NYC FITNESSGRAM: Population-Level Physical Fitness Surveillance for New York City Youth.

NYC FITNESSGRAM, monitored by the New York City (NYC) Department of Education and the NYC Department of Health and Mental Hygiene, functions as the NYC Department of Education's citywide youth fitness surveillance program. Here we present the methods, characteristics, and data used in this surveillance system to monitor physical fitness in public school students (grades kindergarten through 12; initiated in 2006; n = 6,748,265 observations; mean sample of 519,097 observations per year to date) in New York, New York. Youth physical fitness prevalence estimates, longitudinal trends, and spatial analyses may be investigated using continuous fitness composite percentile scores and Cooper Institute for Aerobic Research-defined sex- and age-specific Healthy Fitness Zones. Healthy Fitness Zones are based on individual-child fitness test performance, with standard errors clustered at the school and student levels and adjusted for sociodemographic characteristics. Results may be used to show trends in youth fitness attainment over time and highlight disparities in the fitness prevalence of NYC students. In sum, continuous fitness composite percentile scores offer the opportunity for prospective tracking of shifts in youth physical fitness on a population scale and across subpopulations. NYC FITNESSGRAM can accompany a growing body of surveillance tools demonstrating the potential for population-level surveillance tools to promote global public health.

Longitudinal Associations Between Neighborhood Child Opportunity and Physical Fitness for New York City Public School Youth.

Neighborhood environments can support fitness-promoting behavior, yet little is known about their influence on youth physical fitness outcomes over time. We examined longitudinal associations between neighborhood opportunity and youth physical fitness among New York City (NYC) public school youth. The Child Opportunity Index (COI), a composite index of 29 indicators measuring neighborhood opportunity at the census-tract level, along with scores on 4 selected COI indicators were linked to NYC FITNESSGRAM youth data at baseline. Fitness outcomes (measured annually, 2011-2018) included body mass index, curl-ups, push-ups, and Progressive Aerobic Cardiovascular Endurance Run (PACER) laps. Unstratified and age-stratified, adjusted, 3-level generalized linear mixed models, nested by census tract and time, estimated the association between COI and fitness outcomes. The analytical sample (n = 204,939) lived in very low (41%) or low (30%) opportunity neighborhoods. Unstratified models indicated that overall COI is modestly associated with improved youth physical fitness outcomes. The strongest opportunity-fitness associations were observed for PACER. Stratified models show differences in associations across younger vs. older youth. We find that neighborhood factors are associated with youth fitness outcomes over time, with the strength of the associations dependent on age. Future implications include better informed place-based interventions tailored to specific life stages to promote youth health.

School-level self-reported versus objective measurements of body mass index in public high school students.

Population-level surveillance of student weight status (particularly monitoring students with a body mass index (BMI) ≥95th percentile) remains of public health interest. However, there is mounting concern about objectively measuring student BMI in schools. Using data from the nation's largest school district, we determined how closely students' self-reported BMI approximates objectively-measured BMI, aggregated at the school level, to inform decision-making related to school BMI measurement practices. Using non-matched data from n = 82,543 students with objective height/weight data and n = 7676 with self-reported height/weight from 84 New York City high schools (88% non-white and 75% free or reduced-price meal-eligible enrollment), we compared school-level mean differences in height, weight, BMI, and proportion of students by weight status, between objective and self-reported measures. At the school-level, the self-reported measurement significantly underestimated weight (-1.38 kg; 95% CI: -1.999, -0.758) and BMI (-0.38 kg/m2; 95% CI: -0.574, -0.183) compared to the objective measurement. Based on the objective measurement, 12.1% of students were classified as having obesity and 6.3% as having severe obesity (per CDC definition); the self-report data yielded 2.5 (95% CI: -1.964, -0.174) and 1.4 (95% CI: -2.176, -0.595) percentage point underestimates in students with obesity and severe obesity, respectively. This translates to 13% of students with obesity and 21% of students with severe obesity being misclassified if using self-reported BMI. School-level high school students' self-reported data underestimate the prevalence of students with obesity and severe obesity and is particularly poor at identifying highest-risk students based on BMI percentile.

The longitudinal association between asthma severity and physical fitness among new York City public school youth.

Severe persistent childhood asthma is associated with low physical activity and may be associated with poor physical fitness. Research on the asthma severity-fitness association longitudinally and across sociodemographic subgroups is needed to inform fitness interventions targeting youth with asthma. We evaluated the relationship between asthma severity (categorized as severe, mild, or no asthma) and subsequent fitness in New York City (NYC) public school youth enrolled in grades 4-12 using the NYC Fitnessgram dataset (2010-2018). Longitudinal mixed models with random intercepts were fit to test the association between asthma severity and one-year lagged fitness z-scores by clustering repeated annual observations at the student level. Models were adjusted for sex, race/ethnicity, grade level, poverty status, time, and stratified by sociodemographic factors. The analytic sample included 663,137 students (51% male; 31% non-Hispanic Black, 40% Hispanic; 55% in grades 4-8, 70% high poverty; 87%, 11% and 1% with no, mild, and severe asthma, respectively). Students with severe asthma and mild asthma demonstrated -0.19 (95% CI, -0.20 to -0.17) and - 0.10 (95% CI, -0.11 to -0.10), respectively, lower fitness z-scores in the subsequent year relative to students without asthma. After stratifying by demographics, the magnitude of the asthma severity-fitness relationship was highest for non-Hispanic white vs. all other racial/ethnic subgroups, and was similar across sex, grade level, and household poverty status. Overall, we observed an inverse longitudinal relationship between asthma severity and subsequent fitness among urban youth, particularly non-Hispanic Whites. Future research should examine how neighborhood-level factors impact the asthma severity-fitness relationship across racial/ethnic subgroups.

Severe obesity and fitness in New York City public school youth, 2010-2018.

BACKGROUND: Obesity is associated with poorer youth fitness. However, little research has examined the magnitude of this relationship in youth with severe obesity. Therefore, we sought to determine the relationship between increasing weight status and fitness within a sample of children and adolescents from New York City public schools. METHODS: This study utilized longitudinal data from the NYC Fitnessgram dataset years 2010-2018. Height and weight along with fitness were measured annually during physical education classes. Severity of obesity was defined using body mass index relative to the 95th percentile and then categorized into classes. A composite measure of fitness was calculated based on scores for three fitness tests: aerobic capacity, muscular strength, and muscular endurance. To examine the weight status-fitness relationship, repeated measures mixed models with random-intercepts were constructed. Stratified models examined differences by demographic factors. RESULTS: The sample included 917,554 youth (51.8% male, 39.3% Hispanic, 29.9% non-Hispanic Black, 14.0%, 4.6%, and 1.6% class I, II and III obesity, respectively). Compared to youth with healthy weight, increasing severity of obesity was associated with decreased fitness: overweight (ß = - 0.28, 95% CI:-0.29;-0.28), class I obesity (ß = - 0.60, 95% CI:-0.60; - 0.60), class II obesity (ß = - 0.94, 95% CI:-0.94; - 0.93), and class III obesity (ß = - 1.28; 95% CI:-1.28; - 1.27). Stratified models showed the association was stronger among male and non-Hispanic White youth. CONCLUSION: Findings revealed that more severe obesity was associated with lower fitness. Future research is needed to develop targeted interventions to improve fitness in youth with obesity.

The Association of School Nurse Workload With Student Health and Academic Outcomes: A Cross-Sectional Study.

