Body mass index and height from infancy to adulthood and carotid intima-media thickness at 60-64 years in the 1946 British birth cohort study

William Johnson; Diana Kuh; Valerie Tikhonoff; Marietta Charakida; John Woodside; Peter Whincup; Alun D Hughes; John E Deanfield; Rebecca Hardy

doi:10.1161/ATVBAHA.113.302572

. Author manuscript; available in PMC: 2014 Sep 1.

Published in final edited form as: Arterioscler Thromb Vasc Biol. 2014 Jan 23;34(3):654–660. doi: 10.1161/ATVBAHA.113.302572

Body mass index and height from infancy to adulthood and carotid intima-media thickness at 60-64 years in the 1946 British birth cohort study

William Johnson ¹, Diana Kuh ¹, Valerie Tikhonoff ¹, Marietta Charakida ², John Woodside ², Peter Whincup ³, Alun D Hughes ⁴, John E Deanfield ^2,^*, Rebecca Hardy ^1,^*, on behalf of the NSHD scientific and data collection teams

PMCID: PMC3977342 EMSID: EMS57511 PMID: 24458709

Abstract

Objective

Atherosclerosis begins early in life and obesity is a key determinant. We investigated the role of BMI and height from infancy to adulthood in presenting with high adulthood carotid intima-media thickness (cIMT).

Approach and Results

Odds ratios (OR) of BMI and height Z-scores at 2, 4, 6, 7, 11, 15, 20 years, and changes between 2-4, 4-7, 7-15, 15-20 years, for cIMT at 60-64 years in the upper quartile were estimated for 604 males and 669 females. Confounding by early life environments, mediating by body size and cardio-metabolic measures at 60-64 years, and effect modification were investigated. In males, there was positive association of BMI at 4 years (OR 1.256; 95% CI 1.026, 1.538) and 20 years (1.282; 1.022, 1.609), negative association of height at 4 years (0.780; 0.631, 0.964), and negative association of height growth between 2-4 years (0.698; 0.534, 0.913) with high cIMT. The childhood estimates were robust, but the estimate for BMI at 20 years was attenuated by adjustment for BMI at 60-64 years. The protective influence of greater early childhood height was strongest in those with the lowest systolic blood pressure at 60-64 years. In females, there was no pattern of association and all confidence intervals crossed one.

Conclusions

Early childhood in males might be a sensitive developmental period for atherosclerosis, where changes in BMI and height represent two distinct biological mechanisms. The maintenance of healthy weight in males from adolescence onward may be a useful strategy to avoid the atherosclerotic complications of adiposity tracking.

Keywords: atherosclerosis, carotid intima-media thickness, childhood, body mass index, height, early life environments, longitudinal studies

Introduction

Evidence from autopsy and observational studies suggests that atherosclerosis begins early in life.^1-3 Cardiovascular disease risk factors in childhood are associated with increased carotid intima-media thickness (cIMT) in adulthood,^4-7 a non-invasive marker of atherosclerosis that is a surrogate end point for coronary artery disease.⁸ This research has implicated childhood body mass index (BMI) in the developmental origins of atherosclerosis.

The Bogalusa Heart Study and Cardiovascular Risk in Young Finns study have shown that childhood BMI is positively related to young-adulthood cIMT.^5,7,9-15 These, and other similar studies,^4,16-22 have not typically investigated associations of BMI at multiple ages with cIMT and therefore provide limited information about the ages where excess weight is most strongly associated with cIMT. Multivariable adjustments for smoking, blood pressure, and cardio-metabolic measures are normally made. Which early life environmental factors explain any association between childhood BMI and adulthood cIMT, and whether or not any association varies across different levels of an early life environmental or adulthood biological variable, is however unknown.

Linear growth restriction often results in permanent height deficits,^23,24 which are associated with higher risks of chronic disease.^24-26 For example, the Boyd-Orr cohort demonstrated negative association between height at 2-14 years and ischaemic heart disease.²⁷ In addition to high childhood BMI, linear growth restriction is a core component of the developmental origins of coronary artery disease,²⁸ yet no study has investigated when impaired growth may predispose to high cIMT.

This paper aims to 1) determine the ages between 2-20 years where BMI and height are associated with high cIMT at 60-64 years, 2) identify periods of BMI and height change associated with high cIMT, and 3) examine how any association varies according to early childhood socio-economic position (SEP), household environments, nutrition, physical illness, life course smoking, and BMI, height, leg length, blood pressure, and cardio-metabolic measures at 60-64 years.

Materials and Methods

Materials and Methods are available in the online-only Data Supplement.

Results

The expected sex difference in cIMT was observed (Table 1). There was a low prevalence (~11%) of overweight or obesity at 20 years, but by 60-64 years approximately two-thirds of the sample was overweight or obese.

Table 1. Description of study sample, by sex.

