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Social inequality is at the root of variation in neonatal outcomes. Discuss.

The socioeconomic circumstances in which an infant in conceived and born have a

major effect on their early life chances and may have life course impacts.

(Weightman et al., 2012)

This report will discuss adverse neonatal outcomes and their potential causes and

also consider what impact, if any, social inequality has on these. The neonatal period

discussed is the first 28 days of life following birth.

In order to consider the impact of social inequality on neonatal health, it is first important

to define exactly what is meant by ‘social inequality’. According to McKay (2012: p.1):

“Inequality concerns variations in living standards across a whole population.” This

inequality has various roots, but the inability to access valued resources in society has

a major impact on future success in life (Kramer, 2000). The concept of social inequality

is multifactorial, spanning a broad range of issues, including: ethnicity; age; gender;

disability; occupation; income; and socioeconomic status (SES). In order to develop

interventions aimed at reducing the perceived gap between groups due to the unequal

distribution of resources, much research has focused on the health impacts of social

inequality (Weightman et al., 2012).

This report will consider the relationship between SES, in terms of area deprivation,

education level and income, with neonatal outcomes in the UK. As the topic of neonatal

outcomes is particularly broad, several major adverse outcomes will be considered,

along with potential links and causes, before a conclusion on the relationship between

these specific outcomes and social inequality.

Context of the Report

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There were 2.8 neonatal deaths per 1,000 live births in 2012 in the UK (ONS, 2012).

Although many fewer babies die during their first 28 days of life in the UK than in

countries in the Global South (there were 32 neonatal deaths per 1,000 live births in

sub-Saharan Africa in 2012 (United Nations, 2013), as stated by former Minister for

Public Health Caroline Flint “one avoidable infant death is one too many” (Department

of Health, 2007: p.3).

In order to combat the discrepancies in the infant mortality rate between social groups in

the UK, a Public Service Agreement target was set in 2001 by the Labour Government,

to reduce by 10% the number of low birth weight (LBW) babies born to the manual and

routine employed group (as determined by the father’s occupation), compared to the

general population (Health Department Agency, 2003). This target was intended to

bring the routine and manual group more in line with the population overall, while also

reducing the infant mortality rate as a whole (NHS, 2010). Despite an initial widening of

the gap, the target was eventually exceeded with a 25% reduction (Vizard, 2013).

This target was in line with Goal 4 of the United Nations’ Millennium Development

Goals. Informed by a decade of summits and meetings leading up to the year 2000,

the United Nations created this set of shared goals for the world’s countries to meet

by 2015, aiming to secure a more prosperous, healthy and equal world (United Nations,

2006). However many of the interventions aimed at achieving MDG 4 have focused on

children aged between 1-4 years, meaning that as their life chances have improved

neonatal deaths have come to represent a larger proportion of child deaths overall

(Oestergaard et al, 2011). Despite the marked global improvement in child health (a

47% decrease in deaths of children under the age of 5 since 1990) only four regions of

the world are on target to reach MDG 4 by 2015 (United Nations, 2013). As initiatives

have improved both maternal health and the life chances of children postneonatal,

those within the first 28 days have been left behind. Indeed the WHO/Unicef child

survival programme does not extend to a baby’s first week of life, “the period of highest

risk for child mortality” (Martines et al., 2005: p. 1191). If MDG 4 is to be met, early

interventions which focus on the care of babies under 1 month must be introduced.

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Adverse Neonatal Outcomes: Premature Birth and Low Birth Weight

The vast majority of babies born after 32 weeks gestation share similar development

outcomes to full term infants (Colvin et al., 2004). The majority of neonatal deaths

however, and around 50% of congenital neurologic anomalies, are associated with a

low gestational age at birth (Goldenberg and Rouse, 1998). Premature babies may

develop a range of cognitive and developmental conditions (Colvin et al., 2004), and

many develop respiratory issues (Goldenberg and Rouse, 1998). Although many

children with cerebral palsy are not born prematurely, an early birth places children at

greater risk of developing the condition (Colvin et al., 2004).

