From 2001 to 2021, the age- and sex-adjusted veteran suicide rate in the United States increased 76.3%. Surveillance of suicidal ideation (SI) and nonfatal suicidal self-directed violence (NF-SSDV) is a critical component of public health-oriented suicide prevention efforts. To facilitate national NF-SSDV surveillance, a biennial, population-based survey was initiated: Assessing Social and Community Environments with National Data (ASCEND) for Veteran Suicide Prevention. A total of 17 396 veterans participated in the first large-scale ASCEND survey (2022). This article reports on SI and NF-SSDV prevalence among veterans residing in the continental United States, Hawaii, and Puerto Rico. Lifetime SI was reported by 31.98% (95% CI, 30.97-32.99), post-military SI by 25.88% (95% CI, 24.91-26.85), and past-year SI by 12.69% (95% CI, 11.90-13.47). The most commonly considered SI method among those with past-year SI was gunshot. Additionally, 36.87% (95% CI, 34.84-38.90) of veterans with lifetime SI reported lifetime preparatory behaviors. Moreover, 9.13% (95% CI, 8.43-9.82) of veterans reported lifetime interrupted attempts. Lifetime suicide attempts (SAs) were reported by 6.99% (95% CI, 6.41-7.56) of veterans, with 4.88% (95% CI, 4.39-5.36) reporting post-military SA. The most common method in prior attempts was medication overdose. ASCEND provides a novel opportunity to elucidate the prevalence of SI and different types of NF-SSDV in the veteran population. Recurring administration will elucidate changes in SI and NF-SSDV prevalence in the veteran population over time.

Extreme heat is an important public health concern, and heat stress exposure and related adaptive capacity are not equally distributed across social groups. We conducted a systematic review to answer the question: What is the effect of social disadvantage on exposure to subjective and objective heat stress and related adaptive capacity to prevent or reduce exposure to heat stress in the general population? We systematically searched for peer-reviewed journal articles that assessed differences in heat stress exposure and related adaptive capacity by social factors that were published between 2005 and 2024. One author screened all records and extracted data; a second author screened and extracted 10% for validation. Synthesis included the identification and description of specific social groups unequally exposed to heat stress and with lower adaptive capacity. We assessed European studies for the potential risk of bias in their assessment. We identified 123 relevant publications. Subjective heat stress appeared in 18.7% of articles, objective heat stress in 54.5%, and adaptive capacity in 54.5%. Nearly half came from North America (47.2%), 22.8% from Asia, and 17.1% from Europe. Publishing increased from zero articles in 2005 to 21 in 2023. Most studies considered socioeconomic status (SES) (78.8%), and many considered age (50.4%), race/ethnicity (42.3%), and sex/gender (30.1%). The identified studies show that lower-SES populations, young people, immigrants, unemployed people, those working in outdoor and manual occupations, and racial/ethnic minorities are generally more exposed to heat stress and have lower adaptive capacity. Most studies of objective heat stress use inadequate measures which are not representative of experienced temperatures. European studies generally have a low or moderate risk of bias in their assessments. Social inequalities in heat stress exposure and related adaptive capacity have been documented globally. In general, socially disadvantaged populations are more exposed to heat stress and have lower adaptive capacity. These social inequalities are context-dependent, dynamic, multi-dimensional, and intersectional. It is essential to consider social inequalities during heat-health action planning and when developing and implementing climate change adaptation policies and interventions.

Ambient air pollution is a major risk factor for CVDs, and a plausible mechanism is speculated to be alteration of autonomic nervous system (ANS) function. Yet, the short-term effects of air pollution on heart rate variability (HRV), a measure of ANS balance are inconsistent. This study aimed to evaluate the short-term effects of ambient PM2.5 and NO2 on cardiovascular autonomic function, and to determine vulnerable subgroups and temporal trends from repeated HRV and HR measurements over 14 years in the KORA cohort. We analyzed data from 4,032 participants in KORA S4 (1999–2001) and 1,912 in KORA FF4 (2013–2014). Air pollution data were from fixed monitoring stations, and HRV indices were derived from 5-minute ECG recordings. Generalized additive models (GAMs) and generalized additive mixed models (GAMMs) were used to assess associations. In S4, each IQR increase in PM2.5 at the 14-day moving average was associated with a 2.32

