Childhood lower respiratory tract infections linked to residential airborne bacterial and fungal microbiota.

Residential microbial composition likely contributes to the development of lower respiratory tract infections (LRTI) among children, but the association is poorly understood. We aimed to study the relationship between the indoor airborne dust bacterial and fungal microbiota and childhood LRTI in Ibadan, Nigeria. Ninety-eight children under the age of five years hospitalized with LRTI were recruited and matched by age (±3 months), sex, and geographical location to 99 community-based controls without LRTI. Participants' homes were visited and sampled over a 14-day period for airborne house dust using electrostatic dustfall collectors (EDC). In airborne dust samples, the composition of bacterial and fungal communities was characterized by a meta-barcoding approach using amplicons targeting simultaneously the bacterial 16S rRNA gene and the internal-transcribed-spacer (ITS) region-1 of fungi in association with the SILVA and UNITE database respectively. A 100-unit change in house dust bacterial, but not fungal, richness (OR 1.06; 95%CI 1.03-1.10) and a 1-unit change in Shannon diversity (OR 1.92; 95%CI 1.28-3.01) were both independently associated with childhood LRTI after adjusting for other indoor environmental risk factors. Beta-diversity analysis showed that bacterial (PERMANOVA p < 0.001, R2 = 0.036) and fungal (PERMANOVA p < 0.001, R2 = 0.028) community composition differed significantly between homes of cases and controls. Pair-wise differential abundance analysis using both DESEq2 and MaAsLin2 consistently identified the bacterial phyla Deinococcota (Benjamini-Hochberg (BH) adjusted p-value <0.001) and Bacteriodota (BH-adjusted p-value = 0.004) to be negatively associated with LRTI. Within the fungal microbiota, phylum Ascomycota abundance (BH adjusted p-value <0.001) was observed to be directly associated with LRTI, while Basidiomycota abundance (BH adjusted p-value <0.001) was negatively associated with LRTI. Our study suggests that early-life exposure to certain airborne bacterial and fungal communities is associated with LRTI among children under the age of five years.

Exposure-response relationship of residential dampness and mold damage with severe lower respiratory tract infections among under-five children in Nigeria.

Previous epidemiological studies demonstrated an increased risk of respiratory health effects in children and adults exposed to dampness or mold. This study investigated associations of quantitative indicators of indoor dampness and mold exposure with severe lower respiratory tract infections (LRTI) among children aged 1-59 months in Ibadan, Nigeria. Methods: In-home visits were conducted among 178 children hospitalized with LRTI matched by age (±3 months), sex, and geographical location with 180 community-based children without LRTI. Trained study staff evaluated the indoor environment using a standardized home walkthrough checklist and measured visible dampness and mold damage. Damp-moldy Index (DMI) was also estimated to quantify the level of exposure. Exposure-response relationships of dampness and mold exposure with severe LRTI were assessed using multivariable restricted cubic spline regression models adjusting for relevant child, housing, and environmental characteristics. Results: Severe LRTI cases were more often male than female (61.8%), and the overall mean (SD) age was 7.3 (1.35) months. Children exposed to dampness <0.3 m2 (odds ratio [OR] = 2.11; 95% confidence interval [CI] = 1.05, 4.36), and between 0.3 and 1.0 m2 (OR = 2.34; 95% CI = 1.01, 7.32), had a higher odds of severe LRTI compared with children not exposed to dampness. The restricted cubic spline showed a linear exposure-response association between severe LRTI and residential dampness (P < 0.001) but a nonlinear relationship with DMI (P = 0.01). Conclusions: Residential dampness and DMI were exposure-dependently associated with higher odds of severe LRTI among under-five children. If observed relationships were causal, public health intervention strategies targeted at reducing residential dampness are critically important to mitigate the burden of severe LRTI among under-five children.

Indoor bacterial and fungal aerosols as predictors of lower respiratory tract infections among under-five children in Ibadan, Nigeria.

BACKGROUND: This study aimed to investigate the association between exposure to diverse indoor microbial aerosols and lower respiratory tract infections (LRTI) among children aged 1 to 59 months in Ibadan, Nigeria. METHODS: One hundred and seventy-eight (178) hospital-based LRTI cases among under-five children were matched for age (± 3 months), sex and geographical location with 180 community-based controls (under-five children without LRTI). Following consent from caregivers of eligible participants, a child's health questionnaire, clinical proforma and standardized home-walkthrough checklist were used to collect data. Participant homes were visited and sampled for indoor microbial exposures using active sampling approach by Anderson sampler. Indoor microbial count (IMC), total bacterial count (TBC), and total fungal count (TFC) were estimated and dichotomized into high (> median) and low (≤ median) exposures. Alpha diversity measures including richness (R), Shannon (H) and Simpson (D) indices were also estimated. Conditional logistic regression models were used to test association between exposure to indoor microbial aerosols and LRTI risk among under-five children. RESULTS: Significantly higher bacterial and fungal diversities were found in homes of cases (R = 3.00; H = 1.04; D = 2.67 and R = 2.56; H = 0.82; D = 2.33) than homes of controls (R = 2.00; H = 0.64; D = 1.80 and R = 1.89; H = 0.55; D = 1.88) p < 0.001, respectively. In the multivariate models, higher categories of exposure to IMC (aOR = 2.67, 95% CI 1.44-4.97), TBC (aOR = 2.51, 95% CI 1.36-4.65), TFC (aOR = 2.75, 95% CI 1.54-4.89), bacterial diversity (aOR = 1.87, 95% CI 1.08-3.24) and fungal diversity (aOR = 3.00, 95% CI 1.55-5.79) were independently associated with LRTI risk among under-five children. CONCLUSIONS: This study suggests an increased risk of LRTI when children under the age of five years are exposed to high levels of indoor microbial aerosols.

Epidemiological Study of Risk Factors for Lung Cancer in KwaZulu-Natal, South Africa.

The high incidence cancer rates are due to factors such as behavior, occupational exposures, genetics, environmental pollution and infections. The aim of this study was to identify risk factors associated with lung cancer among patients seen in the public health facilities in KwaZulu-Natal, South Africa. In this case-control study, 75 cases and 159 controls were interviewed using a structured close-ended questionnaire. Logistic regression showed a positive association between lung cancer and tobacco smoking (OR = 2.86, 95% CI: 1.21-6.77) and exposure to passive smoke (OR = 3.28, 95% CI: 1.48-7.30). When adjusted for other covariates, tobacco smoking and passive smoke were still positively associated with increased risk of lung cancer. Alcohol consumption (aORs ranging from 2.79 to 3.35) and history of lung disease (aORs ranging from 9.91 to 12.1) were statistically significantly associated with lung cancer. Our study suggests that tobacco smoke exposure is the major cause of lung cancer, and increased exposure to occupational and environmental carcinogenic substances, alcohol consumption and history of lung disease increase the risk of lung cancer. Based on our findings, policy development and planning of prevention strategies incorporating smoking legislations, occupational health and safety are essential in South Africa.

Maternal exposure to indoor PM2.5 and associated adverse birth outcomes in low socio-economic households, Durban, South Africa.

The association between in utero exposure to indoor PM2.5 and birth outcomes is not conclusive. We assessed the association between in utero exposure to indoor PM2.5 , birth weight, gestational age, low birth weight, and/or preterm delivery. Homes of 800 pregnant women were assessed using a structured walkthrough questionnaire. PM2.5 measurements were undertaken in 300 of the 800 homes for a period of 24 h. Repeated sampling was conducted in 30 of these homes to determine PM2.5 predictors that can reduce within-and/or between-home variability. A predictive model was used to estimate PM2.5 levels in unmeasured homes (n = 500). The mean (SD) for PM2.5 was 37 µg/m3 (29) with a median of 28µg/m3 . The relationship between PM2.5 exposure, birth weight, gestational age, low birth weight, and preterm delivery was assessed using multivariate linear and logistic regression models. We explored infant sex as a potential effect modifier, by creating an interaction term between PM2.5 and infant sex. The odds ratio of low birth weight and preterm delivery was 1.75 (95%CI: 1.47, 2.09) and 1.21 (95%CI: 1.06, 1.39), respectively, per interquartile increase (18 µg/m3 ) in PM2.5 exposure. The reduction in birth weight and gestational age was 75 g (95%CI: 107.89, 53.15) and 0.29 weeks (95%CI: 0.40, 0.19) per interquartile increase in PM2.5 exposure. Infant sex was an effect modifier for PM2.5 on birth weight and gestational age, and the reduction in birth weight and gestational age was 103 g (95%CI: 142.98, 64.40) and 0.38 weeks (95% CI: 0.53, 0.23), respectively, for boys, and 54 g (95%CI: 91.78,15.62) and 0.23 weeks (95%CI:0.37, 0.08), respectively, for girls. Exposure to PM2.5 is associated with adverse pregnancy outcomes. To protect the population during their reproductive period, public health policy should focus on indoor PM2.5 levels.

Establishing and Evaluating Cancer Surveillance System in KwaZulu-Natal, South Africa.

BACKGROUND: The increasing cancer burden remains a public health challenge. Quality and accurate population data is important to improve cancer control, screening, and treatment programmes for the sub-Saharan Africa region. AIM: The aim of this study was to establish hospital-based cancer surveillance system, thereby reporting the burden that cancer diagnosis and treatment place on 3 hospitals - an approach of health systems strengthening. METHODS: A hospital-based cancer surveillance was established in 3 public health facilities that provide oncology services in KwaZulu-Natal. An active method was used for finding cancer cases. The cancer surveillance database was evaluated according to the criteria recommended for cancer registries. Analyses of data included descriptive and crude incidence rates. RESULTS: A total of 2307 newly diagnosed cancer cases were reported in 2018, with a majority from Inkosi Albert Luthuli Central hospital (65.3%), followed by Greys hospital (30.8%) and then Addington hospital (3.94%). Most of the cancer cases were from the 2 major urban areas of the province (eThekwini and uMgungundlovu district). The most commonly diagnosed cancers from all combined 3 facilities for both sexes were breast, cervix, colorectal, Kaposi Sarcoma, and lung. Approximately half of the cancer cases had no staging, and 12.8% of the cases were diagnosed at stage 4. The mostly prescribed treatments for the patients were radiotherapy and chemotherapy. CONCLUSIONS: Based on our hospital-based surveillance, cancer burden is high in the 3 facilities. Strengthening cancer screening and diagnostic policies and procedures that will allow expansion of accurate cancer surveillance system is essential in KwaZulu-Natal and South Africa as a whole.

Association of indoor microbial aerosols with respiratory symptoms among under-five children: a systematic review and meta-analysis.

BACKGROUND: Despite the recognition of the importance of indoor microbial exposures on children's health, the role of different microbial agents in development and aggravation of respiratory symptoms and diseases is only poorly understood. This study aimed to assess whether exposure to microbial aerosols within the indoor environment are associated with respiratory symptoms among children under-5 years of age. METHODS: A systematic literature search was conducted on PubMed, Web of Science, GreenFILE, ScienceDirect, EMBASE and Cochrane library through February 2020. Studies that investigated the exposure-response relationship between components of the indoor microbial communities and respiratory symptoms among under-five children were eligible for inclusion. A random-effect meta-analysis was applied to estimate pooled relative risk (RR) and 95% confidence interval (CI) for study specific high versus low microbial exposures. The potential effect of individual studies on the overall estimate was evaluated using leave-one-out analysis, while heterogeneity was evaluated by I2 statistics using RevMan 5.3. RESULTS: Fifteen studies were eligible for inclusion in a meta-analysis. The pooled risk estimate suggested that increased microbial exposure was associated with an increased risk of respiratory symptoms [pooled relative risk (RR): 1.24 (1.09, 1.41), P = 0.001]. The association was strongest with exposure to a combination of Aspergillus, Penicillium, Cladosporium and Alternaria species [pooled RR: 1.73 (1.30, 2.31), P = 0.0002]. Stratified analysis revealed an increased risk of wheeze [pooled RR: 1.20 (1.05, 1.37), P = 0.007 and allergic rhinitis [RR: 1.18 (0.94, 1.98), P = 0.16] from any microbial exposure. CONCLUSIONS: Microbial exposures are, in general, associated with risk of respiratory symptoms. Future studies are needed to study the indoor microbiome more comprehensively, and to investigate the mechanism of these associations.

Spatial Distribution of Cancer Cases Seen in Three Major Public Hospitals in KwaZulu-Natal, South Africa.

BACKGROUND: Noncommunicable diseases (NCDs) like cancer are posing a challenge in the health system especially in low- and middle-income countries (LMICs). In South Africa, cancer is under-reported due to the lack of a comprehensive cancer surveillance system. The limited knowledge on the extent of cancer burden has led to inaccurate allocation of public health resources. The aim of this study was to describe cancer incidence and spatial distribution of cancer cases seen at 3 main public oncology facilities in KwaZulu-Natal. METHODS: In this retrospective study, cases of cancer observed from year 2015 to 2017 were extracted from medical records. The crude incidence rate was estimated for the total cancer cases and for different type of cancer reported over that period. Age-standardised incidence rates (ASR) per 100 000 was calculated per year using age groups and sex according to the district population data of KwaZulu-Natal. The comparisons of cancer diagnosed incidences were made between 11 districts using the ASR. Choropleth spatial maps and Moran's Index were used to assess the ASR cancer spatial distribution along with geographical patterns among the districts. One sample chi-square test was used to assess the significant increase/decrease over time. RESULTS: The study lost numerous cases due to incompleteness. A total of 4909 new cases were diagnosed with cancer during 2015 to 2017, 62% of which were female. Both uMgungundlovu and eThekwini districts had the highest ASR among district municipalities of KwaZulu-Natal for both male and female (83.6 per 100 000 per men year for men, 158.2 per 100 000 women per year, and 60.1 per 100 000 men per year and 96.9 per 100 000 women per year, respectively). Random distribution of reported cancer cases in KwaZulu-Natal was observed with a high concentration being in and around 2 metropolitan districts. Spatial variation showed a significant difference from year to year between the districts with the random spatial distribution. Overall, there was a significant decline of cancer incidences observed from 2015 to 2017 (P < .05) in the province. CONCLUSION: The overall cancer incidence in the study shows that female cancers (breast and cervical) are still on the rise and still need to be given priority as they were most prevalent in KwaZulu-Natal. Spatial analysis (choropleth maps) was used to show a pattern of higher concentration of cancer incidence in the north-western parts of the province.

Exposure assessment of indoor particulate matter during pregnancy: a narrative review of the literature.

OBJECTIVE: The aim of this review was to summarize the evidence of the exposure assessment approaches of indoor particulate matter (PM) during pregnancy and to recommend future focus areas. CONTENT: Exposure to indoor PM during pregnancy is associated with adverse birth outcomes. However, many questions remain about the consistency of the findings and the magnitude of this effect. This may be due to the exposure assessment methods used and the challenges of characterizing exposure during pregnancy. Exposure is unlikely to remain constant over the nine-month period. Pregnant females' mobility and activities vary - for example, employment status may be random among females, but among those employed, activities are likely to be greater in the early pregnancy than closer to the delivery of the child. SUMMARY: Forty three studies that used one of the five categories of indoor PM exposure assessment (self-reported, personal air monitoring, household air monitoring, exposure models and integrated approaches) were assessed. Our results indicate that each of these exposure assessment approaches has unique characteristics, strengths, and weaknesses. While questionnaires and interviews are based on self-report and recall, they were a major component in the reviewed exposure assessment studies. These studies predominantly used large sample sizes. Precision and detail were observed in studies that used integrated approaches (i. e. questionnaires, measurements and exposure models). OUTLOOK: Given the limitations presented by these studies, exposure misclassification remains possible because of personal, within and between household variability, seasonal changes, and spatiotemporal variability during pregnancy. Therefore, using integrated approaches (i. e. questionnaire, measurements and exposure models) may provide better estimates of PM levels across trimesters. This may provide precision for exposure estimates in the exposure-response relationship.

Predictors of urban household variability of indoor PM2.5 in low socio-economic communities.

In epidemiological studies, levels of PM2.5 need to be estimated over time and space. Because of logistical constraints, very few studies have been conducted to assess the variability within and across homes and the predictors of this variability. This study evaluated within- and between-home variability of indoor PM2.5 and identified predictors for PM2.5 in homes of mothers participating in the urban Mother and Child in the Environment birth cohort study in Durban, South Africa. Thirty homes were selected from 300 homes that were previously sampled for PM2.5. Two measurements of PM2.5 levels were conducted in each home within a 1 week interval in both warm and cold seasons (four samplings per home) using Airmetrics MiniVol samplers. A linear mixed-effect model was used to evaluate within- and between-home variability and to identify fixed effects (predictors) that result in reduced variability. The PM2.5 levels in the 30 homes ranged from 2 to 303 µg m-3. The within-home variability accounted for 94% of the total variability in the log-transformed PM2.5 levels for the 30 homes. The fixed effects extracted from the repeated samplings in the present study were used to improve a previously developed multivariable linear regression model for 300 homes, and thereby increased the R2 from 0.50 to 0.54. Inclusion of fixed-effects in multivariable linear regression models resulted in a reasonably robust model that can be used to predict PM2.5 levels in unmeasured homes of the cohort.

Indoor microbiome and risk of lower respiratory tract infections among children under-five years: A meta-analysis.

We investigated whether exposure to microbiome within the indoor environment is associated with risk of lower respiratory tract infections (LRTI) among children under 5 years of age. Electronic scientific repositories; PubMed, Scopus, Web of Science, GreenFILE, EMBASE, and Cochrane library were searched and screened through July 2019 for published reports for inclusion in the meta-analysis. Studies were eligible for inclusion if they reported an adjusted measure of risk for LRTI associated with IM exposure, including the relative risk (RR) or odds ratio (OR) and confidence interval (CI). The pooled OR was computed using the inverse of variance method for weighting. Sensitivity analysis was used to evaluate the effect of individual studies, while heterogeneity was evaluated by I2 statistics using RevMan 5.3. Seven studies were eligible for inclusion in our meta-analysis. Exposure to a higher concentration of IM was associated with an increased risk of LRTI [OR:1.20 (1.11, 1.33), P < .0001]. The risk was stronger with exposure to total fungal concentration [OR:1.27 (1.13, 1.44), P < .0001] than visible molds [OR:1.20 (1.07, 1.34, P = .001]. Under-five children exposed to higher IM concentration are likely at increased risk of LRTI. Interventions addressing IM exposure should be considered in the management of LRTI among under-five children.

Home Assessment of Indoor Microbiome (HAIM) in Relation to Lower Respiratory Tract Infections among Under-Five Children in Ibadan, Nigeria: The Study Protocol.

The association between household air pollution and lower respiratory tract infections (LRTI) among children under five years of age has been well documented; however, the extent to which the microbiome within the indoor environment contributes to this association is uncertain. The home assessment of indoor microbiome (HAIM) study seeks to assess the abundance of indoor microbiota (IM) in the homes of under-five children (U-5Cs) with and without LRTI. HAIM is a hospital- and community-based study involving 200 cases and 200 controls recruited from three children's hospitals in Ibadan, Nigeria. Cases will be hospital-based patients with LRTI confirmed by a pediatrician, while controls will be community-based participants, matched to cases on the basis of sex, geographical location, and age (±3 months) without LRTI. The abundance of IM in houses of cases and controls will be investigated using active and passive air sampling techniques and analyzed by qualitative detection of bacterial 16SrRNA gene (V3-V4), fungal ITS1 region, and viral RNA sequencing. HAIM is expected to elucidate the relationship between exposure to IM and incidence of LRTI among U-5Cs and ultimately provide evidence base for strategic interventions to curtail the burgeoning burden of LRTI on the subcontinent.

Association of childhood pulmonary tuberculosis with exposure to indoor air pollution: a case control study.

BACKGROUND: Crude measures of exposure to indicate indoor air pollution have been associated with the increased risk for acquiring tuberculosis. Our study aimed to determine an association between childhood pulmonary tuberculosis (PTB) and exposure to indoor air pollution (IAP), based on crude exposure predictors and directly sampled and modelled pollutant concentrations. METHODS: In this case control study, children diagnosed with PTB were compared to children without PTB. Questionnaires about children's health; and house characteristics and activities (including household air pollution) and secondhand smoke (SHS) exposure were administered to caregivers of participants. A subset of the participants' homes was sampled for measurements of PM10 over a 24-h period (n = 105), and NO2 over a period of 2 to 3 weeks (n = 82). IAP concentrations of PM10 and NO2 were estimated in the remaining homes using predictive models. Logistic regression was used to look for association between IAP concentrations, crude measures of IAP, and PTB. RESULTS: Of the 234 participants, 107 were cases and 127 were controls. Pollutants concentrations (µg/m3) for were PM10 median: 48 (range: 6.6-241) and NO2 median: 16.7 (range: 4.5-55). Day-to-day variability within- household was large. In multivariate models adjusted for age, sex, socioeconomic status, TB contact and HIV status, the crude exposure measures of pollution viz. cooking fuel type (clean or dirty fuel) and SHS showed positive non-significant associations with PTB. Presence of dampness in the household was a significant risk factor for childhood TB acquisition with aOR of 2.4 (95% CI: 1.1-5.0). The crude exposure predictors of indoor air pollution are less influenced by day-to-day variability. No risk was observed between pollutant concentrations and PTB in children for PM10 and NO2. CONCLUSION: Our study suggests increased risk of childhood tuberculosis disease when children are exposed to SHS, dirty cooking fuel, and dampness in their homes. Yet, HIV status, age and TB contact are the most important risk factors of childhood PTB in this population.

Indoor air quality of low and middle income urban households in Durban, South Africa.

INTRODUCTION: Elevated levels of indoor air pollutants may cause cardiopulmonary disease such as lower respiratory infection, chronic obstructive lung disease and lung cancer, but the association with tuberculosis (TB) is unclear. So far the risk estimates of TB infection or/and disease due to indoor air pollution (IAP) exposure are based on self-reported exposures rather than direct measurements of IAP, and these exposures have not been validated. OBJECTIVE: The aim of this paper was to characterize and develop predictive models for concentrations of three air pollutants (PM10, NO2 and SO2) in homes of children participating in a childhood TB study. METHODS: Children younger than 15 years living within the eThekwini Municipality in South Africa were recruited for a childhood TB case control study. The homes of these children (n=246) were assessed using a walkthrough checklist, and in 114 of them monitoring of three indoor pollutants was also performed (sampling period: 24h for PM10, and 2-3 weeks for NO2 and SO2). Linear regression models were used to predict PM10 and NO2 concentrations from household characteristics, and these models were validated using leave out one cross validation (LOOCV). SO2 concentrations were not modeled as concentrations were very low. RESULTS: Mean indoor concentrations of PM10 (n=105), NO2 (n=82) and SO2 (n=82) were 64µg/m3 (range 6.6-241); 19µg/m3 (range 4.5-55) and 0.6µg/m3 (range 0.005-3.4) respectively with the distributions for all three pollutants being skewed to the right. Spearman correlations showed weak positive correlations between the three pollutants. The largest contributors to the PM10 predictive model were type of housing structure (formal or informal), number of smokers in the household, and type of primary fuel used in the household. The NO2 predictive model was influenced mostly by the primary fuel type and by distance from the major roadway. The coefficients of determination (R2) for the models were 0.41 for PM10 and 0.31 for NO2. Spearman correlations were significant between measured vs. predicted PM10 and NO2 with coefficients of 0.66 and 0.55 respectively. CONCLUSION: Indoor PM10 levels were relatively high in these households. Both PM10 and NO2 can be modeled with a reasonable validity and these predictive models can decrease the necessary number of direct measurements that are expensive and time consuming.

Characterization of allergens and airborne fungi in low and middle-income homes of primary school children in Durban, South Africa.

BACKGROUND: The South Durban Health Study (SDHS) is a population-based study that examined the relationship between exposure to ambient air pollutants and respiratory disease among school children with high prevalence of asthma who resided in two purposely selected communities in north and south Durban, KwaZulu-Natal, South Africa. METHODS: From the SDHS participants, a subgroup of 135 families was selected for investigation of household characteristics potentially related to respiratory health. In these households, a walkthrough investigation was conducted, and settled dust and air samples were collected for allergen and fungal measurements using standardized techniques. RESULTS: Asp f1 allergen was detected in all homes, and Bla g1 allergen was detected in half of the homes. House dust allergens, Der f1 and Der p1 exceeded concentrations associated with risk of sensitization and exacerbation of asthma in 3% and 13%, respectively, of the sampled homes, while Bla g1 exceeded guidance values in 13% of the homes. Although airborne fungal concentrations in sleep areas and indoors were lower than outdoor concentrations, they exceeded 1,000 CFU/m(3) in 29% of the homes. Multivariate analyses identified several home characteristics that were predictors of airborne fungal concentrations, including moisture, ventilation, floor type, and bedding type. Airborne fungal concentrations were similar indoors and outdoors, which likely reduced the significance of housing and indoor factors as determinants of indoor concentrations. CONCLUSION: Allergen concentrations were highly variable in homes, and a portion of the variability can be attributed to easily recognized conditions.