Can smartphone data identify the local environmental drivers of respiratory disease?

Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors

Exposure scenario and receptor behavior significantly affect PM2.5 exposure quantity of persons and resident groups, which in turn influenced indoor or outdoor air quality & health management. An Internet of Things (IoT) system, EnvironMax+, was developed to accurately and conveniently assess residential dynamic PM2.5 exposure state. A university community "QC", as the application area, was divided into four exposure scenarios and five groups of residents. Low-cost mobile sensors and indoor/outdoor pollution migration (IOP) models jointly estimated multi-scenario real-time PM2.5 concentrations. Questionnaire was used to investigate residents' indoor activity characteristics. Mobile application (app) "Air health management (AHM)" could automatic collect residents' activity trajectory. At last, multi-scenario daily exposure concentrations of each residents-group were obtained. The results showed that residential exposure scenario was the most important one, where residents spend about 60 % of their daily time. Closing window was the most significant behavior affecting indoor contamination. The annual average PM2.5 concentration in the studied scenarios: residential scenario (RS) < public scenario (PS) < outdoor scenario (OS) < catering scenario (CS). Except for CS, the outdoor PM2.5 in other scenarios was higher than indoor by 5-10 μg/m3. The multi-scenario population weighted annual average exposure concentration was 37.1 μg/m3, which was 78 % of the annual average outdoor concentration. The exposure concentration of 5 groups: cooks > outdoor workers > indoor workers > students > the elderly, related to their daily activity time proportion in different exposure scenario.

Decrypting seasonal patterns of key pollen taxa in cool temperate Australia: A multi-barcode metabarcoding analysis

Pollen allergies pose a considerable global public health concern. Allergy risk can vary significantly within plant families, yet some key pollen allergens can only be identified to family level by current optical methods. Pollen information with greater taxonomic resolution is therefore required to best support allergy prevention and self-management. We used environmental DNA (eDNA) metabarcoding to deepen taxonomic insights into the seasonal composition of airborne pollen in cool temperate Australia, a region with high rates of allergic respiratory disease. In Hobart, Tasmania, we collected routine weekly air samples from December 2018 until October 2020 and sequenced the internal transcribed spacer 2 (ITS2) and chloroplastic tRNA-Leucine tRNA-Phenylalanine intergenic spacer (trnL-trnF) regions in order to address the following questions: a) What is the genus-level diversity of known and potential aeroallergens in Hobart, in particular, in the families Poaceae, Cupressaceae and Myrtaceae? b) How do the atmospheric concentrations of these taxa change over time, and c) Does trnL-trnF enhance resolution of biodiversity when used in addition to ITS2? Our results suggest that individuals in the region are exposed to temperate grasses including Poa and Bromus in the peak grass pollen season, however low levels of exposure to the subtropical grass Cynodon may occur in autumn and winter. Within Cupressaceae, both metabarcodes showed that exposure is predominantly to pollen from the introduced genera Cupressus and Juniperus. Only ITS2 detected the native genus, Callitris. Both metabarcodes detected Eucalyptus as the major Myrtaceae genus, with trnL-trnF exhibiting primer bias for this family. These findings help refine our understanding of allergy triggers in Tasmania and highlight the utility of multiple metabarcodes in aerobiome studies.

Understanding the perspectives and needs of multiple stakeholders: Identifying key elements of a digital health intervention to protect against environmental hazards

AirRater is a free environmental health smartphone app developed and available in Australia that collects individual health data and disseminates environmental hazard information to populations. Following previous evaluations with app users, the aim of this study was to better understand how clinicians, government agency and non-government advocacy group representatives perceive an app designed to reduce the impacts of environmental hazards on individual and public health. Nine government agency and non-government advocacy group representatives, along with 11 clinicians based in Australia participated in a semi-structured interview or focus group to explore perspectives on AirRater. Interview and focus group data were transcribed and analysed using the qualitative data analysis software NVivo. Results indicate that for clinicians, apps like AirRater can add value as an educational, patient self-management and diagnostic tool. For government and peak bodies, apps can add value by addressing environmental health literacy and monitoring and forecasting gaps, as well as supporting advocacy efforts and public health surveillance. We conclude that environmental health smartphone apps can support a range of stakeholders to achieve shared goals and priorities related to individual and public health outcomes. Further research is needed to better understand how apps could be embedded into clinical practice and policy settings.