	Male		Female		Total

	N (%) of all males in sample	Median (IQR) or Mean (SD)	N (%) of all females in sample	Median (IQR) or Mean (SD)	N (%) of total sample	Median (IQR) or Mean (SD)	External Z-score^c Mean (SD)
cIMT (mm) at 60-64 years^a	604 (100.0)	0.684	669 (100.0)	0.658	1273 (100.0)	0.667	--
		(0.606, 0.787)		(0.590, 0.727)		(0.600, 0.753)
Birth weight (kg)	603 (99.8)	3.465 (0.515)	666 (99.6)	3.350 (0.452)	1269 (99.7)	3.404 (0.486)	−0.024 (1.070)
BMI (kg/m²)
2 years	475 (78.6)	17.888 (2.326)	521 (77.7)	17.511 (2.273)	995 (78.2)	17.691 (2.305)	0.766 (1.430)
4 years	529 (87.6)	16.391 (1.672)	581 (86.8)	16.038 (1.604)	1110 (87.2)	16.206 (1.645)	0.303 (1.090)
6 years	469 (77.6)	15.907 (1.268)	535 (80.0)	15.671 (1.397)	1004 (78.9)	15.781 (1.343)	0.103 (0.817)
7 years	489 (81.0)	15.848 (1.218)	552 (82.5)	15.637 (1.480)	1041 (81.8)	15.736 (1.366)	−0.051 (0.777)
11 years	486 (80.5)	17.207 (2.044)	558 (83.4)	17.393 (2.426)	1044 (82.0)	17.307 (2.257)	−0.181 (0.954)
15 years	466 (77.2)	19.600 (2.275)	511 (76.4)	20.448 (2.702)	977 (76.7)	20.044 (2.542)	0.002 (0.925)
20 years	485 (80.3)	22.396 (2.272)	573 (85.7)	21.636 (2.745)	1058 (83.1)	21.985 (2.566)	−0.016 (0.869)
Overweight or obese^b	64 (13.2)	--	49 (8.6)	--	113 (10.7)	--	--
60-64 years	596 (98.7)	27.401 (3.665)	666 (99.6)	26.895 (4.736)	1262 (99.1)	27.134 (4.270)	--
Overweight or obese^b	433 (72.7)	--	406 (61.0)	--	839 (66.5)	--	--
Height (m)
2 years	491 (81.3)	0.863 (0.049)	541 (80.9)	0.851 (0.045)	1032 (81.1)	0.857 (0.047)	−0.037 (1.430)
4 years	533 (88.2)	1.037 (0.049)	591 (88.3)	1.036 (0.048)	1124 (88.3)	1.036 (0.048)	0.008 (1.160)
6 years	495 (82.0)	1.150 (0.051)	555 (83.0)	1.145 (0.050)	1050 (82.5)	1.147 (0.051)	−0.194 (1.029)
7 years	505 (83.6)	1.208 (0.053)	573 (85.7)	1.205 (0.054)	1078 (84.7)	1.207 (0.054)	−0.173 (1.037)
11 years	491 (81.3)	1.414 (0.066)	564 (84.3)	1.420 (0.069)	1055 (82.9)	1.417 (0.068)	−0.238 (0.991)
15 years	474 (78.5)	1.629 (0.088)	517 (77.3)	1.595 (0.058)	991 (77.8)	1.611 (0.076)	−0.017 (1.193)
36 years	544 (90.1)	1.761 (0.065)	611 (91.3)	1.632 (0.056)	1155 (90.7)	1.693 (0.089)	--
60-64 years	596 (98.7)	1.756 (0.065)	666 (99.6)	1.622 (0.057)	1262 (99.1)	1.685 (0.091)	--

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cIMT carotid intima-media thickness; BMI body mass index; IQR interquartile range; SD standard deviation

cIMT was taken as the average of six repeat measurements (three on the left hand side of the body and three on the right hand side of the body) at the lateral view of the common carotid artery.

Overweight or obesity was defined as a BMI ≥ 25kg/m².

Calculated according to the UK90 reference.

Body size

Unadjusted models (Table 2) revealed a clear pattern of the ORs of BMI and height for high cIMT in males (Figure 1), but no pattern was seen in females. In males, a one unit increase in Zbmi_4yr incurred an increased odds of high cIMT (OR 1.256; 95% CI 1.026, 1.538) while a one unit increase in Zht_4yr incurred a decreased odds (0.780; 0.631, 0.964). Only tentative evidence of a negative association was seen for height at subsequent ages, but the positive association of BMI with high cIMT re-emerged at 20 years (Zbmi_20yr 1.282; 1.022, 1.609). In females, all confidence intervals crossed one, with the strongest association seen for Zbmi_7yr. A similar pattern of results was observed using the continuous outcome (e.g., estimates of BMI-cIMT associations in males weakened across childhood before strengthening in adolescence) although nominal significance was not always observed at the same ages (Supplementary Table I).

Table 2. Odds ratios of BMI or height for cIMT^{^a} at 60-64 years in the upper quartile versus lower three quartiles: estimates from logistic regression models stratified by anthropometric exposure and sex.

	Male			Female			Male and female

	N^{^b}	~1 SD	OR (95% CI) P-value	N^{^b}	~1 SD	OR (95% CI) P-value	P-value for Z-score-by-sex^{^c}
Weight Z-score^d
Zwt_0yr	147/456	0.5 kg	0.938 (0.769, 1.144) 0.5	164/502	0.5 kg	0.977 (0.803, 1.190) 0.8	0.8
BMI Z-score^d
Zbmi_2yr	118/357	2.3 kg/m²	1.137 (0.918, 1.408) 0.2	130/390	2.3 kg/m²	1.106 (0.901, 1.357) 0.3	0.8
Zbmi_4yr	126/403	1.7 kg/m²	1.256 (1.026, 1.538) 0.03	150/431	1.6 kg/m²	0.992 (0.818, 1.204) 0.9	0.1
Zbmi_6yr	113/356	1.3 kg/m²	1.189 (0.956, 1.479) 0.1	129/406	1.4 kg/m²	0.954 (0.774, 1.176) 0.7	0.2
Zbmi_7yr	115/374	1.2 kg/m²	0.989 (0.787, 1.245) 0.9	129/423	1.5 kg/m²	0.881 (0.720, 1.078) 0.2	0.5
Zbmi_11yr	123/363	2.0 kg/m²	1.058 (0.863, 1.297) 0.6	136/422	2.4 kg/m²	0.941 (0.772, 1.147) 0.5	0.4
Zbmi_15yr	109/357	2.3 kg/m²	1.204 (0.958, 1.512) 0.1	125/386	2.7 kg/m²	0.947 (0.762, 1.176) 0.6	0.1
Zbmi_20yr	113/372	2.3 kg/m²	1.282 (1.022, 1.609) 0.03	141/432	2.7 kg/m²	1.036 (0.847, 1.267) 0.7	0.2
Zbmi_60-64yr	146/450	3.7 kg/m²	1.373 (1.114, 1.692) 0.03	166/500	4.7 kg/m²	1.114 (0.921, 1.349) 0.3	0.1
Height Z-score^d
Zht_2yr	120/371	4.9 cm	0.890 (0.718, 1.102) 0.3	140/401	4.5 cm	0.998 (0.815, 1.222) >0.9	0.4
Zht_4yr	127/406	4.9 cm	0.780 (0.631, 0.964) 0.02	152/439	4.8 cm	0.982 (0.805, 1.198) 0.9	0.1
Zht_6yr	120/375	5.1 cm	0.874 (0.706, 1.082) 0.2	135/420	5.0 cm	1.072 (0.870, 1.320) 0.5	0.2
Zht_7yr	117/388	5.3 cm	0.950 (0.766, 1.178) 0.6	136/437	5.4 cm	1.061 (0.864, 1.301) >0.6	0.5
Zht_11yr	124/367	6.6 cm	1.039 (0.841, 1.283) 0.7	139/425	6.9 cm	1.006 (0.825, 1.226) >0.9	0.8
Zht_15yr	112/362	8.8 cm	1.022 (0.826, 1.265) 0.8	125/392	5.8 cm	0.925 (0.746, 1.148) 0.5	0.5
Zht_36yr	135/409	6.5 cm	0.894 (0.733, 1.090) 0.3	157/454	5.7 cm	1.087 (0.893, 1.324) 0.4	0.2
Zht_60-64yr	146/450	6.5 cm	0.885 (0.733, 1.069) 0.1	166/500	5.7 cm	1.055 (0.879, 1.265) 0.6	0.2

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cIMT carotid intima-media thickness; BMI body mass index; OR odds ratio; CI confidence interval; SD standard deviation

cIMT was taken as the average of six repeat measurements (three on the left hand side of the body and three on the right hand side of the body) at the lateral view of the common carotid artery. Sex-stratified centiles were used to create the two groups (i.e., upper quartile and lower three quartiles).

N in upper quartile / N in lower three quartiles (of carotid intima-media thickness).

From logistic regression models including Z-score, sex (referent: male), and Z-score by-sex.

Z-scores were created internally using the LMS method, stratified by sex and age (0-5, 6-15, 20-64 years).

Change in body size

Accordingly, in males, a one unit increase in ZCHANGEht_2-4yr resulted in a decreased odds of high cIMT (0.698; 0.534, 0.913) (Table 3). No strong evidence of an association of ZCHANGEbmi_2-4yr or ZCHANGEbmi_15-20yr with high cIMT was, however, observed. In females, all confidence intervals crossed one; a positive estimate for ZCHANGEht_2-4yr, where males had a negative estimate, did however result in a Z-score-by-sex interaction with p-value < 0.05 in a sex combined model. A similar pattern of results was observed using the continuous cIMT outcome (e.g., negative estimates were observed for the association in males of early childhood and late adolescent height growth with cIMT) although nominal significance wasn’t always observed at the same ages (Supplementary Table II).

Table 3. Odds ratios of BMI or height change for cIMT^a at 60-64 years in the upper quartile versus lower three quartiles: estimates from logistic regression models stratified by anthropometric exposure and sex.

	Male			Female			Male and female

	N^b	~1 SD	OR (95% CI) P-value	N^b	~1 SD	OR (95% CI) P-value	P-value for Z-score-by-sex^c
Weight Z-score change^d
ZCHANGEwt_0-2yr	129/377	1.3 kg/m²	1.035 (0.825, 1.300) 0.8	134/426	1.4 kg/m²	1.083 (0.878, 1.336) 0.5	0.8
BMI Z-score change^d
ZCHANGEbmi_2-4yr	111/339	1.6 kg/m²	1.173 (0.933, 1.476) 0.2	125/358	1.5 kg/m²	1.017 (0.810, 1.275) 0.9	0.4
ZCHANGEbmi_4-7yr	105/347	1.1 kg/m²	0.856 (0.660, 1.109) 0.2	121/384	1.3 kg/m²	0.842 (0.661, 1.074) 0.2	0.9
ZCHANGEbmi_7-15yr	94/323	1.9 kg/m²	1.267 (0.950, 1.689) 0.1	104/351	2.1 kg/m²	0.972 (0.732, 1.290) 0.8	0.2
ZCHANGEbmi_15-20yr	92/305	1.7 kg/m²	1.283 (0.910, 1.808) 0.2	113/348	1.9 kg/m²	1.174 (0.854, 1.615) 0.3	0.7

Height Z-score change^d
ZCHANGEht_2-4yr	114/353	4.1 cm	0.698 (0.534, 0.913) 0.009	136/374	4.1 cm	1.036 (0.813, 1.322) 0.8	0.03
ZCHANGEht_4-7yr	108/363	3.8 cm	1.280 (0.934, 1.752) 0.1	129/404	3.8 cm	1.099 (0.810, 1.490) 0.5	0.5
ZCHANGEht_7-15yr	97/339	5.7 cm	1.192 (0.842, 1.690) 0.3	111/370	3.8 cm	0.851 (0.603, 1.201) 0.4	0.2
ZCHANGEht_15-36yr	104/333	4.8 cm	0.798 (0.588, 1.082) 0.1	117/358	2.8 cm	1.341 (0.854, 2.107) 0.2	0.06

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cIMT carotid intima-media thickness; BMI body mass index; OR odds ratio; CI confidence interval; SD standard deviation

N in upper quartile / N in lower three quartiles (of carotid intima-media thickness).

From logistic regression models including Z-score, sex (referent: male), and Z-score-by-sex (and baseline Z-score and baseline Z-score-by-sex).

Z-scores were created internally using the LMS method, stratified by sex and age (0-5, 6-15, 20-64 years). Z-score change variables were created as the residuals from sex-stratified general linear regressions of Z-score at time T+1 on Z-score at time T (and a Z-score at time T squared term); when incorporated into a model (with the variable they are conditional on) they can be interpreted as change over the age period, accounting for regression to the mean.

The four anthropometric exposures (Zbmi_4yr, Zbmi_20yr, Zht_4yr, ZCHANGEht_2-4yr) that had a nominally significant (p-value < 0.05) association with high cIMT in males were considered further.

Confounding

Potential confounders were those variables associated with both the outcome and one or more of the four anthropometric exposures at p-value < 0.1, but were not considered to be on the causal pathway. Only father’s education at 4 years was identified as a potential confounder of the relationship of Zbmi_4yr with high cIMT, and only father’s education and energy intake at 4 years were identified as potential confounders of the relationship of Zbmi_20yr with high cIMT. A host of early life SEP variables and energy intake at 4 years were identified as potential confounders of Zht_4yr and ZCHANGEht_2-4yr relationships with high cIMT. Separate adjustment for each potential confounder only marginally attenuated ORs (Table 4), as did multivariable adjustment for all potential confounders (data not shown).

Table 4. Unadjusted and adjusted odds ratios of anthropometric exposures for cIMT^a at 60-64 years in the upper quartile versus lower three quartiles in males: estimates from logistic regression models stratified by exposure and confounder or mediator.

			Unadjusted for confounder or mediator	Adjusted for confounder or mediator
Exposure	Confounder or mediator^b	N^c	Exposure OR (95% CI) P-value	Exposure OR (95% CI) P-value
Zbmi_4yr^d (1 SD ~ 1.7 kg/m²)	Father’s education (when participant 4 years)	116/367	1.289 (1.045, 1.590) 0.02	1.244 (1.007, 1.537) 0.04
	Zbmi_60-64yr^d	126/397	1.253 (1.027, 1.534) 0.03	1.218 (0.992, 1.495) 0.06
	SBP Z-score at 60-64yr^e	126/401	1.259 (1.028, 1.541) 0.03	1.227 (1.000, 1.506) 0.05
	Pulse pressure Z-score at 60-64yr^e	126/401	1.259 (1.028, 1.541) 0.03	1.223 (0.995, 1.503) 0.06
	HbA1c Z-score at 60-64yr^e	122/377	1.268 (1.032, 1.558) 0.02	1.248 (1.013, 1.536) 0.04

Zbmi_20yr^d (1 SD ~ 2.3 kg/m²)	Father’s education (when participant 4 years)	108/334	1.254 (0.991, 1.589) 0.06	1.223 (0.964, 1.551) 0.1
	Energy Z-score at 4yr^e	111/351	1.293 (1.030, 1.624) 0.03	1.271 (1.009, 1.600) 0.04
	Zbmi_60-64yr^d	113/368	1.278 (1.017, 1.606) 0.04	1.105 (0.861, 1.417) 0.4

