Linear Time Trend Research Articles

The association between unemployment and suicide among employed and unemployed people in Hong Kong: A time-series analysis

BackgroundUnemployment is associated with suicide. However, it is unclear whether the influence of unemployment is consistent on suicide across subgroups with different employment status. This study aimed to explore the immediate and delayed association between unemployment and suicide among unemployed and employed people in Hong Kong. MethodsQuarterly statistics on labor force, unemployment rate and suicide count by employment status in Hong Kong (2003–2019) were obtained from the Hong Kong Census and Statistics Department and the Coroner's Court suicide reports. Separate negative binomial autoregressive regressions were used to investigate associations between unemployment and suicide among employed and unemployed people. The models controlled for linear and non-linear time trends, seasonal variations, the number of suicide cases, Consumer Price Index, and gender ratios of the labor force in the previous quarter. ResultsAfter controlling for all covariates, every 1% increase in the present unemployment rate was associated with a 15% increase in the suicide rate among the employed people in the current quarter (Incidence Rate Ratio (IRR) = 1.14, 95% CI = 1.01–1.28), and a 13% decrease in the suicide rate among the unemployed in the next quarter (IRR = 0.87, 95% CI = 0.78–0.98). LimitationsMost recent data on suicide cannot be obtained due to processing time of death investigation. ConclusionsThe influence of unemployment differed on suicide by employment status in different time periods. Employed and unemployed people have different needs in different economic conditions. Hence, it is important to provide timely, targeted and effective measures for suicide prevention to the specific group.

Global and regional spending on dementia care from 2000-2019 and expected future health spending scenarios from 2020-2050: An economic modelling exercise.

SummaryBackgroundThe global burden of dementia is increasing. As diagnosis and treatment rates increase and populations grow and age, additional diagnosed cases will present a challenge to healthcare systems globally. Even modelled estimates of the current and future healthcare spending attributable to dementia are valuable for decision makers and advocates to prepare for growing demand.MethodsWe modelled healthcare spending attributable to dementia from 2000 to 2019 and expected estimated future spending from 2020 to 2050 under multiple scenarios. Data were from the Global Burden of Diseases 2019 study and from two systematic literature reviews. We used meta-regression to estimate the fraction of dementia spending that is attributable to dementia for those receiving nursing home-based care and for those receiving community-based care. We used spatiotemporal Gaussian process regression to account for data missingness and model diagnosis and treatment rates, nursing home-based care and community-based care rates, and unit costs for the many countries without their own underlying estimates. Projections of future spending estimate a baseline scenario from 2020 to 2050 based on ongoing growth. Alternative scenarios assessed faster growth rates for dementia diagnosis and treatment rates, nursing home-based care, and healthcare costs. All spending is reported in 2019 United States dollars or 2019 purchasing-power parity-adjusted dollars.FindingsBased on observed and modelled inputs, we estimated that global spending on dementia increased by 4.5% (95% uncertainty interval: 3.4–5.4%) annually from 2000 to 2019, reaching $263 billion (95% uncertainty interval [UI] $199– $333) attributable to dementia in 2019. We estimated total healthcare spending on patients with dementia was $594 billion (95% UI $457–$843). Under the baseline scenario, we estimated that attributable dementia spending will reach $1.6 trillion (95% UI $0.9–$2.6) by 2050. We project it will represent 11% (95% UI 6–18%) of all expected health spending, although it could be as high as 17% (95% UI 10–26%) under alternative scenarios.InterpretationHealth systems will experience increases in the burden of dementia in the near future. These modelled direct cost estimates, built from a relatively small set of data and linear time trends, highlight the magnitude of health system resources expected to be used to provide care and ensure sufficient and adequate resources for aging populations and their caretakers. More data are needed to corroborate these important trends.

