Oyewale Mayowa Morakinyo*
Godson R. E. E. Ana- Department of Environmental Health Sciences, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
Introduction: Bioaerosols are among pollutants that impair indoor air quality in schools and have been associated with increased respiratory morbidities. Knowledge of bioaerosols’ sizes and the likely deposition sites within the child’s respiratory tract are essential for the identification of associated risks. This study was designed to determine bioaerosols’ size distribution and associated respiratory morbidities among school pupils in Ibadan North Local Government Area (INLGA), Ibadan.
Methods: A descriptive cross-sectional study design was adopted. In nine randomly selected public primary schools in INLGA, indoor air sampling (when occupied and unoccupied) was conducted thrice weekly for 3 months each in the wet and dry seasons, respectively. Airborne Bacterial Respirable Fraction (BRF) and Fungal Respirable Fraction (FRF) of aerodynamic diameter of 1.1–4.7 μm which corresponds to regions between the human primary bronchus and the alveolar duct were sampled using a six-stage cascade impactor. The BRF and FRF were estimated and dichotomised into high (>median) and low (≤median) categories. A standardized questionnaire was adapted to elicit information from 554 randomly selected pupils on socio-demographic characteristics and self-reported respiratory morbidities. Data were analyzed using descriptive and inferential statistics at α0.05.
Results: Median BRF and FRF during the wet season (2,890 and 283 cfu/m3) were significantly higher than dry season (1,661 and 196 cfu/m3), respectively and above WHO standards. Median BRF and FRF were significantly higher when classrooms were occupied (3,906 and 230 cfu/m3) than unoccupied (2,800 and 214 cfu/m3), respectively. About 67.5% of total bacterial and 77.8% fungal aerosols were respirable fractions. Age of pupils was 10.8 ± 1.35 years and 57.4% were males. Exposure to high BRF and FRF was significantly associated with current rhinitis (aOR = 1.78, 95%CI: 1.11–2.85 and aOR = 1.83, 95%CI: 1.14–2.93) and current wheeze (aOR = 2.77, 95%CI: 1.73–4.43 and aOR = 1.88, 95%CI: 1.18–3.00), respectively. Male pupils were more likely to experience current rhinitis (aOR = 1.09, 95%CI: 1.15–1.58) and current wheeze (aOR = 1.11, 95%CI: 1.22–1.62) than females.
Conclusion: Exposure to high levels of respirable bacterial and fungal fractions was associated with respiratory health outcomes among pupils.
1 Introduction
Clean air is a basic human right as well as a necessity for life and good health. Indoor air quality (IAQ) refers to the characteristics of the air in indoor settings where people spend a substantial amount of time each day, such as homes, workplaces, schools, and other built settings. It is a determining factor in ensuring a healthy life and people’s wellbeing (1).
Children spend a significant amount of time indoors, both at home and at school, with the latter being the second most common indoor environment after residences (2). The hours spent in school may expose them to potentially harmful pollutants (3). Children are at a greater risk of being harmed from exposure to indoor pollution than adults since they have smaller airways and underdeveloped respiratory and immunological systems (4). They also breathe in more air per unit mass than adults. While exposures may be small, they can accumulate and, in combination, have the potential to contribute to adverse health conditions (4).
Indoor air in schools is known to harbor bioaerosols (5). Bioaerosols are microbial fractions of solid and liquid particles (6). They are a mix of living (bacteria, fungi, viruses) and non-living microorganisms (endotoxins, metabolites, toxins) dispersed in the air, ranging in diameter from 0.5 to 30 m (7). They represent about 5–10% of airborne particulate matter and are universally present in the environment (8). The ability of bioaerosols to cause disease is determined by the amount of inhaled bioaerosols and their sizes, which dictate the site of deposition on human respiratory systems (9). For instance, inhalable bioaerosols usually settles in the extra thoracic region of humans while respirable bioaerosols can get to the regions of the trachea, bronchial and alveolar (10).
The outcomes of exposure to bioaerosols vary by season and constitute a public health challenge (11). Bioaerosols in indoor air can induce allergies and may be injurious to health (12). A significant population of fungi and bacteria in the indoor environment can cause mucous membrane irritation, fatigue, headaches, memory loss, and newborn bronchiolitis. (13). Studies have revealed that poor IAQ resulted in more illnesses, absenteeism, asthma attacks (9), respiratory and cardiopulmonary pathologies (14).
To lower the incidence of respiratory illnesses among Nigerian children, scientific and evidenced-based findings are needed to understand IAQ in primary schools. There is insufficient data on the types and possible sites of deposition of respirable bioaerosols within the respiratory tract of school children based on their size fractions. Having an understanding of the association between the levels and size fractions of bioaerosols, deposition sites within the respiratory tract and inhalation dose of bioaerosols in the indoor school environment is crucial to instituting appropriate strategies to protecting the vulnerable populations from poor IAQ.
This study sought to (i) quantify the seasonal burden and characteristics of indoor bioaerosols responsible for the reported respiratory morbidities among school children, and (ii) determine the levels, size distributions and deposition sites of bacterial and fungal particles.
2 Methodology
2.1 Study area
This study was carried out in Ibadan, the capital of Oyo State in western Nigeria. Ibadan is located on longitude 7°23′47″N, latitude 3°55′0″E and at an altitude of 152–213 m (15). It has an estimated population of 4,144,130 (16). Ibadan’s climate is tropical, with distinct wet and dry seasons and a mean minimum annual temperature of 210°C. The city has 11 Local Government Areas with a total area of 103.8 sq. km (LGAs). Ibadan North LGA (Figure 1) is one of the 11 LGAs where the study was conducted.
Figure 1. Map of Ibadan North Local Government Area.
2.2 Study design
A mixed study design was adopted involving field and laboratory components comprising questionnaire administration, indoor and outdoor air quality monitoring for bioaerosols’ size distribution and deposition.
2.3 Study population
The study population were primary school pupils in classes three to six (Grade 3–6) in the selected schools. An eligible study participant must have attended the school for at least 1 year. Study participants were selected using a systematic random sampling. A total of 520 consented pupils were recruited into the study.
