Health-related Metrics Research Articles

The Health of Those Who Feed Us: An Assessment of Health Inequities Along the United States Food Chain.

While the health of all depends on the food chain, few studies have focused systematically on the health of food chain workers themselves (production, manufacturing, wholesale, retail, and commercial and institutional services). In this study we used 2018 and 2019 data from the Behavioral Risk Factor Surveillance System (BRFSS) to examine health-related metrics of food chain workers, combined and by industry sector, compared to non-food chain workers, among 32 U.S. states. Logistic regression indicated U.S. food chain workers had higher prevalences of barriers to health care access, smoking, no physical exercise, and poor self-reported health than all other workers. Patterns were similar among food chain workers in all industry sectors except wholesale. Additionally, commercial food services workers had higher prevalence of poor mental health, while institutional food services workers had higher prevalences of obesity, diabetes, and hypertension than all other workers. We discuss implications of these results for interventions, with specific attention to improving employment conditions. Food chain worker health is critical for food system sustainability and population health equity.

Evaluating the Perceived Health-Related Effectiveness of 'The Daily Mile' Initiative in Irish Primary Schools.

Many Irish primary school children do not meet recommended physical activity (PA) guidelines. The Daily Mile (TDM) is a primary school initiative designed to increase children's PA output. This study evaluates TDM's perceived effect on Irish primary school children's health-related metrics. A mixed-methods study, comprising two data collection phases, used the RE-AIM framework to evaluate TDM. Phase One involved teachers, principals and classroom assistants (n = 191) from TDM-registered schools completing a questionnaire. Two TDM-registered schools participated in Phase Two, where (i) interviews were conducted with each principal, (ii) a teacher sub-sample (n = 4) participated in a focus group, and (iii) a child sub-sample (n = 14) participated in separate focus groups. TDM was perceived to positively impact the markers of children's health, including their PA behaviour, physical fitness and social well-being. Inclement weather (66.5%) and a lack of time (56.5%) were reported as the top-ranked implementation barriers. Moreover, TDM's repetitive nature often left children feeling disinterested and resulted in some teachers modifying the initiative to maintain engagement levels. Maintaining the long-term implementation of TDM and its health benefits in primary schools may require bespoke amendments to the original format to preserve children's engagement.

“Whispers from the Wrist”: Wearable Health Monitoring Devices and Privacy Regulations in the U.S.: The Loopholes, the Challenges, and the Opportunities

The growth of wearable technology has enabled the collection of even more personalized information on individuals. New health-related devices marketed to consumers collect health information that might not fall under the traditional category of Protected Health Information, and thus, HIPAA protections do not fully apply. Meaning, commercial wearable health devices do not fall under FDA oversight, and data not paired with a doctor–patient relationship do not fall under HIPAA privacy protection; thus, much of the gathered health-related metrics are left without regulation and open to be sold to data brokers. As such, these data can be leveraged by health insurance, law enforcement, and employers, to name a few. This manuscript explores the loopholes in current regulations and suggests a framework that categorizes wearable data and addresses challenges in data transfer. Furthermore, taking a user perspective, the suggested framework offers solutions that aim to guide users and policymakers in navigating privacy issues in wearable technology.

Monitoring and analysis of physical activity and health conditions based on smart wearable devices

The rapid growth of the Internet of Things (IoT) brings sweeping changes in various industries. Healthcare industries have become a prime example where the Internet of Healthcare Things (IoHT) is making significant progress, particularly in how we approach real-time patient care. Traditional systems for monitoring older people and people with special needs are frequently expensive, require a large workforce, and fall short of providing real-time data. This paper introduces the “3-Tier Health Care Architecture,” an integrated approach to mitigating these issues. This architecture capitalizes on IoHT technologies and is constructed around three principal tiers: Sensor, Fog, and Cloud. The Sensor Tier employs Health Metrics Acquisition Units (HMAUs) fitted with an nRF5340 Development Kit, capturing an extensive range of health-related metrics via wearable sensors. These metrics are then relayed to the Local Processing Units (LPUs) in Fog Tier, which operates on Raspberry Pi Zero 2 W microprocessors for the initial data processing before forwarding to the cloud. The Cloud Tier uses a hybrid CNN-LSTM Machine Learning (ML) model to perform Real-Time Healthcare Monitoring (RTHM) status assessments and includes an Early Warning System for immediate alert issuance. The proposed architecture is resilient, scalable, and efficient, serving as a fortified and all-encompassing solution for RTHM. This enables quick medical interventions, thus elevating healthcare quality and potentially life-saving.

