National Statistics Institute Research Articles

Particulate Matter Exposure during Pregnancy and Childhood Leukemia Incidence

Leukemia is the most common childhood cancer and its etiology could be related to various environmental contaminants such as particulate matter (PM). The objective of our study is to evaluate the potential association between exposure to PM during pregnancy and the incidence of childhood leukemia. We established a population-based nationwide cohort using the Spanish Birth Registry Statistics database of the National Statistics Institute. We used spatiotemporal land use random forest models to estimate the concentrations of PM10 and PM2.5 for the entire pregnancy and by trimesters. We conducted logistic regression analyses adjusted for various covariates. In addition, we fitted generalized additive models (GAMs) to estimate the non-linear relationship between PM levels and leukemia incidence. The study included 3,112,123 children and 1066 cases of leukemia. The results for the continuous variable of PM10 exposure levels suggested an increased risk of childhood leukemia to be associated with higher exposure. The results for the categorized PM10 variable suggest an increased risk of childhood leukemia among pregnant women whose exposure levels were higher than the median (third and fourth quartiles). The results for PM2.5 were weaker. We found association between exposure to PM10 during pregnancy and an increased risk of childhood leukemia. Our findings indicate that public health interventions should aim to reduce air pollution to lower the incidence of childhood leukemia.

Using machine learning algorithms to identify farms on the 2022 Census of Agriculture

As is the case for many National Statistics Institutes, the United States Department of Agriculture’s (USDA’s) National Agricultural Statistics Service (NASS) has observed dwindling survey response rates, and the requests for more information at finer temporal and spatial scales have led to increased response burdens. Non-survey data are becoming increasingly abundant and accessible. Consequently, NASS is exploring the potential to complete some or all of a survey record using non-survey data, which would reduce respondent burden and potentially lead to increased response rates. In this paper, the focus is on a large set of records associated with potential farms, which are operations with undetermined farm status (farm/non-farm) and are referred to here as operations with unknown status (OUS). Although they usually have some agriculture, most OUS records are eventually classified as non-farms. Those OUS that are classified as farms tend to have higher proportions of producers from under-represented groups compared to other records. Determining the probability that an OUS record is a farm is an important step in the imputation process. The OUS records that responded to the 2017 U.S. Census of Agriculture were used to develop models to predict farm status using multiple data sources. Evaluated models include bootstrap random forest (RF), logistic regression (LR), neural network (NN), and support vector machine (SVM). Although the SVM had the best outcomes for three of the five metrics, the sensitivity for identifying farms was the lowest (13.8%). The NN model had a sensitivity of 80.5%, which was substantially higher than the other models, and its specificity of 45.3% was the lowest of all models. Because sensitivity was the primary metric of interest and the NN performed reasonably well on the other metrics, the NN was selected as the preferred model.

Optimising port arrival statistics: Enhancing timeliness through Automatic Identification System (AIS) data

Today, there is a greater demand to produce more timely official statistics at a more granular level. National Statistical Institutes (NSIs) are more and more looking to novel data sources to meet this demand. This paper focuses on the use of one such source to compile more timely and detailed official statistics on port visits. The data source used is sourced from the Automatic Identification System (AIS) used by ships to transmit their position at sea. The primary purpose of AIS is maritime safety. While some experimental statistics have been compiled using this data, this paper evaluates the potential of AIS as a data source to compile official statistics with respect to port visits. The paper presents a novel method called “Stationary Marine Broadcast Method” (SMBM) to estimate the number of port visits using AIS data. The paper also describes how the H3 Index, a spatial index originally developed by Uber, is added to each transmission in the data source. While the paper concludes that the AIS based estimates won’t immediately replace the official statistics, it does recommend a pathway to using AIS-based estimates as the basis for official port statistics in the future.