2.4 Selection of schools and sampling site
One-stage sampling method that involves balloting was used in randomly selecting Ibadan North Local Government Area (INLGA) from the 11 LGAs in Ibadan. Also, balloting was used to select a total of nine public primary (mixed schools) schools in INLGA. The selection of classrooms for the evaluation of the seasonal fluctuations and size distribution of indoor bioaerosols was based on key environmental and building features such as building types, building materials, ventilation type, etc. Also, schools with comparable student populations and classroom occupancy rates were given preference in order to reduce selection bias and improve comparability across study sites.
2.5 Data collection methods
Data collection for this study was carried out in three phases:
i. Air sampling of viable airborne bioaerosols into size fractions using a six-stage microbial impactor.
ii. Estimation of dose rates of respirable bacterial and fungal aerosols.
iii. Determination of the prevalence of reported respiratory symptoms and other characteristics using a semi-structured questionnaire.
2.6 Instrument for bioaerosols’ sampling
A six-stage Honri Airclean (Model FSC-A6) impactor Air Sampler was deployed for sampling of bacterial and fungal aerosols into various sizes. It was designed such that particles of different sizes are aerodynamically sized and compared with the human respiratory tract. As a result, the sampler can estimate the disease-causing potential of airborne particles based on their deposition site within the respiratory tract. The aerodynamic diameters of the six-stage impactor are >7 m (stage 1), 4.7–7 m (stage 2), 3.3–4.7 m (stage 3), 2.1–3.3 m (stage 4), 1.1–2.1 m (stage 5), 0.65–1.1 m (stage 6) corresponding to the surface, pharynx, trachea, and primary, secondary, terminal, and alveoli regions of the human respiratory tract, respectively (17). The impactor allowed for a uniform bioaerosol sampling methodology, which ensured a consistent sampling of bioaerosols across respirable and non-respirable particle fractions. This method allowed size-segregated bioaerosol profiles under various seasonal conditions to be robustly compared.
2.7 Sampling of bioaerosols and culture medium
The field sampling for airborne bacteria and fungi was carried out in nine schools in both outdoor and indoor when the classrooms were unoccupied and occupied. Sampling was done thrice weekly for 3 months each in the wet and dry seasons. Given the impact of meteorological conditions including humidity, rainfall, and temperature, sampling was done both in the wet and dry seasons to accurately capture seasonal fluctuation in bioaerosol concentrations and types. To guarantee equal representation of both seasons in all chosen schools, sample collection was scheduled.
The sampling protocol previously used by Fang et al. (18, 19) was employed in this study. Prior to sampling, each of the six stages of the FSC-A6 microbial sampler were sterilized with 75% alcohol and loaded aseptically (inside a Class II biosafety cabinet) with 90 mm Petri dishes containing MacConkey agar medium and Sabouraud Dextrose Agar medium (contained a 100 mg of chloramphenicol to inhibit bacterial growth) after its sterilization with a 75% alcohol (19) for bacterial and fungal sampling, respectively.
The FSC-A6 microbiological sampler was set up on a platform of height 1.5 m at each sampling point in each school, aiming for the children’ breathing zone and operated at a flow rate of 28.3 L/min for 15 min during two sampling periods (8:00 am and 2:00 pm), respectively. A sampling time of 15 min was selected because according to Tortora et al. (20) and Jensen and Schafer (21), this is the approved sampling time for obtaining between 30 and 100 microbial cells on a single petri dish.
2.8 Estimation of microbial counts
The plates were transported in an icebox to the laboratory and incubated in an incubator for 48 h at 37°C for bacterial samples and 72 h at 25°C for fungal samples (17). To adjust for overlapping colonies, the number of bacterial and fungal colonies that developed was counted using the positive-hole correction technique (22).
Using the formula (Equation 1), the total bacterial count (TBC) and total fungal count (TFC) were calculated in colony-forming units per cubic meter (cfu/m3) (17):
The concentration of bacteria and fungi at each sampling point for each stage was estimated using Equations 2, 3 as follows:
Where Bti: bacterial size fraction (%); Ci: the concentration of bacteria on stage i; TBC: Total bacteria concentration for all the stages.
Where Fti: Fungal size fraction (%); Ci: the concentration of fungi on stage i; TFC: total concentration of fungi (23)The total Bacteria Respirable Fraction and the Total Fungi Respirable Fraction was estimated using Equations 4, 5 as follows:
2.9 Questionnaire administration
A standardized questionnaire by the International study on Asthma and Allergies in Childhood (ISAAC), was adapted and administered on pupils in classes’ three to six to elicit information on socio-demographic characteristics of pupils, environmental conditions of classrooms, perceived health effects, frequency of occurrence of perceived health complaints and symptoms, associated with exposure to indoor air pollutants.
Moreover, another semi-structured questionnaire was used to elicit information from parents on: demographic characteristics, child’s history of respiratory infections, risk factors for respiratory infections, household population and household characteristics, substance use, etc.
2.10 Dependent and independent variables
The dependent variables include current rhinitis, rhinitis ever, current wheeze and wheeze ever. The definition of the health outcomes as stated in the questionnaire is presented in Table 1. The main predictors of the health outcomes in this study include respirable bacterial and fungal aerosols, and total bacterial and fungal aerosols. Other independent variables or covariates identified in this study include age (<10 or ≥10 years) and gender (male or female) of the pupil, and type of fuel used for cooking at home.
Table 1. Dependent variables.
2.11 Data analysis
The data were analyzed using a non-parametric approach because they were not normally distributed. Thus, bacterial and fungal concentrations were described by median and interquartile range. In addition, to better depict the size distribution, geometric median diameter was derived. All statistical calculations, including univariate and multivariate analyses (which included the Pearson correlation coefficient, nonparametric Mann–Whitney U, and Wilcoxon matched pairs tests), were performed using the statistical program for social science (SPSS) version 25.0. The degree of correlation between variables was estimated using Chi square statistics and binary regression. The Mann–Whitney U test was employed to ascertain if bioaerosols’ concentrations varied across seasons and sampling location. The Wilcoxon test compared the size fractions of bioaerosols over different seasons (when classrooms were unoccupied and occupied).
The unadjusted and adjusted odds ratios and 95% confidence intervals were calculated to estimate the likelihood of having rhinitis ever, current rhinitis, wheeze ever, and current wheeze given the presence of a potential risk factor. Step by step, confounding or other independent variables were introduced, beginning with the most significant from the univariate analysis.
