National Center For Health Statistics Research Articles

Addressing the Maternal Mental Health Crisis Through a Novel Tech-Enabled Peer-to-Peer Driven Perinatal Collaborative Care Model

Addressing the Maternal Mental Health Crisis Through a Novel Tech-Enabled Peer-to-Peer Driven Perinatal Collaborative Care Model

Forced intercourse in America: a pandemic update

BackgroundMeasures of forced intercourse from the U.S. National Center for Health Statistics (NCHS) indicate high prevalence among U.S. women, which is likely to produce unintended pregnancies. However, NCHS did not measure forced intercourse during the pandemic, limiting knowledge of recent prevalence rates.MethodsWe use multiple nationally-representative, cross-sectional surveys representing the U.S. population from 2011 to 2022 to document these trends. This includes measures from the National Survey of Family Growth, the Panel Study of Income Dynamics Transition into Adulthood Supplement, and the American Family Health Study (AFHS) to provide population estimates of forced intercourse.ResultsReports of forced intercourse remained high during the pandemic, with more than 25% of U.S. females over 40 reporting lifetime forced intercourse in the AFHS (number of females in AFHS: 1,042). There was a significant increase among females aged 24–28 (p < 0.05) and rates are highest for those who did not complete college. Among females 24–28, 32.5% (S.E. = 5.7%) with less than 4 years of college reported forced intercourse, a significantly (p < 0.05) higher rate than among those with a higher level of education.ConclusionsRates of forced intercourse among U.S. women remained high during the pandemic, increasing significantly in early adulthood. This exposure to forced intercourse is likely to produce an increase in unintended pregnancies and other sexual, reproductive, and mental health problems.

SA42 Innovative Methods for Integrating Social Determinants of Health Data with Administrative Claims to Facilitate Health Equity Research

The Covid-19 pandemic highlighted the importance of considering Social Determinants of Health (SDoH) in healthcare research. Administrative claims databases are widely used for research, but often lack SDoH data or sufficient transparency in how these data were obtained. This study describes innovative methods for integrating SDoH data with administrative claims to facilitate health equity research. The HealthCore Integrated Research Database (HIRD) contains medical and pharmacy claims from a large, national US payer starting in 2006 and includes commercial (Comm), Medicare Advantage (MCare), and Medicaid (MCaid) populations. The HIRD includes individually identifiable information, which was used for linking with SDoH data from the following sources: national neighborhood-level data from the American Community Survey, the Food Access Research Atlas, and the National Center for Health Statistics’ urbanicity classification; and member-level data on race/ethnicity from enrollment files, medical records, self-attestation, and imputation algorithms. We examined SDoH metrics for members enrolled as of 05-July-2022 and compared them to the respective US national data using descriptive statistics. We also examined telehealth utilization in 2022. SDoH data were available for ∼95% of currently active members in the HIRD (Comm/MCare/MCaid 12.5m/1m/7.6m). Socioeconomic characteristics at the neighborhood-level differed by membership type and vs. national data: % of members with at least a high-school education (90/88/84 vs. 87); median family income ($98k/$76k/$70k vs. $82k); % of members living in low-income low-food-access tracts (9/14/18 vs. 13); urban (57/52/47 vs. 61). At the member-level, the % of White Non-Hispanics, Black Non-Hispanics, Asian Non-Hispanics, and Hispanics were 61/6/5/6 (Comm), 76/12/2/2 (MCare), and 45/26/5/19 (MCaid). Imputation contributed 15-60% of race/ethnicity values across membership types. Telehealth utilization increased with socioeconomic status. We successfully integrated SDoH data from a variety of sources with administrative claims. SDoH characteristics differed by type of insurance coverage and were associated with differences in telehealth utilization.

