Indoor air pollutants and respiratory symptoms among residents of an informal urban settlement in Uganda: A cross-sectional study

Solomon T Wafula; Aisha Nalugya; Hilbert Mendoza; Winnifred K Kansiime; Tonny Ssekamatte; Abel W Walekhwa; Richard K Mugambe; Florian Walter; John C Ssempebwa; David Musoke

doi:10.1371/journal.pone.0290170

. 2023 Aug 17;18(8):e0290170. doi: 10.1371/journal.pone.0290170

Indoor air pollutants and respiratory symptoms among residents of an informal urban settlement in Uganda: A cross-sectional study

Solomon T Wafula ^1,^2,^*, Aisha Nalugya ¹, Hilbert Mendoza ³, Winnifred K Kansiime ¹, Tonny Ssekamatte ¹, Abel W Walekhwa ¹, Richard K Mugambe ¹, Florian Walter ⁴, John C Ssempebwa ¹, David Musoke ¹

Editor: Francesco Barone-Adesi⁵

PMCID: PMC10434877 PMID: 37590259

Abstract

Background

Indoor air pollutants (IAP) and household conditions such as dampness, crowding and chemical exposures have been associated with acute and chronic respiratory infections. In Uganda, literature on the effects of IAP on respiratory outcomes in informal settlements is limited.

Methods

We describe the baseline household characteristics of 284 adults and their children in an informal settlement in Uganda from April to May 2022. We monitored same-day indoor concentrations of particulate matter PM_2.5, PM₁₀, Carbon monoxide (CO), relative humidity %, and temperature from 9 am to 2 pm and interviewed caregivers/mothers about their respiratory symptoms and those of their children in the previous 30 days. We employed robust Poisson regressions to evaluate the associations between indoor air indicators and respiratory health symptoms.

Results

Approximately 94.7% of households primarily used biomass fuels and 32.7% cooked from inside their dwelling rooms. The median PM_2.5, PM₁₀ and CO levels were 49.5 (Interquartile range (IQR) = 31.1,86.2) μg/m³, 73.6 (IQR = 47.3,130.5) μg/m³ and 7.70 (IQR = 4.1,12.5) ppm respectively. Among adults, a 10 unit increase in PM_2.5 was associated with cough (Prevalence Ratio (PR) = 3.75, 95%CI 1.15–1.55). Dwelling unit dampness was associated with phlegm (PR = 2.53, 95%CI = 1.39–4.61) and shortness of breath (PR = 1.78, 95% CI 1.23–2.54) while cooking from outside the house was protective against shortness of breath (PR = 0.62, 95% CI = 0.44–0.87). In children, dampness was associated with phlegm (PR = 13.87, 95% CI 3.16–60.91) and cough (PR = 1.62, 95% CI 1.12–2.34) while indoor residual spraying was associated with phlegm (PR = 3.36, 95%CI 1.71–6.61).

Conclusion

Poor indoor air conditions were associated with respiratory symptoms in adults and children. Efforts to address indoor air pollution should be made to protect adults and children from adverse health effects.

Introduction

Indoor air pollution (IAP) is a major environmental and public health challenge in low–and middle-income countries (LMICs), including Uganda [1]. Approximately two million people die prematurely per year from illnesses attributable to IAP from solid fuels such as charcoal and firewood. IAP can be caused by using solid fuels for cooking, lighting candles or oil lamps, fuel-burning space heaters, smoking, and indoor residual insecticide spraying. In LMICs, inefficient and inadequately vented cooking spaces and heating with biomass and coal on simple stoves are critical [2, 3]. Burning these fuels in inefficient stoves produces high levels of health-damaging air pollutants such as particulate matter (PM), carbon monoxide (CO) and a variety of volatile organic compounds (VOCs) [4].

The quantities emitted and relative composition of different emissions are determined by various factors, including the type of fuel, humidity, dampness, stove type and the way the stove and fuel are used by the cook [5]. There is growing evidence that poor IAP and poor housing conditions can lead to various respiratory health problems, such as coughing, wheezing, shortness of breath, chest tightness, irritation of the eyes, nose, and throat, and asthma which can have a significant impact on individuals’ quality of life [6–8]. Additionally, long-term health effects such as pneumonia, chronic obstructive pulmonary disease, heart disease, and lung cancer have also been documented to be associated with exposure to IAP [9]. Evidence suggests that women and children have a higher risk of adverse health effects than men due to prolonged exposure to biomass smoke during food preparation at home and spending much time indoors [10].

There are evident socioeconomic disparities in biomass fuel use, with economically poor households more likely to use unimproved fuels [11, 12]. Indeed, in Uganda, most urban poor live in informal settings such as slums. Informal settings are overcrowded, poorly ventilated spaces and structures are not constructed following existing building codes [13]. Inadequate housing conditions in Ugandan informal settings can negatively affect indoor air quality and hence partly account for disparities in the burden of ARIs [7]. Slum dwellers largely use biomass fuels and tend to cook indoors; conditions that result in elevated levels of air pollutants such as PM, CO, and other VOCs [14]. Our previous study set in an urban informal setting showed 24hr mean PM_2.5 concentrations of 69.62 μg/m³ which are more than four times higher than 15 μg/m³, the World Health Organization (WHO) recommendations.

Studies in high-income countries have reported significant associations between respiratory infections and indoor sources of air pollutants, materials or activities, e.g., recent painting, VOCs, gas appliances, biomass fuel use and exposure to household smoking [15, 16]. However, limited studies especially in sub-Saharan Africa (SSA) have objectively measured concentrations of IAPs which would enable a more robust assessment of the associations with respiratory effects if equipment are calibrated and validated [17]. Instead, the studies in SSA depend on self-reports to assess exposures related to IAP [18], which is subject to inherent biases [19]. Although relying on sources of IAP may be a good proxy of exposure, objectively measured quantitative exposure assessments can be more helpful in assessing the health effects of exposure.

We aimed to investigate the association between selected indoor air pollutants, cooking fuels and objectively measured concentrations of air pollutants and respiratory symptoms among children and adults in an informal urban setting in Uganda. While there is a growing body of evidence that IAP is associated with respiratory health problems, there is a need for further research to better understand the relationship between indoor air quality and respiratory health using various non-specific respiratory symptoms. The use of non-specific respiratory symptoms can provide a more comprehensive understanding of the broader impact of indoor air quality on respiratory health. This is particularly important given the negative impact poor indoor air quality can have on an individual’s quality of life.

Methods

Study setting

This study was conducted in Bwaise slum, an informal settlement in Kawempe Division, Kampala, Uganda (Fig 1). This informal settlement is one of Kampala’s most densely populated slums, distinguished by largely informal and substandard housing and small-scale businesses. It has a large population density, congested households with low socioeconomic status and high dependence on solid fuels [20]. Therefore, we expected higher pollution levels in such a slum than in other outdoor settings.

Study design, area and population

This community-based cross-sectional survey used questionnaires and an observational checklist to collect data on self-reported respiratory symptoms, including coughing, wheezing, and phlegm, shortness of breath among mothers/caregivers (aged 18 years and above) and children (aged 0 to 5 years) in Bwaise 1, Bwaise II and Bwaise III slums of Kawempe Division, Kampala City Council Authority (KCCA), Uganda. Approximately 60% of the urban residents in Kampala city reside in informal areas [13]. The neighborhoods of Bwaise I, Bwaise II, and Bwaise III have an average population of approximately 37,500, 42,000, and 35,000 people, respectively [21]. These areas are characterized by cramped living conditions, with an average household size ranging from 5 to 10 individuals. Typically, these households occupy small dwellings consisting of just one or two rooms [22]. Information on household and individual risk factors was collected from participants from April to May 2022.

The eligible study population consisted of adults (18 years and above) from households who had resided in the area for at least three months, not incapacitated, and would provide informed consent. Those who had severe mental illnesses or declined consent were excluded. Participants provided information on the demographics and respiratory health within the previous 30 days of all children (0–59 months) under their care/household.

Sample size and sampling procedure

Using the Kish Leslie formulae for cross-sectional studies [23], we intended to sample 278 households using a prevalence of self-reported health effects (respiratory symptoms) of 19.4% from a previous study in Uganda, considering a 5% level of significance, 80% power and non-response rate of 15%.

As regards sampling, Bwaise slum was selected purposively because of poor housing and living conditions and over-reliance on solid/biomass fuels. Within each of the three Bwaise parishes, one zone was chosen randomly using the ballot method, and approximately 93 households were selected in each zone using systematic sampling. The sampling interval for each zone was obtained by dividing the number of households (according to records from the zonal local council office) by the number of households needed (i.e., divided by 93). In each zone, we started sampling at the zonal local council office, north direction, and clockwise until we obtained the sample. The following household replaced a selected household if the original household had no eligible respondents or did not consent. In each selected household, one adult or another person generally involved in the cooking responded to the questionnaire. We obtained information from adults on respiratory symptoms among all children under five years in their selected household.

Data collection and measurements

We developed data collection tools and captured relevant covariates following a thorough review of the existing literature [24–27]. Six experienced and trained data collectors with background training in Environmental Health Science administered the tools to eligible participants and captured responses on Kobo Collect, a mobile data collection app [28].

■ Respiratory health: The study’s primary outcomes were self-reported respiratory symptoms among adults and children (reported by parents/guardians) within the last 30 days. These symptoms included cough, phlegm, wheezing, shortness of breath and blocked/running nose and these were responses to the multiple-choice question “Have you had the following symptoms in the last 30 days on at least three days?”. For children, the question was adapted to read “Has ‘(name of the child)’ had the following symptoms in the past 30 days for at least 3 days?” and the responses were yes (coded 1) or no (coded 0)
■ Indoor air conditions: Information was collected on parameters such as indoor dampness, presence of indoor plants (yes or no), and indoor residual spraying (yes or no, and on resident behaviours including smoking (yes or no), biomass fuel use (yes or no), carpet use (yes or no), and cooking place location (indoor kitchen vs outdoors). We defined dampness as evidence of signs of mould growth, moisture stains and peeling walls in indoor spaces [29]. We also asked participants about their use of indoor residual spraying (IRS) since it is one of the vector control methods for malaria given its endemicity in Uganda. This was self-reported. We measured indoor particulate matter of 2.5 microns (PM_2.5), particulate matter of 10 microns (PM₁₀), carbon monoxide (CO), humidity (RH)%, and temperature (°Con the same day ten times at each household over the course of five hours (twice per hour from 9 am to 2 pm) to reduce variability than a single measurement. For each of the ten sampling events, the three-minute average concentrations (mean of three readings per event) of PM_2.5, PM₁₀, CO, humidity, and temperature were measured in the centre of the living room. All meters were placed on the table/platform one meter above the ground. Due to reduced airflow near surfaces, the monitors’ air receivers and inlets were placed at least 1.5 m away from the windows and doors [30]. Three low-cost particle sensors (Temptop M2000c 2^nd edition) were used to measure particulate matter. Temtop M2000c 2^nd sensor utilizes an optical particle counter and its detectors have a laser particle sensor and an operating temperature range of 0–50°C, a relative humidity range of 0–90%, an atmospheric pressure of one atm, and a PM_2.5 measurement range of 0–999 ug/m3 with a resolution of 0.1 ug/m3. Temptop monitors were factory calibrated, and therefore further laboratory calibration was not required for the duration of the study. CO levels were also measured using three AS8700A CO meter, which has a detection range of 0~1000 ppm and with accuracy (± 5% or ± 10 ppm). The temperature was expressed in degrees Celsius (°C), and humidity was shown as a percentage.
■ Covariates: We collected data covariates and potential confounding variables including socio-demographic characteristics such as gender (male or female), age in complete years (adults) and in months (children), marital status (single, married, separated), occupation (employed, unemployed, others), monthly household income and length of residence (in years). The length of the stay was categorized into three: (i) less than or equal to 5 years, (ii) 6 to 10 years, and (iii) more than 10 years. Household income in Uganda shillings to US Dollars (I USD = 3500 UGX) and categorized as follows: (i) less than 50 USD, (ii) between 50 to 150 USD, and (iii) greater than 150 USD. We used the median national monthly household income of around 50 USD as the cut-off for the first category, while the second category upper limit was based on the median monthly income of approximately 150 USD for the capital, Kampala) [13]. Tools were pretested among 20 mothers/caregivers in the Katanga slum, Kampala, which has similar characteristics to Bwaise. Details on the definitions of covariates and simple directed acyclic graph (DAG) is provided in S1 Text.

