diversity or expand healthier food options.

Disparities in routine healthcare utilization disruptions during COVID-19 pandemic among veterans with type 2 diabetes.

BACKGROUND: While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS: We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS: In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS: Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.

Addressing Financial Barriers to Health Care Among People Who are Low-Income and Insured in New York City, 2014-2017.

While health care-associated financial burdens among uninsured individuals are well described, few studies have systematically characterized the array of financial and logistical complications faced by insured individuals with low household incomes. In this mixed methods paper, we conducted 6 focus groups with a total of 55 residents and analyzed programmatic administrative records to characterize the specific financial and logistic barriers faced by residents living in public housing in East and Central Harlem, New York City (NYC). Participants included individuals who enrolled in a municipal community health worker (CHW) program designed to close equity gaps in health and social outcomes. Dedicated health advocates (HAs) were explicitly paired with CHWs to provide health insurance and health care navigational assistance. We describe the needs of 150 residents with reported financial barriers to care, as well as the navigational and advocacy strategies taken by HAs to address them. Finally, we outline state-level policy recommendations to help ameliorate the problems experienced by participants. The model of paired CHW-HAs may be helpful in addressing financial barriers for insured populations with low household income and reducing health disparities in other communities.

Adaptation of a Dietary Screener for Asian Americans.

No brief dietary screeners are available that capture dietary consumption patterns of Asian Americans. The purpose of this article is to describe the cultural adaptation of the validated Dietary Screener Questionnaire (DSQ) for use by clinicians, researchers, and community-based partners seeking to understand and intervene on dietary behaviors among English-speaking Asian Americans, for the six largest Asian subgroups (Chinese, Filipino, Asian Indian, Vietnamese, Korean, Japanese) in the United States. This was mainly accomplished by adding culturally specific examples of foods to the questionnaire items via searching online databases and soliciting input from members of our community partner network representing each of the six largest Asian subgroups. Over half of the 26 items on the DSQ were modified to include more culturally specific foods. Developing high-quality tools that reflect the diversity of the U.S. population are critical to implement nutrition interventions that do not inadvertently widen health disparities.

Self-Assessed Severity as a Determinant of Coronavirus Disease 2019 Symptom Specificity: A Longitudinal Cohort Study.

Coronavirus disease 2019 symptom definitions rarely include symptom severity. We collected daily nasal swab samples and symptom diaries from contacts of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) case patients. Requiring ≥1 moderate or severe symptom reduced sensitivity to predict SARS-CoV-2 shedding from 60.0% (95% confidence interval [CI], 52.9%-66.7%) to 31.5% (95% CI, 25.7%- 38.0%) but increased specificity from 77.5% (95% CI, 75.3%-79.5%) to 93.8% (95% CI, 92.7%-94.8%).

Rapid Community Engagement in Response to SARS-CoV-2 Funding Opportunities: New York City, 2020‒2021.

In response to fast-turnaround funding opportunities, collaborations have been forming across the country to address severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disparities. Here we describe the process, notes from the field, and evaluation results from a new collaboration involving multiple partners, formed in October 2020 in New York City as part of the Rapid Acceleration of Diagnostics initiative. We used the validated Research Engagement Survey Tool to evaluate the partnership. Results can inform future research and improve engagement efforts aimed at reducing SARS-CoV-2 disparities. (Am J Public Health. 2022;112(S9):S904-S908. https://doi.org/10.2105/AJPH.2022.307072).

Building Public Health Surveillance 3.0: Emerging Timely Measures of Physical, Economic, and Social Environmental Conditions Affecting Health.

In response to rapidly changing societal conditions stemming from the COVID-19 pandemic, we summarize data sources with potential to produce timely and spatially granular measures of physical, economic, and social conditions relevant to public health surveillance, and we briefly describe emerging analytic methods to improve small-area estimation. To inform this article, we reviewed published systematic review articles set in the United States from 2015 to 2020 and conducted unstructured interviews with senior content experts in public heath practice, academia, and industry. We identified a modest number of data sources with high potential for generating timely and spatially granular measures of physical, economic, and social determinants of health. We also summarized modeling and machine-learning techniques useful to support development of time-sensitive surveillance measures that may be critical for responding to future major events such as the COVID-19 pandemic. (Am J Public Health. 2022;112(10):1436-1445. https://doi.org/10.2105/AJPH.2022.306917).

