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Conderino S, Anthopolos R, Albrecht SS, Farley SM, Divers J, Titus AR, Thorpe LE. Addressing Information Biases Within Electronic Health Record Data to Improve the Examination of Epidemiologic Associations With Diabetes Prevalence Among Young Adults: Cross-Sectional Study. JMIR Med Inform 2024; 12:e58085. [PMID: 39353204 DOI: 10.2196/58085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 07/10/2024] [Accepted: 07/10/2024] [Indexed: 10/04/2024] Open
Abstract
Background Electronic health records (EHRs) are increasingly used for epidemiologic research to advance public health practice. However, key variables are susceptible to missing data or misclassification within EHRs, including demographic information or disease status, which could affect the estimation of disease prevalence or risk factor associations. Objective In this paper, we applied methods from the literature on missing data and causal inference to assess whether we could mitigate information biases when estimating measures of association between potential risk factors and diabetes among a patient population of New York City young adults. Methods We estimated the odds ratio (OR) for diabetes by race or ethnicity and asthma status using EHR data from NYU Langone Health. Methods from the missing data and causal inference literature were then applied to assess the ability to control for misclassification of health outcomes in the EHR data. We compared EHR-based associations with associations observed from 2 national health surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health and Nutrition Examination Survey, representing traditional public health surveillance systems. Results Observed EHR-based associations between race or ethnicity and diabetes were comparable to health survey-based estimates, but the association between asthma and diabetes was significantly overestimated (OREHR 3.01, 95% CI 2.86-3.18 vs ORBRFSS 1.23, 95% CI 1.09-1.40). Missing data and causal inference methods reduced information biases in these estimates, yielding relative differences from traditional estimates below 50% (ORMissingData 1.79, 95% CI 1.67-1.92 and ORCausal 1.42, 95% CI 1.34-1.51). Conclusions Findings suggest that without bias adjustment, EHR analyses may yield biased measures of association, driven in part by subgroup differences in health care use. However, applying missing data or causal inference frameworks can help control for and, importantly, characterize residual information biases in these estimates.
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Affiliation(s)
- Sarah Conderino
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Rebecca Anthopolos
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Sandra S Albrecht
- Department of Epidemiology, Mailman School of Public Health at Columbia University, New York, NY, United States
| | | | - Jasmin Divers
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
- Department of Foundations of Medicine, New York University Long Island School of Medicine, Mineola, NY, United States
| | - Andrea R Titus
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
| | - Lorna E Thorpe
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States
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Choi JY, Choi D, Mehta NK, Ali MK, Patel SA. Diabetes Disparities in the United States: Trends by Educational Attainment from 2001 to 2020. Am J Prev Med 2024; 67:319-327. [PMID: 38615980 PMCID: PMC11338700 DOI: 10.1016/j.amepre.2024.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 04/06/2024] [Accepted: 04/07/2024] [Indexed: 04/16/2024]
Abstract
INTRODUCTION Tracking changes in socioeconomic disparities in diabetes in the U.S. is important to evaluate progress in health equity and guide prevention efforts. Disparities in diabetes prevalence by educational attainment from 2001 to 2020 were investigated. METHODS Using a serial cross-sectional design, data from 33,220 adults aged 30-79 assessed in nine rounds of the National Health and Nutrition Examination Surveys between 2001 and 2020 were analyzed in 2023-2024. Diabetes was defined as self-reported prior diagnosis, elevated glycated hemoglobin (HbA1c≥6.5%), or use of diabetes medications. Marginalized age- and covariate-adjusted prevalence differences (PD) and prevalence ratios (PR) of diabetes by educational attainment (less than high school graduation, high school graduation, some college education or associate degree, or college graduation [reference]) by calendar period (2001-2004, 2005-2008, 2009-2012, 2013-2016, 2017-2020) were derived from logistic regression models. RESULTS From 2001 to 2020, age-adjusted diabetes prevalence was consistently higher among adults without a college degree. Adults without a high school diploma exhibited the largest disparities in both 2001-2004 (PD 8.0%; 95%CI 5.6-10.5 and PR 2.1; 95%CI 1.5-2.6) and 2017-20 (PD 11.0%; 95%CI 6.7-15.2 and PR 2.1; 95%CI 1.5-2.7). Between 2001-2004 and 2017-2020, the absolute disparity in diabetes changed only among adults with a high school diploma (increase from PD 1.7%; 95%CI -0.5- 3.9 to PD 8.8% 95%CI 4.1-13.4, respectively), while the PR did not change in any group. Education-related disparities in diabetes were attenuated after accounting for socio-demographic factors and BMI. CONCLUSIONS From 2001 to 2020, national education-related disparities in diabetes prevalence have shown no signs of narrowing.
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Affiliation(s)
- Ji Young Choi
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Daesung Choi
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Neil K Mehta
- Department of Preventive Medicine and Population Health, University of Texas Medical Branch, Galveston, Texas
| | - Mohammed K Ali
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia; Department of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, Georgia
| | - Shivani A Patel
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia.
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Mold JW, Lawler FH, Liao X, Bard DE. Associations between hearing loss, peripheral neuropathy, balance, and survival in older primary care patients. J Am Geriatr Soc 2024. [PMID: 39143038 DOI: 10.1111/jgs.19142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 07/05/2024] [Accepted: 07/12/2024] [Indexed: 08/16/2024]
Abstract
BACKGROUND Both age-associated hearing loss (AAHL) and peripheral neuropathy (PN) are common in older patients, and both are associated with impaired balance, falls, and premature mortality. The objectives of this study were to document the prevalence and severity of AAHL in older primary care patients, and to explore associations between AAHL, PN, balance, falls, and mortality. METHODS We analyzed information obtained in 1999 from 793 primary care patients recruited from practices participating in the Oklahoma Longitudinal Assessment of the Health Outcomes of Mature Adults (OKLAHOMA) Studies. Available data included demographic and health information, history of falls and hospitalizations, audiometry, balance testing, examination of the peripheral nerves, 50 foot timed gait, and dates of death up to 22 calendar years and 8106 person-years of follow-up. Proportionate hazards (PH) and structural equation modeling (SEM) were used to examine associations between AAHL, PN, balance, gait time, and mortality. RESULTS 501 of the 793 participants (63%) had AAHL. Another 156 (20%) had low frequency and 32 (4%) had unilateral deficits. Those with moderate or severe AAHL and the 255 (32%) with PN had impaired balance (p < 0.0001), increased gait time (p = 0.0001), and reduced survival time (p < 0.0001). In the PH model, both AAHL and PN were associated with earlier mortality (H.Rs. [95% C.I.]: 1.36 [1.13-1.64] and 1.32 [1.10-1.59] respectively). The combination of moderate or severe AAHL and PN, present in 24% of participants, predicted earlier mortality than predicted by either deficit alone (O.R. [95% C.I.I] 1.55 [1.25-1.92]). In the SEM models, the impacts of both moderate or severe AAHL and PN on survival were mediated, in part, through loss of balance. CONCLUSIONS Hearing loss and PN, both common in older patients, appear to be independently and additively associated with premature mortality. Those associations may be mediated in part by impaired balance. The Mechanisms are likely multiple and complex.