Gender Differences in Body Satisfaction Perception: The Role of Nutritional Habits, Psychological Traits, and Physical Activity in a Strength-Training Population.

The objective of this study is to examine gender disparities in body satisfaction perception, emphasizing the influence of nutritional habits, psychometric assessments, levels of physical activity, and health-related metrics. Employing a sample of 605 strength-trained participants (385 males and 224 females), aged between 20 and 35 years, and regularly engaged in strength training, we conducted a thorough analysis using Google Forms. We evaluated variables including age, anthropometric data, resistance training frequency, food consumption patterns, and psychological profiles. Our findings indicate significant gender-based differences in body satisfaction perception. Females tend to overestimate their muscular size and express heightened concern regarding gluteal shape, while males exhibit a more realistic self-perception, primarily focused on hip width. Dietary patterns also display gender-specific tendencies; females prefer healthier options like vegetables, whereas males consume more milk, fermented products, and carbohydrates. Hydration practices diverge as well, with females showing higher water intake in contrast to males' preference for alcoholic and carbonated beverages. Psychologically, males demonstrate greater extroversion, while females exhibit higher conscientiousness, openness, and a tendency toward negative thoughts and anxiety. Regarding physical activity, females engage in training sessions with greater volume compared to males. This study highlights the intricate interplay of social, cultural, and personal factors shaping gender-specific perceptions of body satisfaction and their subsequent impact on health and lifestyle choices. These insights pave the way for future specialized interventions and research, underscoring the importance of understanding gender-specific nuances to promote healthy body satisfaction and self-perception.

RFID Attendance System with Contagious Disease Prevention Module using Internet-of-Things Technology

This paper presents the development and implementation of an innovative Internet of Things (IoT)-based RFID attendance system integrated with a module focused on curbing the spread of contagious diseases in densely populated settings, such as schools and workplaces. Recognizing the limitations of existing radio frequency identification (RFID) attendance systems, an extensive analysis of prior works was conducted to identify crucial functionalities necessary for an effective solution. Leveraging the IoT paradigm, we devised a 3-layer architecture encompassing thermometer sensors, RFID technology, Arduino microcontrollers, Wi-Fi connectivity, and the message queuing telemetry transport (MQTT) protocol to facilitate seamless data transmission and storage. The resulting prototype enables real-time monitoring of feverish symptoms, serving as an early warning system for potential contagious illnesses while streamlining attendance management. Data collected from the IoT devices is securely stored in a centralized database and accessed through an intuitive information system embedded within the IoT application. Users can effortlessly view and manage attendance data, while administrators gain access to health-related metrics, enabling timely responses to health concerns. User evaluations of the developed system resulted in an outstanding “A” rating, validating its reliability, functionality, and user satisfaction. Future improvements involve real-world testing, scalability assurance, integration with health authorities for comprehensive data management, and automated alerts for potential disease outbreaks.

Worldwide impact of COVID-19 on hospital admissions for non-ST-elevation acute coronary syndromes (NSTACS): a systematic review with meta-analysis of 553 038 cases.

How coronavirus disease 2019 (COVID-19) impacted non-ST-segment elevation acute coronary syndromes (NSTACS) is an object of controversial reports. To systematically review studies reporting NSTACS hospitalizations during the COVID-19 pandemic, and analyse whether differences in COVID-19 epidemiology, methodology of report, or public health-related factors could contribute to discrepant findings. Comprehensive search (Medline, Embase, Scopus, Web of Science, Cochrane Register), of studies reporting NSTACS hospitalizations during the COVID-19 pandemic compared with a reference period, following Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. Data were independently extracted by multiple investigators and pooled using a random-effects model. Health-related metrics were from publicly available sources, and analysed through multiple meta-regression modelling. We retrieved 102 articles (553038 NSTACS cases, 40 countries). During peak COVID-19 pandemic, overall incidence rate ratio (IRR) of NSTACS hospitalizations over reference period decreased (0.70, 95% confidence interval (CI) 0.66-0.75; P<0.00001). Significant heterogeneity was detected among studies (I2=98%; P<0.00001). Importantly, wide variations were observed among, and within, countries. No significant differences were observed by study quality, whereas comparing different periods within 2020 resulted in greater decrease (IRR: 0.61; CI: 0.53-0.71) than comparing 2020vs. previous years (IRR: 0.74; CI 0.69-0.79). Among many variables, major predictors of heterogeneity were severe acute respiratory syndrome coronavirus 2 reproduction rate/country, number of hospitals queried, and reference period length; country stringency index and socio-economical indicators did not contribute significantly. During the COVID-19 pandemic, NSTACS hospitalizations decreased significantly worldwide. However, substantial heterogeneity emerged among countries, and within the same country. Factors linked to public health management, but also to methodologies to collect results may have contributed to this heterogeneity. The protocol was registered in the PROSPERO International Prospective Register of Systematic Reviews (ID: CRD42022308159).

