The longitudinal relationship of changes of adiposity to changes in pulmonary function and risk of asthma in a general adult population
verfasst von:
Runa V Fenger, Arturo Gonzalez-Quintela, Carmen Vidal, Lise-Lotte Husemoen, Tea Skaaby, Betina H Thuesen, Mette Aadahl, Flemming Madsen, Allan Linneberg
Adiposity has been linked to both higher risk of asthma and reduced lung function. The effects of adiposity on asthma may depend on both atopic status and gender, while the relationship is less clear with respect to lung function. This study aimed to explore longitudinal weight changes to changes in forced expiratory volume in first second (FEV1) and forced vital capacity (FVC), as well as to incident cases of asthma and wheezing, according to atopy and gender.
Methods
A general population sample aged 19–72 years was examined with the same methodology five years apart. Longitudinal changes in weight, body mass index, waist circumference, and fat percentage (bio-impedance) were analyzed with respect to changes of FEV1 and FVC (spirometry), and incidence of asthma and wheezing (questionnaire). Gender, atopy (serum specific IgE-positivity to inhalant allergens) and adipose tissue mass prior to adiposity changes were examined as potential effect modifiers.
Results
A total of 2,308 persons participated in both baseline and five-year follow-up examinations. Over the entire span of adiposity changes, adiposity gain was associated with decreasing levels of lung function, whereas adiposity loss was associated with increasing levels of lung function. All associations were dependent on gender (p-interactions < 0.0001). For one standard deviation weight gain or weight loss, FEV1 changed with (+/−)72 ml (66-78 ml) and FVC with (+/−)103 ml (94-112 ml) in males. In females FEV1 changed with (+/−) 27 ml (22-32 ml) and FVC with (+/−) 36 ml (28-44 ml). There were no changes in the FEV1/FVC-ratio. The effect of adiposity changes increased with the level of adipose tissue mass at the start of the study (baseline), thus, indicating an aggregate effect of the total adipose tissue mass. Atopy did not modify these associations. There were no statistically significant associations between changes in adiposity measures and risk of incident asthma or wheeze.
Conclusions
Over a five-year period, increasing adiposity was associated with decreasing lung function, whereas decreasing adiposity was associated with increasing lung function. This effect was significantly greater in males than in females and increased with pre-existing adiposity, but was independent of atopy.
The online version of this article (doi:10.1186/1471-2466-14-208) contains supplementary material, which is available to authorized users.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
RVF and TS carried out the analyses and drafted the paper. AGQ, CV, LLH, and AL designed the study and helped to draft the manuscript. FM collected the spirometry data and participated in the design of the study. BHT and MA helped to draft the manuscript. All authors read and approved the final manuscript.
Background
Adiposity has consistently been associated with asthma [1] and has also been associated with impaired lung function, e.g. as assessed by decreased levels of forced expiratory volume in first second (FEV1) and forced vital capacity (FVC) [2‐6]. Thus, adiposity may influence the lungs in several ways, e.g. through inflammation leading to asthma-like, obstructive changes, or in terms of a mechanical impact on lung function (restrictive changes).
Adiposity increases the risk of asthma and may cause more severe symptoms along with a reduced response to medications [1, 7, 8]. Some studies have indicated that these effects are stronger in non-atopic individuals than atopic individuals [9‐11], although contrary results also have been noted [12]. Further, adiposity has been reported to be more strongly associated with asthma types characterised by non-eosinophilic inflammation rather than by eosinophilic inflammation [13]. However, it has not been investigated whether adiposity also has differential effects on lung function in atopic and non-atopic individuals or in individuals with or without eosinophilic inflammation in the airways. Underlying pathological processes, such as eosinophilic or neutrophilic inflammation [14], could possibly modify the longitudinal relationship of adiposity with lung function.
Anzeige
Mechanically, adiposity may cause an extra load on the thoracic cage [15], increase the intra-abdominal pressure, and impede the movements of the diaphragm [16]. This has in smaller experimental settings been reported to decrease static lung volumes and lead to breathing at smaller tidal volumes [17]. Cross-sectional studies have suggested that these changes are stronger in persons with predominantly abdominal adiposity than in persons with predominantly general adiposity [18]. Yet, prospective population based studies are sparse and have assessed adiposity changes mainly by weight or BMI [2, 3, 19‐22], except from one study that included waist and hip circumferences but not FVC [4]. Therefore, studies quantifying longitudinal changes of lung function with respect to different adiposity phenotypes may add further information about the longitudinal relationship between adiposity and lung function.
