Prevalence of overweight and risk of overweight among 3- to 5-year-old Chicago children, 2002-2003.
It is not yet known how the health consequences of childhood obesity will affect schools and society at large. Will schools need to shoulder more health care responsibilities as more school-aged children develop serious associated conditions? Will we see--and need to deal with--more chronic disease at young ages? For example, will there be a greatly increased need for liver transplants for persons in their early 20s? What will be the health and economic consequences of taking blood pressure or cholesterol medication over decades? To answer these and related questions, it is necessary to describe and monitor the epidemic and those it affects.
The first step in addressing child overweight as a public health issue is to examine the epidemiologic data (the prevalence and geographic and demographic distribution of child overweight). This knowledge is critical to the development of effective prevention, treatment, and management strategies to address the health, social, and emotional problems associated with child overweight. For example, data on child overweight patterns can help school administrators to design and implement school-based prevention and intervention programs, assist health care service providers in developing better services, and guide communities as they undertake to deal with obesity in their children.
National Health and Nutrition Examination Survey (NHANES) data indicate that, nationally, the prevalence of overweight among children aged 2-5 years has more than doubled since 1971, as shown in Figure 1. (11,12) The Early Childhood Longitudinal Study (ECLS) data for 1998-1999 showed a prevalence of overweight for children aged 5-7 years of 11.1% nationally and 8.1% in the Midwest region.(13) (NHANES and ECLS data are not analyzable at the Chicago level because of sampling limitations.)
Existing data on child overweight in Chicago have limitations. The Sinai Health System's Improving Community Health Survey reported alarming rates of overweight for children aged 2-12 years from a low rate of 15% to a high rate of 55% in the 6 community areas surveyed (Unpublished report, "Sinai Health System's Improving Community Health Survey Report, January 2004). However, these data focus on older children, represent only 6 of the 77 Chicago community areas, and are based on parent reports and not actual measurements.
The WIC (Women, Infants, and Children) program, a nutrition assistance program serving pregnant women and children younger than 6 years, provide data on prevalence of overweight among children. However, these data include only low-income families and so are not representative of the population at large.
The Consortium to Lower Obesity in Chicago Children (CLOCC, www.clocc.net) was formed in 2003 to foster a local, multilevel, multisector effort to protect Chicago children from the epidemic of obesity; its focus is on children aged 3-5 years and their families. The absence of data on local patterns of obesity was an obstacle to this work.
To fill the information gap, CLOCC, in cooperation with Chicago Public Schools (CPS) and the Archdiocese of Chicago, conducted a survey of heights and weights in CPS and Archdiocese of Chicago schools, including children 3-5 years of age. The objective was to obtain baseline data on child weight status: to measure progress against future years and to guide strategy development for targeting resources to the populations with the most need.
This article reports the findings of the CLOCC school survey and so provides the first estimates of measured overweight prevalence in Chicago children entering school. Chicago data are compared with those from NHANES and ECLS.
This study was approved by the Children's Memorial Research Center (CMRC) Institutional Review Board. Data collection began in May 2003 and concluded in December 2003.
The data were from 2 separate convenience samples of children aged 3-5 years attending either 18 CPS or 10 Chicago Catholic School pre-K programs. Sample 1 included 1172 children at CPS sites (2002-2003 school year). Schools were selected by CPS administrators on the basis of the availability of school nurses to participate in data collection. Sample 2 included 345 children at Chicago Catholic schools (2003-2004 school year). Schools were selected by researchers on the basis of geographic diversity and the demographic characteristics of the Chicago community areas in which they are located.
Figure 2 maps the distribution of community areas in the sample. Areas with bolded borders are included in the sample. The distribution of students is not even across community areas.
