%0 Journal Article %@ 1947-2579 %I JMIR Publications %V 17 %N %P e52380 %T Expansion and Assessment of a Web-Based 24-Hour Dietary Recall Tool, Foodbook24, for Use Among Diverse Populations Living in Ireland: Comparative Analysis %A Bennett,Grace %A Yang,Shuhua %A Bardon,Laura A %A Timon,Claire M %A Gibney,Eileen R %+ UCD Institute of Food and Health, University College Dublin, Science Centre South, Belfield, Dublin, 4, Ireland, 353 17161147, eileen.gibney@ucd.ie %K dietary assessment %K ethnic diets %K dietary records %K web-based tools %K diverse intake %D 2025 %7 7.2.2025 %9 Original Paper %J Online J Public Health Inform %G English %X Background: Currently, the methods used to collect dietary intake data in Ireland are inflexible to the needs of certain populations, who are poorly represented in nutrition and health data as a result. As the Irish population is becoming increasingly diverse, there is an urgent need to understand the habitual food intake and diet quality of multiple population subgroups, including different nationalities and ethnic minorities, in Ireland. Foodbook24 is an existing web-based 24-hour dietary recall tool, which has previously been validated for use within the general Irish adult population. Because of its design, Foodbook24 can facilitate the improved inclusion of dietary intake assessment in Ireland. Objective: We aimed to examine the suitability of expanding the Foodbook24 tool, improving the reliability and accuracy of dietary intake data collected among prominent nationalities in Ireland. Methods: This study consisted of three distinct parts: (1) expansion of Foodbook24, (2) testing its usability (ie, acceptability study), and (3) examining the accuracy (ie, comparison study) of the updated Foodbook24 tool. To expand Foodbook24, national survey data from Brazil and Poland were reviewed and commonly consumed food items were added to the food list. All foods were translated into Polish and Portuguese. The acceptability study used a qualitative approach whereby participants provided a visual record of their habitual diet. The comparison study consisted of one 24-hour dietary recall using Foodbook24 and one interviewer-led recall completed on the same day, repeated again 2 weeks later. Comparison study data were analyzed using Spearman rank correlations, Mann-Whitney U tests, and κ coefficients. Results: The expansion of the Foodbook24 food list resulted in 546 additional foods. The acceptability study reported that 86.5% (302/349) of foods listed by participants were available in the updated food list. From the comparison study, strong and positive correlations across 8 food groups (44% of a total of 18 food groups) and 15 nutrients (58% of a total of 26 nutrients) were identified (r=0.70-0.99). Only intakes of potatoes and potato dishes and nuts, herbs, and seeds significantly differed across methods of assessment, where correlations across these food groups were low (r=0.56 and r=0.47, respectively). The incidence of food omissions varied across samples, with Brazilian participants omitting a higher percentage of foods in self-administered recalls than other samples (6/25, 24% among the Brazilian vs 5/38, 13% among the Irish cohort). Conclusions: The updated food list is representative of most foods consumed by Brazilian, Irish, and Polish adults in Ireland. Dietary intake data reported in Foodbook24 are not largely different from food groups and nutrient intakes reported via traditional methods. This study has demonstrated that Foodbook24 may be appropriate for use in future research investigating the dietary intakes of Brazilian, Irish, and Polish groups in Ireland. %M 39919284 %R 10.2196/52380 %U https://ojphi.jmir.org/2025/1/e52380 %U https://doi.org/10.2196/52380 %U http://www.ncbi.nlm.nih.gov/pubmed/39919284 %0 Journal Article %@ 2561-6722 %I JMIR Publications %V 8 %N %P e67213 %T Body Fat and Obesity Rates, Cardiovascular Fitness, and the Feasibility of a Low-Intensity Non–Weight-Centric Educational Intervention Among Late Adolescents: Quasi-Experimental Study %A Zuair,Areeg %A Alhowaymel,Fahad M %A Jalloun,Rola A %A Alzahrani,Naif S %A Almasoud,Khalid H %A Alharbi,Majdi H %A Alnawwar,Rayan K %A Alluhaibi,Mohammed N %A Alharbi,Rawan S %A Aljohan,Fatima M %A Alhumaidi,Bandar N %A Alahmadi,Mohammad A %K adolescent obesity %K macronutrient education %K cardiovascular fitness %K body composition %K health literacy %K body image %K macronutrient %K educational %K obesity %K weight %K overweight %K fitness %K nutrition %K diet %K patient education %K student %K school %K youth %K