#1357 Regional and national hospitalization burden of lupus nephritis and systemic lupus erythematous in Spain

Abstract Background and Aims The regional epidemiology of Systemic lupus erythematosus (SLE) and lupus nephritis (LN) within the same country is poorly understood. Being a rare disease, its severity may be influenced by local expertise and treatment protocols, especially when healthcare systems are fragmented, like in Spain (17 different healthcare systems in 17 Autonomous Community (AACC), population range 319.796 to 8.472.407), resulting in potentially different levels of expertise in regional referral centers. Additional heterogeneity may derive from different specialists (rheumatology, internal medicine, nephrology) caring for SLE and LN. We aim to investigate the disease burden of SLE and LN in Spain and its AACC between 2019 and 2021, and to characterize factors that may influence this burden. Method The primary diagnostic data and average cost of SLE and NL hospitalization were extracted from the Minimum Basic Data Set (MBDS, Ministry of Health) that contains data from private and public hospitals. Sociodemographic data were obtained from the National Statistics Institute. Results From 2019 to 2021, there were 872 LN and 3612 SLE nationwide hospitalizations. Over 60% occurred in Andalucia, Catalonia, and Madrid, which account for 48% of Spanish population. Nationwide, the incidence of LN and SLE hospitalization was 1.44 and 4.59 per 100 000, respectively. However, regional variability was large, with a 3.7-fold difference for LN and a 7.3-fold difference for SLE between Madrid and Valencia, 2 of the more populated AACC. The median LN/SLE hospitalization ratio was 0.33. Relative risk for hospitalization, compared to the national mean, ranged in AACC from 0.37 (Baleares) to 2.55 (La Rioja) for LN and from 0.22 (Baleares) to 3.67 (Ceuta and Melilla) for SLE (Fig. 1A). Heterogeneity was larger at the provincial level where 10/50 provinces had significantly higher or lower relative risk than the national mean (Fig. 1B). The length of SLE/LN hospitalizations was very variable across specialties and AACC. There was a trend for shorter duration in Nephrology and longer in Internal Medicine for both LN and SLE. Nephrology was mainly responsible (76%) for LN hospitalization, with regional differences. For SLE hospitalization, Nephrology was also most commonly in charge. Heterogeneity was larger at the province level within the same AACC. The average All-Patient-Related (APR) cost per LN and SLE hospitalization episodes was €5254 and €4376, respectively, with significant geographical variability. Total annual hospitalization costs varied significantly among AACC, ranging from €8683 (Ceuta and Melilla) to €682512 (Catalonia) for LN and from €68361 (Ceuta and Melilla) to €2229456 (Madrid) for SLE. Adjusted per million population, total LN hospitalization cost ranged from €27920 (Baleares) to €179248 (La Rioja), and SLE cost from €91563 (Baleares) to €399693 (Ceuta and Melilla). When adjusted by €1000 of average household net income, the budget burden of LN hospitalization was highest in La Rioja (€5812 per €1000 of average household net income) and lowest in Baleares (€809 per €1000), while for SLE was highest in Murcia (€11186 per €1000) and lowest in Baleares (€2652 per €1000) (Fig. 2A,B). Conclusion In conclusion, the burden of LN and SLE hospitalization is heterogeneous across and within Spanish AACC, with large regional differences in the distribution of cases, costs and specialists who care for these patients. The analysis of these differences may contribute to benchmarking of best practices, decreasing clinical practice heterogeneity, optimizing care for SLE and LN and improving outcomes.

Reorganization of human resources in the tourism industry from the perspective of recent years, in relation to Transylvania

Nowadays, employment in various economic fields and the possession of appropriate professional knowledge are of considerable importance, especially in the services sector, where properly qualified personnel is a key factor in terms of the development of satisfaction in the demand segment. As an apropos of this, the human resource reorganizations taking place in the Transylvanian region and the willingness to work form the subject of the research, focusing on the tourism industry, which was a difficulty for businesses providing various services during the period of the Covid-19 epidemic that spread in 2020. In a significant part of the international studies related to the topic, the difficulties arising because of the change in the attitude of the tourist human resources are mentioned, which can lead to a disadvantageous situation in the long term of the operation of tourist facilities. As a result, the sixteen Romanian counties that make up the Transylvania region became the target of the investigation. Projected on the mentioned counties, relevant data from the Romanian National Statistical Institute (INSSE) were first used, examining the time interval between 2010 and 2022, both yearly and monthly. According to the data used, it is important to focus on the investigation of tourist traffic, as well as on the number of people employed in the sector and its change, as well as on the wages received for doing their work and the associated benefits, which can serve as a motivational factor in addition to valuing employees. An examination of the data related to the topic shows that the 2008 global crisis had a more drastic impact on employment in Romania than the Covid-19 pandemic that spread in 2020, the effects of which can still be felt today.

