709 research outputs found

    The future of death in America

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    Population mortality forecasts are widely used for allocating public health expenditures, setting research priorities, and evaluating the viability of public pensions, private pensions, and health care financing systems. Although we know a great deal about patterns in and causes of mortality, most forecasts are still based on simple linear extrapolations that ignore covariates and other prior information. We adapt a Bayesian hierarchical forecasting model capable of including more known health and demographic information than has previously been possible. This leads to the first age- and sex-specific forecasts of American mortality that simultaneously incorporate, in a formal statistical model, the effects of the recent rapid increase in obesity, the steady decline in tobacco consumption, and the well known patterns of smooth mortality age profiles and time trends. Formally including new information in forecasts can matter a great deal. For example, we estimate an increase in male life expectancy at birth from 76.2 years in 2010 to 79.9 years in 2030, which is 1.8 years greater than the U.S. Social Security Administration projection and 1.5 years more than U.S. Census projection. For females, we estimate more modest gains in life expectancy at birth over the next twenty years from 80.5 years to 81.9 years, which is virtually identical to the Social Security Administration projection and 2.0 years less than U.S. Census projections. We show that these patterns are also likely to greatly affect the aging American population structure. We offer an easy-to-use approach so that researchers can include other sources of information and potentially improve on our forecasts too.age dependency, forecasting, mortality, obesity, smoking

    Molecular mechanisms of phenotypic change in intact nociceptors

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    We have previously shown that regenerated cutaneous afferents exhibit sensitization. These changes were correlated with increased expression of neurotrophic factors in the affected skin, and receptors and ion channels in the dorsal root ganglia (DRG). Here we found that saphenous nerve injury resulted in similar alterations in gene expression in the skin innervated by the uninjured contralateral saphenous nerve. Several Nerve Growth Factor (NGF) and GDNF ligands were upregulated in the dorsal hindpaw hairy skin 7-21 days following contralateral saphenous nerve axotomy. This increase in expression was correlated with upregulation of several receptors and ion channels in the L2,3 DRGs, including GFRα1, nucleotide receptors P2X3, P2Y1, and P2Y2, heat transducing channel TRPV1, and acid-sensing ion channels 1 (ASIC1) and 3 (ASIC3). Characterization of intact saphenous afferent fibers revealed that 4-5 weeks after contralateral injury, C-polymodal population had significantly reduced heat thresholds. There was also a significant increase in the proportion of mechanically insensitive-heat sensitive (CH) neurons. These findings provide evidence of peripheral mechanisms that may be involved in the development of mirror-image pain, a clinical phenomenon in which patients experience pain in the healthy region of the body contralateral to the injury site. The changes in the response properties of intact afferents at 4-5 weeks following contralateral injury were correlated with upregulation of P2Y1 and TRPV1 in the DRGs at 28d post-injury, and we investigated the role of these two targets in the functional plasticity observed by utilizing an in vivo small interfering RNA (siRNA)-mediated knockdown strategy to target the upregulation of P2Y1 and TRPV1 in the L2,3 DRGs at 28 days following contralateral injury. We found that blocking P2Y1 upregulation prevented the heat threshold reduction in C-polymodal afferents and conclude that P2Y1 plays a critical role in the heat sensitivity of these fibers. We then found that blocking the upregulation of TRPV1 blocked the recruitment of C-heat fibers. Taken together, our findings suggest that chronic exposure of intact cutaneous sensory neurons to increased endogenous levels of neurotrophic factors results in upregulation of target receptors and ion channels in the DRG and sensitization and phenotypic changes in intact sensory neurons

    Systematic Bias and Nontransparency in US Social Security Administration Forecasts

