Conceived and designed the experiments: BG GDS. Analyzed the data: BG VM. Wrote the paper: BG VM PM LH JL DL GDS.
The authors have declared that no competing interests exist.
Substantial increases in height have occurred concurrently with economic development in most populations during the last century. In high-income countries, environmental exposures that can limit genetic growth potential appear to have lessened, and variation in height by socioeconomic position may have diminished. The objective of this study is to investigate inequalities in height in a cohort of children born in the early 1990s in England, and to evaluate which factors might explain any identified inequalities.
12,830 children from The Avon Longitudinal Study of Parents and Children (ALSPAC), a population based cohort from birth to about 11.5 years of age, were used in this analysis. Gender- and age-specific z-scores of height at different ages were used as outcome variables. Multilevel models were used to take into account the repeated measures of height and to analyze gender- and age-specific relative changes in height from birth to 11.5 years. Maternal education was the main exposure variable used to examine socioeconomic inequalities. The roles of parental and family characteristics in explaining any observed differences between maternal education and child height were investigated.
Children whose mothers had the highest education compared to those with none or a basic level of education, were 0.39 cm longer at birth (95% CI: 0.30 to 0.48). These differences persisted and at 11.5 years the height difference was 1.4 cm (95% CI: 1.07 to 1.74). Several other factors were related to offspring height, but few changed the relationship with maternal education. The one exception was mid-parental height, which fully accounted for the maternal educational differences in offspring height.
In a cohort of children born in the 1990s, mothers with higher education gave birth to taller boys and girls. Although height differences were small they persisted throughout childhood. Maternal and paternal height fully explained these differences.
Height is a highly heritable trait
Attained adult height is determined by the potential of a child's genotype and the restrictions that the environment places on this
Thus, the aim of this study is to better understand what drives socioeconomic differentials in height from birth to childhood in a contemporary population of UK children born in the early 1990s.
The Avon Longitudinal Study of Parents and Children (ALSPAC) is a population-based study investigating environmental and genetic factors that affect health and development of children. The study methods are described in detail elsewhere
Detailed data about her socioeconomic background, health, welfare and lifestyle characteristics were obtained from the mother using four self-reported questionnaires throughout the pregnancy. Data on delivery and birth measurements were obtained by ALSPAC staff or were otherwise extracted from medical records. Since delivery, regular questionnaires have been completed by the child's main caregiver (most commonly their mother) and as they became older, the children themselves.
Ethical approval for the study was obtained from the ALSPAC Law and Ethics Committee and the Local Research Ethics Committees. Written informed consent was obtained from all participants involved in the study.
Maternal education was ascertained from the antenatal 32-week questionnaire. Education was coded using an ascending mutually exclusive five point scale of highest educational achievement: “None/Certificate of Secondary Education (CSE)”, 2: “Vocational”, 3: “Ordinary- (O-) level (exams taken usually at age 16 years at the completion of legally required school attendance and equivalent to the present UK General Certificate of Secondary Education (GCSE))”, 4: “Advanced- (A-) level (exams taken usually at age 18 years”, and 5: “University Degree”. Levels 1 to 3 refer to different levels (from lowest to highest) of educational qualifications most commonly attained at 16 years of age (the minimum age at which someone could legally leave education in the UK at the time that these mothers were in school); level 4 refers to educational qualifications gained at 18 years of age. Mothers with no educational qualifications most often left the question unanswered which was recoded to none, and those who responded ‘not known’ were left as missing. A previous report on this cohort found similar socioeconomic differentials in birth length and childhood growth irrespective of whether maternal education, head of household occupational social class or father's education was used as the measure of socioeconomic position (SEP)
The height, weight, and smoking habit during pregnancy of the mother's partner were obtained from a partner's self-completed questionnaire that was passed to them via the mother. For 95.5% of the children the mother's partner was the biological father (by mother's self-report). Mid-parental height was calculated using both parents' height adapting Galton's formula
Data on delivery and birth measures (crown-heel length and head circumference) were obtained by trained staff of the ALSPAC team for babies born in the two major maternity hospitals in the region and from medical records for the other participants. Gestational age was estimated using the mother's last menstrual period in most cases and through obstetric assessment for the rest. Whether the mother breastfed, and duration of breastfeeding, were ascertained at 6 months and categorized into a composite variable, as “Never or up to one month” versus “more than one month”.
Height after birth was measured by health visitors and general practitioners as part of standard childcare in the UK. The examinations take place at around the 8th week (median: 8 weeks, range: 1.3 to 58.6 weeks), 8th month (median: 9 months, range: 1.2 to 21 months), 18th month (median: 18 months, range: 10 to 30 months) and at the pre-school child visit at 3.5 years (median: 3.6 years, range: 2.5 to 5.9 years). Thereafter, the whole cohort of children was invited to attend clinical examinations. The first ALSPAC direct measurement of height occurred at an average of 7.5 years (range: 6.8 to 9.2 years) and four subsequent yearly examinations were held at ages 8.5 years (range: 7.5 to 10.5 years), 9.5 years (range: 8.7 to 11.7 years), 10.5 years (range: 9.8 to 11.3 years) and 11.5 years (range: 10.4 to 13.6 years). There are in total a maximum of 10 measurements of height per child. In the clinics (from age 7.5 years) height was measured by trained technicians to the last complete millimetre using the Harpenden stadiometer (Holtain Ltd). As far as possible, all children were measured in their underclothes with their shoes removed. For all measurements taken, the tester recorded any problems that may have affected accuracy. In a previous study we have shown that heights assessed from birth to pre-school by health visitors were accurate, by comparing these with research clinic measurements completed on a random 10% sub-sample of the ALSPAC cohort
Gender- and age-specific z-scores for length/height were calculated. Z-scores control for the association of age and gender on height and its change, and standardise for the increasing variance of the measurements with increasing age. As there was considerable variation in the ages at which the children had their measurements taken, z-scores were calculated within the following time intervals, irrespective of the visit when they were obtained: i) for birth length, gestational age in 1 week intervals for those born from 37 to 43 weeks; ii) for length/height between the 1st week and 6 months, child's age in 1 week intervals; and, iii) heights beyond 6 months, child's age in 1 month intervals. Time intervals with too few observations for appropriate calculation of a z-score were combined with the earlier interval. An alternative method to standardise height using a locally weighted smoother was evaluated but produced similar standardised values (results available from the authors). Z-scores were preferred as they are more easily interpreted and translated to the original scale.
Exploratory cross-sectional analyses were carried out at each visit to evaluate the association of mother's education with child's height at each age. Multilevel modelling was carried out to model height (in z-scores) change with age and to evaluate the role of the mother's educational level on the child's height z-score trajectory. There was strong statistical evidence in both boys and girls, that a random intercept and random slope model provided a better fit to the data than a model that included a random intercept only (maximum likelihood ratio test between a random intercept only and a random intercept and slope model p-value<0.001). The association with maternal education was evaluated as a categorical and ordinal variable and gender differences in the educational effect on height were tested with an interaction term.
The following explanatory variables were evaluated to test mechanisms that could explain differences in child's height according to mother's education. These variables were chosen based on previous reports of the literature of determinants of child's height. Maternal age at delivery (years), maternal height (cm) and body mass index (BMI in kg/cm2), number of children, gestational age (weeks) maternal smoking during gestation, child's early nutrition measured with breastfeeding and maternal food frequency questionnaire at 32-week pregnancy, paternal height (cm), BMI and smoking habit during gestation. These variables were added in the multilevel model as fixed effects using restricted maximum likelihood. Wald tests were used to evaluate the effect of adding each fixed term. All continuous variables were centred on their mean value. Models were also adjusted for a dummy variable indicating the visit at which the measurement took place to adjust for potential differences occurring between measurements.
All analyses were repeated excluding observations with z-scores of height above 2 or below −2 which allowed evaluation of the influence of extreme values on the model (by definition, around 5% of the data) to test the robustness of the results and the assumptions of the models and improve the normality distribution of the outcome variable. All analyses were carried out using STATA (version 10.1 for Windows).