Technological Perception with Rural and Urban Differentiation and Its Influence on the Quality of Life of Older People with Age-Related Macular Degeneration

The past decade has seen a global increase in population age, especially in developed countries, where aging involves visual diseases such as age-related macular degeneration (AMD), which severely affect quality of life (QoL) and mental health, as well as increase isolation and care costs. This study investigated how persons with AMD perceive the impact of technology use on their QoL, focusing on potential disparities between urban and rural contexts in Spain. Using a cross-sectional observational design, data from the 2020 National Statistics Institute’s Disability, Personal Autonomy, and Dependency Situations Survey were analyzed, focusing on QoL aspects based on the WHO items of the WHOQOL-100 scale. The results revealed a generally positive perception of technology among participants, with urban residents perceiving technology’s positive impact more favorably. Sex discrepancies in technology perception were also observed, as women exhibited a more positive outlook on technology’s influence on QoL. The analysis of QoL aspects, such as ‘Visibility’, ‘Learning’, ‘Mobility’, and ‘Domestic life’, highlighted distinct challenges faced by rural and urban populations, underscoring the importance of context-specific approaches in technology interventions. However, these perceptions were intertwined with comorbidities, which can exacerbate AMD-related issues. Furthermore, this study explored the role of technology in enhancing QoL among older adults with AMD, examining how it influences daily activities and independence, particularly in the context of AMD management. This study concluded that developing more-inclusive policies tailored to the specific needs of persons with AMD, with special attention to environmental and sex differences, is imperative to enhance the positive impact of technology on their QoL.

Assessing the quality of data on international migration flows in Europe: The case of undercounting

Abstract Undercounting is a critical issue in migration statistics, resulting in bias. This typically arises from insufficient reporting requirements and problems with enforcing such requirements. The main sources of information on undercounting are the metadata accompanying official statistics and expert opinions. However, metadata and arbitrary expert opinions may be limited by overlooking important details in migration data shared by various countries. This includes potential oversight of changes in methodologies, definitions, or retrospective updates to the data following censuses. This work presents a methodological solution with three objectives to address undercounting in international migration data. First, we provide an overview of available metadata and expert opinions on undercounting in European migration flows. Secondly, we propose a novel data-driven approach that incorporates year-specific and duration-of-stay-adjusted classifications. The proposed methodological solution relies on comparisons of flows in the same direction reported by a given country with high-quality data reported by another set of countries. We use bilateral migration data provided by Eurostat, United Nations, and selected national statistical institutes. Duration-of-stay correction coefficients are derived through an optimization model or borrowed from the literature. Metadata and expert opinion scores can also be integrated to classify undercounting. Finally, we provide a dynamic classification of undercounting for thirty-two European countries (2002–21), accessible through an online Shiny application, offering flexibility and adaptability. The findings highlight significant undercounting in new European Union Member States, particularly Bulgaria, Latvia, and Romania. Interestingly, other European countries, including those presumed to maintain reliable population statistics, also exhibit notable periods of undercounting.

Prevalence of Alcohol Consumption in Mozambique: Analysis Based on Household Budget Survey (IOF 2022)

Worldwide the excessive consumption of alcohol in 2016 was considered as responsible for 5% of deaths and more than 200 illnesses and injuries. There are several studies conducted around the world to understand the prevalence of alcohol consumption. However, in Mozambique, there are few studies conducted to determine the prevalence of alcohol consumption, as well as, to characterize the consumers, using data from nationally representative surveys. The current study, identify the prevalence of alcohol consumption in Mozambique, according to socio-demographic characteristics of population using data from the Household Budget Survey (IOF 2022) carried out by the National Statistics Institute in 2022. The analysis of data was based in descriptive statistics. The study results revel that the prevalence of alcohol consumption in Mozambique is 24.6%, higher among men (27%), compared to woman (23%). The prevalence is high among people between 18 - 65 years old (26%) and people with higher education (34%). Around 17% of teenagers, between 15 and 17 years old, in both sexes, purchased and consumed alcoholic beverages, despite the prohibition of Mozambican legislation. The provinces of Tete (37.2%), Maputo (32.3%) and Zambézia (30.3%) have the highest prevalence of alcoholic beverages consumption and the province of Niassa (3.7%) has the lowest prevalence. Beer (46%) is the most consumed alcoholic beverage in Mozambique, followed by traditional alcoholic beverages (44%).