The emerging role of wearables in cardiac care

In recent years the consumer wearable technology market has experienced remarkable growth, offering consumers an increasing variety of health-related metrics, which include heart rate and electrocardiogram (ECG) data. This development has prompted significant investigation into the role of these devices in cardiac care, revealing numerous advantages and possibilities for innovation. Specifically, wearables have demonstrated value in diagnosing cardiac conditions, assisting with personalized disease management, improving health outcomes, and providing continual monitoring. Current limitations are related to issues such as inaccessibility and device inaccuracy, both of which are significant concerns, due to their impacts on patient well-being and appropriate health resource utilization. Despite these issues, wearables remain an incredibly promising frontier in cardiac care, capable of driving innovation in multiple aspects of cardiovascular practice. This article aims to provide an overview of the current technology available, its demonstrated benefits and limitations, and its future advancement opportunities.

A Systematic Review of the Implementation and Effectiveness of 'The Daily Mile' on Markers of Children's Health.

Currently, a high percentage of children globally fail to meet the World Health Organisation's (WHO) recommended daily physical activity (PA) guidelines. The Daily Mile (TDM) is a school-based PA initiative, designed to improve primary school children's PA behaviour. The purpose of this review was to evaluate the extant TDM implementation process and identify its impact on health-related metrics. Three databases were used to search for articles from the time TDM originated in 2012 until February 2022. The identification and screening process of articles for their ability to meet this review's eligibility criteria were facilitated by use of PRISMA and Rayyan. Sixteen articles from the initial search (n = 202) were deemed eligible for inclusion. An analysis of these articles identified five common outcome categories that permeated throughout the research articles: (1) cardiorespiratory fitness (CRF); (2) anthropometry and body composition; (3) PA; (4) cognition; and (5) process evaluation. Results presented from the included articles suggests TDM positively impacts markers of a variety of health-related metrics, namely CRF and PA. However, implementation barriers including TDM's repetitive nature, time constraints associated with competing curriculum demands and inadequate facilities regularly necessitate the adaptation and development of the original TDM format by schools and teachers.

Needs and preferences of women with prior severe preeclampsia regarding app-based cardiovascular health promotion

BackgroundWomen with prior severe preeclampsia are at an increased risk for cardiovascular diseases later in life compared to women who had a normotensive pregnancy. The objective of this study was to assess their needs and preferences regarding app-based cardiovascular health promotion.MethodsPatients (n = 35) of the Follow-Up PreEClampsia Outpatient Clinic (FUPEC), Erasmus MC, the Netherlands, participated in an anonymous online survey. The main outcomes under study were women’s needs for health behavior promotion, and their preferences with respect to intervention delivery. Descriptive statistics were used to evaluate needs, and thematic analysis was used to analyze preferences.ResultsWomen’s primary need for health behavior promotion pertained to their fat and sugar intake and physical activity; for some, to their mental health (practices), fruit and vegetable intake, salt intake, and water intake; and for a few, to their alcohol and tobacco use. Most women preferred an app-based intervention to include, in descending order: the tracking of health-related metrics, an interactive platform, the use of behavior change strategies, the provision of information, and personalization.ConclusionCardiovascular health promotion targeting women with prior severe preeclampsia should feel relevant to its audience. App-based interventions are likely to be well received if they target fat and sugar intake and physical activity. These interventions should preferably track health-related metrics, be interactive, contain behavior change strategies, provide information, and be personalized. Adopting these findings during intervention design could potentially increase uptake, behavior change, and behavior change maintenance in this population.

Development of a planning support system to evaluate transit-oriented development masterplan concepts for optimal health outcomes

There is growing consensus that planning professionals need clearer guidance on features of the built environment that promote health benefits. Concomitantly, the smart city movement has created renewed opportunity and interest in data-driven urban modelling to support land use planning. Planning Support Systems (PSS) are spatially enabled computer-based analytical tools incorporating health-related metrics that apply empirical evidence on built environment relationships with health-related outcomes to inform real-world urban design, urban planning and transportation planning decisions. This paper presents the development of the Urban Health Check PSS to use local empirical data to explore and predict relative health impacts associated with proposed urban design planning changes from alternative new station precinct masterplan concepts. We present a case study where we compare a baseline scenario with alternative design concepts for a new train station precinct in Perth, Western Australia, that incorporated possible built environment interventions. Subsequently, we discuss potential future applications of health impact PSS for the translation and application of health evidence into practice.

Risk-Based Evaluation of Improvements in Drinking Water Treatment Using Cost-Benefit Analysis

Reliable and safe drinking water supply requires adequate risk management. Decision support models can aid decisionmakers to effectively evaluate risk mitigation measures and allocate societal resources. Here, a Swedish case study illustrates how the installation of ultrafiltration membranes can be evaluated by combining risk assessment and cost-benefit analysis. Quantitative microbial risk assessment was used to assess several contamination sources and estimate the achieved risk reduction from waterborne pathogens using Campylobacter, Norovirus, and Cryptosporidium as reference pathogens. The societal value of the improved water quality was estimated in the cost-benefit analysis by monetising the gained quality adjusted life years and aesthetic water quality improvements. The calculated net present value (mean of 7 MEUR) indicated that the installation of the ultrafiltration membranes was a sound investment from a societal economic perspective. The ultrafiltration membranes reduced the annual probability of infection from 3 × 10−2 to 10−7, well below the U.S. EPA’s acceptable level, as well as improving the aesthetic quality of the drinking water. The results provide a novel example of the importance for water distributors to consider not only health-related metrics when evaluating treatment options or monitoring the drinking water quality, but to also consider the aesthetic quality of the drinking water.

Semantic Constraints Specification and Schematron-Based Validation for Internet of Medical Things’ Data

Fitness and activity trackers are hugely popular wearable devices that monitor various health-related metrics, such as step count, heartbeat rate, or even oxygen saturation. Utilizing personal health information obtained by users&#x2019; personal trackers provides promising results in the fields of telemedicine and personal well-being. However, we face challenges such as data quality, privacy and compliance with standards and regulations. This paper addresses such challenges, with the focus on the last one. Semantic constraints for healthcare datatypes are defined to ensure compliance with standards, making the information medically valid and relevant. A process of semantic verification and Schematron-based validation is proposed. The validation process suggested in this paper will enable the data to be transferred and incorporated into a formal Electronic Health Record. The process is then verified using datasets containing various health-related data types. The aim is to integrate personal health data into Electronic Health Record, which forms a part of Central Health Information System. This would provide personalized medical services to patients and help physicians to make more informed decisions.

Employment status, unemployment duration, and health-related metrics among US adults of prime working age: Behavioral Risk Factor Surveillance System, 2018-2019.

While unemployment has been associated with poor health, few recent studies in the United States have comprehensively assessed associations between employment status (including duration unemployed) and healthcare access, health-related behaviors, and specific health outcomes. We assessed health-related metrics by employment status in 2018-2019 Behavioral Risk Factor Surveillance System respondents ages 25-54. We calculated the unadjusted prevalence and adjusted prevalence ratios to compare employed workers to respondents who were self-employed, short-term (<12 months) unemployed, long-term unemployed, and unable to work. Adverse health outcomes increased with unemployment duration and were highest for those unable to work. Non-Hispanic Blacks were most likely to be unemployed or unable to work. Short-term unemployment and self-employment were associated with poor healthcare access. Health behaviors and outcomes declined with increasing duration of unemployment and were worst for those unable to work. In the United States, access to affordable healthcare is problematic for both the self-employed and the short-term unemployed. Short-term unemployment is a particularly important locus for intervention and provision of resources to prevent health declines that may hinder re-employment.

Worldwide differences of hospitalization for ST-segment elevation myocardial infarction during COVID-19: A systematic review and meta-analysis

BackgroundDiscrepant data were reported about hospital admissions for ST-segment elevation myocardial infarction (STEMI) during COVID-19 pandemic. We reviewed studies reporting STEMI hospitalizations during COVID-19 pandemic, investigating whether differences in COVID-19 epidemiology or public health-related factors could explain discrepant findings in different countries. MethodsSearch through MedLine, Embase, Scopus, Web-of-Science, Cochrane Register of Controlled Trials, of studies comparing STEMI admissions during COVID-19 pandemic with a reference period, without language restrictions, as registered in PROSPERO International Prospective Register of Systematic Reviews. Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines were followed. Data independently extracted by multiple investigators were pooled using a random-effects model. Health-related metrics were from publicly-available sources. ResultsWe included 79 articles (111,557 STEMI cases, from 57 countries). During peak COVID-19 pandemic, overall incidence rate-ratio (IRR) of STEMI hospitalizations over reference period decreased (0.80; 95% CI 0.76–0.84; p < 0.05). Although wide variations and significant heterogeneity were detected among studies (I2 = 89%; p < 0.0001), no significant differences were observed by report methodology (survey vs registry), or observation/reference period. However, large differences emerged at country level not explained by COVID-related epidemiological data, nor by public health strategies. Instead, IRRs for STEMI admissions were inversely related to hospital bed availability in each country (p < 0.05). ConclusionsDuring COVID-19 pandemic hospitalization for STEMI significantly decreased, although to a smaller extent than initially reported. Large variability emerged across countries, unrelated to COVID-related epidemiology or social containment measures. Disparities in healthcare organization likely contributed, indicating that proper organization of emergency medicine should be preserved during pandemics.

COVID-19 in WHO African Region: Account and Correlation of Epidemiological Indices with Some Selected Health-related Metrics.

The coronavirus disease 2019 (COVID-19) is a highly contagious and pathogenic viral disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Since it was first reported in Wuhan, China, it has spread across the continents. The study is aimed at describing epidemiological indices of COVID-19 as reported by the World Health Organization and to examine correlations with some country specific measures of general health status. Data from the WHO African region were extracted from World Health Organization, Global Health Security Index, Worldometer and World Bank databases, as at September 8, 2020. Other epidemiological indices were computed for the various countries. Epidemiological indices of COVID-19 were correlated with some selected health related metrics: Global Health Security index (GHSI) and current health expenditure (CHE). Pearson correlation was used to access the relationship between the health-related metrics and epidemiological indices. Forty-seven (47) countries belonging to the WHO African region were evaluated. A total of 1,086,499 confirmed cases and 23,213 deaths were recorded giving a fatality rate of 2.1%. South Africa recorded the highest cumulative confirmed cases as well as deaths (Cases: 639,362; Deaths: 15,004) while Seychelles (Cases:135) and Eritrea/Seychelles (Deaths:0) had the least cumulative cases and deaths (135;0 and 330;0), respectively. South Africa recorded the highest attack rate (1127.67/100,000) while Republic of Tanzania recorded the least attack rate (0.78/100,000). The highest case fatality rate/ratio was observed in Chad (7.60%) while the least value was observed in Seychelles (0.0%). France was the most common country involved in travel history of index cases. Sporadic transmission was recorded in 3 countries, 9 countries had cluster of cases while the rest had community transmission. The first WHO African region country to record COVID-19 case was Algeria, while Comoros was the last. Significant positive correlation was found between COVID-19 case number/deaths and Global Health Security Index. The WHO African region has had its own share of the pandemic with all the countries being affected. The trio of cluster cases, sporadic and community transmission were recorded with majority being community transmission.

Exploring the potential for planning support systems to bridge the research-translation gap between public health and urban planning

BackgroundThere is consensus that planning professionals need clearer guidance on the features that are likely to produce optimal community-wide health benefits. However, much of this evidence resides in academic literature and not in tools accessible to the diverse group of professionals shaping our cities. Incorporating health-related metrics into the planning support systems (PSS) provides an opportunity to apply empirical evidence on built environment relationships with health-related outcomes to inform real-world land use and transportation planning decisions. This paper explores the role of planning support systems (PSS) to facilitate the translation and application of health evidence into urban planning and design practices to create healthy, liveable communities.MethodsA review of PSS software and a literature review of studies featuring a PSS modelling built environmental features and health impact assessment for designing and creating healthy urban areas was undertaken. Customising existing software, a health impact PSS (the Urban Health Check) was then piloted with a real-world planning application to evaluate the usefulness and benefits of a health impact PSS for demonstrating and communicating potential health impacts of design scenarios in planning practice.ResultsEleven PSS software applications were identified, of which three were identified as having the capability to undertake health impact analyses. Three studies met the inclusion criteria of presenting a planning support system customised to support health impact assessment with health impacts modelled or estimated due to changes to the built environment. Evaluation results indicated the Urban Health Check PSS helped in four key areas: visualisation of how the neighbourhood would change in response to a proposed plan; understanding how a plan could benefit the community; Communicate and improve understanding health of planning and design decisions that positively impact health outcomes.ConclusionsThe use of health-impact PSS have the potential to be transformative for the translation and application of health evidence into planning policy and practice, providing those responsible for the policy and practice of designing and creating our communities with access to quantifiable, evidence-based information about how their decisions might impact community health.

The temporal nature of social context: Insights from the daily lives of patients with HIV

BackgroundPatients’ life contexts are increasingly recognized as important, as evidenced by growing attention to the Social Determinants of Health (SDoH). This attention may be particularly valuable for patients with complex needs, like those with HIV, who are more likely to experience age-related comorbidities, mental health or substance use issues. Understanding patient perceptions of their life context can advance SDoH approaches.ObjectivesWe sought to understand how aging patients with HIV think about their life context and explored if and how their reported context was documented in their electronic medical records (EMRs).DesignWe combined life story interviews and EMR data to understand the health-related daily life experiences of patients with HIV. Patients over 50 were recruited from two US Department of Veterans Affairs HIV clinics. Narrative analysis was used to organize data by life events and health-related metrics.Key resultsEMRs of 15 participants documented an average of 19 diagnoses and 10 medications but generally failed to include social contexts salient to patients. In interviews, HIV was discussed primarily in response to direct interviewer questions. Instead, participants raised past trauma, current social engagement, and concern about future health with varying salience. This led us to organize the narratives temporally according to past-, present-, or future-orientation. “Past-focused” narratives dwelled on unresolved experiences with social institutions like the school system, military or marriage. “Present-focused” narratives emphasized daily life challenges, like social isolation. “Future-focused” narratives were dominated by concerns that aging would limit activities.ConclusionsA temporally informed understanding of patients’ life circumstances that are the foundation of their individualized SDoH could better focus care plans by addressing contextual concerns salient to patients. Trust-building may be a critical first step in caring for past-focused patients. Present-focused patients may benefit from support groups. Future-focused patients may desire discussing long term care options.

Can We Use Consumer-Wearable Activity Tracker Fitbit in Parkinson Disease?

Consumer-wearable activity trackers have been used for monitoring health-related metrics to estimate steps, distance, physical activity, energy expenditure, and sleep. The purpose of this mini review was to summarize the evidence for validity of the most popular wrist-worn activity tracker (Fitbit) to estimate those health-related metrics in Parkinson disease. We researched full-length English studies in PubMed, Science Direct, Google Scholar, and Scopus, through September, 2021. In total, 27 studies and a textbook description were included in the review. To adapt consumer-wearable activity trackers for evaluating health-related metrics in Parkinson’s disease (PD) patients, there may be some points to be elucidated and conquered. First, measurement accuracy and precision are required. Second, inter-device reliability for measuring steps, distance, and energy expenditure must be considered. Third, wearability: there are some types of device such as wrist-worn, ankle-worn, belt-fixed, and so on. Overall, Fitbit has advantage for these points. This mini review indicates that Fitbit has enough measurement accuracy and precision to estimate health-related metrics of PD patients including amount of step, physical activity energy expenditure, and quality of sleep.

Building a sanitary vulnerability map from open source data in Argentina (2010-2018)

BackgroundDesigning public health policies to target the needs of specific places requires highly granular data. When geographic health statistics from official sources are absent or lacking in spatial detail, Sanitary Vulnerability metrics derived from Census and other georeferenced public data can be used to identify areas in particular need of attention. With that aim, a Vulnerability Map was developed, identifying areas with a substantial deficit in its population health coverage. As a result a novel methodology for measuring Sanitary Vulnerability is presented, that can potentially be applied to different time periods or geographies.MethodsCensus, official listings of public health facilities and crowdsourced georeferenced data are used. The Vulnerability Index is built using dimensionality reduction techniques such as Autoencoders and Non-parametric PCA.Main resultsThe high resolution map shows the geographical distribution of a Sanitary Vulnerability Index, produced using official and crowdsourced open data sources, overcoming the lack of official sources on health indicators at the local level.ConclusionsThe Sanitary Vulnerability Map’s value as a tool for place specific policymaking was validated by using it to predict local health related metrics such as health coverage. Further lines of work contemplate using the Map to study the interaction between Sanitary Vulnerability and the prevalence of different diseases, and also applying its methodology in the context of other public services such as education, security, housing, etc.