adolescent %K teenager %K metabolic %K eating %K physical activity %K exercise %D 2025 %7 24.1.2025 %9 %J JMIR Pediatr Parent %G English %X Background: Obesity rates among Saudi adolescents are increasing, with regional variations highlighting the need for tailored interventions. School-based health programs in Saudi Arabia are limited and often emphasize weight and body size, potentially exacerbating body image dissatisfaction. There is limited knowledge on the feasibility of non–weight-centric educational programs in Saudi Arabia and their effects on health behaviors and body image. Objectives: This study aimed to (1) assess the prevalence of obesity using BMI-for-age z score (BAZ) and fat percentage among Saudi adolescents; (2) evaluate key health behaviors, cardiovascular fitness, and health literacy; and (3) assess the feasibility and impact of a low-intensity, non–weight-centric educational intervention designed to improve knowledge of macronutrients and metabolic diseases, while examining its safety on body image discrepancies. Methods: A quasi-experimental, pre-post trial with a parallel, nonequivalent control group design was conducted among 95 adolescents (58 boys and 37 girls; mean age 16.18, SD 0.53 years) from 2 public high schools in Medina City, Saudi Arabia. Participants were randomly assigned to either the weight-neutral Macronutrient + Non-Communicable Diseases Health Education group or the weight-neutral Macronutrient Health Education group. Anthropometry (BAZ and fat percentage), cardiovascular fitness, physical activity, and eating behaviors were measured at baseline. Independent t tests and χ² tests were conducted to compare group differences, and a 2-way mixed ANOVA was used to evaluate the effect of the intervention on macronutrient knowledge and body image discrepancies. A total of 69 participants completed the postintervention assessments. Results: The prevalence of overweight and obesity based on BAZ was 37.9% (36/95), while 50.5% (48/95) of participants were classified as overfat or obese based on fat percentage. Students with normal weight status were significantly more likely to have had prior exposure to health education related to metabolic diseases than students with higher weight status (P=.02). The intervention significantly improved macronutrient-metabolic knowledge (F1,64=23.452; P<.001), with a large effect size (partial η²=0.268). There was no significant change in students’ body image from pre- to postintervention (P=.70), supporting the safety of these weight-neutral programs. The intervention demonstrated strong feasibility, with a recruitment rate of 82.6% and a retention rate of 72.6%. Conclusions: This study reveals a high prevalence of obesity among Saudi adolescents, particularly when measured using fat percentage. The significant improvement in knowledge and the nonimpact on body image suggest that a non–weight-centric intervention can foster better health outcomes without exacerbating body image dissatisfaction. Region-specific strategies that prioritize metabolic health and macronutrient education over weight-centric messaging should be considered to address both obesity and body image concerns in adolescents. %R 10.2196/67213 %U https://pediatrics.jmir.org/2025/1/e67213 %U https://doi.org/10.2196/67213 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53873 %T Research Trends on Metabolic Syndrome in Digital Health Care Using Topic Modeling: Systematic Search of Abstracts %A Lee,Kiseong %A Chung,Yoongi %A Kim,Ji-Su %+ Department of Nursing, Chung-Ang University, 84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea, Seoul, 06974, Republic of Korea, 82 028205991, jisu80@cau.ac.kr %K metabolic syndrome %K digital health care %K topic modeling %K text network analysis %K research trends %K topic modeling %K prevention %K management %K telemedicine %K wearable %K devices %K apps %K applications %K methodological %K cardiovascular disease %D 2024 %7 12.12.