Toward a fine-scale population health monitoring system.

Understanding population health disparities is an essential component of equitable precision health efforts. Epidemiology research often relies on definitions of race and ethnicity, but these population labels may not adequately capture disease burdens and environmental factors impacting specific sub-populations. Here, we propose a framework for repurposing data from electronic health records (EHRs) in concert with genomic data to explore the demographic ties that can impact disease burdens. Using data from a diverse biobank in New York City, we identified 17 communities sharing recent genetic ancestry. We observed 1,177 health outcomes that were statistically associated with a specific group and demonstrated significant differences in the segregation of genetic variants contributing to Mendelian diseases. We also demonstrated that fine-scale population structure can impact the prediction of complex disease risk within groups. This work reinforces the utility of linking genomic data to EHRs and provides a framework toward fine-scale monitoring of population health.

Actionability of unanticipated monogenic disease risks in newborn genomic screening: Findings from the BabySeq Project.

Newborn genomic sequencing (NBSeq) to screen for medically important genetic information is of considerable interest but data characterizing the actionability of such findings, and the downstream medical efforts in response to discovery of unanticipated genetic risk variants, are lacking. From a clinical trial of comprehensive exome sequencing in 127 apparently healthy infants and 32 infants in intensive care, we previously identified 17 infants (10.7%) with unanticipated monogenic disease risks (uMDRs). In this analysis, we assessed actionability for each of these uMDRs with a modified ClinGen actionability semiquantitative metric (CASQM) and created radar plots representing degrees of penetrance of the condition, severity of the condition, effectiveness of intervention, and tolerability of intervention. In addition, we followed each of these infants for 3-5 years after disclosure and tracked the medical actions prompted by these findings. All 17 uMDR findings were scored as moderately or highly actionable on the CASQM (mean 9, range: 7-11 on a 0-12 scale) and several distinctive visual patterns emerged on the radar plots. In three infants, uMDRs revealed unsuspected genetic etiologies for existing phenotypes, and in the remaining 14 infants, uMDRs provided risk stratification for future medical surveillance. In 13 infants, uMDRs prompted screening for at-risk family members, three of whom underwent cancer-risk-reducing surgeries. Although assessments of clinical utility and cost-effectiveness will require larger datasets, these findings suggest that large-scale comprehensive sequencing of newborns will reveal numerous actionable uMDRs and precipitate substantial, and in some cases lifesaving, downstream medical care in newborns and their family members.

Projected Change in the Burden of Excess Cardiovascular Deaths Associated With Extreme Heat by Midcentury (2036-2065) in the Contiguous United States.

BACKGROUND: Climate change is causing an increase in extreme heat. Individuals with cardiovascular disease are at high risk of heat-related adverse health effects. How the burden of extreme heat-associated cardiovascular deaths in the United States will change with the projected rise in extreme heat is unknown. METHODS: We obtained data on cardiovascular deaths among adults and the number of extreme heat days (maximum heat index ≥90 °F [32.2 °C]) in each county in the contiguous United States from 2008 to 2019. Based on representative concentration pathway trajectories that model greenhouse gas emissions and shared socioeconomic pathways (SSP) that model future socioeconomic scenarios and demographic projections, we obtained county-level projected numbers of extreme heat days and populations under 2 scenarios for the midcentury period 2036 to 2065: SSP2-4.5 (representing demographic projections from a "middle-of-the-road" socioeconomic scenario and an intermediate increase in emissions) and SSP5-8.5 (demographic projections in an economy based on "fossil-fueled development" and a large increase in emissions). The association of cardiovascular mortality with extreme heat was estimated with a Poisson fixed-effects model. Using estimates from this model, the projected number of excess cardiovascular deaths associated with extreme heat was calculated. RESULTS: Extreme heat was associated with 1651 (95% CI, 921-2381) excess cardiovascular deaths per year from 2008 to 2019. By midcentury, extreme heat is projected to be associated with 4320 (95% CI, 2369-6272) excess deaths annually, which is an increase of 162% (95% CI, 142-182) under SSP2-4.5, and 5491 (95% CI, 3011-7972) annual excess deaths, which is an increase of 233% (95% CI, 206-259) under SSP5-8.5. Elderly adults are projected to have a 3.5 (95% CI, 3.2-3.8) times greater increase in deaths in the SSP2-4.5 scenario compared with nonelderly adults. Non-Hispanic Black adults are projected to have a 4.6 (95% CI, 2.8-6.4) times greater increase compared with non-Hispanic White adults. The projected change in deaths was not statistically significantly different for other race and ethnicity groups or between men and women. CONCLUSIONS: By midcentury, extreme heat is projected to be associated with a significantly greater burden of excess cardiovascular deaths in the contiguous United States.

