We investigated the relations between ozone (O3), nitrogen dioxide (NO2), and respirable particles less than 10 microm in diameter (PM10) and school absenteeism in a cohort of 4th-grade school children who resided in 12 southern California communities. An active surveillance system ascertained the numbers and types of absences during the first 6 months of 1996. Pollutants were measured hourly at central-site monitors in each of the 12 communities. To examine acute effects of air pollution on absence rates, we fitted a two-stage time-series model to the absence count data that included distributed lag effects of exposure adjusted for long-term pollutant levels. Short-term change in O3, but not NO2 or PM10, was associated with a substantial increase in school absences from both upper and lower respiratory illness. An increase of 20 ppb of O3 was associated with an increase of 62.9% [95% confidence interval (95% CI) = 18.4-124.1%] for illness-related absence rates, 82.9% (95% CI = 3.9-222.0%) for respiratory illnesses, 45.1% (95% CI = 21.3-73.7%) for upper respiratory illnesses, and 173.9% (95% CI = 91.3-292.3%) for lower respiratory illnesses with wet cough. The short-term effects of a 20-ppb change of O3 on illness-related absenteeism were larger in communities with lower long-term average PM10 [223.5% (95% CI = 90.4-449.7)] compared with communities with high average levels [38.1% (95% CI = 8.5-75.8)]. Increased school absenteeism from O3 exposure in children is an important adverse effect of ambient air pollution worthy of public policy consideration.

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BackgroundMobile phone ownership and access have increased rapidly across low- and middle-income countries (LMICs) within the last decade. Concomitantly, LMICs are experiencing demographic and epidemiologic transitions, where non-communicable diseases (NCDs) are increasingly becoming leading causes of morbidity and mortality. Mobile phone surveys could aid data collection for prevention and control of these NCDs but limited evidence of their feasibility exists.ObjectiveThe objective of this paper is to describe a series of sub-studies aimed at optimizing the delivery of interactive voice response (IVR) and computer-assisted telephone interviews (CATI) for NCD risk factor data collection in LMICs. These sub-studies are designed to assess the effect of factors such as airtime incentive timing, amount, and structure, survey introduction characteristics, different sampling frames, and survey modality on key survey metrics, such as survey response, completion, and attrition rates.MethodsIn a series of sub-studies, participants will be randomly assigned to receive different airtime incentive amounts (eg, 10 minutes of airtime versus 20 minutes of airtime), different incentive delivery timings (airtime delivered before survey begins versus delivery upon completion of survey), different survey introductions (informational versus motivational), different narrative voices (male versus female), and different sampling frames (random digit dialing versus mobile network operator-provided numbers) to examine which study arms will yield the highest response and completion rates. Furthermore, response and completion rates and the inter-modal reliability of the IVR and CATI delivery methods will be compared.ResultsResearch activities are expected to be completed in Bangladesh, Tanzania, and Uganda in 2017.ConclusionsThis is one of the first studies to examine the feasibility of using IVR and CATI for systematic collection of NCD risk factor information in LMICs. Our findings will inform the future design and implementation of mobile phone surveys in LMICs.

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