I had a few surprises looking at marital status in the 2016 Australian census, including the combination of the two different marital status variables.
This article is viewable both on this site and on Mappage, my webapp for looking at statistics. If you’re reading this on a large screen, it’s best to read this article in Mappage where I have set it up with maps and charts. If you read this version, you will see references to the charts you can’t see here.
This article is viewable both on this page and in plain form on the Mappage WordPress site. The one-letter links here will show maps and charts. This is not so much an article with a few visualisations embedded; it is my statistics & mapping web app (called Mappage) which I have set up to accommodate articles like this. Clicking those links just changes the settings on the right. You’re not restricted to looking at what the links provide; you can look around for yourself at any other stats.
Most of the data in the text here is from the 2016 census. Another source was this ABS page on marriages and divorces. I wrote this before 2021 was available. I have since loaded the 2021 data in, but 2016 will show by default. In many places you can click Year then 2021 to see the current figures, or click the play button to animate between census years.
The census asked respondents aged 15+ their Registered Marital Status. The breakdown in 2016 was Never married 35%, Widowed 5.2%, Divorced 8.5%, Separated 3.2%, Married 48.1%.
A greater proportion of men are married or never married, while more women are widowed, divorced and separated. The main reasons are women marrying 2 years earlier and living 4 years longer, so they outlast their husbands or exes by about 6 years.
Registered marital status by age: B stackRegAge Never married starts near 100%, passes 50% after age 30 and drops below 5% for the oldest ages1The slope down is not due to older people marrying so much as the older cohorts having fewer never-married than those that followed.. Most common age for first marriage is 27. The Married category peaks at 66% at 69. Divorced is 17.4% at 58, Separated is 5.6% at 48. The rate of Widowed is 1% at 47, 4% at 60, 11% at 70, 30.4% at 80 and 64.3% at 90.
Social Marital Status is determined differently. Married in a registered marriage (47.7%) means those whose Registered status is Married and who were usually living with their spouse and present on census night. Married in a de facto marriage (10.4%) likewise counts those living with a partner and present on census night. Not married (41.9%) are those who weren’t living with a partner and who were home on census night. Those who didn’t do the census at all (~1.2M) or who weren’t home on census night (1.14M) and those in non-private dwellings (833k) join the kids under 15 in Not applicable (which I’ve excluded from the percentages above)2It’s 11.9% of those 15+ or 28.3% of the total. Note also that the larger Not Applicable category means the percentages for Social are of a smaller total than for Registered in the previous paragraph.. We can look at these varying by age too B stackSocAge. Married registered has a local maximum of 62% at age 41 and a maximum of 65.1% at 69. De facto peaks at 23.6% at 27. Not married has a minimum of 25.1% at 39.
When I first saw these two variables, I wondered why they didn’t roll them into one. This article does that, simplifying the situation3That article is about many other things, so it’s fair enough to simply in that way. It does say “Women are more likely to never have been married” which looks wrong based on my look at the stats here., but that overlooks some less common situations that we’ll see by using the two variables and that account for 750,000 Australians.
We’ll put them together and see how the Australian population breaks down, starting from the most common combinations. If we exclude all those with Not applicable, B tableMm there are 11 combinations.4In the 2021 data, there are some 15 combinations. Some methods must have changed to allow Social to be married registered while Registered is something other than married. I don’t know how this works. Has one person described themself as married, but not their supposed spouse? This complication is one reason I haven’t updated the text of this article to reflect the 2021 data. With these extra combinations and no explanation for them, it was all too complicated. For each combination, I’ve put links to five different visualisations:
A: What proportion of each age group is in that category.
B: What proportion is in that category for each country of birth. This will be affected by the age profile of the adults from each birthplace. To hide the Australian-born and see the rest better, click Australia, then click “Exclude Australia”.
C: What proportion is in each SA45The next level down from state/territory, with a mark showing what level would be predicted by the area’s age profile.
S: Scatter plot of all SA3s6The next level down from SA4, typically with populations in the tens of thousands in Australia against the Index of Disadvantage7A composite measure of disadvantage for areas. Family structures are among the inputs, so the correlations may be greater than they would be otherwise. I could have used the similar Index of Advantage and Disadvantage, but the former shows bigger correlations. (IoD) of the area. I typically modify this chart to look at the correlation within a state – click Residence and the state name and it will show just that state at SA2 level. Perhaps more important than the correlation is the slope of the line – when I mention slope below, it refers to the change in the proportion of that category associated with a 100-point increase in the IoD8looking at the scatter plots of each state at SA2 level.
