NSW Perinatal Data Collection (SAPHaRI). Centre for Epidemiology and Evidence, NSW Ministry of Health.
Two questions are asked about smoking behaviour in the NSW Perinatal Data Collection:
- Did the mother smoke at all during the first half of pregnancy?
- Did the mother smoke at all during the second half of pregnancy?
Smoking in pregnancy was defined as smoking in either the first or second half of pregnancy.
Data include all mothers who gave birth (stillbirth or live birth) in a NSW facility (or a home) regardless of place of permanent residence.
The number of ‘not stated’ cases varied by geographic area and year. This may reduce the reliability of the estimates in the instances where ‘not stated’ cases are a large proportion.
Quintiles of socioeconomic status (Index of Relative Socioeconomic Disadvantage) based on the Australian Bureau of Statistics' Socio-Economic Indexes for Areas were allocated based on Statistical Local Area of residence (before 2009-10) or Statistical Area Level 2 of residence (2009-10 and after).
The NSW Perinatal Data Collection (PDC), formerly the NSW Midwives Data Collection (MDC), is a population-based surveillance system covering all births in NSW public and private hospitals, as well as homebirths. The PDC is a statutory data collection under the NSW Public Health Act 2010.
The PDC encompasses all live births, and stillbirths of at least 20 weeks gestation or at least 400 grams birth weight. Prior to 2006 the PDC encompassed all births of at least 20 weeks gestation or at least 400 grams birth weight. The data collection has operated since 1987 but with population coverage since 1990.
For every birth in NSW the attending midwife or medical practitioner completes a notification form (latest version for 2011: http://internal.health.nsw.gov.au/data/collections/mdc/NSWH%20Perinatal%20Data.pdf), or its electronic equivalent, giving demographic, medical and obstetric information on the mother and the condition of the infant. The PDC form was revised in 1998, 2006, 2011, and 2016.
There are several source systems that generate the PDC data. In 2018, 100% of PDC notifications were received electronically from public and private hospitals obstetric information systems. Electronically submitted records were received by secure upload to the state database. Historically, a proportion of records were received via completed paper forms that were submitted to the System Information and Analytics Branch of the NSW Ministry of Health, where they were compiled into the PDC database.
There are several electronic systems that generate the PDC data including ObstetriX, eMaternity, and Cerner in public hospitals and a variety of systems in private hospitals. ObstetriX is the most commonly used maternity information system in public hospitals in NSW.
Table 1. Perinatal Data Collection Notification Sources, NSW 2018
|Notification source||Local Health District or Hospital||
Per cent of PDC records 2018
All public hospitals in South Eastern Sydney, Illawarra Shoalhaven, Hunter New England, Nepean Blue Mountains and Western Sydney Local Health Districts, as well as some hospitals in Murrumbidgee, Southern NSW, Western NSW and Far West Local Health Districts for part of 2017.
|Cerner||Sydney and South Western Sydney Local Health Districts.||19.2|
|Meditech||Ramsay Private Hospitals - North Shore Private Hospital, Westmead Private Hospital, St George Private Hospital, Kareena Private Hospital and Wollongong Private Hospital.||7.6|
|Sydney Adventist Obstetric Information System||Sydney Adventist Hospital||1.8|
|Healthscope||Healthscope hospitals - Prince of Wales Private Hospital, Norwest Private Hospital, Sydney South West Private Hospital, Nepean Private Hospital and Newcastle Private Hospital||8.0|
|The Mater Hospital database||The Mater Hospital, North Sydney||2.2|
|eMaternity||All public hospitals in South Eastern Sydney, Illawarra Shoalhaven, Hunter New England, Nepean Blue Mountains and Western Sydney Local Health Districts, as well as some hospitals in Murrumbidgee, Southern NSW, Western NSW and Far West Local Health Districts for part of 2017.||59.0|
Note: The total from these sources is slightly below 100% as independent midwives and hospitals with small numbers of births report using PeriForm. These figures are not included.
The information sent to the NSW Ministry of Health is checked and compiled into one statewide dataset. One record is reported for each baby, even in the case of a multiple birth. The PDC includes notifications of births which occur in NSW which includes women whose usual place of residence is outside NSW and who give birth in NSW; it does not receive notifications of interstate births where the mother is resident in NSW. The collection is based on the date of birth of the baby. In 2018 there were a number of records with missing information that has resulted in a fluctuation in trends for analyses of subgroups.
Data are reported by calendar year. For this report, the PDC was accessed via SAPHaRI.
The Australian Bureau of Statistics (ABS) has produced measures of socioeconomic disadvantage since the 1971 Census. The Socio-Economic Indexes for Areas (SEIFA) were first produced in 1990 and consisted of five indexes formed from the 1986 Census data (ABS).