Further reductions in the prevalence of obesity in 4-year-old New Zealand children from 2017 to 2019

ObjectiveTo examine whether the prevalence of age- and sex-adjusted BMI at, or above, the 85th, 95th and 99.7th percentiles continues to decline in New Zealand preschool children, over time.MethodsAs part of a national screening programme, 438,972 New Zealand 4-year-old children had their height and weight measured between 2011 and 2019. Age- and sex-adjusted BMI was calculated using WHO Growth Standards and the prevalence of children at, or above, the 85th, 95th, and 99.7th percentiles and at, or below, the 2nd percentile were determined. Log-binomial models were used to estimate linear time trends of ≥85th, ≥95th and ≥99.7th percentiles for the overall sample and separately by sex, deprivation, ethnicity and urban-rural classification.ResultsThe percentage of children at, or above, the 85th, 95th and 99.7th percentile reduced by 4.9% [95% CI: 4.1%, 5.7%], 3.5% [95% CI: 2.9%, 4.1%], and 0.9% [95% CI: 0.7%, 1.2%], respectively, between ‘2011/12’ and ‘2018/19’. There was evidence of a decreasing linear trend (risk reduction, per year) for the percentage of children ≥85th (risk ratio (RR): 0.980 [95% CI: 0.978, 0.982]), ≥95th (RR: 0.966 [95% CI: 0.962, 0.969]) and ≥99.7th (RR: 0.957 [95% CI: 0.950, 0.964]) percentiles. Downward trends were also evident across all socioeconomic indicators (sex, ethnicity, deprivation, and urban-rural classification), for each of the BMI thresholds. Larger absolute decreases were evident for children residing in the most deprived compared with the least deprived areas, at each BMI threshold. There appeared to be no consistent trend for the percentage of children ≤2nd percentile.ConclusionsReassuringly, continued declines of children with age- and sex-adjusted BMI at, or above, the 85th, 95th and 99.7th percentiles are occurring over time, overall and across all sociodemographic indicators, with little evidence for consistent trends in the prevalence of children at, or below, the 2nd percentile.

Carbon intensity of the Japanese Iron and steel Industry: Analysis of factors from 2000 to 2019

In this study, the factors influencing the carbon intensity (tCO2/t crude steel) transition in the Japanese iron and steel industry from FY2000 to FY2019 were empirically evaluated. The results revealed that the upper processes (i.e., the hot-metal ratio, waste plastic, and waste tires), steel product mix, capacity factor, and linear time trend variable explain the actual carbon intensity trajectory reported for the years from FY2000 to FY2019. The upper process and capacity factor were found to be major contributors to the inter-annual fluctuations of carbon intensity. The coefficient of the capacity factor index (FY2005 = 100) was estimated to be −0.23% per 1 percentage point of the capacity factor, indicating that a 1% decrease in the capacity factor resulted in a 0.23% deterioration in the carbon intensity. The coefficient of the time trend variable was estimated to be −0.0034 tCO2/t crude steel/y, which is equivalent to a 0.2%/y average improvement in carbon intensity over the period from FY2000 to FY2019. Because the observed improvement rate of carbon intensity was relatively small, a large-scale diffusion of innovative steelmaking processes such as hydrogen direct reduction will be required to achieve the goal of net zero emissions by 2050.

Changes in prescribing patterns in stage III colon cancer (CC) since the IDEA collaboration.

92 Background: Since the publication of the MOSAIC trial, stage III CC has been treated with a six-month (mo) regimen of FOLFOX (fluorouracil, leucovorin, and oxaliplatin) or CAPOX (capecitabine and oxaliplatin). Recently, the IDEA collaboration challenged this practice by demonstrating that the 3-year rate of disease-free survival (DFS) was non-inferior to 6mo of treatment (Rx) when given for low risk CC (83.1 vs. 83.3%) and resulted in significantly lower rates of grade 2 and higher neuropathy. In high risk (T4, N2) patients (pts) the DFS of 3mo of CAPOX was equivocal to 6mo (64.1 vs. 64.0%), while 3mo of FOLFOX was inferior to 6mo (61.5 vs. 64.7%). We hypothesized that trends in prescribing would favor shorter courses of Rx with a preference towards CAPOX given its efficacy across both high and low risk CC. Methods: We performed a retrospective analysis of stage III CC pts from 4 institutions. We evaluated prescribing patterns of 3mo or 6mo of Rx and CAPOX vs. FOLFOX over a period of 5 years from Jan 2016 to Jan 2021, a time period that traverses before and after the release of IDEA. Logistic and multinomial logistic regression models, with a linear time trend, were used to estimate the percentage of pts receiving CAPOX vs. FOLFOX and the combination of Rx and duration, respectively, while adjusting for baseline characteristics. The prescribing patterns in important subgroups were examined by incorporating the interaction term in the models. Results: A total of 366 pts met inclusion criteria. From 2016-2021, there was a significant increase per quarter in patients treated with CAPOX when compared to FOLFOX (OR 1.16 95% CI 1.11 – 1.21, p <.001). Prior to IDEA, 78.3% of pts received 6mo FOLFOX and 7.4% received 3mo CAPOX. Two years after IDEA, only 17.3% of pts were on 6mo FOLFOX compared to 67.5% of pts on 3mo CAPOX (Table). At present, high risk pts are more likely to receive 6mo FOLFOX (47.8%) than 3mo of FOLFOX (3.9%), 3mo CAPOX (25.8%), or 6mo CAPOX (22.4%). Low risk pts are more likely to receive 3mo of CAPOX (67.9%) than other Rx. Conclusions: Our findings suggest that since IDEA, physician practice has significantly changed in favor of CAPOX and shorter courses of Rx. The use of CAPOX has significantly increased overall, presumably due to its efficacy across all risk groups and relatively reduced toxicity.[Table: see text]

The epidemiology of desmoid tumors in Denmark

Introduction/aimThe epidemiology, demographic, clinical, treatment, and healthcare resource utilization (HRU) characteristics of desmoid tumor (DT) patients treated at two sarcoma centers in Denmark is described. MethodsUsing Danish health registers, we studied DT patients treated at two sarcoma centers between 2009 and 2018. For each patient, ten persons from the general population were randomly matched on birth year, sex, and region of residence. ResultsOf the 179 DT patients identified, 76% were female and the median patient age was 38 years at diagnosis (interquartile range: 31–50). An average annual incidence of DTs over the study period was 3.2 per 1000,000 individuals with the observed annual incidence of DTs ranging from 2.2 (2011) to 4.3 (2017) per 1000,000 individuals. No notable linear time trend in incidence was observed. Anatomical DT sites included extra-abdominal (49%), abdominal wall (40%), and intra-abdominal or retroperitoneal areas (8%). In total, 56% of patients were initially treated surgically. However, while 75% of patients diagnosed with DT between 2009 and 2014 were initially treated surgically, this was true for only 32% of patients diagnosed with DT between 2015 and 2018. A total of 56% of DT patients used chemotherapeutic agents, tyrosine kinase inhibitors, NSAIDs, opioids, antidepressants, or steroids at some point during the three years before their DT diagnoses. In contrast, 70% of surgically treated and 63% of non-surgically treated patients used one of these drugs in the subsequent three years, including NSAIDs (45% surgical vs. 33% non-surgical), opioids (39% surgical vs. 27% non-surgical), and steroids (22% surgical vs. 18% non-surgical). The average number of inpatient and outpatient visits, days of hospitalization, and additional surgical procedures were higher among DT patients than the comparison cohort. ConclusionDTs are rare but have a large impact on patients’ health, HRU, and medication utilization.

Enterprise Financial Asset Risk Measurement Based on Embedded Microprocessor Security Analysis

As the volatility of financial markets continues to increase, the risk structure involved in financial derivatives has become more and more complex. The harmful effects of financial risks can put the company in trouble. Only by understanding the correlation between financial assets can we more accurately measure the risk of a company’s financial assets. This article is aimed at studying the company’s financial asset risk measurement method based on integrated microprocessor security analysis, so that enterprises can effectively manage the risk of financial assets. This paper randomly selects 10 variables related to demographic characteristics, customer needs, and consumption characteristics of 850 customers from the historical customer data of a bank that has been abandoned for customer market segmentation research. Based on the theoretical basis of customer value evaluation, the factor analysis method refers to a multivariate statistical analysis method that starts from the internal dependence relationship of the research index correlation matrix and reduces some variables with overlapping information and intricate relationships into a few unrelated comprehensive factors. The basic idea is to group variables according to the size of the correlation, so that the correlation between the variables in the same group is higher, but the variables of different groups are not correlated or correlated, and each group of variables represents a basic structure—the common factor. This paper uses the factor analysis model in statistical principles to analyze the main factors affecting the pricing of deposit products, and we can obtain three quantitative common factors: customers related to the customer’s willingness to pay demand value, customer loyalty factor, and customer cost factor. Then, the variance contribution rate of the three factors to all observable variables is weighted and converted into the net customer relationship value, at the same time, the embedded microprocessor evolved from the CPU in the general-purpose computer. Its characteristic is that it has a 32-bit or more processor and has high performance. In actual embedded applications, it only retains closeness to embedded applications. Related functional hardware, removing other redundant functional parts so that the special requirements of embedded applications can be realized with the lowest power consumption and resources. Before constructing the structural equation model, it is necessary to test the reliability and validity of the sample data. The data selected in this paper are panel data. In order to judge whether the data is stable, the panel unit root test should be carried out. This article chooses LLC to verify the stability of the panel data. Individual fixed effects and linear time trends are added to the test, and the lag order of the difference lag is 0. Among the intermediary business income of joint-stock commercial banks, bank card fee income accounts for the largest proportion, with China Everbright Bank accounting for 70.12% and China CITIC Bank accounting for 54.16%. The research results show that with the continuous increase of Internet penetration rate, the impact of corporate finance on commercial banks shows phased characteristics. The corporate financial risk measurement method studied in this paper can provide effective help for risk monitoring and early warning. Risk measurement is a management activity that uses certain methods to determine and quantify the possibility of a company’s future financial results deviating from expected financial goals due to various uncertain factors. In practice, it is generally analyzed by a combination of qualitative and quantitative, subjective, and objective methods.

The probabilities of type I and II error of null of cointegration tests: A Monte Carlo comparison.

This paper evaluates the performance of eight tests with null hypothesis of cointegration on basis of probabilities of type I and II errors using Monte Carlo simulations. This study uses a variety of 132 different data generations covering three cases of deterministic part and four sample sizes. The three cases of deterministic part considered are: absence of both intercept and linear time trend, presence of only the intercept and presence of both the intercept and linear time trend. It is found that all of tests have either larger or smaller probabilities of type I error and concluded that tests face either problems of over rejection or under rejection, when asymptotic critical values are used. It is also concluded that use of simulated critical values leads to controlled probability of type I error. So, the use of asymptotic critical values may be avoided, and the use of simulated critical values is highly recommended. It is found and concluded that the simple LM test based on KPSS statistic performs better than rest for all specifications of deterministic part and sample sizes.

Pagellus genus catches time series in the FAO Major Fishing Areas 27 and 34: Analysis of fishery behaviour

Based on, catch reconstructed data, we constructed the fisheries of the Pagellus genus between 1950 and 2014 in FAO Major Fishing Areas 27 and 34 and overall by continent and by species, namely, Pagellus acarne, Pagellus bellottii, Pagellus bogaraveo and Pagellus erythrinus. Additionally, we considered the group Pagellus sp. to include species identified to the genus level only. Regression of estimates of linear time trends, change point analysis and autoregressive integrated moving average (ARIMA) models revealed significant variations and historical changes in catch time series, the trend being a primarily downward with a progressive increase in the intensity of fishing pressure on the populations of this genus. This situation may be attributable to regulatory and technological transitions and environmental variability, as well as the biology of the species. For this reason, the results of this multi-species study may be useful, in guiding changes for more management and more sustainable fisheries, helping to achieve proper governance of this resource.

Beyond Dyadic Coupling: The Method of Multivariate Surrogate Synchrony (mv-SUSY).

Measuring interpersonal synchrony is a promising approach to assess the complexity of social interaction, which however has been mostly limited to dyads. In this study, we introduce multivariate Surrogate Synchrony (mv-SUSY) to extend the current set of computational methods. Methods: mv-SUSY was applied to eight datasets consisting of 10 time series each, all with n = 9600 observations. Datasets 1 to 5 consist of simulated time series with the following characteristics: white noise (dataset 1), non-stationarity with linear time trends (dataset 2), autocorrelation (dataset 3), oscillation (dataset 4), and multivariate correlation (dataset 5). Datasets 6 to 8 comprise empirical multivariate movement data of two individuals (datasets 6 and 7) and between members of a group discussion (dataset 8.) Results: As hypothesized, findings of mv-SUSY revealed absence of synchrony in datasets 1 to 4 and presence of synchrony in dataset 5. In the empirical datasets, mv-SUSY indicated significant movement synchrony. These results were predominantly replicated by two well-established dyadic synchrony approaches, Surrogate Synchrony (SUSY) and Surrogate Concordance (SUCO). Conclusions: The study applied and evaluated a novel synchrony approach, mv-SUSY. We demonstrated the feasibility and validity of estimating multivariate nonverbal synchrony within and between individuals by mv-SUSY.

Physician Network Connections Associated With Faster De-Adoption of Dronedarone for Permanent Atrial Fibrillation.

Physicians' professional networks are an important source of new medical information and have been shown to influence the adoption of new treatments, but it is unknown how physician networks impact the de-adoption of harmful practices. We analyzed changes in physicians' use of dronedarone after the PALLAS trial (Palbociclib Collaborative Adjuvant Study; November 2011) showed that dronedarone increased the risk of death from cardiovascular events among patients with permanent atrial fibrillation. Deidentified administrative claims from the OptumLabs Data Warehouse were combined with physicians' demographic information from the Doximity database and publicly available data on physicians' patient-sharing relationships compiled by the Centers for Medicare and Medicaid Services. We used a linear probability model with an interrupted linear time trend specification to model the impact of the PALLAS trial on physicians' dronedarone usage between 2009 and 2014. Before the PALLAS trial, the use of dronedarone was increasing by 0.22 percentage points per quarter (95% CI, 0.19-0.25) in our Medicare Advantage sample (N=343 429 patient-quarter observations) and 0.63 percentage points per quarter (95% CI, 0.52-0.75) in our commercially insured sample (N=44 402 patient-quarter observations). After the PALLAS trial and subsequent United States Food and Drug Administration black box warning, physicians in the Medicare Advantage sample with an above-median number of network connections to other physicians decreased their quarterly usage of dronedarone by 0.12 percentage points more per quarter (95% CI, -0.20 to -0.04; P=0.031) than physicians with equal to or below the median number of network connections. Similar patterns existed in the commercially insured sample (P=0.0318). After controlling for a wide range of patient, physician, and geographic characteristics, physicians with a greater number of network connections were faster de-adopters of dronedarone for patients with permanent atrial fibrillation after the PALLAS trial and subsequent United States Food and Drug Administration black box warning detailed the harmfulness of dronedarone for these patients. Policies for improving physicians' responsiveness to new medical information should consider utilizing the influence of these important professional network relationships.

Intersectionality of serious psychological distress, cigarette smoking, and substance use disorders in the United States: 2008–2018

BackgroundSerious psychological distress (SPD) is common among adults who smoke cigarettes and among adults with substance use disorders (SUD). It is unknown whether the burden of SPD is even greater among individuals with both cigarette smoking and SUDs. This study examined the intersectionality of SPD, cigarette smoking, and SUD over time. MethodsData came from annual, cross-sectional, nationally representative samples of the United States (US) National Survey on Drug Use and Health (individuals age 12+). Past-month SPD prevalences were estimated each year from 2008 to 2018 for adults age 18+ with current daily, current non-daily, former, and never cigarette smoking by SUD status (combined n = 441,286). Logistic regression models examined linear time trends of SPD. ResultsIn 2018, SPD was significantly more prevalent among adults in each smoking group with SUD versus those without SUD (daily 29.1% vs. 9.0%, non-daily 23.2% vs. 8.6%, former 19.5% vs. 3.2%, never 16.4% vs. 4.3%). After adjusting for sociodemographics, SPD prevalence increased over time across smoking statuses with a larger change for persons with SUD (AOR=1.07; 95% CI: 1.06, 1.09) vs. no SUD (AOR=1.03; 95% CI: 1.02. 1.04). ConclusionsSPD was more than twice as common among adults with SUD who smoke cigarettes compared to those without SUD who do not smoke cigarettes, with the highest prevalence among adults with both SUD and daily smoking. While SPD has increased over time, differences depended on SUD status beyond the effect of cigarette smoking. These results provide further evidence for treating smoking and mental health problems together.

The spectral analysis of the Hodrick–Prescott filter

The Hodrick–Prescott (HP) filter is a commonly used tool in macroeconomics to obtain the HP filter trend of a macroeconomic variable. In macroeconomics, the difference between the original series and this trend is called the ‘cyclical component’. In this article, we derive the autocovariance function and the spectrum of the cyclical component of a series that consists of a constant, a linear time trend, a unit root process, and a weakly stationary process. We show that the autocovariance function of the cyclical component of such a series depends on (i) the autocovariance of the innovations of the unit root process; (ii) the autocovariance of the weakly stationary process and; (iii) a component of the weights of the HP filter that is important in the middle of a large sample. The result for the spectrum of the cyclical component matches with earlier results in the literature that were obtained by using an approximate approach. Lastly, we derive the cross‐covariance function and the cross‐spectrum of the cyclical components of two cointegrated series.

A roadmap to using randomization in clinical trials

BackgroundRandomization is the foundation of any clinical trial involving treatment comparison. It helps mitigate selection bias, promotes similarity of treatment groups with respect to important known and unknown confounders, and contributes to the validity of statistical tests. Various restricted randomization procedures with different probabilistic structures and different statistical properties are available. The goal of this paper is to present a systematic roadmap for the choice and application of a restricted randomization procedure in a clinical trial.MethodsWe survey available restricted randomization procedures for sequential allocation of subjects in a randomized, comparative, parallel group clinical trial with equal (1:1) allocation. We explore statistical properties of these procedures, including balance/randomness tradeoff, type I error rate and power. We perform head-to-head comparisons of different procedures through simulation under various experimental scenarios, including cases when common model assumptions are violated. We also provide some real-life clinical trial examples to illustrate the thinking process for selecting a randomization procedure for implementation in practice.ResultsRestricted randomization procedures targeting 1:1 allocation vary in the degree of balance/randomness they induce, and more importantly, they vary in terms of validity and efficiency of statistical inference when common model assumptions are violated (e.g. when outcomes are affected by a linear time trend; measurement error distribution is misspecified; or selection bias is introduced in the experiment). Some procedures are more robust than others. Covariate-adjusted analysis may be essential to ensure validity of the results. Special considerations are required when selecting a randomization procedure for a clinical trial with very small sample size.ConclusionsThe choice of randomization design, data analytic technique (parametric or nonparametric), and analysis strategy (randomization-based or population model-based) are all very important considerations. Randomization-based tests are robust and valid alternatives to likelihood-based tests and should be considered more frequently by clinical investigators.

Should I stay or should I go? Embracing causal heterogeneity in the study of pandemic policy and citizen behavior

AbstractObjectiveTo test for multicausality between government policy, health outcomes, economic performance, and citizen behavior during the COVID‐19 global pandemic.MethodsWe perform Granger‐causality tests to explore the interrelationship between four endogenous variables, social distancing policy, home isolation, balance rate, and average weekly COVID‐19 deaths, in the 26 states of Brazil. As exogenous variables, we included a linear time trend and a dummy for the week in which the World Health Organization (WHO) declared COVID‐19 a global pandemic.ResultsOur analysis of Granger causal ordering between the four variables demonstrates that there is significant heterogeneity across the Brazilian federation. These findings can be interpreted as underscoring that there is no common model applicable to all states, and that the dynamics are context‐dependent.ConclusionOur suggested approach allows researchers to account for the complex interrelationship between government policy, citizen behavior, the economy, and COVID‐related health outcomes.

Nest survival of the threatened Campo Miner Geositta poeciloptera: a tropical cavity‐nesting grassland bird

AbstractNest survival is a key step in the reproductive biology of birds and is essential for understanding the strategies used to improve the chances of nest success. Here we studied the main factors driving nesting success of the Campo Miner Geositta poeciloptera (Scleruridae), a threatened Neotropical grassland bird that nests in cavities, usually along steep soil banks. We calculated the apparent success and modelled daily nest survival rates (DSR) based on 86 nests monitored to investigate the effects of nest‐related covariates on the nest survival. In the DSR modelling, we looked at the effects of reproductive phase (incubation and nestling periods), breeding seasons (years), temporal‐trends (linear and quadratic) rainfall and nest’s individual covariates (height, distance from the top of the cavity to the top of the bank, cavity depth and cavity entrance area). The overall apparent nest success was 58% and estimates based on DSRs were ˜45%. Nest phase, cavity entrance area, nest height and a linear time trend were the main factors influencing DSRs. The survival during incubation was lower (˜54%) than during the nestling period (˜83%), and both phases showed higher values in the beginning of the breeding season. Predation was the main driver of nest failure (23.3%, N = 20), followed by nest abandonment (10.5%, N = 9) and nest usurpation (7%, N = 6). Our results allow us to better understand and conserve this threatened species and also shed light in the reproductive ecology of a whole family endemic to the Neotropics.

Child Undernutrition following the Introduction of a Large-Scale Toilet Construction Campaign in India.