Harmonized European Union subnational crop statistics can reveal climate impacts and crop cultivation shifts

Abstract. The availability of coherent time series of crop statistics is essential for better analyzing the past, understanding the present, and predicting future trends in yield, area, and production. Importantly, such data also underpin assessments and subsequent policy actions that can shape future food systems that are more resilient in the face of climate change and that are sustainable in terms of resource use efficiency. In the European Union (EU), there currently is no legal obligation for EU countries to provide subnational crop statistics. However, such data could improve in-season crop forecasts, climate change impacts and adaption need assessments, and evaluation of agri-environmental schemes. The dataset described in this paper includes a harmonized collection of subnational crop statistics on area, production, and yield, collected for the EU from National Statistical Institutes (NSIs) and the EUROSTAT REGIO database – subnational crop statistics voluntarily contributed by EU countries. The crops considered are wheat (including soft and durum wheat), barley (including winter and spring barley), grain maize, sunflower, and sugar beet. All data are harmonized towards the hierarchical structure of the EUROSTAT legend and the regional classification of NUTS (Nomenclature of Territorial Units for Statistics) version 2016, to provide coherent time series. A total of 344 282 records is presented here (115 974 for wheat, 122 705 for barley, 35 274 for grain maize, 34 916 for sugar beet, and 35 413 for sunflower) for a total of 961 regions in 27 EU countries. Statistics are reported from 1975 to 2020, with a median time-span range of 21 years. A flagging system details, for each data record, information on data sources, processing steps, and quality-checking results. This includes consistency checks between reported values for area, yield and production, identification of null values, missing and calculated data, information on crop legend matching, and NUTS versioning. We illustrate the value of this dataset by analyzing impacts on crops and production zone shifts in Europe due to climatic and economic factors. Recommendations and future developments of collecting subnational statistics at the EU level are briefly discussed. The dataset is accessible with European Commission Authentication Service (ECAS) login at https://doi.org/10.2905/685949ff-56de-4646-a8df-844b5bb5f835 (Ronchetti et al., 2023b).

THE COVID-19 PANDEMIC IN THE PLEVEN REGION FOR A THREE-YEAR PERIOD (MARCH 2020 – MARCH 2023)

The COVID-19 pandemic had a major impact on the capacity of health systems to continue the delivery of essential health services. While health systems were being challenged by increasing demand for care of COVID-19 patients, it was critical to maintain preventive and curative services, especially for vulnerable populations. Materials and methods: A retrospective analysis was conducted on epidemiological and demographic characteristics of the COVID-19 pandemic in the Pleven region (March 2020 – March 29 2023). Data were obtained from annual reports of the National Statistical Institute and annual epidemiological analyses of Regional Health Inspectorate–Pleven and were analyzed using statistical software (IВМ SPSS Statistics 19.0). Results: There were 36,308 confirmed cases of COVID-19 (medical workers – 2,176 confirmed cases), with 1,895 deaths. The cases during the years were 5,646 (2020), 16,258 (2021), 15,225 (2022). The incidence of COVID-19 in the region was 2,389; 6,964, and 6,668 at 100,000 populations in 2020, 2021 and 2022, respectively. The prevalence of the disease was 93%, 98% and 94% of all registered respiratory transmitted cases (p<0.0005). There were four waves with the highest incidence (November 2020, March 2021, October 2021, and January 2022, in concordance with registered for Bulgaria). The highest mortality of COVID-19 (15% of deaths) was registered during 2021 – 456 and 368 at 100,000 population for males and females, respectively (16% and 15% of deaths, respectively; 81% – at ages 65+). Conclusion: The global implementation of different interventions had a significant impact on slowing down the community transmission of SARS-CoV-2. Health care and resources must be focused on the vulnerable populations.

Characteristics and analysis of the Culture and Arts sector, specifically the Performing dance sector in Bulgaria

The culture and arts sector is often described as a "motor sector" in academic literature. Dance schools, within this sector, offer a unique blend of educational and artistic experiences to their clients, encompassing both instructional classes and the creation of original dance performances. However, cultural and arts organizations are not solely business-oriented but also play a significant role in shaping cultural identity and providing educational opportunities. In Bulgaria, there is a lack of a standardized system for accounting for the number of dance schools and cultural organizations. These entities range from private micro-organizations, such as sole proprietorships, limited liability companies, foundations, and associations, to state and municipal organizations, with the latter forming a small percentage of the sector. Statistical data about cultural organizations and their activities are fragmented and can be found in the annual reports of the National Culture Fund (NCF), registers of the Ministry of Culture, and data from the National Statistical Institute (NSI). This study highlights the complex dynamics within the Culture and Arts sector in Bulgaria, especially in the context of dance schools, and underscores the need for targeted efforts to rekindle public interest and engagement in dance arts.

