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The impact of the Baby Bonus payment in New South Wales: who is having “one for the country”?

Samantha J Lain, Jane B Ford, Camille H Raynes-Greenow, Ruth M Hadfield, Judy M Simpson, Jonathan M Morris and Christine L Roberts
Med J Aust 2009; 190 (5): 238-241. || doi: 10.5694/j.1326-5377.2009.tb02382.x
Published online: 2 March 2009
Methods

Women aged 15–44 years who gave birth in NSW from 1 January 1997 to 31 December 2006 were included in the study population. To examine the effect of the Baby Bonus payment on different population subgroups, birth rates were stratified by age group, socioeconomic status, geographical area and birth order. We defined birth rate as the annual number of women of reproductive age (15–44 years) with a pregnancy that resulted in a birth, divided by the population of women of reproductive age at 30 June each year. We examined which populations of women became pregnant after the introduction of the Baby Bonus; thus, stillbirths were included in the analysis and multiple births (eg, twins) were counted as one birth.

Data sources

Birth data (the numerator) were obtained from the NSW Midwives Data Collection, a legislated, population-based surveillance system of all babies born in NSW of ≥ 20 weeks’ gestation or ≥ 400 g birthweight. The Midwives Data Collection includes information on total number of previous pregnancies for each mother, and is reported reliably.8,9

Population data, used as the denominator for birth-rate calculations, were obtained from ABS Estimated Residential Populations. Data were stratified into age groups and statistical local areas; the latter can be used to identify different socioeconomic and geographical regions. Parity-specific birth rates were calculated by stratifying the female population by the number of children they had given birth to. Thus, for first births, the denominator for birth rate was women who have no children, and that for second births was women who have had one child. The ABS collects information about the number of children ever born to each woman every 10 years, most recently in the 2006 Census. From unpublished ABS data10 and annual birth data, we back-projected the female population in NSW stratified by age, parity and local area for the years before 2006, using a method described by Kippen.11 Parity of the women was grouped into those having their first child, second child, and third or subsequent child.

Women were classified as residing in “metropolitan” or “rural” areas according to the Accessibility/Remoteness Index of Australia.12 Metropolitan areas comprised the capital city and large regional districts, while rural areas included small regional districts and remote regions. Women residing in metropolitan areas were then classified into three socioeconomic groups: “disadvantaged” (0–20th percentile), “average” (21st – 80th percentile) and “advantaged” (81st – 100th percentile). Women in rural areas were not differentiated by socioeconomic status because of similar trends in birth rates among socioeconomic groups.

Socioeconomic status was obtained from the Index of Relative Socio-economic Disadvantage from the Socio-Economic Indexes for Areas,13 derived from the 2006 Census and incorporating attributes such as low income, low educational attainment and high unemployment.

Results

From 1997 to 2006, there were 861 372 women aged 15–44 years who gave birth in NSW. Of these, 853 606 women were included in our study. The women who were excluded resided outside NSW (0.01%) or had missing data for age group, birth order or statistical local area (0.9%). The number of women giving birth decreased from 85 860 in 1997 to 83 467 in 2004 (about 0.8% per annum) then increased to 89 921 in 2006. During the study period there was an increase in the proportion of women giving birth who were aged 30 years or older or of higher socioeconomic status (Box 1). From 1997 to 2004, the proportion of births that were first births increased, and then decreased from 2004 to 2006.

Age-specific birth rates

Annual birth rates and the underlying trend before the introduction of the Baby Bonus for the whole dataset are shown in Box 2. Birth rates for every age group increased significantly in 2005 and continued to rise in 2006. The largest change in birth rates, relative to the trend of the previous years, was seen in teenage women. Before 2004, birth rates for women aged 15–19 years were declining steeply, at an average of 4.5% (95% CI, 4.1%–5.0%) per year. Compared with this sharp decline, the birth rate for this age group increased 7.7% (95% CI, 3.2%–12.4%) in 2005 and 13.5% (95% CI, 8.5%–18.7%) in 2006. Births to women aged 35 years and older had been increasing at an average of 2.6% per year from 1997 to 2004; however, compared with this upward trend, births increased by an additional 7.2% (95% CI, 4.8%–9.6%) in 2005 and 10.9% (95% CI, 8.4%–13.6%) in 2006, the second largest increase of all age groups.

Discussion

These findings suggest that the Baby Bonus affected the birth rate in NSW for second, third or subsequent births, but had limited impact on first births. The increase in second births occurred predominantly among younger women of low and average socioeconomic status. The increase in third or subsequent births appears to have occurred across all age, socioeconomic and geographical groups. These findings indicate that, in the short term, a financial incentive has had an impact on the birth rate among certain subgroups of the population. Studies in other countries have shown that birth rate increases occurring immediately after the introduction of financial incentives were not sustained.3,4 Financial incentives may have a temporary effect on birth rates: couples may change the timing of births, but the resulting family size does not change.2

As pregnancy and childbirth in teenagers are associated with adverse perinatal outcomes,14,15 the increase in births to teenagers after the introduction of the Baby Bonus is of concern, and follows a steep decline in teenage birth rates in the years before 2004. Although the absolute increase in births to teenagers after 2004 was only about 40 births per year, from 1997 to 2004 teenage births were declining on average by 125 births per year. Contrary to anecdotal reports, we did not find that the increase in births only occurred in low socioeconomic or disadvantaged groups.