BACKGROUND:The effects of different ultrafine particle (UFP) metrics on strokes are unclear. This case-crossover study investigated the association between short-term exposure to four size-segregated UFP metrics and stroke occurrence. METHODS:From 2006 to 2020, we included 19,518 stroke cases from the University Hospital Augsburg, Germany, a less polluted area. Meanwhile, daily averages of four UFP metrics, including particle number (PNC), mass (PMC), length (PLC), and surface area (PSC) concentrations, were collected from fixed monitoring sites in Augsburg. Conditional logistic regression was employed to assess the association between UFP metrics and stroke risk. Potential individual vulnerability and effect modification were examined using the stratified and interaction analyses. RESULTS:Elevated risk of stroke events was largely similar across all four UFP metrics. The odds ratios (95 % confidence intervals) of strokes for each interquartile range increase in lag 0-6 days of UFPs were 4.76 % (1.06; 8.60) for PNC, 3.99 % (0.93; 7.13) for PMC, 4.52 % (1.11; 8.05) for PLC, and 4.14 % (1.00; 7.38) for PSC. Stable associations with strokes were mainly found for the size fractions of 10-100 nm and 30-100 nm. The cumulative effects of UFP were more pronounced for ischemic strokes and minor strokes with a lower severity. Cold spells might exaggerate the effects of UFPs. CONCLUSION:UFP metrics like particle length and surface area concentration, aside from particle number, may provide valuable insights into particle properties relevant to stroke risk. Expanding real-time, size-segregated monitoring of UFPs represents an effective strategy to mitigate the health impacts of traffic-related air pollution.

Climate change is the greatest existential threat to planetary and human health, driven by shifts in the Earth's weather and atmospheric conditions due to human activities. It causes extreme temperatures, increased droughts, wildfires, dust storms, coastal flooding, storm surges, hurricanes, and various compounded events. The impacts of climate change on health are complex and include pathways that contribute to non-communicable diseases like cardiovascular disease. A collaborative effort among medical professionals, researchers, public health officials, and policymakers is crucial to mitigate the effects of global warming. This review provides an overview of how climate change affects cardiovascular health through direct exposures like temperature changes, air pollution, wildfires, dust storms, and extreme weather conditions. We also identify vulnerable populations and suggest mitigation strategies.

Previous health impact assessments of temperature-related mortality in Europe indicated that the mortality burden attributable to cold is much larger than for heat. Questions remain as to whether climate change can result in a net decrease in temperature-related mortality. In this study, we estimated how climate change could affect future heat-related and cold-related mortality in 854 European urban areas, under several climate, demographic and adaptation scenarios. We showed that, with no adaptation to heat, the increase in heat-related deaths consistently exceeds any decrease in cold-related deaths across all considered scenarios in Europe. Under the lowest mitigation and adaptation scenario (SSP3-7.0), we estimate a net death burden due to climate change increasing by 49.9

BACKGROUND:Recent climate changes have resulted in a rising frequency of extreme cold events that take place during the warm season. Few studies have investigated the impact of these warm-season cold spells on cardiovascular health. Here, we aimed to investigate the potential relationship between exposure to relatively low temperature exposure during the warm season and stroke risk. METHODS:We conducted a time-stratified case-crossover study using a validated, complete, and detailed registration of all stroke cases in the city of Augsburg, Germany, from 2006 to 2020 to assess the association between the occurrence of stroke and exposure to cold spell events during the warm season (May-October). Six cold spell definitions were created using different relative temperature thresholds (1st, 2.5th, and 5th percentiles) and durations (more than 1-2 consecutive days). Conditional logistic regression with distributed lag models was then applied to assess the accumulated effects of these warm-season cold spells on stroke risk over a lag period of 0-6 days, with adjustments for daily mean temperature. RESULTS:Results confirmed that warm-season cold spells were significantly linked to an elevated risk of stroke with effects that could persist three days after exposure. The cumulative odds ratio (OR) estimates for the cold spells using the 2.5th percentile as air temperature threshold reached 1.29 (95% confidence interval (CI): 1.09-1.53) and 1.23 (95%CI: 1.05-1.44) for durations more than one and two days, respectively. Warm-season cold spells also had significant associations with both transient ischemic attacks and ischemic strokes. The stratified analysis showed that the elderly population (aged ≥ 65 years), females, and stroke cases characterized by minor symptoms demonstrated a significantly increased stroke risk of the effects of warm season cold spells. CONCLUSIONS:This study presents strong evidence for an overlooked association between warm-season cold spells and an increased risk of stroke occurrence. These findings further highlight the multifaceted ways in which climate change can affect human health.