There are four SEIFA indexes currently produced. In each census year, the ABS assigns index SEIFA scores to non-overlapping geographical areas covering all Australia calculated from the various socioeconomic characteristics from the Census of the people living in areas.
Each index is a summary of a different subset of Census variables and focuses on a different aspect of socioeconomic advantage and disadvantage (ABS, 2018). The reference value for the whole of Australia is set to 1,000. Lower values indicate lower socioeconomic status.
The indexes are:
• Index of Relative Socio-Economic Disadvantage (IRSD)
• Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD)
• Index of Economic Resources (IER)
• Index of Education and Occupation (IEO).
In the IRSD, the constituent characteristics relate to occupation, education, non-English speaking background and the economic resources of the household. From 2011, the proportion of Aboriginal people is no longer a constituent variable of IRSD (ABS, 2011).
The score for each index is an ordinal measure with a mean of 1000 and standard deviation of 100 for Australia, and from 2011, based on the index scores of all Statistical Areas Level 1 (SA1) in Australia. Scores for larger geographic areas such as Local Government Areas (LGAs) and Postal Areas (POA) are population-weighted averages of scores in constituent SA1.
The overall scores for states are not available because as the size of an area increases, it becomes correspondingly more heterogeneous and the socioeconomic index becomes less and less meaningful. For very large areas, it is more useful to look at the distribution of SA1 scores within each area. The distributions of SA1 scores within each state and territory are available at the ABS web site (ABS).
The ABS has released SEIFA scores after the last five censuses. The methods used to calculate scores were similar in 1986, 1991 and 1996, but changed in 2001, 2006 and 2011. The major change in 2006 was that the census data used in the calculation of the indexes was based on people's usual area of residence rather than their location on census night (place of enumeration) and in 2011 a new geography standard was used and the proportion of Aboriginal people was no longer a constituent variable of IRSD (ABS 2013). SEIFA 2016 broadly uses the same method that was used for SEIFA 2011, though there were updates to SA1 boundaries in many areas (ABS 2018).
In the Index of Relative Socio-Economic Disadvantage (IRSD), the constituent characteristics relate to occupation, education, non-English speaking background and the economic resources of the household. There are currently 16 variables contributing to the index and the proportion of Aboriginal people is no longer a constituent variable of IRSD (ABS 2018). This is the most frequently used and quoted SEIFA index.
The Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD) consists of 25 contributing variables. They summarise information about the economic and social conditions of people and households within an area, including both relative advantage and disadvantage measures.
A low score indicates relatively greater disadvantage and a lack of advantage in general. For example, an area could have a low score if there are (among other things) many households with low incomes, or many people in unskilled occupations. A high score indicates a relative lack of disadvantage and greater advantage in general. For example, an area may have a high score if there are (among other things) many households with high incomes, or many people in skilled occupations (ABS 2016)
The Index of Economic Resources (IER) focuses on the financial aspects of relative socio-economic advantage and disadvantage, by summarising variables related to income and wealth. Education and occupation variables are excluded from this index because they are not direct measures of economic resources. Some relevant data on assets such as savings or equities are also not included because this information was not collected in the Census. There are 14 contributing variables. (ABS 2018)
The Index of Education and Occupation (IEO) is designed to reflect the educational and occupational level of communities. The education variables in this index show either the level of qualification achieved or whether further education is being undertaken. The occupation variables classify the workforce into the major groups and skill levels of the Australian and New Zealand Standard Classification of Occupations (ANZSCO) and the unemployed. This index does not include any income variables. There are 10 variables contributing to the total score. (ABS 2018)
Socioeconomic disadvantage is associated with a higher prevalence of health risk factors and higher rates of hospitalisations, deaths and other adverse health outcomes. Maps of socioeconomic disadvantage by LGA viewed in conjunction with maps of health outcomes can assist in identifying factors which may be associated with poorer outcomes.
The NSW population was divided into five groups based on the IRSD scores of their SA2 of residence. This means that SA2s were sorted by IRSD score and assigned to population-weighted quintiles, each containing close to one-fifth of the total population. In some charts and data tables on HealthStats NSW, the quintiles were divided into three groups: the lowest SES population-weighted quintile, the highest SES population-weighted quintile, and the rest of the population, comprising the remaining three population-weighted quintiles.
Postal Areas (POAs) were grouped into quintiles of socioeconomic status based on the IRSD.
Adhikari P. Socio-economic indexes for areas: Introduction, use and future directions. ABS Catalogue no. 1351.0.55.015. Canberra: ABS, 2006.
Australian Bureau of Statistics. Socio-Economic Indexes for Areas (SEIFA) - Technical Paper, 2011. SEIFA Cat no 2033.0.55.001. Canberra: ABS, 2013.
Australian Bureau of Statistics. Socio-Economic Indexes for Areas (SEIFA) - Technical Paper, 2016. SEIFA Cat no 2033.0.55.001. Canberra: ABS, 2018.
Australian Bureau of Statistics. 1996 Census of population and housing. Socioeconomic indexes for areas. 2039.0. Canberra: ABS, 1998. Available at http://www.ausstats.abs.gov.au/ausstats/free.nsf/0/C17E9A880591BB45CA256AE9001BCD57/$File/2039.0_1996.pdf
Australian Bureau of Statistics. Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2016. Catalogue no 2033.0.55.001. Canberra: ABS, 2013. Available at http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/by%20Subject/2033.0.55.001~2016~Main%20Features~SOCIO-ECONOMIC%20INDEXES%20FOR%20AREAS%20(SEIFA)%202016~1
Any smoking in pregnancy is included in this indicator.
Up to 2010, the question asked at data collection was: 'Did you smoke at all during pregnancy?' From 2011, there are two questions asked: 'Did you smoke at all during the first half of pregnancy?' and 'Did you smoke at all during the second half of pregnancy?' The revised questions provide more opportunity for women to report their smoking history, and are likely to produce a more reliable measure of smoking rates in pregnancy than the original question.
The current data collection form for the NSW Perinatal Data Collection (PDC) commenced in 2016. Codes are described in the NSW Perinatal Data Collection Manual - 2016 Edition, which is available on the internet at http://www1.health.nsw.gov.au/pds/ActivePDSDocuments/PD2015_025.pdf
In 2019 there were 95,133 births to 93,758 mothers in NSW, a decrease of 1.3% from 96,391 births in 2015. The percentage of multiple (twin and triplet) pregnancies has remained fairly stable over recent years at about 1.4%.
Between 2015 and 2019:
• The proportion of mothers who were teenagers continued to fall, from 2.5% to 1.7%.
• The proportion of births to mothers over 35 years of age has increased slightly from 23.4% to 25.9%.
• The rate of low birth weight (less than 2,500 grams) has remained stable, ranging from 6.4% to 6.8%.
• The perinatal mortality rate was 8.0 per 1,000 births in 2019, decreased from 8.2 per 1,000 births in 2015.
Aboriginal and Torres Strait Islander mothers and babies
Between 2015 and 2019:
• The number of reported births to Aboriginal or Torres Strait Islander mothers increased from 3,872 to 4,479, representing 4.0% and 4.7% respectively of all babies born in NSW.
• The percentage of Aboriginal or Torres Strait Islander mothers who were teenagers fell substantially from 15.4% to 10.5%.
• The perinatal mortality rate of 10.3 per 1,000 births in Aboriginal or Torres Strait Islander mothers in 2019 is higher than the rate of 7.9 per 1,000 births experienced among babies born to non-Aboriginal or Torres Strait Islander mothers.
• The percentage of Aboriginal or Torres Strait Islander mothers who commenced antenatal care before 14 weeks increased from 55.6% to 75.3%.
The health of Australian mothers and babies is generally good by world standards. Maternal deaths are rare, and perinatal mortality rates are low.
The average woman in NSW can currently expect to give birth to 1.9 babies in her lifetime.
NSW mothers are getting older with the mean maternal age at first birth around 29 years and at subsequent birth just over 30. The proportion of teenage mothers is declining.
Aboriginal mothers and babies, those from socioeconomically disadvantaged areas, and some overseas-born mothers and their babies continue to experience worse outcomes than other NSW mothers and babies.
The NSW Ministry of Health maintains two population-based surveillance systems that collect information concerning pregnancy and birth: the NSW Perinatal Data Collection and the NSW Register of Congenital Conditions. They assist in monitoring the health of mothers and babies, and maternity service planning in NSW.
The implementation of the NSW Aboriginal Maternal and Infant Health Strategy has improved access to culturally appropriate maternity services for Aboriginal mothers.
The NSW Maternal and Perinatal Mortality Review Committee reviews each death of a mother or newborn baby to assess the cause and identify any possible avoidable factors. This information is used to improve services for mothers and babies.
NSW Ministry of Health at http://health.nsw.gov.au, in particular see the annual New South Wales Mothers and Babies report, published by the Centre for Epidemiology and Evidence. The latest edition is available at http://www.health.nsw.gov.au/hsnsw/Publications/mothers-and-babies-2018.pdf
Australian Bureau of Statistics at http://www.abs.gov.au, in particular see Births (ABS Cat no 3301.0)
Australian Institute of Health and Welfare at http://www.aihw.gov.au in general and in particular the AIHW's National Perinatal Statistics Unit and the annual publication: Australia’s mothers and babies.
healthdirect at http://www.healthdirect.gov.au
Population and Public Health Division. Improved reporting of Aboriginal and Torres Strait Islander peoples on population datasets in New South Wales using record linkage–a feasibility study. Sydney: NSW Ministry of Health, 2012. Available at: http://www.health.nsw.gov.au/hsnsw/Publications/atsi-data-linkage-report.pdf
Australian Council on Healthcare Standards. Obstetrics Indicator User Manual. Sydney: ACHS. Available at: https://www.achs.org.au/
Data from the NSW Population Health Survey is used to measure the NSW State Government targets on reducing smoking in the population and is comparable with other sources of information on smoking in NSW.
• 11.2% of adults aged 16 years and over (12.1% of men and 10.2% of women) smoked daily in NSW in 2019 and 15.5% (18.0% of men and 13.1% of women) were current (daily or occasional) smokers. Estimates were produced from the NSW Adult Population Health Survey (self-reported using Computer Assisted Telephone Interviewing or CATI).
• 13.9% of NSW adults aged 18 years and over (17.0% of males and 10.9% of females) were daily smokers, as estimated from the 2017-18 National Health Survey (interviewer-administered questionnaire).
• 8.8% of mothers smoked during pregnancy in 2019, as reported to the NSW Perinatal Data Collection.
• 6.4% of students aged 12-17 years (7.0% of boys and 5.7% of girls) were current smokers, as estimated from the 2017 NSW School Students Health Behaviours Survey (self-completed questionnaire).
• 26.4% of Aboriginal adults aged 16 years and over smoked daily in NSW in 2018-2019 and 31.5% were current (daily or occasional) smokers. Estimates were produced from the NSW Adult Population Health Survey (self-reported using CATI).
• 43.2% of Aboriginal mothers smoked during pregnancy in 2019, as reported to the NSW Perinatal Data Collection.
Self-reported data on current smoking have been collected for adults in NSW since 1997 through the NSW Population Health Survey, since 1977-78 through the National Health Survey (from 1995), since 1985 through the National Drug Strategy Household Survey, and since 2011 through the Australian Health Survey.
Self-reported data on current smoking have been collected for students in NSW since 1984 through the NSW School Students Health Behaviours Survey.
Prevalence estimates, although differing slightly between surveys because of different sampling frames, participation rates and modes of collection (telephone, self-completed questionnaires, face-to-face personal interview and drop-and-collect), have all been decreasing over time.
A total of 62,930 hospitalisations were attributed to smoking in NSW in 2018-19, which was approximately 2.0% of all hospitalisations.
The rate of hospitalisations attributable to smoking decreased in males by nearly 36%, compared to a 15% decrease among females in NSW between 2001-02 and 2018-19. Rates have stabilised in recent years.
The rate of hospitalisations attributable to smoking increased in both Aboriginal males and Aboriginal females by 32% aand 24% respectively in the period between 2009-10 and 2018-19.
A total of 6,702 deaths were attributed to smoking in NSW in 2018, which was 12.5% of all deaths in 2018. In 2018, the rate of deaths attributable to smoking in males and females was 84.2 and 50.3 deaths per 100,000 population, respectively.
Australian Institute of Health and Welfare. National Drug Strategy Household Survey report. Available at: https://www.aihw.gov.au/about-our-data/our-data-collections/national-drug-strategy-household-survey
Australian Bureau of Statistics. National Health Survey: First Results, 2017-18. Available at: https://www.abs.gov.au/ausstats/abs@.nsf/Lookup/by%20Subject/4364.0.55.001~2017-18~Main%20Features~New%20South%20Wales~10002
Tobacco smoking is one of the biggest causes of premature death and is a leading preventable cause of chronic disease in New South Wales. It is a major risk factor for cardiovascular disease, a range of cancers, chronic obstructive pulmonary disease, coronary heart disease and a variety of other diseases and conditions. Approximately one in five of all cancer deaths are due to tobacco smoking.
There is a no safe level of exposure to second-hand tobacco smoke. In adults, breathing second-hand smoke can increase the risk of heart disease, lung cancer and other lung diseases. It can worsen the effects of existing illnesses such as asthma and bronchitis. For children, inhaling second-hand smoke is even more dangerous. Children are more likely to suffer health problems due to second-hand smoke such as bronchitis, pneumonia and asthma.
Australia has one of the most comprehensive tobacco control policies and programs in the world. The aim of the tobacco control programs in NSW is to contribute to a continuing reduction of smoking prevalence rates in the community.
Information on NSW Health tobacco and smoking control programs and policies is available at: http://www.health.nsw.gov.au/tobacco.
Cancer Institute at: https://www.cancerinstitute.org.au/
I Can Quit at http://www.icanquit.com.au
Information on NSW Health programs and policies is available at http://www.health.nsw.gov.au/tobacco.
Australian Bureau of Statistics at http://www.abs.gov.au
Australian Institute of Health and Welfare at http://www.aihw.gov.au
I Can Quit at http://www.icanquit.com.au