# Presentation: 682341

## Overweight among Ohio 3rd Grade Students,2004-2005

**Elizabeth J. Conrey, RD, PhD**
**Maternal and Child Health Epidemiologist**
**Ohio Department of Health**

**Notes:**
Angela Norton, Ohio Department of Health
Erinn Hade and OSU Center for Biostatistics

## Pediatric Overweight

**Tripled 1970s to current**
**Comorbidities in childhood**
**Predictive of adult overweight**

**Notes:**
Pediatric overweight is an important and growing public health concern. Nationwide, the prevalence of overweight among US children, tripled from in the last several decades. 
Pediatric overweight is an important public health problem because being overweight impacts a child’s current and future health. Co-morbidities associated with overweight among adults are also found in children. For example, overweight children tend to have increased levels of blood pressure, cholesterol and lipids as well as glucose intolerance. 
Furthermore, overweight children are more likely to become overweight adults, and overweight adults who were also overweight as children have worse health outcomes than overweight adults who were not overweight as children.

## Why collect statewide BMI data on schoolchildren?

**Establish baseline**
**No Ohio data on school aged population**
**Standardize the process**
**Collect accurate data **
**Save resources at the local level**

**Notes:**
In Ohio there was no data available on school-aged population until this survey.  There was a growing interest at the local level so a growing number of local health depts and schools began assessing BMI and not using the proper equipment.
_concern over need for accuracy
-provide accurate information to parents/families
-save locals resources while ensuring accuracy through a standardized process

## Why collect statewide BMI data on schoolchildren?

**Track childhood overweight in Ohio over time**
**Target resources to groups with greatest risk**
**Evaluate success of interventions**
**Provide feedback to schools, communities and other stakeholders**
**Influence state and local policy**

**Notes:**
Plans to monitor the BMI through annual sentinel schools so data is collected over time providing information on a regular basis for more timely evaluations of progress
-Limited resources financial and human requires needs assessment which will enable scarce resources to be utilized in the most needy areas
-tracking over time allows for programs to mark improvements of their program interventions over a longer period of time which will be necessary in order to determine reductions in BMI’s.
-Aggregate information on BMI’s can be used as an indicator of health and wellness for schools and communities.  Stakeholders can take the data and make some assumptions of their communities needs to increase activity, nutrtion, health education etc.
-Aggregate data can be used to influence policy development such as requiring more phys ed in schools or eliminating soda and junk foods In schools.

## What is BMI?

**Excess body fat**
**Consistent and valid measure**
**Relative measure of height and Weight   **
**For children**
**Consider AGE and SEX also**
**Calculate Percentile**

## Methods

**2004-2005 school year**
**BMI Assessment was added to state 3****rd**** Grade Oral Health Survey**
**Efficient ****	****	**
**Saved resources**
**Limit intrusion on class time**

**Notes:**
-system in place for the process, i.e. all forms, letters to school, sampling criteria and trained field staff contacting schools
-Collaborated with BOHS oral health screening add ht and wts to their existing protocol
-save resources make only one visit to schools less interruptions and give a sense of health fair no one student sticking out – very conscience of sensitivity
-we undertook this knowing that the sample size and other aspects of the data collection were designed for the oral health survey, but felt that it was adequate for BMI assessment. That said, this BMI surveillance effort was really a BIG pilot for Ohio.

## Sampling: Schools

**Provide state and county level estimates (88 counties)**
**Stratification to ensure schools with >50% of students FRPM eligible were represented **
**Cluster sampling**
**Schools chosen PPS sampling without replacement within counties**
**If a chosen school refused participation, another school was chosen**

**Notes:**
The sample was chosen to be representative at the county and the state level.
The sample was stratified by county and additionally by the % of students in the school eligible for FRPM. This was to ensure that schools serving a majority of low socioeconomic status students were represented as well as those serving fewer low socioeconomic status students.
Cluster sampling was used, such that within each county, public schools being randomly chosen by PPS 
(probability proportional to size). 
If a chosen school refused participation, another school was chosen

