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Significance of Biostatistics in Public Health

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A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Public Health Statistics and Risk Assessment".

Deadline for manuscript submissions: closed (28 March 2023) | Viewed by 9633

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Prof. Dr. Malgorzata Kowalska

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Department of Epidemiology, Faculty of Medical Sciences in Katowice, Medical University of Silesia, 40-055 Katowice, Poland
Interests: epidemiology; public health

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Dear Colleagues,

Biostatistics, traditional as well as new statistical methods, are of invaluable importance for scientific knowledge in the field of public health. Thanks to them, it becomes possible to study the variability of health phenomena over time and to verify the hypotheses regarding their differentiation in particular groups. Statistical models provide the possibility of forecasting, and at the same time allow the identification of health determinants, as well as assessment of cause–effect relationships in medical sciences. In the proposed Special Issue of the journal, we will allow sharing conclusions from your scientific research in which you used the methods of descriptive or analytical statistics. We are interested in your observations related to the impact of chosen research construction, methods of sampling, and adopted methods of statistical analysis on the obtained results. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems in public health sciences.

Prof. Dr. Malgorzata Kowalska
Guest Editor

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Keywords

public health
epidemiology
biostatistics
research design
sampling method
data analysis
prognosis
reliability of the results

Published Papers (6 papers)

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Research

16 pages, 1760 KiB

Open AccessArticle

The Impact of Meteorological Parameters and Seasonal Changes on Reporting Patients with Selected Cardiovascular Diseases to Hospital Emergency Departments: A Pilot Study

by Paweł Kotecki, Barbara Więckowska and Barbara Stawińska-Witoszyńska

Int. J. Environ. Res. Public Health 2023, 20(6), 4838; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph20064838 - 9 Mar 2023

Cited by 3 | Viewed by 1562

Abstract

(1) Background: So far, research results have confirmed the relationship between heat and cold stress, the fluctuations in atmospheric pressure and high relative humidity, and the vulnerability of patients with so-called “weather-dependent” diseases which could lead to death. This study aimed to determine the meteorological parameters, their interactions, and the seasonal changes of the most significant factors in predicting the number of patients reporting to the Emergency Departments (EDs) in Poznań (Poland) during 2019. (2) Methods: The analysis included the meteorological parameters and data of 3606 patients diagnosed with essential or complicated arterial hypertension, myocardial infarction, chronic ischemic heart disease, and ischemic or unspecified stroke by the International Classification of Diseases (ICD-10). The meteorological data (days per week and seasonal data) were used to build a linear regression model to assess the changes in the daily number of reporting patients. The input data for the final model were selected based on the principal component analysis (PCA), and built for each delay and acceleration (reporting up to 3 days before the change or up to 3 days after the change of the meteorological parameter). (3) Results: A significantly lower number of reports was observed during weekends compared to working days (standardised b = −0.254, p-value < 0.0001) and three days before the maximum daily air temperature in the spring and summer period (standardised b = −0.748, p-value < 0.0001), while two days after the increase in the daily amplitude of atmospheric pressure (standardised b = 0.116, p-value = 0.0267), and also on the day of occurrence of the unfavourable interdiurnal air temperature change, an increase in the number of patients was noted (standardised b = 0.115, p-value = 0.0186). The changes in the last two parameters were statistically insignificant. Based on the obtained results, the negative impact of the changes in the meteorological conditions on the number of reports to the EDs in Poznań was determined. Full article

(This article belongs to the Special Issue Significance of Biostatistics in Public Health)

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11 pages, 380 KiB

Open AccessArticle

How to Use Biomechanical Job Exposure Matrices with Job History to Access Work Exposure for Musculoskeletal Disorders? Application of Mathematical Modeling in Severe Knee Pain in the Constances Cohort

by Guillaume Deltreil, Patrick Tardivel, Piotr Graczyk, Mikael Escobar-Bach and Alexis Descatha

Int. J. Environ. Res. Public Health 2022, 19(23), 16217; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192316217 - 4 Dec 2022

Cited by 2 | Viewed by 1101

Abstract

Introduction: Musculoskeletal disorders related to work might be caused by the cumulative effect of occupational exposures during working life. We aimed to develop a new model which allows to compare the accuracy of duration of work and intensity/frequency associations in application to severe knee pain. Methods: From the CONSTANCES cohort, 62,620 subjects who were working at inclusion and coded were included in the study. The biomechanical job exposure matrix “JEM Constances” was used to assess the intensity/frequency of heavy lifting and kneeling/squatting at work together with work history to characterize the association between occupational exposure and severe knee pain. An innovative model G was developed and evaluated, allowing to compare the accuracy of duration of work and intensity/frequency associations. Results: The mean age was 49 years at inception with 46 percent of women. The G model developed was slightly better than regular models. Among the men subgroup, odds ratios of the highest quartile for the duration and low intensity were not significant for both exposures, whereas intensity/duration were for every duration. Results in women were less interpretable. Conclusions: Though higher duration increased strength of association with severe knee pain, intensity/frequency were important predictors among men. Exposure estimation along working history should have emphasis on such parameters, though other outcomes should be studied and have a focus on women. Full article

(This article belongs to the Special Issue Significance of Biostatistics in Public Health)

7 pages, 440 KiB

Open AccessArticle

The Accuracy of a Screening Tool in Epidemiological Studies—An Example of Exhaled Nitric Oxide in Paediatric Asthma

by Kamil Barański and Vivi Schlünssen

Int. J. Environ. Res. Public Health 2022, 19(22), 14746; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192214746 - 9 Nov 2022

Cited by 1 | Viewed by 1096

Abstract

Diagnostic tests are widely used in medicine, especially in the clinical setting. The doctor’s decision regarding the treatment process is mostly based on the result of the diagnostic test. The value of the test is expressed by its accuracy. It is easier to verify the accuracy of a diagnostic test in a clinical setting in comparison to an epidemiological setting. Moreover, a very good test may not work in epidemiological settings in the same effective way as in a clinical setting, especially because the accuracy is affected by the prevalence of the disease. The aim of the study is to assess the accuracy of FeNO measurement in different respiratory disorders or symptoms, including their prevalence, in a childhood population. The secondary aim is to suggest the optimal FeNO cut-off for epidemiological screening for respiratory diseases and symptoms. Methods: The cross-sectional study included 447 children (50.8% boys and 49.2% girls) aged 6–9 years. An adapted version of the ISAAC questionnaire was used for the assessment of the respiratory status. FeNO was measured with an electrochemical device (Niox Mino) according to ERS/ATS recommendations. For interpretation, the FeNO cut-off values of 20 parts per billion (ppb), 25 ppb and 35 ppb were applied taking the real-life prevalence of the disease or symptoms into consideration and also for simulated prevalences of 20%, 30%, 40%, 50% for the interpretation of the accuracy of the test. The accuracy was calculated according to the following formula: Accuracy = (Prevalence) (Sensitivity) + (1- Prevalence) (Specificity). The area under the curve was calculated based on logistic regression. Results: For all respiratory outcomes, FeNO accuracy decreased with increasing prevalence, and in general the area under the curve (AUC) was low. The highest FeNO accuracy was found for any asthma diagnosis (with possible coexisting diseases/symptoms), i.e., 78.6%, 92.8% and 88.5% for FeNO cut-offs >19 ppb, >24 ppb and >34 ppb, respectively. The AUC was 0.628. For the same FeNO cut-offs, the accuracy of an asthma diagnosis without any coexisting diseases and symptoms was 81.2%, 87.5%, 92.9%, respectively, with an AUC of 0.757. Conclusion: FeNO accuracy decreases with increasing prevalence of the respiratory disease and symptoms. The best accuracy for the FeNO cut-off in the screening of asthma for epidemiological purposes is 35 ppb. For isolated asthma, the best accuracy for FeNO was 92.9%. Full article

(This article belongs to the Special Issue Significance of Biostatistics in Public Health)

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12 pages, 925 KiB

Open AccessArticle

The Prevalence of Anticitrullinated Protein Antibodies in Older Poles—Results from a Population-Based PolSenior Study

by Anna Chudek, Przemysław Kotyla, Małgorzata Mossakowska, Tomasz Grodzicki, Tomasz Zdrojewski, Magdalena Olszanecka-Glinianowicz, Jerzy Chudek and Aleksander J. Owczarek

Int. J. Environ. Res. Public Health 2022, 19(21), 14216; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph192114216 - 31 Oct 2022

Cited by 1 | Viewed by 1342

Abstract

Little is known about the occurrence of antibodies in older subjects. We analyzed the prevalence of anticitrullinated protein antibodies (anti-CCP) in a representative cohort of Polish older adults, participants of PolSenior substudy. Randomly selected 1537 serum samples of community-dwelling participants aged 65 and over. Questionnaires were completed by qualified interviewers and laboratory assessments served as a database for this analysis. The frequency of anti-CCP seropositivity (N = 50) was estimated at 3.25% (95% CI: 2.45–4.30%), being higher among women—4.05% (2.83–5.73%) than men—2.41% (1.48–3.86%). The frequency of anti-CCP seropositivity was decreasing with age from 4.29% in aged 65–74 years and 4.07% in 70–84 years to 1.50% in aged 85 years or above (p < 0.05). Hypoalbuminemia, inflammatory status (C-reactive protein >10 mg/dL or interleukin-6 ≥10 pg/mL), and female gender were associated with increased, while age ≥85 years with decreased risk of seropositivity. Multivariable logistic regression revealed that hypoalbuminemia, inflammatory status, and age ≥85 years were independently associated factors of anti-CCP seropositivity. The decreased frequency of anti-CCP seropositivity in the oldest old suggests shorter survival of the seropositive individuals who developed rheumatoid arthritis. It seems that low symptomatic RA remains frequently undiagnosed in older subjects. Full article

(This article belongs to the Special Issue Significance of Biostatistics in Public Health)

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11 pages, 1061 KiB

Open AccessArticle

Spatial Variability of COVID-19 Hospitalization in the Silesian Region, Poland

by Małgorzata Kowalska and Ewa Niewiadomska

Int. J. Environ. Res. Public Health 2022, 19(15), 9007; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19159007 - 25 Jul 2022

Cited by 1 | Viewed by 1554

Abstract

Assessment of regional variation in the COVID-19 epidemic is an important task for the implementation of effective action in public health, especially in densely populated regions. In this descriptive study, the temporal and spatial variability of morbidity and in-hospital mortality of COVID-19 in the Silesian Voivodship (Poland) was analyzed. Secondary epidemiological data of hospitalized patients due to COVID-19 from 1 March to 31 December 2020 and from 1 January to 31 December 2021 were obtained from the regional registry of the Silesian Voivodship Office in Katowice. A year by year (2020 versus 2021) comparative analysis showed a similar course pattern of the COVID-19 pandemic in the Silesian Voivodeship; with the worst situation occurring in the colder months of the year. The percentage of in-hospital mortality remained at a high level, close to 20% during the second year of observation. The risk of death in patients hospitalized due to COVID-19 increased with the number of comorbidities. The highest number of patients was documented in densely inhabited regions with intensive population movement (Częstochowa and border counties). The epidemiological ‘map’ facilitates the generation of hypotheses needed for the explanation of the observed epidemic hazard in one of the most populated regions of Poland. Full article

(This article belongs to the Special Issue Significance of Biostatistics in Public Health)

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11 pages, 1851 KiB

Open AccessArticle

Concentration–Response Functions as an Essence of the Results from Lags

by Mieczysław Szyszkowicz

Int. J. Environ. Res. Public Health 2022, 19(13), 8116; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph19138116 - 1 Jul 2022

Cited by 2 | Viewed by 1331

Abstract

Among various aspects of environmental epidemiology, one is to assess the relationships between ambient air pollution and health outcomes. The goal of this work is to estimate the associations in the form of the parametric concentration–response functions (C-RF). Various forms of the C-RFs are proposed in this short-term health effect study. Emergency department (ED) visits for all respiratory health problems are analyzed as an illustrative example. A case-crossover (CC) technique is applied as a study design. Daily cases are organized as daily counts by the same day of the week in one common month. A conditional Poisson regression is used in the constructed statistical models. Temperature and relative humidity are included in the statistical models in the form of natural splines. Ground-level ozone concentration is considered an exposure. Ozone concentration values are transformed and submitted to the statistical models. The parameters of the transformation are determined by using the goodness of fit criterion. Counts of ED visits are analyzed in relation to a sequence of lagged exposure to ozone. The C-RF shapes are constructed for each individual lag. In a final step, the set of the estimated C-RF shapes is used to create a pooled C-RF shape. The results are positive and statistically significant for nine lagged exposures, from 0 to 8 days. The following relative risks (RR) were estimated from the constructed C-RFs at 30 ppb concentration of ozone: RR = 1.0531 (95% confidence interval: 1.0231, 1.0718), 1.0462 (1.0253, 1.0677), and 1.0387, (1.0240, 1.0531), realizing the CC method, CC method + transformation, and CC method + flexible transformation, respectively. The pooled C-RF shape gives a summary of the associations between ED visits for respiratory conditions and ambient ozone. The estimated shapes indicate lower air health effects than the standard CC methods. Among three considered statistical models, the CC method + flexible transformation is the most appropriate to use according to the goodness of fit criterion. Full article

(This article belongs to the Special Issue Significance of Biostatistics in Public Health)

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