Protocol for an observational cohort study on psychological, addictive, lifestyle behavior and highly prevalent affective disorders in primary health care adults.

Background: Depression and anxious symptoms are prevalent in the general population, and their onset and persistence may be linked to biological and psychosocial factors, many of which are lifestyle-related. The way we manage our care, physical and emotional health and/or discomfort is highly influenced by our own abilities, skills and attitudes despite life's circumstances. The main aim of this protocol to analyze the relationship between psychological constructs (self-efficacy, activation, health literacy, resilience, personality traits, sense of coherence, self-esteem), and the presence of affective-emotional problems (anxiety, depression) and addictions in primary health care. Methods: This is a protocol of a prospective longitudinal cohort study including people of 35-74 years old of Aragon primary health care centers (Spain). Three evaluations will be conducted: baseline evaluation, and follow-up assessments five and ten years after recruitment. The primary outcomes will be severity of depression, severity of anxiety, and addictive behaviors. A detailed set of secondary outcomes will be assessed across all three assessments. This will include psychosocial or personal factors on health behavior, social support, lifestyle patterns, quality of life, the use of health and social resources, and chronic comorbid pathology. Discussion: The analysis of the impact of psychological constructs and lifestyles on the mental health of people and communities will provide evidence that will make it possible to better address and prevent these prevalent problems and address their improvement from a more global and holistic perspective. The evaluation of psychological constructs should be incorporated into health services to improve people's ability their self-care, the level of knowledge of managing their disease and their physical, mental and social health. Clinical trial registration: https://www.isrctn.com/, identifier ISRCTN12820058.

The MtZ Strain: Molecular Characteristics and Outbreak Investigation of the Most Successful Mycobacterium tuberculosis Strain in Aragon Using Whole-Genome Sequencing.

Since 2004, a tuberculosis surveillance protocol has been carried out in Aragon, thereby managing to detect all tuberculosis outbreaks that take place in the community. The largest outbreak was caused by a strain named Mycobacterium tuberculosis Zaragoza (MtZ), causing 242 cases as of 2020. The main objective of this work was to analyze this outbreak and the molecular characteristics of this successful strain that could be related to its greater transmission. To do this, we first applied whole-genome sequencing to 57 of the isolates. This revealed two principal transmission clusters and six subclusters arising from them. The MtZ strain belongs to L4.8 and had eight specific single nucleotide polymorphisms (SNPs) in genes considered to be virulence factors [ptpA, mc3D, mc3F, VapB41, pks15 (two SNPs), virS, and VapC50]. Second, a transcriptomic study was carried out to better understand the multiple IS6110 copies present in its genome. This allowed us to observe three effects of IS6110: the disruption of the gene in which the IS6110 is inserted (desA3), the overexpression of a gene (ppe38), and the absence of transcription of genes (cut1:Rv1765c) due to the recombination of two IS6110 copies. Finally, because of the disruption of ppe38 and ppe71 genes by an IS6110, a study of PE_PGRS secretion was carried out, showing that MtZ secretes these factors in higher amounts than the reference strain, thereby differing from the hypervirulent phenotype described for the Beijing strains. In conclusion, MtZ consists of several SNPs in genes related to virulence, pathogenesis, and survival, as well as other genomic polymorphisms, which may be implicated in its success among our population.

Analysis of the impact of social determinants and primary care morbidity on population health outcomes by combining big data: A research protocol.

Background: In recent years, different tools have been developed to facilitate analysis of social determinants of health (SDH) and apply this to health policy. The possibility of generating predictive models of health outcomes which combine a wide range of socioeconomic indicators with health problems is an approach that is receiving increasing attention. Our objectives are twofold: (1) to predict population health outcomes measured as hospital morbidity, taking primary care (PC) morbidity adjusted for SDH as predictors; and (2) to analyze the geographic variability of the impact of SDH-adjusted PC morbidity on hospital morbidity, by combining data sourced from electronic health records and selected operations of the National Statistics Institute (Instituto Nacional de Estadística/INE). Methods: The following will be conducted: a qualitative study to select socio-health indicators using RAND methodology in accordance with SDH frameworks, based on indicators published by the INE in selected operations; and a quantitative study combining two large databases drawn from different Spain's Autonomous Regions (ARs) to enable hospital morbidity to be ascertained, i.e., PC electronic health records and the minimum basic data set (MBDS) for hospital discharges. These will be linked to socioeconomic indicators, previously selected by geographic unit. The outcome variable will be hospital morbidity, and the independent variables will be age, sex, PC morbidity, geographic unit, and socioeconomic indicators. Analysis: To achieve the first objective, predictive models will be used, with a test-and-training technique, fitting multiple logistic regression models. In the analysis of geographic variability, penalized mixed models will be used, with geographic units considered as random effects and independent predictors as fixed effects. Discussion: This study seeks to show the relationship between SDH and population health, and the geographic differences determined by such determinants. The main limitations are posed by the collection of data for healthcare as opposed to research purposes, and the time lag between collection and publication of data, sampling errors and missing data in registries and surveys. The main strength lies in the project's multidisciplinary nature (family medicine, pediatrics, public health, nursing, psychology, engineering, geography).