Population-level Interventions Research Articles

The influence of urban exposures and residence on childhood asthma.

Children with asthma who live in urban neighborhoods experience a disproportionately high asthma burden, with increased incident asthma and increased asthma symptoms, exacerbations, and acute visits and hospitalizations for asthma. There are multiple urban exposures that contribute to pediatric asthma morbidity, including exposure to pest allergens, mold, endotoxin, and indoor and outdoor air pollution. Children living in urban neighborhoods also experience inequities in social determinants of health, such as increased poverty, substandard housing quality, increased rates of obesity, and increased chronic stress. These disparities then in turn can increase the risk of urban exposures and compound asthma morbidity as poor housing repair is a risk factor for pest infestation and mold exposure and poverty is a risk factor for exposure to air pollution. Environmental interventions to reduce in‐home allergen concentrations have yielded inconsistent results. Population‐level interventions including smoking bans in public places and legislation to decrease traffic‐related air pollution have been successful at reducing asthma morbidity and improving lung function growth. Given the interface and synergy between urban exposures and social determinants of health, it is likely population and community‐level changes will be needed to decrease the excess asthma burden in children living in urban neighborhoods.

Understanding the role of urban social and physical environment in opioid overdose events using found geospatial data.

Opioid use disorder is a serious public health crisis in the United States. Manifestations such as opioid overdose events (OOEs) vary within and across communities and there is growing evidence that this variation is partially rooted in community-level social and economic conditions. The lack of high spatial resolution, timely data has hampered research into the associations between OOEs and social and physical environments. We explore the use of non-traditional, "found" geospatial data collected for other purposes as indicators of urban social-environmental conditions and their relationships with OOEs at the neighborhood level. We evaluate the use of Google Street View images and non-emergency "311" service requests, along with US Census data as indicators of social and physical conditions in community neighborhoods. We estimate negative binomial regression models with OOE data from first responders in Columbus, Ohio, USA between January 1, 2016, and December 31, 2017. Higher numbers of OOEs were positively associated with service request indicators of neighborhood physical and social disorder and street view imagery rated as boring or depressing based on a pre-trained random forest regression model. Perceived safety, wealth, and liveliness measures from the street view imagery were negatively associated with risk of an OOE. Age group 50-64 was positively associated with risk of an OOE but age 35-49 was negative. White population, percentage of individuals living in poverty, and percentage of vacant housing units were also found significantly positive however, median income and percentage of people with a bachelor's degree or higher were found negative. Our result shows neighborhood social and physical environment characteristics are associated with likelihood of OOEs. Our study adds to the scientific evidence that the opioid epidemic crisis is partially rooted in social inequality, distress and underinvestment. It also shows the previously underutilized data sources hold promise for providing insights into this complex problem to help inform the development of population-level interventions and harm reduction policies.

Self-Efficacy and Willingness to Implement Narrative Communication Interventions: Mixed Methods Study Among Breast Cancer Patients and Survivors at the University College Hospital, Ibadan, Nigeria

PURPOSE Globally, black women experience poorer breast cancer (BC) outcomes suggesting the need for effective health promotion approaches to increase perceived severity and improve screening practices for early detection. Although, narrative communication by patients or survivors are increasingly considered an effective approach for better BC outcomes, there is limited information on its use in Nigeria. This study assessed the self-efficacy and willingness of BC patients and survivors at the University College Hospital, Ibadan to implement narrative communication interventions. METHODS This study utilized a mixed-method convergent parallel design. Five patients were recruited for in-depth interviews (IDI). A semi-structured questionnaire was used to collect data from 102 patients on perception and the generalized self-efficacy to implement narrative communication interventions. Data were analyzed using thematic analysis for qualitative and descriptive and inferential statistics for quantitative data. RESULTS Mean age of the respondents was 49.3 ± 10.2 years. Over three quarters (79.4%) of respondents had good self-efficacy to implement narrative communication. Majority of respondents (87.3%) were willing to share lived experiences during narrative communication interventions. Over 90% (94.1%) agreed that health programs on BC anchored by patients and survivors will enable individuals make healthy decisions than interactions with clinicians only. Respondents' educational attainment was significantly associated with perception and self-efficacy to implement narrative communication intervention programs ( P < .05). Patients opined that a pre-diagnosis discussion with a BC patient or survivor would have increased their perceived severity and susceptibility. CONCLUSION This study highlights the potentials of BC patients and survivors as breast health educators sharing their lived experiences to empower and motivate women to act on health information on BC prevention and screening. Findings could guide the design of population-level interventions on BC prevention and screening.