## Sampling: Students

**All children within sampled schools selected**
**Active permission**
**Parent/guardian reported child’s**
**Date of birth and age in years**
**Sex**
**Race**
**Ethnicity**
**Eligibility for FRMP**

**Notes:**
Once a school was chosen, all 3rd graders in that school were targeted for participation.
-active consent required for both screenings a parent could consent for one or both.
-teachers sent permission slips sent home with children
-teachers responsible for collecting permission slips

## Getting To Yes

**Getting To Yes**

**Contact**
** ****Superintendent**

**Contact**
** ****School**** ****Principal**

**Permission Forms Mailed **

**Nutrition & PA **
**Education **
**Materials Mailed**

**Permission Slips Collected**

**Height & Weight Measured**

**Notes:**
Letters/phone calls to super. If yes contact principals.  If Yes again set up visit.  Collect info on number of classes, select date.  Mail materials to school X days in advance.

## Volunteer health care professionals recruited from each community
WIC 
Child & Family Health Services (CFHS)
 School Nurses
Volunteers trained on protocol
ODH Guidelines were standard
Train the trainer sessions
Training also by video

**WIC **
**Child & Family Health Services (CFHS)**
** ****School Nurses**
**Volunteers trained on protocol**
**ODH Guidelines were standard**
**Train the trainer sessions**
**Training also by video**

**Recruitment & Training of Screeners**

**Notes:**
-Challenge of recruitment of volunteers to augment staff 2 staff dedicated to scheduling and training over 146 vols and transporting equipment to sites
-recruitment of WIC personnel, health dept nurses and school nurses were the pool of vols.
-development of a study protocol required standardization of the process  which we used the ODH guidelines for measuring heights and weights for children as the basis for training.  All vols had to go trhough the training and then had to submit 2 signed forms 1) agreeing to confidentiality 2) documenting they had gone through the training.
-Over60% of the WIC offices helped and some even became trainers and scheduled their own volunteers-again approx. 146 unduplicated folks from around the state
-tremendous collateral benefit of the process was conducting training statewide to over 146 healthcare professionals sharing the guidelines and the educational materials and developing relationships with the local providers.  People worked together from the state and local areas that never knew each other before.

## Slide 11

## Volunteer health care professionals recruited from each community
WIC 
Child & Family Health Services (CFHS)
 School Nurses
Volunteers trained on protocol
ODH Guidelines were standard
Train the trainer sessions
Training also by video

**WIC **
**Child & Family Health Services (CFHS)**
** ****School Nurses**
**Volunteers trained on protocol**
**ODH Guidelines were standard**
**Train the trainer sessions**
**Training also by video**

**Recruitment & Training**

**Notes:**
-Challenge of recruitment of volunteers to augment staff 2 staff dedicated to scheduling and training over 146 vols and transporting equipment to sites
-recruitment of WIC personnel, health dept nurses and school nurses were the pool of vols.
-development of a study protocol required standardization of the process  which we used the ODH guidelines for measuring heights and weights for children as the basis for training.  All vols had to go trhough the training and then had to submit 2 signed forms 1) agreeing to confidentiality 2) documenting they had gone through the training.
-Over60% of the WIC offices helped and some even became trainers and scheduled their own volunteers-again approx. 146 unduplicated folks from around the state
-tremendous collateral benefit of the process was conducting training statewide to over 146 healthcare professionals sharing the guidelines and the educational materials and developing relationships with the local providers.  People worked together from the state and local areas that never knew each other before.

## Medical grade scales and stadiometer purchased by ODH
Height to nearest 1⁄4 inch
Weight to nearest 0.2 lb
Measured twice and averaged
Students could not see weight readout
No results sent home with child

**Height to nearest 1⁄4 inch**
**Weight to nearest 0.2 lb**
**Measured twice and averaged**
**Students could not see weight readout**
**No results sent home with child**

**BMI Assessment**

**Notes:**
-13 sets of equipment use of oral health field staff to transport equipment scale used had a hand held monitor to ensure confidentiality as an added caution not to focus on the weight volunteers were instructed to say to the students “today we are going to see how you’re growing” trying to minimize the stigma brought on by weight issues.
-no data was left at the school and no data was sent home with students (surveillance purposes only).  Families and schools were informed that the data was for research purposes only.   However educational information was given to every 3rd grade student, teacher and a family packet was sent home.  Over 40,000 sheets on improving nutrition and physical activity from Team nutrition was made up into packets that had lesson plans for teacher, tips for parents and fun activities for kids

