Prediabetes in Young Adults and Its Association With Cardiovascular Health Metrics in the Progression to Diabetes
The natural history of young adults with prediabetes and its association with cardiovascular health (CVH) metrics in progression to diabetes remain unknown. We examined the association between CVH metrics and the annual incidence of diabetes in young adults with prediabetes. This observational cohor...
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| Veröffentlicht in: | The journal of clinical endocrinology and metabolism 2022-06, Vol.107 (7), p.1843-1853 |
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| container_title | The journal of clinical endocrinology and metabolism |
| container_volume | 107 |
| creator | Suzuki, Yuta Kaneko, Hidehiro Okada, Akira Matsuoka, Satoshi Itoh, Hidetaka Fujiu, Katsuhito Michihata, Nobuaki Jo, Taisuke Takeda, Norifumi Morita, Hiroyuki Yamaguchi, Satoko Node, Koichi Yamauchi, Toshimasa Yasunaga, Hideo Komuro, Issei |
| description | The natural history of young adults with prediabetes and its association with cardiovascular health (CVH) metrics in progression to diabetes remain unknown.
We examined the association between CVH metrics and the annual incidence of diabetes in young adults with prediabetes.
This observational cohort study used the JMDC Claims Database. We analyzed 18 908 participants aged 18 to 44 years, with available fasting plasma glucose (FPG) data for 5 consecutive years, and who had prediabetes (FPG 100-125 mg/dL) at the initial health checkup. The ideal CVH metrics were as follows: nonsmoking, body mass index (BMI) less than 25 kg/m2, physical activity at goal, optimal dietary habits, blood pressure less than 120/80 mm Hg, and total cholesterol less than 200 mg/dL. We analyzed the association between CVH metrics and the annual incidence of diabetes. We also examined the relationship between 1-year changes in CVH metrics and the subsequent risk of diabetes.
The incidence of diabetes was 3.3% at 1 year and 9.5% at 5 years after the initial health checkup. An increasing number of nonideal CVH metrics have been associated with an increased risk of diabetes. Nonideal BMI, smoking, blood pressure, and total cholesterol level were associated with an increased risk of diabetes. This association was observed both in men and women. A one-point increase in the number of nonideal CVH metric components was associated over 1 year with an increased risk of diabetes.
CVH metrics can stratify the risk of diabetes in young adults with prediabetes. Improving CVH metrics may reduce the risk of developing diabetes. |
| doi_str_mv | 10.1210/clinem/dgac247 |
| format | Article |
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We examined the association between CVH metrics and the annual incidence of diabetes in young adults with prediabetes.
This observational cohort study used the JMDC Claims Database. We analyzed 18 908 participants aged 18 to 44 years, with available fasting plasma glucose (FPG) data for 5 consecutive years, and who had prediabetes (FPG 100-125 mg/dL) at the initial health checkup. The ideal CVH metrics were as follows: nonsmoking, body mass index (BMI) less than 25 kg/m2, physical activity at goal, optimal dietary habits, blood pressure less than 120/80 mm Hg, and total cholesterol less than 200 mg/dL. We analyzed the association between CVH metrics and the annual incidence of diabetes. We also examined the relationship between 1-year changes in CVH metrics and the subsequent risk of diabetes.
The incidence of diabetes was 3.3% at 1 year and 9.5% at 5 years after the initial health checkup. An increasing number of nonideal CVH metrics have been associated with an increased risk of diabetes. Nonideal BMI, smoking, blood pressure, and total cholesterol level were associated with an increased risk of diabetes. This association was observed both in men and women. A one-point increase in the number of nonideal CVH metric components was associated over 1 year with an increased risk of diabetes.
CVH metrics can stratify the risk of diabetes in young adults with prediabetes. Improving CVH metrics may reduce the risk of developing diabetes.</description><identifier>ISSN: 0021-972X</identifier><identifier>EISSN: 1945-7197</identifier><identifier>DOI: 10.1210/clinem/dgac247</identifier><identifier>PMID: 35446413</identifier><language>eng</language><publisher>United States: Oxford University Press</publisher><subject>Blood cholesterol ; Body mass index ; Development and progression ; Dextrose ; Epidemiology ; Exercise ; Glucose ; Glycosylated hemoglobin ; Medicine, Preventive ; Prediabetic state ; Preventive health services ; Teenagers ; Youth</subject><ispartof>The journal of clinical endocrinology and metabolism, 2022-06, Vol.107 (7), p.1843-1853</ispartof><rights>The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.</rights><rights>COPYRIGHT 2022 Oxford University Press</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c402t-b3fa42c3516a32e97487a461e4d22e78878e653259798f5f78ad19022a90bd103</citedby><cites>FETCH-LOGICAL-c402t-b3fa42c3516a32e97487a461e4d22e78878e653259798f5f78ad19022a90bd103</cites><orcidid>0000-0003-2553-6170 ; 0000-0002-2534-0939</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35446413$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Suzuki, Yuta</creatorcontrib><creatorcontrib>Kaneko, Hidehiro</creatorcontrib><creatorcontrib>Okada, Akira</creatorcontrib><creatorcontrib>Matsuoka, Satoshi</creatorcontrib><creatorcontrib>Itoh, Hidetaka</creatorcontrib><creatorcontrib>Fujiu, Katsuhito</creatorcontrib><creatorcontrib>Michihata, Nobuaki</creatorcontrib><creatorcontrib>Jo, Taisuke</creatorcontrib><creatorcontrib>Takeda, Norifumi</creatorcontrib><creatorcontrib>Morita, Hiroyuki</creatorcontrib><creatorcontrib>Yamaguchi, Satoko</creatorcontrib><creatorcontrib>Node, Koichi</creatorcontrib><creatorcontrib>Yamauchi, Toshimasa</creatorcontrib><creatorcontrib>Yasunaga, Hideo</creatorcontrib><creatorcontrib>Komuro, Issei</creatorcontrib><title>Prediabetes in Young Adults and Its Association With Cardiovascular Health Metrics in the Progression to Diabetes</title><title>The journal of clinical endocrinology and metabolism</title><addtitle>J Clin Endocrinol Metab</addtitle><description>The natural history of young adults with prediabetes and its association with cardiovascular health (CVH) metrics in progression to diabetes remain unknown.
We examined the association between CVH metrics and the annual incidence of diabetes in young adults with prediabetes.
This observational cohort study used the JMDC Claims Database. We analyzed 18 908 participants aged 18 to 44 years, with available fasting plasma glucose (FPG) data for 5 consecutive years, and who had prediabetes (FPG 100-125 mg/dL) at the initial health checkup. The ideal CVH metrics were as follows: nonsmoking, body mass index (BMI) less than 25 kg/m2, physical activity at goal, optimal dietary habits, blood pressure less than 120/80 mm Hg, and total cholesterol less than 200 mg/dL. We analyzed the association between CVH metrics and the annual incidence of diabetes. We also examined the relationship between 1-year changes in CVH metrics and the subsequent risk of diabetes.
The incidence of diabetes was 3.3% at 1 year and 9.5% at 5 years after the initial health checkup. An increasing number of nonideal CVH metrics have been associated with an increased risk of diabetes. Nonideal BMI, smoking, blood pressure, and total cholesterol level were associated with an increased risk of diabetes. This association was observed both in men and women. A one-point increase in the number of nonideal CVH metric components was associated over 1 year with an increased risk of diabetes.
CVH metrics can stratify the risk of diabetes in young adults with prediabetes. Improving CVH metrics may reduce the risk of developing diabetes.</description><subject>Blood cholesterol</subject><subject>Body mass index</subject><subject>Development and progression</subject><subject>Dextrose</subject><subject>Epidemiology</subject><subject>Exercise</subject><subject>Glucose</subject><subject>Glycosylated hemoglobin</subject><subject>Medicine, Preventive</subject><subject>Prediabetic state</subject><subject>Preventive health services</subject><subject>Teenagers</subject><subject>Youth</subject><issn>0021-972X</issn><issn>1945-7197</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNptkc1v1DAQxS0EokvLlSOyxKWXtP5KHB9X29JWKqIHUOFkzdqTrVESt7aDxH_fhF04VXN40uj33oz0CPnA2RkXnJ27Pow4nPsdOKH0K7LiRtWV5ka_JivGBK-MFj-OyLucfzHGlarlW3Ika6UaxeWKPN0l9AG2WDDTMNKfcRp3dO2nvmQKo6c3s65zji5ACXGk96E80A0kH-JvyG7qIdFrhH7efsGSgvsbUx6Q3qW4S5jz4iqRXhyunJA3HfQZ3x_0mHz_fPltc13dfr262axvK6eYKNVWdqCEkzVvQAo0WrUaVMNReSFQt61usamlqI02bVd3ugXPDRMCDNt6zuQxOd3nPqb4NGEudgjZYd_DiHHKVizuxrTazOinPbqDHm0Yu1gSuAW3a6113Woul8CzF6h5PA7BxRG7MO9fMrgUc07Y2ccUBkh_LGd2ac_u27OH9mbDx8PL03ZA_x__V5d8BvpKlnI</recordid><startdate>20220616</startdate><enddate>20220616</enddate><creator>Suzuki, Yuta</creator><creator>Kaneko, Hidehiro</creator><creator>Okada, Akira</creator><creator>Matsuoka, Satoshi</creator><creator>Itoh, Hidetaka</creator><creator>Fujiu, Katsuhito</creator><creator>Michihata, Nobuaki</creator><creator>Jo, Taisuke</creator><creator>Takeda, Norifumi</creator><creator>Morita, Hiroyuki</creator><creator>Yamaguchi, Satoko</creator><creator>Node, Koichi</creator><creator>Yamauchi, Toshimasa</creator><creator>Yasunaga, Hideo</creator><creator>Komuro, Issei</creator><general>Oxford University Press</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-2553-6170</orcidid><orcidid>https://orcid.org/0000-0002-2534-0939</orcidid></search><sort><creationdate>20220616</creationdate><title>Prediabetes in Young Adults and Its Association With Cardiovascular Health Metrics in the Progression to Diabetes</title><author>Suzuki, Yuta ; Kaneko, Hidehiro ; Okada, Akira ; Matsuoka, Satoshi ; Itoh, Hidetaka ; Fujiu, Katsuhito ; Michihata, Nobuaki ; Jo, Taisuke ; Takeda, Norifumi ; Morita, Hiroyuki ; Yamaguchi, Satoko ; Node, Koichi ; Yamauchi, Toshimasa ; Yasunaga, Hideo ; Komuro, Issei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c402t-b3fa42c3516a32e97487a461e4d22e78878e653259798f5f78ad19022a90bd103</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Blood cholesterol</topic><topic>Body mass index</topic><topic>Development and progression</topic><topic>Dextrose</topic><topic>Epidemiology</topic><topic>Exercise</topic><topic>Glucose</topic><topic>Glycosylated hemoglobin</topic><topic>Medicine, Preventive</topic><topic>Prediabetic state</topic><topic>Preventive health services</topic><topic>Teenagers</topic><topic>Youth</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Suzuki, Yuta</creatorcontrib><creatorcontrib>Kaneko, Hidehiro</creatorcontrib><creatorcontrib>Okada, Akira</creatorcontrib><creatorcontrib>Matsuoka, Satoshi</creatorcontrib><creatorcontrib>Itoh, Hidetaka</creatorcontrib><creatorcontrib>Fujiu, Katsuhito</creatorcontrib><creatorcontrib>Michihata, Nobuaki</creatorcontrib><creatorcontrib>Jo, Taisuke</creatorcontrib><creatorcontrib>Takeda, Norifumi</creatorcontrib><creatorcontrib>Morita, Hiroyuki</creatorcontrib><creatorcontrib>Yamaguchi, Satoko</creatorcontrib><creatorcontrib>Node, Koichi</creatorcontrib><creatorcontrib>Yamauchi, Toshimasa</creatorcontrib><creatorcontrib>Yasunaga, Hideo</creatorcontrib><creatorcontrib>Komuro, Issei</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>The journal of clinical endocrinology and metabolism</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Suzuki, Yuta</au><au>Kaneko, Hidehiro</au><au>Okada, Akira</au><au>Matsuoka, Satoshi</au><au>Itoh, Hidetaka</au><au>Fujiu, Katsuhito</au><au>Michihata, Nobuaki</au><au>Jo, Taisuke</au><au>Takeda, Norifumi</au><au>Morita, Hiroyuki</au><au>Yamaguchi, Satoko</au><au>Node, Koichi</au><au>Yamauchi, Toshimasa</au><au>Yasunaga, Hideo</au><au>Komuro, Issei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediabetes in Young Adults and Its Association With Cardiovascular Health Metrics in the Progression to Diabetes</atitle><jtitle>The journal of clinical endocrinology and metabolism</jtitle><addtitle>J Clin Endocrinol Metab</addtitle><date>2022-06-16</date><risdate>2022</risdate><volume>107</volume><issue>7</issue><spage>1843</spage><epage>1853</epage><pages>1843-1853</pages><issn>0021-972X</issn><eissn>1945-7197</eissn><abstract>The natural history of young adults with prediabetes and its association with cardiovascular health (CVH) metrics in progression to diabetes remain unknown.
We examined the association between CVH metrics and the annual incidence of diabetes in young adults with prediabetes.
This observational cohort study used the JMDC Claims Database. We analyzed 18 908 participants aged 18 to 44 years, with available fasting plasma glucose (FPG) data for 5 consecutive years, and who had prediabetes (FPG 100-125 mg/dL) at the initial health checkup. The ideal CVH metrics were as follows: nonsmoking, body mass index (BMI) less than 25 kg/m2, physical activity at goal, optimal dietary habits, blood pressure less than 120/80 mm Hg, and total cholesterol less than 200 mg/dL. We analyzed the association between CVH metrics and the annual incidence of diabetes. We also examined the relationship between 1-year changes in CVH metrics and the subsequent risk of diabetes.
The incidence of diabetes was 3.3% at 1 year and 9.5% at 5 years after the initial health checkup. An increasing number of nonideal CVH metrics have been associated with an increased risk of diabetes. Nonideal BMI, smoking, blood pressure, and total cholesterol level were associated with an increased risk of diabetes. This association was observed both in men and women. A one-point increase in the number of nonideal CVH metric components was associated over 1 year with an increased risk of diabetes.
CVH metrics can stratify the risk of diabetes in young adults with prediabetes. Improving CVH metrics may reduce the risk of developing diabetes.</abstract><cop>United States</cop><pub>Oxford University Press</pub><pmid>35446413</pmid><doi>10.1210/clinem/dgac247</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-2553-6170</orcidid><orcidid>https://orcid.org/0000-0002-2534-0939</orcidid><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 0021-972X |
| ispartof | The journal of clinical endocrinology and metabolism, 2022-06, Vol.107 (7), p.1843-1853 |
| issn | 0021-972X 1945-7197 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2653269879 |
| source | Oxford University Press Journals All Titles (1996-Current); EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
| subjects | Blood cholesterol Body mass index Development and progression Dextrose Epidemiology Exercise Glucose Glycosylated hemoglobin Medicine, Preventive Prediabetic state Preventive health services Teenagers Youth |
| title | Prediabetes in Young Adults and Its Association With Cardiovascular Health Metrics in the Progression to Diabetes |
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