Possible risk factors for poor asthma control assessed in a cross-sectional population-based study from Telemark, Norway

Regine Abrahamsen; Gølin Finckenhagen Gundersen; Martin Veel Svendsen; Geir Klepaker; Johny Kongerud; Anne Kristin Møller Fell

doi:10.1371/journal.pone.0232621

. 2020 May 12;15(5):e0232621. doi: 10.1371/journal.pone.0232621

Possible risk factors for poor asthma control assessed in a cross-sectional population-based study from Telemark, Norway

Regine Abrahamsen ¹, Gølin Finckenhagen Gundersen ¹, Martin Veel Svendsen ¹, Geir Klepaker ^1,², Johny Kongerud ^2,³, Anne Kristin Møller Fell ^1,^*

Editor: Davor Plavec⁴

PMCID: PMC7217450 PMID: 32396562

Abstract

This cross-sectional study of the general population of Telemark County, Norway, aimed to identify risk factors associated with poor asthma control as defined by the Asthma Control Test (ACT), and to determine the proportions of patients with poorly controlled asthma who had undergone spirometry, used asthma medication, or been examined by a pulmonary physician. In 2014–2015, the study recruited 326 subjects aged 16–50 years who had self-reported physician-diagnosed asthma and presence of respiratory symptoms during the previous 12 months. The clinical outcome measures were body mass index (BMI), forced vital capacity (FVC) and forced expiratory volume in one second (FEV₁), fractional exhaled nitric oxide (FeNO), immunoglobulin E (IgE) in serum and serum C-reactive protein (CRP). An ACT score ≤ 19 was defined as poorly controlled asthma. Overall, 113 subjects (35%) reported poor asthma control. The odds ratios (ORs) and 95% confidence intervals (CIs) for factors associated with poorly controlled asthma were: self-reported occupational exposure to vapor, gas, dust, or fumes during the previous 12 months (OR 2.0; 95% CI 1.1–3.6), body mass index ≥ 30 kg/m² (OR 2.2; 95% CI 1.2–4.1), female sex (OR 2.6; 95% CI 1.5–4.7), current smoking (OR 2.8; 95% CI 1.5–5.3), and past smoking (OR 2.3; 95% CI 1.3–4.0). Poor asthma control was also associated with reduced FEV₁ after bronchodilation (β –3.6; 95% CI –7.0 to –0.2). Moreover, 13% of the participants with poor asthma control reported no use of asthma medication, 51% had not been assessed by a pulmonary physician, and 20% had never undergone spirometry. Because these data are cross-sectional, further studies assessing possible risk factors in general and objectively measured occupational exposure in particular are needed. However, our results suggest that there is room for improvement with regards to use of spirometry and pulmonary physician referrals when a patient’s asthma is inadequately controlled.

Introduction

Asthma is the most prevalent chronic respiratory disease globally and imposes a substantial burden on patients, families, and communities [1, 2]. In particular, patients with severe asthma are hospitalized more often than other asthma patients, experience frequent exacerbations, and incur the majority of health care costs associated with this group of patients [3]. The Global Initiative for Asthma (GINA) guidelines state that asthma severity is a retrospective label that is assessed based on the treatment needed to control asthma, which in turn is assessed from two domains: symptom control and risk factors [2, 4].

Asthma control has been evaluated in a number of international studies, including several regions of Europe, in which both physicians and patients have reported poor levels of symptom control [5, 6]. These studies show that the prevalence of poor or suboptimal asthma control ranges from 57% to greater than 80%. This discrepancy is most likely related to the different methodologies applied, including the study group selected, because both selected patient populations [5] and samples from the general population [6] have been used. In the International Cross-Sectional and Longitudinal assessment of Asthma Control (LIAISON) study, major determinants for poor asthma control were reported to be seasonal worsening and persistent occupational exposure to allergens/irritants (self-reported and reported by their physician), followed by treatment-related issues. That study also reported that female sex, obesity, and smoking were associated with suboptimal asthma control. The Recognise Asthma and Link to Symptoms and Experience (REALISE) survey found that levels of asthma control were poor in a real-life sample from the general population of 11 European countries: 45% of respondents had uncontrolled asthma, and the level of well-controlled asthma ranged from 15% in Germany to 28% in Austria [6]. While these studies stressed the association between treatment-related issues and poor asthma control, little attention has been given to other important risk factors including occupational exposure to allergens and irritants [2, 4]. This information is considered to be important for improving work participation and asthma-related quality of life.

Our study aimed to assess the associations between possible risk factors and poor asthma control evaluated by the Asthma Control Test (ACT) [7, 8] in a sample of symptomatic asthma patients derived from a general population-based study in southeastern Norway. The following factors were assessed: self-reported exposure to occupational vapor, gas, dust, or fumes (VGDF), body mass index (BMI), sex, smoking, immunoglobulin E (IgE) in serum, serum C-reactive protein (CRP), fractional exhaled nitric oxide (FeNO), and lung function as assessed by spirometry. We also estimated the proportion of symptomatic asthma patients who had undergone spirometry, used asthma medication, or been examined by a pulmonary physician.

Materials and methods

Study sample

In February 2013, a random sample of 50,000 individuals aged 16–50 living in Telemark, a county in southeastern Norway, received a postal questionnaire as part of the Telemark study, which has been described in detail previously [9]. The response rate of the Telemark study was 33% (n = 16,099). Seven hundred non-responders were contacted by phone and/or mail and asked 13 key questions from the original questionnaire. Similar prevalence of physician-diagnosed asthma and several respiratory symptoms in responders and these non-responders were detected, although use of asthma medication was somewhat higher among those who responded (7.5% vs. 3.9% in non-responders).

As part of a nested case-control study conducted between August 2014 and December 2015, 1,857 asthma patients were eligible for medical examinations. Of these, 651 (35%) completed the medical examinations, 9% declined to participate, 34% did not attend their appointment, 11% had moved since 2013, and 10% lived more than 2 h by car from the medical examination locations and were therefore not invited. Altogether, 326 of those attending the medical examination for whom complete data were available reported having asthma symptoms during the previous 12 months. A flowchart of the participant selection process is shown in Fig 1.

Questionnaire

The study participants were asked if they had ever had their lung function measured by spirometry (“Have you ever been examined by spirometry?”), whether they were using asthma medication (“Do you currently use medication for asthma?”), and whether they had ever been examined by a pulmonary physician (“Have you ever visited a pulmonary physician?”). Physician-diagnosed asthma, occupational VDGF exposure, and allergy was defined by an affirmative response to the following questions: “Has a physician ever diagnosed you with asthma?”, and “Do you suffer from any form of allergy?”.

