How Much Labor Was Lost in the US During the Covid-19 Pandemic

Background: American Indians and Alaskan Natives (AI/AN) are a highly diverse group in terms of culture and language, but share a history of oppression and attempted extermination that has left many with a legacy of poverty and poor health. Cultural and biological survival are important issues for many AI/AN groups.Methods: Using US criteria, AI/AN groups are more likely to be poor. The US National Center for Health Statistics reports that US AI/ANs have higher mortality and morbidity rates than the US population. While all groups racially defined by the US National Center for Health Statistics have been experiencing a decline in fertility since 1983, AI/ANs seem to be suffering a substantially greater and earlier decline in fertility. Given the importance of fertility in the survival of AI/AN communities, it is important to identify the source of this decline.Results: A recent study of one AI/AN group living along the St. Lawrence River found that obesity and exposure to a particular group of polychlorinated biphenyls were the factors most highly associated with indicators of impaired fertility. Economic factors are often cited as reasons for fertility declines, however in this situation these other factors may have either primary or contributing roles.Conclusions: If the associations with obesity and toxicant exposure are confirmed, intervening on these factors might be important steps in stemming continued declines in fertility.

Fall-related mortality has increased rapidly over the past two decades in the USA, but the extent to which mortality varies across racial and ethnic populations, counties, and age groups is not well understood. The aim of this study was to estimate age-standardised mortality rates due to falls by racial and ethnic population, county, and age group over a 20-year period. Redistribution methods for insufficient cause of death codes and validated small-area estimation methods were applied to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate annual fall-related mortality. Estimates from 2000 to 2019 were stratified by county (n=3110) and five mutually exclusive racial and ethnic populations: American Indian or Alaska Native (AIAN), Asian or Pacific Islander (Asian), Black, Latino or Hispanic (Latino), and White. Estimates were corrected for misreporting of race and ethnicity on death certificates using published misclassification ratios. We masked (ie, did not display) estimates for county and racial and ethnic population combinations with a mean annual population of less than 1000. Age-standardised mortality is presented for all ages combined and for age groups 20-64 years (younger adults) and 65 years and older (older adults). Nationally, in 2019, the overall age-standardised fall-related mortality rate for the total population was 13·4 deaths per 100 000 population (95% uncertainty interval 13·3-13·6), an increase of 65·3% (61·9-68·8) from 8·1 deaths per 100 000 (8·0-8·3) in 2000, with the largest increases observed in older adults. Fall-related mortality at the national level was highest across all years in the AIAN population (in 2019, 15·9 deaths per 100 000 population [95% uncertainty interval 14·0-18·2]) and White population (14·8 deaths per 100 000 [14·6-15·0]), and was about half as high among the Latino (8·7 deaths per 100 000 [8·3-9·0]), Black (8·1 deaths per 100 000 [7·9-8·4]), and Asian (7·5 deaths per 100 000 [7·1-7·9]) populations. The disparities between racial and ethnic populations varied widely by age group, with mortality among younger adults highest for the AIAN population and mortality among older adults highest for the White population. The national-level patterns were observed broadly at the county level, although there was considerable spatial variation across ages and racial and ethnic populations. For younger adults, among almost all counties with unmasked estimates, there was higher mortality in the AIAN population than in all other racial and ethnic populations, while there were pockets of high mortality in the Latino population, particularly in the Mountain West region. For older adults, mortality was particularly high in the White population within clusters of counties across states including Florida, Minnesota, and Wisconsin. Age-standardised mortality due to falls increased over the study period for each racial and ethnic population and almost every county. Wide variation in mortality across geography, age, and race and ethnicity highlights areas and populations that might benefit most from efficacious fall prevention interventions as well as additional prevention research. US National Institutes of Health (Intramural Research Program, National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; Intramural Research Program, National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research).

