The Association of Ethnic Minority Density with Late Entry into Antenatal Care in the Netherlands
The Association of Ethnic Minority Density with Late Entry into Antenatal Care in the Netherlands
Anke G. Posthumus 0 1
Vera L. N. Schlmerich 0 1
Eric A. P. Steegers 0 1
Ichiro Kawachi 0 1
Semiha Denkta 0 1
0 1 Erasmus University Medical Centre, Department of Obstetrics and Gynecology, Division of Obstetrics and Prenatal Medicine, Rotterdam, the Netherlands, 2 VU University Amsterdam, Department of Organization Sciences, Amsterdam, the Netherlands, 3 Harvard School of Public Health, Department of Social and Behavioral Sciences , Boston, Massachusetts , United States of America
1 Academic Editor: Jennifer L. Baker, Institute of Preventive Medicine , DENMARK
In the Netherlands, non-Western ethnic minority women make their first antenatal visit later than native Dutch women. Timely entry into antenatal care is important as it provides the opportunity for prenatal screening and the detection of risk factors for adverse pregnancy outcomes. In this study we explored whether women's timely entry is influenced by their neighborhood. Moreover, we assessed whether ethnic minority density (the proportion of ethnic minorities in a neighborhood) influences Western and non-Western ethnic minority women's chances of timely entry into care differently. We hypothesized that ethnic minority density has a protective effect against non-Western women's late entry into care. Data on time of entry into care and other individual-level characteristics were obtained from the Netherlands Perinatal Registry (2000-2008; 97% of all pregnancies). We derived neighborhood-level data from three other national databases. We included 1,137,741 pregnancies of women who started care under supervision of a community midwife in 3422 neighborhoods. Multi-level logistic regression was used to assess the associations of individual and neighborhood-level determinants with entry into antenatal care before and after 14 weeks of gestation. We found that neighborhood characteristics influence timely entry above and beyond individual characteristics. Ethnic minority density was associated with a higher risk of late entry into antenatal care. However, our analysis showed that for non-Western women, living in high ethnic minority density areas is less detrimental to their risk of late entry than for Western women. This means that a higher proportion of ethnic minority residents has a protective effect on non-Western women's chances of timely entry into care. Our results suggest that strategies to improve timely entry into care could seek to create change at the neighborhood level in order to target individuals likely of entering care too late.
Data Availability Statement: Data were supplied by
the Netherlands Perinatal Registry and are available
to researchers who meet the criteria for access to
confidential data. To request access to the data,
readers may file a request using the English form on
the website (http://www.perinatreg.nl/uploads/76/189/
information can be found at: (http://www.perinatreg.nl/
home_english). The neighborhood level data on
feeling of safety, level of urbanity of the neighborhood
and home maintenance can be retrieved from (https://
easy.dans.knaw.nl/ui/datasets/id/easydataset:46099). Data on neighborhood level
socioeconomic status is available on (http://www.scp.
nl/Formulieren/Statusscores_opvragen) and data on
neighborhood level ethnic minority density can be
obtained from (http://statline.cbs.nl/StatWeb/?LA=en).
Competing Interests: The authors have declared
that no competing interests exist.
International studies have shown that pregnant women from ethnic minority backgrounds
tend to enter antenatal care at a significantly higher gestational age than ethnic majority
women.[1, 2] Research in the Netherlands points in the same direction. Women from all
nonWestern ethnic minorities except those with a Turkish or Hindustani-Surinamese background
make their first antenatal visit later than their Native Dutch counterparts. For example,
multiparous Creole-Surinamese women entered antenatal care after 14 weeks of gestation in 49% of
cases, against 11% for multiparous Dutch women.
Late entry into antenatal care is problematic, as it is associated with a higher risk for adverse
birth outcomes. These include abruptio placentae, chorioamnionitis, preterm birth, low birth
weight and fetal and neonatal death. Pregnant women in the Netherlands are advised to
enter antenatal care between 8 and 10 weeks of gestation. If they enter care too late, i.e. after 14
weeks of gestation, they miss the opportunity to receive prenatal screening for a range of
syndromes and congenital anomalies.
