Family, socioeconomic and prenatal factors associated with failure to thrive in the Avon Longitudinal Study of Parents and Children (ALSPAC)

PS Blair1, RF Drewett2, PM Emmett1, A Ness1, AM Emond1 and the ALSPAC Study Team

1 The Division of Child Health, University of Bristol, Bristol, BS8 1TQ, UK
2 Department of Psychology, University of Durham, Durham, DH1 3LE, UK

Correspondence: Dr Peter S Blair, The Division of Child Health, University of Bristol, Education Centre, Upper Maudlin St, Bristol, BS2 8AE, UK. E-mail: p.s.blair{at}bris.ac.uk


    Abstract
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 Abstract
 Materials and methods
 Results
 Discussion
 References
 
Background The epidemiological profile of infants failing to thrive is unclear. The aim of this study is to investigate the prenatal and socioeconomic factors associated with these infants using standardized weight gain conditional on previous weight.

Methods In a large UK population cohort study, 11 718 infants born at term in 1991–1992 with no major congenital abnormalities were identified. Using a weight gain criterion conditional on initial weight from birth to 6–8 weeks, 6–8 weeks to 9 months, and birth to 9 months, the slowest gaining 5% were identified.

Results None of the prenatal factors was associated with failure to thrive in the multivariable analysis nor were traditional markers of socioeconomic deprivation such as poor parental education or low occupational status. Parental height was significantly correlated with slow infant weight gain in both separate periods and from birth to 9 months (Pearson's r = +0.20, P < 0.001). Eight times as many infants born to shorter parents (8.7%, 95% CI: 6.6, 11.3) showed slow weight gain as infants born to taller parents (1.1%, 95% CI: 0.5, 2.5). Higher parity was also related to slow infant weight gain; infants born in the fourth or subsequent pregnancy were twice as likely to fail to thrive from birth to 9 months (8.3%, 95% CI: 6.4, 10.6) as first-born infants (3.4%, 95% CI: 2.9, 10.6).

Conclusions Future studies need to take account of parental height when calculating growth standards and look at why failure to thrive is more common, not in poorer families but in larger families.


Keywords Failure to thrive, weight faltering, epidemiology, parental height, parity, socioeconomic status, prenatal factors

Accepted 19 December 2003

Failure to thrive is a term used to describe ‘infants and young children whose growth is substantially less than that of their peers’.1 There is good evidence that it is associated with developmental delay,2–3 and some evidence that it is associated with later intellectual deficits4–5 and insecure attachment.6–8

Although in clinical practice the identification of failure to thrive might also involve these associated features it is usually identified initially from slow weight gain. Much recent discussion of the exact criteria to be used amounts to a discussion of the ‘peers’ who should provide the reference group. Boys and girls grow at different rates, so the peers should be of the same sex. But infants born at different weights also grow at different rates:9 smaller infants tend to grow faster, whilst larger infants grow more slowly. Recently developed conditional standards10,11 take into account this regression towards the mean and summarize how an infant's weight gain compares with the weight gain of other infants of the same sex and initial weight. By taking into account the child's initial weight, one avoids the confounding of poor postnatal and poor prenatal weight gain that is inherent in the use of the more conventional attained weight criteria for failure to thrive (for example, having a weight below the 3rd or 5th centile).

Understanding of the nature of failure to thrive and of its sequelae would be improved if its epidemiology were more clearly understood. Frank and Zeisel12 argued that the most important social risk factor for failure to thrive was poverty, but Skuse13 noted the lack of any direct evidence for this from representative samples of socioeconomically diverse populations. A recent study of a whole one-year birth cohort in Newcastle-upon-Tyne in the UK11 found that the relative risk for failure to thrive was about twice as high in deprived as in the intermediate areas; but it was also substantially higher in affluent areas. An earlier review14 noted the lack of research on pregnancy and birth issues in failure to thrive. Altemeir15 subsequently carried out a prospective study in which several prenatal correlates of failure to thrive were reported, including lower maternal weight gain in pregnancy, more complications of pregnancy and a shorter gestation, though only 15 cases were identified. Dietary restraint during pregnancy has also been reported in mothers of children who failed to thrive16 again in a small study that included only 26 cases.