A large proportion of the increase in births after 2004 was among women over the age of 30 years. This group of women may have had a baby even without the bonus payment. The current Australian Government has announced that, from 1 January 2009, only families earning less than $150 000 per year will be eligible to receive the payment,16 and it remains to be seen how this restriction in policy will affect the birth rate. In 2004, the government also introduced a number of tax rebates to assist with the costs of raising children and with child care, although these tax rebates did not gain as much publicity or stimulate as much public discussion as the Baby Bonus payment. Considered together, these policies may have increased the birth rate by highlighting the importance to society of motherhood and increasing the value that is placed on children.17

The introduction of a policy such as the Baby Bonus also affects maternity services. One startling implication of the announcement of a financial incentive to be paid from 1 July 2004 was the delay of over 1000 births from June to July by rescheduling inductions and caesarean sections.18 Both this short-term disruption to maternity services and the longer-term impact of an increase in births have placed huge pressure on the health system at a time when there are decreasing numbers of practising obstetricians and a shortage of midwives.19

The main strengths of our study lie in the use of a large representative population health dataset, which provides 10 years of longitudinal data, and the ability to analyse the dataset by birth order. To our knowledge, this is the first study to examine the impact of a financial incentive on parity-specific birth rates using individual data. The main limitation of our study is that the follow-up time only allowed short-term effects of the policy to be evaluated. Further research on longer-term impacts is warranted as birth and population data become available.

We could not account for other social and economic changes occurring in Australia over this period that may have affected the birth rate. For example, there may have been an increase in births due to economic prosperity, but it is unlikely that the short-term change of the magnitude seen from 2004 to 2005 is not related to the introduction of the Baby Bonus in mid 2004. We do not have data regarding the impact of the bonus on women’s intentions, so we cannot say whether this policy has altered their childbearing decisions, only that there is an association between the introduction of the policy and the increase in birth rates.

In conclusion, the Baby Bonus appears to have had a differential impact on the birth rate according to age and birth order. In the short term, the policy has had the greatest impact on women having a third or subsequent birth. Whether it has encouraged couples to increase their family size or just change the timing of a birth is yet to be seen, but the results of this social experiment suggest that financial incentives do affect birth rates.

3 Percentage increases (95% CI) in birth rates in women in New South Wales (in age, parity, socioeconomic and geographical subgroups) in 2005 and 2006 relative to the birth-rate trend before the introduction of the Baby Bonus policy

First birth


Second birth*


Third or subsequent birth


2005

2006

2005

2006

2005

2006


15–19 years

Metropolitan area

   Disadvantaged SES

3.2 ( 6.4 to 13.7)

0.7 ( 10.6 to 10.4)

5.7 ( 15.7 to 30.9)

13.2 ( 9.5 to 41.8)

   Average SES

7.2 (0.7 to 14.2)

8.9 (1.8 to 16.5)

18.6 (3.1 to 36.8)

39.1 (20.3 to 60.9)

   Advantaged SES

Rural area

0.2 ( 10.6 to 11.4)

12.8 (0.6 to 26.5)

6.2 ( 14.9 to 32.5)

31.4 (4.8 to 64.6)

20–24 years

Metropolitan area

   Disadvantaged SES

0.6 ( 5.3 to 6.8)

0.5 ( 6.7 to 6.2)

13.5 (5.1 to 22.4)

16.1 (7.0 to 26.0)

24.2 (10.6 to 39.5)

26.6 (11.7 to 43.4)

   Average SES

1.8 ( 5.6 to 2.2)

0.7 ( 3.5 to 5.1)

14.7 (8.8 to 21.0)

13.7 (7.3 to 20.5)

10.9 (1.8 to 20.8)

5.4 ( 4.0 to 15.7)

   Advantaged SES

1.3 ( 11.5 to 10.0)

5.0 ( 6.7 to 17.8)

13.2 ( 6.4 to 36.9)

19.3 ( 2.6 to 46.0)

Rural area

10.7 (1.5 to 20.9)

13.2 (3.1 to 24.5)

0.3 ( 9.9 to 10.4)

5.4 ( 6.3 to 17.5)

14.5 (1.9 to 30.1)

22.3 (6.2 to 40.8)

25–29 years

Metropolitan area

   Disadvantaged SES

4.0 ( 9.4 to 1.6)

1.2 ( 7.3 to 4.6)