Sex Differences in Cardiac Troponin Trajectories Over the Life Course.

BACKGROUND: Cardiac troponin concentrations are lower in women than men. We examined whether age- and risk factor-related changes in cardiac troponin over the life course differ by sex and if the trajectory of cardiac troponin was informative in respect of cardiovascular outcomes in women and men in the general population. METHODS: In the Whitehall II cohort, high-sensitivity cardiac troponin I concentrations were measured on 3 occasions over a 15-year period. Using linear mixed-effects models, the sex-specific trajectories of cardiac troponin were evaluated, and the relationship with conventional cardiovascular risk factors determined. Using multistate joint models, the association between sex-specific trajectories of cardiac troponin and a composite outcome of nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death was evaluated. RESULTS: In 2142 women and 5151 men (mean, 58±7 and 57±7 years of age, respectively), there were 177 (8.3%) and 520 (10.1%) outcome events, respectively, during a median follow-up of 20.9 (25th to 75th percentile, 15.8-21.3) years. Cardiac troponin concentrations were persistently lower in women than in men (median baseline concentration: 2.4 [25th to 75th percentile, 1.7-3.6] ng/L versus 3.7 [25th to 75th percentile, 2.6-5.8] ng/L, respectively, P<0.001), with women exhibiting a relatively larger increase with advancing age as compared with men (Pinteraction<0.001). Apart from age, a significant and divergent interaction with sex was found for the association between cardiac troponin and body mass index (BMI) (Pinteraction=0.008) and diabetes (Pinteraction=0.003). During follow-up, cardiac troponin concentrations were associated to the outcome in both women and men (adjusted hazard ratio per 2-fold difference [95% CI, 1.34 (1.17-1.52) and 1.30 (1.21-1.40), respectively], Pinteraction=0.752). The slope of cardiac troponin was significantly associated with the outcome in women, but not in men (adjusted hazard ratio [95% CI, 2.70 (1.01-7.33) and 1.31 (0.62-2.75), respectively], Pinteraction=0.250). CONCLUSIONS: Trajectories of cardiac troponin differ between women and men in the general population, with differing associations to conventional risk factors and cardiovascular outcomes. Our findings highlight the importance of a sex-specific approach when serial cardiac troponin testing is applied for cardiovascular risk prediction.

More to Offer Than Direct Clinical Benefit: FDA's Vaccine Licensure Process Ignores Population Health and Social Determinants of Disease.

The current US Food and Drug Administration (FDA) licensure process underestimates the potential benefits of vaccines at both the individual and population levels by considering only direct clinical outcomes of vaccination. While all approved vaccines do protect the person who takes them from poor clinical outcomes for a specific infectious disease, many vaccines also have the potential to offer measurable, direct nonclinical benefits. For example, coronavirus disease 2019 (COVID-19) vaccinations for school-aged children may prevent school absenteeism. Also, by preventing infection or reducing its length and severity, some vaccines also protect-to some extent-the patient's immediate contacts from contracting the same disease. These nonclinical and population-level benefits are not considered as part of the FDA's current vaccine approval process, but they could be. We argue that the FDA's structured benefit-risk assessment framework, used for vaccine approvals, can and should consider both clinical and nonclinical benefits of vaccination when sufficient evidence exists to make an informed assessment. Including them could incentivize vaccine developers to measure additional vaccination effects, inform population health, and address health inequalities-including inequalities in the social determinants of health.

Implementation, enrollment, and engagement in an opt-out telehealth pharmacist-assisted tobacco treatment program for patients seen in oncology outpatient clinics.