Ambient air pollution has been linked to neurodegenerative diseases. Nevertheless, the literature on the effects of air pollution on the olfactory system and early cognitive impairment is scarce. In this study, we investigated the association between long-term air pollution exposure and odor identification, which can serve as an early indicator of various neurodegenerative conditions. We used data collected in Augsburg, Germany in 2018-2019 for the population-based KORA FIT study of 3,059 participants born between 1945-1964. The Sniffin' Sticks 12-Item Test was used to assess each participant's odor identification. Air pollution concentrations at residential addresses were estimated using land use regression modeling. We dichotomized the odor identification score to normosmia (score ≥ 10) versus hyposmia (score < 7) or anosmia (score < 10) and applied logistic regression. The models were adjusted for age, sex, socioeconomic characteristics (education, income, socioeconomic status), lifestyle factors (physical activity, smoking, body mass index, alcohol consumption) and disease history (e.g., allergies). We observed increased odds of hyposmia or anosmia compared to normosmia per interquartile range increase in the concentrations of PNC, PM2.5, PM2.5abs, PMcoarse, PM10, NO2 and NOx [OR (95 % CI): 1.12 (1.02, 1.24), 1.10 (0.98, 1.25), 1.14 (1.00, 1.30), 1.20 (1.06, 1.35), 1.20 (1.06, 1.36), 1.20 (1.06, 1.37) and 1.13 (1.01, 1.27); respectively]. For O3, no clear effects were detected. Females and physically active people appeared to be more susceptible. No further significant indications of effect modification were found. The results were consistent across sensitivity analyses. This study provides robust evidence for an association between long-term exposure to traffic-related air pollution and poor odor identification, even in a region with relatively low air pollution levels. These findings suggest a potential link between prolonged air pollution exposure and early changes in the olfactory system and could be indicative of early signs of detrimental effects on the brain.

BACKGROUND:Few studies have examined how air pollutants affect various stroke subtypes and how these effects differ with stroke severity, especially among European populations living in less polluted areas. METHODS:We conducted a time-stratified case-crossover study using 15 years of hospital-based stroke data from the University Hospital Augsburg in Southern Germany. Daily average air pollutants, including particulate matter (PM) with an aerodynamic diameter < 10μm (PM10), coarse particles (PMcoarse), fine particles (PM2.5), ozone (O3), nitrogen oxides (NO2, NO), and meteorological data were obtained from local fixed urban background monitoring sites from 2006 to 2020. Conditional logistic regression was utilized to estimate the relationship between pollutants and daily stroke events, with modification effects being examined through stratified and interaction analyses. RESULTS:Based on 19,518 included stroke cases, each interquartile range (IQR) increase in PM2.5, PM10, PMcoarse, and NO2 was associated with a 2.11 %, 2.55 %, 2.50 %, and 3.48 % rise in overall stroke events 5-6 days later. Positive associations were seen mostly for transient ischemic attacks and hemorrhagic strokes. Notably, people with severe stroke-induced disabilities were disproportionately affected by PM and NO2, while those with mild disabilities were more affected by O3 and NO. Moreover, damaging effects were amplified during warm seasons and the 2016-2020 five-year period. CONCLUSION:Short-term air pollution exposure may trigger stroke events, with differential impacts depending on stroke subtype and severity of pre-existing disability. A coordinated effort is needed for stroke prevention in response to specific air pollutants, especially in the context of global warming.