Estimating the healthcare cost of overweight and obesity in South Africa

ABSTRACT Background Overweight and obesity are major risk factors for noncommunicable diseases. This presents a major burden to health systems and to society in South Africa. Collectively, these conditions are overwhelming public healthcare. This is happening when the country has embarked on a journey to universal health coverage, hence the need to estimate the cost of overweight and obesity. Objective Our objective was to estimate the healthcare cost associated with treatment of weight-related conditions from the perspective of the South African public sector payer. Methods Using a bottom-up gross costing approach, this study draws data from multiple sources to estimate the direct healthcare cost of overweight and obesity in South Africa. Population Attributable Fractions (PAF) were calculated and multiplied by each disease’s total treatment cost to apportion costs to overweight and obesity. Annual costs were estimated for 2020. Results The total cost of overweight and obesity is estimated to be ZAR33,194 million in 2020. This represents 15.38% of government health expenditure and is equivalent to 0.67% of GDP. Annual per person cost of overweight and obesity is ZAR2,769. The overweight and obesity cost is disaggregated as follows: cancers (ZAR352 million), cardiovascular diseases (ZAR8,874 million), diabetes (ZAR19,861 million), musculoskeletal disorders (ZAR3,353 million), respiratory diseases (ZAR360 million) and digestive diseases (ZAR395 million). Sensitivity analyses show that the total overweight and obesity cost is between ZAR30,369 million and ZAR36,207 million. Conclusion This analysis has demonstrated that overweight and obesity impose a huge financial burden on the public health care system in South Africa. It suggests an urgent need for preventive, population-level interventions to reduce overweight and obesity rates. The reduction will lower the incidence, prevalence, and healthcare spending on noncommunicable diseases.

Individualized Biological Age as a Predictor of Disease: Korean Genome and Epidemiology Study (KoGES) Cohort.

Chronological age (CA) predicts health status but its impact on health varies with anthropometry, socioeconomic status (SES), and lifestyle behaviors. Biological age (BA) is, therefore, considered a more precise predictor of health status. We aimed to develop a BA prediction model from self-assessed risk factors and validate it as an indicator for predicting the risk of chronic disease. A total of 101,980 healthy participants from the Korean Genome and Epidemiology Study were included in this study. BA was computed based on body measurements, SES, lifestyle behaviors, and presence of comorbidities using elastic net regression analysis. The effects of BA on diabetes mellitus (DM), hypertension (HT), combination of DM and HT, and chronic kidney disease were analyzed using Cox proportional hazards regression. A younger BA was associated with a lower risk of DM (HR = 0.63, 95% CI: 0.55–0.72), hypertension (HR = 0.74, 95% CI: 0.68–0.81), and combination of DM and HT (HR = 0.65, 95% CI: 0.47–0.91). The largest risk of disease was seen in those with a BA higher than their CA. A consistent association was also observed within the 5-year follow-up. BA, therefore, is an effective tool for detecting high-risk groups and preventing further risk of chronic diseases through individual and population-level interventions.

Calcium deficiency worldwide: prevalence of inadequate intakes and associated health outcomes.

Dietary calcium deficiency is considered to be widespread globally, with published estimates suggesting that approximately half of the world's population has inadequate access to dietary calcium. Calcium is essential for bone health, but inadequate intakes have also been linked to other health outcomes, including pregnancy complications, cancers, and cardiovascular disease. Populations in low‐ and middle‐income countries (LMICs) are at greatest risk of low calcium intakes, although many individuals in high‐income countries (HICs) also do not meet recommendations. Paradoxically, many LMICs with lower calcium intakes show lower rates of osteoporotic fracture as compared with HICs, though data are sparse. Calcium intake recommendations vary across agencies and may need to be customized based on other dietary factors, health‐related behaviors, or the risk of calcium‐related health outcomes. The lack of standard methods to assess the calcium status of an individual or population has challenged efforts to estimate the prevalence of calcium deficiency and the global burden of related adverse health consequences. This paper aims to consolidate available evidence related to the global prevalence of inadequate calcium intakes and associated health outcomes, with the goal of providing a foundation for developing policies and population‐level interventions to safely improve calcium intake and status where necessary.

Developing Ghana’s first Food-based dietary guidelines: An evidence-informed process

Globally, sub-optimal diets across the entire lifecycle have been identified as an important driver of malnutrition in all its forms (global panel, Global burden of disease). The 2020 Global nutrition indicates that several countries on the African continent are off course in their efforts to address malnutrition in all its forms. Food-based dietary guidelines (FBDGs) have been recommended as a necessary public health tool for creating awareness and promoting the consumption of optimal diets. Evidence-informed FBDGs can serve as a communication tool for enabling healthier dietary and lifestyle choices among the lay population. They can also be used by governments and other institutional actors as a policy tool for population-level interventions that improve the nutrition-sensitivity of food systems as well as food environments.

Prevalence and Risk Factors of High-Risk Population for Stroke: A Population-Based Cross-Sectional Survey in Southwestern China

With the aging of the population and the change of lifestyle in China, the prevalence and risk factors of the high-risk population for stroke may change. However, few studies performed community-based high-risk stroke population surveys in China. Hence, we performed this multicenter, cross-sectional, and community-based survey in Sichuan of southwestern China, according to the China National Stroke Screening Survey (CNSSS) program in 2015. The residents aged ≥ 40 years volunteered to participate in the face-to-face survey in 8 communities in Sichuan. The 8 communities were selected using the cluster randomization method. Subjects with at least three of the eight stroke-related risk factors were classified as a high-risk population for stroke. Otherwise were classified as a low-risk population for stroke. Furthermore, 1,011 individuals were randomly selected among the low-risk population for stroke as controls. Among 16,892 participants, 2,369 (14.0%) were high-risk population for stroke. After full adjustments, all eight risk factors for stroke were significantly associated with the high-risk population for stroke (P < 0.001). The largest contributor was hypertension [population-attributable risk (PAR) 28.4%], followed by physical inactivity (PAR 14.2%), dyslipidemia (PAR 11.2%), overweight/obesity (PAR 9.4%), diabetes (PAR 7.2%), family history (PAR 6.8%), smoking (PAR 5.9%), and atrial fibrillation (PAR 3.5%). Carotid atherosclerosis was more serious in the high-risk population for stroke than in controls (P < 0.05). The prevalence of the high-risk population for stroke was high in southwestern China. Hypertension, physical inactivity, and dyslipidemia were stronger contributors for the high-risk population for stroke. Individual-level and population-level interventions for these leading risk factors are very important for the primary prevention of stroke.

Abstract P173: Sex Differences In Risk Factors For Cardiovascular Disease Mortality Among US Women And Men

Ling Tian, Amanda H. Anderson, Kirsten S. Dorans, Marie A. Krousel-wood, Joshua D. Bundy Introduction: Previous studies suggest cardiovascular disease (CVD) risk factors differ among women compared with men. Quantifying sex differences in the associations of risk factors for CVD mortality in US nationally representative data could aid researchers and clinicians in improving the efficiency of primordial prevention of CVD. Hypothesis: Associations of systolic blood pressure (SBP), total cholesterol, glycated hemoglobin (HbA1c), body mass index (BMI), current smoking, and predicted 10-year risk of atherosclerotic CVD with CVD mortality differ among women compared with men, and these sex differences are modified by age. Methods: Data from non-pregnant and non-breastfeeding participants aged ≥40 years from the National Health and Nutrition Examination Survey (NHANES) 1999-2006, linked to the National Death Index through December 31, 2015, were analyzed. Multivariable-adjusted Cox proportional hazards regression was used to estimate hazard ratios (95% confidence intervals) for CVD mortality. Interaction terms were used to model associations by age (40-49, 50-59, and ≥60 years) and sex (women and men) subgroups. Results: 9,486 participants (mean age, 57.7; 51.9% women) were included in the current analysis. During an average 12.3-year follow-up, we observed 807 (8.5%) CVD deaths (328 in women; 479 in men). Associations of risk factors with CVD mortality were similar among women compared with men, although they were attenuated with increasing age (Figure). Conclusions: Among both US women and men, higher levels of SBP, smoking, and predicted 10-year ASCVD risk are strongly associated with higher risk of CVD mortality. Population-level interventions targeting these risk factors as early as possible in US men and women could reduce the burden of CVD.

Impact of weather and pollution on the rate of cerebrovascular events in a large metropolitan area.

Despite mounting evidence, there is uncertainty on the impact of the interplay between weather and pollution features on the risk of acute cerebrovascular events (CVE). We aimed at appraising role of weather and pollution on the daily risk of CVE. Anonymized data from a hub CVE center in a large metropolitan area were collected and analyzed according to weather (temperature, pressure, humidity, and rainfall) and pollution (carbon monoxide [CO], nitrogen dioxide [NO2], nitrogen oxides [NOX], ozone [O3], and particulate matter [PM]) on the same and the preceding days. Poisson regression and time series analyses were used to appraise the association between environmental features and daily CVE, distinguishing also several subtypes of events. We included a total of 2534 days, with 1363 days having ≥1 CVE, from 2012 to 2017. Average daily rate was 1.56 (95% confidence interval: 1.49; 1.63) for CVE, with other event rates ranging between 1.42 for stroke and 0.01 for ruptured intracranial aneurysm. Significant associations were found between CVE and temperature, pressure, CO, NO2, NOX, O3, and PM <10 µm (all P<0.05), whereas less stringent associations were found for humidity, rainfall, and PM <2.5 µm. Time series analysis exploring lag suggested that associations were stronger at same-day analysis (lag 0), but even environmental features predating several days or weeks were significantly associated with events. Multivariable analysis suggested that CO (point estimate 1.362 [1.011; 1.836], P=0.042) and NO2 (1.011 [1.005; 1.016], P<0.001) were the strongest independent predictors of CVE. Environmental features are significantly associated with CVE, even several days before the actual event. Levels of CO and NO2 can be potentially leveraged for population-level interventions to reduce the burden of CVE.

Real-Time Forecasting of COVID-19 Cases Using Human Mobility in Ontario, Canada

PurposeTo minimize the impact of the COVID-19 pandemic, local public health authorities are often required to make prompt and informed decisions on anticipated case-loads, resource allocation for surveillance and testing, and public health intervention appropriateness. The objective of this research was to develop a near-term forecasting model to predict COVID-19 cases using real-time human mobility information in Ontario, Canada to assist public health authorities with outbreak response.Methods & MaterialsWe utilized a deep neural network model to generate a short-term forecast of new COVID-19 cases by two weeks from May to August 2021. Variable selection was informed by a recent literature review and our ongoing research associating COVID-19 cases with human mobility, demographic and socio-economic factors. A real-time human mobility statistics consisting of a weekly summary of short and long-distance movement, demographic characteristics, weather, vaccination coverage, geo-location, and reported COVID-19 cases two weeks prior were included as predictors. We considered weeks as temporal and health regions as geographic units to account for population-level variabilities. We used a holdout method for model validation of over 300 iterations. Average mean squared error (MSE) and 95% confidence interval (CI) along with overlaying forecasted COVID-19 cases over the reported were used to evaluate the overall model fit. The model predictions were summarized as means and 95% CIs.ResultsOur best forecasting model had a mean MSE of 0.53 (95% CI: 0.49 – 0.56). Since May 2021, the overall trend of the reported COVID-19 cases in Ontario closely followed the forecasted cases, about 89% of the reported cases were within 1.5 times the interquartile range (IQR) and all were within the entire range of the distribution of the predictions. Forecasting accuracy also varied by health region characteristics, such a population size and density, remoteness, and reported COVID-19 case volume during the most recent weeks.ConclusionA near-term prediction of new COVID-19 cases with real-time population-level data could help public health authorities anticipate, plan and monitor disease burden in a population. Such predictions also allow the assessment of population-level health interventions to minimize new COVID-19 cases on a real-time basis and inform prompt decision making.

A Population Health Approach to Transplant Access: Challenging the Status Quo

Transplant referral and evaluation are critical steps to waitlisting yet remain an elusive part of the transplant process. Despite calls for more data collection on pre-waitlisting steps, there are currently no national surveillance data to aid in understanding the causes and potential solutions for the extreme variation in access to transplantation. As population health scientists, epidemiologists, clinicians, and ethicists we submit that the transplant community has an obligation to better understand disparities in transplant access as a first necessary step to effectively mitigating these inequities. Our position is grounded in a population health approach, consistent with several new overarching national policy and quality initiatives. The purpose of this Perspective is to (1) provide an overview of how a population health approach should inform current multisystem policies impacting kidney transplantation and demonstrate how these efforts could be enhanced with national data collection on pre-waitlisting steps; (2) demonstrate the feasibility and concrete next steps for pre-waitlisting data collection; and (3) identify potential opportunities to use these data to implement effective population-level interventions, policies, and quality measures to improve equity in access to kidney transplantation.

Prevalence, Deaths and Disability-Adjusted-Life-Years (DALYs) Due to Type 2 Diabetes and Its Attributable Risk Factors in 204 Countries and Territories, 1990-2019: Results From the Global Burden of Disease Study 2019.

AimTo report the point prevalence, deaths and disability-adjusted-life-years (DALYs) due to type 2 diabetes and its attributable risk factors in 204 countries and territories during the period 1990-2019.MethodsWe used the data of the Global Burden of Disease (GBD) Study 2019 to report number and age-standardised rates per 100 000 population of type 2 diabetes. Estimates were reported with 95% uncertainty intervals (UIs).ResultsIn 2019, the global age-standardised point prevalence and death rates for type 2 diabetes were 5282.9 and 18.5 per 100 000, an increase of 49% and 10.8%, respectively, since 1990. Moreover, the global age-standardised DALY rate in 2019 was 801.5 per 100 000, an increase of 27.6% since 1990. In 2019, the global point prevalence of type 2 diabetes was slightly higher in males and increased with age up to the 75-79 age group, decreasing across the remaining age groups. American Samoa [19876.8] had the highest age-standardised point prevalence rates of type 2 diabetes in 2019. Generally, the burden of type 2 diabetes decreased with increasing SDI (Socio-demographic Index). Globally, high body mass index [51.9%], ambient particulate matter pollution [13.6%] and smoking [9.9%] had the three highest proportions of attributable DALYs.ConclusionLow and middle-income countries have the highest burden and greater investment in type 2 diabetes prevention is needed. In addition, accurate data on type 2 diabetes needs to be collected by the health systems of all countries to allow better monitoring and evaluation of population-level interventions.

Cognitive Reserve and Mild Cognitive Impairment: Predictors and Rates of Reversion to Intact Cognition vs Progression to Dementia.

Background and ObjectivesLittle is known about the effect of education or other indicators of cognitive reserve on the rate of reversion from mild cognitive impairment (MCI) to normal cognition (NC) or the relative rate (RR) of reversion from MCI to NC vs progression from MCI to dementia. Our objectives were to (1) estimate transition rates from MCI to NC and dementia and (2) determine the effect of age, APOE, and indicators of cognitive reserve on the RR of reversion vs progression using multistate Markov modeling.MethodsWe estimated instantaneous transition rates between NC, MCI, and dementia after accounting for transition to death across up to 12 assessments in the Nun Study, a cohort study of religious sisters aged 75+ years. We estimated RRs of reversion vs progression for age, APOE, and potential cognitive reserve indicators: education, academic performance (high school grades), and written language skills (idea density, grammatical complexity).ResultsOf the 619 participants, 472 were assessed with MCI during the study period. Of these 472, 143 (30.3%) experienced at least one reverse transition to NC, and 120 of the 143 (83.9%) never developed dementia (mean follow-up = 8.6 years). In models adjusted for age group and APOE, higher levels of education more than doubled the RR ratio of reversion vs progression. Novel cognitive reserve indicators were significantly associated with a higher adjusted RR of reversion vs progression (higher vs lower levels for English grades: RR ratio = 1.83; idea density: RR ratio = 3.93; and grammatical complexity: RR ratio = 5.78).DiscussionKnowledge of frequent reversion from MCI to NC may alleviate concerns of inevitable cognitive decline in those with MCI. Identification of characteristics predicting the rate of reversion from MCI to NC vs progression from MCI to dementia may guide population-level interventions targeting these characteristics to prevent or postpone MCI and dementia. Research on cognitive trajectories would benefit from incorporating predictors of reverse transitions and competing events, such as death, into statistical modeling. These results may inform the design and interpretation of MCI clinical trials, given that a substantial proportion of participants may experience improvement without intervention.

Valuing the cross-sector benefits from improving youth health to drive investment in place-based preventive interventions in the US: A simulation modeling study

Healthcare payment reform has not produced incentives for investing in place-based, or population-level, upstream preventive interventions. This article uses economic modeling to estimate the long-term benefits to different sectors associated with improvements in population health indicators in childhood. This information can motivate policymakers to invest in prevention and provide guidance for cross-sector contracting to align incentives for implementing place-based preventive interventions. A benefit-cost model developed by the Washington State Institute for Public Policy was used to estimate total and sector-specific benefits expected from improvements to nine different population health indicators at ages 17 and 18. The magnitudes of improvement used in the model were comparable to those that could be achieved by high-quality implementation of evidence-based population-level preventive interventions. Benefits accruing throughout the lifecycle and over a ten-year time horizon were modelled. Intervention effect sizes of 0.10 and 0.20 demonstrated substantial long-term benefits for eight of the nine outcomes measured. At an effect size of 0.10, the median lifecycle benefit per participant across the ten indicators was $3080 (ranged: $93 to $14,220). The median over a 10-year time horizon was $242 (range: $14 to $1357). Benefits at effect sizes of 0.20 were approximately double. Policymakers may be able to build will for additional investment based on these cross-sector returns and communities may be able to capture these cross-sector benefits through contracting to better align incentives for implementing and sustaining place-based preventive interventions.

Evidence of the impact of a national anti-tobacco prevention campaign across demographic subgroups.

Mass media campaigns are an effective population-level intervention for preventing tobacco use. However, little evidence exists for whether these campaigns similarly influence demographic subgroups. This study examined the effects of the truth® campaign to reduce tobacco use among demographic subgroups. We used data from a national, continuous, cross-sectional tracking survey of 15-24-year-olds (n = 32 331). We used a measure of weekly aggregated campaign exposure to assess whether cigarette smoking intentions and current cigarette use varied by race/ethnicity, financial situation and population density subgroups, controlling for factors known to be associated with tobacco use. Examining estimates across subgroup categories in light of the overall model estimates revealed that the effects of week-level campaign exposure on cigarette smoking intentions and current cigarette use were similar across subgroups. Wald tests of equality across estimates in each subgroup suggested that the estimates did not differ from one another in any given instance. The truth campaign does not differ significantly in its capacity to prompt declines in tobacco use across a broad spectrum of US youth and young adults. Mass media tobacco prevention campaigns can be an effective and critical component of a comprehensive tobacco control program, particularly with respect to reducing tobacco-related disparities among demographic subgroups.

A picture of health: determining the core population served by an urban NHS hospital trust and understanding the key health needs

BackgroundNHS hospitals do not have clearly defined geographic populations to whom they provide care, with patients able to attend any hospital. Identifying a core population for a hospital trust, particularly those in urban areas where there are multiple providers and high population churn, is essential to understanding local key health needs especially given the move to integrated care systems. This can enable effective planning and delivery of preventive interventions and community engagement, rather than simply treating those presenting to services. In this article we describe a practical method for identifying a hospital’s catchment population based on where potential patients are most likely to reside, and describe that population’s size, demographic and social profile, and the key health needs.MethodsA 30% proportional flow method was used to identify a catchment population using an acute hospital trust in West London as an example. Records of all hospital attendances between 1st April 2017 and 31st March 2018 were analysed using Hospital Episode Statistics. Any Lower Layer Super Output Areas where 30% or more of residents who attended any hospital for care did so at the example trust were assigned to the catchment area. Publicly available local and national datasets were then applied to identify and describe the population’s key health needs.ResultsA catchment comprising 617,709 people, of an equal gender-split (50.4% male) and predominantly working age (15 to 64 years) population was identified. Thirty nine point six percent of residents identified as being from Black and Minority Ethnic (BAME) groups, a similar proportion that reported being born abroad, with over 85 languages spoken. Health indicators were estimated, including: a healthy life expectancy difference of over twenty years; bowel cancer screening coverage of 48.8%; chlamydia diagnosis rates of 2,136 per 100,000; prevalence of visible dental decay among five-year-olds of 27.9%.ConclusionsWe define a blueprint by which a catchment can be defined for a hospital trust and demonstrate the value a hospital-view of the local population could provide in understanding local health needs and enabling population-level health improvement interventions. While an individual approach allows tailoring to local context and need, there could be an efficiency saving were such public health information made routinely and regularly available for every NHS hospital.

Harnessing the Potential of Primary Care Pharmacists to Improve Heart Failure Management.

Improved utilization of guideline-directed medical therapy (GDMT) in the management of heart failure with reduced ejection fraction (HFrEF) can reduce mortality, reduce heart failure hospitalizations, and improve quality of life. Despite well-established clinical guidelines, these therapies remain significantly underprescribed. The goal of this intervention was to increase prescribing of angiotensin-converting enzyme inhibitor (ACEI)/angiotensin II receptor blocker (ARB), angiotensin receptor neprilysin inhibitor (ARNI), and beta-blockers at ≥50% target doses. The study team identified key drivers to adequate dosing of GDMT: (1) frequent and reliable follow-up visits for titration opportunities, (2) identification of actionable patients for therapy initiation and titration, and (3) reduction in prescribing practice variability. The interventions were implemented at an outpatient clinical site and consisted of three main components: (1) establishing a pharmacist-led heart failure medication titration clinic, (2) creation of a standardized titration protocol, and (3) utilization of a patient dashboard to identify eligible patients. For patients seen in the titration clinic, in 14 months, the mean dose per patient increased from 31.3% to 70.5% of target dose for ACEI/ARB/ARNI, and from 45.8% to 85.4% for beta-blockers. At this clinical site, the percentage of HFrEF patients receiving >50% of targeted dose increased from 39.7% to 46.7% for ACEI/ARB/ARNI, and from 39.5% to 42.9% for beta-blockers. For ACEI/ARB/ARNI, use of target doses was 5.9% higher (95% confidence interval [CI] = 3.6%-8.3%, p < 0.0001) for the intervention site, 0.2% higher (95% CI = -2.2%-2.5%, p = 0.89) during the intervention period, and 10.4% higher (95% CI = 6.9%-13.9%, p <0.0001) for the interaction (intervention site during the intervention time period). For beta-blockers, use of target doses was 1.0% higher (95% CI = -0.6%-2.6%, p = 0.20) for the intervention site, 0.8% lower (95% CI = -2.4%-0.8%, p = 0.29) for the intervention period, and 5.8% higher (95% CI = 3.5%-8.1%, p < 0.0001) for the interaction (intervention site during the intervention time period). Through this project's interventions, the prescribing of ACEI/ARB/ARNI and beta-blocker therapy at ≥50% target doses for patients with HFrEF was increased. This study demonstrates the value of a multifaceted, team-based approach that integrates population-level interventions such as clinical dashboard management with a pharmacist-led heart failure medication titration clinic.

Blood lead levels among Broken Hill children born 2009-2015: a longitudinal study to inform prevention strategies.

To describe blood lead levels (BLLs) and their distribution among children in Broken Hill, New South Wales (NSW), at each of the scheduled testing points aligned with childhood immunisation and to determine how BLLs change over time for individual children. These data can inform action to prevent future lead exposure in Broken Hill children. Retrospective longitudinal study. Data were extracted from the Lead Management Program ACCESS database on children born between 2009 and 2015 and living in Broken Hill. BLLs were calculated using capillary blood collected via finger prick, classified according to specific blood lead thresholds and grouped according to the testing schedule. A subset of children tested at each of the first three annual testing points provided data to determine the blood lead trajectories for individual Broken Hill children. Data were analysed using SPSS and ArcGIS. At the first test at 12 months, around half the children recorded a BLL of <5 µg/dL, one in three had a BLL of 5-9 µg/dL and one in five had a BLL of ≥10 µg/dL. A similar pattern was observed for subsequent test points at 18 months, 2 years, 3 years and 4 years. Of the 336 children who had results recorded at each of the 12-month, 2-year and 3-year test points, BLLs in around one-third remained below the recommended threshold of 5 µg/dL. Another one-third of these children had at least one test result ≥10 µg/dL, and the BLL in the remainder did not exceed 5-9 µg/dL at any of the test points. The geospatial distribution of children with very high BLLs shows clustering of these children in some localities, as well as their widespread distribution throughout Broken Hill. It should be possible to keep BLLs below 5 µg/dL for the majority of young children in Broken Hill throughout their preschool years. This could be achieved by an integrated prevention strategy that includes population-level interventions such as targeted zonal remediation for high-risk areas and early intervention for individuals during the first 12 months and beyond, particularly for those who may not benefit directly from targeted zonal remediation. Routinely collected data could be used to guide the development, and monitor the effectiveness, of these interventions.

An Evaluation of Social Bridging and Bonding Mechanisms in the Association of Social Networks and Cognitive Function

Widowhood is associated with decreased emotional well-being, particularly increased depression. Religiosity may help improve mental health among widowed individuals. However, longitudinal studies exploring the role of religiosity on emotional well-being among widowed older adults is lacking, as are studies which examine this relationship using different dimensions of religiosity. This study analyzed data from the 2006-2016 waves of the nationally representative Health and Retirement Study (HRS). Trajectories of depression among older adults >50 years (N=5,486) were examined to explore patterns of depression among those entering widowhood and the potential impact of religiosity on depressive symptoms during widowhood. Ordinary least squares (OLS) regression analysis was used to examine the association between widowhood and depression as well as the role of religiosity as a moderator of this association. Older adults experienced an increase in depressive symptomology after the onset of widowhood, and although the levels of depressive symptomology decrease post-widowhood, they do not return to their pre-widowhood levels. Additionally, high religious service attendance and higher intrinsic religiosity were both associated with lower depressive symptomology. High religious service attendance moderated the relationship between widowhood and depression. The relationship between high religious service attendance and depression was stronger among widowed older adults living alone. This study highlights the long-term effects of widowhood on depressive symptomology among older adults. The findings also suggest that higher religious service attendance can lessen the effects of widowhood on depressive symptoms, especially for those living alone. These findings may inform intervention development around increased screening and treatment for depression.