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Glasser" /><meta name="citation_author_institution" content="Section of General Internal Medicine, University of Chicago, Chicago, Illinois " /><meta name="citation_author" content="Jacob C. Jameson" /><meta name="citation_author_institution" content="Center for Health Decision Science, Harvard T. H. Chan School of Public Health, Boston, Massachusetts" /><meta name="citation_author" content="Elbert S. Huang" /><meta name="citation_author_institution" content="Section of General Internal Medicine, University of Chicago, Chicago, Illinois " /><meta name="citation_author_institution" content="Center for Chronic Disease Research and Policy, University of Chicago, Chicago, Illinois" /><meta name="citation_author" content="Ian M. Kronish" /><meta name="citation_author_institution" content="Center for Behavioral Cardiovascular Health, Columbia University Irving Medical Center, New York, New York" /><meta name="citation_author" content="Stacy Tessler Lindau" /><meta name="citation_author_institution" content="Department of Obstetrics & Gynecology, University of Chicago, Chicago, Illinois" /><meta name="citation_author_institution" content="Department of Medicine-Geriatrics and Palliative Medicine, University of Chicago, Chicago, Illinois" /><meta name="citation_author" content="Monica E. Peek" /><meta name="citation_author_institution" content="Section of General Internal Medicine, University of Chicago, Chicago, Illinois " /><meta name="citation_author_institution" content="MacLean Center for Medical Ethics, University of Chicago, Chicago, Illinois" /><meta name="citation_author_institution" content="Center for the Study of Race, Politics, and Culture, University of Chicago, Chicago, Illinois" /><meta name="citation_author" content="Elizabeth L. Tung" /><meta name="citation_author_institution" content="Section of General Internal Medicine, University of Chicago, Chicago, Illinois " /><meta name="citation_author_institution" content="Center for Center for Diabetes Translation Research, University of Chicago, Chicago, Illinois" /><meta name="citation_author" content="Harold A. Pollack" /><meta name="citation_author_institution" content="Center for Chronic Disease Research and Policy, University of Chicago, Chicago, Illinois" /><meta name="citation_author_institution" content="Crown Family School of Social Work, Policy and Practice, University of Chicago, Chicago, Illinois" /><meta name="citation_author_institution" content="University of Chicago Health Lab, University of Chicago, Chicago, Illinois" /><meta name="citation_author_institution" content="Department of Public Health Sciences, Biological Sciences Division, University of Chicago, Chicago, Illinois" /><meta name="citation_title" content="Male Gender Expressivity and Diagnosis and Treatment of Cardiovascular Disease Risks in Men" /><meta name="citation_firstpage" content="e2441281" /><meta name="citation_lastpage" content="e2441281" /><meta name="citation_doi" content="10.1001/jamanetworkopen.2024.41281" /><meta name="citation_keyword" content="cardiovascular diseases" /><meta name="citation_keyword" content="diabetes mellitus" /><meta name="citation_keyword" content="gene expression" /><meta name="citation_keyword" content="diabetes mellitus, type 2" /><meta name="citation_keyword" content="adolescent" /><meta name="citation_keyword" content="pressure-physical agent" /><meta name="citation_keyword" content="hypertension" /><meta name="citation_keyword" content="cultural factors" /><meta name="citation_keyword" content="hyperlipidemia" /><meta name="citation_abstract" content="<h3>Importance</h3><p>Male gender expressivity (MGE), which reflects prevalent sociocultural pressures to convey masculinity, has been associated with health. Yet, little is known about associations of MGE with the diagnosis and treatment of modifiable cardiovascular disease (CVD) risks.</p><h3>Objective</h3><p>To investigate associations of MGE with modifiable CVD risk diagnoses and treatment in men.</p><h3>Design, Setting, and Participants</h3><p>This population-based cohort study included data from waves I (1994-1995), IV (2008-2009), and V (2016-2018) of the US National Longitudinal Study of Adolescent to Adult Health (Add Health). Participants were male adolescents (age 12-18 years) followed up longitudinally through younger adulthood (age 24-32 years) and adulthood (age 32-42 years). Data were analyzed from January 5, 2023, to August 28, 2024.</p><h3>Exposure</h3><p>Male gender expressivity was quantified in adolescence and younger adulthood using an empirically-derived and validated measurement technique that incorporates participants' responses to existing Add Health survey items to capture how similarly participants behave to same-gendered peers.</p><h3>Main Outcomes and Measures</h3><p>Outcomes included self-reported diagnoses of CVD risk conditions (hypertension, diabetes, or hyperlipidemia) in adult men with elevated blood pressure, hemoglobin A<sub>1c</sub>, or non–high-density lipoprotein cholesterol levels, and self-reported treatment with antihypertensive, hypoglycemic, or lipid-lowering medications in adults reporting hypertension, diabetes, or hyperlipidemia. Multivariable regression was used to examine associations of adolescent and younger adult MGE with adult CVD risk diagnoses and treatment, adjusting for sociodemographic covariates.</p><h3>Results</h3><p>Among 4230 eligible male participants, most were non-Hispanic White (2711 [64%]) and privately insured (3338 [80%]). Their mean (SD) age was 16.14 (1.81) years in adolescence, 29.02 (1.84) years in younger adulthood, and 38.10 (1.95) years in adulthood. Compared with participants whose younger adult MGE was below average, those with higher younger adult MGE were overall less likely to report hypertension (22% vs 26%;<i>P</i> &lt; .001), diabetes (5% vs 8%;<i>P</i> &lt; .001), and hyperlipidemia (19% vs 24%;<i>P</i> &lt; .001) diagnoses and diabetes treatment (3% vs 5%;<i>P</i> = .02) as adults. In multivariable models, every SD increase in adolescent MGE was associated with lower probabilities of adult hypertension treatment (MGE,−0.11; 95% CI, −0.16 to −0.6) and diabetes diagnoses (MGE, −0.15; 95% CI, −0.27 to −0.03). Higher younger adult MGE was associated with lower probabilities of adult hypertension diagnoses (MGE, −0.04; 95% CI, −0.07 to −0.01), hypertension treatment (MGE, −0.07; 95% CI, −0.13 to −0.01), and diabetes treatment (MGE, −0.10; 95% CI, −0.20 to −0.01). Adolescent and younger adult MGE outcomes were not associated with other adult CVD outcomes.</p><h3>Conclusions and Relevance</h3><p>In this cohort study of US males, higher adolescent and younger adult MGE was associated with lower adult hypertension and diabetes diagnoses and treatment. These findings suggest that males with high MGE may bear distinctive risks and correspondingly benefit from tailored public health efforts to prevent downstream CVD.</p>" /><meta name="citation_journal_title" content="JAMA Network Open" /><meta name="citation_journal_abbrev" content="JAMA Netw Open" /><meta name="citation_volume" content="7" /><meta name="citation_issue" content="10" /><meta name="citation_publication_date" content="2024/10/01" /><meta name="citation_publisher" content="American Medical Association" /><meta name="citation_reference" content="citation_title=Real men don’t eat quiche: regulation of gender-expressive choices by men.; citation_author=Gal D; citation_author=Wilkie J; citation_journal_title=Soc Psychol Personal Sci; citation_year=2010; citation_volume=1; citation_issue=4; citation_pages=291-301; " /><meta name="citation_reference" content="citation_title=The Marlboro men don’t cry: understanding the gendered perceptions of people seeking mental health care.; 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Associations of Male Gender Expressivity (MGE) With Adult Diagnosis of Hypertension, Diabetes, and Hyperlipidemia</div><a id="zoi241194f1" class="figure-table-anchor"> </a><div class="figure-table-links right"><a class="view-large figure-table-link is-b desktop-only" path-from-xml="zoi241194f1" href="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194f1_1729266930.9174.png?Expires=1735230885&Signature=goDniN66LRfjyA42aFb29r1Qkqaqd-TsnXfU7q~OEDVYST-s7HRCZ1~CE7XDEUlNX5qb0313pLaiLn8TH6aipI~LdLdhooJyM9F~9Bovhhu-0gGbL9mXvxIboNJi7fTbonlLBbwXKXgmaJ-TC9p67bnz7bFrtQHt06Baxx1yHDuAjsHHYVcbKVIWvtbkYqNiJLrsnkkxdaJV-IgFK4wLwx98kgcRnlwX9bb8uV~garh2zMHjGDkEHu6~HCY8TzBfJy2e~kkT0HmB6h68giEWUcNbv3wheVi3QE6eSlA0k9KRLmgqSeNtWsfYRNU3uuPpVbaITSjg5ROi6uJothJuVw__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" target="_blank" rel="nofollow"><span class="view-large-text">View Large</span></a><a class="download-ppt figure-table-link is-b stats-download-figure-table" path-from-xml="zoi241194f1" href="/downloadimage.aspx?image=https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194f1_1729266930.9174.png?Expires=1735230885&Signature=goDniN66LRfjyA42aFb29r1Qkqaqd-TsnXfU7q~OEDVYST-s7HRCZ1~CE7XDEUlNX5qb0313pLaiLn8TH6aipI~LdLdhooJyM9F~9Bovhhu-0gGbL9mXvxIboNJi7fTbonlLBbwXKXgmaJ-TC9p67bnz7bFrtQHt06Baxx1yHDuAjsHHYVcbKVIWvtbkYqNiJLrsnkkxdaJV-IgFK4wLwx98kgcRnlwX9bb8uV~garh2zMHjGDkEHu6~HCY8TzBfJy2e~kkT0HmB6h68giEWUcNbv3wheVi3QE6eSlA0k9KRLmgqSeNtWsfYRNU3uuPpVbaITSjg5ROi6uJothJuVw__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA&sec=249966594&ar=2825342&imagename=&siteId=214" rel="nofollow"><span class="download-ppt-text">Download</span></a><a class="figure-table-twitter figure-table-link figure-table-social addthis_button_twitter is-b" rel="nofollow"><span class="share-text"> </span></a><a class="figure-table-facebook figure-table-link figure-table-social addthis_button_facebook is-b" rel="nofollow"><span class="share-text"> </span></a></div><div class="figure-table cf cb"><div class="figure-table-image"><a