IJE Advance Access originally published online on April 15, 2005
International Journal of Epidemiology 2005 34(4):905-913; doi:10.1093/ije/dyi071
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Article |
Influence of short stature on the change in pulse pressure, systolic and diastolic blood pressure from age 36 to 53 years: an analysis using multilevel models
1 Department of Epidemiology and Public Health, University College London Medical School, 1-19 Torrington Place, London WC1E 6BT, UK
2 MRC National Survey of Health and Development, Department of Epidemiology and Public Health, University College London Medical School, 1-19 Torrington Place, London WC1E 6BT, UK
3 Department of Family and Preventive Medicine, University of California San Diego, School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
* Corresponding author. Department of Epidemiology and Public Health, University College London Medical School, 1-19 Torrington Place, London WCIE 6BT, UK. E-mail: c.langenberg{at}ucl.ac.uk
 |
Abstract |
|---|
 Top Abstract MethodsResultsDiscussionConclusionsAppendixReferences |
|---|
Background Previous cross-sectional analyses of this cohort have shown that short height and leg length are associated with higher pulse pressure and systolic blood pressure in middle age. It is unclear how these adult measures of childhood growth influence the change in blood pressure as it increases with age.
Methods Multilevel models were fitted to investigate associations between components of height and the change in blood pressure between 36, 43, and 53 years in a prospective national cohort of 1472 men and 1563 women followed-up since birth in 1946.
Results Shorter height and leg length, but not trunk length, were associated with higher blood pressure, similarly in men and women. Longitudinal analyses showed that the effects of both height and leg length on pulse pressure and systolic blood pressure became significantly stronger with age. For example, the change in systolic blood pressure was found to be –0.021 mm Hg (95% confidence interval –0.029 to –0.013) per year lower for every centimetre increase in leg length (P 
0.001). In other words, the increase in systolic blood pressure over a 10 year period of a participant whose legs were 10 centimetres shorter was 2.1 mm Hg higher (P 0.001), compared with a taller participant. Associations were independent of a number of potential confounders.
Conclusions These results support the hypothesis that short people may be more susceptible to the effects of ageing on the arterial tree. Childhood growth may contribute to the tracking of cardiovascular risk throughout life.
Keywords Body height, growth, blood pressure, pulse pressure, cohort study
Accepted 8 March 2005
Atherosclerotic changes of the arterial wall begin at an early age, even in apparently healthy children and adolescents.1 Levels of blood pressure and other cardiovascular risk factors in childhood persist over time and cluster both in childhood and adulthood, influencing subsequent subclinical and clinical cardiovascular disease.2 This suggests early acquired risk tracks into adulthood, but the origins of such risk remain unclear. People of shorter height have an increased risk of cardiovascular disease.3–5 The growth of the two main components of height, leg and trunk length differs in timing and magnitude. Leg length represents the growth of the long bones in the first years of life and may be the component of height responsible for the association between shortness and cardiovascular risk.6–10 Leg length is particularly sensitive to post-natal environmental influences on growth.11,12 It has previously been suggested that prepubertal growth rate is associated with the formation of mechanisms controlling blood pressure in later life,13 and we have previously shown strong, inverse associations between leg length and both systolic blood pressure and pulse pressure, a measure of arterial stiffness, in men and women of this cohort at age 53 years.14 Arterial stiffness, pulse pressure, and blood pressure increase with age and detrimental influences on vascular structure and function in the first years of life may increase vulnerability to the effects of ageing on the arterial tree. If poor early growth contributed to the tracking of pulse pressure and blood pressure, then those with shorter height and shorter legs may experience a steeper increase in these measures throughout life. This may differ between the genders, due to the influence of hormonal levels on vascular function. Earlier findings in this cohort were based on cross-sectional analyses,14 which are unable to investigate the amplification of the effect of short height on the change in blood pressure with age. Longitudinal analyses may contribute to the understanding of how exposures in early life interact with age to influence blood pressure over the life course.
Several explanations have been suggested for the associations between shortness, cardiovascular disease, and associated risk factors, including poor prenatal growth, socioeconomic disadvantage at different ages, and adverse health behaviour. All these factors may contribute to the association between short stature and increased blood pressure.