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Affiliation(s)
- James W Mold
- Department of Family and Preventive Medicine, University of Oklahoma Health Sciences Center, Chapel Hill, North Carolina, USA
| | - Frank H Lawler
- Department of Family and Preventive Medicine, University of Oklahoma Health Sciences Center, Chapel Hill, North Carolina, USA
| | - Xiaolan Liao
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Chapel Hill, North Carolina, USA
| | - David E Bard
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Chapel Hill, North Carolina, USA
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Rein DB, Wittenborn JS. Prevalence of Diabetic Retinopathy in Health Care Settings-An Early Warning Sign? JAMA Ophthalmol 2024; 142:607-608. [PMID: 38869868 DOI: 10.1001/jamaophthalmol.2024.2124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2024]
Affiliation(s)
- David B Rein
- NORC at the University of Chicago, Chicago, Illinois
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Lawler T, Walts ZL, Giurini L, Steinwandel M, Lipworth L, Murff HJ, Zheng W, Warren Andersen S. Metformin's role in lowering colorectal cancer risk among individuals with diabetes from the Southern Community Cohort Study. Cancer Epidemiol 2024; 90:102566. [PMID: 38518387 PMCID: PMC11108092 DOI: 10.1016/j.canep.2024.102566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 02/28/2024] [Accepted: 03/16/2024] [Indexed: 03/24/2024]
Abstract
BACKGROUND Metformin, utilized to manage hyperglycemia, has been linked to a reduced risk of colorectal cancer (CRC) among individuals with diabetes. However, evidence is lacking for non-Hispanic Black individuals and those with lower socioeconomic status (SES), who face elevated risk for both diabetes and CRC. In this study, we investigated the association between metformin use and incident CRC risk within the Southern Community Cohort Study (SCCS), a racially- and SES-diverse prospective cohort. METHODS Participants reported their diabetes diagnosis and medications, including metformin, upon enrollment (2002-2009) and during follow-up surveys approximately every five years. Incident cases of CRC were identified through state cancer registries and the National Death Index. Proportional hazards models were employed to explore the relationship between metformin use and CRC risk, adjusted for cancer risk factors. RESULTS A total of 25,992 participants with diabetes were included in the analysis, among whom 10,095 were taking metformin. Of these participants, 76% identified as non-Hispanic Black, and 60% reported household incomes <$15,000/year. Metformin use was associated with a significantly lower CRC risk (HR [95% CI]: 0.71 [0.55-0.93]), with consistent results for both colon (0.80 [0.59-1.07]) and rectal cancers (0.49 [0.28-0.86]). The protective association appeared to be stronger among non-Hispanic White individuals (0.51 [0.31-0.85]) compared to non-Hispanic Black participants (0.80 [0.59-1.08], p-interaction =.13). Additionally, a protective association was observed among obese individuals (BMI ≥30 kg/m2, 0.59 [0.43-0.82] but not among non-obese participants (0.99 [0.65-1.51], p-interaction =.05) CONCLUSION: Our findings indicate that metformin use is associated with a reduced risk of CRC in individuals with diabetes, including among those from predominantly low SES backgrounds. These results support previous epidemiological findings, and demonstrate that the protective association for metformin in relation to incident CRC likely generalizes to populations with higher underlying risk.
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Affiliation(s)
- Thomas Lawler
- University of Wisconsin Carbone Cancer Center, Madison, WI 53726, USA
| | - Zoe L Walts
- University of Wisconsin Carbone Cancer Center, Madison, WI 53726, USA; Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, 610 Walnut St, WARF Office Building, Madison, WI 53726, USA
| | - Lauren Giurini
- University of Wisconsin Carbone Cancer Center, Madison, WI 53726, USA; Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, 610 Walnut St, WARF Office Building, Madison, WI 53726, USA
| | - Mark Steinwandel
- International Epidemiology Field Station, Vanderbilt Institute for Clinical and Translational Research, 1455 Research Blvd.; Suite 550, Rockville, MD 20850, USA
| | - Loren Lipworth
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, 8th floor, Suite 800, Nashville, TN 37203-1738, USA
| | - Harvey J Murff
- Department of Medicine, Vanderbilt University School of Medicine, 6012 Medical Center East, 1215 21st Avenue South, Nashville, TN 37203-1738, USA
| | - Wei Zheng
- International Epidemiology Field Station, Vanderbilt Institute for Clinical and Translational Research, 1455 Research Blvd.; Suite 550, Rockville, MD 20850, USA
| | - Shaneda Warren Andersen
- University of Wisconsin Carbone Cancer Center, Madison, WI 53726, USA; Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, 610 Walnut St, WARF Office Building, Madison, WI 53726, USA; International Epidemiology Field Station, Vanderbilt Institute for Clinical and Translational Research, 1455 Research Blvd.; Suite 550, Rockville, MD 20850, USA.
