Time Series Regression Analysis Research Articles

For-profit outsourcing and its effects on placement stability and locality for children in care in England, 2011–2022: A longitudinal ecological analysis

BackgroundThe responsibility of local authorities in England to provide children in care with stable, local placements has become increasingly difficult due to the rising number of children in need of care and a shortage of available placements. It is unclear if the trend of outsourcing children's social care to private companies has exacerbated this challenge. This paper examines how the outsourcing of children's social care to the private market has influenced placement locality and long-term stability over time. MethodsWe created a novel dataset of multiple administrative data sources on the outsourcing, placement locality and stability, and characteristics of children in care between 2011 and 2022. We conducted time-series fixed-effects regression analysis of the impact of for-profit outsourcing on placement locality and stability from 2011 to 2022. ResultsOur fully adjusted models demonstrate that for-profit outsourcing is consistently associated with more children being placed outside their home local authority and greater placement instability. We found that an increase of 1 % point of for-profit outsourcing was associated with an average increase of 0.10 % points (95 % CI 0.02–0.17; p = 0.01) more children experiencing placement disruption, and 0.23 % points (95 % CI 0.15–0.30; p < 0.001) more children being placed outside their home local authority. We estimate that an additional 17,001 (95 % CI 9015–24,987) out-of-area placements can be attributed to increases in for-profit provision. DiscussionOur analyses show that placement stability and distance have deteriorated or stagnated over the last decade, and that the local authorities that rely most on outsourcing have the highest rates of placement disruptions and out-of-area placements.

Sales Prediction of Walmart Sales Based on OLS, Random Forest, and XGBoost Models

The technique of estimating future sales levels for a good or service is known as sales forecasting. The corresponding forecasting methods range from initially qualitative analysis to later time series methods, regression analysis and econometric models, as well as machine learning methods that have emerged in recent decades. This paper compares the different performances of OLS, Random Forest and XGBoost machine learning models in predicting the sales of Walmart stores. According to the analysis, XGBoost model has the best sales forecasting ability. In the case of logarithmic sales, R2 of the XGBoost model is as high as 0.984, while MSE and MAE are only 0.065 and 0.124, respectively. The XGBoost model is therefore an option when making sales forecasts. These results compare different types of models, find out the best prediction model, and provide suggestions for future prediction model selection.

Effects of a Province-wide Triaging System for TIA: The ASPIRE Intervention.

Urgent transient ischemic attack (TIA) management to reduce stroke recurrence is challenging, particularly in rural and remote areas. In Alberta, Canada, despite an organized stroke system, data from 1999 to 2000 suggested that stroke recurrence after TIA was as high as 9.5% at 90 days. Our objective was to determine whether a multifaceted population-based intervention resulted in a reduction in recurrent stroke after TIA. In this quasi-experimental health services research intervention study, we implemented a TIA management algorithm across the entire province, centered around a 24-hour physician's TIA hotline and public and health provider education on TIA. From administrative databases, we linked emergency department discharge abstracts to hospital discharge abstracts to identify incident TIAs and recurrent strokes at 90 days across a single payer system with validation of recurrent stroke events. The primary outcome was recurrent stroke; with a secondary composite outcome of recurrent stroke, acute coronary syndrome, and all-cause death. We used an interrupted time series regression analysis of age-adjusted and sex-adjusted stroke recurrence rates after TIA, incorporating a 2-year preimplementation period (2007-2009), a 15-month implementation period, and a 2-year postimplementation period (2010-2012). Logistic regression was used to examine outcomes that did not fit the time series model. We assessed 6,715 patients preimplementation and 6,956 patients postimplementation. The 90-day stroke recurrence rate in the pre-Alberta Stroke Prevention in TIA and mild Strokes (ASPIRE) period was 4.5% compared with 5.3% during the post-ASPIRE period. There was neither a step change (estimate 0.38; p = 0.65) nor slope change (parameter estimate 0.30; p = 0.12) in recurrent stroke rates associated with the ASPIRE intervention implementation period. Adjusted all-cause mortality (odds ratio 0.71, 95% CI 0.56-0.89) was significantly lower after the ASPIRE intervention. The ASPIRE TIA triaging and management interventions did not further reduce stroke recurrence in the context of an organized stroke system. The apparent lower mortality postintervention may be related to improved surveillance after events identified as TIAs, but secular trends cannot be excluded. This study provides Class III evidence that a standardized population-wide algorithmic triage system for patients with TIA did not reduce recurrent stroke rate.

