Estimating risks of heat strain by age and sex: a population-level simulation model.
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ABSTRACT:
SUBMITTER: Glass K
PROVIDER: S-EPMC4454965 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In this article, we develop an admixture F model (AFM) for the estimation of population-level coancestry coefficients from neutral molecular markers. In contrast to the previously published F model, the AFM enables disentangling small population size and lack of migration as causes of genetic differentiation behind a given level of F(ST). We develop a Bayesian estimation scheme for fitting the AFM to multiallelic data acquired from a number of local populations. We demonstrate the performance of the AFM, using simulated data sets and real data on ninespine sticklebacks (Pungitius pungitius) and common shrews (Sorex araneus). The results show that the parameterization of the AFM conveys more information about the evolutionary history than a simple summary parameter such as F(ST). The methods are implemented in the R package RAFM.
| S-EPMC3454884 | biostudies-other
Project description:Background. By defining what is "normal," appropriate, expected, and unacceptable, social norms shape human behavior. However, the individual-level mechanisms through which social norms impact population-level trends in health-relevant behaviors are not well understood. Aims. To test the ability of social norms mechanisms to predict changes in population-level drinking patterns. Method. An individual-level model was developed to simulate dynamic normative mechanisms and behavioral rules underlying drinking behavior over time. The model encompassed descriptive and injunctive drinking norms and their impact on frequency and quantity of alcohol use. A microsynthesis initialized in 1979 was used as a demographically representative synthetic U.S. population. Three experiments were performed in order to test the modelled normative mechanisms. Results. Overall, the experiments showed limited influence of normative interventions on population-level alcohol use. An increase in the desire to drink led to the most meaningful changes in the population's drinking behavior. The findings of the experiments underline the importance of autonomy, that is, the degree to which an individual is susceptible to normative influence. Conclusion. The model was able to predict theoretically plausible changes in drinking patterns at the population level through the impact of social mechanisms. Future applications of the model could be used to plan norms interventions pertaining to alcohol use as well as other health behaviors.
| S-EPMC7069782 | biostudies-literature
Project description:BackgroundThe health risks associated with moderate alcohol consumption continue to be debated. Small amounts of alcohol might lower the risk of some health outcomes but increase the risk of others, suggesting that the overall risk depends, in part, on background disease rates, which vary by region, age, sex, and year.MethodsFor this analysis, we constructed burden-weighted dose-response relative risk curves across 22 health outcomes to estimate the theoretical minimum risk exposure level (TMREL) and non-drinker equivalence (NDE), the consumption level at which the health risk is equivalent to that of a non-drinker, using disease rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 for 21 regions, including 204 countries and territories, by 5-year age group, sex, and year for individuals aged 15-95 years and older from 1990 to 2020. Based on the NDE, we quantified the population consuming harmful amounts of alcohol.FindingsThe burden-weighted relative risk curves for alcohol use varied by region and age. Among individuals aged 15-39 years in 2020, the TMREL varied between 0 (95% uncertainty interval 0-0) and 0·603 (0·400-1·00) standard drinks per day, and the NDE varied between 0·002 (0-0) and 1·75 (0·698-4·30) standard drinks per day. Among individuals aged 40 years and older, the burden-weighted relative risk curve was J-shaped for all regions, with a 2020 TMREL that ranged from 0·114 (0-0·403) to 1·87 (0·500-3·30) standard drinks per day and an NDE that ranged between 0·193 (0-0·900) and 6·94 (3·40-8·30) standard drinks per day. Among individuals consuming harmful amounts of alcohol in 2020, 59·1% (54·3-65·4) were aged 15-39 years and 76·9% (73·0-81·3) were male.InterpretationThere is strong evidence to support recommendations on alcohol consumption varying by age and location. Stronger interventions, particularly those tailored towards younger individuals, are needed to reduce the substantial global health loss attributable to alcohol.FundingBill & Melinda Gates Foundation.