href="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194f1_1729266930.9174.png?Expires=1735230885&Signature=goDniN66LRfjyA42aFb29r1Qkqaqd-TsnXfU7q~OEDVYST-s7HRCZ1~CE7XDEUlNX5qb0313pLaiLn8TH6aipI~LdLdhooJyM9F~9Bovhhu-0gGbL9mXvxIboNJi7fTbonlLBbwXKXgmaJ-TC9p67bnz7bFrtQHt06Baxx1yHDuAjsHHYVcbKVIWvtbkYqNiJLrsnkkxdaJV-IgFK4wLwx98kgcRnlwX9bb8uV~garh2zMHjGDkEHu6~HCY8TzBfJy2e~kkT0HmB6h68giEWUcNbv3wheVi3QE6eSlA0k9KRLmgqSeNtWsfYRNU3uuPpVbaITSjg5ROi6uJothJuVw__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" target="_blank" path-from-xml="zoi241194f1" rel="nofollow"><img data-original="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/m_zoi241194f1_1729266930.9174.png?Expires=1735230885&Signature=klsfnj-UGdvwjDWkcRbRqS9FlSb48tSpaMPanYNaN9Zr0NDykggql71aNKHUE4SNM1~stz3iSwJEVeS4Af5ffauBYB6jpJw2OmPv44j~y1TnCSzS~TmHz0ysMKeNVEYcnKvq73avFP7d3YM-9kOchLPlLT239CeCv9hdWlMGESA3KCPsV1oR1AIBP4aIVHewdQRe~ZS-SVUaz5hV0mIium3qUBZQc2EG0yQ8r37qkQacApu1DQugAQzKE93RNJ4dDdreYdl5H32tBJnRF49rZdjKEt~QOsXrsCq2eyv2-jW2yY4aRMhkpe7m2nc0mu4tBfwHp1aqlHbQP8pb6RLw1A__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" alt="Associations of Male Gender Expressivity (MGE) With Adult Diagnosis of Hypertension, Diabetes, and Hyperlipidemia" class="content-img lazy" path-from-xml="zoi241194f1" /></a></div></div><div class="figure-caption clip-last-child"><p class="para">Higher MGE in adolescence was associated with a lower predicted probability of adult diabetes diagnosis among men with hemoglobin A<sub>1c</sub> levels greater than or equal to 6.5% (to convert to proportion of total hemoglobin, multiply by 0.01). Higher MGE in younger adulthood and higher adolescent-to-younger-adult MGE changes were associated with lower predicted probabilities of adult hypertension diagnosis among men with increased blood pressure (≥130 mm Hg systolic and/or ≥80 mm Hg diastolic). The curves indicate the average marginal effect of male gender expressivity on each outcome. Shaded areas indicate 95% CIs.</p></div></div><div class="figure-table-wrapper thm-bd-top"><div class="figure-label">Figure 2. Associations of Male Gender Expressivity (MGE) With Adult Treatment of Hypertension, Diabetes, and Hyperlipidemia</div><a id="zoi241194f2" class="figure-table-anchor"> </a><div class="figure-table-links right"><a class="view-large figure-table-link is-b desktop-only" path-from-xml="zoi241194f2" href="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194f2_1729266930.92741.png?Expires=1735230885&Signature=lTPxoUayTtYX6peynwCoakUS0rsqKcmxNbZG5SjFbw7bOPbJDE6IGYCvjr832zLc0PmwfEYEz1cTLMdAfvOTVoqjs-7OcPxVgezll-FOMyzypSRpxfF-~QMM-tF6tveTdoew8lJtUCJqc3SWDSoyVkMx7e9jEUqMITOAS4PKWVPqX1u1zCYh80Mv1tka~DIR4epg6RuGW2B3pPlUfAAcQVj1CAlkSNmxgj2yhutIYv6o~Y8tDDbVhytEuo44HW6PSuX5aZfLM0Lu5rfwwY8~O9R9oV94mlOAnyfvVhPF8aK9RirMKsk1BO-Mm7bUoGDWhERhEYQEZOiTwGc0g47vJQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" target="_blank" rel="nofollow"><span class="view-large-text">View Large</span></a><a class="download-ppt figure-table-link is-b stats-download-figure-table" path-from-xml="zoi241194f2" href="/downloadimage.aspx?image=https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194f2_1729266930.92741.png?Expires=1735230885&Signature=lTPxoUayTtYX6peynwCoakUS0rsqKcmxNbZG5SjFbw7bOPbJDE6IGYCvjr832zLc0PmwfEYEz1cTLMdAfvOTVoqjs-7OcPxVgezll-FOMyzypSRpxfF-~QMM-tF6tveTdoew8lJtUCJqc3SWDSoyVkMx7e9jEUqMITOAS4PKWVPqX1u1zCYh80Mv1tka~DIR4epg6RuGW2B3pPlUfAAcQVj1CAlkSNmxgj2yhutIYv6o~Y8tDDbVhytEuo44HW6PSuX5aZfLM0Lu5rfwwY8~O9R9oV94mlOAnyfvVhPF8aK9RirMKsk1BO-Mm7bUoGDWhERhEYQEZOiTwGc0g47vJQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA&sec=249966596&ar=2825342&imagename=&siteId=214" rel="nofollow"><span class="download-ppt-text">Download</span></a><a class="figure-table-twitter figure-table-link figure-table-social addthis_button_twitter is-b" rel="nofollow"><span class="share-text"> </span></a><a class="figure-table-facebook figure-table-link figure-table-social addthis_button_facebook is-b" rel="nofollow"><span class="share-text"> </span></a></div><div class="figure-table cf cb"><div class="figure-table-image"><a href="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194f2_1729266930.92741.png?Expires=1735230885&Signature=lTPxoUayTtYX6peynwCoakUS0rsqKcmxNbZG5SjFbw7bOPbJDE6IGYCvjr832zLc0PmwfEYEz1cTLMdAfvOTVoqjs-7OcPxVgezll-FOMyzypSRpxfF-~QMM-tF6tveTdoew8lJtUCJqc3SWDSoyVkMx7e9jEUqMITOAS4PKWVPqX1u1zCYh80Mv1tka~DIR4epg6RuGW2B3pPlUfAAcQVj1CAlkSNmxgj2yhutIYv6o~Y8tDDbVhytEuo44HW6PSuX5aZfLM0Lu5rfwwY8~O9R9oV94mlOAnyfvVhPF8aK9RirMKsk1BO-Mm7bUoGDWhERhEYQEZOiTwGc0g47vJQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" target="_blank" path-from-xml="zoi241194f2" rel="nofollow"><img data-original="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/m_zoi241194f2_1729266930.92741.png?Expires=1735230885&Signature=YBVGKR5dhdqebtMGRXKqrths5KkkzP9cFX96r32r~RowGmXcvOgqlDf5s92nfBJ14CUhPXim2xzCgHq645sO1B9fRXHC0rhCUkWn1FG-ttK8MdC3eHZbSXefcRP4b2NCYrQwGJVyXbTJpTrpG-sF3OvsMiA5w920kXCLm4-fvdwwqbXTd6jFzkMYXpsx4-2KAivC45lN5Pe6Z8sJET1uJk6wzEbJbpTRpQo56ZDAk1HNIbzLpPDGSrNq0CY1eodRCmfOa8b-5HrSMuqgaLnMpx71yPtR-E8gmKG~ZA3WnHNqnrS3pbsKuXzLZ7qsnL6ucgkH2iRsIgN-rxc2COc4GQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" alt="Associations of Male Gender Expressivity (MGE) With Adult Treatment of Hypertension, Diabetes, and Hyperlipidemia" class="content-img lazy" path-from-xml="zoi241194f2" /></a></div></div><div class="figure-caption clip-last-child"><p class="para">Higher MGE in adolescence was associated with a lower predicted probability of adult treatment of hypertension among men who reported hypertension diagnoses. Higher MGE in younger adulthood was associated with a lower predicted probability of adult treatment of hypertension and diabetes among men who reported diagnoses of hypertension and diabetes. The curves indicate the average marginal effect of male gender expressivity on each outcome. Shaded areas indicate 95% CIs.</p></div></div> </div> <div class="widget-ArticleFiguresAndTables widget-instance-AMA_Article_Tables_Tab"> <div class="figure-table-wrapper thm-bd-top"><div class="table-label">Table 1. Demographic Characteristics of Males Included in the Analytic Sample</div><a class="figure-table-anchor" id="zoi241194t1"> </a><div class="figure-table-links right"><a class="view-large figure-table-link is-b desktop-only" path-from-xml="zoi241194t1" href="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194t1_1729266930.89741.png?Expires=1735230885&Signature=H8TSBnnwFLSa5vpA8VYkgP2qfcmnHVfc-qximzfe-vgbe4f3bBYh6c6gvHKew-F7JrdmSgH40Vg6UAzsXcxfgYRd4m0mjM8czfMub9hldQvz4Lw1tcLGRtvrWvBgPHGAJ3gfayD8FN92Cu0o3zx1jdNhi3sI5f-yiApniAbX5vajzarR0EL7Dc2YRFO9Muy3~dEONvEvpK7wKiDbY-M7s0QbyKbeLhduMdXooKiuKiKy31EfCjp~yuKCNoouaEbIMd9lFrRWR0-I8kSd3QUruroTT03Gtdom3jNNdhvS9MmRoURh0wpBA7xO7xEb9ARuSsruN2B1wyioRwlgjJSGmQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" target="_blank" rel="nofollow"><span class="view-large-text">View Large</span></a><a class="download-ppt figure-table-link is-b stats-download-figure-table" path-from-xml="zoi241194t1" href="/downloadimage.aspx?image=https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194t1_1729266930.89741.png?Expires=1735230885&Signature=H8TSBnnwFLSa5vpA8VYkgP2qfcmnHVfc-qximzfe-vgbe4f3bBYh6c6gvHKew-F7JrdmSgH40Vg6UAzsXcxfgYRd4m0mjM8czfMub9hldQvz4Lw1tcLGRtvrWvBgPHGAJ3gfayD8FN92Cu0o3zx1jdNhi3sI5f-yiApniAbX5vajzarR0EL7Dc2YRFO9Muy3~dEONvEvpK7wKiDbY-M7s0QbyKbeLhduMdXooKiuKiKy31EfCjp~yuKCNoouaEbIMd9lFrRWR0-I8kSd3QUruroTT03Gtdom3jNNdhvS9MmRoURh0wpBA7xO7xEb9ARuSsruN2B1wyioRwlgjJSGmQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA&sec=249966591&ar=2825342&imagename=&siteId=214" rel="nofollow"><span class="download-ppt-text">Download</span></a><a class="figure-table-twitter figure-table-link figure-table-social addthis_button_twitter is-b" rel="nofollow"><span class="share-text"> </span></a><a class="figure-table-facebook figure-table-link figure-table-social addthis_button_facebook is-b" rel="nofollow"><span class="share-text"> </span></a></div><div class="figure-table cf cb"><div class="figure-table-image"><a href="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194t1_1729266930.89741.png?Expires=1735230885&Signature=H8TSBnnwFLSa5vpA8VYkgP2qfcmnHVfc-qximzfe-vgbe4f3bBYh6c6gvHKew-F7JrdmSgH40Vg6UAzsXcxfgYRd4m0mjM8czfMub9hldQvz4Lw1tcLGRtvrWvBgPHGAJ3gfayD8FN92Cu0o3zx1jdNhi3sI5f-yiApniAbX5vajzarR0EL7Dc2YRFO9Muy3~dEONvEvpK7wKiDbY-M7s0QbyKbeLhduMdXooKiuKiKy31EfCjp~yuKCNoouaEbIMd9lFrRWR0-I8kSd3QUruroTT03Gtdom3jNNdhvS9MmRoURh0wpBA7xO7xEb9ARuSsruN2B1wyioRwlgjJSGmQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" target="_blank" path-from-xml="zoi241194t1" rel="nofollow"><img data-original="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/m_zoi241194t1_1729266930.89741.png?Expires=1735230885&Signature=xWgBQbr11EYlXolCmPWkE4cccPynaQcksPB1SLs-jOWR7DT6bRhleNFdIrpqklz5r699Jx-H35ln4CfGYWqpm3ZTnTOrsyZG9VTj-RkkbElnFtnJLdEGV84hLn5zSdu4QXnIrVzdFY0cdux7GqNaaPbvSWNnKAK9-7DiRhEJV9c1~71qb9rRydah2kdVR968y6eKcs0A7zfB0-hG6heC4~3ohCSBGsLVTM2pW2dybHeVg9FMO3lfWQVzRSChDfm52VbsxXh5~olmfFGoQ6OIQTq11-1vg10fopgkxkYb~Sx2au4BvCBM7vPv5gdRTS1fySzlG3jCNWq6OkRGnZzycQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" alt="Demographic Characteristics of Males Included in the Analytic Sample" class="content-img lazy" path-from-xml="zoi241194t1" /></a></div></div><div class="table-caption"></div></div><div class="figure-table-wrapper thm-bd-top"><div class="table-label">Table 2. Average Marginal Effects Coefficients Estimating Associations Between MGE and Adult Diagnosis, Treatment, and Biomeasure Evidence of Adult CVD Risks<sup>a</sup></div><a class="figure-table-anchor" id="zoi241194t2"> </a><div class="figure-table-links right"><a class="view-large figure-table-link is-b desktop-only" path-from-xml="zoi241194t2" href="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194t2_1729266930.90741.png?Expires=1735230885&Signature=0UcnGdIrNI49Ddieqj9Kehl9AF4hmM9XmemX9-srz9OyyIcP2ID96dKLgkK3ZFjOxtbbKF4Rph5tZOV0q6~aT2R1AIUQjGHLhNHRcuCw-Yhzigjl3iuWNVZQdmGudBTIiNpar20JcAHnYleukCI-y0phkk5FwNYCYzF9qJA6U~pI~C8Xtn4vjDfFyz5G2dLZe1qcs-YOemWd~e2T4HNCcUQpl~O2AVCJgLL1-UA2nGbWJg-dsIYPjg-c2G5Bj8ncwcwn-FmSzcnwphcH9fD9sLp69QaG9AQLJ40mtShCMHu1YpQjCP3CoLeg2bQ~J73ju-6PK9arOc9FKmYBxG7iRg__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" target="_blank" rel="nofollow"><span class="view-large-text">View