Certain risk factors are associated with premature birth, although not all causes are

known. Premature birth affects all social groups, however incidence rates are higher in

more deprived areas, with women “at twice the risk of very preterm birth as those living

in the least deprived areas.” (Smith et al., 2009: p. F14). Although such statements

suggest area deprivation strongly impacts on neonatal outcome, additional factors need

to be considered. Preterm birth is associated with a variety of factors, including maternal

age, stress, education, nutrition, the presence of infection and body weight (Whitney

et al., 2014; Goldenberg and Rouse, 1998; Thompson, 2006); therefore individual and

environmental factors contribute to premature births.

Research conducted by Morgen et al. (2008) examined over 75,000 preterm births to

test which SES factor (paternal education, maternal education, maternal occupation,

paternal occupation and household income) had greater influence, concluding that

“...maternal educational level was the indicator of socioeconomic position that most

clearly displayed a social gradient in preterm birth”. In contrast to much other research

(Thompson, 2006; Gouldberg et al., 2008; Kramer et al., 2000), Morgen et al. (2008)

found no link between low income households and preterm birth rates.

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A further factor associated with premature birth is ethnicity. Black women are more

likely to deliver premature babies than white women (Fisher, 2008). Studies which

adjusted for differences in SES indicators consistently found a strong association

between different ethnic groups and premature birth, as well as low birth weight (Muglia

and Katz, 2010). Indeed, “...data show that ethnic minority women and their babies

suffer considerably poorer outcomes in comparison to white UK-born women.” (Fisher,

2008: p.21). As this report focuses on SES in terms of area deprivation and income,

the issue of ethnicity specifically does not need to be discussed at length. However,

research suggests “mothers from all ethnic minority groups, particularly women of

mixed or Black Caribbean ethnicity, were more likely to be living in a household with

low income than white mothers.” (ibid. p.22). Research that focuses on ethnicity and

its relationship with neonatal outcomes in fact often finds a correlation between the two

factors. However given the higher rate of ethnic minorities living in socially deprived

areas, identifying true correlation is complex.

According to The World Health Organisation (2011) babies born below 2.5kg are

classified as having a low birth weight (LBW), which is directly related to gestational

age and the prevalence of Intrauterine Growth Restriction (IUGR) (Health Development

Agency, 2003). Although many preterm babies are born with a LBW, full term babies

are also at risk. Multiple risk factors are associated with LBW include smoking, both pre-

conception and during pregnancy; alcohol consumption; psychosocial factors; ethnicity;

and SES (Fisher, 2008; Kramer, 1987; Manning et al., 2005). Social deprivation is a

risk factor strongly associated with higher rates of LBW (Manning et al., 2005) that is

further associated with neonatal mortality (Kim and Saada, 2013) and morbidity; babies

born below 2.5kg are at an increased risk of severe neurocognitive disorders, diabetes,

and heart disease (Health Development Agency, 2003). In contrast to the findings of

Manning et al. (2003), Kramer (1987) claimed SES itself made no impact on LBW,

representing correlation rather than causation. The extent SES has on neonatal impacts

compared to individual factors which encompass SES will be discussed further, later.

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Due to the risks associated with premature birth and LBW, interventions aimed at

identifying mothers most at risk of delivering early, and precautions against it have

been developed as a means of reducing the impacts (Goldenberg and Rouse, 1998).

The practice of cerclage for at-risk women is contested as research suggests stitching

the cervix does not result in a significant decrease in the number of preterm deliveries

(Chien, 2013). Alternatively, administering steroids to prolong labour has been found

to benefit both the mother and the baby, providing essential time for patients to travel

to special neonatal units (Goldenberg and Rouse, 1998). The location of and access

to neonatal units is further associated with social inequality, however. The ability to

access medical treatment directly impacts on the overall outcomes, with greater rates

of neonatal mortality associated with longer journeys (Ravelli et al., 2010). Neonatal

intensive care units (NICU) are understaffed and under-resourced meaning many

women are forced to transfer to alternative hospitals, placing both the mother and baby

at greater risk (Gill et al., 2003). Although the availability of resources is a national

issue, the likelihood of a baby being admitted to a NICU is greater for women with low

SES (Manning et al., 2005) meaning hospitals in socially deprived areas carry a heavier

burden of mortality and indeed cost (Smith et al., 2009).

