Determinants of health: people can only choose from the options they have
Updated: Oct 27
"They just need to make better choices".
I often hear this when people I care about talk about health. If people ate better, smoked less, and moved more, they’d live longer and healthier lives.
And there's truth to this.
Someone’s behaviour can affect their health. Smoking causes cancer and heart disease, and regular activity helps protect against both.
But there's also more to it than this.
Someone's choices can help explain why they smoke. However, these choices can’t explain why people in the most deprived areas are about five times more likely to smoke than people in the least deprived areas. This is a pattern that reflects the conditions people make their choices in.
People can only choose from the options they have, and some people have far better options than others. To see why, we need to look at the determinants of health.
What are the determinants of health?
Determinants of health are conditions that affect how healthy you are — they’re the circumstances you live in. Think of them as layers of information about you.
Individual factors: your age, your genes, and behaviours like whether you smoke or what you eat. These are the variables a health dataset usually records about you.
Social and community networks: your family, your friends, and the communities you belong to. These are often harder to record in a dataset.
Living and working conditions: your housing, income, education, and employment. These might be recorded about you, your household, or the area you live in. In Aotearoa, the NZ Index of Socioeconomic Deprivation gives areas a score based on census data.
Economic, cultural, and political conditions: the settings chosen by those with power, like governments and companies. These decide what you can buy, how much it costs, and where you see it advertised.
Each layer influences the layers within it. What you eat can depend on the people around you: what your family cooks, and what’s served when your friends get together. Their choices depend on what they can afford and which shops are nearby. What they can afford depends on wages, which depend on employers and minimum wage settings. What shops are nearby depends on where supermarket chains and takeaway outlets choose to open.
When understanding health data, many analysts already account for these conditions, using metrics like a deprivation index. But these conditions show up well beyond health data. Someone's housing, income, and neighbourhood can influence their University Entrance attainment, the kinds of debt they carry, and whether they vote in local elections.
If you work with data about people in any field, these conditions are probably showing up in your results, too. The danger of ignoring them is that you credit individual behaviour for patterns people have little control over.
Where "choices" come from
Let’s go back to smoking. You might be thinking, "but cigarettes are expensive, so wouldn’t we expect people with less money to smoke less?" The determinants of health help explain why the data shows otherwise.
Most people who smoke make that "choice" young. On average, adult smokers had their first cigarette around age 15. Whether a young person starts is influenced by their social networks: children who grow up in households where people smoke are more likely to smoke themselves. And let's not forget, nicotine is highly addictive, so once people start, many keep buying cigarettes even as prices rise, and find themselves unable to simply choose to stop. Cigarettes are also easier to buy where money is tight: there are nearly four times more tobacco retailers in low-income communities than in higher-income ones.
By adulthood, a smoker’s "choice" has been influenced by the people they grew up with, the shops in their neighbourhood, and how governments choose to regulate an addictive product. These are the layers of the determinants of health.
Why the choice story sticks
So, if these conditions shape so much of our health, why do we keep coming back to a narrative about individual choices?
In health, researchers call this pull back to individual choices lifestyle drift. Policy starts out recognising that our income, housing, and the products around us shape health, but then it ends up mostly asking individuals to change.
The same pattern shows up in many areas:
Health: in Aotearoa, health experts criticised the 2015 Childhood Obesity Plan for focusing on individual children and their families, while leaving out measures like restricting junk food marketing.
Climate: in 2004, BP launched a carbon footprint calculator. This encouraged people to see climate change in terms of their personal emissions.
Housing: in 2017, a millionaire property developer told young Australians they’d struggle to buy a home while they were spending money on smashed avocado and coffee.
Gambling: "gamble responsibly" messages frame gambling harm as a matter of personal control.
Governments often respond to big problems by focusing on individual behaviour because that is easier to target than the conditions that surround it. A campaign telling people to change can launch in months, while changing incomes, housing, or what’s sold in our neighbourhoods takes years.
Industries whose products and profits depend on these conditions staying the same also promote the "choice" story.
What this looks like in Aotearoa
New Zealand’s average life expectancy is about 82 years. But this number hides what is happening underneath it.
In Aotearoa, where you live makes a difference to how long you live.
Males in the least deprived areas can expect to live to around 84 years. Males in the most deprived areas can expect to live to around 77.
For females, it's 86 years vs. 81 years.
Māori also have a lower life expectancy than non-Māori, non-Pacific people.
On average, Māori males live shorter lives than non-Māori, non-Pacific males, even in the least deprived areas. In the most deprived areas, their lives are even shorter.
The same pattern shows up for females.
Health New Zealand links gaps like these to racism and the ongoing effects of colonisation. These sit in the outer layer of the country's determinants of health and reach into every layer inside it.
What to do about it
Next time you’re working with data about people, here are three things to check:
Ask what influences the behaviour you see. When your data points to a behaviour, like smoking, ask what conditions make that behaviour more likely, and who controls those conditions. If the data runs the opposite way to what you’d expect from individual choice, as it does with smoking rates in deprived areas, that’s your sign to look at the conditions.
Bring conditions into your analysis. If your dataset only describes individuals, look for ways to add the conditions that surround them. If you’re analysing missed appointments, for example, that could mean adding travel distance, appointment times, or the cost of getting to a clinic.
Describe problems in terms of conditions. Write about the options people have (instead of the choices they make) and name who decides them. How you frame a finding affects what people do about it. "Families in low-income neighbourhoods eat less fresh food" invites a nutrition campaign. "Families in low-income neighbourhoods have fewer affordable places to buy fresh food" invites questions about prices, wages, and where supermarket chains open stores.
People do make choices, but every one is made from the options available. So, when your data points to a behaviour, ask what options people actually had.
I write about data and power, so if you'd like to follow along, the best place to do that is my newsletter. This article is part of the Things We Tell Ourselves series. Each article looks at an everyday saying, what the data shows, and what it means if you tell stories with data.
Kat Greenbrook is a data storytelling consultant, author, and workshop facilitator based in Wellington, New Zealand. She is the founder of Rogue Penguin and the author of The Data Storyteller's Handbook.
