One of the critical texts of modern public health, The Strategy of Preventive Medicine (Rose, 1992) outlines British epidemiologist and physician Geoffrey Rose’s insights on how prevention programmes should work to improve the health of populations. Rose postulated that risk for a specific condition (for example, as Rose points out, hypertension) follows a single distribution for each population. While most people at the ‘upper end’ of this risk distribution might eventually experience hypertension, most cases would occur in the people in the rest of the distribution with low to medium-high levels of risk. Following on, Rose suggests that the best way to address large-scale public health problems is to shift the entire risk distribution, rather than target only those people at highest risk. This points to an intervention approach that is not individual, but structural—that manipulates the environment and context.
Old wine in new bottles? The logic in Rose’s work is essentially demographic. Indeed, the idea of structural shifts in population health appears everywhere in demographic theories. Classical demographic transition theory posits that the decreases in national mortality reduced as a result of better healthcare, nutrition, and economic changes. Even when the relative roles of these structural changes are up for debate, a Rose-like logic comes through. For example, McKeown (1976) posited that the majority of life expectancy increases through 1935 were driven by economic growth, leading to higher standards of living and improved nutrition. In contrast, Szreter (2003) points out that the real drivers of increases in population health in many major British cities were not economic changes, but the implementation of sanitation measures led by elites. In each of these arguments, large, structural-level interventions that shifted the population risk distributions were what led to decreases in mortality.
Demography to the rescue. However, the connection is not just a historical one. As the Rose hypothesis makes clear, demographic tools can play a helpful role in understanding today’s population problems. For example, population subfecundity, which exists at different rates in different countries, could best be treated with a structural, population-based approach. As Basten (2009) points out, while 15% of couples might be sterile, many more are subfecund. While the specific causes of population subfecundity are many, a structural approach will be key to resolving this problem.
Time to make friends. So, demography and The Strategy of Preventive Medicine—they clearly have a lot in common. Demographic understandings can help pave the way to clarity on a population health issue, and the Rose hypothesis can suggest a starting point for addressing the puzzling issues demographers uncover. Perhaps it’s time for demography and preventive medicine—not just public health—to make friends.