Men and women in the prime of their lives are increasingly being diagnosed with serious cancers, including colorectal, breast, prostate, uterine, stomach (gastric), pancreatic, and more. One forecast predicts cancer for this age group will increase by 30% globally from 2019 to 2030.
MSK is a pioneer in caring for the specific needs of people facing what are often called early-onset cancers, who confront very different challenges than older adults. The coming surge in cases is a key reason MSK is building a new state-of-the-art hospital, called the MSK Pavilion.
Just as importantly, MSK experts are leading the investigation into why this is happening.
To determine where residents are most concerned about life insurance, Beca Life ranked them by monthly online searches for terms related to the product, based on data from Google Keyword Planner. The total number of monthly average searches in each state was compared against its population, to determine the average monthly searches per 100,000 people.
The top five states have an average of 852.84 people per 100,000 seeking life insurance via search engine each month.
Today, the working age population in almost half of U.S. metropolitan areas has declined due to demographic shifts, and this trend is set to continue.
As a result, the U.S. workforce is projected to grow at just 0.2% annually over the next decade, roughly a quarter of the rate of markets like India and Mexico. Given the low birth rates and aging populations across many advanced economies, the world’s workforce is set to change significantly, with implications for economic and productivity growth.
This graphic shows the projected growth in major economies’ working age population, based on analysis from Ray Dalio’s Great Powers Index 2024.
This data visualization presents provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. Counts for the most recent final annual data are provided for comparison. National provisional counts include deaths occurring within the 50 states and the District of Columbia as of the date specified and may not include all deaths that occurred during a given time period. Provisional counts are often incomplete and causes of death may be pending investigation (see Technical notes) resulting in an underestimate relative to final counts. To address this, methods were developed to adjust provisional counts for reporting delays by generating a set of predicted provisional counts (see Technical notes).
The provisional data presented in this visualization include: (a) the reported and predicted provisional counts of deaths due to drug overdose occurring nationally and in each jurisdiction; (b) a U.S. map of the percentage changes in provisional drug overdose deaths for the current 12 month-ending period compared with the 12-month period ending in the same month of the previous year, by jurisdiction; and (c) the reported and predicted provisional counts of drug overdose deaths involving specific drugs or drug classes occurring nationally and in selected jurisdictions. The reported and predicted provisional counts represent the numbers of deaths due to drug overdose occurring in the 12-month periods ending in the month indicated. These counts include all seasons of the year and are insensitive to variations by seasonality. Deaths are reported by the jurisdiction in which the death occurred.
Several data quality metrics, including the percent completeness in overall death reporting, percentage of deaths with cause of death pending further investigation, and the percentage of drug overdose deaths with specific drugs or drug classes reported are included to aid in interpretation of provisional data as these measures are related to the accuracy of provisional counts (see Technical notes). Reporting of the specific drugs and drug classes involved in drug overdose deaths varies by jurisdiction, and comparisons of death rates involving specific drugs across selected jurisdictions should not be made (see Technical notes). Provisional data presented in this visualization will be updated on a monthly basis as additional records are received.
Publication Date: Accessed 19 Sept 2024
Publication Site: National Center for Health Statistics, CDC
Introduction More than 30 million adults are released from incarceration globally each year. Many experience complex physical and mental health problems, and are at markedly increased risk of preventable mortality. Despite this, evidence regarding the global epidemiology of mortality following release from incarceration is insufficient to inform the development of targeted, evidence-based responses. Many previous studies have suffered from inadequate power and poor precision, and even large studies have limited capacity to disaggregate data by specific causes of death, sub-populations or time since release to answer questions of clinical and public health relevance.
Objectives To comprehensively document the incidence, timing, causes and risk factors for mortality in adults released from prison.
Methods We created the Mortality After Release from Incarceration Consortium (MARIC), a multi-disciplinary collaboration representing 29 cohorts of adults who have experienced incarceration from 11 countries. Findings across cohorts will be analysed using a two-step, individual participant data meta-analysis methodology.
Results The combined sample includes 1,337,993 individuals (89% male), with 75,795 deaths recorded over 9,191,393 person-years of follow-up.
Conclusions The consortium represents an important advancement in the field, bringing international attention to this problem. It will provide internationally relevant evidence to guide policymakers and clinicians in reducing preventable deaths in this marginalized population.
Author(s): Borschmann, R., Tibble, H., Spittal, M. J., Preen, D., Pirkis, J., Larney, S., Rosen, D. L., Young, J. T., Love, A. D., Altice, F. L., Binswanger, I. A., Bukten, A., Butler, T., Chang, Z., Chen, C.-Y., Clausen, T., Christensen, P. B., Culbert, G. J., Degenhardt, L., Dirkzwager, A. J., Dolan, K., Fazel, S., Fischbacher, C., Giles, M., Graham, L., Harding, D., Huang, Y.-F., Huber, F., Karaminia, A., Kouyoumdjian, F. G., Lim, S., Møller, L., Moniruzzaman, A., Morenoff, J., O’Moore, E., Pizzicato, L. N., Pratt, D., Proescholdbell, S. F., Ranapurwala, S. I., Shanahan, M. E., Shaw, J., Slaunwhite, A., Somers, J. M., Spaulding, A. C., Stern, M. F., Viner, K. M., Wang, N., Willoughby, M., Zhao, B. and Kinner, S. A.
Publication Date: February 2020
Publication Site: International Journal of Population Data Science
FIGURE 1. Provisional* number of COVID-19–associated deaths† and other deaths and percentage of deaths associated with COVID-19, by week of death — National Vital Statistics System, United States, 2023
* National Vital Statistics System provisional data for 2023 are incomplete. Data from December 2023 are less complete because of reporting lags. These data exclude deaths that occurred in the United States among residents of U.S. territories and foreign countries.