Diarrhea don’ts: Reducing inappropriate stool cultures and ova and parasite testing for nosocomial diarrhea

Diarrhea that develops in patients after 72 hours of hospitalization is likely to have a nosocomial or iatrogenic etiology. Testing with stool cultures and stool ova and parasites (O&P) is not recommended. Our goal was to reduce this inappropriate testing within a large, urban safety-net hospital system. This was a quality improvement project. We created a best practice advisory (BPA) within the electronic medical record that fires when a stool culture or O&P order is placed 72 hours after admission for any immunocompetent patient. It states that stool testing is low yield and offers the option to remove the order. We measured weekly counts of stool culture and stool O&P orders pre- and postintervention. We also measured the BPA acceptance rate, the 24-hour stool testing reorder rate, and Clostridioides difficile infection rates. Data were analyzed using Welch tests as well as a quasi-experimental pre- and postintervention interrupted time series regression analysis. Stool culture orders decreased by 24.4% (P < .001). There was a significant level difference and slope difference with linear regression. Five of the 11 hospitals had a significant reduction in stool culture orders. Stool O&P orders decreased by 18.2% (P < .01). Three of the 11 hospitals had a significant reduction in stool O&P orders. Our intervention successfully reduced inappropriate stool testing within a large safety-net hospital system.

Analysis and Modeling of the Impact of Macroeconomic Factors on the Commissioning of Residential Real Estate in Russia

The system of statistical indicators, which is necessary for the construction of mathematical and statistical models that reflect modern domestic trends in the development of the residential real estate market is explained. The official data from the Federal State Statistics Service (Rosstat), the Unified Interdepartmental Information and Statistical System (EMISS), the Central Bank of the Russian Federation (CBR), and the Unified Housing Construction Information System (UIIS) served as information sources for the empirical component of the study.Based on quarterly data for 2010–2021 using ARIMA and SARIMA models, a time series of residential real estate commissions in the Russian Federation was modeled and predicted for 2022. Both models make it possible to account for the influence of the seasonal component. Based on results of the time series regression analysis, the authors selected a mathematical and statistical model with the best approximating characteristics. To model the volume of commissioning of residential real estate in the Russian market, with due regard to the influence of macroeconomic factors, the ARMAX model was used, which has significant explanatory power.The results of the study presented in the article may be of interest to analytical agencies, developers, banking professionals, financiers, economists, analysts of the real estate market or related areas, as well as authorities for strategic planning of the development of the real estate market.

The Association Between Media-Based Exposure to Nonsuicidal Self-Injury and Emergency Department Visits for Self-Harm