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    We offer an evaluation of the Social Security Administration demographic and financial forecasts used to assess the long-term solvency of the Social Security Trust Funds. This same forecasting methodology is also used in evaluating policy proposals put forward by Congress to modify the Social Security program. Ours is the first evaluation to compare the SSA forecasts with observed truth; for example, we compare forecasts made in the 1980s, 1990s, and 2000s with outcomes that are now available. We find that Social Security Administration forecasting errors—as evaluated by how accurate the forecasts turned out to be—were approximately unbiased until 2000 and then became systematically biased afterward, and increasingly so over time. Also, most of the forecasting errors since 2000 are in the same direction, consistently misleading users of the forecasts to conclude that the Social Security Trust Funds are in better financial shape than turns out to be the case. Finally, the Social Security Administration\u27s informal uncertainty intervals appear to have become increasingly inaccurate since 2000. At present, the Office of the Chief Actuary, at the Social Security Administration, does not reveal in full how its forecasts are made. Every future Trustees Report, without exception, should include a routine evaluation of all prior forecasts, and a discussion of what forecasting mistakes were made, what was learned from the mistakes, and what actions might be taken to improve forecasts going forward. And the Social Security Administration and its Office of the Chief Actuary should follow best practices in academia and many other parts of government and make their forecasting procedures public and replicable, and should calculate and report calibrated uncertainty intervals for all forecasts

    "Nudes? {S}houldn't {I} charge for these?" : {E}xploring What Motivates Content Creation on {OnlyFans}

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    Social media platforms are increasingly considering models to incentivize creators to publish high quality content on their platforms. As a result, social media content creation has transformed into a form of gig work for some creators. In order to better design social media platforms to support this labor, we need to understand professional creators' motivations. In this work, we present a qualitative interview study of the motivations of 2222 U.S. OnlyFans creators. OnlyFans is a subscription-based social media platform that is unique in that it is primarily associated with sexual content (although it is not marketed as such) and thus creators are positioned at the intersection of professional content creation and sex work, exposing them to a unique set of potential challenges. Beyond the typical motivations for pursuing other forms of gig work (e.g., flexibility, autonomy) our findings highlight three key factors explaining the rapid growth of OnlyFans despite the potential stigma of sexual content creation: (1) societal visibility and mainstream acceptance of OnlyFans, created through a combination of celebrity hype and the design of the platform itself; (2) platform design: affordances for boundary setting with clients, privacy from the public, and content archives, which together create a labor environment participants viewed as better than other forms of gig work, a natural avenue for sexual expression, and enabling monetization of existing content, audiences, and skills; and (3) the pandemic, which led to both high demand for immediate income while waiting for -- or after running out of -- unemployment benefits, and increased free time, which increased general demand for pornographic content

    Modeling Area-Level Health Rankings

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    We propose a Bayesian factor analysis model to rank the health of localities. Mor-tality and morbidity variables empirically contribute to the resulting rank, and popu-lation and spatial correlation are incorporated into a measure of uncertainty. We use county-level data from Texas and Wisconsin to compare our approach to conventional rankings that assign deterministic factor weights and ignore uncertainty. Greater dis-crepancies in rankings emerge for Texas than Wisconsin since the di¤erences between the empirically-derived and deterministic weights are more substantial. Uncertainty is evident in both states but becomes especially large in Texas after incorporating noise from imputing its considerable missing data

    Futures of Data Ownership: Defining Data Policies in Canadian Context

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    The importance of data is increasing along with its inflation in our world today. In today's world, data is becoming the primary source for innovation, knowledge, insight, and a competitive and financial advantage in the race of information procurement. This interest in acquiring and exploiting data and the current concerns regarding the privacy and security of information raises the question of who should own the data and how policies can preserve data ownership. There is a growing awareness that companies benefit disproportionately from collecting and selling personal information, driving the desire for greater individual control of personal data. As technology progresses exponentially, there is a dire need to regulate Tech organizations. With the increasing use of personal data by tech companies, data privacy and ownership concerns have become more significant in today's society. Although governments worldwide have introduced privacy regulations to protect citizens' data, there is still a need for policies and legislation that safeguard citizens' rights, allow consumers to control their data, and implement strict measures in case of data breaches or violation of data rights. The research project "Futures of Data Ownership - Informing Data Policies in Canadian Context" aims to explore emerging technological shifts and promote ethical use and data protection by developing data policies that consider the Canadian context. The research will employ primary and secondary research methods, including horizon scanning, semi-structured interviews, and a literature review, to inform policy and strategy development. In conclusion, the research project informs potential policies and legislation that regulate tech organizations and protect data ownership, ensuring a secure and trustworthy digital future for all
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