The analyses were restricted to singletons as in-utero conditions may differ for multiple pregnancies (390 multiple pregnancies were excluded) and to pregnancies that resulted in a child alive at 27 days after birth (635 observations excluded, including all foetal losses at any stage of the pregnancy) and were term births (≥37 weeks) (693 observations excluded). Children who had no height measure available throughout the entire follow-up were excluded (n = 115). Finally, measurements of birth length that were obtained later than one week after delivery were not considered (180 measurements), as these may no longer reflect birth length, although all subsequent measures of these children were used in the analyses. The final sample included 12,830 children (6,579 boys with a median of 6 measurements (interquartile range (IQR): 4 to 9); 6,251 girls with a median of 7 measurements (IQR: 4 to 9).
Mother's educational level was available for 89.4% of the children (n = 11,473). Almost 20% (n = 2,289) had either no education or education to CSE level, 9.8% had vocational education, 34.8% had O-levels, 22.5% had A-levels and 12.9% of the mothers had a university degree. The median number of height measurements was greater with higher maternal educational level: 4 measurements (IQR: 3 to 5) for mothers with no education or CSE level, 6 measurements (IQR: 4 to 9) for those with vocational training, 7 measurements (IQR: 5 to 9) for mothers with O-levels, and 8 measurements (IQR: 5 to 9) for mothers with A-level or university degrees. Mean height increased with age similarly among boys and girls. Boys tended to be slightly taller than girls up until the age of 7–8 years. Birth length and height were consistently higher with increasing levels of mother's education although the magnitude of these differences across educational groups was relatively small (
* There were few children aged 5 or 6 and 13, thus their mean height was calculated jointly with those aged 4 and 12, respectively.
None/CSE | Vocational | O –level | A-level | Degree | Trend p-value | ||||||
n | mean | n | mean | n | mean | n | mean | n | mean | ||
|
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Gestational age (weeks) | 2289 | 39.8 | 1128 | 39.7 | 3988 | 39.8 | 2583 | 39.7 | 1485 | 39.8 | 0.74 |
Breastfeeding >1month, n, % | 1717 | 37.9 | 918 | 42.4 | 3524 | 56.2 | 2358 | 73.9 | 1402 | 87.9 | <0.001 |
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Mother's age at delivery (years) | 2289 | 26.9 | 1128 | 26.9 | 3988 | 27.5 | 2583 | 29.5 | 1485 | 31.4 | <0.001 |
Number of children | 2113 | 1.13 | 1068 | 0.84 | 3831 | 0.78 | 2486 | 0.74 | 1450 | 0.68 | <0.001 |
Maternal height (cm) | 2007 | 162.8 | 1042 | 163.2 | 3766 | 164.1 | 2469 | 164.4 | 1432 | 165.8 | <0.001 |
Maternal BMI (kg/m2) | 1855 | 23.5 | 967 | 23.3 | 3575 | 23.0 | 2359 | 22.7 | 1383 | 22.1 | <0.001 |
Maternal diet pregnancy at 33 weeks | |||||||||||
Energy (kcal/day) | 2151 | 1739.9 | 1080 | 1751.0 | 3858 | 1774.4 | 2502 | 1781.7 | 1435 | 1828.8 | <0.001 |
Protein intake (g/day) | 2151 | 60.3 | 1080 | 62.9 | 3858 | 66.1 | 2502 | 68.6 | 1435 | 71.7 | <0.001 |
Total fat (g/day) | 2151 | 69.3 | 1080 | 70.3 | 3858 | 70.7 | 2502 | 69.7 | 1435 | 70.5 | 0.26 |
Saturated fat (g/day) | 2151 | 29.4 | 1080 | 29.3 | 3858 | 29.1 | 2502 | 28.3 | 1435 | 28.5 | 0.001 |
Polyunsaturated fat (g/day) | 2151 | 11.2 | 1080 | 12.2 | 3858 | 12.4 | 2502 | 13.0 | 1435 | 13.7 | <0.001 |
Monounsaturated fat (g/day) | 2151 | 24.5 | 1080 | 24.9 | 3858 | 24.9 | 2502 | 24.5 | 1435 | 24.9 | 0.73 |
Carbohydrates (g/day) | 2151 | 223.7 | 1080 | 220.6 | 3858 | 222.1 | 2502 | 222.2 | 1435 | 227.5 | 0.23 |
Ever smoking during pregnancy, n, % | 2020 | 48.7 | 1010 | 36.1 | 3661 | 26.7 | 2371 | 19.1 | 1405 | 9.3 | <0.001 |
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Partner's height (cm) | 1252 | 174.8 | 682 | 175.0 | 2673 | 176.1 | 1768 | 176.5 | 1135 | 177.6 | <0.001 |
Paternal BMI (kg/m2) | 1228 | 25.4 | 676 | 25.5 | 2641 | 25.3 | 1752 | 25.1 | 1132 | 24.6 | <0.001 |
Partner' smoking, n,% | 2076 | 51.1 | 1064 | 45.2 | 3830 | 39.7 | 2503 | 31.2 | 1459 | 20.1 | <0.001 |
BMI: body mass index.
Boys | Girls | Combined | ||||
Education | β | 95% CI | β | 95% CI | β |
95% CI |
|
ref | - | ref | - | ref | - |
|
0.067 | −0.014, 0.147 | 0.047 | −0.031, 0.126 | 0.060 | 0.003, 0.118 |
|
0.090 | 0.031, 0.148 | 0.098 | 0.041, 0.155 | 0.090 | 0.049, 0.132 |
|
0.120 | 0.056, 0.183 | 0.124 | 0.062, 0.187 | 0.124 | 0.078, 0.169 |
|
0.209 | 0.135, 0.283 | 0.230 | 0.158, 0.302 | 0.220 | 0.168, 0.273 |
|
0.046 | 0.030, 0.062 | 0.051 | 0.036, 0.067 | 0.049 | 0.037, 0.060 |
Adjusted for gender.
β | 95% CI | |
|
0.054 | 0.043, 0.065 |
|
−0.034 | −0.049, −0.019 |
|
0.067 | 0.035, 0.099 |
|
0.011 | 0.008, 0.014 |
|
0.047 | 0.045, 0.049 |
|
0.012 | 0.008, 0.016 |
|
−0.170 | −0.203, −0.137 |
|
−0.00002 | −5.5×10−5,7.1×10−6 |
Protein intake (g/day) | 0.001 | 0.0002, 0.002 |
Total fat (g/day) | −0.0005 | −0.001, 0.0001 |
Saturated fat (g/day) | −0.001 | −0.003, −0.0002 |
Polyunsaturated fat (g/day) | 0.002 | −0.001, 0.004 |
Monounsaturated fat (g/day) | −0.002 | −0.003, 0.0001 |
Carbohydrates (g/day) | −0.0003 | −0.0005, −0.0001 |
|
0.041 | 0.039, 0.044 |
|
−0.048 | −0.078, −0.018 |
0.018 | 0.012, 0.023 | |
|
0.073 | 0.070, 0.076 |
All mean differences are adjusted for gender only.
They are not mutually adjusted for the other characteristics.
When considering growth until 10 years of age only in order to assess whether pubertal changes already occurring in some children could have influenced the results, educational inequalities in child's growth remained similar (ß = 0.048 SD, 95% CI: 0.036, 0.059). When all analyses were repeated excluding observations with standardised height values above 2 or below −2 the effect of maternal education on standardised height growth remained although the magnitude of the effect was slightly reduced (ß = 0.041 SD, 95% CI: 0.031, 0.051). Maternal and partner's height remained as the main explanatory variables of the educational differences in child's height growth (adjusted ß = −0.003; 95% CI: −0.015, 0.008), whereas adjustment for all other characteristics, but not mid-parental height, resulted in attenuation but some association remained (adjusted ß = 0.018, 95% CI: 0.002, 0.033). Finally, educational inequalities in child's growth were slightly greater after removing those with only one or all ten height measures (ß = 0.051 SD, 95% CI: 0.039, 0.064) and the role of the explanatory variables remained the same (maternal education ß adjusted for mid-parental height = 0.0003; 95% CI: −0.014, 0.014; maternal education ß adjusted for all other characteristics except mid-parental height = 0.026; 95% CI: 0.007, 0.014).
