You are here

Article Text

Article menu

Download PDFPDF

Research report
The effect of neighbourhood income and deprivation on pregnancy outcomes in Amsterdam, The Netherlands
  1. C Agyemang1,
  2. T G M Vrijkotte1,
  3. M Droomers2,
  4. M F van der Wal3,
  5. G J Bonsel4,
  6. K Stronks1
  1. 1
    Department of Social Medicine, Academic Medical Centre, University of Amsterdam, The Netherlands
  2. 2
    Centre for Prevention and Health Services Research; National Institute for Public Health and the Environment, Bilthoven, The Netherlands
  3. 3
    Municipal Health Service, Department of Epidemiology, Documentation and Health Promotion, Amsterdam, The Netherlands
  4. 4
    Institute of Health Policy and Management, Erasmus MC Rotterdam, Rotterdam, The Netherlands
  1. Correspondence to Dr C Agyemang, Dept. of Social Medicine, Academic Medical Centre, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands; c.o.agyemang{at}amc.uva.nl

Abstract

Background: Studies suggest that the neighbourhoods in which people live influence their health. The main objective of this study was to investigate the associations of neighbourhood-level income and unemployment/social security benefit on pregnancy outcomes: preterm delivery, small for gestational age (SGA), pregnancy-induced hypertension (PIH) and miscarriage/perinatal death in Amsterdam.

Methods: A random sample of 7883 from 82 neighbourhoods in Amsterdam. Individual-level data from the Amsterdam Born Children and their Development (ABCD) study were linked to data on neighbourhood-level factors. Multilevel logistic regression was used to estimate odds ratios and neighbourhood-level variance.

Results: After adjustment for individual-level factors, women living in low-income neighbourhoods (third, second and first quartiles) were more likely than women living in high-income neighbourhoods (fourth quartile) to have SGA births: OR 1.32 (95% CI 1.04 to 1.68), 1.42 (1.11 to 1.82) and 1.62 (1.25 to 2.08) respectively. Women living in the quartile of neighbourhoods with the highest unemployment/social security benefit were more likely than those living in the quartile with the lowest unemployment/social security benefit to have SGA births 1.36 (1.08 to 1.72). The neighbourhood-level variance was significant only for SGA births. No significant associations were found between neighbourhood-level factors and other pregnancy outcomes.

Conclusion: The findings suggest that neighbourhood income and deprivation are related to SGA births. More research is needed to explore possible mechanisms underlying poor neighbourhood environment and pregnancy outcomes, in particular through stress mechanisms. Such information might be necessary to help improve maternal and fetal health.

https://doi.org/10.1136/jech.2008.080408

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Growing attention is being paid to the impact of residential neighbourhood environment on health outcomes. A large body of literature,123456 suggests that the neighbourhood in which people live influences their health, although a few studies failed to confirm this.789 Neighbourhood socioeconomic status (SES) and deprivation, for example, have been shown to be strongly related to several poor health outcomes.1 It has been proposed that health inequalities are the result of different accumulation of exposures and experiences that have their roots in the material world.101112 The effects of socioeconomic inequalities on health are the consequence of a combination of negative exposures and a lack of individual economic resources associated with a systematic low investment in a whole series of human, physical, health and social infrastructure.10 The unequal distribution of income is the consequence of historical, political, cultural and economic processes. These processes influence the availability of private resources to individuals and determine the nature of public infrastructure for health care services, food availability, education, transport, control of the environment, quality of housing and rules and regulations in the workplace.

    The neighbourhood environmental effects on health could have important policy implications, given the possibility of designing interventions that could potentially affect the health of entire neighbourhoods.13 Consequently, the interest in neighbourhood-level SES and deprivation on pregnancy and birth outcomes is increasing.14151617181920212223 A historical analysis of socioeconomic inequalities in infant and perinatal mortality from 1954 to 1990 in Amsterdam, for example, shows that absolute differences in infant mortality decreased, but relative differences increased during the study period with deprived areas having relatively high rates compared to non-deprived areas.16 However, information on the effect of neighbourhood-level SES and deprivation on some of the important pregnancy outcomes, such as pregnancy-induced hypertension (PIH) is still lacking. In addition, studies of neighbourhood-level SES on pregnancy outcomes have shown inconsistent results.1718 For example, Luo et al.17 found a strong relationship between neighbourhood-level SES (as measured by neighbourhood median income) and preterm birth in Canada. Kaufman et al.,18 however, found no relationship between neighbourhood income and preterm birth in white Americans in the USA. The effect of neighbourhood-level income on pregnancy outcomes has also been shown to vary between different settings.14 Furthermore, many studies did not have information on important individual-level factors that have been shown to influence pregnancy and birth outcomes such as ethnicity, maternal SES, smoking and obesity.24