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Li J, Zhang J, Somers VK, Covassin N, Zhang L, Xu H. Trends and Disparities in Treatment and Control of Atherosclerotic Cardiovascular Disease in US Adults, 1999 to 2018. J Am Heart Assoc 2024; 13:e032527. [PMID: 38639366 PMCID: PMC11179884 DOI: 10.1161/jaha.123.032527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 03/27/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Although cardiovascular mortality continued declining from 2000 to 2019, the rate of this decrease decelerated. We aimed to assess the trends and disparities in risk factor control and treatment among US adults with atherosclerotic cardiovascular disease to find potential causes of the deceleration. METHODS AND RESULTS A total of 55 ,021 participants, aged ≥20 years, from the 1999 to 2018 National Health and Nutrition Examination Survey were included, of which 5717 were with atherosclerotic cardiovascular disease. Risk factor control was defined as hemoglobin A1c <7%, blood pressure <140/90 mm Hg, and non-high-density lipoprotein cholesterol <100 mg/dL. The prevalence of atherosclerotic cardiovascular disease oscillated between 7.3% and 8.9% from 1999 to 2018. A significant increasing trend was observed in the prevalence of diabetes, obesity, heavy alcohol consumption, and self-reported hypertension within the population with atherosclerotic cardiovascular disease (Ptrend≤0.001). Non-high-density lipoprotein cholesterol <100 mg/dL increased from 7.1% in 1999 to 2002 to 15.7% in 2003 to 2006, before plateauing. Blood pressure control (<140/90 mm Hg) increased until 2011 to 2014, but declined to 70.1% in 2015 to 2018 (Ptrend<0.001, Pjoinpoint=0.14). Similarly, the proportion of participants achieving hemoglobin A1c control began to decrease after 2006 (Pjoinpoint=0.05, Ptrend=0.001). The percentage of participants achieving all 3 targets increased significantly from 4.5% to 18.6% across 1999 to 2018 (Ptrend=0.02), but the increasing trend decelerated after 2005 to 2006 (Pjoinpoint<0.001). Striking disparities in risk factor control and medication use persisted between sexes, and between different racial and ethnic populations. CONCLUSIONS Worsened control of glycemia, blood pressure, obesity, and alcohol consumption, leveled lipid control, and persistent socioeconomic disparities may be contributing factors to the observed deceleration in decreasing cardiovascular mortality trends.
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Affiliation(s)
- Jingen Li
- Department of Cardiovascular MedicineDongzhimen Hospital, Beijing University of Chinese MedicineBeijingChina
- Department of Cardiovascular MedicineMayo ClinicRochesterMN
- Cardiovascular Diseases CenterXiyuan Hospital, China Academy of Chinese Medical Sciences, National Clinical Research Center for Chinese Medicine CardiologyBeijingChina
| | - Jie Zhang
- National Integrated Traditional and Western Medicine Center for Cardiovascular Disease, China‐Japan Friendship HospitalBeijingChina
| | | | - Naima Covassin
- Department of Cardiovascular MedicineMayo ClinicRochesterMN
| | - Lijing Zhang
- Department of Cardiovascular MedicineDongzhimen Hospital, Beijing University of Chinese MedicineBeijingChina
| | - Hao Xu
- Cardiovascular Diseases CenterXiyuan Hospital, China Academy of Chinese Medical Sciences, National Clinical Research Center for Chinese Medicine CardiologyBeijingChina
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Antonio-Villa NE, Bello-Chavolla OY, Fermín-Martínez CA, Ramírez-García D, Vargas-Vázquez A, Basile-Alvarez MR, Núñez-Luna A, Sánchez-Castro P, Fernández-Chirino L, Díaz-Sánchez JP, Dávila-López G, Posadas-Sánchez R, Vargas-Alarcón G, Caballero AE, Florez JC, Seiglie JA. Diabetes subgroups and sociodemographic inequalities in Mexico: a cross-sectional analysis of nationally representative surveys from 2016 to 2022. LANCET REGIONAL HEALTH. AMERICAS 2024; 33:100732. [PMID: 38616917 PMCID: PMC11015526 DOI: 10.1016/j.lana.2024.100732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 03/20/2024] [Accepted: 03/22/2024] [Indexed: 04/16/2024]
Abstract
Background Differences in the prevalence of four diabetes subgroups have been reported in Mexico compared to other populations, but factors that may contribute to these differences are poorly understood. Here, we estimate the prevalence of diabetes subgroups in Mexico and evaluate their correlates with indicators of social disadvantage using data from national representative surveys. Methods We analyzed serial, cross-sectional Mexican National Health and Nutrition Surveys spanning 2016, 2018, 2020, 2021, and 2022, including 23,354 adults (>20 years). Diabetes subgroups (obesity-related [MOD], severe insulin-deficient [SIDD], severe insulin-resistant [SIRD], and age-related [MARD]) were classified using self-normalizing neural networks based on a previously validated algorithm. We used the density-independent social lag index (DISLI) as a proxy of state-level social disadvantage. Findings We identified 4204 adults (median age: 57, IQR: 47-66, women: 64%) living with diabetes, yielding a pooled prevalence of 16.04% [95% CI: 14.92-17.17]. When stratified by diabetes subgroup, prevalence was 6.62% (5.69-7.55) for SIDD, 5.25% (4.52-5.97) for MOD, 2.39% (1.95-2.83) for MARD, and 1.27% (1.00-1.54) for SIRD. SIDD and MOD clustered in Southern Mexico, whereas MARD and SIRD clustered in Northern Mexico and Mexico City. Each standard deviation increase in DISLI was associated with higher odds of SIDD (OR: 1.12, 95% CI: 1.06-1.12) and lower odds of MOD (OR: 0.93, 0.88-0.99). Speaking an indigenous language was associated with higher odds of SIDD (OR: 1.35, 1.16-1.57) and lower odds of MARD (OR 0.58, 0.45-0.74). Interpretation Diabetes prevalence in Mexico is rising in the context of regional and sociodemographic inequalities across distinct diabetes subgroups. SIDD is a subgroup of concern that may be associated with inadequate diabetes management, mainly in marginalized states. Funding This research was supported by Instituto Nacional de Geriatría in Mexico.