M: Map showing the same proportion. You can drag and scroll the map around. If you zoom in, it will show a higher level of detail (goes down to SA2 level). The colour scale adjusts to fit the values currently shown.
Inner city areas9The inner SA4s of Sydney and Melbourne show up when looking at SA4s. At SA3 level, the CBD areas of the major cities have these traits. have a different demographic makeup from everywhere else. They are dominated by never married (both not married and de facto, particularly the latter) young adults.10I had written “Inner city areas have the most young adults, therefore the most never married and de facto”. But it’s much more than that; the inner SA4s of Sydney and Melbourne have much higher proportions of never married than their age profiles would predict.
Married, registered marriage: A51 8M, 47.7%, down from 48.9% in 2011. 43.5% for Australian-born, 71.7% Indian-born. 23.1% for Indigenous Australians. A little lower than I thought it would be. Comparing by geography at SA4 level, this ranges from Sydney City & Inner South at 28.3% to 59.7% for Hawkesbury & Baulkham Hills, a remarkable outlier. Higher outside the major cities. IoD slopes of +3.811Victoria has the lowest slope thanks to very low numbers of married people in well-off inner Melbourne. to +6.9% (ie in every state, there are more married people in areas with less disadvantage). This slope was greater in 2016 than it was in 201112This might just reflect a change in the weightings used to calculate the index, or it may be that more married couples have moved to the nicer suburbs..
Never married, not married: A13 4.54M, 27.1% (26.7% in 2011). 31.2% for Australian-born. 47.5% for Indigenous. Some of these may have a partner who lives somewhere else and more will previously have had a partner (30.2% of women in this category have had children). This ranges from 20.5% (WA Wheat Belt) to 41.8% (Sydney City & Inner South). IoD slope of -1.1 to -2.6%.
Never married, de facto: A12 1.25M, 7.4% (6.9% in 2011). NZ-born is 13.8%, Indian only 0.9%, Middle East 1.5%. Indigenous 13%. I thought this would be higher, but there would be many couples who don’t live in the same house. 5.8% of these were in same-sex couples (38.1k M, 33.7k F). Ranges from 2.9% (Hawkesbury & Baulkham Hills) to 17.5% for WA Outback North, with the inner city areas high. IoD slope is around +0.7% in NSW and Victoria (whose poor areas have more south Asian and Middle Eastern) and -0.6 to -1.2% in other states.
Divorced, not married: A33 1.08M, 6.4%. 5% men, 7.6% women. Australian-born are average, Indian-born only 1.6%. Highest levels are in Richmond-Tweed (9.1%) and other NSW sea-change SA4s. IoD slope of -1.1 to -1.5% (-1.2 to -1.7% for men).
Widowed, not married:13This category excludes a large number in aged care homes, because people in non-private dwellings have Social marital status as Not applicable. A23 747k, 4.5%, down from 4.8% in 2011. The drop is because every cohort over age 60 has had significantly more divorces than the cohort 5 years ahead of it. Mid North Coast is an outlier at 7.1%. IoD slope of -0.7 to -1.1% (-1 to -1.6% for women). The largest proportions of widowed people are in areas with the most older people, but there are not quite as many widowed in those areas as their age profiles would predict.14Which means that old couples are spread slightly more unevenly than their widowed counterparts.
Separated, not married: A43 412k, 2.5%. M 2.1%, F 2.8%15The gender gap for separated was mentioned above. There is a small additional excess of overseas-born separated women, suggesting they left their husbands before immigrating or the husbands left Australia. Also, more separated men were away from home and so landed in Not applicable.. The highest are Morton Bay North and Wide Bay. IoD slopes around -0.7%.
Couples must be separated for a at year before being divorced; the median length seems to be 3-4 years16For divorces granted in 2020, the median age at separation was 3.8 years younger than the median age at divorce.. I don’t have data on how many couples separate but don’t divorce.
Some African countries have a high proportion in this category. South Sudan stands out with 11% (7.8% M, 14.4% F)17A few things to note here. 1. The proportion was similar for those to immigrated before 2006 as since. 2. I assume the female excess in this category usually corresponds to the ex-husbands dying first, but given the age profile of South Sudanese, I think other explanations are needed for the 500 excess separated women. Probably men had returned to South Sudan and perhaps some never came. 3. These women had an average of over 4 children. 4. Most people indicating Sudan as their birthplace were born in what is now South Sudan, but Sudan had only 6.7% in this category..