Housing environments and asthma outcomes within population-based samples of adults and children in NYC.

Exposure to indoor environmental risk factors is associated with patterns of asthma morbidity. In this study, we assessed the relationship between housing type (i.e., home ownership, public housing, rental assistance, rent-controlled housing and other rental housing) and asthma outcomes among New York City (NYC) adults and children (ages 1-13). We used the 2019 NYC Community Health Survey (CHS) and 2019 NYC KIDS survey to analyze associations between housing type and ever having been diagnosed with asthma ("ever asthma") and experiencing a past-year asthma attack. We further examined whether associations were modified by smoking status (among adults), smoking within the home (among children), and overweight/obesity. Among adults, living in public housing, compared to home ownership, was associated with higher odds of ever asthma (odds ratio [OR] = 1.95; 95% confidence interval [CI] = 1.35, 2.84), and past-year asthma attack (OR = 2.24; 95% CI 1.21,4.18). Living in rental assistance housing was also significantly associated with ever asthma (OR = 1.75; 95% CI 1.16, 2.66). Associations between public or rental assistance housing and ever asthma were marginally non-significant among children. Associations between living in public or rental assistance housing and ever asthma were more pronounced among ever smokers than among never smokers. Housing environments remain important predictors of both pediatric and adult asthma morbidity. Associations between living in subsidized housing and asthma outcomes among adults are most apparent among ever smokers.

The Prenatal Neighborhood Environment and Geographic Hotspots of Infants with At-risk Birthweights in New York City.

Infants born with low or high ("at-risk") birthweights are at greater risk of adverse health outcomes across the life course. Our objective was to examine whether geographic hotspots of low and high birthweight prevalence in New York City had different patterns of neighborhood risk factors. We performed census tract-level geospatial clustering analyses using (1) birthweight prevalence and maternal residential address from an all-payer claims database and (2) domains of neighborhood risk factors (socioeconomic and food environment) from national and local datasets. We then used logistic regression analysis to identify specific neighborhood risk factors associated with low and high birthweight hotspots. This study examined 2088 census tracts representing 419,025 infants. We found almost no overlap (1.5%) between low and high birthweight hotspots. The majority of low birthweight hotspots (87.2%) overlapped with a socioeconomic risk factor and 95.7% overlapped with a food environment risk factor. Half of high birthweight hotspots (50.0%) overlapped with a socioeconomic risk factor and 48.8% overlapped with a food environment risk factor. Low birthweight hotspots were associated with high prevalence of excessive housing cost, unemployment, and poor food environment. High birthweight hotspots were associated with high prevalence of uninsured persons and convenience stores. Programs and policies that aim to prevent disparities in infant birthweight should examine the broader context by which hotspots of at-risk birthweight overlap with neighborhood risk factors. Multi-level strategies that include the neighborhood context are needed to address prenatal pathways leading to low and high birthweight outcomes.

Impact of land use and food environment on risk of type 2 diabetes: A national study of veterans, 2008-2018.

