Association of lung function with physical, mental and cognitive function in early old age
1,2,3 Archana Singh-Manoux, PhD
1Aline Dugravot, MSc
1,4Francine Kauffmann, MD
5Alexis Elbaz, MD, PhD
3Joel Ankri, MD, PhD
1Hermann Nabi, PhD
2Mika Kivimaki, PhD
1Séverine Sabia, PhD
* Corresponding author & address:
1 INSERM, U1018, Centre for Research in Epidemiology and Population Health
Hôpital Paul Brousse, Bât 15/16
16 Avenue Paul Vaillant Couturier
94807 VILLEJUIF CEDEX, France
Telephone: +33 (0)1 77 74 74 10 Fax: +33 (0)1 77 74 74 03 Email: email@example.com
2Department of Epidemiology and Public Health University College London, UK
3Centre de Gérontologie, Hôpital Ste Périne, AP-HP, France 4 Université de Paris-Sud XI, Paris, France5 INSERM, U708, F-75013, Paris, France
Word count: abstract: 208; main text: 2985
Lung function predicts mortality, whether it is associated with functional status in the general population remains unclear. This study examined the association of lung function with multiple measures of functioning in early old age. Data are drawn from the Whitehall II study;
), walking speed data on lung function (forced expiratory volume in one second, height FEV1
(over 2.44 m), cognitive function (memory and reasoning), and self-reported physical and mental functioning (SF-36) were available on 4443 individuals, aged 50-74 years. In models adjusted for age, one standard deviation (SD) higher height-adjusted FEV was associated 1
with greater walking speed (beta=0.16, 95% CI: 0.13, 0.19), memory (beta=0.09, 95% CI: 0.06, 0.12), reasoning (beta=0.16, 95% CI: 0.13, 0.19), and self-reported physical functioning (beta=0.13, 95% CI: 0.10, 0.16). Socio-demographic measures, health behaviours (smoking, alcohol, physical activity, fruit/vegetable consumption), BMI and chronic conditions explained two-thirds of the association with walking speed and self-assessed physical functioning and over 80% of the association with cognitive function. Our results suggest that lung function is a good “summary” measure of overall functioning in early old age.
Keywords: ageing, lung function, cognitive function, physical function
1;2 as Lung function is known to increase up to the mid-twenties and then diminish with agestatic recoil pressure of the lungs decreases leading to lowered forced expiratory flow and vital capacity. There is evidence, from at least two strands of research, to show that poor lung function is associated with poor functional status. One, research suggests that lung function
3-78 and dementia; perhaps due to changes in the central predicts poor cognitive outcomes
nervous system through processes such as subclinical vascular disease, resulting from
9inflammation, oxidative stress or cardiovascular risk factors, or hypoxia-induced changes in
10;11neurotransmitter metabolism. Two, Chronic Obstructive Pulmonary Disease (COPD) is
12 13;14associated with complex chronic comorbidities,even in middle-aged patients. There is
also some evidence to support the hypothesis that pulmonary function is associated with
14-16physical function in the general population.
1;17-202122Lung function, like cognitive and physical function, declines with age. Whether
lung function is a causal risk factor for cognitive and physical functioning is difficult to establish using observational data, as is the case in most of the studies in this domain. Nevertheless, the interrelationship between different aspects of functioning is important as the decline in lung function might be a forerunner of decline in physical and cognitive function. If this is the case, then determinants of lung function and decline might provide important targets of intervention. In this study we examine the relationship of lung function with cognitive and physical in early old age. As the data come from an observational study and the analysis cross-sectional we cannot infer causality. However, by examining the association of lung function with both cognitive and physical functioning we hope to gain better understanding of the importance of lung function for ageing outcomes.
Data are drawn from Phase 7 (2002-2004) of the Whitehall II study, set up in 1985-
23 All participants gave consent to 1988 on 10,308 (67% men) individuals, aged 35-55 years.
participate and the University College London ethics committee (UCLH Committee Alpha, #85/0938) approved this study.
Participants were allowed to opt out of spirometry testing if they were coughing up blood or had a pneumothorax, severe angina, heart attack, stroke, pulmonary embolism, aneurysm, a perforated ear drum or hernia, recent surgery (ear, eye, stomach, chest), or blood pressure >180/96 mmHg on the day; excluding 25.5% of participants.
Lung function was measured using a portable flow spirometer (MicroPlus Spirometer, Micro
Medical Ltd, Kent, UK), administered by a trained nurse. We assessed Forced Vital Capacity
24(FVC) and Forced Expiratory Volume in 1 second (FEV) based on standardised methods. 1
The largest FVC and FEV values from the three manoeuvres was used in the analysis. As 1
lung volumes are related to body size and standing height is the most important correlating variable, the lung function measure was corrected for height by dividing by the square of the subject's standing height and multiplying by the square of the sample mean height, 1.77 m in
25men and 1.63 m in women. This standard correction procedure ensures that the observed variation in lung function is due to factors other than body size.
Walking speed: Walking speed was measured over a clearly marked 8-ft (2.44m)
26walking course using a standardized protocol. Participants wore either low-heeled close-
fitting footwear or walked barefoot with instructions to “walk to the other end of the course at
your usual walking pace, just as if you were walking down the street to go the shops. Walk all the way past the other end of the tape before you stop.” Three tests were conducted and the
fastest walk (2.44 metres/minutes) was used in the analysis.
Cognitive Function: Two tests were used. The first was a test of short-term verbal
memory, assessed with a 20-word free recall test. Participants were presented a list of 20 one or two syllable words at two second intervals and were then asked to recall in writing as many of the words in any order and had two minutes to do so. The second was a test of reasoning,
the Alice Heim 4-I (AH4-I) test, composed of a series of 65 verbal and mathematical
27. It tests inductive reasoning and with only 10 reasoning items of increasing difficulty
minutes allocated to the test it is also a measure of processing speed.
Self-assessed health functioning was assessed using the Short Form 36 (SF-36)
28General Health Survey Scales. The SF-36 is a 36-item questionnaire on general health status that can be summarized into physical and mental components scores (PCS and MCS) to
29assess physical and mental functioning. Physical functioning declines with age but mental
30functioning has been shown to improve with age.
The covariates were age, sex, ethnicity (white or non-white), education (lower primary
or lower, lower secondary, high school, first university degree or higher), occupational
position, health behaviours, Body Mass Index (BMI) and chronic conditions. Occupational
position, classified as high, (administrative grades), intermediate (professional or executive grades) and low (clerical or support grades) position) is a comprehensive marker of socioeconomic circumstances and is related to salary, social status and level of responsibility at work. As of August 1992 the salary range among high grade employees was ?25 330 - ?87
23620 and among low grade employees ?7 387 – ?11 917.
Smoking status was self-reported (never, ex, or current smoker). Alcohol consumption
was assessed as number of alcoholic drinks (“measures” of spirits, “glasses” of wine, and “pints” of beer) consumed in the last week and converted to number of alcohol units (1
31unit=8g alcohol) consumed per week. This measure was highly skewed and was log
transformed for the analysis. Diet was assessed via a question on the frequency of fruit and
vegetable consumption (8-point scale, ranging from „seldom or never‟ to „two or more times a
32day‟), converted to frequency of consumptions per week. Physical activity was assessed
using 20 items on frequency and duration of participation in different physical activities (e.g., walking, cycling, sports) that were used to compute hours per week of moderate and vigorous activity. Body Mass Index (BMI) was calculated as weight in kg/height in meters squared. Weight was measured in underwear to the nearest 0.1 kg on Soehnle electronic scales. Height was measured in bare feet to the nearest 1mm using a stadiometer with the participant standing erect with head in the Frankfort plane.
Chronic conditions included as covariates were coronary heart disease (CHD), diabetes,
stroke and respiratory illness. CHD events included non-fatal myocardial infarction (MI) and
„definite‟ angina. MI was determined using data from ECGs, cardiac enzymes and physician
33 records following MONICA criteria. Angina was assessed based on the participant‟sreports
34of symptoms, with corroboration in medical records for nitrate medication or ECG abnormalities. Diabetes assessment was based on fasting glucose (>7.0 mmol/L) or 2-hour
postload glucose (>11.1 mmol/L) or previous use of anti-diabetic medication or reported doctor diagnosed diabetes. Both stroke and respiratory illness (chronic bronchitis, emphysema, asthma, allergy resulting in lung or breathing problems, sinusitis) were assessed using self-reports at Phases 1, 3, 5 and 7.
values were divided into tertiles For the descriptive analysis height-corrected FEV1
separately for men and women. Its association with covariates was examined using chi-square or a one way analysis of variance. Subsequently, age and all measures of functioning were standardized to z scores (mean=0 and standard deviation (SD)=1) separately in men and women. As all predictors and outcomes in the regression analyses that follow were continuous measures, we used standardized z-scores (mean = 0, standard deviation = 1) in the analysis. Standardised regression coefficients represent the change in the outcome variable, expressed as a fraction of the standard deviation, per 1 standard deviation change in the predictor variable. Standardised regression estimates allow comparison of the associations of the
35predictor with different outcome measures; in our case first the association of age with
different measures of functioning and then that of lung function with measures of physical, cognitive and mental functioning. We first examined the association between a SD greater age and standardized measures of lung, cognitive, physical and mental functioning using linear regression. These analyses were successively adjusted for ethnicity, sex, education, occupational position, health behaviours (tobacco and alcohol consumption, diet, physical activity), BMI and chronic conditions.
The next set of analysis examined the association between FEVand functioning using 1
linear regression. We used five blocks of covariates to explain this association using the
36following formula 100*(beta– beta )/beta. These blocks unadjustedcontrolling for the covariateunadjusted
were age, ethnicity & sex, education and occupation, health behaviours and BMI, and the final block was chronic conditions. As a next step all these covariates were entered together in order to estimate the attenuation in the association between lung function and measures of cognitive, physical, and mental functioning.
A total of 6483 participants came to the medical examination and 4829 of these undertook the lung function tests, our analysis is based on 4443 (3111 men and 1332 women) participants with complete data; those not in the analysis were older (62.1 vs.60.7 years, p<0.0001). The age of those included in the analysis ranged from 50.5 to 73.6 years, table 1 shows all covariates to be associated with FEV (all p?0.03). The analysis in this study used 1
height-corrected FEV but replacing it with height-corrected FVC did not much change the 1
results (available from the first author).0
Figure 1 presents the cross-sectional associations, modelled to show effects of a SD increment in age on functioning, standardized to allow comparability. The interaction terms showed no sex differences in the association between age and functioning (all p ?0.09) allowing us to combine men and women in the analysis although lung function was standardized separately in men and women due to differences in lung volume. The standardised beta represents the change in the functioning measures, expressed as a fraction of the standard deviation, per 1 standard deviation change in age. The standard deviations were 5.9 years for age, 0.6 litres (0.5 in women) for FEV, 2.4 for memory, 10.8 for reasoning, 0.3 1
metres/minute of walking speed, 8.4 on the physical and 8.8 on mental functioning score. These SDs allow the reader to convert the standardised results back to regression coefficients. For example, 1 SD increase in age (corresponds to 5.9 years) was associated with lower scores on lung function (beta=-0.38, 95% CI: -0.41, -0.36), Figure 1. In men this corresponds to 0.23 litres (.38 multiplied by the standard deviation, here 0.6 litres) and in women 0.19 litres lower FEV1.
One SD increase in age was also associated (Figure 1) with lower memory (beta=-0.25, 95% CI: -0.28, -0.22), reasoning (beta=-0.23, 95% CI: -0.26, -0.20), walking speed (beta=-0.20, 95% CI: -0.23, -0.17), physical functioning (beta=-0.16, 95% CI: -0.19, -0.13) but
higher scores on mental functioning (beta=0.22, 95% CI: 0.19, 0.25) implying that the older participants had better mental functioning. The association with age was strongest for lung function, adjustment for multiple covariates did not much change this association (beta=-.37, 95% CI: -0.40, -0.34), see Figure 1. The association between age and all functioning measures was robust to adjustment for the covariates, results in tabular form available on request.
Table 2 presents the association of lung function with walking speed, cognitive function and self reported physical and mental functioning, again standardized to z-scores.
(all p?0.10) allowed men and The non-significant interaction term between sex and FEV1
women to be combined in the analysis. One standard deviation higher FEV was associated 1
with greater memory (beta=0.17 (95% CI: 0.15, 0.20)), reasoning (beta=0.23 (95% CI: 0.20, 0.26)), walking speed (beta=0.21 (95% CI: 0.18, 0.24)) and physical functioning (beta=0.17 (95% CI: 0.14, 0.20)) but lower mental functioning (beta=-0.07 (95% CI: -0.10, -0.04)). Age explained the largest part of this association, 47% for memory, 30% for reasoning, 24% for walking speed, 24% for physical functioning, and all of it for mental functioning (129%). All covariates taken together explained less of the association of lung function with the measures of physical functioning, walking speed (62%) and self-assessed physical functioning (65%), compared to the measures of cognitive function, memory (82%) and reasoning (91%).
This study, based on a large non-patient sample of adults aged 50-74 years, shows lung function to be associated with both cognitive and physical functioning, associations only partly explained by age. Our results also show lung function to have a pervasive association with a range of socioeconomic, behavioural and health measures. These results extend previous knowledge on the value of lung function as a good “summary” measure of health
and functional status.
Life expectancy is increasing at the rate of five or more hours per day in the developed
37 The challenge posed by population ageing is to ensure that the extra years of life will world.
physical, mental be of good quality and free from high-cost dependency. Thus, functioning –
and cognitive – is increasingly examined as an outcome in the ageing literature. Positive health trajectories are related to higher quality of life, longer independence and considerably lower medical and social care costs. Chronological age is a good indicator of ageing but it does not capture the variability in exposure and response to environmental insults that could well be better captured in lung function tests, even in populations not composed of COPD patients.
Previous research has shown poor lung function to be associated with poor cognitive
3-78 outcomes and dementia.Three mechanisms have been proposed to explain this association: (1) lung function as a risk factor, (2) poor lung function as a consequence of dementia or
8impaired cognition and (3) the common cause hypothesis. Many studies have examined the
3-8;383first explanation; inferring causality due to the analytic method or longitudinal design of
4;5the study. It is clear that the association between lung and cognitive function is not
6restricted to old age or to sick populations. Studies show this association in mid, and late
7midlife. Spirometry tests in children aged 7 are associated with cognition in analysis adjusted
39for multiple covariates, perhaps reflecting shared neural and endocrine regulatory processes as well as common response to environmental exposures.
There is evidence of the impact of COPD on the non-pulmonary system, even in non-elderly populations where it was shown to be associated with lower extremity functioning, exercise performance, skeletal muscle strength and self-reported limitation in basic physical
40actions. Research on COPD increasingly views it not simply as a disease of the lungs but as
12;41a chronic inflammatory syndrome accompanied by complex chronic comorbidities. Our
results show lung function to be associated with both an objective (walking speed) and a