# Associations of childhood adiposity with adult intima-media thickness and inflammation: a 20-year longitudinal population-based cohort

Tomona Fujikawa, Masatake Kobayashi, Sandra Wagner, Kevin Duarte, Pauline Scherdel, Barbara Heude, Vincent Dupont, Erwan Bozec, Emmanuel Bresso, Faiez Zannad, et al.

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## To cite this version:

Tomona Fujikawa, Masatake Kobayashi, Sandra Wagner, Kevin Duarte, Pauline Scherdel, et al. "Associations of childhood adiposity with adult intima-media thickness and inflammation: a 20-year longitudinal population-based cohort." Journal of Hypertension, 2023, 41 (3), pp.402-410. 10.1097/HJH.0000000000003343. hal-04097408

HAL Id: hal-04097408

https://hal.univ-lorraine.fr/hal-04097408

Submitted on 15 May 2023

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# Associations of Childhood Adiposity with Adult Intima Media Thickness and Inflammation: A 20-Year Longitudinal Population-based Cohort

**Running title:** Childhood adiposity, adult carotid IMT and inflammation

Tomona Fujikawa*¹, Masatake Kobayashi*¹, Sandra Wagner¹, Kevin Duarte¹, Pauline Scherdel², Barbara Heude², Vincent Dupont³,⁴, Erwan Bozec¹, Emmanuel Bresso¹, Faiez Zannad¹, Patrick Rossignol¹, Nicolas Girerd¹

1. Université de Lorraine, Centre d'Investigations Cliniques Plurithématique 1433, INSERM 1116, CHRU de Nancy, France; F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists Network, France.

2. INSERM, UMR1153 Epidemiology and Biostatistics Sorbonne Paris Cité Center (CRESS), Early determinants of the child's health and development Team (ORCHAD), Paris, France, Paris Descartes University, France.

3. Departement of Nephrology, Centre Hospitalier Universitaire de Reims, Reims, France.

4. French Clinical Research Infrastructure Network, Investigation Network Initiative - Cardiovascular and Renal Clinical Trialists (F-CRIN INI-CRCT), Reims, France.

**Corresponding Author:**

Pr. Nicolas Girerd

Centre d'Investigation Clinique Pierre Drouin -INSERM - CHRU de Nancy, Institut lorrain du coeur et des vaisseaux Louis Mathieu, Nancy, France

Address: 4, rue du Morvan. 54500 Vandoeuvre-Les-Nancy

E-mail: n.girerd@chru-nancy.fr

Phone: +33383157496

Fax: +33383157324

**Tables and figures:** 2 tables and 2 figures

**Funding:**

The STANISLAS Cohort visit 4 is sponsored by the Nancy CHRU and is funded in part by the Programme Hospitalier de Recherche Clinique Interrégional. Biomarker studies are co-funded by the French National Research Agency Fighting Heart Failure (ANR-15-RHU-0004) and FEDER Lorraine, and all French co-authors are supported by the French PIA project "Lorraine Université d'Excellence" GEENAGE (ANR-15-IDEX-04-LUE) programs, and the Contrat de Plan Etat Région Lorraine and FEDER IT2MP. The research leading to these results has also received funding from the European Union Commission's Seventh Framework program under grant agreement No. 305507 (HOMAGE). We also acknowledge support from the "EXPERT" ERA-CVD 2016 and MR-Focus (both grants managed by the French National Research Agency).

**Acknowledgments:**

We are highly grateful to the Vandoeuvre-Lès Nancy Centre de Médecine Préventive staff, and to Dr Sophie Visvikis-Siest (Inserm U1122) who managed the STANISLAS Cohort for the first three visits.

The authors warmly thank the Staff of the Clinical Investigation Center and other personnel

<footnote>* co-first authors</footnote>
involved in the STANISLAS Cohort management: Biostatisticians: Fay R, Lamiral Z, Machu JL. Computer scientists: Boucenna N, Gallina-Muller C, Maclot PL, Sas T. Co-investigators: Chau K, Di Patrizio P, Dobre D, Gonthier D, Huttin O, Malingrey L, Mauffrey V, Olivier A, Poyeton T, Steyer E, Watfa G. Datamanagers: Cimon P, Eby E, Merckle L. Data entry operators: Batsh M, Blanger O, Bottelin C, Haskour N, Jacquet V, Przybylski MC, Saribekyan Y, Thomas H, Vallee M. Echocardiographists, echographists: Ben Sassi M, Cario S, Camara Y, Coiro S, Frikha Z, Kearney-Schwartz A, Selton-Suty C, Watfa G. Imaging engineer: Bozec E. Laboratory Engineer Nuee-Capiaumont J and Technicians: Fruminet J, Kuntz M, Ravey J, Rousseau E, Tachet C. Project managers: Bouali S, Hertz C. Quality engineer: Lepage X. Registered nurses: Giansily M, Poinsignon L, Robin N, Schmartz M, Senn M, Micor-Patrignani E, Toutlemonde M. Hospital technician: Fleurot MT. Resident physicians: Alvarez- Vasquez R, Amiot M, Angotti M, Babel E, Balland M, Bannay A, Basselin P, Benoit P, Bercand J, Bouazzi M, Boubel E, Boucherab- Brik N, Boyer F, Champagne C, Chenna SA, Clochey J, Czolnowski D, Dal-Pozzolo J, Desse L, Donetti B, Dugelay G, Friang C, Galante M, Garel M, Gellenoncourt A, Guillin A, Hariton ML, Hinsiger M, Haudiquet E, Hubert JM, Hurtaud A, Jabbour J, Jeckel S, Kecha A, Kelche G, Kieffert C, Laurie`re E, Legay M, Mansuy A, Millet-Muresan O, Meyer N, Mourton E, Naude´ AL, Pikus AC, Poucher M, Prot M, Quartino A, Saintot M, Schiavi A, Schumman R, Serot M, Sert C, Siboescu R, Terrier-de-la-Chaise S, Thiesse A, Thietry L, Vanesson M, Viellard M. Secretaries: De Amorin E, Villemain C, Ziegler N. Study Coordinators: Dauchy E, Laurent S, and all persons not listed above who helped in the funding, initiation, accrual, management and analysis of the fourth visit of the STANISLAS cohort. The authors also thank the Nancy CHRU CRB Lorrain for its management of the biobank. Steering committee: Pierre Mutzenhardt, Mehdy Siaghy, Patrick Lacolley, Marie-Ange Luc, Pierre-Yves Marie, Jean-Michel Vignaud. Advisory members: Sophie Visvikis Siest, Faiez Zannad. Technical committee: Christiane Branlant, Isabelle Behm-Ansmant, Jean-Michel Vignaud, Christophe Philippe, Jacques Magdalou, Faiez Zannad, Patrick Rossignol. Scientific committee: Laurence Tiret, Denis Wahl, Athanase Benetos, Javier Diez, Maurizio Ferrari, Jean-Louis Gueant, Georges Dedoussis, François Alla, François Gueyffier, Pierre-Yves Scarabin, Claire Bonithon Kopp, Xavier Jouven, Jean-Claude Voegel, Jan Staessen.

The Knut and Alice Wallenberg Foundation is also acknowledged for its generous support.

**Conflict of interest:**

NG, PR and FZ are supported by the French National Research Agency Fighting Heart Failure (ANR-15-RHU-0004), by the French PIA project Lorraine Université d'Excellence GEENAGE (ANR-15-IDEX-04-LUE) programs, and the Contrat de Plan Etat Région Lorraine and FEDER IT2MP. NG received consulting fees from Novartis, AstraZeneca and Boehringer. PR reports grants and personal fees from AstraZeneca, Bayer, CVRx, Fresenius, and Novartis, personal fees from Grunenthal, Servier, Stealth Peptides, Vifor Fresenius Medical Care Renal Pharma, Idorsia, NovoNordisk, Ablative Solutions, G3P, Corvidia, Relypsa. FZ reports personal fees from Boehringer Ingelheim; personal fees from Janssen, Novartis, Boston Scientific, Amgen, CVRx, AstraZeneca, Vifor Fresenius, Cardior, Cereno Pharmaceutical, Applied Therapeutics, Merck, Bayer and Cellprothera outside the submitted work; and other support from CVCT and Cardiorenal, outside the submitted work. JPF has received consulting fees from Boehringer Ingelheim. All other authors report no conflicts of interest with regard to this article.
**Abstract**

**Background**

The associations between childhood adiposity and adult increased carotid intima thickness (cIMT) have been well-established, which might be corroborated by the association between adiposity in children and inflammation in adults. However, longitudinal data regarding biological pathways associated with childhood adiposity are lacking.