BACKGROUND: Large-scale longitudinal studies evaluating influences of the built environment on risk for type 2 diabetes (T2D) are scarce, and findings have been inconsistent. OBJECTIVE: To evaluate whether land use environment (LUE), a proxy of neighborhood walkability, is associated with T2D risk across different US community types, and to assess whether the association is modified by food environment. METHODS: The Veteran's Administration Diabetes Risk (VADR) study is a retrospective cohort of diabetes-free US veteran patients enrolled in VA primary care facilities nationwide from January 1, 2008, to December 31, 2016, and followed longitudinally through December 31, 2018. A total of 4,096,629 patients had baseline addresses available in electronic health records that were geocoded and assigned a census tract-level LUE score. LUE scores were divided into quartiles, where a higher score indicated higher neighborhood walkability levels. New diagnoses for T2D were identified using a published computable phenotype. Adjusted time-to-event analyses using piecewise exponential models were fit within four strata of community types (higher-density urban, lower-density urban, suburban/small town, and rural). We also evaluated effect modification by tract-level food environment measures within each stratum. RESULTS: In adjusted analyses, higher LUE had a protective effect on T2D risk in rural and suburban/small town communities (linear quartile trend test p-value <0.001). However, in lower density urban communities, higher LUE increased T2D risk (linear quartile trend test p-value <0.001) and no association was found in higher density urban communities (linear quartile trend test p-value = 0.317). Particularly strong protective effects were observed for veterans living in suburban/small towns with more supermarkets and more walkable spaces (p-interaction = 0.001). CONCLUSION: Among veterans, LUE may influence T2D risk, particularly in rural and suburban communities. Food environment may modify the association between LUE and T2D.

Neighborhood walkability and sex steroid hormone levels in women.

BACKGROUND: Neighborhood walkability (NW) has been linked to increased physical activity, which in turn is associated with lower concentrations of sex hormones and higher concentration of SHBG in women. However, no study has directly examined the association of NW with female sex hormone levels. OBJECTIVE: We conducted a cross-sectional study to evaluate the association between NW and circulating levels of sex hormones and SHBG in pre- and post-menopausal women. METHODS: We included 797 premenopausal and 618 postmenopausal women from the New York University Women's Health Study (NYUWHS) who were healthy controls in previous nested case-control studies in which sex hormones (androstenedione, testosterone, DHEAS, estradiol and estrone) and SHBG had been measured in serum at enrollment. Baseline residential addresses were geo-coded and the Built Environment and Health Neighborhood Walkability Index (BEH-NWI) was calculated. Generalized Estimating Equations were used to assess the association between BEH-NWI and sex hormone and SHBG concentrations adjusting for individual- and neighborhood-level factors. RESULTS: In premenopausal women, a one standard deviation (SD) increment in BEH-NWI was associated with a 3.5% (95% CI 0.9%-6.1%) lower DHEAS concentration. In postmenopausal women, a one SD increment in BEH-NWI was related to an 8.5% (95% CI 5.4%-11.5%) lower level of DHEAS, a 3.7% (95% CI 0.5%-6.8%) lower level of testosterone, a 1.8% (95% CI 0.5%-3.0%) lower level of estrone, and a 4.2% (95% CI 2.7%-5.7%) higher level of SHBG. However, the associations with respect to DHEAS and estrone became apparent only after adjusting for neighborhood-level variables. Sensitivity analyses using fixed effects meta-analysis and inverse probability weighting accounting for potential selection bias yielded similar results. CONCLUSION: Our findings suggest that NW is associated with lower concentrations of androgens and estrone, and increased SHBG, in postmenopausal women, and lower levels of DHEAS in premenopausal women.

Disentangling the roles of generational status and acculturation on dietary behaviors in disaggregated Asian American subgroups.

INTRODUCTION: Little is known on the independent effects of generational status and acculturation on the consumption of specific foods among disaggregated Asian American (AA) populations. This study explores the associations of generational status and acculturation with dietary behaviors of a nationwide non-probability sample of 3018 AAs (57.6% East Asian American (EAA), 18.9% South Asian American (SAA), 19.4% Southeast Asian American (SEAA)). METHODS: Recruited participants completed an online dietary survey designed and adapted for AAs to assess a range of diet and food purchasing behaviors. Generational status was assessed through participant and parental country of birth (1st-Gen, 2nd-Gen, 3rd-Gen); the Marin Short Acculturation Scale was adapted to measure acculturation. Linear regression models assessed the association of generational status and acculturation with consumption of 11 food/nutrient groups, adjusted for socio-economic variables. RESULTS: Compared to estimated US averages, participants reported lower fruit, dairy, and seafood intake yet lower red and processed meat, and higher whole grain, calcium, and fiber intake. Compared to EAA, SAA reported higher dairy (1.72 vs. 1.46 cups/day) and calcium (1029 vs. 954 mg/day) intakes, while SEAA reported lower vegetable intake (1.66 vs. 1.78 cups/day). In adjusted analyses, processed meat intake was higher among 2nd-Gen and 3rd-Gen vs.1st-Gen (+0.029 times/day; +0.061 times/day) participants. Higher acculturation was associated with lower vegetable, fiber, and seafood intake (-0.005 cups/day; -0.02 g/day; -0.002 times/day). CONCLUSION: Greater attention to the role of generational status and acculturation in AA dietary behaviors is needed, and findings call for further research to understand the mechanisms behind the dietary influence of different socialization and acculturative processes.

Normative Data and Conversion Equation for Spectral-Domain Optical Coherence Tomography in an International Healthy Control Cohort.

BACKGROUND: Spectral-domain (SD-) optical coherence tomography (OCT) can reliably measure axonal (peripapillary retinal nerve fiber layer [pRNFL]) and neuronal (macular ganglion cell + inner plexiform layer [GCIPL]) thinning in the retina. Measurements from 2 commonly used SD-OCT devices are often pooled together in multiple sclerosis (MS) studies and clinical trials despite software and segmentation algorithm differences; however, individual pRNFL and GCIPL thickness measurements are not interchangeable between devices. In some circumstances, such as in the absence of a consistent OCT segmentation algorithm across platforms, a conversion equation to transform measurements between devices may be useful to facilitate pooling of data. The availability of normative data for SD-OCT measurements is limited by the lack of a large representative world-wide sample across various ages and ethnicities. Larger international studies that evaluate the effects of age, sex, and race/ethnicity on SD-OCT measurements in healthy control participants are needed to provide normative values that reflect these demographic subgroups to provide comparisons to MS retinal degeneration. METHODS: Participants were part of an 11-site collaboration within the International Multiple Sclerosis Visual System (IMSVISUAL) consortium. SD-OCT was performed by a trained technician for healthy control subjects using Spectralis or Cirrus SD-OCT devices. Peripapillary pRNFL and GCIPL thicknesses were measured on one or both devices. Automated segmentation protocols, in conjunction with manual inspection and correction of lines delineating retinal layers, were used. A conversion equation was developed using structural equation modeling, accounting for clustering, with healthy control data from one site where participants were scanned on both devices on the same day. Normative values were evaluated, with the entire cohort, for pRNFL and GCIPL thicknesses for each decade of age, by sex, and across racial groups using generalized estimating equation (GEE) models, accounting for clustering and adjusting for within-patient, intereye correlations. Change-point analyses were performed to determine at what age pRNFL and GCIPL thicknesses exhibit accelerated rates of decline. RESULTS: The healthy control cohort (n = 546) was 54% male and had a wide distribution of ages, ranging from 18 to 87 years, with a mean (SD) age of 39.3 (14.6) years. Based on 346 control participants at a single site, the conversion equation for pRNFL was Cirrus = -5.0 + (1.0 × Spectralis global value). Based on 228 controls, the equation for GCIPL was Cirrus = -4.5 + (0.9 × Spectralis global value). Standard error was 0.02 for both equations. After the age of 40 years, there was a decline of -2.4 µm per decade in pRNFL thickness ( P < 0.001, GEE models adjusting for sex, race, and country) and -1.4 µm per decade in GCIPL thickness ( P < 0.001). There was a small difference in pRNFL thickness based on sex, with female participants having slightly higher thickness (2.6 µm, P = 0.003). There was no association between GCIPL thickness and sex. Likewise, there was no association between race/ethnicity and pRNFL or GCIPL thicknesses. CONCLUSIONS: A conversion factor may be required when using data that are derived between different SD-OCT platforms in clinical trials and observational studies; this is particularly true for smaller cross-sectional studies or when a consistent segmentation algorithm is not available. The above conversion equations can be used when pooling data from Spectralis and Cirrus SD-OCT devices for pRNFL and GCIPL thicknesses. A faster decline in retinal thickness may occur after the age of 40 years, even in the absence of significant differences across racial groups.