Participants who gave a positive response to “Have you experienced an asthma attack during the past 12 months?”, “Have you been awakened by heavy breathing/dyspnea at any time during the past 12 months?”, or “Have you experienced whistling or wheezing in your chest at any time during the past 12 months?” were asked to complete the ACT [8]. The ACT contains questions about asthma symptoms and the use of asthma medication within the previous 4 weeks. In this sample derived from the general population, we chose not to include the group of subjects who reported physician-diagnosed asthma without any symptoms during the previous year. All participants were asked “Have you visited a doctor or accident/emergency unit because of acute breathing difficulties at any time in the past 12 months?”, “Have you been hospitalized because of breathing difficulties at any time during the past 12 months?”, and “Have you used extra cortisone medication or increased your cortisone inhalation at any time during the past 12 months?”.

The single item question regarding self-reported occupational exposure to vapor, gas, dust or fumes (VGDF) was used: “Have you in your work been exposed to: vapor, gas, dust, or fumes during the past 12 months?”. The question shows good agreement with a multiple-item battery assessing such exposures, and modest agreement with a job-exposure matrix-based exposure categorization [10, 11].

Obesity

Study team members measured all participants’ body height and weight. Obesity was defined as BMI ≥ 30 kg/m² [12].

ACT

The ACT is a widely used self-administered assessment tool to determine how well a patient’s asthma is controlled [4, 7, 8]. The questionnaire consists of five questions regarding the occurrence of respiratory symptoms, medication use, and a self-assessment of symptom control during the previous 4 weeks. Each question is rated on a scale from 1–5 and values are summed for the ACT score. A low ACT score [5–19] indicates poorly controlled asthma, and a score of 20–25 indicates well-controlled asthma.

Clinical variables

Lung function was assessed as part of the study in the period from August 2014–December 2015, using pre- and post-bronchodilator spirometry performed in accordance with the American Thoracic Society (ATS)/European Respiratory Society (ERS) guidelines with a Jaeger Master Screen PFT (Erich Jaeger GmbH & Co. KG, Würzburg, Germany) [13]. The spirometer was calibrated daily with a 3 L syringe. Forced vital capacity (FVC) as percent of predicted, forced expiratory volume in one second (FEV₁) as percent of predicted, and the FEV₁/FVC ratio were recorded. All tests were performed under the guidance of one of three trained physicians, and were manually validated by two trained physicians (GK and JK) according to ATS/ERS guidelines using flow–volume and time–volume curves [13]. For the analyses of the lung function indices, we selected those participants with at least one valid spirometry result. All reference values were calculated using the equations from the Global Lung Function Initiative guidelines [14]. The fraction of exhaled nitric oxide (FeNO) in exhaled air was included as a marker of eosinophilic inflammation, and measured according to the ATS/ERS criteria using a NIOX MINO (Aerocrine AB, Solna, Sweden) [15]. This device provides FeNO measurements at a 50 mL/s exhalation flow rate using an electrochemical sensor, with values expressed in parts per billion (ppb).

Peripheral blood was collected from all participants at the same visit as the performance of spirometry and FeNO and analyzed using standard procedures. The concentration of IgE was analyzed to assess allergic response using a Siemens Immulite 2000 XPI at the Department of Laboratory Medicine, Telemark Hospital, Skien. High-sensitivity CRP was included as a marker of systemic inflammatory response and analyzed using a Modul c702 Cobas 8000 modular analyzer (Roche Diagnostics) at the Department of Medical Biochemistry, Oslo University Hospital (Ullevål), Oslo.

Statistical analyses

Pearson’s chi-squared and Fisher’s exact probability tests were used to compare categorical data, t-tests were used for normally distributed continuous data, and Mann–Whitney tests for non-normal continuous data. Multiple logistic regression was used to identify possible risk factors associated with poorly controlled asthma. Both crude and adjusted odds ratios (ORs) for other potential risk factors and confounders were calculated using a forward stepwise regression, which resulted in a model including only the significant risk factors and confounders. Associations between asthma control and clinical variables (lung function, IgE, CRP, FeNO) were analyzed using linear regression analysis, adjusting for age, sex, education, smoking habit, and obesity. Due to skewed distribution of IgE, CRP and FeNO, the regression analysis were performed on the log-transformed variant of these variables. Collinearity was investigated by Pearson correlation showing weak correlations between the included proxies for socioeconomic status (education, smoking, obesity and VGDF). The strongest correlation was between education and smoking (r = 0.16). Sensitivity analyses were performed for lung function, blood samples, and FeNO without adjustment obesity, but did not alter the results. Further, stratification by age was performed but the groups were small and the confidence intervals overlapping (results not shown). Statistical analyses were performed using IBM SPSS Statistics (version 25; IBM SPSS, Armonk, NY, USA), and p < 0.05 was considered significant.

Ethics approval

The Regional Committee for Medical and Health Professional Research Ethics (REC 2012/1665) approved the study. Participation was voluntary, and all participants were informed that they could withdraw from the study at any time without giving a reason. All participants signed an informed consent form. The study is registered at www.clinicaltrials.gov (NCT02073708).

Results

The characteristics of subjects with physician-diagnosed asthma who had experienced respiratory symptoms during the previous 12 months (n = 326), stratified by well-controlled (n = 213) and poorly controlled asthma (n = 113), are presented in Table 1.

Table 1. Population characteristics.

