Do body mass index and waist-to-height ratio over the preceding decade predict retinal microvasculature in 11–12 year olds and midlife adults?

Background/objectives Microvascular changes may contribute to obesity-associated cardiovascular disease. We examined whether body mass index (BMI) and waist-to-height ratio (WHtR) (1) at multiple earlier time points and (2) decade-long trajectories predicted retinal microvascular parameters in mid-c...

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Veröffentlicht in:International Journal of Obesity 2020-08, Vol.44 (8), p.1712-1722
Hauptverfasser: Liu, Mengjiao, Lycett, Kate, Wong, Tien Yin, Kerr, Jessica A., He, Mingguang, Juonala, Markus, Olds, Tim, Dwyer, Terry, Burgner, David, Wake, Melissa
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container_end_page 1722
container_issue 8
container_start_page 1712
container_title International Journal of Obesity
container_volume 44
creator Liu, Mengjiao
Lycett, Kate
Wong, Tien Yin
Kerr, Jessica A.
He, Mingguang
Juonala, Markus
Olds, Tim
Dwyer, Terry
Burgner, David
Wake, Melissa
description Background/objectives Microvascular changes may contribute to obesity-associated cardiovascular disease. We examined whether body mass index (BMI) and waist-to-height ratio (WHtR) (1) at multiple earlier time points and (2) decade-long trajectories predicted retinal microvascular parameters in mid-childhood/adulthood. Methods Participants/design: 1288 11–12 year olds (51% girls) and 1264 parents (87% mothers) in the population-based Child Health CheckPoint (CheckPoint) module within the Longitudinal Study of Australian Children (LSAC). LSAC exposure measures: biennial BMI z -score and WHtR for children at five time points from age 2–3 to 10–11 years and self-reported parent BMI at six time points from child age 0–1 years to 10–11 years. CheckPoint outcome measures: retinal arteriolar and venular caliber. Analyses: BMI/WHtR trajectories were identified by group-based trajectory modeling; linear regression models estimated associations between BMI/WHtR at each time point/trajectories and later retinal vascular caliber, adjusted for age, sex, and family socioeconomic status. Results In time point analyses, higher child BMI/WHtR from age 4 to 5 years was associated with narrower arteriolar caliber at the age of 11–12 years, but not venular caliber. For example, each standard deviation higher in BMI z -score at 4–5 years was associated with narrower arteriolar caliber at 11–12 years (standardized mean difference (SMD): −0.05, 95% confidence interval (CI): −0.10 to 0.01); by 10–11 years, associations had doubled to −0.10 (95% CI: −0.16 to −0.05). In adults, these finding were similar, except the magnitude of BMI and arteriolar associations were similar across all time points (SMD: −0.11 to −0.13). In child and adult BMI trajectory analyses, less favorable trajectories predicted narrower arteriolar ( p- trend  0.1), caliber. Compared with those in the average BMI trajectory, SMDs in arterial caliber for children and adults in the highest trajectory were −0.25 (95% CI: −0.44 to −0.07) and −0.42 (95% CI: −0.73 to −0.10), respectively. Venular caliber showed late associations with child WHtR, but not with BMI in children or adults. Conclusions Associations of decade-long high BMI trajectories with narrowed retinal arteriolar caliber emerge in children, and are clearly evident by midlife. Adiposity appears to exert its early adverse life course impacts on the microcirculation more via arteriolar than venular mechanisms.
doi_str_mv 10.1038/s41366-020-0584-9
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We examined whether body mass index (BMI) and waist-to-height ratio (WHtR) (1) at multiple earlier time points and (2) decade-long trajectories predicted retinal microvascular parameters in mid-childhood/adulthood. Methods Participants/design: 1288 11–12 year olds (51% girls) and 1264 parents (87% mothers) in the population-based Child Health CheckPoint (CheckPoint) module within the Longitudinal Study of Australian Children (LSAC). LSAC exposure measures: biennial BMI z -score and WHtR for children at five time points from age 2–3 to 10–11 years and self-reported parent BMI at six time points from child age 0–1 years to 10–11 years. CheckPoint outcome measures: retinal arteriolar and venular caliber. Analyses: BMI/WHtR trajectories were identified by group-based trajectory modeling; linear regression models estimated associations between BMI/WHtR at each time point/trajectories and later retinal vascular caliber, adjusted for age, sex, and family socioeconomic status. Results In time point analyses, higher child BMI/WHtR from age 4 to 5 years was associated with narrower arteriolar caliber at the age of 11–12 years, but not venular caliber. For example, each standard deviation higher in BMI z -score at 4–5 years was associated with narrower arteriolar caliber at 11–12 years (standardized mean difference (SMD): −0.05, 95% confidence interval (CI): −0.10 to 0.01); by 10–11 years, associations had doubled to −0.10 (95% CI: −0.16 to −0.05). In adults, these finding were similar, except the magnitude of BMI and arteriolar associations were similar across all time points (SMD: −0.11 to −0.13). In child and adult BMI trajectory analyses, less favorable trajectories predicted narrower arteriolar ( p- trend &lt; 0.05), but not venular ( p- trend &gt; 0.1), caliber. Compared with those in the average BMI trajectory, SMDs in arterial caliber for children and adults in the highest trajectory were −0.25 (95% CI: −0.44 to −0.07) and −0.42 (95% CI: −0.73 to −0.10), respectively. Venular caliber showed late associations with child WHtR, but not with BMI in children or adults. Conclusions Associations of decade-long high BMI trajectories with narrowed retinal arteriolar caliber emerge in children, and are clearly evident by midlife. Adiposity appears to exert its early adverse life course impacts on the microcirculation more via arteriolar than venular mechanisms.</description><identifier>ISSN: 0307-0565</identifier><identifier>EISSN: 1476-5497</identifier><identifier>DOI: 10.1038/s41366-020-0584-9</identifier><identifier>PMID: 32424266</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>692/163/2743/393 ; 692/499 ; Adipose tissue ; Adults ; Age ; Body mass index ; Body size ; Cardiovascular diseases ; Children ; Children &amp; youth ; Confidence intervals ; Correlation analysis ; Epidemiology ; Health aspects ; Health Promotion and Disease Prevention ; Internal Medicine ; Longitudinal studies ; Medicine ; Medicine &amp; Public Health ; Metabolic Diseases ; Microvasculature ; Obesity ; Parents ; Prognosis ; Public Health ; Regression analysis ; Regression models ; Retina ; Socioeconomics ; Statistical analysis ; Trajectory analysis</subject><ispartof>International Journal of Obesity, 2020-08, Vol.44 (8), p.1712-1722</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Limited 2020</rights><rights>COPYRIGHT 2020 Nature Publishing Group</rights><rights>The Author(s), under exclusive licence to Springer Nature Limited 2020.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c541t-8d88605f0609d2aa112e926c24e7c6fc679b8ae2c5e62e9b2baa91ab4213d283</citedby><cites>FETCH-LOGICAL-c541t-8d88605f0609d2aa112e926c24e7c6fc679b8ae2c5e62e9b2baa91ab4213d283</cites><orcidid>0000-0002-2091-7663 ; 0000-0002-8337-7633 ; 0000-0001-9498-364X ; 0000-0002-3150-4047</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/s41366-020-0584-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/s41366-020-0584-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32424266$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liu, Mengjiao</creatorcontrib><creatorcontrib>Lycett, Kate</creatorcontrib><creatorcontrib>Wong, Tien Yin</creatorcontrib><creatorcontrib>Kerr, Jessica A.</creatorcontrib><creatorcontrib>He, Mingguang</creatorcontrib><creatorcontrib>Juonala, Markus</creatorcontrib><creatorcontrib>Olds, Tim</creatorcontrib><creatorcontrib>Dwyer, Terry</creatorcontrib><creatorcontrib>Burgner, David</creatorcontrib><creatorcontrib>Wake, Melissa</creatorcontrib><title>Do body mass index and waist-to-height ratio over the preceding decade predict retinal microvasculature in 11–12 year olds and midlife adults?</title><title>International Journal of Obesity</title><addtitle>Int J Obes</addtitle><addtitle>Int J Obes (Lond)</addtitle><description>Background/objectives Microvascular changes may contribute to obesity-associated cardiovascular disease. We examined whether body mass index (BMI) and waist-to-height ratio (WHtR) (1) at multiple earlier time points and (2) decade-long trajectories predicted retinal microvascular parameters in mid-childhood/adulthood. Methods Participants/design: 1288 11–12 year olds (51% girls) and 1264 parents (87% mothers) in the population-based Child Health CheckPoint (CheckPoint) module within the Longitudinal Study of Australian Children (LSAC). LSAC exposure measures: biennial BMI z -score and WHtR for children at five time points from age 2–3 to 10–11 years and self-reported parent BMI at six time points from child age 0–1 years to 10–11 years. CheckPoint outcome measures: retinal arteriolar and venular caliber. Analyses: BMI/WHtR trajectories were identified by group-based trajectory modeling; linear regression models estimated associations between BMI/WHtR at each time point/trajectories and later retinal vascular caliber, adjusted for age, sex, and family socioeconomic status. Results In time point analyses, higher child BMI/WHtR from age 4 to 5 years was associated with narrower arteriolar caliber at the age of 11–12 years, but not venular caliber. For example, each standard deviation higher in BMI z -score at 4–5 years was associated with narrower arteriolar caliber at 11–12 years (standardized mean difference (SMD): −0.05, 95% confidence interval (CI): −0.10 to 0.01); by 10–11 years, associations had doubled to −0.10 (95% CI: −0.16 to −0.05). In adults, these finding were similar, except the magnitude of BMI and arteriolar associations were similar across all time points (SMD: −0.11 to −0.13). In child and adult BMI trajectory analyses, less favorable trajectories predicted narrower arteriolar ( p- trend &lt; 0.05), but not venular ( p- trend &gt; 0.1), caliber. Compared with those in the average BMI trajectory, SMDs in arterial caliber for children and adults in the highest trajectory were −0.25 (95% CI: −0.44 to −0.07) and −0.42 (95% CI: −0.73 to −0.10), respectively. Venular caliber showed late associations with child WHtR, but not with BMI in children or adults. Conclusions Associations of decade-long high BMI trajectories with narrowed retinal arteriolar caliber emerge in children, and are clearly evident by midlife. Adiposity appears to exert its early adverse life course impacts on the microcirculation more via arteriolar than venular mechanisms.</description><subject>692/163/2743/393</subject><subject>692/499</subject><subject>Adipose tissue</subject><subject>Adults</subject><subject>Age</subject><subject>Body mass index</subject><subject>Body size</subject><subject>Cardiovascular diseases</subject><subject>Children</subject><subject>Children &amp; youth</subject><subject>Confidence intervals</subject><subject>Correlation analysis</subject><subject>Epidemiology</subject><subject>Health aspects</subject><subject>Health Promotion and Disease Prevention</subject><subject>Internal Medicine</subject><subject>Longitudinal studies</subject><subject>Medicine</subject><subject>Medicine &amp; Public Health</subject><subject>Metabolic Diseases</subject><subject>Microvasculature</subject><subject>Obesity</subject><subject>Parents</subject><subject>Prognosis</subject><subject>Public Health</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Retina</subject><subject>Socioeconomics</subject><subject>Statistical analysis</subject><subject>Trajectory analysis</subject><issn>0307-0565</issn><issn>1476-5497</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9ks9u1DAQxiMEoqXwAFyQJSTEJcV2bCc5oar8lSpx6d2a2JNdV0682E5hbzwCEm_Ik-DtFkoRIB8szfy-Gc3MV1WPGT1mtOleJMEapWrKaU1lJ-r-TnXIRKtqKfr2bnVIG9qWjJIH1YOULiilUlJ-vzpouChPqcPq66tAhmC3ZIKUiJstfiYwW_IJXMp1DvUa3WqdSYTsAgmXGEleI9lENGjdvCIWDdirgHWmcJjdDJ5MzsRwCcksHvISsZQmjH3_8o1xskWIJHibrjpNzno3IgG7-JxePqzujeATPrr-j6rzN6_PT9_VZx_evj89OauNFCzXne06ReVIFe0tB2CMY8-V4QJbo0aj2n7oALmRqEpm4ANAz2AQnDWWd81R9XxfdhPDxwVT1pNLBr2HGcOSNBdUKFG2qgr69A_0IiyxDLmjWtUKIVv-f4qrlkratTfUCjxqN48hRzC71vpENVTyrlesUMd_oWC36LLXMOPoSvyW4NlvgjWCz-sU_FJuNqfbINuD5TopRRz1JroJ4lYzqnee0ntP6eIpvfOU7ovmyfVkyzCh_aX4aaIC8D2QSmpeYbwZ_d9VfwBAJ9S8</recordid><startdate>20200801</startdate><enddate>20200801</enddate><creator>Liu, Mengjiao</creator><creator>Lycett, Kate</creator><creator>Wong, Tien Yin</creator><creator>Kerr, Jessica A.</creator><creator>He, Mingguang</creator><creator>Juonala, Markus</creator><creator>Olds, Tim</creator><creator>Dwyer, Terry</creator><creator>Burgner, David</creator><creator>Wake, Melissa</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T2</scope><scope>7TK</scope><scope>7TS</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-2091-7663</orcidid><orcidid>https://orcid.org/0000-0002-8337-7633</orcidid><orcidid>https://orcid.org/0000-0001-9498-364X</orcidid><orcidid>https://orcid.org/0000-0002-3150-4047</orcidid></search><sort><creationdate>20200801</creationdate><title>Do body mass index and waist-to-height ratio over the preceding decade predict retinal microvasculature in 11–12 year olds and midlife adults?</title><author>Liu, Mengjiao ; 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We examined whether body mass index (BMI) and waist-to-height ratio (WHtR) (1) at multiple earlier time points and (2) decade-long trajectories predicted retinal microvascular parameters in mid-childhood/adulthood. Methods Participants/design: 1288 11–12 year olds (51% girls) and 1264 parents (87% mothers) in the population-based Child Health CheckPoint (CheckPoint) module within the Longitudinal Study of Australian Children (LSAC). LSAC exposure measures: biennial BMI z -score and WHtR for children at five time points from age 2–3 to 10–11 years and self-reported parent BMI at six time points from child age 0–1 years to 10–11 years. CheckPoint outcome measures: retinal arteriolar and venular caliber. Analyses: BMI/WHtR trajectories were identified by group-based trajectory modeling; linear regression models estimated associations between BMI/WHtR at each time point/trajectories and later retinal vascular caliber, adjusted for age, sex, and family socioeconomic status. Results In time point analyses, higher child BMI/WHtR from age 4 to 5 years was associated with narrower arteriolar caliber at the age of 11–12 years, but not venular caliber. For example, each standard deviation higher in BMI z -score at 4–5 years was associated with narrower arteriolar caliber at 11–12 years (standardized mean difference (SMD): −0.05, 95% confidence interval (CI): −0.10 to 0.01); by 10–11 years, associations had doubled to −0.10 (95% CI: −0.16 to −0.05). In adults, these finding were similar, except the magnitude of BMI and arteriolar associations were similar across all time points (SMD: −0.11 to −0.13). In child and adult BMI trajectory analyses, less favorable trajectories predicted narrower arteriolar ( p- trend &lt; 0.05), but not venular ( p- trend &gt; 0.1), caliber. Compared with those in the average BMI trajectory, SMDs in arterial caliber for children and adults in the highest trajectory were −0.25 (95% CI: −0.44 to −0.07) and −0.42 (95% CI: −0.73 to −0.10), respectively. Venular caliber showed late associations with child WHtR, but not with BMI in children or adults. Conclusions Associations of decade-long high BMI trajectories with narrowed retinal arteriolar caliber emerge in children, and are clearly evident by midlife. Adiposity appears to exert its early adverse life course impacts on the microcirculation more via arteriolar than venular mechanisms.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>32424266</pmid><doi>10.1038/s41366-020-0584-9</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-2091-7663</orcidid><orcidid>https://orcid.org/0000-0002-8337-7633</orcidid><orcidid>https://orcid.org/0000-0001-9498-364X</orcidid><orcidid>https://orcid.org/0000-0002-3150-4047</orcidid><oa>free_for_read</oa></addata></record>
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source Nature Journals Online; SpringerLink Journals - AutoHoldings
subjects 692/163/2743/393
692/499
Adipose tissue
Adults
Age
Body mass index
Body size
Cardiovascular diseases
Children
Children & youth
Confidence intervals
Correlation analysis
Epidemiology
Health aspects
Health Promotion and Disease Prevention
Internal Medicine
Longitudinal studies
Medicine
Medicine & Public Health
Metabolic Diseases
Microvasculature
Obesity
Parents
Prognosis
Public Health
Regression analysis
Regression models
Retina
Socioeconomics
Statistical analysis
Trajectory analysis
title Do body mass index and waist-to-height ratio over the preceding decade predict retinal microvasculature in 11–12 year olds and midlife adults?
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