No previous study has investigated the influence of poor childhood growth on the change in blood pressure during middle age. Using adult leg and trunk length as markers of growth at different phases of development, we compare associations between components of height and change in pulse pressure, and systolic and diastolic blood pressure from age 36 to 53 years in a prospective birth cohort study.
|
Methods |
|---|
|
TopAbstractMethodsResultsDiscussionConclusionsAppendixReferences |
|---|
Participants
The Medical Research Council's National Survey of Health & Development (NSHD) is a prospective birth cohort study of a class stratified sample (5362 births; 2547 women, 2815 men) of all births that occurred in the first week of March 1946 in England, Scotland, and Wales. Follow-up included 20 contacts with the whole cohort between birth and 53 years of age, when 3035 participants (1472 men and 1563 women) provided information. The majority of participants (2989) were then interviewed and measured at home by trained research nurses using a standardized protocol. Those not visited at home completed a postal questionnaire (46). The participation rate was 70.4% among survivors still resident in England, Wales, or Scotland, and 89.6% for whom contact was attempted. Contact was not attempted for those previously refusing to take part (640), living abroad at time of interview (119), emigrated (461), or those who had already died (469). The data collection received MREC approval, and respondents gave informed consent to each set of questions and measures. The sample is reasonably representative of the national population of the same or similar age.15 Similar data collections occurred at ages 36 (N = 3322) and 43 years (N = 3262).16
Measurements
Blood pressure
Blood pressure was measured by trained research nurses at 36, 43, and 53 years, according to a standardized protocol. Peripheral blood pressure was measured twice in the brachial artery of the upper left arm after 5 min rest, with the participant in the sitting position. At age 53 years blood pressure was measured with the validated Omron HEM-705 (Omron Corp., Tokyo, Japan) automated digital oscillometric sphygmomanometer, and at 43 and 36 years the Hawksley random zero sphygmomanometer was used. Second blood pressure readings were used for analysis except if only the first was available. Pulse pressure was calculated as the difference between systolic and diastolic pressure at each age.
Anthropometric variables
At 53 and 43 years measures of weight (kilograms (kg)), height (centimetres (cm)), and trunk length (cm) were obtained. Weight was measured to the nearest 0.1 kg with participants wearing light indoor clothing and no shoes. Height was measured to the nearest 0.5 cm, using a portable stadiometer with participants standing without shoes and with heels against the wall as tall as possible with the head in the Frankfort plane. Sitting height, used to represent trunk length, was measured to the nearest 0.5 cm. Participants were asked to sit upright, with their back against the vertical stand of the stadiometer, on the base plate located on a hard, flat seat, with the head in the Frankfort plane and their feet on the floor. Leg length was calculated as the difference between standing and sitting heights. Height and weight at 36 years were measured according to the same standard protocol. Body mass index was defined as weight/height2 (kg/m2). Trunk length was not measured at 36 years and so leg length was unavailable at this age. Information on height, leg and trunk length at 53 years was therefore used or, if unavailable, at 43 years (474 participants).
Birthweight
Birthweight was extracted, to the nearest quarter of a pound, from medical records by health visitors within a few weeks of delivery, and converted into kilograms.
Social class
Social class (manual/non-manual) was based on occupation according to the Registrar General's Classification. Childhood social class was based on father's occupation when survey members were 4 years old, or if unavailable, when survey members were aged 11 years (n = 125) or 15 years (n = 48). Adult social class was based on survey member's own occupation at 53 years or if unavailable on occupation at 43 years (n = 513) or 36 years (n = 185).
Education
Highest educational or training qualifications achieved by 26 years (Department of Education and Science, 1972), were grouped into either less than advanced secondary education (‘A’-levels usually attained at 18 years, and their training equivalents) or advanced secondary or higher.
Smoking and exercise
At 53 years participants reported smoking status, and ‘current’ smokers were distinguished from ‘previous’ and ‘never’ smokers. Information on physical exercise was based on reported participation in sports or vigorous leisure time activities during spare time in the last 4 weeks.
Medication
Nurses recorded participants' current medication at 53 years, which was coded according to the British National Formula (BNF) Number 40 (2000). Current use of antihypertensive medication (BNF sections 2.2—Diuretics, 2.4—Beta blockers, 2.5—Drugs affecting the renin–angiotensin system and some other antihypertensive drugs, 2.6.2—Calcium-channel blockers) was used in this analysis. At ages 43 and 36 years participants were asked whether they had taken any prescribed medicines or tablets for high blood pressure in the last year.