This study aimed to evaluate the association between media-based exposure to nonsuicidal self-injury (NSSI) and emergency department (ED) visits due to self-harm in Korea, specifically before and after the initial broadcast of the song Barcode, which has an explicit focus on NSSI. We used the national emergency department information system to obtain data related to ED visits due to self-harm between January 1, 2014, and December 31, 2018. Using interrupted time series regression analysis, we assessed the monthly ED visits due to self-harm before and after the media-based exposure to NSSI on March 30, 2018. In addition, self-harm methods were assessed. A total of 35,928,834 visits to ED were identified, of which 115,647 were due to self-harm. ED visits due to self-harm showed a significant step increase in the 10- to 14-year-old (β= 0.883, p= .001), 15- to 19-year-old (β= 2.941, p< .001), 20- to 24-year-old (β= 1.997, p= 0.002), and 25- to 29-year-old (β= 1.438, p= .029) age groups, before and after the media-based exposure to NSSI. The most pronounced increase was observed in male participants aged 20 to 24 years (β= 1.790, p= .012) and female participants aged 15 to 19 years (β= 5.158, p< .001). Self-harm by cutting has increased significantly in participants aged 10 to 29 years, and self-harm by poisoning has also increased significantly in participants aged 10 to 19 and 25 to 29 years. ED visits due to self-harm increased significantly, especially in adolescents and young adults, following the exposure to NSSI. Responsible media reporting on NSSI and appropriate guidelines would help prevent a further increase in self-harm. We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

Impact of COVID-19 Pandemic in Antibiotic Consumption in Navarre (Spain): An Interrupted Time Series Analysis

On 11 March 2020, the World Health Organization declared coronavirus disease 19 (COVID-19) a global pandemic. This exceptional situation changed the world not only in terms of mortality and morbidity, but also in terms of epidemiology and health system resources consumption. The objective of this work was to analyze the consumption of antibiotics during the period around the pandemic in our region. A drug utilization study was performed comparing the antibiotic consumption in the community during the years 2018, 2019, 2020, and 2021. Quarterly antibiotic use (defined daily doses (DDD) per 1000 inhabitants per day (DID)) and number of patients treated were the outcomes. Interrupted time series regression analysis was performed to estimate the statistical significance of the change in level of consumption before and after the COVID-19 pandemic. The drop of global antibiotic consumption was statistically significant, both in number of patients and in DID when analyzing pre-pandemic period versus pandemic period. The use of strategic antibiotics for respiratory infections such as amoxicillin, amoxicillin-clavulanic acid, and levofloxacin also decreased significantly. Seasonal pattern of use of antibiotics disappeared due to the global measures imposed over the world to work against COVID-19.

A Natural Quasi-Experiment of the Monetary Policy Shocks on the Housing Markets of New Zealand during COVID-19

It is hard to experimentally test the impacts of monetary policy shocks on housing markets as it is very unlikely for a central bank to change monetary policies swiftly twice within a short period of time for exogenous reasons. However, during the pandemic, the central bank of New Zealand changed its policies 180 degree in 2 years, from an unprecedented low interest rate and a relaxed mortgage policy in 2020 to a 13-year record high interest rate and a tightened mortgage policy in 2022. Among the OECD members, New Zealand is the country that increased the interest rate the earliest and also the country that had its house prices fall the earliest. It provides natural quasi-experiments to test the monetary policy hypothesis empirically by the two policy changes as treatments on house prices. This study conducts a time series regression analysis on the housing markets of New Zealand to test the hypothesis in the pre-COVID and the COVID periods, ranging from 2016 Q2 to 2022 Q3. The results confirm that mortgage rates have a negative and significant effect on house price changes after controlling for the economic growth factor and the housing supply factor, no matter whether the monetary policy switches to expansionary or contractionary mode. The robustness test results of the housing markets show that a 1% fall/rise in the mortgage rate caused a 5.6% increase/decrease in house prices, ceteris paribus, in the COVID period. The results also do not support the housing supply hypothesis in New Zealand.

Trends in the Rates of Extended-Spectrum-β-Lactamase-Producing Enterobacterales Isolated from Urine Cultures during the COVID-19 Pandemic in Ontario, Canada.