Adverse Neonatal Outcomes: Congenital Abnormalities

According to the World Health Organisation, “Congenital anomalies can be defined

as structural or functional anomalies … which are present at the time of birth.” (WHO,

2014). There are several hundred congenital anomalies, which can be categorised

into four distinct groups: structural, functional, metabolic, and hereditary (Kurinczuk

et al., 2010). Although congenital anomalies are the second most common cause of

neonatal mortality in the UK (Linhart et al., 2000), the vast majority of babies born with

a congenital anomaly will survive (Kurinczuk et al., 2010). For the purposes of this

report it is not necessary to discuss at length individual congenital anomalies, however

attention will be given to the perceived causes and risk factors associated with certain

anomalies in an attempt to consider what impact social inequality may have on the

prevalence of such anomalies.

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As the term congenital anomaly refers to all conditions (minor and major) arising

throughout pregnancy (Smith et al., 2011), the available literature is vast. Congenital

anomalies are more prevalent in preterm babies, and those classified as LBW (Linhart

et al., 2000). Although the causes of congenital anomalies are largely unknown

(Kurinczuk et al., 2010), certain conditions are strongly associated with maternal age

and lifestyle. An example of this is gastroschisis - when the abdominal wall fails to fully

develop, exposing the intestines (Kilby, 2006). This is strongly associated with younger

mothers, with 75% of cases reported by Draper et al. (2007) born to mothers under 25

years old. Furthermore, as the anomaly results from the interruption of blood supply

(Kilby, 2006) the use of recreational drugs, smoking and alcohol consumption are

strongly associated with the condition (ibid; Draper et al., 2007). In addition, research

suggests advancing maternal age is associated with the incidence of Down syndrome

(Gaulden, 1992), with the risk of chromosomal abnormalities inversely associated with a

mother’s age. This is contested however, as 80% of children born with the condition are

to mothers below 35 years of age (NDSS, 2012). The correlation between maternal age

and Down syndrome is complex, with discrepancies in age groups attributed to mothers

opting to terminate fetuses diagnosed with the condition (Morris and Alberman, 2009).

Research by Olesen et al. (2009: p. 1) looked at the association between congenital

anomalies, parental education and family income, concluding that: “… low social

position is associated with increased risk of neural tube defects [and] orofacial clefts”.

However as mothers with more education tend to access antenatal screening earlier

than their less educated counterparts, the increased rate of children being born with

congenital anomalies to mothers with low SES could be due to either mothers not being

screened prior to birth, or opting not to terminate the fetus (Grewal et al., 2009).

The practice of drawing associations between neonatal outcomes and SES has been

challenged, as it not only neglects other factors but has the potential to overlook

marginalised women (NHS, 2009). As SES is often determined by area deprivation

a mother may be regarded as well-resourced based on her postcode, but may

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lack a support network and therefore be vulnerable (NHS,, 2009). To combat this,

research by Grewal et al. (2009) considered both individual factors and neighbourhood

socioeconomic status in order to analyse the true impact of social deprivation on

congenital anomalies. Although findings suggested there is a correlation between low

maternal education and increased incidence rates of neural tube defects, the education

level itself is not a cause of the defect, as “low maternal education could be associated

with poor access to a well-balanced diet that includes food rich in folates” (Grewal et al.

2009: p. 5). The issue of maternal nutrition will be returned to later.

Ultimately, a mother’s low income alone is unlikely to impact on the risk of developing

a congenital anomaly; the lifestyle associated with low income may, however, meaning

the cause is highly likely to be multifactorial. Low income has a direct impact on

housing, nutrition, health care, and general attitude – all factors which have been shown

to impact on pregnancy and neonates.

Antenatal Screening:

At this point, it is beneficial to consider the issue of screening. In the UK it is national

policy to offer pregnant women antenatal screening before 12 weeks gestation (NHS,,

2009). Although screenings are used to monitor the baby’s progress and determine

gestational age, certain congenital anomalies, for instance Down syndrome can

be diagnosed. Such screening has proven controversial as “perceptions of a good

reproductive outcome are very personal and influenced by many social, cultural and

religious factors” (Kurinczuk, et al., 2010: p.9). Screening uptake rates vary depending

on ethnicity, although little difference is seen between SES groups (Rowe et al., 2008).

However entry times of prenatal care does tend to differ between SES groups (NHS,,

2009). Early and regular attendance at antenatal appointments enables the diagnosis

of anomalies, provides women with essential advice and information for a range of

services, and helps to create a support network (NHS,, 2009). Such services should be

accessible to all, regardless of ethnicity, language or SES, with adequate advice and

high quality services offered universally.