| S-EPMC9289789 | biostudies-literature
Project description:Background and purposeEstimating age- and sex-specific population attributable risks (PARs) of major risk factors for stroke may be a useful strategy to identify risk factors for targeting preventive strategies.MethodsFor this case-control matched study, consecutive patients aged 18-90 years and admitted to nine nationwide hospitals with acute ischemic stroke between December 2008 and June 2010, were enrolled as cases. Controls, individually matched by age and sex, were chosen from the 4th Korean National Health & Nutrition Examination Survey (2008-2010). Based on odds ratios and prevalence, standardized according to the age and sex structure of the Korean population, PARs of major risk factors were estimated according to age (young, ≤ 45; middle-aged, 46-65; and elderly, ≥ 66 years) and sex subgroups.ResultsIn 4,743 matched case-control sets, smoking (PAR, 45.1%) was the greatest contributing risk factor in young men, followed by hypertension (28.5%). In middle-aged men, the greatest contributing factors were smoking (37.4%), hypertension (22.7%), and diabetes (14.6%), whereas in women the greatest factors were hypertension (22.7%) and stroke history (10.6%). In the elderly, hypertension was the leading factor in men (23.7%) and women (23.4%). Other noticeable factors were stroke history (men, 19.7%; women, 17.3%) and diabetes (men, 12.5%; women, 15.1%). In young women, risk factors with a PAR greater than 10% were not found.ConclusionsSmoking cessation in young people and hypertension and diabetes control in older people may be effective in reducing the burden of stroke on the population. In the elderly, secondary prevention could also be emphasized.
| S-EPMC4635707 | biostudies-literature
Project description:BACKGROUND/AIM:In 2016, in the United States, more than 50% of breast cancer (BC) cases were diagnosed in patients older than 60 years of age. Our study aimed to estimate the risk of locoregional recurrence (LR) in patients who underwent breast-conservative treatment (BCT), according to age. PATIENTS AND METHODS:This retrospective monocentric study analyzed 613 cases of patients who underwent BCT between 2003 and 2014. Patients were divided into groups according to age: Under70 (under 70 years old) and Over70 (above 70 years old). Margins width, histology results, prognostic and predictive factors were compared. Subgroup analysis was performed for patients who experienced LR. RESULTS:LR Incidence among Under70 and Over70 was 5.4% and 1.7%, respectively (p<0.01). Group Over70 is characterized by larger tumors and a lower Ki67 index (p<0.01). CONCLUSION:Operation time reduction, better aesthetic results and reduced LR risk support BCT. The Over70 group exhibited better outcomes in terms of LR despite larger tumor dimensions.
| S-EPMC7279857 | biostudies-literature
Project description:Although screening is effective in reducing incidence, mortality, and costs of treating colorectal cancer (CRC), it remains underutilized, in part due to limited insurance access. We used microsimulation to estimate the health and financial effects of insurance expansion and reduction scenarios in North Carolina (NC). We simulated the full lifetime of a simulated population of 3,298,265 residents age-eligible for CRC screening (ages 50-75) during a 5-year period starting January 1, 2018, including polyp incidence and progression and CRC screening, diagnosis, treatment, and mortality. Insurance scenarios included: status quo, which in NC includes access to the Health Insurance Exchange (HIE) under the Affordable Care Act (ACA); no ACA; NC Medicaid expansion, and Medicare-for-all. The insurance expansion scenarios would increase percent up-to-date with screening by 0.3 and 7.1 percentage points for Medicaid expansion and Medicare-for-all, respectively, while insurance reduction would reduce percent up-to-date by 1.1 percentage points, compared to the status quo (51.7% up-to-date), at the end of the 5-year period. Throughout these individuals' lifetimes, this change in CRC screening/testing results in an estimated 498 CRC cases averted with Medicaid expansion and 6031 averted with Medicare-for-all, and an additional 1782 cases if health insurance gains associated with ACA are lost. Estimated cost savings - balancing increased CRC screening/testing costs against decreased cancer treatment costs - are approximately $30?M and $970?M for Medicaid expansion and Medicare-for-all scenarios, respectively, compared to status quo. Insurance expansion is likely to improve CRC screening both overall and in underserved populations while saving money, with the largest savings realized by Medicare.
| S-EPMC7065511 | biostudies-literature
Project description:BackgroundHow sex and age influence post-myocardial infarction (post-MI) outcomes remains unclear. This study evaluated the influence of sex and age on drug therapy, echocardiographic parameters, and outcomes in post-MI patients undergoing percutaneous coronary intervention (PCI).MethodsWe retrospectively enrolled 643 patients with first acute MI who underwent successful PCI and two echocardiographic examinations within 1 year after MI. Clinical characteristics and 4-year follow-up outcomes were compared between sexes and age groups. Primary endpoints were cardiovascular mortality and hospitalization for heart failure (HF).ResultsCompared with males, female patients with MI, particularly older females, had more systemic diseases. Younger females received fewer guideline-directed therapies. Older patients presented with higher left ventricular volume and mass index but no significant differences in left ventricular ejection fraction. The Kaplan-Meier analysis revealed increased mortality in both younger and older females. Elderly patients, particularly older females, exhibited significantly higher post-MI HF incidence but no difference in recurrent MI, ventricular arrhythmia, or revascularization.ConclusionsIn MI patients receiving PCI, outcome differences between sexes are age-dependent. Age influences outcome more heavily in females than in males. Females are likely to exhibit worse overall survival, and older females are at higher risk of post-MI HF.