Levounis to Emphasize Public Engagement in Presidential Year Focused on Addiction Treatment

Levounis to Emphasize Public Engagement in Presidential Year Focused on Addiction Treatment

Estimated Costs of Intervening in Health-Related Social Needs Detected in Primary Care

Health-related social needs are increasingly being screened for in primary care practices, but it remains unclear how much additional financing is required to address those needs to improve health outcomes. To estimate the cost of implementing evidence-based interventions to address social needs identified in primary care practices. A decision analytical microsimulation of patients seen in primary care practices, using data on social needs from the National Center for Health Statistics from 2015 through 2018 (N = 19 225) was conducted. Primary care practices were categorized as federally qualified health centers (FQHCs), non-FQHC urban practices in high-poverty areas, non-FQHC rural practices in high-poverty areas, and practices in lower-poverty areas. Data analysis was performed from March 3 to December 16, 2022. Simulated evidence-based interventions of primary care-based screening and referral protocols, food assistance, housing programs, nonemergency medical transportation, and community-based care coordination. The primary outcome was per-person per-month cost of interventions. Intervention costs that have existing federally funded financing mechanisms (eg, the Supplemental Nutrition Assistance Program) and costs without such an existing mechanism were tabulated. Of the population included in the analysis, the mean (SD) age was 34.4 (25.9) years, and 54.3% were female. Among people with food and housing needs, most were program eligible for federally funded programs, but had low enrollment (eg, due to inadequate program capacity), with 78.0% of people with housing needs being program eligible vs 24.0% enrolled, and 95.6% of people with food needs being program eligible vs 70.2% enrolled. Among those with transportation insecurity and care coordination needs, eligibility criteria limited enrollment (26.3% of those in need being program eligible for transportation programs, and 5.7% of those in need being program eligible for care coordination programs). The cost of providing evidence-based interventions for these 4 domains averaged $60 (95% CI, $55-$65) per member per month (including approximately $5 for screening and referral management in clinics), of which $27 (95% CI, $24-$31) (45.8%) was federally funded. While disproportionate funding was available to populations seen at FQHCs, populations seen at non-FQHC practices in high-poverty areas had larger funding gaps (intervention costs not borne by existing federal funding mechanisms). In this decision analytical microsimulation study, food and housing interventions were limited by low enrollment among eligible people, whereas transportation and care coordination interventions were more limited by narrow eligibility criteria. Screening and referral management in primary care was a small expenditure relative to the cost of interventions to address social needs, and just under half of the costs of interventions were covered by existing federal funding mechanisms. These findings suggest that many resources are necessary to address social needs that fall largely outside of existing federal financing mechanisms.

0233 Racial/ethnic Residential Segregation - a Component of Structural Racism - and Sleep Health by Neighborhood-level Poverty

Abstract Introduction Racial/ethnic residential segregation may contribute to sleep disparities by concentrating poverty and impairing sleep among minoritized groups. Yet, due to racism, equitable access to sleep-promoting resources may not occur in integrated neighborhoods. Further, social/cultural factors within ethnic enclaves could be protective. Methods To investigate whether relationships between racial/ethnic residential segregation and sleep vary by census tract-level poverty among US adults, we linked nationally-representative National Health Interview Survey data (2011-2017) to 2012 and 2017 American Community Survey census tract-level data. We used the local Getis-Ord Gi* statistic to categorize residential segregation (high, medium, low [reference]), considering differences between racial/ethnic composition within a census tract to the surrounding county. Survey-weighted, Poisson regressions with robust variance estimation were stratified by race/ethnicity and approximate census tract-level poverty tertile (high [&amp;gt;16.9% of residents below poverty level], medium [&amp;gt;7.9%-16.9%], low [0%-7.9%]) to estimate prevalence ratios (PRs) and 95% confidence intervals (CIs) for self-reported sleep health measures. Results Among 126,539 participants (mean age±SE=46±0.1 years), non-Hispanic (NH)-Black and Latino adults were most likely to report short sleep (41%) and non-restorative sleep (37%), respectively. Racial/ethnic residential segregation was most common among NH-Black (38%), followed by non-Mexican Latino (34%) and NH-Asian adults (34%), and was least prevalent among NH-White adults (17%) but was not associated with sleep among Mexican, non-Mexican Latino, or NH-Black adults. Among NH-Asian adults, high segregation was marginally associated with a higher prevalence of short sleep (&amp;lt; 7-hours vs. recommended [7-9 hours]) in low-poverty neighborhoods (PR=1.17 [95% CI:0.97-1.42]) but was associated with recommended sleep in medium-poverty neighborhoods (PRshort sleep=0.79 [0.63-0.99]). Among NH-White adults, high residential segregation was associated with more restorative sleep only in high-poverty (PR=1.13 [1.06-1.20]) and low-poverty (PR=1.03 [1.00-1.07]) neighborhoods. Conclusion Associations between racial/ethnic residential segregation and sleep health varied by neighborhood-level poverty among NH-Asian and NH-White adults. The lack of differences among most minoritized groups may be related to the close proximity of higher-income and lower-income neighborhoods due to structural racism. Future studies including spatial analyses are warranted. The findings/conclusions in this research are those of the authors and do not necessarily represent the views of the Research Data Center, National Center for Health Statistics, or CDC. Support (if any)

