Associations between lung function and physical and cognitive health in the Canadian Longitudinal Study on Aging (CLSA): A cross-sectional study from a multicenter national cohort.

BACKGROUND: Low lung function is associated with high mortality and adverse cardiopulmonary outcomes. Less is known of its association with broader health indices such as self-reported respiratory symptoms, perceived general health, and cognitive and physical performance. The present study seeks to address the association between forced expiratory volume in 1 second (FEV1), an indicator of lung function, with broad markers of general health, relevant to aging trajectory in the general population. METHODS AND
FINDINGS: From the Canadian general population, 22,822 adults (58% females, mean age 58.8 years [standard deviation (SD) 9.6]) were enrolled from the community between June 2012 and April 2015 from 11 Canadian cities and 7 provinces. Mixed effects regression was used to assess the cross-sectional relationship between FEV1 with self-reported respiratory symptoms, perceived poor general health, and cognitive and physical performance. All associations were adjusted for age, sex, body mass index (BMI), education, smoking status, and self-reported comorbidities and expressed as adjusted odds ratios (aORs). Based on the Global Lung Function Initiative (GLI) reference values, 38% (n = 8,626) had normal FEV1 (z-scores >0), 37% (n = 8,514) mild (z-score 0 to > -1 SD), 19% (n = 4,353) moderate (z-score -1 to > -2 SD), and 6% (n = 1,329) severely low FEV1 (z-score = < -2 SD). There was a graded association between lower FEV1 with higher aOR [95% CI] of self-reported moderate to severe respiratory symptoms (mild FEV1 1.09 [0.99 to 1.20] p = 0.08, moderate 1.45 [1.28 to 1.63] p < 0.001, and severe 2.67 [2.21 to 3.23] p < 0.001]), perceived poor health (mild 1.07 [0.9 to 1.27] p = 0.45, moderate 1.48 [1.24 to 1.78] p = <0.001, and severe 1.82 [1.42 to 2.33] p < 0.001]), and impaired cognitive performance (mild 1.03 [0.95 to 1.12] p = 0.41, moderate 1.16 [1.04 to 1.28] p < 0.001, and severe 1.40 [1.19 to 1.64] p < 0.001]). Similar graded association was observed between lower FEV1 with lower physical performance on gait speed, Timed Up and Go (TUG) test, standing balance, and handgrip strength. These associations were consistent across different strata by age, sex, tobacco smoking, obstructive, and nonobstructive impairment on spirometry. A limitation of the current study is the observational nature of these findings and that causality cannot be inferred.
CONCLUSIONS: We observed graded associations between lower FEV1 with higher odds of disabling respiratory symptoms, perceived poor general health, and lower cognitive and physical performance. These findings support the broader implications of measured lung function on general health and aging trajectory.

Introduction

Pulmonary function measurements expressed as the forced expiratory volume in 1 second (FEV1) or forced vital capacity (FVC) significantly predicts all-cause and cardiovascular mortality. This has been consistently shown in numerous epidemiological studies and across populations of diverse ethnic, geographic, and socioeconomic backgrounds [1-7]. Low FEV1 is also significantly associated with noncardiopulmonary comorbidities including diabetes, chronic kidney diseases, osteoporosis, and dementia in the general population [8-11]. This is independent of tobacco smoking, age, chronic lung diseases, and other comorbidities [2,5]. Due to these strong and consistent associations, it has been suggested that pulmonary function may be a marker of general physiological health and closely relate to the processes of aging [12-15].

Aging is associated with a gradual decline in physiological and functional capacity, which affects all tissues, organs, and systems in a nonuniform way [15]. Furthermore, the decline in physiological and functional capacity is a common risk factor for many chronic noncommunicable diseases and confers high morbidity and mortality [14]. A notable and universal feature of aging is the progressive and generalized dysfunction of the musculoskeletal system leading to reduced muscle mass, strength, and endurance [16]. In its severest form, generalized musculoskeletal dysfunction is associated with significantly higher risks for disability, falls, fractures, hospitalizations, and mortality [17, 18]. While there are many chronic comorbidities including pulmonary diseases that can exacerbate dysfunction of the musculoskeletal system and functional impairment, we speculate that impaired lung function may also be a feature of the primary and generalized process of functional decline associated with aging. In the present study, we seek to understand the relationship between low FEV1 with muscle strength, physical performance, and self-reported health measures independent of lung disease and whether these relationships may be modified by age and other similar risk factors.

The Canadian Longitudinal Study on Aging (CLSA) is an ongoing interdisciplinary cohort study that aims to study the predictors and consequences of aging in a random sample of adults from the Canadian population [19]. In the present study, we examined the cross-sectional baseline data, for associations between FEV1, with self-reported respiratory symptoms, self-perceived poor general health, and cognitive and physical performance. The findings will help to understand the burden and broader implications of low pulmonary function in the general population independent of lung disease. It can also inform on potential novel pathways that can lead to improved lung health and reduce the burden of symptoms and cognitive and physical impairment as the population ages.

Methods

A protocol of the planned analysis (S1 Protocol) was submitted to the CLSA Data and Sample Access Committee and Hamilton Health Sciences Ethnics Committee for approval prior to accessing the data and analysis. CLSA is a large, nationally representative, stratified random sample of 51,338 participants aged 45 to 85 years old at baseline. The study design and methodology has been published [19]. Enrollment was limited to participants who speak and read English or French. Residents from the Canadian 3 territories, remote geographical regions, First Nations reserves, long-term care facilities, and members of the Armed Forces were excluded. A subset of the CLSA cohort (n = 30,097) was randomly selected from 25- to 50-km radius across 11 centers and 7 Canadian provinces (Victoria, Vancouver mainland, Calgary, Winnipeg, Hamilton, Ottawa, Montreal, Sherbrooke, Halifax, and St John’s) to attend a data collection site (DCS) for more comprehensive assessments. At these dedicated DCS, participants were interviewed and underwent standardized physical, cognitive, and clinical assessments (comprehensive cohort) to provide data on demographics, lifestyle, health, and clinical information. In the remaining participants (tracking cohort, n = 21,241), similar data were collected by a telephone interview. The demographics of the tracking and comprehensive cohorts are provided in S1 Table, which showed comparable baseline characteristics. For the present study, only participants from the comprehensive cohort, with complete baseline data and high-quality spirometry, were included. Selection of high-quality spirometry data was in accordance with the American Thoracic and European Respiratory Society (ATS/ERS) quality standards, which required 3 acceptable maximal efforts and a reproducibility of <150 cc between the 2 highest FEV1 and FVC [20]. The protocol and conduct of CLSA study were approved by the Canadian Institute of Health Research Advisory Committee on Ethical, Legal and Social Issues, Hamilton Research Ethics Board, and all institutional research ethics board of participating sites. All participants provided informed written consent to partcipate in CLSA the study. This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 STROBE Checklist).

Spirometry measurements

Lung function was measured with the TruFlow Easy-One Air Spirometer (NDD Medical Technologies, Switzerland) and in DCS following a standardized protocol in keeping with ATS/ERS recommendations [20]. Prior to spirometry testing, all participants completed an interviewed-based questionnaire, physical measurements, electrocardiograph, and carotid ultrasound, which took approximately 45 to 60 minutes to complete. During this time, participants did not consume any large meals, alcohol, or cigarettes. Those screened positive for major contraindications to spirometry were excluded (S2 Table) [21]. The highest FEV1 and FVC from 3 acceptable maximal efforts were selected. The Global Lung Function Initiative (GLI) reference values appropriate for age, sex, height, and ethnicity z-scores were used to classify participants into grades of reduced FEV1 [22]. These included (1) normal FEV1 (z-scores >0 standard deviation [SD]); (2) mild (0 to > −1 SD); (3) moderate (−1 SD to > −2 SD); and (4) severe FEV1 (= <−2 SD). The FEV1/FVC GLI lower limit of normal (LLN) was used to identify obstructive impairment. It is important to note that while we have considered all GLI FEV1 z-scores below the population mean (z-score <0 SD) as low, current guidelines considers z-scores >−2 SD to be within the normal range [22].