Among children born in the UK in the early 1990s, those born to mothers with higher educational levels were taller than those born to mothers of lower educational levels. These height inequalities were present at birth and persisted over time (0.39 cm in birth length, 1.4 cm at the age of 11.5 years). Mid-parental height fully explained the differentials in child's height growth across maternal educational levels. Although most of the other explanatory variables investigated were associated with the child's height and were socially patterned, they accounted for little of the maternal educational inequalities in the child's height.
The improvements in pre-natal and maternal care and child nutrition, along with fewer childhood infections would suggest that inequalities in height due to environmental exposures should have decreased or disappeared in high income countries
The Boyd Orr study, a cohort of 4999 children surveyed between 1937–39 in the UK, showed a general pattern of greater stature and body proportions (leg and foot length, trunk and shoulder width were also investigated) with better childhood socioeconomic and housing circumstances as well as diet
We found a similar pattern of association of potentially modifiable exposures with height growth in ALSPAC with those reported in the literature
However, although these factors were associated with child's height they explained little of the inequalities, whereas educational inequalities in childhood height were no longer present when comparing children whose parents had the same mid-parental height. Li et al compared the effect of parental height in the two generations and found parental height had a stronger association in the offspring than the parents' generation
Parental height is often used as proxy for the genetic component of height. Indeed, the fact that the combination of both parents' height was necessary to account for the height differences, rather than maternal height alone, does seem to point to a strong genetic contribution. However, parental height partly reflects the embodiment of a range of social and environmental characteristics shared within a family that relate to the parents' stature and will also influence offspring height (e.g. socially patterned behaviours that are transmitted through generations and therefore can influence parental height as well as that of the offspring). These could be transmitted to subsequent generations through several mechanisms. Assortative mating by social class can result in parents of higher education, who are taller, transmitting their genetic, social and environmental characteristics to their children who then also grow to be taller. In the ALSPAC cohort, maternal and partner's height increased with increasing education and the educational level of the mother's partner tended to be similar to her own (65% of the mothers with no or basic education had partner with no or basic education whereas 75% of mothers with a degree had a partner with a degree). On the other hand, a gene-by-environment correlation with respect to genetic variants related to height could also generate this pattern. Mid-parental height might also incorporate effects due to exposures that are not measured accurately, e.g. maternal smoking during pregnancy. Smoking has a negative effect on height
The next step in understanding the associations of height and height inequalities in high income countries requires understanding the determinants of parental height that are transmitted across generations, and disentangling the different aspects, genetic and environmental, that are captured by this variable. On the one hand, we need more knowledge on the genetic variants related to height, as up until now these can only explain about 45% of the height variance
Some methodological limitations need to be considered in interpreting results from this study. Birth measures were available for about 60% of the total sample. Height measures from the first child visit were available for more than 80% of the cohort but this decreased to about 50% by age 11.5 years. There were fewer height measurements for children of mothers with lower levels of education. This loss to follow-up will only bias the results if the direction of the association in those who did not participate or were lost to follow-up was in a different direction to the one reported here. A previous report from this cohort analysed participants with at least 9 height measures and found similar results as to when children with 1 or more measures were included
As some heights were standardised over a wider age range (intervals were collapsed when there were too few observations for appropriate calculation of a z-score) this resulted in a positive correlation of height z-scores with age, and therefore all models were additionally adjusted for an age z-score to fully account for differential ages at measurement. The effect of education on height did not differ between the models that included this additional adjustment and those that didn't.
In conclusion, inequalities in child's growth, although relatively small in magnitude, persist in England. These were fully explained by maternal and paternal reported height. Disentangling the genetic and environmental factors that this variable captures will help understanding the preventable factors that underlie height inequalities in rich income countries.
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We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses.
We are grateful to Sam Leary who managed and provided the database for this analysis.