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Journal of Public Health Advance Access published online on July 21, 2008
Journal of Public Health, doi:10.1093/pubmed/fdn057
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© The Author 2008, Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved

Why does birthweight vary among ethnic groups in the UK? Findings from the Millennium Cohort Study


Y. Kelly, Senior Lecturer in Epidemiology and Public Health1
L. Panico, Research Fellow1
M. Bartley, Professor of Medical Sociology1
M. Marmot, Professor of Epidemiology1
J. Nazroo, Professor of Sociology2
A. Sacker, Professor of Quantitative Social Science3

1 Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK
2 Department of Sociology, University of Manchester, Manchester M13 9PL, UK
3 Institute for Social and Economic Research (ISER), University of Essex, Colchester CO4 3SQ, UK


Address correspondence to Y. J. Kelly, E-mail: y.kelly{at}ucl.ac.uk

Background Birthweight varies according to ethnic group, but it is not clear why such differences exist. We examine the contribution of socioeconomic, maternal and behavioural factors to differences in mean birthweight and the prevalence of low birthweight across ethnic groups.

Methods Data from the nationally representative UK Millennium Cohort Study (n = 16 157) on White, Indian, Pakistani, Bangladeshi, Black Caribbean and Black African infants were analysed. Cohort members were born in 2000–02, and data on birthweight, maternal, infant, behavioural and socioeconomic factors were collected by home interviews.

Results Indian, Pakistani and Bangladeshi infants were 280–350 g lighter, and 2.5 times more likely to be low birthweight compared with White infants. Black Caribbean infants were 150 g and Black African infants 70 g lighter compared with White infants, and Black Caribbean and Black African infants were 60% more likely to be low birthweight compared with White infants. For Black Caribbean, Black African, Bangladeshi and Pakistani infants, socioeconomic factors were important in explaining birthweight differences and, for Indian and Bangladeshi infants, maternal and infant factors were important in explaining birthweight differences.

Conclusion Future policies aimed at reducing inequalities in birthweight must pay attention to the different socioeconomic and culturally-related profiles of ethnic minority groups in the UK.

Keywords: birthweight, epidemiology, ethnicity, inequality, socioeconomic


   Introduction
TOP
 Introduction
Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
In the UK and elsewhere, mean birthweight and the risk of low birthweight vary according to ethnic group.1–4 In UK babies born to South Asian and Black mothers, the observed average weight is up to 300 g less than those of White mothers, and the rates of low birthweight are up to two and a half times those for Whites.1,2,5–8 Previous work suggests that birthweight influences the risk of development of chronic disease in later life,9 and it may be that rapid post-natal growth has a role in later disease risk.10

Ethnic inequalities in health have been linked to socioeconomic disadvantage.11–13 However, studies have failed to establish socioeconomic and behavioural explanations for ethnic differences in birthweight,14–17 and this apparent lack of evidence has led some to suggest that lower birthweights in certain ethnic groups are in some way ‘normal’.

This paper adds to existing research by using a detailed ethnic group categorization, and by examining a range of socioeconomic, maternal and behavioural factors in explanatory models. The objective of this paper was to examine the contribution of socioeconomic, maternal and behavioural factors to differences in mean birthweight and the likelihood of low birthweight among ethnic groups.

The conceptual model
First, we consider the association of potential explanatory factors with ethnicity and birthweight. Maternal factors that affect birthweight include mother's height and weight, parity and complications during pregnancy. Behavioural factors that influence birthweight include cigarette smoking and alcohol consumption during pregnancy and receiving antenatal care. The effect of socioeconomic status is investigated using household income, housing tenure, occupational class, education, maternal employment status and lone parenthood. Of course, the categorization of variables in this way is partly arbitrary and boundaries between groups of variables are blurred. For example, cigarette smoking could be included as a behavioural or socioeconomic marker. Maternal height may be considered as a characteristic of the mother, a marker of socioeconomic status and cultural location over multiple generations, as well as historical and relative economic development of the country of origin for migrants.

Secondly, we assess the contributions of potential explanatory factors in explaining observed ethnic differences. Current attributes, such as height or socio-economic status, may also represent such attributes over historical time, and thus have different meanings in populations with different histories, such as ethnic minorities, and have different effects by ethnicity. For example, maternal stature is expected to be protective for Black Caribbean and Black African groups, and a risk factor for Indian, Pakistani and Bangladeshi groups. Broadly, given the favourable behavioural profiles of most ethnic minority groups, it is expected that the relative lack of cigarette smoking will be protective across ethnic minority groups. As the Indian group has a more advantaged socioeconomic profile, we expect that socioeconomic circumstances will be protective for the Indian group; conversely, socioeconomic markers will be risk factors for Pakistani, Bangladeshi, Black Caribbean and Black African groups.


   Methods
TOP
 Introduction
 Methods
Results
 Discussion
 Funding
 Acknowledgements
 References
 
The Millennium Cohort Study
The survey design, recruitment process and fieldwork have been described in detail elsewhere.18 Briefly, the Millennium Cohort Study (MCS) is a nationally representative longitudinal study of 18 819 infants who were born in the UK. A random sample of all infants who were born in England and Wales between September 2000 and August 2001 and in Scotland and Northern Ireland between November 2000 and January 2002 and were alive and living in the United Kingdom at 9 months of age were drawn from Child Benefit registers. Child Benefit claims in the UK cover virtually all children except those who are ineligible as a result of recent or temporary immigrant status. The sample was stratified by electoral ward, with over sampling of ethnic minority and disadvantaged areas. The first sweep interview response rate was 85%, and involved home visits by interviewers when the cohort member was aged, on average, 9 months. During the interview, questions were asked about the pregnancy, the cohort member's birth, socioeconomic circumstances, parental health related behaviours and household composition. The sample on which this analysis is based includes all singleton infants whose mothers participated in the first survey of the MCS (n = 18 268). Of these, 499 cohort members had ‘other’ ethnicities and were not included in this study for the analysis, leaving 17 769 in the sample. Missing data on the questionnaire items of interest reduced the sample to 16 157 (91%).

Ethical approval for the MCS was gained from the relevant Ethics Committees, and parents gave informed consent before interviews took place.

Ethnicity
The cohort member's ethnicity was given by the main carer, usually the mother, during the first sweep interview, using the 2001 UK Census categories. The groups used for analysis are: White, Indian, Pakistani, Bangladeshi, Black Caribbean and Black African. To prevent problems with small cell sizes, cohort members of mixed ethnicity were categorized according to the mother's ethnicity or, if the mother's ethnicity was White, the father's non-White ethnicity was used. Initial analysis indicated that these aggregations have not affected the conclusions drawn in this paper.

These ethnic minority groups have on the whole very different migration histories. The Black Caribbean and Indian groups mainly migrated to the UK in the 1950s and 1960s, the Pakistanis in the 1960s and 1970s, the Bangladeshis in the 1980s and the Black Africans in the 1990s. Furthermore, migrants to the UK originate from different countries with different political and economic histories and people who migrate may also differ in their economic backgrounds.

Birthweight
Data on birthweight were collected from the main carer and are used in this analysis as a continuous measure in kilograms and using the low birthweight cut-point of <2500 g, rather than an ethnic group specific cut-point.19 We did not use registration data as this was not available for the whole sample, and the average birthweight obtained from Birth Registration data has been shown not to be different from mother-reported birthweight in England and Wales.8 Gestational age was based on questions about when the infant was due to be born and date of birth. It is not clear whether the due date was based on ultrasonography or date of last menstrual period.

Explanatory factors
The explanatory effects of maternal and infant characteristics, behavioural and socioeconomic factors were assessed. Maternal and infant factors were infant gender, gestational age (whether or not the infant was born before 37 weeks gestation), complications during pregnancy (yes or no), mother's height and pre-pregnancy weight, mother's age at time of birth (<20, 20–24, 25–29, 30–34, ≥35 years), parity (one, two, three or more children). Behavioural factors were received ante-natal care (yes or no), cigarette smoking during pregnancy (yes or no) and alcohol consumption during pregnancy (yes or no). Socioeconomic markers were household income (less than £10 400–equivalent to the poverty line in 2001, £10 400–£20 800, £20 801–£31 200, £31 201–£52 000, more than £52 000, ‘refusal and don't know’), housing tenure (own/mortgage, renting, other arrangement), highest education level in the household (higher degree, first degree/diploma, A/AS levels, GCSE grades A–C, GCSE grades D–G, Overseas qualification, None), highest occupation in the household (National Statistics Socio-economic Classification (NS-SEC) categories: managerial and professional, intermediate, small employer and self-employed, supervisory and technical, semi-routine and routine, and unclassifiable20), employment status (working full time, working part time, not working), lone parenthood.

Statistical methods
Evidence of different associations by ethnicity was assessed from the heterogeneity across strata and the statistical significance of an interaction term obtained by running models with and without the interaction term and examining the statistical significance of the likelihood ratio test of the difference between the two models on the relevant chi-squared distribution.

Regression models investigate the relative importance of maternal and infant, behavioural and socioeconomic factors in the prediction of birthweight within ethnic groups. Model A adjusts for maternal and infant-related factors, model B adjusts for behavioural measures and model C adjusts for socioeconomic indicators.

Multivariate analyses were based on participants with complete data and allowed for the clustered stratified sample using the ‘survey commands’ in Stata, version 9.2.21


   Results
TOP
 Introduction
 Methods
 Results
Discussion
 Funding
 Acknowledgements
 References
 
Data are shown for White (n = 14 068), Indian (n = 433), Pakistani (n = 687), Bangladeshi (n = 215), Black Caribbean (n = 427) and Black African (n = 327) cohort members. Table 1 shows the distribution of maternal, infant, behavioural and socioeconomic factors by ethnic group.


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  		Table 1 Explanatory factors by cohort member's ethnicity

 
Table 2 shows mean birthweight (95% confidence interval) and percentage low birthweight (<2500 g) by ethnic group. Indian, Pakistani and Bangladeshi infants were on average between 280 and 350 g lighter, and about 2.5 times more likely to be low birthweight compared with White infants. Black Caribbean infants were on average 150 g and Black African infants 70 g lighter and were about 60% more likely to be low birthweight compared with White infants.


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  		Table 2 Birthweight (kg) and prevalence of low birthweight (<2500 g) by cohort member's ethnicity

 
Tests for interactions showed that there were statistically significant differences for maternal height (P = 0.034), highest academic qualification in the household (P = 0.022) and lone parenthood (P = 0.039) on birthweight across ethnic groups. Given the different associations of some aspects of socio-economic status and maternal height with birth weight by ethnicity, we present models stratified by ethnicity (Table 2).

Differences in mean birthweight on adjustment for explanatory factors in multivariate models reflect the skewed distribution of factors within ethnic groups compared with the average distribution. On adjustment for maternal and infant factors (model A), mean birthweight tended to decrease for White, Black Caribbean and Black African groups, whereas it increased for Indian and Bangladeshi groups reflecting their relative disadvantage. On adjustment for behavioural factors (model B), birthweight increased for the Pakistani group, reflecting differences in antenatal care. Adjustment for socioeconomic factors (model C) tended to increase birthweight for Bangladeshi, Pakistani, Black Caribbean and Black African groups, thus reflecting their disadvantage.


   Discussion
TOP
 Introduction
 Methods
 Results
 Discussion
Funding
 Acknowledgements
 References
 
Main finding of this study
The results of this large nationally representative UK study suggest that socioeconomic factors are important in explaining birthweight differences in Black Caribbean, Black African, Bangladeshi and Pakistani infants. Maternal and infant characteristics are important in explaining birthweight differences in Indian and Bangladeshi groups.

What is already known on this topic?
There are ethnic differences in average birthweight and risk of low birthweight in the UK1,2,5–7 and elsewhere,3,4 but these differences are largely unexplained.14–17

What this study adds
Our findings contrast with those of previous studies that reported that only about 10% of ethnic differences in birthweight were explained by socioeconomic factors,14–17 leading some to suggest that ethnic differences in birthweight are immutable biological phenomena. However, these assertions are not convincing: first, ethnicity is a social, not a biological construct;22 secondly, socioeconomic and behavioural variables used in models lack precision as they are surrogates for a myriad of ill-defined socio-environmental factors, and this is particularly problematic when considering ethnic minority groups and, therefore, in reality, their importance is underestimated.23,24 Large unexplained differences remained in our models, because of the only partial capture of ethnic differences in socioeconomic profiles11 with the measures available in the data. Thirdly, there is more genetic variation within than between ethnic groups25 and fourthly, genetic factors that influence birthweight have not been well characterized, nor have their frequencies across ethnic groups been established. Therefore, the default position of a genetic explanation over that of environmental effects is not warranted. We show that consideration of a wider range of socioeconomic variables (income, occupation, employment, education, lone parenthood and housing tenure) than the more limited range (income and education) used in previous studies14–17 can explain substantial proportions of ethnic differences in birthweight.

Another consideration is the use of aggregated ethnic groups, as previous studies investigating the potential roles of environmental factors on birthweight have tended to use broad ethnic group categories.5–7 Such aggregations often serve to obscure important differences in socioeconomic and risk profiles, as well as the diverse migratory histories of ethnic minority groups. In our explanatory models, we used ethnic categories that split ‘South Asian’ and ‘Black’ groups and so were able to reveal important differences in socioeconomic profiles and the contributions of these factors to differences in birthweight across more distinct ethnic groups. We were able to test the effects of a range of explanatory factors, and in the modelling did this in separate batteries so were able to show the sometimes opposing effects of protective and risk factors, for example, behavioural (protective) and socioeconomic variables (risk) for the Bangladeshi group.

The categorization of explanatory factors into maternal, behavioural and socioeconomic markers is somewhat arbitrary with clear overlaps between groups of variables. Maternal height reflecting contemporary and historic socioeconomic profiles is an important determinant of infant birthweight, and along with other socioeconomic factors and markers of cultural location varies widely across ethnic groups. Formal tests for statistical interactions showed that maternal height, lone parenthood and education have different effects on birthweight across ethnic groups. Mothers from Indian, Pakistani and Bangladeshi groups were on average up to 8 cm shorter than White mothers, and it may take several generations for individuals within ethnic groups to reach their height potential.26 However, it may be that increases in maternal height do not happen in the first couple of migrant generations due to the accumulative effects of disadvantage, including racism, discrimination and poverty that are disproportionately experienced by migrants.11,13,27 There may also be ethnic differences in access to antenatal care reflected in this sample by lower reported rates of the receipt of antenatal care, and perhaps paradoxically lower reported rates of complications during pregnancy among certain ethnic groups.

There are differences in the degree of historic economic development in countries of origin,28 as well as different migratory histories for the ethnic minority groups studied in this paper. Migrant generations are heterogeneous in their socioeconomic profiles, and this heterogeneity will be different for each ethnic group and there are likely to be cohort effects within and between ethnic groups,29 for example, migration of advantaged individuals of some groups versus migration of relatively disadvantaged individuals of other ethnic groups, and this is further influenced by immigration policies of host countries. We were unable to test hypotheses about the effects of migrant generation on birthweight due to small cell sizes, for example, for second or subsequent generation Bangladeshi or first generation Black Caribbean cohort members.

Limitations of this study
Limitations of this paper include that MCS is a sample of 9-month-old survivors, and it is important to point out that infants who died in the first 9 months of life were not included in the sample, and that infants who die are disproportionately of low birthweight and from ethnic minority groups.2,30 Because the data were collected when infants were 9-months old, reports of birthweight could potentially be affected by recall bias, however, maternal recall of birthweight has been shown to be reliable.31 It was not possible to test directly hypotheses around the links between mothers' experience of racism/discrimination and birthweight27,32,33 as the data were not collected as part of the survey.

Conclusions
We have shown that differences in birthweight can be explained by socioeconomic disadvantage in some ethnic groups, whereas maternal factors are important in other ethnic groups. Birthweight is an important marker of infant health and a large body of work suggests links between birthweight and the development of chronic disease. For future policies aimed at reducing inequalities in birthweight among ethnic minority groups to be effective, it is crucial that policy makers pay attention to the different socioeconomic and culturally related profiles of ethnic minority groups in the UK.


   Funding
TOP
 Introduction
 Methods
 Results
 Discussion
 Funding
Acknowledgements
 References
 
The MCS is funded by ESRC grants to Professor Heather Joshi (study director). This research was supported by funding from the Economic and Social Research Council, grant nos RES-000-23-1191 and RES-596-28-0001.


   Acknowledgements
TOP
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
References
 
We would like to thank the Millennium Cohort Study (MCS) families for their time and cooperation, as well as the MCS team at the Institute of Education. We would also like to thank the reviewers for their helpful comments on this paper.


   References
TOP
 Introduction
 Methods
 Results
 Discussion
 Funding
 Acknowledgements
 References
 

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