	Received ACT (n = 326)	Well-controlled asthma (n = 213)	Poorly controlled asthma (n = 113)	Well-controlled vs. poorly controlled
	N (%)	N (%)	N (%)	P
Residential area
Urban	220 (67)	149 (70)	71 (63)	0.215^*
Rural	106 (33)	64 (30)	42 (37)
Sex
Male	104 (32)	81 (38)	23 (20)	0.001^*
Female	222 (68)	132 (62)	90 (80)
Age (years)
16–30	62 (19)	40 (19)	22 (19)
31–40	87 (27)	64 (30)	23 (20)	0.361^‡
41–50	177 (54)	109 (51)	68 (60)
Education (years)
Elementary school (1–2)	44 (13)	24 (11)	20 (18)
Upper secondary and certificate (2–4)	133 (41)	83 (39)	50 (44)	0.026^‡
University (≥ 4)	149 (46)	106 (50)	43 (38)
Smoking habits
Never smoker	177 (54)	133 (62)	44 (39)
Past smoker	92 (28)	51 (24)	41 (36)	<0.001^†
Current smoker	57 (17)	29 (14)	28 (25)
Body mass index (kg/m²)
Normal weight (≤ 24.9)	119 (37)	87 (41)	32 (28)
Overweight (25–29.9)	111 (34)	73 (34)	38 (34)	0.006^‡
Obese (≥ 30)	96 (29)	53 (25)	43 (38)
Allergy
No	92 (28)	63 (30)	29 (26)	0.518*
Yes	234 (72)	150 (70)	84 (74)
Occupational VGDF previous 12 months
No	245 (75)	163 (77)	82 (73)	0.501^*
Yes	81 (25)	50 (23)	31 (27)
	N (Poorly-/well-controlled)^#	Median (IQR)	Median (IQR)
Blood samples
IgE (Ku/L, ref^** >87)	323 (112/211)	48 (128)	74 (196)	0.179^§
CRP (mg/L, ref^** <5)	323 (112/211)	1.3 (2.0)	2.0 (2.6)	0.005^§
FeNO (ppb, ref^** <25)	307 (103/204)	14.5 (14)	11.0 (12)	0.002^§
	N (Poorly/well controlled)^#	Mean (SD)	Mean (SD)
Spirometry
Pre-bronchodilator
FVC, % predicted	311 (106/205)	97.6 (11.7)	94.0 (14.2)	0.027^¶
FEV₁, % predicted	311 (106/205)	91.2 (14.4)	86.9 (17.3)	0.031^¶
FEV₁/FVC ratio in %	311 (106/205)	75.9 (8.0)	75.0 (8.8)	0.381^¶
Post-bronchodilator
FVC, % predicted	279 (91/188)	98.8 (11.1)	97.0 (13.3)	0.252^¶
FEV₁, % predicted	279 (91/188)	95.2 (13.2)	92.0 (15.4)	0.092^¶
FEV₁/FVC ratio in %	279 (91/188)	78.4 (7.6)	77.2 (8.3)	0.259^¶

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Statistically significant findings (p < 0.05) are in bold

* Fisher’s exact probability test

**Reference values

† Pearson’s chi-squared test

‡ Trend

§ Mann–Whitney test

¶ t-test

# Number of missing: IgE and CRP n = 3, FeNO n = 19, FVC, FEV₁, FEV₁/FVC ratio Pre-bronchodilator n = 15, Post-bronchodilator n = 47

ACT = asthma control test; VGDF = vapor, gas, dust, or fumes; FeNO = fraction of exhaled nitric oxide; IQR = interquartile range; SD = standard deviation

In the age group, 16–30; 36% of participants reported exposure to VGDF, while the percentage for those aged 31–40 and 41–50 were 27% and 24%, respectively.

Risk factors for poorly controlled asthma are presented in Table 2.

Table 2. Logistic regression-estimated odds ratios for risk factors associated with poorly controlled asthma (n = 113).

	OR_crude (95% CI)	OR_adj (95% CI)^*	OR_adj (95% CI)^**
Residential area
Urban	1.0	1.0	NS
Rural	1.4 (0.85–2.2)	1.4 (0.81–2.3)
Sex
Male	1.0	1.0	1.0
Female	2.4 (1.4–4.1)	2.6 (1.4–4.8)	2.6 (1.5–4.7)
Age (years)
16–30	1.0	1.0
31–40	0.65 (0.32–1.3)	0.53 (0.25–1.2)	NS
41–50	1.1 (0.62–2.1)	0.83 (0.42–1.6)
Education (years)
Elementary school (1–2)	1.0	1.0
Upper secondary and certificate (2–4)	0.72 (0.36–1.4)	0.76 (0.35–1.6)	NS
University (≥ 4)	0.49 (0.24–0.97)	0.58 (0.26–1.3)
Smoking habits
Never smoker	1.0	1.0	1.0
Past smoker	2.4 (1.4–4.1)	2.2 (1.2–3.9)	2.3 (1.3–4.0)
Current smoker	2.9 (1.6–5.4)	2.6 (1.4–5.2)	2.8 (1.5–5.3)
Body mass index (kg/m²)
Normal weight (18.5–24.9)	1.0	1.0	1.0
Overweight (25–29.9)	1.4 (0.81–2.5)	1.5 (0.83–2.9)	1.6 (0.88–2.9)
Obese (≥ 30)	2.2 (1.2–3.9)	2.2 (1.2–4.1)	2.2 (1.2–4.1)
Allergy
No	1.0	1.0	NS
Yes	1.2 (0.73–2.0)	1.3 (0.73–2.3)
Occupational VGDF previous 12 months
No	1.0	1.0	1.0
Yes	1.2 (0.73–2.1)	1.8 (1.0–3.4)	2.0 (1.1–3.6)

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Statistically significant findings (p < 0.05) are in bold.

* Adjusted for all other variables in the model

** Adjusted only for significant variables using forward conditional regression. OR; odds ratio; CI; confidence interval; NS = not significant; VGDF = vapor, gas, dust, or fumes.

Women were more likely than men to have poorly controlled asthma (OR 2.6; 95% CI 1.5–4.7). Self-reported exposure to VGDF was associated with poor asthma control (OR 2.0; 95% CI 1.1–3.6), as was obesity (BMI ≥ 30 kg/m²) (OR 2.2; 95% CI 1.2–4.1). Both past and current smoking were associated with poor asthma control (OR 2.3; 95% CI 1.3–4.0 and OR 2.8; 95% CI 1.5–5.3, respectively). The prevalence of having undergone spirometry, been examined by a pulmonary physician, and medication use, and the distribution of respiratory symptoms stratified by well-controlled and poorly controlled asthma, are shown in Table 3.

Table 3. Prevalence of spirometry, pulmonary physician examination, and medication use among those with physician-diagnosed asthma and symptoms during the previous 12 months.

	Received ACT^* (n = 326)	Well-controlled asthma (n = 213)	Poorly controlled asthma (n = 113)	p-value^**
Have you ever been examined by spirometry?	253 (78%)	163 (77%)	90 (80%)	0.578
Have you ever visited a pulmonary physician?	154 (47%)	99 (47%)	55 (49%)	0.728
Do you use asthma medication?	246 (76%)	148 (70%)	98 (87%)	0.001
Have you experienced an asthma attack during the past 12 months?	122 (37%)	61 (29%)	61 (54%)	<0.001
Have you been awakened by heavy breathing/dyspnea any time during the past 12 months?	92 (28%)	38 (18%)	54 (48%)	<0.001
Have you experienced whistling or wheezing in your chest at any time during the past 12 months?	229 (70%)	134 (63%)	95 (84%)	<0.001
Have you visited a doctor or accident/emergency unit because of acute breathing difficulties at any time during the past 12 months?	52 (16%)	18 (9%)	34 (30%)	<0.001
Have you used extra cortisone medication or increased your cortisone inhalation at any time during the past 12 months?	129 (40%)	61 (29%)	68 (60%)	<0.001
Have you been hospitalized because of breathing difficulties at any time during the past 12 months?	4 (1%)	2 (<1%)	2 (2%)	0.612

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*ACT; Asthma Control Test.