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Affiliation(s)
| | | | - Carlos A. Fermín-Martínez
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- MD/PhD (PECEM) Program, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Daniel Ramírez-García
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Arsenio Vargas-Vázquez
- MD/PhD (PECEM) Program, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Martín Roberto Basile-Alvarez
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Alejandra Núñez-Luna
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Paulina Sánchez-Castro
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | | | - Juan Pablo Díaz-Sánchez
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- MD/PhD (PECEM) Program, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Gael Dávila-López
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Rosalinda Posadas-Sánchez
- Departamento de Endocrinología, Instituto Nacional de Cardiología Ignacio Chávez, Mexico City, Mexico
| | - Gilberto Vargas-Alarcón
- Dirección de Investigación, Instituto Nacional de Cardiología Ignacio Chávez, Mexico City, Mexico
| | - A. Enrique Caballero
- Division of Endocrinology, Diabetes and Hypertension, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jose C. Florez
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jacqueline A. Seiglie
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
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Jaroenlapnopparat A, Mettler SK, Guillen H, Chayanupatkul M, Rajbhandari R. Changes in the Prevalence, Incidence, and Disability-Adjusted Life Years of Non-alcoholic Fatty Liver Disease in the United States Between 1990 and 2019. Dig Dis Sci 2024; 69:702-712. [PMID: 38190072 DOI: 10.1007/s10620-023-08230-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 12/04/2023] [Indexed: 01/09/2024]
Abstract
INTRODUCTION This study aimed to determine trends in the prevalence, incidence, and disability-adjusted life years (DALYs) of Non-alcoholic Fatty Liver Disease (NAFLD) in the US across different states and age groups between 1990 and 2019. METHODS Using the Global Burden of Disease database, this study analyzed the prevalence, incidence, and DALYs of NAFLD in the US between 1990 and 2019. We computed relative percentage changes, performed Joinpoint regression analyses of trends, and compared these between states and age groups (5-19, 20-55, and more than 55 years old). RESULTS In the United States, the prevalence of NAFLD increased more than the global average over the study period (+ 30.7% vs. + 24.5%), especially in the 5-19-year-old age group. Among all states, Kansas, Washington, and California had the highest increase in prevalence and the District of Columbia followed by Massachusetts and North Carolina had the lowest increase in prevalence. The increase in incidence was greater in the US than the global average (+ 37.18% vs. + 7.28%). West Virginia, Ohio, and Kentucky had the highest increase in incidence. The increase in DALYs was greater in the US compared to the global average (+ 57.15% vs. + 12.65%). Alaska, West Virginia, and Kentucky had the highest increase in DALYs. The increased incidence and DALYs were found in all states except in the District of Columbia. CONCLUSION The prevalence of NAFLD in the US has increased more rapidly than the global average, especially in the pediatric population. South and Midwest states have the highest increase in prevalence, incidence, and DALYs of NAFLD. The District of Columbia was the only state that has decreased incidence and DALYs.
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Affiliation(s)
- Aunchalee Jaroenlapnopparat
- Mount Auburn Hospital/Beth Israel Lahey Health, Cambridge, MA, 02138, USA.
- Harvard Medical School, Boston, MA, 02115, USA.
| | - Sofia K Mettler
- Mount Auburn Hospital/Beth Israel Lahey Health, Cambridge, MA, 02138, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Hendrik Guillen
- Mount Auburn Hospital/Beth Israel Lahey Health, Cambridge, MA, 02138, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Maneerat Chayanupatkul
- Center of Excellence in Alternative and Complementary Medicine for Gastrointestinal and Liver Diseases, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Ruma Rajbhandari
- Harvard Medical School, Boston, MA, 02115, USA
- Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, 02114, USA
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Stallings EB, Isenburg JL, Rutkowski RE, Kirby RS, Nembhard WN, Sandidge T, Villavicencio S, Nguyen HH, McMahon DM, Nestoridi E, Pabst LJ. National population-based estimates for major birth defects, 2016-2020. Birth Defects Res 2024; 116:e2301. [PMID: 38277408 PMCID: PMC10898112 DOI: 10.1002/bdr2.2301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 12/26/2023] [Accepted: 01/03/2024] [Indexed: 01/28/2024]
Abstract
BACKGROUND We provide updated crude and adjusted prevalence estimates of major birth defects in the United States for the period 2016-2020. METHODS Data were collected from 13 US population-based surveillance programs that used active or a combination of active and passive case ascertainment methods to collect all birth outcomes. These data were used to calculate pooled prevalence estimates and national prevalence estimates adjusted for maternal race/ethnicity for all conditions, and maternal age for trisomies and gastroschisis. Prevalence was compared to previously published national estimates from 1999 to 2014. RESULTS Adjusted national prevalence estimates per 10,000 live births ranged from 0.63 for common truncus to 18.65 for clubfoot. Temporal changes were observed for several birth defects, including increases in the prevalence of atrioventricular septal defect, tetralogy of Fallot, omphalocele, trisomy 18, and trisomy 21 (Down syndrome) and decreases in the prevalence of anencephaly, common truncus, transposition of the great arteries, and cleft lip with and without cleft palate. CONCLUSION This study provides updated national estimates of selected major birth defects in the United States. These data can be used for continued temporal monitoring of birth defects prevalence. Increases and decreases in prevalence since 1999 observed in this study warrant further investigation.
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Affiliation(s)
- Erin B. Stallings
- National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jennifer L. Isenburg
- National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Rachel E. Rutkowski
- Chiles Center, College of Public Health, University of South Florida, Tampa, Florida, USA
- National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Russell S. Kirby
- Chiles Center, College of Public Health, University of South Florida, Tampa, Florida, USA
| | - Wendy N. Nembhard
- Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
- Arkansas Center for Birth Defects Research and Prevention, Little Rock, Arkansas, USA
| | - Theresa Sandidge
- Illinois Department of Public Health, Springfield, Illinois, USA
| | - Stephan Villavicencio
- Chiles Center, College of Public Health, University of South Florida, Tampa, Florida, USA
| | - Hoang H. Nguyen
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Daria M. McMahon
- South Carolina Department of Health and Environmental Control, Columbia, South Carolina, USA
| | - Eirini Nestoridi
- Division for Surveillance, Research, and Promotion of Perinatal Health, Massachusetts Department of Public Health, Boston, Massachusetts, USA
| | - Laura J. Pabst
- National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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Lhoste VPF, Zhou B, Mishra A, Bennett JE, Filippi S, Asaria P, Gregg EW, Danaei G, Ezzati M. Cardiometabolic and renal phenotypes and transitions in the United States population. NATURE CARDIOVASCULAR RESEARCH 2023; 3:46-59. [PMID: 38314318 PMCID: PMC7615595 DOI: 10.1038/s44161-023-00391-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 11/13/2023] [Indexed: 02/06/2024]
Abstract
Cardiovascular and renal conditions have both shared and distinct determinants. In this study, we applied unsupervised clustering to multiple rounds of the National Health and Nutrition Examination Survey from 1988 to 2018, and identified 10 cardiometabolic and renal phenotypes. These included a 'low risk' phenotype; two groups with average risk factor levels but different heights; one group with low body-mass index and high levels of high-density lipoprotein cholesterol; five phenotypes with high levels of one or two related risk factors ('high heart rate', 'high cholesterol', 'high blood pressure', 'severe obesity' and 'severe hyperglycemia'); and one phenotype with low diastolic blood pressure (DBP) and low estimated glomerular filtration rate (eGFR). Prevalence of the 'high blood pressure' and 'high cholesterol' phenotypes decreased over time, contrasted by a rise in the 'severe obesity' and 'low DBP, low eGFR' phenotypes. The cardiometabolic and renal traits of the US population have shifted from phenotypes with high blood pressure and cholesterol toward poor kidney function, hyperglycemia and severe obesity.
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Affiliation(s)
- Victor P. F. Lhoste
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Bin Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Anu Mishra
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - James E. Bennett
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Sarah Filippi
- Department of Mathematics, Imperial College London, London, UK
| | - Perviz Asaria
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Edward W. Gregg
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- School of Population Health, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Goodarz Danaei
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Majid Ezzati
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
- Regional Institute for Population Studies, University of Ghana, Accra, Ghana
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11
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Senn MK, Goodarzi MO, Ramesh G, Allison MA, Graff M, Young KL, Talavera GA, McClain AC, Garcia TP, Rotter JI, Wood AC. Associations between avocado intake and measures of glucose and insulin homeostasis in Hispanic individuals with and without type 2 diabetes: Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Nutr Metab Cardiovasc Dis 2023; 33:2428-2439. [PMID: 37798236 PMCID: PMC10842938 DOI: 10.1016/j.numecd.2023.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 07/27/2023] [Accepted: 08/01/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND AND AIMS To investigate associations between avocado intake and glycemia in adults with Hispanic/Latino ancestry. METHODS AND RESULTS The associations of avocado intake with measures of insulin and glucose homeostasis were evaluated in a cross-sectional analysis of up to 14,591 Hispanic/Latino adults, using measures of: average glucose levels (hemoglobin A1c; HbA1c), fasting glucose and insulin, glucose and insulin levels after an oral glucose tolerance test (OGTT), and calculated measures of insulin resistance (HOMA-IR, and HOMA-%β), and insulinogenic index. Associations were assessed using multivariable linear regression models, which controlled for sociodemographic factors and health behaviors, and which were stratified by dysglycemia status. In those with normoglycemia, avocado intake was associated with a higher insulinogenic index (β = 0.17 ± 0.07, P = 0.02). In those with T2D (treated and untreated), avocado intake was associated with lower hemoglobin A1c (HbA1c; β = -0.36 ± 0.21, P = 0.02), and lower fasting glucose (β = -0.27 ± 0.12, P = 0.02). In the those with untreated T2D, avocado intake was additionally associated with HOMA-%β (β = 0.39 ± 0.19, P = 0.04), higher insulin values 2-h after an oral glucose load (β = 0.62 ± 0.23, P = 0.01), and a higher insulinogenic index (β = 0.42 ± 0.18, P = 0.02). No associations were observed in participants with prediabetes. CONCLUSIONS We observed an association of avocado intake with better glucose/insulin homeostasis, especially in those with T2D.
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Affiliation(s)
- MacKenzie K Senn
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, 1100 Bates Avenue Houston, TX 77030, USA; The University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler Street, Houston, TX 77030, USA
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Gautam Ramesh
- School of Medicine, University of California, La Jolla, San Diego, CA 92037, USA
| | - Matthew A Allison
- Division of Preventive Medicine, Department of Family Medicine, University of California, La Jolla, San Diego, CA 92037, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Kristin L Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Gregory A Talavera
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA
| | - Amanda C McClain
- School of Exercise and Nutritional Sciences, San Diego State University, San Diego, CA 92182, USA
| | - Tanya P Garcia
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Alexis C Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, 1100 Bates Avenue Houston, TX 77030, USA.
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12
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Wu X, Gao J, Zhu L, Wang W, Zhang Y. Dietary vitamins modified the association of dietary iron with type 2 diabetes: the National Health and Nutrition Examination Survey, 2003-2014. Chin Med J (Engl) 2023; 136:2759-2761. [PMID: 37914677 PMCID: PMC10684183 DOI: 10.1097/cm9.0000000000002874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Indexed: 11/03/2023] Open
Affiliation(s)
- Xiaoyan Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Guilin Medical University, Guilin, Guangxi 514499, China
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, School of Public Health, Guilin Medical University, Guilin, Guangxi 514499, China
| | - Jian Gao
- Department of Nutrition and Food Hygiene, the National Key Discipline, School of Public Health, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Lin Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Guilin Medical University, Guilin, Guangxi 514499, China
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, School of Public Health, Guilin Medical University, Guilin, Guangxi 514499, China
| | - Wenjie Wang
- Department of Epidemiology and Biostatistics, School of Public Health, School of Medicine, Chronic Disease Research Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Yunlong Zhang
- Department of Nutrition and Food Hygiene, the National Key Discipline, School of Public Health, Harbin Medical University, Harbin, Heilongjiang 150081, China
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13
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Sun X, Du T. Trends in weight change patterns across life course among US adults, 1988-2018: population-based study. BMC Public Health 2023; 23:2168. [PMID: 37932673 PMCID: PMC10626664 DOI: 10.1186/s12889-023-17137-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 11/02/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND To examine trends in weight change patterns from young adulthood through midlife to late adulthood and their sex and racial/ethnic disparities among US adults from 1988 to 2018. METHODS A total of 48,969 participants from the National Health and Nutrition Examination Survey 1988-1994 and 2001-2018 were included. RESULTS The age-adjusted prevalence of stable non-obesity between young adulthood and midlife declined significantly from 84.1% (95 CI, 82.9-85.3%) in 1988-1994 to 68.7% (67.1-70.2%) in 2013-2018, and between midlife and late adulthood from 71.2% (69.2-73.1%) to 52.4% (50.5-54.2%). The magnitude of increase in the prevalence of weight gain from young adulthood to midlife (from 10.8% [9.9-11.6%] in 1988-1994 to 21.2% [20-22.3%] in 2013-2018; P < 0.001 for trend) was greater than that from midlife to late adulthood (from 14.1% [12.9-15.3%] to 17.2% [16.2-18.1%]; P = 0.002 for trend). The magnitude of increase in the prevalence of stable obesity from young adulthood to midlife (from 3.9% [3.1-4.8%] in 1988-1994 to 9.2% [8.2-10.3%] in 2013-2018; P < 0.001 for trend) was smaller than that from midlife to late adulthood (from 11.2% [10.1-12.2%] to 24.8% [23.3-26.3%]; P < 0.001 for trend). The declining trends in the prevalence of stable non-obesity and increasing trends in the prevalence of weight gain and stable obesity from young adulthood through midlife to late adulthood were also observed for all sex and race/ethnicity subgroups. The magnitude of decrease in the prevalence of stable non-obesity, and the magnitude of increase in the prevalence of weight gain from young adulthood through midlife to late adulthood were greater in men than in women (all P for interaction < 0.01). Weight gain patterns for those aged ≥ 65 years were substantially different from the younger age groups. CONCLUSIONS More young people born in later years are encountering obesity and accumulate greater obesity exposure across their lives than young people born in earlier years.