2.12 Ethical approval
The University of Ibadan and the University College Hospital Ethical Board (UI/UCH) Ethics Committee approved the study (Approval number: UI/EC/16/0045). The Oyo State Ministry of Education and the State Ministry of Health granted permission to conduct the research. The Boards and Management of the selected schools, as well as the Parents’ and Teachers’ Association of the schools, also approved the study. Each pupil was given a consent form to obtain informed parental consent. Informed assent was also sought from each pupil before inclusion in the study.
3 Results
3.1 Bacteria and fungi count in indoor classroom environment
The median TFC in wet season (70.0 CFU/m3) was higher than the counts in the dry season (48.33 CFU/m3). Likewise, the TBC in wet season (706.33 CFU/m3) was higher than that of dry season (419.17 CFU/m3) (p < 0.001). However, the TFC (in wet season) and TBC (in wet and dry seasons) exceeded the WHO guideline limit of ≤50 CFU/m3 for TFC and ≤500 CFU/m3 for TBC in an indoor environment.
3.2 Total bacterial and fungal counts across sampling locations
Figure 2 shows the distribution of the median TFC across sampling locations. The median TBC were 527.0 CFU/m3, 467.0 CFU/m3, and 526.0 CFU/m3 in the outdoor, empty classrooms and occupied classrooms, respectively. There was a significant difference between empty and occupied classrooms, and between empty classrooms and outdoor (p < 0.05).
Figure 2. Total bacteria counts across sampling locations. Whisker box plots with non-similar alphabets are significantly different from each other (p < 0.05).
The median TFC in outdoor, empty classrooms and occupied classrooms were 54.0 CFU/m3, 53.0 CFU/m3, and 57.0 CFU/m3, respectively (Figure 3). The 25 and 75% percentiles of TFC were 40.0 and 68.0 CFU/m3 for outdoor, 41.0 and 73.0 CFU/m3 for empty classrooms and 43.0 and 75.0 CFU/m3 for occupied classrooms. There was a significant difference between TFC in empty and occupied classrooms (p < 0.05), and also between occupied classrooms and outdoor (p < 0.05).
Figure 3. Total fungal counts across sampling locations. Whisker box plots with non-similar alphabets are significantly different from each other (p < 0.05).
3.3 TFC and TBC across sampling locations during wet and dry seasons
In Figures 4a–d, the median TFC in outdoor, empty and occupied classrooms (60.0, 67.0, 73.0 CFU/m3) during the wet season were higher than the TFC in outdoor, empty and occupied classrooms (50.0, 48.0, 48.0 CFU/m3) during the dry season, respectively. In the wet season, the median concentration of TFC was highest when classrooms were occupied by pupils while it was highest in the outdoor environment during the dry season. There was a significant difference in the levels of TFC in the outdoor environment and empty classrooms, and empty and occupied classrooms during wet season.
Figure 4. (a–d) TFC and TBC across sampling locations during wet and dry seasons. Whisker box plots with non-similar alphabets are significantly different from each other (p < 0.05).
Also, the median TBC in outdoor, empty and occupied classrooms (997.0, 589.0, 811.0 CFU/m3) were highest in the wet season than the median TBC in outdoor, empty and occupied classrooms (393.0, 424.0, 423.0.0 CFU/m3) in the dry season, respectively (Figures 4a–d). The median TBC was highest in the outdoor environment in the wet season while the highest mean TBC was recorded in occupied classrooms in the dry season. The median TBC across all sampling locations in the wet season exceeded the WHO recommended guideline of ≤500 CFU/m3 for an indoor environment. There was a significant difference in the levels of TBC in the outdoor environment and empty classrooms, and empty and occupied classrooms during the wet season. No statistical difference was observed in the levels of TFC and TBC between the sample locations during the dry season.
3.4 TFC, TBC and sampling time in sampled schools
The TFC in the morning hours (54.00 CFU/m3) was not statistically different from the TFC in the afternoon hours (54.67 CFU/m3). Higher TBC was recorded in the afternoon hours (510.00 CFU/m3) than in the morning hours (489.67 CFU/m3) (p = 0.009). The observed TFC in the morning and afternoon exceeded the WHO guideline limit of ≤50 CFU/m3 for an indoor environment, while the TBC in the afternoon hours exceeded the standard limit of ≤500 CFU/m3 in an indoor environment.
3.5 Size distribution of bacteria and fungi
In the wet season, the dominant median bacterial fraction (21.7%) was recorded on the fourth stage (2.1–3.3 μm), and the least (11.6%) on the sixth (0.65–1.1 μm) stage. During the dry season, airborne bacteria aerosols presented maximum concentration (20.3%) on the second stage (4.7–7.0 μm) stage and the minimum (12.2%) on the fifth (1.1–2.1 μm). Statistically, there was a significant difference in airborne bacteria was observed among all the stages in dry and wet seasons (p < 0.001).
The highest proportion of fungi in the wet season was recorded in the size range 2.1–3.3 μm and 0.65–1.1 μm (stages four and six) with fraction of 18.5%, respectively. The least proportion was found in the size range 1.1–2.1 μm (stage 5) with a fraction of 13.9%. In contrast, in the dry season, the highest (17.6%) and lowest (15.6%) fungi concentrations were found at the size fractions 1.1–2.1 μm and 2.1–3.3 μm, respectively. A significant statistical difference in fungi levels was observed among all the stages in dry and wet seasons (p < 0.001).
3.6 Fungal and bacterial respirable fractions during wet and dry seasons
The respirable airborne bacterial and fungal counts (sum of the third stage to the sixth stage) in the wet and dry seasons are summarized in Table 2. The fungal respirable fraction (FRF) and the bacterial respirable fraction (BRF) in the wet season (283.00 and 2,890.00 CFU/m3) were higher than the FRF and BRF in the dry season (196.00 and 1,661.00 CFU/m3), respectively.
Table 2. Fungal and bacterial respirable fractions during wet and dry seasons.
3.7 Fungal and bacterial respirable fractions and sample location
Table 3 illustrates the median concentration of FRF and BRF across sampling locations. The median FRF was 217.00, 214.00 and 230.00 CFU/m3 in the outdoor, empty classrooms and occupied classrooms, respectively. Moreover, the median BFR was 3,164.00 CFU/m3, 3,232.23 CFU/m3, and 3,906.92 CFU/m3 in the outdoor, empty classrooms and occupied classrooms, respectively. Higher proportion of FRF and BRF was recorded in occupied classrooms.
Table 3. Fungal and bacterial respirable fractions and sample locations.
3.8 Estimation of dose rates
The estimated inhaled doses of bacteria and fungi in wet and dry seasons are presented in Table 4. In the wet seasons, children and adults inhaled larger dosages of bacterial and fungal spores than in the dry seasons. Furthermore, children inhaled higher levels of bacterial and fungal aerosols in the air than adults. The ADD of children in the wet and dry seasons (6.67 × 102 and 3.10 × 102 CFU/Kg/day) were two times higher than that of adults (3.48 × 102 and 1.61 × 102 CFU/Kg/day).
Table 4. Dose rates (CFU/Kg/day) of total bacteria and fungi aerosols in occupied classrooms.
3.9 Pupil socio-demographic characteristics and prevalence of respiratory symptoms
The pupils’ average age was 10.23 + 1.31 years. More than half (53.6%) of the pupils were females and in class six (67.0%). Also, more than half (55.2%) of the pupils have mothers whose highest educational level was secondary school, ditto for father’s education (54.5%) and mother’s occupation (57.9%) (Table 5).
Table 5. Socio-demographic characteristics of pupils.
The overall prevalence of rhinitis ever, current rhinitis, wheeze ever and current wheeze were 41.9, 40.4, 47.4 and 35.9%, respectively Pupils who were males and ≤10 years experienced higher prevalence of rhinitis ever (57.4 and 54.6%), current rhinitis (51.5 and 50.9%) and current wheeze (43.4 and 43.4%), respectively. More than half, of pupils with rhinitis ever (55.2%) and wheeze ever (54.3%) have fathers who are self-employed. Pupils whose mothers were farmers recorded higher prevalence of rhinitis ever (70.0%), current rhinitis (66.7%), wheeze ever (63.3%) and current wheeze (63.3%). The overall prevalence of rhinitis ever, current rhinitis, wheeze ever and current wheeze were 41.9, 40.4, 47.4 and 35.9%, respectively (Table 6).
Table 6. Relationship between socio-demographic characteristics and reported respiratory morbidities among pupils.
3.10 Unadjusted and adjusted odds ratio of FRF and BRF and other factors influencing rhinitis ever
The relationship between indoor FRF, BRF and rhinitis ever is presented in Table 7. At the unadjusted level of analysis, the odds of rhinitis ever were significantly higher among children whose classroom’s FRF was ≥50 (OR = 3.06, CI: 2.01–4.67, p < 0.001) and whose classroom’s BRF (OR = 3.12, CI: 0.06–4.73, p < 0.001) were higher than ≥500.
Table 7. Unadjusted and adjusted odds ratio of FRF and BRF and covariates of rhinitis ever.
At the adjusted level of analysis, FRF and BRF were significantly associated with rhinitis ever even when other covariates were controlled for. For instance, the odds of having rhinitis ever were 2.12 (CI: 1.30–3.47, p = 0.003) and 2.20 (CI: 1.35–3.59, p = 0.002) higher among pupils who occupied classrooms with greater than the median score for FRF and BRF, respectively. The identified predictors of rhinitis ever are; being a male child (aOR = 1.51, CI: 1.03–2.20, p = 0.034) and living a house cooking with unclean fuel (aOR = 1.15, CI: 0.77–1.73, p = 0.498).
Tables 8–10 summarizes the results of the unadjusted and adjusted logistic regression for current rhinitis, wheeze ever and current wheeze, respectively. At the unadjusted level of analysis, exposure to high FRF (≥50 cfu/m3) at school was significantly associated with increased likelihood of having current rhinitis (OR = 2.73, CI: 1.81–4.13, p < 0.001), wheeze ever (OR = 1.74, CI: 0.16–2.61, p < 0.001) and current wheeze (OR = 2.88, CI: 1.81–4.59, p < 0.001). Moreover, exposure to high BFR increased the likelihood of having current rhinitis (OR = 2.69, CI: 1.80–4.04, p < 0.001), wheeze ever (OR = 2.32, CI: 1.54–3.51, p < 0.001) and current wheeze (OR = 6.99, CI: 3.84–12.72, p < 0.001).
Table 8. Unadjusted and adjusted odds ratio of FRF, BRF and covariates of current rhinitis.
Table 9. Unadjusted and adjusted odds ratio of FRF, BRF and covariates of wheeze ever.
Table 10. Unadjusted and adjusted odds ratio of respirable fungal and bacterial counts and other factors influencing current wheeze.
At the adjusted level of analysis, FRF and BRF were significantly associated with current rhinitis (aOR = 1.83, CI: 1.14–2.93, p < 0.001, aOR = 1.78, CI: 1.11–2.85, p < 0.001), wheeze ever (aOR = 1.38, CI: 0.87–2.19, p = 0.166, OR = 1.93, CI: 1.21–3.08, p = 0.006) and current wheeze (aOR = 1.88, CI: 1.18–3.00, p = 0.008, aOR = 2.77, CI: 1.73–4.43, p < 0.001), respectively when covariates were adjusted for.
4 Discussion
4.1 Levels of TBC and TFC in indoor classroom environment
In this study, the median TFC and TBC in wet season was significantly higher than the TFC and TBC in dry season. The TFC (in wet season) and TBC (in wet and dry seasons) exceeded the WHO guideline limit. Pupils who spend long hours within these settings may be unduly exposed to the burden of bioaerosols present in such environment across different seasons. The high burden of bioaerosols recorded in wet season may account for the high prevalence of respiratory outcomes that usually characterize this season (24).
4.2 TBC and TFC in empty and occupied classrooms
This study shows that the TBC and TFC in occupied classrooms were higher than the TBC and TFC in empty classrooms. The difference in observed concentrations between occupied and unoccupied classrooms was probably caused by variations in room use patterns, student density, and children’s activity. Children’s activity, conversation, and material interaction during school hours might resuspend settled particles and increase the amount of bioaerosols’ shedding from surfaces, clothing, and skin. Studies have reported that the presence of humans in an indoor environment are the major sources of bioaerosols in built environment (25). Humans harbor 1012 microbes on their skin, 1014 microbes in their respiratory tract (26), have an emission rate of ~30 mg per person hour, corresponding to 3.7 × 107 and 7.3 × 106 bacterial and fungal genome copies and sheds 107 bacteria per person in an hour (27). Bioaerosols are released from humans into the indoor air during respiration, shedding of the cells of the skin, sweating, and repeated movement resulting in particle resuspension (27).
4.3 Size distribution of bacteria and fungi
Findings from this study show variations in the distribution of bacteria and fungi counts across the six-stages of the impactor during the wet and dry seasons. The dominant bacteria fraction in the wet season was recorded at the aerodynamic size fractions of 2.1–3.3 μm (stage 4) while the dominant fungi fraction was recorded in the size range 2.1–3.3 μm and 0.65–1.1 μm (stages four and six). In the dry season, there was variation in the distribution of bioaerosols with the maximum fractions being of the aerodynamic diameter 4.7–7.0 μm and 1.1–3.3 μm, respectively.
Different microorganisms have varying aerodynamic sizes ranging from about 0.02–100 μm (23). The aerodynamic diameter (AD) determines their survival, period of aerosolisation in the air and site of deposition within the human respiratory system and the corresponding health impact in human (28, 29). Bacterial cells occur as single cells or small aggregates, typically falling within smaller particle size ranges (respirable fractions). In contrast, fungal spores vary widely in size depending on species—some (e.g., Aspergillus, Penicillium) produce smaller spores that are captured in lower stages, while others (e.g., Alternaria, Cladosporium) produce larger spores more likely to be collected at upper stages.
Moreover, this current study shows that a statistically significant difference exists between the bacteria fractions recorded across all the stages in dry and wet seasons (p < 0.001). This was also true for the fungal fractions. These findings were consistent with that of Li et al. (30), who also reported seasonal and regional variations in the size distribution of bioaerosols. Seasonal environmental factors are important in determining how bacteria and fungus proliferate, sporulate, and aerosolize. Higher temperatures and humidity during the rainy season foster microbial growth and active sporulation on interior surfaces, increasing the number of larger and more viable spores in the atmosphere. This usually leads to a more widespread dispersion of bioaerosols throughout the different impactor stages, including the upper stages that absorb bigger particles (30). Nonetheless, some studies have reported no significant difference among the size distributions of bacteria and fungi under different weather conditions (11, 30).
Furthermore, the findings from this study show that the respirable bacterial fractions and the fungi fractions in the wet season were higher than those in the dry season. This translates to about 67.5% of the total bacterial and 77.8% of the fungal aerosols being of the respirable size fractions (aerodynamic diameter of 1.1–4.7 μm), which corresponds to the region between the human bronchus and the alveolar duct (lower respiratory tract) (31). The presence of these bioaerosols in the human bronchus and the alveolar duct are of great concern because of the absence of cilia in these airways. These bioaerosols can be resident within the lungs for longer periods except if they are degraded or removed with the help of pulmonary macrophages (32).
Within the human bronchus and the alveolar duct, bioaerosols can cause allergic alveolitis and other adverse health outcomes (33). Bioaerosols deposited in the upper airways can trigger some allergic or inflammatory response (e.g., rhinitis) and may induce lung diseases in susceptible populations (32). For instance, some bioaerosols including Aspergillus spp., Bacillus spp., and Mycobacterium spp. are capable of causing pulmonary infection if they penetrate deeper into the smaller air ways (32). With more than 60% of the TBC and TFC in this study being of the respirable size fraction, the indoor air quality in the sampled schools may pose a significant threat to the health of the pupils.
The concentrations of respirable bioaerosols are greatly influenced by meteorological factors including temperature, humidity, and rainfall; in the research area, there are noticeable seasonal differences between the wet and dry seasons. The development and sporulation of bacteria and fungus on interior surfaces and in the surrounding environment are facilitated by high humidity and increased surface moisture during the rainy season, which may result in larger concentrations of airborne microbial particles. On the other hand, during the dry season, especially in areas with inadequate ventilation or high human activity, decreased humidity and higher dust levels may promote the resuspension of deposited spores and particulate matter into the indoor air.
4.4 Average daily absorbed dose of bioaerosols
The findings from this study show that children breathe in higher doses of bioaerosols in wet and dry seasons (667 and 310 CFU/Kg/day) than adults in wet and dry seasons (348 and 161 CFU/Kg/day). The absorbed dose in children were up to two times higher than in adults. This position has been reported in similar studies (13, 34). Bragoszewska et al. (23), reported that bacterial inhaled dose in children ranged between 545.8 and 929.9 CFU/Kg/day, and ranged between 272.6 and 331.9 CFU/Kg/day in adults. The inhalation rates of children differ significantly from that of adults because of their physiology, size and activity level. Children have weaker defenses against air pollutants than adults, have a lower ability to metabolize and detoxify environmental agents, and have a more porous airway epithelium to inhaled air pollutants (35). They possess a greater oxygen intake rate per unit body weight than adults due to their rapidly growing rate and the large surface area of their lungs. This implies that the volume of air passing through the lungs of a child is twice that of adults.
Although the cross-sectional design makes it difficult to assess causality, the correlation between greater absorbed doses and respiratory symptoms is consistent with other research that shows indoor bioaerosol exposure is associated with poor respiratory outcomes, particularly in children. In line with other research showing a dose–response relationship, our results lend biological credence to the fact that microbial exposure contributes to respiratory morbidity.
4.5 Socio-demographic characteristics and respiratory symptoms
The overall prevalence of rhinitis ever, current rhinitis, wheeze ever and current wheeze in this study were 41.9, 40.4, 47.4, and 35.9%, respectively. According to a report from different centers across the globe that took part in the ISAAC Phase III study, the global average for present wheeze in 13–14 year old children is 14% (36). Differences in prevailing weather conditions, geographical locations, indoor air quality, size distribution and concentration of bioaerosols may explain the marked differences in the prevalence of respiratory symptoms across countries.
Individual personal characteristics such as age and gender play a significant role in the occurrence of respiratory disorders (37). Findings from this study show that pupils who were males and ≤10 years experienced higher prevalence of rhinitis ever, current rhinitis, wheeze ever and current wheeze. The United Nations had reported that the natural environment in developing countries favors female survival (38). The reason being that male infants possess some biological characteristics that make them less likely to live than female infants. The influence of the x-linked immunoregulatory genes, which provides females better resistance to infection, is one of these characteristics (39, 40). According to Waldron et al. (39), there is a danger of lung immaturity in males as a result of testosterone’s action on the lungs, which predisposes them to respiratory distress syndrome. There is also a difference in surfactant synthesis, the size of the airway, and airway resistance between male and female children (41). This makes male children to be more vulnerable to childhood respiratory illnesses due to these sex differences.
Higher prevalence of respiratory symptoms among pupils whose mothers were farmers was documented in this study. Since different occupations involve varied levels of environmental exposure, occupational activities are expected to affect indoor levels of bacterial and fungal spores in the respirable fraction. People who work in agriculture, for instance, are exposed to organic dust, dirt, decomposing vegetation, and animal waste—all of which are known to contain significant concentrations of microbial spores. In settings where work and home spaces frequently overlap, these bioaerosols may enter the home through contaminated clothing and tools.
Evidence presented in literature suggests that prenatal air pollution exposure is linked to the occurrence of respiratory and immune symptoms in their children, which can lead to respiratory morbidity and allergic reactions later in life (42). Rural school-aged children living on and off farms in Canada were found to have a link between farming activities and respiratory health in related studies (43). In children and adults, these exposures have been related to asthma, rhinitis, chronic bronchitis and decreased forced expiratory volume (FEV1) (44). However, instances of reduction in the incidence of allergic respiratory morbidities among farmers’ children have been reported (45, 46).
4.6 Predictors of respiratory allergic symptoms in school pupils
Furthermore, the findings from this study show that at the adjusted level of analysis, fungi and bacteria within the respirable size fractions were significantly associated with rhinitis ever, current rhinitis, wheeze ever and current wheeze. This clearly shows that the aforementioned risk factors are predictors of the observed respiratory symptoms.
The size fractions of fungal and bacterial species determine their deposition site within the human respiratory tract. The size distribution of indoor airborne bioaerosols and the accompanying deposition site within the lungs or airways establish the association between exposure to these bioaerosols and probable health effects (9). For instance, fungal spores such as Penicillium brevicompactum, Aspergillus fumigatus, Cladosporium macrocarpum, and Aspergillus niger, with a diameter of less than 10 μm, can penetrate into the bronchi and trigger allergic responses of the lower respiratory tract (32, 47).
5 Study limitations
A significant drawback of this research is that wheeze and rhinitis were analyzed independently using the ISAAC questionnaire framework, which made it impossible to evaluate their co-occurrence or synergistic effects. The study only used validated but self-reported symptom data, which made it harder to support causal inference. Additionally, the lack of inflammatory biomarkers hindered understanding of underlying immunopathological pathways. However, given the limited data on indoor air quality and respiratory health in school settings within our context, this research contributes to filling a critical knowledge gap and lays the foundation for future longitudinal or intervention-based studies that can further clarify causality and mechanisms.
6 Conclusion
This study provides key information about the spatial and temporal trends of indoor bioaerosol exposure in educational settings and how they can relate to respiratory symptoms in pupils. We were able to characterize bioaerosol size distribution, concentrations and types that can affect respiratory health outcomes by gathering data across seasons and analyzing bioaerosols size distributions.
The levels of bacterial and fungal spores of respirable fractions observed varied greatly in terms of season and occupancy with higher concentrations recorded in occupied classrooms and during the wet season. These levels exceeded the recommended guideline limits which implies a higher adverse health risk for pupils.
Moreover, variations in the distribution in the levels of bacteria and fungi across the six-stages of the impactor during the wet and dry seasons was reported in this study. A greater proportion of the bacterial and fungal aerosols were of the respirable size fractions which corresponds to the region between the human bronchus and the alveolar duct (lower respiratory tract). The presence of these bioaerosols in the human bronchus and the alveolar duct are of great concern because of the absence of cilia in these airways.
In addition, children have higher tendency to inhaled higher bacterial and fungal aerosols than adults. The absorbed dose in children were up to two times higher than in adults. These shows that school environment is an important location for children’s exposure to biological and chemical contaminants, given their high level of vulnerability. The highly absorbed dose of bioaerosols among the pupils may explain the increased prevalence of respiratory outcomes documented in this study.
Moreover, the study integrated health data based on symptoms using the validated ISAAC questionnaire, which enabled us to investigate correlations between exposure indicators and reported respiratory symptoms. Although causal inference is limited by the study’s cross-sectional design, the discovered connections provide significant epidemiological evidence of possible risk links in an understudied, real-world population.
Improvement in indoor sanitary conditions and hygiene practices are key to dipping the levels of indoor bioaerosols fractions and consequently, reduction in the prevalence of associated respiratory morbidities. While dry sweeping should be avoided, wet cleaning techniques and regular surface disinfection help reduce the resuspension of settled particles. Encouraging handwashing and respiratory etiquette, as well as providing access to clean water, soap, and hand sanitizers, is still a low-cost but efficient way to promote hygiene.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors without undue reservation.
Ethics statement
The studies involving humans were approved by University College Hospital Ethical Board (UI/UCH) Ethics Committee. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.
Author contributions
OM: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. GA: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing.
Funding
The author(s) declare that no financial support was received for the research and/or publication of this article.
Acknowledgments
The authors are grateful to CARTA and the head of the schools selected for this study for their support and cooperation. We also thank all the pupils who participated in this research and their parents. The authors appreciate Dr. Adekunle G. Fakunle for his support with data analysis and Dr. Adedayo O. Faneye for her support with the identification of the bioaerosols.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The authors declare that no Gen AI was used in the creation of this manuscript.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1. World Health Organization. WHO guidelines for indoor air quality: selected pollutants. World Health Organization. Regional Office for Europe. Copenhagen, Denmark (2010), pp. 1–454.
2. Slezakova, K, Texeira, C, Morais, S, and Pereira, MDC. Children’s indoor exposures to (ultra) fine particles in an urban area: comparison between school and home environments. J Toxicol Environ Health A. (2015) 78:886–96. doi: 10.1080/15287394.2015.1051203
3. Chatzidiakou, L, Mumovic, D, and Summerfield, AJ. What do we know about indoor air quality in school classrooms? A critical review of the literature. Intell Build Int. (2012) 4:228–59. doi: 10.1080/17508975.2012.725530
4. Madureira, J, Paciência, I, Rufo, J, Ramos, E, Barros, H, Teixeira, JP, et al. Indoor air quality in schools and its relationship with children's respiratory symptoms. Atmos Environ. (2015) 118:145–56. doi: 10.1016/j.atmosenv.2015.07.028
5. Madureira, J, Aguiar, L, Pereira, C, Mendes, A, Querido, MM, Neves, P, et al. Indoor exposure to bioaerosol particles: levels and implications for inhalation dose rates in schoolchildren. Air Qual Atmos Health. (2018) 11:955–64. doi: 10.1007/s11869-018-0599-8
6. Barberán, A, Dunn, RR, Reich, BJ, Pacifici, K, Laber, EB, Menninger, HL, et al. The ecology of microscopic life in household dust. Proc Biol Sci. (2015) 282:20151139. doi: 10.1098/rspb.2015.1139
7. Boreson, J, Dillner, AM, and Peccia, J. Correlating bioaerosol load with PM2.5 and PM10cf concentrations: a comparison between natural desert and urban-fringe aerosols. Atmos Environ. (2004) 38:6029–41. doi: 10.1016/j.atmosenv.2004.06.040
8. Bowers, RM, McCubbin, IB, Hallar, AG, and Fierer, N. Seasonal variability in airborne bacterial communities at a high-elevation site. Atmos Environ. (2012) 50:41–9. doi: 10.1016/j.atmosenv.2012.01.005
9. Yamamoto, N, Bibby, K, Qian, J, Hospodsky, D, Rismani-Yazdi, H, Nazaroff, WW, et al. Particle-size distributions and seasonal diversity of allergenic and pathogenic fungi in outdoor air. ISME J. (2012) 6:1801–11. doi: 10.1038/ismej.2012.30
10. Haas, D, Galler, H, Luxner, J, Zarfel, G, Buzina, W, Friedl, H, et al. The concentrations of culturable microorganisms in relation to particulate matter in urban air. Atmos Environ. (2013) 65:215–22. doi: 10.1016/j.atmosenv.2012.10.031
11. Gao, M, Qiu, T, Jia, R, Han, M, Song, Y, and Wang, X. Concentration and size distribution of viable bioaerosols during non-haze and haze days in Beijing. Environ Sci Pollut Res. (2015) 22:4359–68. doi: 10.1007/s11356-014-3675-0
12. Dannemiller, KC, Gent, JF, Leaderer, BP, and Peccia, J. Influence of housing characteristics on bacterial and fungal communities in homes of asthmatic children. Indoor Air. (2016) 26:179–92. doi: 10.1111/ina.12205
13. Madureira, J, Paciência, I, Rufo, JC, Pereira, C, Teixeira, JP, and de Oliveira, FE. Assessment and determinants of airborne bacterial and fungal concentrations in different indoor environments: homes, child day-care centres, primary schools and elderly care centres. Atmos Environ. (2015) 109:139–46. doi: 10.1016/j.atmosenv.2015.03.026
14. Sohn, JR, Moon, HJ, Ryu, SH, and Hwang, T. Indoor air quality in school classrooms with mechanical ventilation systems. In Proceedings of the 7th international symposium on sustainable healthy buildings, Seoul, Korea (2012) 349.
15. Falola, T. The political economy of a pre-colonial state: Ibadan, 1830–1900. Ile-Ife: University of Ile-Ife Press (1984).
16. World Population Review. Ibadan population 2025. (2024). Available online at: https://worldpopulationreview.com/cities/nigeria/ibadan (Accessed March 31, 2025).
17. Li, Y, Fu, H, Wang, W, Liu, J, Meng, Q, and Wang, W. Characteristics of bacterial and fungal aerosols during the autumn haze days in Xi'an, China. Atmos Environ. (2015) 122:439–47. doi: 10.1016/j.atmosenv.2015.09.070
18. Fang, Z, Ouyang, Z, Hu, L, Wang, X, Zheng, H, and Lin, X. Culturable airborne fungi in outdoor environments in Beijing, China. Sci Total Environ. (2005) 350:47–58. doi: 10.1016/j.scitotenv.2005.01.032
19. Fang, Z, Ouyang, Z, Zheng, H, and Wang, X. Concentration and size distribution of culturable airborne microorganisms in outdoor environments in Beijing, China. Aerosol Sci Technol. (2008) 42:325–34. doi: 10.1080/02786820802068657
20. Tortora, GJ, Funke, BR, and Case, CL. Microbiology -an introduction (3rd ed.). Redwood City: The Benjamin/Cummings Publishing Company, Inc. (1989) 82-83: 215–216.
21. Jensen, PA, and Schafer, MP. Sampling and characterization of bioaerosols. NIOSH Man Anal Methods. (1998) 1:82–112.
22. Andersen, AA. New sampler for the collection, sizing, and enumeration of viable airborne particles. J Bacteriol. (1958) 76:471–84. doi: 10.1128/jb.76.5.471-484.1958
23. Brągoszewska, E, Mainka, A, and Pastuszka, JS. Bacterial and fungal aerosols in rural nursery schools in southern Poland. Atmos. (2016) 7:142. doi: 10.3390/atmos7110142
24. Torresin, S, Pernigotto, G, Cappelletti, F, and Gasparella, A. Combined effects of environmental factors on human perception and objective performance: a review of experimental laboratory works. Indoor Air. (2018) 28:525–38. doi: 10.1111/ina.12457
25. Adams, RI, Miletto, M, Taylor, JW, and Bruns, TD. Dispersal in microbes: fungi in indoor air are dominated by outdoor air and show dispersal limitation at short distances. ISME J. (2013) 7:1262–73. doi: 10.1038/ismej.2013.28
26. Prussin, AJ, and Marr, LC. Sources of airborne microorganisms in the built environment. Microbiome. (2015) 3:1–10. doi: 10.1186/s40168-015-0144-z
27. Hospodsky, D, Yamamoto, N, Nazaroff, WW, Miller, D, Gorthala, S, and Peccia, J. Characterizing airborne fungal and bacterial concentrations and emission rates in six occupied children's classrooms. Indoor Air. (2015) 25:641–52. doi: 10.1111/ina.12172
28. Sadyś, M, Kennedy, R, and West, JS. Potential impact of climate change on fungal distributions: analysis of 2 years of contrasting weather in the UK. Aerobiologia. (2016) 32:127–37. doi: 10.1007/s10453-015-9402-6
29. Dybwad, M, Skogan, G, and Blatny, JM. Temporal variability of the bioaerosol background at a subway station: concentration level, size distribution, and diversity of airborne bacteria. Appl Environ Microbiol. (2014) 80:257–70. doi: 10.1128/AEM.02849-13
30. Li, Y, Lu, R, Li, W, Xie, Z, and Song, Y. Concentrations and size distributions of viable bioaerosols under various weather conditions in a typical semi-arid city of Northwest China. J Aerosol Sci. (2017) 106:83–92. doi: 10.1016/j.jaerosci.2017.01.007
31. Oh, HJ, Nam, IS, Yun, H, Kim, J, Yang, J, and Sohn, JR. Characterization of indoor air quality and efficiency of air purifier in childcare centers, Korea. Build Environ. (2014) 82:203–14. doi: 10.1016/j.buildenv.2014.08.019
32. Lindsley, WG, Green, BJ, Blachere, FM, Martin, SB, Law, BF, Jensen, PA, et al. Sampling and characterization of bioaerosols. NIOSH Manual Anal Methods. 5th edition (2017):1–115.
33. Ahmed, JA, Katz, MA, Auko, E, Njenga, MK, Weinberg, M, Kapella, BK, et al. Epidemiology of respiratory viral infections in two long-term refugee camps in Kenya, 2007-2010. BMC Infect Dis. (2012) 12:1–8. doi: 10.1186/1471-2334-12-7
34. Brągoszewska, E, Mainka, A, Pastuszka, JS, Lizończyk, K, and Desta, YG. Assessment of bacterial aerosol in a preschool, primary school and high school in Poland. Atmos. (2018) 9:87. doi: 10.3390/atmos9030087
35. Schwartz, J. Air pollution and children’s health. Pediatrics. (2004) 113:1037–43. doi: 10.1542/peds.113.S3.1037
36. Wichmann, J, Wolvaardt, JE, Maritz, C, and Voyi, KV. Household conditions, eczema symptoms and rhinitis symptoms: relationship with wheeze and severe wheeze in children living in the Polokwane area, South Africa. Matern Child Health J. (2009) 13:107–18. doi: 10.1007/s10995-007-0309-x
37. Mentese, S, Mirici, NA, Otkun, MT, Bakar, C, Palaz, E, Tasdibi, D, et al. Association between respiratory health and indoor air pollution exposure in Canakkale, Turkey. Build Environ. (2015) 93:72–83. doi: 10.1016/j.buildenv.2015.01.023
38. United States Environmental Protection Agency. Exposure factors handbook: 2011 edition. National Center for Environmental Assessment, Washington, DC; EPA/600/R-09/052F. (2011). National Technical Information Service, Springfield, VA. Available online at: http://www.epa.gov/ncea/efh
39. Waldron, I. Sex differences in human mortality: the role of genetic factors. Soc Sci Med. (1983) 17:321–33. doi: 10.1016/0277-9536(83)90234-4
40. Ruggieri, A, Anticoli, S, D’Ambrosio, A, Giordani, L, and Viora, M. The influence of sex and gender on immunity, infection and vaccination. Ann Ist Super Sanita. (2016) 52:198–204. doi: 10.4415/ANN_16_02_11
41. Ishak, N, Sozo, F, Harding, R, and De Matteo, R. Does lung development differ in male and female fetuses? Exp Lung Res. (2014) 40:30–9. doi: 10.3109/01902148.2013.858197
42. Vieira, SE. The health burden of pollution: the impact of prenatal exposure to air pollutants. Int J Chron Obstruct Pulmon Dis. (2015) 10:1111–21. doi: 10.2147/COPD.S40214
43. Farthing, P, Rennie, D, Pahwa, P, Janzen, B, and Dosman, J. The association between farming activities and respiratory health in rural school age children. J Agromedicine. (2009) 14:256–62. doi: 10.1080/10599240902799798
44. Sigsgaard, T, Basinas, I, Doekes, G, de Blay, F, Folletti, I, Heederik, D, et al. Respiratory diseases and allergy in farmers working with livestock: a EAACI position paper. Clin Transl Allergy. (2020) 10:29–30. doi: 10.1186/s13601-020-00334-x
45. Elholm, G, Schlünssen, V, Doekes, G, Basinas, I, Bibby, BM, Hjort, C, et al. Become a farmer and avoid new allergic sensitization: adult farming exposures protect against new-onset atopic sensitization. J Allergy Clin Immunol. (2013) 132:1239. doi: 10.1016/j.jaci.2013.07.003
46. Gern, JE. Promising candidates for allergy prevention. J Allergy Clin Immunol. (2015) 136:23–8. doi: 10.1016/j.jaci.2015.05.017
Keywords: indoor air quality, microbial aerosols, aerosol size distribution, public primary school, Ibadan
Citation: Morakinyo OM and Ana GREE (2025) Seasonal levels and size fractions of indoor air bioaerosols as predictors of respiratory morbidities among school pupils in Ibadan, Nigeria. Front. Public Health. 13:1611167. doi: 10.3389/fpubh.2025.1611167
Edited by:
Xinming Wang, Chinese Academy of Sciences (CAS), ChinaReviewed by:
Roberto Alonso González-Lezcano, CEU San Pablo University, SpainRen Shuang Cao, China Academy of Chinese Medical Sciences, China
Copyright © 2025 Morakinyo and Ana. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Oyewale Mayowa Morakinyo, b21vcmFraW55b0BjYXJ0YWZyaWNhLm9yZw==