Data were taken from each student's Certificate of Child Health Examination (CCHE) completed by a health professional. Illinois requires parents and guardians to submit health exams to schools for students upon enrollment or kindergarten and fifth- and ninth-grade entry (Section 27-8.1 in the School Code of Illinois: 105 ILCS 527-8.1 and 2-3-6). Students must have a current complete exam on file to attend school, though in practice, enforcement of this rule varies by school. Typically, the school keeps these documents at the school site in the student's health file. The CCHE includes a record of immunizations, measured height and weight, date of birth, and notation of chronic health conditions (such as diabetes and asthma). Race and ethnicity are not recorded on the CCHE.
Height, weight, date of birth, date of measurement, and gender were taken from the CCHE in the student's health file at the school and entered into an Excel spreadsheet using a data entry program developed for this purpose. The program uses the date of birth and date of measurement to calculate the student's age, stores age in the data set, and discards date of birth. This system allowed the project to meet Health Insurance Portability and Accountability Act of 1996 (HIPAA) restrictions on the use of personal identifiers such as date of birth. The data entry program also includes safeguards for catching misinformation or missing data through protections such as not allowing for birth dates after measurement dates and requiring specification of units of measure.
The CPS data were extracted by CPS nurses; Catholic school data were extracted by CMRC-based research associates. All data collectors were trained in the use of the data entry program and familiarized with the CCHE prior to data collection.
After data entry, the individual Excel spreadsheets from CPS and Catholic schools were merged and the master spreadsheet imported into SAS version 9.1 (Cary, NC) for data cleaning and analysis.
Data were cleaned to remove cases with missing data (n = 2, leaving 1517 subjects for analysis). Data were checked for unit of measure consistency and units converted when necessary.
"At risk of overweight" (AROW) is defined as between 85th and 94th percentile for the sex- and age-specific body mass index (BMI). "Overweight" (OW) is defined as [greater than or equal to] 95th percentile. The BMI percentile was calculated using a SAS program developed for this purpose and based on the 2000 Centers for Disease Control and Prevention growth charts (http://www.cdc.gov/nccdphp/dnpa/growthcharts/sas.htm).
Height, weight, and BMI statistics including means and standard deviations and confidence intervals were calculated using the SAS PROC UNIVARIATE procedure. Comparisons between group mean height, weight, and BMI scores were done using the SAS TTEST procedure. Group mean data were compared by sample (public vs private school), gender, and age.
Overweight Prevalence in 3- to 5-Year-Old Chicago School Children. Overall, the prevalence of subjects with BMI percentiles [greater than or equal to] 95th percentile was 24%, 2 to 3 times higher than both the national prevalence of 10% for 2- to 5-year-olds documented by NHANES (1999-2002) and the 1998-1999 ECLS prevalence estimate of 8% for 5- to 7-year-olds in the Midwest region (Table 1 and Figure 3).
The prevalence of OW (24%) was higher than the prevalence of AROW (16%). The ratio of OW to AROW is twice as high in these samples (24%/16% 1.5) as at the national level (10%/12% = 0.8 for 2- to 5-year-olds, NHANES, 1999-2002).
Comparison of Public and Parochial School Children; Boys and Girls. As shown in Table 2, the findings from the 2 samples are very similar. Table 3 shows that the findings were also similar for boys and girls. There were no significant differences in percent overweight by gender (p > .22) or sample source (p > .27).
The data presented provide the first description of measured heights and weights in Chicago school children at the time they start school. The results make it clear that Chicago has an unusually high prevalence of overweight in this age range, as compared with national and regional data. Further, in Chicago, overweight children comprise a larger portion of "overweight and at risk for overweight" combined than at the national level.
These findings are consistent across samples and gender. They are also consistent with other recent urban data from Chicago and elsewhere. Data on child overweight in 6 Chicago community areas from the Sinai Health System's Improving Community Health Survey indicate similar levels of overweight (Unpublished report, "Sinai Health System's Improving Community Health Survey Report, January 2004). Others have documented similar levels in New York City. (14) Data on pre-K-aged children from Arkansas, a relatively more rural state, show slightly lower rates of overweight (15%), suggesting a possible urban/rural disparity in prevalence of child overweight, which needs further investigation. (15)
We believe that these results are accurate and that they indicate an urgent problem facing Chicago children, families, health providers, and schools. Ongoing monitoring of child weight status is warranted.