To compare the effectiveness of treating malnourished children in different centers, the authors believe there is a need to have a simple method of adjusting mortality rates so that differences in the nutritional status of the children are taken into account. The authors compared different anthropometric indices based on weight and height to predict the risk of death among severely malnourished children. Anthropometric data from 1,047 children who survived were compared with those of 147 children who died during treatment in therapeutic feeding centers set up in African countries in 1993. The optimal ratio of weight to height determined by logistic regression was weight (kg)/height (m)1.74 (95% confidence interval of beta estimate 1.65-1.84). The receiver operating curves (sensitivity vs. specificity) showed that the body mass index (weight (kg)/height (m)2), optimal ratio of weight to height, and weight/height index expressed as the percentage of the median of the National Center for Health Statistics' standard were equivalent and superior to the weight/height index expressed as the z score of the National Center for Health Statistics' standard to predict death. As the optimal ratio of weight to height is easier to calculate than the weight/height index expressed as the percentage of the median or z score and does not depend upon either standards or tables, the optimal ratio of weight to height could be conveniently used to adjust mortality rates for nutritional status in therapeutic feeding centers.

Two hundred eighty-five primary schoolgirls from the urban area of Thugba, Al-Khobar, in the Eastern Province of Saudi Arabia were examined anthropometrically. Hemoglobin estimations and laboratory...

Measurements of weight and height of 21,638 Saudi boys and girls ages six to 16 years from the Eastern Province were taken. It was observed that the occurrence age of children could only be made out in Hegira years, as age is recorded by parents and at schools by the Hegira calendar. Age is a crucial factor in studies such as this and for valid comparison with any international reference standard, the latter must be adapted to the Hegira calendar year. Curves for weight and height percentiles for age have been constructed and compared with the Hegira adaptation of the NCHS growth standard.

This study examined the effect of maternal age on birth outcomes among young adolescents, ages 10 through 15. All records representing single births of primipara, Black or White adolescents, were selected for analysis from the 1983-1986 National Center for Health Statistics' Public Use Linked Live Birth-Infant Death Data File (n = 127,668). Logistic regression analyses controlled for effects of maternal race, marital status, prenatal care, gravidity, education, and metropolitan/nonmetropolitan residency. Univariate analyses indicated that the youngest adolescents were at greatest risk for negative birth outcomes including very preterm and preterm delivery, low birth weight, small for gestational age (SGA), and neonatal mortality. Logistic analyses showed similar results, with the exception that differences in SGA were insignificant. This study indicates the importance of examining age-specific birth outcomes among a population that has traditionally been studied in aggregate and underscores the need for increased prevention efforts.

Cause-specific mortality by county, race, and ethnicity in the USA, 2000–19: a systematic analysis of health disparities

Trends in premature mortality in the USA by sex, race, and ethnicity from 1999 to 2014: an analysis of death certificate data

The United States has higher infant and youth mortality rates than other high-income countries, with striking disparities by racial/ethnic group. Understanding changing trends by age and race/ethnicity for leading causes of death is imperative for focused intervention. To estimate trends in US infant and youth mortality rates from 1999 to 2015 by age group and race/ethnicity, identify leading causes of death, and compare mortality rates with Canada and England/Wales. This descriptive study analyzed death certificate data from the US National Center for Health Statistics, Statistics Canada, and the UK Office of National Statistics for all deaths among individuals younger than 25 years. The study took place from January 1, 1999, to December 31, 2015, and analyses started in September 2017. Race/ethnicity. Average annual percent changes in mortality rates from 1999 to 2015 and absolute rate change between 1999 to 2002 and 2012 to 2015 for each age group, race/ethnicity, and cause of death. Among individuals from birth to age 24 years, 1 169 537 deaths occurred in the United States, 80 540 in Canada, and 121 183 in England/Wales from 1999 to 2015. In the United States, 64% of deaths occurred in male individuals and 52.6% occurred in white individuals (25.1% deaths occurred in black individuals and 17.9% in Latino individuals). All-cause mortality declined for all age groups (infants younger than 1 year [38.5% of deaths], children aged 1-9 years [10.6%], early adolescents aged 10-14 years [5%], late adolescents aged 15-19 years [17.7%], and young adults aged 20-24 years [28.1%]) in the United States, Canada, and England/Wales from 1999 to 2015. However, rates were highest in the United States. Within the United States, annual declines in all-cause mortality rates occurred among all age groups of black, Latino, and white individuals, except for white individuals aged 20 to 24 years, whose rates remained stable. Mortality rates declined across most major causes of death from 1999 to 2002 and 2012 to 2015, with notable declines observed for sudden infant death syndrome, unintentional injury death, and homicides. Among infants, unintentional suffocation and strangulation in bed increased (difference between 2012-2015 and 1999-2002 range, 6.11-29.03 per 100 000). Further, suicide rates among Latino and white individuals aged 10 to 24 years (range, 0.21-2.63 per 100 000) and black individuals aged 10 to 19 years (range, 0.10-0.45 per 100 000) increased, as did unintentional injury deaths in white young adults (0.79 per 100 000). The rise in unintentional injury deaths is attributed to increases in drug poisonings and was also observed in black and Latino young adults. Mortality rates in the United States have generally declined for infants and youths from 1999 to 2015 owing to reductions in sudden infant death syndrome, unintentional injury death, and homicides. However, US mortality rates remain higher than Canada and England/Wales, with particularly elevated rates among black and American Indian/Alaskan Native youth. Further, there is a concerning increase in suicide and drug poisoning death rates among US adolescents and young adults.