This study assessed associations between school nurse workload and student health and academic outcomes. We hypothesized that lower school nurse workload would be associated with better student outcomes, with associations being greater for members of groups who experience health disparities. Our methods entailed secondary analysis of data for New York City school students in kindergarten through 12th grade during 2015-2016 (N = 1,080,923), using multilevel multivariate regression as the analytic approach. Results demonstrated lower school nurse workload was associated with better outcomes for student participation in asthma education but not chronic absenteeism, early dismissals, health office visits, immunization compliance, academic achievement, or overweight/obesity. Our findings suggest school nurses may influence proximal outcomes, such as participation in disease-related education, more easily than downstream outcomes, such as absenteeism or obesity. While contrary to our hypotheses, results align with the fact that school nurses deliver community-based, population health-focused care that is inherently complex, multilevel, and directly impacted by social determinants of health. Future research should explore school nurses' perspectives on what factors influence their workload and how they can best impact student outcomes.

Exposure to urban green space may both promote and harm mental health in socially vulnerable neighborhoods: A neighborhood-scale analysis in New York City.

BACKGROUND: There is growing evidence that exposure to green space can impact mental health, but these effects may be context dependent. We hypothesized that associations between residential green space and mental health can be modified by social vulnerability. METHOD: We conducted an ecological cross-sectional analysis to evaluate the effects of green space exposure on mental disorder related emergency room (ER) visits in New York City at the level of census tract. To objectively represent green space exposure at the neighborhood scale, we calculated three green space exposure metrics, namely proximity to the nearest park, percentage of green space, and visibility of greenness. Using Bayesian hierarchical spatial Poisson regression models, we evaluated neighborhood social vulnerability as a potential modifier of greenness-mental disorder associations, while accounting for the spatially correlated structures. RESULTS: We found significant associations between green space exposure (involving both proximity and visibility) and total ER visits for mental disorders in neighborhoods with high social vulnerability, but no significant associations in neighborhoods with low social vulnerability. We also identified specific neighborhoods with particularly high ER utilization for mental disorders. CONCLUSIONS: Our findings suggest that exposure to green space is associated with ER visits for mental disorders, but that neighborhood social vulnerability can modify this association. Future research is needed to confirm our finding with longitudinal designs at the level of individuals.

Population-Based Estimates of Coronavirus Disease 2019 (COVID-19)-like Illness, COVID-19 Illness, and Rates of Case Ascertainment, Hospitalizations, and Deaths-Noninstitutionalized New York City Residents, March-April 2020.

Using a population-based, representative telephone survey, ~930 000 New York City residents had COVID-19 illness beginning 20 March-30 April 2020, a period with limited testing. For every 1000 persons estimated with COVID-19 illness, 141.8 were tested and reported as cases, 36.8 were hospitalized, and 12.8 died, varying by demographic characteristics.

ZIP Code-Level Estimates from a Local Health Survey: Added Value and Limitations.

We assessed the added value and limitations of generating directly estimated ZIP Code-level estimates by aggregating 5 years of data from an annual cross-sectional survey, the New York City Community Health Survey (n = 44,886) from 2009 to 2013, that were designed to provide reliable estimates only of larger geographies. Survey weights generated directly-observed ZIP Code (n = 128) level estimates. We assessed the heterogeneity of ZIP Code-level estimates within coarser United Hospital Fund (UHF) neighborhood areas (n = 34) by using the Rao-Scott Chi-Square test and one-way ANOVA. Orthogonal linear contrasts assessed whether there were linear trends at the UHF level from 2009 to 2013. 22 of 37 health indicators were reliable in over 50% of ZIP Codes. 14 of the 22 variables showed heterogeneity in ≥4 UHFs. Variables for drinking, nutrition, and HIV testing showed heterogeneity in the most UHFs (9-24 UHFs). In half of the 32 UHFs, >20% variables had within-UHF heterogeneity. Flu vaccination and sugary beverage consumption showed significant time trends in the largest number of UHFs (12 or more UHFs). Overall, heterogeneity of ZIP Code-level estimates suggests that there is value in aggregating 5 years of data to make direct small area estimates.

The impact of change in neighborhood poverty on BMI trajectory of 37,544 New York City youth: a longitudinal study.