    These inconsistent results and the lack of data on pertinent pregnancy outcomes such as PIH clearly indicate the need for more studies on this topic especially in Europe where information is very limited.

    The main objective of this present study was, therefore, to assess the effect of neighbourhood income and unemployment/social security benefit (deprivation) on pregnancy outcomes (preterm delivery, small for gestational age (SGA), PIH and miscarriage/perinatal death) in Amsterdam, The Netherlands. It was hypothesised that low neighbourhood income and deprivation would be associated with poor pregnancy outcomes after adjustment for individual-level characteristics.

    Methods

    The data for this study came from two different sources. The individual-level data were obtained from the Amsterdam Born Children and their Development (ABCD) study, and the neighbourhood-level data were from Statistics Netherlands.

    Data collection at the individual level

    The ABCD study was a community cohort investigation of pregnant women residing in Amsterdam, The Netherlands. The ABCD study (see www.abcd-study.nl) investigated differences in pregnancy outcomes with a focus on maternal lifestyle.2526

    Between January 2003 and March 2004, all pregnant women in Amsterdam were invited to participate at their first antenatal visit (median: 13 weeks; interquartile range: 3 weeks) with their obstetric caregiver. In addition to the routine prenatal care provided, a modular pregnancy questionnaire was distributed via mail 2 weeks later, to be returned in a prepaid envelope. This validated questionnaire was administered in four languages via a translator’s service, and included information on women’s sociodemographic characteristics, lifestyle and obstetric history. A reminder was sent 2 weeks later to women who had not returned the questionnaire. In total, 12 373 women were invited to participate, and 8266 women returned the questionnaire (response rate: 67%). For those women who gave permission for follow-up, additional data were obtained from the National Perinatal Register. Data on gestational age (based on ultrasound or, if unavailable, onset of most recent menstrual period), and birth weight were obtained from the Youth Health Care Registration of Amsterdam’s Municipal Health Service. Multiple births (n = 131) were excluded from the analysis. The study protocol was approved by the medical ethical committees of all Amsterdam hospitals and the Municipal Privacy Protection Committee of Amsterdam. All participating women gave informed written consent.

    Individual level variables

    Outcome variables

    Preterm births

    Preterm birth was defined as gestational age of less than 37 weeks.

    Small for gestational age (SGA)

    Small for gestational age was defined as a birth weight below the 10th percentile for gestational age on the basis of gender and parity-specific standards.27

    Pregnancy-induced hypertension (PIH)

    Pregnancy-induced hypertension was based on all women who answered yes to the question “Did you have hypertension or use blood pressure medication during your pregnancy?” or who had, according to the national obstetric register, a high diastolic blood (⩾90 mmHg) pressure during pregnancy (filled out by the health care professionals), or a diagnostic code for eclampsia, pre-eclampsia or PIH (optional fields). Women with a previous hypertension history before pregnancy or before 20 weeks gestational age (ie, chronic hypertension) were excluded from the analyses.

    Miscarriage/fetal and neonatal death (miscarriage/perinatal death)

    Miscarriage/perinatal death was determined from four overlapping sources: (1) the National Midwifery Registry, (2) the National Obstetric Registry, (3) the National Neonatal Registry and (4) self-reporting. Miscarriage was defined as death of the fetus occurring before 22 weeks of gestation. The miscarriage group excludes all those with induced abortion. Fetal death was defined as birth of a fetus weighing at least 500 g (or, where birth weight was unavailable, of at least 22 weeks gestation), which showed no signs of life, and neonatal death was defined as death of infants under 7 days according to existing standards.

    Maternal explanatory variables were derived from women’s questionnaire responses: age, parity, ethnicity, educational level (measured as years of education completed after primary school), smoking during pregnancy (yes/no) and pre-pregnancy body mass index (BMI). The ABCD study has no information on maternal income. Hence, maternal education has been used as a proxy for individual-level socioeconomic status. The ethnic groups were classified according to country of birth and/or country of birth of the parents in accordance with the definition of Statistics Netherlands.28

    Neighbourhood-level variable

    The neighbourhood income data were obtained “from the basic statistics for districts and neighbourhoods” registered by Statistics Netherlands. The neighbourhood income was based on the percentage of median income of people aged between 15 and 64 years in 2003 for each Amsterdam neighbourhood. The neighbourhood unemployment/social security benefit was based on the percentage of people aged between 15 and 64 years who were unemployed or received social security benefit for each Amsterdam neighbourhood. Nine neighbourhoods had small sample sizes (<10 subjects/neighbourhood) and were therefore excluded from the analyses. Data were analysed for 7883 women from 82 neighbourhoods. The average number of participants per neighbourhood was 96, ranging from 12 to 386. In The Netherlands, neighbourhoods are areas with a similar type of buildings, often delineated by natural boundaries. As a result of these natural boundaries, they are a socioculturally homogeneous group.29

    Data analysis

    Individual-level data were linked to neighbourhood-level data via participants’ postcodes, creating a multilevel design for data analysis. The data were analysed using multilevel logistic regression. First, models were adjusted for age and parity (ie physiological characteristics), and then sociodemographic and lifestyle factors (education, ethnicity, smoking and body mass index) were added to determine independent associations between neighbourhood-level factors and pregnancy outcomes. Maternal socioeconomic status, ethnicity, smoking and obesity have all been shown to influence pregnancy and birth outcomes.2425263031

    In addition, the intraclass correlation (ICC) was calculated to estimate the proportion of total variation in pregnancy outcomes that occurred at the neighbourhood level, using the latent variable method.32 Furthermore, the median odds ratio (MOR) was calculated, which has a consistent and intuitive interpretation.3334 Median odds ratio quantifies cluster variance in terms of odds ratios. It is therefore comparable to the fixed effects odds ratio, which is the most widely used measure of effect for dichotomous outcomes. Statistical analyses were performed using Stata version 9.0 (Stata Corp., College Station, Texas, USA).

    Results

    Table 1 shows the characteristics of the study population. Mothers living in low-income or deprived neighbourhoods were younger, less educated, and were more likely to smoke, and to be obese than their counterparts living in high-income neighbourhoods. Ethnic minority mothers were more likely than Dutch mothers to live in low-income or deprived neighbourhoods.

    View this table:
    Table 1

    Maternal characteristics by neighbourhood income and unemployment/social security benefit quartiles in Amsterdam

    Table 2 shows the distribution of the adverse pregnancy outcomes by neighbourhood factors whilst table 3 shows the associations between neighbourhood factors and pregnancy outcomes. Pregnant women living in low-income neighbourhoods were significantly more likely than those living in high-income neighbourhoods to have preterm births, SGA births and miscarriage/perinatal deaths. After further adjustment for educational level, ethnicity, smoking and obesity, however, only SGA births differences persisted. Women living in the quartile of neighbourhoods with the highest percentage of people on unemployment/social security benefit were significantly more likely than those living in the quartile with the lowest percentage on unemployment/social security benefit to have SGA births. The difference persisted after further adjustment for educational level, ethnicity, smoking and obesity: OR 1.36 (95% CI 108 to 1.72). Women living in the quartile of neighbourhoods with the highest unemployment/social security benefit were also significantly more likely to have a miscarriage/perinatal death than those living in the quartile with the lowest unemployment/social security benefit. The differences were no longer statistically significant after further adjustment for education, ethnicity, smoking and obesity. There were no statistically significant associations between neighbourhood income, unemployment/social security benefit and other adverse birth outcomes.

