{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T14:43:33Z","timestamp":1791816213890,"version":"4.3.4"},"reference-count":24,"publisher":"American Medical Association (AMA)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n There have been major advances in insulin delivery and formulations over the past several decades. It is unclear whether these changes have resulted in improved glycemic control for patients with diabetes.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To characterize trends and disparities in glycemic control and severe hyperglycemia in US adults with diabetes using insulin.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This serial population-based cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) between 1988-1994 and 1999-2020. Participants were nonpregnant US adults aged 20 years or older who had a diagnosis of diabetes and were currently using insulin.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n Diabetes diagnosis and use of insulin.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n \n Trends in glycemic control (glycated hemoglobin [HbA\n 1c<\/jats:sub>\n ] level &amp;lt;7%) and severe hyperglycemia (HbA\n 1c<\/jats:sub>\n level &amp;gt;10%; to convert percentage of total hemoglobin to proportion of total hemoglobin, multiply by 0.01; to convert to millimoles per mole, multiply by 10.93 and subtract by 23.50) overall and by age, race and ethnicity, and indicators of socioeconomic status were evaluated using logistic regression. Analyses incorporated sample weights to account for oversampling of certain populations and survey nonresponse.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n There were 2482 participants with diabetes using insulin included in the analyses (mean [SD] age, 59.8 [0.4] years); 51.3% were men, 7.0% were Mexican American individuals, 17.9% were non-Hispanic Black individuals, and 65.2% were non-Hispanic White individuals. From 1988-1994 to 2013-2020, the proportion of patients with diabetes who received insulin and achieved glycemic control did not significantly change, from 29.2% (95% CI, 22.6%-36.8%) to 27.5% (95% CI, 21.7%-34.2%). Mexican American adults who received insulin were less likely than non-Hispanic White adults to achieve glycemic control, and disparities increased during the study period. The proportion of adults with severe hyperglycemia did not significantly change and was 14.6% (95% CI, 12.0-17.5) in 2013-2020. Adults who were Mexican American or non-Hispanic Black, were uninsured, or had low family income had the highest prevalence of severe hyperglycemia.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this population-based cross-sectional study of NHANES data over the past 3 decades, glycemic control stagnated and racial and ethnic disparities increased among US adults with diabetes who received insulin. Efforts to improve access to insulin may optimize glycemic control and reduce disparities in this population.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2022.47656","type":"journal-article","created":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T11:01:10Z","timestamp":1671534070000},"page":"e2247656","source":"Crossref","is-referenced-by-count":57,"title":["Trends and Disparities in Glycemic Control and Severe Hyperglycemia Among US Adults With Diabetes Using Insulin, 1988-2020"],"prefix":"10.1001","volume":"5","author":[{"given":"Siddharth","family":"Venkatraman","sequence":"first","affiliation":[{"name":"Johns Hopkins University School of Medicine, Baltimore, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justin B.","family":"Echouffo-Tcheugui","sequence":"additional","affiliation":[{"name":"Welch Center for Prevention, Epidemiology, and Clinical Research, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth","family":"Selvin","sequence":"additional","affiliation":[{"name":"Welch Center for Prevention, Epidemiology, and Clinical Research, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Fang","sequence":"additional","affiliation":[{"name":"Welch Center for Prevention, Epidemiology, and Clinical Research, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10","published-online":{"date-parts":[[2022,12,20]]},"reference":[{"key":"zoi221347r1","doi-asserted-by":"publisher","first-page":"S98","DOI":"10.2337\/dc20-S009","article-title":"9. 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