Large</span></a><a class="download-ppt figure-table-link is-b 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class="share-text"> </span></a></div><div class="figure-table cf cb"><div class="figure-table-image"><a href="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194t2_1729266930.90741.png?Expires=1735230885&Signature=0UcnGdIrNI49Ddieqj9Kehl9AF4hmM9XmemX9-srz9OyyIcP2ID96dKLgkK3ZFjOxtbbKF4Rph5tZOV0q6~aT2R1AIUQjGHLhNHRcuCw-Yhzigjl3iuWNVZQdmGudBTIiNpar20JcAHnYleukCI-y0phkk5FwNYCYzF9qJA6U~pI~C8Xtn4vjDfFyz5G2dLZe1qcs-YOemWd~e2T4HNCcUQpl~O2AVCJgLL1-UA2nGbWJg-dsIYPjg-c2G5Bj8ncwcwn-FmSzcnwphcH9fD9sLp69QaG9AQLJ40mtShCMHu1YpQjCP3CoLeg2bQ~J73ju-6PK9arOc9FKmYBxG7iRg__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" target="_blank" path-from-xml="zoi241194t2" rel="nofollow"><img data-original="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/m_zoi241194t2_1729266930.90741.png?Expires=1735230885&Signature=MjYZFDBexKLddIGE9gWyJrt1rLGmMvtesaD8tAodRTgINv4S~14LeH54k71XmanB3LIxmgxqUavkJTONUAlrhFxeCBoKCIF1rTWSg60CaiUGIPM86pjRR2FbyefPJuJtQ1vRi75o7wbGjLqjBEXkhD9ux3LSUR181G0OCfiI5rVuz39FMRmaJ8pT~0lywmkKXke8EnlQ4ihEqxPjoWhoJLqFRAgg8REw7b0SKA2mwjbyzXFls8Vu9LocRVjZte~qGWyTwxTsY0UC0xsK8Zf7Ol8IPlwZoWHMGMvvHvKGT92HwE4MJVL7cnSgu9aTEPxbQ7p04wXZ1AWlbreSvmkRcQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" alt="Average Marginal Effects Coefficients Estimating Associations Between MGE and Adult Diagnosis, Treatment, and Biomeasure Evidence of Adult CVD Risksa" class="content-img lazy" path-from-xml="zoi241194t2" /></a></div></div><div class="table-caption"></div></div> </div> </div> <div id="multimedia-tab" class="resource-tab js-resource-tab multimedia-tab need-jobs-ad"> </div> <div id="supplemental-tab" class="resource-tab js-resource-tab supplemental-tab need-jobs-ad"> <div class="widget-ArticleDataSupplements widget-instance-AMA_Data_Supplements_Tab"> <div class="supplement"> <a id="note-ZOI241194-1" href="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194supp1_prod_1729266930.73967.pdf?Expires=1735994843&Signature=fnsV2Jr0lE76cAvzgLX4nmBd6pZ-LTcxrIwy-y~NRdM2RmtVCepSrvJ1Ijr4zonWmT15eG45vLjDoqZWViE6iIMST8pdnIiKmZ28l7Z3FclLINrg0Z-JktLEWG6u7CFvRv76bhRsa5i9IQuI6yPs77NVpU6ordzg04vwPn1rHQAgIt4SPFUP9jeosGic35KrWSTl7GJPps-wSzf~cSxU0AhU2rQCGpdM5gbhdyq5rMsFcmzcjEkbpOu4DECvEEDG3ruKOKV7pxhc2oCO66iooO8Yn3fUzOS1-esL7~-7D~4Crk7iAty9ZI~pANJ7AQZlc8XmvcgUYZZrhYekpbIGlA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" class="supplement-link supplement-download stats-supplement-download" rel="nofollow"> <div class="pdf supplement-type"></div> <div class="supplement-title"><span class="title-label">Supplement 1.</span><p class="para"><strong>eFigure.</strong> Survey Participation and Follow-Up</p><p class="para"><strong>eTable 1.</strong> Survey Items Used to Create MGE Variables in A) Waves I and B) Wave IV</p><p class="para"><strong>eTable 2.</strong> Item Missingness of Covariates</p><p class="para"><strong>eTable 3.</strong> Sensitivity Analysis of Missing Data: Comparison of Participants With and Without Complete Data, Add Health Waves I (1994-1995), IV (2008-2009), and V (2016-2018)</p><p class="para"><strong>eTable 4.</strong> Average Marginal Effects Coefficients <i>(dy/dx)</i> Estimating Associations Between MGE and Adult Diagnoses, Treatment, and Biomeasure Evidence of Hypertension Using Alternate Classification</p><p class="para"><strong>eTable 5.</strong> Marginal Effects Coefficients <i>(dy/dx)</i> Estimating Associations Between MGE and Adult Treatment of Modifiable CVD Risks</p></div> </a> </div> <div class="supplement"> <a id="note-ZOI241194-1" href="https://cdn.jamanetwork.com/ama/content_public/journal/jamanetworkopen/939467/zoi241194supp2_prod_1729266930.75467.pdf?Expires=1735994843&Signature=duiI2ggm-pMgmslvTfmQwl8OYEuZv8bVrX402ee~eYJmpQOogDGrKd-LDJAJ0xXIFCEDDlterFwt4Ur6prODnpI2cZSsxyrVlpTW~~BCrocJZJPf0Sp3e4cedWnl9wLfcxzQU0LaWf4pYZikqbrFvmoDeVOxgwzDRNiY34rmT~C1R~SmXzBqC0~zck3Zqslh7CmZIBEWxmY7YDaHldO6qLmYJDlhJUyygNt-ecxlyw76ZXgQugyYSvXHW9TeEwfyMvifOmA4ZCK8GZk29UCg8F0yCGIOOQxyFOBkwgIWIKFRx7YmxRjpTypSNNenSnYCy9EwmwwtqhdSDANMDyHhmA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" class="supplement-link supplement-download stats-supplement-download" rel="nofollow"> <div class="pdf supplement-type"></div> <div class="supplement-title"><span class="title-label">Supplement 2.</span><p class="para"><strong>Data Sharing Statement</strong></p></div> </a> </div> </div> </div> <div id="references-tab" class="resource-tab js-resource-tab references-tab need-jobs-ad"> <div class="references-wrap"> <div class="widget-SectionDisplay 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<span class="hide tagmanagervalue" data-attribute="articleId" data-value="2825342" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="arrArticleAuthor" data-value="Nathaniel%20J.%C2%A0Glasser%2C%C2%A0MD%2C%20MPP,Jacob%20C.%C2%A0Jameson%2C%C2%A0MS,Elbert%20S.%C2%A0Huang%2C%C2%A0MD%2C%20MPH,Ian%20M.%C2%A0Kronish%2C%C2%A0MD%2C%20MPH,Stacy%20Tessler%C2%A0Lindau%2C%C2%A0MD%2C%20MAPP,Monica%20E.%C2%A0Peek%2C%C2%A0MD%2C%20MPH%2C%20MS,Elizabeth%20L.%C2%A0Tung%2C%C2%A0MD%2C%20MS,Harold%20A.%C2%A0Pollack%2C%C2%A0PhD%2C%20MPP" data-type="array"></span> <span class="hide tagmanagervalue" data-attribute="articleDOI" data-value="10.1001/jamanetworkopen.2024.41281" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="articleTitle" data-value="Male Gender Expressivity and Diagnosis and Treatment of Cardiovascular Disease Risks in Men" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="type" data-value="Original Investigation" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="thematicLabel" data-value="Public Health" data-type="array"></span> <span class="hide tagmanagervalue" data-attribute="issueVolume" data-value="7" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="issueNo" data-value="10" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="publishDate" data-value="October 1, 2024" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="topics" data-value="Public Health, Treatment Adherence, LGBTQIA Medicine, Equity, Diversity, and Inclusion, Cardiology, Dyslipidemia, Diabetes, Cardiovascular Risk Factors, Diabetes and Endocrinology, Hypertension, Genetics and Genomics, Adolescent Medicine, Pediatrics" data-type="array"></span> <span class="hide tagmanagervalue" data-attribute="topicCode" data-value="42128, 5942, 46327, 46387, 5548, 5721, 6262, 42101, 44011, 5697, 5664, 5495, 5843" data-type="array"></span> <span class="hide tagmanagervalue" data-attribute="category" data-value="Research" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="journalClub" data-value="No" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="contentStatus" data-value="Open Access" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="articlePubState" data-value="Final" data-type="string"></span> <span class="hide tagmanagervalue" data-attribute="contentMedium" data-value="Article" data-type="string"></span> <div class="meta-article-type-wrap"> <div class="meta-article-type thm-col">Original Investigation </div> <div class="meta-super-class">Public Health</div> </div> <div class="meta-date"><span class="epub"><span class="month">October </span><span class="day">25, </span><span class="year">2024</span></span></div> <div class="meta-article-title-wrap"> <h1 class="meta-article-title ">Male Gender Expressivity and Diagnosis and Treatment of Cardiovascular Disease Risks in Men</h1> </div> <div class="meta-authors"> <span class="meta-authors--limited"><span class="wi-fullname brand-fg"><a href="/searchresults?author=Nathaniel+J.+Glasser&q=Nathaniel+J.+Glasser" rel=nofollow target="_blank">Nathaniel J. Glasser, MD, MPP<sup>1</sup></a></span><span class='al-author-delim'>; </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Jacob+C.+Jameson&q=Jacob+C.+Jameson" rel=nofollow target="_blank">Jacob C. Jameson, MS<sup>2</sup></a></span><span class='al-author-delim'>; </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Elbert+S.+Huang&q=Elbert+S.+Huang" rel=nofollow target="_blank">Elbert S. Huang, MD, MPH<sup>1,3</sup></a></span>; <a class="meta-authors--etal td-u stats-meta-authors--etal">et al</a></span> <span class="meta-authors--remaining"><span class="wi-fullname brand-fg"><a href="/searchresults?author=Ian+M.+Kronish&q=Ian+M.+Kronish" rel=nofollow target="_blank">Ian M. Kronish, MD, MPH<sup>4</sup></a></span><span class='al-author-delim'>; </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Stacy+Tessler+Lindau&q=Stacy+Tessler+Lindau" rel=nofollow target="_blank">Stacy Tessler Lindau, MD, MAPP<sup>5,6</sup></a></span><span class='al-author-delim'>; </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Monica+E.+Peek&q=Monica+E.+Peek" rel=nofollow target="_blank">Monica E. Peek, MD, MPH, MS<sup>1,7,8</sup></a></span><span class='al-author-delim'>; </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Elizabeth+L.+Tung&q=Elizabeth+L.+Tung" rel=nofollow target="_blank">Elizabeth L. Tung, MD, MS<sup>1,9</sup></a></span><span class='al-author-delim'>; </span><span class="wi-fullname brand-fg"><a href="/searchresults?author=Harold+A.+Pollack&q=Harold+A.