† Deaths with confirmed or presumed COVID-19 as an underlying or contributing cause of death, with International Classification of Diseases, Tenth Revision code U07.1.
Excerpt:
Abstract
Final annual mortality data from the National Vital Statistics System for a given year are typically released 11 months after the end of the calendar year. Provisional data, which are based on preliminary death certificate data, provide an early estimate of deaths before the release of final data. In 2023, a provisional total of 3,090,582 deaths occurred in the United States. The age-adjusted death rate per 100,000 population was 884.2 among males and 632.8 among females; the overall rate, 750.4, was 6.1% lower than in 2022 (798.8). The overall rate decreased for all age groups. Overall age-adjusted death rates in 2023 were lowest among non-Hispanic multiracial (352.1) and highest among non-Hispanic Black or African American persons (924.3). The leading causes of death were heart disease, cancer, and unintentional injury. The number of deaths from COVID-19 (76,446) was 68.9% lower than in 2022 (245,614). Provisional death estimates provide an early signal about shifts in mortality trends. Timely and actionable data can guide public health policies and interventions for populations experiencing higher mortality.
Author(s): Farida B. Ahmad, MPH1; Jodi A. Cisewski, MPH1; Robert N. Anderson, PhD
Suggested citation for this article: Ahmad FB, Cisewski JA, Anderson RN. Mortality in the United States — Provisional Data, 2023. MMWR Morb Mortal Wkly Rep 2024;73:677–681. DOI: http://dx.doi.org/10.15585/mmwr.mm7331a1
Housing affordability continues to soar out of reach of most buyers. Not only are prices at a new record level, mortgage rates remain close to 7.0 percent.
Chart Notes
Case-Shiller measures repeat sales of the same price over time. It is the best measure of price, but it lags. Current data is as of May which reflects sales 1-3 months prior.
The CPI, OER, and Rent of Primary Residence are all from the BLS.
OER stands for Owners’ Equivalent Rent. It is the rent one would pay if someone was renting instead of paying a mortgage.
There were 8,400 more deaths in Australia in 2023 than predicted had the pandemic not occurred – less than half of the almost 20,000 excess deaths estimated for 2022.
The new Research Paper from the Mortality Working Group explores how COVID-19 affected mortality in Australia from 2020 to 2023 and how Australia’s experience compares with the rest of the world.
In brief:
The steep decline in excess deaths in 2023 was primarily due to the number of people dying from COVID-19 falling to 4,600 in 2023 from 10,300 in 2022.
While Australia’s excess mortality rate had dropped substantially, it remains significantly higher than the 1-2% excess observed in years of high flu deaths prior to the pandemic.
When analysing the excess mortality of 40 countries from 2020 to 2023, Australia’s excess mortality over the four-year period (5%) was low by global standards (11%).
Author(s): Mortality Working Group. Members Karen Cutter, Ronald Lai, Jennifer Lang, Han Li, Richard Lyon, Matt Ralph, Amitoze Singh, Michael Seymour, Zhan Wang.
New data shows $9.9 billion flowed from Illinois to other states because people moved out in 2022. Most of those leaving earned $100,000 or more.
When Illinoisans move away, they take their money with them: $9.9 billion in 2022, according to new data from the Internal Revenue Service.
Tax returns for 2021 and 2022 show Illinois lost 86,693 individuals and $9.9 billion because of outmigration. Most of them were high-income Illinoisans.
One factor undermining older Americans’ ability to prepare financially for retirement is the debt burden they carry. Increasingly, adults are carrying debt into retirement, according to Mingli Zhong, research associate, and Jennifer Andre, data scientist at the Urban Institute.
The authors also reported racial disparities in debt levels. Compared to an older adult in a majority-white community, a typical older adult in a community of color is more likely to have any type of delinquent debt, carry a higher balance of total delinquent debt, and have a higher balance of medical debt in collections. The older adult living in a majority-white area has a higher balance of delinquent student loan debt and delinquent credit card debt, they also found.
The analysis of national mortality trends is critically dependent on the quality of the population, exposures and deaths data that underpin death rates. We develop a framework that allows us to assess data reliability and to identify anomalies, illustrated, by way of example, using England and Wales population data. First, we propose a set of graphical diagnostics that help to pinpoint anomalies. Second, we develop a simple Bayesian model that allows us to quantify objectively the size of any anomalies. Two-dimensional graphical diagnostics and modelling techniques are shown to improve significantly our ability to identify and quantify anomalies. An important conclusion is that significant anomalies in population data can often be linked to uneven patterns of births of people in cohorts born in the distant past. In the case of England and Wales, errors of more than 9% in the estimated size of some birth cohorts can be attributed to an uneven pattern of births. We propose methods that can use births data to improve estimates of the underlying population exposures. Finally, we consider the effect of anomalies on mortality forecasts and annuity values, and we find significant effects for some cohorts. Our methodology has general applicability to other sources of population data, such as the Human Mortality Database.
Keywords: Baby boom;Cohort–births–deaths exposures methodology; Convexity adjustment ratio; Deaths; Graphical diagnostics; Population data
Author(s): Andrew J.G.Cairns, Heriot-Watt University, Edinburgh, UK David Blake, Cass Business School, London, UK Kevin Dowd Durham University Business School, UK and Amy R. Kessler Prudential Retirement, Newark, USA
Publication Date: 2016
Publication Site: Journal of the Royal Statistical Society
J. R. Statist. Soc. A (2016) 179, Part 4, pp. 975–1005
