Health as if everybody counted blog

Code Red for maternal and child health: The BORN project *

Posted by Ted Schrecker
Ted Schrecker
Ted Schrecker is a clinical scientist at the Élisabeth Bruyère Research Institut
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on Thursday, 12 July 2012
in CHNET-Works!

In 1997, Ontario’s health ministry set a goal of reducing the percentage of babies born with low birthweight (less that 2,500 grams at birth) from 5.7 to 4 percent by 2010.  Such babies are at increased risk for poor health outcomes, and their care involves substantial health system costs.  The target was not met; in fact, by 2010 the figure had risen to 6.5 percent.   In a followup to the Code Red project, described in a previous posting, researchers at McMaster University and reporters at the Hamilton Spectator examined 535,000 Ontario birth records to find out why.  The results of the BORN project, which turned into a much larger-scale investigation into the socioeconomic influences on maternal and child health, offer a disturbing look not only at the reasons but also at the straightforward economic consequences.

The study found a strong socioeconomic gradient in low birthweight.  “Of the 20 neighbourhoods in Ontario with the worst,” i.e. highest, “rates of low-birth-weight babies, three of them are in the lower part of the former City of Hamilton” – in other words, the low-income downtown.  In one of the neighbourhoods, “74 percent of children live below the poverty line” and more than one family in four is headed by a single mother – statistically, one of the most important risk factors for poverty.  There are also some conspicuous outliers.  For example, the high-income Toronto suburb of Vaughan has the highest incidence of low birth weight in Ontario: 16.4 percent – emphasizing the complex causal pathways that may be involved.  McMaster researcher Neil Johnston, who was part of the study team, noted that there is “not a single smoking gun.  It’s almost a conspiracy of things that preclude [mothers] from ensuring the child they’re carrying will be as healthy as possible.”

born pic 1 prenatal care Ont1

One of those things is uneven access to prenatal care:  in some Ontario communities, like downtown Windsor, just over half of all expectant mothers receive prenatal care during the first trimester; in other communities, for the most part relatively wealthy, more than 19 out of 20 mothers receive first-trimester care.  Interestingly, although a socioeconomic gradient exists across neighbourhoods in Hamilton, levels of access are generally high.  Another issue is teenage pregnancy.   Within the region at the west end of Lake Ontario there is a steep socioeconomic gradient.  In one of Hamilton’s poorest downtown areas, between 2006 and 2010 one in seven babies was born to a teen mother.  In a wealthy area of nearby Burlington, where the median household income is three times as high, among a comparable number of births not a single one involved a teenage mother.  Comparable differences were observed across the province, with many of the highest rates (between 20 and 40 percent of births to teen mothers) observed in low-income First Nations reserves across northern Ontario.  Conversely, in 20 rural and suburban municipalities across southern Ontario, including high-income Richmond Hill and Oakville, the highest percentage of teen mothers was 1.8.  (The Town of Vaughan was one of these, showing the complexity of the low birthweight problem.)

born-pic-2teen-mom-rate2

As with the original Code Red series, the statistics are accompanied by interviews that should be required reading for every student of public health or health promotion.  Interviews with people like “Kristen,” pregnant at 16 after her boyfriend poked holes in the condoms because “he figured it would make me stay with him,” and researcher Lea Caragata, who points out the links among poverty, economic insecurity and lack of a sense of the future. “For those middle-class kids in Ancaster, pregnancy will ruin their prospects and their aspirations …”  It is critically important not to pathologize teen motherhood, but equally important to recognize that all too often it ensures the reproduction of patterns of disadvantage and marginalization across generations.

All of us concerned with action on health equity need to ask questions like the one posed at the start of the third and final instalment of the series:

born-pic-3-quotation

Turning around the Ontario situation will require coordination among a variety of service providers – a “symphony orchestra” rather than “a wonderful jam session,” in the words of McMaster’s Johnson, who emphasizes that the province “must take accountability for what happens” in the health system.  This is easier said than done – too often no one anywhere in the health care system seems accountable for outcomes, as shown by Ontario’s lacklustre performance in diabetes management – yet the challenges raised by the series are even bigger.  One set is summarized in Lea Caragata’s passionate critique of the “opportunity deficit” facing too many of today’s youth.   Another, related set is suggested by remarkable calculations that show the Gini coefficient – a standard measure of income inequality – at the neighbourhood level.

“It turns out that the Hamilton neighbourhoods with the greatest income inequality are also the same neighbourhoods with the highest levels of poverty. …. Perhaps it’s a coincidence,” said the final story, that these neighbourhoods “also happen to be the neighbourhoods that performed poorly for any number of health variables based on the findings of both Code Red and Born.

“Perhaps it’s not a coincidence.”

In Canada as in much of the rest of the world, economic restructuring and social policy retrenchment are driving an increase in economic inequality on every scale from the neighbourhood to the nation.  By failing to face up to this trend and address its consequences for health, we are betting the future of many Ontarians on its being just a coincidence.  We are also, of course, betting hundreds of millions, if not billions of dollars in future health care costs that could be avoided.    

Or, perhaps, we just don’t care?

born-pic-4-Gini coefficients

* Sincere thanks to the Hamilton Spectator and the Center for Spatial Analysis, McMaster University for the illustrations

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