BACKGROUND:Climate change threatens human health and general welfare via multiple dimensions. However, the associations of short-term exposure to temperature variability, a crucial aspect of climate change, with myocardial infarction (MI) hospital admissions remains unclear. METHODS AND FINDINGS:This population-based nationwide study employed a time-stratified, case-crossover design to investigate the association between ambient temperature variability and MI hospital admissions among 233,617 patients recorded in the SWEDEHEART registry in Sweden between 2005 and 2019. High-resolution (1 × 1 km) daily mean ambient temperature was assigned to patients' residential areas. Temperature variability was calculated as the difference between the same-day (as the MI event) ambient temperature and the average temperature over the preceding 7 days. An upward temperature shift represents a rise in the current day's temperature relative to the 7-day average, while a downward temperature shift indicates a corresponding decrease. A conditional logistic regression model with distributed lag non-linear model was applied to estimate the association between ambient temperature variability and total MI (encompassing all MI types), ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) hospital admissions at lag 0-6 days. Potential effect modifiers, such as sex, history of diseases, and season, were also examined. The patients had an average age of 70.6 years, and 34.5% of them were female. Our study found that an upward temperature shift was associated with increased risks of total MI (encompassing all MI types), STEMI, and NSTEMI hospital admissions at lag 0 day, with odds ratios (OR, 95% confidence intervals [CIs]) of 1.009 (1.005, 1.013; p < 0.001), 1.014 (1.006, 1.022; p < 0.001), and 1.007 (1.001, 1.012; p = 0.014) per 1 °C increase, respectively. These associations attenuated and became non-significant over lags 1-6 days. Furthermore, a downward temperature shift was associated with increased risks of hospital admissions for total MI (encompassing all MI types) at a lag of 2 days with an OR (95% CI): 1.003 (1.001, 1.005; p = 0.014), and for STEMI at lags 2 and 3 days with ORs (95% CI): 1.006 (1.002, 1.010; p = 0.001) and 1.005 (1.001, 1.008; p = 0.011), per 1 °C decrease, respectively. Conversely, higher downward temperature shifts were associated with decreased risks of total MI (encompassing all MI types) and NSTEMI at lag 0 day. No significant associations were observed at other lag days for downward temperature shifts. Males and patients with diabetes had higher MI hospitalization risks from upward temperature shift exposure, while downward temperature shift exposure in cold seasons posed greater MI hospitalization risks. A methodological limitation was the use of ambient temperature variability as a proxy for personal exposure, which, while practical for large-scale studies, may not precisely reflect individual temperature exposure. CONCLUSIONS:This nationwide study contributes insights that short-term exposures to higher temperature variability-greater upward or downward temperature shifts-are associated with an increased risk of MI hospitalization. Our finding highlights the cardiovascular health threats posed by higher temperature variability, which are anticipated to increase in frequency and intensity due to climate change.

Temperature extremes are one facet of global warming caused by climate change. They have a broad impact on population health globally. Due to specific individual- and area-level factors, some subgroups of the population are at particular risk. Observational data has demonstrated that the association between temperature and mortality and cardiovascular mortality is U- or J-shaped. This means that beyond an optimal temperature, both low and high temperatures increase cardiovascular risk. In addition, there is emerging epidemiological data showing that climate change-related temperature fluctuations may be particularly challenging for cardiovascular health. Biological plausibility for these observations comes from the effect of cold, heat, and temperature fluctuations on risk factors for cardiovascular disease. Shared mechanisms of heat and cold adaptation include sympathetic activation, changes in vascular tone, increased cardiac strain, and inflammatory and prothrombotic stimuli. The confluence of these mechanisms can result in demand ischemia and/or atherosclerotic plaque rupture. In conclusion, public health and individual-level measures should be taken to protect susceptible populations, such as patients with risk factors and/or pre-existing cardiovascular disease, from the adverse effects of non-optimal temperatures. This review aims to provide an overview of the association between temperature extremes and cardiovascular disease through the lens of pathophysiology and observational data. It also highlights some specific meteorological aspects, gives insight to the interplay of air temperature and air pollution, touches upon social dimensions of climate change, and tries to give a brief outlook into what to expect from the future.

Objective: To examine whether neurobehavioral symptoms mediate the relationship between comorbid mental health conditions (major depressive disorder [MDD] and/or posttraumatic stress disorder [PTSD]) and participation restriction among Veterans with mild traumatic brain injury (mTBI). Setting: Veterans Health Administration (VHA). Participants: National sample of Veterans with mTBI who received VHA outpatient care between 2012 and 2020. Design: Secondary data analysis of VHA clinical data. We specified a latent variable path model to estimate relationships between: (1) comorbid mental health conditions and 3 latent indicators of neurobehavioral symptoms (vestibular-sensory; mood-behavioral; cognitive); (2) latent indicators of neurobehavioral symptoms and 2 latent indicators of participation restriction (social and community participation; productivity); and (3) comorbid mental health conditions and participation restriction. Main Measures: International Classification of Diseases codes, Neurobehavioral Symptom Inventory, and Mayo-Portland Adaptability Inventory Participation Index to measure mental health conditions, neurobehavioral symptoms, and participation restrictions, respectively. Results: Indirect effect estimates indicated that comorbid MDD and/or PTSD was associated with greater social and community participation restrictions, as mediated by mood-behavioral (β = .22-.33; 99% CI 0.18-0.4; small to medium effect) and cognitive symptoms (β = .08-.13; 99% CI 0.05-0.18; small effect), and with greater productivity restrictions, as mediated by vestibular-sensory (β = .06-.11; 99% CI 0.04-0.15; small effect) and cognitive symptoms (β = .08-.13; 99% CI 0.05-0.18; small effect). Direct effect estimates indicated that comorbid MDD and/or PTSD was associated with greater challenges with both social and community participation (β = .19-.40; 99% CI 0.12-0.49; small to medium effect) and productivity (β = .08-.44; 99% CI −0.02 to 0.55; small to medium effect). Conclusion: Neurobehavioral symptoms partially mediated the impact of MDD and/or PTSD on participation restrictions among Veterans with mTBI. These findings advance the understanding of explanatory mechanisms underlying participation challenges among Veterans with comorbid mTBI and mental health challenges, thereby informing the development of tailored intervention strategies.

BACKGROUND:Heatwaves pose significant risks to human health. Implementing heat health warning systems (HHWS) has been widely adopted as a preventive measure. However, the effectiveness of the German HHWS in reducing mortality during heat episodes across different cities has scarcely been researched. OBJECTIVE:This study aimed to assess the effect of HHWS on mortality during heat episodes in 15 major cities in Germany and explore city-specific factors influencing the effectiveness of heat alerts. METHODS:Daily all-cause mortality data during the warm-season months (May to September) from 1993 to 2020 were linked with heat alert data and meteorological information. A difference-in-differences approach was employed to estimate the city-specific effects of heat alerts on mortality. In the second stage, meta-regression models were used to pool the city-specific estimates and examine the heterogeneity across cities. RESULTS:Substantial variation in the city-specific associations was observed, with some cities exhibiting significant reductions in mortality during heat episodes after the HHWS implementation while others showed no significant effect. The pooled relative risk (RR) from the second-stage analysis, based on the meta-variables averaged across all cities studied, suggested no overall significant protective effect of heat alerts on mortality (RR = 1.00, 95 %CI:0.98 to 1.01). However, when controlling for the meta-variables recreational area per person, total population, and population density, we found a significant but small protective effect of heat alerts across all cities studied (RR = 0.85, 95 %CI:0.75 to0.97). CONCLUSION:According to our results, the effectiveness of heat alerts varied considerably across the cities, suggesting the importance of considering city-specific factors, such as population size, population density, and the presence of blue and green urban infrastructure. Understanding these factors can help improve the effectiveness of HHWS and tailor interventions to address the specific characteristics of different urban areas within heat-health action plans.

Cardiovascular disease (CVD) is the leading cause of mortality globally, with over 20 million deaths each year. While traditional risk factors—such as hypertension, diabetes, smoking, and poor diet—are well-established, emerging evidence underscores the profound impact of environmental exposures on cardiovascular health. Air pollution, particularly fine particulate matter (PM2.5), contributes to approximately 8.3 million deaths annually, with over half attributed to CVD. Similarly, noise pollution, heat extremes, toxic chemicals, and light pollution significantly increase the risk of CVD through mechanisms involving oxidative stress, inflammation, and circadian disruption. Recent translational and epidemiological studies show that chronic exposure to transport noise increases the risk of myocardial infarction, stroke, and heart failure. Air pollution, even below regulatory thresholds, promotes atherosclerosis, vascular dysfunction, and cardiac events. Novel threats such as micro- and nano-plastics are emerging as contributors to vascular injury and systemic inflammation. Climate change exacerbates these risks, with heatwaves and wildfires further compounding the cardiovascular burden, especially among vulnerable populations. The cumulative effects of these exposures—often interacting with behavioural and socioeconomic risk factors—are inadequately addressed in current prevention strategies. The exposome framework offers a comprehensive approach to integrating lifelong environmental exposures into cardiovascular risk assessment and prevention. Mitigation requires systemic interventions including stricter pollution standards, noise regulations, sustainable urban design, and green infrastructure. Addressing environmental determinants of CVD is essential for reducing the global disease burden. This review calls for urgent policy action and for integrating environmental health into clinical practice to safeguard cardiovascular health in the Anthropocene.