Are older adults considered in asthma and chronic obstructive pulmonary disease mobile health research? A scoping review

BACKGROUND

The use of mobile health (mHealth) for asthma and chronic obstructive pulmonary disease (COPD) is rapidly growing and may help address the complex respiratory care needs of our ageing population. However, little is currently known about how airways mHealth is developed and used among older adults (≥65 years).

OBJECTIVE

To identify if and how older adults with asthma and COPD have been incorporated across the mHealth research cycle.

METHODS

We searched Ovid MEDLINE, EMBASE, CINAHL and the Cochrane Central Registry of Controlled Trials for studies pertaining to the development or evaluation of asthma and COPD mHealth for adults published after 2010. Study, participant and mHealth details, including any considerations of older age, were extracted, synthesised and charted.

RESULTS

A total of 334 studies of 191 mHealth tools were identified. Adults ≥65 years old were included in 33.3% of asthma mHealth studies and 85.3% of COPD studies. Discussions of older age focused on barriers to technology use. Methodologic and/or analytic considerations of older age were mostly absent throughout the research cycle. Among the 28 instances quantitative age-related analyses were detailed, 12 described positive mHealth use and satisfaction outcomes in older adults versus negative or equivocal outcomes.

CONCLUSION

We identified an overall lack of consideration for older age throughout the airways mHealth research cycle, even among COPD mHealth studies that predominantly included older adults. We also found a contrast between the perceptions of how older age might negatively influence mHealth use and available quantitative evaluations. Future airways mHealth research must better integrate the needs and concerns of older adults.

Climate change, airborne allergens, and three translational mitigation approaches

One of the important adverse impacts of climate change on human health is increases in allergic respiratory diseases such as allergic rhinitis and asthma. This impact is via the effects of increases in atmospheric carbon dioxide concentration and air temperature on sources of airborne allergens such as pollen and fungal spores. This review describes these effects and then explores three translational mitigation approaches that may lead to improved health outcomes, with recent examples and developments highlighted. Impacts have already been observed on the seasonality, production and atmospheric concentration, allergenicity, and geographic distribution of airborne allergens, and these are projected to continue into the future. A technological revolution is underway that has the potential to advance patient management by better avoiding associated increased exposures, including automated real-time airborne allergen monitoring, airborne allergen forecasting and modelling, and smartphone apps for mitigating the health impacts of airborne allergens.

Evaluating User Preferences, Comprehension, and Trust in Apps for Environmental Health Hazards: Qualitative Case Study

BACKGROUND

Climate change is projected to increase environmental health hazard risks through fire-related air pollution and increased airborne pollen levels. To protect vulnerable populations, it is imperative that evidence-based and accessible interventions are available. The environmental health app, AirRater, was developed in 2015 in Australia to provide information on multiple atmospheric health hazards in near real time. The app allows users to view local environmental conditions, and input and track their personal symptoms to enable behaviors that protect health in response to environmental hazards.

OBJECTIVE

This study aimed to develop insights into users' perceptions of engagement, comprehension, and trust in AirRater to inform the future development of environmental health apps. Specifically, this study explored which AirRater features users engaged with, what additional features or functionality needs users felt they required, users' self-perception of understanding app information, and their level of trust in the information provided.