Zht_4yr^d (1 SD ~ 4.9 cm)	Father’s occupation class (when participant 4 years)	126/401	0.782 (0.632, 0.966) 0.02	0.820 (0.659, 1.019) 0.07
	Father’s education (when participant 4 years)	117/369	0.787 (0.632, 0.981) 0.03	0.829 (0.662, 1.037) 0.1
	Mother’s education (when participant 4 years)	117/373	0.792 (0.636, 0.986) 0.04	0.814 (0.651, 1.018) 0.07
	Household crowding (when participant 4 years)	127/406	0.780 (0.631, 0.964) 0.02	0.804 (0.649, 0.997) 0.05
	Energy Z-score at 4yr^e	126/402	0.789 (0.638, 0.975) 0.03	0.808 (0.653, 1.000) 0.05
	Zbmi_60-64yr^d	127/400	0.772 (0.625, 0.954) 0.02	0.790 (0.638, 0.979) 0.03
	Zht_60-64yr^d	127/400	0.772 (0.625, 0.954) 0.02	0.706 (0.540, 0.923) 0.01
	Leg length Z-score at 60-64yr^e	127/397	0.770 (0.624, 0.951) 0.02	0.795 (0.625, 1.010) 0.06
	SBP Z-score at 60-64yr^e	127/404	0.777 (0.629, 0.960) 0.02	0.794 (0.639, 0.986) 0.04
	Pulse pressure Z-score at 60-64yr^e	127/404	0.777 (0.629, 0.960) 0.02	0.806 (0.648, 1.003) 0.04

ZCHANGEht_2-4yr^d,f (1 SD ~ 4.1 cm)	Father’s occupation class (when participant 4 years)	113/350	0.689 (0.526, 0.903) 0.007	0.724 (0.551, 0.952) 0.02
	Father’s education (when participant 4 years)	106/325	0.693 (0.525, 0.914) 0.01	0.718 (0.543, 0.949) 0.02
	Mother’s education (when participant 4 years)	106/328	0.698 (0.530, 0.921) 0.01	0.716 (0.542, 0.946) 0.02
	Household crowding (when participant 4 years)	114/353	0.699 (0.535, 0.914) 0.009	0.719 (0.548, 0.942) 0.02
	Energy Z-score at 4yr^e	113/350	0.709 (0.542, 0.928) 0.01	0.724 (0.552, 0.948) 0.02
	Zbmi_6o-64yr^d	114/347	0.685 (0.524, 0.896) 0.006	0.701 (0.535, 0.919) 0.01
	Zht_60-64yr^d	114/347	0.685 (0.524, 0.896) 0.006	0.670 (0.498, 0.904) 0.009
	Leg length Z-score at 60-64yr^e	114/344	0.684 (0.523, 0.895) 0.006	0.726 (0.546, 0.964) 0.03
	SBP Z-score at 60-64yr^e	114/351	0.695 (0.532, 0.909) 0.008	0.714 (0.542, 0.940) 0.02
	Pulse pressure Z-score at 60-64yr^e	114/351	0.695 (0.532, 0.967) 0.008	0.723 (0.548, 0.954) 0.02
	Glucose Z-score at 60-64yr^e	111/335	0.698 (0.533, 0.915) 0.009	0.716 (0.544, 0.941) 0.02

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cIMT carotid intima-media thickness; BMI body mass index; SBP systolic blood pressure, HbAlc glycosylated haemoglobin; OR odds ratio; CI confidence interval

Potential confounders (not on the causal pathway) and mediators (on the causal pathway) were selected as those variables associated with both the outcome and anthropometric exposure at p-value < 0.1.

N in upper quartile / N in lower three quartiles (of carotid intima-media thickness).

Z-scores were created internally using the LMS method, stratified by sex and age (0-5, 6-15, 20-64 years).

Calculated as internal Z-scores (i.e., measurement – mean / SD).

Z-score change variables were created as the residuals from sex-stratified general linear regressions of Z-score at time T+1 on Z-score at time T (and a Z-score at time T squared term); when incorporated into a model (with the variable they are conditional on) they can be interpreted as change over the age period, accounting for regression to the mean.

Mediation

Potential mediators were identified in the same way as potential confounders, but were considered to be on the causal pathway. Potential mediators of the relationships of BMI exposures with high cIMT included Zbmi_60-64yr and SBP, pulse pressure, and HbA1c at 60-64 years; whereas potential mediators of height exposures relationships with high cIMT included Zbmi_60-64yr, Zheight_60-64yr, and leg length, SBP, pulse pressure, and blood glucose at 60-64 years. Associations of exposures with high cIMT were only partially mediated by size and cardio-metabolic measures at 60-64 years, with the exception of Zbmi_20yr, which was largely accounted for by BMI tracking, as indicated by comparison of the unadjusted (1.278; 1.017, 1.606) and adjusted for Zbmi_60-64yr (1.105; 0.861, 1.417) estimates (Table 4). Multivariable adjustment for all mediators did not further attenuate ORs considerably (data not shown).