+Pollack" rel=nofollow target="_blank">Harold A. Pollack, PhD, MPP<sup>3,10,11,12</sup></a></span></span> </div> <div class="meta-author"> <a class="meta-author-title is-b stats-meta-author-toggle" data-tog-target=".meta-author-content">Author Affiliations</a> <a class="meta-articleinfo-jumplink section-jump-link scroll-to stats-scroll-to-articleinfo" data-tab-toggle=".tab-nav-full-text" href="#249966611">Article Information</a> <div class="meta-author-content"> <ul class="meta-author-affiliations"> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>1</sup>Section of General Internal Medicine, University of Chicago, Chicago, Illinois </div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>2</sup>Center for Health Decision Science, Harvard T. H. Chan School of Public Health, Boston, Massachusetts</div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>3</sup>Center for Chronic Disease Research and Policy, University of Chicago, Chicago, Illinois</div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>4</sup>Center for Behavioral Cardiovascular Health, Columbia University Irving Medical Center, New York, New York</div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>5</sup>Department of Obstetrics & Gynecology, University of Chicago, Chicago, Illinois</div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>6</sup>Department of Medicine-Geriatrics and Palliative Medicine, University of Chicago, Chicago, Illinois</div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>7</sup>MacLean Center for Medical Ethics, University of Chicago, Chicago, Illinois</div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>8</sup>Center for the Study of Race, Politics, and Culture, University of Chicago, Chicago, Illinois</div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>9</sup>Center for Center for Diabetes Translation Research, University of Chicago, Chicago, Illinois</div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>10</sup>Crown Family School of Social Work, Policy and Practice, University of Chicago, Chicago, Illinois</div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>11</sup>University of Chicago Health Lab, University of Chicago, Chicago, Illinois</div> </li> <li class="meta-author-affiliation"> <div class="meta-author-name"><sup>12</sup>Department of Public Health Sciences, Biological Sciences Division, University of Chicago, Chicago, Illinois</div> </li> </ul> </div> </div> <div class="meta-citation-wrap"> <span class="meta-citation-journal-name">JAMA Netw Open. </span><span class="meta-citation"> 2024;7(10):e2441281. doi:10.1001/jamanetworkopen.2024.41281</span> </div> </div> <div class="widget-EditorsChoice widget-instance-AMA_EditorsChoice_Links"> </div> <div class="widget-LinkedContentToolbar widget-instance-AMA_LinkedContentToolbar"> <div class="linked-content-toolbar"> <div class="hidden js-search-open-multimedia-by-default" showContentByDefault="False"></div> <div class="linked-content-controls"> <a class="linked-content-trigger td-n stats-graphical-abstract" href="#graphical-abstract-tab"> <i class="icon-visual-abstract"><span class="sr-t">visual abstract icon</span></i> <div class="trigger-text d-ib va-m ta-l fw-5">Visual <div>Abstract</div></div> </a> <a class="linked-content-trigger td-n stats-editorial-comment" href="#editorial-comment-tab"> <i class="icon-document"><span class="sr-t">editorial comment icon</span></i> <div class="trigger-text d-ib va-m ta-l fw-5">Editorial 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linked-listen-to-this-article-tab"> <div class="widget-AudioPlayer widget-instance-AMA_LinkedContentToolbar_PlatformAudioPlayer_ListenToThisArticle"> </div> </div> <div id="more-multimedia-tab" class="linked-content-tab more-multimedia-tab"> </div> </div> </div> </div> <div class="widget-ArticleFulltext widget-instance-AMA_Article_FullText_Widget"> <div class="article-full-text" data-userHasAccess="True"> <a class="article-section-id-anchor" id="249966565"></a> <span class="heading-text thm-col h3 cb section-type-keyPoints decorated-hed sb-sc ">Key Points</span><p><strong>Question</strong> <span>What is the association of male gender expressivity (MGE)—a measure reflecting sociocultural pressures to convey male gender identity—with the diagnosis and treatment of modifiable cardiovascular disease risks?</span></p><p><strong>Findings</strong> <span>This cohort study involving 4230 male participants found that every SD increase in participants’ adolescent MGE was associated with an 11-percentage point lower probability of adult hypertension treatment and 15-percentage point lower probability of adult diabetes diagnosis. Higher younger adult MGE was associated with lower adult probabilities of hypertension diagnosis, hypertension treatment, and diabetes treatment.</span></p><p><strong>Meaning</strong> <span>The findings of this study suggest that sociocultural pressures to convey male gender may be associated with suboptimal cardiovascular disease outcomes through decreased risk diagnosis and treatment.</span></p> <a class="article-section-id-anchor" id="249966566"></a> <div class="h3 cb section-type-abstract decorated-hed "> <div class="heading-text thm-col sb-sc"> Abstract </div> </div> <p><strong>Importance</strong> <span>Male gender expressivity (MGE), which reflects prevalent sociocultural pressures to convey masculinity, has been associated with health. Yet, little is known about associations of MGE with the diagnosis and treatment of modifiable cardiovascular disease (CVD) risks.</span></p><p><strong>Objective</strong> <span>To investigate associations of MGE with modifiable CVD risk diagnoses and treatment in men.</span></p><p><strong>Design, Setting, and Participants</strong> <span>This population-based cohort study included data from waves I (1994-1995), IV (2008-2009), and V (2016-2018) of the US National Longitudinal Study of Adolescent to Adult Health (Add Health). Participants were male adolescents (age 12-18 years) followed up longitudinally through younger adulthood (age 24-32 years) and adulthood (age 32-42 years). Data were analyzed from January 5, 2023, to August 28, 2024.</span></p><p><strong>Exposure</strong> <span>Male gender expressivity was quantified in adolescence and younger adulthood using an empirically-derived and validated measurement technique that incorporates participants' responses to existing Add Health survey items to capture how similarly participants behave to same-gendered peers.</span></p><p><strong>Main Outcomes and Measures</strong> <span>Outcomes included self-reported diagnoses of CVD risk conditions (hypertension, diabetes, or hyperlipidemia) in adult men with elevated blood pressure, hemoglobin A<sub>1c</sub>, or non–high-density lipoprotein cholesterol levels, and self-reported treatment with antihypertensive, hypoglycemic, or lipid-lowering medications in adults reporting hypertension, diabetes, or hyperlipidemia. Multivariable regression was used to examine associations of adolescent and younger adult MGE with adult CVD risk diagnoses and treatment, adjusting for sociodemographic covariates.</span></p><p><strong>Results</strong> <span>Among 4230 eligible male participants, most were non-Hispanic White (2711 [64%]) and privately insured (3338 [80%]). Their mean (SD) age was 16.14 (1.81) years in adolescence, 29.02 (1.84) years in younger adulthood, and 38.10 (1.95) years in adulthood. Compared with participants whose younger adult MGE was below average, those with higher younger adult MGE were overall less likely to report hypertension (22% vs 26%; <i>P</i> < .001), diabetes (5% vs 8%; <i>P</i> < .001), and hyperlipidemia (19% vs 24%; <i>P</i> < .001) diagnoses and diabetes treatment (3% vs 5%; <i>P</i> = .02) as adults. In multivariable models, every SD increase in adolescent MGE was associated with lower probabilities of adult hypertension treatment (MGE,−0.11; 95% CI, −0.16 to −0.6) and diabetes diagnoses (MGE, −0.15; 95% CI, −0.27 to −0.03). Higher younger adult MGE was associated with lower probabilities of adult hypertension diagnoses (MGE, −0.04; 95% CI, −0.07 to −0.01), hypertension treatment (MGE, −0.07; 95% CI, −0.13 to −0.01), and diabetes treatment (MGE, −0.10; 95% CI, −0.20 to −0.01). Adolescent and younger adult MGE outcomes were not associated with other adult CVD outcomes.</span></p><p><strong>Conclusions and Relevance</strong> <span>In this cohort study of US males, higher adolescent and younger adult MGE was associated with lower adult hypertension and diabetes diagnoses and treatment. These findings suggest that males with high MGE may bear distinctive risks and correspondingly benefit from tailored public health efforts to prevent downstream CVD.</span></p> <div class="movable-ad-target bta"> </div> <a class="article-section-id-anchor" id="249966571"></a> <div class="h3 cb section-type-section "> <div class="heading-text thm-col sb-sc"> Introduction </div> </div> <a class="article-section-id-anchor" id="249966572"></a> <p class="para">Prevalent sociocultural pressures (eg, narratives, norms, values, and expectations) to convey male gender identity have been shown to shape boys’ and men’s behaviors, preferences, and beliefs.<sup><a href="#zoi241194r1" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">1</a></sup><sup>-<a href="#zoi241194r1" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">4</a></sup> These pressures frequently encourage displays of self-reliance, emotional control, and strength while discouraging help-seeking, vulnerability, or weakness.<sup><a href="#zoi241194r1" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">1</a></sup><sup>-<a href="#zoi241194r1" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">7</a></sup> The degree to which boys and men adopt behaviors similar to those of same-gendered peers (and different from those of other genders)—their male gender expressivity (MGE)—has been understood and measured as a proxy for the association between these pressures and their behaviors and outlook.<sup><a href="#zoi241194r8" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">8</a></sup><sup>-<a href="#zoi241194r8" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">10</a></sup> Increasingly, MGE and related measures have been linked to health behaviors,<sup><a href="#zoi241194r11" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">11</a></sup> including substance use<sup><a href="#zoi241194r10" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">10</a></sup><sup>-<a href="#zoi241194r10" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">13</a></sup> and COVID-19 prevention.<sup><a href="#zoi241194r14" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">14</a></sup> Previous analyses have observed that individuals’ MGE at developmental stages as early as adolescence might forecast downstream outcomes, such as tobacco use and weight control.