Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China Using Machine Learning Emulation.

Machine learning models can emulate chemical transport models, reducing computational costs and enabling more experimentation. We developed emulators to predict annual-mean fine particulate matter (PM2.5) and ozone (O3) concentrations and their associated chronic health impacts from changes in five major emission sectors (residential, industrial, land transport, agriculture, and power generation) in China. The emulators predicted 99.9% of the variance in PM2.5 and O3 concentrations. We used these emulators to estimate how emission reductions can attain air quality targets. In 2015, we estimate that PM2.5 exposure was 47.4 µg m-3 and O3 exposure was 43.8 ppb, associated with 2,189,700 (95% uncertainty interval, 95UI: 1,948,000-2,427,300) premature deaths per year, primarily from PM2.5 exposure (98%). PM2.5 exposure and the associated disease burden were most sensitive to industry and residential emissions. We explore the sensitivity of exposure and health to different combinations of emission reductions. The National Air Quality Target (35 µg m-3) for PM2.5 concentrations can be attained nationally with emission reductions of 72% in industrial, 57% in residential, 36% in land transport, 35% in agricultural, and 33% in power generation emissions. We show that complete removal of emissions from these five sectors does not enable the attainment of the WHO Annual Guideline (5 µg m-3) due to remaining air pollution from other sources. Our work provides the first assessment of how air pollution exposure and disease burden in China varies as emissions change across these five sectors and highlights the value of emulators in air quality research.

Emission Sector Impacts on Air Quality and Public Health in China From 2010 to 2020.

Anthropogenic emissions and ambient fine particulate matter (PM2.5) concentrations have declined in recent years across China. However, PM2.5 exposure remains high, ozone (O3) exposure is increasing, and the public health impacts are substantial. We used emulators to explore how emission changes (averaged per sector over all species) have contributed to changes in air quality and public health in China over 2010-2020. We show that PM2.5 exposure peaked in 2012 at 52.8 µg m-3, with contributions of 31% from industry and 22% from residential emissions. In 2020, PM2.5 exposure declined by 36% to 33.5 µg m-3, where the contributions from industry and residential sources reduced to 15% and 17%, respectively. The PM2.5 disease burden decreased by only 9% over 2012 where the contributions from industry and residential sources reduced to 15% and 17%, respectively 2020, partly due to an aging population with greater susceptibility to air pollution. Most of the reduction in PM2.5 exposure and associated public health benefits occurred due to reductions in industrial (58%) and residential (29%) emissions. Reducing national PM2.5 exposure below the World Health Organization Interim Target 2 (25 µg m-3) would require a further 80% reduction in residential and industrial emissions, highlighting the challenges that remain to improve air quality in China.

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China.

Air pollution exposure remains a leading public health problem in China. The use of chemical transport models to quantify the impacts of various emission changes on air quality is limited by their large computational demands. Machine learning models can emulate chemical transport models to provide computationally efficient predictions of outputs based on statistical associations with inputs. We developed novel emulators relating emission changes in five key anthropogenic sectors (residential, industry, land transport, agriculture, and power generation) to winter ambient fine particulate matter (PM2.5) concentrations across China. The emulators were optimized based on Gaussian process regressors with Matern kernels. The emulators predicted 99.9% of the variance in PM2.5 concentrations for a given input configuration of emission changes. PM2.5 concentrations are primarily sensitive to residential (51%-94% of first-order sensitivity index), industrial (7%-31%), and agricultural emissions (0%-24%). Sensitivities of PM2.5 concentrations to land transport and power generation emissions are all under 5%, except in South West China where land transport emissions contributed 13%. The largest reduction in winter PM2.5 exposure for changes in the five emission sectors is by 68%-81%, down to 15.3-25.9 µg m-3, remaining above the World Health Organization annual guideline of 10 µg m-3. The greatest reductions in PM2.5 exposure are driven by reducing residential and industrial emissions, emphasizing the importance of emission reductions in these key sectors. We show that the annual National Air Quality Target of 35 µg m-3 is unlikely to be achieved during winter without strong emission reductions from the residential and industrial sectors.

Regional Policies Targeting Residential Solid Fuel and Agricultural Emissions Can Improve Air Quality and Public Health in the Greater Bay Area and Across China.

Air pollution exposure is a leading public health problem in China. The majority of the total air pollution disease burden is from fine particulate matter (PM2.5) exposure, with smaller contributions from ozone (O3) exposure. Recent emission reductions have reduced PM2.5 exposure. However, levels of exposure and the associated risk remain high, some pollutant emissions have increased, and some sectors lack effective emission control measures. We quantified the potential impacts of relevant policy scenarios on ambient air quality and public health across China. We show that PM2.5 exposure inside the Greater Bay Area (GBA) is strongly controlled by emissions outside the GBA. We find that reductions in residential solid fuel use and agricultural fertilizer emissions result in the greatest reductions in PM2.5 exposure and the largest health benefits. A 50% transition from residential solid fuel use to liquefied petroleum gas outside the GBA reduced PM2.5 exposure by 15% in China and 3% within the GBA, and avoided 191,400 premature deaths each year across China. Reducing agricultural fertilizer emissions of ammonia by 30% outside the GBA reduced PM2.5 exposure by 4% in China and 3% in the GBA, avoiding 56,500 annual premature deaths across China. Our simulations suggest that reducing residential solid fuel or industrial emissions will reduce both PM2.5 and O3 exposure, whereas other policies may increase O3 exposure. Improving particulate air quality inside the GBA will require consideration of residential solid fuel and agricultural sectors, which currently lack targeted policies, and regional cooperation both inside and outside the GBA.

Assessment of Oropharyngeal and Laryngeal Cancer Treatment Delay in a Private and Safety Net Hospital System.

Objective To examine the impact of treatment setting and demographic factors on oropharyngeal and laryngeal cancer time to treatment initiation (TTI). Study Design Retrospective case series. Setting Safety net hospital and adjacent private academic hospital. Subjects and Methods Demographic, staging, and treatment details were retrospectively collected for 239 patients treated from January 1, 2014, to June 30, 2016. TTI was defined as days between diagnostic biopsy and initiation of curative treatment (defined as first day of radiotherapy [RT], surgery, or chemotherapy). Results On multivariable analysis, safety net hospital treatment (vs private academic hospital treatment), initial diagnosis at outside hospital, and oropharyngeal cancer (vs laryngeal cancer) were all associated with increased TTI. Surgical treatment, severe comorbidity, and both N1 and N2 status were associated with decreased TTI. Conclusion Safety net hospital treatment was associated with increased TTI. No differences in TTI were found when language spoken and socioeconomic status were examined in the overall cohort.

Nutrition and Swallowing Therapy in Head and Neck Cancer: Utilization of Care and Preventative Efficacy.

PURPOSE: To examine the impact of ethnicity, Spanish language preference, socioeconomic status, and treatment setting on utilization of supportive services before radiotherapy (RT) among head and neck cancer patients and to determine whether a lack of these services is associated with an increased rate of adverse events. METHODS AND MATERIALS: Demographic, staging, and treatment details were retrospectively collected for patients treated at a safety-net hospital (n = 56) or adjacent private academic hospital (n = 183) from January 1, 2014, to June 30, 2016. Supportive care services evaluated were limited to speech/swallowing therapy and nutrition therapy. Adverse events and performance measures examined included weight loss during RT, gastric tube placement, emergency department visits, hospital admissions, and missed RT days. RESULTS: On multivariable analysis, patients receiving treatment at the safety-net hospital were less likely to receive speech/swallowing services. Receiving speech/swallowing therapy before treatment was associated with less weight loss during treatment, and in conjunction with nutrition therapy, was associated with fewer missed RT days. CONCLUSION: Safety-net hospital treatment was associated with a lack of utilization of pre-RT speech/swallowing therapy which in turn was associated with increased weight loss. Interventions aimed at improving utilization of these services would improve treatment tolerance and patient outcomes.

Systematic Review of Measures of Impairment and Activity Limitation for Persons With Upper Limb Trauma and Amputation.

OBJECTIVE: (1) To identify outcome measures used in studies of persons with traumatic upper limb injury and/or amputation; and (2) to evaluate focus, content, and psychometric properties of each measure. DATA SOURCES: Searches of PubMed and CINAHL for terms including upper extremity, function, activities of daily living, outcome assessment, amputation, and traumatic injuries. STUDY SELECTION: Included articles had a sample of ≥10 adults with limb trauma or amputation and were in English. Measures containing most items assessing impairment of body function or activity limitation were eligible. DATA EXTRACTION: There were 260 articles containing 55 measures that were included. Data on internal consistency; test-retest, interrater, and intrarater reliability; content, structural, construct, concurrent, and predictive validity; responsiveness; and floor/ceiling effects were extracted and confirmed by a second investigator. DATA SYNTHESIS: The mostly highly rated performance measures included 2 amputation-specific measures (Activities Measure for Upper Limb Amputees and University of New Brunswick Test of Prosthetic Function skill and spontaneity subscales) and 2 non-amputation-specific measures (Box and Block Test and modified Jebsen-Taylor Hand Function Test light and heavy cans tests). Most highly rated self-report measures were Disabilities of the Arm, Shoulder and Hand; Patient Rated Wrist Evaluation; QuickDASH; Hand Assessment Tool; International Osteoporosis Foundation Quality of Life Questionnaire; and Patient Rated Wrist Evaluation functional recovery subscale. None were amputation specific. CONCLUSIONS: Few performance measures were recommended for patients with limb trauma and amputation. All top-rated self-report measures were suitable for use in both groups. These results will inform choice of outcome measures for these patients.

Refinements of the Medicare Outpatient Therapy Annual Expenditure Limit Policy.

BACKGROUND: A Medicare beneficiary's annual outpatient therapy expenditures that exceed congressionally established caps are subject to extra documentation and review requirements. In 2011, these caps were $1,870 for physical therapy and speech-language pathology combined and $1,870 for occupational therapy separately. OBJECTIVE: This article considers the distributional effects of replacing current cap policy with equal caps by therapy discipline (physical therapy, occupational therapy, and speech-language pathology) or a single combined cap, and risk adjusting the physical therapy cap using beneficiary characteristics and functional status. METHODS: Alternative therapy cap policies are simulated with 100% Medicare claims for 2011 therapy users (N=4.9 million). A risk-adjusted cap for annual physical therapy expenditures is calculated from a quantile regression estimated on a sample of physical therapy users with diagnoses and clinician assessments of functional ability merged to their claims (n=4,210). RESULTS: Equal discipline-specific caps of $1,710 each for physical therapy, occupational therapy, and speech-language pathology result in the same aggregate Medicare expenditures above the caps as 2011 cap policy. A single combined-disciplines cap of $2,485 also results in the same aggregate expenditures above the cap. Risk adjustment varies the physical therapy cap by as much as 5 to 1 across beneficiaries and equalizes the probability of exceeding the physical therapy cap across diagnosis and functional status groups. LIMITATIONS: One limitation of the study was the assumption of no behavioral response on the part of beneficiaries or providers to a change in cap policy. Additionally, analysis of risk adjusting the therapy caps was limited by sample size. CONCLUSIONS: Equal discipline-specific caps for physical therapy, occupational therapy, and speech-language pathology are more equitable to high users of both physical therapy and speech-language pathology than current cap policy. Separating the physical therapy and speech-language pathology caps is a change that policy makers could consider. Risk adjustment of the therapy caps is a first step in incorporating beneficiary need for services into Medicare outpatient therapy payment policy.