Divorced, de facto: A32 336k, 2%. This is the first combination that necessarily involves two different relationships. But it reminded me that for any registered status other than Never married, we don’t know how many previous marriages the person had. 20% of people marrying had been married before18From 2010 to 2020, 72% of marriages were the first marriage for both partners, 16% were the first for one and 12% were remarriage for both. Remarriages were more common in 2000 when 24% of those marrying had been married before.. 2.5% of this category were in same-sex de facto relationships (3050 M, 5420 F19While almost equal numbers of men and women were in same-sex relationships (45.5k M, 44.6k F), more of those men were never married while more of the women were divorced or separated.). Unlike divorced not married, this category has near-zero relationship with IoD.
Married, not married: A53 245k, 1.5% (up from 1.1% in 2011). Married, but not living with their spouse. This combination surprised me and it’s why I’m writing this.
NT Outback is an outlier with 5.5%20Within NT Outback, East Arnhem is highest at 8.6%. For indigenous people Australia-wide, the rate is only 1.5%.. In Sydney at SA3 level, Auburn stands out with 6.3%21Auburn North SA2 is 14.2%. That SA2 is most notable for having only 9.7% speaking English-only, in 4th place behind Nepali, Mandarin and Urdu..
The age profile is fairly balanced but trimodal. Many older people in this category have their spouse in aged care, creating a peak over age 80. The small peak at age 50-62 middle is majority female. The larger 25-36 peak is majority male.
The rate varies a lot by country of birth: Only 0.8% for Australian-born (33.9% of this category). Afghanistan 16.4%, Nepal 12.1%, Pakistan 8.4%, mainland China 6.1%, India 5.1%.
B stackMnmSex This chart shows the category by birthplace and gender. For some nationalities, this group is mostly male. For east Asians, there is a female majority. There are many families where the father works in their home country while the mother and kids live in Australia so they can come to school here (creating that middle age peak).
Only 30.6% of them lived alone (higher for those born in Australia or Europe, higher for men). A similar number (mostly women) lived with children. 26.2% lived with people other than their family (this includes most of those from Afghanistan and Nepal). 6.5% of them were university students22Including 30.7% of those from Nepal, 25% of those born in Bhutan, 21.4% of those from Bangladesh..
I haven’t known many people in this category and I wonder about all the different situations that led to them being where they are. I wonder how long those people are “married, not married” and how many more there will be in the future. The 2021 stats will show these changes as well as some effects of the pandemic on families split between countries.
Separated, de facto: A42 108k, 0.64%, up from 0.32%! I’m surprised at this dramatic change in 5 years23This might just reflect a shift in attitudes toward subsequent relationships, but it could also reflect a longer time to divorce, hence more people an extra two years into separation (I haven’t checked this) or higher housing prices, nudging someone to move in with their newish partner sooner (I haven’t checked, and it may be the 2022 housing prices talking).. Queensland is highest with 0.73%. SA is only 0.55%, despite being higher for separated not married. Strong negative relationship with IoD. Born in Lebanon, 1.9%, with other Middle Eastern countries also high.
Married, de facto: A52 30.6k, 0.18% (0.12% in 2011). Married to one person and living de facto with someone else. Highest in NT Outback (1%). Sydney Inner City also stands out. Australian-born only 1.4%, in fact only 52% of this category were born in Australia. Birthplaces with a high rate include Brazil 1.1%, Columbia 0.7%, Vietnam 0.6%, Thailand 0.6%. 0.5% for Indigenous. 26.2% of these were in same-sex couples.
Widowed, de facto: A22 29.9k, 0.18%. Varies with age profile, but much more than expected. So widowed de facto are more likely than retired married couples to move to a high-retiree area, while widowed not married are less likely to.
Final notes: That was probably more info than anyone wanted. There’s no need to dig into the different Not applicable categories (or the extra, seemingly contradictory categories in the 2021 data), although stats of people in non-private dwellings might be interesting another time. Thinking about all the different marriage, relationship and migration situations many others are in makes me grateful for my simple and privileged life.
While I find the stats interesting, I admit I’m mostly doing this to show off what Mappage can do. Last month I tried getting Covid data into Mappage and found it harder than expected. I chose this topic over other ideas I had because I thought I could just gather & analyse the numbers and then write about them, rather than finding features I want to add or fix. I still had plenty of the latter.