**Methods**

The present study included participants from the STANISLAS cohort who had adiposity measurements at age 5-18 years (N=519, mean [SD] age, 13.0 [2.9] years; 46.4% male), and who were measured with cIMT, vascular- and metabolic-related proteins at a median follow-up of 19±2 years. Body mass index (BMI), waist-to-height ratio and waist circumference were converted to age- and sex-specific z-scores.

**Results**

A minority of children were overweight/obese (16.2% overweight-BMI z-score>1; 1.3% obesity-z-score>2). Higher BMI, waist-height ratio and waist circumference in children were significantly associated with greater adult cIMT in univariable analysis, although not after adjusting for C-reactive protein (CRP). These associations were more pronounced in those with consistently high adiposity status from childhood to middle-adulthood. Participants with higher adiposity during childhood (BMI or waist-height ratio) had higher levels of insulin-like growth factor binding protein-1, and -2, matrix metalloproteinase-3, osteoponin, hemoglobin and CRP at adulthood. Network analysis showed that interleukin-6, insulin-like growth factor-1 and fibronectin were the key proteins associated with childhood adiposity.

**Conclusions**

In a population-based cohort followed for 20 years, higher BMI or waist-to-height ratio in childhood was significantly associated with greater cIMT and enhanced levels of proteins reflective of inflammation, supporting the importance of inflammation as the progressive atherosclerosis in childhood adiposity.

**Keywords:** childhood adiposity, carotid intima media thickness, biomarkers, inflammation.
**Introduction**

The prevalence of overweight and obesity has substantially increased in children over the last decades ¹. Large epidemiological studies have established that a high childhood adiposity status is associated with a risk of increased carotid intima media thickness (cIMT) in mid-adulthood ²,³. However, given that childhood adiposity is highly related to adult adiposity, the attributable risk specific to childhood adiposity is difficult to quantify. Hence, the assessment of trajectories of child-to-adult adiposity may better discriminate the relative impact of childhood and/or adult adiposity status on adult increased cIMT.

The underlying mechanisms in adults associated with childhood adiposity might underpin the associations between childhood adiposity and adult increased cIMT. Inflammation is related to adiposity and atherosclerotic disease but the interplay between these 3 features (adiposity, atherosclerotic disease, and inflammation) were predominantly studied in cross-sectional studies⁴⁻⁶. Longitudinal data whether children with adiposity status were prone to have heightened inflammation status in adults are lacking. An approach to better understand biological pathways is to use knowledge-based network analysis on the results retrieved by circulating protein analysis. This approach may help better understand which circulating proteins may be pivotal of these protein-protein relationships ⁷,⁸.

In the STANISLAS (Suivi Temporaire Annuel Non-Invasif de la Santé des Lorrains Assurés Sociaux) cohort followed over 20 years, circulating proteins of various pathophysiological pathways were collected⁹. In the present study, we aimed at exploring: 1) the association between childhood adiposity and adult cIMT as well as circulating proteins expressing vasculature and adiposity, 2) the associations of child-to-adult adiposity trajectories with adult cIMT, and 3) identifying the biological pathways underlying the association between childhood adiposity and adult vascular alterations.
# Methods

## Study population

The STANISLAS cohort is a single-center familial longitudinal cohort from the Nancy region in France, the features of which have been previously described¹⁰. Among 4,295 participants undergoing the 1st cohort visit from 1993 to 1995, 519 children aged 5 to 18 years with available data on vascular variables at the 4th visit (from 2011 to 2016) were included in the current analysis (Supplemental Figure 1). The study was approved by the Ethics Committee (Comité de Protection des Personnes Est III, Nancy, France), and all study participants gave their written informed consent to participate (ClinicalTrials.gov identifier NCT01391442).

All participants completed medical and socio-demographic questionnaires, and underwent a physical examination and vascular measurements. Collected variables included age, sex, height, weight, smoking status and physical activity. Standard biochemical blood parameters included triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, blood glucose, glycated hemoglobin and estimated glomerular filtration rate (eGFR, as calculated from the Schwartz formula in children¹¹, and the Chronic Kidney Disease Epidemiology Collaboration formula in adults¹²). Metabolic syndrome in adults was defined according to Adult Treatment Panel III criteria¹³.

## Body mass index, waist circumference and waist-to-height ratio

BMI was calculated by weight in kilograms divided by the square of the height in meters. Waist circumference was measured at the narrowest level, and waist-to-height ratio was calculated from the ratio of waist circumference and height. Body mass index (BMI) was converted to age- and sex-specific z score based on the International Obesity Task Force (IOTF)¹⁴, while waist-to-height ratio and waist circumference were based on the Third National Health and Nutrition Examination Survey (NHANES III)¹⁵. Overweight and obesity
were respectively defined by a BMI z-score >1 and >2 as proposed by the IOTF¹⁶.

## Vascular variables

cIMT was measured by high-resolution echo-tracking in a controlled environment at 22±1°C after 10 min of rest in the supine position. Carotid diameter, distension and intima media thickness were measured on the right common carotid artery¹⁷. Examinations were successively performed with the wall track system (WTS, ESOATE, Maastricht, The Netherlands) and the ART.LAB (ESAOTE, Maastricht, The Netherlands). The detailed methodology and excellent reproducibility of cIMT measurements in this cohort has previously been reported¹⁸.

## Circulating proteins

For vascular-related biomarkers, extracellular matrix remodeling in vasculature, angiogenesis and endothelial cell dysfunction were supported by the expression of matrix metalloproteinase-2 (MMP-2), MMP-3, MMP-9, vascular endothelial growth factor A (VEGF-A), bone morphogenetic protein-9 (BMP-9), insulin-like growth factor binding protein-1 (IGFBP-1), IGFBP-2, osteopontin (OPN) and Cystatin C¹⁹⁻²⁶. For adiposity-related biomarkers, fatty acid-binding protein-4 (FABP-4), leptin, resistin, cystatin C, kidney injury molecule-1 (KIM-1), hemoglobin, interferon-gamma (IFN-γ), C-reactive protein (CRP), triglycerides were also studied²⁷⁻²⁹. These selected biomarkers were measured using Olink Proseek® Multiplex cardiometabolic, cardiovascular II, III and Inflammation 96x96 kits in serum using proximity extension assay technology (https://www.olink.com/products/complete-protein-biomarkers-list) ³⁰.

## Complex network analysis

The Fight-HF graph knowledge box was used to build the complex network⁷. Direct interaction between studied biomarkers were extracted from the STRING database ³¹. The other proteins known to directly interact with at least five biomarkers were added to the
network. Biomarkers belonging to the same REACTOME pathway were linked as indirect interaction<sup>32</sup>.

**Statistical analysis**

Categorical variables are presented as frequencies (percentages) and continuous variables as means ± standard deviation or median (25th and 75th percentiles) depending on variable distribution. Comparisons of demographic, clinical and biological variables according to tertiles of childhood adiposity status were analyzed using ANOVA, Kruskal-Wallis test and $\chi^2$ test, as appropriate.

Linear regression analyses were used to study the associations of childhood adiposity as assessed by BMI, waist-height ratio, and waist-circumference with adult vascular variables. These models were adjusted for clinical variables specific for the childhood and adult periods, respectively: childhood model – age, sex, systolic blood pressure (BP), blood glucose, total cholesterol, triglycerides and natural log of C-reactive protein (CRP); adult model – age, sex, prevalence of metabolic syndrome<sup>33</sup>, hypertension, systolic BP, diastolic BP, total cholesterol and triglycerides.

To assess whether the biomarkers were expressed differently between children with higher (top tertile) and lower (bottom tertile) BMI or waist-height ratio, multinomial logistic regression analyses were performed after adjustment for respective BMI or waist-height ratio in adults as an independent variable plus age, a prevalence of metabolic syndrome, hypertension, diabetes mellitus, systolic BP and total cholesterol.

