Talk:Australian Statistics
| About Discussion Pages |
|---|
Glossary Links
Cite this page: Hill, M.A. (2024, April 20) Embryology Australian Statistics. Retrieved from https://embryology.med.unsw.edu.au/embryology/index.php/Talk:Australian_Statistics |
2019
Congenital heart disease in Australia
Globally, congenital heart disease affects around 9 in every 1,000 babies born. In Australia, a large number of children, young people and adults live with congenital heart disease. This report presents latest statistics and trends on the incidence of congenital heart disease, and on hospitalisation and mortality.
- There were almost 5,000 congenital heart disease hospitalisations in 2016–17.
- There were 70 infant deaths from congenital heart disease in 2017, comprising 6.9% of all infant deaths.
- Around 9 in every 1,000 live births are affected by congenital heart disease.
- Advances in paediatric cardiac care has led to more adults living with congenital heart disease.
Australian Institute of Health and Welfare 2019. Congenital heart disease in Australia. Cat. no. CDK 14. Canberra: AIHW.
Hearing health outreach services for Aboriginal and Torres Strait Islander children in the Northern Territory: July 2012 to December 2018
Australian Institute of Health and Welfare 2019. Hearing health outreach services for Aboriginal and Torres Strait Islander children in the Northern Territory: July 2012 to December 2018. Cat no. [https://www.aihw.gov.au/reports/indigenous-health-welfare-services/hearing-health-outreach-services/contents/table-of-contents
IHW 213]. Canberra: AIHW.
47% of Indigenous children who received a service had hearing loss
57% of Indigenous children who had hearing loss at their first service showed improvement at their last service
Australian Institute of Health and Welfare 2019. Diabetes in pregnancy 2014–2015. Bulletin no. 146. Cat. no. CDK 7. Canberra: AIHW.
Australian Institute of Health and Welfare 2019. Diabetes in pregnancy 2014–2015. Bulletin no. 146. Cat. no. CDK 7. Canberra: AIHW.
https://www.aihw.gov.au/reports/diabetes/diabetes-in-pregnancy-2014-2015/contents/summary
2018
Australian Institute of Health and Welfare 2018. Improving national reporting on diabetes in pregnancy: technical report. AIHW bulletin series no. 146. Cat. no. CDK 13. Canberra: AIHW.
Australian Institute of Health and Welfare 2018. Improving national reporting on diabetes in pregnancy: technical report. AIHW bulletin series no. 146. Cat. no. CDK 13. Canberra: AIHW.
2017
Progress in closing the gap in life expectancy at birth for Aboriginal people in the Northern Territory, 1967-2012
Med J Aust. 2017 Jul 3;207(1):25-30.
Georges N1, Guthridge SL2, Li SQ2, Condon JR2, Barnes T3, Zhao Y2. Author information Abstract OBJECTIVES: To compare long term changes in mortality and life expectancy at birth (LE) of Aboriginal people in the Northern Territory and of the overall Australian population; to determine the contributions of changes in mortality in specific age groups to changes in LE for each population.
DESIGN, SETTING, PARTICIPANTS: Retrospective trend analysis of death and LE data for the NT Aboriginal and Australian populations, 1967-2012.
MAIN OUTCOME MEASURES: LE estimates based on abridged life tables; mortality estimates (deaths per 100 000 population); and age decomposition of LE changes by sex and time period.
RESULTS: Between 1967 and 2012, LE increased for both NT Aboriginal and all Australians; the difference in LE between the two populations declined by 4.6 years for females, but increased by one year for males. Between 1967-1971 and 1980-1984, LE of NT Aboriginal people increased rapidly, particularly through reduced infant mortality; from 1980-1984 to 1994-1998, there was little change; from 1994-1998 to 2008-2012, there were modest gains in older age groups. Decomposition by age group identified the persistent and substantial contribution of the 35-74-year age groups to the difference in LE between NT Aboriginal people and all Australians.
CONCLUSIONS: Early gains in LE for NT Aboriginal people are consistent with improvements in nutrition, maternal and infant care, and infectious disease control. A rapid epidemiological transition followed, when LE gains in younger age groups plateaued and non-communicable diseases became more prevalent. Recent LE gains, across all adult age groups, are consistent with improved health service access and chronic disease management. If LE is to continue improving, socio-economic disadvantage and its associated risks must be reduced.
KEYWORDS: Life expectancy; Longitudinal studies; Population health; Vital statistics PMID: 28659111
2014
Birthweight percentiles by gestational age for births following assisted reproductive technology in Australia and New Zealand, 2002-2010
Hum Reprod. 2014 Jun 7. pii: deu120. [Epub ahead of print]
Li Z1, Wang YA1, Ledger W2, Sullivan EA3.