Urban and Rural Mpox Incidence Among Persons Aged 15–64 Years — United States, May 10–December 31, 2022

During May 10-December 31, 2022, a total of 29,980 confirmed and probable† U.S. monkeypox (mpox) cases were reported to CDC, predominantly in cisgender adult men reporting recent same-gender sexual partners (1). Urban-rural differences in health (2) and diagnosis of HIV (3,4) and other sexually transmitted infections (5) are well documented nationally. This report describes urban-rural differences in mpox incidence (cases per 100,000 population) among persons aged 15-64 years, by gender and race and ethnicity. Urbanicity was assessed using the 2013 National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme for Counties (2). Substantial differences in incidence by urbanicity, gender, and race and ethnicity were observed; most (71.0%) cases occurred in persons residing in large central urban areas. Among the cases in large central urban areas, most (95.7%) were in cisgender men. The overall incidence of mpox in the United States was 13.5 per 100,000 persons aged 15-64 years and peaked in August in both urban and rural areas. Among cisgender men, incidence in rural areas was approximately 4% that in large central urban areas (risk ratio [RR]=0.04). Among cisgender women, incidence in rural areas was approximately 11% that in large central urban areas (RR=0.11). In both urban and rural areas, incidence among non-Hispanic Black or African American (Black) and Hispanic or Latino (Hispanic) persons was consistently higher than that among non-Hispanic White (White) persons; RRs between Black and White persons were highest in rural areas. Support and maintenance of mpox surveillance and prevention efforts including vaccinations should focus on urban areas with the highest incidence of mpox during the 2022 outbreak; however, surveillance and prevention efforts should include all genders, persons of color, and persons residing in both urban and rural areas who are at increased risk for mpox.

American Indian/Alaskan Native Child and Adolescent Mortality.

The American Indian/Alaskan Native (AI/AN) population experiences substantial health disparities, but the extent is not well characterized especially among children and adolescents. In data from the National Center for Health Statistics, AI/AN persons are often not recognized as such on death certificates. As AI/AN deaths are undercounted, racial/ethnic comparisons showing greater death rates among AI/AN are "Estimates of Minimal Difference" (EMD): the difference in rates between groups that is an estimate of the minimal difference. It is the minimal difference because that difference would only be increased by more accurate race/ethnic classification on certificates as more AI/AN individuals would be counted as such. We compare rates of non-Hispanic AI/AN leading causes of death to non-Hispanic White (n-HW) and non-Hispanic Black (n-HB) children and adolescents using annual reports for "Deaths: Leading Causes" from 2015 to 2017 from the National Vital Statistics System. Among AI/AN 1-19 year-olds, suicide deaths are significantly higher (p<0.00001) than among n-HB (OR=4.34; CI=3.68-5.1) and n-HWs (p<0.007; OR=1.23; CI=1.05-1.42); deaths from accidents are significantly higher (p<0.001) than among n-HB (OR=1.71; CI=1.49-1.93); and deaths due to assault (homicide) are significantly higher (p<0.00002) than among n-HWs (OR=1.64; CI=1.3-2.05). The appearance of suicide as a leading cause of death among AI/AN children and adolescents occurs in the 10-14-year age group and is significantly more common in the 15-19-year age group compared to both n-HB (p<0.00001; OR=5.35; CI=4.40-6.48) and n-HW (p=0.00064; OR=1.36; CI=1.14-1.63). Even without adjusting for undercounting, EMDs show that there are significant health disparities for preventable deaths of AI/AN children and adolescents to be addressed by public health policy.