All analyses were performed using R version 4.0.1 (R Development Core Team, Vienna, Austria). A two-sided p-value <0.05 was considered statistically significant.

**Results**

**Baseline characteristics according to childhood adiposity**

Among the 519 children included in this study, slightly less than a half were males
(46.4%), mean age (SD) was 13.0 (2.9) years, 38.7% (N=201) were adolescents (≥14 years), mean BMI z-score was 0.04 (0.90) (16.2% overweight, 1.3% obesity) and the median follow-up period was 19.1 years (25th and 75th centiles 17.9 to 20.0).

Children with higher age- and sex-standardized BMI had higher CRP levels at childhood, and more frequent prevalence of metabolic syndrome at adulthood (all-p-values < 0.05) (Table 1). Children with higher age- and sex-standardized waist-height ratio were male, had higher blood pressure, lower heart rates, greater inflammation status at childhood, higher BP and cIMT at adulthood (Table 1).

Baseline characteristics according to the tertiles of age- and sex-standardized waist circumference are presented in *Supplemental Table 1*. Baseline characteristics associated with waist circumference were similar to those associated with waist-to-height ratio.

## Associations between childhood adiposity and adult intima media thickness

In univariable models, high childhood adiposity status as assessed by higher BMI, waist-height ratio and waist circumference was significantly and consistently associated with greater cIMT at adulthood. These associations persisted after adjustment for clinical covariates measured at both childhood and adult periods. However, after adjustment for covariates including CRP measured at childhood, these associations no longer remained significant (all p-values > 0.05) (Table 2).

The observed associations between childhood adiposity status and adult cIMT were similar in adolescents (≥14years) and children (<14years) (all-P for interaction > 0.10), whereas the associations between childhood adiposity status and cIMT were prominent in females (all-P for interaction < 0.01) (Supplemental Table 2).

The association of overweight or obesity in children with adult cIMT was not modified by CRP levels in children (P-value>0.10).

## Association between child-to-adult adiposity trajectories and adult intima media
thickness

Subjects were divided into 4 categories according to a median value of childhood and adult adiposity (i.e., BMI, waist-to-height ratio and waist circumference). Subjects with consistently high BMI from childhood to middle adulthood were likely to have a greater cIMT than those who had low BMI in both periods, with these associations persisting after adjustment for potential confounders (Figure 1 & Supplemental Table 3). In addition, subjects who had a high waist-to-height ratio as adults, irrespective of their childhood waist-to-height ratio, were likely to have greater cIMT, with these associations also remaining significant even in multivariable models (Figure 1 & Supplemental Table 3).

Complex network analysis

IGFBP-1, IGFBP-2, MMP-3, osteoponin, hemoglobin and CRP levels were significantly higher (up-regulated), whereas VEGF-A, FABP-4, leptin, and IFN-gamma were significantly lower (down-regulated) in individuals with higher childhood adiposity status (based on BMI or waist-height ratio) (Supplemental Table 4). Among these proteins associated with childhood adiposity, interleukin-6 (IL-6), insulin-like growth factor-1 (IGF-1) and fibronectin were the pivotal proteins linked to 5 proteins. Figure 2.

Discussion

In the present French population-based cohort followed over a period of 20 years, a higher adiposity status as assessed by higher BMI, waist-height ratio or waist circumference in childhood was found to be consistently and independently associated with greater cIMT in adulthood, although these associations no longer remained significant after adjusting for inflammation (as assessed by CRP at childhood). In addition, subjects with consistently high BMI from childhood to adulthood were likely to have greater cIMT in adulthood. Inflammation, as expressed by IL-6 and IGF-1, may possibly represent central proteins associated with childhood
adiposity.

Taken together, these data point to the potential relevance of inflammatory-related pathways in explaining the associations between childhood adiposity and middle-age atherosclerosis.

## Associations between childhood adiposity and adult cIMT

In the present study, the proportions of overweight and obese children were similar to those documented in previous reports³⁴, ³⁵. Childhood adiposity as assessed by higher BMI, waist-height-ratio or waist circumference was associated with greater cIMT in middle-aged adults², 3, 36, 37. Furthermore, subjects with consistently high BMI from childhood to adulthood were likely to have greater cIMT in adults, which are consistent with previous reports³, 36. By contrast, higher waist-to-height ratio in adults rather than children was associated with greater adult cIMT. These findings suggest that waist circumference may less likely express adiposity status particularly in children, and that assessing childhood abdominal fat may be less reliable to predict the degree of adult cIMT. Interestingly, although physiological studies show overweight or obese individuals have higher or similar heart rate than lean ones, in the current analysis, higher waist circumference was associated with lower heart rate. As, in prior studies, body weight and height-based measurements (i.e., BMI) were used to define overweight or obesity ³⁸, ³⁹. This may have an impact on the results as larger height has been shown to be associated with lower heart rate⁴⁰, which may counterbalance the differences in heart rate among BMI tertile groups.

Of note, the association between childhood adiposity status and adult increased cIMT was more pronounced in females than in males, which may be partly explained by the substantial sex-related differences in the adipose distribution ⁴¹, ⁴². Women are likely to have greater peripheral fat depots and lower skeletal muscle mass, while men are likely to have greater central adiposity and higher skeletal muscle mass. Although prior longitudinal data was consistent with our results ⁴³, such sex-related differences are modified by several
environmental factors (i.e., diet, physical activity), and further data are required to rigorously
evaluate these sex-related interactions. Of further interest, all observed associations between
childhood adiposity status and adult cIMT lost their statistical significance when CRP was
included in the multivariable models. Although, among middle-aged adults, our team reported
that adiposity was an important predictor of long-term increases in pulse wave velocity,
independent of inflammation status<sup>44</sup>, the current findings may highlight that adiposity status
in children induces an inflammation state, which may be involved in atherosclerotic
progression<sup>45, 46</sup>. Our observations, therefore, suggest that inflammation may be a key
biological factor underlying the association between childhood adiposity status and adult
cIMT.

Inflammation markers as central proteins associated with childhood adiposity

A growing number of papers use many circulating proteins resulting in many relevant
associations. Filtration and/or integration of these associations, therefore, should be required
to better interpret the results. In this regard, network analysis is becoming a relevant step of
omics-based analyses to better demonstrate protein, disease, and pathway relations.

Our network analysis demonstrated that childhood adiposity was associated with
inflammatory response over 20 years, which was mainly mediated by IL-6 and IGF-1 in the
network analysis. IL-6 is a well-known cytokine involved in the regulation of the
inflammation and immune response<sup>47</sup>. IL-6 and interleukin-1β as a driver of IL-6, play important
roles on progressive atherosclerosis such as the development of atherothrombotic plaque, the
advancement of monocyte/leukocyte adhesion to vascular endothelial cells, and the progress of
vascular smooth-muscle cells<sup>48, 49</sup>. Prior reports showed higher IL-6 levels were associated with
greater degrees of cIMT in population settings<sup>50, 51</sup>. IGF-1 is also known as a mediator of
inflammation response, and its excess induces pro-inflammatory cytokine production, may
promote endothelial dysfunction, and increase oxidative stress, possibly contributing to the
progression of atherosclerosis<sup>52, 53</sup>. Fibronectin, another central protein in our network, may represent a link between inflammation and vascular remodeling: Budatha and collegues reported that fibronectin and integrin α5 signaling are key elements of pathological vascular remodeling in hypertension models<sup>54</sup>. Fibronectin in injured, remodeled, or inflamed vessels, could sensitize endothelial cells to inflammation through integrins upregulation<sup>54</sup>.

Taken together, these findings highlighted that childhood adiposity was associated with inflammatory-related process in adults, irrespective of adult adiposity status, and that inflammation, supported by fibronectin sensitization, may be a key determinant of progressing atherosclerosis as evaluated by cIMT.

**Clinical perspectives**

Increased cIMT is associated with a high risk of future development of atherosclerotic diseases such as stroke and/or coronary artery disease<sup>55, 56</sup>. Our results consequently suggest that childhood adiposity is associated with deleterious long-term vascular evolution. From a prevention perspective, assessing childhood adiposity status and subsequently implementing interventions toward weight reduction should therefore be promoted, as already emphasized in several studies<sup>3, 36</sup>.

Our findings emphasize the importance of inflammation pathway in the link between childhood adiposity and adult atherosclerotic disease. Indeed, the conjunction of adiposity and inflammation, possibly related to visceral obesity, appears as a potent vector of long-term vascular impairment<sup>57</sup>.

Recently published data showed that, canakinumab, as anti-inflammatory agents for Il-6 cytokine, diminished atherosclerotic progression in an experimental animal study<sup>58</sup>. Moreover, this treatment significantly reduced rate of recurrent cardiovascular events (i.e., myocardial infarction, stroke, or cardiovascular death), compared with placebo, independent of lipid-level lowering agents<sup>59</sup>. Further studies, therefore, should be required to test the effects of canakinumab on alterations in
intima media thickness, particularly in people who had a childhood adiposity status, in light of our
results.

## Limitations

Our results should be interpreted in light of the following limitations. This study is
limited by its inherent observational design; thus, causality cannot be inferred. The
proportions of overweight and obese children were relatively small, although these
proportions were similar to those in previous reports ³⁴, ³⁵. Waist-to-height ratio and waist
circumference were converted to age- and sex-specific z scores based on the NHANES III,
which is often applied to children in the US ¹⁵. Nevertheless, we observed similar associations
of BMI, waist-to-height ratio and waist circumference, suggesting that different scales may
have less of an impact on the observed associations between childhood adiposity and adult
vascular alterations. In addition, no data were available regarding vascular-related proteins
measured in the childhood period. Further study is warranted to externally validate our
findings in other community-based cohorts.

## Conclusions

In a population-based cohort followed for 20 years, higher BMI or waist-to-height
ratio in childhood was significantly associated with greater cIMT and enhanced levels of
proteins reflective of inflammation, supporting the importance of inflammation as the
progressive atherosclerosis in childhood adiposity.

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**Graphical abstract**

BMI, body mass index; IMT, intima media thickness; MMP3, matrix metalloproteinase-3; OPN, osteopontin; IGFBP1, insulin-like growth factor-1; IGFBP2, insulin-like growth factor-2; IFNG, interferon-gamma; LEP, leptin; FABP4, fatty acid-binding protein-4; CRP, C-reactive protein; VEGF-A, vascular endothelial growth factor-A; IL-6, interleukin-6; IGF-1, insulin-like growth factor-1; FN, fibronectin.

**Figure 1. Univariable model for the association of childhood-to-adult adiposity with adult cIMT**

Abbreviations are presented in Table 1.

**Figure 2. Network analysis relating the top proteins associated with body mass index and/or waist-height-ratio in children**

Network analysis presents that the top proteins are associated with higher vs lower levels of body mass index and/or waist-height-ratio in children.

MMP3, matrix metalloproteinase-3; OPN, osteopontin; IGFBP-1, insulin-like growth factor-1; IGFBP-2, insulin-like growth factor-2; IFNG, interferon-gamma; LEP, leptin; FABP-4, fatty acid-binding protein-4; CRP, C-reactive protein; VEGF-A, vascular endothelial growth factor-A; IL-6, interleukin-6; IGF-1, insulin-like growth factor-1; FN, fibronectin.
Graphical abstract

<figure><img src="image_3.png" /></figure>
<figure><img src="image_4.png" /><figcaption>Figure 1. Univariable model for the association of childhood-to-adult adiposity with adult cIMT</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figure 2. Network analysis relating the top proteins associated with body mass index and/or waist-height-ratio in children</figcaption></figure>
**Table 1. Baseline characteristics according to the tertiles of BMI and waist-to-height ratio z-scores in children**

Values are expressed as mean ±SD, n (%) or median (25th to 75th percentile)

BMI was converted to age- and sex-specific z score based on the International Obesity Task Force (IOTF)¹, while waist-to-height ratio was based on the Third National Health and Nutrition Examination Survey ².

BMI, body mass index; BP, blood pressure; eGFR, estimated glomerular filtration rate, CRP, C-reactive protein; MET, metabolic equivalent; IMT, intima media thickness.

**Table 2. Linear regression analyses of the association between childhood adiposity and adult cIMT**

A dependent variable was 10µm increase in adult carotid intima media thickness.

BMI was converted to age- and sex-specific z score based on the International Obesity Task Force (IOTF)¹, while waist-to-height ratio and waist circumference were based on the Third National Health and Nutrition Examination Survey ². Overweight and obesity were respectively defined by a BMI z-score >1 and >2 as proposed by the IOTF³.

Model for the childhood period included age, sex, systolic blood pressure, blood glucose, total cholesterol, and triglycerides.
Model for the adult period included age, sex, metabolic syndrome, hypertension, systolic blood pressure, blood glucose, total cholesterol, and triglycerides.

CI, confidential interval; remaining abbreviations are presented in Table 1.

**(References)**

1. Cole TJ and Lobstein T. Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity. Pediatr Obes. 2012;7:284-94.

2. Sharma AK, Metzger DL, Daymont C, Hadjiyannakis S and Rodd CJ. LMS tables for waist-circumference and waist-height ratio Z-scores in children aged 5-19 y in NHANES III: association with cardio-metabolic risks. Pediatr Res. 2015;78:723-9.

3. Cole TJ, Bellizzi MC, Flegal KM and Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ (Clinical research ed). 2000;320:1240-3.
<table><caption>Table 1. Baseline characteristics according to the tertiles of BMI and waist-to-height ratio z-scores in children</caption><thead><tr><th rowspan="2"></th><th colspan="3">BMI z score tertile</th><th colspan="4">Waist-to-height ratio z score tertile</th></tr><tr><th>T1,<br/>&lt; -0.35<br/>(N=173)</th><th>T2,<br/>-0.35 - 0.40<br/>(N=173)</th><th>T3,<br/>&gt; 0.40<br/>(N=173)</th><th>p-value</th><th>T1,<br/>&lt; -1.20<br/>(N=148)</th><th>T2,<br/>-1.20 - -0.53<br/>(N=146)</th><th>T3,<br/>&gt; -0.53<br/>(N=146)</th><th>p-value</th></tr></thead><tbody><tr><td colspan="9"><strong>Variables for the childhood period</strong></td></tr><tr><td>Age, years</td><td>12.5 ± 2.9</td><td>12.9 ± 2.9</td><td>13.1 ± 2.8</td><td>0.13</td><td>13.0 ± 2.8</td><td>12.9 ± 2.9</td><td>13.1 ± 2.8</td><td>0.84</td></tr><tr><td>Age ≥14 years, N (%)</td><td>57 (32.9 %)</td><td>73 (42.2 %)</td><td>71 (41.0 %)</td><td>0.16</td><td>56 (37.6 %)</td><td>66 (44.0 %)</td><td>58 (39.2 %)</td><td>0.50</td></tr><tr><td>Male, N (%)</td><td>83 (48.0 %)</td><td>81 (46.8 %)</td><td>77 (44.5 %)</td><td>0.81</td><td>35 (23.5 %)</td><td>73 (48.7 %)</td><td>98 (66.2 %)</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Height, cm</td><td>150 ± 16</td><td>154 ± 16</td><td>157 ± 15</td><td><strong>&lt;0.001</strong></td><td>155 ± 14</td><td>154 ± 17</td><td>154 ± 15</td><td>0.83</td></tr><tr><td>Weight, kg</td><td>37 ± 11</td><td>44 ± 12</td><td>54 ± 15</td><td><strong>&lt;0.001</strong></td><td>41 ± 11</td><td>44 ± 13</td><td>51 ± 16</td><td><strong>&lt;0.001</strong></td></tr><tr><td>BMI (z score)</td><td>-0.91 ± 0.48</td><td>-0.02 ± 0.21</td><td>1.05 ± 0.49</td><td><strong>&lt;0.001</strong></td><td>-0.63 ± 0.68</td><td>-0.01 ± 0.62</td><td>0.79 ± 0.79</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Waist circumference, cm</td><td>59 ± 6</td><td>63 ± 6</td><td>69 ± 8</td><td><strong>&lt;0.001</strong></td><td>59 ± 5</td><td>63 ± 6</td><td>69 ± 8</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Waist/Height ratio</td><td>0.39 ± 0.02</td><td>0.41 ± 0.02</td><td>0.44 ± 0.03</td><td><strong>&lt;0.001</strong></td><td>0.38 ± 0.01</td><td>0.41 ± 0.01</td><td>0.45 ± 0.03</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Regular sports activity</td><td>105 (60.7 %)</td><td>108 (62.4 %)</td><td>113 (65.3 %)</td><td>0.67</td><td>89 (59.7 %)</td><td>95 (63.3 %)</td><td>103 (69.6 %)</td><td>0.20</td></tr><tr><td colspan="9"><strong>Means for commuting to school</strong></td></tr><tr><td>Walking</td><td>73 (42.2 %)</td><td>64 (37.0 %)</td><td>62 (35.8 %)</td><td>0.55</td><td>62 (41.6 %)</td><td>64 (42.7 %)</td><td>48 (32.4 %)</td><td>0.19</td></tr><tr><td>Bicycle</td><td>3 (1.7 %)</td><td>3 (1.7 %)</td><td>1 (0.6 %)</td><td></td><td>4 (2.7 %)</td><td>1 (0.7 %)</td><td>2 (1.4 %)</td><td></td></tr><tr><td>Other</td><td>97 (56.1 %)</td><td>106 (61.3 %)</td><td>110 (63.6 %)</td><td></td><td>83 (55.7 %)</td><td>85 (56.7 %)</td><td>98 (66.2 %)</td><td></td></tr><tr><td>Birth weight, g</td><td>3231 ± 481</td><td>3265 ± 452</td><td>3376 ± 414</td><td>0.06</td><td>3235 ± 394</td><td>3314 ± 484</td><td>3309 ± 518</td><td>0.44</td></tr><tr><td>Birth height, cm</td><td>55 ± 45</td><td>50 ± 2</td><td>50 ± 2</td><td>0.33</td><td>50 ± 2</td><td>50 ± 2</td><td>50 ± 2</td><td>0.37</td></tr><tr><td>Systolic BP, mmHg</td><td>118 ± 11</td><td>119 ± 10</td><td>120 ± 13</td><td>0.55</td><td>117 ± 9</td><td>119 ± 12</td><td>121 ± 12</td><td><strong>0.03</strong></td></tr><tr><td>Diastolic BP, mmHg</td><td>62 ± 11</td><td>65 ± 10</td><td>65 ± 10</td><td>0.053</td><td>64 ± 10</td><td>62 ± 12</td><td>66 ± 9</td><td><strong>0.02</strong></td></tr><tr><td>Heart rate, bpm</td><td>72 ± 12</td><td>70 ± 11</td><td>68 ± 11</td><td>0.08</td><td>72 ± 11</td><td>70 ± 12</td><td>68 ± 11</td><td><strong>0.04</strong></td></tr><tr><td>Total cholesterol, g/l</td><td>1.84 ± 0.30</td><td>1.80 ± 0.30</td><td>1.84 ± 0.32</td><td>0.38</td><td>1.83 ± 0.31</td><td>1.81 ± 0.31</td><td>1.84 ± 0.32</td><td>0.57</td></tr><tr><td>Triglyceride, g/l</td><td>0.65 ± 0.35</td><td>0.64 ± 0.29</td><td>0.68 ± 0.33</td><td>0.35</td><td>0.64 ± 0.28</td><td>0.66 ± 0.36</td><td>0.68 ± 0.32</td><td>0.55</td></tr><tr><td>eGFR, ml/min/1.73m<sup>2</sup></td><td>126 ± 20</td><td>126 ± 21</td><td>126 ± 19</td><td>0.95</td><td>123 ± 19</td><td>128 ± 18</td><td>129 ± 23</td><td><strong>0.02</strong></td></tr><tr><td>CRP, mg/l</td><td>0.17<br/>(0.16 - 0.43)</td><td>0.22<br/>(0.16 - 0.52)</td><td>0.45<br/>(0.21 - 0.95)</td><td><strong>&lt;0.001</strong></td><td>0.17<br/>(0.16 - 0.53)</td><td>0.27<br/>(0.16 - 0.45)</td><td>0.38<br/>(0.17 - 0.81)</td><td><strong>&lt;0.001</strong></td></tr><tr><td colspan="9"><strong>Variables for the adult period</strong></td></tr><tr><td>Age, yrs</td><td>31.3 ± 3.8</td><td>31.3 ± 4.1</td><td>31.9 ± 3.7</td><td>0.20</td><td>31.6 ± 3.7</td><td>31.6 ± 3.5</td><td>31.9 ± 3.7</td><td>0.66</td></tr><tr><td>Height, cm</td><td>171 ± 9</td><td>171 ± 9</td><td>171 ± 10</td><td>0.97</td><td>170 ± 8</td><td>171 ± 9</td><td>173 ± 9</td><td><strong>0.018</strong></td></tr><tr><td>BMI, kg/m<sup>2</sup></td><td>22 ± 3</td><td>24 ± 3</td><td>27 ± 5</td><td><strong>&lt;0.001</strong></td><td>22 ± 3</td><td>24 ± 4</td><td>27 ± 5</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Hypertension, N (%)</td><td>3 (1.7 %)</td><td>4 (2.3 %)</td><td>7 (4.0 %)</td><td>0.39</td><td>4 (2.7 %)</td><td>3 (2.0 %)</td><td>5 (3.4 %)</td><td>0.76</td></tr><tr><td>Diabetes mellitus, N (%)</td><td>1 (0.6 %)</td><td>1 (0.6 %)</td><td>2 (1.2 %)</td><td>0.78</td><td>2 (1.3 %)</td><td>0 (0.0 %)</td><td>1 (0.7 %)</td><td>0.36</td></tr><tr><td>Metabolic syndrome, N (%)</td><td>2 (1.2 %)</td><td>3 (1.7 %)</td><td>13 (7.5 %)</td><td><strong>0.002</strong></td><td>1 (0.7 %)</td><td>4 (2.7 %)</td><td>11 (7.4 %)</td><td><strong>0.006</strong></td></tr><tr><td>Total MET, MET/min/week</td><td>1578<br/>(552 - 3930)</td><td>1288<br/>(356 - 2816)</td><td>1580<br/>(690 - 4044)</td><td>0.10</td><td>1212<br/>(445 - 2945)</td><td>1438<br/>(507 - 2868)</td><td>1427<br/>(594 - 4158)</td><td>0.33</td></tr><tr><td>Systolic BP, mmHg</td><td>114 ± 13</td><td>114 ± 13</td><td>115 ± 14</td><td>0.65</td><td>110 ± 12</td><td>114 ± 13</td><td>117 ± 14</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Diastolic BP, mmHg</td><td>65 ± 8</td><td>65 ± 7</td><td>66 ± 9</td><td>0.19</td><td>64 ± 7</td><td>65 ± 8</td><td>67 ± 9</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Heart rate, bpm</td><td>66 ± 9</td><td>63 ± 9</td><td>63 ± 9</td><td><strong>0.004</strong></td><td>65 ± 8</td><td>63 ± 10</td><td>63 ± 9</td><td>0.06</td></tr><tr><td>Total cholesterol, g/l</td><td>1.94 ± 0.36</td><td>1.96 ± 0.34</td><td>1.93 ± 0.33</td><td>0.78</td><td>1.96 ± 0.32</td><td>1.91 ± 0.38</td><td>1.97 ± 0.32</td><td>0.30</td></tr><tr><td>Triglyceride, g/l</td><td>0.92 ± 0.59</td><td>0.91 ± 0.50</td><td>0.97 ± 0.52</td><td>0.61</td><td>0.90 ± 0.47</td><td>0.93 ± 0.63</td><td>1.01 ± 0.56</td><td>0.22</td></tr><tr><td>Carotid IMT, µm</td><td>517<br/>(468 - 563)</td><td>522<br/>(484 - 579)</td><td>528<br/>(475 - 598)</td><td>0.15</td><td>518<br/>(475 - 572)</td><td>514<br/>(478 - 562)</td><td>540<br/>(478 - 610)</td><td><strong>0.038</strong></td></tr></tbody></table>