Effect modification

Effect modification by each of the potential confounders and mediators was examined by adding interaction terms to the adjusted models in Table 4 (data not shown). Evidence of effect modification was observed in 2 instances (p-value of interaction term < 0.1). The protective associations of Zht_4yr and ZCHANGEht_2-4yr with high cIMT were stronger in participants with lower SBP at 60-64 years (Supplementary Figures I and II).

Discussion

Our study suggests that in males early childhood BMI and height have robust associations with high cIMT that act in opposite directions, and that the BMI association re-emerges during adolescence, where it operates through tracking.

Although the finding of a protective effect of greater early childhood height growth is novel, there is a body of literature reporting similar associations with other health outcomes.^24-27,29,30 The fact that height growth in early childhood only was associated with high cIMT supports this literature and suggests that this stage in the life course may be a sensitive period for the programming of atherosclerosis risk. It is known that height is positively associated with lumen diameter, which is in turn positively associated with cIMT.^18,31 Lumen diameter would not, however, explain our findings since greater height was associated with lower, not higher, cIMT. Moreover, compensatory lumen enlargement is an adaptive response to the arterial wall disease process.^32,33

Excess adiposity from 3 years onward has previously been implicated in the development of atherosclerosis,^4,5,7,9-20 which is consistent with our findings. Rapid infant weight gain has been found to be a chronic disease risk factor,^28,34,35 yet we did not find an association of weight gain between 0-2 years with high cIMT. Faster infant weight gain in our sample may represent the acquisition of adipose tissue as a life history strategy, to buffer against nutritional disruption and infection during weaning.^36,37 It may be that high BMI in early childhood, when there is typically minimal investment in the adipose tissue due to reduced risk of energy stress,^36,37 is a better reflection of the disease process in this study.

Similarly to other studies,^9,11,17 we showed considerable attenuation of the association of BMI at 20 years with high cIMT after adjustment BMI at the age of cardiovascular assessment, thereby suggesting that tracking of BMI from adolescence to adulthood is important. A review paper of the Cardiovascular Risk in Young Finns study publications concluded that childhood BMI-adulthood cIMT relationships are only “partly explained by tracking of obesity”.³⁸ Whereas, a systematic review reported little evidence of an association of childhood and adolescent BMI with adulthood cIMT independent of adulthood BMI.³⁹ Research into the association of childhood and adulthood weight status (e.g., obese child/ normal weight adult) with cIMT has been conducted,^10,12 but estimates of the direct and indirect associations of obesity across the life course with cIMT still cannot be found in the literature.

Shorter children tend to have higher adulthood SBP than their peers,⁴⁰ which is in turn associated with greater cIMT.^41,42 Adjusting for adulthood SBP only marginally attenuated the early childhood height-high cIMT associations observed in the present study, however. Instead, we found novel evidence of effect modification, such that the protective influence of greater early childhood height was greatest in those with the lowest systolic blood pressure at 60-64 years. This finding needs to be confirmed in other studies with larger sample sizes and, as shown in Supplementary Figures I and II, does not necessarily mean that any deleterious effect of being a short child can be offset by avoiding high blood pressure in adulthood.

The lower cIMT of females compared to males until approximately 75 years⁴³ may explain why no association was observed in our sample of females aged 60-64 years. This sex advantage in cardiovascular disease risk gradually disappears after the menopause^44,45 so oestrogen protection has been debated as the causal mechanism,^46,47 despite it actually resulting from deceleration in cardiovascular disease rates in men with no change in rates in women around the age of menopause.⁴⁸ Some studies have reported associations of childhood and adolescent BMI with adulthood cIMT in women as well as men,^7,14 although it may be possible that sex specific associations of BMI with cIMT develop over age differently in different cohorts.

The strengths of this study are the use of cIMT in mid- to late-adulthood, prospective objective measures of BMI and height spanning the life course, and a wide range of variables characterising the early life environment and cardiometabolic health in adulthood. The missing data did have the potential to introduce some bias, but because similar patterns of association were observed in a restricted sample with BMI and height data at all studied ages (data not shown), it is unlikely that this source of bias had a substantial impact on findings. Each anthropometric exposure, and each anthropometric exposure-confounder or mediator dyad, was considered separately, which may have increased risk for type one error. This approach was, however, necessary to allow us to investigate the extent to which each confounder or mediator attenuated an exposure estimate. Finally, the sample comprised individuals born in 1946, which may limit generalizability of results to the modern day British population. The NSHD cohort was relatively thin between 2-20 years so any associations observed here may be greater in more recent cohorts.

In conclusion, we provide evidence that early childhood in males might be a sensitive developmental period for atherosclerosis, where BMI and height represent two distinct biological mechanisms. The maintenance of healthy weight in males from adolescence onward may be a useful strategy to avoid the atherosclerotic complications of adiposity tracking.

Supplementary Material

Supplementary Materials and Methods

NIHMS57511-supplement-supp1.pdf^{(92.5KB, pdf)}

Supplementary Tables 1-2 qnd Figures 1-2

NIHMS57511-supplement-supp2.pdf^{(174.6KB, pdf)}

Significance.

This paper is the first to investigate the role of BMI and height from infancy to adulthood in presenting with high cIMT in mid- to late-adulthood. A host of environmental and biological factors that might explain any association are considered. We demonstrate when BMI and height influences emerge and how they develop from infancy to adulthood. This novel information on sensitive developmental periods for atherosclerosis provides useful target ages for prevention programs. Early childhood in males might be a sensitive developmental period for atherosclerosis, where BMI and height represent two distinct biological mechanisms. The maintenance of healthy weight in males from adolescence onward may be a useful strategy to avoid the atherosclerotic complications of adiposity tracking.

Acknowledgements

The authors are grateful to NSHD participants who took part in the latest data collection for their continuing support. We thank members of the NSHD scientific and data collection team at the following centres: MRC Unit for Lifelong Health and Ageing at UCL; Welcome Trust (WT) Clinical Research Facility (CRF) Manchester, the Manchester Heart Centre; WTCRF, and the Department of Cardiology at the Western General Hospital in Edinburgh; WTCRF, Department of Cardiology at University Hospital Birmingham; WTCRF at UCL Hospital; CRF, the Department of Cardiology at the University Hospital of Wales; CRF and Twin Research Unit at St Thomas’ Hospital London; Vascular Physiology Unit, Institute of Child Health, London; National Heart and Lung Institute, Imperial College London; Divisional of Cardiovascular & Medical Sciences, Western Infirmary, Glasgow; Cardiovascular Institute, Sahlgrenska Academy, Gothenburg University.

Sources of funding: This work was supported by the Medical Research Council [U1200632239 and U123092720] and John E Deanfield is supported by the British Heart Foundation.

Abbreviations

BMI: Body mass index
cIMT: carotid intima-media thickness
CRF: clinical research facilities
CI: confidence Interval
NSHD: MRC National Survey of Health and Development
OR: odds ratios
SEP: socio-economic position
SBP: systolic blood pressure
DBP: diastolic blood pressure
HDL: high-density lipoprotein
LDL: low-density lipoprotein
HbA1c: glycosylated haemoglobin

Footnotes

Disclosures: None.

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References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Materials and Methods

NIHMS57511-supplement-supp1.pdf^{(92.5KB, pdf)}

Supplementary Tables 1-2 qnd Figures 1-2

NIHMS57511-supplement-supp2.pdf^{(174.6KB, pdf)}

[R1] 1.Berenson GS, Srinivasan SR, Bao W, Newman WP, Tracy RE, Wattigney WA. Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. The Bogalusa Heart Study. N Engl J Med. 1998;338:1650–1656. doi: 10.1056/NEJM199806043382302. [DOI] [PubMed] [Google Scholar]

[R2] 2.Jarvisalo MJ, Jartti L, Nanto-Salonen K, Irjala K, Ronnemaa T, Hartiala JJ, Celermajer DS, Raitakari OT. Increased aortic intima-media thickness: a marker of preclinical atherosclerosis in high-risk children. Circulation. 2001;104:2943–2947. doi: 10.1161/hc4901.100522. [DOI] [PubMed] [Google Scholar]

[R3] 3.McGill HC, Jr., McMahan CA, Herderick EE, Tracy RE, Malcom GT, Zieske AW, Strong JP. Effects of coronary heart disease risk factors on atherosclerosis of selected regions of the aorta and right coronary artery. PDAY Research Group. Pathobiological Determinants of Atherosclerosis in Youth. Arterioscler Thromb Vasc Biol. 2000;20:836–845. doi: 10.1161/01.atv.20.3.836. [DOI] [PubMed] [Google Scholar]

[R4] 4.Davis PH, Dawson JD, Riley WA, Lauer RM. Carotid intimal-medial thickness is related to cardiovascular risk factors measured from childhood through middle age: The Muscatine Study. Circulation. 2001;104:2815–2819. doi: 10.1161/hc4601.099486. [DOI] [PubMed] [Google Scholar]

[R5] 5.Li S, Chen W, Srinivasan SR, Bond MG, Tang R, Urbina EM, Berenson GS. Childhood cardiovascular risk factors and carotid vascular changes in adulthood: the Bogalusa Heart Study. JAMA. 2003;290:2271–2276. doi: 10.1001/jama.290.17.2271. [DOI] [PubMed] [Google Scholar]

[R6] 6.Magnussen CG, Venn A, Thomson R, Juonala M, Srinivasan SR, Viikari JS, Berenson GS, Dwyer T, Raitakari OT. The association of pediatric low- and high-density lipoprotein cholesterol dyslipidemia classifications and change in dyslipidemia status with carotid intima-media thickness in adulthood evidence from the cardiovascular risk in Young Finns study, the Bogalusa Heart study, and the CDAH (Childhood Determinants of Adult Health) study. J Am Coll Cardiol. 2009;53:860–869. doi: 10.1016/j.jacc.2008.09.061. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R7] 7.Raitakari OT, Juonala M, Kahonen M, Taittonen L, Laitinen T, Maki-Torkko N, Jarvisalo MJ, Uhari M, Jokinen E, Ronnemaa T, Akerblom HK, Viikari JS. Cardiovascular risk factors in childhood and carotid artery intima-media thickness in adulthood: the Cardiovascular Risk in Young Finns Study. JAMA. 2003;290:2277–2283. doi: 10.1001/jama.290.17.2277. [DOI] [PubMed] [Google Scholar]

[R8] 8.O’Leary DH, Polak JF. Intima-media thickness: a tool for atherosclerosis imaging and event prediction. Am J Cardiol. 2002;90:18L–21L. doi: 10.1016/s0002-9149(02)02957-0. [DOI] [PubMed] [Google Scholar]

[R9] 9.Freedman DS, Patel DA, Srinivasan SR, Chen W, Tang R, Bond MG, Berenson GS. The contribution of childhood obesity to adult carotid intima-media thickness: the Bogalusa Heart Study. Int J Obes. 2008;32:749–756. doi: 10.1038/sj.ijo.0803798. [DOI] [PubMed] [Google Scholar]

[R10] 10.Juonala M, Raitakari M, J SAV, Raitakari OT. Obesity in youth is not an independent predictor of carotid IMT in adulthood. The Cardiovascular Risk in Young Finns Study. Atherosclerosis. 2006;185:388–393. doi: 10.1016/j.atherosclerosis.2005.06.016. [DOI] [PubMed] [Google Scholar]

[R11] 11.Juonala M, Viikari JS, Kahonen M, et al. Life-time risk factors and progression of carotid atherosclerosis in young adults: the Cardiovascular Risk in Young Finns study. Eur Heart J. 2010;31:1745–1751. doi: 10.1093/eurheartj/ehq141. [DOI] [PubMed] [Google Scholar]

[R12] 12.Juonala M, Magnussen CG, Berenson GS, Venn A, Burns TL, Sabin MA, Srinivasan SR, Daniels SR, Davis PH, Chen W, Sun C, Cheung M, Viikari JS, Dwyer T, Raitakari OT. Childhood adiposity, adult adiposity, and cardiovascular risk factors. N Engl J Med. 2011;365:1876–1885. doi: 10.1056/NEJMoa1010112. [DOI] [PubMed] [Google Scholar]

[R13] 13.Kivimaki M, Smith GD, Timpson NJ, Lawlor DA, Batty GD, Kahonen M, Juonala M, Ronnemaa T, Viikari JS, Lehtimaki T, Raitakari OT. Lifetime body mass index and later atherosclerosis risk in young adults: examining causal links using Mendelian randomization in the Cardiovascular Risk in Young Finns study. Eur Heart J. 2008;29:2552–2560. doi: 10.1093/eurheartj/ehn252. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R14] 14.Li S, Chen W, Srinivasan SR, Tang R, Bond MG, Berenson GS. Race (black-white) and gender divergences in the relationship of childhood cardiovascular risk factors to carotid artery intima-media thickness in adulthood: the Bogalusa Heart Study. Atherosclerosis. 2007;194:421–425. doi: 10.1016/j.atherosclerosis.2006.08.026. [DOI] [PubMed] [Google Scholar]

[R15] 15.Li S, Chen W, Srinivasan SR, Xu J, Berenson GS. Relation of childhood obesity/cardiometabolic phenotypes to adult cardiometabolic profile: the Bogalusa Heart Study. Am J Epidemiol. 2012;176(Suppl 7):S142–149. doi: 10.1093/aje/kws236. [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

Body mass index and height from infancy to adulthood and carotid intima-media thickness at 60-64 years in the 1946 British birth cohort study

William Johnson

Diana Kuh

Valerie Tikhonoff

Marietta Charakida

John Woodside

Peter Whincup

Alun D Hughes

John E Deanfield

Rebecca Hardy

Abstract

Objective

Approach and Results

Conclusions

Introduction

Materials and Methods

Results

Table 1. Description of study sample, by sex.

Body size

Table 2. Odds ratios of BMI or height for cIMTa at 60-64 years in the upper quartile versus lower three quartiles: estimates from logistic regression models stratified by anthropometric exposure and sex.

Figure 1. Body mass index (BMI) and height by level of carotid intima-media thickness (cIMT) at 60-64 years in males.

Change in body size

Table 3. Odds ratios of BMI or height change for cIMTa at 60-64 years in the upper quartile versus lower three quartiles: estimates from logistic regression models stratified by anthropometric exposure and sex.

Confounding

Table 4. Unadjusted and adjusted odds ratios of anthropometric exposures for cIMTa at 60-64 years in the upper quartile versus lower three quartiles in males: estimates from logistic regression models stratified by exposure and confounder or mediator.

Mediation

Effect modification

Discussion

Supplementary Material

Significance.

Acknowledgements

Abbreviations

Footnotes

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases

Table 2. Odds ratios of BMI or height for cIMT^{^a} at 60-64 years in the upper quartile versus lower three quartiles: estimates from logistic regression models stratified by anthropometric exposure and sex.

Table 3. Odds ratios of BMI or height change for cIMT^a at 60-64 years in the upper quartile versus lower three quartiles: estimates from logistic regression models stratified by anthropometric exposure and sex.

Table 4. Unadjusted and adjusted odds ratios of anthropometric exposures for cIMT^a at 60-64 years in the upper quartile versus lower three quartiles in males: estimates from logistic regression models stratified by exposure and confounder or mediator.