Commentary: Life course epidemiology: the past two decades and future directions

Life course epidemiology has the great potential to help us understand why and how we age. Ultimately, the goal of such research is to identify the critical time points where interventions could ameliorate the disabling consequences of ageing. Epidemiological studies have assessed risk for disability in late life or have focused on longevity. It is now clear that we need to look back to earlier points in life to understand the origins of these important outcomes. The review by Ben-Shlomo, Cooper and Kuh1 provides an important perspective on how life course and ageing research are linked and can inform each other. Ageing is most easily recognized in the very old with a stereotypical pattern of slowing gait, greying hair and loss of function in many organ systems. For being so universally recognizable, it is perhaps surprising that ageing is so difficult to measure. Genetic and environmental manipulations such as caloric restriction clearly promote longevity in animal models.2 In these models, researchers are advocating for more emphasis on measuring health span and adopting measures of the signs of ageing such as motility or mobility.3 In humans, measures of physical and cognitive performance are often used to define the degree or rate of ageing.4 Changes in these domains are often only apparent very late in life.5 This lack of sensitivity results in a ‘ceiling effect’, where we cannot detect better than usual function. Since most younger-old and middle-aged adults function in this usual range, it is not possible to use basic measures of physical and cognitive function to understand ageing earlier in life. Biomarkers of the process of ageing have long been sought, but no single measure has been found that can compete with chronological age itself in prediction mortality or health span.6 Measures that are informative about the ageing process across the lifespan are needed to advance life course epidemiology to study ageing. One important question for life course epidemiology of ageing is: ‘When does ageing begin’? This would reveal opportunities for delaying its start or maximizing development before its onset. Some would argue that ageing begins at conception, or even before conception,7 in that measures linked to ageing like telomere length8 and mitochondrial heteroplasmy9 are inherited. Certainly there is much to learn from the field of the developmental origins of health and disease (DOHaD). Current studies are limited in design by the selection of measures chosen for purposes other than ageing, yet are currently most valuable to address questions of risk for disease, disability and death from the vantage point of early life determinants. Looking further down the line, others would define the start of ageing as the period starting after the achievement of peak development. After this point, there can be stability or the earliest signs of decline. Endurance in physical activity, particularly maximal oxygen consumption, is well known to begin to decline around age 40.10 This is recognized in the age of peak performance of marathon runners as well as in physiological studies that assess volume of oxygen uptake (VO2) serially. Many epidemiological studies of ageing have started only at age 65 or 70, and thus have missed the opportunity to understand the roles of peak development and early decline as risk factors for future function and ageing. Conversely, many of the ongoing studies in middle age or younger have not included age-sensitive measures. Promising measures include VO2 max,10 bone density11 and muscle strength,12 all of which have been shown to have age-related declines well before age 65. The variable course of ageing is an important challenge in doing life course research. Variability itself is prognostic for poor health outcomes.13 Increasing the frequency of assessment can aid in understanding this. Perhaps the field could borrow the approach of using frequent ’burst’ assessments from psychology14 which has been shown to capture response to stress and recovery. Potentially, the process of ageing might be revealed earlier by the use of tests of vulnerability or resilience to stressors. Such an approach is being adopted in the development of drugs in model organisms. Testing endurance with VO2 max might be considered a stress test of capacity to respond to a stressor, reflecting vulnerability or resilience due to ageing. As noted by Ben-Shlomo, Copper and Kuh,1 the assessment of response to stressors can be considered in the context of the sensitive periods in the life course. Ageing and age-related chronic disease are intrinsically linked in that age is a risk factor for disease and multimorbidity is a major contributor to age-related decline. It is not certain whether these can be disentangled in longitudinal studies. The previous emphasis of ageing studies on disease outcomes has considered many diseases such as osteoporosis and cardiovascular disease (CVD) individually, limiting our ability to look at ageing or shared environmental risk as common underlying factors. Many of these conditions share smoking, diet and activity as common aetiological factors. Attempts to estimate an individual’s biological age have considered many chronic diseases as being driven primarily by age.15 One of the reasons that age is a strong risk factor is that it captures cumulative exposure to modifiable risk factors. However, these factors are often specific to a particular population or time. Ideally, markers for biological age should be capturing processes that are universal and intrinsic to the ageing process and should be distinguished from factors that are external and selective.4 Comparisons across populations show large differences in certain age-related diseases such as CVD, diabetes and some cancers. Much of this variation can be explained by long-term exposure to risk factors. Age may appear to be important because it is capturing the duration of exposure. This is not the same as ageing per se. As we consider the opportunities to leverage ongoing longitudinal studies to understand ageing outcomes, we need to recognize that there are birth cohort differences and secular trends that will challenge our research. For example, rates of smoking have declined in each successive birth cohort so that the oldest adults in the population now represent a less selected survivorship of their birth cohort.16 It will continue to be important to monitor trends in health to determine whether morbidity is expanding or contracting with increasing longevity. We should continue to follow cohorts into old age, but with an urgent need to identify measures that can reveal the earliest critical time points that can be targeted to optimize ageing.