OBJECTIVE: To describe the workflow, reach, cost, and self-reported quit rates for an opt-out tobacco treatment program (TTP) for patients seen in 43 oncology outpatient clinics. METHODS: Between May 25, 2021, and December 31, 2022, adult patients (≥18 years) visiting clinics affiliated with the Medical University of South Carolina Hollings Cancer Center were screened for smoking status. Those currently smoking were referred to a telehealth pharmacy-assisted TTP. An attempt was made to contact referred patients by phone. Patients reached were offered free smoking cessation counseling and a 2-week starter kit of nicotine replacement medication. A random sample of 420 patients enrolled in the TTP were selected to participate in a telephone survey to assess smoking status 4 to 12 months after enrollment. RESULTS: During the reference period 35,756 patients were screened and 9.3% were identified as currently smoking. Among the 3319 patients referred to the TTP at least once, 2393 (72.1%) were reached by phone, of whom 426 (12.8%) were ineligible for treatment, 458 (13.8%) opted out of treatment, and 1509 (45.5%) received treatment. More than 90% of TTP enrollees smoked daily, with an average of 13.1 cigarettes per day. Follow-up surveys were completed on 167 of 420 patients, of whom 23.4% to 33.5% reported not smoking; if all nonresponders to the survey are counted as smoking, the range of quit rates is 9.3% to 13.3%. CONCLUSION: The findings demonstrate the feasibility of reaching and delivering smoking cessation treatments to patients from a diverse set of geographically dispersed oncology clinics.

Chronic kidney disease: detect, diagnose, disclose-a UK primary care perspective of barriers and enablers to effective kidney care.

Chronic kidney disease (CKD) is a global public health problem with major human and economic consequences. Despite advances in clinical guidelines, classification systems and evidence-based treatments, CKD remains underdiagnosed and undertreated and is predicted to be the fifth leading cause of death globally by 2040. This review aims to identify barriers and enablers to the effective detection, diagnosis, disclosure and management of CKD since the introduction of the Kidney Disease Outcomes Quality Initiative (KDOQI) classification in 2002, advocating for a renewed approach in response to updated Kidney Disease: Improving Global Outcomes (KDIGO) 2024 clinical guidelines. The last two decades of improvements in CKD care in the UK are underpinned by international adoption of the KDIGO classification system, mixed adoption of evidence-based treatments and research informed clinical guidelines and policy. Interpretation of evidence within clinical and academic communities has stimulated significant debate of how best to implement such evidence which has frequently fuelled and frustratingly forestalled progress in CKD care. Key enablers of effective CKD care include clinical classification systems (KDIGO), evidence-based treatments, electronic health record tools, financially incentivised care, medical education and policy changes. Barriers to effective CKD care are extensive; key barriers include clinician concerns regarding overdiagnosis, a lack of financially incentivised care in primary care, complex clinical guidelines, managing CKD in the context of multimorbidity, bureaucratic burden in primary care, underutilisation of sodium-glucose co-transporter-2 inhibitor (SGLT2i) medications, insufficient medical education in CKD, and most recently - a sustained disruption to routine CKD care during and after the COVID-19 pandemic. Future CKD care in UK primary care must be informed by lessons of the last two decades. Making step change, over incremental improvements in CKD care at scale requires a renewed approach that addresses key barriers to detection, diagnosis, disclosure and management across traditional boundaries of healthcare, social care, and public health. Improved coding accuracy in primary care, increased use of SGLT2i medications, and risk-based care offer promising, cost-effective avenues to improve patient and population-level kidney health. Financial incentives generally improve achievement of care quality indicators - a review of financial and non-financial incentives in CKD care is urgently needed.

Climate Change, Landscape Fires, and Human Health: A Global Perspective.

Landscape fires are an integral component of the Earth system and a feature of prehistoric, subsistence, and industrial economies. Specific spatiotemporal patterns of landscape fire occur in different locations around the world, shaped by the interactions between environmental and human drivers of fire activity. Seven distinct types of landscape fire emerge from these interactions: remote area fires, wildfire disasters, savanna fires, Indigenous burning, prescribed burning, agricultural burning, and deforestation fires. All can have substantial impacts on human health and well-being directly and indirectly through (a) exposure to heat flux (e.g., injuries and destructive impacts), (b) emissions (e.g., smoke-related health impacts), and (c) altered ecosystem functioning (e.g., biodiversity, amenity, water quality, and climate impacts). Minimizing the adverse effects of landscape fires on population health requires understanding how human and environmental influences on fire impacts can be modified through interventions targeted at individual, community, and regional levels.

The Economics of Treatment for Depression.

The global prevalence of depression has risen over the past three decades across all socioeconomic groups and geographic regions, with a particularly rapid increase in prevalence among adolescents (aged 12-17 years) in the United States. Depression imposes large health, economic, and societal costs, including reduced life span and quality of life, medical costs, and reduced educational attainment and workplace productivity. A wide range of treatment modalities for depression are available, but socioeconomic disparities in treatment access are driven by treatment costs, lack of culturally tailored options, stigma, and provider shortages, among other barriers. This review highlights the need for comparative research to better understand treatments' relative efficacy, cost-effectiveness, scalability, and potential heterogeneity in efficacy across socioeconomic groups and country and cultural contexts. To address the growing burden of depression, mental health policy could consider reducing restrictions on the supply of providers, implementing digital interventions, reducing stigma, and promoting healthy lifestyles.

Be Well™ Acres Homes: a community-driven, evidence-based approach to reduce health inequities through sustained cross-sector partnership.

PURPOSE: Be Well Communities™ is MD Anderson's signature place-based approach for cancer prevention and control, working with communities to promote wellness and address modifiable risk factors for cancer. The purpose of this paper is to describe implementation of the planning phase of the Be Well Communities model in Acres Homes which began in 2019. METHODS: A community advisory group (Steering Committee) including residents, non-profit organizations, health care partners, city and county agencies, plus other stakeholders, was convened and aligned through a structured process to develop shared goals, foster multisector collaboration, as measured by a stakeholder survey administered twice, and enhance community capacity to improve health outcomes through development of a Community Action Plan. RESULTS: Clear, achievable goals were developed, multisector collaboration was enhanced, and more than 400 h of capacity building support led to a Community Action Plan initially focused on healthy eating and active living, including 15 evidence-based interventions led by 18 organizations. The majority (93%) of the Steering Committee reports that this plan reflects community priorities and will reach the residents most in need. CONCLUSION: By listening and developing trust, the Be Well Communities team successfully worked with Acres Homes residents and organizations to enhance community capacity to address health inequities in one of Houston's most diverse and historic communities.

Development and Optimization of the Veterans Affairs' National Heart Failure Dashboard for Population Health Management.

BACKGROUND: In 2020, the Veterans Affairs (VA) health care system deployed a heart failure (HF) dashboard for use nationally. The initial version was notably imprecise and unreliable for the identification of HF subtypes. We describe the development and subsequent optimization of the VA national HF dashboard. MATERIALS AND METHODS: This study describes the stepwise process for improving the accuracy of the VA national HF dashboard, including defining the initial dashboard, improving case definitions, using natural language processing for patient identification, and incorporating an imaging-quality hierarchy model. Optimization further included evaluating whether to require concurrent ICD-codes for inclusion in the dashboard and assessing various imaging modalities for patient characterization. RESULTS: Through multiple rounds of optimization, the dashboard accuracy (defined as the proportion of true results to the total population) was improved from 54.1% to 89.2% for the identification of HF with reduced ejection fraction (HFrEF) and from 53.9% to 88.0% for the identification of HF with preserved ejection fraction (HFpEF). To align with current guidelines, HF with mildly reduced ejection fraction (HFmrEF) was added to the dashboard output with 88.0% accuracy. CONCLUSIONS: The inclusion of an imaging-quality hierarchy model and natural-language processing algorithm improved the accuracy of the VA national HF dashboard. The revised dashboard informatics algorithm has higher use rates and improved reliability for the health management of the population.

Automated Reminders Enhance Mailed Fecal Immunochemical Test Completion Among Veterans: a Randomized Controlled Trial.

BACKGROUND: The Veterans Affairs (VHA) is working to establish a population-based colorectal cancer screening program for average-risk patients using mailed fecal immunochemical testing (FIT). However, low response rates to mailed FIT may hinder success. Key features of mailed FIT programs, including the use of reminders, differ among various national programs, with limited evidence among veterans. OBJECTIVE: We sought to test whether using reminders, either via telephone call or text message, was effective in improving mailed FIT response rates. DESIGN: We conducted a prospective, randomized quality improvement trial ( ClinicalTrials.gov NCT05012007). Veterans who had not returned a FIT within 2 weeks of receiving the kit were randomized to one of three groups: (1) control (no reminder); (2) an automated telephone call reminder; or (3) an automated text message reminder. PARTICIPANTS: A total of 2658 veterans enrolled at VA Puget Sound Health Care System who were aged 45-75 and had an average risk of colorectal cancer. INTERVENTIONS: A single automated telephone call or text message reminder prompting veterans to return the FIT kit. MAIN MEASURES: Our primary outcome was FIT return at 90 days and our secondary outcome was FIT return at 180 days. KEY RESULTS: Participant average age was 62 years, 88% were men, and 66% White. At 90 days, both the phone and text reminder interventions had higher FIT return rates compared to control (intention-to-treat results (ITT): control 28%, phone 39%, text 38%; p<0.001). At 180 days, FIT kit return remained higher in the reminder interventions (ITT: control 32%, phone 42%, text 40%; p<0.001). CONCLUSIONS: Automated reminders increased colorectal cancer screening completion among average-risk veterans. An automated phone call or text message was equally effective. VHA facilities seeking to implement a mailed FIT program should consider using phone or text reminders, depending on available resources.