The data presented, though valuable, have limitations related to several methods issues. The preferred source of weight/height/BMI data is measurements taken by standardized equipment and staff trained in standard measurement techniques. While CCHE forms are likely to be a more accurate form of data than self- or parent report, they lack standardization.
Our use of a convenience sample may introduce bias. The CPS selected schools for participation in the project based on the availability of nurses for entering data. While the schools represent a diverse array of geographic areas and demographic characteristics, they may not be representative of the system. We selected Catholic schools based on geographic diversity. A larger sample of these schools would improve the generalizability of the data.
The CCHE forms do not contain data on race or ethnicity, which could be useful in interpreting variations in prevalence and comparisons to national prevalence. This makes it impossible to explore likely local population disparities related to race and ethnicity. Nationally, for the 2- to 5-year-old age group in 1999-2002, overweight prevalence varied among Mexican Americans (13.1%), non-Hispanic whites (8.6%), and non-Hispanic blacks (8.8%). (11) Other approaches are needed to explore these. In the future, as the Child Health Examination form is revised, it would be helpful to include race/ethnicity.
Focus on Youngest Students. The data obtained on young children reflect student nutritional status before school entry and so the health influences of the home/ community environment before a child is exposed to the school environment. This clarifies the burden that faces the schools when the children first arrive, which has to be anticipated and planned for. We believe that all school districts should collect and monitor data on this age group.
Our data were collected on these young children because of CLOCC's focus on this age group, dictated by the fact that this is a particularly important time in the development of childhood adiposity. Young children undergo a biological process called the adipose rebound, in which adipose ceils proliferate. This is 1 of 4 periods during which adipose cells normally multiply, and the fat cells added during this period often persist throughout life. (16,17)
Early childhood is also a critical period for establishing healthy behaviors. Studies have shown that behaviors, both healthy and unhealthy, are learned at an early age. (18) Healthy eating habits and physical activity in childhood affect growth and development and are related to risks of obesity in childhood and beyond. (19) This is an important consideration because overweight in childhood is significantly associated with severe overweight among adults. One study found that overweight young children (2-5 years of age) were more than 4 times as likely to become overweight adults as those with BMI for age below the 50th percentile. (20)
Other public health issues have taught us that it is often effective to begin to address difficult public health topics with a focus on young children. This can be seen from work to increase the use of car passenger restraints, to reduce tobacco use, and to reduce exposure to handguns. A focus on young children also has the advantage of integrating prevention approaches in the lives of mothers and young families and helping to raise a generation of children familiar with prevention messages and behaviors.
Building a Child Health Database. To build on the utility of the data presented here, Chicago needs to develop an ongoing system for monitoring student weights. The longitudinal information provided by such a system will indicate which geographic areas need most attention, which are getting better, and which worse, and will be a helpful element in evaluating prevention and management programs in schools and communities.
Our experience working with CCHE data led to the exploration of the use of this data source to create a statewide child health database for Illinois. Illinois already mandates that schools collect CCHE forms for students at specific times. These forms contain a wealth of information on the health status of children, including immunization status, previous diagnoses, lead screening results, and other health information. To date, only immunization status has been reported to state and federal agencies.
Centralized reporting of the data on these forms to the Illinois Department of Public Health could create a statewide child health database for use in directing child health policy, program development, and resource targeting for prevention, intervention, and treatments. Such an approach would use already-collected data and has the potential to be cost effective if appropriate centralized reporting methods are developed.
In early 2004, CLOCC put together a team to develop a proposal amending the Illinois School Code to require (1) school districts to report Certification of Child Health Exam data to the Illinois Department of Public Health and (2) the use of those data to create a statewide child health database. That proposal was developed into Senate Bill 2940, which was passed by wide margins by both houses of the Illinois General Assembly in the spring of 2004. In August 2004, SB 2940 was enacted by the Governor of Illinois. This law (PA-093-0966) provides for monitoring of a variety of child health parameters, not only weight status.