The Effect of Maternal Race, Ethnicity, and Nativity on Macrosomia Among Infants Born in the United States.

This study aims to elucidate the influence of race, ethnicity, and nativity on macrosomia rates, hypothesizing that higher rates are observed among White non-Latina mothers and United States (US)-born mothers. We analyzed data from 1,791,718 US births sourced from the National Center for Health Statistics of the Centers for Disease Control and Prevention. Logistic regression analyses were conducted to examine the associations between macrosomia rates and maternal race, ethnicity, and nativity. After excluding non-singleton, preterm, post-term births, and those with missing data, six maternal cohorts were identified: White non-Latina US-born (1,147,096) and foreign-born (75,542), Black non-Latina US-born (174,540) and foreign-born (32,200), and Latina US-born (223,968) and foreign-born (137,515). White non-Latina US-born mothers had the highest rates of excessive gestational weight gain (58.9%). Black non-Latina US-born mothers exhibited the highest rates of pre-pregnancy diabetes (0.7%) and obesity (29.5%). Macrosomia rates were highest among White non-Latina US-born mothers (10.7%) compared to other cohorts. After adjusting for socioeconomic and health-related factors, this group maintained the highest odds of macrosomia (OR: 1.876; 95%CI 1.832-1.922, P<0.001). Our findings reveal that White non-Latina US-born mothers experience the highest macrosomia rates, which persist after adjusting for known confounders. These results have significant implications for the development of gestational surveillance tools and targeted public health interventions aimed at improving pregnancy outcomes among high-risk cohorts.

A national analysis of ED presentations for early pregnancy and complications: Implications for post-Roe America

BackgroundMost obstetric emergencies are initially managed in the emergency department (ED). The Supreme Court decision of Dobbs v. Jackson Women's Health Organization, overturning Roe v. Wade, in June 2022, eliminated constitutional protection of abortion rights, allowing states to swiftly enact laws that can greatly change reproductive medicine. In this post-Roe landscape, the ambiguity and uncertainty being imposed on clinicians regarding the legality of certain interventions may have catastrophic effects. To understand and plan for the changes that will come and attempt to mitigate adverse outcomes, the authors first assessed the current state of pregnancy-related complication care in the ED setting. This study utilized data obtained from the National Hospital Ambulatory Medical Care Survey (NHAMCS) to evaluate trends in pregnancy-related ED visits from 2016 to 2020 that could be impacted by restricted abortion access and trigger laws. The authors subsequently analyzed the legislative changes and translated the pertinent ones to dispel misunderstandings and provide a framework for appropriate medical practice. MethodsThe retrospective study utilized data from the NHAMCS database from 2016 to 2020, encompassing an estimated total of 4,556,778 pregnancy-related ED visits. NHAMCS is a multi-stage probabilistic sample collected by the National Center for Health Statistics (NCHS) at the Centers for Disease Control and Prevention (CDC) using an annual survey of EDs in the United States. All data were summarized using descriptive statistics such as proportions and 95% confidence intervals Furthermore, the supreme court decision was analyzed in addition to multiple state laws and legal texts. The findings were summarized and discussed. ResultsThe majority (79.4%) of all studied visits were for patients between the ages of 18–34 years, capturing those in peak reproductive years. This age group also comprised of the bulk (76.4%) of visits for pathologic pregnancies, including ectopic and molar pregnancies, and 79.8% of visits for a spontaneous miscarriage or threatened miscarriage in early pregnancy. Black patients accounted for 25.7%, white patients 70.1%. Regarding ethnicity, patients were separated into Hispanic and non-Hispanic, with Hispanic patients comprising 27% of all ED visits for included diagnoses between 2016 and 2020. Most visits for complications following an induced abortion occurred in the south (70.8%) and were nearly twice as likely to occur in non-metropolitan areas. Approximately 18% patients presenting with a pathologic pregnancy required admission to the hospital and approximately 50% of those visits for pathologic pregnancies and visits for bleeding in pregnancy had a procedure in the ED (49.8% and 49.5%). There were 111,264 estimated visits in which methotrexate was administered, amounting to approximately 1 in 7 visits for ectopic or molar pregnancy. In this data set, approximately 14,000 miscarriage and early bleeding patients received misoprostol. ConclusionPregnancy-related ED visits comprise of a significant proportion of emergency care. As it relates to many of the trends previously elucidated on, the true extent of the burden cannot be predicted. It must be emphasized that contrary to popular belief, Dobbs v. Jackson does not prohibit termination of pregnancy in the setting of life-threatening conditions to the mother, including ectopic pregnancy, preeclampsia, and others, but the resultant uncertainty and ambiguity surrounding the constitutional change is leading to an over-compliance of the law, necessarily obstructing reproductive health care. The authors recommend that physicians be mindful of the rapidly-evolving laws in their particular state, and to also practice in accordance with Emergency Medical Treatment and Active Labor Act (EMTALA). Patient safety must be prioritized.