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Late entry to prenatal care is associated with adverse outcomes (Kramer et al., 2000).

Many conditions can be diagnosed and monitored through screening, allowing risk-

specific interventions to be given (Goldenberg and Rouse, 1998). However research

suggests “... those who are at the greatest risk of poor pregnancy outcomes are the

least likely to access and/or benefit from the healthcare that they need.” (The Scottish

Government, 2011: p.10). Women from low SES groups are less likely to access certain

services, with many reporting negative previous experiences or language difficulties

as barriers to services (Fisher, 2008; NHS,, 2009). Furthermore, research suggests

women in the most deprived areas are less likely to be offered certain screening tests

(Rowe et al., 2008), or are unable to make an informed choice as they are not given

the necessary information (Dormandy et al., 2005). As “pregnant women with complex

social” needs tend to book antenatal appointments late and cancel more frequently,

addressing the barriers preventing their engagement is essential - although few

evidenced-based interventions are currently practiced (NICE, 2010: p.27).

It is important to note that much of the research that finds a link between SES and

neonatal mortality due to congenital anomalies only considers live births (Kurinczuk et

al., 2010). Figures from pregnancies that ended in termination due to diagnosis of a

congenital anomaly are not included. As 92% of mothers carrying fetuses diagnosed

with Down syndrome opt to terminate the pregnancy (Morris and Alberman, 2009),

such omissions may have a huge impact on understanding which factors are directly

associated with congenital anomalies, and which do not merely show correlation. As

research suggests particular groups respond differently to the offer and outcome of

antenatal screenings (Smith et al., 2011), it is crucial links are not seen which do not

truly exist.

Adverse Neonatal Outcomes: Infant Mortality and Stillbirths

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Low birthweight and preterm delivery are the main proximal risk factors for

death under one year, especially under one month, and both factors are highly

associated with socio-economic status and deprivation.

(Oakley et al., 2009: p. 32)

Despite improvements in neonatal survival rates stillbirths “account for two-thirds of

perinatal deaths in the UK” (Lawn et al., 2011: p.1448). As with premature births and

LBW, the cause of stillbirth is multifactorial (Flenady et al., 2011). Associated risk

factors include household smoking habits, maternal age, maternal BMI score, maternal

and fetal infection, and congenital anomalies (Seaton et al., 2012; ASH, 2013).

Although underlying mechanisms are difficult to determine, stillbirths can be categorised

into three types: placental abruption, congenital anomalies, and intrapartum events

(Seaton et al., 2012). Mothers with lower SES have an increased risk of stillbirth

originating from placental abruption (ibid.), as well as a 20% increase in stillbirths due

to congenital anomalies (Smith et al., 2011). Higher levels of social deprivation are

consistently associated with increased rates of stillbirth (Guildea, 2001). As parental

SES influences access to “healthy practices and avoiding harmful risks” it impacts on

infant mortality rates (Kim and Saada, 2013: p.2313). For stillbirths associated with

placental abruption, maternal lifestyle and pregnancy history are contributing factors

(Seaton et al., 2012). Placental abruption is strongly associated with recreational drug

use, which is further associated with a low maternal age and low SES (Paranjothy et al.,

2008).

Although Sudden Unexplained Death in Infancy (SUDI) is more often associated with

post-neonatal deaths occurring between 2-4 months of age, the rate of SUDI in the

neonatal period “account[s] for a significant part of all SUDI” (Hoffend and Sperhake,

2013: p.3). LBW, gender, maternal or paternal smoking habits, and the mother’s

parity are strongly associated with SUDS (Sullivan and Barlow, 2001; DoH, 2007).

Furthermore, bed-sharing is often associated with SUDI, which when combined

with smoking or alcohol consumption, can be fatal (Blair and Ball, 2004). In contrast

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to research which links low SES to stillbirths however, Blair and Ball (2004) found

bed-sharing with neonates more common in the least deprived areas, possibly as it

facilitates breastfeeding which similarly is more commonly practiced amongst higher

SES groups (Hauck et al., 2011).

Common Risk Factors

Although particular risk factors in relation to specific outcomes have been discussed,

certain factors are relevant to all highlighted outcomes.

Smoking

There is a strong link between adverse neonatal outcomes, particularly LBW and

premature birth, and smoking during pregnancy (Health Development Agency, 2003).