Covariates

Self-reported data from questionnaires included age (45 to 54, 55 to 64, 65 to 74, and 75+ years), sex, smoking status (never [lifetime <100 cigarettes], former [last cigarette smoked >12 months], and current), education (primary and below, secondary, and >secondary), known cardiovascular disease (CVD) (angina, congestive heart failure, and myocardial infarction), chronic obstructive pulmonary disease (COPD), asthma, and major chronic diseases (incorporated into the comorbidity index 0, 1 to 2, and >=3). Height and weight were measured with standardized methods and equipment. Body mass index (BMI) was calculated as weight divided by height-squared and categorized into <25, 25 to 30, and >30 kg/m2. Self-reported physical activity was assessed by the Physical Activity Scale for the Elderly (PASE) questionnaire with higher weighted scores indicating higher activity levels in the previous 7 days [23].

Outcomes

Self-perceived general health was assessed by asking participants to rate their present heath as either excellent, very good, good, fair, or poor. Responses were reclassified as “POOR” (fair/poor) or “GOOD” (for all else). This self-rating of global health has been extensively studied and shown to be a robust predictor of later health outcomes including mortality [24,25]. Self-reported breathlessness, wheeze, or cough occurring at least 1 night per week or while walking on flat surfaces were classified as moderate to severe respiratory symptoms. Handgrip strength was measured with a dynamometer (Tracker Freedom Wireless), and the highest value from 3 consecutive trials in the dominant hand was recorded [26]. The Timed Up and Go (TUG) test (TUG) was recorded as the time (seconds) to rise from a chair, walk 3 meters at usual pace (with or without walking aids), turn around, walk back, and sit down [27]. Gait speed recorded the speed (meters per second) to walk 4 meters at usual pace [28]. Standing balance recorded the time (seconds) standing on one leg with hands on hips, eyes open, up to a maximum of 60 seconds [29]. All of these physical performance tests have been shown to be strongly predictive of poor long-term health and functional outcomes including mortality [30]. The semantic fluency test assessed cognitive performance by asking participants to name as many animals within 60 seconds. Test scores were standardized for age, sex, and education, with scores <45 showing significant associations with low self-rated health, mental health, activities of daily living, and psychiatric disorders [31,32].

Analysis

Means (SD) and frequency (%) statistics were used to summarize normally distributed continuous variables and categorical data, respectively. The assumption of normality and constant variance of the FEV1, FVC, and covariates were assessed by visual inspection of histograms and plots of residuals against fitted values. Multilevel logistic regression was used to estimate the association between low FEV1 severity categories (relative to FEV1 > 0 SD as reference) with categorical outcomes. Similar multilevel linear regression was used to estimate the mean differences in physical performance outcomes for each FEV1 levels relative to the reference group (FEV1 > 0 SD). Unadjusted estimates are provided, and adjusted estimates were calculated controlling for age, sex, BMI, education, smoking status, self-reported asthma, COPD, CVD, and comorbidity index (excluding asthma, COPD, and CVD), with centers as random effect. The goodness of fit tests (likelihood ratio test, deviance, Akaike information criterion [AIC], and Bayesian information criterion [BIC]), multicollinearity (tolerance and variance inflation factor), and visual inspection of residuals were conducted to assess model stability and robustness. Trimmed inflation and analytical (rescaled) weights were applied to reduce the effect of selection bias and maintain the national representativeness and generalizability of the data [19]. Similar analyses after removing participants with spirometric airflow obstruction (AO; FEV1/FVC

Results

From the comprehensive cohort, 22,822 participants (52% females, mean age 58.8 [SD 9.6]) with high-quality spirometry and no missing data were included in the study. The baseline characteristics of included participants are provided in Table 1. Among this cohort, 38% (n = 8,626) had normal FEV1, 37% (n = 8,514) mild, 19% (n = 4,353) moderate, and 6% (n = 1,329) severely low FEV1 (=<−2 SD). The overall prevalence of AO defined by FEV1/FVC<0.70 was 11% (n = 2,661) and by GLI FEV1/FVC 30 (26% versus 38%), lower education level (4% versus 8%), and lower mean physical activity (153.2 ± 76.6 versus 139.2 ± 81.8). There were also higher percentages of self-reported asthma (13% versus 29%), COPD (4% versus 16%), CVD (9% versus 17%), and multiple comorbidities (35% versus 45%).

Table 1

Baseline characteristics by categories of FEV1 levels.

	Overall	Categories of FEV1 according to GLI z-scores
		>0 SD	0 to > −1 SD	−1 to > −2 SD	=<−2 SD
		Normal	Mild	Moderate	Severe
N, %	22,822 (100%)	8,626 (38%)	8,514 (37%)	4,353 (19%)	1,329 (6%)
FEV1%	95% (SD 15.4%)	109.7% (SD 8.1)	93% (SD 4.2)	79.5% (SD 4.8%)	61.1% (SD 9.1)
FEV1/FVC ratio < 0.70	2,661 (11%)	202 (2%)	654 (7%)	1,007 (22%)	798 (58%)
<LLN	1,155 (5.4%)	24 (0.2%)	151 (2%)	392 (10%)	588 (45%)
Female	11,981 (52%)	4,629 (53%)	4,494 (52%)	2,193 (49%)	665 (49%)
Age, years 45 to 54	6,235 (44%)	2,351 (44%)	2,306 (44%)	1,209 (45%)	369 (44%)
55 to 64	7,769 (30%)	2,934 (30%)	2,937 (31%)	1,488 (30%)	410 (27%)
65 to 74	5,396 (16%)	2,079 (17%)	2,011 (17%)	977 (15%)	329 (17%)
75+	3,422 (10%)	1,262 (9%)	1,260 (9%)	679 (10%)	221 (11%)
Height, m	1.69 (SD 0.1)	1.69 (SD 0.1)	1.69 (SD 0.1)	1.69 (SD 0.1)	1.69 (SD 0.1)
BMI, kgm−2 <25	7,082 (33%)	3,084 (38%)	2,486 (32%)	1,150 (29%)	362 (30%)
25 to 30	9,226 (40%)	3,671 (42%)	3,491 (41%)	1,620 (37%)	444 (32%)
>30	6,496 (26%)	1,866 (20%)	2,527 (27%)	1,580 (34%)	523 (38%)
Education primary	1,074 (4%)	309 (3%)	402 (4%)	248 (5%)	115 (8%)
Secondary/trade	2,114 (9%)	744 (8%)	780 (8%)	440 (10%)	150 (11%)
University	19,602 (87%)	7,561 (89%)	7,323 (87%)	3,659 (86%)	1,059 (80%)
Smoking never	7,318 (34%)	2,933 (36%)	2,789 (35%)	1,288 (32%)	308 (26%)
Former	13,515 (57%)	5,238 (59%)	5,033 (57%)	2,524 (56%)	720 (51%)
Current	1,851 (8%)	395 (5%)	641 (8%)	518 (12%)	297 (22%)
Physical activity	153.2 (SD 76.6)	158.7 (SD 75.8)	152.3 (SD 75.7)	147.9 (SD 77.6)	139.2 (SD 81.8)
COPD	1,040 (4%)	194 (2%)	306 (3%)	289 (6%)	251 (16%)
Asthma	2,940 (13%)	727 (8%)	1,064 (13%)	776 (18%)	373 (29%)
CVD	2,593 (9%)	750 (7%)	932 (9%)	647 (12%)	264 (17%)
No chronic conditions	3,297 (10%)	1,409 (22%)	1,231 (20%)	533 (18%)	124 (13%)
>= 3 chronic conditions	8,664 (35%)	3,043 (33%)	3,203 (35%)	1,825 (39%)	593 (45%)

Data are provided as counts and % of total within each FEV1 category/column or as means and SDs for continuous variables. FEV1 z-scores were calculated using the GLI 2012 predicted values appropriate for age, sex, height, and ethnicity.

N = sample size within each FEV1 category.

Physical activity was self-reported for the previous 7 days using the PASE instrument with higher scores indicating higher physical activity. Low physical activity was defined as achieving less than 150 minutes per week of moderate intensity activity. Asthma, COPD, CVD, and chronic conditions were self-reported at baseline.

