The adaptation of noise-induced temporary hearing threshold shift predictive models for modelling the public health policy.

OBJECTIVES: It has been shown that monitoring temporary threshold shift (TTS) after exposure to noise may have a predictive value for susceptibility of developing permanent noise-induced hearing loss. The aim of this study is to present the assumptions of the TTS predictive model after its verification in normal hearing subjects along with demonstrating the usage of this model for the purposes of public health policy. MATERIAL AND METHODS: The existing computational predictive TTS models were adapted and validated in a group of 18 bartenders exposed to noise at the workplace. The performance of adapted TTS predictive model was assessed by receiver operating characteristic (ROC) analysis. The demonstration example of the usage of this model for estimating the risk of TTS in general unscreened population after exposure to loud music in discotheque bars or music clubs is provided. RESULTS: The adapted TTS predictive model shows a satisfactory agreement in distributions of actual and predicted TTS values and good correlations between these values in examined bartenders measured at 4 kHz, and as a mean at speech frequencies (0.5-4 kHz). An optimal cut-off level for recognizing the TTS events, ca. 75% of young people (aged ca. 35 years) may experience TTS >5 dB, while <10% may exhibit TTS of 15-18 dB. CONCLUSIONS: The final TTS predictive model proposed in this study needs to be validated in larger groups of subjects exposed to noise. Actual prediction of TTS episodes in general populations may become a helpful tool in creating the hearing protection public health policy. Int J Occup Med Environ Health. 2023;36(1):125-38.

Geospatial clustering of childhood IgA vasculitis and IgA vasculitis-associated nephritis.

OBJECTIVES: Research on spatial variability of the incidence of IgA vasculitis (IgAV) in children and its potential implications for elucidation of the multifactorial aetiology and pathogenesis is limited. We intended to observe spatial variability of the incidence of IgAV and IgA vasculitis-associated nephritis (IgAVN) using modern geostatistical methods, and hypothesised that their spatial distribution may be spatially clustered. METHODS: Patients' data were retrospectively collected from 2009 to 2019 in five Croatian University Hospital Centres for paediatric rheumatology, and census data were used to calculate the incidence of IgAV. Using spatial empirical Bayesian smoothing, local Morans' I and local indicator of spatial autocorrelation (LISA), we performed spatial statistical analysis. RESULTS: 596 children diagnosed with IgAV were included in this study, of which 313 (52.52%) were male. The average annual incidence proportion was estimated to be 6.79 per 100 000 children, and the prevalence of IgAVN was 19.6%. Existence of spatial autocorrelation was observed in both IgAV and IgAVN; however, clustering distribution differed. While IgAV showed clustering in Mediterranean and west continental part around cities, IgAVN was clustered in the northern Mediterranean and eastern continental part, where a linear cluster following the Drava and Danube river was observed. CONCLUSION: IgAV incidence in Croatia is similar to other European countries. Spatial statistical analysis showed a non-random distribution of IgAV and IgAVN. Although aetiological associations cannot be inferred, spatial analytical techniques may help in investigating and generating new hypotheses in non-communicable diseases considering possible environmental risk factors and identification of potential genetic or epigenetic diversity.

Public health policy-making for hearing loss: stakeholders' evaluation of a novel eHealth tool.

BACKGROUND: Hearing loss (HL) affects 466 million people of all ages worldwide, with a rapidly increasing prevalence, and therefore requires appropriate public health policies. Multi-disciplinary approaches that make use of eHealth services can build the evidence to influence public policy. The European Union-funded project EVOTION developed a platform that is fed with real-time data from hearing aids, a smartphone, and additional clinical data and makes public health policy recommendations based on hypothetical public health policy-making models, a big data engine and decision support system. The present study aimed to evaluate this platform as a new tool to support policy-making for HL. METHODS: A total of 23 key stakeholders in the United Kingdom, Croatia, Bulgaria and Poland evaluated the platform according to the Strengths, Weaknesses, Opportunities and Threats methodology. RESULTS: There was consensus that the platform, with its advanced technology as well as the amount and variety of data that it can collect, has huge potential to inform commissioning decisions, public health regulations and affect healthcare as a whole. To achieve this, several limitations and external risks need to be addressed and mitigated. Differences between countries highlighted that the EVOTION tool should be used and managed according to local constraints to maximise success. CONCLUSION: Overall, the EVOTION platform can equip HL policy-makers with a novel data-driven tool that can support public health policy-making for HL in the future.

A Data-informed Public Health Policy-Makers Platform.

Hearing loss is a disease exhibiting a growing trend due to a number of factors, including but not limited to the mundane exposure to the noise and ever-increasing size of the older population. In the framework of a public health policymaking process, modeling of the hearing loss disease based on data is a key factor in alleviating the issues related to the disease and in issuing effective public health policies. First, the paper describes the steps of the data-driven policymaking process. Afterward, a scenario along with the part of the proposed platform responsible for supporting policymaking are presented. With the aim of demonstrating the capabilities and usability of the platform for the policy-makers, some initial results of preliminary analytics are presented in the framework of a policy-making process. Ultimately, the utility of the approach is validated throughout the results of the survey which was presented to the health system policy-makers involved in the policy development process in Croatia.

Challenges and Strengths of Multidisciplinary Research in Audiology: The EVOTION Example.

Purpose The EU-funded research project EVOTION has brought together clinical, technical, and public health experts with the aim to offer a solution for the holistic management of hearing loss. This report presents the challenges, strengths, and key take-home messages of working in this multidisciplinary consortium. Method Fifteen consortium members completed an online survey with 6 open-ended questions. Responses were analyzed using a thematic approach. Results Analysis identified 4 main themes: (a) communication, that is, cross-disciplinary communication difficulties but also range of expertise; (b) opportunities, that is, innovation, learning, and collaborations; (c) technology, that is, technical requirements and data collection and management issues; and (d) local constraints, that is, institutional limitations, resources, and planning. Conclusions Although the challenges reported differed by country and specialty, there was consensus about the value, expertise, and opportunities of the project. It is recommended that in future similar multidisciplinary projects in audiology, researchers establish a common language and assess technical requirements and local constraints prior to initiating research activities.

Indoor carbon dioxide concentrations in Croatian elementary school classrooms during the heating season.

Aware that exposure to stuffy indoor air with high levels of carbon dioxide (CO2) is associated with higher absenteeism and reduced academic performance in school pupils, the World Health Organization (WHO) Regional Office for Europe initiated indoor air quality surveys in schools, including CO2 monitoring, to assess ventilation and exposure to stuffy air. Here we report the findings of the first such survey in Croatia. It was conducted in 60 classrooms of 20 urban and rural elementary schools throughout the country during the heating season. Measurements of CO2 levels showed that all 60 classrooms exceeded the international guidelines of 1938 mg/m3. Mean CO2 concentrations ranged from 2771 to 7763 mg/m3. The highest concentration measured in urban schools was 7763 mg/m3 and in rural schools 4771 mg/m3. Average CO2 levels were higher in continental schools (3683 mg/m3) than the coastal ones (3134 mg/m3), but all demonstrate poor ventilation during the heating season all over Croatia.

Big Data for Sound Policies: Toward Evidence-Informed Hearing Health Policies.

PURPOSE: The scarcity of health care resources calls for their rational allocation, including within hearing health care. Policies define the course of action to reach specific goals such as optimal hearing health. The process of policy making can be divided into 4 steps: (a) problem identification and issue recognition, (b) policy formulation, (c) policy implementation, and (d) policy evaluation. Data and evidence, especially Big Data, can inform each of the steps of this process. Big Data can inform the macrolevel (policies that determine the general goals and actions), mesolevel (specific services and guidelines in organizations), and microlevel (clinical care) of hearing health care services. The research project EVOTION applies Big Data collection and analysis to form an evidence base for future hearing health care policies. METHOD: The EVOTION research project collects heterogeneous data both from retrospective and prospective cohorts (clinical validation) of people with hearing impairment. Retrospective data from clinical repositories in the United Kingdom and Denmark will be combined. As part of a clinical validation, over 1,000 people with hearing impairment will receive smart EVOTION hearing aids and a mobile phone application from clinics located in the United Kingdom and Greece. These clients will also complete a battery of assessments, and a subsample will also receive a smartwatch including biosensors. Big Data analytics will identify associations between client characteristics, context, and hearing aid outcomes. RESULTS: The evidence EVOTION will generate is relevant especially for the first 2 steps of the policy-making process, namely, problem identification and issue recognition, as well as policy formulation. EVOTION will inform microlevel, mesolevel, and macrolevel of hearing health care services through evidence-informed policies, clinical guidelines, and clinical care. CONCLUSION: In the future, Big Data can inform all steps of the hearing health policy-making process and all levels of hearing health care services.

Multi-lag tone-entropy in neonatal stress.

Heart rate variability (HRV) has been analysed using linear and nonlinear methods. In the framework of a controlled neonatal stress model, we applied tone-entropy (T-E) analysis at multiple lags to understand the influence of external stressors on healthy term neonates. Forty term neonates were included in the study. HRV was analysed using multi-lag T-E at two resting and two stress phases (heel stimulation and a heel stick blood drawing phase). Higher mean entropy values and lower mean tone values when stressed showed a reduction in randomness with increased sympathetic and reduced parasympathetic activity. A ROC analysis was used to estimate the diagnostic performances of tone and entropy and combining both features. Comparing the resting and simulation phase separately, the performance of tone outperformed entropy, but combining the two in a quadratic linear regression model, neonates in resting as compared to stress phases could be distinguished with high accuracy. This raises the possibility that when applied across short time segments, multi-lag T-E becomes an additional tool for more objective assessment of neonatal stress.

Asymmetric detrended fluctuation analysis in neonatal stress.

OBJECTIVE: To detect stress in newborns by observing heart rate (HR) variability utilizing an asymmetric detrended fluctuation analysis (ADFA), we sought to determine the fractal structure of the series of inter-beat intervals, so as to distinguish the periods of acceleration of the HR from decelerations. Thus, two scaling exponents, α + and α -, representing decelerations and accelerations respectively, are obtained. APPROACH: Forty healthy term newborns were included in this study, undergoing two different types of stress stimuli: routine heel lance blood sampling for metabolic screening purposes, and its simulation by applying dull pressure on the heel. MAIN RESULTS: It appears that when newborns face stress, the scaling exponent related to accelerations significantly increases and becomes higher than the deceleration scaling exponent. To test the diagnostic properties of the scaling exponents, an ROC curve analysis was applied; α - showed good diagnostic performance with an AUC between 0.626 and 0.826, depending on the length of the time series. The joint use of α + and α - further increased the diagnostic performance, in particular for shorter series of RR intervals, with an AUC between 0.691 and 0.833. SIGNIFICANCE: ADFA, particularly of the acceleration scaling exponent, may be a useful clinical diagnostic tool for monitoring neonatal stress.

The EVOTION Decision Support System: Utilizing It for Public Health Policy-Making in Hearing Loss.

As Decision Support Systems start to play a significant role in decision making, especially in the field of public-health policy making, we present an initial attempt to formulate such a system in the concept of public health policy making for hearing loss related problems. Justification for the system's conceptual architecture and its key functionalities are presented. The introduction of the EVOTION DSS sets a key innovation and a basis for paradigm shift in policymaking, by incorporating relevant models, big data analytics and generic demographic data. Expected outcomes for this joint effort are discussed from a public-health point of view.

Tree pollen spectra and pollen allergy risk in the Osijek-Baranja County.

The forests of north-eastern Croatia, as well as various plants and trees in the parks and streets of the Osijek-Baranja County, produce large amounts of pollen during the pollen season, which can cause allergy symptoms in pollen sensitive individuals. The aim of this study was to determine the most frequent types of pollen in this area and estimate possible health risks, especially the risk of allergy. In 2009 and 2010, the staff of the Health Ecology Department of the Osijek Public Health Institute monitored tree pollen concentrations in four cities from the Osijek - Baranja County (Osijek, Nasice, Dakovo and Beli Manastir) using a Burkard volumetric instrument. The results were affected by weather conditions. Windy and sunny days facilitated the transfer of pollen, whereas during rainy days, the concentration of pollen grains decreased. High pollen concentrations of Cupressaceae/Taxaceae, Betulaceae, Salicaceae and Aceraceae could be the cause for symptoms of pollen allergy. In 2009, conifers, birch and poplar pollen were dominant at all monitoring stations with 5000 pollen grains (PG), 3188 PG and 3113 PG respectively. The highest number of pollen grains was recorded at measuring site Osijek. The variations in airborne pollen concentration between pollen seasons were recorded at all monitoring stations. The most obvious variations were recorded at measuring site Osijek. The usual pollination period lasts two to three months, which means that most pollen grains remain present from February to early June. However, the Cupressaceae / Taxaceae pollination periods last the longest and their pollen grains remain present until the end of summer. The risk of allergy was determined at four monitored measuring stations and the obtained data confirmed that the largest number of days with a high health risk was at the Dakovo measuring station for a species of birch. The research information aims to help allergologists and individuals allergic to plant pollen develop preventive measures and proper treatment therapies.