Commonly cited risk factors in international studies for late entry into care are single status,
young maternal age, poor language proficiency, maternal education of less than 5 years,
multiparity, unplanned and unwanted pregnancy, difficulty in arranging an appointment for
antenatal care, and being uninsured. In the Netherlands, research has shown that a lack of
knowledge of the Western healthcare system and poor language proficiency are important
reasons for inadequate antenatal care usage among non-Western ethnic minority women.
While studies conducted in the Netherlands on time of entry into antenatal care have focused
on these individual-level determinants, previous research in the United States and Canada
found associations between the area of residence and timing of entry into antenatal care.[3, 8
10] Neighborhood characteristics may affect health outcomes over and beyond the influence of
individual determinants. In other words, it is possible that certain neighborhoods are more or
less conducive to pregnant womens timing of entry into care.
In this study we explored the association between the proportion of non-Western ethnic
minorities in a neighborhood (i.e. ethnic minority density) and late entry into antenatal care in
the Netherlands. Moreover, we assessed whether ethnic minority density has a different
influence on Western and non-Western ethnic minority womens time of entry into care. We
hypothesized that ethnic minority density has a protective effect on non-Western womens timely
entry into care. This is based on the findings of a recent Dutch study by Schlmerich et al. who
found that while non-Western ethnic minorities generally have more adverse birth outcomes
compared to Western women, this trend is reversed in areas with high ethnic minority density.
 This means that while non-Western ethnicity is a risk factor at the individual-level,
residence in a neighborhood of high ethnic minority density is a protective factor for non-Western
womens birth outcomes. A similar protective effect of high ethnic minority density has been
found in studies on other health outcomes such as mental health and self-rated health and is
known as the ethnic density effect.
Studies have explored possible mechanisms underlying this ethnic density effect. One
explanation is that ethnic minorities residing in neighborhoods with high ethnic minority density
exhibit better health outcomes than ethnic majority groups because they experience higher
levels of bonding social capital. Bonding social capital refers to horizontal ties between members
of a network who see themselves as similar (homogenous networks, such as ethnic groups).[14,
15] Social capital has been conceptualized to influence health in several different
waysplausibly, these patterns also apply to bonding social capital: firstly, by promoting the exchange of
resources between residents, secondly by residents engaging in collective action to improve
access to local services and amenities, thirdly through social control over healthy behavior, and
lastly by more efficient diffusion of health related information.[16, 17]
While social capital is generally seen as having a positive influence on health (behaviors),
studies have found that bonding social capital may promote health but may also act as a source
of strain (and hence a detriment to health) in resource-poor settings. Scholars have
explained this phenomenon via two pathways. For one, bonding social capital may facilitate good
health through the exchange of resources between neighbors, but high reliance on mutual
exchange of reciprocity can result in excessive obligations placed upon residents to help each
other, which might be detrimental to health. In addition, while bonding social capital can assist
in the diffusion of information, the closed nature of social ties in such communities can also
restrict the flow of information from the outside (e.g. new information about changes in the
Dutch obstetric system) and maintain the circulation of unreliable information. This could
lead to less timely and adequate use of antenatal care. This means that neighborhood ethnic
minority density could either have a detrimental or beneficial effect on utilization of
As we assume that the neighborhood characteristic ethnic minority density is a proxy for
bonding social capital for non-Western residents, we also wanted to control for bonding social
capital of Western residents. Based on a recent study by Schlmerich et al, we use a
measurement of neighborhood social capital for this proxy. This measurement was derived from a
nationally representative data set, of which 82.7% of the respondents were Western.
Furthermore, we control for the following other neighborhood characteristics: feeling of safety,
socioeconomic status, level of urbanity and home maintenance. We included these variables because
prior studies in the Netherlands found an association between them and adverse birth
outcomes as well as general health.[11, 20, 21] The causal pathways between neighborhood
influences on (prenatal) health have not been completely unraveled and may be mediated by
adverse health behaviors such as late entry into care.
