Life course epidemiology

Table of Contents

Life course epidemiology
Initial notes
Annotations on common readings
Annotated additions by students
Idea: How do we identify and disentangle the biological and social factors that build on each other over the life course from gestation through to old age?

Initial notes

The readings mostly relate to "life course epidemiology," that is, Fetal & developmental origins of diseases in late life (Barker being generalized by Ben-Shlomo=common reading 1), in some tension with development over the life course (incl. Berney reviewing lifetime accumulation of hazards in relation to health in old age). In contrast to this approach, we have Brown on life course influences on depression (not necessarily in old age)=common reading 2. In what ways could either side usefully draw methods, data, results from the other?
Mini-lecture
Notes and annotations from 2007 course, 2009
Common readings and cases: Ben-Shlomo 2002 (Life course development of disease), Brown 1978 (Life Events and Difficulties)
Supplementary Reading: Barker 1998,pp43-80, Berney 2000, Davey-Smith 2007, Krieger 2005b, Kuh 2003, Lynch 2005.

Annotations on common readings



Annotated additions by students

(In alphabetical order by author's name with contributor's initials and date at the end.)

Berney, L., D. Blane, et al. (2000). Life course influences on health in old age. Understanding health inequalities. H. Graham. Buckingham [England], Open University Press: 79-95.

“The ‘life course perspective’ holds that social organisation structures life
chances so that advantages and disadvantages cluster cross-sectionally and accumulate
longitudinally (Berney et al.)”

Previous studies have shown that childhood circumstances modulate adult health and socioeconomic standing. Additively, living and working conditions in adult life influences health after retirement. Berney and colleagues notes a lack of research focusing on health inequalities in relation to the post-retirement population (a group possessing the highest levels of morbidity, mortality and health service utilization). It is contended that cross-sectional studies are able to explain only some of the variations observed in the distribution of illnesses. The authors posit, since most chronic illnesses tend to take several decades to develop, birth cohort studies constitute the most powerful research method for examining life course influences on health. However, their time lag to maturation (age where common illnesses of old age are manifested) renders the collection of retrospective life course data necessary for progression.

Berney and colleagues employed a stratified random sample (N=294) of the surviving participants of the Boyd Orr cohort (a 1937-1939 study of the diet and health of British children). Gathering lifegrid retrospective data on households, residences, occupations and tobacco smoking since baseline contact. Additionally, current socio-economic circumstances, self-reported illness and major diseases, prescribed medication, anthropometric measures, blood pressure and lung function were ascertained. The selected hazards of this study exhibited social patterning in exposure. Furthermore, they offered a biologically plausible link between exposure and morbidity/mortality. The calculated lifetime hazard exposure score is said to have provided, “a measure of the combined ‘insults’ with which the body’s regenerative mechanism has to cope. (Berney et al.).”

Berney and colleagues claim that the results of their study were consistent with the theory that material and environmental disadvantage accumulates over the life course. For both men and women, social class of last main occupation was strongly associated with previous lifetime hazard exposure, the largest difference in exposure was found between the manual and non-manual groups of this indicator. Among the non-occupational indicators, housing tenure and benefits status was strongly associated with previous lifetime hazard exposure for men and for women respectively. Interestingly, the effects of life course influences were observed to be more apparent on objective than subjective (self-reported) measures. Berney and colleagues surmise that self-reported measures are more a gauge of current social circumstances and physiological well-being, while objective measures index the impact of the combined life course exposures on an individual’s physiological state. It is proposed that health inequalities in adulthood reflect a lifetime of differential accumulation of exposure to health damaging and health promoting environments

The authors assert that no stage of the life course is “particularly privileged”, thus policy interventions improving living and working conditions for people at all stages would work to reduce health inequalities. The deficits of this study includes, small sample size (low statistical power) and follow-up loss of the more disadvantaged individuals (any resulting bias was argued to be conservative). (SY)