Skip to main content
Download PDF

The prevalence of small airways disease and association with handgrip strength in young Hispanic farmworkers

BMC Pulmonary Medicine volume 24, Article number: 636 (2024) Cite this article

Abstract

Background

Small airways disease (SAD) is a key risk in developing obstructive lung diseases (OLD). Handgrip strength (HGS) is found to be associated with pulmonary function in populations with lung conditions. Hispanics remain the main workforce in farming industry, but their prevalence of lung conditions remain understudied. Likewise, HGS also remains understudied in Hispanic and farmworker populations. Our study investigated the prevalence of SAD and OLD as well as their associations with HGS among Hispanic farmworkers.

Methods

A cross-sectional study analyzed 113 Hispanic farmworkers (54% female) who were screened using pulmonary function tests during annual health fairs in rural Southeastern US from 2013 to 2017. Smoking status was self-reported. SAD was defined as forced expiratory flow at 25–75% predicted of vital capacity (FEF25-75%predicted) ≤ 60% per literature and OLD defined as forced expiratory volume in 1 s/ forced vital capacity (FEV1/FVC) ratio < 70% per Global Initiative for Chronic Obstructive Lung Disease criteria. Seated isometric absolute (the sum of both hands) and relative (absolute handgrip strength divided by body mass index) handgrip strengths were collected.

Results

26.5% of subjects had SAD and 15.9% had OLD. 50% of subjects with SAD had OLD while 83% of subjects with OLD had SAD. 13% of overall population smoked. Lower absolute and relative HGS groups had higher prevalence of SAD and OLD. Multivariate linear regression showed that lower absolute and relative HGS were associated with worsened small airway function. Age and FEF25-75%predicted were associated with FEV1/FVC. Smoking, body mass index, blood pressures, hemoglobin A1C and lipids were not predictors in either model.

Conclusions

This is one of the first studies reporting prevalence of pulmonary function in Hispanic farmworkers. Although this population was relatively young and healthy, there was high prevalence of SAD and OLD, which was higher than the overall prevalence in Hispanic population. There were more females subjects with SAD. Most of the subjects with OLD had SAD but not vice versa. Lower HGS levels were associated with worsened pulmonary function, and HGS was a significant predictor of FEF25-75%predicted, a potential marker for small airway physiology.

Peer Review reports

Background

The majority of labor force for agriculture in the United States is composed of migrant minority populations, in particular 70% is Hispanic [1]. Health care services are less available in rural areas compared to urban areas and these migrant working populations may have even more barriers to care including language and finance. In general, farmers are at higher risks of developing pulmonary and cardiometabolic diseases [1, 2]. We previously published our findings for a young Hispanic farmworking population with high prevalence of overweight/obesity, prehypertension/hypertension, and prediabetes/diabetes [2]. Despite having high risks for developing lung diseases, farmers, in particular of Hispanic heritage, remain understudied [3].

More than 140,000 Americans die from chronic obstructive pulmonary disease (COPD) each year (approximately 1 death every 4 min) with COPD mortality rate doubling since 1969 [4]. COPD, a major type of obstructive lung diseases (OLD) with main phenotypes of emphysema or chronic bronchitis, is the third leading disease-related cause of death in the US and fourth in the world. Although smoking continues to be one of the most significant risk factors for COPD, around one third of all US adults with COPD have never smoked. Approximately 6% of US workers (3.4 million) have COPD but 65% of these workers have never smoked [5].

Small airways is usually defined as airways with diameter less than 2 mm without cartilage [6]. Recent research has suggested that small airways disease (SAD) may be present in various lung conditions including OLD such as asthma and COPD [7]. Moreover, SAD is hypothesized to be involved in the early pathogenesis of OLD before the onset of major clinical symptoms because small airways often represent areas of the lung where defects can occur without becoming clinically noticeable [8]. These changes at the small airways can accumulate over time leading to loss of lung function [9]. Reviews have suggested that SAD and subsequent airflow limitation is a key predisposing factor leading to airway obstruction in OLD [10, 11]. One study found that the prevalence of SAD in COPD patients was 74% [12]. However, SAD continues to be understudied for reasons including natural limitations of biopsy [10]. No diagnostic standard exists for identifying SAD. Forced expiratory flow between 25 to 75% of vital capacity (FEF25-75%predicted) is a common spirometry value used for predicting SAD [13]. One review found the prevalence of SAD to be between 7.5% to 45.9% in the general population with age-dependency [14]. Two review articles found studies to have varying cutoffs for FEF25-75%predicted, as high as 80% and as low as 60% [14, 15]. Some studies have found high variation of FEF25-75%predictedamong subjects; while, others have shown that this marker is highly sensitive to detect early lung changes [10]. Both SAD and OLD have been hypothesized to be affected by environmental and workplace exposures [16].

The force during gripping motion produced from activities of both deep and superficial upper extremity muscles is known as handgrip strength (HGS) [17]. Lower HGS has been shown to be associated with all-cause mortality and worsened cardiometabolic and respiratory outcomes [17,18,19,20]. Studies have also found associations between lower HGS and worsened pulmonary functions and mortality in COPD patients [19,20,21,22,23]. HGS is an inexpensive, noninvasive and easy-to-implement tool with one clinical trial finding training nursing staff and assessing patients using HGS to be cost-effective [24]. This makes HGS an appealing measurement requiring additional investigation for potential diagnostic value across many populations, in particular the underserved as they often do not have resources to see additional experts or undergo diagnostic testing which can be expensive with limited or even no health insurance. One of these underserved groups is Hispanic farmworkers. We have previously shown that HGS was associated with cardiometabolic risk in this Hispanic farmworker population in a sex-specific manner [25].