<sup><a href="#zoi241194r10" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">10</a></sup><sup>,<a href="#zoi241194r11" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">11</a>,<a href="#zoi241194r13" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">13</a></sup><sup>,<a href="#zoi241194r15" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">15</a></sup><sup>,<a href="#zoi241194r16" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">16</a></sup></p> <a class="article-section-id-anchor" id="249966573"></a> <p class="para">Cardiovascular disease (CVD), a leading cause of morbidity and mortality in the US and globally,<sup><a href="#zoi241194r17" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">17</a></sup><sup>-<a href="#zoi241194r17" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">20</a></sup> results in well-established sex- and gender-based health disparities.<sup><a href="#zoi241194r21" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">21</a></sup><sup>-<a href="#zoi241194r21" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">26</a></sup> Yet, except for several small, primarily qualitative inquiries, we know of no studies examining associations between MGE and CVD outcomes in a nationally representative US sample.<sup><a href="#zoi241194r4" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">4</a></sup><sup>,<a href="#zoi241194r27" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">27</a></sup><sup>-<a href="#zoi241194r27" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">29</a></sup> The qualitative studies provide evidence of how various context-specific pressures to convey male gender appear to influence help-seeking for CVD-related symptoms and diagnoses among men, often leading to suppressed help-seeking efforts.<sup><a href="#zoi241194r4" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">4</a></sup><sup>,<a href="#zoi241194r27" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">27</a></sup><sup>,<a href="#zoi241194r28" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">28</a></sup></p> <a class="article-section-id-anchor" id="249966574"></a> <p class="para">Further evidence suggests that even in younger adults, including those with only borderline evidence of CVD risk factors, such as hypertension, diabetes, and hyperlipidemia, the presence of these risk factors may be associated with increased downstream CVD-related morbidity and mortality, underscoring the clinical and public health importance of early recognition and treatment.<sup><a href="#zoi241194r30" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">30</a></sup><sup>-<a href="#zoi241194r30" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">41</a></sup> Many guidelines resultingly now recommend universal screening for hypertension and hyperlipidemia in children and adolescents<sup><a href="#zoi241194r42" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">42</a></sup><sup>,<a href="#zoi241194r43" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">43</a></sup> in addition to broadly targeted screening for hypertension, diabetes, and hyperlipidemia in adults.<sup><a href="#zoi241194r44" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">44</a></sup><sup>-<a href="#zoi241194r44" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">47</a></sup> Despite this emphasis on early detection, evidence suggests that up to 75% of younger adults with uncontrolled CVD risk factors are unaware they have these conditions.<sup><a href="#zoi241194r40" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">40</a></sup><sup>,<a href="#zoi241194r41" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">41</a></sup> Prior studies suggest that younger age, lack of insurance, and no regular source of preventive health care are generally associated with lower CVD risk awareness.<sup><a href="#zoi241194r40" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">40</a></sup><sup>,<a href="#zoi241194r41" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">41</a>,<a href="#zoi241194r48" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">48</a></sup><sup>-<a href="#zoi241194r48" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">50</a></sup></p> <a class="article-section-id-anchor" id="249966575"></a> <p class="para">We used data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to investigate associations of adolescent and younger adult MGE with adult diagnoses and treatment of modifiable CVD risks, namely hypertension, diabetes, and hyperlipidemia. Existing, primarily qualitative, evidence suggests that boys and men experience especially strong social pressures to portray gender-congruent behaviors that emphasize dominance and deny vulnerability,<sup><a href="#zoi241194r3" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">3</a></sup><sup>,<a href="#zoi241194r4" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">4</a>,<a href="#zoi241194r6" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">6</a></sup><sup>,<a href="#zoi241194r51" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">51</a></sup> including through the avoidance of preventive health care and rejection of recommended medical therapies.<sup><a href="#zoi241194r7" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">7</a></sup><sup>,<a href="#zoi241194r14" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">14</a></sup><sup>,<a href="#zoi241194r52" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">52</a></sup><sup>-<a href="#zoi241194r52" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">54</a></sup> We thus hypothesized that increased MGE is associated with lower diagnoses and treatment of CVD risks.</p> <a class="article-section-id-anchor" id="249966576"></a> <div class="h3 cb section-type-section "> <div class="heading-text thm-col sb-sc"> Methods </div> </div> <a class="article-section-id-anchor" id="249966577"></a> <p class="para">This longitudinal cohort study used data from waves I (1994-1995), IV (2008-2009), and V (2016-2018) of Add Health. Participants were adolescents (age 12-18 years) in wave I, younger adults (age 24-32 years) in wave IV, and adults (age 32-42 years) in wave V. Wave I participants (n = 20 745; 10 263 male) comprised a randomly selected, nationally representative probability sample of US adolescents. The sample included in the present analysis was restricted to respondents followed up through waves IV (n = 15 197; 7341 male) and V (n = 12 300; 5324 males) who participated and identified as male in all 3 waves (n = 4230) (eFigure in <a class="supplement-link section-jump-link" data-tab-toggle=".tab-nav-supplemental" href="#note-ZOI241194-1">Supplement 1</a>). A smaller subset that participated in biomeasure collection in wave V (n = 5381; 2132 males) was included in analyses involving biomeasure and medication use data. Add Health participants provided written informed consent for participation in all aspects of Add Health in accordance with the University of North Carolina School of Public Health Institutional Review Board. This secondary analysis of previously collected Add Health data was approved by the University of Chicago Institutional Review Board. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (<a href="http://www.equator-network.org/reporting-guidelines/strobe/">STROBE</a>) reporting guideline<sup><a href="#zoi241194r55" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">55</a></sup></p> <a class="article-section-id-anchor" id="249966578"></a> <p class="para">To quantify MGE, we used a reliable valid measure developed from Add Health data and applied in multiple prior analyses.<sup><a href="#zoi241194r9" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">9</a></sup><sup>-<a href="#zoi241194r9" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">11</a>,<a href="#zoi241194r13" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">13</a></sup> The measure uses participants’ responses to the 25 wave I and 22 wave IV Add Health survey items answered most differently by female vs male participants (eTable 1 in <a class="supplement-link section-jump-link" data-tab-toggle=".tab-nav-supplemental" href="#note-ZOI241194-1">Supplement 1</a>). Participants’ responses were then used in logistic regression models predicting their reported gender. Male participants’ scores thus allowed us to quantify their MGE by capturing how similarly they responded to same-gendered peers on survey items that elicited the largest gender-based differences in responses. Predicted probabilities were standardized using <i>z</i> scores across male participants in each wave such that 0 represented the mean, +1 represented 1 SD above, and so on. Empirically derived, the measure does not project contemporary norms onto noncontemporary samples. Instead, participants’ responses themselves are used to construct the measure.<sup><a href="#zoi241194r10" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">10</a></sup></p> <a class="article-section-id-anchor" id="249966579"></a> <p class="para">Given prior findings that MGE typically develops in adolescence but evolves into younger adulthood, separate MGE scores were calculated for adolescence and younger adulthood.<sup><a href="#zoi241194r9" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">9</a></sup><sup>,<a href="#zoi241194r11" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">11</a></sup><sup>,<a href="#zoi241194r56" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">56</a></sup><sup>,<a href="#zoi241194r57" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">57</a></sup> We also measured participants’ adolescent to younger adult MGE change as the difference between adolescent and younger adult MGE <i>z</i> scores.</p> <a class="article-section-id-anchor" id="249966580"></a> <p class="para">Primary dependent variables were constructed from adult (wave V) data to allow greater power as CVD risk becomes increasingly detectable with age.<sup><a href="#zoi241194r58" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">58</a></sup><sup>,<a href="#zoi241194r59" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">59</a></sup> Binary variables were based on yes and no responses to survey items, asking “whether a doctor, nurse, or other health care provider ever told you that you have or had [high blood pressure or hypertension, high blood sugar or diabetes, high blood cholesterol, triglycerides, lipids, or hyperlipidemia].” Yes responses indicated diagnoses of hypertension, diabetes, or hyperlipidemia.</p> <a class="article-section-id-anchor" id="249966581"></a> <p class="para">Consistent with current American Heart Association/American College of Cardiology Task Force guidance on hypertension classification,<sup><a href="#zoi241194r60" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">60</a></sup> elevated blood pressure (BP) was defined as systolic BP exceeding 130 mm Hg or diastolic BP exceeding 80 mm Hg based on the average of 3 measurements obtained using factory-calibrated oscillometric BP monitors (Microlife Corp).<sup><a href="#zoi241194r61" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">61</a></sup> Consistent with the American Diabetes Association diabetes classification,<sup><a href="#zoi241194r62" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">62</a></sup> an elevated hemoglobin A<sub>1c</sub> (HbA<sub>1c</sub>) level was defined as 6.5% or greater (to convert to proportion of total hemoglobin, multiply by 0.01) on a venous blood sample.<sup><a href="#zoi241194r63" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">63</a></sup> Hyperlipidemia was defined as serum non–high-density lipoprotein cholesterol (HDL-C) 190 mg/dL (to convert to millimoles per liter, multiply by 0.259) on venous blood samples, consistent with 2019 American Heart Association/American College of Cardiology guidance.<sup><a href="#zoi241194r47" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">47</a></sup><sup>,<a href="#zoi241194r64" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">64</a></sup><sup>,<a href="#zoi241194r65" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">65</a></sup> The non–HDL-C measure was chosen given evidence of its utility in predicting CVD mortality.<sup><a href="#zoi241194r65" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">65</a></sup></p> <a class="article-section-id-anchor" id="249966582"></a> <p class="para">Finally, treatment was assessed by participants’ self-report of all medications used during the 4 weeks before biomeasure collection. Medications were categorized based on classifications listed in Micromedex and Lexicomp as antihypertensive, hypoglycemic, and lipid-lowering.<sup><a href="#zoi241194r66" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">66</a></sup> Treatment was defined as self-reporting at least 1 medication for a corresponding risk category.</p> <a class="article-section-id-anchor" id="249966583"></a> <p class="para">Participant-level covariates included self-reported adult race and ethnicity (participants categorized as “other” included those who indicated “some other race or origin” and those who indicated multiple races but did not indicate a specific race), educational attainment, and health insurance status on close-coded survey questions, and a composite measure of adolescent socioeconomic origin.<sup><a href="#zoi241194r67" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">67</a></sup> Neighborhood-level covariates included a composite measure of adolescent neighborhood socioeconomic disadvantage.<sup><a href="#zoi241194r67" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">67</a></sup> Individual- and neighborhood-level sociodemographic covariates (including race and ethnicity) were included to account for possible sociodemographic differences in the association between MGE and CVD prevention efforts.</p> <a class="article-section-id-anchor" id="249966584"></a> <div class="h4 cb section-type-section "> <div class="heading-text "> Statistical Analysis </div> </div> <a class="article-section-id-anchor" id="249966585"></a> <p class="para">Data were analyzed from January 5, 2023, to August 28, 2024. Descriptive statistics were calculated for participant- and neighborhood-level characteristics. Logistic regression was used to examine associations of adolescent, younger adult, and adolescent-to-younger-adult MGE change, controlling for adolescent MGE, with adult CVD risk outcomes. Average marginal effects (dy/dx) were then calculated, which illustrate associations of differences in MGE at each developmental stage with differences in the predicted probabilities of adult CVD outcomes.</p> <a class="article-section-id-anchor" id="249966586"></a> <p class="para">In model 1, we evaluated associations of adolescent, younger adult, and adolescent-to-younger adult MGE changes with adult hypertension, diabetes, and hyperlipidemia diagnoses. This model included an interaction term between MGE and relevant biomeasure levels (ie, models testing associations of MGE with hypertension diagnoses included an interaction with BP, diabetes with HbA<sub>1c</sub>, and hyperlipidemia with non–HDL-C). This interaction term allowed us to test associations of MGE with adult CVD risk diagnoses, specifically among men with biomeasure evidence of the disease. Model 2 assessed associations of MGE with treatment among adult men who reported relevant diagnoses (eg, evaluation of antihypertensive use included an interaction term between MGE and self-reported hypertension diagnoses). Model 3 evaluated associations of MGE with adult biomeasure levels (BP, HbA<sub>1c</sub>, and non–HDL-C). This model adjusted for relevant medication use (eg, regressions modeling associations with BP adjusted for antihypertensive use). All models adjusted for individual- and neighborhood-level sociodemographic covariates. Sensitivity analyses were conducted, assessing BP at a higher threshold (systolic BP≥140 mm Hg or diastolic BP≥90 mm Hg) and associations of MGE with treatment adjusting for biomeasure level.</p> <a class="article-section-id-anchor" id="249966587"></a> <p class="para">Add Health sampling weights were incorporated into regression models to account for the complex survey design of Add Health, which included an unequal probability of selection, differential survey-item nonresponse, and missing surveys (ie, participants not interviewed during a particular wave). Further analysis of item missingness is provided in eTable 2 in <a class="supplement-link section-jump-link" data-tab-toggle=".tab-nav-supplemental" href="#note-ZOI241194-1">Supplement 1 </a>and comparison of participants with complete vs missing covariate data in eTable 3 in <a class="supplement-link section-jump-link" data-tab-toggle=".tab-nav-supplemental" href="#note-ZOI241194-1">Supplement 1</a>.</p> <a class="article-section-id-anchor" id="249966588"></a> <p class="para">Significance levels were set at <i>P</i> < .05 for 2-tailed tests. Analyses were performed using Stata SE, version 17 (StataCorp LLC) and replicated using R Programming Language, version 4.3.3 (R Foundation for Statistical Computing).</p> <a class="article-section-id-anchor" id="249966589"></a> <div class="h3 cb section-type-section "> <div class="heading-text thm-col sb-sc"> Results </div> </div> <a class="article-section-id-anchor" id="249966590"></a> <p class="para">Overall, 4230 male participants were included in the study (<a href="#zoi241194t1" class="table-link section-jump-link" data-tab-toggle=".tab-nav-figure-table">Table 1</a>). Their mean (SD) age was 16.14 (1.81) years in adolescence, 29.02 (1.84) years in younger adulthood, and 38.10 (1.95) years in adulthood. Participants self-identified as Asian American or Pacific Islander (298 [7%]), Hispanic (487 [12%]), non-Hispanic Black (668 [16%]), non-Hispanic White (2711 [64%]), or multiple race and/or ethnicity or other (54 [1%]). Most participants were privately insured (3338 [80%]). Participants whose younger adult MGE was above average, compared with those whose MGE was below average, were more likely to be White (1692 [67%] vs 1019 [60%]; <i>P</i> < .001) and report a primarily military source of insurance (eg, TRICARE; 139 [6%] vs 23 [1%]; <i>P</i> < .001), but less likely to have received a college degree (887 [35%] vs 720 [42%]; <i>P</i> < .001). They were also significantly less likely to report diagnoses of hypertension (546 [22%] vs 441 [26%]; <i>P</i> < .001), diabetes (124 [5%] vs 143 [8%]; <i>P</i> < .001), and hyperlipidemia (488 [19%] vs 406 [24%]; <i>P</i> < .001), although only increased HbA<sub>1c</sub> (ie, not BP or non–HDL-C) was significantly less prevalent in this group (39 [4%] vs 48 [7%]; <i>P</i> = .008). Overall, the prevalence of increased CVD risk factor biomeasure levels was 64% for BP, 5% for HbA<sub>1c</sub>, and 10% for non–HDL-C.</p> <a class="article-section-id-anchor" id="249966592"></a> <p class="para">Associations of MGE at each developmental stage with adult CVD risk factor outcomes are reported in <a href="#zoi241194t2" class="table-link section-jump-link" data-tab-toggle=".tab-nav-figure-table">Table 2</a>. In model 1 (<a href="#zoi241194f1" class="figure-link section-jump-link" data-tab-toggle=".tab-nav-figure-table">Figure 1</a>), examining associations of MGE with CVD risk factor diagnoses among participants with biomeasure evidence of these conditions, we found that among adult men with increased BP, every SD increase in younger adult MGE was associated with a 4-percentage point lower probability (MGE, −0.04; 95% CI, −0.07 to −0.01) of adult hypertension diagnoses. Every SD increase in adolescent-to-younger adult MGE change, adjusting for adolescent MGE, was associated with a 5-percentage point (MGE, −0.05; 95% CI, −0.08 to −0.01) lower probability of adult hypertension diagnoses among this group of adult men. Among adult men with HbA<sub>1c</sub> greater than or equal to 6.5%, every SD increase in adolescent MGE was associated with a 15-percenatge point lower probability (MGE, −0.15; 95% CI, −0.27 to −0.03) of adult diabetes diagnoses. There was no association between MGE and hyperlipidemia diagnoses among men with high non–HDL-C.</p> <a class="article-section-id-anchor" id="249966595"></a> <p class="para">In model 2 (<a href="#zoi241194f2" class="figure-link section-jump-link" data-tab-toggle=".tab-nav-figure-table">Figure 2</a>), evaluating associations of MGE with adult treatment, we found that among men who reported hypertension diagnoses, every SD increase in adolescent MGE was associated with an 11-percentage point lower probability (MGE,−0.11; 95% CI, −0.16 to −0.6) of adult antihypertensive use. Each SD increase in younger adult MGE was associated with a 7-percentage point lower probability (MGE, −0.07; 95% CI, −0.13 to −0.01) of adult antihypertensive use. Among adult men who reported diabetes diagnoses, higher younger adult MGE was associated with a lower probability (MGE, −0.10; 95% CI, −0.20 to −0.01) of hypoglycemic use. There was no association between MGE and hyperlipidemia treatment.</p> <a class="article-section-id-anchor" id="249966597"></a> <p class="para">In model 3, examining associations of MGE with adult biomeasure outcomes showed no associations of MGE with adult BP, HbA1c, and n-HDL levels. Sensitivity analyses that used a higher BP threshold (systolic BP≥140 mm Hg or diastolic BP≥90 mm Hg) (eTable 4 in <a class="supplement-link section-jump-link" data-tab-toggle=".tab-nav-supplemental" href="#note-ZOI241194-1">Supplement 1</a>) and evaluated associations of MGE with treatment adjusting for biomeasure levels (eTable 5 in <a class="supplement-link section-jump-link" data-tab-toggle=".tab-nav-supplemental" href="#note-ZOI241194-1">Supplement 1</a>) found no substantive differences in observed associations, with 2 exceptions: younger adult MGE was not associated with hypertension diagnoses in men with BPs above the alternate cutoff level or with hypoglycemic use in adults adjusting for HbA<sub>1c</sub>.</p> <a class="article-section-id-anchor" id="249966598"></a> <div class="h3 cb section-type-section "> <div class="heading-text thm-col sb-sc"> Discussion </div> </div> <a class="article-section-id-anchor" id="249966599"></a> <p class="para">In this analysis of nationally representative Add Health data, we found associations between participants’ MGE at multiple developmental stages and downstream modifiable CVD risk diagnoses and treatment, particularly hypertension and diabetes. We did not observe associations of MGE with biomeasure outcomes among adult men aged 32 to 42 years, suggesting similar levels of disease but differences in help-seeking behaviors. Our findings support the hypothesis that prevalent sociocultural pressures to maintain and convey male gender identity—quantified by MGE—may be associated with lower diagnoses and treatment of important, modifiable CVD risks.</p> <a class="article-section-id-anchor" id="249966600"></a> <p class="para">Estimates for the prevalence of physiologic CVD risk within our study are consistent with prior reports.<sup><a href="#zoi241194r58" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">58</a></sup><sup>,<a href="#zoi241194r68" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">68</a></sup><sup>-<a href="#zoi241194r68" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">71</a></sup> For instance, 64% of adult men in our sample displayed hypertensive BP, compared with approximately 59% in published estimates for similar populations,<sup><a href="#zoi241194r68" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">68</a></sup> 5% had diabetes-range HbA<sub>1c</sub> levels compared with published estimates of approximately 4% in people aged 10 to 44 years,<sup><a href="#zoi241194r58" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">58</a></sup><sup>,<a href="#zoi241194r69" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">69</a></sup> and 10% had increased non–HDL-C levels, also consistent with published estimates.<sup><a href="#zoi241194r70" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">70</a></sup><sup>,<a href="#zoi241194r71" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">71</a></sup> Prior reports have further corroborated that diagnoses of CVD risk conditions frequently do not match higher levels of physiologic risk prevalent in US populations, especially among adolescents and younger adults.<sup><a href="#zoi241194r40" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">40</a></sup><sup>,<a href="#zoi241194r41" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">41</a>,<a href="#zoi241194r48" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">48</a></sup> By some earlier estimates, less than 25% of younger adults with borderline CVD risk levels are aware of their risk.<sup><a href="#zoi241194r40" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">40</a></sup></p> <a class="article-section-id-anchor" id="249966601"></a> <p class="para">Such low diagnosis rates are troubling and suggest a need for focused public health messaging. Borderline levels of CVD risk, even in younger adults, have been associated with heightened morbidity and mortality and decreased longevity.<sup><a href="#zoi241194r30" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">30</a></sup><sup>-<a href="#zoi241194r30" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">39</a></sup> Male gender expressivity was not associated with biomeasure levels in our study, consistent with a lower prevalence during the stage of adulthood examined (age 32-42 years). However, lower levels of diagnosis and treatment remain concerning, given the importance of early recognition and treatment of CVD risk factors.<sup><a href="#zoi241194r41" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">41</a></sup><sup>,<a href="#zoi241194r58" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">58</a></sup><sup>,<a href="#zoi241194r59" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">59</a>,<a href="#zoi241194r72" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">72</a></sup><sup>-<a href="#zoi241194r72" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">75</a></sup></p> <a class="article-section-id-anchor" id="249966602"></a> <p class="para">Prior investigations have explored factors associated with suboptimal CVD prevention efforts.<sup><a href="#zoi241194r40" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">40</a></sup><sup>,<a href="#zoi241194r41" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">41</a>,<a href="#zoi241194r48" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">48</a></sup><sup>,<a href="#zoi241194r49" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">49</a>,<a href="#zoi241194r76" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">76</a></sup><sup>-<a href="#zoi241194r76" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">78</a></sup> Such past studies reveal evidence that younger age, lack of insurance, lack of routine care, and belief that one is in excellent health may all be associated with decreased diagnoses.<sup><a href="#zoi241194r40" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">40</a></sup><sup>,<a href="#zoi241194r41" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">41</a></sup> However, to our knowledge, no studies have examined associations with MGE, despite qualitative evidence suggesting that prevalent sociocultural pressures to convey male gender often lead to decreased help-seeking.<sup><a href="#zoi241194r27" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">27</a></sup><sup>-<a href="#zoi241194r27" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">29</a></sup></p> <a class="article-section-id-anchor" id="249966603"></a> <p class="para">Many efforts to address gender-based disparities in CVD have focused mainly on factors associated with inadequate risk detection and reduction among women.<sup><a href="#zoi241194r79" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">79</a></sup><sup>-<a href="#zoi241194r79" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">81</a></sup> Such attempts to improve CVD awareness and treatment among women are necessary. Our findings suggest further efforts are also needed to uncover overlooked mechanisms by which sociocultural pressures around gender may precipitate preventable CVD morbidity and mortality among men.</p> <a class="article-section-id-anchor" id="249966604"></a> <p class="para">While our analysis focused on participants who identified as male—without distinguishing between cisgender, transgender, or other gender-diverse identities—prior publications identify manhood generally as a precarious social identity, requiring continuous social proof.<sup><a href="#zoi241194r3" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">3</a></sup><sup>-<a href="#zoi241194r3" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">6</a>,<a href="#zoi241194r82" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">82</a></sup> Evidence suggests that persons who experience what they believe to be threats to their male gender identity are especially likely to enact compensatory, stereotype-consistent behaviors to reclaim their gender identity, which may include rejecting help.<sup><a href="#zoi241194r3" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">3</a></sup><sup>,<a href="#zoi241194r7" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">7</a></sup><sup>,<a href="#zoi241194r27" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">27</a></sup><sup>,<a href="#zoi241194r82" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">82</a></sup><sup>,<a href="#zoi241194r83" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">83</a></sup> Future efforts should seek to understand how associations of MGE with CVD diagnoses and treatment may be moderated, especially by marginalized social identities, including transgender and other gender-diverse identities. Equally, public health messaging and related efforts to encourage CVD prevention might be designed to reach people for whom interactions of identity and gender expressivity appear predictive of CVD risk.