Percentage Points Research Articles

RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration.

Successful point cloud registration relies on accurate correspondences established upon powerful descriptors. However, existing neural descriptors either leverage a rotation-variant backbone whose performance declines under large rotations, or encode local geometry that is less distinctive. To address this issue, we introduce RIGA to learn descriptors that are Rotation-Invariant by design and Globally-Aware. From the Point Pair Features (PPFs) of sparse local regions, rotation-invariant local geometry is encoded into geometric descriptors. Global awareness of 3D structures and geometric context is subsequently incorporated, both in a rotation-invariant fashion. More specifically, 3D structures of the whole frame are first represented by our global PPF signatures, from which structural descriptors are learned to help geometric descriptors sense the 3D world beyond local regions. Geometric context from the whole scene is then globally aggregated into descriptors. Finally, the description of sparse regions is interpolated to dense point descriptors, from which correspondences are extracted for registration. To validate our approach, we conduct extensive experiments on both object- and scene-level data. With large rotations, RIGA surpasses the state-of-the-art methods by a margin of 8 ° in terms of the Relative Rotation Error on ModelNet40 and improves the Feature Matching Recall by at least 5 percentage points on 3DLoMatch.

Accuracy of continuous glucose monitoring during exercise-related hypoglycemia in individuals with type 1 diabetes

BackgroundHypoglycemia is common in individuals with type 1 diabetes, especially during exercise. We investigated the accuracy of two different continuous glucose monitoring systems during exercise-related hypoglycemia in an experimental setting.Materials and methodsFifteen individuals with type 1 diabetes participated in two separate euglycemic-hypoglycemic clamp days (Clamp-exercise and Clamp-rest) including five phases: 1) baseline euglycemia, 2) plasma glucose (PG) decline ± exercise, 3) 15-minute hypoglycemia ± exercise, 4) 45-minute hypoglycemia, and 5) recovery euglycemia. Interstitial PG levels were measured every five minutes, using Dexcom G6 (DG6) and FreeStyle Libre 1 (FSL1). Yellow Springs Instruments 2900 was used as PG reference method, enabling mean absolute relative difference (MARD) assessment for each phase and Clarke error grid analysis for each day.ResultsExercise had a negative effect on FSL1 accuracy in phase 2 and 3 compared to rest (ΔMARD = +5.3 percentage points [(95% CI): 1.6, 9.1] and +13.5 percentage points [6.4, 20.5], respectively). In contrast, exercise had a positive effect on DG6 accuracy during phase 2 and 4 compared to rest (ΔMARD = -6.2 percentage points [-11.2, -1.2] and -8.4 percentage points [-12.4, -4.3], respectively). Clarke error grid analysis showed a decrease in clinically acceptable treatment decisions during Clamp-exercise for FSL1 while a contrary increase was observed for DG6.ConclusionPhysical exercise had clinically relevant impact on the accuracy of the investigated continuous glucose monitoring systems and their ability to accurately detect hypoglycemia.

A fused multi-subfrequency bands and CBAM SSVEP-BCI classification method based on convolutional neural network.

For the brain-computer interface (BCI) system based on steady-state visual evoked potential (SSVEP), it is difficult to obtain satisfactory classification performance for short-time window SSVEP signals by traditional methods. In this paper, a fused multi-subfrequency bands and convolutional block attention module (CBAM) classification method based on convolutional neural network (CBAM-CNN) is proposed for discerning SSVEP-BCI tasks. This method extracts multi-subfrequency bands SSVEP signals as the initial input of the network model, and then carries out feature fusion on all feature inputs. In addition, CBAM is embedded in both parts of the initial input and feature fusion for adaptive feature refinement. To verify the effectiveness of the proposed method, this study uses the datasets of Inner Mongolia University of Technology (IMUT) and Tsinghua University (THU) to evaluate the performance of the proposed method. The experimental results show that the highest accuracy of CBAM-CNN reaches 0.9813 percentage point (pp). Within 0.1-2s time window, the accuracy of CBAM-CNN is 0.0201-0.5388 (pp) higher than that of CNN, CCA-CWT-SVM, CCA-SVM, CCA-GNB, FBCCA, and CCA. Especially in the short-time window range of 0.1-1s, the performance advantage of CBAM-CNN is more significant. The maximum information transmission rate (ITR) of CBAM-CNN is 503.87bit/min, which is 227.53bit/min-503.41bit/min higher than the above six EEG decoding methods. The study further results show that CBAM-CNN has potential application value in SSVEP decoding.

Open-Set Recognition of Individual Cows Based on Spatial Feature Transformation and Metric Learning

The automated recognition of individual cows is foundational for implementing intelligent farming. Traditional methods of individual cow recognition from an overhead perspective primarily rely on singular back features and perform poorly for cows with diverse orientation distributions and partial body visibility in the frame. This study proposes an open-set method for individual cow recognition based on spatial feature transformation and metric learning to address these issues. Initially, a spatial transformation deep feature extraction module, ResSTN, which incorporates preprocessing techniques, was designed to effectively address the low recognition rate caused by the diverse orientation distribution of individual cows. Subsequently, by constructing an open-set recognition framework that integrates three attention mechanisms, four loss functions, and four distance metric methods and exploring the impact of each component on recognition performance, this study achieves refined and optimized model configurations. Lastly, introducing moderate cropping and random occlusion strategies during the data-loading phase enhances the model’s ability to recognize partially visible individuals. The method proposed in this study achieves a recognition accuracy of 94.58% in open-set scenarios for individual cows in overhead images, with an average accuracy improvement of 2.98 percentage points for cows with diverse orientation distributions, and also demonstrates an improved recognition performance for partially visible and randomly occluded individual cows. This validates the effectiveness of the proposed method in open-set recognition, showing significant potential for application in precision cattle farming management.

Hypoglycemia and Hyperglycemia According to Type of Diabetes: Observations During Fully Closed-Loop Insulin Delivery in Adults With Type 1 and Type 2 Diabetes.

CamAPS HX fully closed-loop (FCL) system, with no user input required at mealtimes, has been shown to be safe and effective in adults with type 1 and type 2 diabetes. We assessed whether time spent in hypoglycemia and hyperglycemia during FCL insulin delivery in adults varied by type of diabetes over the 24-hour period. We retrospectively analyzed eight weeks of data from 52 participants (adults with type 1 diabetes and adults with insulin-treated type 2 diabetes) recruited to two single-center randomized controlled studies using FCL insulin delivery during unrestricted-living conditions. Key outcomes were time spent in hypoglycemia <70 mg/dL and marked hyperglycemia >300 mg/dL by type of diabetes. The median percentage of time spent in hypoglycemia <70 mg/dL over the 24-hour period was lower for those with type 2 diabetes than for those with type 1 diabetes (median [interquartile range (IQR)] 0.43% [0.20-0.77] vs 0.86%, [0.54-1.46]; mean difference 0.46 percentage points [95% CI 0.23-0.70]; P < .001). Median percentage time in marked hyperglycemia >300 mg/dL was lower for those with type 2 diabetes than for those with type 1 diabetes (median [IQR] 1.8% [0.6-3.5] vs 9.3% [6.9-11.8]; mean difference 7.8 percentage points [95% CI 5.5-10.0]; P < .001). Using the FCL system, hypoglycemia and marked hyperglycemia exposure were lower in type 2 diabetes than in type 1 diabetes.

Impact of Family Group Conference Referrals at Pre-Proceedings Stage on Child Outcomes: A Randomised Controlled Trial

Abstract Previous evidence on the impact of Family Group Conferencing in the UK cannot establish causality. This article presents results from the first UK randomised controlled trial of Family Group Conferences. All families entering pre-proceedings between September 2020 and May 2022 in twenty-one local authorities in England were eligible for inclusion in the trial. In total, 1,511 families were randomised and child outcomes were collected from administrative data until up to twenty-one months post-referral. Half of the families were randomly allocated to be referred for a Family Group Conference, on top of usual practice during pre-proceedings. The (pre-registered) primary outcome is the child’s looked-after status twelve months after the pre-proceedings letter. This was 8.6 percentage points lower among referred families (36.2 percent vs 44.8 percent). Children were also less likely to have care proceedings issued (59.2 percent vs 71.7 percent) and spent less time in care (87 vs. 115 days). However, there was no significant difference in whether a child’s living arrangement remained the same or changed in the months after the decision. These findings have implications for the support given to families during pre-proceedings; they provide evidence in favour of Family Group Conferences as a way to reduce the chances of children going into care.

Understanding Global Commodity Price Shocks on Exchange Rates and Inflation in Emerging Economies: ARDL Perspective

Aims: To analyze the changing relationship between commodity prices (cocoa, diesel, gold, oil, petrol) and macroeconomic factors (exchange rate and inflation) in Ghana and differentiate between long-term and short-term effects.&#x0D; Study Design: Quantitative Design with Time series analysis using the Autoregressive Distributed Lag (ARDL) technique.&#x0D; Methodology: The study utilized cointegration and Error Correction Model in econometric estimation. Time series data for commodity prices and macroeconomic factors were collected for the period 2003M01 to 2023M10. The ARDL technique was applied to differentiate between long-term and short-term effects of inflation and exchange rates.&#x0D; Results: The short-run and long-run results indicate a positive relationship between commodity prices and inflation and exchange rates. A 1% increase in diesel prices is associated with a 0.23% appreciation in Ghana's currency in the short run (p=0.019) and a 1.76% rise in inflation in the long run (p=0.012). Past inflation has a dominant influence on current inflation, with a 1 percentage point increase in the previous year's inflation leading to a 0.45 percentage point increase in the current inflation rate.&#x0D; Conclusion:  Policymakers should prioritize stabilizing diesel prices, invest in storage facilities, promote alternative energy sources, strengthen domestic production and distribution of essential commodities, and adopt targeted monetary and fiscal policies to anchor inflationary expectations and address inflation inertia in Ghana.

Effect of Face Masks on Automatic Speech Recognition Accuracy for Mandarin

Automatic speech recognition (ASR) has been widely used to realize daily human–machine interactions. Face masks have become everyday wear in our post-pandemic life, and speech through masks may have impaired the ASR. This study explored the effects of different kinds of face masks (e.g., surgical mask, KN95 mask, and cloth mask) on the Mandarin word accuracy of two ASR systems with or without noises. A mouth simulator was used to play speech audio with or without wearing a mask. Acoustic signals were recorded at distances of 0.2 m and 0.6 m. Recordings were mixed with two noises at a signal-to-noise ratio of +3 dB: restaurant noise and speech-shaped noise. Results showed that masks did not affect ASR accuracy without noise. Under noises, masks did not significantly influence ASR accuracy at 0.2 m but had significant effects at 0.6 m. The activated-carbon mask had the most significant impact on ASR accuracy at 0.6 m, reducing the accuracy by 18.5 percentage points compared to that without a mask, whereas the cloth mask had the least effect on ASR accuracy at 0.6 m, reducing the accuracy by 0.9 percentage points. The acoustic attenuation of masks on the high-frequency band at around 3.15 kHz of the speech signal attributed to the effects of masks on ASR accuracy. When training ASR models, it may be important to consider mask robustness.

Effectiveness of Value Added Tax (VAT) analysis in Nepal

This research aims to assess the evasion of the Value added tax in Nepal. The specific objectives are: evaluating the VAT evasion on the Nepalese economy; the study follows explanatory research designs. The primary data is collected by conducting field survey using pre-structured questionnaires. Altogether 400 respondents from the four categories are interviewed: 100 from VAT payers, 100 from VAT administration, 100 from VAT experts and 100 from business community all over the country, respondents were requested to indicate their degree of conformity with specified statements using 5-point scale.&#x0D; The results of the regression model shows that the expected sign of the variable included in the model as per priory expectation. VAT rate complication and complex legal provisions are negatively related, while administrative efficiency and incentive for VAT collection are positively related with VAT collection efficiency. The computed F-statistic is also higher than table value at 95% level of significance. The coefficient of VRC is 0.08932, meaning that the change in 1% on VAT rate will decreases in VAT effectiveness by 0.089 percent point. The regression model shows that the t-statistic 1.135 and p-value 0.2569&gt;0.05 not significant at 5%. Therefore, the null hypothesis is accepted, indicating that VAT rate has no significant impact on VAT effectiveness.