| S-EPMC6441739 | biostudies-literature
Project description:It is important to understand the amounts and types of money laundering flows, since they have very different effects and, therefore, need different enforcement strategies. Countries that mainly deal with criminals laundering their proceeds locally, need other measures than countries that mainly deal with foreign illegal investments or dirty money just flowing through the country. This paper has two main contributions. First, we unveil the country preferences of money launderers empirically in a systematic way. Former money laundering estimates used assumptions on which country characteristics money launderers are looking for when deciding where to send their ill-gotten gains. Thanks to a unique dataset of transactions suspicious of money laundering, provided by the Dutch Institute infobox Criminal and Unexplained Wealth (iCOV), we can empirically test these assumptions with an econometric gravity model estimation. We use this information for our second contribution: iteratively simulating all money laundering flows around the world. This allows us, for the first time, to provide estimates that distinguish between three different policy challenges: the laundering of domestic crime proceeds, international investment of dirty money and money just flowing through a country.
| S-EPMC7596494 | biostudies-literature
Project description:AimsTo develop methods to disaggregate World Health Orgagnization estimates of tuberculosis (TB) incidence and mortality for each country by sex and age.MethodsFor countries where incidence estimates derived from a factor adjustment of notifications and case detection ratio over 0.85, or with <1000 reported TB cases, we disaggregated incidence proportional to notifications. For each other country, a prior was constructed using a hierarchical model of age-stratified prevalence survey data, meta-analysis of sex ratios, and mathematical modelling for children under 15 years. Samples from this prior were used to disaggregate incidence and accepted if incidence exceeded notifications in each age/sex category. Results were inspected and, if implausible, incidence was disaggregated proportional to notifications. Mortality was disaggregated proportional to patterns in vital registration (VR) data in countries with VR data. Where VR data were lacking, a case-fatality ratio (CFR) approach was applied to estimated incidence, with separate CFRs by HIV/ART status, child/adult age groups, and anti-TB treatment status. Uncertainty in all disaggregated country estimates was constructed to be consistent with corresponding overall uncertainty.ResultsWe generated disaggregated results for 216 countries. For 125 countries, incidence disaggregation was based on notifications. Of the rest, accepted samples from the prior were considered implausible in 4 countries. For 72 countries, mortality disaggregation was based on VR data; the rest were based on the CFR approach.ConclusionsWhile multi-stage, this approach is comparatively simple in overall logic. Disaggregated estimates have relatively larger uncertainty and should be used with caution.
| S-EPMC8128472 | biostudies-literature
Project description:BackgroundReliable evaluations of state-level policies are essential for identifying effective policies and informing policymakers' decisions. State-level policy evaluations commonly use a difference-in-differences (DID) study design; yet within this framework, statistical model specification varies notably across studies. More guidance is needed about which set of statistical models perform best when estimating how state-level policies affect outcomes.MethodsMotivated by applied state-level opioid policy evaluations, we implemented an extensive simulation study to compare the statistical performance of multiple variations of the two-way fixed effect models traditionally used for DID under a range of simulation conditions. We also explored the performance of autoregressive (AR) and GEE models. We simulated policy effects on annual state-level opioid mortality rates and assessed statistical performance using various metrics, including directional bias, magnitude bias, and root mean squared error. We also reported Type I error rates and the rate of correctly rejecting the null hypothesis (e.g., power), given the prevalence of frequentist null hypothesis significance testing in the applied literature.ResultsMost linear models resulted in minimal bias. However, non-linear models and population-weighted versions of classic linear two-way fixed effect and linear GEE models yielded considerable bias (60 to 160%). Further, root mean square error was minimized by linear AR models when we examined crude mortality rates and by negative binomial models when we examined raw death counts. In the context of frequentist hypothesis testing, many models yielded high Type I error rates and very low rates of correctly rejecting the null hypothesis (< 10%), raising concerns of spurious conclusions about policy effectiveness in the opioid literature. When considering performance across models, the linear AR models were optimal in terms of directional bias, root mean squared error, Type I error, and correct rejection rates.ConclusionsThe findings highlight notable limitations of commonly used statistical models for DID designs, which are widely used in opioid policy studies and in state policy evaluations more broadly. In contrast, the optimal model we identified--the AR model--is rarely used in state policy evaluation. We urge applied researchers to move beyond the classic DID paradigm and adopt use of AR models.
| S-EPMC8666265 | biostudies-literature