Objective: To examine whether co-morbid insomnia, post-traumatic stress disorder (PTSD), depression, and chronic pain mediate the relationship between traumatic brain injury (TBI) and positive airway pressure (PAP) treatment adherence. Setting: One Veterans Health Administration (VHA) sleep medicine site. Participants: Veterans (n = 8836) who were prescribed a modem-enabled PAP device. Design: Secondary analysis of clinical data. We used path analysis to examine: (1) whether Veterans with a history of TBI were more likely to experience insomnia, PTSD, depression, and chronic pain; (2) in turn, whether Veterans with these co-morbid conditions exhibited lesser PAP adherence; and (3) whether Veterans with a history of TBI will exhibit lesser PAP adherence, even while accounting for such co-morbid conditions. Model estimates were adjusted for sociodemographic (eg, race/ethnicity) and clinical characteristics (eg, mask leakage). Main Measures: Health conditions were abstracted from the VHA medical record. PAP adherence was measured using average nightly use (hours). Results: Among 8836 Veterans, 12% had a history of TBI. TBI history was not associated with PAP adherence when accounting for the presence of insomnia, PTSD, depression, and chronic pain. Indirect effect estimates indicated that a history of mild, moderate-severe, or unclassified TBI was associated with lesser PAP adherence, as mediated by the presence of co-morbid insomnia and chronic pain. Generally, TBI was associated with an increased likelihood of co-morbid insomnia, PTSD, depression, and chronic pain. In turn, insomnia and chronic pain, but not PTSD or depression, were associated with lesser PAP adherence. Conclusions: Our study offers empirical support for insomnia and chronic pain as potential explanatory mechanisms underlying the relationship between TBI history and suboptimal PAP adherence. While additional research is needed to confirm causality, findings offer preliminary evidence that can inform the development of tailored PAP adherence interventions for Veterans with TBI and obstructive sleep apnea.

We aimed to assess the exposure to multiple environmental indicators and compare the spatial variation across participants of the German National Cohort (NAKO) to lay the foundation for health analyses. We collected highly resolved German-wide data to capture the following environmental drivers: urbanisation by population density; outdoor air pollution by particulate matter (PM2.5), nitrogen dioxide (NO2), ozone; road traffic noise; meteorology by air temperature, relative humidity; and the built environment by greenspace and land cover. All assessed exposures were assigned to the NAKO participants based on their baseline residential addresses. The NAKO study regions ranged from highly urbanised areas (Berlin, Hamburg) to rural regions (Neubrandenburg). This large variation is reflected in the individual environmental exposures at the place of residence. In 2019, annual PM2.5 and NO2 levels ranged from 6.0 to 14.6 and 3.7-33.6 mu g/m(3), respectively. Annual mean air temperature ranged between 7.8 and 12.7 degrees C. Noise data was available for a subset of urban residents (22 %), of which 42 % fell into the lowest and 1.8 % into the highest category of Lden 55-59 and Lden >75 dB(A), respectively. Greenspace also showed considerable differences (Normalised Difference Vegetation Index between 0.08 and 0.84). Spearman correlation was moderate to high within the different exposure groups, but mostly low to moderate between the groups. For the first time, a comprehensive population-based dataset with high quality environmental indicators is available for the whole of Germany. Expanding the database by adding innovative indicators such as light pollution, walkability, biodiversity as well as contextual socioeconomic factors will further increase its usefulness for science and public health.

Background Intersectionality has contributed to novel insights in epidemiology. However, participants of epidemiological studies have rarely been characterised from an intersectional perspective. We aimed to show the gained insights of an intersectionality-informed approach to describing a study population by comparing it to a conventional approach. Methods We used data of the German National Cohort (NAKO), which recruited 205,415 participants between 2014 and 2019. In the conventional approach, marginal proportions of educational level, cohabitation status, and country of birth were compared between the study populations of the NAKO and the German census survey (MZ) of 2014. In the intersectionality-informed approach, so-called intersectional population strata were constructed by cross-classifying educational level, cohabitation status, and country of birth. Proportions of these strata were also compared between NAKO and MZ. All analyses were stratified by sex and age group. Results The conventional approach showed that the proportion of people with low education was lower in the NAKO compared to the MZ in all sex and age strata. Similarly, proportions of all intersectional population strata with low education were lower in the NAKO. Concerning cohabitation, the conventional approach showed that the proportion of those living without a partner was lower in the NAKO than in the MZ for women under 60 and men. The intersectionality-informed approach revealed that the proportions of some subgroups of those living without a partner were higher in the NAKO than in the MZ. These were intersectional population strata who lived without a partner, had a high level of education and were born in Germany. The intersectionality-informed approach revealed similar within-group heterogeneity for country of birth, showing that not all proportions of foreign-born people were lower in the NAKO compared to the MZ. Proportions of foreign-born with high education who lived with a partner were higher. Conclusions Our results showed that heterogeneity within social categories can be revealed by applying the concept of intersectionality when comparing study participants with an external population. This way, an intersectionality-informed approach contributes to describing social complexity among study participants more precisely. Furthermore, results can be used to reduce participation barriers in a more targeted way.

