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Special Issue "Statistical and Epidemiological Methods in Public Health"

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 (30 April 2021) | Viewed by 8656

Special Issue Editors

Dr. Sören Möller
E-Mail Website
Guest Editor
Open Patient data Explorative Network, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
Interests: biostatistics; epidemiological methods; risk prediction scores; unusual bias sources; probability theory
Special Issues, Collections and Topics in MDPI journals
Dr. Linda Juel Ahrenfeldt
E-Mail Website
Assistant Guest Editor
Unit of Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, 5000 Odense, Denmark
Interests: sex differences in health and mortality; aging; twin research

Special Issue Information

Dear Colleagues,

Epidemiology has been the cornerstone of public health research for decades and has come even more to the center of health research and public awareness during the 2020 COVID-19 pandemic. Thus, it is of utmost importance that epidemiological studies investigating issues relevant to public health are carried out by applying correct and state-of-the-art statistical and epidemiological methods to ensure the validity of scientific results and relevance of resulting public health interventions.

The purpose of this Special Issue is to provide a collection of articles that describe, evaluate, or discuss modern statistical and epidemiological methods relevant to research in public health with the aim of evolving the area toward an even higher degree of epidemiological and statistical rigor. Articles providing theoretical considerations, practical applications, best practice recommendations, and pedagogical advice are welcome.

Dr. Sören Möller
Dr. Linda Juel Ahrenfeldt
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biostatistics
  • epidemiology
  • public health
  • statistical methods
  • epidemiological methods
  • bias

Published Papers (7 papers)