Statistical analysis

We used the median and interquartile range (IQR) to describe continuous variables, and frequencies and percentages to describe categorical variables. For the associations between indoor air conditions and selected respiratory symptoms among caregivers/mothers and children, we performed separate multivariable modified Poisson regressions [31], producing prevalence ratios (PRs) and corresponding 95% confidence interval (95%CI) adjusting for age, gender, smoking status. The outcomes-: respiratory symptoms cough, phlegm, wheezing, and shortness of breath. For this model, we included two latent variables, each calculated as one-tenth of the logarithmically transformed average concentrations of the original PM2.5 and PM10 values, respectively. To account for potential confounding factors, we included additional covariates in the multivariable model, along with the well-established confounders such as age, gender, and smoking. These additional covariates were selected based on a priori knowledge and guided by the Directed Acyclic Graph (DAG) to ensure comprehensive adjustment for potential confounding effects. The data were analyzed using the statistical software Stata 14.0 version. All statistical tests were two-tailed, and statistical significance was assumed when a p value was < = 0.05.

Ethical consideration

We obtained the study’s ethical approval from Makerere University School of Public Health Research and Ethics Committee (Ref No. SPH-2021-99) and the Uganda National Council of Science and Technology (UNCST: Ref No. SS996ES). Administrative clearance was sought from Kampala City Council Authority (KCCA), which presides over the study area. Information sheets and consent forms were available in the local language (Luganda) or English with details on the purpose of the project, procedures to be followed and the risks and benefits of participation. We obtained written informed consent from each participant (adults). We assured participants of the confidentiality and anonymity of their information. We advised participants in households with higher particulate matter levels to adopt appropriate exposure mitigation strategies, and we advised those with chronic respiratory infections to seek medical attention.

Results

Background characteristics of the participants

Out of the 284 adult participants who took part in the study, the majority (85.2%) were females and 51.4% of the participants were below the age of 30 years m. The median age (IQR) was 29 years. Nearly half, 47.9%, were married or living with a partner, 51.1% had attained a post-primary level of education, and 68.6% were employed. More than half, 57.4%, had a monthly household income between 50–150 US dollars, and 52.1% had stayed in their current area of residence for less than five years. About 14.4% (41) adults had smoked in the previous 30 days. Of the 284 households, 187 had at least a child below the age of 5. The median age of the children was 24.0 months (IQR = 4,48). Of these, 52.6% were females, and 72.2% were not in school. Information was also obtained on 230 children under 5 (52.6% Female; 72.2% were not yet in school) (Table 1).

Table 1. Background characteristics of adult household participants.

Characteristics	Number of participants,	Percentage
Characteristics	N = 284	(%)
Gender: Female	242	85.2
Age of respondents (in years)
< 30	146	51.4
30–45	108	38.0
> 45	30	10.6
Marital status
Married or living with a partner	136	47.9
Separated	43	15.1
Single	105	37.0
Education level
No formal education	25	8.8
Primary	114	40.1
Post-primary	145	51.1
Occupation
Employed	195	68.6
Unemployed	72	25.4
Other	17	6.0
Owner of the dwelling	26	9.2
Household monthly income (USD)
< 50	77	27.1
50–150	163	57.4
> 150	44	15.5
Duration of stay in the area of residence (years)
< 5	148	52.1
5–10	57	20.1
> 10	79	27.8
Current smoker
No	243	85.6
Yes	41	14.4

Open in a new tab

Cooking fuels, indoor conditions and air pollutant levels

Of 284 households, 269 (94.7%) used biomass fuels (wood and charcoal). The median PM_2.5, PM₁₀ and CO levels were 49.5 (IQR = 31.1,86.2) μg/m³, 73.6 (IQR = 47.3,130.5) μg/m³ and 7.70 (4.1,12.5) ppm respectively. Dampness was found in 123 (43.3%) of the households (Table 2).

Table 2. Cooking fuels, indoor conditions and air pollutant levels.

Indoor air parameters	Number, N = 284	Summary statistic
Meteorological parameters (Median (IQR))
Humidity	272	70.2 (66.9, 73.2)
Temperature	272	28.2 (27.2, 29.1)
Air quality parameters (Median (IQR))
PM _2.5 (μg/m³)	272	49.5 (31.1–86.2)
PM₁₀ (μg/m³)	272	73.6 (47.3,130.5)
Carbon monoxide (ppm)	272	7.70 (4.1,12.5)
Main fuel type
Biomass	269	94.7%
Non-biomass	15	5.3%
Cooking from outside	194	68.3%
Rearing pets	25	8.8%
Carpets in living room	127	44.7%
Home dampness (mould)	123	43.3%

Open in a new tab

Note: For fuel type, cooking from outside, rearing pets, carpets in living room and dampness (mould); the summary statistic is percentages otherwise median and interquartile range

Respiratory symptoms among adults and children

Of the 284 adults, 66.2% reported coughing, 41.9% reported a running nose, 33.5% reported shortness of breath, 17.6% reported phlegm and 14.8% reported wheezing. Most respondents (84.6%) reported having at least one of these respiratory symptoms in the previous 30 days. A total of 230 children were included in this study, of which 80.0% had morning cough, 44.8% had a running nose, 34.4% reported day or night cough, 26.5% had shortness of breath, 20.0% had wheezing, and 13.5% had phlegm during the previous 30 days. The distribution of respiratory outcomes among participants is presented in S1 and S2 Tables for adults and children, respectively.

Associations between indoor air conditions and respiratory problems among adults

At multivariable analysis, the respondents with dampness in their dwelling units reported a higher prevalence of phlegm (PR = 2.53, 95%CI = 1.39–4.61) and shortness of breath (PR = 1.78, 95% CI = 1.23–2.54). Similarly, respondents whose cooking place was located outside their living house reported a 38% lower risk of shortness of breath (PR = 0.62, 95% CI = 0.44–0.87) and 15% lower risk of cough (PR = 0.85, 95% CI = 0.71–0.99) than those whose cooking place was inside the living rooms. A 10 unit increase in PM_2.5 levels was associated with increased risk of cough (PR = 3.75, 95%CI = 1.15–12.10) among adults. Use of indoor residual sprays was associated with shortness of breath (PR = 1.44, 95%CI = 1.02–2.03) while pet rearing was associated with cough (PR = 1.31, 95% CI = 1.11–1.55) (Table 3).

Table 3. Adjusted models for association between indoor air quality parameters and respiratory problems among adult residents.

Attributes	Cough	Phlegm	Wheezing	Blocked /Runny nose	Shortness of breath
Attributes	PR (95% CI)	PR (95% CI)	PR (95% CI)	PR (95% CI)	PR (95% CI)
Demographic characteristics
Gender: Male	1.12 (0.89–1.40)	1.26 (0.64–2.47)	0.15 (0.02–1.15)	0.92 (0.56–1.52)	0.84 (0.53–1.32)
Age (in complete years)
< 30	1	1	1	1
30–45	1.02 (0.86–1.20)	0.94 (0.52–1.68)	1.44 (0.80–2.59)	0.95 (0.71–1.28)	0.94 (0.67–1.33)
45 +	0.75 (0.53–1.06)	0.88 (0.40–1.92)	0.89 (0.26–3.01)	0.42 (0.21–0.85)	0.78 (0.43–1.43)
Education level
Non-formal	1	1	1	1	1
Primary	0.93 (0.71–1.20)	1.87 (0.58–6.01)	0.54 (0.23–1.27)	0.89 (0.47–1.67)	1.29 (0.66–2.52)
Post-primary	0.95 (0.74–1.23)	1.27 (0.38–4.12)	0.47 (0.20–1.12)	1.08 (0.59–1.98)	1.09 (0.55–2.18)
Occupation
Employed (including business)	1	1	1	1	1
Unemployed	0.86 (0.69–1.07)	0.77 (0.38–1.54)	0.67 (0.29–1.54)	1.09 (0.78–1.52)	0.81 (0.54–1.21)
Other	0.79 (0.53–1.18)	0.59 (0.18–1.89)	1.40 (0.49–4.01)	1.93 (1.22–3.04)	0.28 (0.08–0.90)
Housing characteristics
HH Income
< 50	1	1	1	1	1
50–150	1.08 (0.88–1.33)	1.63 (0.82–3.21)	1.58 (0.69–3.63)	0.93 (0.65–1.32)	1.09 (0.73–1.63)
>150	1.08 (0.82–1.43)	0.73 (0.22–2.39)	1.29 (0.43–3.83)	1.56 (1.05–2.33)	0.95 (0.52–1.72)
Cooking outside living house	0.85 (0.71–0.99)	0.88 (0.49–1.55)	0.77 (0.42–1.39)	1.10 (0.82–1.49)	0.62 (0.44–0.87)
PM _2.5¹	3.75 (1.15–12.10)	1.21 (0.04–39.89)		1.14 (0.14–9.62)	2.27 (0.20–26.31)
Carbon monoxide	1.00 (0.99–1.01)	1.01 (0.98–1.02)	0.94 (0.91–1.07)	1.00 (0.99–1.01)	0.98 (0.97–1.00)
Main fuel: Biomass	1.75 (0.94–3.25)	1.83 (0.26–12.76)	1.24 (0.20–7.84)	0.94 (0.55–1.62)	0.94 (0.44–1.98)
Rearing pets	1.31 (1.11–1.55)	1.11 (0.53–2.30)	1.51 (0.69–3.31)	0.81 (0.47–1.39)	1.20 (0.72–2.03)
Carpets in the living room	0.92 (0.77–1.10)	0.91 (0.54–1.54)	0.59 (0.30–1.15)	0.93 (0.70–1.23)	0.88 (0.62–1.23)
Home dampness	0.99 (0.84–1.18)	2.53 (1.39–4.61)	1.46 (0.81–2.62)	0.89 (0.65–1.22)	1.78 (1.23–2.54)
Smoker	1.12 (0.93–1.35)	1.52 (0.79–2.93)	0.96 (0.38–2.40)	0.97 (0.62–1.52)	0.87 (0.54–1.41)
Indoor spraying for insecticides	1.15 (0.98–1.36)	1.21 (0.70–2.09)	1.09 (0.59–2.00)	0.95 (0.69–1.31)	1.44 (1.02–2.03)

Open in a new tab

Note: ¹ PM2.5; 1/10 of log transformed PM2.5 average values; All models adjusted for age, gender, income, and education and smoking

Associations between indoor air conditions and respiratory problems among parent-reported respiratory problems among children

At the multivariable level, the prevalence of phlegm among children in households that did indoor spraying of insecticides (PR = 3.36, 95% CI = 1.71–6.61) was 3.4 times higher compared to that among households that did not. Dampness was associated with Increased risk of phlegm (PR = 13.87, 95% CI 3.16–60.91) and day/night cough (PR = 1.62, 95% CI 1.12–2.34). Smoking by the parent/ guardian was associated with an increased risk of running nose while pet rearing was associated with wheezing (PR = 1.74, 95% CI 1.03–3.23) (Table 4).