<table><caption>Table 2. Linear regression analyses of the association between childhood adiposity and adult cIMT</caption><thead><tr><th rowspan="3"></th><th colspan="6">Models with covariates measured in the childhood period</th><th colspan="2">Models with covariates measured at the adult period</th></tr><tr><th colspan="2">Crude model</th><th colspan="2">without CRP</th><th colspan="2">with CRP</th><th rowspan="2">p</th><th rowspan="2">adjusted-beta (95% CI)</th></tr><tr><th>beta (95% CI)</th><th>p</th><th>adjusted-beta (95% CI)</th><th>p</th><th>adjusted-beta (95% CI)</th><th>p</th></tr></thead><tbody><tr><td><strong>Body mass index</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Continuous</td><td>0.55 (0.31 to 0.78)</td><td><strong>&lt;0.001</strong></td><td>0.36 (0.01 to 0.72)</td><td><strong>0.043</strong></td><td>0.28 (-0.09 to 0.65)</td><td>0.14</td><td>0.44 (0.16 to 0.73)</td><td><strong>0.002</strong></td></tr><tr><td>Continuous (z-score)</td><td>0.97 (0.16 to 1.79)</td><td><strong>0.02</strong></td><td>0.91 (-0.06 to 1.89)</td><td>0.07</td><td>0.74 (-0.27 to 1.74)</td><td>0.15</td><td>0.92 (0.08 to 1.76)</td><td><strong>0.03</strong></td></tr><tr><td>Tertile, T1</td><td>(reference)</td><td></td><td>(reference)</td><td></td><td>(reference)</td><td></td><td>(reference)</td><td></td></tr><tr><td>T2</td><td>1.35 (-0.46 to 0.05)</td><td>0.14</td><td>1.67 (-0.50 to 3.85)</td><td>0.13</td><td>1.96 (-0.20 to 4.11)</td><td>0.08</td><td>1.48 (-0.40 to 3.35)</td><td>0.12</td></tr><tr><td>T3</td><td>1.86 (3.16 to 3.67)</td><td><strong>0.04</strong></td><td>1.67 (-0.52 to 3.85)</td><td>0.13</td><td>1.40 (-0.80 to 3.59)</td><td>0.21</td><td>1.69 (-0.18 to 3.56)</td><td>0.08</td></tr><tr><td>Overweight</td><td>1.52 (-0.50 to 3.53)</td><td>0.14</td><td>1.91 (-0.54 to 4.35)</td><td>0.17</td><td>0.82 (-1.79 to 3.44)</td><td>0.54</td><td>1.69 (-0.38 to 3.76)</td><td>0.11</td></tr><tr><td>Obesity</td><td>6.47 (0.11 to 12.82)</td><td><strong>0.046</strong></td><td>4.74 (-2.37 to 11.85)</td><td>0.19</td><td>1.80 (-5.77 to 9.37)</td><td>0.64</td><td>4.18 (-1.99 to 10.35)</td><td>0.18</td></tr><tr><td><strong>Waist/Height</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Continuous</td><td>2.39 (-0.02 to 4.80)</td><td>0.052</td><td>2.09 (-0.95 to 5.13)</td><td>0.18</td><td>1.16 (-2.03 to 4.36)</td><td>0.47</td><td>1.53 (-1.05 to 4.10)</td><td>0.24</td></tr><tr><td>Continuous (z-score)</td><td>1.41 (0.36 to 2.46)</td><td><strong>0.009</strong></td><td>0.78 (-0.57 to 2.13)</td><td>0.26</td><td>0.36 (-1.03 to 1.75)</td><td>0.61</td><td>0.69 (-0.47 to 1.86)</td><td>0.24</td></tr><tr><td>Tertile, T1</td><td>(reference)</td><td></td><td>(reference)</td><td></td><td>(reference)</td><td></td><td>(reference)</td><td></td></tr><tr><td>T2</td><td>0.05 (-1.93 to 2.02)</td><td>0.96</td><td>-0.57 (-2.90 to 1.76)</td><td>0.63</td><td>-0.41 (-2.74 to 1.91)</td><td>0.73</td><td>-0.96 (-2.98 to 1.06)</td><td>0.35</td></tr><tr><td>T3</td><td>2.77 (0.79 to 4.74)</td><td><strong>0.006</strong></td><td>0.86 (-1.64 to 3.37)</td><td>0.50</td><td>0.69 (-1.88 to 3.26)</td><td>0.60</td><td>0.97 (-1.17 to 3.12)</td><td>0.37</td></tr><tr><td><strong>Waist circumference</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Continuous</td><td>0.31 (0.21 to 0.41)</td><td><strong>&lt;0.001</strong></td><td>0.20 (0.03 to 0.37)</td><td><strong>0.02</strong></td><td>0.14 (-0.03 to 0.31)</td><td>0.11</td><td>0.22 (0.09 to 0.36)</td><td><strong>0.001</strong></td></tr><tr><td>Continuous (z-score)</td><td>1.76 (0.75 to 2.77)</td><td><strong>0.001</strong></td><td>1.40 (0.15 to 2.65)</td><td><strong>0.03</strong></td><td>1.02 (-0.25 to 2.29)</td><td>0.12</td><td>1.27 (0.16 to 2.37)</td><td><strong>0.03</strong></td></tr><tr><td>Tertile, T1</td><td>(reference)</td><td></td><td>(reference)</td><td></td><td>(reference)</td><td></td><td>(reference)</td><td></td></tr><tr><td>T2</td><td>1.52 (-0.45 to 3.50)</td><td>0.13</td><td>1.37 (-0.94 to 3.68)</td><td>0.24</td><td>1.69 (-0.61 to 3.98)</td><td>0.15</td><td>0.05 (-1.98 to 2.07)</td><td>0.96</td></tr><tr><td>T3</td><td>2.89 (0.91 to 4.87)</td><td><strong>0.004</strong></td><td>1.69 (-0.74 to 4.11)</td><td>0.17</td><td>0.78 (-1.65 to 3.20)</td><td>0.53</td><td>1.28 (-0.83 to 3.40)</td><td>0.23</td></tr></tbody></table>
<figure><img src="image_6.png" /><figcaption>Supplemental Figure 1. Study flow chart</figcaption></figure>
<table><caption>Supplemental Table 1. Baseline characteristics according to the tertiles of waist circumference z-score</caption><thead><tr><th rowspan="2"></th><th colspan="3">Waist circumference z-score tertile</th><th rowspan="2">p-value</th></tr><tr><th>T1, -4.60 - -0.99<br>(N=147)</th><th>T2, -0.99 - -0.32<br>(N=148)</th><th>T3, -0.32 - 1.79<br>(N=145)</th></tr></thead><tbody><tr><td colspan="5"><strong>Variables for the childhood period</strong></td></tr><tr><td>Age, years</td><td>12.7 ± 2.8</td><td>13.1 ± 2.9</td><td>13.1 ± 2.8</td><td>0.40</td></tr><tr><td>Age ≥ 14 years, N (%)</td><td>53 (35.1 %)</td><td>63 (42.9 %)</td><td>64 (43.0 %)</td><td>0.28</td></tr><tr><td>Male, N (%)</td><td>42 (27.8 %)</td><td>73 (49.7 %)</td><td>91 (61.1 %)</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Height, cm</td><td>149 ± 14</td><td>155 ± 15</td><td>159 ± 15</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Weight, kg</td><td>38 ± 10</td><td>45 ± 12</td><td>54 ± 15</td><td><strong>&lt;0.001</strong></td></tr><tr><td>BMI (z score)</td><td>-0.66 ± 0.65</td><td>-0.05 ± 0.64</td><td>0.86 ± 0.69</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Waist circumference, cm</td><td>58 ± 4</td><td>64 ± 5</td><td>71 ± 7</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Waist/Height ratio</td><td>0.39 ± 0.02</td><td>0.41 ± 0.02</td><td>0.44 ± 0.03</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Regular sports activity</td><td>89 (58.9 %)</td><td>101 (68.7 %)</td><td>97 (65.1 %)</td><td>0.20</td></tr><tr><td colspan="5"><strong>Means of commuting to school</strong></td></tr><tr><td>Walking</td><td>61 (40.4 %)</td><td>59 (40.1 %)</td><td>54 (36.2 %)</td><td>0.31</td></tr><tr><td>Bicycle</td><td>4 (2.6 %)</td><td>3 (2.0 %)</td><td>0 (0.0 %)</td><td></td></tr><tr><td>Other</td><td>86 (57.0 %)</td><td>85 (57.8 %)</td><td>95 (63.8 %)</td><td></td></tr><tr><td>Commuting time<br>(min/week)</td><td>100 (60 - 200)</td><td>120 (90 - 250)</td><td>130 (80 - 210)</td><td>0.57</td></tr><tr><td>Birth weight, g</td><td>3185 ± 448</td><td>3288 ± 429</td><td>3387 ± 506</td><td><strong>0.015</strong></td></tr><tr><td>Birth height, cm</td><td>50 ± 2</td><td>50 ± 2</td><td>50 ± 2</td><td>0.60</td></tr><tr><td>Systolic BP, mmHg</td><td>116 ± 10</td><td>119 ± 10</td><td>122 ± 13</td><td><strong>0.003</strong></td></tr><tr><td>Diastolic BP, mmHg</td><td>61 ± 11</td><td>64 ± 11</td><td>67 ± 9</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Heart rate, bpm</td><td>72 ± 12</td><td>71 ± 10</td><td>67 ± 11</td><td><strong>0.003</strong></td></tr><tr><td>Total cholesterol, g/l</td><td>1.86 ± 0.30</td><td>1.83 ± 0.32</td><td>1.79 ± 0.31</td><td>0.18</td></tr><tr><td>Triglyceride, g/l</td><td>0.65 ± 0.26</td><td>0.65 ± 0.35</td><td>0.68 ± 0.34</td><td>0.66</td></tr><tr><td>eGFR, ml/min/1.73m<sup>2</sup></td><td>121 ± 18</td><td>127 ± 21</td><td>131 ± 20</td><td><strong>&lt;0.001</strong></td></tr><tr><td>CRP, mg/l</td><td>0.17 (0.16 - 0.53)</td><td>0.26 (0.16 - 0.54)</td><td>0.35 (0.17 - 0.76)</td><td><strong>0.001</strong></td></tr><tr><td colspan="5"><strong>Variables for the adult period</strong></td></tr><tr><td>Age, yrs</td><td>31.4 ± 3.7</td><td>32.0 ± 3.4</td><td>31.8 ± 3.9</td><td>0.36</td></tr><tr><td>Height, cm</td><td>167 ± 8</td><td>172 ± 8</td><td>175 ± 9</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Body mass index, kg/m<sup>2</sup></td><td>22 ± 3</td><td>24 ± 4</td><td>27 ± 5</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Hypertension</td><td>3 (2.0 %)</td><td>4 (2.7 %)</td><td>5 (3.4 %)</td><td>0.76</td></tr><tr><td>Diabetes</td><td>2 (1.3 %)</td><td>0 (0.0 %)</td><td>1 (0.7 %)</td><td>0.38</td></tr><tr><td>Metabolic syndrome</td><td>0 (0.0 %)</td><td>5 (3.4 %)</td><td>11 (7.4 %)</td><td><strong>0.003</strong></td></tr><tr><td>Total MET,<br>MET/min/week</td><td>1188 (432 - 3012)</td><td>1326 (463 - 2775)</td><td>1488 (720 - 4044)</td><td>0.14</td></tr><tr><td>Systolic BP, mmHg</td><td>110 ± 11</td><td>114 ± 14</td><td>117 ± 13</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Diastolic BP, mmHg</td><td>63 ± 7</td><td>66 ± 8</td><td>67 ± 9</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Heart rate, bpm</td><td>66 ± 8</td><td>63 ± 8</td><td>62 ± 9</td><td><strong>&lt;0.001</strong></td></tr><tr><td>Total cholesterol, g/l</td><td>1.93 ± 0.32</td><td>1.97 ± 0.38</td><td>1.94 ± 0.32</td><td>0.55</td></tr><tr><td>Triglyceride, g/l</td><td>0.89 ± 0.47</td><td>0.90 ± 0.55</td><td>1.05 ± 0.63</td><td><strong>0.018</strong></td></tr><tr><td>Carotid IMT, µm</td><td>518 (466 - 561)</td><td>526 (486 - 586)</td><td>532 (477 - 602)</td><td>0.08</td></tr></tbody></table>

Values are expressed as mean ±SD, n (%) or median (25th to 75th percentile)

Waist circumference was converted to age- and sex-specific z score based on the Third National Health and Nutrition Examination Survey¹.

BMI, body mass index; BP, blood pressure; eGFR, estimated glomerular filtration rate, CRP, C-reactive protein; MET, metabolic equivalent; IMT, intima media thickness.

(reference)

1.Sharma AK, Metzger DL, Daymont C, Hadjiyannakis S and Rodd CJ. LMS tables for waist-circumference and waist-height ratio Z-scores in children aged 5-19 y in NHANES III: association with cardio-metabolic risks. Pediatr Res. 2015;78:723-9.
<table><caption>Supplemental Table 2. Linear regression analyses for the association between childhood adiposity and adult IMT according to men and women</caption><thead><tr><th rowspan="2"></th><th colspan="2">Women</th><th colspan="2">Men</th><th rowspan="2">p-value for interaction<br>with sex difference</th></tr><tr><th>beta (95% CI)</th><th>p-value</th><th>beta (95% CI)</th><th>p-value</th></tr></thead><tbody><tr><td><strong>Body mass index</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Continuous (z-score)</td><td>0.94</td><td>-0.03 to 1.90</td><td>0.06</td><td>-0.25 to 2.42</td><td>0.11</td></tr><tr><td>Tertile, T1</td><td></td><td>(reference)</td><td></td><td>(reference)</td><td></td></tr><tr><td>T2</td><td>2.05</td><td>-0.07 to 4.16</td><td>0.06</td><td>-2.33 to 3.60</td><td>0.67</td></tr><tr><td>T3</td><td>2.03</td><td>-0.07 to 4.13</td><td>0.06</td><td>-1.10 to 4.89</td><td>0.21</td></tr><tr><td>Overweight</td><td>0.98</td><td>-1.36 to 3.32</td><td>0.41</td><td>-1.06 to 5.62</td><td>0.18</td></tr><tr><td>Obesity</td><td>8.45</td><td>0.17 to 16.74</td><td><strong>0.046</strong></td><td>-5.06 to 13.8</td><td>0.36</td></tr><tr><td><strong>Waist/Height</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Continuous (z-score)</td><td>1.15</td><td>-0.21 to 2.51</td><td>0.10</td><td>-1.41 to 2.08</td><td>0.71</td></tr><tr><td>Tertile, T1</td><td></td><td>(reference)</td><td></td><td>(reference)</td><td></td></tr><tr><td>T2</td><td>-0.12</td><td>-2.30 to 2.06</td><td>0.92</td><td>-6.33 to 1.54</td><td>0.23</td></tr><tr><td>T3</td><td>2.05</td><td>-0.46 to 4.55</td><td>0.11</td><td>-3.88 to 3.66</td><td>0.95</td></tr><tr><td><strong>Waist circumference</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Continuous (z-score)</td><td>1.73</td><td>0.46 to 2.99</td><td><strong>0.008</strong></td><td>-0.85 to 2.46</td><td>0.34</td></tr><tr><td>Tertile, T1</td><td></td><td>(reference)</td><td></td><td>(reference)</td><td></td></tr><tr><td>T2</td><td>2.14</td><td>-0.08 to 4.35</td><td>0.06</td><td>-5.21 to 2.27</td><td>0.44</td></tr><tr><td>T3</td><td>1.93</td><td>-0.47 to 4.32</td><td>0.11</td><td>-3.00 to 4.31</td><td>0.72</td></tr></tbody></table>

BMI was converted to age- and sex-specific z score based on the International Obesity Task Force (IOTF), while waist-to-height ratio and waist circumference were based on the Third National Health and Nutrition Examination Survey. Overweight and obesity were respectively defined by a BMI z-score >1 and >2 as proposed by the IOTF.
<table><caption>Supplemental Table 3. Associations between childhood-to-adult adiposity and adult IMT in multivariable models</caption><thead><tr><th rowspan="2"></th><th colspan="3">Univariable</th><th colspan="3">Multivariable</th></tr><tr><th>beta</th><th>95% CI</th><th>p-value</th><th>beta</th><th>95% CI</th><th>p-value</th></tr></thead><tbody><tr><td><strong>Body mass index</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Low in children & Low in adults</td><td></td><td>(reference)</td><td></td><td></td><td>(reference)</td><td></td></tr><tr><td>High in children & Low in adults</td><td>-0.10</td><td>-0.54 to 0.34</td><td>0.67</td><td>0.18</td><td>-0.43 to 0.80</td><td>0.56</td></tr><tr><td>Low in children & High in adults</td><td>0.38</td><td>-0.06 to 0.82</td><td>0.092</td><td>0.21</td><td>-0.37 to 0.79</td><td>0.48</td></tr><tr><td>High in children & High in adults</td><td>0.68</td><td>0.32 to 1.04</td><td><strong>&lt;0.001</strong></td><td>0.63</td><td>0.12 to 1.14</td><td><strong>0.015</strong></td></tr><tr><td><strong>Waist/Height ratio</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Low in children & Low in adults</td><td></td><td>(reference)</td><td></td><td></td><td>(reference)</td><td></td></tr><tr><td>High in children & Low in adults</td><td>0.23</td><td>-0.26 to 0.73</td><td>0.36</td><td>0.46</td><td>-0.17 to 1.08</td><td>0.15</td></tr><tr><td>Low in children & High in adults</td><td>0.71</td><td>0.21 to 1.21</td><td><strong>0.005</strong></td><td>0.70</td><td>0.06 to 1.34</td><td><strong>0.033</strong></td></tr><tr><td>High in children & High in adults</td><td>0.73</td><td>0.35 to 1.12</td><td><strong>&lt;0.001</strong></td><td>0.48</td><td>-0.05 to 1.01</td><td>0.074</td></tr><tr><td><strong>Waist circumference</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Low in children & Low in adults</td><td></td><td>(reference)</td><td></td><td></td><td>(reference)</td><td></td></tr><tr><td>High in children & Low in adults</td><td>0.35</td><td>-0.15 to 0.86</td><td>0.17</td><td>0.46</td><td>-0.21 to 1.13</td><td>0.18</td></tr><tr><td>Low in children & High in adults</td><td>0.47</td><td>-0.01 to 0.95</td><td>0.055</td><td>0.12</td><td>-0.56 to 0.80</td><td>0.73</td></tr><tr><td>High in children & High in adults</td><td>0.85</td><td>0.46 to 1.24</td><td><strong>&lt;0.001</strong></td><td>0.38</td><td>-0.21 to 0.97</td><td>0.20</td></tr></tbody></table>

The multivariable model included variables measured in the childhood period (i.e., birth weight, systolic BP, heart rate, total cholesterol, eGFR, natural log of C-reactive protein) and those measured in the adult period (i.e., height, metabolic syndrome, peripheral systolic BP and heart rate).
<table><caption>Supplemental Table 4. Circulating proteins associated with body mass index and waist-to-height ratio z-scores</caption><thead><tr><th rowspan="2"></th><th colspan="3">BMI z-scores >T3 vs <T1</th><th colspan="3">Waist/Height z-scores >T3 vs <T1</th></tr><tr><th>Adjusted-OR (95% CI)</th><th>p-value</th><th>FDR</th><th>Adjusted-OR (95% CI)</th><th>p-value</th><th>FDR</th></tr></thead><tbody><tr><td>IGFBP-1</td><td>1.43 (1.14 - 1.80)</td><td><strong>0.002</strong></td><td><strong>0.011</strong></td><td>1.29 (1.01 - 1.63)</td><td>0.11</td><td>0.19</td></tr><tr><td>IGFBP-2</td><td>1.86 (1.37 - 2.52)</td><td><strong>&lt;0.001</strong></td><td><strong>&lt;0.001</strong></td><td>2.58 (1.82 - 3.66)</td><td><strong>&lt;0.001</strong></td><td><strong>&lt;0.001</strong></td></tr><tr><td>MMP-2</td><td>2.03 (1.09 - 3.79)</td><td>0.057</td><td>0.16</td><td>1.03 (0.48 - 2.21)</td><td>0.99</td><td>0.99</td></tr><tr><td>MMP-3</td><td>0.79 (0.55 - 1.15)</td><td>0.12</td><td>0.22</td><td>1.91 (1.30 - 2.80)</td><td><strong>0.003</strong></td><td><strong>0.009</strong></td></tr><tr><td>MMP-9</td><td>0.87 (0.64 - 1.19)</td><td>0.66</td><td>0.70</td><td>1.21 (0.89 - 1.66)</td><td>0.32</td><td>0.44</td></tr><tr><td>Osteopontin</td><td>1.38 (0.89 - 2.12)</td><td><strong>0.011</strong></td><td><strong>0.04</strong></td><td>3.09 (1.80 - 5.29)</td><td><strong>&lt;0.001</strong></td><td><strong>&lt;0.001</strong></td></tr><tr><td>VEGF-A</td><td>0.40 (0.26 - 0.61)</td><td><strong>&lt;0.001</strong></td><td><strong>&lt;0.001</strong></td><td>1.25 (0.82 - 1.91)</td><td>0.034</td><td>0.071</td></tr><tr><td>BMP-9</td><td>0.77 (0.52 - 1.14)</td><td>0.42</td><td>0.50</td><td>0.53 (0.32 - 0.89)</td><td><strong>0.021</strong></td><td>0.05</td></tr><tr><td>FABP-4</td><td>1.25 (0.81 - 1.93)</td><td>0.60</td><td>0.67</td><td>0.42 (0.27 - 0.65)</td><td><strong>&lt;0.001</strong></td><td><strong>&lt;0.001</strong></td></tr><tr><td>Leptin</td><td>0.64 (0.40 - 1.02)</td><td>0.16</td><td>0.28</td><td>0.43 (0.34 - 0.54)</td><td><strong>&lt;0.001</strong></td><td><strong>&lt;0.001</strong></td></tr><tr><td>Resistin</td><td>0.82 (0.66 - 1.03)</td><td>0.20</td><td>0.31</td><td>1.70 (1.00 - 2.89)</td><td>0.12</td><td>0.19</td></tr><tr><td>Cystatin-C</td><td>1.25 (0.81 - 1.93)</td><td>0.091</td><td>0.20</td><td>1.51 (0.89 - 2.58)</td><td>0.14</td><td>0.21</td></tr><tr><td>KIM-1</td><td>1.32 (0.86 - 2.02)</td><td>0.28</td><td>0.38</td><td>1.20 (0.78 - 1.86)</td><td>0.71</td><td>0.80</td></tr><tr><td>Hemoglobin</td><td>0.96 (0.61 - 1.51)</td><td>0.91</td><td>0.91</td><td>1.44 (1.15 - 1.82)</td><td><strong>0.006</strong></td><td><strong>0.016</strong></td></tr><tr><td>IFN-gamma</td><td>0.68 (0.45 - 1.03)</td><td>0.094</td><td>0.20</td><td>0.00 (0.00 - 0.02)</td><td><strong>&lt;0.001</strong></td><td><strong>&lt;0.001</strong></td></tr><tr><td>C-reactive protein</td><td>14.39 (2.09 - 99.26)</td><td><strong>0.004</strong></td><td><strong>0.021</strong></td><td>1.02 (0.96 - 1.09)</td><td>0.52</td><td>0.62</td></tr><tr><td>Triglyceride</td><td>0.95 (0.90 - 1.01)</td><td>0.30</td><td>0.38</td><td>1.00 (0.99 - 1.00)</td><td>0.52</td><td>0.62</td></tr></tbody></table>

OR, odd ratio; FDR, false discovery rate.

IGFBP-1, insulin-like growth factor-1; IGFBP-2, insulin-like growth factor-2; MMP-2, matrix metalloproteinase-2; MMP-3, matrix metalloproteinase-3; MMP-9, matrix metalloproteinase-9; VEGF-A, vascular endothelial growth factor-A; BMP-9, bone morphogenetic protein-9; FABP-4, Fatty Acid-Binding Protein 4; KIM-1, Kidney Injury Molecule-1; IFN, interferon.

The multivariable model included variables measured in the adult period (i.e., age, body mass index [or waist and height ratio], metabolic syndrome, hypertension, diabetes mellitus, systolic blood pressure and total cholesterol).