BACKGROUND: Neighborhood poverty may increase childhood obesity risk. However, evidence for the neighborhood poverty-obesity relationship is limited. The purpose of this study was to examine how moving to a higher or lower poverty neighborhood impacts body mass index (BMI) z-score trajectories among youth, with the goal of informing policy change, interventions, and clinical practices to reduce childhood obesity. METHODS: Methods entailed secondary analysis of existing longitudinal data. The sample included youth attending New York City public schools in grades kindergarten through twelfth from school years 2006/2007 through 2016/2017. Eligibility criteria included moving to a higher or lower poverty neighborhood during the data midpoint [school years 2010/2011 through 2013/2014] of the 12-year data-period; New York City-specific metrics were used to define both neighborhood (Neighborhood Tabulation Area) and relevant neighborhood poverty levels (< 5, 5 to < 10%, 10 to < 20%, 20 to < 30%, 30 to < 40% and ≥ 40% of individuals below Federal Poverty Level). Two-piece latent growth curve models were used to describe BMI z-score trajectories of youth who moved to higher versus lower poverty neighborhoods, with propensity score weighting to account for preexisting differences between the two groups. Primary analyses were stratified by sex and exploratory subgroup analyses were stratified by sex and developmental stage (early childhood, middle childhood, and adolescence) to explore sensitive periods for neighborhood poverty exposure. RESULTS: Of 532,513 youth with home address data, 18,370 youth moved to a higher poverty neighborhood and 19,174 moved to a lower poverty neighborhood (n = 37,544). Females and males who moved to a higher poverty neighborhood experienced less favorable BMI z-score trajectories for obesity risk, though effects were small. Exploratory subgroup analyses demonstrated that negative effects of neighborhood poverty were most pronounced among young and adolescent females and young males, whereas effects were mixed for other subgroups. CONCLUSIONS: Youth who moved to higher poverty neighborhoods experienced less favorable BMI z-score trajectories for obesity risk, though effects were small and most consistent for females and younger youth. Additional research is needed to illuminate neighborhood poverty's impact on obesity, in order to inform policy, intervention, clinical, and research efforts to reduce obesity and improve child well-being.

The effects of student, school and neighborhood poverty on the association between fitness and absenteeism in New York City middle school youth.

Recent research demonstrates that youth fitness improvements are associated with lower absenteeism. This study assessed whether the effects of poverty on the longitudinal fitness-absenteeism relationship are consistent across poverty measures at the student, school, and neighborhood levels and across sex in New York City (NYC) public school youth individually followed over 4 years. Negative binomial longitudinal mixed models with random-intercepts were developed stratified by five dichotomized student, school and neighborhood poverty measures and sex to test the change in fitness-lagged absenteeism relationship in six cohorts of NYC middle school students (2006/7-2012/13). Models were adjusted for individual-level race/ethnicity, place of birth, change in obesity status, grade, time, and school size. The sample included 360,743 students (51% male, 39% Hispanic, 28% non-Hispanic black, 69% qualifying for free/reduced price school meals). Adjusted estimates showed an inverse dose-response fitness-absenteeism relationship in high poverty youth across all poverty measures, including the student, school and neighborhood levels. For example, in girls exposed to high poverty based on school neighborhood, absenteeism decreased by 11.3% (IRR = -0.12, 95% CI: -0.20, -0.04), 10.4% (IRR = -0.11, 95% CI: -0.21, -0.02), 6.8% (IRR = -0.07, 95% CI: -0.14, 0.00) and 4.9% (IRR = -0.05, 95% CI: -0.15, 0.04) for students who had a >20% increase, 10-20% increase, <10% change, and 10-20% decrease in fitness from the prior year, respectively, relative to the reference group (>20% decrease in fitness). Future research should explore the impact of tailored interventions for youth that aim to promote youth physical activity at each of the individual, school and neighborhood levels, and particularly among high poverty subgroups.

Individual-Level Fitness and Absenteeism in New York City Middle School Youths, 2006-2013.