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Affiliation(s)
- Xingxing Sun
- Department of Anesthesiology, Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, and Wuhan Clinical Research Center for Geriatric Anesthesia, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Tingting Du
- Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
- Branch of National Clinical Research Center for Metabolic Diseases, Wuhan, Hubei, China.
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14
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Misra S, Wagner R, Ozkan B, Schön M, Sevilla-Gonzalez M, Prystupa K, Wang CC, Kreienkamp RJ, Cromer SJ, Rooney MR, Duan D, Thuesen ACB, Wallace AS, Leong A, Deutsch AJ, Andersen MK, Billings LK, Eckel RH, Sheu WHH, Hansen T, Stefan N, Goodarzi MO, Ray D, Selvin E, Florez JC, Meigs JB, Udler MS. Precision subclassification of type 2 diabetes: a systematic review. COMMUNICATIONS MEDICINE 2023; 3:138. [PMID: 37798471 PMCID: PMC10556101 DOI: 10.1038/s43856-023-00360-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 09/15/2023] [Indexed: 10/07/2023] Open
Abstract
BACKGROUND Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. METHODS We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. RESULTS Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. CONCLUSION Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.
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Affiliation(s)
- Shivani Misra
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
- Department of Diabetes and Endocrinology, Imperial College Healthcare NHS Trust, London, UK.
| | - Robert Wagner
- Department of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Bige Ozkan
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Martin Schön
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Magdalena Sevilla-Gonzalez
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Katsiaryna Prystupa
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Caroline C Wang
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Raymond J Kreienkamp
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Pediatrics, Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
| | - Sara J Cromer
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mary R Rooney
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anne Cathrine Baun Thuesen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Amelia S Wallace
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Aaron Leong
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, 100 Cambridge St 16th Floor, Boston, MA, USA
| | - Aaron J Deutsch
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mette K Andersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Liana K Billings
- Division of Endocrinology, Diabetes and Metabolism, NorthShore University Health System, Skokie, IL, USA
- Department of Medicine, Pritzker School of Medicine, University of Chicago, Chicago, IL, USA
| | - Robert H Eckel
- Division of Endocrinology, Metabolism and Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
| | - Wayne Huey-Herng Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institute, Miaoli County, Taiwan, ROC
- Division of Endocrinology and Metabolism, Taichung Veterans General Hospital, Taichung, Taiwan, ROC
- Division of Endocrinology and Metabolism, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Norbert Stefan
- German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- University Hospital of Tübingen, Tübingen, Germany
- Institute of Diabetes Research and Metabolic Diseases (IDM), Helmholtz Center Munich, Neuherberg, Germany
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Debashree Ray
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Elizabeth Selvin
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jose C Florez
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - James B Meigs
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, 100 Cambridge St 16th Floor, Boston, MA, USA
| | - Miriam S Udler
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
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15
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Ordoñez-Guillen NE, Gonzalez-Compean JL, Lopez-Arevalo I, Contreras-Murillo M, Aldana-Bobadilla E. Machine learning based study for the classification of Type 2 diabetes mellitus subtypes. BioData Min 2023; 16:24. [PMID: 37608329 PMCID: PMC10463725 DOI: 10.1186/s13040-023-00340-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 08/07/2023] [Indexed: 08/24/2023] Open
Abstract
PURPOSE Data-driven diabetes research has increased its interest in exploring the heterogeneity of the disease, aiming to support in the development of more specific prognoses and treatments within the so-called precision medicine. Recently, one of these studies found five diabetes subgroups with varying risks of complications and treatment responses. Here, we tackle the development and assessment of different models for classifying Type 2 Diabetes (T2DM) subtypes through machine learning approaches, with the aim of providing a performance comparison and new insights on the matter. METHODS We developed a three-stage methodology starting with the preprocessing of public databases NHANES (USA) and ENSANUT (Mexico) to construct a dataset with N = 10,077 adult diabetes patient records. We used N = 2,768 records for training/validation of models and left the remaining (N = 7,309) for testing. In the second stage, groups of observations -each one representing a T2DM subtype- were identified. We tested different clustering techniques and strategies and validated them by using internal and external clustering indices; obtaining two annotated datasets Dset A and Dset B. In the third stage, we developed different classification models assaying four algorithms, seven input-data schemes, and two validation settings on each annotated dataset. We also tested the obtained models using a majority-vote approach for classifying unseen patient records in the hold-out dataset. RESULTS From the independently obtained bootstrap validation for Dset A and Dset B, mean accuracies across all seven data schemes were [Formula: see text] ([Formula: see text]) and [Formula: see text] ([Formula: see text]), respectively. Best accuracies were [Formula: see text] and [Formula: see text]. Both validation setting results were consistent. For the hold-out dataset, results were consonant with most of those obtained in the literature in terms of class proportions. CONCLUSION The development of machine learning systems for the classification of diabetes subtypes constitutes an important task to support physicians for fast and timely decision-making. We expect to deploy this methodology in a data analysis platform to conduct studies for identifying T2DM subtypes in patient records from hospitals.