Lack of toilets and the widespread practice of open defecation may contribute to India's large burden of child undernutrition. We examine whether a large national sanitation campaign launched in 2014, the Swachh Bharat Mission (SBM), precedes a reduction in stunting and wasting among under 5-y-old (u5) children in India. In this observational study, we used district-level data from before (2013-2014) and after (2015-2016) SBM from 3 national surveys to derive, as our outcomes, the percentage of u5 children per district who are stunted and wasted. We defined our exposures as 1) binary indicator of SBM and 2) percentage of households with toilets per district. Our analytic sample comprised nearly all 640 Indian districts (with ∼1200 rural/urban divisions per district per time point). Linear regression analyses controlled for baseline differences in districts, linear time trends by state, and relevant covariates. Relative to pre-SBM, u5 stunting declines by 0.06% (95% CI: -0.10, -0.01; P=0.009) with every percentage increase in households with toilets post-SBM. Rural regions and districts with higher pre-SBM toilet availability show greater decline in u5 stunting post-SBM. An increase in toilet availability on a national scale, precipitated by the SBM sanitation campaign, is associated with a reduction in undernutrition among u5 children in India over the early phase of the campaign.

Study of the trend pattern of COVID-19 using spline-based time series model: a Bayesian paradigm.

A vast majority of the countries are under economic and health crises due to the current epidemic of coronavirus disease 2019 (COVID-19). The present study analyzes the COVID-19 using time series, an essential gizmo for knowing the enlargement of infection and its changing behavior, especially the trending model. We consider an autoregressive model with a non-linear time trend component that approximately converts into the linear trend using the spline function. The spline function splits the series of COVID-19 into different piecewise segments between respective knots in the form of various growth stages and fits the linear time trend. First, we obtain the number of knots with their locations in the COVID-19 series to identify the transmission stages of COVID-19 infection. Then, the estimation of the model parameters is obtained under the Bayesian setup for the best-fitted model. The results advocate that the proposed model appropriately determines the location of knots based on different transmission stages and know the current transmission situation of the COVID-19 pandemic in a country.

Post-Schooling off-The-Job training and its benefits

Post-schooling off-the-job training (Off-JT) is common, but little is known about how recent benefits vary across levels of formal education. Using a fixed-effects difference-in-differences regression coupled with the National Longitudinal Study of Youth 1997 data, I estimate how Off-JT certificate completion impacts employment and real (2014) annual income. Among those with a college degree, there is a significant increase in annual income. The total effect when individual-specific linear time trends are included ranges from $4,803.6 to $5,844.7. In contrast, for those with less than a college degree there is no significant change in income, despite a significant increase in employment. This is likely due to the small impact on hours worked for those without a college degree (an increase of 27 hours over the year, on average). The results suggest that the recent returns to Off-JT certificate completion depend on the formal level of education acquired prior to Off-JT.

High School Seniors Who Used E-Cigarettes May Have Otherwise Been Cigarette Smokers: Evidence From Monitoring the Future (United States, 2009–2018)

Abstract Introduction Studies have indicated that youth who use e-cigarettes are more likely to progress to cigarette smoking; however, the likelihood that these youth would have used tobacco products in the pre-vaping era is unclear. Aims and Methods This study sought to determine whether youth who used e-cigarettes in 2014–2018 would have likely been smokers in the period preceding e-cigarette availability. Analyzing Monitoring the Future 12th grade data (United States, 2009–2018), we forecasted the prevalence of current smoking with logistic regression-derived propensity scores. Models predicted smoking for all subsequent years, incorporating sociodemographic, family, alcohol, and school-related variables, and a linear time trend. We compared forecasted to observed smoking prevalence annually, and prevalence of current e-cigarette use among nonsmokers across smoking propensity tertiles. Results Until 2014, observed smoking prevalence mirrored forecasted prevalence. Afterward, forecasted rates consistently overestimated prevalence. Among nonsmoking youth, e-cigarette use was lowest among those with lowest predicted probability of cigarette smoking (3.8%; 95% confidence interval [CI]: 3.3, 4.4) and highest among those with highest probability (23.5%; 95% CI: 22.2, 24.9). Conclusions Youth e-cigarette use has increased rapidly, with high prevalence among nonsmoking youth. However, the decline in current smoking among 12th graders has accelerated since e-cigarettes have become available. E-cigarette use is largely concentrated among youth who share characteristics with smokers of the pre-vaping era, suggesting e-cigarettes may have replaced cigarette smoking. Implications Among nonsmoking youth, vaping is largely concentrated among those who would have likely smoked prior to the introduction of e-cigarettes, and the introduction of e-cigarettes has coincided with an acceleration in the decline in youth smoking rates. E-cigarettes may be an important tool for population-level harm reduction, even considering their impact on youth.