Epidemiology, mortality, and health service use of local-level multimorbidity patterns in South Spain.

Multimorbidity -understood as the occurrence of chronic diseases together- represents a major challenge for healthcare systems due to its impact on disability, quality of life, increased use of services and mortality. However, despite the global need to address this health problem, evidence is still needed to advance our understanding of its clinical and social implications. Our study aims to characterise multimorbidity patterns in a dataset of 1,375,068 patients residing in southern Spain. Combining LCA techniques and geographic information, together with service use, mortality, and socioeconomic data, 25 chronicity profiles were identified and subsequently characterised by sex and age. The present study has led us to several findings that take a step forward in this field of knowledge. Specifically, we contribute to the identification of an extensive range of at-risk groups. Moreover, our study reveals that the complexity of multimorbidity patterns escalates at a faster rate and is associated with a poorer prognosis in local areas characterised by lower socioeconomic status. These results emphasize the persistence of social inequalities in multimorbidity, highlighting the need for targeted interventions to mitigate the impact on patients' quality of life, healthcare utilisation, and mortality rates.

Social determinants of multimorbidity patterns: A systematic review.

Social determinants of multimorbidity are poorly understood in clinical practice. This review aims to characterize the different multimorbidity patterns described in the literature while identifying the social and behavioral determinants that may affect their emergence and subsequent evolution. We searched PubMed, Embase, Scopus, Web of Science, Ovid MEDLINE, CINAHL Complete, PsycINFO and Google Scholar. In total, 97 studies were chosen from the 48,044 identified. Cardiometabolic, musculoskeletal, mental, and respiratory patterns were the most prevalent. Cardiometabolic multimorbidity profiles were common among men with low socioeconomic status, while musculoskeletal, mental and complex patterns were found to be more prevalent among women. Alcohol consumption and smoking increased the risk of multimorbidity, especially in men. While the association of multimorbidity with lower socioeconomic status is evident, patterns of mild multimorbidity, mental and respiratory related to middle and high socioeconomic status are also observed. The findings of the present review point to the need for further studies addressing the impact of multimorbidity and its social determinants in population groups where this problem remains invisible (e.g., women, children, adolescents and young adults, ethnic groups, disabled population, older people living alone and/or with few social relations), as well as further work with more heterogeneous samples (i.e., not only focusing on older people) and using more robust methodologies for better classification and subsequent understanding of multimorbidity patterns. Besides, more studies focusing on the social determinants of multimorbidity and its inequalities are urgently needed in low- and middle-income countries, where this problem is currently understudied.

Multimorbidity Patterns and Their Association with Social Determinants, Mental and Physical Health during the COVID-19 Pandemic.

BACKGROUND: The challenge posed by multimorbidity makes it necessary to look at new forms of prevention, a fact that has become heightened in the context of the pandemic. We designed a questionnaire to detect multimorbidity patterns in people over 50 and to associate these patterns with mental and physical health, COVID-19, and possible social inequalities. METHODS: This was an observational study conducted through a telephone interview. The sample size was 1592 individuals with multimorbidity. We use Latent Class Analysis to detect patterns and SF-12 scale to measure mental and physical quality-of-life health. We introduced the two dimensions of health and other social determinants in a multinomial regression model. RESULTS: We obtained a model with five patterns (entropy = 0.727): 'Relative Healthy', 'Cardiometabolic', 'Musculoskeletal', 'Musculoskeletal and Mental', and 'Complex Multimorbidity'. We found some differences in mental and physical health among patterns and COVID-19 diagnoses, and some social determinants were significant in the multinomial regression. CONCLUSIONS: We identified that prevention requires the location of certain inequalities associated with the multimorbidity patterns and how physical and mental health have been affected not only by the patterns but also by COVID-19. These findings may be critical in future interventions by health services and governments.

Social inequalities in multimorbidity patterns in Europe: A multilevel latent class analysis using the European Social Survey (ESS).