Objective: To examine the relationship between neighborhood disadvantage and severity of vestibular, sensory, mood-behavioral, and cognitive neurobehavioral symptoms among Veterans with a mild traumatic brain injury (mTBI); and whether Veterans in underrepresented racial/ethnic groups with high neighborhood disadvantage experience the most severe symptoms. Setting: Outpatient Veterans Health Administration (VHA). Participants: Veterans with the following data available in the electronic health record (2014-2020): (1) clinician-confirmed mTBI and complete neurobehavioral symptom inventory (NSI) as part of their comprehensive traumatic brain injury evaluation (CTBIE) and (2) area deprivation index (ADI) scores assessing neighborhood disadvantage from the same quarter as their CTBIE. Design: Retrospective cohort study. Latent variable regression was used to examine unique and interactive relationships between neighborhood disadvantage, race/ethnicity, and neurobehavioral symptoms. Main Measures: NSI and ADI national percentile rank. Results: The study included 58 698 eligible Veterans. Relative to Veterans in the first quintile of ADI national percentile rank, representing those with the least neighborhood disadvantage, Veterans in the ADI quintiles indicating greater neighborhood disadvantage reported more severe vestibular, sensory, mood-behavioral, and cognitive symptoms. The strongest associations between neighborhood disadvantage and neurobehavioral symptoms were observed within the sensory ( β = 0.07-0.16) and mood-behavioral domains ( β = 0.06-0.15). Statistical interactions indicated that the association between underrepresented racial/ethnic group status (vs. identifying as white, non-Hispanic) and the severity of neurobehavioral symptoms did not differ among those with severe neighborhood disadvantage versus those without. Conclusion: Veterans with mTBI living in more disadvantaged neighborhoods reported more severe neurobehavioral symptoms relative to those in the most advantaged neighborhoods, with the strongest relationships detected within the sensory and mood-behavioral domains. While neighborhood disadvantage and underrepresented race/ethnicity were both independently associated with symptoms, these factors did not interact to produce more severe symptoms. Findings suggest that addressing factors driving socioeconomic disadvantage may assist in mitigating symptoms in this population.

Abstract Background Veterans are at elevated risk for suicide compared to non-Veteran U.S. adults. Data sources and analyses to inform prevention efforts, especially for those who do not use Department of Veterans Affairs (VA) healthcare services, are needed. This study aimed to link VA and CDC’s National Violent Death Reporting System (NVDRS) data to create a novel data source to characterize the circumstances precipitating and preceding suicide among Veterans, including among those who did not use VA healthcare. Methods Multi-variable, multi-stage, deterministic linkage of VA-Department of Defense (DoD) Mortality Data Repository (MDR) and NVDRS-Restricted Access Database suicide and undetermined intent mortality records within 189 state-year strata (42 states, 2012–2018). Three linkage stages: (1) exact (matched on: age, sex, death date, underlying cause of death, day of month of birth, first initial of last name); (2) probable (all but one variable matched); (3) possible (all but 2 variables matched). Linkage success and accuracy of NVDRS-documented military history were assessed. Results Across all state-years, 22,019 matches (89.20% of 24,685 MDR Veteran records) were identified (65.47% exact). When high missingness (2 + matching variables in > 10% of records; n = 23) or incomplete reporting (n = 12) state-years were excluded, match rate increased to 94.29% (77.15% exact). NVDRS-documented military history (ever served) was accurate for 87.79% of matched records, with an overall sensitivity of 84.62%. Sensitivity was lower for female (61.01%) and younger (17–39 years; 77.51%) Veterans. Conclusions Accurate linkage of VA-DoD and NVDRS data is feasible and offers potential to improve understanding of circumstances surrounding suicide among Veterans.