However, multiple SEPs measured at different stages of the life course, which provide a more complete picture of the effect of SEP on health,, have rarely been explored in population-based studies of chronic pain.
Patient views towards cardiovascular screening have been explored in populations at high risk of developing CVD, but these may differ from people at lower risk [ 13].
Biological data mining approaches, particularly those related to artificial intelligence and machine learning, could address current epidemiologic limitations and are starting to be explored in population-based studies that include patient and biologic level data [ 5, 6].
However, the relationship between these factors and their associated psychopathological impact has not been explored in this population.
The impact of type of organism on development of recurrent sepsis has previously been explored in this population and was not found to be significant [ 6].
Although patients with type 2 diabetes have double the risk of dementia, potential racial/ethnic differences in dementia risk have not been explored in this population.
While the chromatin accessibility landscape of this process has been explored in defined populations, single-cell regulatory variation has been hidden by ensemble averaging.
This has not, however, been explored in African populations where enteric microflora and opportunistic infections may be different and the HIV pandemic is at its peak.
In recent years, the co-variation between SAD and PTSS has been explored in adult populations [ 19].
Furthermore, previous studies have typically explored curative effects of CCT in MDD patients whereas only more recently the preventive potential of CCT has been explored in student populations.
