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A tremendous number of studies describe results on the evolution of the COVID-19 impact on infected patients, hospital admissions, deaths, mental health and well-being of the population. However, there are hardly any reports on its impact and evolution since the beginning of the pandemic with clinical, contextual and individual perception information. Our work describes the research project called Health Care and Social Survey (ESSOC, Encuesta Sanitaria y SOCial). It arises from the need to provide specific, reliable, early, and timely data on the impact of COVID-19 that can be considered when making decisions to prepare and provide an effective Public Health response in the different affected populations. It is linked to official statistical operations included in the Andalusian Regional Government and has also been granted a favorable opinion by the Research Ethics Committee. The ESSOC is based on a Real-World Data design. It integrates observational data extracted from multiple sources including information based on surveys and clinical, epidemiological, population, and environmental registries. The surveys have an overlapping panel design with a total of over 22,000 effective interviews being carried out over three years from the beginning of the state of alarm in Spain. Their geographical scope is the Autonomous Region of Andalusia (8.4MM people, the fifth most populated region in Europe), and the population scopes are general population, population residing in disadvantaged areas, and population over the age of 55. The conceptual approach of this study encompasses all aspects affecting health that will contribute to an extraordinary increase in the current knowledge of the impact of the COVID-19 pandemic. Its results will be very useful for crossdisciplinary comparisons in population-based studies, and the methodology developed will serve as a model to be applied in other epidemiological studies. Key messages: It is needed to provide specific, reliable, early, and timely data on the impact of COVID-19 that can be considered when making decisions to prepare and provide an effective Public Health response. Our research project integrates observational data extracted from multiple sources including information based on surveys and clinical, epidemiological, population, and environmental registries. [ABSTRACT FROM AUTHOR]

Objectives: Few panel studies have investigated how different types of mental health (MH) and socio-emotional wellbeing (SEW) outcomes have changed during the pandemic and if their burden has been equally distributed at the population-level. We aimed to examine temporal changes in these outcomes and their socio-ecological predictors using panel data., Study Design: Longitudinal population-based survey with overlapping panels., Methods: Analyses were carried out using four measurements of data from the Health and Social Survey (April 2020 to April 2021). Participants included Andalusian (Spanish) residents aged 16 years or older who participated in all four measurements (n = 1223). Seven dichotomous MH and SEW outcomes, as well as several socio-ecological predictors informed by a conceptual model, were examined in descriptive and multivariate analyses., Results: Unadjusted odds of regular/bad perceived mental health (vs. excellent/very good/good), low socio-emotional wellbeing (vs. regular), low happiness (vs. regular), and feeling anxious (vs. not feeling anxious) decreased significantly from the first to the second measurement; however, in the fourth, low socio-emotional wellbeing significantly increased while low optimism decreased. Considering varying coefficients, objectively measured COVID-19 status and self-reported severity levels of the infection were statistically significant. Health status, social support, and household financial difficulty predicted higher adjusted odds in most of the seven assessed outcomes., Conclusions: Significant temporal variations in MH and SEW outcomes, along with their predictors, were observed during the first year of the pandemic. Some of these outcomes worsened as the pandemic progressed, whereas others improved. Findings also suggest that some individuals such as those experiencing poor health, limited social support, and low socioeconomic status are disproportionately impacted., (© 2024. The Author(s).)

Background: Surveys have been used worldwide to provide information on the COVID-19 pandemic impact so as to prepare and deliver an effective Public Health response. Overlapping panel surveys allow longitudinal estimates and more accurate cross-sectional estimates to be obtained thanks to the larger sample size. However, the problem of non-response is particularly aggravated in the case of panel surveys due to population fatigue with repeated surveys., Objective: To develop a new reweighting method for overlapping panel surveys affected by non-response., Methods: We chose the Healthcare and Social Survey which has an overlapping panel survey design with measurements throughout 2020 and 2021, and random samplings stratified by province and degree of urbanization. Each measurement comprises two samples: a longitudinal sample taken from previous measurements and a new sample taken at each measurement., Results: Our reweighting methodological approach is the result of a two-step process: the original sampling design weights are corrected by modelling non-response with respect to the longitudinal sample obtained in a previous measurement using machine learning techniques, followed by calibration using the auxiliary information available at the population level. It is applied to the estimation of totals, proportions, ratios, and differences between measurements, and to gender gaps in the variable of self-perceived general health., Conclusion: The proposed method produces suitable estimators for both cross-sectional and longitudinal samples. For addressing future health crises such as COVID-19, it is therefore necessary to reduce potential coverage and non-response biases in surveys by means of utilizing reweighting techniques as proposed in this study., (© 2024. The Author(s).)

