Australia Average Number of Dependent Children in Household: Multiple Family data was reported at 1.200 Person in 2020. This records a decrease from the previous number of 1.400 Person for 2018. Australia Average Number of Dependent Children in Household: Multiple Family data is updated yearly, averaging 1.300 Person from Jun 2004 (Median) to 2020, with 9 observations. The data reached an all-time high of 1.500 Person in 2016 and a record low of 1.200 Person in 2020. Australia Average Number of Dependent Children in Household: Multiple Family data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.H039: Survey of Income and Housing: Average Number of Dependent Children in Household: by Family Composition.

Australia Average Number of Dependent Children in Household: One Family: Couple with Dependent Children data was reported at 1.900 Person in 2020. This stayed constant from the previous number of 1.900 Person for 2018. Australia Average Number of Dependent Children in Household: One Family: Couple with Dependent Children data is updated yearly, averaging 1.900 Person from Jun 2003 (Median) to 2020, with 10 observations. The data reached an all-time high of 2.000 Person in 2008 and a record low of 1.900 Person in 2020. Australia Average Number of Dependent Children in Household: One Family: Couple with Dependent Children data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.H039: Survey of Income and Housing: Average Number of Dependent Children in Household: by Family Composition.

Australia Children Out of School: Male: % of Male Primary School Age data was reported at 0.398 % in 2022. This records a decrease from the previous number of 0.491 % for 2021. Australia Children Out of School: Male: % of Male Primary School Age data is updated yearly, averaging 2.525 % from Dec 1971 (Median) to 2022, with 39 observations. The data reached an all-time high of 4.972 % in 2000 and a record low of 0.268 % in 2018. Australia Children Out of School: Male: % of Male Primary School Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Social: Education Statistics. Children out of school are the percentage of primary-school-age children who are not enrolled in primary or secondary school. Children in the official primary age group that are in preprimary education should be considered out of school.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

Growing Up in Australia: the Longitudinal Study of Australian Children (LSAC) is a major study following the development of 10,090 children and families from all parts of Australia. LSAC explores family and social issues while addressing a range of research questions about children’s development and wellbeing. The Wave 1 data collection was undertaken for AIFS by private social research companies Colmar Brunton Social Research and I-view/NCS Pearson. Data collection for Waves 2-6 was undertaken by the ABS. From 2004, participating families have been interviewed every two years, and between-wave mail-out questionnaires were sent to families in 2005 (Wave 1.5), 2007 (Wave 2.5) and 2009 (Wave 3.5). Additional between-wave questionnaires (Waves 4.5 and 5.5) were undertaken via online web forms from 2009 for the purposes of updating the contact details of study participants. The sampling unit of interest is the study child and there were two cohorts of children selected from children born within two 12-month periods: (1) B cohort ("Baby" cohort) - children born March 2003–February 2004, and (2) K cohort ("Kinder" cohort) - children born March 1999–February 2000. Please note that this release of LSAC is now superseded, and is available by request for approved training courses only. For the current release, please visit https://ada.edu.au/lsac_current

Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) is a major study following the development of approximately 10,000 young people and their families from all parts of Australia. It is conducted in partnership between the Department of Social Services, the Australian Institute of Family Studies and the Australian Bureau of Statistics with advice provided by a consortium of leading researchers. The study began in 2003 with a representative sample of children (who are now teens and young adults) from urban and rural areas of all states and territories in Australia. The study has a multi-disciplinary base, and examines a broad range of research questions about development and wellbeing over the life course in relation to topics such as parenting, family, peers, education, child care and health. It will continue to follow participants into adulthood. The study informs social policy and is used to identify opportunities for early intervention and prevention strategies. Participating families have been interviewed every two years from 2004, and between-wave mail-out questionnaires were sent to families in 2005 (Wave 1.5), 2007 (Wave 2.5) and 2009 (Wave 3.5). The B cohort (“Baby” cohort) of around 5,000 children was aged 0–1 years in 2003–04, and the K cohort (“Kinder” cohort) of around 5,000 children was aged 4–5 years in 2003–04. Study informants include the young person, their parents (both resident and non-resident), carers and teachers. The study links to administrative databases including Medicare (Immunisation, MBS and PBS), NAPLAN, AEDC and Centrelink – with participant consent – thereby adding valuable information to supplement the data collected during fieldwork. In 2014-15, a special one-off physical health and biomarkers assessment of parent-child pairs was undertaken in the younger cohort. The cross-generational datasets from this ‘Child Health CheckPoint’ are available in the Additional Release files.

Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) is a major study following the development of approximately 10,000 young people and their families from all parts of Australia. It is conducted in partnership between the Department of Social Services, the Australian Institute of Family Studies and the Australian Bureau of Statistics with advice provided by a consortium of leading researchers. The study began in 2003 with a representative sample of children (who are now teens and young adults) from urban and rural areas of all states and territories in Australia. The study has a multi-disciplinary base, and examines a broad range of research questions about development and wellbeing over the life course in relation to topics such as parenting, family, peers, education, child care and health. It will continue to follow participants into adulthood. The study informs social policy and is used to identify opportunities for early intervention and prevention strategies. Participating families have been interviewed every two years from 2004, and between-wave mail-out questionnaires were sent to families in 2005 (Wave 1.5), 2007 (Wave 2.5) and 2009 (Wave 3.5). The B cohort (“Baby” cohort) of around 5,000 children was aged 0–1 years in 2003–04, and the K cohort (“Kinder” cohort) of around 5,000 children was aged 4–5 years in 2003–04. Study informants include the young person, their parents (both resident and non-resident), carers and teachers. The study links to administrative databases including Medicare (Immunisation, MBS and PBS), NAPLAN, AEDC and Centrelink – with participant consent – thereby adding valuable information to supplement the data collected during fieldwork. In 2014-15, a special one-off physical health and biomarkers assessment of parent-child pairs was undertaken in the younger cohort. The cross-generational datasets from this ‘Child Health CheckPoint’ are available in the Additional Release files.

UNICEF's country profile for Australia, including under-five mortality rates, child health, education and sanitation data.

Australia: Primary school enrollment, percent of all eligible children: The latest value from 2022 is 99.13 percent, a decline from 99.93 percent in 2021. In comparison, the world average is 100.44 percent, based on data from 149 countries. Historically, the average for Australia from 1971 to 2022 is 105.04 percent. The minimum value, 99.13 percent, was reached in 2022 while the maximum of 112.22 percent was recorded in 1971.

Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) is a major study following the development of approximately 10,000 young people and their families from all parts of Australia. It is conducted in partnership between the Department of Social Services, the Australian Institute of Family Studies and the Australian Bureau of Statistics with advice provided by a consortium of leading researchers. The study began in 2003 with a representative sample of children (who are now teens and young adults) from urban and rural areas of all states and territories in Australia. The study has a multi-disciplinary base, and examines a broad range of research questions about development and wellbeing over the life course in relation to topics such as parenting, family, peers, education, child care and health. It will continue to follow participants into adulthood. The study informs social policy and is used to identify opportunities for early intervention and prevention strategies. Participating families have been interviewed every two years from 2004, and between-wave mail-out questionnaires were sent to families in 2005 (Wave 1.5), 2007 (Wave 2.5) and 2009 (Wave 3.5). The B cohort (“Baby” cohort) of around 5,000 children was aged 0–1 years in 2003–04, and the K cohort (“Kinder” cohort) of around 5,000 children was aged 4–5 years in 2003–04. Study informants include the young person, their parents (both resident and non-resident), carers and teachers. Please note that this release of LSAC is now superseded, and is available by request for approved training courses only. For the current release, please visit https://ada.edu.au/lsac_current

Australia: Ratio of female to male students in secondary school: The latest value from 2020 is 0.96 percent, an increase from 0.93 percent in 2019. In comparison, the world average is 1.01 percent, based on data from 111 countries. Historically, the average for Australia from 1993 to 2020 is 0.95 percent. The minimum value, 0.87 percent, was reached in 2015 while the maximum of 1.03 percent was recorded in 1997.

This database is comprised of 603 participants who provided self-report data online in their school classrooms. The data was collected in 2016 and 2017. The dataset is comprised of 208 males (34%) and 395 females (66%). Their ages ranged from 12 to 15 years. Their age in years at baseline is provided. The majority were born in Australia. Data were drawn from students at two Australian independent secondary schools. The data contains total responses for the following scales: The Intolerance of Uncertainty Scale (IUS-12; Short form; Carleton et al, 2007) is a 12-item scale measuring two dimensions of Prospective and Inhibitory intolerance of uncertainty. Two subscales of the Children’s Automatic Thoughts Scale (CATS; Schniering & Rapee, 2002) were administered. The Peronalising and Social Threat were each composed of 10 items. UPPS Impulsive Behaviour Scale (Whiteside & Lynam, 2001) which is comprised of 12 items. Dispositional Envy Scale (DES; Smith et al, 1999) which is comprised of 8 items. Spence Children’s Anxiety Scale (SCAS; Spence, 1998) which is comprised of 44 items. Three subscales totals included were the GAD subscale (labelled SCAS_GAD), the OCD subscale (labelled SCAS_OCD) and the Social Anxiety subscale (labelled SCAS_SA). Each subscale was comprised of 6 items. Avoidance and Fusion Questionnaire for Youth (AFQ-Y; Greco et al., 2008) which is comprised of 17 items. Distress Disclosure Index (DDI; Kahn & Hessling, 2001) which is comprised of 12 items. Repetitive Thinking Questionnaire-10 (RTQ-10; McEvoy et al., 2014) which is comprised of 10 items. The Brief Fear of Negative Evaluation Scale, Straightforward Items (BFNE-S; Rodebaugh et al., 2004) which is comprised of 8 items. Short Mood and Feelings Questionnaire (SMFQ; Angold et al., 1995) which is comprised by 13 items. The Self-Compassion Scale Short Form (SCS-SF; Raes et al., 2011) which is comprised by 12 items. The subscales include Self Kindness, Self Judgment, Social Media subscales - These subscale scores were based on social media questions composed for this project and also drawn from three separate scales as indicated in the table below. The original scales assessed whether participants experience discomfort and a fear of missing out when disconnected from social media (taken from the Australian Psychological Society Stress and Wellbeing Survey; Australian Psychological Society, 2015a), style of social media use (Tandoc et al., 2015b) and Fear of Missing Out (Przybylski et al., 2013c). The items in each subscale are listed below. Pub_Share Public Sharing When I have a good time it is important for me to share the details onlinec On social media how often do you write a status updateb On social media how often do you post photosb Surveillance_SM On social media how often do you read the newsfeed On social media how often do you read a friend’s status updateb On social media how often do you view a friend’s photob On social media how often do you browse a friend’s timelineb Upset Share On social media how often do you go online to share things that have upset you? Text private On social media how often do you Text friends privately to share things that have upset you? Insight_SM Social Media Reduction I use social media less now because it often made me feel inadequate FOMO I am afraid that I will miss out on something if I don’t stay connected to my online social networksa. I feel worried and uncomfortable when I can’t access my social media accountsa. Neg Eff of SM I find it difficult to relax or sleep after spending time on social networking sitesa. I feel my brain ‘burnout’ with the constant connectivity of social mediaa. I notice I feel envy when I use social media.
I can easily detach from the envy that appears following the use of social media (reverse scored) DES_SM Envy Mean acts online Feeling envious about another person has led me to post a comment online about another person to make them laugh Feeling envious has led me to post a photo online without someone’s permission to make them angry or to make fun of them Feeling envious has prompted me to keep another student out of things on purpose, excluding her from my group of friends or ignoring them. Substance Use: Two items measuring peer influence on alcohol consumption were adapted from the SHAHRP “Patterns of Alcohol Use” measure (McBride, Farringdon & Midford, 2000). These items were “When I am with friends I am quite likely to drink too much alcohol” and “Substances (alcohol, drugs, medication) are the immediate way I respond to my thoughts about a situation when I feel distressed or upset. Angold, A., Costello, E. J., Messer, S. C., & Pickles, A. (1995). Development of a short questionnaire for use in epidemiological studies of depression in children and adolescents. International Journal of Methods in Psychiatric Research, 5(4), 237–249. Australian Psychological Society. (2015). Stress and wellbeing in Australia survey. https://www.headsup.org.au/docs/default-source/default-document-library/stress-and-wellbeing-in-australia-report.pdf?sfvrsn=7f08274d_4 Greco, L.A., Lambert, W. & Baer., R.A. (2008) Psychological inflexibility in childhood and adolescence: Development and evaluation of the Avoidance and Fusion Questionnaire for Youth. Psychological Assessment, 20, 93-102. https://doi.org/10.1037/1040-3590.20.2.9 Kahn, J. H., & Hessling, R. M. (2001). Measuring the tendency to conceal versus disclose psychological distress. Journal of Social and Clinical Psychology, 20(1), 41–65. https://doi.org/10.1521/jscp.20.1.41.22254 McBride, N., Farringdon, F. & Midford, R. (2000) What harms do young Australians experience in alcohol use situations. Australian and New Zealand Journal of Public Health, 24, 54–60 https://doi.org/10.1111/j.1467-842x.2000.tb00723.x McEvoy, P.M., Thibodeau, M.A., Asmundson, G.J.G. (2014) Trait Repetitive Negative Thinking: A brief transdiagnostic assessment. Journal of Experimental Psychopathology, 5, 1-17. Doi. 10.5127/jep.037813 Przybylski, A. K., Murayama, K., DeHaan, C. R., & Gladwell, V. (2013). Motivational, emotional, and behavioral correlates of fear of missing out. Computers in human behavior, 29(4), 1841-1848. https://doi.org/10.1016/j.chb.2013.02.014 Raes, F., Pommier, E., Neff, K. D., & Van Gucht, D. (2011). Construction and factorial validation of a short form of the self-compassion scale. Clinical Psychology and Psychotherapy, 18(3), 250-255. https://doi.org/10.1002/cpp.702 Rodebaugh, T. L., Woods, C. M., Thissen, D. M., Heimberg, R. G., Chambless, D. L., & Rapee, R. M. (2004). More information from fewer questions: the factor structure and item properties of the original and brief fear of negative evaluation scale. Psychological assessment, 16(2), 169. https://doi.org/10.1037/10403590.16.2.169 Schniering, C. A., & Rapee, R. M. (2002). Development and validation of a measure of children’s automatic thoughts: the children’s automatic thoughts scale. Behaviour Research and Therapy, 40(9), 1091-1109. . https://doi.org/10.1016/S0005-7967(02)00022-0 Smith, R. H., Parrott, W. G., Diener, E. F., Hoyle, R. H., & Kim, S. H. (1999). Dispositional envy. Personality and Social Psychology Bulletin, 25(8), 1007-1020. https://doi.org/10.1177/01461672992511008 Spence, S. H. (1998). A measure of anxiety symptoms among children. Behaviour Research and Therapy, 36(5), 545-566. https://doi.org/10.1016/S0005-7967(98)00034-5 Tandoc, E. C., Ferrucci, P., & Duffy, M. (2015). Facebook use, envy, and depression among college students: Is facebooking depressing? Computers in Human Behavior, 43, 139–146. https://doi.org/10.1016/j.chb.2014.10.053 Whiteside, S.P. & Lynam, D.R. (2001) The five factor model and impulsivity: using a structural model of personality to understand impulsivity. Personality and Individual Differences 30,669-689. https://doi.org/10.1016/S0191-8869(00)00064-7 The data was collected by Dr Danielle A Einstein, Dr Madeleine Fraser, Dr Anne McMaugh, Prof Peter McEvoy, Prof Ron Rapee, Assoc/Prof Maree Abbott, Prof Warren Mansell and Dr Eyal Karin as part of the Insights Project. The data set has the option of downloading an excel file (composed of two worksheet tabs) or CSV files 1) Data and 2) Variable labels.

The Australian Early Development Census is a measure of how young children are developing in Australian communities. It involves collecting information to help create a snapshot of early childhood development in communities across Australia. Australian Early Development Census 2009-2015.

This database is comprised of 951 participants who provided self-report data online in their school classrooms. The data was collected in 2016 and 2017. The dataset is comprised of 509 males (54%) and 442 females (46%). Their ages ranged from 12 to 16 years (M = 13.69, SD = 0.72). Seven participants did not report their age. The majority were born in Australia (N = 849, 89%). The next most common countries of birth were China (N = 24, 2.5%), the UK (N = 23, 2.4%), and the USA (N = 9, 0.9%). Data were drawn from students at five Australian independent secondary schools.

The data contains item responses for the Spence Children’s Anxiety Scale (SCAS; Spence, 1998) which is comprised of 44 items. The Social media question asked about frequency of use with the question “How often do you use social media?”. The response options ranged from constantly to once a week or less. Items measuring Fear of Missing Out were included and incorporated the following five questions based on the APS Stress and Wellbeing in Australia Survey (APS, 2015). These were “When I have a good time it is important for me to share the details online; I am afraid that I will miss out on something if I don’t stay connected to my online social networks; I feel worried and uncomfortable when I can’t access my social media accounts; I find it difficult to relax or sleep after spending time on social networking sites; I feel my brain burnout with the constant connectivity of social media. Internal consistency for this measure was α = .81. Self compassion was measured using the 12-item short-form of the Self-Compassion Scale (SCS-SF; Raes et al., 2011).

The data set has the option of downloading an excel file (composed of two worksheet tabs) or CSV files 1) Data and 2) Variable labels.

