Context: Community-level data are necessary to inform community health assessments and to plan for appropriate interventions. However, data derived from public health surveys may be limited or unavailable in rural locations.
Objective: We compared 2 sources of data for community health assessment in rural Colorado, electronic health records (EHRs) and routine public health surveys.
Design: Comparison of cross-sectional measures of childhood/youth obesity prevalence and data quality.
Setting: Two rural Colorado counties, La Plata and Prowers.
Participants: The EHR cohort comprised patients 2 to 19 years of age who underwent a visit with the largest health care provider in each county. These data included sex, age, weight, height, race, ethnicity, and insurance status. Public health survey data were obtained from 2 surveys, the Colorado Child Health Survey (2-14 years of age) and the Healthy Kids Colorado Survey (15-19 years of age) and included caregiver and self-reported height and weight estimates.
Main Outcome Measures: We calculated body mass index percentile for each patient and survey respondent and determined overweight/obesity prevalence by county. We evaluated data source quality indicators according to a rubric developed for this analysis.
Results: The EHR sample captured approximately 35% (n = 3965) and 70% (n = 2219) of all children living in La Plata and Prowers Counties, respectively. The EHR prevalence estimates of overweight/obesity were greater in precision than survey data in both counties among children 2 to 14 years of age. In addition, the EHR data were more timely and geographically representative than survey data and provided directly measured height and weight. Conversely, survey data were easier to access and more demographically representative of the overall population.
Conclusions: Electronic health records describing the prevalence of obesity among children/youth living in rural Colorado may complement public health survey data for community health assessment and health improvement planning.
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http://dx.doi.org/10.1097/PHH.0000000000000589 | DOI Listing |
J Glob Health
December 2024
Hunan Key Laboratory of Molecular Epidemiology, School of Medicine, Hunan Normal University, Changsha, Hu Nan, China.
Background: Since 2019, China has implemented Public Health and Social Measures (PHSMs) to manage the coronavirus disease 2019 (COVID-19) outbreak. As the threat from SARS-CoV-2 diminished, these measures were relaxed, leading to increased respiratory infections and strained health care resources by mid-2023.
Methods: The study utilised WHO's FluNet and Oxford's COVID-19 Government Response Tracker to assess how policy shifts have affected influenza.
J Stud Alcohol Drugs
December 2024
Center for Alcohol and Addiction Studies, Brown University School of Public Health, Providence, RI.
Objective: Despite an abundance of public discourse about the opioid crisis in the media, there is little research characterizing opioid-related content on TikTok, a popular video-based social media platform. This study sought to examine how opioids are portrayed on TikTok.
Methods: This study used mixed-methods to analyze top opioid-related posts marked with the hashtag "#opioids" collected in May 2023.
J Interpers Violence
December 2024
School of Mental Health, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Intimate partner violence (IPV) is a significant public health issue affecting many women worldwide. While extensive research exists on IPV during pregnancy and postpartum, there is limited information on IPV against mothers during the critical child-rearing stage, specifically the first three years following childbirth. This study examines the prevalence and patterns of IPV among mothers in China during this stage, identifying associated factors across four family subsystems: individual, husband-and-wife, mother-child, and family context, to guide the development of tailored prevention strategies.
View Article and Find Full Text PDFJMIR Ment Health
December 2024
Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, Netherlands.
Background: The FAIR (Findable, Accessible, Interoperable, Reusable) data principles are a guideline to improve the reusability of data. However, properly implementing these principles is challenging due to a wide range of barriers.
Objectives: To further the field of FAIR data, this study aimed to systematically identify barriers regarding implementing the FAIR principles in the area of child and adolescent mental health research, define the most challenging barriers, and provide recommendations for these barriers.
JMIR Hum Factors
December 2024
Institute of Medical Sociology and Rehabilitation Science, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Charitéplatz 1, Berlin, 10117, Germany, 49 30-450576364.
Background: Dementia management presents a significant challenge for individuals affected by dementia, as well as their families, caregivers, and health care providers. Digital applications may support those living with dementia; however only a few dementia-friendly applications exist.
Objective: This paper emphasizes the necessity of considering multiple perspectives to ensure the high-quality development of supportive health care applications.
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