Moving to opportunity? Low birth weight outcomes among Southern-born Black mothers during the Great Migration

ObjectiveThe Great Migration was a mass movement in the United States during the twentieth century of roughly eight million Black Southerners to the Northeast, Midwest, and West. Despite its significance, little is known about the health outcomes associated with this internal migration. This study assessed the relationship between migration and low birth weight among mothers born in the South between 1950 and 1969. MethodsWe used approximately 1.4 million birth records of Black infants maintained by the US National Center for Health Statistics. To tease out the roles of the healthy migrant bias and of destination contexts, we compared two migration groups to Southern non-migrators: (1) migrators moving to the North and (2) migrators moving within the South. Non-migrants were matched to migrants using coarsened exact matching. We estimated the relationship between migration status and low birth weight stratified by birth year cohorts using logistic regression models. ResultsThere was positive selection in education and marriage among migrants moving out of the South and within the South. Results showed lower odds of low birth weight in both migration groups compared to Southern non-migrants. The odds ratios of low birth weight were similar in both comparisons. ConclusionWe found evidence consistent with a healthy migrant bias in infant health among mothers during the last decades of the Great Migration. Despite better economic opportunity, migrating to the North may not have offered additional protection for infant birth weight outcomes.

Urine Drug Testing in Pain Medicine

The recent Institute of Medicine report declared that greater than 100 million Americans have chronic pain with an associated cost of up to $635 billion each year due to medical treatment and lost productivity.[1,2] The explosion in opioid prescribing since the 1990s has resulted in opioids being the most frequently prescribed medication in the United States.[3–5] Manchikanti et al.'s study revealed a 149% increase in retail opioid sales and a 402% increase in average sales of opioids per person in the United States from 1997 to 2007 [6]. Looking at 1999–2012, the National Center for Health Statistics found that among patients aged 20 or older prescription opioid use increased from 5% to 6.9% until 2006 and then stayed at 6.9% until 2012.7 However, the percentage of patients using an opioid stronger than morphine dramatically increased from 17% to 37% over the same period.[7] Among the top 25 dispensed prescriptions in the United States, hydrocodone, tramadol, and oxycodone accounted for 1, 21, and 22 dispensed prescriptions, respectively. 5 Opioids represent one of many therapeutic options for treating chronic nonmalignant pain (CNMP), but their widespread use has resulted in a concomitant increase in misuse, abuse, addiction, overdose, and diversion. While there is evidence of the short-term benefit of opioids for treating pain based on randomized trials lasting less than 3 months, there are few studies reporting outcomes at 12 months or longer [8,9].

Changes in cancer mortality after Medicaid expansion and the role of stage at diagnosis.

Medicaid expansion is associated with improved survival following cancer diagnosis. However, little research has assessed how changes in cancer stage may mediate improved cancer mortality or how expansion may have decreased population-level cancer mortality rates. Nationwide state-level cancer data from 2001 to 2019 for individuals ages 20-64 years were obtained from the combined Surveillance, Epidemiology, and End Results National Program of Cancer Registries (incidence) and the National Center for Health Statistics (mortality) databases. We estimated changes in distant stage cancer incidence and cancer mortality rates from pre- to post-2014 in expansion vs nonexpansion states using generalized estimating equations with robust standard errors. Mediation analyses were used to assess whether distant stage cancer incidence mediated changes in cancer mortality. There were 17 370 state-level observations. For all cancers combined, there were Medicaid expansion-associated decreases in distant stage cancer incidence (adjusted odds ratio = 0.967, 95% confidence interval = 0.943 to 0.992; P = .01) and cancer mortality (adjusted odds ratio = 0.965, 95% confidence interval = 0.936 to 0.995; P = .022). This translates to 2591 averted distant stage cancer diagnoses and 1616 averted cancer deaths in the Medicaid expansion states. Distant stage cancer incidence mediated 58.4% of expansion-associated changes in cancer mortality overall (P = .008). By cancer site subgroups, there were expansion-associated decreases in breast, cervix, and liver cancer mortality. Medicaid expansion was associated with decreased distant stage cancer incidence and cancer mortality. Approximately 60% of the expansion-associated changes in cancer mortality overall were mediated by distant stage diagnoses.

Association between android fat mass, gynoid fat mass and cardiovascular and all-cause mortality in adults: NHANES 2003-2007.

Evidence of the relationship between android fat mass and gynoid fat mass with the mortality prediction is still limited. Current study analyzed the NHANES database to investigate the relationship between android fat mass, gynoid fat mass and CVD, with all-cause mortality. The study subjects were NHANES participants over 20 years old, two indicators of regional body composition, android fat and gynoid fat were measured by Dual Energy x-ray Absorptiometry (DEXA). The other various covariates data obtained from the NHANES questionnaire and laboratory measurements, including age, gender, education, race/ethnicity, uric acid, total serum cholesterol, albumin, Vitamin C, folate, alcohol drinking, smoking status, history of diabetes, and hypertension. Mortality status was ascertained from a linked mortality file prepared by the National Center for Health Statistics. The study population was divided quartiles based on the distribution of android fat mass and gynoid fat mass. The relationship between these two indicators with cardiovascular and all-cause mortality was investigated by using Cox regression. The covariates age, gender, smoking status, drinking status, history of diabetes, and history of hypertension were stratified. In the fully adjusted model, Q3 had the lowest HR in android fat mass and gynoid fat mass. When examining the relationship between android fat mass and CVD mortality, current smokers and drinkers had the lowest CVD risk in Q2 [smoking: 0.21 (0.08, 0.52), drinking: 0.14 (0.04, 0.50)]. In diabetic patients, compared with Q1, other groups with increased android fat mass can significantly reduce the risk of CVD [Q4: 0.17 (0.04, 0.75), Q3: 0.18 (0.03, 1.09), Q2: 0.27 (0.09, 0.83)]. In ≥60 years old and female, the greater the gynoid fat mass, the smaller the HR of all-cause mortality [Q4 for ≥60 years old: 0.57 (0.33, 0.96), Q4 for female: 0.37 (0.23, 0.58)]. People <60 years old had a lower risk of all-cause mortality with gynoid fat mass in Q3 than those ≥60 years old [<60 years: 0.50 (0.27, 0.91), ≥60 years: 0.65 (0.45, 0.95)]. Among subjects without hypertension, the group with the largest android fat mass had the lowest risk of CVD mortality, and the group with the largest gynoid fat mass had the lowest risk of all-cause mortality [Android fat mass: 0.36 (0.16, 0.81), gynoid fat mass: 0.57 (0.39, 0.85)]. Moderate android fat mass and gynoid fat mass (Q3) had the most protective effect. Smokers and drinkers need to control their body fat. Being too thin is harmful to people with diabetes. Increased gynoid fat mass is a protective factor for all-cause mortality in older adults and females. Young people's gynoid fat mass is more protective in the moderate range than older people's. If no high blood pressure exists, people with more android and gynoid fat mass have a lower risk of CVD or all-cause mortality.

Progress in reducing cancer mortality in the United States by congressional district, 1996-2003 to 2012-2020.