Multimorbidity is associated with lower quality of life, greater disability and higher use of health services and is one of the main challenges facing governments in Europe. There is a need to identify and characterize patterns of chronic conditions and analyse their association with social determinants not only from an individual point of view but also from a collective point of view. This paper aims to respond to this knowledge gap by detecting patterns of chronic conditions and their social determinants in 19 European countries from a multilevel perspective. We used data from the ESS round 7. The final sample consisted of 18,933 individuals over 18 years of age, and patterns of multimorbidity from 14 chronic conditions were detected through Multilevel Latent Class Analysis, which also allows detecting similarities between countries. Gender, Age, Housing Location, Income Level and Educational Level were used as individual covariates to determine possible associations with social inequalities. The goodness-of-fit indices derived in a model with six multimorbidity patterns and five countries clusters. The six patterns were "Back, Digestive and Headaches", "Allergies and Respiratory", "Complex Multimorbidity", "Cancer and Cardiovascular", "Musculoskeletal" and "Cardiovascular"; the five clusters could be associated with some geographical areas or welfare states. Patterns showed significant differences in the covariates of interest, with differences in education and income being of particular interest. Some significant differences were found among patterns and the country groupings. Our findings show that chronic diseases tend to appear in a combined and interactive way, and socioeconomic differences in the occurrence of patterns are not only of the individual but also of group importance, emphasising how the welfare states in each country can influence in the health of their inhabitants.

Behavior Change Around an Online Health Awareness Campaign: A Causal Impact Study.

National Eating Disorders Association conducts a NEDAwareness week every year, during which it publishes content on social media and news aimed to raise awareness of eating disorders. Measuring the impact of these actions is vital for maximizing the effectiveness of such interventions. This study is an effort to empirically measure the change in behavior of users who engage with NEDAwareness content, and compare the detected changes between campaigns in two different years. We analyze a total of 35,895 tweets generated during two campaigns of NEDAwareness campaigns in 2019 and 2020. In order to assess the reach of each campaign, we consider the users participating in the campaigns and their number of followers, as well as retweeting engagement. We use the Linguistic Inquiry and Word Count (LIWC) text modeling and causal impact analysis in order to gauge the change in self-expression of users who have interacted with the NEDAwareness content, compared to a baseline group of users. We further enrich our understanding of the users by extracting gender information from their display names. We find that, despite large media corporations (such as MTV and Teen Vogue) participating in the campaign, it is governmental and nonprofit accounts who are among the accounts that attract the most retweets. Whereas the most influential accounts were well-connected in 2019, the 2020 campaign saw little retweeting between such accounts, negatively impacting the reach of the material. Both campaigns engaged women at around 40% and men 17%, supporting previous research showing women to be more likely to share their experiences with eating disorders. Further, women were more likely to mention other health topics within the 15 days of the intervention, including pregnancy and abortion, as well as depression and anxiety, and to discuss the developing COVID pandemic in 2020. Despite the positive message of the campaign, we find that the users who have engaged with this content were more likely to mention the linguistic categories concerning anxiety and risk. Thus, we illustrate the complex, gender-specific effects of NEDAwareness online health intervention campaign on the continued self-expression of its audience and provide actionable insights for potential improvement of such public health efforts.

Assessing the Role of Social Bots During the COVID-19 Pandemic: Infodemic, Disagreement, and Criticism.

BACKGROUND: Social media has changed the way we live and communicate, as well as offering unprecedented opportunities to improve many aspects of our lives, including health promotion and disease prevention. However, there is also a darker side to social media that is not always as evident as its possible benefits. In fact, social media has also opened the door to new social and health risks that are linked to health misinformation. OBJECTIVE: This study aimed to study the role of social media bots during the COVID-19 outbreak. METHODS: The Twitter streaming API was used to collect tweets regarding COVID-19 during the early stages of the outbreak. The Botometer tool was then used to obtain the likelihood of whether each account is a bot or not. Bot classification and topic-modeling techniques were used to interpret the Twitter conversation. Finally, the sentiment associated with the tweets was compared depending on the source of the tweet. RESULTS: Regarding the conversation topics, there were notable differences between the different accounts. The content of nonbot accounts was associated with the evolution of the pandemic, support, and advice. On the other hand, in the case of self-declared bots, the content consisted mainly of news, such as the existence of diagnostic tests, the evolution of the pandemic, and scientific findings. Finally, in the case of bots, the content was mostly political. Above all, there was a general overriding tone of criticism and disagreement. In relation to the sentiment analysis, the main differences were associated with the tone of the conversation. In the case of self-declared bots, this tended to be neutral, whereas the conversation of normal users scored positively. In contrast, bots tended to score negatively. CONCLUSIONS: By classifying the accounts according to their likelihood of being bots and performing topic modeling, we were able to segment the Twitter conversation regarding COVID-19. Bot accounts tended to criticize the measures imposed to curb the pandemic, express disagreement with politicians, or question the veracity of the information shared on social media.