According to a report commissioned by the Department of Health (ASH, 2013: p.4):

“Smoking during pregnancy causes up to 2,200 premature births, 5,000 miscarriages

and 300 perinatal deaths every year in the UK”. The dangers are well researched

and much effort is put into cessation programmes to encourage mothers and other

household members to stop. Smoking during pregnancy is most highly associated with

young mothers (under 20 years old) with the least education (Health Development

Agency, 2003). All social classes smoke however prevalence rates differ, with fewer

people continuing to smoke during pregnancy in higher SES groups (ASH, 2013). As

smoking is associated with LBW and preterm birth, which are then further associated

with neonatal death, congenital anomalies and developmental issues, all mothers

are advised to stop smoking (Health Development Agency, 2003). Despite all social

groups being equally motivated to cease smoking those in the lowest SES groups are

less successful (Health Development Agency, 2001) with “women of lower education,

income and employment status far more likely to continue smoking than women from

higher SES groups.” (Health Development Agency, 2003: p.1).

Rates of babies born with LBW or Intrauterine Growth Restriction are persistently linked

to smoking (Health Development Agency, 2003; Raisanen et al., 2013). As a result,

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smoking is heavily debated in the literature regarding neonatal outcomes with “the

incidence of low birth weight [being] twice as high among smokers as nonsmokers”

(Health Development Agency, 2003: p. 17). Smoking during pregnancy exposes the

fetus to toxins while preventing oxygen and nutrients from being absorbed, leading to

growth restriction (Roza et al. 2007). Therefore, babies born to mothers who smoke

are at risk of being born Small for Gestational Age (SGA) - meaning they are “below

the tenth percentile for weight and length for their gestational age.” (Räisänen et

al. 2013: p.1-2). The occurrence of being SGA can affect babies born at any age of

gestation and it has been linked to greater risks of adverse birth outcomes (Health

Development Agency, 2003). Research produced by Räisänen et al. (2013) investigated

the prevalence of SGA babies born in Finland over a 23-year period. Although many

factors were found to heighten the risk of SGA:

Smoking alone made the largest contribution, explaining around 40-50% of

the excess of SGA among the lowest SES group. In contrast, the combined

contribution of amniocentesis, placental abruption, placenta previa, congenital

anomaly, and prior CS [cesarean section] was only around 4%.

The underlying mechanisms which mean mothers in lower SES have a tendency to

continue smoking despite knowing the dangers (providing they have been educated on

the risks and were able to access cessation programmes), is the essential difference

between SES groups and the prevalence of adverse neonatal outcomes. Indeed,

“...smoking during pregnancy...can account for some of the gap [between social groups,

but] it does not account for all of it.” (Grey et al., 2007).

The link between smoking during pregnancy and adverse birth outcomes is quite clear,

and indeed well researched. Programmes targeting those most at risk of continuing to

smoke through pregnancy which aim to educate mothers about the risks associated

with such habits and how to stop are crucial. Difficulties recruiting pregnant smokers

arise due to over-reliance on self-reporting; many mothers who do smoke are not

enrolled in cessation programmes as they do not tell staff about their habit (Health

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Development Agency, 2003). Furthermore, similar barriers which prevent women from

accessing antenatal sessions make smoking mothers in lower SES groups harder to

reach (NHS,, 2009).

Maternal Stature and Age

Poor maternal nutrition is linked with poor neonatal outcomes (Abu-saad and Fraser,

2010). Low BMI scores suggest the mother is underweight, which is often related to

preterm birth and/or LBW (Kalk et al., 2009), as both the growing maternal body and

fetus compete for nutrients (King, 2003). A high maternal BMI score and obesity are

associated with admission to neonatal intensive care units (ibid.), with a three-fold

higher risk of stillbirth (Walsh, 2013). Obese women are “at an increased risk of a range

of congenital anomalies” (Kurinczuk et al., 2010), including birth defects related to heart

conditions (Tommy’s, 2014).

SES can influence dietary habits before and during pregnancy, with mothers in low

SES more likely to be nutritionally deficient (Abu-Saad and Fraser, 2010). To reduce

risks associated with dietary problems, women are routinely advised to take certain

supplements, for example folic acid, which has been linked to better outcomes and

reduced risk of neural tube defects (NHS, 2012). Despite this, strong associations

between low SES and poorer outcomes linked to nutrition are consistently found

(Grewal et al., 2009).

