<?xml version="1.0"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "JATS-journalpublishing1.dtd"[]><article xml:lang="en" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" dtd-version="1.2" article-type="research-article"><front><journal-meta><journal-id journal-id-type="publisher-id">IJPDS</journal-id><journal-title-group><journal-title>International Journal of Population Data Science</journal-title><abbrev-journal-title>IJPDS</abbrev-journal-title></journal-title-group><issn pub-type="epub">2399-4908</issn><publisher><publisher-name>Swansea University</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.23889/ijpds.v6i1.1699</article-id><article-id pub-id-type="publisher-id">6:1:1699</article-id><article-id pub-id-type="pii">S2399490821016992</article-id><article-categories><subj-group subj-group-type="heading"><subject>Population Data Science</subject></subj-group></article-categories><title-group><article-title>Benefits of not smoking during pregnancy for non-Aboriginal women and their babies in New South Wales, Australia: a record linkage study</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Patterson</surname><given-names initials="JA">Jillian A.</given-names></name><xref ref-type="aff" rid="affil-1">1</xref><xref ref-type="aff" rid="affil-2">2</xref><xref ref-type="corresp" rid="correspondingAurthor">*</xref></contrib><contrib contrib-type="author"><name><surname>Cashmore</surname><given-names initials="A">Aaron</given-names></name><xref ref-type="aff" rid="affil-3">3</xref><xref ref-type="aff" rid="affil-4">4</xref></contrib><contrib contrib-type="author"><name><surname>Ioannides</surname><given-names initials="S">Sally</given-names></name><xref ref-type="aff" rid="affil-3">3</xref><xref ref-type="aff" rid="affil-5">5</xref></contrib><contrib contrib-type="author"><name><surname>Milat</surname><given-names initials="AJ">Andrew J.</given-names></name><xref ref-type="aff" rid="affil-3">3</xref><xref ref-type="aff" rid="affil-4">4</xref></contrib><contrib contrib-type="author"><name><surname>Nippita</surname><given-names initials="TA">Tanya A.</given-names></name><xref ref-type="aff" rid="affil-1">1</xref><xref ref-type="aff" rid="affil-2">2</xref></contrib><contrib contrib-type="author"><name><surname>Morris</surname><given-names initials="JM">Jonathan M.</given-names></name><xref ref-type="aff" rid="affil-1">1</xref><xref ref-type="aff" rid="affil-2">2</xref></contrib><contrib contrib-type="author"><name><surname>Torvaldsen</surname><given-names initials="S">Siranda</given-names></name><xref ref-type="aff" rid="affil-1">1</xref><xref ref-type="aff" rid="affil-2">2</xref><xref ref-type="aff" rid="affil-5">5</xref></contrib><aff id="affil-1"><label>1</label><institution>The University of Sydney Northern Clinical School, Women and Babies Research, St Leonards, 2065, New South Wales, Australia</institution></aff><aff id="affil-2"><label>2</label><institution>Northern Sydney Local Health District, Kolling Institute, New South Wales, Australia</institution></aff><aff id="affil-3"><label>3</label><institution>NSW Ministry of Health, Centre for Epidemiology and Evidence, St Leonards, 2065, New South Wales, Australia</institution></aff><aff id="affil-4"><label>4</label><institution>The University of Sydney School of Public Health, Faculty of Medicine and Health, Sydney, 2006, New South Wales, Australia</institution></aff><aff id="affil-5"><label>5</label><institution>School of Population Health, UNSW, Kensington, 2052, New South Wales, Australia</institution></aff></contrib-group><author-notes><corresp id="correspondingAurthor"><label>*</label>Corresponding author: Jillian A. Patterson <email>jillian.patterson@sydney.edu.au</email></corresp><fn fn-type="conflict"><label>Conflicts of interest</label><p>The authors have no conflicts of interest to declare.</p></fn></author-notes><pub-date date-type="pub" publication-format="electronic"><day></day><month></month><year></year></pub-date><pub-date date-type="collection" publication-format="electronic"><year></year></pub-date><volume>6</volume><issue>1</issue><elocation-id>1699</elocation-id><permissions><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by-nc-nd/4.0/"><license-p>This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.</license-p></license></permissions><self-uri xlink:href="https://ijpds.org/article/view/1699">This article is available from the IJPDS website at: https://ijpds.org/article/view/1699</self-uri><abstract><title>Abstract</title><sec><title>Background</title><p>Smoking rates among pregnant women in New South Wales (NSW) have plateaued at 8&#x2013;9%. To inform relevant smoking reduction efforts, we aimed to quantify the benefits of <italic>not</italic> smoking during pregnancy for non-Aboriginal NSW mothers and their babies. The benefits of <italic>not</italic> smoking during pregnancy for NSW Aboriginal mothers have previously been described. These data are important inputs in modelling health and economic impacts of smoking cessation interventions.</p></sec><sec><title>Methods</title><p>This population-based cohort study used linked-data from routinely collected data sets. Not smoking during pregnancy was the exposure of interest among all NSW non-Aboriginal women who became mothers of singleton babies in 2012&#x2013;2016. Unadjusted and adjusted relative risks (aRR) were used to examine associations between not smoking during pregnancy and adverse outcomes including severe morbidity, inter-hospital transfer, perinatal death, preterm birth and small-for-gestational age. Population attributable fractions (PAFs) were calculated to quantify adverse perinatal outcomes avoided in the population if all mothers were non-smokers.</p></sec><sec><title>Results</title><p>Compared with babies born to mothers who smoked during pregnancy, babies born to non-smoking mothers had a lower risk of all adverse perinatal outcomes including perinatal death (aRR = 0.68, 95%CI 0.61&#x2013;0.76), preterm birth (aRR = 0.58, 95%CI 0.56&#x2013;0.61) and small-for-gestational age (aRR = 0.48, 95%CI 0.47&#x2013;0.50). PAFs(%) were 3.9% for perinatal death, 5.6% for preterm birth and 7.3% for small-for-gestational-age. Compared with women who smoked during pregnancy (n = 36,518), those who did not smoke (n = 413,072) had a lower risk of suffering severe maternal morbidity (aRR = 0.87, 95%CI 0.81&#x2013;0.93) and being transferred to another hospital (aRR = 0.92, 95%CI 0.86&#x2013;0.99).</p></sec><sec><title>Conclusions</title><p>Mothers who reported not smoking during pregnancy had a small reduction in their risk of morbidity and of being transferred to another hospital whilst their babies had substantially reduced risks of all adverse perinatal outcomes. Results have implications for clinician training, clinical care standards, and performance management.</p></sec></abstract><kwd-group><kwd>smoking cessation</kwd><kwd>pregnancy</kwd><kwd>stillbirth</kwd><kwd>neonatal outcomes</kwd></kwd-group></article-meta></front><body><sec><title>Introduction</title><p>The NSW State Health Plan &#x2018;Towards 2021&#x2019; aimed to reduce smoking rates among pregnant women in NSW by 0.5% per year, to 7.5% in 2015 [<xref ref-type="bibr" rid="ref-1">1</xref>]. Whilst smoking rates among pregnant women in NSW declined from 22.1% in 1994 to 8.3% in 2016 [<xref ref-type="bibr" rid="ref-2">2</xref>], the target of 7.5% has not been met and there are concerns that the rates have plateaued.</p><p>Although the risks of smoking during pregnancy are well established, 8.8% of pregnant women in NSW reported smoking in 2019 [<xref ref-type="bibr" rid="ref-3">3</xref>]. A recent study clearly demonstrated the benefits of not smoking during pregnancy among NSW Aboriginal women and showed that babies born to Aboriginal mothers who did not smoke during pregnancy were at a significantly reduced risk of adverse perinatal outcomes compared to infants born to similar mothers who did not smoke [<xref ref-type="bibr" rid="ref-4">4</xref>]. Results from that study are currently being used to inform smoking cessation materials for Aboriginal women and their families. As there are large differences in smoking rates between Aboriginal and non-Aboriginal mothers, smoking cessation strategies which may be effective for Aboriginal women may have little or no effect in non-Aboriginal women. A need for similar evidence on benefits of not smoking during pregnancy among the remainder of the NSW population has been identified. This evidence is needed in both system level planning and individual patient counselling. Hence, this study aimed to quantify the benefits of <italic>not</italic> smoking during pregnancy for non-Aboriginal NSW mothers and their babies.</p></sec><sec><title>Methods</title><p>The study population was all singleton babies born to non-Aboriginal NSW mothers residing in NSW between 1 January 2012 and 31 December 2016, and their mothers. Births were identified from the NSW Perinatal Data Collection (birth data), which is a statutory record of all livebirths and stillbirth of at least 20 weeks gestation or 400g birthweight in NSW. Women who were recorded as Australian Aboriginal in the birth data or who were assigned Aboriginal status according to the Enhanced Reporting of Aboriginality algorithm used in the previous study [<xref ref-type="bibr" rid="ref-5">5</xref>] were excluded from this study.