Statistical analysis
Linear regression analysis was used to estimate cross-sectional relationships between the explanatory variables and blood pressure measures at ages 36, 43, and 53 years. Models were fitted including both men and women and an interaction term between sex and either height, leg, or trunk length was used to investigate whether the effect of anthropometry on blood pressure differed significantly between the sexes. These analyses were performed using Stata 7.0 software.17
Multilevel models18 were then used, with blood pressure as a repeated outcome measure, using the package MLwiN.19 These models take account of the correlation between repeated measures on the same individual and allow for incomplete outcome data as long as a missing at random process can be assumed.18,20,21 First, the change in blood pressure with age was modelled. The intercept (mean blood pressure at 36 years) and linear and quadratic terms for age were used to model the non-linear change in pulse pressure and systolic blood pressure over time. The change in diastolic blood pressure with age was found to be linear and the quadratic increase observed for pulse pressure and systolic blood pressure was non-significant and omitted from models for diastolic blood pressure. In all models, the variance of blood pressure was allowed to change with age (level 1 random variation), and both intercept and linear changes with age (slope) were allowed to vary between individual cohort members (level 2 random variation). In all analyses, separate curves were modelled for men and women by including a sex variable in the model and also interactions between sex and the linear effect of age and sex and the quadratic effect of age (Appendix, Equation 1).
The intercept was then allowed to vary according to height, leg or trunk length. To test whether associations between components of height and blood pressure changed with increasing age, interactions between the anthropometric measures and age were added to each model. Initially, interactions with the linear as well as the quadratic effect of age were considered; however, the latter was non-significant in all models and was therefore omitted from further analyses (Appendix, Equation 2). 
2-tests based on 
, where 
is the regression coefficient, were carried out to assess levels of significance for the fixed effect parameters as suggested by Goldstein.18
Analyses were first performed with the maximum number of observations (9086) and repeated including only observations from participants with information on all covariates (7304), required for adjusted analyses.
Adjustments were performed introducing potential confounders (or groups of confounders representing similar underlying mechanisms) one at a time and all together, to investigate their separate and joint effects on the associations of interest. First, antihypertensive treatment status for each time point was considered. Interactions between components of height and treatment status were also added to assess whether associations differed according to treatment status. Second, body mass index at each time point was added to the model, influencing both intercept and slope, as a time varying covariate. Third, the influence of the other adult factors, social class, smoking, exercise, and educational attainment was considered. Fourth, the impact of early life factors was investigated by introducing birthweight and father's social class into the model. Finally, a model was fitted including all variables.
Analyses were repeated using sex-standardized measures of blood pressure (z-scores) to assess whether the increase in the variance of blood pressure with age, potentially due to the different measurement instruments used, had an impact on the findings.
|
Results |
|---|
|
TopAbstractMethodsResultsDiscussionConclusionsAppendixReferences |
|---|
A total of 3414 participants (1721 men and 1693 women) had at least one measure of blood pressure (both systolic and diastolic blood pressure) and corresponding height and leg length measures. Mean pulse pressure, and systolic and diastolic blood pressure increased with age in both men and women between 36 and 53 years (Table 1). The increase in pulse pressure and systolic blood pressure was greater between 43 and 53 years, compared with their earlier change; their variation was also found to increase with age.
|
Pulse pressure, and systolic and diastolic blood pressure at 53 and 43 years decreased significantly with increasing height and leg length, but not trunk length (Table 2). Regression estimates for all three measures of blood pressure were smaller at 43 years for both height and leg length, compared with those at age 53 years. Taller height was also significantly associated with lower systolic and diastolic blood pressure at 36 years, as was shorter leg length with lower diastolic blood pressure. Although regression coefficients for pulse pressure at this age were in the same direction, effects were smaller and not statistically significant.
|
Of 27 tests for interactions that were carried out to assess whether the effect of components of height differed between the genders, only three were statistically significant (P < 0.05) (Table 2). At 53 and 43 years, none of the tests for interaction reached conventional levels of statistical significance. We therefore present estimates for men and women combined, adjusted for sex, in all further analyses.