BMI, body mass index calculated as weight (kg) divided by height (m) squared; COPD, chronic obstructive pulmonary disease; CVD, cardiovascular disease; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; GLI, Global Lung function Initiative; LLN, lower limits of normal from GLI predicted norms for age, height, sex, and ethnicity; PASE, Physical Activity Scale for the Elderly; SD, standard deviation.

Self-perceived poor general health, respiratory symptoms, cognitive impairment, and FEV1

The proportion of the overall cohort, reporting mild-moderate respiratory symptoms, was approximately 24% (n = 5,367), perceived poor health 8% (n = 1,736), and impaired cognitive performance 30% (n = 6,684) (Table 2). The prevalence, unadjusted odds ratios (ORs), and adjusted odds ratios (aORs) for all 3 outcomes showed a graded increase with lower FEV1 (Table 2, Fig 1). For perceived poor health, the unadjusted OR across the mild, moderate, and severe FEV1 categories were 1.34 (95% CI 1.16 to 1.54; p < 0.001), 2.28 (1.96 to 2.66; p < 0.001), and 4.07 (3.35 to 4.94; p < 0.001), respectively. After adjusting for differences in demographics between categories, the corresponding aORs were 1.07 (0.9 to 1.27; p = 0.45), 1.48 (1.24 to 1.78; p < 0.001), and 1.82 (1.42 to 2.33; p < 0.001). For self-reported moderate to severe respiratory symptoms, the unadjusted ORs across categories were 1.34 (1.23 to 1.46; p < 0.001), 2.03 (1.83 to 2.25; p < 0.001), and 5.11 (4.36 to 6.00; p < 0.001), with corresponding aORs of 1.10 (0.98 to 1.12; p = 0.41), 1.45 (1.28 to 1.63; p < 0.001), and 2.67 (2.21 to 3.23; p < 0.001). Similar trend was observed for impaired cognitive performance, with unadjusted ORs of 1.06 (0.99 to 1.15; p = 0.113), 1.19 (1.09 to 1.31; p < 0.001), and 1.53 (1.33 to 1.76; p < 0.001) across increasing lower FEV1 categories. The corresponding aORs for impaired cognitive performance were 1.03 (0.95 to 1.12; p = 0.41), 1.16 (1.04 to 1.28; p = 0.005), and 1.40 (1.19 to 1.64; p < 0.001). While the ORs for severe FEV1 were the highest for all outcomes, the absolute numbers of affected participants in the mild and moderate FEV1 categories combined exceeded the numbers with severe FEV1. For example, 1,063, 3,165, and 3,814 participants in the mild and moderate FEV1 groups combined, reported poor general health, moderate to severe respiratory symptoms, and impaired cognitive performance, respectively. These numbers were 5- to 8-folds higher than the 229 (perceived poor health), 595 (moderate to severe respiratory symptoms), and 475 (impaired cognitive performance) participants in the severe FEV1 categories.

Table 2

Self-reported perceived poor health, respiratory symptoms, and cognitive impairment for different grades of low FEV1 compared to reference (FEV1 > 0 SD) in the overall cohort and in a subgroup without spirometry AO (shown here as FEV1/FVC > = LLN).

	Categories of FEV1 according to GLI z-scores
	>0 SD (reference)	0 to > −1 SD	−1 to > −2 SD	=<−2 SD
Total 22,822	Normal 8,626	Mild 8,514	Moderate 4,353	Severe 1,329
Perceived poor health
Overall 1,736 (7.6%)	444 (5%)	574 (7%)	489 (11%)	229 (18%)
Unadjusted OR for overall	1	1.34 (1.16, 1.54) p < 0.001	2.28 (1.96, 2.66) p < 0.001	4.07 (3.35, 4.94) p < 0.001
aOR for overall	1	1.07 (0.9, 1.27) p = 0.450	1.48 (1.24, 1.78) p < 0.001	1.82 (1.42, 2.33) p < 0.001
Unadjusted OR for FEV1/FVC > = LLN	1	1.33 (1.15, 1.54) p < 0.001	2.34 (2.01, 2.74) p < 0.001	4.50 (3.36, 5.68) p < 0.001
aOR for FEV1/FVC > = LLN	1	1.08 (0.91, 1.28) p = 0.363	1.60 (1.33, 1.92) p < 0.001	1.91 (1.42, 2.55) p < 0.001
Moderate to severe symptoms
Overall 5,367 (24%)	1,607 (20%)	1,919 (22%)	1,246 (29%)	595 (45%)
Unadjusted OR for overall	1	1.34 (1.23, 1.46) p < 0.001	2.03 (1.83, 2.25) p < 0.001	5.11 (4.36, 6.00) p < 0.001
aOR for overall cohort	1	1.10 (0.98, 1.20) p = 0.085	1.45 (1.28, 1.63) p < 0.001	2.67 (2.21, 3.23) p < 0.001
Unadjusted OR for FEV1/FVC > = LLN	1	1.34 (1.23, 1.47) p < 0.001	2.00 (1.80, 2.22) p < 0.001	4.92 (4.02, 6.02) p < 0.001
aOR for FEV1/FVC > = LLN	1	1.15 (1.04, 1.26) p = 0.007	1.56 (1.39, 1.76) p < 0.001	2.95 (2.33, 3.72) p < 0.001
Cognitive impairment
Overall 6,684 (30.3%)	2,365 (28%)	2,456 (30%)	1,358 (33%)	475 (40%)
Unadjusted OR for overall	1	1.06 (0.99, 1.15) p = 0.113	1.19 (1.09, 1.31) p < 0.001	1.53 (1.33, 1.76) p < 0.001
aOR for overall	1	1.03 (0.95, 1.12) p = 0.414	1.16 (1.04, 1.28) p = 0.005	1.40 (1.19, 1.64) p < 0.001
Unadjusted OR for FEV1/FVC > = LLN	1	1.06 (0.98, 1.15) p = 0.126	1.21 (1.11, 1.33) p < 0.001	1.70 (1.42, 2.03) p < 0.001
aOR for FEV1/FVC > = LLN	1	1.03 (0.95, 1.12) p = 0.479	1.17 (1.05, 1.29 p = 0.003	1.44 (1.17, 1.76) p < 0.001

For each outcome, raw data expressed as frequencies (%) of each FEV1 category/column are provided for the overall cohort in the first row. Unadjusted and aORs relative to reference group (FEV1 > 0 SD) with 95% CI and p-values were estimated for different FEV1 categories for the overall cohort and for subgroup excluding spirometric AO (participants with FEV1/FVC< LLN excluded). aORs were adjusted for age, sex, BMI, smoking status (never, former, and current), education (less than secondary, secondary, and postsecondary), physical activity, self-reported asthma/COPD/CVD, and the number of chronic conditions. Moderate to severe respiratory symptoms refer to breathlessness, cough, or wheeze with walking on flat surfaces or occurring at nighttime at least once per week. Analyses were performed for the overall cohort and separately for the remaining participants (n = 21,667) after removing those with GLI FEV1/FVC < LLN.

AO, airflow obstruction; aOR, adjusted odds ratio; BMI, body mass index; COPD, chronic obstructive pulmonary disease; CVD, cardiovascular disease; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; GLI, Global Lung function Initiative; LLN, lower limit of normal for age, sex, height, and ethnicity using the GLI reference values; SD, standard deviation.

Fig 1

Unadjusted and aORs (95% CI) for self-reported perceived poor health status, respiratory symptoms, and low cognitive scores by grades of low FEV1 relative to reference group in the overall cohort and in participants without spirometry AO.

AO, airflow obstruction; aOR, adjusted odds ratio; FEV1, forced expiratory volume in 1 second; SD, standard deviation.