INTRODUCTION: Youth health-related fitness positively affects academic outcomes, although limited research has focused on the relationship between fitness and school absenteeism. We examined the longitudinal association between individual children's fitness and lagged school absenteeism over 4 years in urban middle schools. METHODS: Six cohorts of New York City public school students were followed from grades 5 through 8 (school years 2006-2007 through 2012-2013; n = 349,381). A 3-level longitudinal generalized linear mixed model was used to test the association of change in fitness composite percentile scores and 1-year lagged child-specific days absent. RESULTS: Adjusted 3-level negative binomial models showed that students with a more than 20% increase, 10% to 20% increase, less than 10% increase or decrease, and 10% to 20% decrease in fitness from the year prior had 11.9% (95% confidence interval [CI], 7.2-16.8), 6.1% (95% CI, 1.0-11.4), 2.6% (95% CI, -1.1 to 6.5), and 0.4% (95% CI, -4.3 to 5.4) lower absenteeism compared with students with a more than 20% fitness decrease. CONCLUSION: Cumulative effects of fitness improvement could have a significant impact on child absenteeism over time, particularly in high-need subgroups. Future research should examine the potential for school-based fitness interventions to reduce absenteeism rates, particularly for youths who have fitness drop-offs in adolescence.

Relationship between Recreational Resources in the School Neighborhood and Changes in Fitness in New York City Public School Students.

Physical fitness in children has many beneficial effects, including the maintenance of a healthy weight. The built environment may influence youths' physical fitness by encouraging physical activity. This paper assessed whether higher density of parks, playgrounds, and sports facilities around a school is related to improvements in fitness in middle school boys and girls. Fitness scores and other student covariates collected as part of NYC FITNESSGRAM between the 2006-2007 and 2010-2011 school years were linked with school neighborhood data on characteristics of the built environment for NYC public school students in grades 6-8. Data were analyzed in 2015. Medium, but not high, density of recreational resources in the area surrounding a school was associated with greater annual improvements in fitness for both boys and girls. This association appeared to be driven mainly by the presence of parks. Findings for sports facilities and playgrounds were inconsistent. Overall, few associations were observed between recreational resources near a school and changes in student fitness. Future studies of school influences on student fitness should consider the influence of school resources and the home neighborhood.

Estimating Potential Reductions in Premature Mortality in New York City From Raising the Minimum Wage to $15.

OBJECTIVES: To assess potential reductions in premature mortality that could have been achieved in 2008 to 2012 if the minimum wage had been $15 per hour in New York City. METHODS: Using the 2008 to 2012 American Community Survey, we performed simulations to assess how the proportion of low-income residents in each neighborhood might change with a hypothetical $15 minimum wage under alternative assumptions of labor market dynamics. We developed an ecological model of premature death to determine the differences between the levels of premature mortality as predicted by the actual proportions of low-income residents in 2008 to 2012 and the levels predicted by the proportions of low-income residents under a hypothetical $15 minimum wage. RESULTS: A $15 minimum wage could have averted 2800 to 5500 premature deaths between 2008 and 2012 in New York City, representing 4% to 8% of total premature deaths in that period. Most of these avertable deaths would be realized in lower-income communities, in which residents are predominantly people of color. CONCLUSIONS: A higher minimum wage may have substantial positive effects on health and should be considered as an instrument to address health disparities.

Ten-year cancer incidence in rescue/recovery workers and civilians exposed to the September 11, 2001 terrorist attacks on the World Trade Center.