United States cancer death rates have been steadily declining since the early 1990s, but information on disparities in progress against cancer mortality across congressional districts is lacking. This study examined trends in cancer death rates, overall and for lung, colorectal, female breast, and prostate cancer by congressional district. County level cancer death counts and population data from the National Center for Health Statistics were used to estimate relative change in age-standardized cancer death rates from 1996-2003 to 2012-2020 by sex and congressional district. From 1996-2003 to 2012-2020, overall cancer death rates declined in every congressional district, with most congressional districts showing a 20%-45% decline among males and a 10%-40% decline among females. In general, the smallest percent of relative declines were found in the Midwest and Appalachia, whereas the largest declines were found in the South along the East Coast and the southern border. As a result, the highest cancer death rates generally shifted from congressional districts across the South in 1996-2003 to districts in the Midwest and central divisions of the South (including Appalachia) in 2012-2020. Death rates for lung, colorectal, female breast, and prostate cancers also declined in almost all congressional districts, although with some variation in relative changes and geographical patterns. Progress in reducing cancer death rates during the past 25years considerably vary by congressional district, underscoring the need for strengthening existing and implementing new public health policies for broad and equitable application of proven interventions such as raising tax on tobacco and Medicaid expansion.

A Quantitative Framework to Identify and Prioritize Opportunities in Biomedical Product Innovation

Prioritization and funding for health initiatives, including biomedical innovation, may not consistently target unmet public health needs. To (1) develop a quantitative, databased framework to identify and prioritize opportunities for biomedical product innovation investments based on a multicriteria decision-making model (MCDM) that includes comprehensive measures of public health burden and health care costs, and (2) pilot test the model. The Department of Health and Human Services (HHS) convened public and private experts to develop a model, select measures, and complete a longitudinal pilot study to identify and prioritize opportunities for investment in biomedical product innovations that have the greatest public health benefit. Cross-sectional and longitudinal data (2012-2019) for 13 pilot medical disorders were obtained from the Institute for Health Metrics Global Burden of Disease database (IHME GBD) and the National Center for Health Statistics (NCHS). The main outcome measure was an overall gap score reflecting high public health burden (composite measure of mortality, prevalence, years lived with disability, and health disparities), or high health care costs (composite measure of total, public, and out-of-pocket health spending) relative to low biomedical innovation. Sixteen innovation metrics were selected to reflect the pipeline of biomedical products from research and development to market approval. A higher score indicates a greater gap. Normalized composite scores were calculated for public health burden, cost, and innovation investment using the MCDM Technique for Order of Preference by Similarity to Ideal Solution method. Among the 13 conditions tested in the pilot study, diabetes (0.61), osteoarthritis (0.46), and drug-use disorders (0.39) had the highest overall gap score reflecting high public health burden, or high health care costs relative to low biomedical innovation in these medical disorders. Chronic kidney disease (0.05), chronic obstructive pulmonary disease (0.09), and cirrhosis and other liver diseases (0.10) had the least amount of biomedical product innovation despite similar public health burden and health care cost scores. In this cross-sectional pilot study, we developed and implemented a data-driven, proof-of-concept model that can help identify, quantify, and prioritize opportunities for biomedical product innovation. Quantifying the relative alignment between biomedical product innovation, public health burden, and health care cost may help identify and prioritize investments that can have the greatest public health benefit.

Provisional Mortality Data - United States, 2022.

The National Center for Health Statistics' (NCHS) National Vital Statistics System (NVSS) collects and reports annual mortality statistics using U.S. death certificate data. Because of the time needed to investigate certain causes of death and to process and review death data, final annual mortality data for a given year are typically released 11 months after the end of the calendar year. Provisional data, which are based on the current flow of death certificate data to NCHS, provide an early estimate of deaths, before the release of final data. NVSS routinely releases provisional mortality data for all causes of death and for deaths associated with COVID-19.* This report is an overview of provisional U.S. mortality data for 2022, including a comparison with 2021 death rates. In 2022, approximately 3,273,705 deaths† occurred in the United States. The estimated 2022 age-adjusted death rate decreased by 5.3%, from 879.7 per 100,000 persons in 2021 to 832.8. COVID-19 was reported as the underlying cause or a contributing cause in an estimated 244,986 (7.5%) of those deaths (61.3 deaths per 100,000). The highest overall death rates by age, race and ethnicity, and sex occurred among persons who were aged ≥85 years, non-Hispanic American Indian or Alaska Native (AI/AN), non-Hispanic Black or African American (Black), and male. In 2022, the four leading causes of death were heart disease, cancer, unintentional injuries, and COVID-19. Provisional death estimates provide an early indication of shifts in mortality trends and can guide public health policies and interventions aimed at reducing mortality, including deaths directly or indirectly associated with the COVID-19 pandemic.

COVID-19 Mortality Update — United States, 2022

The National Center for Health Statistics' (NCHS) National Vital Statistics System (NVSS) collects and reports annual mortality statistics using U.S. death certificate data. Provisional data, which are based on the current flow of death certificate data to NCHS, provide an early estimate of deaths before the release of final data.* This report summarizes provisional U.S. COVID-19 death data for 2022. In 2022, COVID-19 was the underlying (primary) or contributing cause in the chain of events leading to 244,986 deaths† that occurred in the United States. During 2021-2022, the estimated age-adjusted COVID-19-associated death rate decreased 47%, from 115.6 to 61.3 per 100,000 persons. COVID-19 death rates were highest among persons aged ≥85 years, non-Hispanic American Indian or Alaska Native (AI/AN) populations, and males. In 76% of deaths with COVID-19 listed on the death certificate, COVID-19 was listed as the underlying cause of death. In the remaining 24% of COVID-19 deaths, COVID-19 was a contributing cause. As in 2020 and 2021, during 2022, the most common location of COVID-19 deaths was a hospital inpatient setting (59%). However, an increasing percentage occurred in the decedent's home (15%), or a nursing home or long-term care facility (14%).§ Provisional COVID-19 death estimates provide an early indication of shifts in mortality trends and can help guide public health policies and interventions aimed at reducing COVID-19-associated mortality.

Increased Reports of Depression in Hawaiʻi during the first wave of COVID-19

Introduction: Reports of mental health issues increased nationally in the USA during the COVID-19 pandemic, often attributed to the effects of quarantine, isolation, and restriction of travel. Given that Hawaiʻi State’s population is unique in its largely ethnic minority population, geographic isolation, and economic dependence on tourism, it is important to document if similar mental health outcomes have occurred during the beginning of the COVID-19 pandemic.&#x0D; Methods: This study compares Hawaiʻi’s rates of depression using data from the National Center for Health Statistics collected in 2020 and the Hawaiʻi Behavioral Risk Factor Surveillance System collected in 2016.&#x0D; Results: Hawaiʻi’s rate of depression, like the rest of the nation, increased significantly during the first wave. A chi-square test of independence was conducted, and the results were significant, χ2 (1, n = 20,261.42) = 582.48, p &lt; .001. Before COVID-19, typical rates of depression were at 11.03%, 95% CI [10.51%, 11.55%]. During the COVID-19 pandemic, reports of depression increased to 24.23%, 95% CI [23.16%, 25.31%].&#x0D; Conclusion: Depressive symptoms doubled during the early stages of the pandemic in Hawaiʻi. Evidence-based strategies should be developed now to help prevent future possible mental health related issues that are attributable to pandemic related safety protocols.

Longitudinal study of COVID-19 stay-at-home orders' impact on deaths of despair in the United States, January 2019 to December 2020.

The COVID-19 pandemic led to increase in mental health problems and substance misuse. Yet, little is known about its impact on rates of deaths of despair (death by suicide and drug overdose). Our objective was to determine the impact of COVID-19 stay-at-home orders on deaths of despair using population-level data. We hypothesized that the longer duration of stay-at-home orders would increase rates of deaths of despair. Utilizing quarterly suicide and drug-overdose mortality data from the National Center for Health Statistics from January 2019 through December 2020, we estimated fixed-effects models to examine the effects of the duration of stay-at-home orders as differentially implemented in 51 jurisdictions in the United States on each outcome. Controlling for seasonal patterns, the duration of jurisdictional-level stay-at-home order was positively associated with drug-overdose death rates. The duration of stay-at-home orders was not associated with suicide rates when adjusting for calendar quarter. Findings suggest an increase in age-adjusted drug-overdose death rates in the United States from 2019 to 2020 possibly attributable to the duration of jurisdictional COVID-19 stay-at-home orders. This effect may have operated through various mechanisms, including increases in economic distress and reduced access to treatment programs when stay-at-home orders were in effect.