Multilevel modelling of the associations between components of height and repeated measures of blood pressure at 36, 43, and 53 years
Separate inclusion of height, leg, or trunk length and interactions between each of the components of height and the linear effect of age showed that the effects of both height and leg length on pulse pressure became significantly stronger with age (Table 3). The linear change in pulse pressure was found to be –0.020 mm Hg [95% Confidence Interval (CI)] (–0.026 to –0.014) per year lower for every centimetre increase in leg length. The change in systolic blood pressure was found to be –0.021 mm Hg (–0.029 to –0.013) per year lower for every centimetre increase in leg length. The model leads to an estimated effect of leg length on systolic blood pressure at 36 years of –0.086 mm Hg (–0.18–0.012) per centimetre increase in leg length and one of –0.44 mm Hg per centimetre increase in leg length at 53 years. These estimates are of similar magnitude to those observed in the cross-sectional analysis (Table 2). According to this model, the estimated systolic blood pressure of a participant whose legs were 10 centimetres shorter compared with a taller participant was just under 1 mm Hg higher at age 36 years and increased by 3.6 mm Hg more over the 17 years of follow-up (or 0.21 mm Hg per year), resulting in a difference of 4.4 mm Hg at age 53 years.
|
Diastolic blood pressure at 36 years (intercept) was significantly influenced by height and leg length, however, these effects did not appear to get stronger over time, as indicated by the non-significant results for the slope (P > 0.5 in both cases). Trunk length was not related to any of the blood pressure measures at 36 years, and none of these associations changed with age. Trunk length was therefore omitted from all further analyses.
Results from analyses in the restricted sample with complete information (7304 observations) showed that estimates for the amplification of the effect of height and leg length on pulse pressure and systolic blood pressure with age were of similar magnitude compared with previous analyses. Levels of significance remained identical (Table 4).
|
Adjusted analyses
For pulse pressure, individual adjustment for confounders or groups of confounders had only a small effect on the estimates, but coefficients were reduced slightly further when all variables were included simultaneously in the same model (Table 4). However, levels of significance remained unchanged (P
0.001 in all cases). For systolic blood pressure, body mass index and the significant change of its effect on blood pressure with age had the largest impact on the amplification of the effect of height or leg length. Full adjustment including all variables under consideration did not reduce the estimates much further. Again, levels of significance remained high (P 0.01 in all cases). In addition, no evidence was found that the associations between either height or leg length and blood pressure were modified by treatment status (results not shown).
Sensitivity analysis
Replacing the blood pressure measures by their internally derived standard deviation scores did not alter associations between the anthropometric measures and pulse pressure or systolic blood pressure. A significant increasing effect of height and leg length with age remained for both pulse pressure and systolic blood pressure using standardized outcomes (results not shown).
|
Discussion |
|---|
|
TopAbstractMethodsResultsDiscussionConclusionsAppendixReferences |
|---|
Main findings and their interpretation
In this prospective birth cohort study we found strong evidence that the inverse associations between both height and leg length, and pulse pressure and systolic blood pressure were amplified with age, independently of potential confounders.
Early endocrine control (hormonal levels and receptor expression) may simultaneously influence growth spurts of the long bones (of the leg) and arterial growth, leading to changes in the structure and function of the developing vasculature, and altering the susceptibility for arterial stiffness and hypertension in later life.22 We show that short leg length is the key component of height associated with larger than average increases in pulse pressure and systolic blood pressure up to middle age. Systolic blood pressure and arterial stiffness increase with age. If poor early growth contributed to the tracking of these measures, its detrimental influence on vascular structure and function in the first years of life may amplify the vulnerability of those with shorter legs to the effects of ageing on the arterial tree. Our evidence supports this hypothesis by showing an amplification of the effect of leg length, as a marker of early growth, on pulse pressure and systolic blood pressure between 36 and 53 years.
One previous small study suggested that poor growth in childhood is an important determinant of systolic blood pressure and pulse pressure, but not diastolic blood pressure, using a single measure of blood pressure taken in early old age.13 Interestingly, as in our study, associations were observed with systolic blood pressure and pulse pressure, but not diastolic blood pressure. In industrialized countries, systolic blood pressure increases progressively throughout adult life, while diastolic blood pressure increases less steeply and ceases to rise or even falls around 55 years,23 resulting in a rise in pulse pressure throughout adult life. Accordingly, in this study of blood pressure in the middle years of life, pulse pressure and systolic blood pressure show a greater rise with age, compared with diastolic blood pressure. If growth limiting factors influence the age–blood pressure relationship, then stronger associations may therefore be expected with those measures of blood pressure whose increase is more closely linked with ageing.
The majority of cardiovascular risk associated with hypertension is due to blood pressure gradually increasing with age. The age specific rise, and therefore hypertension, is essentially absent in certain rural communities, and studies have shown that this protection is partly lost through migration to industrialized communities.23 This suggests that protective environmental factors are necessary for maintaining low pressures into later life, and hence supporting the hypothesis that environmental influences on growth modify the age–blood pressure relationship.
Several determinants of growth may contribute to the association of blood pressure with its age-related rise. The quality of early nutrition, rather than simply energy intake, has a critical influence on growth.24 Dietary interventions may affect the individual age–blood pressure relationship and therefore impact on the population burden of hypertension and associated cardiovascular disease. Growth limiting factors such as impaired fetal development and disadvantageous socioeconomic conditions have been associated with high blood pressure and cardiovascular risk and were considered as alternative explanations in previous investigations.14 In this study, associations remained unchanged after adjustment for birthweight; however, as birthweight is only a crude marker of growth and development before birth, this does not preclude the possibility of prenatal factors simultaneously influencing growth and later blood pressure. Adjustment for childhood social class, educational attainment, adult social class and potential confounding factors in adulthood (obesity, smoking, and lack of exercise) slightly reduced the estimates, but did not alter the levels of significance. Some of these factors, particularly obesity, showed independent effects on blood pressure, and their importance for the control of cardiovascular risk should not be understated. Furthermore, a great variety of influences on growth are socially distributed, and these contribute to the shorter height, and particularly leg length, of children growing up in disadvantageous social conditions.11,12,25,26 These influences include prenatal development, prematurity, maternal health, behaviour and care for the child, early nutrition, living conditions, infections, and age at puberty.26–30 Adjustment for childhood social conditions is unlikely to fully account for the diverse influences of these factors on early and later blood pressure.
Short height and blood pressure regulation might be jointly genetically determined, but this cannot be investigated in the NSHD. However, the evidence of a genetically determined association between height and cardiovascular risk factors to date is weak.31
Strengths and limitations of the study
This is the oldest ongoing birth cohort internationally, and no other birth cohort study is available with earlier measures of blood pressure and a follow-up till middle age. Potentially avoidable loss of participants in this study and the impact of survivor bias have previously been discussed in detail14,15,32 and would result in an underestimation of the observed associations.
This study is restricted to an investigation of changes in blood pressure measured at three time points during the middle years of life. It may be that the observed associations will become stronger as the cohort ages and arterial stiffness and blood pressure increase further due to the continuing effects of ageing on the arterial tree. This will be investigated at future data collections. The availability of just three measures of blood pressure taken at fairly distant time points allows for only relatively simplistic modelling of changes in blood pressure, which may be unable to account for short-term changes or more complex variations of blood pressure over time.
We used adult leg and trunk length as markers of growth at different phases, rather than height measured during childhood, for two reasons. First, this approach is comparable with recent studies suggesting that leg length, as opposed to trunk length, is the component of height most closely linked to cardiovascular risk in adult life. Second, the importance of children's height at a given age for determining their final adult height depends on rate (growth tempo) and timing of maturation. The comparison of leg to trunk length distinguishes the rapid growth of long bones occurring in childhood from the slower and later growth of the trunk.24 Adult leg and trunk length were used, as components of height in childhood were not available in this cohort.
Using adult indicators of childhood growth has some disadvantages. Although leg length is regarded as a marker of environmental exposures during the first years of life, pubertal growth and timing of puberty as well as genetic factors will also influence attained leg length. Even if leg length is predominantly a marker of the prepubertal growth phase, it remains unclear whether it is early post-natal or later prepubertal growth that is most important. Shrinkage may introduce error in measures of adult height. However, previous studies have shown that loss of stature at these early ages (before 53 years) is only small.33 In this study, only total and sitting height (trunk length) were measured, and leg length calculated from them, resulting in greater measurement error in leg length (non-differential misclassification), which may bias results towards the null. Nevertheless, associations with blood pressure were observed for leg length, not trunk length, and the strength of the association may therefore be even greater if leg length was measured more accurately.
Leg and trunk length were only measured at 43 and 53 years. Participants measured at 36 years, therefore, needed to participate at 43 or 53 years to be included in the analysis, possibly resulting in selection bias.
The increase in mean levels of blood pressure between 43 and 53 years may be influenced systematically by differences in the sphygmomanometers used. However, readings between instruments are not likely to vary systematically by components of height. The variation in blood pressure reading might also vary between instruments or increase with age, as observed for pulse pressure and systolic blood pressure in this study. Using a standardized outcome measure, which accounts for the increase in the variation in blood pressure with age, a significant increasing effect of height and leg length with age was observed for pulse pressure and systolic blood pressure, suggesting that the amplification of the effects of height and leg length were not simply due to increasing variance with age or change in measurement instrument.
|
Conclusions |
|---|
|
TopAbstractMethodsResultsDiscussionConclusionsAppendixReferences |
|---|
In this middle-aged cohort pulse pressure and systolic blood pressure increased linearly with decreasing height and leg length, but not trunk length, suggesting the role of poor childhood growth for the development of high blood pressure in later life. Importantly, these associations were shown to be significantly amplified with age. This is evidence for the hypothesis that people with restricted growth in the first years of life may be more susceptible to the effects of ageing on the arterial tree. Poor early growth may therefore contribute to the tracking of cardiovascular risk throughout life and indicate the need for early prevention of increasing blood pressure during mid-life. Early growth restricting factors may be potential mediators. While infant diet, childhood infections, and psychosocial deprivation limit early growth,34,35 previous studies have not investigated how these factors may link short height and cardiovascular risk. Future research on these childhood factors could therefore provide further insights into the aetiology of hypertension and arterial stiffness. This may help to identify modifiable childhood factors, which can be targeted during specific periods of development, increasing the practicality of a public health intervention.
|
Appendix |
|---|
|
TopAbstractMethodsResultsDiscussionConclusionsAppendixReferences |
|---|
Parameters and estimates of the basic and extended multilevel models
In the following equations, yij denotes the blood pressure (pulse pressure, systolic or diastolic blood pressure) of subject j (j = 1, ...,N) on measurement occasion i (i = 1, 2, 3) and ageij, the age at which that measurement was taken (36, 43, and 53 years). The fixed parameter ß0 represents the mean intercept, in this example, the overall mean blood pressure at age 36 years. The fixed parameter ß1 represents the mean slope or equivalently the linear change in blood pressure for each yearly increase in age. ß2–ß5 denote the fixed effects of age2, sex, and the interaction terms age by sex and age2 by sex, respectively. The basic multilevel model for repeated measures of blood pressure at age 36, 43, and 53 years is then written as
 | (1) |
For diastolic blood pressure, the quadratic increase of blood pressure was non-significant and age2 and its interaction with sex were therefore omitted. The parameters u0j and u1j are the random (between-individual) effects, which allow each individual to have their own intercept and slope, respectively, and indicate the deviation of each individual's intercept and slope from the mean intercept and slope. These ‘level 2’ random effects parameters are assumed to be bivariate normal with mean 0 and variance defined by the variance–covariance matrix, having entries given by the variance of 
, the variance of 
, and the covariance between u0j and 
. The random effect of the quadratic effect of age was considered, but found to be very small and statistically non-significant and was therefore not included in the final models. The within-individual (‘level 1’) variation was allowed to increase with age and is represented by the terms e0ij and e1ij. These ‘level 1’ random effects are assumed to be bivariate normally distributed, with mean 0 and variance defined by the variance–covariance matrix, having entries given by the variance of 
, the variance of 
and the covariance between e0ij and 
. The variance 
was set to 0, so that the level 1 variance increased linearly with age.
The model given in Equation 1 was then extended to assess how anthropometric measures influenced both the intercept and the increase in blood pressure with age
 | (2) |
KEY MESSAGES
|
|
Acknowledgments |
|---|
The study has been supported by grants from the Medical Research Council. C.L. is funded by a Medical Research Council and Department of Health Research Training Fellowship. R.H., D.K., and M.W. are supported by the Medical Research Council. The views expressed in this publication are those of the authors and not necessarily those of the Department of Health or MRC.
|
References |
|---|
|
TopAbstractMethodsResultsDiscussionConclusionsAppendixReferences |
|---|
1 Berenson GS, Srinivasan SR, Bao W Newman WP III, 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;338:1650–56.
2 Bao W, Srinivasan SR, Wattigney WA, Berenson GS. Persistence of multiple cardiovascular risk clustering related to syndrome X from childhood to young adulthood. The Bogalusa Heart Study. Arch Intern Med 1994;154:1842–47.
3 Marmot MG, Shipley MJ, Rose G. Inequalities in death—specific explanations of a general pattern? Lancet 1984;1:1003–06.[CrossRef][Web of Science][Medline]
4 McCarron P, Okasha M, McEwen J, Davey Smith G. Height in young adulthood and risk of death from cardiorespiratory disease: a prospective study of male former students of Glasgow University, Scotland. Am J Epidemiol 2002;155:683–87.
5 Song YM, Davey Smith G, Sung J. Adult height and cause-specific mortality: a large prospective study of South Korean men. Am J Epidemiol 2003;158:479–85.
6 Gunnell DJ, Davey Smith G, Frankel S et al. Childhood leg length and adult mortality: follow up of the Carnegie (Boyd Orr) survey of diet and health in pre-war britain. J Epidemiol Community Health 1998;52:142–52.[Abstract]
7 Davey Smith G, Greenwood R, Gunnell D, Sweetnam P, Yarnell J, Elwood P. Leg length, insulin resistance, and coronary heart disease risk: the Caerphilly Study. J Epidemiol Community Health 2001;55:867–72.
8 Lawlor DA, Ebrahim S, Davey Smith G. The association between components of adult height and Type II diabetes and insulin resistance: British Women's Heart and Health Study. Diabetologia 2002;45:1097–1106.[CrossRef][Web of Science][Medline]
9 Gunnell D, Whitley E, Upton MN, McConnachie A, Davey Smith G, Watt GC. Associations of height, leg length, and lung function with cardiovascular risk factors in the Midspan Family Study. J Epidemiol Community Health 2003;57:141–46.
10 Lawlor DA, Taylor M, Davey Smith G, Gunnell D, Ebrahim S. Associations of components of adult height with coronary heart disease in postmenopausal women: the British women's heart and health study. Heart 2004;90:745–49.
11 Gunnell DJ, Davey Smith G, Frankel SJ, Kemp M, Peters TJ. Socio-economic and dietary influences on leg length and trunk length in childhood: a reanalysis of the Carnegie (Boyd Orr) survey of diet and health in prewar Britain (1937–39). Paediatr Perinat Epidemiol 1998; 12 (Suppl. 1):96–113.[CrossRef][Web of Science][Medline]
12 Wadsworth MEJ, Hardy RJ, Paul AA, Marshall SF, Cole TJ. Leg and trunk length at 43 years in relation to childhood health, diet and family circumstances; evidence from the 1946 national birth cohort. Int J Epidemiol 2002;31:383–90.
13 Montgomery SM, Berney LR, Blane D. Prepubertal stature and blood pressure in early old age. Arch Dis Child 2000;82:358–63.
14 Langenberg C, Hardy R, Kuh D, Wadsworth ME. Influence of height, leg and trunk length on pulse pressure, systolic and diastolic blood pressure. J Hypertens 2003;21:537–43.[CrossRef][Web of Science][Medline]
15 Wadsworth ME, Butterworth SL, Hardy RJ et al. The life course prospective design: an example of benefits and problems associated with study longevity. Soc Sci Med 2003;57:2193–205.[CrossRef][Web of Science][Medline]
16 Hardy R, Kuh D, Langenberg C, Wadsworth ME. Birthweight, childhood social class, and change in adult blood pressure in the 1946 British birth cohort. Lancet 2003;362:1178–83.[CrossRef][Web of Science][Medline]
17 Stata Statistical Software: Release 7.0 College Station. Texas: Stata Corporation, 2002.
18 Goldstein H. Multilevel Statistical Models. 2nd edn. London: Edward Arnold, 1995.
19 Goldstein H, Rasbash J, Plewis I et al. A User's Guide to MLwiN. Multilevel Models Project. 2nd edn. London: Institute of Education, University of London, 1998.
20 Raudenbush SW, Bryck AS. Hierarchical Linear Models. 2nd edn. Thousand Oaks, CA: Sage Publications, 2002.
21 Little RJ, Raghunathan T. On summary measures analysis of the linear mixed effects model for repeated measures when data are not missing completely at random. Stat Med 1999;18:2465–78.[CrossRef][Web of Science][Medline]
22 Leeson CP, Kattenhorn M, Deanfield JE, Lucas A. Duration of breast feeding and arterial distensibility in early adult life: population based study. BMJ 2001;322:643–47.
23 Rose G. Hypertension in the community. In: Bulpitt C (ed). Epidemiology of Hypertension. Amsterdam: Elsevier, 1985, pp. 1–14.
24 Cole TJ. Secular trends in growth. Proc Nutr Soc 2000;59:317–24.[Web of Science][Medline]
25 Tanner JM. A History of the Study of Human Growth. Cambridge: Cambridge University Press, 1981.
26 Kuh D, Wadsworth M. Parental height: childhood environment and subsequent adult height in a national birth cohort. Int J Epidemiol 1989;18:663–68.
27 Goldstein H. Factors influencing the height of seven year old children—results from the National Child Development Study. Hum Biol 1971;43:92–111.[Web of Science][Medline]
28 Rona RJ, Swan AV, Altman DG. Social factors and height of primary schoolchildren in England and Scotland. J Epidemiol Community Health 1978;32:147–54.
29 Smith AM, Chinn S, Rona RJ. Social factors and height gain of primary schoolchildren in England and Scotland. Ann Hum Biol 1980;7:115–24.[CrossRef][Web of Science][Medline]
30 Michaelsen KF, Larsen PS, Thomsen BL, Samuelson G. The Copenhagen cohort study on infant nutrition and growth: duration of breast feeding and influencing factors. Acta Paediatr 1994;83:565–71.[Web of Science][Medline]
31 Langenberg C, Marmot M. Commentary: disentangling the association between short height and cardiovascular risk-genes or environment? Int J Epidemiol 2003;32:614–16.
32 Kuh D, Hardy R, Langenberg C, Richards M, Wadsworth ME. Mortality in adults aged 26–54 years related to socioeconomic conditions in childhood and adulthood: post war birth cohort study. BMJ 2002;325:1076–80.
33 Cline MG, Meredith KE, Boyer JT, Burrows B. Decline of height with age in adults in a general population sample: estimating maximum height and distinguishing birth cohort effects from actual loss of stature with aging. Hum Biol 1989;61:415–25.[Web of Science][Medline]
34 Nystrom Peck AM, Lundberg O. Short stature as an effect of economic and social conditions in childhood. Soc Sci Med 1995;41:733–38.[CrossRef][Web of Science][Medline]
35 Zimet GD, Owens R, Dahms W, Cutler M, Litvene M, Cuttler L. Psychosocial outcome of children evaluated for short stature. Arch Pediatr Adolesc Med 1997;151:1017–23.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  C. Thomas and C. Power Do early life exposures explain associations in mid-adulthood between workplace factors and risk factors for cardiovascular disease? Int. J. Epidemiol., January 16, 2010; (2010) dyp365v1. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E Webb, D Kuh, A Peasey, A Pajak, S Malyutina, R Kubinova, R Topor-Madry, D Denisova, N Capkova, M Marmot, et al. Childhood socioeconomic circumstances and adult height and leg length in central and eastern Europe J Epidemiol Community Health, April 1, 2008; 62(4): 351 - 357. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. M. Schooling, C. Jiang, T. H. Lam, G. N. Thomas, M. Heys, Bmbs, X. Lao, W. Zhang, P. Adab, K. K. Cheng, et al. Height, Its Components, and Cardiovascular Risk Among Older Chinese: A Cross-Sectional Analysis of the Guangzhou Biobank Cohort Study Am J Public Health, October 1, 2007; 97(10): 1834 - 1841. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Langenberg, M. R. G. Araneta, J. Bergstrom, M. Marmot, and E. Barrett-Connor Diabetes and Coronary Heart Disease in Filipino-American Women: Role of growth and life-course socioeconomic factors Diabetes Care, March 1, 2007; 30(3): 535 - 541. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. E Ferrie, C. Langenberg, M. J Shipley, and M. G Marmot Birth weight, components of height and coronary heart disease: evidence from the Whitehall II study Int. J. Epidemiol., December 1, 2006; 35(6): 1532 - 1542. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||