Racial and Ethnic Disparities in Attendance to Well-Child Visit Recommendations during COVID-19

ObjectivesTo measure the impact of the COVID-19 pandemic on racial and ethnic disparities in attendance to well-child visit recommendations. MethodsWe used the nationally representative Medical Expenditure Panel Survey (MEPS) to compare pre-pandemic (2018-2019) and pandemic (2020 and 2021) ratios of well-child visits to age-based recommendations, presenting both unadjusted and adjusted attendance disparities over time. We also used the 1996-2021 MEPS to place the pandemic changes in an historical context. ResultsAverage attendance decreased from 66.6% in 2018-2019 (95% confidence interval [CI]: 64.1, 69.1) to 58.6% in 2020 (95% CI: 55.5, 61.6), rebounding to 65.1% in 2021 (95% CI: 61.5, 68.7). The unadjusted disparity in attendance between White non-Hispanic and Black non-Hispanic children widened from 9.6 percentage points in 2018-2019 (95% CI: 2.8, 16.4) to 24.8 percentage points in 2020 (95% CI: 17.5, 32.2) and 21.4 percentage points in 2021 (95% CI: 11.2, 31.5). The unadjusted disparity in attendance between White non-Hispanic and Hispanic children widened from 14.8 percentage points in 2018-2019 (95% CI: 9.7, 19.8) to 26.3 percentage points in 2020 (95% CI: 19.9, 32.7) and 24.9 percentage points in 2021 (95% CI: 17.5, 32.3). Changes in disparities were large even when we controlled for health status, demographic and socioeconomic characteristics, health insurance, and state of residence. Magnitudes of the racial and ethnic attendance disparities during the pandemic’s first two years were unprecedented since before 1996. ConclusionsWidening attendance disparities during the pandemic highlight the need to build a more equitable healthcare system for all children. WHAT’S NEWUsing nationally representative household data we show that racial and ethnic disparities in attendance to well-child visit recommendations widened to unprecedented levels during the first two years of the COVID-19 pandemic.

Using the WHO individual near miss case review (NMCR) cycle to improve quality of emergency obstetric care and maternal outcome in Keren hospital, Eritrea: an interrupted time series analysis

BackgroundIn 2016, the WHO regional office for Europe prepared a manual for conducting routine facility based individual near miss case review cycle. This study evaluates the effectiveness of the individual near miss case review (NMCR) cycle in improving quality of emergency obstetric care and maternal outcome in Keren hospital.MethodsAn interrupted time series design was used to achieve the objectives of this study. Monthly data on women with potentially life-threatening conditions (PLTCs) admitted between April 2018 and October 2022 (i.e. 33 months pre-implementation and 22 months post-implementation) were collected from medical records. Segmented regression analysis was used to assess the intervention’s effect on three process and outcome measures, namely, SMO, delayed care, and substandard care. The intervention was expected a priori to show immediate improvements without time-lag followed by gradual increment in slope. Segmented regression analyses were performed using the “itsa’ command in STATA.ResultsDuring the entire study period, 4365 women with potentially life threatening conditions were identified. There was a significant reduction in the post-implementation period in the proportion of mothers with PLTC who experienced SMO (− 8.86; p <  0.001), delayed care (− 8.76; p <  0.001) and substandard care (− 5.58; p <  0.001) compared to pre-implementation period. Results from the segmented regression analysis revealed that the percentage of women with SMO showed a significant 4.75% (95% CI: − 6.95 to − 2.54, p <  0.001) reduction in level followed by 0.28 percentage points monthly (95% CI: − 0.37 to − 0.14, p <  0.001) drop in trend. Similarly, a significant drop of 3.50% (95% CI: − 4.74 to − 2.26, p <  0.001) in the level of substandard care along with a significant decrease of 0.21 percentage points (95% CI: − 0.28 to − 0.14, p < 0.001) in the slope of the regression line was observed. The proportion of women who received delayed care also showed a significant 7% (95% CI: − 9.28 to − 4.68, p < 0.001) reduction in post-implementation level without significant change in slope.ConclusionsOur findings suggest that the WHO individual NMCR cycle was associated with substantial improvements in quality of emergency obstetric care and maternal outcome. The intervention also bears a great potential for scaling-up following the guidance provided in the WHO NMCR manual.

Resilience of territorial communities amid the war against Ukraine: The role of budgetary instruments

Russia’s war against Ukraine has exacerbated challenges and risks to community development. Improving the ability to withstand the shocks of the external and internal environment, adapt to changes in the security environment, respond to threats, maintain sustainable functioning, and recover to the desired equilibrium will contribute to strengthening the resilience of communities. Budgetary instruments are crucial for ensuring the resilience of communities in such conditions. This study aims to identify the impact of budgetary instruments on ensuring the resilience of territorial communities amid the war in Ukraine (the case of Lviv oblast). The methods include a systemic and structural approach (building an information and analytical model of resilience research) and indicative and GAP analysis (identifying the impact of budgetary instruments on community resilience, in particular, local taxes, transfers, and personal income tax (PIT)). The data of 73 communities in Lviv oblast for 2021–2023 were collected. The study shows that the resilience of the territorial communities of Lviv oblast during the study period was at a moderate and above-moderate level; most were in the zones of resistance (resilience indicators ranging from 0.43-0.65) and decreasing resilience (0.42-0.20); the resilience of 8% was at a critically low level (2022–2023). The results estimate that the resilience of 90% communities in 2024 will not change significantly if military PIT is redirected from local to state budgets, except for those communities whose resilience is highly dependent on the amount of military PIT (the decrease in resilience will range from 12.5 to 4.2 percentage points).

Morbus Crohn: Top-down-Behandlungsschema erreicht substanziell höhere Remissionsraten, jedoch unabhängig von einem vorgeschlagenen Biomarker

&lt;b&gt;Background:&lt;/b&gt; Management strategies and clinical outcomes vary substantially in patients newly diagnosed with Crohn’s disease. We evaluated the use of a putative prognostic biomarker to guide therapy by assessing outcomes in patients randomised to either top-down (ie, early combined immunosuppression with infliximab and immunomodulator) or accelerated step-up (conventional) treatment strategies. &lt;b&gt;Methods:&lt;/b&gt; PROFILE (PRedicting Outcomes For Crohn’s disease using a moLecular biomarker) was a multicentre, open-label, biomarker-stratified, randomised controlled trial that enrolled adults with newly diagnosed active Crohn’s disease (Harvey-Bradshaw Index ≥7, either elevated C-reactive protein or faecal calprotectin or both, and endoscopic evidence of active inflammation). Potential participants had blood drawn to be tested for a prognostic biomarker derived from T-cell transcriptional signatures (PredictSURE-IBD assay). Following testing, patients were randomly assigned, via a secure online platform, to top-down or accelerated step-up treatment stratified by biomarker subgroup (IBDhi or IBDlo), endoscopic inflammation (mild, moderate, or severe), and extent (colonic or other). Blinding to biomarker status was maintained throughout the trial. The primary endpoint was sustained steroid-free and surgery-free remission to week 48. Remission was defined by a composite of symptoms and inflammatory markers at all visits. Flare required active symptoms (HBI ≥5) plus raised inflammatory markers (CRP &amp;#x3e; upper limit of normal or faecal calprotectin ≥200 μg/g, or both), while remission was the converse – ie, quiescent symptoms (HBI &amp;#x3c;5) or resolved inflammatory markers (both CRP ≤ the upper limit of normal and calprotectin &amp;#x3c;200 μg/g) or both. Analyses were done in the full analysis (intention-to-treat) population. The trial has completed and is registered (ISRCTN11808228). &lt;b&gt;Findings:&lt;/b&gt; Between Dec 29, 2017, and Jan 5, 2022, 386 patients (mean age 33.6 years [SD 13.2]; 179 [46%] female, 207 [54%] male) were randomised: 193 to the top-down group and 193 to the accelerated step-up group. Median time from diagnosis to trial enrolment was 12 days (range 0–191). Primary outcome data were available for 379 participants (189 in the top-down group; 190 in the accelerated step-up group). There was no biomarker-treatment interaction effect (absolute difference 1 percentage points, 95% CI –15 to 15; p = 0.944). Sustained steroid-free and surgery-free remission was significantly more frequent in the top-down group than in the accelerated step-up group (149 [79%] of 189 patients vs 29 [15%] of 190 patients, absolute difference 64 percentage points, 95% CI 57 to 72; p &amp;#x3c; 0.0001). There were fewer adverse events (including disease flares) and serious adverse events in the top-down group than in the accelerated step-up group (adverse events: 168 vs 315; serious adverse events: 15 vs 42), with fewer complications requiring abdominal surgery (one vs ten) and no difference in serious infections (three vs eight). &lt;b&gt;Interpretation:&lt;/b&gt; Top-down treatment with combination infliximab plus immunomodulator achieved substantially better outcomes at 1 year than accelerated step-up treatment. The biomarker did not show clinical utility. Top-down treatment should be considered standard of care for patients with newly diagnosed active Crohn’s disease.

Zombie Credit and (Dis‐)Inflation: Evidence from Europe

ABSTRACTWe show that “zombie credit”—subsidized credit to nonviable firms—has a disinflationary effect. By keeping these firms afloat, zombie credit creates excess aggregate supply, thereby putting downward pressure on prices. Granular European data on inflation, firms, and banks confirm this mechanism. Markets affected by a rise in zombie credit experience lower firm entry and exit, capacity utilization, markups, and inflation, as well as a misallocation of capital and labor, which results in lower productivity, investment, and value added. If weakly capitalized banks were recapitalized in 2009, inflation in Europe would have been up to 0.21 percentage points higher post‐2012.

Utilization of dental care and dentate status in diabetic and nondiabetic patients across US states: An analysis using the 2020 Behavioral Risk Factor Surveillance System.

This study examines the differences, by state, in dental care utilization and tooth retention between adults with and without diabetes mellitus (DM). We conducted a secondary analysis of data from the 2020 Behavioral Risk Factor Surveillance System, an annual, state-based, random telephone survey of noninstitutionalized US civilian adults. The predictor variable was DM status. The outcome variables were time since the last dental appointment and tooth loss. We utilized multiple multinomial logistic regression models followed by postestimation procedures to determine state-level adjusted proportions for dental visits within the last year and complete teeth retention among DM and non-DM adults. Among adults with DM, 60.0% reported dentist visits within a year of survey participation, while 53.6% had complete tooth retention. As education and income levels increased, dental attendance and tooth retention increased among adults with DM. Most Southern states had a higher prevalence of DM, a lower proportion of dentist visits, and worse tooth retention among DM adults. Nationally, DM individuals were 4.3 percentage points less likely to visit a dentist and were 7 percent less likely to have complete teeth retention than non-DM adults. Compared with the national average, 25/50 states had greater disparities in dental visits between DM and non-DM adults, and 27/50 states had greater disparities in tooth loss between DM and non-DM adults. State-level variations indicate geographical and dental coverage influences on DM and dental outcomes. There is a need for state-specific interventions to improve dental access and outcomes for adults with DM.

Have the recent advancements in cancer therapy and survival benefitted patients of all age groups across the Nordic countries? NORDCAN survival analyses 2002-2021.

Since the early 2000s, overall and site-specific cancer survival have improved substantially in the Nordic countries. We evaluated whether the improvements have been similar across countries, major cancer types, and age groups. Using population-based data from the five Nordic cancer registries recorded in the NORDCAN database, we included a cohort of 1,525,854 men and 1,378,470 women diagnosed with cancer (except non-melanoma skin cancer) during 2002-2021, and followed for death until 2021. We estimated 5-year relative survival (RS) in 5-year calendar periods, and percentage points (pp) differences in 5-year RS from 2002-2006 until 2017-2021. Separate analyses were performed for eight cancer sites (i.e. colorectum, pancreas, lung, breast, cervix uteri, kidney, prostate, and melanoma of skin). Five-year RS improved across nearly all cancer sites in all countries (except Iceland), with absolute differences across age groups ranging from 1 to 21 pp (all cancer sites), 2 to 20 pp (colorectum), -1 to 36 pp (pancreas), 2 to 28 pp (lung), 0 to 9 pp (breast), -11 to 26 pp (cervix uteri), 2 to 44 pp (kidney), -2 to 23 pp (prostate) and -3 to 30 pp (skin melanoma). The oldest patients (80-89 years) exhibited lower survival across all countries and sites, although with varying improvements over time. Nordic cancer patients have generally experienced substantial improvements in cancer survival during the last two decades, including major cancer sites and age groups. Although survival has improved over time, older patients remain at a lower cancer survival compared to younger patients.

Ethnic differences in metabolic syndrome in high-income countries: A systematic review and meta-analysis.

This review aimed to systematically quantify the differences in Metabolic Syndrome (MetS) prevalence across various ethnic groups in high-income countries by sex, and to evaluate the overall prevalence trends from 1996 to 2022. We conducted a systematic literature review using MEDLINE, Web of Science Core Collection, CINAHL, and the Cochrane Library, focusing on studies about MetS prevalence among ethnic groups in high-income countries. We pooled 23 studies that used NCEP-ATP III criteria and included 147,756 healthy participants aged 18 and above. We calculated pooled prevalence estimates and 95% confidence intervals (CI) using both fixed-effect and random-effect intercept logistic regression models. Data were analysed for 3 periods: 1996-2005, 2006-2009, and 2010-2021. The pooled prevalence of MetS in high-income countries, based on the NCEP-ATP III criteria, was 27.4% over the studied period, showing an increase from 24.2% in 1996-2005 to 31.9% in 2010-2021, with men and women having similar rates. When stratified by ethnicity and sex, ethnic minority women experienced the highest prevalence at 31.7%, while ethnic majority women had the lowest at 22.7%. Notably, MetS was more prevalent in ethnic minority women than men. Among ethnic minorities, women had a higher prevalence of MetS than men, and the difference was highest in Asians (about 15 percentage points). Among women, the prevalence of MetS was highest in Asians (41.2%) and lowest in Blacks/Africans (26.7%). Among men, it was highest in indigenous minority groups (34.3%) and lowest among in Blacks/Africans (19.8%). MetS is increasing at an alarming rate in high-income countries, particularly among ethnic minority women. The burden of MetS could be effectively reduced by tailoring interventions according to ethnic variations and risk profiles.

Digitalization and predictability in the BRICS countries: what can be learned from information about the dynamics of stock prices

The study aims to identify the impact of digitalization on predictability in the BRICS countries’ stock markets. It is based on an analysis of the dynamics of stock markets volatility during the 1990-2023 period. The paper seeks to prove that the standard deviation of stock returns is determined by the volume of incoming new information, and higher volatility of returns indicates lower predictability. Digitalization may cause a reduction in uncertainty as it uses more data, improves their quality and develops data analysis methods. On the other hand, digitalization may lead to increased uncertainty due to the emergence and development of new industries, in which it is more difficult to predict cash flows in comparison with traditional industries because of increased complexity of supply chains and technologies. Based on quantitative analysis, it has been revealed that digitalization has led to a statistically significant decrease in the volatility of stock markets in the BRICS countries. In 2015-2023, relative to the period of the 1990s-2006, volatility in Russia decreased by 1 percentage point, in India by 0.4–0.5 percentage points, in China by 0.8 percentage points, in the UAE (Dubai) by 0.5-0.7 percentage points. Statistically insignificant decreases in volatility were observed in Brazil and South Africa. In the developed capital markets, the decrease in volatility between these two periods was also statistically insignificant, amounting to less than 0.1 percentage points. These findings may indicate that the processes of digitalization in the BRICS countries contributed to an accelerated increase in predictability thanks to an increase in the volume and quality of information and the emergence of new methods of analysis. At the same time, part of the decrease in volatility may be explained by further development and improved efficiency of capital markets. The joint influence of these effects on the complexity of forecasting turned out to be more significant than the impact of innovative technologies and new industries.

Effectiveness of substance use disorder treatment as an alternative to imprisonment

IntroductionDrug courts are criminal justice programs to divert people with substance use disorders from incarceration into treatment. Drug courts have become increasingly popular in the US and other countries. However, their effectiveness in reducing important public health outcomes such as recidivism and substance-related health harms remains ambiguous and contested. We used nationwide register data from Sweden to evaluate the effectiveness of contract treatment sanction, the Swedish version of drug court, in reducing substance misuse, adverse somatic and mental health outcomes, and recidivism.MethodsIn this prospective cohort study, two quasi-experimental designs were used: difference-in-differences and the within-individual design. In the latter, we compared the risk of outcomes during time on contract treatment to, 1) parole after imprisonment and, 2) probation.ResultsThe cohort included 11,893 individuals (13% women) who underwent contract treatment. Contract treatment was associated with a reduction of 7 percentage points (95% CI: -.088, -.055) in substance misuse, 5 percentage points (-.064, -.034) in adverse mental health events, 9 percentage points (-.113, -.076) in adverse somatic health events, and 3 fewer charges (-3.16, -2.85) for crime in difference-in-differences analyses. Within-individual associations suggested that the same individual had longer times-to-event for all outcomes during contract treatment than on parole or on probation.ConclusionsContract treatment is an effective intervention from both public health and criminal justice perspective. Our findings suggest that it is a superior alternative to incarceration in its target group. Further, we find that an implementation approach that is less punitive and more inclusive than what is typical in the US can be successful.

Firearm Ownership and Support for Political Violence in the United States

Little is known about support for and willingness to engage in political violence in the United States. Such violence would likely involve firearms. To evaluate whether firearm owners' and nonowners' support for political violence differs and whether support among owners varies by type of firearms owned, recency of purchase, and frequency of carrying a loaded firearm in public. This cross-sectional nationally representative survey study was conducted from May 13 to June 2, 2022, among US adult members of the Ipsos KnowledgePanel, including an oversample of firearm owners. Firearm ownership vs nonownership. Main outcomes concern (1) support for political violence, in general and to advance specific political objectives; (2) personal willingness to engage in political violence, by severity of violence and target population; and (3) perceived likelihood of firearm use in political violence. Outcomes are expressed as weighted proportions and adjusted prevalence differences, with P values adjusted for the false-discovery rate and reported as q values. The analytic sample comprised 12 851 respondents: 5820 (45.3%) firearm owners, 6132 (47.7%) nonowners without firearms at home, and 899 (7.0%) nonowners with firearms at home. After weighting, 51.0% (95% CI, 49.9%-52.1%) were female, 8.5% (95% CI, 7.5%-9.5%) Hispanic, 9.1% (95% CI, 8.1%-10.2%) non-Hispanic Black, and 62.6% (95% CI, 61.5%-63.8%) non-Hispanic White; the mean (SD) age was 48.5 (18.0) years. Owners were more likely than nonowners without firearms at home to consider violence usually or always justified to advance at least 1 of 17 specific political objectives (owners: 38.8%; 95% CI, 37.3%-40.4%; nonowners: 29.8%; 95% CI, 28.5%-31.2%; adjusted difference, 6.5 percentage points; 95% CI, 4.5-9.3 percentage points; q < .001) but were not more willing to engage in political violence. Recent purchasers, owners who always or nearly always carry loaded firearms in public, and to a lesser extent, owners of assault-type rifles were more supportive of and willing to engage in political violence than other subgroups of firearm owners. In this study of support for political violence in the United States, differences between firearm owners and nonowners without firearms at home were small to moderate when present. Differences were greater among subsets of owners than between owners and nonowners. These findings can guide risk-based prevention efforts.