This manuscript describes the rationale and protocol of a real-world data (RWD) study entitled Health Care and Social Survey (ESSOC, Encuesta Sanitaria y Social). The study's objective is to determine the magnitude, characteristics, and evolution of the COVID-19 impact on overall health as well as the socioeconomic, psychosocial, behavioural, occupational, environmental, and clinical determinants of both the general and more vulnerable population. The study integrates observational data collected through a survey using a probabilistic, overlapping panel design, and data from clinical, epidemiological, demographic, and environmental registries. The data will be analysed using advanced statistical, sampling, and machine learning techniques. The study is based on several measurements obtained from three random samples of the Andalusian (Spain) population: general population aged 16 years and over, residents in disadvantaged areas, and people over the age of 55. Given the current characteristics of this pandemic and its future repercussions, this project will generate relevant information on a regular basis, commencing from the beginning of the State of Alarm. It will also establish institutional alliances of great social value, explore and apply powerful and novel methodologies, and produce large, integrated, high-quality and open-access databases. The information described here will be vital for health systems in order to design tailor-made interventions aimed at improving the health care, health, and quality of life of the populations most affected by the COVID-19 pandemic.

Background: industrially contaminated sites (ICSs) have been recognised as a major public health concern since they involve exposure to multiple environmental stressors, normally distributed unevenly within population. The COST Action on Industrially Contaminated Sites and Health Network (ICSHNet) comprises a European network of experts and institutions to clarify needs and priorities for better characterising the impact on environment and health of ICS., Objectives: evaluate the availability of information and studies concerning selected ICSs in participating Countries within the ICSHNet, with particular consideration on the accessibility to environmental, health and demographic data, and research and assessment tools., Methods: to evaluate the availability of data, an Action Questionnaire (AQ) was developed based on previous questionnaires used in different European projects and on expert consultation. The AQ, with 84 items organised in eight sections, was adapted to an on-line version using the software LimeSurvey. The survey was sent to 47 participants within the ICSHNet, to report over a list of 99 ICSs previously identified., Results: information was gathered from 81 sites out of the initially selected 99, reported by 45 participants from 27 Countries (82% of Countries in the ICSHNet). The predominant polluting activities were waste disposal (46%) and chemical industries (37%), affecting all environmental media, but more extensively surface and groundwater (70%) and soil (68%). Main categories of contaminants affecting different media were heavy metals and chlorinated hydrocarbons, but also BTEX (benzene, toluene, ethylbenzene, and xylene) and ambient air pollutants (e.g., particulate matter, SOx). Human health risk assessment was the most prevalent methodological approach for characterising impacts on health (32%), followed by epidemiological studies (26%), and health impact assessment (12%). The low reporting, both referring to data availability or methodologies, could be due to absence of data, or to the fact that the reporting person (many of them from the public health sector) did not know how to reach the environmental information., Conclusions: survey findings suggest that improving the collection and access to specific environmental, health and demographic data related to ICSs is crucial to meet the methodological requirement to better analyse the health impact of ICSs.

Objective: To analyze perceived health status and other health-related indicators in the adult population in Granada (Spain) undergoing an eviction process from their homes, whether rented or owned, in comparison with health indicators in the general adult population in Andalusia., Methods: A cross-sectional survey was administered by trained staff. The survey included instruments from the Andalusian Health Survey 2011 for measuring variables related to physical and mental health, as well as health-related habits. We compared the results with those obtained from the Andalusian general population through the Andalusian Health Survey. A bivariate analysis using the χ2 test and a multivariate logistic regression analysis were conducted., Results: We obtained a total sample of 205 people in the process of eviction. A total of 59.5% (n=122) were women, and 40.5% (n=83) were men. Participants were more likely to have poor health (odds ratio [OR]: 12.63, 95% confidence interval [95%CI]: 8.74-18.27), have cardiovascular diseases (OR: 3.08; 95%CI: 1.54- 6.16), or to smoke (OR: 1.68; 95% CI: 1.21-2.33) compared with the Andalusian general population. Most of the health indicators analyzed showed a worse outcome for women undergoing an eviction process., Conclusions: Our results suggest that, in the current context of economic crisis, people undergoing a process of eviction in Granada and its metropolitan area show poorer health than the Andalusian general population. Further research is needed on health and evictions from different methodological approaches, for a better understanding of the topic., (Copyright © 2015 SESPAS. Published by Elsevier Espana. All rights reserved.)

