Educational Differences in Self-Rated Health Trends Among Middle-Aged and Older Adults Living Alone, 1972–2018

Objectives: This study examines educational differences in living alone and in self-rated health trends among middle-aged and older adults. Methods: We used logistic regression to analyze data from the 1972–2018 National Health Interview Survey ( n = 795,239 aged 40–64; n = 357,974 aged 65–84). Results: Between 1972–1974 and 2015–2018, living alone became more prevalent, particularly among men and at lower levels of education. Self-rated health trends varied by living arrangement and education. We found self-rated health declines among middle-aged adults having no college degree and living alone, but trends in self-rated health were mostly stable or even improved among middle-aged adults living with others. Among older adults, self-rated health improved over time, but for the least-educated older Americans living alone, the probability of reporting fair or poor health increased between 1972–1974 and 2015–2018. Discussion: The findings suggest growing disparities by social class, in living arrangements and in self-rated health.

Accelerating Digital Health Trends and Transformation through Scientific Communications

The editorial is taken from commentary presented at the ConVerge2Xcelerate (#ConV2X) 2021 Symposium entitled "Blueprint for a New Digital Health Era." Tory Cenaj is the Owner and Publisher of Partners in Digital Health (PDH). The views expressed are solely her own and do not reflect those of the editorial board, reviewers, ambassadors, licensees or staff members affiliated with PDH.

APCDs can Provide Important Insights for Surveilling the Opioid Epidemic, With Caveats

State-level all-payer claims databases (APCDs) are a possible new public health surveillance tool, but their reliability is unclear. We compared Colorado’s APCD with other state-level databases for use in monitoring the opioid epidemic (Colorado Hospital Association and Colorado’s Prescription Drug Monitoring Program database for 2010–2017), using descriptive analyses comparing quarterly counts/rates of opioid-involved inpatient and emergency department visits and counts/rates of 30-day opioid fills between databases. Utilization is lower in the Colorado APCD than the other databases for all outcomes but trends are parallel and consistent between databases. State APCDs hold promise for researchers, but they may be better suited to individual-level analyses or comparisons of providers than for surveillance of public health trends related to addiction.

Community Workforce Differences in Mental Health Across Gender and Job Description in Southwest Indiana

Background and Hypothesis: In May 2020, a community partnership was built in Southwest Indiana to determine the local prevalence of COVID-19 to guide reopening in the region. One year later, a follow-up survey study was launched to address new, pressing questions related to mental health in the community workforce. We hypothesized that adverse mental health symptoms would be disproportionately experienced by specific worker groups based on degree of in-person contact over the past year and demographic characteristics such as age and gender. Methods: For the 2021 survey, participants were invited through their place of employment or via phone to participate in a short online survey consisting of questions related to demographics, general work roles, company policies over the past year, and wellness. When examining mental health, the Patient Health Questionnaire-2 (PHQ-2) and General Anxiety Disorder-2 (GAD-2) were used to determine feelings of depression and anxiety, respectively. Results: 480 participants filled out the 2021 online survey (73% of which were returning). 442 of these responses were complete and eligible for analysis of mental health and degree of in-person contact. 345 responses were complete and eligible for information regarding age. No correlation was found between age and mental health. However, differences were observed based on gender and job description. Women (n=244) and customer-facing employees (n=99) reported more frequent symptoms of anxiety and depression, with customer-facing women reporting the most. Comparing only employees that did not work remotely during the pandemic, customer-facing employees still reported more frequent symptoms of anxiety and depression. Conclusion and Potential Impact: The impacts of COVID-19 on the workforce are still being studied, but the pandemic continues to take its toll. These mental health trends will help guide future policies to support and improve employee wellbeing, both within participating companies and the workforce at large.

A Systematic Review of Interventions That Reduce Family Caregiving Time

Due to multiple long-term sociodemographic and health trends contributing to the impending family care gap, there likely is no single policy or intervention that could increase the number of family caregivers in the U.S. to the levels required to fill such a gap. However, the amount of time that a family caregiver spends providing assistance is potentially mutable. Given the pressing concerns of the family care gap, identifying interventions or approaches that could reduce existing caregiving time is of considerable importance. This presentation provides the results of a systematic review of published research to identify the effects of interventions on the amount of time family caregivers spend on their caregiving tasks. Pharmaceutical approaches directed to care recipients, technology interventions, case management, multicomponent interventions, and care settings all appeared to reduce caregiving time. Improved operationalization, study design, and similar factors will help guide future intervention research to reduce caregiving time.

Death by Robots? Automation and Working-Age Mortality in the United States

The decline of manufacturing employment is frequently invoked as a key cause of worsening U.S. population health trends, including rising mortality due to ‘deaths of despair’. Increasing automation—the use of industrial robots to perform tasks previously done by human workers—is one major structural force driving the decline of manufacturing jobs and wages. In this study we examine the impact of automation on age-sex specific mortality. Using exogenous variation in automation to support causal inference, we find that increases in automation over the period 1993–2007 led to substantive increases in all-cause mortality for both men and women aged 45-54. Disaggregating by cause, we find evidence automation is associated with increases in drug overdose deaths, suicide, homicide and cardiovascular mortality although patterns differ across age-sex groups. We go on to examine heterogeneity in effects by safety net program generosity, labor market policies, and the supply of prescription opioids.