Systemic diseases associated with various types of retinal vein occlusion

Cancer is the leading cause of death at ages ≤80 in the US. To understand the burden of cancer death potentially addressable by new or improved screening approaches, we estimated the proportion of US cancer deaths without recommended guideline-based screening, especially after accounting for lung cancer screening eligibility and adherence. Using 2018-2019 mortality data from the National Center for Health Statistics and published estimates of the proportion of screening-eligible lung cancer patients, we estimated that 31.4% of nearly 600,000 annual cancer deaths were from colorectal, female breast, cervical, and smoking-eligible lung cancers (Table). Further accounting for adherence to lung cancer screening guidelines reduced the estimated proportion of screened cancer deaths to 17.4%; thus, 82.6% of cancer deaths may not be addressed by current guideline-based screening. Among the cancers not covered by guideline-based screening are uncommon cancer types, which (as defined by the National Cancer Institute) comprised 30.4% of cancer deaths. According to incidence-based mortality data from Surveillance, Epidemiology, and End Results registries, 24.7% of all cancer deaths were from stage 4 cancer types without guideline-based screening. These estimates, based on population data without patient-level information on mode of diagnosis, almost certainly underestimate the percentage of cancer deaths missed by currently available screening efforts. The large proportion of cancer deaths unaddressed by guideline-based screening represents a vast opportunity for new cancer screening technologies that are safe, effective, accessible, and affordable to enable earlier detection and successful treatment of the full spectrum of cancer types that contribute to the overall cancer burden. Table. Deaths from cancer by primary type in 2018-2019, US National Center for Health Statistics, with eligibility for and adherence to guideline-based low-dose computed tomography screening for lung cancer All cancer types Lung Colon/rectum Breast (female) Uterine cervix Total screened % of all All cancer deaths 1,198,854 281,681 104,059 84,745 8,290 478,775 39.9% Eligible for screening based on smoking (63.7% of lung)* 179,431 104,059 84,745 8,290 376,525 31.4% Adherent to smoking-guideline-based screening (6.6% of lung)† 11,842 104,059 84,745 8,290 208,936 17.4% *Modeled estimate of proportion of lung cancer patients eligible for screening (Landy et al. 2023). †Lung cancer screening receipt from 2019 American College of Radiology Lung Cancer Screening Registry (Fedewa et al. 2022). Citation Format: Ellen T. Chang, Anuraag Kansal, Earl A. Hubbell, Graham A. Colditz, Allison W. Kurian, Christina A. Clarke. Most cancer deaths are unaddressed by current screening paradigms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6075.

The objectives of this study were to estimate the accuracy of using mid-upper-arm circumference (MUAC) measurements to diagnose severe wasting by comparing the new standards from the World Health Organization (WHO) with those from the US National Center for Health Statistics (NCHS) and to analyze the age independence of the MUAC cutoff values for both curves. We used cross-sectional anthropometric data for 34,937 children between the ages of 6 and 59 months, from 39 nutritional surveys conducted by Doctors Without Borders. Receiver operating characteristic curves were used to examine the accuracy of MUAC diagnoses. MUAC age independence was analyzed with logistic regression models. With the new WHO curve, the performance of MUAC measurements, in terms of sensitivity and specificity, deteriorated. With different cutoff values, however, the WHO standards significantly improved the predictive value of MUAC measurements over the NCHS standards. The sensitivity and specificity of MUAC measurements were the most age independent when the WHO curve, rather than the NCHS curve, was used. This study confirms the need to change the MUAC cutoff value from <110 mm to <115 mm. This increase of 5 mm produces a large change in sensitivity (from 16% to 25%) with little loss in specificity, improves the probability of diagnosing severe wasting, and reduces false-negative results by 12%. This change is needed to maintain the same diagnostic accuracy as the old curve and to identify the children at greatest risk of death resulting from severe wasting.

Summary The World Health Organization revises the international classification of diseases about every 10 years to stay abreast of advances in medical science and to compare international health statistics. However, the new revision (i.e. the 10th revision) introduces discontinuities in mortality trends, making it impossible to compare the mortality statistics before and after the revision directly. The US National Center for Health Statistics published comparability ratios to correct the discontinuities between the two sets of mortality data: one coded by the ninth revision and the other by the 10th revision. We propose a parametric two-stage model to produce new comparability ratios and use these ratios to correct the discontinuities. The asymptotic behaviour of the comparability ratios is investigated. Our model not only measures the extent of discontinuities in trends in mortality but also can be used to forecast future mortality. Comparing with the National Center for Health Statistics’s ratios, our comparability ratios smooth out the discontinuities better for most causes.

BackgroundFor ages 5–19 years, the World Health Organization (WHO) publishes reference charts based on ‘core data’ from the US National Center for Health Statistics (NCHS), collected from 1963–75 on 22,917 US children. To promote the use of body mass index in older children, weight-for-age was omitted after age 10. Health providers have subsequently expressed concerns about this omission and the selection of centiles. We therefore sought to extend weight-for-age reference curves from 10 to 19 years by applying WHO exclusion criteria and curve fitting methods to the core NCHS data and to revise the choice of displayed centiles.MethodsWHO analysts first excluded ~ 3% of their reference population in order to achieve a “non-obese sample with equal height”. Based on these exclusion criteria, 314 girls and 304 boys were first omitted for ‘unhealthy’ weights-for-height. By applying WHO global deviance and information criteria, optimal Box-Cox power exponential models were used to fit smoothed weight-for-age centiles. Bootstrap resampling was used to assess the precision of centile estimates. For all charts, additional centiles were included in the healthy range (3 to 97%), and the more extreme WHO centiles 0.1 and 99.9% were dropped.ResultsIn addition to weight-for-age beyond 10 years, our charts provide more granularity in the centiles in the healthy range −2 to +2 SD (3–97%). For both weight and BMI, the bootstrap confidence intervals for the 99.9th centile were at least an order of magnitude wider than the corresponding 50th centile values.ConclusionsThese charts complement existing WHO charts by allowing weight-for-age to be plotted concurrently with height in older children. All modifications followed strict WHO methodology and utilized the same core data from the US NCHS. The additional centiles permit a more precise assessment of normal growth and earlier detection of aberrant growth as it crosses centiles. Elimination of extreme centiles reduces the risk of misclassification. A complete set of charts is available at the CPEG web site (http://cpeg-gcep.net).

The COVID-19 pandemic has exposed undeniable health inequities among marginalized communities (MC), including black, indigenous, and other people of color (BIPOC) in the United States (Forno and Celedón 2012, Kaiser Family Foundation 2017, US National Center for Health Statistics 2019, Glasgow 2020). The lack of centralized support for local health responses has jeopardized many MC/BIPOC (Baah, Teitelman, and Riegel 2019). We propose the Department of Health and Human Services (HHS) implement the following policy steps: 1. Centrally collect patient data on social determinants of health and equity and post-COVID-19 health outcomes (Paradies et al. 2015, Jones et al. 2009, Magnan 2017). Real-time data collection allows for real-time quality improvement and implementation of policies to mitigate inequities in the short-term. 2. Expand and implement Centers for Medicare and Medicaid (CMS) value-based care models (VBCM) to address inequities in the long-term. VBCMs institutionalize data collection initiated in Step 1 while concurrently implementing interventions. 3. Temporarily expand Medicaid coverage for individuals needing subsidized insurance. This provides a safety net for those suffering employment instability during the crisis, alleviating some root causes of health inequities. These steps will centralize resources, empowering local health systems to control and contain outbreaks disproportionately occurring among MC/BIPOC. HHS is positioned to implement these policies and mitigate further damage from COVID-19. HHS agencies such as the Food and Drug Administration (FDA) and Centers for Disease Control and Prevention (CDC) have successfully implemented centralization responses, such as the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) in response to the HIV/AIDS epidemic, effectively targeting disparities (Valdiserri and Holtgrave 2020). These previous successful responses by the HHS should compel intervention in the present crisis.