METHODS

A total of 42 adult AirRater users were recruited from 3 locations in Australia to participate in semistructured interviews to capture location- or context-specific experiences. Participants were notified of the recruitment opportunity through multiple avenues including newsletter articles and social media. Informed consent was obtained before participation, and the participants were remunerated for their time and perspectives. A preinterview questionnaire collected data including age range, any preexisting conditions, and location (postcode). All participant data were deidentified. Interviews were recorded, transcribed, and analyzed using thematic analysis in NVivo 12 (QSR International).

RESULTS

Participants discussed app features and functionality, as well as their understanding of, and trust in, the information provided by the app. Most (26/42, 62%) participants used and valued visual environmental hazard features, especially maps, location settings, and hazard alerts. Most (33/42, 78%) found information in the app easy to understand and support their needs, irrespective of their self-reported literacy levels. Many (21/42, 50%) users reported that they did not question the accuracy of the data presented in the app. Suggested enhancements include the provision of meteorological information (eg, wind speed or direction, air pressure, UV rating, and humidity), functionality enhancements (eg, forecasting, additional alerts, and the inclusion of health advice), and clarification of existing information (eg, symptom triggers), including the capacity to download personal summary data for a specified period.

CONCLUSIONS

Participants' perspectives can inform the future development of environmental health apps. Specifically, participants' insights support the identification of key elements for the optimal development of environmental health app design, including streamlining, capacity for users to customize, use of real time data, visual cues, credibility, and accuracy of data. The results also suggest that, in the future, iterative collaboration between developers, environmental agencies, and users will likely promote better functional design, user trust in the data, and ultimately better population health outcomes.

Real-world data using mHealth apps in rhinitis, rhinosinusitis and their multimorbidities

Digital health is an umbrella term which encompasses eHealth and benefits from areas such as advanced computer sciences. eHealth includes mHealth apps, which offer the potential to redesign aspects of healthcare delivery. The capacity of apps to collect large amounts of longitudinal, real-time, real-world data enables the progression of biomedical knowledge. Apps for rhinitis and rhinosinusitis were searched for in the Google Play and Apple App stores, via an automatic market research tool recently developed using JavaScript. Over 1500 apps for allergic rhinitis and rhinosinusitis were identified, some dealing with multimorbidity. However, only six apps for rhinitis (AirRater, AllergyMonitor, AllerSearch, Husteblume, MASK-air and Pollen App) and one for rhinosinusitis (Galenus Health) have so far published results in the scientific literature. These apps were reviewed for their validation, discovery of novel allergy phenotypes, optimisation of identifying the pollen season, novel approaches in diagnosis and management (pharmacotherapy and allergen immunotherapy) as well as adherence to treatment. Published evidence demonstrates the potential of mobile health apps to advance in the characterisation, diagnosis and management of rhinitis and rhinosinusitis patients.

Automatic market research of mobile health apps for the self-management of allergic rhinitis

BACKGROUND

Only a small number of apps addressing allergic rhinitis (AR) patients have been evaluated. This makes their selection difficult. We aimed to introduce a new approach to market research for AR apps, based on the automatic screening of Apple App and Google Play stores.

METHODS

A JavaScript programme was devised for automatic app screening, and applied in a market assessment of AR self-management apps. We searched the Google Play and Apple App stores of three countries (USA, UK and Australia) with the following search terms: "hay fever", "hayfever", "asthma", "rhinitis", "allergic rhinitis". Apps were eligible if symptoms were evaluated. Results obtained with the automatic programme were compared to those of a blinded manual search. As an example, we used the search to assess apps that can be used to design a combined medication score for AR.

RESULTS

The automatic search programme identified 39 potentially eligible apps out of a total of 1593 retrieved apps. Each of the 39 apps was individually checked, with 20 being classified as relevant. The manual search identified 19 relevant apps (out of 6750 screened apps). Combining both methods, a total of 21 relevant apps were identified, pointing to a sensitivity of 95% and a specificity of 99% for the automatic method. Among these 21 apps, only two could be used for the combined symptom-medication score for AR.

CONCLUSIONS

The programmed algorithm presented herein is able to continuously retrieve all relevant AR apps in the Apple App and Google Play stores, with high sensitivity and specificity. This approach has the potential to unveil the gaps and unmet needs of the apps developed so far.

Birch pollen, air pollution and their interactive effects on airway symptoms and peak expiratory flow in allergic asthma during pollen season - a panel study in Northern and Southern Sweden

BACKGROUND

Evidence of the role of interactions between air pollution and pollen exposure in subjects with allergic asthma is limited and need further exploration to promote adequate preventive measures. The objective of this study was to assess effects of exposure to ambient air pollution and birch pollen on exacerbation of respiratory symptoms in subjects with asthma and allergy to birch.

METHODS

Thirty-seven subjects from two Swedish cities (Gothenburg and Umeå) with large variation in exposure to both birch-pollen and air pollutants, participated in the study. All subjects had confirmed allergy to birch and self-reported physician-diagnosed asthma. The subjects recorded respiratory symptoms such as rhinitis or eye irritation, dry cough, dyspnoea, the use of any asthma or allergy medication and peak respiratory flow (PEF), daily for five consecutive weeks during two separate pollen seasons and a control season without pollen. Nitrogen oxides (NO_x), ozone (O₃), particulate matter (PM_2.5), birch pollen counts, and meteorological data were obtained from an urban background monitoring stations in the study city centres. The data were analysed using linear mixed effects models.

RESULTS

During pollen seasons all symptoms and medication use were higher, and PEF was reduced in the subjects. In regression analysis, exposure to pollen at lags 0 to 2 days, and lags 0 to 6 days was associated with increased ORs of symptoms and decreased RRs for PEF. Pollen and air pollution interacted in some cases; during low pollen exposure, there were no associations between air pollution and symptoms, but during high pollen exposure, O₃ concentrations were associated with increased OR of rhinitis or eye irritation, and PM_2.5 concentrations were associated with increased ORs of rhinitis or eye irritation, dyspnea and increased use of allergy medication.

CONCLUSIONS

Pollen and air pollutants interacted to increase the effect of air pollution on respiratory symptoms in allergic asthma. Implementing the results from this study, advisories for individuals with allergic asthma could be improved, minimizing the morbidities associated with the condition.

Association between air pollution and outpatient visits for allergic rhinitis: Effect modification by ambient temperature and relative humidity

Mounting evidence indicated the associations between air pollution and outpatient visits for allergic rhinitis (AR), while few studies assessed the effect modification of these associations by ambient temperature and relative humidity (RH). In this study, dataset of AR outpatients was obtained from Chinese People's Liberation Army Strategic Support Force Characteristic Medical Center in Beijing during 2014 to 2019, and the average concentrations of air pollutants including particulate matter ≤2.5 μm in diameter (PM_2.5) and ≤10 μm (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and meteorological factors (temperature and RH) at the same period were collected from one nearby air monitoring station. We performed a time-series study with Poisson regression model to examine the effects of air pollutants on AR outpatients after adjustment for potential confounders. And the effects modification analysis was further conducted by stratifying temperature and RH by tertiles into three groups of low, middle and high. In total of 33,599 outpatient visits for AR were recorded during the study period. Results found that a 10 μg/m³ increase in PM_2.5, PM₁₀, NO₂ and SO₂ was associated with significant increases in AR outpatients of 1.24% (95% confidence interval (CI): 0.69%, 1.78%), 0.79% (95% CI: 0.43%, 1.15%), 3.05% (95% CI: 1.72%, 4.40%) and 5.01% (95% CI: 1.18%, 8.96%), respectively. Stronger associations were observed in males than those in females, as well as in young adults (18-44 years) than those in other age groups. Air pollution effects on AR outpatients increased markedly at low temperature (<33.3th percentile) and high RH (>66.7th percentile). Findings in this study indicate that air pollution is associated with increased risk of AR outpatients, and the effects of air pollution on AR could be enhanced at low temperature and high RH.

Exposome mapping in chronic respiratory diseases: the added value of digital technology

PURPOSE OF REVIEW

The development and progression of chronic respiratory diseases are impacted by a complex interplay between genetic, microbial, and environmental factors. Here we specifically summarize the effects of environmental exposure on asthma, allergic rhinitis, and chronic rhinosinusitis. We furthermore discuss how digital health technology may aid in the assessment of the environmental exposure of patients and how it may be of added value for them.

RECENT FINDINGS

It is well established that one gets allergic symptoms if sensitized and exposed to the same allergen. Viruses, bacteria, pollutants, irritants, and lifestyle-related factors modify the risk of getting sensitized and develop symptoms or may induce symptoms themselves. Understanding these processes and how the various factors interact with each other and the human body require big data and advanced statistics. Mobile health technology enables integration of multiple sources of data of the patients' exposome and link these to patient outcomes. Such technologies may contribute to the increased understanding of the development of chronic respiratory disease.

SUMMARY

Implementation of digital technologies in clinical practice may in future guide the development of preventive strategies to tackle chronic respiratory diseases and eventually improve outcomes of the patient.

Ambulance dispatches and heatwaves in Tasmania, Australia: A case-crossover analysis

BACKGROUND

Climate change is causing an increase in the frequency and severity of heatwave events, with a corresponding negative impact on human health. Health service utilisation during a heatwave is increased, with a greater risk of poor health outcomes identified for specific population groups. In this study, we examined the impact of heatwave events on ambulance dispatches in Tasmania, Australia from 2008 to 2019 to explore health service utilisation and identify the most vulnerable populations at a local level.

METHODS

We used a time-stratified case-crossover analysis with conditional logistic regression to examine the association between ambulance dispatches and three levels of heatwave events (extreme, severe, and low-intensity). We examined the relationship for the whole study population, and by age, gender, socio-economic advantage and clinical diagnostic group.

RESULTS

We found that ambulance dispatches increase by 34% (OR 1.34, 95% CI 1.18-1.52) during extreme heatwaves, by 10% (OR 1.10, 95% CI 1.05-1.15) during severe heatwaves and by 4% (OR 1.04, 95% CI 1.02-1.06) during low-intensity heatwaves. We found significant associations for the elderly (over 65), the young (5 and under) and for regions with the greatest socio-economic disadvantage.

CONCLUSION

Heatwaves were associated with increased demands on ambulance services in Tasmania. In subgroups of people aged over 65 or under 5 years of age, and those from areas of higher disadvantage, we generally observed greater effect sizes than for the population as a whole.

Characterising non-linear associations between airborne pollen counts and respiratory symptoms from the AirRater smartphone app in Tasmania, Australia: A case time series approach

Pollen is a well-established trigger of asthma and allergic rhinitis, yet concentration-response relationships, lagged effects, and interactions with other environmental factors remain poorly understood. Smartphone technology offers an opportunity to address these challenges using large, multi-year datasets that capture individual symptoms and exposures in real time. We aimed to characterise associations between six pollen types and respiratory symptoms logged by users of the AirRater smartphone app in Tasmania, Australia. We analyzed 44,820 symptom reports logged by 2272 AirRater app users in Tasmania over four years (2015-2019). With these data we evaluated associations between daily respiratory symptoms and atmospheric pollen concentrations. We implemented Poisson regression models, using the case time series approach designed for app-sourced data. We assessed potentially non-linear and lagged associations with (a) total pollen and (b) six individual pollen taxa. We adjusted for seasonality and meteorology and tested for interactions with particulate air pollution (PM_2.5). We found evidence of non-linear associations between total pollen and respiratory symptoms for up to three days following exposure. For total pollen, the same-day relative risk (RR) increased to 1.31 (95% CI: 1.26-1.37) at a concentration of 50 grains/m³ before plateauing. Associations with individual pollen taxa were also non-linear with some diversity in shapes. For all pollen taxa the same-day RR was highest. The interaction between total pollen and PM_2.5 was positive, with risks associated with pollen significantly higher in the presence of high concentrations of PM_2.5. Our results support a non-linear response between airborne pollen and respiratory symptoms. The association was strongest on the day of exposure and synergistic with particulate air pollution. The associations found with Dodonaea and Myrtaceae highlight the need to further investigate the role of Australian native pollen types in allergic respiratory disease.

Pollen forecasting and its relevance in pollen allergen avoidance

Pollinosis and allergic asthma are respiratory diseases of global relevance, heavily affecting the quality of life of allergic subjects. Since there is not a decisive cure yet, pollen allergic subjects need to avoid exposure to high pollen allergens concentrations. For this purpose, pollen forecasting is an essential tool that needs to be reliable and easily accessible. While forecasting methods are rapidly evolving towards more complex statistical and physical models, the use of simple and traditional methods is still preferred in routine predictions. In this review, we summarise and explain the main parameters considered when forecasting pollen, and classify the different forecasting methods in two groups: observation-based and process-based. Finally, we compare these approaches based on their usefulness to allergic patients, and discuss possible future developments of the field.

Policy Implications for Protecting Health from the Hazards of Fire Smoke. A Panel Discussion Report from the Workshop Landscape Fire Smoke: Protecting Health in an Era of Escalating Fire Risk

Globally, and nationally in Australia, bushfires are expected to increase in frequency and intensity due to climate change. To date, protection of human health from fire smoke has largely relied on individual-level actions. Recent bushfires experienced during the Australian summer of 2019–2020 occurred over a prolonged period and encompassed far larger geographical areas than previously experienced, resulting in extreme levels of smoke for extended periods of time. This particular bushfire season resulted in highly challenging conditions, where many people were unable to protect themselves from smoke exposures. The Centre for Air pollution, energy and health Research (CAR), an Australian research centre, hosted a two-day symposium, Landscape Fire Smoke: Protecting health in an era of escalating fire risk, on 8 and 9 October 2020. One component of the symposium was a dedicated panel discussion where invited experts were asked to examine alternative policy settings for protecting health from fire smoke hazards with specific reference to interventions to minimise exposure, protection of outdoor workers, and current systems for communicating health risk. This paper documents the proceedings of the expert panel and participant discussion held during the workshop.

Environmental Hazards and Behavior Change: User Perspectives on the Usability and Effectiveness of the AirRater Smartphone App

AirRater is a free smartphone app developed in 2015, supporting individuals to protect their health from environmental hazards. It does this by providing (i) location-specific and near real-time air quality, pollen and temperature information and (ii) personal symptom tracking functionality. This research sought to evaluate user perceptions of AirRater's usability and effectiveness. We collected demographic data and completed semi-structured interviews with 42 AirRater users, identified emergent themes, and used two frameworks designed to understand and support behavior change-the Behavior Change Wheel (BCW) and the Protective Action Decision Model (PADM)-to interpret results. Of the 42 participants, almost half indicated that experiencing symptoms acted as a prompt for app use. Information provided by the app supported a majority of the 42 participants to make decisions and implement behaviors to protect their health irrespective of their location or context. The majority of participants also indicated that they shared information provided by the app with family, friends and/or colleagues. The evaluation also identified opportunities to improve the app. Several study limitations were identified, which impacts the generalizability of results beyond the populations studied. Despite these limitations, findings facilitated new insights into motivations for behavior change, and contribute to the existing literature investigating the potential for smartphone apps to support health protection from environmental hazards in a changing climate.

The Role of Mobile Health Technologies in Stratifying Patients for AIT and Its Cessation: The ARIA-EAACI Perspective

Allergen immunotherapy (AIT) is a proven therapeutic option for the treatment of allergic rhinitis and/or asthma. Many international or national practice guidelines have been produced, but the evidence-based method varies and they do not usually propose care pathways. The present article considers the possible role of mobile health in AIT for allergic rhinitis/asthma. There are no currently available validated biologic biomarkers that can predict AIT success, and mobile health biomarkers have some relevance. In the current article, the following aspects will be discussed: patient stratification for AIT, symptom-medication scores for the follow-up of patients, clinical trials, as well as the approach of the European Academy of Allergy and Clinical Immunology.

Smartphone-Based Data Collection in Ophthalmology

Due to their widespread use among the population and their wide range of functions and sensors, smartphones are suitable for data collection for medical purposes. App-supported input masks, patient diaries, and patient information systems, mobile access to the patient file as well as telemedical services will continue to find their way into our field of expertise in the future. In addition, the use of smartphone sensors (GPS and motion sensors, touch display, microphone) and coupling possibilities with biosensors (for example with Continuous Glucose Monitoring [CGM] systems), advanced camera technology, the possibility of regular and appointment independent checking of the visual system (visual acuity/contrast vision) as well as real-time data transfer offer interesting possibilities for patient treatment and clinical research. The present review deals with the current status and future perspectives of smartphone-based data collection and possible applications in ophthalmology.

Air Pollution and Asthma: Critical Targets for Effective Action

Evidence to advocate for cleaner air for people with asthma is not in short supply. We know that air pollution is associated with the development and worsening of the condition and that mitigating interventions can improve respiratory outcomes. We have clear targets, particularly traffic emissions, especially in urban areas, and plenty of potentially effective actions. Road traffic must be reduced, and what remains should be cleaner and greener. Urban green spaces, safe cycle networks and wider pavements will promote active travel and leisure time exercise. Healthcare professionals must ensure people are aware of their air quality, its impact on asthma and the appropriate behaviour to safeguard health. What remains are realistic policies and effective measures, based on the correct scientific evidence, to be taken forth with political courage and investment so that air pollution no longer contributes to the development or worsening of respiratory ill health.

Associations between air pollution and outpatient visits for allergic rhinitis in Xinxiang, China

Several epidemiological studies have investigated the adverse health effects of air pollution, but studies reporting its effects on allergic rhinitis (AR) are limited, especially in developing countries having the most severe pollution. Limited studies have been conducted in China, but their results were inconsistent. So, we conducted a time-series study to evaluate the acute effect of six air pollutants (fine particulate matter [PM_2.5], particulate matter with diameter less than 10 μm [PM₁₀], sulfur dioxide [SO₂], nitrogen dioxide [NO₂], ozone [O₃], and carbon monoxide [CO]) on hospital outpatient visits for AR in Xinxiang, China from January 1, 2015, to December 31, 2018. An over-dispersed Poisson generalized additive model adjusting for weather conditions, long-term trends, and day of the week was used. In total, 14,965 AR outpatient records were collected during the study period. Results found that each 10 μg/m³ increase in PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO corresponded to 0.70% (95% confidence interval 0.00-1.41%), 0.79% (0.35-1.23%), 3.43% (1.47-5.39%), 4.54% (3.01-6.08%), 0.97% (- 0.11-2.05%), and 0.07% (0.02-0.12%) increments in AR outpatients on the current day, respectively. In the stratification analyses, statistically stronger associations were observed with PM_2.5, PM₁₀, SO₂, NO₂, and CO for AR outpatients < 15 years of age than in those 15-65 and ≥ 65 years of age, whereas the opposite result was found with O₃. Associations between PM₁₀, SO₂, NO₂, O₃, and AR outpatients were higher in the warm season than those in the cool season. This study suggests that exposure to PM_2.5, PM₁₀, SO₂, NO₂, and CO was associated with increased AR risk and children younger than 15 years might be more vulnerable.