Consumption of Tap Water and Sociodemographic-Associated Characteristics: A Nationwide Cross-Sectional Study.

Safe water is a global public health concern amid increasing scarcity and pollution. Bottled water production and consumption contribute to these problems. This study examines tap water consumption in Italy, assessing associated sociodemographic factors and related health outcomes such as obesity and self-perceived health status. Data from the Italian National Statistics Institute's "Aspects of daily life" survey (N = 45,597) were analyzed. Covariates included education, age, gender, economic status, region, concerns about waste and climate change, consumption of carbonated drinks excluding water, alcohol consumption, consumption of vegetables, consumption of snacks, body mass index, and self-perceived health status. Bivariate analyses and mixed-effect logistic regression models explored the associations. People who drink tap water made up 19,674, with a higher prevalence in people aged 45 to 59 old, people with a graduate/post-graduate degree diploma, with optimal economic resources, people concerned about waste production and climate change, and those coming from the north-east regions of Italy. Underweight people showed a higher prevalence of TW consumption as well as those who less than occasionally drank carbonated drinks, drank alcohol, consumed vegetables more than once a day and snacks less than once a week, dairy products more than once a day, sweet less than once a week, cured meat less than once a week, and chicken meat less than once a week, those with no consumption of sheep meat, consumption of beef meat less than once a week and consumption of pork meat less than once a week, and those with a satisfactory level of perceived health status. Regressions showed that all other age classes are less likely to drink tap water than people younger than 20 years old. The category with "inadequate" economic resources is more likely to consume tap water. Low educational classes show a low likelihood of consuming tap water as well as islands. A concern about waste production and climate change is associated with an increased likelihood of consuming tap water. Tap water consumption was negatively associated with obesity but not with a satisfactory self-perceived health status. Insights from this study can inform public health strategies.

FINANCIAL PLANNING AND DECISION MAKING AS PREDICTORS OF FINANCIAL PERFORMANCE IN MSMES

Purpose: the present study demonstrates that the combination of financial planning and decision making jointly contribute as predictors of efficient financial performance, permeating into MSMEs’ market sustainability. Theoretical Framework: Micro, small and medium enterprises (MSMEs) currently have a relevant role in gross domestic product and direct job creation in Latin American countries. The literature shows that financial planning is a highly valuable tool for large businesses, facilitating decision making and creating positive impacts on financial performance. However, these studies are centered on businesses classified as large, excluding MSMEs. Recent studies have approached financial planning, decision making, and financial performance in MSMEs on an individualized basis. Methodology: The study carried out was quantitative, non-experimental, correlation, cross-sectional, and explanatory. A total of 308 MSMEs participated, obtained from the National Geography and Statistics Institute (INEGI, 2019), of which 34.41% were industrial, 32.14% commercial, and 33.41% from the service sector. Normal distribution tests were done (Kolmogorov-Smirnov tests), along with symmetry and kurtosis. Findings: The findings suggest that MSMEs which have been around for seven years or more have financial planning knowledge favoring their decision-making and generating efficient financial performance, making time a determining factor. Research, Practical & Social Implications: Our findings have significant implications for generating proper planning based on solid tools, with the effect of assertive decision making which favors financial performance. Originality/Value: The most important contribution from this study to MSMEs is to show that financial planning is not only for large organizations, but can apply to them as well.

Harmonized disposable income dataset for Europe at subnational level

In recent decades, detailed country-level estimates of income and wealth have become widely available and inform us about the evolution of inequality between and within countries. But a substantial portion of these available datasets lack sub-national geographical information, precluding the exploration of the spatial distribution and evolution of inequalities within countries. We present here a new dataset of disposable income for Europe at the subnational level. It has been compiled from existing income data (gross income, gross earnings, equivalised income, etc.) published by national statistical institutes at different geographical levels. We used linear regressions and numerical operations to estimate disposable income from other available socio-economic statistics (e.g. household size, tax rates). We developed a harmonization and adjustment procedures to ensure of the consistency of statistical units, income indicators, costs of living and inflation. The dataset covers 42 European countries distributed over more than 120,000 geographical entities on the 1995 to 2021 period (most of the data being available for the 2010–2020 decade). This new dataset opens avenues for investigating the links between income inequality and other socio-economic or ecological processes.

Spain's Rising Melanoma Threat: A Comprehensive 30-Year Analysis (1990-2019).

This study aims to elucidate the factors driving melanoma incidence trends in Spain by analyzing the GBD-2019 dataset (1990-2019) and investigating the age-specific, birth cohort, and period effects on incidence rates. This study analyzed melanoma incidence trends in Spain from 1990 to 2019 using an ecological design. Data were sourced from the Global Burden of Disease Study 2019 and Spain's National Statistics Institute. Age-standardized incidence rates (ASIRs) were calculated using joinpoint regression analysis, and age-period-cohort (A-P-C) modeling was employed to assess the effects of age, time period, and birth cohort on incidence rates. Between 1990 and 2019, an estimated 147,823 melanoma cases were diagnosed in Spain. The ASIRs showed a steady increase for both sexes, with slightly higher rates observed in men. Both men (average annual percentage change (AAPC): 2.8%) and women (AAPC: 2.4%) showed a steady increase in the ASIR over the period. Joinpoint analysis revealed distinct periods of incidence rate changes, with significant upward trends in earlier years followed by stabilization in recent years. Incidence rates increased steadily with age, with the highest rates in the 80-84 age group. Women tended to have slightly higher rates in younger age groups, while men had higher rates in older age groups. Both men and women experienced a steady increase in relative risk of melanoma throughout the 30-year study period, with significant upward trends across birth cohorts. Despite limitations, this study provides valuable insights into factors influencing melanoma incidence in Spain. By understanding age, period, and cohort effects, effective prevention strategies can be developed to reduce melanoma incidence.

Multilateral indices in official price statistics and a new additive splicing method

A substitution of the traditional data sources allows National Statistical Institutes to collect large samples of product items with corresponding prices recorded over more frequent time periods. For some product categories, a frequent replacement of product items requires a dynamic approach to define a product sample that can be achieved by a monthly update of the sample. In a month-on-month comparison of price changes, bilateral indices must be chained that can lead to a chain drift bias. Multilateral methods are designed to reduce the chain drift, albeit not completely eliminate it. A disadvantage of multilateral methods is its ambiguous interpretability and a revision problem. The main objective of this paper is to show an implementation of multilateral methods for official price statistics in practice. The multilateral GEKS method is decomposed into elementary components that identifies the effect of successive price relatives used in its compilation. An importance of the decomposition is shown when interpreting the GEKS index in the context of official price statistics. We demonstrate that it can lead to an inaccurate public dissemination of the consumer price index. Moreover, we propose a new method for the splice extension that is required to avoid the revision of previously published indices. The method uses a Stein-type shrinkage estimator for the splice extension that is applied additively to the last published index. In the empirical study, we use web scraped data, which are obtained from the Slovak market, for comparison of bilateral and multilateral indices.

Are there differences in the perceived advantages and disadvantages of teleworking? The identification of distinct classes of teleworkers

PurposePrevious research has focused on the outcomes of telework, investigating the advantages and disadvantages of teleworking for employees. However, these investigations do not examine whether there are differences between teleworkers when evaluating the advantages and disadvantages of teleworking. The aim of this study is to identify of distinct classes of teleworkers based on the advantages and disadvantages that teleworking has for them.Design/methodology/approachThis study used secondary survey data collected by the Spanish National Statistics Institute (INE). A sample of 842 people was used for this study. To identify the distinct classes of teleworkers, their perceived advantages and disadvantages of teleworking were analyzed using latent class analysis.FindingsThree different classes of teleworkers were distinguished. Furthermore, sociodemographic covariates were incorporated into the latent class model, revealing that the composition of the classes varied in terms of education level, household income, and the amount of time spent on teleworking per week. This study also examined the influence of these emergent classes on employees’ experience of teleworking.Originality/valueThis study contributes to previous research investigating if telework is advantageous or disadvantageous for teleworkers, acknowledging that teleworkers are not identical and may respond differently to teleworking.

How does accounting save lives? An econometric analysis exploring the effectiveness of the Crispi-Pagliani Health Reform (1888) in Italy

This study compares the healthcare management systems for cholera epidemics in Italy before and after the Crispi-Pagliani Health Reform of 1888. Specifically, we compare the monitoring, accounting, and reporting systems of deaths and infections during the 1884 and 1893 epidemics. Based on an econometric analysis of data from the Italian National Statistical Institute, we demonstrate that the post-reform system was more effective in reducing deaths by optimising medical personnel allocation in areas with higher epidemic intensity. From a Foucauldian perspective, we provide insights into the role of accounting in supporting noso-politics, bio-politics, and bio-power. Further, this study advances our understanding of reporting systems and the dynamics that governments trigger as part of strategies for preventing or containing contagion during epidemics. Finally, this study supports the use of econometrics in accounting history.

Geotourism, a New Perspective of Post-COVID-19-Pandemic Relaunch through Travel Agencies—Case Study: Bucegi Natural Park, Romania

The proposed approach—geotourism, a new medium- and long-term post-pandemic recovery perspective—provides a theoretical foundation for future research regarding the interactions between tourism agencies and tourists, visitors and landforms, as well as cooperation and support between local residents and tourists, for Bucegi Natural Park. In the current context, the nature monuments and nature reserves within the park are located in rural and urban areas. These can be capitalized and included directly in the tourism agencies’ supply, and they can be used for zonal and regional development without degrading the surrounding environment. The “Babele and the Sphinx” landmarks with interesting shapes offer benefits for the development of geotourism in the Romanian landscape. In addition to those listed previously, this study proposes and analyses the image of the geotourism destination and a slogan for the international promotion of the park. Thus, the research presents two sources of data collection: (1) primary data, i.e., those obtained following a questionnaire and analysed with the help of the SPSS Statistics software, version 15.0, and (2) secondary statistical data from the database of the National Institute of Statistics (NIS) that are available and constantly updated. Another method used with a significant impact on tourism analysis was represented using the Geographic Information System (GIS). With its help, we mapped the tourist routes and the two elements, nature reserves and nature monuments within the park, that constitute the basis of the geotourism relaunch after COVID-19. The final objective of the paper is to strengthen the role of travel agencies in promoting geotourism by offering visits to tourist attractions in the park.

Socioeconomic differences in dietary habits in Italy before and during COVID-19 pandemic: secondary analysis of a nationwide cross-sectional study

BackgroundSeveral socioeconomic conditions may influence subjects’ adherence to healthy eating habits. Food consumption may be influenced by external stress during crisis periods; however, the effects of these events on food habits are difficult to predict. Also, a pandemic crisis like the recent COVID-19 pandemic may have influenced dietary habits and food consumption. The objective of this study was to compare the dietary habits of Italian people before the COVID-19 pandemic with those belonging to the year 2020 in a nationwide population sample.Materials and methodsInformation on dietary habits has been obtained from the multi-purpose survey on families’ “Aspects of daily life”, carried out in Italy by the Italian National Statistics Institute (ISTAT). We analyzed data coming from 2016 and 2020 editions of the survey (43,000 subjects each year). We used population attributable fraction (PAF) adjusted for age, defined as the proportional reduction in unhealthy diet that would occur if all participants had had a higher education, assuming higher educated individuals as more socially advantaged. Prevalence association for each dietary exposition has been calculated through logistic regression.ResultsLooking at aggregated data from 2016 and 2020 both men and women showed a high prevalence of unhealthy dietary habits. Regarding men, excessive consumption of eggs, pork meat, and bovine meat was characterized by a PAF attributable to socioeconomic conditions to an extent greater than 30%. Women showed the same trend. Focusing on different years of investigation, in 2020, during the COVID-19 pandemic, men and women increased their consumption of eggs, cooked fats, snacks, and sweets, and reduced consumption of fruits and vegetables. Additionally, women increased the assumption of dietary products and meat. Both sexes registered an increase in overweight and obese subjects in 2020.ConclusionsTo our knowledge, this study was the first in our country to use a yearly, nationwide sample to analyze dietary habits by examining specific types of various foods on a nationwide scale and establishing a correlation between these habits and the COVID-19 pandemic. Our results showed unbalanced dietary habits of the Italian population with an excess of consumption of several foods like eggs, cooked fats snacks, and sweets with low consumption of fruits and vegetables. Socioeconomic differences influence food choices but in a complex way since they seemed to affect some wrong dietary habits but not others, especially regarding fruits and vegetables assumption where differences were less evident among social classes. Outside stressors like a crisis period such as the COVID-19 pandemic seem to have an important role in both men and women regarding the assumption of so-called “junk food”.