pathways.lshtm.ac.uk [email protected] @ pathwaysncrm

Allostatic load and health: a crossed-lagged analysis of the

English Longitudinal Study of Ageing (ELSA)

Sanna Read and Emily Grundy

http://pathways.lshtm.ac.uk [email protected]

@PathwaysNCRM

Allostatic load and health

• Need for early indicators of health problems: self-rated health has been used as a predictor, but it is subjective measure → could allostatic load be one?

• Allostatic load is an objective composite measure of accumulated physical wear and tear (McEwen & Stellar, 1993).

frequent and long-term environmental demands → chronic stress→ early signs in primary mediators (stress hormones and anti-inflammatory cytokines) → activation of secondary outcomes (metabolic, cardiovascular and immune systems) → tertiary outcomes (poor health, diseases and eventually death)

• Previous research suggest that allostatic load could be a useful measure of early health problems, but very few longitudinal studies using repeated measures on the topic.

• Disablement process (Verbrugge & Jette ,1994) Pathological changes → Impairments → Functional Limitations → Disability

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Study direction of sequences

• Disablement process and accumulation of allostatic load assume a causal path between the factors.

• To study the directions longitudinal methods are needed.• An effective method to detect direction of sequences of

effects in longitudinal settings is to apply cross-lagged models.


Cross-lagged model


Functional limitation

Self-rated health


Self-rated health

Time 1 Time 2

Allostatic load Allostatic load

Aim

• To investigate the reciprocal association between allostatic load, self-rated health and walking speed as a measure of functional limitation.– allostatic load would predict functional limitation– the association between self-rated health and allostatic

load may be reciprocal or self-rated health may even precede allostatic load.


Cross-lagged model



Self-rated health


Self-rated health

Time 1 Time 2


Aim

• To investigate the reciprocal association between allostatic load, self-rated health and walking speed as a measure of functional limitation.– allostatic load would predict functional limitation– the association between self-rated health and allostatic

load may be reciprocal or self-rated health may even precede allostatic load.


Cross-lagged model



Self-rated health


Self-rated health

Time 1 Time 2


Data

• English Longitudinal Study of Ageing (ELSA) waves 2 and 4 (2004 and 2008) - nationally representative survey of men and women aged 50+ (mean = 63, SD = 9.2 in wave 1). In the present study those aged 60+ in Wave 2 (n = 6132) were used (walking speed available only among 60+)

• Socio-demographic information and self reported health collected in all waves

• Detailed health data including biomarkers collected in alternate waves –biomarker data used to derive an index of allostatic load


MeasuresHealth measures:

Allostatic load; self-rated health; walking speed (functional limitation) (Wave 2 and Wave 4)

Covariates:Age, gender, education (Wave 2)Married/not married; wealth; smoking; physical activity; social support; (Wave 2 and Wave 4)


Allostatic load scores in ELSA• Allostatic load: multisystem physical dysregulation resulting from long-term exposure to stress• Grouped allostatic load index: number of biomakers indicating high risk (upper 25th percentile,

except for peak expiratory flow lower 25th percentile) calculated separately for men and women, weighted by the number of markers per system and adjusted for medication and fasting


System Biomarker

Cardiovascular Systolic blood pressure

Diastolic blood pressure

Inflammation Fibrinogen

C-reactive protein

Lipid metabolism Triglycerides

Glycosylated haemoglobin

Total/HDL cholesterol ratio

Body fat Waist/hip ratio

Respiratory Peak expiratory flow

Self-rated health

Walking speed

Walking speed

Self-rated health

Wave 2 Wave 4

0.51 (0.015)

0.42 (0.016)

0.05 (0.015)

Allostatic load

Allostatic load

0.54 (0.016)

-0.09 (0.020)

-0.07 (0.013)

0.11 (0.014)

-0.04 (0.015)

Results: Cross-lagged model

Adjusted for age, gender, education, marital status, wealth, smoking, physical activity, and social support.

Conclusions & Discussion• Allostatic load predicts functional limitation

→ allostatic load may be a useful early objective indicator of health problems. The drawbacks of using it is that it is a complex composite measure which involves invasive data collection methods and therefore subject to refusal and drop-out. No standardized way of measuring it.

• The association between self-rated health and allostatic load and functional limitations were reciprocal, although the strength of the associations suggested that self-rated health may be an earlier indicator of health problems → The role of self-rate health in the disablement process seem to be less clear: it predicts better functioning, but it is also an outcome of good functioning. Self-rated health is simple and quick to use with high response rates. The limitations are its subjective content and variation from one population to another.


Conclusions & Discussion• As hypothesised, allostatic load predicts later functional

limitations. In the future, it is important to include earlier indicators of chronic stress (neuroendocrine and inflammatory markers) and study longer time spans from middle adulthood to old age to detect the accumulation of stress.


Wave 2 Wave 4

Men Women Men Women

Inflammation (n = 1853) (n = 2187-2194) (n = 1885-1958) (n = 2218-2360)

C-reactive protein >3.3 >3.8 >3.3 >3.5

Fibrinogen >3.6 >3.8 >3.7 >3.8

Cardiovascular (n = 2072) (n = 2616) (n = 2554) (n = 3033)

Systolic blood pressure >148 >149 >145 >145

Diastolic blood pressure >81 >80 >79 >80

Lipid metabolism (n = 1821-1855) (n = 2171-2196) (n = 1993-2017) (n = 2385-2419)

HDL/Total cholesterol ratio >4.73 >4.46 >4.45 >4.15

Triglycerides >2.2 >2.1 >2.1 >2.0

Glycosylated haemoglobin >5.8 >5.8 >6.1 >6.1

Body fat (n = 2304) (n = 2850) (n = 2653) (n = 3152)

Waist/hip ratio >1.00 >0.89 >1.00 >0.90

Respiratory (n = 2199) (n = 2642) (n = 2461) (n = 2882)

Peak expiratory flow <323 <208 <334 <214

Allostatic load 25th percentile high risk cut-off points for all men and women 60+ in the

English Longitudinal Study of Ageing wave 2 (2004) and wave 4 (2008)

Covariates All

Wave 2

n

With complete data

Wave 2

(n = 2349)

With complete data

Wave 4

(n = 2349)

Age 6132 71.5 (8.33) 69.2 (6.80) -

Female 6132 55.5 54.0 -

No qualification 6127 45.6 35.4 -

Being married 6131 62.0 68.6 65.2

Wealth quintile 6064 3.0 (1.39) 3.3 (1.35) 3.4 (1.30)

Physical activity 6075 1.9 (0.88) 2.2 (0.68) 2.0 (0.80)

Current smoking 6131 12.9 10.4 8.3

Perceived social support 5399 4.2 (0.52) 4.2 (0.49) 4.2 (0.50)

Distributions of covariates (% or mean and SD) among men and women in the

English Longitudinal Study of Ageing.

All

Wave 2

n

With complete data

Wave 2

(n = 2349)

With complete data

Wave 4

(n = 2349)

Allostatic load weighted score 4176 1.5 (1.12) 1.3 (1.06) 1.4 (1.05)

Self-rated health 6073

Poor 6.2 3.5 4.5

Fair 18.0 15.8 17.9

Good 31.6 33.5 35.3

Very good 30.3 32.5 31.5

Excellent 13.9 14.7 10.8

Walking speed (m/s) 5438 0.8 (0.28) 0.9 (0.25) 0.8 (0.26)

Distributions of health measures (% or mean and SD) among men and women in

the English Longitudinal Study of Ageing.

Health measures

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