Health status is to be reported at the school level, in contrast to the law in Arkansas that requires reporting of school-assessed child weight status to parents. (22)
In the spring of 2005, CLOCC advocated for the appropriation of funds to develop and pilot methods for creating an Illinois Child Health Data Base using CCHE data. A small appropriation was received, and work began on the piloting process in the summer of 2005. Throughout this process, CLOCC has engaged the Illinois Department of Public Health in dialogue to discuss promulgation of the rules that would guide enactment of this initiative. The CLOCC is now consulting with the Centers for Disease Control and Prevention's Working Group on Obesity Surveillance and Screening to develop proposals for small-scale piloting of the data reporting and database creation effort.
Implications for Schools and School Health
These preliminary data indicate that child overweight is likely to become a driving force in shaping the ways in which schools address student health in the future. Below we offer a discussion on a variety of ways in which the high prevalence of child overweight may affect school health in the coming years.
Perhaps the most immediate impact will be on the allocation of health service resources at the school level. The CPS administrators have already begun changing their strategies for deploying school nurses in response to issues associated with child overweight and an increase in the number of students with insulin-dependent diabetes. For example, school nurses have been reassigned to deal with the administration of medication, taking them away from established prevention and health services.
The longer-term implications of high levels of prevalence of child overweight are not as clear. As our nation's attention has been captivated by the growing problem of child overweight, the federal government has responded by requiring local education agencies that participate in the School Nutrition Programs of United States Department of Agriculture (most often school districts) to create wellness polices that prioritize fitness and nutrition programs. This requirement specifically addresses child overweight and is designed to promote healthy lifestyle behaviors in children. This mandate may increase competition for resources for other school health initiatives, such as vision screening, immunization, and dental and mental health services.
Schools may struggle to meet the new mandate, in part, because there are relatively few programs and treatment options known to be effective in addressing child overweight. As a result, there is a danger that some local educational agencies may hastily implement programs that are ineffective or even harmful. Evaluation of implemented programs will be essential. Ideally, this need will be met by partnerships between schools and evaluation resources at universities and other research institutions.
More generally, the high prevalence of child overweight may require schools to begin an overall shift in their approach to student health. Child overweight differs from more familiar health school health issues such as acute injuries and short-term illnesses (such as fevers and colds). It also requires different types of health services from those are typically provided through schools. Health services commonly provided in schools, such as immunization and vision and hearing screening, are one-time services with defined responses. In contrast, child overweight is a chronic condition requiring long-term management and with no one proven treatment model.
Schools will likely need more resources and external partnerships to deal effectively with the chronic and complex nature of child overweight. Preventing, treating, and managing child overweight requires the involvement of families and communities. Improvements are typically achieved over a long period of time. This may require that schools modify the ways in which they work with families and other community institutions (such as parks, recreational facilities, local food outlets) and alter both physical and social aspects of school environments to support the needs of overweight children. As these kinds of efforts move forward, it will be important to document and evaluate varied approaches and to disseminate those results.
The data reported here document that nearly one quarter of children entering school in Chicago are already overweight. This clearly establishes a need for local schools to develop protocols and procedures to support the physical and mental health needs of affected and at-risk children. The findings also make it plain that ongoing weight status monitoring is needed and that current plans to implement this should go forward.
Cities that lack data on the weight status of their young children can use the data from Chicago and New York City (15) to guide their planning until local data are available. The child health data gathering and reporting system that is being developed in Illinois may serve as a model for other locales.