</p> <a class="article-section-id-anchor" id="249966605"></a> <p class="para">Our analysis also identified the need for further research regarding how changes in MGE across the life course may relate to downstream CVD risk. We found associations between younger adult MGE and adult hypertension diagnoses. Yet in the case of diabetes, we found associations between adolescent but not younger adult MGE and adult diagnoses. Some of this variation may be due to the mixing of type 1 diabetes, an autoimmune disease that arises mostly in childhood and adolescence, with type 2 diabetes, a form that develops primarily in middle age and older adulthood. We might expect type 1 diabetes recognition and treatment to have less association with MGE, as it is frequently diagnosed in childhood when parents primarily manage health; however, adolescents diagnosed with conditions that undercut their sense of identity (gender or otherwise) may be more likely to downplay their existence.<sup><a href="#zoi241194r84" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">84</a></sup><sup>,<a href="#zoi241194r85" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">85</a></sup> Some variation may also be due to the ways that context-specific, cultural scripts for gender identities change over time, possibly shifting the association between MGE and help-seeking for specific CVD diagnoses across decades.</p> <a class="article-section-id-anchor" id="249966606"></a> <p class="para">Relatedly, the lack of an association between MGE and hyperlipidemia diagnoses and treatment provides circumstantial evidence of the potential influence of such context-specific scripts for how male gender is expected to be expressed on specific CVD risk diagnoses and treatment. This lack of significance is consistent with research finding that, unlike hypertension and diabetes, hyperlipidemia control is higher among men than women.<sup><a href="#zoi241194r21" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">21</a></sup> Prior researchers have suggested such disparities may be attributable to sex-linked physiologic differences.<sup><a href="#zoi241194r21" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">21</a></sup> Our results suggest alternative possibilities, including differences in risk-mitigation behavior, possibly associated with direct-to-consumer advertising,<sup><a href="#zoi241194r86" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">86</a></sup> which has been shown to substantially increase statin use.<sup><a href="#zoi241194r87" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">87</a></sup> It is possible that direct-to-consumer advertising messages have shifted cultural beliefs and perceptions associating hyperlipidemia, statin use, and male gender, as with other health behaviors, such as smoking.<sup><a href="#zoi241194r1" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">1</a></sup><sup>,<a href="#zoi241194r88" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">88</a></sup><sup>,<a href="#zoi241194r89" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">89</a></sup></p> <a class="article-section-id-anchor" id="249966607"></a> <div class="h4 cb section-type-section "> <div class="heading-text "> Limitations </div> </div> <a class="article-section-id-anchor" id="249966608"></a> <p class="para">Our findings should be interpreted in the context of several limitations. First, participants’ survey responses may be affected by imperfect recall and social desirability biases, which may co-vary with MGE. Second, Add Health data are unavailable past the fifth decade of life. Since many CVD risk factors are subclinical at younger ages, this may limit our power, biasing findings toward the null. Third, measures of diagnosis may also include findings of increased BP (prehypertension) and blood glucose (prediabetes) below the biomeasure thresholds we used, also potentially biasing findings toward the null. Fourth, BP is ideally based on BP readings over multiple days rather than 3 readings during a single in-home examination. The prevalence of increased BP should be interpreted in this light as well as concerns about a possible white coat effect, although the hypertension prevalence in our study is consistent with earlier population estimates. Add Health BP measurement protocols and materials have also been rigorously validated and reliably assessed.<sup><a href="#zoi241194r90" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">90</a></sup><sup>,<a href="#zoi241194r91" class="ref-link section-jump-link" data-tab-toggle=".tab-nav-references">91</a></sup> Fifth, restricting some analyses to only those who participated in biomeasure examinations may have introduced bias based on who was likeliest to participate, although this too would have biased results toward the null. Sixth, our measure of treatment (medication use) realistically reflects an interplay between prescribers’ behaviors and participants’ adherence and self-report, and thus cannot be attributed to participants alone.</p> <a class="article-section-id-anchor" id="249966609"></a> <div class="h3 cb section-type-section "> <div class="heading-text thm-col sb-sc"> Conclusions </div> </div> <a class="article-section-id-anchor" id="249966610"></a> <p class="para">The findings of this cohort study suggest important yet easily overlooked connections between prevalent sociocultural pressures to convey masculinity and CVD risk. While we did not find significant links between MGE and biomeasure evidence of CVD risk among adults aged 32 to 42 years, our data revealed associations of MGE with CVD risk diagnoses and treatment. Given what is known about failures to identify and address risks, this finding should inform efforts to improve CVD prevention.</p> <a class="article-section-id-anchor" id="249966611"></a> <div class="h3 cb section-type-acknowledgements has-back-to-top"> <a href="#top" class="section-jump-link back-to-top" data-tab-toggle=".tab-nav-full-text">Back to top</a> <div class="heading-text thm-col sb-sc"> Article Information </div> </div> <p class="para"><strong>Accepted for Publication:</strong> August 30, 2024.</p><p class="parapublished-online"><strong>Published:</strong> October 25, 2024. doi:10.1001/jamanetworkopen.2024.41281</p><p class="paraopen-access-note"><strong>Open Access:</strong> This is an open access article distributed under the terms of the <a href="https://jamanetwork.com/pages/cc-by-license-permissions">CC-BY License</a>. © 2024 Glasser NJ et al. <i>JAMA Network Open</i>.</p><p class="authorInfoSection"><strong>Corresponding Author:</strong> Nathaniel J. Glasser, MD, MPP, Section of General Internal Medicine, University of Chicago, 5841 S Maryland Ave, MC 2007B, Room B219, Chicago, IL 60637 (<a href="mailto:nglasser@uchicago.edu" target="_blank">nglasser@uchicago.edu</a>).</p><p class="paraauthor-contributions"><strong>Author Contributions:</strong> Dr Glasser and Mr Jameson had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.</p><p class="para"><i>Concept and design:</i> Glasser, Jameson, Pollack.</p><p class="para"><i>Acquisition, analysis, or interpretation of data:</i> Glasser, Jameson, Huang, Kronish, Lindau, Peek, Tung.</p><p class="para"><i>Drafting of the manuscript:</i> Glasser, Pollack.</p><p class="para"><i>Critical review of the manuscript for important intellectual content:</i> Jameson, Huang, Kronish, Lindau, Peek, Tung, Pollack.</p><p class="para"><i>Statistical analysis:</i> Glasser, Jameson, Tung, Pollack.</p><p class="para"><i>Obtained funding:</i> Glasser.</p><p class="para"><i>Administrative, technical, or material support:</i> Glasser, Pollack.</p><p class="para"><i>Supervision:</i> Huang, Pollack.</p><p class="parafinancial-disclosure"><strong>Conflict of Interest Disclosures:</strong> Dr Lindau reported being a shareholder, formerly paid advisor, and currently unpaid advisor for Unite USA Inc for work unrelated to this study; being a shareholder in Glenbervie Health LLC unrelated to this study; receiving fees paid to the University of Chicago for editorial services for UpToDate Inc unrelated to this study; and being cofounder, chief innovation officer, and shareholder of STEAMe LLC outside the submitted work. Dr Peek reported receiving grants from Kaiser Permanente, the National Institutes of Health (NIH), Patient-Centered Outcomes Research Institute, and the California Endowment during the conduct of the study. Dr Tung reported receiving grants from the NIH National Heart, Lung, and Blood Institute, NIH Eunice Kennedy Shriver National Institute of Child Health and Human Development, and the Department of Justice Office of Juvenile Justice and Delinquency Prevention outside the submitted work. No other disclosures were reported.</p><p class="parafunding-statement"><strong>Funding/Support:</strong> This research uses data from Add Health, funded by grant P01 HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. This work was supported by the Health Resources and Services Administration under a Ruth L. Kirschstein National Research Service Institutional Research Training Grant (T32-HP42019) and NIH grants (K24AG069080, R01AG060756, P30DK092949, P50MD017349, R01 HL152699, 1K23HL145090-01, R01AG064949, R01MD012630, 5R01HL150909, UG3HL154297, and 1R01DK127961). Dr Lindau's effort was also supported in part by grants R01HL150909, UH3HL154297, and UG3HL154297.</p><p class="para"><strong>Role of the Funder/Sponsor:</strong> The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.</p><p class="para"><strong>Disclaimer:</strong> This content is solely the responsibility of the authors and does not represent the official views of the Health Resources and Services Administration or the NIH. Neither the University of Chicago nor the University of Chicago Medicine is endorsing or promoting Unite Us or STEAMe on their business, products, or services.</p><p class="paradata-sharing-statement"><strong>Data Sharing Statement:</strong> See <a class="supplement-link section-jump-link" data-tab-toggle=".tab-nav-supplemental" href="#note-ZOI241194-1">Supplement 2</a>.</p><p class="para"><strong>Additional Information: </strong>Add Health is currently directed by Robert A. Hummer and funded by the National Institute on Aging cooperative agreements U01 AG071448 (Hummer) and U01AG071450 (Aiello and Hummer) at the University of North Carolina at Chapel Hill. Add Health was designed by J. Richard Udry, Peter S. 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