Effectiveness of a Population Health Intervention on Disparities in Hypertension Control: A Stepped Wedge Cluster Randomized Clinical Trial.

BACKGROUND: Disparities in hypertension control across race, ethnicity, and language have been a long-standing problem in the United States. OBJECTIVE: To assess whether a multi-pronged intervention can improve hypertension control for a target population and reduce disparities. DESIGN: This stepped wedge cluster randomized trial was conducted at 15 adult primary care clinics affiliated with Massachusetts General Hospital. PCPs were randomized to receive the intervention in twelve groups. PARTICIPANTS: The target population was patients who met one of the following criteria based on self-identification: (1) Asian, Black, Indigenous, multi-racial, or other race; (2) Hispanic ethnicity; or (3) preferred language other than English. Reference population was White, English-speaking patients. INTERVENTIONS: PCPs were given access to an online equity dashboard that displays disparities in chronic disease management and completed an equity huddle with population health coordinators (PHCs), which involved reviewing target patients whose hypertension was not well controlled. In addition, community health workers (CHWs) were available in some practices to offer additional support. MAIN MEASURES: The primary outcome was change in the proportion of target patients meeting the hypertension control goal when comparing intervention and control periods. KEY RESULTS: Of the 365 PCPs who were randomized, 311 PCPs and their 10,865 target patients were included in the analysis. The intervention led to an increase in hypertension control in the target population (RD 0.9%; 95% CI [0.3,1.5]) and there was a higher intervention effect in the target population compared to the reference population (DiD 2.1%; 95% CI [1.1, 3.1]). CONCLUSIONS: Utilizing data on disparities in quality outcome measures in routine clinical practice augmented by clinical support provided by PHCs and CHWs led to modest, but statistically significant, improvement in hypertension control among BIPOC, Hispanic, and LEP patients. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05278806.

Social Phenotyping for Cardiovascular Risk Stratification in Electronic Health Registries.

PURPOSE OF REVIEW: Evaluation of social influences on cardiovascular care requires a comprehensive analysis encompassing economic, societal, and environmental factors. The increased utilization of electronic health registries provides a foundation for social phenotyping, yet standardization in methodology remains lacking. This review aimed to elucidate the primary approaches to social phenotyping for cardiovascular risk stratification through electronic health registries. RECENT FINDINGS: Social phenotyping in the context of cardiovascular risk stratification within electronic health registries can be separated into four principal approaches: place-based metrics, questionnaires, ICD Z-coding, and natural language processing. These methodologies vary in their complexity, advantages and limitations, and intended outcomes. Place-based metrics often rely on geospatial data to infer socioeconomic influences, while questionnaires may directly gather individual-level behavioral and social factors. Z-coding, a relatively new approach, can capture data directly related to social determinant of health domains in the clinical context. Natural language processing has been increasingly utilized to extract social influences from unstructured clinical narratives-offering nuanced insights for risk prediction models. Each method plays an important role in our understanding and approach to using social determinants data for improving population cardiovascular health. These four principal approaches to social phenotyping contribute to a more structured approach to social determinant of health research via electronic health registries, with a focus on cardiovascular risk stratification. Social phenotyping related research should prioritize refining predictive models for cardiovascular diseases and advancing health equity by integrating applied implementation science into public health strategies.

Multisector Collaboration vs. Social Democracy for Addressing Social Determinants of Health.

Policy Points Multisector collaboration, the dominant approach for responding to health harms created by adverse social conditions, involves collaboration among health care insurers, health care systems, and social services organizations. Social democracy, an underused alternative, seeks to use government policy to shape the civil (e.g., civil rights), political (e.g., voting rights), and economic (e.g., labor market institutions, property rights, and the tax-and-transfer system) institutions that produce health. Multisector collaboration may not achieve its goals, both because the collaborations are difficult to accomplish and because it does not seek to transform social conditions, only to mitigate their harms. Social democracy requires political contestation but has greater potential to improve population health and health equity.

Is White Evangelical Antistructural Theology Related to Poor Health Outcomes?

Policy Points White evangelical theology has an "antistructural" component. Counties with a high percentage of White evangelicals have higher mortality rates and more persons with fair/poor health. The potential influence of antistructural components in evangelical theology on decision making and resource allocation and, ultimately, the length and quality of life of community members presents a point of intervention for religious leaders and policymakers to improve population health. CONTEXT: Structural factors are important determinants of health. Because antistructuralism has been identified as a tenet of White evangelical theology, we explored if there is an association of the percentage of White evangelicals in a US county with two county health outcomes: premature mortality and percentage of fair/poor health. METHODS: Regression analysis was performed with data from 2022 County Health Rankings and the American Value Atlas from the Public Religion Research Institute. FINDINGS: Every percent of evangelicals in a county is associated with 4.01 more premature deaths per 100,000 population and 0.13% fair/poor health. After controlling for income, education, political ideology, and county school funding adequacy (a proxy for antistructuralism), the associations remain positive and significant. CONCLUSIONS: We hope these findings could inform dialogue and critical analysis among individuals of evangelical faith, particularly fundamental and Pentecostal subsets, regarding a belief system that is inclusive of individual dimensions and health-promoting structural policies like school funding, Medicaid expansion, and antipoverty programs. These findings also demonstrate the importance of considering cultural factors like religion and political ideology in population health outcomes research.

Prevalence of lifestyle-related behavioral information in claims data in the U.S.

OBJECTIVE: Given their association with varying health risks, lifestyle-related behaviors are essential to consider in population-level disease prevention. Health insurance claims are a key source of information for population health analytics, but the availability of lifestyle information within claims data is unknown. Our goal was to assess the availability and prevalence of data items that describe lifestyle behaviors across several domains within a large U.S. claims database. METHODS: We conducted a retrospective, descriptive analysis to determine the availability of the following claims-derived lifestyle domains: nutrition, eating habits, physical activity, weight status, emotional wellness, sleep, tobacco use, and substance use. To define these domains, we applied a serial review process with three physicians to identify relevant diagnosis and procedure codes within claims for each domain. We used enrollment files and medical claims from a large national U.S. health plan to identify lifestyle relevant codes filed between 2016 and 2020. We calculated the annual prevalence of each claims-derived lifestyle domain and the proportion of patients by count within each domain. RESULTS: Approximately half of all members within the sample had claims information that identified at least one lifestyle domain (2016 = 41.9%; 2017 = 46.1%; 2018 = 49.6%; 2019 = 52.5%; 2020 = 50.6% of patients). Most commonly identified domains were weight status (19.9-30.7% across years), nutrition (13.3-17.8%), and tobacco use (7.9-9.8%). CONCLUSION: Our study demonstrates the feasibility of using claims data to identify key lifestyle behaviors. Additional research is needed to confirm the accuracy and validity of our approach and determine its use in population-level disease prevention.

Population-level changes in perinatal death for pregnancies prior to and during the COVID-19 pandemic: A pregnancy cohort analysis.

BACKGROUND: Results of population-level studies examining the effect of the COVID-19 pandemic on the risks of perinatal death have varied considerably. OBJECTIVES: To explore trends in the risk of perinatal death among pregnancies beginning prior to and during the pandemic using a pregnancy cohort approach. METHODS: This secondary analysis included data from singleton pregnancies ≥20 weeks' gestation in Alberta, Canada, beginning between 5 March 2017 and 4 March 2021. Perinatal death (i.e. stillbirth or neonatal death) was the primary outcome considered. The risk of this outcome was calculated for pregnancies with varying gestational overlap with the pandemic (i.e. none, 0-20 weeks, entire pregnancy). Interrupted time series analysis was used to further determine temporal trends in the outcome by time period of interest. RESULTS: There were 190,853 pregnancies during the analysis period. Overall, the risk of perinatal death decreased with increasing levels of pandemic exposure; this outcome was experienced in 1.0% (95% confidence interval [CI] 0.9, 1.0), 0.9% (95% CI 0.8, 1.1) and 0.8% (95% CI 0.7, 0.9) of pregnancies with no overlap, partial overlap and complete pandemic overlap respectively. Pregnancies beginning during the pandemic that had high antepartum risk scores less frequently led to perinatal death compared to those beginning prior; 3.3% (95% CI 2.7, 3.9) versus 5.7% (95% CI 5.0, 6.5) respectively. Interrupted time-series analysis revealed a decreasing temporal trend in perinatal death for pregnancies beginning ≤40 weeks prior to the start of the COVID-19 pandemic (i.e. with pandemic exposure), with no trend for pregnancies beginning >40 weeks pre-pandemic (i.e. no pandemic exposure). CONCLUSION: We observed a decrease in perinatal death for pregnancies overlapping with the COVID-19 pandemic in Alberta, particularly among those at high risk of these outcomes. Specific pandemic control measures and government response programmes in our setting may have contributed to this finding.

MHQ: constructing an aggregate metric of population mental wellbeing.

BACKGROUND: According to the World Health Organization (WHO), mental health is 'a state of wellbeing in which the individual realizes his or her own abilities, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to his or her community'. Any population metric of mental health and wellbeing should therefore not only reflect the presence or absence of mental challenges but also a person's broad mental capacity and functioning across a range of cognitive, social, emotional and physical dimensions. However, while existing metrics of mental health typically emphasize ill health, existing metrics of wellbeing typically focus on happiness or life satisfaction, indirectly infer wellbeing from a selection of social and economic factors, or do not reflect a read out of the full spectrum of mental functioning that impacts people's everyday life and that spans the continuum from distress and the inability to function, through to the ability to function to one's full potential. METHODS: We present the Mental Health Quotient, or MHQ, a population metric of mental wellbeing that comprehensively captures mental functioning, and examine how it relates to functional productivity. We describe the 47-item assessment and the life impact rating scale on which the MHQ metric is based, as well as the rationale behind each step of the nonlinear algorithm used to construct the MHQ metric. RESULTS: We demonstrate a linear relationship between the MHQ metric and productive life function where movement on the scale from any point or in any direction relates to an equivalent shift in productive ability at the population level, a relationship that is not borne out using simple sum scores. We further show that this relationship is the same across all age groups. Finally, we demonstrate the potential for the types of insights arising from the MHQ metric, offering examples from the Global Mind Project, an initiative that aims to track and understand our evolving mental wellbeing, and since 2020 has collected responses from over 1 million individuals across 140 + countries. CONCLUSION: The MHQ is a metric of mental wellbeing that aligns with the WHO definition and is amenable to large scale population monitoring.

Decomposing the gaps in healthy and unhealthy life expectancies between Indigenous and non-Indigenous Australians: a burden of disease and injury study.

BACKGROUND: The gaps in healthy life expectancy (HLE) between Indigenous and non-Indigenous Australians are significant. Detailed and accurate information is required to develop strategies that will close these health disparities. This paper aims to quantify and compare the causes and their relative contributions to the life expectancy (LE) gaps between the Indigenous and non-Indigenous population in the Northern Territory (NT), Australia. METHODS: The age-cause decomposition was used to analyse the differences in HLE and unhealthy life expectancy (ULE), where LE = HLE + ULE. The data was sourced from the burden of disease and injury study in the NT between 2014 and 2018. RESULTS: In 2014-2018, the HLE at birth in the NT Indigenous population was estimated at 43.3 years in males and 41.4 years in females, 26.5 and 33.5 years shorter than the non-Indigenous population. This gap approximately doubled the LE gap (14.0 years in males, 16.6 years in females) at birth. In contrast to LE and HLE, ULE at birth was longer in the Indigenous than non-Indigenous population. The leading causes of the ULE gap at birth were endocrine conditions (explaining 2.9-4.4 years, 23-26%), followed by mental conditions in males and musculoskeletal conditions in females (1.92 and 1.94 years, 15% and 12% respectively), markedly different from the causes of the LE gap (cardiovascular disease, cancers and unintentional injury). CONCLUSIONS: The ULE estimates offer valuable insights into the patterns of morbidity particularly useful in terms of primary and secondary prevention.