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Maryann Mason, PhD, Research Director, Center on Obesity Management and Prevention (COMP), Children's Memorial Research Center: and Research Assistant Professor, Northwestern University Feinberg School of Medicine, 2300 Children's Plaza, Box 157, Chicago, IL 60614, (firstname.lastname@example.org); Patricia Meleedy-Rey, MPH. Data Coordinator, (email@example.com), Child Health Data Lab, Mary Ann and J. Milburn Smith Child Health Research Program, Children's Memorial Research Center, 2300 Children's Plaza, Box 157, Chicago, IL 60614: Katherine Kaufer Christoffel, MD, MPH, Director, Center on Obesity Management and Prevention (COMP), Children's Memorial Research Center, and Professor of Pediatrics and Preventive Medicine, Northwestern University Feinberg School of Medicine, 2300 Children's Plaza, Box 157, Chicago, IL 60614, (firstname.lastname@example.org); Matt Longjohn, MD, MPH, Executive Director, Consortium in Lower Obesity in Chicago Children (CLOCC), Children's Memorial Research Center, and Research Assistant Professor, Northwestern University Feinberg School of Medicine, 2300 Children's Plaza, Box 157, Chicago, IL 60614, (email@example.com): Myrna P. Garcia, EdD, MEd, MA, CSN, BSN, Director of Student Health Services (retired) (firstname.lastname@example.org), Chicago Public Schools, 25 S. Clark St, 8th floor, Chicago, IL 60603; and Catherine Ashlaw, RN, MS, MEd, IL CSN, NCSN, Certified School Nurse (email@example.com), Chicago Public Schools, LeMoyne School, 851 W. Waveland Ave, Chicago, IL 60613.
Table 1 Comparison of OW to AROW * % OW % AROW Ratio NHANES (2- to 5-year-olds) 0.0 12.0 0.8 3- to 5-year-olds 24.0 16.0 1.5 3-year-olds 21.1 14.3 1.5 4-year-olds 23.4 16.1 1.5 5-year-olds 25.8 16.6 1.7 * OW, Overweight; AROW, at risk of overweight; NHANES, National Health and Nutrition Examination Survey. Table 2 Subject Characteristics, by Data Source Chicago Public Chicago Catholic Schools Schools p N (%) 1172 (77.3) 345 (22.7) Age, mean [+ or -] SD (years) 4.3 [+ or -] 0.7 4.2 [+ or -] 0.8 3-year-olds 14.7% 22.9% 4-year-olds 45.3% 36.8% 5-year-olds 40.2% 40.3% Gender (% Male reported) 51 47 Anthropometry, mean [+ or -] SD Height (cm) 107.3 [+ or -] 8.0 107.5 [+ or -] 7.6 .65 Weight (kg) 19.7 [+ or -] 4.6 20.0 [+ or -] 5.0 .23 BMI * 17.0 [+ or -] 2.8 17.2 [+ or -] 3.2 .23 Mean BMI 95% CI * 16.8 [+ or -] 17.1 16.9 [+ or -] 17.5 * BMI, body mass index; CI, confidence interval. Table 3 Subject Characteristics, by Gender Boys Girls p N (%) 761 (50.1) 756 (49.9) Age, mean SD (years) 4.2 [+ or -] 0.7 4.2 [+ or -] 0.7 .91 Anthropometry, mean [+ or -] SD Height (cm) 107.8 [+ or -] 8.2 106.9 [+ or -] 7.6 .02 * Weight (kg) 20.0 [+ or -] 4.8 19.5 [+ or -] 4.5 .02 * BMI ([dagger]) 17.1 [+ or -] 2.9 17.0 [+ or -] 2.9 .22 Mean BMI 95% CI ([dagger]) 16.9-17.3 16.7-17.1 * Statistically significant at .02. ([dagger]) BMI, body mass index; CI, confidence interval. Figure 1 Trends in Prevalence of Child Overweight Child (Ages 2-5) Overweight (1971-2002) % overweight 1971-1974 5 1976-1980 5 1988-1994 7.2 1999-2002 10.3 Data source: NHANES
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|Title Annotation:||Research Papers|
|Author:||Mason, Maryann; Meleedy-Rey, Patricia; Christoffel, Katherine Kaufer; Longjohn, Matt; Garcia, Myrna|
|Publication:||Journal of School Health|
|Date:||Mar 1, 2006|
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