BACKGROUND: Cancer incidence in exposed rescue/recovery workers (RRWs) and civilians (non-RRWs) was previously reported through 2008. METHODS: We studied occurrence of first primary cancer among World Trade Center Health Registry enrollees through 2011 using adjusted standardized incidence ratios (SIRs), and the WTC-exposure-cancer association, using Cox proportional hazards models. RESULTS: All-cancer SIR was 1.11 (95% confidence interval (CI) 1.03-1.20) in RRWs, and 1.08 (95% CI 1.02-1.15) in non-RRWs. Prostate cancer and skin melanoma were significantly elevated in both populations. Thyroid cancer was significantly elevated only in RRWs while breast cancer and non-Hodgkin's lymphoma were significantly elevated only in non-RRWs. There was a significant exposure dose-response for bladder cancer among RRWs, and for skin melanoma among non-RRWs. CONCLUSIONS: We observed excesses of total and specific cancers in both populations, although the strength of the evidence for causal relationships to WTC exposures is somewhat limited. Continued monitoring of this population is indicated. Am. J. Ind. Med. 59:709-721, 2016. © 2016 Wiley Periodicals, Inc.

Reaching children never previously vaccinated for influenza through a school-located vaccination program.

OBJECTIVES: We determined the success of the school-located vaccination (SLV) program, implemented in 2009 in New York City to deliver pandemic influenza A (H1N1) monovalent vaccine (pH1N1), versus provider offices in reaching children who had never previously received influenza vaccine. METHODS: We compared the immunization history of children vaccinated in school versus provider offices. We included records in the Citywide Immunization Registry with pH1N1 administered between October 2009 and March 2010 to elementary school-aged children. RESULTS: In total, 96,524 children received pH1N1 vaccine in schools, and 102,933 children received pH1N1 vaccine in provider offices. Of children vaccinated in schools, 34% had never received seasonal influenza vaccination in the past, compared with only 10% of children vaccinated at provider offices (P < .001). Children vaccinated in schools were more likely to have received a second dose of pH1N1 in 2009-2010 than those vaccinated in provider offices (80% vs 45%). CONCLUSIONS: The SLV program was more successful at reaching children who had never received influenza immunization in the past and should be considered as a strategy for delivering influenza vaccine in routine and emergency situations.

Description of a school nurse visit syndromic surveillance system and comparison to emergency department visits, New York City.

OBJECTIVES: We compared school nurse visit syndromic surveillance system data to emergency department (ED) visit data for monitoring illness in New York City schoolchildren. METHODS: School nurse visit data recorded in an electronic health record system are used to conduct daily surveillance of influenza-like illness, fever-flu, allergy, asthma, diarrhea, and vomiting syndromes. We calculated correlation coefficients to compare the percentage of syndrome visits to the school nurse and ED for children aged 5 to 14 years, from September 2006 to June 2011. RESULTS: Trends in influenza-like illness correlated significantly (correlation coefficient = 0.89; P < .001) and 72% of school signals occurred on days that ED signaled. Trends in allergy (correlation coefficient = 0.73; P < .001) and asthma (correlation coefficient = 0.56; P < .001) also correlated and school signals overlapped with ED signals on 95% and 51% of days, respectively. Substantial daily variation in diarrhea and vomiting visits limited our ability to make comparisons. CONCLUSIONS: Compared with ED syndromic surveillance, the school nurse system identified similar trends in influenza-like illness, allergy, and asthma syndromes. Public health practitioners without school-based surveillance may be able to use age-specific analyses of ED syndromic surveillance data to monitor illness in schoolchildren.

Reassessing Google Flu Trends data for detection of seasonal and pandemic influenza: a comparative epidemiological study at three geographic scales.

The goal of influenza-like illness (ILI) surveillance is to determine the timing, location and magnitude of outbreaks by monitoring the frequency and progression of clinical case incidence. Advances in computational and information technology have allowed for automated collection of higher volumes of electronic data and more timely analyses than previously possible. Novel surveillance systems, including those based on internet search query data like Google Flu Trends (GFT), are being used as surrogates for clinically-based reporting of influenza-like-illness (ILI). We investigated the reliability of GFT during the last decade (2003 to 2013), and compared weekly public health surveillance with search query data to characterize the timing and intensity of seasonal and pandemic influenza at the national (United States), regional (Mid-Atlantic) and local (New York City) levels. We identified substantial flaws in the original and updated GFT models at all three geographic scales, including completely missing the first wave of the 2009 influenza A/H1N1 pandemic, and greatly overestimating the intensity of the A/H3N2 epidemic during the 2012/2013 season. These results were obtained for both the original (2008) and the updated (2009) GFT algorithms. The performance of both models was problematic, perhaps because of changes in internet search behavior and differences in the seasonality, geographical heterogeneity and age-distribution of the epidemics between the periods of GFT model-fitting and prospective use. We conclude that GFT data may not provide reliable surveillance for seasonal or pandemic influenza and should be interpreted with caution until the algorithm can be improved and evaluated. Current internet search query data are no substitute for timely local clinical and laboratory surveillance, or national surveillance based on local data collection. New generation surveillance systems such as GFT should incorporate the use of near-real time electronic health data and computational methods for continued model-fitting and ongoing evaluation and improvement.

The impact of neighborhood park access and quality on body mass index among adults in New York City.

OBJECTIVE: To evaluate the association between adult individuals' body mass index (BMI) and characteristics of parks (size and cleanliness) in an urban environment taking into account the physical and social environments of the neighborhood. METHODS: Cross-sectional, hierarchical linear models were used to determine whether park effects were associated with BMI using self-reported height and weight data obtained from the Community Health Survey in New York City (2002-2006). RESULTS: Both the proportion of the residential zip code that was large park space and the proportion that was small park space had significant inverse associations with BMI after controlling for individual socio-demographic and zip code built environment characteristics (-0.20 BMI units across the inter-quartile range (IQR) for large parks, 95% CI -0.32, -0.08; -0.21 BMI units across the IQR for small parks, 95% CI -0.31, -0.10, respectively). Poorer scores on the park cleanliness index were associated with higher BMI, 0.18 BMI units across the IQR of the park cleanliness index (95% CI 0.05, 0.30). CONCLUSIONS: This study demonstrated that proportion of neighborhoods that was large or small park space and park cleanliness were associated with lower BMI among NYC adults after adjusting for other neighborhood features such as homicides and walkability, characteristics that could influence park usage.

Severe obesity among children in New York City public elementary and middle schools, school years 2006-07 through 2010-11.

INTRODUCTION: Although studies have shown that childhood obesity overall is on the decline among New York City (NYC) public school children, the prevalence of severe childhood obesity has not been studied. METHODS: We used height and weight measurements of 947,765 NYC public school students aged 5 to 14 years in kindergarten through 8th grade (K-8), from school years 2006-07 through 2010-11. We used age- and sex-specific body mass index (BMI) percentiles according to Centers for Disease Control and Prevention growth charts to define childhood obesity (BMI ≥ 95th percentile) and severe childhood obesity (BMI ≥120% of 95th percentile) and to identify biologically implausible values (BIV). Multivariable logistic models tested for trends in obesity and severe obesity prevalence. To evaluate misclassification, we recalculated prevalence estimates for the most recent school year (2010-11) including the student records identified as BIV who were also declared severely obese (BMI ≥ 120% of 95th percentile). We refer to this subgroup of BIVs as "high BIV." RESULTS: Severe obesity among NYC public school students in grades K-8 decreased 9.5% from the 2006-07 school year (6.3%) to the 2010-11 school year (5.7%), and obesity decreased 5.5% (from 21.9% to 20.7%). The prevalence of severe obesity and obesity was highest among minority, poor, and male children. Severe obesity declined in prevalence among every subgroup, with the greatest effect among white students and wealthy students. Severe obesity prevalence increased with age, and obesity prevalence peaked among those aged 7 to 10 years. For the 2010-11 school year, including high BIVs increased severe obesity prevalence from 5.7% to 6.6% and increased obesity prevalence from 20.7% to 21.5%. CONCLUSION: Among all subgroups of NYC public school children in grades K-8, the reduction in severe obesity was greater than the reduction in overall obesity. Efforts to decrease obesity in NYC have affected the severely obese; however, monitoring of this specific subgroup should continue because of differences in trends and greater health risks.