Given that OLD, especially COPD, are usually chronic conditions, it is important to identify early pathophysiology such as SAD to prevent disease progression [10]. Although farmworkers, composed mainly of Hispanic adult population, are at higher risks of developing lung diseases, there have been few studies in this population. They may also not have the resource to obtain formal spirometry testing in clinic; therefore, it is important to identify additional tools, such as HGS, which may help elucidate their respiratory health. Thus we aimed to study the prevalence of SAD as well as OLD and whether lower HGS is associated with worsened pulmonary function in a Hispanic rural, migrant farming population living in Southeastern US.

Methods

Participants

This community outreach project was performed by the university and community partnership between Augusta University and Costa-Layman Farm during the summers 2013 to 2017. The Costa-Layman nursery is a wholesale supplier for perennials, located in Trenton, South Carolina. It was established in 1990, consisting of three farms, collectively totaling more than 1200 acres. Fliers were distributed among the employees and were posted on the noticeboards throughout the farms. All the employees working at the Costa-Layman Farms were invited to participate in this annual health-screenings. The consent form was translated in Spanish with proofreading from certified medical interpreters. Study information and consent process were conducted during the farm business hours with help of certified Spanish interpreters. Written informed consent was obtained from each participant. One hundred thirteen subjects had their HGS and spirometry obtained. The protocol was approved by the Institutional Review Board at Augusta University. All measurements were performed in the morning at the Costa-Layman horticulture farm.

Demographics

Anthropometry, blood pressure, and smoking status

Height and weight were obtained according to standard procedures, using a wall-mounted stadiometer (Tanita Corporation of American, Arlington Heights, IL) and calibrated electronic scale (model CN2OL; Cardinal Detecto, Webb City, MO). Body mass index (BMI) was calculated using CDC formula, weight (kg)/height (m2) for which we used for body weight classification: < 25 kg/m2 (normal weight), 25 -29.9 kg/m2 (overweight), or ≥ 30 kg/m2 (obese) [12]. After 5 min of rest, systolic (SBP) and diastolic blood pressures (DBP) were measured twice, each at least 1 min apart, in sitting position using manual mercury sphygmomanometer by trained research staff. The averages of two measurements were reported and used for analyses. Smoking status was assessed by self-reporting asking subjects whether they have ever smoked at least once in their lifetime. Number of packs and years of smoking were also asked.

Biochemical variables

Samples, including venous blood, were collected after an overnight fast, and all blood samples were processed immediately for following analyses. Glycosylated hemoglobin (HbA1C) and lipid profile (total cholesterol, low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglycerides) were assessed by standard clinical laboratory methods at Premier Medical Laboratory Services (Greenville, SC). HbA1C was determined based on turbidimetric inhibition immunoassay. Lipid parameters were measured by an enzymatic colorimetric method, using automated analyzer (Cobas c 311/501 and Cobas c 502) and Cobas enzymatic reagents.

Handgrip strength measurement

Isometric handgrip strength was measured using a Jamar Hydraulic Hand Dynamometer (Jamar; Bolingbrook, IL). Grip strength was measured in both hands in a seated position with the arm at a 90-degree angle according to the National Health and Nutrition Examination Survey guidelines for hand dynamometry [26]. Handgrip strength was measured three times, and the highest score was used for each hand. The combined strength (in kilograms) of the right and left hands were used to create the absolute handgrip value. The relative handgrip was then calculated as the absolute handgrip divided by their BMI (kg/BMI) [27].

Pulmonary function test (PFT)

American Thoracic Society (ATS) standard protocol was followed and administered by licensed respiratory therapists. Subjects blew three times to measure forced vital capacity (FVC) for each effort. If FVC was normal during the first effort, then test ended. If FVC was abnormal, then subjects blew three more efforts. If any result did not meet ATS standard, no further testing occurred. If all three results were abnormal and met ATS standard, then subjects were advised to visit their primary care physician for further evaluation. Forced expiratory volume in 1 s (FEV1), FEV1%predicted, peak expiratory flow (PEF), PEF%predicted, FEF 25–75%, FEF 25–75%predicted, FEV1/FVC and FEV1/FVC%predicted were collected as well. SAD was defined as FEF25-75%≤ 60% and OLD was defined as FEV1/FVC < 70% per Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria [14, 15].

Statistical analysis

Statistical analyses were performed using SPSS software (version 25, IBM SPSS Statistics, Chicago, IL). P-values < 0.05 were considered statistically significant for all analyses. Normal distribution and homogeneity of variances were confirmed by Shapiro-Wilks W and Leven’s tests, respectively. Continuous variables were summarized by median and ranges. Categorical variables were summarized by relative frequencies. Categorical variables were analyzed using chi-square tests, whereas continuous variables were compared using t-tests. LDL, HDL and triglycerides were log-transformed. Partial Pearson’s correlation coefficients were used to examine the associations of FEF25-75% and FEV1/FVC with risk factors. Multivariate linear regressions were used to estimate beta (β) and 95% confidence intervals (CI) for pulmonary function according to age, sex, smoking status, BMI, HbA1C, lipid profile and HGS.