Use and Effectiveness of Social-Media-Delivered Weight Loss Interventions among Teenagers and Young Adults: A Systematic Review.

Obesity is a risk factor that exponentially increases morbidity and mortality in the world. Today, new health strategies are being implemented based on the use of social media but the use and effectiveness for these interventions needs to be assessed. The objective of this systematic review is to assess the impact of social-media-delivered weight loss interventions among teenagers and young adults. We searched PubMed, Scopus, Google Scholar, PsycINFO, and OVID to identify articles that focused on this topic. Fourteen studies were included in the final review. The commitment of the participants was found to be fundamental factor when assessing the impact of social-media-delivered weight loss interventions, but also the social context in which the interventions were carried out. Our study highlights the potential of social media platforms to address weight loss interventions among younger groups. The works evaluated showed the usefulness of social media for the adequate monitoring and control in these groups. Finally, the current variety of study designs in this field highlights the need for greater homogeneity in their methodology and applications, which is a fundamental step before these tools could be considered a suitable tool for overweight management in clinical practice.

Determinants of Infodemics During Disease Outbreaks: A Systematic Review.

Background: The widespread use of social media represents an unprecedented opportunity for health promotion. We have more information and evidence-based health related knowledge, for instance about healthy habits or possible risk behaviors. However, these tools also carry some disadvantages since they also open the door to new social and health risks, in particular during health emergencies. This systematic review aims to study the determinants of infodemics during disease outbreaks, drawing on both quantitative and qualitative methods. Methods: We searched research articles in PubMed, Scopus, Medline, Embase, CINAHL, Sociological abstracts, Cochrane Library, and Web of Science. Additional research works were included by searching bibliographies of electronically retrieved review articles. Results: Finally, 42 studies were included in the review. Five determinants of infodemics were identified: (1) information sources; (2) online communities' structure and consensus; (3) communication channels (i.e., mass media, social media, forums, and websites); (4) messages content (i.e., quality of information, sensationalism, etc.,); and (5) context (e.g., social consensus, health emergencies, public opinion, etc.). Studied selected in this systematic review identified different measures to combat misinformation during outbreaks. Conclusion: The clarity of the health promotion messages has been proven essential to prevent the spread of a particular disease and to avoid potential risks, but it is also fundamental to understand the network structure of social media platforms and the emergency context where misinformation might dynamically evolve. Therefore, in order to prevent future infodemics, special attention will need to be paid both to increase the visibility of evidence-based knowledge generated by health organizations and academia, and to detect the possible sources of mis/disinformation.

Structural determinants of suicide during the global financial crisis in Spain: Integrating explanations to understand a complex public health problem.

INTRODUCTION: Suicide is a complex public health problem in contemporary societies. Macroeconomic downturns derived from the economic crisis have been found to be associated with growing suicide mortality in the United States and in Europe. The present work is aimed to assess the association between the recent economic downturns and suicide patterns using interrupted time series analysis and, particularly, adjusting this relationship by indicators of social cohesion and community values that might provide additional insights on the complex explanation of suicidal trends. METHODS: We combined suicide, social and economic data extracted from the National Statistics Institute (INE), the Eurostat database, and the World Values Survey to assess the association between the socio-economic factors and trends in suicide rates. To study the association between the financial crisis and changes in suicide rates in Spain, we used interrupted time series analysis (ITSA). RESULTS: Our findings confirm that suicides increased after the 2011 recession, but remained moderately constant after the 2008 economic downturn. Suicides particularly increased after the 2011 recession in the 10-14, and 45-64 years old intervals between males and females, and apparently in older groups. However, during the 2008-2011 time period suicide rates decreased during working years (specifically among 40-44, 45-49, and 55-59 years old groups). Our results highlight the importance of social protection against unemployment and, to a lesser extent, social protection in disability and family, in reducing suicides, as well as the economic prosperity of the country. CONCLUSION: This result corroborates that the economic crisis has possibly impacted the growing suicide rates of the most vulnerable groups, but exclusively during the period characterised by economic cuts after the 2011 recession. This study highlights the need to implement tailored policies that protect these collectives against suicide.

Prevalence of Health Misinformation on Social Media: Systematic Review.

BACKGROUND: Although at present there is broad agreement among researchers, health professionals, and policy makers on the need to control and combat health misinformation, the magnitude of this problem is still unknown. Consequently, it is fundamental to discover both the most prevalent health topics and the social media platforms from which these topics are initially framed and subsequently disseminated. OBJECTIVE: This systematic review aimed to identify the main health misinformation topics and their prevalence on different social media platforms, focusing on methodological quality and the diverse solutions that are being implemented to address this public health concern. METHODS: We searched PubMed, MEDLINE, Scopus, and Web of Science for articles published in English before March 2019, with a focus on the study of health misinformation in social media. We defined health misinformation as a health-related claim that is based on anecdotal evidence, false, or misleading owing to the lack of existing scientific knowledge. We included (1) articles that focused on health misinformation in social media, including those in which the authors discussed the consequences or purposes of health misinformation and (2) studies that described empirical findings regarding the measurement of health misinformation on these platforms. RESULTS: A total of 69 studies were identified as eligible, and they covered a wide range of health topics and social media platforms. The topics were articulated around the following six principal categories: vaccines (32%), drugs or smoking (22%), noncommunicable diseases (19%), pandemics (10%), eating disorders (9%), and medical treatments (7%). Studies were mainly based on the following five methodological approaches: social network analysis (28%), evaluating content (26%), evaluating quality (24%), content/text analysis (16%), and sentiment analysis (6%). Health misinformation was most prevalent in studies related to smoking products and drugs such as opioids and marijuana. Posts with misinformation reached 87% in some studies. Health misinformation about vaccines was also very common (43%), with the human papilloma virus vaccine being the most affected. Health misinformation related to diets or pro-eating disorder arguments were moderate in comparison to the aforementioned topics (36%). Studies focused on diseases (ie, noncommunicable diseases and pandemics) also reported moderate misinformation rates (40%), especially in the case of cancer. Finally, the lowest levels of health misinformation were related to medical treatments (30%). CONCLUSIONS: The prevalence of health misinformation was the highest on Twitter and on issues related to smoking products and drugs. However, misinformation on major public health issues, such as vaccines and diseases, was also high. Our study offers a comprehensive characterization of the dominant health misinformation topics and a comprehensive description of their prevalence on different social media platforms, which can guide future studies and help in the development of evidence-based digital policy action plans.

The impact of financial crisis and austerity policies in Andalusia, Spain: disentangling the mechanisms of social inequalities in health through the perceptions and experiences of experts and the general population.

BACKGROUND: Andalusia has been one of the regions most damaged by the economic crisis in Spain. A qualitative study of the effects of the economic crisis and austerity policies in this region has been conducted within the framework of the IMPACT-A project. This research seeks to analyse the perceived impact of the crisis upon the health of the Andalusian population through the first-hand discourses of professionals from the health and social sectors on the one hand, and citizens of different socioeconomic status (SES) on the other. METHODS: A total of five focus groups and ten semi-structured interviews were conducted and analysed following an inductive process based on Grounded Theory (GT). RESULTS: Our results show a general perception among professionals: the financial crisis has either directly or indirectly affected population health in Andalusia, though mostly impacting low-income individuals who were already at risk of social exclusion. Professionals' perceptions have been confirmed through the discourses of citizens of a lower SES, which differ from those of middle and upper SES. CONCLUSION: Findings reveal some of the most salient consequences on the socially vulnerable groups and people at risk of social exclusion. In particular, our study highlights the importance of addressing three areas of priority action: mental health, unmet (basic and medical) needs, and decline in the health system.