This prospective general population study aimed to investigate the association of longitudinal changes in weight, body mass index (BMI), waist circumference (WC), and fat percentage with longitudinal changes in FEV1 and FVC, and with concomitant incidence of asthma and wheezing. Further, we examined whether these associations were modified by gender, atopy, or eosinophilic inflammation of the lower airways as reflected by forced expiratory nitric oxide (FENO).
Methods
Study population
The current study used already sampled data from the Health2006 study and the Health2006-follow-up study conducted five years apart. The participants in the baseline Health2006 cohort were drawn as a random sample from the background population aged 18–69 years, living in 11 municipalities in the south-western part of suburban Copenhagen. A total of 3471 individuals (44.7%) entered the study and participated in the health examination, which took place in 2006–08 (Health2006 baseline [23]). In 2011–12, participants in the baseline Health2006 were invited for a 5-year follow-up examination including essentially the same study protocol. A total of 3,405 were eligible for invitation (21 had emigrated and 45 died). A total of 2,308 (68.6%) agreed to participate and were re-examined between November 2011 and November 2012. Fourteen participants did not have valid measures of either FEV1 or FVC at either baseline or follow-up and were excluded from the study, which for the main analyses was based on 2,294 participants. All participants gave written informed consent before taking part in the study, which was approved by the ethics committee of the Capital Region of Denmark, Copenhagen (KA20060011).
Questionnaire data
Information on socio-demographic variables, leisure time physical activity, smoking habits, chronic illnesses, respiratory symptoms, and medication were obtained from a questionnaire that was mailed to and answered by the participants before their visit to the research centre. Asthma was defined according to the ECRHS criteria [24] as a confirmatory answer to at least one of the following three questions ‘Have you been woken by an attack of shortness of breath at any time during the last 12 months?’, ‘Have you had an attack of asthma within the last 12 months?’ and ‘Are you currently taking any medication (including inhalers, aerosols or tablets) for asthma?’ Wheezing without a cold (in the following referred to as wheezing) was defined as a confirmatory answer to ‘Have you had wheezing or whistling in your chest at any time during the last 12 months?’ combined with a confirmatory answer to ‘If yes, have you had this wheezing or whistling when you did not have a cold?’. Smoking was recorded as pack years (one pack year equalling one pack of cigarettes per day for a year) and categorised in five levels: (1) never smokers, (2) 0- ≤ 10, (3) 10- ≤ 30, (4) 30- ≤ 50, or (5) more than 50 pack years but was also used as a continuous measure. Educational level was categorised as: (1) less than 2 years, (2) skilled worker, (3) less than 3 years, (4) 3–4 years, and (5) more than four years. All questions used in the present analyses were identical in the baseline and follow-up studies.
Anzeige
Physical measurements and assessment of lung function and FENO
Anthropometric measures were obtained with participants in light clothing and without shoes. Height was measured to the nearest cm, weight to the nearest 0.1 kg, and body mass index (BMI) was calculated as kg/m2. Waist circumference (WC) was measured to the nearest cm using a tape measure midway between the lower rib margin and the iliac crest. Fat percentage was measured using a foot-to-foot Tanita Body Composition Analyzer (TBF-300, TANITA Corporation of America, Inc., Illinois, U.S.A.). Spirometry was performed according to American Thoracic Society and the European Respiratory Society (ATS/ERS) standard [25] using Spiro USB Spirometers (MicroMedical Limited, Rochester, Kent, UK). Spirometers were checked daily with a 3-liter calibrated syringe, and checked every six months with a decompression flow simulator [26]. FENO measurements were performed only at baseline using a NIOX MINO (Aerocrine AB, Stockholm, Sweden). A dynamic flow restrictor yielded a constant flow rate of 50 mL/s, in accordance with recommendations of the ATS/ERS guidelines for FENO measurement [27]. Nitric oxide concentrations between 5 and 300 ppb were measured and measurements below 5 ppb were set to zero by the NIOX MINO. Nitric oxide concentrations above 20 ppb were considered high.
Biomarkers
Baseline serum samples were analysed for serum specific IgE against the four most clinically important inhalant allergens in Denmark: birch, grass, cat, and the house dust mite Dermatophagoides pteronyssinus, using the ADVIA Centaur Specific IgE assay [28]. Atopy was defined as at least one positive test (≥0.35 kilo units/L) against specific IgE. Plasma glucose concentrations were analysed by a hexokinase/glucose-6-phosphate dehydrogenase assay (Roche Diagnostic, Germany), and insulin concentrations were measured by fluoroimmunoassay technique (Dako Diagnostics Ltd., UK). The homeostatic model assessment-insulin resistance (HOMA-IR) index was calculated as: fasting plasma glucose (mmol/L) x fasting serum insulin (mU/L)/22.5 and applied only to the non-diabetic individuals. High-density lipoprotein (HDL) and triglyceride concentrations were measured by standard enzymatic techniques (Roche Diagnostic, Germany).
Statistics
We used the R-statistical package, version 3.0.2 (http://www.r-project.org/) for all analyses. All p-values are two-tailed and statistical significance defined as p <0.05. P-values of likelihood ratio tests were used to test for significance of all multivariate analyses. We used linear regression and checked for equal residual variance across the full range of all exposure variables to check the linear model assumptions. We also tested possible non-linear associations by dividing the exposure variables in splines and by testing the quadratic term of the variables in the regression models. For our main analyses, we used absolute or percentage changes (between baseline and five-year follow up) of the adiposity measures to changes in FEV1 and FVC. The changes of FEV1 (or FVC) were modelled as five-year FEV1 (or FVC) adjusted for FEV1 (or FVC) at baseline. We also tested the ‘reverse’ association of baseline lung function measures to changes of adiposity measures. The adiposity measures were standardised by division of each measure by its own standard error to ease interpretation of the regression coefficients and to ease a comparison of the magnitude of effects between the different adiposity measures. In analyses of incidence of asthma and wheezing, logistic regression was used, similar model checks were applied, and the adiposity measures were categorised in four equally sized groups by quartiles of their respective distributions. Possible interactions were tested by adding an interaction term to the regression models, e.g. (adiposity measure*atopy) or (adiposity measure*gender). Finally, all analyses were repeated with s-Trig, s-HDL, and HOMA-IR included in the models to test whether these metabolic markers would attenuate the estimates found for adiposity. Sensitivity analyses included exclusion of the lower and upper 0.0025, 0.005, 0.01 fractiles of the adiposity measures, as well as separate analyses in non- and never smokers, and in younger or older (age categories were +/− 40, +/−45, +/−50 years) individuals.
Finally, we made a simulation-model based on randomly generated heights, BMI-levels, and levels of lung volume dependent on height. This model gives an example of how adipose tissue above a certain ‘person-dependent ideal’ would influence lung function (Additional file 1).
Results
The baseline characteristics of the study population are given in Table 1. All characteristics are listed separately for participants and non-participants in the follow-up study. Of note is that non-participants as compared to participants had significantly higher levels of adiposity measures and higher levels of FEV1 and FVC. However, the baseline associations of adipose tissue levels with asthma, wheezing, FEV1 or FVC were not significantly different between participants and non-participants, all p-values for interaction between participation and each adiposity measure were between 0.12 and 0.98. Sensitivity analyses did not change the pattern of results presented.
Table 1
Baseline characteristics of the study population according to participation in the five-year follow-up study
Participants follow-up
Non-participants follow-up
N = 2294
N = 1163
Mean
Sd
n miss
Mean
Sd
n miss
Age (y)
50.02
12.49
48.02
13.98
FEV1 (liter)
3.16
0.79
9
3.04
0.88
5
FVC (liter)
4.03
0.96
9
3.89
1.06
5
N
% group
N
% group
Gender
Males
1048
45.7
495
42.6
Adiposity measures
18.5 > BMI (kg/m2)
38
1.7
27
2.3
18.5 < =BMI < 25 (kg/m2)
1096
47.8
491
42.2
25 < =BMI < 30 (kg/m2)
839
36.6
408
35.1
30 < =BMI (kg/m2)
319
13.9
2
237
20.4
WC, normal§
1748
76.2
359
50.7
WC, high§
545
23.8
2
349
49.3
3
Serum lipids
HDL, normal§
2036
89.1
10
993
86.3
13
HDL, low§
249
10.9
158
13.7
Triglyc <150 mg/dl
1901
83.2
887
77.1
Triglyc 150–500 mg/dl
230
10.1
161
14.0
Triglyc > = 500 mg/dl
154
6.7
10
103
8.9
13
Atopy, asthma, wheezing
Atopy*, not present
1741
75.9
924
79.4
Atopy*, present
553
24.1
239
20.6
Asthma, not present
1872
82.2
906
78.9
Asthma, present
405
17.8
17
242
21.1
15
Wheezing, not present
1974
86.7
915
79.9
Wheezing, present
303
13.3
17
230
20.1
18
Lifestyle
Smoking, never
1027
48.2
18
417
38.9
Smoking, 0- ≤ 10 pack years
492
23.1
253
23.6
Smoking, >10 pack years
613
28.8
403
37.6
89
Alcohol, no drinking
225
10.1
159
14.3
Alcohol 1–14 units/week
1448
65.0
714
64.4
Alcohol >14 units/week
555
24.9
66
236
21.3
54
Education§, none
239
10.5
215
18.8
Education§, 1 year/practical
543
23.9
272
23.8
Education§§, 2–3 years
943
41.4
450
39.3
Education§§, > = 4 years
551
24.2
18
208
18.2
18
FEV1, forced expiratory volumes first second; FVC, forced vital capacity; BMI, body mass index; WC, waist circumference; Diabetes*, either self-reported diabetes or fasting p-glucose > =7.1 mmol/L; HDL, serum level of high-density lipoprotein; Triglyc, serum level of triglyceride; *Atopy defined as serum specific IgE positivity (> = .35 kU/l) to inhalant allergens; §above primary school, §§above high school.
From baseline to five-year follow-up, lung function was inversely associated with the level of adiposity as reflected by all four adiposity measures. In participants with weight gain, lung function declined; whereas in participants with weight loss, lung function increased to a similar extend (Figure 1 and Table 2). This pattern was observed in both males and females but the strength of these associations differed significantly between the two genders (Table 2): For all four adiposity measures, the estimated effect of adiposity changes on changes in FEV1 and FVC were approximately three times higher in males than in females in absolute numbers. The percentage changes were the double in males as compared to females. For instance, for every one standard deviation of weight change (5.4 kg) from baseline to follow-up, FEV1 either increased or decreased with approximately 72 ml (66-78 ml) in males and 26 ml (21-31 ml) in females, similarly FVC either increased or decreased with 111 ml (101-121 ml) in males and 35 ml (27-43 ml) in females. The metabolic markers, s-triglyceride, s-HDL, or HOMA-IR did not attenuate the effects of adiposity measures on changes in FEV1 and FVC (data not shown). Estimated mean declines for one year of increasing age were approximately 32.8 (31.3-34.4) ml FEV1 and 21.4 (19.0-23.9) ml FVC. In never-smokers, the corresponding estimates were 31.0 (28.7-33.3) ml FEV1and 21.0 (17.4-24.6) ml FVC. All age-estimates were essentially similar in males and females but were significantly smaller in younger than in older individuals.
Figure 1
Changes of lung function according to weight changes. Five-year changes of FEV1 (upper panel) and FVC (lower panel) in quintiles of weight change in males (circles) and females (diamonds). Quintile one-two include individuals with weight loss, quintile four-five include individuals with weight gain. The middle quintile is used as reference. Analysis adjusted for age, tobacco use (pack years), and atopy.
×
Table 2
Five-year changes of FEV (ml) and FVC (ml) in males and females per one standard deviation (1 sd) increase of adiposity measure
Males
Females
Est (ml)
Se (ml)
P
Est (ml)
Se (ml)
p
p-i
FEV1
Weight (1 sd)
−72.6
5.8
<.001
−27.3
4.9
<.0001
<.001
BMI (1 sd)
−78.5
6.5
<.001
−25.5
4.6
<.0001
<.001
WC (1 sd)
−66.4
6.1
<.001
−23.4
4.8
<.0001
<.001
FatP (1 sd)
−52.0
6.2
<.001
−19.2
4.9
<.0001
<.001
FVC
Weight (1 sd)
−103.2
9.0
<.001
−36.2
7.6
<.0001
<.001
BMI (1 sd)
−113.6
10.0
<.001
−32.6
7.1
<.0001
<.001
WC (1 sd)
−90.7
9.4
<.001
−28.1
7.4
<.0001
<.001
FatP (1 sd)
−54.3
9.7
<.001
−18.0
7.6
0.01
0.002
Linear regression models fitted with interaction between the specific adiposity measure and gender. Adjusted for age, atopy, tobacco use (pack years). Est, beta-estimate; Se, standard error for Est; p, p-value; p-i, p-value for difference (interaction) between males and females; BMI, body mass index; WC, waist circumference; FatP, fat percentage.
The five-year adiposity changes had a differential impact on lung function changes according to baseline adiposity levels, as assessed as baseline BMI (Figure 2). Five-year adiposity changes were associated with dose-dependent greater declines of FEV1 and FVC in participants who were overweight and obese at baseline as compared to participants who were lean at baseline (Figure 2). Again, this effect was significantly different in males and females but the interaction of baseline-BMI*five-year changes of adiposity was only significant with respect to FVC (p = 0.02). Essentially similar results can be obtained by running our simulation example (Additional file 1). There were not any associations between changes of adiposity with changes of the FEV1/FVC-ratio between baseline and follow-up. For one standard deviation change of any adiposity measure, the FEV1/FVC-ratio changed between −0.0023 (fat percentage) to 0.00097 (BMI) in males (p-values 0.14-0.83) and this was not different in females (p for interactions 0.66-0.99).
Figure 2
Changes of lung function according to weight changes and baseline adiposity. Five-year changes of FEV1 (upper panel) and FVC (lower panel) per one standard deviation increase of weight between baseline and follow-up according to baseline levels of BMI (X-axis) in males (circles) and females (diamonds), adjusted for age, atopy, tobacco use (pack years), and atopy.
×
To further investigate the temporal relationship of associations between changes in adiposity and lung function, we performed ‘reverse’ analyses where baseline FEV1 and FVC were used as explanatory variables for subsequent adiposity changes. However, there were no such statistically significant associations. Thus, these results support that changes in adiposity have an influence on lung function, but lung function does not have a similar influence on changes in adiposity.
Anzeige
The inverse association of adiposity with lung function was confirmed in both persons with and without asthma at baseline (Table 3). The gender differences in lung function declines from baseline to follow-up were also independent of asthma status at baseline (Table 3). With respect to atopy and FENO -levels, there were essentially no differences in the associations of adiposity changes to changes of FEV1 and FVC between atopic and non-atopic individuals or between persons with or without elevated FENO-levels (Table 4). Analyses in never- and non-smokers gave similar results (data not shown).
Table 3
Five-year changes of FEV1 (ml) and FVC (ml) in males and females per one standard deviation increase of BMI from baseline to follow-up, according to asthma status at baseline
Males
Females
Est
Se
p
Est
Se
p
FEV1
Asthma
−96.4
16.7
<.001
−10.7
10.8
0.32
Non-asthma
−75.6
7.0
<.001
−29.1
5.2
<.001
FVC
Asthma
−109.7
24.4
<.001
−15.0
15.8
0.34
Non-asthma
−115.0
11.0
<.001
−37.3
8.1
<.001
All models fitted with BMI-gender interaction (all interactions significant, p ≤ .001) and adjusted for age, atopy, and smoking (pack years). BMI, body mass index; Est, beta-estimate; Se, standard error; ml, milliliter; p, p-value for Est.
Table 4
Five-year changes of FEV (ml) and FVC (ml) in non-atopic and atopic individuals (upper panel), and in individuals with or without elevated FeNO-levels (lower panel), per one standard deviation increase of adiposity measures
Est (ml)
Se (ml)
P
Est (ml)
Se (ml)
P
p-i
Non-atopic
Atopic
FEV1
Weight (1 sd)
−46.0
4.2
<.001
−46.2
8.5
<.001
ns
BMI (1 sd)
−42.3
4.2
<.001
−47.0
8.6
<.001
ns
WC (1 sd)
−38.9
4.3
<.001
−43.1
8.3
<.001
ns
FatP (1 sd)
−30.6
4.3
<.001
−35.8
8.5
<.001
ns
FVC
Weight (1 sd)
−65.5
6.5
<.001
−59.3
13.1
<.001
ns
BMI (1 sd)
−61.6
6.6
<.001
−54.8
13.2
<.001
ns
WC (1 sd)
−53.2
6.6
<.001
−48.6
12.8
<.001
ns
Fat (1 sd)
−32.3
6.7
<.001
−32.1
13.1
<.02
ns
Normal FeNO (<=20 ppb)
Elevated FeNO (>20 ppb)
FEV1
Weight (1 sd)
−45.6
4.7
<.001
−48.7
7.6
<.001
ns
BMI (1 sd)
−43.4
4.7
<.001
−43.9
7.7
<.001
ns
WC (1 sd)
−43.3
4.8
<.001
−31.7
7.2
<.001
ns
FatP (1 sd)
−31.8
4.8
<.001
−24.3
7.4
<.001
ns
FVC
Weight (1 sd)
−57.1
7.2
<.001
−85.2
12.6
<.001
0.04
BMI (1 sd)
−54.5
7.2
<.001
−78.5
12.8
<.001
ns
WC (1 sd)
−48.1
7.5
<.001
−59.4
11.9
<.001
ns
FatP (1 sd)
−32.2
7.5
<.001
−28.1
12.4
<.02
ns
Linear regression models fitted with interaction between adiposity measure and either atopy or elevated FeNO and adjusted for age, atopy, and smoking (pack years); p-i, p-values for interaction test. Est, beta-estimate; Se, standard error of Est; p, p-value; Atopy defined as serum specific IgE positivity (> = .35 kU/l) to inhalant allergens; FeNO, fractional expiratory nitric oxide;1 sd, one standard deviation; ns, non-significant; BMI, body mass index; WC, waist circumference; FatP, fat percentage.
Finally, we investigated whether baseline levels of adiposity measures or changes of adiposity levels from baseline to follow-up were associated with incident asthma and wheezing. The incidence of asthma and wheezing between baseline and follow-up was 7.0% (158/2265) and 5.9% (133/2263), respectively. There were no statistically significant associations of any adiposity measure (baseline or changes) with incident asthma but for changes of weight and BMI there was a positive association with wheezing (Table 5). Notably, the novel cases of asthma in our cohort could be categorised as ‘late-onset’ asthma because all participants were > =19 years at baseline. Restricting our analysis further to novel cases of asthma and wheezing in participants e.g. above > = 25 years or > = 40 years yielded similar results. There were no differences between atopic and non-atopic individuals or individuals with or without elevated FENO-levels with respect to incident asthma or wheezing (data not shown).
Table 5
The association of changes of adiposity measures (quartiles) between baseline and five-year follow-up with risk of novel (incident) asthma and wheezing
Incident asthma
Incident wheezing
N
n
n/N
OR
CI1
CI2
n
n/N
OR
CI1
CI2
Weight
Kg
q1
<−1.93
570
32
5.7
ref
-
-
26
4.7
ref
-
-
q2
1.93 - <0.7
573
47
8.3
1.47
0.91
2.42
27
4.7
0.89
0.48
1.63
q3
0.7 - <3.2
570
32
5.7
0.95
0.56
1.62
34
6.0
1.25
0.72
2.20
q4
>3.2
576
46
8.1
1.17
0.71
1.95
46
8.1
1.57
0.93
2.70
BMI
Kg/m2
q1
<−0.57
572
36
6.4
ref
-
-
25
4.5
ref
-
-
q2
−0.57 - <0.31
572
43
7.6
1.17
0.72
1.90
27
4.8
1.02
0.56
1.86
q3
0.31 - <1.216
572
36
6.4
1.00
0.61
1.65
35
6.2
1.35
0.77
2.41
q4
>1.22
573
42
7.4
0.88
0.53
1.43
46
7.1
1.69
0.99
2.94
WC
Cm
q1
<−1.5
564
30
5.4
Ref
-
-
27
4.9
ref
-
-
q2
−1.5 - <2
576
39
6.9
1.15
0.68
1.96
25
4.4
0.85
0.46
1.57
q3
2 - <5
525
45
8.7
1.62
0.98
2.71
43
8.3
1.67
0.98
2.91
q4
>5
626
43
6.9
1.14
0.69
1.91
38
6.2
1.27
0.74
2.22
FatP
Percentage points
q1
<−1.40
569
32
5.7
ref
-
-
31
5.0
ref
-
-
q2
−1.40 - <0.50
570
47
8.3
1.45
0.89
2.38
34
6.0
1.13
0.66
1.96
q3
0.50 - <2.402
569
42
7.5
1.24
0.75
2.06
25
4.5
0.77
0.42
1.38
q4
>2.40
570
33
5.8
0.78
0.45
1.35
40
7.1
1.20
0.71
2.05
Number of participants in each group (N), number of novel cases (n) and age, gender, and tobacco (pack years) adjusted odds ratios (OR) with 95% confidence intervals (CI1-CI2)); q1-q4, quartiles 1-4; BMI, body mass index; WC, waist circumference; FatP, Fat percentage.
Discussion
We quantified the longitudinal relationship of several adiposity measures, including waist circumference and fat percentage, with lung function reflected by FEV1 and FVC. Thus, we confirmed changes of FEV1 and FVC per one kilo weight increase as summarised in Additional file 2 and extended that knowledge by reporting longitudinal estimates for abdominal adiposity (waist circumference) and fat percentage. We found that an increase in adiposity over five years was associated with declines in FEV1 and FVC, whereas a decrease in adiposity was associated with increases of FEV1 and FVC. These associations were more pronounced in males than in females but were independent of atopy and FENO -levels. Adiposity changes were not associated with changes in the FEV1/FVC-ratio and were not associated with incident asthma.
Adipose tissue and especially upper body fat have in cross-sectional studies been shown to be associated with decreased static lung volumes as assessed by functional residual capacity and expiratory reserve volume [16, 17, 29]. As expiratory flow velocity is dependent on the degree of previous lung inflation due to the elastic properties of the lung [30], lower static lung volumes would subsequently impact on expiratory flows. Our results support such mechanical changes in a longitudinal setting. Firstly, the longitudinal adiposity changes were inversely associated with expiratory flow as reflected by FEV1. Secondly, pre-existing adiposity (at baseline) enhanced the negative impact of adiposity gain (Figure 2). Thus, the cumulative mass of adipose tissue was associated with reduced lung function as assessed by FEV1 and FVC. Adding that the FEV1/FVC-ratio remained unchanged, there was not a measurable increasing obstructive pattern with increasing adiposity. In comparison, inflammatory mechanisms would be expected to induce asthma-like, obstructive alterations in lung function [31].
Anzeige
The gender differences in the adiposity-lung function associations in this study were substantial, and may emphasise the mechanical aspects as males have more abdominal fat for the same degree of adiposity than females [32]. Similar conclusions have been put forward by authors in other studies [4, 33, 34] but supplementary explanations may exist. At least in asthma patients, recent cluster analyses have shown that a subgroup of non-adipose males have a high yearly loss of FEV1 that is not explained by presence or absence of atopy, the duration of disease etc. [35, 36]. This could indicate that another pathological mechanism towards declines of lung volumes occurs in those males, and this could also apply to males without asthma. Differences in sex hormonal levels, which are emphasised by decreasing gender differences in lung volume decline in elderly [3] is a possible explanation for an apparently different airway pathology in males and females. Other possibilities are different thresholds for the detrimental effects of pulmonary irritants, or differences in airway calibre between males and females [37], although none have been fully documented so far.
Atopy or FENO-levels did not modify the effects of adiposity on lung function. Thus, an underlying atopic as compared to non-atopic condition or an underlying eosinophilic as compared to non-eosinophilic airway inflammation did not appear to enhance the inverse association of adiposity with lung function in our general population. It is possible that a characterisation of participants by e.g. eosinophils in sputum or blood would have yielded other results, as elevated FENO-levels only are indicative of eosinophil airway inflammation [38]. For instance, cluster analyses have indicated that some groups of asthma patients are characterised by eosinophil airway inflammation and low lung function [39]. Further, faster declines of lung volumes in non-atopic as compared to atopic asthma patients have also been reported [36, 40, 41]. However, our study was conducted in a general population and not in specific groups of patients. Thus, absence of effect modification by atopy or FENO-levels in our study appears to emphasise restrictive changes of lung function with increasing adiposity. However, our study was not powered to investigate effect modifications. Therefore, more studies are needed to confirm or refute the presence of effect modification by atopy or elevated FENO-levels.
We did not find an association between increasing adiposity and asthma incidence but for increasing weight and BMI there was a positive association with incident wheezing. This is in contrast with findings of most longitudinal studies, which have reported a positive association between increasing BMI and incidence of asthma [1]. However, the power to detect such differences in the present study was relatively low as indicated by relatively wide 95% confidence intervals. Possibly, testing the association of adiposity with bronchial hyperreactivity (BHR) would have yielded other results; in a previous study we found a positive association of adiposity with BHR [42], but such information was not available in the current study.
The strengths of the study include the prospective design, validated and similar methods for measurements of FEV1 and FVC at baseline and follow-up, assessment of atopy by serum specific IgE and airway eosinophil inflammation by FENO. The limitations include the lack of tests for variability of lung function to define asthma, lack of measures of lung volumes, and that the analyses are based on the assumption that increases or decreases of weight and BMI were due to adipose tissue and not muscle mass. Selection bias may have decreased the generalisability of the study and loss to follow-up influenced the reported associations. However, we found similar baseline associations of adipose tissue measures with all outcomes in participants and non-participants in the follow-up indicating that our results may apply to a general population.
Anzeige
Conclusion
In conclusion, changes of adiposity had a high, gender specific impact on FEV1 and FVC but not on the FEV1/FVC-ratio. Increasing adiposity was associated with lung function decline, whereas loss of adiposity was associated with increasing lung function. These associations were independent of atopy, FENO -levels, and metabolic markers, but were modified by the level of adipose tissue prior to the adiposity changes indicating the importance of aggregate adipose tissue mass. The adiposity changes leading to declines of FEV1 and FVC were not concomitantly associated with incidence of asthma or wheezing, however, a low number of novel cases of asthma and wheezing may have limited the power to detect associations with these outcomes.
Acknowledgements
We are very grateful for the funding that we have received from: Aase and Einar Danielsens Foundation and The Danish Scientific Research Council and the Danish Lung Association.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
RVF and TS carried out the analyses and drafted the paper. AGQ, CV, LLH, and AL designed the study and helped to draft the manuscript. FM collected the spirometry data and participated in the design of the study. BHT and MA helped to draft the manuscript. All authors read and approved the final manuscript.
Die Therapie von Echinokokkosen sollte immer in spezialisierten Zentren erfolgen. Eine symptomlose Echinokokkose kann – egal ob von Hunde- oder Fuchsbandwurm ausgelöst – konservativ erfolgen. Wenn eine Op. nötig ist, kann es sinnvoll sein, vorher Zysten zu leeren und zu desinfizieren.
Seit November 2023 gibt es evidenzbasierte Empfehlungen zum perioperativen Management bei gastrointestinalen Tumoren (POMGAT) auf S3-Niveau. Vieles wird schon entsprechend der Empfehlungen durchgeführt. Wo es im Alltag noch hapert, zeigt eine Umfrage in einem Klinikverbund.
Mit dem demographischen Wandel versorgt auch die Chirurgie immer mehr betagte Menschen. Von Entwicklungen wie Fast-Track können auch ältere Menschen profitieren und bei proximaler Humerusfraktur können selbst manche 100-Jährige noch sicher operiert werden.
Worauf kommt es beim Management von Personen mit infektiöser Endokarditis an? Eine Kardiologin und ein Kardiologe fassen die zehn wichtigsten Punkte der neuen ESC-Leitlinie zusammen.
Update Innere Medizin
Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.