    View this table:
    Table 2

    Adverse birth outcomes by neighbourhood income and unemployment/social security benefit quartiles in Amsterdam

    View this table:
    Table 3

    Odds ratios (95% CI) of adverse birth outcomes and neighbourhood income and unemployment/social security benefit quartiles

    Only the neighbourhood variation in SGA births (ie the random intercept in the empty model) was statistically significant (neighbourhood variance (standard error) was 0.092 (0.028), ICC was 0.022, and median OR was 1.34 (95% CI 1.20 to 1.44). The variance between neighbourhoods attenuated but still remained significant after adjustment for all the individual level factors (neighbourhood variance was 0.035 (0.017), ICC was 0.011 and median odds ratio was 1.20 (95% CI 1.04 to 1.28). Further adjustment for neighbourhood-level factors removed the significant variation between neighbourhoods and reduced neighbourhood variance to 0.011 (0.015).

    Discussion

    Key findings

    The main objective of this study was to assess the effect of neighbourhood income and deprivation on pregnancy outcomes in Amsterdam, The Netherlands. The present study findings indicate that neighbourhood income and deprivation are related to SGA births. Neighbourhood variation in SGA births were also observed, and neighbourhood-level factors contributed to the variation between neighbourhoods. There were no significant associations between neighbourhood income, deprivation and other pregnancy outcomes.

    Strengths and limitations

    One of the main strengths of the present study is that it included several individual level factors pertinent to birth outcomes as compared to previous studies.1417182123 The current study is also one of the few studies to assess the effect of neighbourhood income and deprivation on several pregnancy outcomes. The neighbourhoods considered in the present study were socioculturally homogeneous communities. It has been emphasised that contextual or area-bound factors such as low income may have a greater impact on health if a neighbourhood relates to a socioculturally homogeneous community.29 The present study also has limitations. Due to small numbers, miscarriage, fetal and neonatal deaths were combined. Future studies should assess the possible differences in the effect of neighbourhood income and deprivation on each of these outcomes. In addition, the inclusion of the pregnant women occurred during their first prenatal visit, which was on average at 12th (inter quartile range 9–14) week gestational age. This indicates that women were missed who had their miscarriage before the first visit.

    Discussion of the key findings

    The present finding of associations between neighbourhood income, deprivation and SGA births is consistent with a previous study,14 and supports the importance of the effect of neighbourhood factors on pregnancy outcomes. Socioeconomic factors can have profound effects on individuals’ health as well as the health of populations, and the perinatal domain is particularly prone to such influences.30 The principal pathways by which SES affects perinatal health include those that operate through lifestyle and behavioural factors such as smoking and obesity.30

    Small for gestational age is often used as a proxy for intra-uterine growth restriction (IUGR).2431 Intra-uterine growth restriction is believed to be related to poor fetal nutrition and/or reduced fetal oxygenation.35 The mechanism underlying the effect of poor neighbourhoods on SGA is unclear. Neighbourhood-level determinants, such as low income or deprivation, are, however, considered as antecedent to individual-level exposures and behaviours,24 which may increase the risk of poor pregnancy outcomes. For example, it has been shown that poor maternal nutrition especially around the time of conception is associated with an increased risk of SGA births.36 Pregnant women’s dietary choices may be influenced by the availability of food stores and food service places in their neighbourhoods. Neighbourhoods that share socioeconomic characteristics also tend to share physical (eg pollution and availability of nutritious food), social (eg crime and behavioural norms) and service (eg transportation and health care) environments and these environments could influence health above and beyond the health effects of the socioeconomic characteristics of residents living within them.3738 It is therefore possible that pregnant women living in poor or deprived neighbourhoods may have limited access to essential services such as access to healthy food, which may affect fetal nutrition and/or oxygenation, and subsequently increase the risk of SGA. Studies from the USA and the UK, for example, suggest that because of unequal geographical distribution, people with low income have fewer choices and less access to healthy food than their high-income counterparts.3940

    The associations between neighbourhood income, deprivation and SGA remained after further adjustments for individual-level factors, which suggest that other factors may also play a role. For example, both neighbourhood-level and individual-level psychosocial factors have been shown to be related to an increased risk of SGA births.4142 Pregnant women with low SES experience more stressful life events during their pregnancy than women with high SES.43 It has been shown that chronic stressors are embedded within and accrued from the environment of women with low SES.44 More studies are needed to explore the role of other neighbourhood factors, such as psychosocial stressors,4546 on pregnancy outcomes.