Results

The population was composed of 113 Hispanic farmworkers and the median age was 36.9 years. The clinical characteristics of the participants are presented in Table 1. SAD was defined as FEF25-75%predicted ≤ 60%. More females were found to have SAD than males. The overall median BMI was 28.9. The overall median blood pressure was 122/76 which was significantly higher in the non-SAD group. The median absolute and relative HGS were 69.7 kg and 2.5 kg/BMI respectively. SAD group had significantly lower absolute and relative HGS values. The median values for FEV1% predicted, FVC, FVC% predicted, PEF, PEF% predicted, FEF25-75%, FEF25-75%predicted, FEV1/FVC, and FEV1/FVC predicted were significantly lower in the SAD group. Approximately 26.5% of subjects (30/113) had SAD and 15.9% had OLD (Figs. 1 and 2).

Table 1 General characteristics of the participants
Full size table

Comparison of prevalence of SAD and OLD

Fig. 1
figure 1

Prevalence of OLD in subjects based on FEF 25–75% predicted

Full size image
Fig. 2
figure 2

Prevalence of SAD in subjects based on FEV1/FVC (%). SAD was defined as FEF25-75%predicted ≤ 60%. OLD was defined as FEV1/FVC < 70%. P-value < 0.001 is labeled as*

Full size image

Variations in lung capacity by absolute and relative HGS groups

No significant difference was found comparing age groups to SAD but the oldest age group had a higher proportion (29.3%) of subjects having OLD. Approximately 13.3% of subjects (15/113) smoked at least once in their lifetime. There was also no significant difference for smoking status for SAD or OLD comparison. Significant differences were found comparing absolute HGS to SAD and OLD in Fig. 3. Significant differences were also found comparing relative HGS to SAD but not OLD, which was near significance (p-value < 0.06) in Fig. 4. The lowest absolute HGS group had 42.4% subjects with SAD and 21.2% with OLD. The highest absolute HGS group had 2.8% of subjects with SAD or OLD. The lowest relative HGS group had 45.2% of subjects with SAD and 25.8% with OLD. The highest HGS group had 11.4% of subjects with SAD and 6.8% of subjects with OLD.

Fig. 3
figure 3

Prevalence of SAD and OLD in Absolute HGS Tertiles

Full size image
Fig. 4
figure 4

Prevalence of SAD and OLD in Relative HGS Tertiles. P-value < 0.001 is labeled as*. P-value < 0.01 is labeled as #. Statistical test used was Chi-Squared comparing SAD or OLD with absolute and relative HGB tertiles. The number of participants in each tertile from lowest to highest for HGS were respectively 33, 44 and 36

Full size image

Associations between SAD with absolute and relative HGS

Table 2 shows multivariate linear regression adjusting for age, sex, smoking status and cardiometabolic markers. β and standardized β were reported along with 95% confidence intervals. Absolute HGS was found to be a positive significant predictor of FEF25-75%predicted.

Table 2 Dependent variable: FEF25-75%predicted
Full size table

Table 3 shows multivariate linear regression adjusting for age, sex, smoking status and cardiometabolic markers. β and standardized β were reported along with 95% confidence intervals. Relative HGS was found to be a positive significant predictor of FEF25-75%predicted.

Table 3 Dependent variable: FEF25-75%predicted
Full size table

Associations between OLD with absolute and relative HGS as well as FEF25-75%predicted

Table 4 shows multivariate linear regression adjusting for age, sex, smoking status and cardiometabolic markers. β and standardized β were reported along with 95% confidence intervals. Age was found to be a negative significant predictor of FEV1/FVC; while, FEF25-75%predictedwas a positive predictor.

Table 4 Dependent variable: FEV1/FVC
Full size table

Table 5 shows multivariate linear regression adjusting for age, sex, smoking status and cardiometabolic markers. β and standardized β were reported along with 95% confidence intervals. Age was found to be a negative significant predictor of FEV1/FVC; while, FEF25-75%predictedwas a positive predictor.

Table 5 Dependent variable: FEV1/FVC
Full size table

Discussion

This study investigated pulmonary function of Hispanic farmworkers located in Southeastern US. In this relatively young and healthy Hispanic adult working population approximately 13% of the subjects smoked at least once in their lifetime, 26.5% had small airways disease (SAD) and 15.9% had obstructive lung diseases (OLD). Approximately 50% of subjects with SAD had OLD while 83% of OLD patients had SAD. Smoking was not an independent predictor for SAD or OLD. Lower FEF25-75%predicted value was associated with lower FEV1/FVC ratio and weakened absolute or relative handgrip strength (HGS) was associated with lower pulmonary function. The weakest absolute or relative HGS groups had the most subjects with SAD or OLD; while, the strongest absolute or relative HGS groups had the least subjects with SAD or OLD.