ORs and 95% CIs are presented as adjusted (circle symbols) and unadjusted (square symbols) estimates relative to reference group (FEV1 z score >0 SD). For adjusted multilevel logistic regression model, see Methods section. ORs were calculated for the overall cohort (closed) and after removing participants with spirometric AO (AO = FEV1/FVC

FEV1 and physical performance

There were similar trends observed between lower FEV1 with declining physical performances on the TUG, gait speed, standing balance, and handgrip strength (Table 3, Fig 2). Compared to normal FEV1, the unadjusted mean difference in gait speed for mild, moderate, and severe FEV1 were −0.011 m/s (95% CI −0.017, −0.004; p = 0.001), −0.034 (−0.042, −0.026; p < 0.001), and −0.074 (−0.087, −0.062; p < 0.001), respectively. These corresponded to adjusted mean differences of −0.002 m/s (−0.008, 0.004; p = 0.54), −0.018 (−0.026, −0.009; p < 0.001), and −0.039 (−0.053, −0.026; p < 0.001). Similar graded increase in unadjusted (−2.19 seconds [−2.86, −1.52; p < 0.001], −4.72 [−5.60, −3.85; p < 0.001], and −9.40 [−10.93, −7.87; p < 0.001]) and adjusted (−0.97 seconds [−1.59, −0.35; p = 0.020], −2.57 [−3.37, −1.77; p < 0.001], and −5.31 [−6.75, −3.87; p < 0.001]) mean differences in standing balance were observed with lower FEV1 categories. For TUG, the unadjusted (0.129 seconds [0.068, 0.190; p < 0.001], 0.471 [0.386, 0.556; p < 0.001], and 0.950 [0.763, 1.137; p < 0.001] and adjusted (0.033 seconds [−0.029, 0.094; p = 0.304], 0.276 [0.189, 0.362; p < 0.001), and 0.503 [0.301, 0.705; p < 0.001]) mean differences showed a similar trend with lower FEV1 categories. Last, the unadjusted (−0.95 kg [−1.39, −0.51; p < 0.001], −1.23 [−1.77, −0.69; p < 0.001], and −2.79 [−3.65, −1.93; p < 0.001]) and adjusted (−1.08 kg [−1.36, −0.81; p < 0.001], −1.88 [−2.23, −1.53; p < 0.001], and −3.44 [−4.10, −2.80; p < 0.001]) mean differences in handgrip strength showed a strong and significant increase in effect size with progressively lower FEV1 categories.

Table 3

Mean differences (unadjusted and adjusted) in physical performance by different grades of low FEV1 compared to reference group (FEV1 > 0 SD) for the overall cohort and subgroup without AO on spirometry (shown here as FEV1/FVC > = LLN).

	Categories of FEV1 according to GLI z-scores
OVERALL	>0 SD (ref)	0 to > −1 SD	−1 to > −2 SD	=<−2 SD
Total22,822	Normal 8,626	Mild8,514	Moderate4,353	Severe1,329
Gait speed, m/s
Mean 1.01 (SD 0.19)	1.02 (0.18)	1.01 (0.19)	0.99 (0.19)	0.95 (0.20)
Unadjusted: overall	0	−0.011 (−0.017, −0.004) p = 0.001	−0.034 (−0.042, −0.026) p < 0.001	−0.074 (−0.087, −0.062) p < 0.001
Adjusted: overall	0	−0.002 (−0.008, 0.004) p = 0.535	−0.018 (−0.026, −0.009) p < 0.001	−0.039 (−0.053, −0.026) p < 0.001
Unadjusted: FEV1/FVC > = LLN	0	−0.012 (−0.018, −0.005) p < 0.001	−0.036 (−0.044, −0.028) p < 0.001	−0.086 (−0.103, −0.070) p < 0.001
Adjusted: FEV1/FVC > = LLN	0	−0.002 (−0.009, 0.004) p = 0.455	−0.018 (−0.027, −0.01) p < 0.001	−0.051 (−0.068, −0.033) p < 0.001
Standing balance, seconds
Mean 45.4 (SD 21.3)	47.6 (20)	45.4 (21.4)	43.1 (22.3)	38 (23.8)
Unadjusted: Overall	0	−2.19 (−2.86, −1.52) p < 0.001	−4.72 (−5.60, −3.85) p < 0.001	−9.40 (−10.93, −7.87) p < 0.001
Adjusted: Overall	0	−0.97 (−1.59, −0.35) p = 0.002	−2.57 (−3.37, −1.77) p < 0.001	−5.31 (−6.75, −3.87) p < 0.001
Unadjusted: FEV1/FVC > = LLN	0	−2.22 (−2.89, −1.54) p < 0.001	−5.31 (−6.23, −4.89) p < 0.001	−10.65 (−12.69, −8.61) p < 0.001
Adjusted: FEV1/FVC > = LLN	0	−0.95 (−1.57, −0.33) p = 0.003	−3.04 (−3.87, −2.20) p < 0.001	−6.78 (−8.72, −4.85) p < 0.001
TUG, seconds
Mean 9.2 (SD 2.1)	9.0 (2)	9.2 (2)	9.5 (2.4)	10 (2.8)
Unadjusted: Overall	0	0.129 (0.068, 0.190) p < 0.001	0.471 (0.386, 0.556) p < 0.001	0.950 (0.763, 1.137) p < 0.001
Adjusted: Overall	0	0.03 (−0.03, 0.09) p = 0.304	0.28 (0.19, 0.36) p < 0.001	0.50 (0.30, 0.70) p < 0.001
Unadjusted: FEV1/FVC > = LLN	0	0.133 (0.072, 0.194) p < 0.001	0.507 (0.417, 0.596) p < 0.001	1.168 (0.882, 1.454) p < 0.001
Adjusted: FEV1/FVC > = LLN	0	0.03 (−0.031, 0.093) p = 0.324	0.30 (0.21, 0.39) p < 0.001	0.71 (0.39, 1.03) p < 0.001
Grip strength, kg
Mean 37.0 (SD 12.2)	37.8 (12.2)	36.7 (12.2)	36.5 (12.1)	35.0 (12)
Unadjusted: Overall	0	−0.95 (−1.39, −0.51) p < 0.001	−1.23 (−1.77, −0.69) p < 0.001	−2.79 (−3.65, −1.93) p < 0.001
Adjusted: Overall	0	−1.08 (−1.36, −0.81) p < 0.001	−1.88 (−2.23, −1.53) p < 0.001	−3.44 (−4.10, −2.80) p < 0.001
Unadjusted: FEV1/FVC > = LLN	0	−0.93 (−1.37, −0.48) p < 0.001	−1.22 (−1.78, −0.66) p < 0.001	−2.91 (−4.00, −1.82) p < 0.001
Adjusted: FEV1/FVC > = LLN	0	−1.10 (−1.37, −0.82) p < 0.001	−1.96 (−2.32, −1.60) p < 0.001	−4.20 (−5.05, −3.34) p < 0.001

For each outcome, raw data expressed as means (SD) observed for each FEV1 category/column are provided in the first row for the overall cohort. Unadjusted and adjusted mean differences (95% CI) relative to the reference group (FEV1 > 0 SD) were estimated for the different FEV1 category for the overall cohort and after removing participants with AO (GLI FEV1/FVC

AO, airflow obstruction; BMI, body mass index; COPD, chronic obstructive pulmonary disease; CVD, cardiovascular disease;; FVC, forced vital capacity; GLI, Global Lung function Initiative; LLN, lower limit of normal for age, sex, height, and ethnicity using the GLI reference values; SD, standard deviation; TUG, Timed Up and Go.

Fig 2

Unadjusted and adjusted mean differences (95% CI) in physical performance by grades of low FEV1 relative to reference group (FEV1 > 0 SD) in the overall cohort and in participants without AO on spirometry.

AO, airflow obstruction; FEV1, forced expiratory volume in 1 second; SD, standard deviation.

Unadjusted (square symbols) mean differences between each level of low FEV1 relative to reference (FEV1%> 0 SD) for TUG, gait speed, standing balance, and handgrip strength. For the methods used to calculate adjusted estimates (circle symbols), see Methods section. Closed symbols represent data for the overall cohort; open symbols represent data for subgroup after removing participants with spirometry AO (AO = FEV1/FVC

Sensitivity analyses

To avoid any confounding by undiagnosed COPD or AO, we conducted 2 sensitivity analyses. First, all analyses were repeated after removing participants with AO using the GLI FEV1/FVC

Stratified analyses by age, sex, smoking status, and COPD/asthma

Unadjusted and adjusted analyses showed similar pattern of graded association between lower FEV1 with higher odds of respiratory symptoms, perceived poor health, impaired cognitive performance (S4 and S5 Tables), and lower physical performance (S6 and S7 Tables) were observed across stratified groups by sex (Fig 3), smoking status (Fig 4), and age (Fig 5).

Fig 3

Associations between physical performances with grades of FEV1 stratified by sex.

FEV1, forced expiratory volume in 1 second; SD, standard deviation.

Fig 4

Associations between physical performances with grades of FEV1 stratified by smoking history.

FEV1, forced expiratory volume in 1 second; SD, standard deviation.

Fig 5

Associations between physical performances with grades of FEV1 stratified by age.

FEV1, forced expiratory volume in 1 second; SD, standard deviation.

Multilevel linear regression was used to estimate the differences between each level of FEV1 relative to reference (FEV1% > 0 SD) on gait speed, standing balance, TUG, and handgrip strength stratified by males (closed symbols) and females (open symbols). All analyses were adjusted for age, BMI, smoking status, education, physical activity, self-reported asthma/COPD/CVD, and number of self-reported chronic noncommunicable conditions. Only p-values of <0.005 and <0.0005 compared to reference within stratum are reported. Corresponding numerical data can be found in Appendix 7. Unadjusted estimates can be found in Appendix 6.

Multilevel linear regression was used to estimate the differences between each level of FEV1 z-score relative to reference (FEV1% > 0 SD) on gait speed, standing balance, TUG, and handgrip strength stratified by self-reported smoking history: nonsmokers (open symbols) and smokers (close symbols). All analyses were adjusted for age, sex, BMI, education, physical activity, self-reported asthma/COPD/CVD, and number of self-reported chronic noncommunicable conditions. Only p-values of <0.005 and <0.0005 compared to reference within stratum are reported. Corresponding numerical data can be found in Appendix 7. Unadjusted estimates are provided in Appendix 6.

Multilevel linear regression was used to estimate the differences between each level of FEV1 z-score relative to reference (FEV1% > 0 SD) on gait speed, standing balance, TUG, and handgrip strength stratified by baseline age categories. All analyses were adjusted for sex, BMI, smoking status, education, physical activity, self-reported asthma/COPD/CVD, and number of self-reported chronic noncommunicable conditions. Only p-values of <0.005 and <0.0005 compared to reference within stratum are reported. Corresponding numerical data can be found in Appendix 7 and adjusted estimates in Appendix 6.

Discussion

In this large representative sample of the Canadian population aged 45 to 85 years living independently in the community, we found significant and graded associations between higher odds of perceived poor general health, moderate to severe respiratory symptoms, and impaired cognitive performance with lower FEV1. The pattern of association persisted even after controlling for potential confounders and differences in baseline characteristics between FEV1 severity groups. Similar graded associations were observed between lower FEV1 with lower performance on validated physical assessment tools. These relationships was evident throughout all grades of lower FEV1, even for mildly reduced levels generally regarded as within the limits of normal (i.e., above −2 SD). Furthermore, these associations were highly consistent across different age groups, sex, smoking status, and obstructive and nonobstructive impairment on spirometry. These findings suggest that the association between lung function with quality of life and functional measures are robust and generalizable to the wider population, independent of lung disease. It also highlights the potential underestimation of the burden associated with mild to moderately reduced levels of FEV1.

The association between lower lung function with excess mortality in the general population has long been recognized by numerous population-based studies [1-7]. There is emerging evidence for a wider association between low lung function with various chronic nonpulmonary diseases [8-11]. However, there is a paucity of data linking lung function with burden of symptoms, functional, and physical impairment in the wider population without lung diseases. Addressing this gap may help to better understand the burden of low lung function in the general population and offer new insight into pathways that may link low lung function with nonpulmonary comorbidities. The novel finding here is the consistent and graded association between lower FEV1 with higher ORs for self-reported respiratory symptoms, perceived poor health status, cognitive impairment, and lower physical performance. Since these were cross sectional data, the cause–effect implications are not known. These findings, however, suggest that there may be common pathways between reduced lung function with reduced cognitive and physical performance. As the latter outcomes are strongly associated with future risks of disability, falls, hospitalization, and mortality in later years [16-18,33] we propose that reduced lung function even at very mild levels may be an important early indicator of functional impairment as the population age. Therefore, public health strategies, which effectively maintain optimal lung health, may have wider impact and benefits to perceived general health, respiratory symptoms, cognitive and physical functioning, and the overall health trajectory.

A number of previous studies have reported on the high prevalence of physical function impairment and sarcopenia with COPD [16,33-36]. We found that removing participants with obstructive lung function impairment (a cardinal feature of COPD) did not change our findings. Furthermore, we found similar graded and significant associations between FVC levels with these same outcomes. These findings further support the generalizability of these associations to the wider population independent of AO. In fact, the large majority of low FEV1 were nonobstructive impairment and in keeping with the high prevalence of “restrictive” pulmonary impairment previously reported in other populations from high-income countries [37]. Moreover, we found that these associations were present in nonsmokers to the same extent as smokers, supporting their independence from COPD and tobacco smoking.

It is important to note that the effect sizes for low FEV1 for different physical performance measures were only mild to moderate, which is to be expected as the CLSA cohort is a community-based cohort and likely to be relatively healthy at baseline. In addition, we had carefully adjusted for a large number of potential confounders to avoid the effect of concomitant diseases. Nonetheless, the ORs for symptoms, perceived poor health, cognitive function, and lower physical performance showed an increase in effect size with lower FEV1. Importantly, while the ORs for mild to moderate FEV1 categories were lower compared to severe FEV1, the numbers of participants affected by these outcomes were considerably higher for these milder categories. This suggest that the burden associated with milder grades of low FEV1 are high, and their contribution to poor cognitive, physical, and functional outcomes may be underrecognized, since current practices would regard these FEV1 levels as within the normal limits [22].

Last, we observed the strength of the association was particularly strong between FEV1 with handgrip strength, standing balance, and moderate to severe respiratory symptoms. This is consistent with the growing body of literature, highlighting the association between reduced lung function with sarcopenia in the general populations [36,38,39]. Our findings add to this field by showing that reduced lung function is a part of the generalized manifestations of functional and cognitive decline and potentially frailty. Since lung function is an accessible and easily quantifiable measure, we propose that it may be an important indicator of general health and functional status irrespective of age, sex, smoking status, and underlying lung diseases. Its routine use in the community may lead to an increase in case finding and diagnosis of preclinical disability in the general population. Identifying these early and mild individuals will more likely offer greater opportunity for interventions and to modify their trajectory.

The strengths of this study include the large sample size and the representativeness of the general population. Data were collected using validated, standardized, and high-quality control methodology. The large number of covariates collected allowed for careful adjustments to reduce any confounding effects. The limitations include the cross-sectional analysis, which limits our ability to infer causality. The respiratory symptoms and perceived poor general health outcomes were self-reported and are subjected to recall bias. However, these questionnaires have been used in other epidemiological studies and have demonstrated robust associations with poor health outcomes and mortality [24,25,40]. The strict quality standards for spirometry measurements in CLSA may have selected mostly healthy individuals. However, the distribution in FEV1 z-scores showed a slight skewness to the left with higher numbers of individuals with moderate to severe FEV1 impairment (z-scores <-1 SD). Finally, these findings need to be examined in other populations from different ethnic and geographic backgrounds to confirm their generalizability.

In conclusion, we found a consistent and graded association between lower FEV1 with higher odds of self-reported poor health, moderate to severe respiratory symptoms, and impaired cognitive performance in a large representative sample of the general population. Similar gradient of associations were observed for physical performance on validated tests, which have important prognostication for future functional impairment and poor health outcomes. Our findings suggest that low lung function may be an important and early finding of preclinical disability in the general population. There is also a high burden of moderate to severe respiratory symptoms and poor perceived health status even with very mild to moderate low FEV1. Future studies are needed to examine the longitudinal associations between lower FEV1 with future physical impairment, disability, and morbidity and whether strategies that promote lung health can improve the overall health trajectory with aging.

Protocol of planned analysis submitted to Hamilton Integrated Research Ethics Board.

(DOCX)

Click here for additional data file.

STROBE checklist.

STROBE, Strengthening the Reporting of Observational Studies in Epidemiology.

(DOCX)

Click here for additional data file.

Baseline characteristics of the comprehensive and tracking cohorts.

(DOCX)

Click here for additional data file.

Contraindications to performing spirometry.

(DOCX)

Click here for additional data file.

Analyses on self-reported respiratory symptoms, self-perceived poor health status, and cognitive and physical performance for different grades of low FVC compared to reference (FVC > 0 SD) in the overall cohort and in participants without spirometry AO (shown here as FEV1/FVC >= LLN).

AO, airflow obstruction; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; LLN, lower limit of normal.

(DOCX)

Click here for additional data file.

Unadjusted stratified analysis by gender, smoking history, and baseline age for self-perceived poor health, respiratory symptoms, and low cognitive scores by grades of low FEV1 relative to reference group (FEV1 > 0 SD).

(DOCX)

Click here for additional data file.

Adjusted stratified analyses by gender, smoking history, and baseline age for self-perceived poor health, respiratory symptoms, and low cognitive scores by grades of low FEV1 relative to reference group (FEV1 > 0 SD).

(DOCX)

Click here for additional data file.

Unadjusted stratified analyses by gender, smoking history, and baseline age groups on physical performance according to grades of low FEV1 relative to reference group (FEV1 > 0 SD).

(DOCX)

Click here for additional data file.

Adjusted stratified analyses by gender, smoking history, and baseline age groups on physical performance according to grades of lower FEV1 z scores relative to reference group (FEV1 > 0 SD).

(DOCX)

Click here for additional data file.

4 Mar 2021

Dear Dr Duong,

Thank you for submitting your manuscript entitled "Impact of FEV1  on Physical and Cognitive Health in the Canadian Longitudinal Study on Aging (CLSA)." for consideration by PLOS Medicine.

Your manuscript has now been evaluated by the PLOS Medicine editorial staff as well as by an academic editor with relevant expertise and I am writing to let you know that we would like to send your submission out for external peer review.

However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.

Please re-submit your manuscript within two working days, i.e. by .

Login to Editorial Manager here: https://www.editorialmanager.com/pmedicine

Once your full submission is complete, your paper will undergo a series of checks in preparation for peer review. Once your manuscript has passed all checks it will be sent out for review.

Feel free to email us at plosmedicine@plos.org if you have any queries relating to your submission.

Kind regards,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

8 Mar 2021

Dear Dr Duong,

Thank you for submitting your manuscript entitled "Impact of FEV1 on Physical and Cognitive Health in the Canadian Longitudinal Study on Aging (CLSA)." for consideration by PLOS Medicine.

Your manuscript has now been evaluated by the PLOS Medicine editorial staff as well as by an academic editor with relevant expertise and I am writing to let you know that we would like to send your submission out for external peer review.

However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.

Please re-submit your manuscript within two working days, i.e. by .

Login to Editorial Manager here: https://www.editorialmanager.com/pmedicine

Once your full submission is complete, your paper will undergo a series of checks in preparation for peer review. Once your manuscript has passed all checks it will be sent out for review.

Feel free to email us at plosmedicine@plos.org if you have any queries relating to your submission.

Kind regards,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

5 Sep 2021

Dear Dr. Duong,

Thank you very much for submitting your manuscript "Impact of FEV1 on Physical and Cognitive Health in the Canadian Longitudinal Study on Aging (CLSA)." (PMEDICINE-D-21-01015R2) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to four independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We expect to receive your revised manuscript by Sep 24 2021 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

https://www.editorialmanager.com/pmedicine/

Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

From the Academic Editor:

1. I agree with one of the reviewers that this is an association study. The use of 'effect' suggests causality. This should be attended to.

2. The focus is on FEV1. it would be nice to get some more information on the standardisation procedures for its measurement. This is a notorious measure in the field, especially if it is being done by several different research assistants (which is likely to be the case). There are some pre-requirements - not having smoked for an hour, not after a large meal, avoid alcohol, etc. It is best done in the office, but field measurement may have been the only option. When compared to normative data, they had 25% <1 SD and 6% <2 SD, which suggests a sample skewed to the left (although this is a large population-based study). This does not negate the results, but is worthy of discussion.

3. There are several measures of frailty that are being linked to cognition and to each other. A multivariate regression model may be instructive to see if FEV1 has any predictive value over and above the other measures? Is it a unique association, or is it that since frailty is known to be linked to cognition, and the measures of frailty are correlated, and we are seeing this in a univariate analysis.

4. Do they have any other measure of general health? Many studies do use self-report on one question, but it would be nice to have something more comprehensive and/or objective.

Additional editorial requests:

5. Please revise your title according to PLOS Medicine's style. Your title must be nondeclarative and not a question. It should begin with main concept if possible. "Effect of" should be used only if causality can be inferred, i.e., for an RCT. Please place the study design ("A randomized controlled trial," "A retrospective study," "A modelling study," etc.) in the subtitle (ie, after a colon).

6. Financial disclosure: Please describe the sources of funding for the study, in addition to noting that The funders had no role in study design, data collection and analysis, decision to

publish, or preparation of the manuscript.

7. Data availability statement: The Data Availability Statement (DAS) requires revision. PLOS Medicine requires that the de-identified data underlying the specific results in a published article be made available, without restrictions on access, in a public repository or as Supporting Information at the time of article publication, provided it is legal and ethical to do so. Please see the policy at

http://journals.plos.org/plosmedicine/s/data-availability

and FAQs at

http://journals.plos.org/plosmedicine/s/data-availability#loc-faqs-for-data-policy

For each data source used in your study:

a) If the data are freely or publicly available, note this and state the location of the data: within the paper, in Supporting Information files, or in a public repository (include the DOI or accession number).

b) If the data are owned by a third party but freely available upon request, please note this and state the owner of the data set and contact information for data requests (web or email address). Note that a study author cannot be the contact person for the data.

c) If the data are not freely available, please describe briefly the ethical, legal, or contractual restriction that prevents you from sharing it. Please also include an appropriate contact (web or email address) for inquiries (again, this cannot be a study author).

8. Throughout: Please include line numbers with the revised version.

9. Abstract: Please structure your abstract using the PLOS Medicine headings (Background, Methods and Findings, Conclusions). Please combine the Methods and Findings sections into one section, “Methods and findings”.

10. Abstract: Background: Abstract Background: The final sentence should clearly state the study question.

11. Abstract: Methods and Findings: * Please include the study design, population and setting, number of participants, years during which the study took place, length of follow up, and main outcome measures. * Please quantify the main results (with 95% CIs and p values). * In the last sentence of the Abstract Methods and Findings section, please describe the main limitation(s) of the study's methodology.

12. Abstract: Conclusions: * Please address the study implications without overreaching what can be concluded from the data; the phrase "In this study, we observed ..." may be useful.

13. Author summary: At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

14. Throughout: For in-text reference citations, please place reference numbers in square brackets before the sentence punctuation, like this [1]. For multiple references, please do not include spaces within brackets.

15. Methods: Please provide the name(s) of the institutional review board(s) that provided ethical approval for the study, and please specify whether informed consent of participants was written or oral.

16. Methods: Please provide more clarification on the selection of/ any differences between those selected for physical/cognitive/clinical assessments vs the tracking cohort. “Selected participants

were interviewed and had standardized physical, cognitive and clinical assessments

(comprehensive cohort) to provide data on demographics, lifestyle, health, and clinical

information. In the remaining participants (tracking cohort, n=21,241), similar data was collected

by a telephone interview”

17. Methods: Please clarify: “Participants screened positive for major contra-indications were

Excluded.”

18. Methods: Please remove the trademark symbol from (Tracker Freedom®

Wireless)

19. Methods: Did your study have a prospective protocol or analysis plan? Please state this (either way) early in the Methods section.

a) If a prospective analysis plan (from your funding proposal, IRB or other ethics committee submission, study protocol, or other planning document written before analyzing the data) was used in designing the study, please include the relevant prospectively written document with your revised manuscript as a Supporting Information file to be published alongside your study, and cite it in the Methods section. A legend for this file should be included at the end of your manuscript.

b) If no such document exists, please make sure that the Methods section transparently describes when analyses were planned, and when/why any data-driven changes to analyses took place.

c) In either case, changes in the analysis-- including those made in response to peer review comments-- should be identified as such in the Methods section of the paper, with rationale.

20. Methods: Please ensure that the study is reported according to the STROBE guideline, and include the completed STROBE checklist as Supporting Information. Please add the following statement, or similar, to the Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)."

The STROBE guideline can be found here: http://www.equator-network.org/reporting-guidelines/strobe/

When completing the checklist, please use section and paragraph numbers, rather than page numbers.

21. Results: Throughout, please present the main results in the text, with 95% CIs and p values. For the assessment of respiratory, health, cognitive status with FEV1, please report both the adjusted and unadjusted analyses (with 95% CIs and p values).

22. Results: Please provide quantitative results for these findings (reported with 95% CIs and p values): “The proportion of obstructive impairment (whether defined by FEV1/FVC <0.70 or 30 kg/m2), asthma, COPD, CVD and multiple co-morbidities.”

23. Discussion: Please present and organize the Discussion as follows: a short, clear summary of the article's findings; what the study adds to existing research and where and why the results may differ from previous research; strengths and limitations of the study; implications and next steps for research, clinical practice, and/or public policy; one-paragraph conclusion.

24. Discussion: We suggest tempering this statement, as a formal dose-response analysis did not seem to be reported: “The novel finding here, is the highly consistent dose-response relationship between lower FEV1 with higher prevalence and ORs of self-reported respiratory symptoms…”

25. Table 2 and Table 3: Please provide the exact p values rather than p<0.05, etc. Please report p<0.001 where applicable. Please also provide the results from unadjusted analyses.

26. Figure 1-2: Please provide exact p values, or indicate in the legend that these are reported elsewhere. Please also include the results from unadjusted analyses.

27. Appendix 1 and Appendix 2: Please report exact p values, except for p<0.001, where applicable. Please also provide results from unadjusted analyses.

Comments from the reviewers:

Reviewer #1: This study examines cross-sectional baseline data for associations between FEV1 with self-reported respiratory symptoms, perceived poor health, cognitive and physical performance.

Comments:

Can the authors please assess whether the comprehensive cohort with complete baseline data (22,822 participants) is representative of the wider nationally representative CLSA (51,338 participants)?

"Self-reported data from questionnaires included: age (45-54, 55-64, 65-74 & 75+ years); sex; smoking status (never [lifetime <100 cigarettes], former [last cigarette smoked >12 months], and current); education (below secondary, secondary and >secondary); known cardiovascular disease (CVD) (angina, congestive heart failure, myocardial infarction), chronic obstructive pulmonary disease (COPD), asthma and major chronic diseases (incorporated into the co-morbidity index 0, 1-2, >3). Height and weight were measured with standardized methods and equipment. Body mass index (BMI) was calculated as weight divided by height-squared and categorized into <25, 25-30, >30 kg/m2 . Self-reported physical activity was assessed by the Physical Activity Scale for the Elderly (PASE) questionnaire with higher weighted scores indicating higher activity levels in the previous 7 days."

Did the authors consider treating age and BMI as continuous variables (if available in this format from the questionnaires)?

Can the authors please acknowledge the potential bias of self-reporting, for both covariates and outcomes (e.g. perceived general health) in the study limitations?

"The semantic fluency test assessed cognitive performance by asking participants to name as many animals within 60 seconds. Test scores were standardized for age, sex and education; and scores <45 considered impaired".

Did the authors consider treating cognitive assessment (i.e. semantic fluency test results) as a continuous variable?

Did the authors complete any sensitivity analyses on the cut-off of <45?

"Means and frequencies (%) were used to describe the sample. Hierarchical logistic regression was used to estimate the effects of low FEV1 (relative to FEV1>0sd as reference), adjusted for age, sex,

BMI, education, smoking status, self-reported asthma, COPD, CVD, co-morbidity index (excluding asthma, COPD and CVD). Centers were treated as random effect. The goodness-of-fit tests (likelihood ratio test, deviance, AIC, BIC criteria), multi-collinearity (tolerance and variance inflation factor) and visual inspection of residuals were performed to assess model stability and robustness. Trimmed inflation and analytical (rescaled) weights were applied; to reduce the effect of selection bias and maintain the national representativeness and generalizability of the data. Similar analyses after removing participants with spirometric obstruction (FEV1/FVC

Did the authors examine the distribution of data, in order to confirm if mean or median may be more appropriate?

The authors should state in the methods section that they computed SD for continuous variables (as shown in Table 1).

Furthermore, the authors have completed suitable multilevel linear regression models to estimate the differences between each level of low FEV1 z-score relative to reference (FEV1%>0sd), but have not mentioned this in the methods section.

"The prevalence and adjusted odds ratios (ORs) for these three outcomes showed a graded increase with lower FEV1 (Figure 1). The relationship was particularly strong (steep) between worsening FEV1 and increasing odds of moderate-severe respiratory symptoms, after accounting for differences in demographic and clinical factors. While the ORs were highest for the severely low FEV1 category; the absolute numbers of participants affected by these outcomes were far higher for the mild and moderately low FEV1 categories than for the severely low FEV1 group. "

Can the authors please quote accompanying relevant statistics in the main text, alongside each stated study finding?

Table 1: Can the authors please complete statistical tests comparing baseline differences between groups, and present the results within this table?

Overall, the authors have appropriately applied multilevel modelling, suitably assessing model stability and exploring multi-collinearity. Selection bias has been somewhat accounted for, and a thorough sensitivity analysis has been undertaken. The authors rightly acknowledge that the cross-sectional analysis limits the ability to infer causality, and that generalisability is restricted requiring findings to be examined in other populations.

Reviewer #2: Many epidemiologic studies have demonstrated that poor lung function, as indicated by a low forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC), is associated with an increased risk of adverse outcomes, cardiovascular or pulmonary. The FEV1 indicator is included in frailty models. The reviewed article adds new information about its association with self reported symptoms, cognitive and physical performance in the general population. The researchers found a consistent and graded association between lower FEV1 with higher odds of self-reported poor health, moderate-severe respiratory symptoms and impaired cognitive performance, in a large representative sample of the general population. This results add that reduced lung function is a part of the generalized manifestations of functional and cognitive decline and potentially frailty. The results are important to the researches in geriatric, lung functions, cognitive disorders. There are the implications for patient care and public policy.

In general the research is of very high methodological quality. The sample size is sufficient to prove the hypothesis. The data and analyses fully support the claims. The strength of the study is that large representative sample of the Canadian population aged 45 to 85 years living independently in the community was investigated. The large number of covariates collected allowed for careful adjustments to reduce any confounding effects. The figures and tables are correct and of high technical quality. The manuscript is well organized and written clearly enough to be accessible to non-specialists.

I do not see any needs of major or minor improvement.

Reviewer #3: This is a cohort of a population-based Canadian about lung function and the associated with higher mortality and adverse cardiopulmonary outcomes.The author analyse 22,822 adults (52% females, mean age 58.8 [sd 9.6]); the association between forced expiratory volume in 1 second (FEV1) with self-reported moderate to severe respiratory symptoms, perceived poor health, cognitive and physical performance were examined; using multilevel regression adjusted for potential confounders. The study is weel desging and the methdods and statitics sounds correct. The authors concluded that there is a consistent and graded association between lower FEV1 with higher odds of self-reported poor health, moderate-severe respiratory symptoms and impaired cognitive performance, in a large representative sample of the general population. Similar gradient of associations were observed for physical performance on validated tests, which have important prognostication for future functional impairment and poor health outcomes.

I have seen on the system three version of the article, I have read the R2 and I have any important consideration. There is no ethical and methodological issues. The introduction sounds good as well discussion and conclusioin that is machet with the objetctive of the article.

Reviewer #4: This study addresses an interesting association between low FEV1 and self reported "present health". The findings are of interest but should be qualified. Firstly the authors report an association and all implications of causality should be deleted. Secondly the participants were asked to "rate their present health" this is not the same as health status as measured by specific instruments. It is not clear why one of the validated measures of health status was not used and tis should be discussed. It would also be interesting to know if the findings also held true for the FVC measurements, as this would support the concept that the finding either reflects poor lung development or poor muscle strength rather than being related to airflow obstruction - the authors should present these data as well and discuss the results.

Any attachments provided with reviews can be seen via the following link:

[LINK]

19 Nov 2021

Submitted filename: Reviewer_responseNov2021.1.docx

Click here for additional data file.

23 Dec 2021

Dear Dr. Duong,

Thank you very much for re-submitting your manuscript "Associations between lung function with physical and cognitive health in the Canadian Longitudinal Study on Aging (CLSA), a multi-center population-based observational cohort study." (PMEDICINE-D-21-01015R3) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by two reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

We expect to receive your revised manuscript within 2 weeks. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

Please note, when your manuscript is accepted, an uncorrected proof of your manuscript will be published online ahead of the final version, unless you've already opted out via the online submission form. If, for any reason, you do not want an earlier version of your manuscript published online or are unsure if you have already indicated as such, please let the journal staff know immediately at plosmedicine@plos.org.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Jan 06 2022 11:59PM.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

------------------------------------------------------------

Requests from Editors:

1. Financial disclosure: Please clarify the funding statement associated with your manuscript. Youn note both that “There was no funding support for the current analysis and work in this report.” but also list a number of funding sources as well as that “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of this manuscript.”

Please address this discrepancy. This information should describe sources of funding that have supported the work included in this submission.The statement should include:Specific grant numbers, Initials of authors who received each award, and URLs to sponsors’ websites. Also state whether any sponsors or funders (other than the named authors) played any role in: Study design, Data collection and analysis, Decision to publish, Preparation of the manuscript. If they had no role in the research, include this sentence: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.” If the study was unfunded, include this sentence as the Financial Disclosure statement: “The author(s) received no specific funding for this work."

2. Data availability statement: Please update this section of the manuscript submission system with the details provided in the Data Access section of the main text (and please remove this section from the main text).

3. Throughout: Please include line numbers running continuously throughout the text of the manuscript.

4. Abstract: Background We suggest revising to “...forced expiratory volume in 1 second (FEV1), an indicator of lung function, with broad markers of general health…”

5. Abstract: Methods and Findings: Please clarify what is meant by “Compared to the Global Lung Function Initiative predictive values” (could this be written as: “Based on Global Lung Function Initiative reference values”?).

6. Abstract: Methods and Findings: For the OR provided for perceived poor health and impaired cognitive performance, please indicate which of the three levels is being described for each (mild, moderate, severely low). Please also note that these are the adjusted OR, and please mention the factors adjusted for.

7. Abstract: Methods and Findings, final sentence: Please revise to make the study limitations more clear: “A limitation is that the study is observational and causality cannot be inferred.” or similar.

8. Abstract: Conclusions: First sentence: Please remove the word “robust” from the sentence.

Author summary: Why was this study done? We suggest combining the first two bullet points.

9. Funding: Please remove the “Funding” section from the main text of the manuscript. Please ensure that all information is accurately entered into the manuscript submission system “Financial disclosure” section.

10. Data Access: As mentioned above, please remove the “Data Access” section from the main text of the manuscript. Please ensure that all information is completely and accurately entered in the manuscript submission system in the “Data availability” section.

11. Results: Please clarify this sentence “Compared to the overall cohort, the proportion of individuals with airflow obstruction whether defined by the GLI FEV1/FVC

12. Results: Sensitivity analyses: Please note the location where the data are shown for the analyses where participants with airflow obstruction were removed (e.g. Table 2 and Table 3).

13. Discussion: First paragraph: There is a typo in the sentence: “Furthermore, they were These associations were highly consistent across different age groups…”

14. Table 1: It would be helpful to provide a label at the top to indicate that the column headers indicate z score categories for GLI-FEV1 measures (this applies to all tables presented with z score column headers). Please define the abbreviation “FEV”

15. Table 2 and Table 3: Please define the abbreviations for FFV, LLN, FVC in the legend.

16. Figure 1: Please note in the legend the p values are reported in Table 2. Please provide a visual key within the figure indicating the definition of the open/closed circles and squares.

17. Figure 2: Please note in the legend the p values are reported in Table 3.Please provide a visual key within the figure indicating the definition of the open/closed circles and squares.

18. References: Please remove the italicized fonts from the reference list. Please check the formatting of each reference. Please note that there should be punctuation following the journal title. Please use the "Vancouver" style for reference formatting, and see our website for other reference guidelines https://journals.plos.org/plosmedicine/s/submission-guidelines#loc-references

Please use the same guidelines for formatting the references listed in the appendix.

19. STROBE Checklist: Thank you for including the STROBE Checklist. Please revise to indicate the locations within the text using Section and Paragraph Numbers (e.g. Methods, paragraph 1). Please do not report page numbers or line numbers.

20. Supporting Information files: List supporting information captions at the end of the manuscript file. Do not submit captions in a separate file. The file number and name are required in a caption, and we highly recommend including a one-line title as well. You may also include a legend in your caption, but it is not required. Authors may use almost any description as the item name for a supporting information file as long as it contains an “S” and number. For example, “S1 Appendix” and “S2 Appendix,” “S1 Table” and “S2 Table,” and so forth.

21. Appendix 1: We suggest including the protocol as a separate file, and we suggest renaming to “S1_Protocol” or similar.

22. Appendix 2: In the legend, it would be helpful to briefly define what is meant by “comprehensive” and “tracking” cohort.

23. Appendix 4: Please note that under “Cognitive Impairment” the categories for Smokers vs Non-smokers are repeated, and it seems the male/female stratification is missing.

Comments from Reviewers:

Reviewer #1: The authors have satisfactorily considered and responded to each comment in turn, and have amended the manuscript accordingly.

Reviewer #4: The authors have addressed my concerns

Any attachments provided with reviews can be seen via the following link:

[LINK]

6 Jan 2022

Submitted filename: REPONSE to reviewers 23 Dec2021.docx

Click here for additional data file.

10 Jan 2022

Dear Dr Duong,

On behalf of my colleagues and the Academic Editor, Perminder Singh Sachdev, I am pleased to inform you that we have agreed to publish your manuscript "Associations between lung function with physical and cognitive health in the Canadian Longitudinal Study on Aging (CLSA), a multi-center population-based observational cohort study." (PMEDICINE-D-21-01015R4) in PLOS Medicine.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. Once you have received these formatting requests, please note that your manuscript will not be scheduled for publication until you have made the required changes.

In the meantime, please log into Editorial Manager at http://www.editorialmanager.com/pmedicine/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process.

Please also address the following points:

-Title: Please revise the title (and please update this in the submission system as well as on the manuscript) to: "Associations between lung function with physical and cognitive health in the Canadian Longitudinal Study on Aging (CLSA): A cross-sectional study from a multi-center national cohort"

-Acknowledgement: Please move the “Acknowledgements” section to follow the Discussion section.

-Abstract: Methods and Findings: Please revise to “58% females, mean age 58.8 years [standard deviation (sd) 9.6]”.

-Abstract: Methods and Findings: Please revise the final sentence of this section to: “A limitation of the current study is the observational nature of these findings and that causality cannot be inferred.”

-Abstract: Conclusions: Please revise to: “These findings support the broader implications…”

-Author summary: “What do these findings mean” Please revise to” …and cognitive and physical outcomes in the general population.”

-Methods: Line 61: Please verify if “ndd” should be “NDD”.

-STROBE Checklist: Please do not refer to page numbers in the checklist. Please revise the checklist, using only section and paragraph numbers to refer to locations in the text (e.g. Methods, paragraph 1).

PRESS

We frequently collaborate with press offices. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximise its impact. If the press office is planning to promote your findings, we would be grateful if they could coordinate with medicinepress@plos.org. If you have not yet opted out of the early version process, we ask that you notify us immediately of any press plans so that we may do so on your behalf.

We also ask that you take this opportunity to read our Embargo Policy regarding the discussion, promotion and media coverage of work that is yet to be published by PLOS. As your manuscript is not yet published, it is bound by the conditions of our Embargo Policy. Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit http://www.plos.org/about/media-inquiries/embargo-policy/.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Thank you again for submitting to PLOS Medicine. We look forward to publishing your paper.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine