Precipitation and Adolescent Respiratory Health in the Northeast United States.

Rationale: With more frequent and intense precipitation events across the globe due to a changing climate, there is a need to understand the relationship between precipitation and respiratory health. Precipitation may trigger asthma exacerbations, but little is known about how precipitation affects lung function and airway inflammation in early adolescents. Objectives: To determine if short-term precipitation exposure is associated with lung function and airway inflammation in early adolescents and if ever having a diagnosis of asthma modifies associations of precipitation with lung function and airway inflammation. Methods: In a prospective prebirth cohort, Project Viva, that included 1,019 early adolescents born in the northeastern United States, we evaluated associations of 1-, 2-, 3-, and 7-day moving averages of precipitation in the preceding week and forced expiratory volume in 1 second, forced vital capacity, and fractional exhaled nitric oxide (FeNO) using linear regression. We used log-transformed FeNO with effect estimates presented as percentage change. We adjusted for maternal education and household income at enrollment; any smoking in the home in early adolescence; child sex, race/ethnicity, and ever asthma diagnosis; and age, height, weight, date, and season (as sine and cosine functions of visit date) at the early adolescent visit and moving averages for mean daily temperature (same time window as exposure). Results: In fully adjusted linear models, 3- and 7-day moving averages for precipitation were positively associated with FeNO but not lung function. Every 2-mm increase in the 7-day moving average for precipitation was associated with a 4.0% (95% confidence interval, 1.1, 6.9) higher FeNO. There was evidence of effect modification by asthma status: Precipitation was associated with lower forced vital capacity and higher FeNO among adolescents with asthma. We also found that outdoor aeroallergen sensitization (immunoglobulin E against common ragweed, oak, ryegrass, or silver birch) modified associations of precipitation with FeNO, with higher FeNO in sensitized adolescents compared with nonsensitized adolescents. The associations of precipitation with FeNO were not explained by relative humidity or air pollution exposure. Conclusions: We found that greater short-term precipitation may trigger airway inflammation in adolescents, particularly among those with asthma.

Trends in Quick-Service Restaurants near Public Schools in the United States: Differences by Community, School, and Student Characteristics.

BACKGROUND: More than one-third of children and adolescents consume foods from quick-service restaurants (QSRs) daily, which is associated with an increased risk of diet-related adverse health conditions. OBJECTIVE: To examine trends in the proximity of top-selling QSR chains to all public schools across the United States between 2006 and 2018 by community-, school-, and student-level characteristics. DESIGN: This longitudinal study examined changes in the number QSRs between the 2006-2007 and 2017-2018 school years using data from National Center for Education Statistics, Infogroup US Historical Business Data, and the US Department of Agriculture's Economic Research Service. STATISTICAL ANALYSIS: A mixed-model analysis of variance using census tract as a random effect and accounting for repeated measures by school was used to examine the proximity of QSRs near schools. Models adjusted for demographic characteristics and census tract population density. Data were analyzed in 2021. RESULTS: During 2006, 9% of schools had QSRs within 400 m, and 25% of schools in the most populated areas had at least one QSR within 400 m. There were more QSRs near schools with a high percentage of poverty (12%), and near schools with high school students with the highest population of Black or African American (16%) and Hispanic or Latino (18%) students. By 2018, the percent of all public schools within 400 m of QSRs increased to 12%. The increase over time was greater near schools with a high percentage of poverty (16%) and near schools with high school students with the highest population of Black or African American students (22%) and Hispanic or Latino (23%) students. CONCLUSIONS: This is the first nationwide study to examine trends in QSR proximity to all public schools. QSRs were most likely to be located near schools with high school students, near schools with a high percentage of poverty, and near schools with a higher proportion of racial and ethnic minority students. Over time, there were greater increases in QSRs near these schools which may have important implications for children's health and diet-related disparities.

Estimating the Burden of Child Undernutrition for Smaller Electoral Units in India.

Importance: Geographic targeting of public health interventions is needed in resource-constrained developing countries. Objective: To develop methods for estimating health and development indicators across micropolicy units, using assembly constituencies (ACs) in India as an example. Design, Setting, and Participants: This cross-sectional study included children younger than 5 years who participated in the fourth National Family and Health Survey (NFHS-4), conducted between January 2015 and December 2016. Participants lived in 36 states and union territories and 640 districts in India. Children who had valid weight and height measures were selected for stunting, underweight, and wasting analysis, and children between age 6 and 59 months with valid blood hemoglobin concentration levels were included in the anemia analysis sample. The analysis was performed between February 1 and August 15, 2020. Exposures: A total of 3940 ACs were identified from the geographic location of primary sampling units in which the children's households were surveyed in NFHS-4. Main Outcomes and Measures: Stunting, underweight, and wasting were defined according to the World Health Organization Child Growth Standards. Anemia was defined as blood hemoglobin concentration less than 11.0 g/dL. Results: The main analytic sample included 222 172 children (mean [SD] age, 30.03 [17.01] months; 114 902 [51.72%] boys) from 3940 ACs in the stunting, underweight, and wasting analysis and 215 593 children (mean [SD] age, 32.63 [15.47] months; 112 259 [52.07%] boys) from 3941 ACs in the anemia analysis. The burden of child undernutrition varied substantially across ACs: from 18.02% to 60.94% for stunting, with a median (IQR) of 35.56% (29.82%-42.42%); from 10.40% to 63.24% for underweight, with a median (IQR) of 32.82% (25.50%-40.96%); from 5.56% to 39.91% for wasting, with a median (IQR) of 19.91% (15.70%-24.27%); and from 18.63% to 83.05% for anemia, with a median (IQR) of 55.74% (48.41%-63.01%). The degree of inequality within states varied across states; those with high stunting, underweight, and wasting prevalence tended to have high levels of inequality. For example, Uttar Pradesh, Jharkhand, and Karnataka had high mean AC-level prevalence of child stunting (Uttar Pradesh, 45.29%; Jharkhand, 43.76%; Karnataka, 39.77%) and also large SDs (Uttar Pradesh, 6.90; Jharkhand, 6.02; Karnataka, 6.72). The Moran I indices ranged from 0.25 to 0.80, indicating varying levels of spatial autocorrelation in child undernutrition across the states in India. No substantial difference in AC-level child undernutrition prevalence was found after adjusting for possible random displacement of geographic location data. Conclusions and Relevance: In this cross-sectional study, substantial inequality in child undernutrition was found across ACs in India, suggesting the importance of considering local electoral units in designing targeted interventions. The methods presented in this paper can be further applied to measuring health and development indicators in small electoral units for enhanced geographic precision of public health data in developing countries.

Precision mapping child undernutrition for nearly 600,000 inhabited census villages in India.

There are emerging opportunities to assess health indicators at truly small areas with increasing availability of data geocoded to micro geographic units and advanced modeling techniques. The utility of such fine-grained data can be fully leveraged if linked to local governance units that are accountable for implementation of programs and interventions. We used data from the 2011 Indian Census for village-level demographic and amenities features and the 2016 Indian Demographic and Health Survey in a bias-corrected semisupervised regression framework to predict child anthropometric failures for all villages in India. Of the total geographic variation in predicted child anthropometric failure estimates, 54.2 to 72.3% were attributed to the village level followed by 20.6 to 39.5% to the state level. The mean predicted stunting was 37.9% (SD: 10.1%; IQR: 31.2 to 44.7%), and substantial variation was found across villages ranging from less than 5% for 691 villages to over 70% in 453 villages. Estimates at the village level can potentially shift the paradigm of policy discussion in India by enabling more informed prioritization and precise targeting. The proposed methodology can be adapted and applied to diverse population health indicators, and in other contexts, to reveal spatial heterogeneity at a finer geographic scale and identify local areas with the greatest needs and with direct implications for actions to take place.

Estimating the burden of child malnutrition across parliamentary constituencies in India: A methodological comparison.

In India, data on key developmental indicators used to formulate policies and interventions are routinely available for the administrative unit of districts but not for the political unit of parliamentary constituencies (PC). Recently, Swaminathan et al. proposed two methodologies to generate PC estimates using randomly displaced GPS locations of the sampling clusters ('direct') and by building a crosswalk between districts and PCs using boundary shapefiles ('indirect'). We advance these methodologies by using precision-weighted estimations based on hierarchical logistic regression modeling to account for the complex survey design and sampling variability. We exemplify this application using the latest National Family Health Survey (NFHS, 2016) to generate PC-level estimates for two important indicators of child malnutrition - stunting and low birth weight - that are being monitored by the Government of India for the National Nutrition Mission targets. Overall, we found a substantial variation in child malnutrition across 543 PCs. The different methodologies yielded highly consistent estimates with correlation ranging r = 0.92-0.99 for stunting and r = 0.81-0.98 for low birth weight. For analyses involving data with comparable nature to the NFHS (i.e., complex data structure and possibility to identify a potential PC membership), modeling for precision-weighted estimates and direct methodology are preferable. Further field work and data collection at the PC level are necessary to accurately validate our estimates. An ideal solution to overcome this gap in data for PCs would be to make PC identifiers available in routinely collected surveys and the Census.

Association of Prenatal Exposure to Population-Wide Folic Acid Fortification With Altered Cerebral Cortex Maturation in Youths.

Importance: Presently, 81 countries mandate the fortification of grain products with folic acid to lessen the risk of neural tube defects in the developing fetus. Epidemiologic data on severe mental illness suggest potentially broader effects of prenatal folate exposure on postnatal brain development, but this link remains unsubstantiated by biological evidence. Objective: To evaluate associations among fetal folic acid exposure, cortical maturation, and psychiatric risk in youths. Design, Setting, and Participants: A retrospective, observational clinical cohort study was conducted at Massachusetts General Hospital (MGH) among 292 youths 8 to 18 years of age born between January 1993 and December 2001 (inclusive of folic acid fortification rollout ±3.5 years) with normative results of clinical magnetic resonance imaging, divided into 3 age-matched groups based on birthdate and related level of prenatal folic acid fortification exposure (none, partial, or full). Magnetic resonance imaging was performed between January 2005 and March 2015. Two independent, observational, community-based cohorts (Philadelphia Neurodevelopmental Cohort [PNC] and National Institutes of Health Magnetic Resonance Imaging Study of Normal Brain Development [NIH]) comprising 1078 youths 8 to 18 years of age born throughout (PNC, 1992-2003) or before (NIH, 1983-1995) the rollout of folic acid fortification were studied for replication, clinical extension, and specificity. Statistical analysis was conducted from 2015 to 2018. Exposures: United States-mandated grain product fortification with folic acid, introduced in late 1996 and fully in effect by mid-1997. Main Outcomes and Measures: Differences in cortical thickness among nonexposed, partially exposed, and fully exposed youths (MGH) and underlying associations between age and cortical thickness (all cohorts). Analysis of the PNC cohort also examined the association of age-cortical thickness slopes with the odds of psychotic symptoms. Results: The MGH cohort (139 girls and 153 boys; mean [SD] age, 13.3 [2.3] years) demonstrated exposure-associated cortical thickness increases in bilateral frontal and temporal regions (9.9% to 11.6%; corrected P < .001 to P = .03) and emergence of quadratic (delayed) age-associated thinning in temporal and parietal regions (ß = -11.1 to -13.9; corrected P = .002). The contemporaneous PNC cohort (417 girls and 444 boys; mean [SD] age, 13.5 [2.7] years) also exhibited exposure-associated delays of cortical thinning (ß = -1.59 to -1.73; corrected P < .001 to P = .02), located in similar regions and with similar durations of delay as in the MGH cohort. Flatter thinning profiles in frontal, temporal, and parietal regions were associated with lower odds of psychosis spectrum symptoms in the PNC cohort (odds ratio, 0.37-0.59; corrected P < .05). All identified regions displayed earlier thinning in the nonexposed NIH cohort (118 girls and 99 boys; mean [SD] age, 13.3 [2.6] years). Conclusions and Relevance: The results of this study suggest an association between gestational exposure to fortification of grain products with folic acid and altered cortical development and, in turn, with reduction in the risk of psychosis in youths.

Evaluation of the positional difference between two common geocoding methods.

Geocoding, the process of matching addresses to geographic coordinates, is a necessary first step when using geographical information systems (GIS) technology. However, different geocoding methodologies can result in different geographic coordinates. The objective of this study was to compare the positional (i.e. longitude/latitude) difference between two common geocoding methods, i.e. ArcGIS (Environmental System Research Institute, Redlands, CA, USA) and Batchgeo (freely available online at http://www.batchgeo.com). Address data came from the YMCA-Harvard After School Food and Fitness Project, an obesity prevention intervention involving children aged 5-11 years and their families participating in YMCA-administered, after-school programmes located in four geographically diverse metropolitan areas in the USA. Our analyses include baseline addresses (n = 748) collected from the parents of the children in the after school sites. Addresses were first geocoded to the street level and assigned longitude and latitude coordinates with ArcGIS, version 9.3, then the same addresses were geocoded with Batchgeo. For this analysis, the ArcGIS minimum match score was 80. The resulting geocodes were projected into state plane coordinates, and the difference in longitude and latitude coordinates were calculated in meters between the two methods for all data points in each of the four metropolitan areas. We also quantified the descriptions of the geocoding accuracy provided by Batchgeo with the match scores from ArcGIS. We found a 94% match rate (n = 705), 2% (n = 18) were tied and 3% (n = 25) were unmatched using ArcGIS. Forty-eight addresses (6.4%) were not matched in ArcGIS with a match score ≥80 (therefore only 700 addresses were included in our positional difference analysis). Six hundred thirteen (87.6%) of these addresses had a match score of 100. Batchgeo yielded a 100% match rate for the addresses that ArcGIS geocoded. The median for longitude and latitude coordinates for all the data was just over 25 m. Overall, the range for longitude was 0.04-12,911.8 m, and the range for latitude was 0.02-37,766.6 m. Comparisons show minimal differences in the median and minimum values, while there were slightly larger differences in the maximum values. The majority (>75%) of the geographic differences were within 50 m of each other; mostly <25 m from each other (about 49%). Only about 4% overall were ≥400 m apart. We also found geographic differences in the proportion of addresses that fell within certain meter ranges. The match-score range associated with the Batchgeo accuracy level "approximate" (least accurate) was 84-100 (mean = 92), while the "rooftop" Batchgeo accuracy level (most accurate) delivered a mean of 98.9 but the range was the same. Although future research should compare the positional difference of Batchgeo to criterion measures of longitude/latitude (e.g. with global positioning system measurement), this study suggests that Batchgeo is a good, free-of-charge option to geocode addresses.