</p><p>The birth data were probabilistically linked with the Admitted Patient Data Collection (hospital data) and the Registry of Births, Deaths and Marriages deaths data (death data). Record linkage was performed by the NSW Centre for Health Record Linkage using personal identifiers, with de-identified data provided to researchers. The rate of false links was low (5 per 1000) [<xref ref-type="bibr" rid="ref-6">6</xref>], meaning it was rare that records belonging to different people were wrongly assessed as belonging to the same person. The hospital data contain information on diagnoses and procedures for all inpatient admissions to public and private hospitals for both mothers and infants coded according to the International Classification of Diseases version 10-Australian modification and the Australian Classification of Health Interventions [<xref ref-type="bibr" rid="ref-7">7</xref>]. The death data, recording fact of death for deaths registered within NSW, was used in conjunction with birth and hospital data to identify neonatal deaths.</p><p>The exposure of interest was absence of maternal smoking throughout the pregnancy (&#x2018;Non-Smokers&#x2019;), as opposed to any smoking during pregnancy (&#x2018;Smokers&#x2019;). Smoking was identified through self-report in the birth data and/or a diagnosis code indicating current smoking (Z72.0, F17) in the hospital record associated with the delivery. The sensitivity of current smoking from the most recent separation in the hospital data is estimated to be 58.5% and the specificity 98.4% [<xref ref-type="bibr" rid="ref-8">8</xref>].</p><p>Two maternal outcomes of interest were identified from the birth data and the hospital record(s) related to the delivery. Outcomes considered were a composite indicator of severe maternal morbidity which includes transfusion, assisted ventilation and organ failure (<xref ref-type="supplementary-material" rid="sup-a">Supplementary Table 1</xref> [<xref ref-type="bibr" rid="ref-9">9</xref>]) and inter-hospital transfer (reflecting the need for higher level care). Both these outcomes were binary.</p><p>Perinatal outcomes included those occurring at birth and within the first 28 days of life, and were identified from the hospital, birth and death data. Perinatal outcomes were preterm birth (&#x003C;37 weeks gestation), birthweight less than the 3<sup>rd</sup> and 10<sup>th</sup> centiles for gestational age and sex [<xref ref-type="bibr" rid="ref-10">10</xref>], severe neonatal morbidity, and perinatal death (stillbirth and neonatal death) and its components. Severe neonatal morbidity was measured using a validated composite indicator [<xref ref-type="bibr" rid="ref-11">11</xref>] containing procedures and diagnoses associated with severe morbidity and was calculated amongst live births only (<xref ref-type="supplementary-material" rid="sup-a">Supplementary Table 2</xref>).</p><p>Maternal age was obtained from the birth data. Other covariates included any hypertension and any diabetes and were obtained from the birth and hospital data. Socioeconomic status and remoteness were assigned based on the statistical local area of residence of the mother using the NSW ranking of the Australian Bureau of Statistics 2011 Socio-Economic Index for Areas (SEIFA) Index of Relative Socio-Economic Disadvantage and the 2011 Remoteness Areas. Hospitals were grouped according to birth volume, location and ownership [<xref ref-type="bibr" rid="ref-12">12</xref>].</p><p>Unadjusted and adjusted relative risks were calculated using modified Poisson regression with robust error variances. All analysis was performed in SAS [<xref ref-type="bibr" rid="ref-13">13</xref>]. Given the established causal relationship between smoking and adverse perinatal outcomes, we also quantified the proportion of adverse perinatal outcomes that would not have occurred in this population if all the mothers had been non-smokers during pregnancy. We used the formula: PAF = [Ps(RRs-1)]/RRs, where Ps is the proportion of babies with the given outcome whose mothers smoked and RRs is the adjusted RR for smokers. The RRs is the inverse of the RR for non-smokers.</p></sec><sec><title>Results</title><p>Between 2012 and 2016 there were 488,768 babies born to 382,268 mothers in NSW. Of these, 20,961 (4.3%) babies were identified as having Aboriginal mothers (15,438 mothers). After restricting the population to singletons and NSW residents there were 449,590 babies born to 358,308 non-Aboriginal mothers (<xref ref-type="fig" rid="fig-1">Figure 1</xref>).</p><fig id="fig-1"><label>Figure 1: Flow diagram of mothers and babies eligible for inclusion in the final study population</label><graphic xlink:href="ijpds-06-1699-g001.tif"/></fig><p>Most (92%) mothers reported not smoking during their pregnancy and this proportion increased slightly over time, from 90.8% in 2012 to 92.8% in 2016. Mothers who reported not smoking in pregnancy were more likely to be older, be having their first baby, live in an area with the least disadvantage (i.e. more likely to be high socioeconomic status), live in a city, and not suffer from any chronic conditions (<xref ref-type="table" rid="table-1">Table 1</xref>). The same proportion (8%) of smoking and non-smoking mothers suffered from hypertension in their pregnancy, and a slightly greater proportion of non-smoking mothers had a diagnosis of diabetes than smoking mothers (12.4% vs 10.5%).</p><table-wrap id="table-1"><label>Table 1: Demographics at the time of birth of mothers who gave birth to at least one singleton baby in NSW between 2012 and 2016 reported for all births and by smoking status during pregnancy</label><table frame="hsides" rules="groups"><thead><tr><th rowspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="left"></th><th colspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>All births N = 449,590</bold></th><th rowspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="left"></th><th colspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>Non-smoking N<sub>ns</sub> =413,072 (91.9%)</bold></th><th rowspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="left"></th><th colspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>Smoking N<sub>s</sub> = 36,518 (8.1%)</bold></th></tr><tr><th valign="middle" align="center"><bold>n</bold></th><th valign="middle" align="center"><bold>%</bold></th><th valign="middle" align="center"><bold>n</bold></th><th valign="middle" align="center"><bold>%</bold></th><th valign="middle" align="center"><bold>n</bold></th><th valign="middle" align="center"><bold>%</bold></th></tr></thead><tbody><tr><td colspan="9" valign="middle" align="left"><bold>Year (Baby&#x2019;s DOB)</bold></td></tr><tr><td valign="middle" align="left">2012</td><td valign="middle" align="center">91,732</td><td valign="middle" align="center">20.4</td><td valign="middle" align="center"></td><td valign="middle" align="center">83,322</td><td valign="middle" align="center">90.8*</td><td valign="middle" align="center"></td><td valign="middle" align="center">8,410</td><td valign="middle" align="center">9.2*</td></tr><tr><td valign="middle" align="left">2013</td><td valign="middle" align="center">89,095</td><td valign="middle" align="center">19.8</td><td valign="middle" align="center"></td><td valign="middle" align="center">81,506</td><td valign="middle" align="center">91.5*</td><td valign="middle" align="center"></td><td valign="middle" align="center">7,589</td><td valign="middle" align="center">8.5*</td></tr><tr><td valign="middle" align="left">2014</td><td valign="middle" align="center">89,664</td><td valign="middle" align="center">19.9</td><td valign="middle" align="center"></td><td valign="middle" align="center">82,427</td><td valign="middle" align="center">91.9*</td><td valign="middle" align="center"></td><td valign="middle" align="center">7,237</td><td valign="middle" align="center">8.1*</td></tr><tr><td valign="middle" align="left">2015</td><td valign="middle" align="center">88,759</td><td valign="middle" align="center">19.7</td><td valign="middle" align="center"></td><td valign="middle" align="center">81,955</td><td valign="middle" align="center">92.3*</td><td valign="middle" align="center"></td><td valign="middle" align="center">6,804</td><td valign="middle" align="center">7.7*</td></tr><tr><td valign="middle" align="left">2016</td><td valign="middle" align="center">90,340</td><td valign="middle" align="center">20.1</td><td valign="middle" align="center"></td><td valign="middle" align="center">83,862</td><td valign="middle" align="center">92.8*</td><td valign="middle" align="center"></td><td valign="middle" align="center">6,478</td><td valign="middle" align="center">7.2*</td></tr><tr><td colspan="9" valign="middle" align="left"><bold>Maternal age</bold></td></tr><tr><td valign="middle" align="left">Under 20</td><td valign="middle" align="center">9,754</td><td valign="middle" align="center">2.2</td><td valign="middle" align="center"></td><td valign="middle" align="center">7,085</td><td valign="middle" align="center">1.7</td><td valign="middle" align="center"></td><td valign="middle" align="center">2,669</td><td valign="middle" align="center">7.3</td></tr><tr><td valign="middle" align="left">20&#x2013;24</td><td valign="middle" align="center">50,808</td><td valign="middle" align="center">11.