This is one of the few studies to report detailed lung physiology in farmworkers and in Hispanics. Our analysis supports a positive association between FEF25-75%and FEV1/FVC. Half of the subjects with SAD had OLD; while, most subjects with OLD had SAD. The prevalence of SAD in farmworkers is not known due to limited studies. In a cross-sectional study of Chinese farmworkers, the prevalence of SAD was found to be approximately 50% [28]. This study focused on greenhouse workers, who are different from our subjects working both indoors and outdoors. In addition, a cross-sectional study of 1996 Hispanic farmworkers in Indiana, found the prevalence of SAD to be approximately 14%, and a lower prevalence than the Costa Layman population [29]. There is currently no gold standard measurement in diagnosing SAD; however, FEF25-75%predicted is the most commonly used and widely available assessment obtained via standard spirometry. There is no standard cutoff value for predicted FEF25-75%predicted, only that clinically lower values suggest SAD. FEF25-75% remains an understudied value despite being a commonly reported value on spirometry. Current evidence suggests that FEF25-75% is a sensitive marker to obstructive changes in peripheral airways [30, 31]. Two studies have proposed 60% be a cutoff value with higher sensitivity and specificity, and was incorporated into our study [32, 33]. Some studies have suggested physiological variability of FEF25-75%predicted [34]. However studies have shown that it is correlated with alveolar nitric oxide which is a tool used to detect small airway dysfunction, airway hyperresponsiveness and useful as an asthma control test, including the EGEA1 cohort [31, 35, 36]. It has also been shown to be associated with emphysema supported by radiological findings, including in the SPIRIOMICS cohort [37]. A review found that there are sex-related biological differences in lung pathology with small airway changes found more in females and emphysematous features found more in males [38]. This could help explain why females in our population were associated with higher SAD prevalence.

Approximately 13% of the Costa Layman population had smoked at least once in their lifetime. Studies indicate that the prevalence of smoking in the farmworking population is similar to that of the overall average of the working adult populations which is approximately 15% [39]. The prevalence of smoking in the US for Hispanic adult population is 12.4% and for non-Hispanic adult population is 25.6% [40]. The prevalence of Costa Layman subjects who developed SAD among those who smoked and those who did not was similar, which suggests that there are independent of smoking etiologies in this relatively young population. This finding is supported by other studies that also did not find an association between smoking and SAD [34]. It is hypothesized that farmworkers are at increased risk of developing SAD independent of smoking status due to chemicals, aerosols and pollutant exposures which can cause molecular injuries leading to immune and inflammatory system activation, mucus plugging and airway remodeling [16, 41]. One study suggested that some of these particles may alter DNA methylation affecting the airways even at the epigenetics level [42].

This study showed that most OLD subjects had SAD but not vice versa and is supported by literature showing worsening COPD conditions were associated with worsening SAD [12, 43]. This adds to the growing evidence that SAD is perhaps a predisposing factor in early OLD, which is important clinically as a potential therapeutic target [44,45,46]. Some inhalers and biologics may improve symptom control of OLD via targeting small airway inflammation and structural changes such as bronchiolar remodeling [6]. Mechanistically this suggests that increased peripheral airflow resistance is associated with central physiological airflow obstruction such as loss of elastic recoil and hyperinflation.

The prevalence of COPD in Hispanics in the US is approximately 5% [47]. The prevalence of OLD in our population of Hispanic farmworkers was higher at 16%. However, this is similar to the prevalence found in non-Hispanic farmworker studies [48, 49].. One review suggested that 15 to 20% of COPD is attributable to occupational exposures and agricultural sector is associated with increased risks for developing various pulmonary conditions compared to non-agricultural workers [49]. The Health and Retirement study found that farmworkers and those with exposure to organic solvents and pesticides had higher COPD incidences and subhazard ratios [3]. A large Chinese cross-sectional study found that greenhouse farmworkers have high COPD prevalence [50]. Horticulture farmworkers in this study work both outdoor and indoor environments with possible exposures to various chemicals including pesticides and solvents. Additionally, age was associated with OLD, congruent with previous studies suggesting that physiological changes at the cellular level due to aging can accelerate emphysematous changes [51]. The prevalence of OLD in subjects who smoked and those who did not smoke was similar, suggesting that there may be etiologies independent of smoking for developing OLD and is supported by a meta-analysis in which approximately 20% of patients who develop COPD are nonsmokers [52]. The overall higher prevalence of OLD in the Costa Layman Hispanic population compared to the national average suggest that there may be additional risk factors among these farmworkers..

Handgrip strength (HGS) has been rarely reported in farmworking and Hispanic populations. This study observed that weaker HGS was associated with worsened pulmonary function in Hispanic farmworkers. Several studies have reported positive associations between HGS and lung function in healthy and COPD populations [18,19,20,21,22,23]. One study found that weaker HGS among male workers in the manufacturing industry was associated with lower spirometric values [53]. We previously reported that lower HGS was associated with higher cardiometabolic risk factors in this Hispanic farmworker population [53]. To the best of our knowledge, this is the first report investigating the relationship between HGS and spirometric values in Hispanic or farmworker populations. HGS could also be a surrogate marker for overall muscular strength, respiratory muscles and exercise capacity [19, 54]. Spirometric values were also found to be associated with exercise capacity [55]. One study suggested that the inverse relationship between muscular strength and mobility was mediated by spirometry in older populations [56]. Although lower HGS groups had higher percentage of subjects with OLD, no significant association was identified in regression. This may be because most of these subjects are relatively young and therefore even if they have OLD, it could be at early stages which could be reflected by their relatively similar FEV1/FVC ratios. The differences in FEF25-75%predictedhowever was noticeable despite their young ages. It’s important to note that SAD often can occur before major clinical symptoms are detected. Although the underlying etiology for the association between HGS and pulmonary function remains unknown, HGS is a cost-effective tool to implement and its association with small airway physiology may suggest that it has the potential to become a tool used to screen for respiratory health which may led to earlier detection of lung diseases. This can be particularly useful in situations where patients may have difficulty obtaining spirometry [19].

