load and health a crossedlagged analysis of the English Longitudinal Study of Ageing ELSA Sanna Read and Emily Grundy httppathwayslshtmacuk pathwayslshtmacuk PathwaysNCRM ID: 327807
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Slide1
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 pathways@lshtm.ac.uk @PathwaysNCRMSlide2
Allostatic load and healthNeed 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
http://pathways.lshtm.ac.ukSlide3
Study direction of sequencesDisablement 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.
http://pathways.lshtm.ac.ukSlide4
Cross-lagged modelhttp://pathways.lshtm.ac.ukFunctional limitationSelf-rated health
Functional limitationSelf-rated healthTime 1
Time 2
Allostatic load
Allostatic loadSlide5
Cross-lagged modelhttp://pathways.lshtm.ac.ukFunctional limitationSelf-rated health
Functional limitationSelf-rated healthTime 1
Time 2
Allostatic load
Allostatic loadSlide6
Cross-lagged modelhttp://pathways.lshtm.ac.ukFunctional limitationSelf-rated health
Functional limitationSelf-rated healthTime 1
Time 2
Allostatic load
Allostatic loadSlide7
Cross-lagged modelhttp://pathways.lshtm.ac.ukFunctional limitationSelf-rated health
Functional limitationSelf-rated healthTime 1
Time 2
Allostatic load
Allostatic loadSlide8
Cross-lagged modelhttp://pathways.lshtm.ac.ukFunctional limitationSelf-rated health
Functional limitationSelf-rated healthTime 1
Time 2
Allostatic load
Allostatic loadSlide9
AimTo investigate the reciprocal association between allostatic load, self-rated health and walking speed as a measure of functional limitation.allostatic load would predict functional limitationthe association between self-rated health and allostatic load may be reciprocal or self-rated health may even precede allostatic load.
http://pathways.lshtm.ac.ukSlide10
Cross-lagged modelhttp://pathways.lshtm.ac.ukFunctional limitationSelf-rated health
Functional limitationSelf-rated healthTime 1
Time 2
Allostatic load
Allostatic loadSlide11
AimTo investigate the reciprocal association between allostatic load, self-rated health and walking speed as a measure of functional limitation.allostatic load would predict functional limitationthe association between self-rated health and allostatic load may be reciprocal or self-rated health may even precede allostatic load.
http://pathways.lshtm.ac.ukSlide12
Cross-lagged modelhttp://pathways.lshtm.ac.ukFunctional limitationSelf-rated health
Functional limitationSelf-rated healthTime 1
Time 2
Allostatic load
Allostatic loadSlide13
Cross-lagged modelhttp://pathways.lshtm.ac.ukFunctional limitationSelf-rated health
Functional limitationSelf-rated healthTime 1
Time 2
Allostatic load
Allostatic loadSlide14
DataEnglish 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 wavesDetailed health data including biomarkers collected in alternate waves –biomarker data used to derive an index of allostatic load
http://pathways.lshtm.ac.ukSlide15
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) http://pathways.lshtm.ac.ukSlide16
Allostatic load scores in ELSAAllostatic load: multisystem physical dysregulation resulting from long-term exposure to stressGrouped 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 http://pathways.lshtm.ac.uk
System
Biomarker
Cardiovascular
Systolic blood pressure
Diastolic blood pressure
InflammationFibrinogen
C-reactive protein
Lipid metabolism
Triglycerides
Glycosylated
haemoglobin
Total/HDL cholesterol ratio
Body fat
Waist/hip ratio
Respiratory
Peak expiratory flowSlide17
Self-rated health
Walking speedWalking 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.Slide18
Self-rated health
Walking speedWalking 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.Slide19
Self-rated health
Walking speedWalking 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.Slide20
Conclusions & DiscussionAllostatic 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.
http://pathways.lshtm.ac.ukSlide21
Conclusions & DiscussionAs 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.
http://pathways.lshtm.ac.ukSlide22
Wave 2Wave 4
MenWomen
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 25
th
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
)Slide23
CovariatesAll Wave 2n
With complete dataWave 2(n = 2349)
With complete dataWave 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.Slide24
All Wave 2nWith complete data
Wave 2(n = 2349)With complete dataWave 4(n = 2349)
Allostatic load weighted score
4176
1.5 (1.12)
1.3 (1.06)1.4 (1.05) Self-rated health6073
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