References:

Australian Psychological Society. (2015). Stress and wellbeing in Australia survey. _{https://www.headsup.org.au/docs/default-source/default-document-library/stress-and-wellbeing-in-australia-report.pdf?sfvrsn=7f08274d_4}

Raes, F., Pommier, E., Neff, K. D., & Van Gucht, D. (2011). Construction and factorial validation of a short form of the self-compassion scale. Clinical Psychology and Psychotherapy, 18(3), 250-255. _{https://doi.org/10.1002/cpp.702}

Spence, S. H. (1998). A measure of anxiety symptoms among children. Behaviour Research and Therapy, 36(5), 545-566. _{https://doi.org/10.1016/S0005-7967(98)00034-5}

The child mortality rate in Australia, for children under the age of five, was 391 deaths per thousand births in 1860. This means that just under forty percent of all children born in 1860 did not make it to their fifth birthday. This number dropped drastically over the next ten years, then it remained between 150 and two hundred for the remainder of the 1800s, before dropping consistently from 1900 until today. By 2020, child mortality in Australia is expected to be approximately four deaths per thousand births.

Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) is a major study following the development of approximately 10,000 young people and their families from all parts of Australia. It is conducted in partnership between the Department of Social Services, the Australian Institute of Family Studies and the Australian Bureau of Statistics with advice provided by a consortium of leading researchers. The study began in 2003 with a representative sample of children (who are now teens and young adults) from urban and rural areas of all states and territories in Australia. The study has a multi-disciplinary base, and examines a broad range of research questions about development and wellbeing over the life course in relation to topics such as parenting, family, peers, education, child care and health. It will continue to follow participants into adulthood. The study informs social policy and is used to identify opportunities for early intervention and prevention strategies. Participating families have been interviewed every two years from 2004, and between-wave mail-out questionnaires were sent to families in 2005 (Wave 1.5), 2007 (Wave 2.5) and 2009 (Wave 3.5). The B cohort (“Baby” cohort) of around 5,000 children was aged 0–1 years in 2003–04, and the K cohort (“Kinder” cohort) of around 5,000 children was aged 4–5 years in 2003–04. Study informants include the young person, their parents (both resident and non-resident), carers and teachers. The study links to administrative databases including Medicare (Immunisation, MBS and PBS), NAPLAN, and Centrelink – with participant consent – thereby adding valuable information to supplement the data collected during fieldwork. In 2014-15, a special one-off physical health and biomarkers assessment of parent-child pairs was undertaken in the younger cohort. The cross-generational datasets from this ‘Child Health CheckPoint’ are available in the Additional Release files. LSAC Wave 9 (aka 9C) covered the impact of the COVID-19 pandemic on young persons, their families and communities. Wave 9C was unlike any other wave undertaken by LSAC. Instead of the traditional face-to-face methodology, the data collection was split into two shorter online surveys (9C1 and 9C2), with Survey 9C2 also offering a telephone interview option. Two short survey in Wave 9C allows measurement of similarities and differences in responses as COVID-19 restrictions changed over time. Survey 9C1 was in field October–December 2020 and Survey 9C2 was in-field June–September 2021.

Children (0-14) living with HIV in Australia was reported at 100 Persons in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Australia - Children (0-14) living with HIV - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

SA1 based data for Family Composition and Country of Birth of Parents by Age of Dependent Children, in General Community Profile (GCP), 2016 Census. Count of dependent children. Excludes overseas …Show full descriptionSA1 based data for Family Composition and Country of Birth of Parents by Age of Dependent Children, in General Community Profile (GCP), 2016 Census. Count of dependent children. Excludes overseas visitors. Includes same-sex couple families. The data is by SA1 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census. Copyright attribution: Government of the Commonwealth of Australia - Australian Bureau of Statistics, (2017): ; accessed from AURIN on 12/16/2021. Licence type: Creative Commons Attribution 2.5 Australia (CC BY 2.5 AU)

The South Australian perinatal statistics collection is data collected from births in SA, notified by hospital and homebirth midwives and neonatal nurses. Further information can be found at the SA Health Website.

The Student visas lodged, granted and grant rate reports are based on lodgement and grant data recorded for visa subclass 500 and subclass 570 to 576 in the current financial year and previous financial years.

The dimensions include the financial year and quarter of visa grant, the gender, age, education provider registered state, sector, client location, lodgement channel and citizenship country.

These de-identified statistics are periodically checked for privacy and other compliance requirements. The statistics were temporarily removed in March 2024 in response to a question about privacy within the emerging technological environment. Following a thorough review and risk assessment, the Department of Home Affairs has republished the dataset.

List of male and female baby names in South Australia from 1944 to 2024. The annual data for baby names is published January/February each year.