Introduction and Objectives: Ischemic heart disease is the leading cause of death and one of the top 4 causes of burden of disease worldwide. The aim of this study was to evaluate age-period-cohort effects on mortality from ischemic heart disease in Andalusia (southern Spain) and in each of its 8 provinces during the period 1981-2008., Methods: A population-based ecological study was conducted. In all, 145 539 deaths from ischemic heart disease were analyzed for individuals aged between 30 and 84 years who died in Andalusia in the study period. A nonlinear regression model was estimated for each sex and geographical area using spline functions., Results: There was an upward trend in male and female mortality rate by age from the age of 30 years. The risk of death for men and women showed a downward trend for cohorts born after 1920, decreasing after 1960 with a steep slope among men. Analysis of the period effect showed that male and female death risk first remained steady from 1981 to 1990 and then increased between 1990 and 2000, only to decrease again until 2008., Conclusions: There were similar age-period-cohort effects on mortality in all the provinces of Andalusia and for Andalusia as a whole. If the observed cohort and period effects persist, male and female mortality from ischemic heart disease will continue to decline., (Copyright © 2014 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.)

Background: It has been identified differences of medical care practice in primary care related to physician's sex. Simultaneously, there are gender inequalities in the assignment of health resources. Both aspects give rise to an increasing growing interest in the management and provision of health services., Objectives: To examine the differences in the referral practice made by female and male primary care physicians working in health centers in Andalusia, to consider whether there are disparities in referrals received by men and women, and to examine the interaction between patient's sex and physician's sex., Methods: Observational, cross-sectional, and multicenter study., Population: 4 health districts in Andalucía and their physicians., Sample: 382 physicians., Measurements: referral rate per visit (RV), referral rate per patient quota (RQ), patient's sex, physician: sex, age, postgraduate family medicine specialty, size of the patient quota by sex, mean number of patients/day by sex, mean age of the patient quota by sex, and proportion of men in the quota. Health center: urban / rural, size of the team, enrolled population, and postgraduate family medicine specialty's accreditation., Sources: databases of health districts., Period of Study: 2010., Analysis: Bivariate and multivariate multilevel analysis of the referral rate per visit with mixed Poisson model., Results: In 2010 382 physicians made 129,161 referrals to specialized care. The RQ was 23.47 and the RV was 4.92. The RQ in women and men was 27.23 and 19.78 for women physicians, being 27.37 and 19.51 for male physicians. The RV in women and men was 4.92 and 5.48 for women physicians, being 4.54 and 4.93 for male physicians., Conclusion: There are no differences in referral according to physician's sex. However, there are signs that might indicate the existence of gender inequality, and women patient received less referrals. There are no physician-patient's sex interaction.

Objective: To analyse the impact of using the electronic prescription on pharmaceutical expenditure (PE), and to explore the factors determining its use., Methods: Two multiple regression models were constructed. For these two models, the PE and the percentage of electronic prescription use were taken respectively as dependent variables. Data from nine Primary care centres were included., Results: Each point increase in prescription by active principle (PAP) was associated with an average reduction of 2,079 PE € per year. In contrast, every percentage increase in the use of electronic prescriptions was associated with an annual increase of 1,027 €. In addition, factors like card adjusted for age and type of pharmacy (TAFE) allocated (€ 36.71/year), the burden of care (€ 2,585/year) and frequency of clinic visits (€ 17,148/year), were also associated with increased PE. The other factors associated with an increase in the electronic prescriptions were, lower rurality rates, greater distance from the capital, greater PAP, as well as less clinic visits., Conclusions: Electronic prescription use seems to be a predictor of pharmaceutical expenditure in which every percentage increase relates to an average annual increase of 1,027 Euros. This variable along with the prescription by active principle, and the amount of TAFEs assigned, as well as the burden of care and number of visits, are variables which help to explain more than 65% of the PE variability between physicians. Likewise, the increase in expenditures related to electronic prescriptions seems to occur at the expense of increasing number of prescriptions per patient., (Copyright © 2012 Elsevier España, S.L. All rights reserved.)

Mortality is one of the most widely used indicators in small-area ecologic studies. Both accessibility to mortality data and advances in the development of new disease mapping techniques have contributed to an abundance of mortality maps and atlases over the last decade. Results may be biased in this kind of study if there has been unmeasured geographic mobility of the population. Most published papers tend to neglect this possibility. We use the theory of dynamics systems to demonstrate that migratory flows unmonitored by official population registers may lead to major errors in mortality rates and relative risks. Simulations in 4 scenarios showed more than 8% underestimation of the mortality rate and more than 11% underestimation of relative risk in areas with high uncontrolled emigration, and above 19% overestimation of mortality rate and above 15% overestimation of relative risk in areas with high uncontrolled immigration.Researchers conducting small-area epidemiologic studies should explore the reliability of population information in geographic areas before drawing hypothesis or conclusions on other possible causes of mortality differences.

Until now, mortality atlases have been static. Most of them describe the geographical distribution of mortality using count data aggregated over time and standardized mortality rates. However, this methodology has several limitations. Count data aggregated over time produce a bias in the estimation of death rates. Moreover, this practice difficult the study of temporal changes in geographical distribution of mortality. On the other hand, using standardized mortality hamper to check differences in mortality among groups. The Interactive Mortality Atlas in Andalusia (AIMA) is an alternative to conventional static atlases. It is a dynamic Geographical Information System that allows visualizing in web-site more than 12.000 maps and 338.00 graphics related to the spatio-temporal distribution of the main death causes in Andalusia by age and sex groups from 1981. The objective of this paper is to describe the methods used for AIMA development, to show technical specifications and to present their interactivity. The system is available from the link products in www.demap.es. AIMA is the first interactive GIS that have been developed in Spain with these characteristics. Spatio-temporal Hierarchical Bayesian Models were used for statistical data analysis. The results were integrated into web-site using a PHP environment and a dynamic cartography in Flash. Thematic maps in AIMA demonstrate that the geographical distribution of mortality is dynamic, with differences among year, age and sex groups. The information nowadays provided by AIMA and the future updating will contribute to reflect on the past, the present and the future of population health in Andalusia.

The purpose of this paper is to study the linkage between type of habitat and mortality from all causes in small areas of Southern Spain. An ecological study was conducted on 99,870 people who died between 1985 and 1999. The municipality was taken as the unit of analysis. Data analysis was carried out through hierarchical spatio-temporal bayesian models. Results show a 13.3% reduction in mortality rates among men and 14.1% among women in the most rural areas compared to more urban environments. The study demonstrates the usefulness of socio-demographic indices in small-area geographical analyses.

An ecological design was used to study the relationship between cancer incidence and both socioeconomic and environmental features in Southern Spain. Twenty-four sites and 26,380 cases diagnosed in 1985--1996 were analysed. Generalised Additive Models were used for data analysis. Except for lip cancer, the urban areas showed an increase in cancer risk for all sites. The relative risks among urban and rural municipalities ranges between 1.09 for skin non-melanoma (95% CI: 1.00-1.18) and 1.64 for cervix cancer (95% CI: 1.28-2.12). The relative risk among areas with high and low unemployment was 1.29 for stomach cancer (95% CI: 1.07-1.57), 1.45 for oral cavity cancer (95% CI: 1.10-1.93) and 1.77 for oesophagus cancer (95% CI: 1.02-3.05). Areas with highest unemployment showed the lowest incidence of melanoma. Risk for leukaemia, gall bladder, breast and prostate cancer showed a significant decreases by approximately 28% in the municipalities with the highest illiteracy score. A high percentage of land under cultivation was related to uterine tumours, larynx, rectum, lung, skin non-melanoma and brain cancers. For these sites, the risk had a significant increase by between 23% (skin non-melanoma) and 70% (rectum). Areas with high intensive farming showed a significant increase in cancer risk for lip, oral cavity, larynx, oesophagus, colon, lung, and bladder cancer. The relative risks ranges between 1.16 for colon cancer (95% CI: 1.04-1.29) and 1.47 for oesophagus cancer (95% CI: 1.15-1.87). The results of this study reveal how important socio-economic and environmental factors are for the analysis of cancer incidence in small areas of Southern Spain.