Limitations of this study should be acknowledged. This cross-sectional analysis reveals associations and does not address causality, in the setting of a community health fair. Demographic data including country of origin and duration of residence in the US were not collected per requests from study participants. Additional challenges include a lack of detail regarding smoking history as well as post-bronchodilator PFT’s and the subsequent diagnostic disease within obstructive lung physiology. Thus the prevalence of obstructive lung diseases such as asthma could not be calculated. FEF25-75%predictedwas used to define SAD due to the widely availability of this measurement and the ease of using spirometry. However, there were no standard cutoffs for this measurement and less than 60% was selected based on studies which showed higher sensitivity [57]. Spirometry is naturally limited by the design of the test which is effort-dependent and potential physiological variabilities exist [7, 57, 58]. Additionally, the spirometry data collected was the average of each subject’s attempts rather than collecting all attempts from each participant; thus we were not able to analyze variations among each participant’s attempts. Because the collection of handgrip data was started during the second year of annual health fair, there are less participants in this study compared to the overall cohort. Nonetheless, pulmonary diseases and handgrip strengths are understudied in Hispanic and farmworker populations. In absence of such data, our findings help to bridge the knowledge gap.

Conclusions

This is one of the first studies to report prevalence of SAD and OLD in Hispanic farmworkers. More females had SAD than males, and most subjects with OLD had SAD but not vice versa. SAD could be an early predictor of OLD. In addition, weaker HGS was associated with lower FEF25-75%predicted. From a public health perspective, it may be important to screen farmers for pulmonary diseases regardless of their smoking status. HGS could be a cost-effective way to assess their overall respiratory health in particular small airway physiology. Identifying patients with SAD to help prevent developing OLD could be potential future preventive and therapeutic strategies.

Data availability

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

SAD:

Small airways disease

OLD:

Obstructive lung disease

HGS:

Handgrip strength

FEF25-75%predicted :

Forced expiratory flow at 25–75% predicted of vital capacity

FEV1/FVC:

Forced expiratory volume in 1s/ forced vital capacity ratio

COPD:

Chronic obstructive pulmonary disease

BMI:

Body mass index

SBP:

Systolic blood pressure

DBP:

Diastolic blood pressure

HbA1C:

Glycosylated hemoglobin

LDL:

Low-density lipoprotein

HDL:

High-density lipoprotein

PFT:

Pulmonary function test

ATS:

American Thoracic Society

FVC:

Forced vital capacity

FEV1:

Forced expiratory volume in 1s

PEF:

Peak expiratory flow

GOLD:

Global Initiative for Chronic Obstructive Lung Disease criteria

CI:

Confidence interval

References

  1. Respiratory Health Hazards in Agriculture. Am J Respir Crit Care Med. 1998;158(supplement_1):S1–76. https://doiorg.publicaciones.saludcastillayleon.es/10.1164/ajrccm.158.supplement_1.rccm1585s1.

    Article  Google Scholar 

  2. Raed A, Bhagatwala J, Cromer P, Zhu H, Pollock NK, Mazzoli A, Acharya N, Basu R, Patel K, Patterson G, Ramayya T, Alias S, Kotak I, Dong Y, Huang Y, Parikh SJ, Li W, Houk C, Layman D, Dong Y. Obesity and related cardiometabolic risk in young US Hispanic farmworkers: A neglected public health problem. J J Commun Med. 2017;3(1):030.

  3. Silver SR, Alarcon WA, Li J. Incident chronic obstructive pulmonary disease associated with occupation, industry, and workplace exposures in the Health and Retirement Study. Am J Ind Med. 2021;64(1):26–38. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/ajim.23196.

    Article  PubMed  Google Scholar 

  4. Pace WD, Brandt E, Carter VA, et al. COPD Population in US Primary Care: Data From the Optimum Patient Care DARTNet Research Database and the Advancing the Patient Experience in COPD Registry. The Annals of Family Medicine. 2022;20(4):319. https://doiorg.publicaciones.saludcastillayleon.es/10.1370/afm.2829.

    Article  PubMed  Google Scholar 

  5. Syamlal G, Doney B, Hendricks S, Mazurek JM. Chronic Obstructive Pulmonary Disease and U.S. Workers: Prevalence, Trends, and Attributable Cases Associated With Work. Am J Prev Med. 2021;61(3):e127–37. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.amepre.2021.04.011.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Cottini M, Lombardi C, Passalacqua G, et al. Small Airways: The “Silent Zone” of 2021 GINA Report? Front Med (Lausanne). 2022;9: 884679. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fmed.2022.884679.

    Article  PubMed  Google Scholar 

  7. Li Y, Li XY, Yuan LR, Wang HL, Pang M. Evaluation of small airway function and its application in patients with chronic obstructive pulmonary disease (Review). Exp Ther Med. 2021;22(6):1386. https://doiorg.publicaciones.saludcastillayleon.es/10.3892/etm.2021.10822.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Usmani OS, Dhand R, Lavorini F, Price D. Why We Should Target Small Airways Disease in Our Management of Chronic Obstructive Pulmonary Disease. Mayo Clin Proc. 2021;96(9):2448–63. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.mayocp.2021.03.016.

    Article  PubMed  Google Scholar 

  9. Lange P, Ahmed E, Lahmar ZM, Martinez FJ, Bourdin A. Natural history and mechanisms of COPD. Respirology. 2021;26(4):298–321. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/resp.14007.

    Article  PubMed  Google Scholar 

  10. Polverino F, Soriano JB. Small airways and early origins of COPD: pathobiological and epidemiological considerations. Eur Respir J. 2020;55(3):1902457. https://doiorg.publicaciones.saludcastillayleon.es/10.1183/13993003.02457-2019.

    Article  PubMed  Google Scholar 

  11. Radovanovic D, Contoli M, Braido F, et al. Future Perspectives of Revaluating Mild COPD. Respiration. 2022;101(7):688–96. https://doiorg.publicaciones.saludcastillayleon.es/10.1159/000524102.

    Article  CAS  PubMed  Google Scholar 

  12. Crisafulli E, Pisi R, Aiello M, et al. Prevalence of Small-Airway Dysfunction among COPD Patients with Different GOLD Stages and Its Role in the Impact of Disease. Respiration. 2017;93(1):32–41. https://doiorg.publicaciones.saludcastillayleon.es/10.1159/000452479.

    Article  PubMed  Google Scholar 

  13. Almeshari MA, Alobaidi NY, Sapey E, Usmani O, Stockley RA, Stockley JA. Small Airways Response to Bronchodilators in Adults with Asthma or COPD: A Systematic Review. Int J Chron Obstruct Pulmon Dis. 2021;16:3065–82. https://doiorg.publicaciones.saludcastillayleon.es/10.2147/copd.S331995.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Knox-Brown B, Mulhern O, Feary J, Amaral AFS. Spirometry parameters used to define small airways obstruction in population-based studies: systematic review. Respiratory Res. 2022;23(1):67. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12931-022-01990-2.

    Article  Google Scholar 

  15. Usmani OS, Singh D, Spinola M, Bizzi A, Barnes PJ. The prevalence of small airways disease in adult asthma: A systematic literature review. Respiratory Med. 2016;116:19–27. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.rmed.2016.05.006.

    Article  Google Scholar 

  16. Fransen LFH, Leonard MO. Small Airway Susceptibility to Chemical and Particle Injury. Respiration. 2022;101(3):321–33. https://doiorg.publicaciones.saludcastillayleon.es/10.1159/000519344.

    Article  CAS  PubMed  Google Scholar 

  17. Leong DP, Teo KK, Rangarajan S, et al. Prognostic value of grip strength: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet. 2015;386(9990):266–73. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/s0140-6736(14)62000-6.

    Article  PubMed  Google Scholar 

  18. Bjørn Heine S, Rachel C, Astrid B, et al. The association of grip strength from midlife onwards with all-cause and cause-specific mortality over 17 years of follow-up in the Tromsø Study. J Epidemiol Community Health. 2016;70(12):1214. https://doiorg.publicaciones.saludcastillayleon.es/10.1136/jech-2015-206776.

    Article  Google Scholar 

  19. Mgbemena NC, Aweto HA, Tella BA, Emeto TI, Malau-Aduli BS. Prediction of lung function using handgrip strength in healthy young adults. Physiol Rep. 2019;7(1): e13960. https://doiorg.publicaciones.saludcastillayleon.es/10.14814/phy2.13960.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Chen L, Liu X, Wang Q, et al. Better pulmonary function is associated with greater handgrip strength in a healthy Chinese Han population. BMC Pulmonary Med. 2020;20(1):114. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12890-020-1155-5.

    Article  CAS  Google Scholar 

  21. Han CH, Chung JH. Association between hand grip strength and spirometric parameters: Korean National health and Nutrition Examination Survey (KNHANES). J Thorac Dis. 2018;10(11):6002–9.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Puhan MA, Siebeling L, Zoller M, Muggensturm P, ter Riet G. Simple functional performance tests and mortality in COPD. Eur Respir J. 2013;42(4):956–63. https://doiorg.publicaciones.saludcastillayleon.es/10.1183/09031936.00131612.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Son D-H, Yoo J-W, Cho M-R, Lee Y-J. Relationship Between Handgrip Strength and Pulmonary Function in Apparently Healthy Older Women. J Am Geriatr Soc. 2018;66(7):1367–71. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/jgs.15410.

    Article  PubMed  Google Scholar 

  24. Ibrahim K, May CR, Patel HP, Baxter M, Sayer AA, Roberts HC. Implementation of grip strength measurement in medicine for older people wards as part of routine admission assessment: identifying facilitators and barriers using a theory-led intervention. BMC Geriatr. 2018;18(1):79. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-018-0768-5.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Raed A, Bilz J, Cortez-Cooper M, et al. Handgrip and sex-specific cardiometabolic risk factors in Hispanic/Latino migrant farmworkers. Sci Rep. 2021;11(1):10272. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41598-021-89138-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Lawman HG, Troiano RP, Perna FM, Wang CY, Fryar CD, Ogden CL. Associations of Relative Handgrip Strength and Cardiovascular Disease Biomarkers in U.S. Adults, 2011–2012. Am J Prev Med. 2016;50(6):677–83. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.amepre.2015.10.022.

    Article  PubMed  Google Scholar 

  27. Laukkanen JA, Voutilainen A, Kurl S, Araujo CGS, Jae SY, Kunutsor SK. Handgrip strength is inversely associated with fatal cardiovascular and all-cause mortality events. Ann Med May-Jun. 2020;52(3–4):109–19. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/07853890.2020.1748220.

    Article  Google Scholar 

  28. Zhu X, Gao P, Gu Y, et al. Positive Rates and Factors Associated with Abnormal Lung Function of Greenhouse Workers in China: A Cross-Sectional Study. Int J Environ Res Public Health. 2017;14(9). https://doiorg.publicaciones.saludcastillayleon.es/10.3390/ijerph14090956.

  29. Garcia JG, Matheny Dresser KS, Zerr AD. Respiratory health of Hispanic migrant farm workers in Indiana. Am J Ind Med. 1996;29(1):23–32. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/(sici)1097-0274(199601)29:1<23::Aid-ajim4>3.0.Co;2-#.

    Article  CAS  PubMed  Google Scholar 

  30. Kwon DS, Choi YJ, Kim TH, et al. FEF(25–75%) Values in Patients with Normal Lung Function Can Predict the Development of Chronic Obstructive Pulmonary Disease. Int J Chron Obstruct Pulmon Dis. 2020;15:2913–21. https://doiorg.publicaciones.saludcastillayleon.es/10.2147/copd.S261732.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Qin R, An J, Xie J, et al. FEF25–75% Is a More Sensitive Measure Reflecting Airway Dysfunction in Patients with Asthma: A Comparison Study Using FEF25–75% and FEV1%. J Allergy Clin Immunol In Practice. 2021;9(10):3649–3659.e6. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jaip.2021.06.027.

    Article  Google Scholar 

  32. Yolanda RQ, Jorge CM, Rosa GG, Julio VE, Rosa María RMT, Luis PM. Validity of the forced expiratory flow 25–75 for identification of bronchial hyperresponsiveness in a pulmonary function laboratory. Eur Respir J. 2013;42(Suppl 57):1280.

    Google Scholar 

  33. The PD, Van TT, Duong-Quy S. Study of forced expiratory flow of 25%-75% values (FEF25–75) in the control of asthma according to GINA. 2020.

  34. Perez T, Chanez P, Dusser D, Devillier P. Small airway impairment in moderate to severe asthmatics without significant proximal airway obstruction. Respir Med. 2013;107(11):1667–74. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.rmed.2013.08.009.

    Article  PubMed  Google Scholar 

  35. Williamson PA, Clearie K, Menzies D, Vaidyanathan S, Lipworth BJ. Assessment of Small-Airways Disease Using Alveolar Nitric Oxide and Impulse Oscillometry in Asthma and COPD. Lung. 2011;189(2):121–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s00408-010-9275-y.

    Article  PubMed  Google Scholar 

  36. Siroux V, Boudier A, Dolgopoloff M, et al. Forced midexpiratory flow between 25% and 75% of forced vital capacity is associated with long-term persistence of asthma and poor asthma outcomes. J Allergy Clin Immunol. 2016;137(6):1709–1716.e6. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jaci.2015.10.029.

    Article  PubMed  Google Scholar 

  37. Ronish BE, Couper DJ, Barjaktarevic IZ, et al. Forced Expiratory Flow at 25%-75% Links COPD Physiology to Emphysema and Disease Severity in the SPIROMICS Cohort. Chronic Obstr Pulm Dis. 2022;9(2):111–21. https://doiorg.publicaciones.saludcastillayleon.es/10.15326/jcopdf.2021.0241.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Somayaji R, Chalmers JD. Just breathe: a review of sex and gender in chronic lung disease. Eur Respir Rev. 2022;31(163). https://doiorg.publicaciones.saludcastillayleon.es/10.1183/16000617.0111-2021. 

  39. Syamlal G, King BA, Mazurek JM. Tobacco Use Among Working Adults - United States, 2014–2016. MMWR Morb Mortal Wkly Rep. 2017;66(42):1130–5. https://doiorg.publicaciones.saludcastillayleon.es/10.15585/mmwr.mm6642a2.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Cornelius ME, Loretan CG, Jamal A, et al. Tobacco Product Use Among Adults - United States, 2021. MMWR Morb Mortal Wkly Rep. 2023;72(18):475–83. https://doiorg.publicaciones.saludcastillayleon.es/10.15585/mmwr.mm7218a1.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Higham A, Quinn AM, Cançado JED, Singh D. The pathology of small airways disease in COPD: historical aspects and future directions. Respir Res. 2019;20(1):49. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12931-019-1017-y.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Hoang TT, Qi C, Paul KC, et al. Epigenome-Wide DNA Methylation and Pesticide Use in the Agricultural Lung Health Study. Environ Health Perspect. 2021;129(9):97008. https://doiorg.publicaciones.saludcastillayleon.es/10.1289/ehp8928.

    Article  CAS  PubMed  Google Scholar 

  43. Singh D. Small Airway Disease in Patients with Chronic Obstructive Pulmonary Disease. Tuberc Respir Dis (Seoul). 2017;80(4):317–24. https://doiorg.publicaciones.saludcastillayleon.es/10.4046/trd.2017.0080.

    Article  PubMed  Google Scholar 

  44. Wang C, Zhou J, Wang J, et al. Progress in the mechanism and targeted drug therapy for COPD. Signal Trans Target Ther. 2020;5(1):248. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41392-020-00345-x.

    Article  CAS  Google Scholar 

  45. Usmani OS, Dhand R, Lavorini F, Price D. Why We Should Target Small Airways Disease in Our Management of Chronic Obstructive Pulmonary Disease. Mayo Clin Proc. 2021;96(9):2448–63. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.mayocp.2021.03.016.

    Article  PubMed  Google Scholar 

  46. Rogliani P, Ritondo BL, Puxeddu E, Cazzola M, Calzetta L. Impact of long-acting muscarinic antagonists on small airways in asthma and COPD: A systematic review. Respir Med. 2021;189. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.rmed.2021.106639.

  47. Xuan L, Han F, Gong L, et al. Association between chronic obstructive pulmonary disease and serum lipid levels: a meta-analysis. Lipids Health Dis. 2018;17(1):263. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12944-018-0904-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Cushen B, Sulaiman I, Donoghue N, et al. High prevalence of obstructive lung disease in non-smoking farmers: The Irish farmers lung health study. Respir Med. 2016;115:13–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.rmed.2016.04.006.

    Article  PubMed  Google Scholar 

  49. Fontana L, Lee SJ, Capitanelli I, Re A, Maniscalco M, Mauriello MC, Iavicoli I. Chronic Obstructive Pulmonary Disease in Farmers: A Systematic Review. J Occup Environ Med. 2017;59(8):775–88. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/JOM.0000000000001072. 

  50. Liu S, Wen DL, Li LY, Li ZH. An epidemiological study of chronic obstructive pulmonary disease in greenhouse farmers in Liaoning Province from 2006 to 2009. Zhonghua Jie He He Hu Xi Za Zhi. 2011;34(10):753–6.

    PubMed  Google Scholar 

  51. MacNee W. Is Chronic Obstructive Pulmonary Disease an Accelerated Aging Disease? Ann Am Thorac Soc. 2016;13(Supplement_5):S429–37. https://doiorg.publicaciones.saludcastillayleon.es/10.1513/AnnalsATS.201602-124AW.

    Article  PubMed  Google Scholar 

  52. Ntritsos G, Franek J, Belbasis L, et al. Gender-specific estimates of COPD prevalence: a systematic review and meta-analysis. Int J Chron Obstruct Pulmon Dis. 2018;13:1507–14. https://doiorg.publicaciones.saludcastillayleon.es/10.2147/copd.S146390.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Kanai M, Kanai O, Fujita K, Mio T, Ito M. Decreased handgrip strength can predict lung function impairment in male workers: a cross sectional study. BMC Pulmonary Med. 2020;20(1):97. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12890-020-1135-9.

    Article  Google Scholar 

  54. Kim W, Park SH, Kim WS, et al. Handgrip Strength as a Predictor of Exercise Capacity in Coronary Heart Disease. J Cardiopulm Rehabil Prev. 2020;40(2):E10–e13. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/hcr.0000000000000458.

    Article  PubMed  Google Scholar 

  55. Luzak A, Karrasch S, Thorand B, et al. Association of physical activity with lung function in lung-healthy German adults: results from the KORA FF4 study. BMC Pulm Med. 2017;17(1):215. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12890-017-0562-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Sillanpää E, Stenroth L, Bijlsma AY, et al. Associations between muscle strength, spirometric pulmonary function and mobility in healthy older adults. Age (Dordr). 2014;36(4):9667. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s11357-014-9667-7.

    Article  PubMed  Google Scholar 

  57. Knox-Brown B, Mulhern O, Feary J, Amaral AFS. Spirometry parameters used to define small airways obstruction in population-based studies: systematic review. Respir Res. 2022;23(1):67. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12931-022-01990-2.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Almeshari MA, Alobaidi NY, Edgar RG, Stockley J, Sapey E. Physiological tests of small airways function in diagnosing asthma: a systematic review. BMJ Open Respir Res. 2020;7(1). https://doiorg.publicaciones.saludcastillayleon.es/10.1136/bmjresp-2020-000770.

Download references

Acknowledgements

Special thanks to Andrew Mazzoli, PhD, RRT and his team of respiratory therapists and students for administering and collecting PFT data.

Funding

This study was supported in part by Community Partnership Study Award to DL and YD from Institute of Preventative and Public Health at Augusta University.

Author information

Authors and Affiliations

  1. Pulmonary-Critical Care Fellowship, Mount Sinai Hospital, 1468 Madison Ave, New York, NY, 10029, USA

    Yutong Dong

  2. College of Nursing, Augusta University, Augusta, GA, USA

    Pam Cromer

  3. Community Liaison Between Augusta University and Costa-Layman Farm, Augusta, GA, USA

    Debbie Layman

  4. Department of Medicine, Georgia Prevention Institute, Medical College of Georgia, Augusta University, 1120 15 Street, Augusta, GA, 30912, USA

    Michelle Altvater, Yanbin Dong & Haidong Zhu

Authors
  1. Yutong Dong
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Pam Cromer
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Debbie Layman
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Michelle Altvater
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Yanbin Dong
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Haidong Zhu
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

YTD developed study theory, performed formal analysis and drafted the manuscript. YTD, DL, PC, MLA, YD and HZ carried out the investigation, collected data, and/or revised the manuscript.

Corresponding author

Correspondence to Yutong Dong.

Ethics declarations

Ethics approval and consent to participate

Written consent was obtained from each subject with study protocol approved by Institutional Review Board at Augusta University (IRB#Pro00001160).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dong, Y., Cromer, P., Layman, D. et al. The prevalence of small airways disease and association with handgrip strength in young Hispanic farmworkers. BMC Pulm Med 24, 636 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12890-024-03382-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12890-024-03382-2

Keywords

BMC Pulmonary Medicine

ISSN: 1471-2466

Contact us