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">41,782</td><td valign="middle" align="center">10.1</td><td valign="middle" align="center"></td><td valign="middle" align="center">9,026</td><td valign="middle" align="center">24.7</td></tr><tr><td valign="middle" align="left">25&#x2013;29</td><td valign="middle" align="center">121,393</td><td valign="middle" align="center">27.0</td><td valign="middle" align="center"></td><td valign="middle" align="center">110,993</td><td valign="middle" align="center">26.9</td><td valign="middle" align="center"></td><td valign="middle" align="center">10,400</td><td valign="middle" align="center">28.5</td></tr><tr><td valign="middle" align="left">30&#x2013;34</td><td valign="middle" align="center">159,555</td><td valign="middle" align="center">35.5</td><td valign="middle" align="center"></td><td valign="middle" align="center">150,966</td><td valign="middle" align="center">36.5</td><td valign="middle" align="center"></td><td valign="middle" align="center">8,589</td><td valign="middle" align="center">23.5</td></tr><tr><td valign="middle" align="left">35 and over</td><td valign="middle" align="center">108,080</td><td valign="middle" align="center">24.0</td><td valign="middle" align="center"></td><td valign="middle" align="center">102246</td><td valign="middle" align="center">24.8</td><td valign="middle" align="center"></td><td valign="middle" align="center">5,834</td><td valign="middle" align="center">16.0</td></tr><tr><td valign="middle" align="left">Total</td><td valign="middle" align="center">449,590</td><td valign="middle" align="center">100</td><td valign="middle" align="center"></td><td valign="middle" align="center">413,072</td><td valign="middle" align="center">100</td><td valign="middle" align="center"></td><td valign="middle" align="center">36,518</td><td valign="middle" align="center">100</td></tr><tr><td colspan="9" valign="middle" align="left"><bold>Parity</bold></td></tr><tr><td valign="middle" align="left">0</td><td valign="middle" align="center">199,082</td><td valign="middle" align="center">44.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">186,760</td><td valign="middle" align="center">45.2</td><td valign="middle" align="center"></td><td valign="middle" align="center">12,322</td><td valign="middle" align="center">33.7</td></tr><tr><td valign="middle" align="left">1</td><td valign="middle" align="center">153,926</td><td valign="middle" align="center">34.2</td><td valign="middle" align="center"></td><td valign="middle" align="center">143,852</td><td valign="middle" align="center">34.8</td><td valign="middle" align="center"></td><td valign="middle" align="center">10,074</td><td valign="middle" align="center">27.6</td></tr><tr><td valign="middle" align="left">2</td><td valign="middle" align="center">62,100</td><td valign="middle" align="center">13.8</td><td valign="middle" align="center"></td><td valign="middle" align="center">55,308</td><td valign="middle" align="center">13.4</td><td valign="middle" align="center"></td><td valign="middle" align="center">6,792</td><td valign="middle" align="center">18.6</td></tr><tr><td valign="middle" align="left">3+</td><td valign="middle" align="center">34,278</td><td valign="middle" align="center">7.6</td><td valign="middle" align="center"></td><td valign="middle" align="center">26,959</td><td valign="middle" align="center">6.5</td><td valign="middle" align="center"></td><td valign="middle" align="center">7,319</td><td valign="middle" align="center">20.0</td></tr><tr><td valign="middle" align="left">Total</td><td valign="middle" align="center">449,386</td><td valign="middle" align="center">100</td><td valign="middle" align="center"></td><td valign="middle" align="center">412,879</td><td valign="middle" align="center">100</td><td valign="middle" align="center"></td><td valign="middle" align="center">36,507</td><td valign="middle" align="center">100</td></tr><tr><td colspan="9" valign="middle" align="left"><bold>SEIFA IRSD quintiles<sup>**</sup></bold></td></tr><tr><td valign="middle" align="left">1st &#x2013; most disadvantaged</td><td valign="middle" align="center">97,232</td><td valign="middle" align="center">21.6</td><td valign="middle" align="center"></td><td valign="middle" align="center">85,864</td><td valign="middle" align="center">20.8</td><td valign="middle" align="center"></td><td valign="middle" align="center">11,368</td><td valign="middle" align="center">31.1</td></tr><tr><td valign="middle" align="left">2nd</td><td valign="middle" align="center">81,278</td><td valign="middle" align="center">18.1</td><td valign="middle" align="center"></td><td valign="middle" align="center">70,972</td><td valign="middle" align="center">17.2</td><td valign="middle" align="center"></td><td valign="middle" align="center">10,306</td><td valign="middle" align="center">28.2</td></tr><tr><td valign="middle" align="left">3rd</td><td valign="middle" align="center">90,765</td><td valign="middle" align="center">20.2</td><td valign="middle" align="center"></td><td valign="middle" align="center">82,405</td><td valign="middle" align="center">19.9</td><td valign="middle" align="center"></td><td valign="middle" align="center">8,360</td><td valign="middle" align="center">22.9</td></tr><tr><td valign="middle" align="left">4th</td><td valign="middle" align="center">89,672</td><td valign="middle" align="center">19.9</td><td valign="middle" align="center"></td><td valign="middle" align="center">85,045</td><td valign="middle" align="center">20.6</td><td valign="middle" align="center"></td><td valign="middle" align="center">4,627</td><td valign="middle" align="center">12.7</td></tr><tr><td valign="middle" align="left">5th &#x2013; least disadvantaged</td><td valign="middle" align="center">87,577</td><td valign="middle" align="center">19.5</td><td valign="middle" align="center"></td><td valign="middle" align="center">85,894</td><td valign="middle" align="center">20.8</td><td valign="middle" align="center"></td><td valign="middle" align="center">1,683</td><td valign="middle" align="center">4.6</td></tr><tr><td valign="middle" align="left">Total</td><td valign="middle" align="center">446,524</td><td valign="middle" align="center">99.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">410,180</td><td valign="middle" align="center">99.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">36,344</td><td valign="middle" align="center">99.5</td></tr><tr><td colspan="9" valign="middle" align="left"><bold>Remoteness area</bold></td></tr><tr><td valign="middle" align="left">Major cities</td><td valign="middle" align="center">360,860</td><td valign="middle" align="center">80.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">337,783</td><td valign="middle" align="center">81.8</td><td valign="middle" align="center"></td><td valign="middle" align="center">23,077</td><td valign="middle" align="center">63.2</td></tr><tr><td valign="middle" align="left">Inner regional</td><td valign="middle" align="center">67,506</td><td valign="middle" align="center">15.0</td><td valign="middle" align="center"></td><td valign="middle" align="center">57,359</td><td valign="middle" align="center">13.9</td><td valign="middle" align="center"></td><td valign="middle" align="center">10,147</td><td valign="middle" align="center">27.8</td></tr><tr><td valign="middle" align="left">Outer regional</td><td valign="middle" align="center">16,546</td><td valign="middle" align="center">3.7</td><td valign="middle" align="center"></td><td valign="middle" align="center">13,662</td><td valign="middle" align="center">3.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">2,884</td><td valign="middle" align="center">7.9</td></tr><tr><td valign="middle" align="left">Remote</td><td valign="middle" align="center">1,401</td><td valign="middle" align="center">0.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">1193</td><td valign="middle" align="center">0.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">208</td><td valign="middle" align="center">0.6</td></tr><tr><td valign="middle" align="left">Very remote</td><td valign="middle" align="center">215</td><td valign="middle" align="center">0.0</td><td valign="middle" align="center"></td><td valign="middle" align="center">186</td><td valign="middle" align="center">0.0</td><td valign="middle" align="center"></td><td valign="middle" align="center">29</td><td valign="middle" align="center">0.1</td></tr><tr><td valign="middle" align="left">Total</td><td valign="middle" align="center">446,528</td><td valign="middle" align="center">99.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">410,183</td><td valign="middle" align="center">99.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">36,345</td><td valign="middle" align="center">99.6</td></tr><tr><td colspan="9" valign="middle" align="left"><bold>Hospital level</bold></td></tr><tr><td valign="middle" align="left">Tertiary</td><td valign="middle" align="center">132,913</td><td valign="middle" align="center">29.6</td><td valign="middle" align="center"></td><td valign="middle" align="center">122,386</td><td valign="middle" align="center">29.6</td><td valign="middle" align="center"></td><td valign="middle" align="center">10,527</td><td valign="middle" align="center">28.8</td></tr><tr><td valign="middle" align="left">Small and medium urban</td><td valign="middle" align="center">12,282</td><td valign="middle" align="center">2.7</td><td valign="middle" align="center"></td><td valign="middle" align="center">11,413</td><td valign="middle" align="center">2.8</td><td valign="middle" align="center"></td><td valign="middle" align="center">869</td><td valign="middle" align="center">2.4</td></tr><tr><td valign="middle" align="left">Large urban</td><td valign="middle" align="center">114,370</td><td valign="middle" align="center">25.4</td><td valign="middle" align="center"></td><td valign="middle" align="center">103,461</td><td valign="middle" align="center">25.0</td><td valign="middle" align="center"></td><td valign="middle" align="center">10,909</td><td valign="middle" align="center">29.9</td></tr><tr><td valign="middle" align="left">Small and medium regional</td><td valign="middle" align="center">47,989</td><td valign="middle" align="center">10.7</td><td valign="middle" align="center"></td><td valign="middle" align="center">39,744</td><td valign="middle" align="center">9.6</td><td valign="middle" align="center"></td><td valign="middle" align="center">8,245</td><td valign="middle" align="center">22.6</td></tr><tr><td valign="middle" align="left">Large regional</td><td valign="middle" align="center">30,878</td><td valign="middle" align="center">6.9</td><td valign="middle" align="center"></td><td valign="middle" align="center">26,171</td><td valign="middle" align="center">6.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">4,707</td><td valign="middle" align="center">12.9</td></tr><tr><td valign="middle" align="left">Private</td><td valign="middle" align="center">110,504</td><td valign="middle" align="center">24.6</td><td valign="middle" align="center"></td><td valign="middle" align="center">109,288</td><td valign="middle" align="center">26.5</td><td valign="middle" align="center"></td><td valign="middle" align="center">1,216</td><td valign="middle" align="center">3.3</td></tr><tr><td valign="middle" align="left">Other</td><td valign="middle" align="center">654</td><td valign="middle" align="center">0.1</td><td valign="middle" align="center"></td><td valign="middle" align="center">609</td><td valign="middle" align="center">0.1</td><td valign="middle" align="center"></td><td valign="middle" align="center">45</td><td valign="middle" align="center">0.1</td></tr><tr><td valign="middle" align="left">Total</td><td valign="middle" align="center">449,590</td><td valign="middle" align="center">100</td><td valign="middle" align="center"></td><td valign="middle" align="center">413,072</td><td valign="middle" align="center">99.9</td><td valign="middle" align="center"></td><td valign="middle" align="center">36,518</td><td valign="middle" align="center">100</td></tr><tr><td colspan="9" valign="middle" align="left"><bold>Chronic conditions<sup>^</sup></bold></td></tr><tr><td valign="middle" align="left">Yes</td><td valign="middle" align="center">11,425</td><td valign="middle" align="center">2.5</td><td valign="middle" align="center"></td><td valign="middle" align="center">9,866</td><td valign="middle" align="center">2.4</td><td valign="middle" align="center"></td><td valign="middle" align="center">1,559</td><td valign="middle" align="center">4.3</td></tr><tr><td colspan="9" valign="middle" align="left"><bold>Any hypertension</bold></td></tr><tr><td valign="middle" align="left">Yes</td><td valign="middle" align="center">36,571</td><td valign="middle" align="center">8.1</td><td valign="middle" align="center"></td><td valign="middle" align="center">33,659</td><td valign="middle" align="center">8.1</td><td valign="middle" align="center"></td><td valign="middle" align="center">2,912</td><td valign="middle" align="center">8.0</td></tr><tr><td colspan="9" valign="middle" align="left"><bold>Any diabetes</bold></td></tr><tr><td valign="middle" align="left">Yes</td><td valign="middle" align="center">55,127</td><td valign="middle" align="center">12.3</td><td valign="middle" align="center"></td><td valign="middle" align="center">51,295</td><td valign="middle" align="center">12.4</td><td valign="middle" align="center"></td><td valign="middle" align="center">3,832</td><td valign="middle" align="center">10.5</td></tr></tbody></table><table-wrap-foot><p>* Percentage of all births within each year.</p><p>**Socio-Economic Index for Areas &#x2013; Index of Relative Socio-Economic Disadvantage (SEIFA IRSD). When ranking areas within NSW in order of their relative disadvantage, the lowest 20% (most disadvantaged) fall in the 1<sup>st</sup> quintile and the highest 20% (least disadvantaged) fall in 5<sup>th</sup> quartile.</p><p>&#x005E;Chronic conditions encompasses renal, cardiac, thyroid, asthma, psychiatric, and autoimmune conditions [<xref ref-type="bibr" rid="ref-14">14</xref>].</p></table-wrap-foot></table-wrap><p>Overall rates of severe maternal morbidity and transfer to another hospital during the birth admission were low (&#x003C;3%) and both outcomes were lower among non-smoking mothers than mothers who smoked (<xref ref-type="table" rid="table-2">Table 2</xref>). These differences remained statistically significant after adjustment (<xref ref-type="table" rid="table-2">Table 2</xref>). Not smoking during pregnancy was associated with a 13% reduction in risk of severe maternal morbidity (adjusted Relative Risk, aRR: 0.87 (0.81,0.93)) and 8% lower risk for transfer during the birth admission (aRR 0.92 (0.86,0.99)).</p><table-wrap id="table-2"><label>Table 2:  Frequencies of maternal outcomes at the time of birth by smoking status during pregnancy</label><table frame="hsides" rules="groups"><thead><tr><th rowspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="left"></th><th colspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="left"><bold>All births N = 449,590</bold></th><th rowspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="left"></th><th colspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>Non-smoking N<sub>ns</sub> = 413,072</bold></th><th rowspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="left"></th><th colspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>Smoking N<sub>s</sub> = 36,518</bold></th><th rowspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="left"></th><th valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>Unadjusted</bold></th><th valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>Adjusted</bold></th></tr><tr><th valign="middle" align="center"><bold>n</bold></th><th valign="middle" align="center"><bold>%</bold></th><th valign="middle" align="center"><bold>n</bold></th><th valign="middle" align="center"><bold>%</bold></th><th valign="middle" align="center"><bold>n</bold></th><th valign="middle" align="center"><bold>%</bold></th><th valign="middle" align="center"><bold>RR (95% CI)</bold></th><th valign="middle" align="center"><bold>RR (95% CI)</bold></th></tr></thead><tbody><tr><td colspan="12" valign="middle" align="left"><bold>Severe maternal morbidity</bold></td></tr><tr><td valign="middle" align="left">Yes</td><td valign="middle" align="center">9,742</td><td valign="middle" align="center">2.2</td><td valign="middle" align="center"></td><td valign="middle" align="center">8,763</td><td valign="middle" align="center">2.1</td><td valign="middle" align="center"></td><td valign="middle" align="center">979</td><td valign="middle" align="center">2.7</td><td valign="middle" align="center"></td><td valign="middle" align="center">0.79 (0.74,0.85)</td><td valign="middle" align="center">0.87 (0.81,0.93)*</td></tr><tr><td colspan="12" valign="middle" align="left"><bold>Inter-hospital transfer</bold></td></tr><tr><td valign="middle" align="left">Yes</td><td valign="middle" align="center">7,302</td><td valign="middle" align="center">1.6</td><td valign="middle" align="center"></td><td valign="middle" align="center">6,398</td><td valign="middle" align="center">1.5</td><td valign="middle" align="center"></td><td valign="middle" align="center">904</td><td valign="middle" align="center">2.5</td><td valign="middle" align="center"></td><td valign="middle" align="center">0.63 (0.58,0.67)</td><td valign="middle" align="center">0.92 (0.86,0.99)**</td></tr></tbody></table><table-wrap-foot><p>*adjusted for maternal age, any hypertension, any diabetes, parity and socio-economic status (SEIFA).</p><p>** adjusted for maternal age, any hypertension, any diabetes, parity and remoteness area.</p></table-wrap-foot></table-wrap><p>Babies born to non-smoking mothers had substantially lower risks of all adverse perinatal outcomes, compared with babies born to mothers who reported smoking during their pregnancy (<xref ref-type="table" rid="table-3">Table 3</xref>). These differences remained statistically significant after adjusting for maternal age, socioeconomic status, parity, any hypertension and any diabetes. Adjusted relative risks varied from as low as 0.36 for being born with a birthweight lower than the third percentile for gestational age and sex, to 0.69 for being stillborn (<xref ref-type="table" rid="table-3">Table 3</xref>). As indicated by the PAFs (%) in <xref ref-type="table" rid="table-3">Table 3</xref>, between 3.7 and 11.4% of all these adverse perinatal outcomes were attributable to smoking in this cohort of babies.</p><table-wrap id="table-3"><label>Table 3:  Frequencies of perinatal outcomes among by maternal smoking status</label><table frame="hsides" rules="groups"><thead><tr><th rowspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="left"></th><th rowspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>NSW population</bold> <break/><bold>%</bold></th><th colspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>All births N = 449,590</bold></th><th colspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>Non-smoking N<sub>ns</sub> = 413,072</bold></th><th colspan="2" valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>Smoking N<sub>s</sub> = 36,518</bold></th><th valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>Unadjusted</bold></th><th valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>Adjusted<sup>*</sup></bold></th><th valign="middle" style="border-top: solid 1pt; border-bottom: solid 1pt" align="center"><bold>PAF (%)</bold></th></tr><tr><th valign="middle" align="center"><bold>n</bold></th><th valign="middle" align="center"><bold>%</bold></th><th valign="middle" align="center"><bold>n</bold></th><th valign="middle" align="center"><bold>%</bold></th><th valign="middle" align="center"><bold>n</bold></th><th valign="middle" align="center"><bold>%</bold></th><th valign="middle" align="center"><bold>RR (95% CI)</bold></th><th valign="middle" align="center"><bold>RR (95% CI)</bold></th><th valign="middle" align="center"></th></tr></thead><tbody><tr><td colspan="11" valign="middle" align="left"><bold>Preterm birth (&#x003C;37 weeks)</bold></td></tr><tr><td valign="middle" align="left">Yes</td><td valign="middle" align="center">8</td><td valign="middle" align="center">26,722</td><td valign="middle" align="center">5.9</td><td valign="middle" align="center">23,160</td><td valign="middle" align="center">5.6</td><td valign="middle" align="center">3,562</td><td valign="middle" align="center">9.8</td><td valign="middle" align="center">0.57 (0.56,0.60)</td><td valign="middle" align="center">0.58 (0.56,0.61)</td><td valign="middle" align="center">5.6</td></tr><tr><td colspan="11" valign="middle" align="left"><bold>SGA (&#x003C;3<sup>rd</sup> population centile)</bold></td></tr><tr><td valign="middle" align="left">Yes</td><td valign="middle" align="center">3</td><td valign="middle" align="center">10,826</td><td valign="middle" align="center">2.4</td><td valign="middle" align="center">8,890</td><td valign="middle" align="center">2.2</td><td valign="middle" align="center">1,936</td><td valign="middle" align="center">5.3</td><td valign="middle" align="center">0.40 (0.39,0.43)</td><td valign="middle" align="center">0.36 (0.34,0.38)</td><td valign="middle" align="center">11.4</td></tr><tr><td colspan="11" valign="middle" align="left"><bold>SGA (&#x003C;10<sup>th</sup> population centile)</bold></td></tr><tr><td valign="middle" align="left">Yes</td><td valign="middle" align="center">10</td><td valign="middle" align="center">41,679</td><td valign="middle" align="center">9.3</td><td valign="middle" align="center">35,797</td><td valign="middle" align="center">8.7</td><td valign="middle" align="center">5,882</td><td valign="middle" align="center">16.1</td><td valign="middle" align="center">0.54 (0.52,0.55)</td><td valign="middle" align="center">0.48 (0.47,0.50)</td><td valign="middle" align="center">7.3</td></tr><tr><td colspan="2" valign="middle" align="left"><bold>Severe neonatal morbidity</bold></td><td colspan="9" valign="middle" align="center"><bold>Among live births only</bold></td></tr><tr><td valign="middle" align="left">Yes</td><td valign="middle" align="center">5</td><td valign="middle" align="center">19,778</td><td valign="middle" align="center">4.4</td><td valign="middle" align="center">17,487</td><td valign="middle" align="center">4.2</td><td valign="middle" align="center">2,291</td><td valign="middle" align="center">6.3</td><td valign="middle" align="center">0.67 (0.64,0.70)</td><td valign="middle" align="center">0.68 (0.65,0.71)</td><td valign="middle" align="center">3.7</td></tr><tr><td colspan="2" valign="middle" align="left"><bold>Perinatal death</bold></td><td colspan="9" valign="middle" align="center"><bold>Rate per 1,000 total births</bold></td></tr><tr><td valign="middle" align="left">Yes</td><td valign="middle" align="center">8</td><td valign="middle" align="center">3,469</td><td valign="middle" align="center">0.8</td><td valign="middle" align="center">3,043</td><td valign="middle" align="center">0.7</td><td valign="middle" align="center">426</td><td valign="middle" align="center">1.2</td><td valign="middle" align="center">0.63 (0.57,0.70)</td><td valign="middle" align="center">0.68 (0.61,0.76)</td><td valign="middle" align="center">3.9</td></tr><tr><td valign="middle" align="left">Stillborn</td><td valign="middle" align="center">6</td><td valign="middle" align="center">2,486</td><td valign="middle" align="center">0.6</td><td valign="middle" align="center">2,192</td><td valign="middle" align="center">0.5</td><td valign="middle" align="center">294</td><td valign="middle" align="center">0.8</td><td valign="middle" align="center">0.66 (0.58,0.74)</td><td valign="middle" align="center">0.69 (0.60,0.78)</td><td valign="middle" align="center">3.7</td></tr><tr><td colspan="2" valign="middle" align="left"></td><td colspan="9" valign="middle" align="center"><bold>Rate per 1,000 live births</bold></td></tr><tr><td valign="middle" align="left">Neonatal death</td><td valign="middle" align="center">2</td><td valign="middle" align="center">983</td><td valign="middle" align="center">0.2</td><td valign="middle" align="center">851</td><td valign="middle" align="center">0.2</td><td valign="middle" align="center">132</td><td valign="middle" align="center">0.4</td><td valign="middle" align="center">0.57 (0.47,0.68)</td><td valign="middle" align="center">0.66 (0.54,0.81)</td><td valign="middle" align="center">4.6</td></tr></tbody></table><table-wrap-foot><p>* Adjusted for maternal age, any hypertension, any diabetes, parity and socioeconomic status.</p><p>** SGA: small for gestational age.</p></table-wrap-foot></table-wrap></sec><sec><title>Discussion</title><p>This study quantifies the benefits of not smoking during pregnancy for non-Aboriginal mothers and their babies in NSW. The reduction in risk of all adverse perinatal outcomes for babies whose mothers did not smoke during pregnancy was considerable. After adjusting for the effects of maternal age, socioeconomic status, parity, any hypertension and any diabetes, babies born to mothers who reported not smoking during pregnancy had a 31% lower risk of being stillborn, 34% less risk of dying in the first 28 days of life, a 42% lower risk of being born preterm, 52% less risk of being born small for gestational age (&#x003C; percentile) and a 64% lower risk of being born with a birthweight lower than the third percentile for gestational age and sex. The PAFs for the adverse perinatal outcomes highlight the potential for the reduction in the rates of these adverse events in NSW if smoking rates during pregnancy could be reduced. Currently there is a focus in Australian maternity care on reducing the rates of stillbirth (The Safer Baby Bundle) [<xref ref-type="bibr" rid="ref-15">15</xref>] and preterm birth (the focus of the Australian Preterm Birth Prevention Alliance) [<xref ref-type="bibr" rid="ref-16">16</xref>]. Our findings show that among singleton babies born to non-Aboriginal women in NSW, 5.6% of preterm births and 3.7% of stillbirths are attributable to maternal smoking during pregnancy. These fractions are likely to be higher in areas with higher smoking rates. Addressing maternal smoking is an important contributor to reducing both stillbirth and preterm birth rates. Across Australia, rates of smoking during pregnancy range from 5.6% in the Australian Capital Territory to 20.7% in the Northern Territory, with an overall rate of 10.2% in 2019 [<xref ref-type="bibr" rid="ref-17">17</xref>] Although all states and territories have seen a reduction in smoking over the last decade, in some areas smoking rates have started to increase. Reducing smoking rates in regions with higher smoking rates could have greater even returns in stillbirth and preterm birth prevention.</p><p>Consistent with the widely-documented association between smoking and socioeconomic status, non-smoking mothers tended to be less disadvantaged, older, reside in cities and have had fewer previous pregnancies than mothers who smoked during their pregnancy. Almost one third of the mothers who smoked lived in an area classified as the most disadvantaged SEIFA quintile and/or were aged less than 25 years. Mothers who are young and/or of low socioeconomic status are known to be at higher risk of smoking and less likely to quit, both in Australia and overseas [<xref ref-type="bibr" rid="ref-2">2</xref>, <xref ref-type="bibr" rid="ref-18">18</xref>&#x2013;<xref ref-type="bibr" rid="ref-20">20</xref>]. However, similarly to the findings of a Victorian study which considered absolute and relative risk reduction in tobacco control policy [<xref ref-type="bibr" rid="ref-18">18</xref>], each high risk group comprised only a small proportion of mothers, with the greatest <italic>number</italic> of smokers in the 25&#x2013;29 year age group and resident of a major city. The authors of the Victorian study commented that high risk group approaches only have the potential to make very small reductions in overall smoking during pregnancy rates, and argue that although these priority groups should not be forgotten, they must not detract from population-wide and cost-effective policies that have been shown to reduce the prevalence of antenatal smoking [<xref ref-type="bibr" rid="ref-18">18</xref>]. Elsewhere this is referred to as the &#x2018;Prevention Paradox&#x2019; [<xref ref-type="bibr" rid="ref-21">21</xref>]. A recent study in NSW also illustrated the benefit of targeting groups with higher numbers, rather than rates, of smokers [<xref ref-type="bibr" rid="ref-2">2</xref>]. The same study also highlighted that smoking rates in NSW are not distributed evenly across the 15 Local Health Districts and showed that over half the mothers who smoked during their pregnancy lived in just four Local Health Districts [<xref ref-type="bibr" rid="ref-2">2</xref>]. Targeting these four Local Health Districts with an effective program to reduce smoking in pregnancy has the greatest potential to reduce adverse perinatal outcomes, including stillbirth and preterm birth.</p><p>As the costs of any intervention need to be balanced against the potential benefits, the results of this study are potentially important inputs into modelling the impact of smoking cessation interventions in NSW and broader economic analyses that can inform strategic decision making. Births with adverse events such as preterm birth and stillbirth, are associated with increased healthcare costs [<xref ref-type="bibr" rid="ref-22">22</xref>, <xref ref-type="bibr" rid="ref-23">23</xref>] and savings through avoiding these via reductions in smoking can be balanced against the costs associated with an intervention. A recent American study by Bacheller et al used similar estimates from the American population to assess the cost-effectiveness of a hypothetical smoking cessation intervention [<xref ref-type="bibr" rid="ref-24">24</xref>]. As there are differences between smoking rates, demographics and healthcare provision and access between Australia and the United States, it is important that these data be available on a local population.</p><p>The results of this study could be used to enhance current training for NSW Health staff on delivering smoking cessation support during pregnancy, including online modules offered by The Health Education &#x0026; Training Institute [<xref ref-type="bibr" rid="ref-25">25</xref>]. Although the risks of smoking during pregnancy are well documented, presentation of the benefits of not smoking may be more beneficial in encouraging pregnant women to stop smoking. A recent review of attitudes towards smoking cessation programs found that healthcare workers found it difficult to communicate health advice on smoking during pregnancy without making the pregnant woman feel guilty and damaging the relationship with the pregnant woman [<xref ref-type="bibr" rid="ref-26">26</xref>]. The same study reported pregnant women feeling pressured and stigmatized for smoking. Positive reframing of the situation to present the expected benefits of not smoking may be more effective in prompting behavior change [<xref ref-type="bibr" rid="ref-27">27</xref>]. Highlighting the proportion of small for gestational age and other adverse outcomes that would be avoided if antenatal smoking rates were negligible could be particularly motivating at both the health service and individual levels.</p><p>Results might also inform an NSW-wide plan for enhancing clinician training, clinical care standards to improve the management of smoking before, during and after pregnancy, and monitoring and management of the performance of NSW Health services. Reducing antenatal smoking and increasing quitting during pregnancy are key performance targets for Local Health Districts [<xref ref-type="bibr" rid="ref-28">28</xref>]. The findings of this study highlight the flow on benefits to the health service of lower rates of smoking during pregnancy in terms of adverse outcomes and associated healthcare burden avoided, which underscores the public health significance of the afore-mentioned performance targets and may provide an additional incentive to change.</p><p>In addition to providing system level insights, this study provides local information, which can be used by health professionals to further engage the community on the benefits of not smoking for mothers and their babies. A similar study [<xref ref-type="bibr" rid="ref-4">4</xref>], focusing on the benefits of not smoking in Aboriginal women is being used to inform culturally relevant educational material for that population. The data from the current study can likewise be used to tailor advice given to local women. Studies have found that policy makers, practitioners and researchers tend to value locally generated evidence over studies conducted abroad [<xref ref-type="bibr" rid="ref-29">29</xref>, <xref ref-type="bibr" rid="ref-30">30</xref>].</p><p>A key strength of this study is that it was co-produced by academic researchers at Women and Babies Research and policy makers and practitioner-scholars at the NSW Ministry of Health, from conception and planning through to results dissemination and translation. This way of working has been shown to increase the policy-relevance of research, the translation of results into practice, and the exchange of knowledge and skills [<xref ref-type="bibr" rid="ref-31">31</xref>&#x2013;<xref ref-type="bibr" rid="ref-34">34</xref>]. Another strength of this study is that it was a large population-based cohort study capturing data from almost half a million babies. The main limitation is the lack of information on variables of interest such as heaviness of smoking as well as potential confounders such as alcohol consumption. In addition, smoking status was based on self-report supplemented by diagnosis codes within the medical record. As such, this might underestimate the smoking rate and bias effects towards the null.</p></sec><sec><title>Conclusion</title><p>Babies born to mothers who reported not smoking during their pregnancy were at a significantly reduced risk of all adverse maternal and perinatal outcomes compared with those born to mothers of similar demographics who reported smoking during their pregnancy. Mothers who reported not smoking during pregnancy had a small reduction in their risk of morbidity and of being transferred to another hospital.</p></sec><sec sec-type="supplementary-material"><title>Supplementary Files</title><supplementary-material id="sup-a"><label>Supplementary Appendices</label> <media mimetype="application" mime-subtype="pdf" xlink:href="ijpds-06-1699-s001.pdf"/></supplementary-material></sec></body><back><ack><title>Acknowledgements</title><p>We thank the data custodians for access to the population health data and the NSW Centre for Health Record Linkage for linking the datasets. This work was supported by the Prevention Research Support Program, funded by the NSW Ministry of Health. We would also like to acknowledge Jo Mitchell for her role in the early stages of this study.</p></ack><sec><title>Ethics statement</title><p>Ethics approval was obtained from the NSW Population and Health Services Research Ethics Committee (HREC/12/ CIPHS/85). A waiver of informed consent was granted by the Ethics Committee.</p></sec><ref-list><title>References</title><ref id="ref-1"><label>1</label><mixed-citation publication-type="other"><collab>Office of the Secretary NSW Ministry of Health</collab>. <article-title>The NSW State Health Plan Towards 2021</article-title>; <year>2014</year>.</mixed-citation></ref><ref id="ref-2"><label>2</label><mixed-citation publication-type="journal"><string-name><surname>Patterson</surname> <given-names>JA</given-names></string-name>, <string-name><surname>Torvaldsen</surname> <given-names>S</given-names></string-name>, <string-name><surname>Nippita</surname> <given-names>TA</given-names></string-name>, <string-name><surname>Ford</surname> <given-names>JB</given-names></string-name>, <string-name><surname>Morris</surname> <given-names>JM</given-names></string-name>. <article-title>Determining a strategy to reduce smoking in pregnancy</article-title>. <source>Aust N Z J Obstet Gynaecol</source>. <year>2020</year>;<volume>60</volume>(<issue>6</issue>):<fpage>935</fpage>&#x2013;<lpage>41</lpage>. <pub-id pub-id-type="doi">10.1111/ajo.13205</pub-id></mixed-citation></ref><ref id="ref-3"><label>3</label><mixed-citation publication-type="website"><collab>Centre for Epidemiology and Evidence</collab>. <article-title>HealthStats: Smoking in pregnancy Sydney</article-title><year>2021</year> [Available from: <uri>http://www.healthstats.nsw.gov.au/Indicator/mab_smo_cat/mab_smo_cat</uri>].</mixed-citation></ref><ref id="ref-4"><label>4</label><mixed-citation publication-type="journal"><string-name><surname>McInerney</surname> <given-names>C</given-names></string-name>, <string-name><surname>Ibiebele</surname> <given-names>I</given-names></string-name>, <string-name><surname>Ford</surname> <given-names>JB</given-names></string-name>, <string-name><surname>Randall</surname> <given-names>D</given-names></string-name>, <string-name><surname>Morris</surname> <given-names>JM</given-names></string-name>, <string-name><surname>Meharg</surname> <given-names>D</given-names></string-name>, <etal>et al</etal>. <article-title>Benefits of not smoking during pregnancy for Australian Aboriginal and Torres Strait Islander women and their babies: a retrospective cohort study using linked data</article-title>. <source>BMJ Open</source>. <year>2019</year>;<volume>9</volume>(<issue>11</issue>):<fpage>e032763</fpage>. <pub-id pub-id-type="doi">10.1136/bmjopen-2019-032763</pub-id></mixed-citation></ref><ref id="ref-5"><label>5</label><mixed-citation publication-type="journal"><string-name><surname>McInerney</surname> <given-names>C</given-names></string-name>, <string-name><surname>Ibiebele</surname> <given-names>I</given-names></string-name>, <string-name><surname>Torvaldsen</surname> <given-names>S</given-names></string-name>, <string-name><surname>Ford</surname> <given-names>JB</given-names></string-name>, <string-name><surname>Morris</surname> <given-names>JM</given-names></string-name>, <string-name><surname>Nelson</surname> <given-names>M</given-names></string-name>, <etal>et al</etal>. <article-title>Defining a study population using enhanced reporting of Aboriginality and the effects on study outcomes</article-title>. <source>Int J Popul Data Sci</source>. <year>2020</year>;<volume>5</volume>(<issue>1</issue>):<fpage>1114</fpage>. <pub-id pub-id-type="doi">10.23889/ijpds.v5i1.1114</pub-id></mixed-citation></ref><ref id="ref-6"><label>6</label><mixed-citation publication-type="website"><collab>Centre for Health Record Linkage</collab>. <article-title>CHeReL Quality Assurance Procedures for Record Linkage</article-title>. <uri>http://www.cherel.org.au/quality-assurance</uri> [Internet]. <month>October</month> <year>2016</year>.</mixed-citation></ref><ref id="ref-7"><label>7</label><mixed-citation publication-type="website"><collab>The Independent Hospital Pricing Authority</collab>. <article-title>ICD-10-AM/ACHI/ACS 2021 [9/11/2021]</article-title>. Available from: <uri>https://www.ihpa.gov.au/what-we-do/icd-10-am-achi-acs-current-edition</uri>.</mixed-citation></ref><ref id="ref-8"><label>8</label><mixed-citation publication-type="journal"><string-name><surname>Havard</surname> <given-names>A</given-names></string-name>, <string-name><surname>Jorm</surname> <given-names>LR</given-names></string-name>, <string-name><surname>Lujic</surname> <given-names>S</given-names></string-name>. <article-title>Risk adjustment for smoking identified through tobacco use diagnoses in hospital data: a validation study</article-title>. <source>PLoS One</source>. <year>2014</year>;<volume>9</volume>(<issue>4</issue>):<fpage>e95029</fpage>. <pub-id pub-id-type="doi">10.1371/journal.pone.0095029</pub-id></mixed-citation></ref><ref id="ref-9"><label>9</label><mixed-citation publication-type="journal"><string-name><surname>Roberts</surname> <given-names>CL</given-names></string-name>, <string-name><surname>Cameron</surname> <given-names>CA</given-names></string-name>, <string-name><surname>Bell</surname> <given-names>JC</given-names></string-name>, <string-name><surname>Algert</surname> <given-names>CS</given-names></string-name>, <string-name><surname>Morris</surname> <given-names>JM</given-names></string-name>. <article-title>Measuring maternal morbidity in routinely collected health data: development and validation of a maternal morbidity outcome indicator</article-title>. <source>Med Care</source>. <year>2008</year>;<volume>46</volume>(<issue>8</issue>):<fpage>786</fpage>&#x2013;<lpage>94</lpage>. <pub-id pub-id-type="doi">10.1097/MLR.0b013e318178eae4</pub-id></mixed-citation></ref><ref id="ref-10"><label>10</label><mixed-citation publication-type="journal"><string-name><surname>Dobbins</surname> <given-names>TA</given-names></string-name>, <string-name><surname>Sullivan</surname> <given-names>EA</given-names></string-name>, <string-name><surname>Roberts</surname> <given-names>CL</given-names></string-name>, <string-name><surname>Simpson</surname> <given-names>JM</given-names></string-name>. <article-title>Australian national birthweight percentiles by sex and gestational age, 1998-2007</article-title>. <source>Med J Aust</source>. <year>2012</year>;<volume>197</volume>(<issue>5</issue>):<fpage>291</fpage>&#x2013;<lpage>4</lpage>. <pub-id pub-id-type="doi">10.5694/mja11.11331</pub-id></mixed-citation></ref><ref id="ref-11"><label>11</label><mixed-citation publication-type="journal"><string-name><surname>Lain</surname> <given-names>SJ</given-names></string-name>, <string-name><surname>Algert</surname> <given-names>CS</given-names></string-name>, <string-name><surname>Nassar</surname> <given-names>N</given-names></string-name>, <string-name><surname>Bowen</surname> <given-names>JR</given-names></string-name>, <string-name><surname>Roberts</surname> <given-names>CL</given-names></string-name>. <article-title>Incidence of severe adverse neonatal outcomes: use of a composite indicator in a population cohort</article-title>. <source>Matern Child Health J</source>. <year>2012</year>;<volume>16</volume>(<issue>3</issue>):<fpage>600</fpage>&#x2013;<lpage>8</lpage>. <pub-id pub-id-type="doi">10.1007/s10995-011-0797-6</pub-id></mixed-citation></ref><ref id="ref-12"><label>12</label><mixed-citation publication-type="journal"><string-name><surname>Falster</surname> <given-names>MO</given-names></string-name>, <string-name><surname>Roberts</surname> <given-names>CL</given-names></string-name>, <string-name><surname>Ford</surname> <given-names>J</given-names></string-name>, <string-name><surname>Morris</surname> <given-names>J</given-names></string-name>, <string-name><surname>Kinnear</surname> <given-names>A</given-names></string-name>, <string-name><surname>Nicholl</surname> <given-names>M</given-names></string-name>. <article-title>Development of a maternity hospital classification for use in perinatal research</article-title>. <source>NSW Public Health Bull</source>. <year>2012</year>;<volume>23</volume>(<issue>1&#x2013;2</issue>):<fpage>12</fpage>&#x2013;<lpage>6</lpage></mixed-citation></ref><ref id="ref-13"><label>13</label><mixed-citation publication-type="other"><collab>SAS Institute</collab>. <article-title>SAS for Windows 9.4. Cary, NC, USA</article-title>.</mixed-citation></ref><ref id="ref-14"><label>14</label><mixed-citation publication-type="journal"><string-name><surname>Chen</surname> <given-names>JS</given-names></string-name>, <string-name><surname>Roberts</surname> <given-names>CL</given-names></string-name>, <string-name><surname>Simpson</surname> <given-names>JM</given-names></string-name>, <string-name><surname>Ford</surname> <given-names>JB</given-names></string-name>. <article-title>Use of hospitalisation history (lookback) to determine prevalence of chronic diseases: impact on modelling of risk factors for haemorrhage in pregnancy</article-title>. <source>BMC Med Res Methodol</source>. <year>2011</year>;<volume>11</volume>:<fpage>68</fpage>. <pub-id pub-id-type="doi">10.1186/1471-2288-11-68</pub-id></mixed-citation></ref><ref id="ref-15"><label>15</label><mixed-citation publication-type="website"><collab>Stillbirth Centre of Research Excellence</collab>. <article-title>Safer Baby Bundle</article-title> <year>2019</year> [Available from: <uri>https://www.stillbirthcre.org.au/safer-baby-bundle/</uri>].</mixed-citation></ref><ref id="ref-16"><label>16</label><mixed-citation publication-type="website"><collab>Australian Preterm Birth Prevention Alliance</collab>. <article-title>Australian Preterm Birth Prevention Alliance</article-title> <year>2020</year> [Available from: <uri>https://www.pretermalliance.com.au/</uri>].</mixed-citation></ref><ref id="ref-17"><label>17</label><mixed-citation publication-type="website"><collab>Australian Institute of Health and Welfare</collab>. <article-title>Australia&#x2019;s Mothers and Babies [11/10/2021]</article-title>. Available from: <uri>https://www.aihw.gov.au/reports/mothers-babies/australias-mothers-babies/contents/antenatal-period/smoking</uri>.</mixed-citation></ref><ref id="ref-18"><label>18</label><mixed-citation publication-type="journal"><string-name><surname>Grills</surname> <given-names>N</given-names></string-name>, <string-name><surname>Bolam</surname> <given-names>B</given-names></string-name>, <string-name><surname>Piers</surname> <given-names>LS</given-names></string-name>. <article-title>Balancing absolute and relative risk reduction in tobacco control policy: the example of antenatal smoking in Victoria, Australia</article-title>. <source>Aust N Z J Public Health</source>. <year>2010</year>;<volume>34</volume>(<issue>4</issue>):<fpage>374</fpage>&#x2013;<lpage>8</lpage>. <pub-id pub-id-type="doi">10.1111/j.1753-6405.2010.00569.x</pub-id></mixed-citation></ref><ref id="ref-19"><label>19</label><mixed-citation publication-type="journal"><string-name><surname>Mohsin</surname> <given-names>M</given-names></string-name>, <string-name><surname>Bauman</surname> <given-names>AE</given-names></string-name>, <string-name><surname>Forero</surname> <given-names>R</given-names></string-name>. <article-title>Socioeconomic correlates and trends in smoking in pregnancy in New South Wales, Australia</article-title>. <source>J Epidemiol Community Health</source>. <year>2011</year>;<volume>65</volume>(<issue>8</issue>):<fpage>727</fpage>&#x2013;<lpage>32</lpage>. <pub-id pub-id-type="doi">10.1136/jech.2009.104232</pub-id></mixed-citation></ref><ref id="ref-20"><label>20</label><mixed-citation publication-type="journal"><string-name><surname>Reitan</surname> <given-names>T</given-names></string-name>, <string-name><surname>Callinan</surname> <given-names>S</given-names></string-name>. <article-title>Changes in Smoking Rates Among Pregnant Women and the General Female Population in Australia, Finland, Norway, and Sweden</article-title>. <source>Nicotine Tob Res</source>. <year>2017</year>;<volume>19</volume>(<issue>3</issue>):<fpage>282</fpage>&#x2013;<lpage>9</lpage>. <pub-id pub-id-type="doi">10.1093/ntr/ntw188</pub-id></mixed-citation></ref><ref id="ref-21"><label>21</label><mixed-citation publication-type="journal"><string-name><surname>Rose</surname> <given-names>G</given-names></string-name>. <article-title>Strategy of prevention: lessons from cardiovascular disease</article-title>. <source>Br Med J (Clin Res Ed)</source>. <year>1981</year>;<volume>282</volume>(<issue>6279</issue>):<fpage>1847</fpage>&#x2013;<lpage>51</lpage>. <pub-id pub-id-type="doi">10.1136/bmj.282.6279.1847</pub-id></mixed-citation></ref><ref id="ref-22"><label>22</label><mixed-citation publication-type="journal"><string-name><surname>Callander</surname> <given-names>EJ</given-names></string-name>, <string-name><surname>Thomas</surname> <given-names>J</given-names></string-name>, <string-name><surname>Fox</surname> <given-names>H</given-names></string-name>, <string-name><surname>Ellwood</surname> <given-names>D</given-names></string-name>, <string-name><surname>Flenady</surname> <given-names>V</given-names></string-name>. <article-title>What are the costs of stillbirth? Capturing the direct health care and macroeconomic costs in Australia</article-title>. <source>Birth</source>. <year>2020</year>;<volume>47</volume>(<issue>2</issue>):<fpage>183</fpage>&#x2013;<lpage>90</lpage>. <pub-id pub-id-type="doi">10.1111/birt.12469</pub-id></mixed-citation></ref><ref id="ref-23"><label>23</label><mixed-citation publication-type="journal"><string-name><surname>Owen</surname> <given-names>KB</given-names></string-name>, <string-name><surname>Ibiebele</surname> <given-names>I</given-names></string-name>, <string-name><surname>Simpson</surname> <given-names>JM</given-names></string-name>, <string-name><surname>Morton</surname> <given-names>RL</given-names></string-name>, <string-name><surname>Morris</surname> <given-names>JM</given-names></string-name>, <string-name><surname>Torvaldsen</surname> <given-names>S</given-names></string-name>. <article-title>Comparison of costs related to infant hospitalisations for spontaneous, induced and Caesarean births: population-based cohort study</article-title>. <source>Aust Health Rev</source>. <year>2021</year>;<volume>45</volume>(<issue>4</issue>):<fpage>418</fpage>&#x2013;<lpage>24</lpage>. <pub-id pub-id-type="doi">10.1071/AH20237</pub-id></mixed-citation></ref><ref id="ref-24"><label>24</label><mixed-citation publication-type="journal"><string-name><surname>Bacheller</surname> <given-names>HL</given-names></string-name>, <string-name><surname>Hersh</surname> <given-names>AR</given-names></string-name>, <string-name><surname>Caughey</surname> <given-names>AB</given-names></string-name>. <article-title>Behavioral Smoking Cessation Counseling During Pregnancy: A Cost-Effectiveness Analysis</article-title>. <source>Obstet Gynecol</source>. <year>2021</year>;<volume>137</volume>(<issue>4</issue>):<fpage>703</fpage>&#x2013;<lpage>12</lpage>. <pub-id pub-id-type="doi">10.1097/AOG.0000000000004327</pub-id></mixed-citation></ref><ref id="ref-25"><label>25</label><mixed-citation publication-type="website"><collab>Health Education and Training</collab>. <article-title>Health Education and Training 2021 [16/08/2021]</article-title>. Available from: <uri>https://www.heti.nsw.gov.au/about-heti</uri>.</mixed-citation></ref><ref id="ref-26"><label>26</label><mixed-citation publication-type="journal"><string-name><surname>Kumar</surname> <given-names>R</given-names></string-name>, <string-name><surname>Stevenson</surname> <given-names>L</given-names></string-name>, <string-name><surname>Jobling</surname> <given-names>J</given-names></string-name>, <string-name><surname>Bar-Zeev</surname> <given-names>Y</given-names></string-name>, <string-name><surname>Eftekhari</surname> <given-names>P</given-names></string-name>, <string-name><surname>Gould</surname> <given-names>GS</given-names></string-name>. <article-title>Health providers&#x2019; and pregnant women&#x2019;s perspectives about smoking cessation support: a COM-B analysis of a global systematic review of qualitative studies</article-title>. <source>BMC Pregnancy Childbirth</source>. <year>2021</year>;<volume>21</volume>(<issue>1</issue>):<fpage>550</fpage>. <pub-id pub-id-type="doi">10.1186/s12884-021-03773-x</pub-id></mixed-citation></ref><ref id="ref-27"><label>27</label><mixed-citation publication-type="journal"><string-name><surname>Gallagher</surname> <given-names>KM</given-names></string-name>, <string-name><surname>Updegraff</surname> <given-names>JA</given-names></string-name>. <article-title>Health message framing effects on attitudes, intentions, and behavior: a meta-analytic review</article-title>. <source>Ann Behav Med</source>. <year>2012</year>;<volume>43</volume>(<issue>1</issue>):<fpage>101</fpage>&#x2013;<lpage>16</lpage>. <pub-id pub-id-type="doi">10.1007/s12160-011-9308-7</pub-id></mixed-citation></ref><ref id="ref-28"><label>28</label><mixed-citation publication-type="website"><collab>NSW Health</collab>. <article-title>Performance Framework Schedule E: Performance against Strategies and Objective 2021 [17/08/2021]</article-title>. Available from: <uri>https://www.health.nsw.gov.au/Performance/Documents/service-indicators-measures.pdf</uri>.</mixed-citation></ref><ref id="ref-29"><label>29</label><mixed-citation publication-type="journal"><string-name><surname>Huckel Schneider</surname> <given-names>C</given-names></string-name>, <string-name><surname>Milat</surname> <given-names>AJ</given-names></string-name>, <string-name><surname>Moore</surname> <given-names>G</given-names></string-name>. <article-title>Barriers and facilitators to evaluation of health policies and programs: Policymaker and researcher perspectives</article-title>. <source>Eval Program Plann</source>. <year>2016</year>;<volume>58</volume>:<fpage>208</fpage>&#x2013;<lpage>15</lpage>. <pub-id pub-id-type="doi">10.1016/j.evalprogplan.2016.06.011</pub-id></mixed-citation></ref><ref id="ref-30"><label>30</label><mixed-citation publication-type="journal"><string-name><surname>Milat</surname> <given-names>AJ</given-names></string-name>, <string-name><surname>King</surname> <given-names>L</given-names></string-name>, <string-name><surname>Newson</surname> <given-names>R</given-names></string-name>, <string-name><surname>Wolfenden</surname> <given-names>L</given-names></string-name>, <string-name><surname>Rissel</surname> <given-names>C</given-names></string-name>, <string-name><surname>Bauman</surname> <given-names>A</given-names></string-name>, <etal>et al</etal>. <article-title>Increasing the scale and adoption of population health interventions: experiences and perspectives of policy makers, practitioners, and researchers</article-title>. <source>Health Res Policy Syst</source>. <year>2014</year>;<volume>12</volume>(<issue>1</issue>):<fpage>18</fpage>. <pub-id pub-id-type="doi">10.1186/1478-4505-12-18</pub-id></mixed-citation></ref><ref id="ref-31"><label>31</label><mixed-citation publication-type="journal"><string-name><surname>Bullock</surname> <given-names>A</given-names></string-name>, <string-name><surname>Morris</surname> <given-names>ZS</given-names></string-name>, <string-name><surname>Atwell</surname> <given-names>C</given-names></string-name>. <article-title>Collaboration between health services managers and researchers: making a difference?</article-title> <source>J Health Serv Res Policy</source>. <year>2012</year>;<supplement>17</supplement> Suppl <volume>2</volume>:<fpage>2</fpage>&#x2013;<lpage>10</lpage>. <pub-id pub-id-type="doi">10.1258/jhsrp.2011.011099</pub-id></mixed-citation></ref><ref id="ref-32"><label>32</label><mixed-citation publication-type="journal"><string-name><surname>Jackson</surname> <given-names>CL</given-names></string-name>, <string-name><surname>Greenhalgh</surname> <given-names>T</given-names></string-name>. <article-title>Co-creation: a new approach to optimising research impact?</article-title> <source>Med J Aust</source>. <year>2015</year>;<volume>203</volume>(<issue>7</issue>):<fpage>283</fpage>&#x2013;<lpage>4</lpage>. <pub-id pub-id-type="doi">10.5694/mja15.00219</pub-id></mixed-citation></ref><ref id="ref-33"><label>33</label><mixed-citation publication-type="journal"><string-name><surname>Mitchell</surname> <given-names>P</given-names></string-name>, <string-name><surname>Pirkis</surname> <given-names>J</given-names></string-name>, <string-name><surname>Hall</surname> <given-names>J</given-names></string-name>, <string-name><surname>Haas</surname> <given-names>M</given-names></string-name>. <article-title>Partnerships for knowledge exchange in health services research, policy and practice</article-title>. <source>J Health Serv Res Policy</source>. <year>2009</year>;<volume>14</volume>(<issue>2</issue>):<fpage>104</fpage>&#x2013;<lpage>11</lpage>. <pub-id pub-id-type="doi">10.1258/jhsrp.2008.008091</pub-id></mixed-citation></ref><ref id="ref-34"><label>34</label><mixed-citation publication-type="journal"><string-name><surname>Morris</surname> <given-names>ZS</given-names></string-name>, <string-name><surname>Bullock</surname> <given-names>A</given-names></string-name>, <string-name><surname>Atwell</surname> <given-names>C</given-names></string-name>. <article-title>Developing engagement, linkage and exchange between health services managers and researchers: Experience from the UK</article-title>. <source>J Health Serv Res Policy</source>. <year>2013</year>;<volume>18</volume>(<supplement>1</supplement> Suppl):<fpage>23</fpage>&#x2013;<lpage>9</lpage>. <pub-id pub-id-type="doi">10.1177/1355819613476863</pub-id></mixed-citation></ref></ref-list><glossary><title>Abbreviations</title><array><tbody><tr><td>aRR</td><td>adjusted relative risk</td></tr><tr><td>DOB</td><td>date of birth</td></tr><tr><td>IRSD</td><td>Index of Relative Socio-Economic Disadvantage</td></tr><tr><td>NSW</td><td>New South Wales</td></tr><tr><td>PAF</td><td>population attributable fraction</td></tr><tr><td>SEIFA</td><td>Socio-Economic Index for Areas</td></tr><tr><td>SGA</td><td>small for gestational age</td></tr></tbody></array></glossary></back></article>