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a large on-going population-based cohort study of child growth, development, and health in the South West of England in which pregnant mothers were recruited between 1991 and 1992. The analyses we report examine further the epidemiology of failure to thrive, concentrating particularly on social and prenatal factors.


    Materials and methods
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 Abstract
 Materials and methods
 Results
 Discussion
 References
 
The ALSPAC study was designed to examine environmental and genetic influences on the health and development of young children. The study started during pregnancy, and aimed to enrol all women who were resident in the three Bristol-based health districts of the county of Avon (population 940 000) and who had an expected date of delivery between 1 April 1991 and 31 December 1992. Avon has a predominantly white population with a mixture of urban and rural communities and a socioeconomic mix similar to the rest of the UK. Within this 21-month period there were 14 062 live births amongst mothers recruited into the study (85% of all eligible mothers in the study area). Information was obtained both from self-completion questionnaires and from clinical records. Ethical permission was granted by the Ethics Committees of United Bristol Healthcare Trust and Frenchay and Southmead Healthcare Trusts, and the study was also monitored by the ALSPAC Ethics and Law Advisory Committee.17 Methodological details of the study have previously been published18,19 and further information including the questionnaires used can be found at www.alspac.bris.ac.uk

Growth measurements made by health professionals as part of the infant health surveillance programme were extracted from the child health computer and verified with weight data recorded through ALSPAC questionnaires. Thus although the identification of failure to thrive was made retrospectively, the growth data used were collected prospectively. The measurements taken were those at birth, and as near as possible to 6–8 weeks and 9 months when child health reviews are conducted nationally in the UK. Some infants may grow poorly in the first few weeks of life purely because of early neonatal problems or difficulties with establishing feeding; the current study was able to take account of this by examining infant growth over the first few weeks separately from that over subsequent months.

Using the British 1990 Growth Reference,10 the infants' weights were converted to z-scores. Their z-scores for weight gain were then calculated using an EXCEL algorithm incorporating Cole's procedure.10 These estimates are conditional on the earlier weight as well as on gender, and so take into account regression to the mean. A positive value denotes weight gain faster than average and a negative value denotes weight gain slower than average. Cases were identified as infants whose weight gain was below the 5th centile (i.e. below a z-score of –1.645). This definition is comparable with traditional criteria for failure to thrive when it is used over the period birth to 9 months or 6–8 weeks to 9 months.11 The same analyses were conducted using both the 10th and 2.5th centile cut-offs (not reported), with similar findings to those presented here.

Variable definition
Data were collected using a series of postal questionnaires for both the mother and partner throughout the pregnancy and at different stages in the first year of the infant's life. Data included self-reported parental characteristics, social habits, socioeconomic status, obstetric history, and factors relating to the current pregnancy and birth outcome. Parental body mass index (BMI) was computed as weight (kg) over height (m) squared. An infant born at term was born from the 37th to 41st completed weeks inclusive. Parity was the number of pregnancies resulting in a live or stillbirth. Social class was defined using the UK Registrar General's occupational coding; the occupation of both parents were coded from social class V (unskilled manual) to social class I (professional), the parental categorization closest to the latter being allocated to the family.

Statistical methodology
Given the large number of variables under study, a simple dichotomy was used where possible to ease the interpretation of the multivariable results; if a standard cut-off point for a continuous variable was not available we examined the approximate lowest quartile of the cohort (or quintile if both ends of the distribution were of interest). The probability of a Type-1 error (a false positive result) was reduced by focussing on those factors significant in the multivariable analysis below the 1% significance level.

Normal distributions were described using the mean and standard deviation (SD) and other distributions using medians and inter-quartile ranges (IQR). Odds ratios (OR), 95% CI, and P-values (all quoted as two-sided) were calculated for both the univariable and multivariable analyses. Correlation was calculated as Pearson's r for normal data and Spearman's {rho} for ordinal data. CI for single proportions were calculated using Wilson's' method.20 In the univariable analysis differences were evaluated using the {chi}2 test with Yates's continuity correction (or Fisher's Exact Test when an expected cell count was less than 5). Variables significant at the 5% level in the univariable analysis were entered into subsequent multivariable models. Variables in the univariable analysis with more than 20% missing values (mainly data relating to the partner or previous pregnancies) were initially excluded from the multivariable process and later added to the finalized model to test for significance.

Multivariable analysis was conducted using logistic regression with the statistical package SAS,21 the dependent variable indicating whether the infant was in the slowest growing 5%. Multivariable models were constructed using the stepwise method for selection of variables.22


    Results
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 Abstract
 Materials and methods
 Results
 Discussion
 References
 
Ascertainment
Of the 14 062 live births in the study a small proportion (0.7%) were lost to follow-up mainly because the family moved out of the study region. A further 89/13 970 infants (0.6%) with major congenital abnormality (e.g. cerebral palsy, Down's syndrome, cleft palate, congenital heart disease) were excluded along with 893/13 970 infants (6.4%) not born at term (22 of which also had a major congenital abnormality). Of the remaining 13 010 infants, 11 718 (90.1%) had weights available at birth, 6–8 weeks, and 9 months and the analyses were carried out on these infants.

The median weight of the 11 718 infants at birth was 3.46 kg (IQR: 3.15–3.76 kg), at 6 weeks it was 5.00 kg (IQR: 4.58–5.47 kg), and at 9 months it was 9.10 kg (IQR: 8.39–9.87 kg). Corrected for gestational age and gender, birth weight z-scores were normally distributed with an SD of one and a mean just above zero (+0.07). The weight gain z-score of the infants from birth to 9 months was also normally distributed with a mean slightly above zero (+0.15) and an SD around one (1.06). Weight gain was similarly distributed from birth to 6–8 weeks (mean weight gain z-score = –0.02, SD 0.95) and from 6–8 weeks to 9 months (mean weight gain z-score = +0.19, SD 1.11).

The number of cases and controls for each period of growth measured and the median number of days between measurement are given in Table 1.


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Table 1 Slowest growing infants (z-score < –1.645) in each period. Avon Longitudinal Study of Parents and Children (ALSPAC) 1991/1992, N = 11 718 infants

 
Only 30/11 718 (0.3%) infants with slow weight gain in the first period from birth to 6–8 weeks were also identified as having slow weight gain in the second period from 6–8 weeks to 9 months. Of those infants with slow weight gain from birth to 9 months, 97/531 (18.3%) had slow weight gain in the first period and 334/531 (62.9%) in the second period.

Univariable analysis
Table 2 relates the prevalence of infants with slow weight gain over the three time periods to the family and the socioeconomic conditions.


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Table 2 Proportion of slowest growing infants (z-score < –1.645) by family and socioeconomic variables: univariable findings Avon Longitudinal Study of Parents and Children (ALSPAC) 1991/1992, N = 11 718 infants

 
The median age of the mothers in the study was 28 years (IQR: 24–31 years). Slow weight gain was more common amongst infants of both younger (<24 years) and older mothers (>32 years) in the first 6–8 weeks after birth, but not over the later period; in fact fewer infants born to younger mothers had slow weight gain in this period. The median height of the mothers in the study was 162.5 cm (IQR: 160–167 cm). Short maternal height (<160 cm) was associated with a higher prevalence of slow weight gain in all three time periods. Low maternal weight (<55 kg) before pregnancy was not associated with slow weight gain over the first period of study but was over the second period, whilst low maternal BMI (<20 kg/m2) was associated with slow weight gain over the whole 9-month period.

These associations were similar when treating these factors as continuous variables. Maternal height was correlated with weight gain for all three time periods (Pearson's r: birth to 6–8 weeks = +0.09, P < 0.001; 6–8 weeks to 9 months = +0.11, P < 0.001, birth to 9 months = +0.15, P < 0.001). Maternal pre-pregnancy weight was not significantly correlated with weight gain for the first time period (+0.02, P = 0.13) but was for the other periods (6–8 weeks to 9 months = +0.08, P < 0.001; and birth to 9 months = +0.09, P < 0.001). Paternal height (and to a lesser extent paternal weight) was a significant predictor, but not paternal BMI.

Characteristics of the family unit and the socioeconomic status in which they lived were also examined. Being a single mother was not associated with slow weight gain, but higher parity was from 6–8 weeks to 9 months. Using first-born study infants as the reference group the risk for a second-born infant was 1.51 (95% CI: 1.21, 1.88), P = 0.0003, for a third-born it was 1.81 (95% CI: 1.38, 2.38), P < 0.0001, and for fourth or higher-born infants it was 2.16 (95% CI: 1.52, 3.07), P < 0.0001. As an ordinal factor, parity was negatively correlated with weight gain measured from 6–8 weeks to 9 months (Spearman's {rho}{perp} = +0.11, P < 0.001). Figure 1 shows a similar association from birth to 9 months; the proportion of slowest gaining infants was much larger (8.3%, 95% CI: 6.4, 10.6) amongst families with ≥4 children than among primiparous families (3.4%, 95% CI: 2.9, 4.0).



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Figure 1 Proportion and 95% CI of slowest growing infantsa from birth to 9 months by size of family. ALSPAC study from 1991 (N = 10 592)

a Defined as those with a growth z-score < –1.645.

Actual numbers: Parity 1 = 166/4860, 2 = 177/3864, 3 = 91/1575, ≥4 = 54/653

 
Several variables were used to measure different aspects of socioeconomic status within the families. Slow weight gain was not associated with parental social class based on occupation either as a dichotomous variable or when broken down further. Indeed, Figure 2 shows that the slightly higher proportion of infants with slow weight gain in social class IV and V was also observed in social class I.



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Figure 2 Proportion and 95% CI of slowest growing infantsa from birth to 9 months in each social stratum.b ALSPAC study from 1991 (N = 9798)

a Defined as those with a growth z-score < –1.645.

b UK Registrar General's occupational classification ranges from I—professional, II—managerial, IIIn—skilled non-manual, IIIm—skilled manual to IV/V—semi-skilled and unskilled occupations

Actual numbers: I = 63/1207, II = 167/4078, IIIn = 110/2633, IIIm = 67/1318, IV/V = 30/562

 
Slow weight gain was not related to parental educational level. However, it was associated with living in rented accommodation and no use of a telephone or a car in the univariable analyses. Most of the factors relating to the mother's obstetric history (Table 3) were not associated with subsequent slow weight gain of the infant. These included previous miscarriages and child deaths, young age at first pregnancy, prior pre-term births, self-reported history of an eating disorder such as anorexia nervosa or bulimia, or a short inter-pregnancy interval.


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Table 3 Proportion of slowest growing infants (z-score < –1.645) by prenatal variables: univariable findings. Avon Longitudinal Study of Parents and Children (ALSPAC) study from1991, N = 11 718 infants

 
Other factors such as a history of previous abortions or stillbirths, older age at first pregnancy, and previous small births showed a weak univariable association. Factors relating to the pregnancy of the study infant were even less likely to predict subsequent slow weight gain; being on a diet during pregnancy or vegetarianism in the mothers were not predictive; nor was having an infection during pregnancy, smoking, or high caffeine or alcohol consumption. Taking illegal drugs during pregnancy (mainly cannabis) was associated with slow weight gain in the first 6 to 8 weeks of life although the number of mothers who reported using drugs was small. Factors relating to the birth of the infant such as multiple birth or admission to a neonatal intensive care unit (NICU) were not associated with slow weight gain. A slightly higher prevalence of slow weight gain was observed among female infants and those with lower birthweight.

Multivariable analysis
Factors significant in the univariable analysis at the 5% level from Tables 2 and 3 were entered into a multivariable regression model for the three time periods. Table 4 lists those factors that were independently significant at the 1% level in at least one of the models.


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Table 4 Predictive variables of slowest growing infants: multivariable findings Avon Longitudinal Study of Parents and Children (ALSPAC) 1991/1992, N = 11 718 infants

 
Slow weight gain in the first few weeks of life was independently associated with maternal height (shorter mothers), maternal age (older mothers), and use of a car (no use of a car in the household). Lack of transport was strongly associated with other socioeconomic markers such as lower social class, poor parental education, insecure tenure, unsupported mothers, and lack of a telephone but none of these were significant predictors in the multivariable model when lack of transport was removed from the analysis.

Slow weight gain from 6–8 weeks to 9 months was even more strongly associated with maternal height and was also associated with higher parity but was not associated with older maternal age or lack of transport.

Over the period from birth to 9 months the associations with short maternal height and parity were also evident. These factors along with low maternal BMI were the strongest predictors of slow weight gain over the whole period from birth to 9 months. The mean growth of infants born to the shortest mothers (defined as <160 cm) in z-scores was –0.08 (95% CI: –0.04, –0.12) compared with +0.15 (95% CI: +0.12, +0.18) for those mothers with heights in the second and third quartiles and +0.35 (95% CI: +0.31, +0.39) for the tallest mothers (>170 cm).

Few of the prenatal factors were predictive of poor infant growth in the univariable analysis and none were significant when added to the multivariable models. Some predictive univariable factors such as paternal weight and height and previous pregnancies involving small infants had a large number of missing values and were not added to the multivariable models until the end. These factors were not predictors when measuring weight gain from birth to 6–8 weeks or 6–8 weeks to 9 months but small paternal height (<171 cm) was significant when measuring infant weight gain over the whole period (OR = 1.65, 95% CI: 1.28, 2.13). Measurements of paternal height were available for less than two-thirds of the children and adding this factor to the multivariable model nearly halved the numbers under study. However paternal height was positively correlated with infant weight gain (Pearson's correlation coefficient from birth to 9 months = +0.15, P < 0.001). Short maternal height (OR = 1.75, 95% CI: 1.35, 2.26), smaller maternal BMI (OR = 1.46, 95% CI: 1.10, 1.95), and increased family size (OR = 1.60, 95% CI: 1.22, 2.11) remained predictive in the model that included paternal height.

Table 5 shows the proportion of infants who failed to thrive cross-tabulated by the heights of both their parents.


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Table 5 Cross-tabulation of slowest growing infants (z-score < –1.645) from birth to 9 month by parental height Avon Longitudinal Study of Parents and Children (ALSPAC) 1991/1992, N = 7177 infants

 
Amongst the infants with two shorter parents 8.7% (95% CI: 6.6, 11.3) showed slow weight gain from birth to 9 months, whilst among those with two taller parents the proportion was only 1.1% (95% CI: 0.5, 2.5). The significant correlation between infant weight gain and the height of the mother or partner was even stronger when these two heights were added together (Pearson's correlation coefficient = +0.20, P < 0.001).


    Discussion
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 Abstract
 Materials and methods
 Results
 Discussion
 References
 
The most striking aspect of the results given the size of the study is the small number of variables that are independently associated with slow weight gain. No large systematic effects were found either of social or of prenatal variables. There is an element of selection bias in the ALSPAC sample, as there is in other samples of this kind, with a greater representation of more affluent families (data on this can be found at http://www.alspac.bris.ac.uk/AlspacExt/MainProtocol/rep_nature_of_sample.sh).

But the number of children from social class IV and V families (562) is still very large in comparison with previous studies. Obviously we are not intending to say that poor weight gain is never associated with social variables, since in other parts of the world its strong association with poverty is clear. The association is not found in the UK, however, perhaps as a result of the relative cheapness of food and of a reasonable system of benefits for families with young children.

The infants in the study had a slightly higher mean birthweight than the reference population. The slightly higher score was in line with Government statistics of the period which showed that 5.8% of infants born in Avon weighed below 2500 g in 199123 and 6.1% in 1992,24 a smaller proportion than in England & Wales generally (6.9% in 1991, 7.0% in 1992). The infants in the study also had a slightly higher mean growth score reflected in the fact that the proportion of cases for each period was under 5%. This is partly due to the removal from the population of those with major disorders but may also be due to temporal or geographical variation, as the reference population lived 10 years earlier in Cambridge. The results are restricted to infants born at term. Failure to thrive is common in infants born preterm in this as in other populations but the special nutritional and oral-motor problems found in preterm populations led us to consider infants born preterm separately.25

Both maternal and paternal height were associated with infant weight gain. Maternal heights were available for most of the cohort, and short maternal height was clearly associated with slower weight gain in multivariable analyses, both over the first 9 months and over the two periods birth to 6–8 weeks and 6–8 weeks to 9 months separately. Paternal height was available for fewer infants but did have an additional association when added to the multivariable model. Parental height is systematically related to social class and it is not appropriate to treat it as a purely biological variable.26 However, traditional indicators of social class (parental occupation and level of education) were not associated with slower weight gain, even at the univariable stage; nor were factors strongly associated with these markers such as maternal smoking and alcohol consumption. In the multivariable analysis lack of private transportation was associated with poor growth. This factor is used in deprivation indices such as Townsend Scores27 as a marker for low income; it could also reflect family isolation. However, this was only a predictor of poor infant growth when measuring slow weight gain from birth to 6–8 weeks whereas parental height was associated with slow weight gain for all periods measured. Recent concerns raised by WHO regarding the adequacy of currently existing growth references prompted a large study of growth across Europe which concluded that mid-parental height was the best single predictor of the recumbent length of an infant.28 It is striking that in the study we report here poor infant weight gain is also strongly associated with the height of the mother and father; clearly this association should be taken into account in identifying failure to thrive.

The second strong association was with parity. Skuse13 earlier reported parity to be unassociated with failure to thrive. In this population, however, there was a strong and systematic relationship between the two. Using first-born infants as the reference, the relative risk increased for each subsequent sibling. Parity was an important predictor for poor infant growth from birth or from 6–8 weeks to 9 months. In the shorter period from birth to 6–8 weeks older maternal age rather than parity was a more important predictor. Given that parity and maternal age are strongly correlated with family size this could suggest that both factors may be proxy markers for some other family characteristic we have yet to identify. To investigate the reasons for such an association further study is required of how infant care practices, particularly infant feeding, vary with parity.

Previous studies15,16 have suggested that lack of weight gain during pregnancy and maternal dietary restraint may be factors associated with subsequent poor infant growth. Our findings suggest slow weight gain was slightly more common amongst the infants of mothers with a history of eating disorders and those who dieted or were on a vegetarian diet during pregnancy; these differences were not statistically significant, although our data on eating disorders were based on self-reported histories of past eating disorders rather than diagnostic interviews of present problems.

We have investigated a number of factors potentially associated with slow weight gain therefore running the risk of obtaining false-positive results. However, we have minimized the possibility of Type II error by focusing on those results significant in the multivariable analyses at the 1% level. The main findings of these analyses is that parental height correlates with infant weight gain in the first 9 months of life and should be taken into consideration in future growth standards. Slow infant weight gain is also strongly associated with parity, suggesting that larger families constitute a risk factor for failure to thrive that deserves further investigation.


KEY MESSAGES

  • Poor infant weight gain in the UK is not associated with traditional markers of socioeconomic deprivation.
  • Weight gain is positively correlated with parental height, thus infants with poor weight gain are more common amongst smaller parents.
  • The risk of poor weight gain increases in subsequent siblings.

 


    Acknowledgments
 
We are extremely grateful to all the parents and children who took part in this study and to the midwives for their help in recruiting them. We would like to acknowledge the dedicated work of the ALSPAC study team; this includes interviewers, computer technicians, clerical workers, research scientists, volunteers, and managers. The ALSPAC study could not have taken place without the financial support of the Wellcome Trust, MRC, the Department of the Environment, Department of Health, MAFF, British Gas, and other companies. This analysis has been supported by the Wellcome Trust. The ALSPAC study is part of the WHO initiated European Longitudinal Study of Pregnancy and Childhood.


    References
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 Abstract
 Materials and methods
 Results
 Discussion
 References
 
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