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Advances in Measuring Health and Wellbeing

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

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 33414

Special Issue Editors


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Guest Editor
Statistics Department, Universidad Carlos III de Madrid, 28903 Getafe, Spain
Interests: applied statistics; data science; machine learning; robust statistics

E-Mail Website
Guest Editor
Statistics Department, Universidad Carlos III de Madrid, 28903 Getafe, Spain
Interests: data mining; health insurance; long-term care; predictive models

Special Issue Information

Dear Colleagues,

We are currently organizing a Special Issue entitled “Advances in Measuring Health and Wellbeing” in the International Journal of Environmental Research and Public Health. IJERPH is a peer-reviewed scientific journal that publishes articles and communications in the interdisciplinary area of environmental health sciences and public health. For detailed information on the journal, we refer you to https://www.mdpi.com/journal/ijerph.

Population ageing is a global phenomenon. Every country in the world is experiencing growth in the size and proportion of older persons in their population. The trend is increasing over time—according to World Population Prospects 2019 (United Nations (2019)), by 2050, one out of six people in the world will be 65 or over, up from one out of eleven in 2019. In an ageing society, the states not only need to worry about the shrinking labor market, but also, importantly, financial problems including pensions and the expenditures of maintaining health care systems, social supports, and other public services for older adult populations. Of particular interest is the long-term care needs of older individuals, particularly of those who have disabilities that prevent them from performing certain tasks that relate to daily life.

Several goals of United Nations’ 2030 Agenda for Sustainable Development are related to reducing the risks of being unhealthy and socially vulnerable in later life. Recently, we have experienced that, under the shock of a pandemic, these goals are scarcely fulfilled, even in developed countries. Thus, it is important to generate knowledge about the vulnerability of elderly people.

With this Special Issue we seek to attract contributions from diverse research lines, representing different geographies in order to develop instruments and methods that help to visualize data and produce reliable measurements of health and wellbeing that are comparable across countries. The use of data science, big data, and machine learning techniques in the area are welcome. These tools will help to better understand the health problems of older adults globally, and to facilitate appropriate health and social policy responses.

Prof. Dr. Aurea Grané
Prof. Irene Albarrán
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 monthly 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

  • aging
  • dependency
  • disabilities
  • health care
  • health insurance
  • long-term care
  • pensions
  • public health
  • wellbeing

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Published Papers (12 papers)

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Editorial

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3 pages, 287 KiB  
Editorial
Editorial on S.I. “Advances in Measuring Health and Wellbeing” in the International Journal of Environmental Research and Public Health
by Aurea Grané and Irene Albarrán
Int. J. Environ. Res. Public Health 2022, 19(9), 5103; https://doi.org/10.3390/ijerph19095103 - 22 Apr 2022
Cited by 2 | Viewed by 2110
Abstract
Measuring the health and wellbeing of the population is the first step in visualizing the real needs of the population in order to promote healthy habits, as well as effective health and social policy responses [...] Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)

Research

Jump to: Editorial

13 pages, 1786 KiB  
Article
Estimation of Life Expectancy for Dependent Population in a Multi-State Context
by Irene Albarrán Lozano, Pablo J. Alonso-González and José Javier Núñez-Velázquez
Int. J. Environ. Res. Public Health 2021, 18(21), 11162; https://doi.org/10.3390/ijerph182111162 - 24 Oct 2021
Cited by 3 | Viewed by 2265
Abstract
Population statistics show that there was an increase in life expectancy during the last century. However, this fact hides that this increase was not equal for all groups of the population. One of the most problematic cases for measuring this increase is that [...] Read more.
Population statistics show that there was an increase in life expectancy during the last century. However, this fact hides that this increase was not equal for all groups of the population. One of the most problematic cases for measuring this increase is that of the dependent population because of the absence of specific statistics. This paper describes a methodology for calculating life expectancy using multistate models that take into account the diversity of situations considered by Spanish legislation. For this purpose, statistical information contained in the national survey on disability and dependency (EDAD 2008) is used. The results suggest that life expectancies are lower than those of the general population and that they differ according to gender and intensity of suffering from this contingency. The calculations were made considering the legal framework currently existing in Spain. This fact conditions the definition of dependent person and, therefore, the set of individuals, their characteristics, and therefore, their final results. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
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13 pages, 861 KiB  
Article
Interactions of Comorbidity and Five Simple Environmental Unhealthy Habits Concerning Physical and Mental Quality of Life in the Clinical Setting
by Diego Martínez-Urbistondo, Rafael Suarez del Villar, Omar Ramos-Lopez, María Agud Fernández, Ramón Costa Segovia, Andrea Domínguez, Rocío García de la Garza, María López-Cano Gómez, Laura Prósper Ramos, Rodrigo San-Cristobal, Lidia Daimiel, Paula Villares Fernández and Jose Alfredo Martinez
Int. J. Environ. Res. Public Health 2021, 18(18), 9590; https://doi.org/10.3390/ijerph18189590 - 12 Sep 2021
Cited by 3 | Viewed by 2160
Abstract
The objective of this study was to examine the interactions between comorbidity and five lifestyle single habits concerning different subscales of quality of life (QoL). For the study, 302 patients were consecutively recruited at the internal medicine department of a tertiary teaching hospital. [...] Read more.
The objective of this study was to examine the interactions between comorbidity and five lifestyle single habits concerning different subscales of quality of life (QoL). For the study, 302 patients were consecutively recruited at the internal medicine department of a tertiary teaching hospital. Lifestyle habits, comorbidities and QoL were recorded according to validated questionnaires. Five single unhealthy habits, such as tobacco consumption, dietary intake of ultra-processed pastries, raw nuts or carbonated drinks, sleep time and physical activity patterns were selected according to previously published data. The main outcomes of the study were the scores of the eight subscales of the SF-36 QoL survey. The aggregate of unhealthy habits showed statistically significant association to every category in the SF-36 questionnaire, both in the univariate and the multivariate analysis when adjusting by age, sex and comorbidity. An interaction was found between comorbidity and unhealthy habits in both physical and mental summaries of SF-36. In conclusion, the lifestyle assessment according to five unhealthy habits is associated with a worse QoL. The interaction between comorbidity and unhealthy habits is especially clear in diseased patients due to the interplay between illness and lifestyle in the prediction of QoL. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
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59 pages, 64504 KiB  
Article
Fear in a Handful of Dust: The Epidemiological, Environmental, and Economic Drivers of Death by PM2.5 Pollution
by James Ming Chen, Mira Zovko, Nika Šimurina and Vatroslav Zovko
Int. J. Environ. Res. Public Health 2021, 18(16), 8688; https://doi.org/10.3390/ijerph18168688 - 17 Aug 2021
Cited by 3 | Viewed by 3390
Abstract
This study evaluates numerous epidemiological, environmental, and economic factors affecting morbidity and mortality from PM2.5 exposure in the 27 member states of the European Union. This form of air pollution inflicts considerable social and economic damage in addition to loss of life [...] Read more.
This study evaluates numerous epidemiological, environmental, and economic factors affecting morbidity and mortality from PM2.5 exposure in the 27 member states of the European Union. This form of air pollution inflicts considerable social and economic damage in addition to loss of life and well-being. This study creates and deploys a comprehensive data pipeline. The first step consists of conventional linear models and supervised machine learning alternatives. Those regression methods do more than predict health outcomes in the EU-27 and relate those predictions to independent variables. Linear regression and its machine learning equivalents also inform unsupervised machine learning methods such as clustering and manifold learning. Lower-dimension manifolds of this dataset’s feature space reveal the relationship among EU-27 countries and their success (or failure) in managing PM2.5 morbidity and mortality. Principal component analysis informs further interpretation of variables along economic and health-based lines. A nonlinear environmental Kuznets curve may describe the fuller relationship between economic activity and premature death from PM2.5 exposure. The European Union should bridge the historical, cultural, and economic gaps that impair these countries’ collective response to PM2.5 pollution. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
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18 pages, 574 KiB  
Article
Analysis of the Impact of Disease Acceptance, Demographic, and Clinical Variables on Adherence to Treatment Recommendations in Elderly Type 2 Diabetes Mellitus Patients
by Iwona Bonikowska, Katarzyna Szwamel and Izabella Uchmanowicz
Int. J. Environ. Res. Public Health 2021, 18(16), 8658; https://doi.org/10.3390/ijerph18168658 - 16 Aug 2021
Cited by 11 | Viewed by 3106
Abstract
This project aimed to analyze the impact of disease acceptance and selected demographic and clinical factors on the adherence to treatment recommendations in elderly type 2 diabetes mellitus patients. The observational study was performed using standardized research questionnaires: the Acceptance of Illness Scale [...] Read more.
This project aimed to analyze the impact of disease acceptance and selected demographic and clinical factors on the adherence to treatment recommendations in elderly type 2 diabetes mellitus patients. The observational study was performed using standardized research questionnaires: the Acceptance of Illness Scale (AIS), the Self-Care of Diabetes Inventory (SCODI), and the Adherence in Chronic Diseases Scale (ACDS). Two hundred patients with T2DM were studied (age M = 70.21 years, SD = 6.63 years). The median degree of disease acceptance was 29 (min–max = 8–40) and the median level of adherence was 24 (min–max = 13–28). Disease acceptance was a significant (p = 0.002) independent predictor of the odds of qualifying for non-adherence OR = 0.903, 95% CI = 0.846–0.963. The respondents gave the lowest scores for glycemic control (Mdn = 38.99, min–max = 8.33–150), and health control (Mdn = 55.88, min–max = 11.76–100). A one-way ANOVA showed that the non-adhering patients were significantly older compared to the adherence group and were taking significantly more diabetes pills per day. The level of disease acceptance was average, but it turned out to be an independent predictor of adherence. Therefore, it is justified to use psychological and behavioral interventions that are aimed at increasing the level of diabetes acceptance in elderly people with T2DM. It is important to have a holistic approach to the patient and to take actions that consider the patient’s deficits in the entire biopsychosocial sphere. The obtained result confirmed the legitimacy of interventions aimed at increasing the level of disease acceptance in this group of patients. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
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10 pages, 789 KiB  
Article
Deepening Well-Being Evaluation with Different Data Sources: A Bayesian Networks Approach
by Federica Cugnata, Silvia Salini and Elena Siletti
Int. J. Environ. Res. Public Health 2021, 18(15), 8110; https://doi.org/10.3390/ijerph18158110 - 30 Jul 2021
Cited by 3 | Viewed by 2292
Abstract
In this paper, we focus on a Bayesian network s approach to combine traditional survey and social network data and official statistics to evaluate well-being. Bayesian networks permit the use of data with different geographical levels (provincial and regional) and time frequencies (daily, [...] Read more.
In this paper, we focus on a Bayesian network s approach to combine traditional survey and social network data and official statistics to evaluate well-being. Bayesian networks permit the use of data with different geographical levels (provincial and regional) and time frequencies (daily, quarterly, and annual). The aim of this study was twofold: to describe the relationship between survey and social network data and to investigate the link between social network data and official statistics. Particularly, we focused on whether the big data anticipate the information provided by the official statistics. The applications, referring to Italy from 2012 to 2017, were performed using ISTAT’s survey data, some variables related to the considered time period or geographical levels, a composite index of well-being obtained by Twitter data, and official statistics that summarize the labor market. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
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17 pages, 387 KiB  
Article
Characterization of People with Functional Limitations from ICF Components Using the Longitudinal Social Protection Survey (ELPS) of Uruguay
by Julia Córdoba and María José Bagnato
Int. J. Environ. Res. Public Health 2021, 18(15), 8012; https://doi.org/10.3390/ijerph18158012 - 29 Jul 2021
Cited by 2 | Viewed by 1892
Abstract
Characterising people with disabilities at the population level using the ICF approach is a challenge, as it implies that researchers are able to identify variables that can account for the components that make up the multidimensional definition of disability. The purpose of this [...] Read more.
Characterising people with disabilities at the population level using the ICF approach is a challenge, as it implies that researchers are able to identify variables that can account for the components that make up the multidimensional definition of disability. The purpose of this study is to generate updated information on disability in Uruguay, as there has been no in-depth analysis of how this population lives, how they access the services and benefits that affect their quality of life, and what the significant differences are between those who make up this population. A quantitative analysis was applied to the target population, consisting of participants in the Longitudinal Survey of Social Protection (2016) who reported at least one limitation in performing ADLs and who were in the age range of 18–64 years. Significant differences were found between the different groups in terms of their reported limitations in relation to obtaining necessary services due to their health condition, dropping out of education before completing the compulsory level, low labour market insertion, feelings of loneliness, and low participation. More research needs to be done as it is clear that people with disabilities do not have access to the support they need, which leads to even greater exclusion. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
20 pages, 703 KiB  
Article
Population with Long-Term Care Needs in Six Latin American Countries: Estimation of Older Adults Who Need Help Performing ADLs
by Mauricio Matus-Lopez and Alexander Chaverri-Carvajal
Int. J. Environ. Res. Public Health 2021, 18(15), 7935; https://doi.org/10.3390/ijerph18157935 - 27 Jul 2021
Cited by 7 | Viewed by 2563
Abstract
The population in Latin America is ageing, and there is an inevitable demand for long-term care services. However, there are no comparative analyses between Latin American countries of the dependency situation of older adults. This study aims to calculate and compare percentages of [...] Read more.
The population in Latin America is ageing, and there is an inevitable demand for long-term care services. However, there are no comparative analyses between Latin American countries of the dependency situation of older adults. This study aims to calculate and compare percentages of older adults who need help performing the activities of daily living in six Latin American nations. The study is observational, transversal, and cross-national and uses microdata drawn from national surveys conducted in Argentina (n = 3291), Brazil (n = 3903), Chile (n = 31,667), Colombia (n = 17,134), Mexico (n = 7909), and Uruguay (n = 4042). Comparable indicators of the need for help in performing the basic and instrumental activities of daily living were calculated. The percentages of older adults in need of help for basic activities of daily living ranged from 5.8% in Argentina to 11% in Brazil; for instrumental activities of daily living, from 13.8% in Mexico to 35.7% in Brazil; and combined, from 18.1% in Argentina to 37.1% in Brazil. Brazil thus has the highest indicators, followed by Colombia. The results warn of the frail physical condition of older people and the high potential demand for long-term care services. The information provided could be useful for further research on and planning for long-term care needs in Latin American and middle-income countries. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
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16 pages, 349 KiB  
Article
The Effect of Health Shock and Basic Medical Insurance on Family Educational Investment for Children in China
by Pu Liao, Zhihong Dou and Xingxing Guo
Int. J. Environ. Res. Public Health 2021, 18(10), 5242; https://doi.org/10.3390/ijerph18105242 - 14 May 2021
Cited by 3 | Viewed by 2403
Abstract
This paper explores the role of basic medical insurance in protecting family investment in child education. First, this paper establishes a two-phase overlapping generation model to theoretically analyse the impact of basic medical insurance on investment in child education under the influence of [...] Read more.
This paper explores the role of basic medical insurance in protecting family investment in child education. First, this paper establishes a two-phase overlapping generation model to theoretically analyse the impact of basic medical insurance on investment in child education under the influence of the impact of parental health. The results show that health shock reduces parental investment in child education, and medical insurance significantly alleviates the negative impact of parental health shock on investment in child education. Furthermore, this paper establishes a two-way fixed effect regression model based on the data of China Family Panel Studies (CFPS) in 2014 and 2016 to empirically test the above results. The results showed that parental health shocks negatively affect investment in child education, and paternal health shock has a more significant impact than maternal health shock. However, medical insurance significantly reduces this negative impact, provides security in investment in child education, and promotes the improvement of human capital. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
26 pages, 6455 KiB  
Article
Impact of Pandemic on European Well-Being: Visualizing Scenarios from the SHARE Database
by Aurea Grané, Irene Albarrán and David E. Merchán
Int. J. Environ. Res. Public Health 2021, 18(9), 4620; https://doi.org/10.3390/ijerph18094620 - 27 Apr 2021
Cited by 10 | Viewed by 3331
Abstract
The objective of this study is to analyse the effect of a pandemic shock on the well-being of the European population aged 50 or over. Data comes from wave 7 of the Survey of Health, Ageing and Retirement in Europe (SHARE), carried out [...] Read more.
The objective of this study is to analyse the effect of a pandemic shock on the well-being of the European population aged 50 or over. Data comes from wave 7 of the Survey of Health, Ageing and Retirement in Europe (SHARE), carried out in 28 countries and representing over 170 million aged individuals in Europe. We start by designing two indicators in order to capture the risk of being unhealthy and economically vulnerable; next, we combine them with socio-demographic information and obtain the vulnerability profiles by means of the k-prototypes clustering algorithm. Subsequently, we design a shock similar to the COVID-19 pandemic and measure its effects on the vulnerability profiles. The results suggest that the average level of economic and health vulnerability is relatively low, although levels differ across European regions, with the most vulnerable being Eastern European countries. It was observed that the shock most affected countries with a greater proportion of individuals initially deemed vulnerable in terms of mental and physical health, as well as countries where tourism and retail sectors are the most vital for their economies. These findings led us to conclude that public policies should be differentiated by European regions, and Governments must establish action plans in order to better meet the physical and mental health needs of their citizens, as well as addressing monetary poverty and financial difficulties. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
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16 pages, 9883 KiB  
Article
Cost-Free LTC Model Incorporated into Private Pension Schemes
by J. Iñaki De La Peña, M. Cristina Fernández-Ramos and Asier Garayeta
Int. J. Environ. Res. Public Health 2021, 18(5), 2268; https://doi.org/10.3390/ijerph18052268 - 25 Feb 2021
Cited by 8 | Viewed by 2893
Abstract
Long-term care coverage is not integrated into an individual’s retirement strategy. It is an additional public health service that is not considered into private pension funds. Nevertheless, this coverage is not sufficient due to the problems of financial sustainability of the public pension [...] Read more.
Long-term care coverage is not integrated into an individual’s retirement strategy. It is an additional public health service that is not considered into private pension funds. Nevertheless, this coverage is not sufficient due to the problems of financial sustainability of the public pension systems. However, there are large sums in pension plans dedicated to paying retirement pensions that can be transformed into support for long-term care coverage. This paper develops a mechanism of pension transformation through the different mortality of the beneficiary when becoming a dependent beneficiary. This mechanism allows the beneficiary to convert their pension to LTC support at their own choice, without increasing the cost of the private pension scheme. The proposed model provides consistency in the pension that a retiree receives and adapts it to a retiree’s life expectancy: the retiree receives a higher pension when he/she needs it most. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
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16 pages, 497 KiB  
Article
Do Different Models Induce Changes in Mortality Indicators? That Is a Key Question for Extending the Lee-Carter Model
by Ana Debón, Steven Haberman, Francisco Montes and Edoardo Otranto
Int. J. Environ. Res. Public Health 2021, 18(4), 2204; https://doi.org/10.3390/ijerph18042204 - 23 Feb 2021
Cited by 2 | Viewed by 3282
Abstract
The parametric model introduced by Lee and Carter in 1992 for modeling mortality rates in the USA was a seminal development in forecasting life expectancies and has been widely used since then. Different extensions of this model, using different hypotheses about the data, [...] Read more.
The parametric model introduced by Lee and Carter in 1992 for modeling mortality rates in the USA was a seminal development in forecasting life expectancies and has been widely used since then. Different extensions of this model, using different hypotheses about the data, constraints on the parameters, and appropriate methods have led to improvements in the model’s fit to historical data and the model’s forecasting of the future. This paper’s main objective is to evaluate if differences between models are reflected in different mortality indicators’ forecasts. To this end, nine sets of indicator predictions were generated by crossing three models and three block-bootstrap samples with each of size fifty. Later the predicted mortality indicators were compared using functional ANOVA. Models and block bootstrap procedures are applied to Spanish mortality data. Results show model, block-bootstrap, and interaction effects for all mortality indicators. Although it was not our main objective, it is essential to point out that the sample effect should not be present since they must be realizations of the same population, and therefore the procedure should lead to samples that do not influence the results. Regarding significant model effect, it follows that, although the addition of terms improves the adjustment of probabilities and translates into an effect on mortality indicators, the model’s predictions must be checked in terms of their probabilities and the mortality indicators of interest. Full article
(This article belongs to the Special Issue Advances in Measuring Health and Wellbeing)
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