Table 4. Associations between indoor air quality conditions and respiratory problems among children (adjusted analysis).

Attributes	Morning Cough	Day or night cough	Phlegm	Wheezing	Blocked / Runny nose	Shortness of breath
Demographic characteristics
Gender: Male	1.06 (0.93–1.20)	0.66 (0.46–0.95)	0.98 (0.52–1.83)	0.88 (0.52–1.49)	0.81 (0.61–1.07)	0.85 (0.55–1.33)
Age (in complete years)
< = 2	1	1	1	1	1	1
2+	1.06 (0.92–1.22)	1.32 (0.89–1.97)	1.05 (0.56–1.95)	1.36 (0.77–2.41)	1.32 (0.97–1.78)	1.11 (0.70–1.75)
Child Education
Not in school	1	1	1	1	1	1
School	1.00 (0.86–1.15)	1.02 (0.69–1.52)	0.86 (0.43–1.72)	0.60 (0.29–1.23)	0.89 (0.64–1.24)	0.71 (0.39–1.28)
Housing conditions
Cooking place: Outside	1.05 (0.90–1.23)	1.25 (0.84–1.85)	0.69 (0.38–1.25)	0.63 (0.36–1.10)	0.82 (0.61–1.10)	0.80 (0.51–1.24)
PM_2.5¹	1.23 (0.47–3.23)	0.45 (0.03–6.36)	6.06 (0.08–457.4)	1.98 (0.04–110.98)	0.22 (0.02–2.47)	0.88 (0.63–1.22)
Carbon monoxide	1.00 (0.99–1.00)	0.99 (0.97–1.01)	1.02 (1.00–1.04)	0.98 (0.95–1.01)	0.99 (0.98–1.01)	1.01 (0.99–1.02)
Main fuel: Biomass	0.88 (0.67–1.14)	1.46 (0.47–4.56)		1.56 (0.23–10.33)	1.18 (0.52–2.70)	1.15 (0.33–4.02)
Rearing pets	0.89 (0.70–1.14)	1.29 (0.78–2.12)	1.08 (0.50–2.32)	1.74 (1.03–3.23)	0.56 (0.32–1.00)	0.96 (0.47–1.97)
Carpets in the living room	1.06 (0.93–1.21)	1.31 (0.90–1.92)	1.08 (0.59–1.98)	1.13 (0.66–1.93)	0.90 (0.67–1.20)	1.15 (0.742–1.84)
Home dampness	1.09 (0.96–1.25)	1.62 (1.12–2.34)	13.87 (3.16–60.9)	1.53 (0.88–2.68)	1.26(0.95–1.67)	1.32 (0.83–2.11)
Parent / guardian smokes	0.94 (0.75–1.17)	0.65 (0.37–1.12)	0.60 (0.25–1.46)	0.95 (0.48–1.89)	1.46 (1.06–2.00)	0.87 (0.44–1.72)
Indoor spraying for insecticides	1.00 (0.48–1.16)	0.65 (0.44–1.00)	3.36 (1.71–6.61)	1.14 (0.67–1.46)	0.50 (0.33–1.17)	0.83 (0.52–1.34)

Open in a new tab

Note: ¹ PM2.5; 1/10 of log transformed PM2.5 average values; All models adjusted for child’s age, gender, education and regular smoking by household member.

Discussion

Understanding the impact of indoor air pollution on respiratory health is critical because many people spend nearly two-thirds of their time at home [14]. This is one of the first studies to investigate the association between indoor air quality conditions and respiratory symptoms among adults and children in informal settlements in Uganda. Higher than normal ranges of indoor PM_2.5 and PM₁₀ levels were observed in most study households. Among adults, increases in PM_2.5 was associated with cough and wheezing. Dwelling unit dampness was associated with phlegm and shortness of breath while outside cooking was protective against cough and shortness of breath. In children, dampness was associated with phlegm and cough, pet rearing was associated with wheezing while indoor residual spraying was associated with phlegm.

We found median PM_2.5 and PM₁₀ levels of 49.6 μg/m³ and 73.6 μg/m³. Limited studies have measured indoor PM_2.5 and PM₁₀ concentrations in Uganda although Kansiime et al. [32] reported mean indoor PM_2.5 concentrations of 124.29 μg/m³ in Fort Portal city based on single-time measurements. The high levels particulate matter levels highlights may imply increase in risk to human health including respiratory problems, cardiovascular diseases, and reduced life expectancy. Most households relied on biomass fuels which due to inefficient burning emit higher levels of pollutants, including particulate matter and CO [33]. We therefore suggest a need for interventions that promote clean fuels such as gas and electricity. The effect of fuel type on respiratory health could not be robustly determined since nearly all households used biomass fuels.

This study revealed a high prevalence (84.6%) of self-reported acute respiratory symptoms (at least one symptom) in adults, which included wheezing, cough and phlegm in the last 30 days before the survey. Likewise, 80% of children had morning cough, 44.8% reported a runny nose, 34.4% reported day or night cough, and 26.5% reported shortness of breath at least three times during the preceding 30 days. Although self-reported, the high prevalence of respiratory symptoms highlights the significant burden among residents and requires efforts to reduce associated risk factors. The prevalence of respiratory symptoms in our study population was much higher than the 20% prevalence which was assumed in the sample size calculation [34]. The high prevalence of respiratory symptoms in the study population may be attributed to the high levels of IAP in the study area and the widespread use of solid fuels for cooking. Moreover, our study was conducted in an informal settlement in Kampala, where indoor air quality conditions are significantly poorer than in upscale settings. In contrast, the study by siddharthan [34] was conducted in both rural and urban Uganda. This marked differences in setting could partly explain the high prevalence of respiratory symptoms in our study than the 20% assumed in the sample size calculation. The high prevalence underscores the urgent need for interventions to improve indoor air quality in slum settings.

Our study identified showed that elevated risk of cough with 10 unit increase in PM_2.5 levels in adults. Although this is among the first studies to document this association in Uganda, the finding is consistent with published evidence elsewhere in high-income countries [35–37]. Indoor PM concentration is related to inflammation and a decrease in lung function [38]; hence cough can be one of the manifestations of this effect. This underscores the need to reduce all activities that may encourage the deposition of particulate matter in indoor environments, such as minimizing biomass use and better ventilation. Whereas we did not assess outdoor air quality, studies elsewhere indicate that poor outdoor air quality could aggravate/increase the risk of respiratory symptoms [39, 40]. Further studies should also consider the role of outdoor pollution on respiratory morbidity.

We also found reduced risk of shortness of breath and coughing among adults in households whose cooking place was outside their living house than those who cooked from inside their living spaces. This could be attributed to the fact that outside cooking is protective as indoors cooking with the poor ventilation in the slums facilitates the pollutant accumulation from the cooking fuels, consequently impairing respiratory system. When cooking occurs outside the house or in an open area, the cooking smoke dissipates quickly, reducing exposure to individuals and lowering the risk of respiratory problems. Previous studies have documented a higher concentration of these air pollutants in households where indoor cooking takes place [41] However, it is important to note that our study did not find statistically significant differences in pollutant levels. Our findings reaffirm those reported in studies in Thailand and Ethiopia which indicated that cooking inside a home was predictive of higher risk of respiratory symptoms, such as dyspnea (shortness of breath) [42, 43]. Therefore, there is a need to increase the sensibilization of residents of slum settlements on the health risks associated with cooking indoors, especially when using unclean fuels such as firewood and charcoal.

Our findings indicate that owning pets in the household was associated with increased likelihood of cough among adults and wheezing among children. Allergens from domestic pets, such as cats, dogs, and birds, can trigger sensitivities in individuals who are predisposed to allergies and cause respiratory problems [44]. Therefore, individuals who are susceptible to these allergens are advised to either avoid rearing these pets in their homes or take necessary precautions to minimize exposure to allergens. Additionally, we observed an association between indoor insecticide spraying (IRS) and shortness of breath in adults and phlegm in children. Although IRS is a control measure for disease vectors, including mosquitoes and other vectors, it emits various indoor air pollutants, including hazardous air pollutants and VOCs, which can settle on surfaces, furniture and counters and can also be inhaled by occupants of the houses. Overuse or incorrect use leads to the build-up of residues that may contribute to respiratory health problems when inhaled. A direct relationship between respiratory symptoms in children and exposure to insecticides has been demonstrated elsewhere [45]. Our findings indicate a need to emphasize and promote non-chemical insect/pest control methods in informal settlements to reduce exposure to harmful chemical pollutants. Ensuring enough time is allowed between spraying and occupation of the sprayed room can also minimise the residual effect, lowering the risk of respiratory problems.

Dampness was found to be associated with symptoms such as phlegm and shortness of breath in adults, as well as cough and phlegm in children. Nearly half of the households were characterised by indoor dampness which is not surprising since Bwaise frequently floods and has poor drainage. Dampness creates an environment for mould spores to grow, which can trigger allergic reactions and respiratory problems. In addition, existing evidence indicates that dampness can encourage chemical or biological degradation of materials and thus increase the indoor concentration of pollutants which could increase the risk of respiratory problems [25]. Extant research in developed countries also indicates a high likelihood of phlegm among household occupants in damp and moist dwellings [46, 47]. Although there is limited evidence of the association between residential dampness and phlegm in adults, Simoni and colleagues, in a study conducted in Italy, previously reported that dampness increased the risk of phlegm in children [48].

Strengths and limitations

This is among Uganda’s first studies to explore the associations between indoor air conditions and respiratory health among adults and children. Nevertheless, our study had some limitations regarding the design and interpretation of findings. This was a cross-sectional study in which causality between exposure to indoor air pollution and respiratory outcomes cannot be confirmed since we cannot determine temporality. Our measurement of air quality parameters was limited to 5 hours of same-day measurement and not 24 hours. However, we captured the most active period when most households would at least do some cooking, and at least 10 measurements (3-minute averages each) were made at each household throughout the monitoring. There is a need to use prospective analytical study designs with longer duration of measurements to examine the hypotheses further and determine the predictors of respiratory problems among urban slum dwellers. In addition, the study was subject to recall bias and subjectivity as we relied on self-reports in assessing respiratory problems and other indoor air conditions. Few households were using cleaner fuels, making it difficult to study the impact on respiratory outcomes.

Conclusions

Our study supports evidence that poor indoor air conditions can adversely affect the respiratory health of adults and children in informal urban settings. Our findings emphasize the importance of identifying and developing interventions to reduce environmental triggers through simple home modifications and household education. We suggest that residents must limit time indoors and ensure sufficient ventilation. We also recommend additional prospective studies with longer-duration of pollutant measurements are necessary to characterize the dose-response relationships between the various home air pollutants and respiratory symptoms.

Supporting information

S1 Fig. Temperature and humidity changes.

(DOCX)

Click here for additional data file.^{(20.5KB, docx)}

S1 Table. Distribution of respiratory outcomes in adults.

(DOCX)

Click here for additional data file.^{(20.2KB, docx)}

S2 Table. Distribution of respiratory outcomes in children.

(DOCX)

Click here for additional data file.^{(18.2KB, docx)}

S1 Text. DAGs and univariable analysis.

(DOCX)

Click here for additional data file.^{(48.7KB, docx)}

S2 Text. PLOS questionnaire on inclusivity in global health.

(DOCX)

Click here for additional data file.^{(67.4KB, docx)}

S1 Data. Dataset for adults information.

(CSV)

Click here for additional data file.^{(210.2KB, csv)}

S2 Data. Dataset for children information.

(CSV)

Click here for additional data file.^{(99.9KB, csv)}

Acknowledgments

We appreciate the research assistants and the participants and the local authorities, without which this study would not have been possible.

Data Availability

All relevant data are available from within the manuscript as well as a supplemental information file.

Funding Statement

This work was supported by Makerere University School of Public Health under the Small Grants Programme (MakSPH-GRCB/18-19/01/02). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.WHO. Household air pollution and health. 2021. https://www.who.int/news-room/fact-sheets/detail/household-air-pollution-and-health. Accessed 20th July 2022.
2.Tanimowo MO. Air pollution and respiratory health in Africa: a review. East Afr Med J. 2000;77:71–5. [PubMed] [Google Scholar]
3.Orozco-Levi M, Garcia-Aymerich J, Villar J, Ramírez-Sarmiento A, Antó JM, Gea J. Wood smoke exposure and risk of chronic obstructive pulmonary disease. The European respiratory journal. 2006;27:542–6. doi: 10.1183/09031936.06.00052705 [DOI] [PubMed] [Google Scholar]
4.Bruce N, Perez-Padilla R, Albalak R. Indoor air pollution in developing countries: a major environmental and public health challenge. Bull World Health Organ. 2000;78:1078–92. [PMC free article] [PubMed] [Google Scholar]
5.WHO. Burden of disease from household air pollution for 2012. 2017 [Google Scholar]
6.Hasan M, Tasfina S, Haque SMR, Saif-Ur-Rahman KM, Khalequzzaman M, Bari W, et al. Association of biomass fuel smoke with respiratory symptoms among children under 5 years of age in urban areas: results from Bangladesh Urban Health Survey, 2013. Environ Health Prev Med. 2019;24:65. doi: 10.1186/s12199-019-0827-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Gan WQ, Sanderson WT, Browning SR, Mannino DM. Different types of housing and respiratory health outcomes. Preventive medicine reports. 2017;7:124–9. doi: 10.1016/j.pmedr.2017.05.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Regalado J, Pérez-Padilla R, Sansores R, Páramo Ramirez JI, Brauer M, Paré P, et al. The effect of biomass burning on respiratory symptoms and lung function in rural Mexican women. American journal of respiratory and critical care medicine. 2006;174:901–5. doi: 10.1164/rccm.200503-479OC [DOI] [PubMed] [Google Scholar]
9.Mortimer K, Gordon SB, Jindal SK, Accinelli RA, Balmes J, Martin WJ 2nd. Household air pollution is a major avoidable risk factor for cardiorespiratory disease. Chest. 2012;142:1308–15. doi: 10.1378/chest.12-1596 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Saha A, Rao NM, Kulkarni PK, Majumdar PK, Saiyed HN. Pulmonary function and fuel use: a population survey. Respiratory research. 2005;6:127. doi: 10.1186/1465-9921-6-127 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2224–60. doi: 10.1016/S0140-6736(12)61766-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Loomis D, Grosse Y, Lauby-Secretan B, El Ghissassi F, Bouvard V, Benbrahim-Tallaa L, et al. The carcinogenicity of outdoor air pollution. Lancet Oncol. 2013;14:1262–3. doi: 10.1016/s1470-2045(13)70487-x [DOI] [PubMed] [Google Scholar]
13.UBOS. Uganda National Household Survey 2019/2020. UBOS. 2021. https://www.ubos.org/wp-content/uploads/publications/09_2021Uganda-National-Survey-Report-2019-2020.pdf. [Google Scholar]
14.Nandasena YL, Wickremasinghe AR, Sathiakumar N. Air pollution and health in Sri Lanka: a review of epidemiologic studies. BMC Public Health. 2010;10:300. doi: 10.1186/1471-2458-10-300 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Viegi G, Simoni M, Scognamiglio A, Baldacci S, Pistelli F, Carrozzi L, et al. Indoor air pollution and airway disease. Int J Tuberc Lung Dis. 2004;8:1401–15. [PubMed] [Google Scholar]
16.Zhang J, Smith KR. Indoor air pollution: a global health concern. Br Med Bull. 2003;68:209–25. doi: 10.1093/bmb/ldg029 [DOI] [PubMed] [Google Scholar]
17.Emmelin A, Wall S. Indoor air pollution: a poverty-related cause of mortality among the children of the world. Chest. 2007;132:1615–23. doi: 10.1378/chest.07-1398 [DOI] [PubMed] [Google Scholar]
18.Kelly MS, Wirth KE, Madrigano J, Feemster KA, Cunningham CK, Arscott-Mills T, et al. The effect of exposure to wood smoke on outcomes of childhood pneumonia in Botswana. Int J Tuberc Lung Dis. 2015;19:349–55. doi: 10.5588/ijtld.14.0557 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Adaji EE, Ekezie W, Clifford M, Phalkey R. Understanding the effect of indoor air pollution on pneumonia in children under 5 in low-and middle-income countries: a systematic review of evidence. Environ Sci Pollut Res. 2019;26:3208–25. doi: 10.1007/s11356-018-3769-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Mguni P, van Vliet B, Spaargaren G, Nakirya D, Osuret J, Isunju JB, et al. What could go wrong with cooking? Exploring vulnerability at the water, energy and food Nexus in Kampala through a social practices lens. Glob Environ Change. 2020;63:102086. [Google Scholar]
21.KCCA. Kampala Profiles: Kawempe. 2023. https://askyourgov.ug/request/37/response/37/attach/2/Kawempe%20Municipality.pdf?cookie_passthrough=1. Accessed May 15, 2023.
22.Richmond A, Myers I, Namuli H. Urban Informality and Vulnerability: A Case Study in Kampala, Uganda. Urban Sci. 2018;2:22. [Google Scholar]
23.Kish L. Survey sampling. 1965. (04; HN29, K5.). [Google Scholar]
24.Jafta N, Barregard L, Jeena PM, Naidoo RN. Indoor air quality of low and middle income urban households in Durban, South Africa. Environ Res. 2017;156:47–56. doi: 10.1016/j.envres.2017.03.008 [DOI] [PubMed] [Google Scholar]
25.Heseltine E, Rosen J. WHO guidelines for indoor air quality: dampness and mould. 2009. https://apps.who.int/iris/handle/10665/164348. [PubMed] [Google Scholar]
26.Rumchev K, Zhao Y, Spickett J. Health risk assessment of indoor air quality, socioeconomic and house characteristics on respiratory health among women and children of Tirupur, South India. Int J Environ Res. 2017;14:429. doi: 10.3390/ijerph14040429 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Nadali A, Arfaeinia H, Asadgol Z, Fahiminia M. Indoor and outdoor concentration of PM10, PM2. 5 and PM1 in residential building and evaluation of negative air ions (NAIs) in indoor PM removal. Environ Pollut Bioavailab. 2020;32:47–55. [Google Scholar]
28.Lakshminarasimhappa M. Web-based and smart mobile app for data collection: Kobo Toolbox/Kobo collect. Journal of Indian Library Association. 2022;57:72–9. [Google Scholar]
29.Andriessen Brunekreef, Roemer. Home dampness and respiratory health status in European children. Clin Exp Allergy. 1998;28:1191–200. [DOI] [PubMed] [Google Scholar]
30.WHO. Methods for monitoring indoor air quality in schools: report of a meeting, Bonn, Germany, 4–5 April 2011. 2011. https://apps.who.int/iris/handle/10665/108596. Accessed 2 Apr 2022.
31.Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159:702–6. doi: 10.1093/aje/kwh090 [DOI] [PubMed] [Google Scholar]
32.Kansiime WK, Mugambe RK, Atusingwize E, Wafula ST, Nsereko V, Ssekamatte T, et al. Use of biomass fuels predicts indoor particulate matter and carbon monoxide concentrations; evidence from an informal urban settlement in Fort Portal city, Uganda. BMC Public Health. 2022;22:1723. doi: 10.1186/s12889-022-14015-w [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Jiang R, Bell ML. A comparison of particulate matter from biomass-burning rural and non-biomass-burning urban households in northeastern China. Environ Health Perspect. 2008;116:907–14. doi: 10.1289/ehp.10622 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Siddharthan T, Grigsby M, Morgan B, Kalyesubula R, Wise RA, Kirenga B, et al. Prevalence of chronic respiratory disease in urban and rural Uganda. Bulletin of the World Health Organization. 2019;97:318–27. doi: 10.2471/BLT.18.216523 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Simoni M, Annesi-Maesano I, Sigsgaard T, Norback D, Wieslander G, Nystad W, et al. School air quality related to dry cough, rhinitis and nasal patency in children. The European respiratory journal. 2010;35:742–9. doi: 10.1183/09031936.00016309 [DOI] [PubMed] [Google Scholar]
36.Annesi-Maesano I, Hulin M, Lavaud F, Raherison C, Kopferschmitt C, de Blay F, et al. Poor air quality in classrooms related to asthma and rhinitis in primary schoolchildren of the French 6 Cities Study. Thorax. 2012;67:682–8. doi: 10.1136/thoraxjnl-2011-200391 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Hamatui N, Beynon C. Particulate Matter and Respiratory Symptoms among Adults Living in Windhoek, Namibia: A Cross Sectional Descriptive Study. Int J Environ Res Public Health. 2017;14. [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Delfino RJ, Gong H Jr., Linn WS, Pellizzari ED, Hu Y. Asthma symptoms in Hispanic children and daily ambient exposures to toxic and criteria air pollutants. Environ Health Perspect. 2003;111:647–56. doi: 10.1289/ehp.5992 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Checkley W, Pollard SL, Siddharthan T, Babu GR, Thakur M, Miele CH, et al. Managing threats to respiratory health in urban slums. Lancet Respir. 2016;4:852–4. doi: 10.1016/S2213-2600(16)30245-4 [DOI] [PubMed] [Google Scholar]
40.Arora S, Rasania SK, Bachani D, Gandhi A, Chhabra SK. Air pollution and environmental risk factors for altered lung function among adult women of an urban slum area of Delhi: A prevalence study. Lung India: official organ of Indian Chest Society. 2018;35:193–8. doi: 10.4103/lungindia.lungindia_263_17 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Smith KR, Pillarisetti A. Household Air Pollution from Solid Cookfuels and Its Effects on Health. In: Mock CN, Nugent R, Kobusingye O, Smith KR, eds. 3rd edition. Washington (DC): The International Bank for Reconstruction and Development / The World Bank; 2017. Oct 27. Chapter 7. Injury Prev Environ Health. 2018 [PubMed] [Google Scholar]
42.Geremew A, Gebremedhin S, Mulugeta Y, Yadeta TA. Place of food cooking is associated with acute respiratory infection among under-five children in Ethiopia: multilevel analysis of 2005–2016 Ethiopian Demographic Health Survey data. Trop Med Health 2020;48:95. doi: 10.1186/s41182-020-00283-y [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Juntarawijit Y, Juntarawijit C. Cooking smoke exposure and respiratory symptoms among those responsible for household cooking: A study in Phitsanulok, Thailand. Heliyon. 2019;5:e01706. doi: 10.1016/j.heliyon.2019.e01706 [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Chew FT, Teo J, Quak SH, Connett GJ, Lee BW. Presence of domestic pets and respiratory symptoms in asthmatic children. Ann Acad Med Singap. 1997;26:294–8. [PubMed] [Google Scholar]
45.Buralli RJ, Dultra AF, Ribeiro H. Respiratory and Allergic Effects in Children Exposed to Pesticides-A Systematic Review. Int J Environ Res Public Health. 2020;17 doi: 10.3390/ijerph17082740 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Bornehag CG, Sundell J, Bonini S, Custovic A, Malmberg P, Skerfving S, et al. Dampness in buildings as a risk factor for health effects, EUROEXPO: a multidisciplinary review of the literature (1998–2000) on dampness and mite exposure in buildings and health effects. Indoor Air. 2004;14:243–57. doi: 10.1111/j.1600-0668.2004.00240.x [DOI] [PubMed] [Google Scholar]
47.Clark N, Ammann H, Brunekreef B, Eggleston P, Fisk W, Fullilove R, et al. Damp indoor spaces and health. Washington, DC: Institute of Medicine of the National Academies. 2004 [Google Scholar]
48.Simoni M, Lombardi E, Berti G, Rusconi F, La Grutta S, Piffer S, et al. Mould/dampness exposure at home is associated with respiratory disorders in Italian children and adolescents: the SIDRIA-2 Study. Occup Environ Med. 2005;62:616–22. doi: 10.1136/oem.2004.018291 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0290170.r001

Decision Letter 0

Francesco Barone-Adesi

23 Mar 2023

PONE-D-22-35748Indoor air pollutants and respiratory symptoms among residents of an informal urban setting in Uganda: a cross-sectional studyPLOS ONE

Dear Dr. Wafula,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Statistical analysis needs to be revised. In particular:

1) an analysis using exposure on the continuous scale should be performed, or a valid reason not to do it should be provided (Reviewer 2)

2) the multivariable analysis should be conducted on an a-priori set of confounders, not basing on data-driven strategies (Reviewer 2).

3) the use of p-value categorization should be avoided (Reviewer 2)

Some additional information needs to be provided. In particular:

1) Number of inhabitants in the different Bwaise districts (Reviewer 1/ Reviewer 2)

2) proportion of non-respondents (Reviewer 1)

Please also consider these additional comments from my side:

In table 2, the line about main fuel type is not clear. I assume that about 95% of household used biomass. Please correct the table accordingly.

According to the methods section, all children under five years in the selected households were included in the analysis. However, in the results section is reported that analysis was carried out on 230 children out of 284 households, less than one per household. Could you please double-check this number?

In the results section, you reported that prevalence of wheezing was 2.26 higher among single participants compared to married ones. However, this is the result of the univariable analysis, which is not adjusted for age, gender, smoking, etc. if you want to analyze this association (even if it is out of the main scope of the paper), you should report the adjusted results.

Apparently, the paragraph titled “Associations between indoor air conditions and respiratory problems among parent-reported respiratory problems among children” include only one sentence. It should be merged with the following one.

Minor issues

At line 234 you may want to say “the effect of fuel type” instead of “The predictive value of fuel type”

Line 246 “…and the finding is consistent” please cancel “and”

Line 247 for sake of clarity, you may want to say “Indoor PM concentration is related to inflammation and a decrease in lung function”

Line 264 please use sensibilization instead of sensitization

Line 287 please refer to “Simoni and colleagues”

Please submit your revised manuscript by May 07 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

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

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Francesco Barone-Adesi

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please note that the supplementary data file "SI Data. Dataset for children information" contains potentially identifying information (i.e. names of the children). These should be anonymised as this information may breach patient confidentiality and these specific case details should not be included.

3. You indicated that you had ethical approval for your study. In your Methods section, please ensure you have also stated whether you obtained consent from parents or guardians of the minors (participants under the age of 18 years) included in the study or whether the research ethics committee or IRB specifically waived the need for their consent.

4. We note that Figure 1 in your submission contain map images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

a. You may seek permission from the original copyright holder of Figure 1 to publish the content specifically under the CC BY 4.0 license.

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

b. If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

5. We note you have included a table to which you do not refer in the text of your manuscript. Please ensure that you refer to Table 3 in your text; if accepted, production will need this reference to link the reader to the Table.

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

**********

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

Reviewer #1: Yes

Reviewer #2: No

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This paper is one of the first aimed at providing some information on the effects of environmental pollution on the health of residents in Uganda. Some findings (eg the protective effect of outdoor cooking) are convincing and may have an impact on public health policies.

The authors honestly recognize the limitations of their study.

Thus, the manuscript deserves consideration. However, it cannot be published in the present form. Reasons for refusal and suggestions for improvement are given below:

• what was the population of Bwaise?

• Forty-two participants were male caregivers (Table 1): however, gender is not considered in the analyses.

• Active tobacco smoke as a risk factor for respiratory symptoms on its own merits is hardly considered. According to Table 1, in 41 of 284 households included in the survey (14.4%) there was a residing member who was an active smoker. Risks from environmental factors are estimated without any distinction between active and passive smokers.

• Similarly, data on active and passive tobacco smoke are unclear: lines 147-48, 151 and 171 describe respectively “smoking”, “household smoking” and “indoor smoking” as a confounder. Do these terms correspond each other? Do they include exposure to passive tobacco smoke?

• Some details are missed in the description of the conduct of the survey How many data collectors / interviewers? Which the number of persons refused to be interviewed or could to be interviewed for other reasonss?

• Throughout the text, I have not been able to find the absolute number of childlren which were included in the survey. I have only learnt that among the 284 households, 187 had at least a child.

• Tables 3-6 are too crowded (particularly tables 3 and 5) and difficult to read. Wouldn’t it be possible to produce a summary index for the 5 respiratory problems which are considered?

• Tables 3 and 5 report risk estimates based on “bivariate” (monovariate?) analyses whereas Tables 4 and 6 report results of multivariate analyses. Which criteria were used for selecting risk factors to be included in the latter tables?

Reviewer #2: The manuscript entitled “Indoor air pollutants and respiratory symptoms among residents of an informal urban setting in Uganda: a cross-sectional study” describes the relationship between Indoor Air Pollution and respiratory symptoms in a slum area of the Uganda. The major strength of the manuscript is that it provides useful empirical data collected in difficult settings. The major limitation is its cross-sectional nature, the small sample size, and some modelling strategy.

Introduction:

Overall, the introduction is too much focused on the relationship between Indoor Air Pollution (IAP) and Acute Respiratory Infection (ARI), while the aim of the study is to assess a more general the relationship between IAQ and respiratory health, using different set of non-specific respiratory symptoms.

Line 38 Page 1: I would expand the section briefly introducing also other respiratory health problems that might be linked to IAP as “irritation of the eyes, nose, and throat”, “lung development”, and “asthma”.

Page 2, Line 47: “Inadequate housing conditions in Ugandan informal settings can negatively affect IAQ and hence partly account for disparities in the burden of ARIs”. Please indicate a reference.

Methods:

Sampling strategy: Please provide the total number of inhabitants/households of the Bwaise slum. In addition, it should be provided the number of inhabitants/households for each district of Bwaise (Bwaise I, II, III).

Data collection and measurements: Please report that indoor residual spraying was self-reported (in the current version of the manuscript it is not clear)

Statistical analysis:

Even if authors collect quantitatively the IAP and state in the introduction that: “ relying on sources of IAP may be a good proxy of exposure, objectively measured quantitative exposure assessments can be more helpful in assessing the health effects of exposure”, they eventually dichotomise the exposure, without testing possible linear or non linear effect on a continuous scale of the exposure. I would suggest modelling the relationship on a continuous scale, as well as testing linearity and non-linearity of the relationship between exposure and outcome.

Bivariate modelling seems correct, however I do not agree with the multivariable modelling strategy. Authors adjust all models for age, gender and smoking recognizing them as a priori confounders.

However, for each exposure-outcome model they decided to include as additional covariate all variables having a p-value <0.20. If would suggest to not adapt this data-driven selection of confounder, especially in a small dataset as the one of this study. I will opt for a-priori selection of a set of confounders. For instance some analyses are not adjusted for Household income, even if I see it as a confounder in all exposure-outcome relationship. A re-run of analysis using a-priori selected confounders is essential for the manuscript to be considered for publication.

As an example let’s take Table 6, Phlegm outcome. Here estimate for Cooking from outside the living room is adjusted for PM2.5 concentration. PM2.5 concentration is not a confounder, but rather a mediator.

Results:

I discourage the use of the p-value categorizing in 0.05,0.005,0.001. In all results table is not clear why some estimates are presented in bold font, and others not. It does not seem to be due to the statistical significance, because asterisk and bold font do not correspond. Please remove asterisk, significance test, and report only point estimates and confidence intervals.

Discussion:

Page 15 Line 239: How authors motivate the high proportion of respiratory symptoms in the target population? In the sample size computation, they assumed a 20% prevalence of respiratory symptoms, while in the study population they found proportion >80%.

Page 16 Line 254: Authors state “This study found that the risk of shortness of breath was 44% lower among adults in households whose cooking place was outside their living house than those who cooked from inside their living spaces. […] Indeed, previous studies have reported a higher concentration of these pollutants in homes where cooking was done indoors (43).”

Authors can check this relationship using their own data, since they have collected information on both cooking location and indoor air pollutants.

**********

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

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

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

Reviewer #1: No

Reviewer #2: Yes: Giovenale Moirano

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2023 Aug 17;18(8):e0290170. doi: 10.1371/journal.pone.0290170.r002

Author response to Decision Letter 0

9 Jun 2023

Makerere University

School of Public Health

P.O Box 7072, Kampala

27th May 2023

The Editor,

PLOS ONE Journal.

Re: Submission of a revised review article for publication

We would like to express our gratitude to you for providing us with the opportunity to revise our manuscript titled “Indoor air pollutants and respiratory symptoms among residents of an informal urban settlement in Uganda: a cross-sectional study”. We are also thankful to the peer reviewers for their valuable insights, which have significantly enhanced the quality of our work.

In response to the reviewers' comments, we have made diligent efforts to address each point raised, striving to incorporate their suggestions and improve the manuscript accordingly. We are now pleased to submit the revised version of our manuscript for your consideration.

Sincerely,

Solomon Wafula

#General comments

Statistical analysis needs to be revised. In particular:

1) an analysis using exposure on the continuous scale should be performed, or a valid reason not to do it should be provided (Reviewer 2)

We have now performed re-analysis using exposure on the continuous scale where necessary in the revised manuscript. A detailed response is under specific comments.

2) the multivariable analysis should be conducted on an a-priori set of confounders, not basing on data-driven strategies (Reviewer 2).

Thank you for the suggestion. We have conducted the multivariable analysis on an a-priori set of confounders based on the DAG theory and we provide rationale for the choice of priori set of confounders in the methods.

3) the use of p-value categorization should be avoided (Reviewer 2)

Response: We have avoided the use of p-value categorization in the revised manuscript as per your suggestion.

Some additional information needs to be provided. In particular:

1) Number of inhabitants in the different Bwaise districts (Reviewer 1/ Reviewer 2)

We have provided the number of inhabitants in the different Bwaise zones…. on page 4

2) proportion of non-respondents (Reviewer 1)

Thank you for the suggestion but in this study, we did not have any non-response.

Please also consider these additional comments from my side:

In table 2, the line about main fuel type is not clear. I assume that about 95% of household used biomass. Please correct the table accordingly.

We have corrected table 2 to make the line about main fuel type clearer.

Thank you for the comment. We understand that the number of children included in the analysis is lower than expected but we confirm that this number is correct. We found fewer children (n = 230) than households (n = 284) as many households had no children. Having a child under 5 was not a requirement for a household to be included in the study.

Thank you for your observation. We have now reported the updated adjusted results. However, since the study focused on indoor air conditions and respiratory problem, we do not provide narratives for the association between socio-demographic variables and respiratory problems.

We have merged the two paragraphs combining the narratives from bivariate analysis and multivariable analysis

Minor issues

Comment: At line 234 you may want to say “the effect of fuel type” instead of “The predictive value of fuel type”

Response: We have corrected the wording to read “the effect of fuel type” instead of “The predictive value of fuel type.”

Comment: Line 246 “…and the finding is consistent” please cancel “and”

Response: We have removed “and” from line 246 for clarity.

Comment: Line 247 for sake of clarity, you may want to say “Indoor PM concentration is related to inflammation and a decrease in lung function”

Response: We have revised the wording at line 247 to read “Indoor PM concentration is related to inflammation and decreased lung function” for clarity.

Comment: Line 264 please use sensibilization instead of sensitization

Response: We have used “sensibilization” instead of “sensitization” in line 264.

Comment: Line 287 please refer to “Simoni and colleagues”

Response: We have referred to “Simoni et al.” at line 287

The authors honestly recognize the limitations of their study.

Response: Thank you for reviewing our manuscript and providing constructive feedback. We appreciate the time and effort you have taken to read and evaluate our study. Below is our point-by-point response to your comments:

Thus, the manuscript deserves consideration. However, it cannot be published in the present form. Reasons for refusal and suggestions for improvement are given below:

• what was the population of Bwaise?

The population of Bwaise has now been clearly stated per zone in the manuscript.

• Forty-two participants were male caregivers (Table 1): however, gender is not considered in the analyses.

Thank you for pointing out this oversight. We have added gender as a covariate in our analyses and have updated the relevant sections of the manuscript.

Thank you for the comment. We agree that active tobacco smoke is an important risk factor for respiratory symptoms and have included this information in our revised manuscript. In this study, we assessed active smoking for adults.

We apologize for any confusion caused by our use of different terms to describe smoking and exposure to tobacco smoke. It was active smoking and we have harmonized this for consistency.

• Some details are missed in the description of the conduct of the survey. How many data collectors / interviewers? Which the number of persons refused to be interviewed or could to be interviewed for other reasons?

Thank you for your feedback on the survey conduct. We worked with 6 research assistants (indicated in the methods under section “Data collection and measurements” on page 5) and we had no refusals in this study.

• Throughout the text, I have not been able to find the absolute number of childlren which were included in the survey. I have only learnt that among the 284 households, 187 had at least a child.

We apologize for not providing the absolute number of children included in the survey. We have updated the manuscript to reflect that a total of 230 children were included in our study----page 9, line 229 and page 9 line 210-11.

• Tables 3-6 are too crowded (particularly tables 3 and 5) and difficult to read. Wouldn’t it be possible to produce a summary index for the 5 respiratory problems which are considered?

We understand that Tables 3 and 5 were difficult to read and have taken steps to improve them for clarity. We have now provided these tables as part of the supplementary files. We wanted to zoom in the specific respiratory problems than a summary index because there is not even a clear framework for generating summary index.

Thank you for bringing this to our attention. We have added information on the criteria used for selecting risk factors in the multivariate analyses and have made this more explicit in the revised manuscript. We have now provided a DAG which guided the variables to consider for modelling.

Reviewer #2:

The manuscript entitled “Indoor air pollutants and respiratory symptoms among residents of an informal urban setting in Uganda: a cross-sectional study” describes the relationship between Indoor Air Pollution and respiratory symptoms in a slum area of the Uganda. The major strength of the manuscript is that it provides useful empirical data collected in difficult settings. The major limitation is its cross-sectional nature, the small sample size, and some modelling strategy.

Thank you for your detailed review of our manuscript. We appreciate your comments and suggestions and have addressed them as follows.

Introduction:

Response: We have revised the introduction to provide a broader perspective of the relationship between indoor air pollutants and respiratory health, including other respiratory symptoms that may be linked to indoor air pollution. We have also included references to support these additional points.

Response: Thank you for your suggestion to expand on the respiratory health problems linked to IAP. We have revised the paragraph to include additional respiratory health problems such as irritation of the eyes, nose, and throat, and asthma, as well as long-term health effects associated with exposure to indoor air pollutants such as pneumonia, chronic obstructive pulmonary disease, heart disease, and lung cancer. This additional information helps to provide a more comprehensive understanding of the impact of IAQ on respiratory health.

Response: We have added a reference to support the statement that inadequate housing conditions in Ugandan informal settings can negatively affect IAQ on page 2, line 49.

Methods:

Response: Sampling strategy: We have provided the total number of inhabitants/households of the Bwaise slum and the number of inhabitants/households for each district of Bwaise (Bwaise I, II, III) - see page 4, lines 121 to 125.

Comment: Data collection and measurements: Please report that indoor residual spraying was self-reported (in the current version of the manuscript it is not clear)

Response: Data collection and measurements: We have clarified that indoor residual spraying was self-reported in the revised manuscript (page 6, lines 136-137).

Statistical analysis:

Thank you for the suggestion. We have used a continuous exposure though we scaled it and a variable equal to 1/10th of PM2.5 for easier interpretation i.e “ 10 unit increase in pm2.5 was associated with…..”. page 7, line 239. The linearity assumption was violated and this was addressed by scaling. This was log-transformed to achieve linearity.

Bivariate modelling seems correct; however, I do not agree with the multivariable modelling strategy. Authors adjust all models for age, gender and smoking recognizing them as a priori confounders.

Thank you for raising this concern. We have now modelled variables based on the simple Directed Acyclic Graph -DAG (the DAG is now provided as part of the supplementary file 3). We have also described the analysis approach on page 7, lines 240 - 244.

However, for each exposure-outcome model they decided to include as additional covariate all variables having a p-value <0.20. If would suggest to not adapt this data-driven selection of confounder, especially in a small dataset as the one of this study. I will opt for a-priori selection of a set of confounders. For instance, some analyses are not adjusted for Household income, even if I see it as a confounder in all exposure-outcome relationship. A re-run of analysis using a-priori selected confounders is essential for the manuscript to be considered for publication.

Thank you for the suggestion. We have now used theory driven approach based on the DAG. We have provided the DAG, statistical analysis section and actual analysis.

As an example, let’s take Table 6, Phlegm outcome. Here estimate for Cooking from outside the living room is adjusted for PM2.5 concentration. PM2.5 concentration is not a confounder, but rather a mediator.

Thank you for the concern raised. We believe that outdoor cooking could influence PM2.5 but is also associated with respiratory health on its own. We agree PM2.5 may be a mediator of the path between outdoor cooking and respiratory problem but our exposure is not outdoor cooking but PM.25 concentration and other indoor air pollutant sources. Outdoor is only a parent of the exposure and therefore we have to control it (treat it as confounder) as per these assumptions. Thank you.

Results:

We have removed the p-values and the asterisks and have reported only point estimates and confidence intervals.

Discussion:

Comment: Page 15 Line 239: How authors motivate the high proportion of respiratory symptoms in the target population? In the sample size computation, they assumed a 20% prevalence of respiratory symptoms, while in the study population they found proportion >80%.

Response: Thank you for this comment. We have acknowledged in our discussion that the prevalence of respiratory symptoms in our study population was much higher than the 20% prevalence we had assumed in our sample size calculation. We have also explained that the high prevalence of respiratory symptoms in the study population may be attributed to the high levels of IAP in the study area and the widespread use of solid fuels for cooking and heating as compared to the study which provided the p for sample size estimation. Additionally, we noted that the study by Siddharthan, Grigsby (23) was conducted in rural and urban Uganda, while our study was conducted in an informal settlement in Kampala. Informal settlements are known to have significantly poorer IAQ conditions, which may also explain the higher prevalence of respiratory symptoms observed in our study. Overall, the high prevalence of respiratory symptoms in the study population underscores the urgent need for interventions to improve indoor air quality in slum settings.

We have checked the relationship between cooking location and indoor air pollutants using our data and have included the results in the revised manuscript. Our data however did not show significant differences in the lower levels of indoor air pollutants between to those who cooked indoors and outdoors (page 15 line 549, and page 16, line 703-704).

Thank you so much,

Solomon Wafula (on behalf of all authors)

Attachment

Submitted filename: Response to IAQ comments_27052023.docx

Click here for additional data file.^{(29.6KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0290170.r003

Decision Letter 1

Francesco Barone-Adesi

21 Jul 2023

PONE-D-22-35748R1Indoor air pollutants and respiratory symptoms among residents of an informal urban setting in Uganda: a cross-sectional studyPLOS ONE

Dear Dr. Wafula,

Please submit your revised manuscript by Sep 04 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

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

We look forward to receiving your revised manuscript.

Kind regards,

Francesco Barone-Adesi

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

SUMMARY OF COMMENTS

Most of the previous comments have been addressed. Some minor inconsistencies still need to be double-checked.

Required changes:

1) Lines 247 and Table 4: check data about PR for dampness and phlegm: 1.42 (line 250) or 16.5 (Table 4)? If PR = 16.5, add absolute number of observations.

2) Reader does not immediately appreciate that in both tables 3 and 4 prevalence rates for exposure to PM2.5 refer to 10 unit increase in concentration: a footnote would help.

3) Lines 345-347: where in the text or in the tables does the study reveal any differences between married and unmarried responders?

4) Make sure all acronyms are spelled out (e.g, IAQ: inner air quality?)

5) Authors should state for which additional covariates the model are adjusted in the manuscript or in the footnote of results table. Currently, they are only reported in the supplementary materials S3.

6) In table 2 please report that, for what concerns Main fuel type, Cooking from outside, Rearing pets, Carpets in living room and Home dampness (mould), the reported summary statistics represent percentage and absolute numbers.

Recommended changes:

1) In the analysis of PM2.5 and PM10 instead of reporting an increase of 10th, authors could report the effect for an increase of 20? Estimates for 10 unit increase seems slightly small.

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: N/A

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: Current manuscript is much improved over the previous one and can be published. A final re-reading by the authors hunting for minor inconsistencies is needed.

Some minor points require rewriting, such as:

Lines 247 and Table 4: check data about PR for dampness and phlegm: 1.42 (line 250) or 16.5 (Table 4)????. If PR = 16.5, add absolute number of observations.

Reader does not immediately appreciate that in both tables 3 and 4 prevalence rates for exposure to PM2,5 refer to 10 unit increase in concentration: a footnote would help.

Lines 345-347: where in the text or in the tables does the study reveal any differences between married and unmarried respondere?

Make sure all acronyms are decoded (IAQ: inner air quality?)

Reviewer #2: The majority of my comments have been addresses.

Here I report only some additional comments.

1. In the analysis of PM2.5 and PM10 instead of reporting an increase of 10th, authors could report the effect for an increase of 20? Estimates for 10 unit increase seems slighlty small.

2. Authors should state for which additional covariates the model are adjusted in the manuscript or in the footnote of results table. At the moment are only reported in the supplementary materials S3.

3. In table 2 please report that for Main fuel type, Cooking from outside, Rearing pets ,Carpets in living room and

Home dampness (mould) the summary statistics represent percentage and absolute numbers.

**********

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

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

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

Reviewer #1: No

Reviewer #2: Yes: Giovenale Moirano

**********

PLoS One. 2023 Aug 17;18(8):e0290170. doi: 10.1371/journal.pone.0290170.r004

Author response to Decision Letter 1

25 Jul 2023

Makerere University

School of Public Health

P.O Box 7072, Kampala

22nd July 2023

The Editor,

PLOS ONE Journal.

Re: Submission of a revised review article for publication

Sincerely,

Solomon Wafula

Required changes:

1) Lines 247 and Table 4: check data about PR for dampness and phlegm: 1.42 (line 250) or 16.5 (Table 4)? If PR = 16.5, add absolute number of observations.

Thanks for this observation. We have corrected the PR. We have now provided row by column tables for distribution of outcomes by several covariables in the supplementary file.

2) Reader does not immediately appreciate that in both tables 3 and 4 prevalence rates for exposure to PM2.5 refer to 10 unit increase in concentration: a footnote would help.

Thank you for the comment, we now provide the footnote for the readers.

3) Lines 345-347: where in the text or in the tables does the study reveal any differences between married and unmarried responders?

Thanks for the observation. We have removed variable gender in adjusted models because we were not convinced it was a good confounder to adjust for. We have therefore removed the discussion point on gender and wheezing.

4) Make sure all acronyms are spelled out (e.g, IAQ: inner air quality?)

We have now spelled out IAQ throughout the manuscript. We have spelled other acronyms the first time they are used.

Thanks for the suggestion, we have added the variables adjusted for under the footnotes.

Thank you. We have modified and provided footnote with this guidance.

Recommended changes:

1) In the analysis of PM2.5 and PM10 instead of reporting an increase of 10th, authors could report the effect for an increase of 20? Estimates for 10 unit increase seems slightly small.

Thanks for the information, after performing a logarithmic transformation, we proceeded with using a 10-unit increase. The results remain informative and valuable for our analysis.

PLoS One. doi: 10.1371/journal.pone.0290170.r005

Decision Letter 2

Francesco Barone-Adesi

3 Aug 2023

Indoor air pollutants and respiratory symptoms among residents of an informal urban settlement in Uganda: a cross-sectional study

PONE-D-22-35748R2

Dear Dr. Wafula,

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

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

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

Kind regards,

Francesco Barone-Adesi

Academic Editor

PLOS ONE

Additional Editor Comments:

Line 250 I think there is a bracket missing at the end of the sentence "((PR=1.31, 95% CI = 1.11 – 1.55 (Table 3)."

Line 256, I would suggest to use the same number of digits for the results reported in the text and in table 4 (i.e., PR= 13.9, 95% CI 3.16 – 60.9)

PLoS One. doi: 10.1371/journal.pone.0290170.r006

Acceptance letter

Francesco Barone-Adesi

9 Aug 2023

PONE-D-22-35748R2

Indoor air pollutants and respiratory symptoms among residents of an informal urban settlement in Uganda: a cross-sectional study

Dear Dr. Wafula:

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

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

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Professor Francesco Barone-Adesi

Academic Editor

PLOS ONE

Associated Data

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

Supplementary Materials

S1 Fig. Temperature and humidity changes.

(DOCX)

Click here for additional data file.^{(20.5KB, docx)}

S1 Table. Distribution of respiratory outcomes in adults.

(DOCX)

Click here for additional data file.^{(20.2KB, docx)}

S2 Table. Distribution of respiratory outcomes in children.

(DOCX)

Click here for additional data file.^{(18.2KB, docx)}

S1 Text. DAGs and univariable analysis.

(DOCX)

Click here for additional data file.^{(48.7KB, docx)}

S2 Text. PLOS questionnaire on inclusivity in global health.

(DOCX)

Click here for additional data file.^{(67.4KB, docx)}

S1 Data. Dataset for adults information.

(CSV)

Click here for additional data file.^{(210.2KB, csv)}

S2 Data. Dataset for children information.

(CSV)

Click here for additional data file.^{(99.9KB, csv)}

Attachment

Submitted filename: Response to IAQ comments_27052023.docx

Click here for additional data file.^{(29.6KB, docx)}

Data Availability Statement

All relevant data are available from within the manuscript as well as a supplemental information file.

[pone.0290170.ref001] 1.WHO. Household air pollution and health. 2021. https://www.who.int/news-room/fact-sheets/detail/household-air-pollution-and-health. Accessed 20th July 2022.

[pone.0290170.ref002] 2.Tanimowo MO. Air pollution and respiratory health in Africa: a review. East Afr Med J. 2000;77:71–5. [PubMed] [Google Scholar]

[pone.0290170.ref003] 3.Orozco-Levi M, Garcia-Aymerich J, Villar J, Ramírez-Sarmiento A, Antó JM, Gea J. Wood smoke exposure and risk of chronic obstructive pulmonary disease. The European respiratory journal. 2006;27:542–6. doi: 10.1183/09031936.06.00052705 [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref004] 4.Bruce N, Perez-Padilla R, Albalak R. Indoor air pollution in developing countries: a major environmental and public health challenge. Bull World Health Organ. 2000;78:1078–92. [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref005] 5.WHO. Burden of disease from household air pollution for 2012. 2017 [Google Scholar]

[pone.0290170.ref006] 6.Hasan M, Tasfina S, Haque SMR, Saif-Ur-Rahman KM, Khalequzzaman M, Bari W, et al. Association of biomass fuel smoke with respiratory symptoms among children under 5 years of age in urban areas: results from Bangladesh Urban Health Survey, 2013. Environ Health Prev Med. 2019;24:65. doi: 10.1186/s12199-019-0827-3 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref007] 7.Gan WQ, Sanderson WT, Browning SR, Mannino DM. Different types of housing and respiratory health outcomes. Preventive medicine reports. 2017;7:124–9. doi: 10.1016/j.pmedr.2017.05.018 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref008] 8.Regalado J, Pérez-Padilla R, Sansores R, Páramo Ramirez JI, Brauer M, Paré P, et al. The effect of biomass burning on respiratory symptoms and lung function in rural Mexican women. American journal of respiratory and critical care medicine. 2006;174:901–5. doi: 10.1164/rccm.200503-479OC [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref009] 9.Mortimer K, Gordon SB, Jindal SK, Accinelli RA, Balmes J, Martin WJ 2nd. Household air pollution is a major avoidable risk factor for cardiorespiratory disease. Chest. 2012;142:1308–15. doi: 10.1378/chest.12-1596 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref010] 10.Saha A, Rao NM, Kulkarni PK, Majumdar PK, Saiyed HN. Pulmonary function and fuel use: a population survey. Respiratory research. 2005;6:127. doi: 10.1186/1465-9921-6-127 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref011] 11.Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2224–60. doi: 10.1016/S0140-6736(12)61766-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref012] 12.Loomis D, Grosse Y, Lauby-Secretan B, El Ghissassi F, Bouvard V, Benbrahim-Tallaa L, et al. The carcinogenicity of outdoor air pollution. Lancet Oncol. 2013;14:1262–3. doi: 10.1016/s1470-2045(13)70487-x [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref013] 13.UBOS. Uganda National Household Survey 2019/2020. UBOS. 2021. https://www.ubos.org/wp-content/uploads/publications/09_2021Uganda-National-Survey-Report-2019-2020.pdf. [Google Scholar]

[pone.0290170.ref014] 14.Nandasena YL, Wickremasinghe AR, Sathiakumar N. Air pollution and health in Sri Lanka: a review of epidemiologic studies. BMC Public Health. 2010;10:300. doi: 10.1186/1471-2458-10-300 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref015] 15.Viegi G, Simoni M, Scognamiglio A, Baldacci S, Pistelli F, Carrozzi L, et al. Indoor air pollution and airway disease. Int J Tuberc Lung Dis. 2004;8:1401–15. [PubMed] [Google Scholar]

[pone.0290170.ref016] 16.Zhang J, Smith KR. Indoor air pollution: a global health concern. Br Med Bull. 2003;68:209–25. doi: 10.1093/bmb/ldg029 [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref017] 17.Emmelin A, Wall S. Indoor air pollution: a poverty-related cause of mortality among the children of the world. Chest. 2007;132:1615–23. doi: 10.1378/chest.07-1398 [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref018] 18.Kelly MS, Wirth KE, Madrigano J, Feemster KA, Cunningham CK, Arscott-Mills T, et al. The effect of exposure to wood smoke on outcomes of childhood pneumonia in Botswana. Int J Tuberc Lung Dis. 2015;19:349–55. doi: 10.5588/ijtld.14.0557 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref019] 19.Adaji EE, Ekezie W, Clifford M, Phalkey R. Understanding the effect of indoor air pollution on pneumonia in children under 5 in low-and middle-income countries: a systematic review of evidence. Environ Sci Pollut Res. 2019;26:3208–25. doi: 10.1007/s11356-018-3769-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref020] 20.Mguni P, van Vliet B, Spaargaren G, Nakirya D, Osuret J, Isunju JB, et al. What could go wrong with cooking? Exploring vulnerability at the water, energy and food Nexus in Kampala through a social practices lens. Glob Environ Change. 2020;63:102086. [Google Scholar]

[pone.0290170.ref021] 21.KCCA. Kampala Profiles: Kawempe. 2023. https://askyourgov.ug/request/37/response/37/attach/2/Kawempe%20Municipality.pdf?cookie_passthrough=1. Accessed May 15, 2023.

[pone.0290170.ref022] 22.Richmond A, Myers I, Namuli H. Urban Informality and Vulnerability: A Case Study in Kampala, Uganda. Urban Sci. 2018;2:22. [Google Scholar]

[pone.0290170.ref023] 23.Kish L. Survey sampling. 1965. (04; HN29, K5.). [Google Scholar]

[pone.0290170.ref024] 24.Jafta N, Barregard L, Jeena PM, Naidoo RN. Indoor air quality of low and middle income urban households in Durban, South Africa. Environ Res. 2017;156:47–56. doi: 10.1016/j.envres.2017.03.008 [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref025] 25.Heseltine E, Rosen J. WHO guidelines for indoor air quality: dampness and mould. 2009. https://apps.who.int/iris/handle/10665/164348. [PubMed] [Google Scholar]

[pone.0290170.ref026] 26.Rumchev K, Zhao Y, Spickett J. Health risk assessment of indoor air quality, socioeconomic and house characteristics on respiratory health among women and children of Tirupur, South India. Int J Environ Res. 2017;14:429. doi: 10.3390/ijerph14040429 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref027] 27.Nadali A, Arfaeinia H, Asadgol Z, Fahiminia M. Indoor and outdoor concentration of PM10, PM2. 5 and PM1 in residential building and evaluation of negative air ions (NAIs) in indoor PM removal. Environ Pollut Bioavailab. 2020;32:47–55. [Google Scholar]

[pone.0290170.ref028] 28.Lakshminarasimhappa M. Web-based and smart mobile app for data collection: Kobo Toolbox/Kobo collect. Journal of Indian Library Association. 2022;57:72–9. [Google Scholar]

[pone.0290170.ref029] 29.Andriessen Brunekreef, Roemer. Home dampness and respiratory health status in European children. Clin Exp Allergy. 1998;28:1191–200. [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref030] 30.WHO. Methods for monitoring indoor air quality in schools: report of a meeting, Bonn, Germany, 4–5 April 2011. 2011. https://apps.who.int/iris/handle/10665/108596. Accessed 2 Apr 2022.

[pone.0290170.ref031] 31.Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159:702–6. doi: 10.1093/aje/kwh090 [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref032] 32.Kansiime WK, Mugambe RK, Atusingwize E, Wafula ST, Nsereko V, Ssekamatte T, et al. Use of biomass fuels predicts indoor particulate matter and carbon monoxide concentrations; evidence from an informal urban settlement in Fort Portal city, Uganda. BMC Public Health. 2022;22:1723. doi: 10.1186/s12889-022-14015-w [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref033] 33.Jiang R, Bell ML. A comparison of particulate matter from biomass-burning rural and non-biomass-burning urban households in northeastern China. Environ Health Perspect. 2008;116:907–14. doi: 10.1289/ehp.10622 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref034] 34.Siddharthan T, Grigsby M, Morgan B, Kalyesubula R, Wise RA, Kirenga B, et al. Prevalence of chronic respiratory disease in urban and rural Uganda. Bulletin of the World Health Organization. 2019;97:318–27. doi: 10.2471/BLT.18.216523 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref035] 35.Simoni M, Annesi-Maesano I, Sigsgaard T, Norback D, Wieslander G, Nystad W, et al. School air quality related to dry cough, rhinitis and nasal patency in children. The European respiratory journal. 2010;35:742–9. doi: 10.1183/09031936.00016309 [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref036] 36.Annesi-Maesano I, Hulin M, Lavaud F, Raherison C, Kopferschmitt C, de Blay F, et al. Poor air quality in classrooms related to asthma and rhinitis in primary schoolchildren of the French 6 Cities Study. Thorax. 2012;67:682–8. doi: 10.1136/thoraxjnl-2011-200391 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref037] 37.Hamatui N, Beynon C. Particulate Matter and Respiratory Symptoms among Adults Living in Windhoek, Namibia: A Cross Sectional Descriptive Study. Int J Environ Res Public Health. 2017;14. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref038] 38.Delfino RJ, Gong H Jr., Linn WS, Pellizzari ED, Hu Y. Asthma symptoms in Hispanic children and daily ambient exposures to toxic and criteria air pollutants. Environ Health Perspect. 2003;111:647–56. doi: 10.1289/ehp.5992 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref039] 39.Checkley W, Pollard SL, Siddharthan T, Babu GR, Thakur M, Miele CH, et al. Managing threats to respiratory health in urban slums. Lancet Respir. 2016;4:852–4. doi: 10.1016/S2213-2600(16)30245-4 [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref040] 40.Arora S, Rasania SK, Bachani D, Gandhi A, Chhabra SK. Air pollution and environmental risk factors for altered lung function among adult women of an urban slum area of Delhi: A prevalence study. Lung India: official organ of Indian Chest Society. 2018;35:193–8. doi: 10.4103/lungindia.lungindia_263_17 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref041] 41.Smith KR, Pillarisetti A. Household Air Pollution from Solid Cookfuels and Its Effects on Health. In: Mock CN, Nugent R, Kobusingye O, Smith KR, eds. 3rd edition. Washington (DC): The International Bank for Reconstruction and Development / The World Bank; 2017. Oct 27. Chapter 7. Injury Prev Environ Health. 2018 [PubMed] [Google Scholar]

[pone.0290170.ref042] 42.Geremew A, Gebremedhin S, Mulugeta Y, Yadeta TA. Place of food cooking is associated with acute respiratory infection among under-five children in Ethiopia: multilevel analysis of 2005–2016 Ethiopian Demographic Health Survey data. Trop Med Health 2020;48:95. doi: 10.1186/s41182-020-00283-y [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref043] 43.Juntarawijit Y, Juntarawijit C. Cooking smoke exposure and respiratory symptoms among those responsible for household cooking: A study in Phitsanulok, Thailand. Heliyon. 2019;5:e01706. doi: 10.1016/j.heliyon.2019.e01706 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref044] 44.Chew FT, Teo J, Quak SH, Connett GJ, Lee BW. Presence of domestic pets and respiratory symptoms in asthmatic children. Ann Acad Med Singap. 1997;26:294–8. [PubMed] [Google Scholar]

[pone.0290170.ref045] 45.Buralli RJ, Dultra AF, Ribeiro H. Respiratory and Allergic Effects in Children Exposed to Pesticides-A Systematic Review. Int J Environ Res Public Health. 2020;17 doi: 10.3390/ijerph17082740 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0290170.ref046] 46.Bornehag CG, Sundell J, Bonini S, Custovic A, Malmberg P, Skerfving S, et al. Dampness in buildings as a risk factor for health effects, EUROEXPO: a multidisciplinary review of the literature (1998–2000) on dampness and mite exposure in buildings and health effects. Indoor Air. 2004;14:243–57. doi: 10.1111/j.1600-0668.2004.00240.x [DOI] [PubMed] [Google Scholar]

[pone.0290170.ref047] 47.Clark N, Ammann H, Brunekreef B, Eggleston P, Fisk W, Fullilove R, et al. Damp indoor spaces and health. Washington, DC: Institute of Medicine of the National Academies. 2004 [Google Scholar]

[pone.0290170.ref048] 48.Simoni M, Lombardi E, Berti G, Rusconi F, La Grutta S, Piffer S, et al. Mould/dampness exposure at home is associated with respiratory disorders in Italian children and adolescents: the SIDRIA-2 Study. Occup Environ Med. 2005;62:616–22. doi: 10.1136/oem.2004.018291 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Indoor air pollutants and respiratory symptoms among residents of an informal urban settlement in Uganda: A cross-sectional study

Solomon T Wafula

Aisha Nalugya

Hilbert Mendoza

Winnifred K Kansiime

Tonny Ssekamatte

Abel W Walekhwa

Richard K Mugambe

Florian Walter

John C Ssempebwa

David Musoke

Roles

Abstract

Background

Methods

Results

Conclusion

Introduction

Methods

Study setting

Fig 1. Map Showing the location of Bwaise within Kampala.

Study design, area and population

Sample size and sampling procedure

Data collection and measurements

Statistical analysis

Ethical consideration

Results

Background characteristics of the participants

Table 1. Background characteristics of adult household participants.

Cooking fuels, indoor conditions and air pollutant levels

Table 2. Cooking fuels, indoor conditions and air pollutant levels.

Respiratory symptoms among adults and children

Associations between indoor air conditions and respiratory problems among adults

Table 3. Adjusted models for association between indoor air quality parameters and respiratory problems among adult residents.

Associations between indoor air conditions and respiratory problems among parent-reported respiratory problems among children

Table 4. Associations between indoor air quality conditions and respiratory problems among children (adjusted analysis).

Discussion

Strengths and limitations

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Francesco Barone-Adesi

Roles

Author response to Decision Letter 0

Decision Letter 1

Francesco Barone-Adesi

Roles

Author response to Decision Letter 1

Decision Letter 2

Francesco Barone-Adesi

Roles

Acceptance letter

Francesco Barone-Adesi

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases