Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study
Previous studies have explored the relationship between body mass index (BMI) and multimorbidity. However, the relationship between other obesity indicators and their dynamic changes and multimorbidity has not been systematically estimated. Therefore, we aimed to investigate the association of BMI a...
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| description | Previous studies have explored the relationship between body mass index (BMI) and multimorbidity. However, the relationship between other obesity indicators and their dynamic changes and multimorbidity has not been systematically estimated. Therefore, we aimed to investigate the association of BMI and other obesity indicators, including waist circumference (WC), waist-to-height ratio (WHtR), waist divided by height.sup.0.5 (WHT.5R), and body roundness index (BRI) and their changes and the risk of multimorbidity in middle-aged and older adults through a retrospective cohort study. Data collected from annual health examination dataset in the Jinshui during 2017 and 2021. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the effect of baseline and dynamic changes in the anthropometric indices on the risk of multimorbidity. A total of 75,028 individuals were included in the study, and 5,886 participants developed multimorbidity during the follow-up. Multivariate Cox regression analysis revealed a progressive increase in the risk of multimorbidity with increasing anthropometric indicators (BMI, WC, WHtR, WHT.5R, and BRI) (all P |
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However, the relationship between other obesity indicators and their dynamic changes and multimorbidity has not been systematically estimated. Therefore, we aimed to investigate the association of BMI and other obesity indicators, including waist circumference (WC), waist-to-height ratio (WHtR), waist divided by height.sup.0.5 (WHT.5R), and body roundness index (BRI) and their changes and the risk of multimorbidity in middle-aged and older adults through a retrospective cohort study. Data collected from annual health examination dataset in the Jinshui during 2017 and 2021. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the effect of baseline and dynamic changes in the anthropometric indices on the risk of multimorbidity. A total of 75,028 individuals were included in the study, and 5,886 participants developed multimorbidity during the follow-up. Multivariate Cox regression analysis revealed a progressive increase in the risk of multimorbidity with increasing anthropometric indicators (BMI, WC, WHtR, WHT.5R, and BRI) (all P<0.001). Regardless of general obesity status at baseline, increased WC was associated with a high risk of multimorbidity. Compared to the subjects with baseline BMI<24 kg/m.sup.2 and WC<90 (men)/80 (women), the HRs (95% CI) of the baseline BMI<24 kg/m.sup.2 and WC[greater than or equal to]90 (men)/80 (women) group and BMI[greater than or equal to]24 kg/m.sup.2 and WC[greater than or equal to]90 (men)/80 (women) group were 1.31 (1.08, 1.61) and 1.82 (1.68, 1.97), respectively. In addition, the dynamics of WC could reflect the risk of multimorbidity. When subjects with baseline WC<90 (men)/80 (women) progressed to WC[greater than or equal to]90 (men)/80 (women) during follow-up, the risk of multimorbidity significantly increased (HR = 1.78; 95% CI, 1.64, 1.95), while the risk of multimorbidity tended to decrease when people with abnormal WC at baseline reversed to normal at follow-up (HR = 1.40; 95% CI, 1.26, 1.54) compared to those who still exhibited abnormal WC at follow-up (HR = 2.00; 95% CI, 1.82, 2.18). Central obesity is an independent and alterable risk factor for the occurrence of multimorbidity in middle-aged and elderly populations. In addition to the clinical measurement of BMI, the measurement of the central obesity index WC may provide additional benefits for the identification of multimorbidity in the Chinese middle-aged and elderly populations.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0276216</identifier><identifier>PMID: 36240163</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Adults ; Aged ; Anthropometry ; Biology and Life Sciences ; Body mass ; Body mass index ; Body measurements ; Body size ; Cardiovascular disease ; Chronic diseases ; Chronic illnesses ; Cohort analysis ; Comorbidity ; Complications and side effects ; Confidence intervals ; Diagnosis ; Exercise ; Health aspects ; Health risks ; Indicators ; Medicine and Health Sciences ; Men ; Multimorbidity ; Obesity ; Older people ; Populations ; Regression analysis ; Regression models ; Risk analysis ; Risk factors ; Roundness ; Statistical analysis ; Women</subject><ispartof>PloS one, 2022-10, Vol.17 (10), p.e0276216-e0276216</ispartof><rights>COPYRIGHT 2022 Public Library of Science</rights><rights>2022 Geng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 Geng et al 2022 Geng et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c599t-25e33c32ea3e5211485eb7f3fa3529f8fea6e39a6023e2c37f35b581f3cbeac83</citedby><cites>FETCH-LOGICAL-c599t-25e33c32ea3e5211485eb7f3fa3529f8fea6e39a6023e2c37f35b581f3cbeac83</cites><orcidid>0000-0002-2214-1440</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9565419/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9565419/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2100,2926,23865,27923,27924,53790,53792,79371,79372</link.rule.ids></links><search><contributor>Reischak-Oliveira, Alvaro</contributor><creatorcontrib>Geng, Shuoji</creatorcontrib><creatorcontrib>Chen, Xuejiao</creatorcontrib><creatorcontrib>Shi, Zhan</creatorcontrib><creatorcontrib>Bai, Kaizhi</creatorcontrib><creatorcontrib>Shi, Songhe</creatorcontrib><title>Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study</title><title>PloS one</title><description>Previous studies have explored the relationship between body mass index (BMI) and multimorbidity. However, the relationship between other obesity indicators and their dynamic changes and multimorbidity has not been systematically estimated. Therefore, we aimed to investigate the association of BMI and other obesity indicators, including waist circumference (WC), waist-to-height ratio (WHtR), waist divided by height.sup.0.5 (WHT.5R), and body roundness index (BRI) and their changes and the risk of multimorbidity in middle-aged and older adults through a retrospective cohort study. Data collected from annual health examination dataset in the Jinshui during 2017 and 2021. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the effect of baseline and dynamic changes in the anthropometric indices on the risk of multimorbidity. A total of 75,028 individuals were included in the study, and 5,886 participants developed multimorbidity during the follow-up. Multivariate Cox regression analysis revealed a progressive increase in the risk of multimorbidity with increasing anthropometric indicators (BMI, WC, WHtR, WHT.5R, and BRI) (all P<0.001). Regardless of general obesity status at baseline, increased WC was associated with a high risk of multimorbidity. Compared to the subjects with baseline BMI<24 kg/m.sup.2 and WC<90 (men)/80 (women), the HRs (95% CI) of the baseline BMI<24 kg/m.sup.2 and WC[greater than or equal to]90 (men)/80 (women) group and BMI[greater than or equal to]24 kg/m.sup.2 and WC[greater than or equal to]90 (men)/80 (women) group were 1.31 (1.08, 1.61) and 1.82 (1.68, 1.97), respectively. In addition, the dynamics of WC could reflect the risk of multimorbidity. When subjects with baseline WC<90 (men)/80 (women) progressed to WC[greater than or equal to]90 (men)/80 (women) during follow-up, the risk of multimorbidity significantly increased (HR = 1.78; 95% CI, 1.64, 1.95), while the risk of multimorbidity tended to decrease when people with abnormal WC at baseline reversed to normal at follow-up (HR = 1.40; 95% CI, 1.26, 1.54) compared to those who still exhibited abnormal WC at follow-up (HR = 2.00; 95% CI, 1.82, 2.18). Central obesity is an independent and alterable risk factor for the occurrence of multimorbidity in middle-aged and elderly populations. In addition to the clinical measurement of BMI, the measurement of the central obesity index WC may provide additional benefits for the identification of multimorbidity in the Chinese middle-aged and elderly populations.</description><subject>Adults</subject><subject>Aged</subject><subject>Anthropometry</subject><subject>Biology and Life Sciences</subject><subject>Body mass</subject><subject>Body mass index</subject><subject>Body measurements</subject><subject>Body size</subject><subject>Cardiovascular disease</subject><subject>Chronic diseases</subject><subject>Chronic illnesses</subject><subject>Cohort analysis</subject><subject>Comorbidity</subject><subject>Complications and side effects</subject><subject>Confidence intervals</subject><subject>Diagnosis</subject><subject>Exercise</subject><subject>Health aspects</subject><subject>Health risks</subject><subject>Indicators</subject><subject>Medicine and Health 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intervals</topic><topic>Diagnosis</topic><topic>Exercise</topic><topic>Health aspects</topic><topic>Health risks</topic><topic>Indicators</topic><topic>Medicine and Health Sciences</topic><topic>Men</topic><topic>Multimorbidity</topic><topic>Obesity</topic><topic>Older people</topic><topic>Populations</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Roundness</topic><topic>Statistical analysis</topic><topic>Women</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Geng, Shuoji</creatorcontrib><creatorcontrib>Chen, Xuejiao</creatorcontrib><creatorcontrib>Shi, Zhan</creatorcontrib><creatorcontrib>Bai, Kaizhi</creatorcontrib><creatorcontrib>Shi, Songhe</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central 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explored the relationship between body mass index (BMI) and multimorbidity. However, the relationship between other obesity indicators and their dynamic changes and multimorbidity has not been systematically estimated. Therefore, we aimed to investigate the association of BMI and other obesity indicators, including waist circumference (WC), waist-to-height ratio (WHtR), waist divided by height.sup.0.5 (WHT.5R), and body roundness index (BRI) and their changes and the risk of multimorbidity in middle-aged and older adults through a retrospective cohort study. Data collected from annual health examination dataset in the Jinshui during 2017 and 2021. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the effect of baseline and dynamic changes in the anthropometric indices on the risk of multimorbidity. A total of 75,028 individuals were included in the study, and 5,886 participants developed multimorbidity during the follow-up. Multivariate Cox regression analysis revealed a progressive increase in the risk of multimorbidity with increasing anthropometric indicators (BMI, WC, WHtR, WHT.5R, and BRI) (all P<0.001). Regardless of general obesity status at baseline, increased WC was associated with a high risk of multimorbidity. Compared to the subjects with baseline BMI<24 kg/m.sup.2 and WC<90 (men)/80 (women), the HRs (95% CI) of the baseline BMI<24 kg/m.sup.2 and WC[greater than or equal to]90 (men)/80 (women) group and BMI[greater than or equal to]24 kg/m.sup.2 and WC[greater than or equal to]90 (men)/80 (women) group were 1.31 (1.08, 1.61) and 1.82 (1.68, 1.97), respectively. In addition, the dynamics of WC could reflect the risk of multimorbidity. When subjects with baseline WC<90 (men)/80 (women) progressed to WC[greater than or equal to]90 (men)/80 (women) during follow-up, the risk of multimorbidity significantly increased (HR = 1.78; 95% CI, 1.64, 1.95), while the risk of multimorbidity tended to decrease when people with abnormal WC at baseline reversed to normal at follow-up (HR = 1.40; 95% CI, 1.26, 1.54) compared to those who still exhibited abnormal WC at follow-up (HR = 2.00; 95% CI, 1.82, 2.18). Central obesity is an independent and alterable risk factor for the occurrence of multimorbidity in middle-aged and elderly populations. In addition to the clinical measurement of BMI, the measurement of the central obesity index WC may provide additional benefits for the identification of multimorbidity in the Chinese middle-aged and elderly populations.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>36240163</pmid><doi>10.1371/journal.pone.0276216</doi><tpages>e0276216</tpages><orcidid>https://orcid.org/0000-0002-2214-1440</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adults Aged Anthropometry Biology and Life Sciences Body mass Body mass index Body measurements Body size Cardiovascular disease Chronic diseases Chronic illnesses Cohort analysis Comorbidity Complications and side effects Confidence intervals Diagnosis Exercise Health aspects Health risks Indicators Medicine and Health Sciences Men Multimorbidity Obesity Older people Populations Regression analysis Regression models Risk analysis Risk factors Roundness Statistical analysis Women |
| title | Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T10%3A29%3A02IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Association%20of%20anthropometric%20indices%20with%20the%20development%20of%20multimorbidity%20in%20middle-aged%20and%20older%20adults:%20A%20retrospective%20cohort%20study&rft.jtitle=PloS%20one&rft.au=Geng,%20Shuoji&rft.date=2022-10-14&rft.volume=17&rft.issue=10&rft.spage=e0276216&rft.epage=e0276216&rft.pages=e0276216-e0276216&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0276216&rft_dat=%3Cgale_plos_%3EA722408937%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2724869384&rft_id=info:pmid/36240163&rft_galeid=A722408937&rft_doaj_id=oai_doaj_org_article_4a55e9a98eda492bbecf02273a1903ea&rfr_iscdi=true |