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Affiliation(s)
- Nelson E Ordoñez-Guillen
- Cinvestav Tamaulipas, Carretera Victoria-Soto la Marina km 5.5, Victoria, 87130, Tamaulipas, Mexico
| | | | - Ivan Lopez-Arevalo
- Cinvestav Tamaulipas, Carretera Victoria-Soto la Marina km 5.5, Victoria, 87130, Tamaulipas, Mexico
| | - Miguel Contreras-Murillo
- Cinvestav Tamaulipas, Carretera Victoria-Soto la Marina km 5.5, Victoria, 87130, Tamaulipas, Mexico
| | - Edwin Aldana-Bobadilla
- CONAHCYT-Centro de Investigación y de Estudios Avanzados del IPN, Unidad Tamaulipas, Carretera Victoria-Soto la Marina km 5.5, Victoria, Tamaulipas, 87130, Mexico
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16
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El Khoury R, Dardik A. Toward a targeted approach to diabetes-related peripheral arterial occlusive disease. JVS Vasc Sci 2023; 4:100112. [PMID: 37496885 PMCID: PMC10366572 DOI: 10.1016/j.jvssci.2023.100112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/28/2023] Open
Affiliation(s)
- Rym El Khoury
- Division of Vascular and Endovascular Surgery, Department of Surgery, University of California San Francisco, CA
| | - Alan Dardik
- Department of Surgery, Yale School of Medicine, New Haven, CT
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17
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Misra S, Wagner R, Ozkan B, Schön M, Sevilla-Gonzalez M, Prystupa K, Wang CC, Kreienkamp RJ, Cromer SJ, Rooney MR, Duan D, Thuesen ACB, Wallace AS, Leong A, Deutsch AJ, Andersen MK, Billings LK, Eckel RH, Sheu WHH, Hansen T, Stefan N, Goodarzi MO, Ray D, Selvin E, Florez JC, Meigs JB, Udler MS. Systematic review of precision subclassification of type 2 diabetes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.19.23288577. [PMID: 37131632 PMCID: PMC10153304 DOI: 10.1101/2023.04.19.23288577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.
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18
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Fang L, Sheng H, Tan Y, Zhang Q. Prevalence of diabetes in the USA from the perspective of demographic characteristics, physical indicators and living habits based on NHANES 2009-2018. Front Endocrinol (Lausanne) 2023; 14:1088882. [PMID: 36960397 PMCID: PMC10028205 DOI: 10.3389/fendo.2023.1088882] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 02/21/2023] [Indexed: 03/09/2023] Open
Abstract
Objective To determine differences in DM in the U.S. population according to demographic characteristics, physical indicators and living habits. Methods 23 546 participants in the 2009 to 2018 National Health and Nutrition Examination Survey (NHANES) who were 20 year of age or older and not pregnant. All analyses used weighted samples and considered the stratification and clustering of the design. Specific indicators include length of leg (cm), BMI (kg/cm2), TCHOL (mg/dL), fasting plasma glucose (mg/dL) and comparison of means and the proportion of participants with DM. Results The prevalence of DM in the USA has been rising modestly in the past decade, and were consistent and robust for the observed differences in age, sex, and ethnicity. Compared with white participants, black participants and Mexican-American were both more likely (P<0.001) to have diabetes: 14.6% (CI, 13.6% to 15.6%) among black participants, 10.6% (CI, 9.9% to 11.3%) among white participants, and 13.5% (CI, 11.9% to 15.2%) among Mexican-American participants. The prevalence of diabetes is increasing with age, males peaked around the 60s, and women around the 70s. The overall mean leg length and TCHOL was lower in diabetics than in non-diabetics (1.07 cm, 18.67 mg/dL, respectively), while mean BMI were higher in diabetics than in non-diabetics (4.27 kg/cm2). DM had the greatest effect on decline of TCHOL in white participants (23.6 mg/dL), less of an effect in black participants (9.67 mg/dL), and the least effect in Mexican-American participants (8.25 mg/dL). Notably, smoking had great effect on percent increment of DM in whites (0.2%), and have little effect on black and Mexican-Americans. Conclusions DM is more common in the general population than might be clinically recognized, and the prevalence of DM was associated to varying degrees with many indicators of demographic characteristics, physical indicators, and living habits. These indicators should be linked with medical resource allocation and scientific treatment methods to comprehensively implement the treatment of DM.
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Affiliation(s)
- Ling Fang
- Shaanxi Key Laboratory of Chinese Medicine Encephalopathy, Shaanxi University of Chinese Medicine, Xianyang, China
| | - Huafang Sheng
- Department of Laboratory Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China
| | - Yingying Tan
- Shaanxi Key Laboratory of Chinese Medicine Encephalopathy, Shaanxi University of Chinese Medicine, Xianyang, China
| | - Qi Zhang
- Shaanxi Key Laboratory of Chinese Medicine Encephalopathy, Shaanxi University of Chinese Medicine, Xianyang, China
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19
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Goldberg EM, Polachek WS, Hynes K. Ankle Fractures in Diabetic Patients: A Critical Analysis. JBJS Rev 2023; 11:01874474-202303000-00003. [PMID: 36927706 DOI: 10.2106/jbjs.rvw.22.00147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
» Patients with diabetes are at higher risk for complications after surgical fixation of unstable fractures due to impaired neurovascular functioning and wound-healing capabilities. » Patients with uncontrolled diabetes have higher rates of complications when compared with patients with controlled diabetes. » Despite higher rates of complications, operative fixation of unstable ankle fractures in diabetic patients reliably leads to a functional lower extremity with an overall lower rate of complications than nonoperative management. » Operatively and nonoperatively managed ankle fractures in patients with diabetes should remain non-weight-bearing for an extended period of time. » Discussion of risk of poor outcomes including deep infection, loss of reduction, return to the operating room, and risk of arthrodesis or amputation should be explicitly discussed with patients and families when managing unstable ankle fractures in diabetic patients.
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Affiliation(s)
- Ellen M Goldberg
- University of Chicago Pritzker School of Medicine, Chicago, Illinois
| | - William S Polachek
- Department of Orthopaedic Surgery, University of Chicago, Chicago, Illinois
| | - Kelly Hynes
- Department of Orthopaedic Surgery, University of Chicago, Chicago, Illinois
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20
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Bello-Chavolla OY, Antonio-Villa NE, Fermín-Martínez CA, Fernández-Chirino L, Vargas-Vázquez A, Ramírez-García D, Basile-Alvarez MR, Hoyos-Lázaro AE, Carrillo-Larco RM, Wexler DJ, Manne-Goehler J, Seiglie JA. Diabetes-Related Excess Mortality in Mexico: A Comparative Analysis of National Death Registries Between 2017-2019 and 2020. Diabetes Care 2022; 45:2957-2966. [PMID: 36286591 PMCID: PMC7613876 DOI: 10.2337/dc22-0616] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 09/27/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To estimate diabetes-related mortality in Mexico in 2020 compared with 2017-2019 after the onset of the coronavirus disease 2019 (COVID-19) pandemic. RESEARCH DESIGN AND METHODS This retrospective, state-level study used national death registries of Mexican adults aged ≥20 years for the 2017-2020 period. Diabetes-related death was defined using ICD-10 codes listing diabetes as the primary cause of death, excluding certificates with COVID-19 as the primary cause of death. Spatial and negative binomial regression models were used to characterize the geographic distribution and sociodemographic and epidemiologic correlates of diabetes-related excess mortality, estimated as increases in diabetes-related mortality in 2020 compared with average 2017-2019 rates. RESULTS We identified 148,437 diabetes-related deaths in 2020 (177 per 100,000 inhabitants) vs. an average of 101,496 deaths in 2017-2019 (125 per 100,000 inhabitants). In-hospital diabetes-related deaths decreased by 17.8% in 2020 versus 2017-2019, whereas out-of-hospital deaths increased by 89.4%. Most deaths were attributable to type 2 diabetes (130 per 100,000 inhabitants). Compared with 2018-2019 data, hyperglycemic hyperosmolar state and diabetic ketoacidosis were the two contributing causes with the highest increase in mortality (128% and 116% increase, respectively). Diabetes-related excess mortality clustered in southern Mexico and was highest in states with higher social lag, rates of COVID-19 hospitalization, and prevalence of HbA1c ≥7.5%. CONCLUSIONS Diabetes-related deaths increased among Mexican adults by 41.6% in 2020 after the onset of the COVID-19 pandemic, occurred disproportionately outside the hospital, and were largely attributable to type 2 diabetes and hyperglycemic emergencies. Disruptions in diabetes care and strained hospital capacity may have contributed to diabetes-related excess mortality in Mexico during 2020.
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Affiliation(s)
| | - Neftali Eduardo Antonio-Villa
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- MD/PhD (PECEM) Program, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Carlos A. Fermín-Martínez
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- MD/PhD (PECEM) Program, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Luisa Fernández-Chirino
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- Facultad de Química, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Arsenio Vargas-Vázquez
- MD/PhD (PECEM) Program, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Daniel Ramírez-García
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Martín Roberto Basile-Alvarez
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Ana Elena Hoyos-Lázaro
- Research Division, Instituto Nacional de Geriatría, Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Rodrigo M. Carrillo-Larco
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, U.K
- CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Deborah J. Wexler
- Diabetes Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Jennifer Manne-Goehler
- Harvard Center for Population and Development Studies, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Jacqueline A. Seiglie
- Diabetes Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
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21
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Nguyen KH, Cemballi AG, Fields JD, Brown W, Pantell MS, Lyles CR. Applying a socioecological framework to chronic disease management: implications for social informatics interventions in safety-net healthcare settings. JAMIA Open 2022; 5:ooac014. [PMID: 35571359 PMCID: PMC9097756 DOI: 10.1093/jamiaopen/ooac014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Revised: 01/11/2022] [Accepted: 02/22/2022] [Indexed: 11/25/2022] Open
Abstract
Objective Vulnerable populations face numerous barriers in managing chronic disease(s). As healthcare systems work toward integrating social risk factors into electronic health records and healthcare delivery, we need better understanding of the interrelated nature of social needs within patients' everyday lives to inform effective informatics interventions to advance health equity. Materials and Methods We conducted in-depth interviews, participant-led neighborhood tours, and clinic visit observations involving 10 patients with diabetes in underserved San Francisco neighborhoods and 10 community leaders serving those neighborhoods. We coded health barriers and facilitators using a socioecological framework. We also linked these qualitative data with early persona development, focusing on patients' experiences in these communities and within the healthcare system, as a starting place for our future informatics design. Results We identified social risk and protective factors across almost every socioecological domain and level-from physical disability to household context to neighborhood environment. We then detailed the complex interplay across domains and levels within two critical aspects of patients' lives: housing and food. Finally, from these data we generated 3 personas that capture the intersectional nature of these determinants. Conclusion Drawing from different disciplines, our study provides a socioecological approach to understanding health promotion for patients with chronic disease in a safety-net healthcare system, using multiple methodologies. Future digital health research should center the lived experiences of marginalized patients to effectively design and implement informatics solutions for this audience.
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Affiliation(s)
- Kim Hanh Nguyen
- Department of Medicine, Center for Vulnerable Populations, University of
California, San Francisco, California, USA
- Division of General Internal Medicine, Zuckerberg San Francisco General
Hospital, San Francisco, California, USA
- Department of Epidemiology and Biostatistics, University of
California, San Francisco, California, USA
| | - Anupama G Cemballi
- Department of Medicine, Center for Vulnerable Populations, University of
California, San Francisco, California, USA
- Division of General Internal Medicine, Zuckerberg San Francisco General
Hospital, San Francisco, California, USA
| | - Jessica D Fields
- Department of Medicine, Center for Vulnerable Populations, University of
California, San Francisco, California, USA
- Division of General Internal Medicine, Zuckerberg San Francisco General
Hospital, San Francisco, California, USA
- Department of Epidemiology and Biostatistics, University of
California, San Francisco, California, USA
| | - William Brown
- Department of Medicine, Center for Vulnerable Populations, University of
California, San Francisco, California, USA
- Department of Epidemiology and Biostatistics, University of
California, San Francisco, California, USA
- Division of Prevention Science, Department of Medicine, Center for AIDS
Prevention Studies, University of California, San Francisco, California,
USA
- Bakar Computational Health Science Institute, University of
California, San Francisco, California, USA
| | - Matthew S Pantell
- Department of Pediatrics, University of California, San
Francisco, California, USA
- Department of Family and Community Medicine, Center for Health and Community,
University of California, San Francisco, California, USA
| | - Courtney Rees Lyles
- Department of Medicine, Center for Vulnerable Populations, University of
California, San Francisco, California, USA
- Division of General Internal Medicine, Zuckerberg San Francisco General
Hospital, San Francisco, California, USA
- Department of Epidemiology and Biostatistics, University of
California, San Francisco, California, USA
- Bakar Computational Health Science Institute, University of
California, San Francisco, California, USA
- Corresponding Author: Courtney Rees Lyles, PhD, UCSF General
Internal Medicine ZSFG, Box 1364, 1001 Potrero Ave San Francisco CA 94110, USA;
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