Younger mothers are more likely to live in highly deprived areas and have less

education (Paranjothy et al., 2008). The maternal versus fetal competition over nutrients

is one issue associated with young mothers and those with a low BMI score, but a

low maternal age is also linked to stillbirths, with the highest incident rate in 2012

attributed to mothers younger than 20 years old (ONS, 2014). The direct cause of this

is unclear however, as behavioural factors, such as increased rates of smoking, alcohol

consumption and drug use, in addition to higher levels of deprivation can influence

stillbirth rates (Paranjothy et al., 2008).

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Adverse neonatal outcomes are not only linked to young mothers. Advancing maternal

age has been associated with certain congenital anomalies, increased risk of premature

birth and the presence of Intrauterine Growth Restriction (Gaulden, 1998). One potential

explanation for the additional risk of adverse outcomes for older mothers is the more

common use of fertility treatment. Assisted fertility is highly associated with multiple

births, which is further associated with adverse outcomes (Reddy et al., 2007). As

older mothers tend to use fertility treatment more than younger women there is a link

between older mothers and particular adverse outcomes, however due to the increased

use of fertility treatment such an association does not necessarily indicate causation.

Furthermore, the use of fertility treatment challenges links between low SES and

adverse outcomes as such treatment is more often sought by those with higher SES

(Dhalwani et al., 2012).

Psychosocial Factors

Associations have been reported between preterm birth and stressful life events,

anxiety, depression, stressful work, physical abuse and low levels of social

support.

(Kramer et al., 2000: p.200)

Area deprivation alone is not sufficient to influence adverse outcomes; it is the

consequences of living in certain areas and being exposed to external factors that

create the result (Kramer et al., 2000). Mothers living in socially deprived areas may

experience heightened levels of stress, anxiety and depression (Giscombe and Lobel,

2005). A potential underlying mechanism of SES influencing preterm birth is the

presence of stress and other psychosocial factors (Kim and Saada, 2013). Chronic

stressors - for example inadequate or overcrowded housing, domestic violence, low

income and overwork - are associated with adverse neonatal outcomes (Kramer et al.,

2000). Living arrangements and “daily hassles” (Kramer et al., 2000: p. 200) are linked

to stress levels, and although not exclusive to lower SES groups, the inability to escape

certain circumstances further compound the effects of stress (Kim and Saada, 2013).

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Various explanations have been postulated as to how psychosocial factors may cause

adverse outcomes. Heightened stress levels promote the production and release of

various hormones, including corticotrophin, which is associated with premature delivery,

placing mothers who experience stressful events at risk of delivering early (Mulder

et al., 2002). Furthermore, mothers who feel anxious or depressed are more likely to

engage in risky behaviour “... such as drinking alcohol, smoking, skipping prenatal

visits, entering prenatal care late and skipping meals” (Littleton et al., 2010: p.219).

Consequently, stress during pregnancy is associated with LBW, preterm birth, structural

changes, spontaneous abortion and pre-elampsia (Mulder et al., 2002).

A closer look as SES

Although this report has used headings to consider the risk factors associated with

adverse neonatal outcomes in relation to SES, the factors which determine a person’s

socioeconomic status are not so easily separated. A broad range of factors, including

education levels, income and place of residence can determine socioeconomic status

(McKay, 2002). These factors alone however are not sufficient to cause particular

outcomes; indeed research which claims to show causation may indeed merely

indicate correlation. Research does not clearly indicate that SES is a direct link to birth

outcomes; the combination of low SES together with particular lifestyle choices and the

inability to access certain services create strong associations with adverse neonatal

outcomes. Furthermore, it cannot be assumed all members of a given society share

common individual attributes. Although certain social groups may statistically engage in

particular habits more often than others, or have poorer educational attainment, there

will be individual differences within the group; people’s “reactions and responses to …

conditions alter their risk to adverse pregnancy outcomes.” (Kramer et al. 2000: p.197).

When determining the impact of SES on neonatal outcomes, it is important to consider

both direct and indirect factors which influence the outcome. As discussed, smoking is

strongly associated with LBW. Smoking is also associated with low SES (ASH, 2013).

Determining which factor is the direct influence on adverse outcomes though, and not

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merely a correlation between the two, is complex. According to Fisher (2008: p.25)

Disadvantaged women are often exposed to multiple adversities, such as

poverty, language and communication difficulties, lack of a supportive partner

and late or infrequent access to antenatal care, thus heightening their

vulnerability.

When trying to understand the relationship between SES and neonatal outcomes,

all factors which contribute to SES will play a role in that outcome. To see SES as a

single entity neglects the role of the contributing factors. It is therefore important to

consider what treatment and assistance women and babies need from a multi-agency

perspective.

Although research into SES and neonatal outcomes highlights common adversities,

over reliance on SES as a determining factor poses problems. Interventions aimed at

supporting those at risk of certain outcomes attempts to alleviate disadvantage arising

from social inequality (Health Development Agency, 2001). However such a sweeping

approach may allow some women to fall through the gaps (NHS, 2009). Women who

are not classified as vulnerable may not receive the care and attention they require.

We tend to focus on deprivation but there are women who I would

describe as vulnerable, who might be fairly well off but don’t have the

support of family or even the community. They’re lonely and that can make them

vulnerable.

(NHS,, 2009: p. 68)

Therefore, examining a mother’s circumstances holistically is important when

determining what interventions should be given.

Conclusion

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This report has considered several adverse neonatal outcomes and risk factors

associated with them. It has attempted to determine what role socioeconomic status

has in the prevalence of such outcomes. Factors which indicate a low socioeconomic

status however and those associated with adverse neonatal outcomes overlap. As a

result more LBW babies and preterm births are found in areas of social deprivation

(Thompson et al., 2006). Determining whether low SES is the root cause of these

outcomes, or merely an additional risk factor is less clear (Taylor-Robinson et al., 2011).

The vast amount of literature examining the relationship between social inequality and

adverse neonatal outcomes varies in the tool used to determine inequality, with little

consistency between studies. Yet despite these differences, the outcomes are the

same: mothers and babies who are socially deprived, regardless of the measure used

to classify that deprivation, fare worse than their better socially placed counterparts.

As stated at the beginning of this report, social inequality relates to the distribution

of valued resources that assist in people’s lives, enabling them to lead a healthy,

well-informed and resource-rich life. Neonatal outcomes are influenced by a variety

of factors. It is overly simplistic to say one factor alone causes adverse neonatal

outcomes; it is the combination of certain risk factors which impact on a baby’s

development and first month of life. The use of area deprivation to determine SES,

although a useful tool when comparing groups, largely ignores individual differences

and is therefore insufficient, as “...wide social disparities exist between different

individuals residing in the same area.” (Fisher, 2008: p.21). In order to implement

adequate interventions which will enable more babies to survive, attention needs to

be paid to the underlying causes of adverse outcomes (Black et al., 2003). To take

smoking as an example: certainly, it is a risk factor associated with high incidence rates

of low birth weight, which is associated with neonatal mortality, but the reasons the

mother is smoking whilst pregnant need to be understood before significant changes

can be made.

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If levels of deprivation were equalled to that of the least deprived, discrepancies in

the rates of premature birth, LBW and congenital anomalies associated to SES would

largely disappear (End Child Poverty, 2008). Interventions aimed at closing the gap

between social groups cannot tackle one factor alone and succeed. It is necessary to

adopt a multidisciplinary approach in order to facilitate holistic change. Furthermore,

biological changes need time to fully develop. Essential to all interventions aimed at

preventing adverse neonatal outcomes is time; in order to witness the benefits, society

needs the opportunity to fully explore and use initiatives (Kim and Saada, 2013).

Factors commonly associated with low SES - stress, inadequate housing, strenuous

work, and poor nutrition - each impact on birth outcomes (End Child Poverty, 2008).

However, such features and higher SES are not mutually exclusive; low SES is not the

cause of adverse neonatal outcomes, it is the vehicle for complex issues. Currently, “the

mechanisms giving rise to the social inequalities are still largely unknown”; until that is

rectified, the poor will continue to do more poorly.

Social inequality is such a complex construct, identifying the prevailing feature that

most greatly impacts on neonatal outcomes presents many difficulties. Programmes

aimed at educating future parents in nutrition, the importance of antenatal screening,

healthy lifestyle choices and how to identify signs of preterm birth would enable the

gap between social groups to close. Moving forward, further research which focuses on

intergenerational deprivation and the development of targeted provisions would add to

the great body of work related to social inequality.

Word Count: 5464

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