Mental distress among young adults in Great Britain: long-term trends and early changes during the COVID-19 pandemic

Purpose In Great Britain, few studies documented mental health trends in young adults in the years preceding 2020, the mental health dimensions affected, and how these compare with changes observed during the COVID-19 pandemic. Methods Long-term trends in mental health among 16–34 year old men and women between 1991 and 2018, and changes between 2018–19 and July–September 2020 were examined using all waves from the British Household Panel Study (1991–2008), the UK Household Longitudinal Study (2009–20), and the first five UKHLS COVID-19 waves administered in April, May, June, July, and September 2020. Findings are based on the GHQ-12 continuous score (0–36), clinically significant cases (4 + /12) and severe cases (7 + /12) for mental distress, and item endorsements. Results Between 1991 and 2018, the prevalence of cases (4 + /12) increased from 14–22% to 19–32% across groups. Increases were largest in women aged 16–24. In April 2020, the risk of caseness (4 + /12) increased across groups by 55% to 80% compared to the 2018–19 baseline. This increase, however, rapidly diminished over time: in July–September 2020, there was only a higher risk of caseness (4 + /12) in men aged 25–34 (prevalence ratio = 1.29, 95% CI 1.01–1.65) compared to the 2018–19 baseline. Conclusion Whereas distress surged in April 2020, its return to pre-pandemic levels by September 2020 highlights the nuanced impact that the pandemic may have over time. Given the magnitude of the decline in mental health over the past decade, attention must be given to young adults once the pandemic ends.

The State of Health in Belgium, 1990–2019: A Benchmarking Analysis Based on the Global Burden of Disease 2019 Study

BackgroundIn spite of high health expenditures and several reforms, Belgian healthcare system shows unsatisfactory health outcomes. Evidence-based decision-making is essential in a context of decreasing resources and growing health needs. This study aims to assess the health trends in Belgium between 1990 and 2019, to compare the Belgian health status to that of the EU-15 countries, and to identify the main drivers in trends over time and country differences within the EU-15.MethodsWe extracted estimates from the GBD 2019 study via the GBD results tool and visualization tools. We compared the Belgian health status with 14 European Union comparator countries between 1990 and 2019. Results Life expectancy (LE) in Belgium improved significantly between 1900 and 2019 for both men and women. Belgium Age-standardised (AS) mortality dropped significantly for men (-40%) and women (-33%) between 1990 and 2019. Belgium performed significantly better in 2019 than in 1990 in terms of AS Year of Life Lost (YLL) rates. The main contributors to the significant premature mortality decrease were ischemic heart disease, lung cancer and road injuries in men; ischemic heart disease, stroke and breast cancer in women. AS Years lived with disability (YLD) did not significantly differ between 1990 and 2019. Overall, Belgium AS Disability-Adjusted Life Year (DALY) rates dropped by 23%. This decrease is mainly due to decreasing trend in YLL rates while YLDs rates remained stable. Compared to EU-15, Belgium ranking worsened in terms of AS DALY rates for both men and women in 2019. The main contributors for AS DALY rates were ischemic heart disease, lung cancer and self-harm in men; headache disorders, low back pain and gynaecological disorders in women.ConclusionNon-communicable diseases are the main contributors for health burden in Belgium since 1990. Despite the considerable improvement, Belgium’s ranking for DALYs decreased between 1990 and 2019 compared to the EU-15. Primary and secondary prevention could be crucial elements to improve patient health outcomes and reduce their burden on the healthcare system.

Public health surveillance

Public health surveillance provides the epidemiologic foundation for modern public health practice. The ongoing monitoring of disease or health trends within populations informs what public health actions are taken and reflects whether those actions are effective. Surveillance may involve monitoring of diseases and other health-related conditions as well as their antecedents, characteristics, and consequences. Surveillance can guide the local response to individual cases of disease or more broadly inform public health programmes and policies. A key function of surveillance is to identify circumstances that merit further public health scrutiny, such as groups or locations that are disproportionately affected or changes in disease occurrence or severity. General principles that underlie the practice of surveillance are essentially the same for all countries, regardless of economic development. However, in many resource-poor countries, challenges to meeting needs for population health information are heightened and include potential tensions between groups with differing interests. Public health surveillance is conducted in many ways, depending on the nature of the health event under surveillance, the nature of healthcare and information infrastructures, the population involved, resources available, and information needs. The widespread and expanding use of the internet, electronic media, communication technologies, and mobile computing have enabled innovations in public health surveillance that reach far beyond traditional methods. Although surveillance methods were originally developed as part of efforts to control infectious diseases, basic concepts of surveillance have been applied to all areas of public health.

Predicting ICD-9 Codes Using Self-Report of Patients

The International Classification of Diseases (ICD) is a globally recognized medical classification system that aids in the identification of diseases and the regulation of health trends. The ICD framework makes it easy to keep track of records and evaluate medical data for evidence-based decision-making. Several methods have predicted ICD-9 codes based on the discharge summary, clinical notes, and nursing notes. In our study, our approach only utilizes the subjective component to predict ICD-9 codes. Data cleaning and segmentation, and Natural Language Processing (NLP) techniques are applied on the subjective component during the pre-processing. Our study builds the Long Short-Term Memory (LSTM) and the Gated Recurrent Unit (GRU) to develop a model for predicting ICD-9 codes. The ICD-9 codes contain different ICD levels such as chapter, block, three-digit code, and full code. The GRU model scores the highest recall of 57.91% in the chapter level and the top-10 experiment has a recall of 67.37%. Based on the subjective component, the model can help patients in the form of a remote assistance tool.