    The neighbourhood median income differences in preterm births and miscarriage/perinatal death disappeared after adjustments for individual-level factors. This finding on miscarriage/perinatal death is consistent with previous studies.141617 However, the lack of relationship between neighbourhood income, deprivation and preterm births after adjustments for individual-level factors contrasts with other studies.1417 The relationship between neighbourhood income, deprivation and preterm births remains inconsistent.1417182123 Canadian studies,1417 for example, found a strong relationship between neighbourhood income and preterm births after further adjustment for individual-level factors. Some USA studies,1821 however, found neighbourhood income to be associated with preterm births but only in African–Americans. One recent study from the USA,21 by contrast, found weaker associations among African–Americans compared with white Americans. The explanations for these inconsistent results are unclear. However, differences in study design, neighbourhood context, and the different definitions of neighbourhood deprivation may contribute to these observed differences.

    As far as the authors are aware, this is the first study to assess the effect of neighbourhood-level deprivation on PIH. No association was found between neighbourhood deprivation and PIH. However, there was a significant age- and parity-adjusted association between neighbourhood median income (ie first quartile and fourth quartile) and chronic hypertension 1.41 (95% CI 1.00 to 1.99). This suggests that women in deprived neighbourhoods, especially ethnic minority women, might still be at an increased risk of hypertension-related problems in pregnancy, despite the lack of differences in PIH. Hypertension is highly prevalent among some ethnic minority women in The Netherlands.4748 In the SUNSET study, for example, African–Surinamese women were nearly four times and Hindustani–Surinamese women were nearly three times more likely than Dutch women to be hypertensive.47

    The present study findings may have public health and clinical implications. Small for gestational infants are more likely to have problems with perinatal asphyxia, and are at increased risk of long-term growth deficits and early infant mortality.49 They also have an increased long-term risk of developing metabolic and cardiovascular diseases (Barker hypothesis).50 Prevention of SGA is therefore of clinical and public health importance. The present findings clearly indicate the need for further studies to unravel the possible mechanism underlying the effect of poor neighbourhood environment on pregnancy outcomes.

    In conclusion, the present findings suggest that neighbourhood income and deprivation are related to SGA births and that more clinical attention may be needed during pregnancy for women from low income or deprived neighbourhoods. More work is needed to explore possible mechanisms underlying poor neighbourhood environment and pregnancy outcomes. Such information might be necessary to help improve maternal and fetal health.

    What is already known on this subject

    • Neighbourhood in which people live influences their health.

    • Information on the effect of neighbourhood-level SES and deprivation on pregnancy outcomes is limited and inconsistent.

    What this study adds

    Neighbourhood-level income and deprivation are associated with SGA births but not preterm birth, child loss and PIH in Amsterdam, The Netherlands.

    Acknowledgments

    We thank Dr A. de Jonge (TNO, Leiden) and Mrs Margot Witvliet for providing useful comments on an earlier draft.

    REFERENCES

    1. ↵
      1. Pickett KE,
      2. Pearl M
      . Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review. J Epidemiol Community Health 2001;55:111–22.
      OpenUrlAbstract/FREE Full Text
    2. ↵
      1. van Kamp I,
      2. van Loon J,
      3. Droomers M,
      4. et al
      . Residential environment and health: a review of methodological and conceptual issues. Rev Environ Health 2004;19:381–401.
      OpenUrlPubMed
    3. ↵
      1. Yen IH,
      2. Syme SL
      . The social environment and health: a discussion of the epidemiologic literature. Annu Rev Public Health 1999;20:287–308.
      OpenUrlCrossRefPubMedWeb of Science
    4. ↵
      1. Sampson RJ,
      2. Morenoff J,
      3. Gannon-Rowley T
      . Assessing ‘neighborhood effects’: social processes and new directions in research. Annual Review of Sociology 2002;28:443–78.
      OpenUrlCrossRefWeb of Science
    5. ↵
      1. Ellen IG,
      2. Tod M,
      3. Keri-Nicole D
      . Neighborhood effects on health: Exploring the links and assessing the evidence. J Urban Aff 2001;23:391–408.
      OpenUrlCrossRef
    6. ↵
      1. Culhane JF,
      2. Elo IT
      . Neighborhood context and reproductive health. Am J Obstet Gynecol 2005;192(5 Suppl):S22–S29.
      OpenUrlCrossRefPubMedWeb of Science
    7. ↵
      1. Jessop EG
      . Individual morbidity and neighbourhood deprivation in a non-metropolitan area. J Epidemiol Community Health 1992;46:543–6.
      OpenUrlAbstract/FREE Full Text
    8. ↵
      1. Smith GD,
      2. Hart C,
      3. Blane D,
      4. et al
      . Lifetime socioeconomic position and mortality: prospective observational study. BMJ 1997;314:547–52.
      OpenUrlAbstract/FREE Full Text
    9. ↵
      1. Humphreys K,
      2. Carr-Hill R
      . Area variations in health outcomes: artefact or ecology. Intern J Epidemiolog 1991;20:251–8.
      OpenUrlAbstract/FREE Full Text
    10. ↵
      1. Lynch J,
      2. Davey Smith G,
      3. Kaplan G,
      4. et al
      . Income inequality and mortality: Importance to health of individual income, psychosocial environment or material conditions. BMJ 2000;320:1200–4.
      OpenUrlFREE Full Text
    11. ↵
      1. Lynch J,
      2. Davey Smith G,
      3. Harper S,
      4. et al
      . Is Income Inequality a Determinant of Population Health? Part 1. A Systematic Review. Milbank Q 2004;82:5–99.
      OpenUrlCrossRefPubMedWeb of Science
    12. ↵
      1. Muntaner C,
      2. Lynch J,
      3. Hillemeier M,
      4. et al
      . Economic inequality, working-class power, social capital, and cause-specific mortality in wealthy countries. Int J Health Serv 2002;32:423–32.
      OpenUrlCrossRefPubMedWeb of Science
    13. ↵
      1. Cubbin C,
      2. Marchi K,
      3. Lin M,
      4. et al
      . Is neighborhood deprivation independently associated with maternal and infant health? Evidence from Florida and Washington. Matern Child Health J 2008;12:61–74.
      OpenUrlCrossRefPubMedWeb of Science
    14. ↵
      1. Zhong-Cheng L,
      2. Wilkins R,
      3. Kramer MS
      . Effect of neighborhood income and maternal education on birth outcomes: a population-based study. CMAJ 2006;174:1415–20.
      OpenUrlAbstract/FREE Full Text
    15. ↵
      1. Pickett KE,
      2. Collins J,
      3. Masi CM,
      4. et al
      . The effects of racial density and income incongruity on pregnancy outcomes. Soc Sci Med 2005;60:2229–38.
      OpenUrlPubMedWeb of Science
    16. ↵
      1. van de Mheen H,
      2. Reijneveld SA,
      3. Mackenbach JP
      . Socioeconomic inequalities in perinatal and infant mortality from 1854 to 1990 in Amsterdam, The Netherlands. Eur J Public Health 1996;6:166–74.
      OpenUrlAbstract/FREE Full Text
    17. ↵
      1. Luo ZC,
      2. Kierans WJ,
      3. Wilkins R,
      4. et al
      . Disparities in birth outcomes by neighborhood income: temporal trends in rural and urban areas, British Columbia. Epidemiology 2004;15:679–86.
      OpenUrlCrossRefPubMedWeb of Science
    18. ↵
      1. Kaufman JS,
      2. Dole N,
      3. Savitz DA,
      4. et al
      . Modeling community level effects on preterm birth. Ann Epidemiol 2003;13:377–84.
      OpenUrlCrossRefPubMedWeb of Science
    19. ↵
      1. Ahern J,
      2. Pickett KE,
      3. Selvin S,
      4. et al
      . Preterm birth among African American and white women: a multilevel analysis of socioeconomic characteristics and cigarette smoking. J Epidemiol Community Health 2003;57:606–11.
      OpenUrlAbstract/FREE Full Text
    20. ↵
      1. O’Campo P,
      2. Xue X,
      3. Wang MC,
      4. et al
      . Neighborhood risk factors for low birthweight in Baltimore: a multilevel analysis. Am J Public Health 1997;87:1113–18.
      OpenUrlCrossRefPubMedWeb of Science
    21. ↵
      1. Pickett KE,
      2. Ahern JE,
      3. Selvin S,
      4. et al
      . Neighborhood socioeconomic status, maternal race and preterm delivery: a case control study. Ann Epidemiol 2002;12:410–18.
      OpenUrlCrossRefPubMedWeb of Science
    22. ↵
      1. Rauh VA,
      2. Andrews HF,
      3. Garfinkel RS
      . The contribution of maternal age to racial disparities in birthweight: a multilevel perspective. Am J Public Health 2001;91:1815–24.
      OpenUrlPubMedWeb of Science
    23. ↵
      1. O’Campo P,
      2. Burke JG,
      3. Culhane J,
      4. et al
      . Neighborhood deprivation and preterm birth among non-Hispanic Black and White women in eight geographic areas in the United States. Am J Epidemiol 2008;167:155–63.
      OpenUrlAbstract/FREE Full Text
    24. ↵
      1. Kramer MS
      . Determinants of low birth weight: methodological assessment and meta-analysis. Bull World Health Organ 1987;65:663–737.
    25. ↵
      1. Alderliesten ME,
      2. Vrijkotte TG,
      3. van der Wal MF,
      4. et al
      . Late start of antenatal care among ethnic minorities in a large cohort of pregnant women. BJOG 2007;114:1232–9.
      OpenUrlCrossRefPubMedWeb of Science
    26. ↵
      1. Goedhart G,
      2. van Eijsden M,
      3. van der Wal MF,
      4. et al
      . Ethnic differences in preterm birth and its subtypes: the effect of a cumulative risk profile. BJOG 2008;115:710–19.
      OpenUrlCrossRefPubMedWeb of Science
    27. ↵
      The Netherlands Perinatal Registry. Perinatal care in The Netherlands 2001 (in Dutch: Perinatale zorg in Nederland 2001). Personal communication Prof.dr. G.J. Bonsel.
    28. ↵
      Central Bureau of Statistics. Standaarddefinitie van allochtonen. Index, No. 10, CBS, 2000:10–13.
    29. ↵
      1. Reijneveld SA,
      2. Verheij RA,
      3. Bakker DH
      . The impact of area deprivation on differences in health: Does the choice of the geographical classification matter? J Epidemiol Community Health 2000;54:306–13.
      OpenUrlAbstract/FREE Full Text
    30. ↵
      1. Joseph KS,
      2. Liston RM,
      3. Dodds L,
      4. et al
      . Socioeconomic status and perinatal outcomes in a setting with universal access to essential health care services. CMAJ 2007;177:583–90.
      OpenUrlAbstract/FREE Full Text
    31. ↵
      1. Kramer MS,
      2. Séguin L,
      3. Lydon J,
      4. et al
      . Socio-economic disparities in pregnancy outcome: why do the poor fare so poorly? Paediatr Perinat Epidemiol 2000;14:194–210.
      OpenUrlCrossRefPubMedWeb of Science
    32. ↵
      1. Snijders TAB,
      2. Bosker RJ
      . Multilevel analysis: an introduction to basic and advanced multilevel modeling. Thousand Oaks, CA: Sage, 1999.
    33. ↵
      1. Larsen K,
      2. Merlo J
      . Appropriate assessment of neighborhood effects on individual health—integrating random and fixed effects in multilevel logistic regression. Am J Epidemiol 2005;161:81–8.
      OpenUrlAbstract/FREE Full Text
    34. ↵
      1. Larsen K,
      2. Petersen JH,
      3. Budtz-Jorgensen E,
      4. et al
      . Interpreting parameters in the logistic regression model with random effects. Biometrics 2000;56:909–14.
      OpenUrlCrossRefPubMedWeb of Science
    35. ↵
      1. Ergaz Z,
      2. Avgil M,
      3. Ornoy A
      . Intrauterine growth restriction-etiology and consequences: what do we know about the human situation and experimental animal models? Reprod Toxicol 2005;20:301–22.
      OpenUrlCrossRefPubMedWeb of Science
    36. ↵
      1. Mitchell EA,
      2. Robinson E,
      3. Clark PM,
      4. et al
      . Maternal nutritional risk factors for small for gestational age babies in a developed country: a case-control study. Arch Dis Child Fetal Neonatal Ed 2004;89:431–5.
      OpenUrlCrossRef
    37. ↵
      1. Macintyre S,
      2. Ellaway A,
      3. Cummins S
      . Place effects on health: How can we conceptualise, operationalise and measure them? Soc Sci Med 2002;55:125–39.
      OpenUrlCrossRefPubMedWeb of Science
    38. ↵
      1. Jessop EG
      . Individual morbidity and neighbourhood deprivation in a non-metropolitan area. J Epidemiol Community Health 1992;46:543–6.
      OpenUrlAbstract/FREE Full Text
    39. ↵
      1. Ellaway A,
      2. Macintyre S
      . Shopping for food in socially contrasting localities. Br Food J 2000;102:52–9.
      OpenUrlCrossRef
    40. ↵
      1. Morland K,
      2. Wing S,
      3. Diez Roux A,
      4. et al
      . Neighborhood characteristics associated with the location of food stores and food service places. Am J Prev Med 2002;22:23–9.
      OpenUrlCrossRefPubMedWeb of Science
    41. ↵
      1. Masi CM,
      2. Hawkley LC,
      3. Piotrowski ZH,
      4. et al
      . Neighborhood economic disadvantage, violent crime, group density, and pregnancy outcomes in a diverse, urban population. Soc Sci Med 2007;65:2440–57.
      OpenUrlCrossRefPubMedWeb of Science
    42. ↵
      1. Dejin-Karlsson E,
      2. Hanson BS,
      3. O’stergren PO,
      4. et al
      . Association of a lack of psychosocial resources and the risk of giving birth to small for gestational age infants: a stress hypothesis. BJOG 2000;107:89–100.
      OpenUrlCrossRefPubMed
    43. ↵
      1. Rutter DR,
      2. Quine L
      . Inequalities in pregnancy outcome: a review of psychosocial and behavioural mediators. Soc Sci Med 1990;30:553–68.
    44. ↵
      1. Séguin L,
      2. Potvin L,
      3. Loiselle J,
      4. et al
      . Chronic stressors, social support, and depression during pregnancy. Obstet Gynecol 1995;85:583–9.
      OpenUrlCrossRefPubMedWeb of Science
    45. ↵
      1. Agyemang C,
      2. van Hooijdonk C,
      3. Wendel-Vos W,
      4. et al
      . Ethnic differences in the effect of environmental stressors on blood pressure and hypertension in The Netherlands. BMC Public Health 2007;7:118.
      OpenUrlCrossRefPubMed
    46. ↵
      1. Agyemang C,
      2. van Hooijdonk C,
      3. Wendel-Vos W,
      4. et al
      . The association of neighbourhood psychosocial stressors and self-rated health in Amsterdam, The Netherlands. J Epidemiol Community Health 2007;61:1042–9.
      OpenUrlAbstract/FREE Full Text
    47. ↵
      1. Agyemang C,
      2. Bindraban N,
      3. Mairuhu G,
      4. et al
      . Prevalence, awareness, treatment, and control of hypertension among Black Surinamese, South Asian Surinamese and White Dutch in Amsterdam, The Netherlands: the SUNSET study. J Hypertens 2005;23:1971–7.
      OpenUrlCrossRefPubMedWeb of Science
    48. ↵
      1. Agyemang C,
      2. van Valkengoed I,
      3. van den Born BJ,
      4. et al
      . Prevalence and determinants of prehypertension among African Surinamese, Hindustani Surinamese, and White Dutch in Amsterdam, The Netherlands: the SUNSET study. Eur J Cardiovasc Prev Rehabil 2007;14:775–81.
      OpenUrlAbstract/FREE Full Text
    49. ↵
      1. Yanney M,
      2. Marlow N
      . Paediatric consequences of fetal growth restriction. Semin Fetal Neonatal Med 2004;9:411–18.
      OpenUrlCrossRefPubMed
    50. ↵
      1. Osmond C,
      2. Barker DJ
      . Fetal, infant, and childhood growth are predictors of coronary heart disease, diabetes, and hypertension in adult men and women. Environ Health Perspect 2000;108(Suppl 3):P545–P553.
      OpenUrl

    Footnotes

    • Funding C. Agyemang was supported by a VENI fellowship (grant number 916.76.130) awarded by the Board of the Council for Earth and Life Sciences (ALW) of The Netherlands Organisation for Scientific Research (NWO).

    • Competing interests None.

    • Ethics approval The study protocol was approved by the medical ethical committees of all Amsterdam hospitals and the Municipal Privacy Protection Committee of Amsterdam.