Worldwide, extended-spectrum β-lactamase (ESBL) rates are increasing at an alarming level with increasing rates of health care exposures, international travel, and antibiotic usage. In this study, we investigated whether enhanced social isolation, travel restrictions, and the reduced use of antibiotics in Ontario, Canada during coronavirus disease 2019 (COVID-19) pandemic had an impact on ESBL rates in urine cultures collected from the community and long-term-care (LTC) facilities across the province. Data from a total of 8.6 million urine cultures performed at LifeLabs Ontario from 2016 to 2021 were utilized for analysis. ESBL-producing Escherichia coli (ESBL Escherichia coli) and ESBL Klebsiella pneumoniae were identified using standard operating procedures. Data trends were estimated by interrupted time series (ITS) regression analysis. Among 2.3 million positive urine cultures, 48.9% and 7.2% grew E. coli and K. pneumoniae, of which 5.8% and 3.3% produced ESBLs, respectively. While the overall rate of ESBL isolation was higher in the pandemic period than in the prepandemic period, by ITS regression analysis of the monthly rates of ESBL isolation, decreasing trends were noted for ESBL E. coli in both the community and LTC facilities and for ESBL K. pneumoniae in the community. The ESBL K. pneumoniae rates in LTC facilities continued to increase throughout the COVID-19 period. By subgroup analysis for different genders, age groups, and local health integration network (LHIN) units, similar trends were seen in most cases (P < 0.05), except for a few densely populated LHINs where rate changes were not statistically significant. IMPORTANCE Community-onset urinary tract infections (UTIs) caused by ESBL-producing Enterobacterales, particularly E. coli and K. pneumoniae, are a major public health concern. In this study, we assessed the impact of COVID-19 on ESBL rates in urine cultures in Ontario, Canada. Our results show the recent epidemiology of ESBL-producing Enterobacterales in urine cultures from both the community and LTC facilities in Ontario, Canada, and the impact of COVID-19 restrictions on ESBL trends for the entire province as well as different subgroups of the population based on demographic and geographic characteristics. Our results may have important public health implications in the context of the gradual easing of COVID-19 restrictions.

The Relationship between Trade Openness and Economic Growth in Nigeria from 2000 to 2020

The study aimed to explore the relationship between trade openness and economic growth in Nigeria from 2000 to 2020, utilizing an ex-post facto research design. Secondary data was collected from the Central Bank of Nigeria Statistical Bulletin for the year 2022, and data analysis was conducted using SmartPLS 12.1 software, which is suitable for time series regression analysis. The findings of the study reveal that there is no significant relationship between export and both gross domestic product (GDP) and per capita income in Nigeria during the specified time frame. Similarly, the study indicates that there is no significant impact between foreign direct investment (FDI) and both GDP and per capita income in Nigeria. However, it was demonstrated that import significantly affects both the gross domestic product (GDP) and per capita income (PCI) in the country. This suggests that the influx of imports plays a more substantial role in influencing Nigeria’s economic growth during the review period. Based on the above findings, the study establishes that trade openness has a significant impact on the economic growth of the Nigerian economy, with the exception of export and foreign direct investment (FDI). It emphasizes the need for the Nigerian government to address security challenges posed by Boko Haram insurgency, Bandits, and Fulani Herdsmen activities. By ensuring a secure and stable environment, the country can attract both foreign and domestic investors, fostering economic development. The study also recognizes the vast potential in the agricultural sector and advocates for revitalizing agriculture in Nigeria. By prioritizing agricultural development, the country can create more job opportunities, enhance food security, and increase its export capabilities, contributing to overall economic growth and stability.

Evolution of Public Opinion on COVID-19 Vaccination in Japan: Large-Scale Twitter Data Analysis.

Vaccines are promising tools to control the spread of COVID-19. An effective vaccination campaign requires government policies and community engagement, sharing experiences for social support, and voicing concerns about vaccine safety and efficiency. The increasing use of online social platforms allows us to trace large-scale communication and infer public opinion in real time. This study aimed to identify the main themes in COVID-19 vaccine-related discussions on Twitter in Japan and track how the popularity of the tweeted themes evolved during the vaccination campaign. Furthermore, we aimed to understand the impact of critical social events on the popularity of the themes. We collected more than 100 million vaccine-related tweets written in Japanese and posted by 8 million users (approximately 6.4% of the Japanese population) from January 1 to October 31, 2021. We used Latent Dirichlet Allocation to perform automated topic modeling of tweet text during the vaccination campaign. In addition, we performed an interrupted time series regression analysis to evaluate the impact of 4 critical social events on public opinion. We identified 15 topics grouped into the following 4 themes: (1) personal issue, (2) breaking news, (3) politics, and (4) conspiracy and humor. The evolution of the popularity of themes revealed a shift in public opinion, with initial sharing of attention over personal issues (individual aspect), collecting information from news (knowledge acquisition), and government criticism to focusing on personal issues. Our analysis showed that the Tokyo Olympic Games affected public opinion more than other critical events but not the course of vaccination. Public opinion about politics was significantly affected by various social events, positively shifting attention in the early stages of the vaccination campaign and negatively shifting attention later. This study showed a striking shift in public interest in Japan, with users splitting their attention over various themes early in the vaccination campaign and then focusing only on personal issues, as trust in vaccines and policies increased. An interrupted time series regression analysis showed that the vaccination rollout to the general population (under 65 years) increased the popularity of tweets about practical advice and personal vaccination experience, and the Tokyo Olympic Games disrupted public opinion but not the course of the vaccination campaign. The methodology developed here allowed us to monitor the evolution of public opinion and evaluate the impact of social events on public opinion, using large-scale Twitter data.

752. Decreased Echinocandin Resistance among Candida glabrata over an Eleven-Year Period at a University Hospital

Abstract Background Invasive candidiasis (IC) is associated with significant morbidity and mortality. Echinocandins (ECH; caspofungin (CAS), micafungin (MFG), anidulafungin (AFG)) are first line therapy for IC. ECH resistance has emerged widely, most commonly among Candida glabrata. At some centers, &amp;gt; 10% of C. glabrata are ECH resistant. We reported ECH resistance in 8% of C. glabrata at our hospital from 2008–2014, which prompted stewardship strategies to limit prolonged ECH treatment courses. We evaluated trends of ECH resistance from Jan 2010-Dec 2020 among C. glabrata clinical isolates, and assayed isolates for FKS hot spot (HS) mutations. Methods We mined electronic medical records for ECH MIC data against C. glabrata clinical isolates at UPMC. We defined ECH resistance using Clinical and Laboratory Standards Institute clinical breakpoints. Isolates resistant to any ECH underwent FKS Sanger sequencing. Statistical analysis was performed using Stata. Results Overall CAS, AFG and MFG resistance rates among 516 isolates were 4%, 3%, and 2.5%, respectively. There was no significant difference in resistance rates between blood and non-blood sites (Table 1). There was a significant decrease in MFG resistance over the 12-year period (Fig 1). Time series regression analysis showed a decrease in rate of MFG resistance of 0.73% per year (p=.007). Trends for decreases in AFG and CAS resistance rates were also noted (p=.1 and p=.17). Similar analyses showed annual decreases in MFG MICs (0.019 μg/mL per year; p=.07). The average percentage of AFG resistant isolates was significantly lower in 2017–2020 than in 2012–2016 (p=.04); similar trends were evident for MFG (p=.07) and CAS (p=.08) (Fig 2). Sanger sequencing of FKS1/2 was performed for 27 isolates resistant to ≥1 ECH. Mutations were found in 44% (12/27) of isolates: 5 mutations in HS1 FKS1, 1 in HS2 FKS1, 5 in HS1 FKS2 and 1 in HS2 FKS2. Using both CAS and AFG MICs was most predictive of FKS mutations (Fig. 3). Conclusion ECH resistance among C. glabrata stabilized or decreased over 11-years at our hospital, in keeping with stewardship interventions to reduce prolonged use of ECHs. These results demonstrate that it is feasible to conserve ECH susceptibility. Disclosures Cornelius J. Clancy, MD, receives research funding paid to his institution from Astellas and Merck: Grant/Research Support|serves as an advisory Board member for Astellas, Cidara, and Scynexis, served on the advisory board for Merck, Qpex Biopharma, and Shionogi: Advisor/Consultant|Venatorx and Needham &amp; Associates: Advisor/Consultant Minh-Hong Nguyen, MD, QPX: Grant/Research Support.

Kinder, gentler – and crisis-proof? Consensus democracy, inclusive institutions and COVID-19 pandemic performance

Which patterns of democracy perform best? Although a decades-long research tradition has fairly robustly suggested that consensual democracies outperform their Westminster-style majoritarian counterparts, the scope of previous studies has been limited to ‘normal times’. In this article, the endogenous context of the COVID-19 pandemic is leveraged to study whether the alleged superiority of consensualism also holds during crises. It is hypothesised that, in addition to consensus democracy, inclusive institutions – i.e. cabinet size and interest-group corporatism – enhance crisis-related performance. Drawing on new and original data, cross-sectional and hierarchical time-series regression analyses show that horizontal power-sharing and the number of ministers substantively reduced excess mortality, while the structure of the interest-group system had no effect. Although established consensus democracies can draw on their built-in institutional assets even during crises, our findings indicate that majoritarian systems may, as a compensatory performance-enhancing tool, flexibly gear up for crisis-induced necessities by adding more ministers to the cabinet.

Analysis of Death Toll from COVID-19 in China with Uncertain Time Series and Uncertain Regression Analysis

This paper employs uncertain time series and uncertain regression analysis to model the evolution of the cumulative death toll from COVID-19 in China. Then parameter estimation, residual analysis, forecast and confidence interval are investigated. Uncertain hypothesis test is proposed to determine whether the estimated uncertain statistical models are appropriate. By analyzing the characteristics of the residual plot, the reason of using uncertain statistics instead of probabilistic statistics is explained.

Sex disparity in childhood cancer in India: a multi-centre, individual patient data analysis

Sex disparity and its determinants in childhood cancer in India remain unexplored, with scarce information available through summary statistics of cancer registries. This study analysed the degree of sex bias in childhood cancer in India and its clinical and demographical associations. In this retrospective, multicentre cohort study, we collected individual data of children (aged 0-19 years) with cancer extracted from the hospital-based records of three cancer centres in India between Jan 1, 2005, and Dec 31, 2019, and two population-based cancer registries (PBCRs; Delhi [between Jan 1, 2005, and Dec 31, 2014] and Madras Metropolitan Tumour Registry [between Jan 1, 2005, and Dec 31, 2017]). We extracted data on age, sex, and confirmed diagnosis of malignancy (according to the International Classification of Diseases-10 coding),and excluded participants if they were without a recorded diagnosis, had a benign diagnosis, had missing sex information, resided outside of India, or were a donor for haematopoietic stem cell transplantation (HSCT). The primary outcome was the male-to-female incidence rate ratio (MF-IRR) in the two PBCRs and the male-to-female ratios (MFR) from the hospital-based and the HSCT data. For PBCR data, MF-IRR was estimated by dividing the MFR by the total population at risk. MFR was analysed for patients seeking treatment at the cancer centres and for those undergoing HSCT. Logistic regression analyses were done to explore the association of clinical and demographical variables with sex of the patients seeking treatment and those undergoing HSCT in hospital-based data and multivariable analyses were done to determine independent sociodemographic predictors of sex bias. Annual time trends of MFR and MF-IRR during the 15-year study period were ascertained by time series regression analyses. We included 11 375 children from PBCRs in the study. 26 891 children from hospital-based records were screened, and data from 22 893 (85·1%) were included (including 514 who underwent HSCT). Residence details were missing for 257 (1·1%) of 22 893 patients from hospital-based records. The crude MFR of children at diagnosis was in favour of boys: 2·00 (95% CI 1·92-2·09) in the Delhi PBCR and 1·44 (1·32-1·57) in Madras Metropolitan Tumour Registry. The MF-IRRs for cancer diagnosis were also skewed in favour of boys in both PBCRs (Delhi 1·69 [95% CI 1·61-1·76]; Madras Metropolitan Tumour Registry 1·37 [1·26-1·49]). The MFR for children seeking treatment from hospital-based records was 2·06 (95% CI 2·00-2·12) in favour of boys. In subgroup analyses, the proportion of boys seeking treatment was higher in northern India than southern India (p<0·0001); in private centres than in centres providing subsidised treatment (p<0·0001); in patients with haematological malignancies than those with solid malignancies (p<0·0001); in those residing 100 km or further from the hospital than those within 100 km of a hospital (p<0·0001); and those living in rural areas than those living in urban areas (p=0·0006). The MFR of 514 children who underwent HSCT was 2·81 (95% CI 2·32-3·43) in favour of boys. Time trend analysis showed that MFR did not show any significant annual change in either the overall cohort or in any of the individual centres for hospital-based data; however, the analysis did show a declining MF-IRR in the Delhi PBCR from 2005 to 2014 (p=0·031). The sex ratio for childhood cancer in India has a bias towards boys at the level of diagnosis, which is more pronounced in northern India and in situations demanding greater financial commitment. Addressing societal sex bias and enhancing affordable health care for girls should be pursued simultaneously in India. None. For the Hindi translation of the abstract see Supplementary Materials section.

Impact of Gross Domestic Product on the Growth of Bond Markets in Kenya

Purpose: Bond markets are an example of financial markets that are very essential in promoting greater economic efficiency by channeling funds from savers to investors. This study investigated the influence of gross domestic product on growth of bond market in Kenya. The study further examined the moderating effect of diaspora remittance on the relationship between gross domestic product and the growth of bond market in Kenya.&#x0D; Methodology: Secondary data was obtained from the CBK, KNBS and NSE and covered a period of 20 years. Time series regression analysis was used in the study. The study employed descriptive research design.&#x0D; Findings: The study established that the gross domestic product had a major effect on the growth of bond market for the period of study. The study findings revealed that the GDP had a strong positive influence on the growth of bond markets. After moderation the effect improved more with the significance p-value. The study concluded that there was a positive statistically significant effect of GDP on bond market growth in Kenya.&#x0D; Unique Contribution to Theory, Policy and Practice: The study recommended that the capital market authority as a policy maker should enhance policies that promote investment in the bond market. Further studies should also be carried out incorporating other macroeconomic variables not included in this study. Finally, the study also recommended that CBK should ensure that it improves on measures that control the GDP and diaspora remittance as they influence the growth of bond market.

Association between grass, tree and weed pollen and asthma health outcomes in Adelaide, South Australia: a time series regression analysis

ObjectivesWe aim to establish daily risk estimates of the relationships between grass, tree and weed pollen and asthma health outcomes.DesignTime series regression analysis of exposure and health outcomes using interaction...

Temperature-related mortality and associated vulnerabilities: evidence from Scotland using extended time-series datasets

BackgroundAdverse health impacts have been found under extreme temperatures in many parts of the world. The majority of such research to date for the UK has been conducted on populations in England, whilst the impacts of ambient temperature on health outcomes in Scottish populations remain largely unknown.MethodsThis study uses time-series regression analysis with distributed lag non-linear models to characterise acute relationships between daily mean ambient temperature and mortality in Scotland including the four largest cities (Aberdeen, Dundee, Edinburgh and Glasgow) and three regions during 1974–2018. Increases in mortality risk under extreme cold and heat in individual cities and regions were aggregated using multivariate meta-analysis. Cold results are summarised by comparing the relative risk (RR) of death at the 1st percentile of localised temperature distributions compared to the 10th percentile, and heat effects as the RR at the 99th compared to the 90th percentile.ResultsAdverse cold effects were observed in all cities and regions, and heat effects were apparent in all cities and regions except northern Scotland. Aggregate all-cause mortality risk in Scotland was estimated to increase by 10% (95% confidence interval, CI: 7%, 13%) under extreme cold and 4% (CI: 2%, 5%) under extreme heat. People in urban areas experienced higher mortality risk under extreme cold and heat than those in rural regions. The elderly had the highest RR under both extreme cold and heat. Males experienced greater cold effects than females, whereas the reverse was true with heat effects, particularly among the elderly. Those who were unmarried had higher RR than those married under extreme heat, and the effect remained after controlling for age. The younger population living in the most deprived areas experienced higher cold and heat effects than in less deprived areas. Deaths from respiratory diseases were most sensitive to both cold and heat exposures, although mortality risk for cardiovascular diseases was also heightened, particularly in the elderly. Cold effects were lower in the most recent 15 years, which may be linked to policies and actions in preventing the vulnerable population from cold impacts. No temporal trend was found with the heat effect.ConclusionsThis study assesses mortality risk associated with extreme temperatures in Scotland and identifies those groups who would benefit most from targeted actions to reduce cold- and heat-related mortalities.

Pregnancy outcomes in Italy during COVID-19 pandemic: a population-based cohort study.

To compare the estimates of preterm birth (PTB; 22-36 weeks gestational age, GA) and stillbirth rates during COVID-19 pandemic in Italy with those recorded in the three previous years. A population-based cohort study of liveborn and stillborn infants was conducted using data from Regional Health Systems and comparing the pandemic period (March 1st , 2020-March 31st , 2021, N= 362,129) to an historical period (January 2017- February 2020, N=1,117,172). The cohort covered 84.3% of the births in Italy. Poisson regressions were run in each Region and meta-analyses were performed centrally. We used an interrupted time series regression analysis to study the trend of preterm births from 2017 to 2021. The primary outcomes were PTB and stillbirths. Secondary outcomes were late PTB (32-36 weeks' GA), very PTB (<32 weeks' GA), and extremely PTB (<28 weeks' GA), overall and stratified into singleton and multiples. The pandemic period compared with the historical one was associated with a reduced risk for PTB (Risk Ratio: 0.91; 95% Confidence Interval, CI: 0.88, 0.93), late PTB (0.91; 0.88, 0.94), very PTB (0.88; 0.84, 0.91), and extremely PTB (0.88; 0.82, 0.95). In multiples, point estimates were not very different, but had wider CIs. No association was found for stillbirths (1.01; 0.90, 1.13). A linear decreasing trend in PTB rate was present in the historical period, with a further reduction after the lockdown. We demonstrated a decrease in PTB rate after the introduction of COVID-19 restriction measures, without an increase in stillbirths.

Remembering the “Human” in Human Trafficking: An Analysis of Female Leadership and Anti-Trafficking Policy Choices

Abstract Could gender expectations play a role in executive leadership policy choices on human trafficking? To help explain why executive leaders of different genders may prioritize starkly different policies on the same issue, we situate our argument within the political double bind. We posit that human trafficking, a crime that exists at the nexus between foreign and domestic and masculine and feminine policy choices, is an arena where women will be more likely to demonstrate that they are compassionate domestically, thus choosing to fulfill the “feminine” side of the double bind over the “masculine” side. Using a cross-sectional time series regression analysis of forty-eight women leaders, we test this expected pattern for the years 2000–2016 and find that as the double bind suggests, women leaders prioritize protection measures over prosecution or prevention measures when addressing human trafficking, thereby fulfilling the domestic expectations of “feminine” leadership performance over the international expectations of “masculine” leadership performance to combat this crime. We also find that women have higher scores for anti-trafficking policy on the aggregate, indicating flexibility, and pointing to the careful balancing act women leaders must play when making policy choices.