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Metabolic syndrome (MetS) is a prevalent health condition that affects 20%-40% of the global population. Lifestyle modification is essential for the prevention and management of MetS. Digital health care, which incorporates technologies like wearable devices, mobile apps, and telemedicine, is increasingly becoming integral to health care systems. By analyzing existing research trends in the application of digital health care for MetS management, this study identifies gaps in current knowledge and suggests avenues for future research. Objective: This study aimed to identify core keywords, topics, and research trends concerning the use of digital health care in the management of MetS. Methods: A systematic search of abstracts from peer-reviewed papers was conducted across 6 academic databases. Following eligibility screening, 162 abstracts were selected for further analysis. The methodological approach included text preprocessing, text network analysis, and topic modeling using the BERTopic algorithm. Results: Analysis of the 162 selected abstracts yielded a keyword network comprising 1047 nodes and 34,377 edges. The top 5 core keywords were identified as “MetS,” “use,” “patient,” “health,” and “intervention.” We identified 12 unique topics, with topic 1 focusing on the use of telehealth for self-management of diabetes. The diversity of the 12 topics reflected various aspects of digital health care, including telehealth for diabetes management, electronic health records for MetS complications, and wearable devices for monitoring metabolic status. Research trends showed an expanding field of precision medicine driven by the demand for tailored interventions and the significant impact of the COVID-19 pandemic. Conclusions: By analyzing past research trends and extracting data from scholarly databases, this study has provided valuable insights that can guide future investigations in the field of digital health care and MetS management. %M 39666378 %R 10.2196/53873 %U https://www.jmir.org/2024/1/e53873 %U https://doi.org/10.2196/53873 %U http://www.ncbi.nlm.nih.gov/pubmed/39666378 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 13 %N %P e50754 %T Weight and Lifestyle Behavior Changes in Chinese Health Care Workers During the COVID-19 Pandemic: 3-Year Retrospective Survey %A Guo,Xinyue %A Gong,Shaoqing %A Chen,Ying %A Hou,Xiaohui %A Sun,Tong %A Wen,Jianqiang %A Wang,Zhiyao %A He,Jingyang %A Sun,Xuezhu %A Wang,Sufang %A Chen,Zhixin %A Feng,Xue %A Tian,Xiangyang %+ Chinese Center for Health Education, Building 12, District 1, Anhua Xili, outside Andingmen, Beijing, Beijing, China, 1 01064263018, healthtian@163.com %K COVID-19 %K healthcare workers %K lifestyle behavior %K overweight %K obesity %K physical activity %K mental health %K stress %K anxiety,depression %K pandemic %D 2024 %7 10.12.2024 %9 Original Paper %J Interact J Med Res %G English %X Background: Health care workers (HCWs) played a key role in preventing and controlling COVID-19. Higher infection risks and intensive work led to occupational burnout for many HCWs, which may affect their lifestyle behaviors and weight. Objective: This study aimed to assess HCWs’ self-rated health status, overweight and obesity rates, lifestyle behaviors, and psychoemotional changes from 2019 to 2022 across China and to analyze the factors associated with changes from underweight or normal weight in 2019 to overweight or obese in 2022. Methods: In this retrospective study, 100 health care institutions were randomly selected from 5 provinces or regions in China. All HCWs who worked in the institutions for at ≥3 years were invited to complete the electronic questionnaire and participate in the online survey from August 1, 2022, to August 31, 2022. Collected data included changes in lifestyle behaviors (dietary habits, physical activity, sleep quality, smoking, alcohol consumption), psychoemotional conditions (persistent stress or recurrent anxiety or depressed mood), health status, and chronic disease control from December 2019 to August 2022. Height and weight in 2019 and 2022 were retrieved from annual physical examination records. Overweight and obesity were defined as 24.0 kg/m2≤BMI<28.0 kg/m2 (overweight) and BMI≥28.0 kg/m2 (obesity). Chi square tests and ANOVAs were used to assess the associations between groups. Logistic regression models were used to analyze the factors associated with HCWs becoming overweight or obese from 2019 to 2022. Results: The questionnaire was submitted by 23,234 HCWs. Of the underweight or normal weight HCWs in 2019, 12.67% (1486/23,234) became overweight or obese in 2022; this change was associated with the following factors: 34-43 years old (OR 0.843, 95% CI 0.740-0.960), 44-53 years old (OR 0.738, 95% CI 0.635-0.960), and 54-63 years old (OR 0.503, 95% CI 0.368-0.685; reference: 24-33 years old), reduction in or never or rarely engaging in physical activity (OR 1.201, 95% CI 1.055-1.368; reference: increase in physical activity; P=.006), increased appetite (OR 2.043, 95% CI 1.788-2.034; reference: reduction or no change in appetite; P<.001). From 2019 to 2022, 51.29% (11,917/23,234) of the respondents experienced increased persistent stress or recurrent anxiety or depressed mood; 44.38% (10,311/23,234) stayed up late more often. Increased persistent stress or recurrent anxiety or depressed mood was associated with physical activity (OR 0.421, 95% CI 0.398-0.447; P<.001) and appetite (OR 1.601, 95% CI 1.483-1.728; P<.001). Conclusions: The pandemic was associated with overweight and obesity for HCWs due to changes in lifestyle behaviors, especially reduced physical activity and increased appetite related to increased persistent stress or recurrent anxiety or depressed mood caused by excessive workload. An integrated approach is needed to address overweight and obesity and lifestyle changes among HCWs by releasing negative psychoemotional conditions through workload reduction in future stressful events. %M 39657182 %R 10.2196/50754 %U https://www.i-jmr.org/2024/1/e50754 %U https://doi.org/10.2196/50754 %U http://www.ncbi.nlm.nih.gov/pubmed/39657182 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e57799 %T Utility of Anthropometric Indexes for Detecting Metabolic Syndrome in Resource-Limited Regions of Northwestern China: Cross-Sectional Study %A Yang,Danyu %A Ma,Ling %A Cheng,Yin %A Shi,Hongjuan %A Liu,Yining %A Shi,Chao %K metabolic syndrome %K MetS %K anthropometric indexes %K lipid accumulation product %K LAP %K waist-to-height ratio %K WHtR %K anthropometric %K adult %K aging %K NingXia %K China %K cross-sectional study %K population-based survey %K logistic regression %K waist-to-height %K threshold %K diagnosis %K public health %D 2024 %7 29.11.2024 %9 %J JMIR Public Health Surveill %G English %X Background: Anthropometric indexes offer a practical approach to identifying metabolic syndrome (MetS) and its components. However, there is a scarcity of research on anthropometric indexes tailored to predict MetS in populations from resource-limited regions. Objective: This study aimed to examine the association between 8 easy-to-collect anthropometric indexes and MetS, and determine the most appropriate indexes to identify the presence of MetS for adults in resource-limited areas. Methods: A total of 10,520 participants aged 18‐85 years from Ningxia Hui Autonomous Region, China, were included in this cross-sectional study. Participants were recruited through a stratified sampling approach from January 1, 2020, to December 31, 2021. MetS was defined using the International Diabetes Federation (IDF) criteria. Eight anthropometric indexes were examined, including BMI, waist-to-height ratio (WHtR), weight-adjusted waist index (WWI), conicity index, a body shape index (ABSI), lipid accumulation products (LAP), visceral obesity index (VAI), and the triglyceride-glucose (TyG) index. Logistic regression analysis and restricted cubic splines (RCSs) were applied to identify the association between the anthropometric indexes. The receiver operating characteristic curve and the area under the curve (AUC) were analyzed to identify and compare the discriminative power of anthropometric indexes in identifying MetS. The Youden index was used to determine a range of optimal diagnostic thresholds. Logistic regression analysis was applied to identify the association between the anthropometric indexes. Results: A total of 3324 (31.60%) participants were diagnosed with MetS. After adjusting for age, ethnicity, current residence, education level, habitual alcohol consumption, and tobacco use, all the 8 indexes were positively correlated with the risks of MetS (P<.05). LAP presented the highest adjusted odds ratios (adjOR 35.69, 95% CI 34.59‐36.80), followed by WHtR (adjOR 29.27, 95% CI 28.00‐30.55), conicity index (adjOR 11.58, 95% CI 10.95‐12.22), TyG index (adjOR 5.53, 95% CI 5.07‐6.04), BMI (adjOR 3.88, 95% CI 3.71‐4.05), WWI (adjOR 3.23, 95% CI 3.02‐3.46), VAI (adjOR 2.11, 95% CI 2.02‐2.20), and ABSI (adjOR 1.71, 95% CI 1.62‐1.80). Significantly nonlinear associations between the 8 indexes and the risk of MetS (all Pnonlinear<.001) were observed in the RCSs. WHtR was the strongest predictor of MetS for males (AUC 0.91, 95% CI 0.90-0.92; optimal cutoff 0.53). LAP were the strongest predictor of MetS for females (AUC 0.89, 95% CI 0.89-0.90; optimal cutoff 28.67). Statistical differences were present between WHtR and all other 7 anthropometric indexes among males and overall (all P<.05). In females, the AUC values between LAP and BMI, WWI, ABSI, conicity index, VAI, and TyG index were significantly different (P<.001). No statistical difference was observed between LAP and WHtR among females. Conclusions: According to 8 anthropometric and lipid-related indices, it is suggested that WHtR and LAP are the most appropriate indexes for identifying the presence of MetS in resource-limited areas. %R 10.2196/57799 %U https://publichealth.jmir.org/2024/1/e57799 %U https://doi.org/10.2196/57799 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e57803 %T National Trends in the Prevalence of Self-Perceived Overweight Among Adolescents Between 2005 and 2022: Nationwide Representative Study %A Jeong,Jinyoung %A Lee,Seungjun %A Lee,Kyeongmin %A Kim,Seokjun %A Park,Jaeyu %A Son,Yejun %A Lee,Hyeri %A Lee,Hayeon %A Kang,Jiseung %A Rahmati,Masoud %A Pizzol,Damiano %A Smith,Lee %A López Sánchez,Guillermo F %A Dragioti,Elena %A Fond,Guillaume %A Boyer,Laurent %A Woo,Selin %A Rhee,Sang Youl %A Yon,Dong Keon %+ Department of Medicine, Kyung Hee University College of Medicine, 26, Kyungheedae-ro, Seoul, 02447, Republic of Korea, 82 2 6935 2476, yonkkang@gmail.com %K self-perceived overweight %K trend %K prevalence %K South Korea %K adolescent %D 2024 %7 9.10.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Despite several studies on self-evaluation of health and body shape, existing research on the risk factors of self-perceived overweight is insufficient, especially during the COVID-19 pandemic. Objective: This study aims to identify the risk factors affecting self-perceived overweight and examine how the prevalence of self-perceived overweight has changed before and during the COVID-19 pandemic. Specifically, we analyzed the impact of altered lifestyles due to COVID-19 on this phenomenon. Methods: The data used in the study were obtained from middle and high school students who participated in the Korean Youth Risk Behavior Web-based Survey (N=1,189,586). This survey was a 2-stage stratified cluster sampling survey representative of South Korean adolescents. We grouped the survey results by year and estimated the slope in the prevalence of self-perceived overweight before and during the pandemic using weighted linear regression, as well as the prevalence tendencies of self-perceived overweight according to various risk factors. We used prevalence ratios to identify the risk factors for self-perceived overweight. In addition, we conducted comparisons of risk factors in different periods to identify their associations with the COVID-19 pandemic. Results: The prevalence of self-perceived overweight was much higher than BMI-based overweight among 1,189,586 middle and high school participants (grade 7-12) from 2005 to 2022 (female participants: n=577,102, 48.51%). From 2005 to 2019 (prepandemic), the prevalence of self-perceived overweight increased (β=2.80, 95% CI 2.70-2.90), but from 2020 to 2022 (pandemic) it decreased (β=–0.53, 95% CI –0.74 to –0.33). During the pandemic, individuals with higher levels of stress or lower household economic status exhibited a more substantial decrease in the rate of self-perceived overweight. The prevalence of self-perceived overweight tended to be higher among individuals with poor academic performance, lower economic status, poorer subjective health, and a higher stress level. Conclusions: Our nationwide study, conducted over 18 years, indicated that self-perceived overweight decreased during the COVID-19 period while identifying low academic performance and economic status as risk factors. These findings suggest the need for policies and facilities to address serious dieting and body dissatisfaction resulting from self-perceived overweight by developing counseling programs for adolescents with risk factors such as lower school performance and economic status. %M 39382947 %R 10.2196/57803 %U https://publichealth.jmir.org/2024/1/e57803 %U https://doi.org/10.2196/57803 %U http://www.ncbi.nlm.nih.gov/pubmed/39382947 %0 Journal Article %@ 2562-0959 %I JMIR Publications %V 7 %N %P e50143 %T Nutrition, Obesity, and Seborrheic Dermatitis: Systematic Review %A Woolhiser,Emily %A Keime,Noah %A Patel,Arya %A Weber,Isaac %A Adelman,Madeline %A Dellavalle,Robert P %+ Department of Dermatology, University of Minnesota, 420 Delaware St SE, Minneapolis, MN, 55455, United States, 1 7208480500, robert.dellavalle@cuanschutz.edu %K seborrheic dermatitis %K systematic review %K diet %K nutritional supplements %K alcohol %K BMI %K body mass index %K skin %K review methods %K review methodology %K nutrition %K nutritional %K supplement %K supplements %K dermatology %K dermatitis %K skin %K nutrient %K nutrients %K micronutrient %K micronutrients %K vitamin %K vitamins %K mineral %K minerals %K obesity %K obese %K weight %D 2024 %7 5.8.2024 %9 Review %J JMIR Dermatol %G English %X Background: Pathogenesis of seborrheic dermatitis involves lipid secretion by sebaceous glands, Malassezia colonization, and an inflammatory response with skin barrier disruption. Each of these pathways could be modulated by diet, obesity, and nutritional supplements. Current treatment options provide only temporary control of the condition; thus, it is essential to recognize modifiable lifestyle factors that may play a role in determining disease severity. Objective: This study aimed to summarize published evidence on diet, nutritional supplements, alcohol, obesity, and micronutrients in patients with seborrheic dermatitis and to provide useful insights into areas of further research. Methods: A literature search of Scopus, PubMed, and MEDLINE (Ovid interface) for English language papers published between 1993 and 2023 was conducted on April 16, 2023. Case-control studies, cohort studies, and randomized controlled trials with 5 or more subjects conducted on adult participants (>14 years) were included, case reports, case series, and review papers were excluded due to insufficient level of evidence. Results: A total of 13 studies, 8 case-control, 3 cross-sectional, and 2 randomized controlled trials, involving 13,906 patients were included. Seborrheic dermatitis was correlated with significantly increased copper, manganese, iron, calcium, and magnesium concentrations and significantly lower serum zinc and vitamin D and E concentrations. Adherence to the Western diet was associated with a higher risk for seborrheic dermatitis in female patients and an increased consumption of fruit was associated with a lower risk of seborrheic dermatitis in all patients. The prebiotic Triphala improved patient satisfaction and decreased scalp sebum levels over 8 weeks. Most studies find associations between regular alcohol use and seborrheic dermatitis, but the association between BMI and obesity on seborrheic dermatitis severity and prevalence is mixed. Conclusions: This review sheds light on specific promising areas of research that require further study, including the need for interventional studies evaluating serum zinc, vitamin D, and vitamin E supplementation for seborrheic dermatitis. The negative consequences of a Western diet, alcohol use, obesity, and the benefits of fruit consumption are well known; however, to fully understand their specific relationships to seborrheic dermatitis, further cohort or interventional studies are needed. Trial Registration: PROSPERO CRD42023417768; https://tinyurl.com/bdcta893 %M 39102684 %R 10.2196/50143 %U https://derma.jmir.org/2024/1/e50143 %U https://doi.org/10.2196/50143 %U http://www.ncbi.nlm.nih.gov/pubmed/39102684 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 11 %N 1 %P e9805 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2019 %7 ..2019 %9 %J Online J Public Health Inform %G English %X ObjectiveTo discuss the use of electronic health records (EHRs) for estimation of overweight and obesity prevalence in children aged 2 to 19 years and to compare prevalence between the convenience sample obtained from EHRs to prevalence adjusted for potential selection bias.IntroductionAlthough recent data suggests childhood obesity prevalence has stabilized, an estimated 1 in 3 U.S. children are overweight or obese.1 Further, there is variation by racial and ethnic groups, location, age, and poverty2, resulting in a need for local data to support public health planning and evaluation efforts. Current methods for surveillance of childhood weight status rely on self-report from community-based surveys. However, surveys have long time intervals between data collection periods, are expensive, and are not often able to produce precise small-area estimates. EHRs have been increasingly proposed as an alternative or supplement to community surveys. Childhood weight and height is collected as a part of routine care, and leveraging these data from EHRs may provide rapid and locally precise estimates of childhood weight status. A concern for the use of EHRs is the potential for selection bias. EHRs represent only those seeking healthcare and may not generalize to the population. Additionally, the type of clinical visit (e.g., wellness vs. acute) may affect the prevalence estimates and the likelihood of collecting height and weight data in the EHR. Thus, in addition to EHRs being a convenience sample, there may be additional selection biases based on the type of visit and whether height and weight was measured and recorded. The current work sought to quantify the effect of visit type on childhood overweight and obesity prevalence and generate weights to adjust prevalence for potential EHR-related selection bias.MethodsTwo years (2014-2015) of EHR data were obtained from the Indiana Network for Patient Care, a community health information exchange. Data included clinical encounters of patients living in the eight-county metropolitan area of Indianapolis, Indiana. BMI was calculated using recorded height and weight from the most recent encounter. Encounters were screened for valid BMI entries by examining records in the 0-5th and 95-100th percentiles. BMI results were validated using the following procedure: censoring records with one encounter; removing encounters with implausible values (5 < BMI < 100); calculating the mean BMI across remaining encounters; calculating the percent difference from the mean BMI for each encounter; and removing encounters with BMI results greater or less than 10% from the mean BMI. Records which could not be validated were censored and treated as missing height and weight. Using the age- and sex- specific Centers for Disease Control and Prevention growth charts, patients were classified as underweight (0-5th percentiles), normal weight (5-85th percentiles), overweight (85-95th percentiles), and obese (>95th percentile).Wellness visits were identified using the following ICD-9-CM or ICD-10-CM diagnosis codes: V20.2, V70.0, V70.9; and Z00.121, Z00.129, Z00.00, Z00.01. To adjust for potential selection bias, two stabilized inverse probability weights (SIPW) were constructed. First, to account for potential selection bias induced by visit type and, second, to account for potential selection bias due to censoring (i.e., missing height and weight data). The SIPW were generated using logistic regression models to calculate the predicted probabilities for visit type and uncensored observations as a function of the covariates race, ethnicity, age, gender, and insurance. The SIPW weights were specified as depicted below, where W=1 is a wellness visit, L=observed covariates, and C=0 is uncensored for each child, i.[Insert formulas here]The final weight (SWFinal) was applied to the sample to create a pseudo-population in which there is no association between covariates, L and visit type and which has the same distribution of covariates, L, as the censored individuals not included in the pseudo-population, thus making censoring occur at random, given the observed covariates. Under the assumption of exchangeability and no unmeasured or residual confounding, the pseudo-population will no longer have selection bias due to differences in visit type and missing data.ResultsThe sample consisted of 130,626 unique individuals between the ages of 2 and 19 years, of which 92,755 (71%) had at least one recorded height and weight result. Of the 10,184 records screened for BMI results, 5,242 (51%) were validated using measurements from previous encounters. The final sample consisted of 87,804 records with a valid BMI result (67%) and 42,822 records censored due to missing data (33%). Compared to the U.S. Census, the EHR sample over-represented older girls (e.g., 31.2% vs. 41.2% 15-19 year-old girls) and under-represented younger girls (e.g., 34.3% vs. 29.5% for 5-9 year-old girls). Wellness visits were associated with censoring due to missing data; only 3% of censored encounters were wellness visits compared to 33% of uncensored encounters [P(χ21>14437 =< 0.0001)].In the unweighted sample, the overall prevalence of overweight or obesity was 36.5%. The overweight or obesity prevalence was lower among wellness visits (33.9%) than other visits (37.8%; P(χ21>124.2=< 0.0001). Similarly, wellness visits had lower prevalence estimates when stratified by sex, race, age, ethnicity, and insurance (Table 1). After weighting the sample by SWFinal, the overall prevalence of overweight or obesity was 36.2% and the difference between wellness (35.1%) and other visits (36.7%) was attenuated, though statistically significant [P(χ21>22.2 =<0.001). Likewise, the differences between wellness and other visits in the weighted pseudo-population were attenuated when stratified by covariates, compared to unweighted analyses (Table 1). While the SIPW method demonstrated some adjustment for selection bias due to visit type and censoring due to missing data, the adjustment was incomplete, likely as a result of unmeasured and imperfectly measured covariates.ConclusionsWellness visits were associated with lower childhood overweight and obesity prevalence and were more likely to have weight and height measurements recorded in the EHR than other visit types. Adjusting prevalence for EHR-related selection bias using stabilized inverse probability weights may produce more valid estimates but the lack of social determinant data in EHRs results in imperfect adjustment. Future work should integrate individual- or community-level social determinants of health data into the weighting models.References1. Skinner, AC, & Skelton, JA. Prevalence and trends in obesity and severe obesity among children in the United States, 1999-2012. JAMA Pediatr. 2014; 168(6).2. Ogden CL. et al. Differences in Obesity Prevalence by Demographics and Urbanization in US Children and Adolescents, 2013-2016. JAMA. 2018;319(23). %R 10.5210/ojphi.v11i1.9805 %U %U https://doi.org/10.5210/ojphi.v11i1.9805 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 4 %N 1 %P e3936 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2012 %7 ..2012 %9 %J Online J Public Health Inform %G English %X The aim of this study was to examine the association between the local food environment and obesity proportions among 3- to 4-year-old children who were participants in the WIC program in Los Angeles County using spatial analyses techniques. Spatial analysis software, ArcGIS and Geoda, were used to compute the retail food environment index (RFEI) per ZIP code, to check for spatial autocorrelation and to control for permeability of the boundaries. Linear regression and ANOVA were used to examine the impact of the food environment on childhood obesity. Fast-food restaurants represented 30% and convenience stores represented 40% of the sum of food outlets in areas where WIC participants reside. Although there was no statistically significant association between RFEI and 3- to 4-year-old obesity proportions among WIC children, analysis of variance (ANOVA) tests demonstrated statistically significant positive associations between obesity and the number of convenience stores and the number of supermarkets. Our findings suggest that RFEI, as currently constructed, may not be the optimal way to capture the food environment. This study suggests that convenience stores and supermarkets are a likely source of excess calories for children in low-income households. Given the ubiquity of convenience stores in low-income neighborhoods, interventions to improve availability of healthy food in these stores should be part of the many approaches to addressing childhood obesity. This study adds to the literature by examining the validity of the RFEI and by demonstrating the need and illustrating the use of spatial analyses, using GeoDA, in the environment/obesity studies. %M 23569623 %R 10.5210/ojphi.v4i1.3936 %U %U https://doi.org/10.5210/ojphi.v4i1.3936 %U http://www.ncbi.nlm.nih.gov/pubmed/23569623 %0 Journal Article %@ 1947-2579 %I JMIR Publications %V 3 %N 1 %P e3392 %T Roles of Health Literacy in Relation to Social Determinants of Health and Recommendations for Informatics-Based Interventions: Systematic Review %D 2011 %7 ..2011 %9 %J Online J Public Health Inform %G English %X Objectives:Develop a website, the OLC, which supports those people who work on promoting a healthy weight and tackling obesity. Research shows that original networks where sharing of information and peer interaction take place create solutions to current public health challenges.Methods:Considerations that are relevant when building a new information service as well as the technical set up and information needs of users were taken into account prior to building the OLC and during continuous development and maintenance.Results:The OLC provides global news, resources and tools and link out to other networks, websites and organisations providing similar useful information. The OLC also uses social networking tools to highlight new and important information.Discussion:Networks contribute to a stronger community that can respond to emerging challenges in public health. The OLC improves connections of people and services from different backgrounds and organisations. Some challenges exist in the technical set up and also because of other aspects, e.g. public health information and differing information needs.Conclusion:Public health work programmes should include networking opportunities where public policy can be disseminated. The provision of necessary tools and resources can lead to better decision-making, save time and money and lead to improved public health outcomes. %M 23569599 %R 10.5210/ojphi.v3i1.3392 %U %U https://doi.org/10.5210/ojphi.v3i1.3392 %U http://www.ncbi.nlm.nih.gov/pubmed/23569599