Abstract
STUDY QUESTION: What is the standard of birthweight for gestational age for babies following assisted reproductive technology (ART) treatment? SUMMARY ANSWER: Birthweight for gestational age percentile charts were developed for singleton births following ART treatment using population-based data. WHAT IS KNOWN ALREADY: Small for gestational age (SGA) and large for gestational age (LGA) births are at increased risks of perinatal morbidity and mortality. A birthweight percentile chart allows the detection of neonates at high risk, and can help inform the need for special care if required. STUDY DESIGN, SIZE, DURATION: This population study used data from the Australian and New Zealand Assisted Reproduction Database (ANZARD) for 72 694 live born singletons following ART treatment between January 2002 and December 2010 in Australia and New Zealand. PARTICIPANTS/MATERIALS, SETTING, METHODS: A total of 69 315 births (35 580 males and 33 735 females) following ART treatment were analysed for the birthweight percentile. Exact percentiles of birthweight in grams were calculated for each gestational week between Week 25 and 42 for fresh and thaw cycles by infant sex. Univariate analysis was used to determine the exact birthweight percentile values. Student t-test was used to examine the mean birthweight difference between male and female infants, between single embryo transfer (SET) and double embryo transfer (DET) and between fresh and thaw cycles. MAIN RESULTS AND THE ROLE OF CHANCE: Preterm births (birth before 37 completed weeks of gestation) and low birthweight (<2500 g) were reported for 9.7 and 7.0% of live born singletons following ART treatment. The mean birthweight was 3280 g for live born singletons following fresh cycles (3338 g for male infants and 3217 for female infants) and 3413 g for live born singletons following thaw cycles (3475 g for male infants and 3349 for female infants). The proportion of SGA for male ART births following thaw cycles at 35-41 weeks gestation was significantly lower than for the Australian general population, ranging from 3.8% (95% confidence interval (CI): 1.3%, 6.2%) at 35 weeks gestation to 7.9% (95% CI: 6.3%, 9.5%) at 41 weeks gestation. The proportion of LGA for male ART births following thaw cycles was significantly higher than for the Australian general population between 33 weeks (17.1%, 95% CI: 8.9%, 25.2%) and 41 weeks (14.4%, 95% CI: 12.3%, 16.5%). A similar trend was shown for female infants following thaw cycles. The live born singletons following SET were, on average, 45 g heavier than live born singletons following DET (P< 0.001). Overall, SGA was reported for 8.9% (95% CI: 8.6%, 9.1%) of live born singletons following SET and for 9.9% (95% CI: 9.5%, 10.3%) of live born singletons following DET. LIMITATIONS, REASONS FOR CAUTION: Birthweight percentile charts do not represent fetal growth standards but only the weight of live born infants at birth. WIDER IMPLICATIONS OF THE FINDINGS: The comparison of birthweight percentile charts for ART births and general population births provide evidence that the proportion of SGA births following ART treatment was comparable to the general population for SET fresh cycles and significantly lower for thaw cycles. Both fresh and thaw cycles showed better outcomes for singleton births following SET compared with DET. Policies to promote single embryo transfer should be considered in order to minimize the adverse perinatal outcomes associated with ART treatment. STUDY FUNDING/COMPETING INTERESTS: No specific funding was obtained. The authors have no conflicts of interest to declare. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com. KEYWORDS: assisted reproductive technology; birthweight; gestational age; single embryo transfer; small for gestational age
PMID 24908671
2013
Pregnancy And Neonatal Diabetes Outcomes in Remote Australia (PANDORA) Study
BMC Pregnancy Childbirth. 2013 Dec 1;13:221. doi: 10.1186/1471-2393-13-221.
Maple-Brown LJ, Brown A, Lee IL, Connors C, Oats J, McIntyre HD, Whitbread C, Moore E, Longmore D, Dent G, Corpus S, Kirkwood M, Svenson S, van Dokkum P, Chitturi S, Thomas S, Eades S, Stone M, Harris M, Inglis C, Dempsey K, Dowden M, Lynch M, Boyle J, Sayers S, Shaw J, Zimmet P, O'Dea K. Author information
Abstract
BACKGROUND: Diabetes in pregnancy carries an increased risk of adverse pregnancy outcomes for both the mother and foetus, but it also provides an excellent early opportunity for intervention in the life course for both mother and baby. In the context of the escalating epidemic of chronic diseases among Indigenous Australians, it is vital that this risk is reduced as early as possible in the life course of the individual. The aims of the PANDORA Study are to: (i) accurately assess rates of diabetes in pregnancy in the Northern Territory (NT) of Australia, where 38% of babies are born to Indigenous mothers; (ii) assess demographic, clinical, biochemical, anthropometric, socioeconomic and early life development factors that may contribute to key maternal and neonatal birth outcomes associated with diabetes in pregnancy; and (iii) monitor relevant post-partum clinical outcomes for both the mothers and their babies.
METHODS/DESIGN: Eligible participants are all NT women with diabetes in pregnancy aged 16 years and over. Information collected includes: standard antenatal clinical information, diagnosis and management of diabetes in pregnancy, socio-economic status, standard clinical birth information (delivery, gestational age, birth weight, adverse antenatal and birth outcomes). Cord blood is collected at the time of delivery and detailed neonatal anthropometric measurements performed within 72 hours of birth. Information will also be collected regarding maternal post-partum glucose tolerance and cardio-metabolic risk factor status, breastfeeding and growth of the baby up to 2 years post-partum in the first instance.
DISCUSSION: This study will accurately document rates and outcomes of diabetes in pregnancy in the NT of Australia, including the high-risk Indigenous Australian population. The results of this study should contribute to policy and clinical guidelines with the goal of reducing the future risk of obesity and diabetes in both mothers and their offspring.
PMID 24289168
Age, mode of conception, health service use and pregnancy health: a prospective cohort study of Australian women
BMC Pregnancy Childbirth. 2013 Apr 8;13:88. doi: 10.1186/1471-2393-13-88.
Fisher J, Wynter K, Hammarberg K, McBain J, Gibson F, Boivin J, McMahon C. Source Jean Hailes Research Unit, School of Public Health and Preventive Medicine, Monash University, Clayton, , Victoria, 3168, Australia. jane.fisher@monash.edu. Abstract BACKGROUND: There is limited evidence about the ways in which maternal age and mode of conception interact with psychological, sociodemographic, health and health service factors in governing pregnancy health. The aim of this study was to establish in what ways maternal age and mode of conception are associated with, health behaviours, health service use and self-rated physical and mental health during pregnancy. METHOD: A prospective cohort study was conducted in a collaboration between universities, infertility treatment services and public and private obstetric hospitals in Melbourne and Sydney, Australia,. Consecutive cohorts of nulliparous English-literate women at least 28 weeks pregnant who had conceived through ART (ARTC) or spontaneously (SC) in three age-groups: 20-30; 31-36 and at least 37 years were recruited. Data were obtained via structured individual telephone interviews and self-report postal questionnaires at recruitment and four months postpartum. Study-specific questions assessed: sociodemographic characteristics; reproductive health; health behaviours and health service use. Standardized instruments assessed physical health: SF 12 Physical Component Score (PCS) and mental health: SF12 Mental Component Score (MCS); State Trait Anxiety Inventory and Edinburgh Postnatal Depression Scale. The main outcome measures were the SF 12 PCS, SF12 MCS scores and pregnancy-related hospital admissions. RESULTS: Of 1179 eligible women 791 (67%) participated, 27 had fertility treatment without oocyte retrieval and were excluded and 592/764 (78%) completed all pregnancy assessments. When other factors were controlled speaking a language other than English, having private health insurance and multiple gestation were associated with worse physical health and having private health insurance and better physical health were associated with better mental health. Pregnancy-related hospital admissions were associated with worse physical health and multiple gestation. CONCLUSIONS: Maternal age and mode of conception are not associated with pregnancy health and health service use when sociodemographic factors are considered.
PMID 23565589
Perinatal Statistics Unit National Perinatal Statistics Unit | Queensland | South Australia | Teenage Pregnancies South Australia | ACT | New South Wales | Northern Territory | Western Australia | Tasmania
Kolling Institute of Medical Research (RNS) - Clinical and Population Perinatal Health Research http://www.kolling.usyd.edu.au/research/clinical-population-perinatal/index.php | Professor Jonathan Morris
Australian BS
3301.0 - Births, Australia, 2011 Quality Declaration LATEST ISSUE Released at 11:30 AM (CANBERRA TIME) 25/10/2012
http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/3301.0Main+Features12011?OpenDocument
http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/3301.02011?OpenDocument
Indigenous population (ABS data)
http://www.abs.gov.au/ausstats/abs@.nsf/Products/946D4BC28DB92E1BCA25762A001CBF38?opendocument
The estimated resident Indigenous population of Australia at 30 June 1991 was 351,000 people. In 2006, there were 517,000 people, representing 2.5% of the total Australian population. Between 1991 and 2006 the Indigenous population increased by 2.6% per year on average, compared with 1.2% for the total Australian population.
The Indigenous population has a relatively young age structure. Between 1991 and 2006 the median age of the Indigenous population is estimated to have increased from 20.1 to 21.0 years, and is projected to increase to between 23.9 and 24.1 years in 2021.
National best practice guidelines for collecting Indigenous status in health data sets
AIHW 2010. National best practice guidelines for collecting Indigenous status in health data sets. Cat. no. IHW 29. Canberra: AIHW. http://www.aihw.gov.au/publication-detail/?id=6442468342&tab=2
In the event of a birth
For perinatal data collections, the mother’s Indigenous status should be asked directly of the mother, regardless of the information separately recorded in the hospital database. Some service providers in some jurisdictions separately ascertain and record the Indigenous status of both the mother and of the newborn baby. While the Indigenous status of the baby is not currently a requirement for perinatal data collections, this may become a requirement in future. If the Indigenous status of the newborn is to be collected, the mother should be asked to provide this information for herself and for her baby. It should not be assumed that the baby’s status is the same as that of the mother. If the mother has not reported her status as Aboriginal or Torres Strait Islander, it should not be assumed that the newborn is therefore not of Aboriginal and/or Torres Strait Islander origin.
Population Data Neighbours
|
|
|
New Zealand |
Indonesia |
Papua |
Singapore |
Malaysia |
|
Population |
18,613,087 |
3,625,388 |
212,941,810 |
4,599,785 |
3,490,356 |
20,932,901 |
|
Age structure | ||||||
|
0-14 years: |
21% |
23% |
31% |
40% |
21% |
36% |
|
15-64 years: |
66% |
65% |
65% |
57% |
72% |
60% |
|
65 years +: |
13% |
12% |
4% |
3% |
7% |
4% |
|
Population growth rate |
0.93% |
1.04% |
1.49% |
2.27% |
1.2% |
2.11% |
|
Birth rate |
13.47 |
14.89 |
23.1 |
32.37 |
13.79 |
26.5 |
|
Death rate |
6.89 |
7.6 |
8.22 |
9.65 |
4.68 |
5.36 |
|
Sex ratio (male(s)/female) | ||||||
|
at birth: |
1.06 |
1.05 |
1.05 |
1.05 |
1.08 |
1.06 |
|
under 15 years: |
1.05 |
1.05 |
1.03 |
1.05 |
1.06 |
1.05 |
|
15-64 years: |
1.02 |
1.01 |
0.99 |
1.09 |
1 |
1 |
|
65 years +: |
0.77 |
0.76 |
0.79 |
0.84 |
0.8 |
0.77 |
|
Infant mortality rate |
5.26 |
6.37 |
59.23 |
57.09 |
3.87 |
22.45 |
|
Life expectancy at birth (years) | ||||||
|
total population: |
79.89 |
77.55 |
62.49 |
58.06 |
78.49 |
70.36 |
|
male: |
76.95 |
74.35 |
60.28 |
57.18 |
75.46 |
67.35 |
|
female: |
82.98 |
80.91 |
64.81 |
58.98 |
81.77 |
73.56 |
|
Total fertility rate (children born/woman) |
1.82 |
1.91 |
2.61 |
4.26 |
1.46 |
3.37 |
Historic Country Data (July 1998)
|
|
|
|
|
|
|
|
|
Population |
18,613,087 |
270,311,756 |
58,970,119 |
82,079,454 |
1,236,914,658 |
984,003,683 |
|
Age structure | ||||||
|
0-14 years: |
21% |
22% |
19% |
16% |
26% |
34% |
|
15-64 years: |
66% |
66% |
65% |
68% |
68% |
61% |
|
65 years +: |
13% |
12% |
16% |
16% |
6% |
5% |
|
Population growth rate |
0.93% |
0.87% |
0.25% |
0.02% |
0.83% |
1.71% |
|
Birth rate |
13.47 |
14.4 |
12.01 |
8.84 |
15.73 |
25.91 |
|
Death rate |
6.89 |
8.8 |
10.72 |
10.77 |
6.99 |
8.69 |
|
Sex ratio (male(s)/female) | ||||||
|
at birth: |
1.06 |
1.05 |
1.05 |
2.08 |
1.15 |
1.05 |
|
under 15 years: |
1.05 |
1.05 |
1.05 |
1.06 |
1.13 |
1.06 |
|
15-64 years: |
1.02 |
0.99 |
1.01 |
1.05 |
1.07 |
1.08 |
|
65 years +: |
0.77 |
0.7 |
0.7 |
0.59 |
0.88 |
1.04 |
|
Infant mortality rate |
5.26 |
6.44 |
5.87 |
5.2 |
45.46 |
63.14 |
|
Life expectancy at birth (years) | ||||||
|
total population: |
79.89 |
76.13 |
77.19 |
76.99 |
69.59 |
62.9 |
|
male: |
76.95 |
72.85 |
74.57 |
73.83 |
68.32 |
62.11 |
|
female: |
82.98 |
79.58 |
79.96 |
80.33 |
71.06 |
63.73 |
|
Total fertility rate (children born/woman) |
1.82 |
2.07 |
1.7 |
1.25 |
1.8 |
3.24 |