The objective of our study was to explore the independent association between
neighborhood ethnic minority density and late entry into antenatal care in the Netherlands. Moreover
we wanted to investigate whether neighborhood ethnic minority density affects Western and
non-Western women differently. We hypothesize that in line with the study by Schlmerich
et al., ethnic minority density will have a beneficial effect on time of entry into care for
nonWestern women when compared to Western women.
Data & Methods
To determine the association between ethnic minority density and the risk of late entry into
antenatal care in the Netherlands, we extracted neighborhood-level variables from three national
datasets, and linked this with a large dataset on individual pregnancy cases using the four-digit
zip code for neighborhoods.
Ethics and consent
The use of the anonymized patient data for this study was approved by the Netherlands
Perinatal Registry (project number 13.50) (additional information on the registry: www.perinatreg.nl/
home_english). Written consent from pregnant women was not needed as the registry protects
Timely entry into care was defined as entry at any time before 14 weeks of gestation; late entry
into care was defined as starting after 14 weeks of gestation (0 = not late, 1 = late). The cut-off
point of after 14 weeks of gestation was chosen because entry into care after 14 weeks of
gestation excludes a woman from prenatal screening on Down, Edwards and Patau syndrome in the
Netherlands and early detection and modification of other medical and non-medical risk
factors (such as illicit drug use) for adverse pregnancy outcome.[5, 22]
Individual level determinants
The data on entry into care were acquired from the Netherlands Perinatal Registry, which
contains 97% of Dutch pregnancies since the year 2000. Midwives, gynecologists and
neonatologists supply these data. Validation studies comparing the data from the Perinatal Registry and
Statistics Netherlands (national statistics bureau ) have shown that underreporting of
information by practitioners for the Perinatal Registry is negligible. However no specific
validation has taken place for the data on time of entry into care. We will further elaborate on this in
the discussion section.
For this study data we selected singleton pregnancies in the datasets from 2000 up to and
including 2008, because then both individual (i.e. pregnancy cases) and neighborhood level data
are derived from approximately the same time frame. The weeks of gestation at entry into care
were regrouped dichotomously into up to and including 14 weeks of gestation and after 14
weeks of gestation. Based on previous studies on the association of maternal covariates and
time of entry in to care, we included the following maternal covariates: maternal age, parity
In the Netherlands Perinatal Registry, ethnicity is divided into the following categories:
Western Dutch, Western Other, Mediterranean, Asian, African, South Asian, or other
nonWestern. Most non-Western immigrants in the Netherlands are from Turkey, Morocco,
Surinam and the Dutch Antilles. The recording of ethnicity in the Netherlands Perinatal Registry is
challenging for two reasons: 1) Maternal ethnicity is based on either self-declared ethnicity or
country of birth of the mother or her parents causing heterogeneity in registration; 2) the
categorization in the registry is not in line with international classifications, making comparisons
difficult. Therefore we dichotomized ethnicity into being from Western or non-Western
descent for the purpose of this study.
Neighborhood level determinants
Four-digit zip code areas were used to define neighborhoods. In 2006 the four-digit zip code
neighborhoods hadon average4080 residents. This makes the neighborhoods comparable
to Lower Layer Super Output Areas in the United Kingdom or census tracts in the United
States. Because neighborhoods in the Netherlands are sufficiently uniform in terms of their
socio-cultural characteristics, the four-digit zip code areas are adequate units for contextual
investigation.  Data on the neighborhood characteristics were obtained from Statistics
Netherlands, the Housing & Living Survey and the Netherlands Institute for Social Research.[23, 25,
26] These data were collected between 2005 and 2006.
As mentioned in the introduction, we included six neighborhood characteristics in our
analysis. A more detailed description of the characteristics is given in Table 1. All neighborhood
characteristics were recoded into z-scores. The characteristics were constructed using the same
aggregation techniques and data sets that Schlmerich et al. and Mohnen et al. applied in their
respective studies.[11, 20].
In this study only women who started care with a community midwife (the first tier) were
included. The Dutch obstetric care system consists of three tiers. The first tier consists of
autonomously working community midwives who take care of low risk women. When
complications (threaten to) occur, women are referred to the second tier of care, consisting of
Concentration of people from ethnic minorities
% of residents from non-Western ethnic
backgrounds per 4 digit zip code.