12.9 (6.2 to 20.0)

13.4 (6.2 to 21.1)

12.8 (5.2 to 20.8)

14.4 (6.3 to 23.3)

   Average SES

1.3 ( 1.2 to 4.6)

1.6 ( 1.8 to 5.0)

4.1 (0.3 to 8.0)

10.0 (5.7 to 14.4)

14.3 (8.9 to 19.9)

20.7 (14.7 to 27.0)

   Advantaged SES

3.7 ( 1.8 to 9.5)

3.8 ( 2.1 to 10.1)

0.9 ( 7.2 to 9.7)

10.7 (1.4 to 20.8)

14.0 ( 2.0 to 32.7)

31.2 (12.3 to 53.4)

Rural area

1.0 ( 7.5 to 10.2)

3.9 ( 12.6 to 5.7)

13.3 (3.9 to 23.6)

8.6 ( 1.1 to 19.4)

18.1 (8.1 to 28.9)

21.2 (10.2 to 33.2)

30–34 years

Metropolitan area

   Disadvantaged SES

0.1 ( 7.9 to 7.3)

7.8 ( 0.2 to 16.4)

2.5 ( 4.2 to 9.2)

3.7 ( 3.1 to 10.9)

13.6 (6.8 to 20.9)

13.1 (5.8 to 20.8)

   Average SES

8.1 (4.5 to 11.8)

7.6 (3.7 to 11.8)

1.5 ( 2.8 to 4.9)

1.5 ( 2.3 to 5.1)

11.2 (7.1 to 15.6)

18.6 (13.9 to 23.6)

   Advantaged SES

4.8 (0.5 to 9.4)

7.3 (2.5 to 12.3)

3.2 ( 7.7 to 1.2)

2.7 ( 8.5 to 2.4)

9.7 (1.8 to 18.2)

16.8 (7.8 to 26.5)

Rural area

0.7 ( 9.6 to 12.2)

3.5 ( 7.8 to 16.3)

8.7 ( 0.5 to 18.7)

5.3 ( 4.4 to 16.0)

5.1 ( 2.9 to 13.8)

17.9 (8.5 to 28.1)

35–44 years§

Metropolitan area

   Disadvantaged SES

11.0 ( 2.0 to 25.8)

15.3 (1.0 to 31.5)

7.7 ( 2.7 to 19.1)

20.7 (8.8 to 34.0)

15.8 (7.1 to 25.4)

12.9 (3.7 to 22.9)

   Average SES

0.8 ( 4.8 to 6.6)

4.8 ( 2.3 to 11.2)

1.3 ( 3.7 to 6.5)

1.9 ( 3.4 to 7.4)

12.6 (7.3 to 18.2)

13.1 (7.4 to 19.1)

   Advantaged SES

4.1 ( 2.3 to 11.2)

10.8 (3.4 to 18.8)

3.3 ( 2.8 to 9.7)

1.1 ( 2.8 to 9.7)

10.3 (2.6 to 18.6)

9.6 (1.4 to 18.5)

Rural area

1.4 ( 16.7 to 22.6)

2.5 ( 16.1 to 25.1)

20.5 (3.8 to 39.7)

18.5 (1.1 to 39.0)

18.4 (6.4 to 31.7)

14.8 (2.3 to 28.8)


Statistically significant results (P < 0.05) are in bold type. SES = socioeconomic status. Disadvantaged SES = lower 20%; average SES = 21%–80%; and advantaged SES = upper 20%. * Second or subsequent births for women aged 15–19 years. No data analysed for third or subsequent births for women aged 15–19 years due to small numbers. Very small numbers of births resulting in unstable estimates. § Women aged 35–39 and 40–44 years were combined into one group due to similar patterns in births over the study period.

  • Samantha J Lain1
  • Jane B Ford1
  • Camille H Raynes-Greenow1
  • Ruth M Hadfield1
  • Judy M Simpson2
  • Jonathan M Morris3
  • Christine L Roberts1

  • 1 Perinatal Research, Kolling Institute of Medical Research, University of Sydney, Sydney, NSW.
  • 2 School of Public Health, University of Sydney, Sydney, NSW.
  • 3 Northern Clinical School (Royal North Shore Hospital), University of Sydney, Sydney, NSW.


Correspondence: samlain@med.usyd.edu.au

Acknowledgements: 

We acknowledge the efforts of the hospital staff who collect the data, and NSW Health Department staff for their role in the design and maintenance of the HOIST data warehouse system. Samantha Lain is the recipient of a Northern Sydney Health Research Grant for this study. Christine Roberts is supported by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship. Jane Ford is supported by the Health Research and Outcomes Network, an NHMRC Capacity Building Grant in Population Health Research. Camille Raynes-Greenow and Ruth Hadfield are supported by NHMRC Australian Research Training Fellowships.

Competing interests:

None identified.

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