** Fisher’s exact test

More frequent use of asthma medication and more healthcare visits because of recent breathing difficulties were seen among patients with poorly controlled asthma than among those with well-controlled asthma. Moreover, 20% and 51% of patients with poor asthma control had never undergone spirometry or been examined by a pulmonary physician, respectively. Twenty-four percent of participants with asthma symptoms during the previous 12 months, and 13% of those with poorly controlled asthma had not used asthma medication.

Linear regression analysis was performed to identify differences in clinical variables between poor and well controlled asthma cases (Table 4).

Table 4. Linear regression to identify clinical differences between poor and well controlled asthma cases.

	N^* (poor/well-control)	β (95% CI)	p-value
Pre-bronchodilator
FVC-% predicted	311 (106/205)	–3.7 (–6.7, –0.7)	0.015^*
FEV₁% predicted	311 (106/205)	–4.3 (–7.9, –0.6)	0.022^*
FEV₁/FVC ratio in percent	311 (106/205)	–0.8 (–2.7, 1.1)	0.411^*
Post-bronchodilator
FVC % predicted	279 (91/188)	–2.5 (–5.5, 0.5)	0.105^*
FEV₁% predicted	279 (91/188)	–3.6 (–7.0, –0.2)	0.036^*
FEV₁/FVC ratio in percent	279 (91/188)	–1.0 (–2.8, 0.8)	0.278^*
Ln(IgE)	323 (112/211)	0.22 (–0.15, 0.59)	0.251^*
Ln(CRP)	323 (112/211)	0.09 (–0.13, 0.30)	0.428^*
Ln(FeNO)	307 (103/204)	-0.08 (–0.25, 0.09)	0.357^*

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Statistically significant findings (p < 0.05) are in bold.

*Number of missing values: Pre-bronchodilator FVC, FEV1, FEV1/FVC ratio n = 15, Post-bronchodilator FVC, FEV1, FEV1/FVC ratio n = 47, IgE n = 3, FeNO n = 19.

**Adjusted for age, sex, education, smoking habits, obesity

Table 4 shows that subjects with poor asthma control had post-bronchodilator FEV₁, while FeNO, IgE, and CRP were not statistically significant reduced.

Discussion

In this sample from the general population, 35% of patients with asthma and respiratory symptoms during the previous 12 months reported having poorly controlled asthma, defined as an ACT score ≤ 19. Poor asthma control was associated with obesity, female sex, smoking and self-reported occupational VGDF exposure. Low asthma control was also associated with a small reduction in post-bronchodilatory FEV_1.. More than half (51%) of those reporting poor asthma control had not been examined by a pulmonary physician, 13% had not used asthma medication, and 20% had never undergone spirometry.

In this study, self-reported occupational VGDF was associated with poor asthma control (Table 2). Unfortunately, as in most population-based studies, objective measurements for occupational exposure were not available. However, the applied single item question regarding self-reported occupational exposure to vapor, gas, dust or fumes (VGDF), is commonly used in occupational epidemiology and has been tested against responses to a 16-item battery assessing specific inhalation exposures and against a job exposure matrix (JEM) [9, 10]. The authors concluded that the single VGDF survey item appears to delineate exposure risk at least as well as a multiple-item battery assessing such exposures [9], and shows modest agreement with a JEM-based exposure categorization [9, 10]. Few studies have assessed occupation as a possible risk factor for poor asthma control [4], but our finding is consistent with those of previous studies reporting exacerbation of asthma from such exposure, and the LIAISON study, which found that self-reported occupational exposure to allergens/irritants was associated with poor asthma control [6, 16–18]. This cumulative evidence emphasizes the need for further efforts to reduce this possible risk factor, and for physicians to address occupational exposure in all asthma patients.

Obesity was also significantly associated with poor asthma control (Table 2). This observation is consistent with findings from several previous studies, and highlights the difficulty of achieving good asthma control in this group [6, 19–21]. Because weight loss may improve asthma control and lung function and reduce the need for medication in this group, our findings encourage the assessment of lifestyle factors in patients with poorly controlled asthma.

In this study, the OR for poor asthma control among women was more than twice that among men. This is in line with findings from a Swedish study from 2013 that showed that younger women had well-controlled asthma less often than men of the same age (OR 1.5; 95% CI 1.00–2.13) after adjusting for smoking, educational level, and BMI [22]. In a study from Saudi Arabia, 59% of men and 77% of women had uncontrolled asthma (p = 0.002) [23]. The international LIAISON study also reported that poor asthma control was associated with sex (men vs. women; OR 0.73; 95% CI 0.65–0.81) [6]. These findings highlight that special attention should be paid to women with poor asthma control.

Our results regarding smoking habits show that both past and current smokers may be more than twice as likely to have poorly controlled asthma than never smokers (Table 2). This is consistent with the GINA evidence showing that smoking exacerbates asthma, even in those with few symptoms [2]. Our findings may, in line with other studies presenting evidence of reduced asthma control and a greater need for health care among current smokers than among non-smokers and past smokers, emphasizes the importance of smoking cessation for asthma control. [24]

Table 1 shows that poor asthma control was associated with both an elevated level of the systemic inflammatory marker CRP and a reduced level of FeNO. After adjusting for possible confounders, CRP and FeNO were no longer significant (Table 4). This may imply that the univariate association is due to the confounders. Alternatively, the inclusion of not only severe asthma patients with signs of systemic inflammation or allergic response, but the whole range of subjects who had reported asthma symptoms in the previous 12 months could explain this finding.

Our results showed that post-bronchodilator FEV₁ was reduced in patients with poor asthma control (Table 4). A previous Swedish study reported that FEV₁ was associated with mortality [25], and a similar study from the US indicated that low FEV₁ was associated with increased mortality among patients with asthma [26]. However, in the Swedish study, post-bronchodilator tests were available only for parts of the cohort, while it is not clear whether the latter study used pre- or post-bronchodilator spirometry. In our study, both pre- and post-bronchodilator FEV₁ was associated with poor asthma control, whereas post-bronchodilator FVC was no longer significant after adjustment for possible confounders, including obesity. These findings combined underline the need for particular attention and close follow-up of patients with asthma who have reduced FEV₁.

To our knowledge, few studies have investigated the association between serum IgE and asthma control. In this study, no significant differences in IgE levels were observed between those with well- and poorly controlled asthma. Although a study from the US using data from the Severe Asthma Research Program found an inverse relationship between IgE levels and exacerbation [27], other studies have reported a positive association between IgE levels and asthma control [28, 29]. A possible explanation for these divergent results may be that some studies have evaluated the association between asthma control and a single measurement of total IgE, not longitudinal changes in asthma control and total IgE. Information regarding current treatment may also be important when interpreting total IgE levels in these patients [29]. Unfortunately, detailed information regarding treatment was not available in our study.

It is well known that patients with severe asthma may develop chronic airflow limitation [2]. The Norwegian guidelines for treatment of obstructive respiratory disease state that routine use of spirometry in general practice must be considered for patients at high risk of developing chronic airway obstruction [30]. Since the implementation of these guidelines, spirometry use in general practice increased from 24% in 1995/96 to 41% in 2003/04 [31]. A 2010 study from northern Norway showed that 70% of general practitioners used spirometry, consistent with our findings that 78% of our subjects had undergone spirometry (Table 2) [32]. International findings show large discrepancies in the use of spirometry by primary care services, from 6.7% in Australia to 42% in Belgium in 2011 [33]. Although spirometry use in Norway appears to be higher than that in many other countries, our results indicate that more than one in five patients with poorly controlled asthma may not have undergone spirometry.

Few studies have evaluated the proportion of patients with poorly controlled asthma who have been examined by a pulmonary physician. In our sample, only 49% of those with poorly controlled asthma had ever been assessed by a pulmonary physician. There are few specialist allergologists or severe asthma centers in Norway, hence, pulmonary physicians handle most cases with poor asthma control and severe asthma. According to the GINA guidelines, a lack of symptom control indicates the need for referral to a pulmonary physician or a severe asthma center to achieve better control and prevent disease progression [2]. We also observed a high prevalence of visits to a physician or accident/emergency department because of acute breathing difficulties among patients with poorly controlled asthma, supporting the need for specialist assessment. We found no significant difference between patients with well or poorly controlled asthma in terms of hospitalization because of respiratory problems. However, there were only four hospitalizations reported, so a larger sample size would be necessary to determine whether referral to a specialist leads to fewer hospitalizations and improved asthma control, as has been reported by others [2].

Twenty-four percent of participants who had asthma symptoms during the previous 12 months and 13% of those with poorly controlled asthma had not used any asthma medication. This is somewhat surprising because according to the Norwegian prescription register, Telemark County has been among the top five counties for use of asthma and COPD medication for several years, with an increase between 2012 and 2016 from 91 to 94 instances per 1000 inhabitants of all ages [34]. Potential reasons for the low use of asthma medication by the participants in this study may include that asthma patients are not using their prescribed medication, or that not all asthma patients with poor symptom control are assessed regularly or by a pulmonary physician; studies assessing asthma control over time are needed to clarify this issue.

There are a number of potential causes of poor symptom control in asthma, but our results suggest that patients with poorly controlled asthma may benefit from risk-factor evaluation and specialist assessment [35].

Limitations

An important limitation in this study was that physician diagnosis of asthma was self-reported and could not be directly verified. However, the sensitivity and specificity of self-reported physician-diagnosed asthma has been validated [36], and it is widely used and regarded as well suited for epidemiological studies. To reduce the probability of chronic obstructive pulmonary disease (COPD), we restricted the study group to ≤50 years. However, self-report of asthma medication use, respiratory symptoms, and occupational VGDF exposure may have resulted in recall bias, which may have led to differential misclassification. Nevertheless, this study used the validated ACT combined with standardized and validated questionnaires about respiratory symptoms and diseases, which likely reduced the probability of misclassification [8, 36–38]. An important limitation of our study was that objective measurements of occupational exposure were not available. Hence, the observed association between occupational exposure and poor asthma control should be interpreted with caution.

The response rate of the Telemark-study, from which the present study population was derived, was relatively low (33%). Although assessment showed a slightly higher prevalence of chronic cough and use of asthma medication among the study participants compared with non-responders, the prevalences of other respiratory symptoms and physician-diagnosed asthma were similar in participants and non-responders, indicating the validity of the estimates [11]. We also observed a relatively low response rate (35%) among those invited to the medical examinations. We have shown in a separate study that attendance to medical examinations was associated with BMI, sex, education, and smoking habits [39]. To decrease the likelihood of biased results, all regression analyses were adjusted for these factors. Further, it can be reasonably assumed that prevalence estimates would be more affected by increasing non-participation than associations between a risk factor and an outcome [40, 41]. Nevertheless, it is important to acknowledge that our sample size was limited, and that the results may not be entirely representative of an unselected population of people with symptomatic asthma.

We restricted the inclusion of participants to the age group 16 to 50 years. The youngest participants (16 to 30 years) reported the highest prevalence of occupational VGDF exposure (36% versus 27% and 24%). Although a substantial proportion of these subjects were unexposed students, apprentices and young workers may have a higher probability of exposure [42].

It could be argued that the analyses should have included all subjects with physician-diagnosed asthma, not only those who reported asthma symptoms within the previous 12 months. However, only 29% of the long-term asymptomatic subjects reported that they had used asthma medication. We considered it likely that asymptomatic subjects derived from a general population sample largely comprised those reporting childhood asthma without asthma symptoms in adulthood, and that the exclusion of these has probably resulted in somewhat lower estimates than if we had included all those who have ever been diagnosed with asthma.

Although our data are cross-sectional, they are from a sample of the general population and include all categories of patients with recent asthma symptoms, not only those with severe disease or a history of hospitalization. Importantly, as for all cross-sectional studies, no causal inferences could be drawn. This study was also limited in terms of size and geographic area; hence, larger, longitudinal studies are needed to confirm our findings.

Recommendations

When assessing asthma control, we recommend an increased focus on patients who have occupational exposure, a history of tobacco smoking, are obese, or are women. In agreement with the Nordic consensus statement on the systematic assessment and management of possible severe asthma in adults, referral to a pulmonary physician or a severe asthma center should be considered when a patient’s asthma is not well-controlled [35]. Consistent with the GINA strategy, we encourage physicians to use spirometry routinely to monitor all patients with asthma, particularly those with poorly controlled disease [2, 30].

Conclusion

One in three patients with physician-diagnosed asthma reported poor asthma control as assessed by the ACT. Poorly controlled asthma was associated with self-reported occupational VGDF exposure, obesity, female sex, smoking, and reduced FEV₁. Given the uncertainty about the temporal sequence of events that is inherent in its cross-sectional design, and the lack of objective measurements of occupational exposure, this study could not evaluate any causal relationships between risk factors and asthma control. Nevertheless, our results may indicate that even in a country with a high level of social security and health services, there is room for improvement in the use of spirometry, asthma medication, and referral to a pulmonary physician, as well as assessment of possible risk factors for patients with poorly controlled asthma.

Patient and public involvement

To realize the full potential of the study, we have involved user representatives in study planning, design piloting, and transfer of knowledge. A representative from The Norwegian Asthma and Allergy Association (NAAF) is a member of the study steering committee and has made valuable contributions to the development of questionnaires and methods for examination.

Supporting information

S1 File. Study questionnaire Norwegian.

(PDF)

Click here for additional data file.^{(260.1KB, pdf)}

S2 File. Study questionnaire English.

(PDF)

Click here for additional data file.^{(256.4KB, pdf)}

Acknowledgments

We thank the Blood Cell Research Group, Department of Medical Biochemistry, Oslo University Hospital and Department of Laboratory Medicine, Telemark Hospital, for the analysis of CRP.

Data Availability

We consider our minimal underlying data set to contain sensitive data, and also potentially identifiable individuals due to small groups. Sharing restrictions on the minimal data set are imposed from: The Regional Committee for Medical and Health Professional Research Ethics in South-east Norway (Study ID: REC 2012/1665), The Norwegian Data Inspectorate and the Telemark Hospital Department of Research and Development. However, data may be shared for researchers who meet the criteria for access to confidential data upon request to the head of the Telemark-Study steering committee: Dr. Trude K. Fossum, Department of Occupational and Environmental Medicine, Telemark Hospital, Post box 2900 Kjøbekk, 3710 Skien. E-mail: fotr@sthf.no The minimal data set identification (file name): 2020-02-05 Minimal data set PLOS ONE.sav

Funding Statement

The funder of this study was the Department of Research and Development at Telemark Hospital, Skien, Norway; grant number 18.72, grant receiver Ms. Gølin Finckenhagen Gundersen. The funders had no role in study design, data collection, analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0232621.r001

Decision Letter 0

Davor Plavec

3 Feb 2020

PONE-D-19-34283

Poor asthma control associated with occupational exposure, body mass index, sex, and smoking in a cross-sectional population-based study from Telemark, Norway

PLOS ONE

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Reviewer #1: No

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Reviewer #1: This was a very interesting study, which was well-written. Here are my specific observations and suggestions:

1. Line 38: how likely is it that the youngest participants were exposed to occupational fumes? It would be helpful to provide an additional table stratifying the descriptive statistics by age category due to heterogeneity in the sample.

2. Sensitivity analysis conducted by age group. Stratify the analysis by age groups due to the different stages of lung development across the age range. It is possible that some older participants have COPD, for example, and thus poorer lung function. Furthermore, teenagers are likely to under/mis-report smoking habits.

3. Education, smoking, obesity and possibly VGDF are likely to be proxies for socio-economic status and all correlated. The authors should investigate multicollinearity in their models and the relationships between these variables before including them in the regression models.

4. Line 164: “adjustment obesity” - please add “for”.

5. Table 1: Poorly controlled asthma for age: %s do not add to 100.

6. What are the reference/normal ranges for the clinical variables? This would provide greater clarity about differences and severity between both groups.

7. Greater clinical context is required about what the clinical variables mean and why they are relevant. To reader with limited clinical knowledge, it isn’t clear what the measures imply given the results. For example, there is no discussion about what CRP is, why it has been included in the study, and what the results mean clinically.

8. Table 4 and Methods: This is very confusing and unclear. I thought that poor asthma control (a binary variable) is the outcome throughout the paper (as also implied by the title of Table 4). If this is the case, your model is incorrect. Linear regression is for continuous outcomes. In light of these comments, the analysis and discussion surrounding Table 4 is unclear. Clarity is required on why you have chosen the model, what is the hypothesised causal relationship, and which variables are the dependent/independent variables.

9. The median and IQR has been reported for some clinical variables, suggesting they are not normally distributed. The authors should check whether the assumptions of the linear regression model have been upheld and whether these variables require transformation (e.g., logged).

10. Line 249: The authors should investigate whether non-significance of clinical variables could be due to the distribution of these variables.

11. Results have been presented for the first time in the Discussion section. I suggest that these should be presented in the Results section.

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Reviewer #1: No

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PLoS One. 2020 May 12;15(5):e0232621. doi: 10.1371/journal.pone.0232621.r002

Author response to Decision Letter 0

2 Mar 2020

Point to point response to editors and reviewers’ comments:

First, we would like to thank the reviewer for the thorough review and valuable comments that have allowed us to adjust accordingly, and improve the manuscript significantly.

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We have now labelled the files according to the style template.

We have now included both a Norwegian and an English copy of the questionnaire as Supporting Information.

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"The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

a. Please provide an amended Funding Statement that declares *all* the funding or sources of support received during this specific study (whether external or internal to your organization) as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now.

This is now included in the cover letter.

b. Please state what role the funders took in the study. If any authors received a salary from any of your funders, please state which authors and which funder. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

This is now included in the cover letter.

4. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability. Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. Any potentially identifying patient information must be fully anonymized. Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access. We will update your Data Availability statement to reflect the information you provide in your cover letter.

This is also included in the cover letter.

5. Review Comments to the Author

Reviewer #1: This was a very interesting study, which was well-written. Here are my specific observations and suggestions:

We have performed the stratification on age for the results in table 1. We have chosen not to include these in a new table because the table would be considerably larger and the important and interesting results are the following: “In the age group, 16-30; 36% of participants reported exposure to VGDF, while the percentage for those aged 31-40 and 41-50 were 27% and 24%, respectively.” This sentence is now included in the results section.

As suggested, we have performed sensitivity analyses (stratification) by age. However, the groups were small and the confidence intervals overlapping (results not shown) and thus to our opinion no meaningful information could be derived from these analyses. However, we have included the following to the statistic section: “ Further, stratification by age was performed but the groups were small and the confidence intervals overlapping (results not shown).”

In addition, we added the following regarding COPD and young participants (regarding the latter a new reference was added nr. 42) to the limitation section of the discussion:

1. “To reduce the probability of chronic obstructive pulmonary disease (COPD), we restricted the study group to ≤50 years.”

2. “We restricted the inclusion of participants to the age group 16 to 50 years. The youngest age group (16 to 30 years) reported the highest prevalence of occupational VGDF exposure (36%). Although a substantial proportion of these subjects were unexposed students, apprentices and young workers may have a higher probability of exposure [42].”

The following has been included in the statistics section: “Collinearity was investigated by Pearson correlation showing weak correlations between the included proxies for socioeconomic status (education, smoking, obesity and VGDF). The strongest correlation was between education and smoking (r=0.157).”

Because income is not necessarily a good measure of socioeconomic status in Scandinavia, education is often used. We have choose also to adjust for smoking because of the association with asthma severity. We have shown in other studies (based on the same cohort) that asthma is associated with obesity and exposure to VGDF. Hence, the results were adjusted for these four variables.

4. Line 164: “adjustment obesity” - please add “for”.

Thank you, this has been corrected.

5. Table 1: Poorly controlled asthma for age: %s do not add to 100.

This is due to rounding of numbers.

6. What are the reference/normal ranges for the clinical variables? This would provide greater clarity about differences and severity between both groups.

The reference values/range are now included in table 2.

We have met this comment by inclusion of the following information in the methods section (the new text is underlined) : Measurement of the concentration of IgE was included to assess allergic response and analyzed using a Siemens Immulite 2000 XPI at the Department of Laboratory Medicine, Telemark Hospital, Skien. High-sensitivity CRP was included as a marker of systemic inflammation and analyzed using a Modul c702 Cobas 8000 modular analyzer (Roche Diagnostics) at the Department of Medical Biochemistry, Oslo University Hospital (Ullevål), Oslo.

Accordingly, the following adjustment was made regarding FeNO: The fraction of exhaled nitric oxide (FeNO) in exhaled air was included as a marker of eosinophilic inflammation, and was measured according to the ATS/ERS criteria using a NIOX MINO (Aerocrine AB, Solna, Sweden) [13].

In addition, the following adjustment (the new text is underlined) is made to the corresponding text in the discussion section: Table 1 shows that poor asthma control was associated with both an elevated level of the systemic inflammatory marker CRP and a reduced level of FeNO. After adjusting for possible confounders, CRP and FeNO were no longer significant (Table 4). This may imply that the univariate association is due to the confounders. Alternatively, the inclusion of not only severe asthma patients with signs of systemic inflammation or allergic response, but the whole range of subjects who had reported asthma symptoms in the previous 12 months could explain this finding.

Thank you for this important comment. We agree that the table title and text was unclear. Linear regression was used to identify differences in clinical variables between poor and well controlled asthma cases. The clinical variables were the dependent in these analyses. We have now changed the title of table 4 and the text referring to this table in the results and discussion sections accordingly.

We have now performed the analyses on log transformed variables for IgE, CRP and FeNO (table 4). The conclusions are upheld, but we agree that the log transformed variables should be used and have included them in table 4.

10. Line 249: The authors should investigate whether non-significance of clinical variables could be due to the distribution of these variables.

Log transformed variables for IgE, CRP and FeNO are now used and did slightly influence the numbers, but the results are still not statistical significant (table 4). Please see also our response to comment 9.

11. Results have been presented for the first time in the Discussion section. I suggest that these should be presented in the Results section.

Thank you, we have now also included the following to the text in the results section: “Twenty-four percent of participants with asthma symptoms during the previous 12 months, and 13% of those with poorly controlled asthma had not used asthma medication.”

On behalf of the authors,

Sincerely yours

Anne Kristin M. Fell, MD, PhD

Corresponding author

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(22.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0232621.r003

Decision Letter 1

Davor Plavec

3 Apr 2020

PONE-D-19-34283R1

Poor asthma control associated with occupational exposure, body mass index, sex, and smoking in a cross-sectional population-based study from Telemark, Norway

PLOS ONE

Dear Dr Fell,

Based on significant arguments of the reviewer the manuscript needs major revision. The single question used in your study to assess possible occupational exposure can not be the proper argument to use this in both the Title and throughout the article. If you remove this kind of statement there is not much left regarding your methodology. Please revise your manuscript according to the reviewers remarks but be careful about your statements. They have to be based on proper argumentation and scientific proof.

We would appreciate receiving your revised manuscript by May 18 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Davor Plavec, MD, MSc, PhD, Prof.

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

Based on significant arguments of the reviewer the manuscript need major revision. The single question used in your study to assess possible occupational exposure can not be the proper argument to use this in both the Title and throughout the article. If you remove this kind of statement there is not much left regarding your methodology. Please revise your manuscript according to the reviewers remarks but be careful about your statements. They have to be based on proper argumentation and scientific proof.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: No

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #2: Respecting the comments from the previous review, the authors competently answered all the questions asked and made the required changes in the course of the manuscript.

Unfortunately, while reading the manuscript, I noticed some significant weaknesses.

Specifically, the title, methods, results, discussion, and conclusions of the article should be changed because it refers to poor asthma control associated with occupational exposures, ... which is actually based on a conclusion drawn from the answer to just one question asked in the questionnaire " Have you been exposed to: vapor, gas, dust or fumes during the past 12 months? ".

Therefore, no objective measurements were carried out or occupational exposure was objectively evaluated based on a validated questionnaire, as well.

A major revision of the article is needed, and the same should be pointed out in limitation in the study.

It is also necessary to validate the questionnaire.

The final number of respondents for the "population study" is also doubtful.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

PLoS One. 2020 May 12;15(5):e0232621. doi: 10.1371/journal.pone.0232621.r004

Author response to Decision Letter 1

16 Apr 2020

Point to point response to editors and reviewers’ comments:

First, we would like to thank the editor for the possibility to revise the manuscript a second time, and the reviewer for the additional comments that have allowed us to adjust accordingly and improve the manuscript.

Editors comment:

We agree that the best way to assess occupational exposure is by performing objective measurements of the agents involved. However, this is often not feasible in population-based studies. We have changed the title and adjusted the manuscript throughout to meet this important comment. We apologize for not including references regarding the validation of the single-item question regarding occupational exposure, this has now been included. The manuscript has been changed throughout regarding this issue, the most important changes are listed below (I-IV):

I: To underline the limitations of a single item question regarding occupational exposure, we have added the following to the limitation part (p.18): “An important limitation of our study was that objective measurements of occupational exposure were not available. Hence, the observed association between occupational exposure and poor asthma control should be interpreted with caution.”

II: We have added the following to the methods section including references (p. 7): “The single item question regarding self-reported occupational exposure to vapor, gas, dust or fumes (VGDF) was applied: ““Have you in your work been exposed to: vapor, gas, dust, or fumes during the past 12 months?”. The question shows good agreement with a multiple-item battery assessing such exposures, and modest agreement with a job exposure matrix-based exposure categorization [9, 10].”

II: We have also added the following text to the discussion (p. 13-14): “Unfortunately, as in most population-based studies, objective measurements for occupational exposure were not available. However, the applied single item question regarding self-reported occupational exposure to vapor, gas, dust or fumes (VGDF), is commonly used in occupational epidemiology and has been tested against responses to a 16-item battery assessing specific inhalation exposures and against a job exposure matrix (JEM) [9, 10]. The authors concluded that the single VGDF survey item appears to delineate exposure risk at least as well as a multiple-item battery assessing such exposures [9], and modest agreement with a JEM-based exposure categorization [9 ,10].“

We would like to add that the applied VGDF question has been used also in more recent studies [1, 2].

1. Paulin LM, Smith BM, Koch A, et al. Occupational Exposures and Computed Tomographic Imaging Characteristics in the SPIROMICS Cohort. Ann Am Thorac Soc 2018;15(12):1411-1419.

2. Murphy D, Bellis K, Hutchinson D. Vapour, gas, dust and fume occupational exposures in male patients with rheumatoid arthritis resident in Cornwall (UK) and their association with rheumatoid factor and anti-cyclic protein antibodies: a retrospective clinical study. BMJ Open 2018;8:e021754. doi:10.1136/bmjopen-2018-021754.

IV: Finally, the conclusion has been changed (the new text is underlined): “Given the uncertainty about the temporal sequence of events that is inherent in its cross-sectional design, and the lack of objective measurements of occupational exposure, this study could not evaluate any causal relationships between risk factors and asthma control.”

Reviewer 2:

Respecting the comments from the previous review, the authors competently answered all the questions asked and made the required changes in the course of the manuscript.

Unfortunately, while reading the manuscript, I noticed some significant weaknesses.

1. Specifically, the title, methods, results, discussion, and conclusions of the article should be changed because it refers to poor asthma control associated with occupational exposures, ... which is actually based on a conclusion drawn from the answer to just one question asked in the questionnaire " Have you been exposed to: vapor, gas, dust or fumes during the past 12 months? ". Therefore, no objective measurements were carried out or occupational exposure was objectively evaluated based on a validated questionnaire, as well. A major revision of the article is needed, and the same should be pointed out in limitation in the study.

Thank you for this important comment. We have changed the manuscript throughout accordingly (including the limitation section). Please see our reply to the editor above.

2. It is also necessary to validate the questionnaire.

The applied questionnaire has been validated, this was addressed in our manuscript (limitations p. 17): “Nevertheless, this study used the validated ACT combined with standardized and validated questionnaires about respiratory symptoms and diseases, which likely reduced the probability of misclassification [8, 36–38].“

Regarding validation of the single item question addressing occupational VGDF exposure, we have added more information. Please see also our response to the editors’ comment above.

3. The final number of respondents for the "population study" is also doubtful.

We agree with the reviewer that the final number of respondents is limited. We have addressed non-response in the limitation part of the discussion (p. 18): “The response rate of the Telemark-study, from which the present study population was derived, was relatively low (33%). Although assessment showed a slightly higher prevalence of chronic cough and use of asthma medication among the study participants compared with non-responders, the prevalences of other respiratory symptoms and physician-diagnosed asthma were similar in participants and non-responders, indicating the validity of the estimates [11]. We also observed a relatively low response rate (35%) among those invited to the medical examinations. We have shown in a separate study that attendance to medical examinations was associated with BMI, sex, education, and smoking habits [39]. To decrease the likelihood of biased results, all regression analyses were adjusted for these factors. Further, it can be reasonably assumed that prevalence estimates would be more affected by increasing non-participation than associations between a risk factor and an outcome [40, 41].”

On page 19 the problem of our limited sample size was addressed: “This study was also limited in terms of size and geographic area; hence, larger, longitudinal studies are needed to confirm our findings.”

To meet the reviewers comment, and to further underline the limited sample size, we have now added the following (p. 18, new text is underlined): “Nevertheless, it is important to acknowledge that our sample size was limited, and that the results may not be entirely representative of an unselected population of people with symptomatic asthma.”

We hope that we have been able to address the comments in a satisfactory way and are looking forward to your response.

On behalf of the authors,

Sincerely yours

Anne Kristin M. Fell, MD, PhD

Corresponding author

PLoS One. doi: 10.1371/journal.pone.0232621.r005

Decision Letter 2

Davor Plavec

20 Apr 2020

Possible risk factors for poor asthma control assessed in a cross-sectional population-based study from Telemark, Norway

PONE-D-19-34283R2

Dear Dr. Fell,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Davor Plavec, MD, MSc, PhD, Prof.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

After making a suggested revisions to your manuscript the manuscript is acceptable for publication in its current form. Thanks for working with our reviewers and our editors on improving the quality of your manuscript.

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0232621.r006

Acceptance letter

Davor Plavec

23 Apr 2020

PONE-D-19-34283R2

Possible risk factors for poor asthma control assessed in a cross-sectional population-based study from Telemark, Norway

Dear Dr. Fell:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Davor Plavec

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 File. Study questionnaire Norwegian.

(PDF)

Click here for additional data file.^{(260.1KB, pdf)}

S2 File. Study questionnaire English.

(PDF)

Click here for additional data file.^{(256.4KB, pdf)}

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(22.8KB, docx)}

Data Availability Statement

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PERMALINK

Possible risk factors for poor asthma control assessed in a cross-sectional population-based study from Telemark, Norway

Regine Abrahamsen

Gølin Finckenhagen Gundersen

Martin Veel Svendsen

Geir Klepaker

Johny Kongerud

Anne Kristin Møller Fell

Roles

Abstract

Introduction

Materials and methods

Study sample

Fig 1. Inclusion of participants reporting symptoms during the past 12 months (n = 326), and those with poorly controlled asthma (n = 113). ACT; Asthma control Test.

Questionnaire

Obesity

ACT

Clinical variables

Statistical analyses

Ethics approval

Results

Table 1. Population characteristics.

Table 2. Logistic regression-estimated odds ratios for risk factors associated with poorly controlled asthma (n = 113).

Table 3. Prevalence of spirometry, pulmonary physician examination, and medication use among those with physician-diagnosed asthma and symptoms during the previous 12 months.

Table 4. Linear regression to identify clinical differences between poor and well controlled asthma cases.

Discussion

Limitations

Recommendations

Conclusion

Patient and public involvement

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Davor Plavec

Roles

Author response to Decision Letter 0

Decision Letter 1

Davor Plavec

Roles

Author response to Decision Letter 1

Decision Letter 2

Davor Plavec

Roles

Acceptance letter

Davor Plavec

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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