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Research

Article
Prevalence and Associated Factors of Falls among Older Adults between Urban and Rural Areas of Shantou City, China
Int. J. Environ. Res. Public Health 2021, 18(13), 7050; https://doi.org/10.3390/ijerph18137050 - 01 Jul 2021
Cited by 2 | Viewed by 1252
Abstract
Background: To investigate the prevalence of falls and associated factors among older adults in urban and rural areas and to facilitate the design of fall prevention interventions. Methods: We used cluster random sampling to investigate the sociodemographic information, living habits, medical status, falls, [...] Read more.
Background: To investigate the prevalence of falls and associated factors among older adults in urban and rural areas and to facilitate the design of fall prevention interventions. Methods: We used cluster random sampling to investigate the sociodemographic information, living habits, medical status, falls, home environment, and balance ability among 649 older adult participants. Univariate and multivariate logistic regression were used to examine the associated factors of falls. Results: The incidence of falls among older adults in Shantou City was 20.65%. Among them, the incidence was 27.27% in urban areas and 16.99% in rural areas. The rate of injury from falls among older adults was 14.48%, with18.61% in urban area and 12.20% in rural area. Multivariate analysis showed that the associated factors of falls among older adults in Shantou City included a high school or below education level (OR = 2.387, 95% CI: 1.305–4.366); non-farming as the previous occupation (OR = 2.574, 95% CI: 1.613–4.109); incontinence(OR = 2.881, 95% CI: 1.517–5.470); lack of fall prevention education (OR = 1.856, 95% CI: 1.041–3.311); and reduced balance ability (OR = 3.917, 95% CI: 2.532–6.058). Discussion: Older adults have a higher rate of falling in Shantou City, compared to the average rate in China. There are similarities and differences in the associated factors of falls among older adults between urban and rural areas of Shantou City. Targeted interventions for older adults in different regions may be more effective in reducing the risk of falls. Full article
(This article belongs to the Special Issue Statistical and Epidemiological Methods in Public Health)
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Article
Relationships between Renewable Energy and the Prevalence of Morbidity in the Countries of the European Union: A Panel Regression Approach
Int. J. Environ. Res. Public Health 2021, 18(12), 6548; https://doi.org/10.3390/ijerph18126548 - 18 Jun 2021
Cited by 6 | Viewed by 1031
Abstract
The main objective of the presented study was to examine the associations between the use of renewable energy sources in selected sectors (transport, electricity, heating, and cooling) and the prevalence of selected groups of diseases in the European Union, with an emphasis on [...] Read more.
The main objective of the presented study was to examine the associations between the use of renewable energy sources in selected sectors (transport, electricity, heating, and cooling) and the prevalence of selected groups of diseases in the European Union, with an emphasis on the application of statistical methods considering the structure of data. The analyses included data on 27 countries of the European Union from 2010 to 2019 published in the Eurostat database and the Global Burden of Disease Study. Panel regression models (pooling model, fixed (within) effects model, random effects model) were primarily used in analytical procedures, in which a panel variable was represented by countries. In most cases, positive and significant associations between the use of renewable energy sources and the prevalence of diseases were confirmed. The results of panel regression models could be generally interpreted as meaning that renewable energy sources are associated with the prevalence of diseases such as cardiovascular diseases, diabetes and kidney diseases, digestive diseases, musculoskeletal disorders, neoplasms, sense organ diseases, and skin and subcutaneous diseases at a significance level (α) of 0.05 and lower. These findings could be explained by the awareness of the health problem and the response in the form of preference for renewable energy sources. Regarding statistical methods used for country data or for data with a specific structure, it is recommended to use the methods that take this structure into account. The absence of these methods could lead to misleading conclusions. Full article
(This article belongs to the Special Issue Statistical and Epidemiological Methods in Public Health)
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Article
Estimating Relative Risk When Observing Zero Events—Frequentist Inference and Bayesian Credibility Intervals
Int. J. Environ. Res. Public Health 2021, 18(11), 5527; https://doi.org/10.3390/ijerph18115527 - 21 May 2021
Cited by 3 | Viewed by 984
Abstract
Relative risk (RR) is a preferred measure for investigating associations in clinical and epidemiological studies with dichotomous outcomes. However, if the outcome of interest is rare, it frequently occurs that no events are observed in one of the comparison groups. In this case, [...] Read more.
Relative risk (RR) is a preferred measure for investigating associations in clinical and epidemiological studies with dichotomous outcomes. However, if the outcome of interest is rare, it frequently occurs that no events are observed in one of the comparison groups. In this case, many of the standard methods used to obtain confidence intervals (CIs) for the RRs are not feasible, even in studies with strong statistical evidence of an association. Different strategies for solving this challenge have been suggested in the literature. This paper, which uses both mathematical arguments and statistical simulations, aims to present, compare, and discuss the different statistical approaches to obtain CIs for RRs in the case of no events in one of the comparison groups. Moreover, we compare these frequentist methods with Bayesian approaches to determine credibility intervals (CrIs) for the RRs. Our results indicate that most of the suggested approaches can be used to obtain CIs (or CrIs) for RRs in the case of no events, although one-sided intervals obtained by methods based on deliberate, probabilistic considerations should be preferred over ad hoc methods. In addition, we demonstrate that Bayesian approaches can be used to obtain CrIs in these situations. Thus, it is possible to obtain statistical inference for the RR, even in studies with no events in one of the comparison groups, and CIs for the RRs should always be provided. However, it is important to note that the obtained intervals are sensitive to the method chosen in the case of small sample sizes. Full article
(This article belongs to the Special Issue Statistical and Epidemiological Methods in Public Health)
Article
The Reciprocal Relationship between Socioeconomic Status and Health and the Influence of Sex: A European SHARE-Analysis Based on Structural Equation Modeling
Int. J. Environ. Res. Public Health 2021, 18(9), 5045; https://doi.org/10.3390/ijerph18095045 - 10 May 2021
Cited by 1 | Viewed by 1183