NonWestern ethnicity is defined as an individual or
at least one of the individuals parents
originating from Africa, Latin America, Asia
(except Indonesia and Japan) or Turkey.
Higher values indicate a higher concentration
of ethnic minorities
House and Living Survey
(items) Schlmerich et al.
House and Living Survey
Netherlands Institute for
House and Living Survey
House and Living Survey
Perception of safety in the neighborhood
Level of urbanity of Degree of urbanity of the municipality a
the neighborhood neighborhood is situated in
Five-point Likert scale (I totally agreeI totally
do not agree). Statement: I am scared of
being harassed or assaulted in this
neighborhood" Higher values indicate higher
levels of perceived safety
Average income, % of people with low
income, % of people with a low education and
% of unemployed people in a neighborhood.
Higher values indicate a higher socioeconomic
Number of addresses per square kilometer
(km2). 1) Rural, up to 499 addresses per km2;
2) Semi-rural, 500999 addresses per km2; 3)
Intermediate urban-rural, 10001499
addresses per km2; 4) Semi-urban, 1500
2499 addresses per km2; 5) Urban, more than
2499 addresses per km2. Higher values
indicate higher levels of urbanity.
Five-point Likert scale (I totally agreeI totally
do not agree). Question: Is your house in bad
condition? Higher values indicate better home
obstetricians in hospitals. The third tier of care consists of academic obstetric care. A quarter of
women enter obstetric care immediately in the second or third tier because of medical risks or
complications at the start of their pregnancy. We focused on the first tier population
because immediate entry into care in the second and third tier is above all determined by the
patients medical and obstetric history. Typically these women have previously received explicit
instructions about their antenatal care and the importance of timely entry. The women
included in this studythe first tier populationform the greatest portion of all pregnant women in
the Netherlands, namely 74%. These women are not just a low risk population because many
of them will be referred to the second tier of care, either during pregnancy, labor or the
postpartum period because of new risks or complications. This means that the women included
Fig 1. Exclusion of pregnancies. This Fig. shows the number of pregnancies excluded from the multilevel
logistic regression analysis.
in this study are still heterogeneous in terms of their risk profile, making comparison to other
The final analysis included 1,137,741 pregnancies and 3.422 neighborhoods. 35,326 (2.2%)
pregnancies were excluded because they were multiple pregnancies and 31,382 (1.9%)
pregnancies because individual or neighborhood characteristics were missing. Non-Western women
were slightly more likely to have missing values than non-Western women (2.8% vs 2.7%). 580
neighborhoods (14% of the total) were excluded because not all six neighborhood
characteristics were available (Fig 1). Most of the excluded neighborhoods had too few inhabitants to be
included in the study because they were rural or industrial areas.
Because of the hierarchical nature of the data, in which pregnant women (level 1) are nested
within neighborhoods (level 2) we performed multilevel logistic regression analyses. First, to
determine whether clustering was present we fitted a null-model which only contained a
random intercept.To establish the presence of clustering we calculated the intra-class correlation
(ICC), using the following formula in which sigma-squared is the intercept variance:
The ICC can range from 0 to 1. When it deviates from zero, it is appropriate to use
multilevel analyses. We found an ICC of 9.5% (results not shown) justifying this modelling
approach. The null-model was then expanded to include the individual level characteristics
age, parity and ethnicity as fixed effects to examine the influence of these on late entry into care
(model 1). Thereafter, we separately added the neighborhood contextual variables
neighborhood social capital and ethnic density (model 2 and 3) to investigate their specific influence,
before adding the other neighborhood variables (model 4). Consecutively an interaction term
was included for non-Western ethnicity neighborhood social capital (model 5) and
non-Western ethnicity ethnic minority density (model 6) to investigate the potential difference in
impact of these neighborhood characteristics on Western and non-Western women. Although we
were primarily interested in the interaction for non-Western ethnicity ethnic minority
density, we also tested the interaction with neighborhood social capital because Schlmerich et al.
found this interaction term to be significant in their analysis of birth outcomes in the
Netherlands. In the final model, all individual variables, neighborhood contextual variables and
interaction terms were included (model 7). All analyses were performed using SPSS version 20.
Between 2000 and 2008 the prevalence of entry into antenatal care after 14 weeks of gestation
was 17.9%. Table 2 shows the demographic characteristics of the study population and Table 3
shows the descriptive statistics of the neighborhoods. The correlations between the
neighborhood variables are presented in S1 Appendix. Most importantly, neighborhoods with higher
socio-economic status generally had lower ethnic minority density (corr. -0.56, p<0.001).
Table 4 / model 1 shows the odds ratios for the individual level characteristics in our logistic
regression analysis with late entry into care as the outcome variable. Women in the age
category of 30 to 35 years were most likely to enter antenatal care late. Non-Western ethnicity was
also strongly associated with higher risk for late entry into care. Contrarily, we found no
significant association of parity and time of entry into care. Moreover, the estimates for all of these
individual level variables showed minimal change across the models.
(Source: Perinatal Registration Netherlands, 20002008).
The figures presented in this table are crude proportions. For the purpose of our analyses we transformed
these into Z-scores. The median number of deliveries per neighborhood was 349 (range: 56602, 20th-80th
1 Low: <20%; medium: 2080%; high >80% inhabitants from non-Western origin.
2 Low: <3 on the 5-point Likert scale; medium: 3 on the 5-point Likert scale; high: >3 on the 5-point
3 Low: <20th percentile; medium: 20-80th percentile; high >80th percentile.
4 Statement: I am scared of being harassed or assaulted in this neighborhood. Low: on average
inhabitants agree; Medium: on average inhabitants dont agree and dont disagree; high: on average
inhabitants dont agree.
5 Low: <1000 addresses per km2; medium: 10001500 addresses per km2; high: >1500 addresses per
6 Question: Is your house in bad condition? Low: on average inhabitants agree; Medium: on average
inhabitants dont agree and dont disagree; high: on average inhabitants dont agree.
In model 2 of our analysis, neighborhood social capital was added (Table 4). The association
of this variable with late entry into care was not significant and remained so in all other models.
In contrast, ethnic minority density (model 3) was significantly associated with late entry into
care. This effect remained present after controlling for the other neighborhood contextual
variables in model 4. Though feeling of safety had no effect, higher levels of socioeconomic status,
home maintenance and level of urbanity were associated with lower risks of late entry into
care. The latter showed the most notable effect of these three. Model 5 and 6 include the
interaction terms for neighborhood social capital non-Western ethnicity and ethnic minority
density non-Western ethnicity, respectively. Though the interaction term for neighborhood social
capital non-Western showed a significant effect in model 5, this effect was no longer present in
the full model (model 7). However, the interaction term for ethnic minority density
non-Western ethnicity did remain significant in the full model. From this follows that ethnic minority
density is associated with 1.21 times the odds of late entry into care for Western women and
1.13 times the odds for non-Western women (calculated: exp (ln(1.21) + ln(0.93)). In the full
model, again neighborhood level of urbanity showed the most notable association (OR 0.87,
95%CI 0.850.90, p 0.01). Fig 2 illustrates the interaction effect between ethnic status
(nonWestern or Western) and the level of ethnic minority density in a neighborhood for risk of late
entry into care.
We found that neighborhood contexts influence timing of entry into antenatal care in the
Netherlands. In particular, higher rates of neighborhood ethnic minority density are associated
with a higher risk of late entry into antenatal care in the Netherlands. However, our analysis
(Odds ratios, 95% confidence intervals in parentheses).
Table 4. Multilevel logistic regression models of ethnic minority density and other individual and neighborhood characteristics on late entry into
care (after 14 weeks of gestation).
(Ref. = 2529 yrs)
Fig 2. The interaction between ethnic status and neighborhood ethnic minority density level for the odds of late entry. This Fig. demonstrates that
higher proportions of ethnic minority density in a neighborhood have a less detrimental effect on non-Western women than on Western women in terms of
their risk of late entry into care. Low ethnic density: 20 percent neighborhoods with the lowest proportions of non-Western inhabitants; high ethnic density: 20
percent neighborhoods with the highest proportions of non-Western inhabitants.
also shows that for non-Western women, living in high ethnic minority density areas is less
detrimental to their timing of antenatal care than for Western women.
Similar to our study, Heaman et al. reported higher risks of inadequate antenatal care use
for women living in neighborhoods with higher numbers of residents with an indigenous
minority background. It should be noted that inadequate use of care, the outcome measure of
their study, was broader than our outcome measure. Inadequacy of care entails late entry into
care and / or an insufficient number of antenatal appointments. There is no international
consensus on the appropriate number of antenatal visits. Nevertheless, inadequacy of antenatal
care is used in a number of studies because it is believed that it may be associated with adverse
pregnancy outcomes.[1, 3234] We were unable to analyze the number of antenatal visits each
woman had because this is not recorded in the Netherlands Perinatal Registry. However, a
systematic review by Feijen et al. showed that both late entry and an insufficient number of
antenatal appointments share the same set of risk factors. Therefore we believe that it is valid to
compare our results with other studies focusing on inadequate use of antenatal care.
In line with previous studies, being of non-Western ethnic descent was amongst the most
important predictors for late entry into care. This supports the commonly held view that
ethnicity (meaning a non-Western ethnic minority status) is a risk factor for health behavior,
including adequate use of care.[35, 36] However, our analysis shows that for non-Western
women, living in high ethnic minority density areas is less detrimental to their risk of late entry
into antenatal care than for Western women. This means that while ethnic minority status is
indeed not a protective factor in and of itself at the individual level, it seems to act as a
protective factor for time of entry into care at the neighborhood level in areas where ethnic minorities
are in the majority. Our results are in line with a recent study by Schlmerich et al. who found
the same pattern for birth outcomes. Similar to our study, Cubbin and colleagues found
that place of residence influences ethnic minority and majority groups differently in terms of
their risk for late entry into antenatal care. The results were stratified for neighborhood
deprivation levels instead of neighborhood ethnic minority density levels. But prior research
as well as our study (see S1 Appendix)has shown a relation between higher levels of
neighborhood deprivation and higher levels of ethnic minority density. Cubbin and colleagues
found that African American women in the least deprived areas (and presumably areas of
lower ethnic minority density) were at higher risk of delayed entry into antenatal care than
African American women living in moderately deprived areas. Contrastingly, in the most
deprived areas (and presumably areas of higher ethnic minority density) the risk of late / no
initiation of antenatal care was only elevated among European American women.
Various studies have suggested that for ethnic minority groups, ethnic minority density
could be seen as a proxy for bonding social capital.[11, 39, 40] Applied to our study, this would
mean that the non-Western women in our study have higher levels of bonding social capital
than their Western counterparts in areas with high ethnic minority density. As outlined in the
introduction, higher levels of bonding social capital have been associated with both higher and
lower risk of adequate health care use. The findings from our study suggest that bonding social
capital has a positive effect on time of entry into care of non-Western women. For these
women, bonding social capital might enhance the chances of timely entry into care: firstly by
promoting the exchange of resources between residents (for example money to take public
transport to an antenatal care provider); secondly by having residents engage in collective
action to improve access to local antenatal services; thirdly through social control over healthy
behavior (in this case on timely entry into antenatal care); and lastly by more efficient diffusion
of health related information (on the importance of timely entry into care, and access to
antenatal care).[16, 17]
Neighborhood social capital showed no effect in our analysis. This was an unexpected
finding. In the literature higher levels of neighborhood social capital are associated with more
adequate use of care of Western women.  Moreover, based on a recent Dutch study on birth
outcomes we had expected that this variable would act as a proxy for bonding social capital of
Western residents. Our observations suggest that if Western women have access to bonding
social capital, it does not protect them from late entry into care. In contrast, non-Western
women benefit from their access to bonding social capital in terms of protection from late
entry into care.
In line with previous studies in the Netherlands on other neighborhood effects, we found
that home maintenance (reflecting the environmental conditions in a neighborhood) and level
of urbanity were associated with slightly better outcomes.[11, 20] Similarly, Larson et al.
reported that living in rural areas was strongly associated with late entry into antenatal care in
the United States. An explanation mentioned in this study that could also be plausible for
our setting is longer travelling distances to care providers in rural areas. Lower neighborhood
socioeconomic status was associated with a higher risk of late entry into care in all of our
models. Two previous studies also reported that lower neighborhood socioeconomic status was
associated with inadequate use of antenatal care.[9, 10]
Strengths and Limitations
This study has a number of strengths and limitations that merit discussion. An important
strength of our study was that it was conducted with a national dataset, with high coverage
(97%) and a large number of participants (n = 1,137,741). Second, in our analyses we used
appropriate and sophisticated techniques (multi-level analyses) to account for the clustering of
women within neighborhoods. Our study should also be viewed in the light of its limitations.
Due to the retrospective nature of the data no inferences could be made about causation, only
about associations. The use of a dichotomous variable for ethnicity is both a strength and a
weakness. As described in the methods section, it is less misclassified than the multiple
categories in the Dutch Perinatal Registry. Yet, collapsing ethnicity into a dichotomous variable leads
to grouping women together from heterogeneous backgrounds and with different health
behaviors. Therefore the identification of different underlying mechanisms for different ethnic
groups is not possible within this study. Moreover, in this study we did not have information
on the migrant status of women. Although non-Western ethnicity is often associated with
language barriers and lower health literacy levels, time spent in the host country and the degree
of acculturation influence health care behavior.[43, 44] Despite the lack of data on ethnic
groups and migrant status, we hope to have shown with our study that ethnicity can be
beneficial and is not merely a risk factor.
As described in the methods section, the data on time of entry into antenatal care in the
Netherlands Perinatal Registry has not been validated. In our data set, 17.2% of pregnancy
cases were registered as late entry into care. This is comparable to a large Dutch cohort study
the Rotterdam-based Generation R study, which registered 19.8% of cases as entry into care
after 14 weeks of gestation.
The Netherlands Perinatal Registry database only contains information on individual births.
Therefore we were unable to account for clustering of births within mothers. It is conceivable
that mothers repeated their health care behavior (that is: time of entering care) across their
consecutive pregnancies. Moreover, we were not able to control for certain maternal factors
that have been associated with late entry into care in previous studies, such as an unwanted
pregnancy, illicit drug use, individual socioeconomic status, level of education and language
proficiency.[6, 7] Research in an urban group of Dutch pregnant women showed that 0.5% of
them continued using illicit drugs throughout pregnancy. A little less than six percent of
pregnancies in the Netherlands are unwanted, of which only a part is carried to term.
Based on these Figs., unwanted pregnancies and illicit drug use are only present in a small
portion of the population and are therefore less likely to have an important impact on
Lastly, we could not take other neighborhood characteristics into account that may also
have influenced timing of entry into antenatal care in our study. Prior studies have
demonstrated that quality of public transport and the density and accessibility of care facilities in
neighborhoods influence timing of entry into care.[7, 10, 46]
This study shows that place of residence and ethnic background matter for antenatal health
care use in the Netherlands. Future research could concentrate on teasing apart the beneficial
mechanisms within areas of high ethnic minority density leading to early entry into care (e.g.
information sharing, financial support or other factors). Moreover, our results suggest that
strategies to improve timely entry into care could seek to create change at the neighborhood
level (e.g. increase social bonding) in order to target individuals likely of entering care too late.
Also the relative disadvantage of Western women living in areas of high ethnic density needs to
be considered, interventions should also focus on Western women living in these areas.
S1 Appendix. Correlations of neighborhood variables included in the analysis.
Conceived and designed the experiments: AGP VLNS EAPS IK SD. Analyzed the data: AGP
VLNS. Wrote the paper: AGP VLNS EAPS IK SD. Interpretation of the data: AGP VLNS IK
23. Netherlands Institute for Social Research.
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