Abstract
It is well recognized that socioeconomic status (SES) is an important determinant of health, but many studies fail to address the possibility of reverse causation. We aim to investigate the reciprocal relationship between trajectories of SES and health, and how these associations differ [...] Read more.
It is well recognized that socioeconomic status (SES) is an important determinant of health, but many studies fail to address the possibility of reverse causation. We aim to investigate the reciprocal relationship between trajectories of SES and health, and how these associations differ by sex. We performed a longitudinal study including 29,824 men and 37,263 women aged 50+ participating in at least two consecutive waves of the Survey of Health, Ageing and Retirement in Europe (SHARE). Using structural equation modeling, we found that baseline household income and wealth led to improvements in cognitive function, grip strength, quality of life and depressive symptoms, and a better initial health led to higher income and wealth for both sexes. However, the results indicated that the relative effect of cognitive function and grip strength on SES trajectories was overall greater than the corresponding effect of SES on health changes, particularly regarding income among women, but for quality of life and depressive symptoms, the reverse was indicated, though most pronounced for the associations with wealth. The reciprocal associations between SES and physical function were stronger for men than for women, whereas most associations with cognitive function and mental health were similar between sexes. This study demonstrates that both social causation and health selection contribute to social inequalities in health, but the influence of each direction and the importance of sex differences may vary according to the health outcomes investigated. Full article
(This article belongs to the Special Issue Statistical and Epidemiological Methods in Public Health)
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Article
Methods for Estimating Avoidable Costs of Excessive Alcohol Consumption
Int. J. Environ. Res. Public Health 2021, 18(9), 4964; https://doi.org/10.3390/ijerph18094964 - 07 May 2021
Cited by 3 | Viewed by 1054
Abstract
Background: Alcohol is a risk factor with serious consequences for society and individuals. This study aims to present methods and approaches that might be used to estimate the costs related to excessive alcohol consumption. It emphasizes the need for general methods and [...] Read more.
Background: Alcohol is a risk factor with serious consequences for society and individuals. This study aims to present methods and approaches that might be used to estimate the costs related to excessive alcohol consumption. It emphasizes the need for general methods and approaches that are easily applicable, because the level of digitalization and data availability vary across regions. The lack of data makes many methods inapplicable and useless. The ease of applicability will help to make cost-of-illness studies and their results comparable globally. Methods: This study is based on data from the Czech Republic in 2017. Drinking alcohol results in costs of healthcare, social care, law enforcement, and administrative costs of public authorities. To quantify the cost of drinking in the Czech Republic, the top-down approach, bottom-up approach, human capital approach and attributable fractions were used. Results: In 2017, the cost related to alcohol was estimated at 0.66% of the national GDP. Lost productivity represented 54.45% of total cost related to alcohol. All cost related to alcohol is considered to be avoidable. Conclusions: The methods and approaches applied to estimate the cost of disease or any other health issue should be generalized regarding the availability of data and specifics of provided services to people who are addicted or have any kind of disability. Full article
(This article belongs to the Special Issue Statistical and Epidemiological Methods in Public Health)
Article
Variability Matters
Int. J. Environ. Res. Public Health 2021, 18(1), 157; https://doi.org/10.3390/ijerph18010157 - 28 Dec 2020
Cited by 1 | Viewed by 1292
Abstract
Much of science, including public health research, focuses on means (averages). The purpose of the present paper is to reinforce the idea that variability matters just as well. At the hand of four examples, we highlight four classes of situations where the conclusion [...] Read more.
Much of science, including public health research, focuses on means (averages). The purpose of the present paper is to reinforce the idea that variability matters just as well. At the hand of four examples, we highlight four classes of situations where the conclusion drawn on the basis of the mean alone is qualitatively altered when variability is also considered. We suggest that some of the more serendipitous results have their origin in variability. Full article
(This article belongs to the Special Issue Statistical and Epidemiological Methods in Public Health)
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Article
Nonparametric Limits of Agreement in Method Comparison Studies: A Simulation Study on Extreme Quantile Estimation
Int. J. Environ. Res. Public Health 2020, 17(22), 8330; https://doi.org/10.3390/ijerph17228330 - 11 Nov 2020
Cited by 7 | Viewed by 1112
Abstract
Bland–Altman limits of agreement and the underlying plot are a well-established means in method comparison studies on quantitative outcomes. Normally distributed paired differences, a constant bias, and variance homogeneity across the measurement range are implicit assumptions to this end. Whenever these assumptions are [...] Read more.
Bland–Altman limits of agreement and the underlying plot are a well-established means in method comparison studies on quantitative outcomes. Normally distributed paired differences, a constant bias, and variance homogeneity across the measurement range are implicit assumptions to this end. Whenever these assumptions are not fully met and cannot be remedied by an appropriate transformation of the data or the application of a regression approach, the 2.5% and 97.5% quantiles of the differences have to be estimated nonparametrically. Earlier, a simple Sample Quantile (SQ) estimator (a weighted average of the observations closest to the target quantile), the Harrell–Davis estimator (HD), and estimators of the Sfakianakis–Verginis type (SV) outperformed 10 other quantile estimators in terms of mean coverage for the next observation in a simulation study, based on sample sizes between 30 and 150. Here, we investigate the variability of the coverage probability of these three and another three promising nonparametric quantile estimators with n=50(50)200,250(250)1000. The SQ estimator outperformed the HD and SV estimators for n=50 and was slightly better for n=100, whereas the SQ, HD, and SV estimators performed identically well for n150. The similarity of the boxplots for the SQ estimator across both distributions and sample sizes was striking. Full article
(This article belongs to the Special Issue Statistical and Epidemiological Methods in Public Health)
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