## Data Analysis

**Age in months calculated from birthdate and date of assessment**
**CDC growth charts to generate BMI-for-age and sex percentiles**

| Percentile | Status |
| --- | --- |
| ≥ 95th | Overweight |
| ≥ 85th to <95th | At risk of overweight |
| 5th to < 85th | Normal weight |
| <5th | Underweight |

## Data Analysis

**SUDAAN to estimate proportions, standard errors, χ2 tests for differences between groups**
**Analyses weighted on race & FRPM **

**Notes:**
Proportions, standard errors, and χ2 tests (p<0.05) for differences in proportions among subgroups were calculated accounting for the complex sample design.

## Schools
392 Schools were approached
387 Schools participated 

Students....

**392 Schools were approached**
**387 Schools participated **
**Students....**

**Response**

**Notes:**
 392 schools were approached to achieve our sample size of 387 participating schools

## 14,451  

**27,660  **
**Total Enrollment in Sampled Schools**

**16,464  Permission Forms Returned**

**15,209  Granted BMI Permission**

**14,543  Screened for BMI**

**14,539  BMI Calculated**

**14,501  BMI Percentile Calculated**

**14,451  **
**Final BMI Sample Size**

**12,170  No Form Returned**

**1,255  BMI Permission Denied**

**666  Not Screened**

** ****3  Lacking Height or Weight**

**38  Lacking Sex or Age Data**

**50  Implausible BMI for Age & Sex**

**Notes:**
59% returned permission forms
92.3% granted permission
95.6% screened  (52% overall response rate)
99.4% valid data

51.7% overall response rate

outliers defined as too low or too high (implausible BMI) were based on the World Health Organization fixed exclusion ranges

## Ohio 3rd Graders by Weight  Status, 2004-5

|  | Percentage | 95% Confidence Interval |
| --- | --- | --- |
| Overweight | 18.9 | 17.5, 20.3 |
| At risk of overweight | 16.7 | 15.7, 17.7 |
| Healthy Weight | 62.8 | 61.2, 64.4 |
| Underweight | 1.7 | 1.3,   2.0 |

**Ohio 3****rd**** Graders by Weight  Status, 2004-5**

**Notes:**
We found that 20.6% of Ohio’s 3rd graders were overweight and an additional 17% were at risk of overweight. That translates to roughly 26,000 overweight 3rd graders in Ohio public schools and 22,000 3rd graders at risk of overweight.
If we compare this to the most recent NHANES findings for 6-11 year olds nationally, Ohio appears to be slightly higher than the national prevalence which is 18.8 % for overweight and 18.4% for at risk of overweight. However, this is probably isn’t a significant difference as the confidence intervals on those prevalences do overlap slightly.

## Overweight among Ohio 3rd Graders by Sex, 2004-5

**Notes:**
38.4 boys, 36.8 girls
We also compared boys to girls. This graph displays the percent of each who are overweight and at risk of overweight. The error bars display the 95% confidence interval on the combined number. The small difference seen between boys and girls was not significantly different at the 0.05 level.

## Overweight among Ohio 3rd Graders by Race & Ethnicity, 2004-5

*** Different from NH White and Hispanic by ****χ****2****, p< 0.05**

*****

**Notes:**
This slide shows the prevalence of overweight by race and ethnicity. Non-Hispanic black children appear to have a higher prevalence of overweight in Ohio, as has been found in other studies of overweight. However, this this difference was not statistically significant, perhaps do to the small sample sizes we had for all these groups except non-Hispanic whites.

	NH White 36.4, NH Black	 43.2, NH Other 38.9, and  Hispanic 39.0%

## Overweight among Ohio 3rd Graders by Free & Reduced Price Meal (FRPM) Eligibility, 2004-5

*****

*** ****Different by ****χ****2****, p< 0.05**

**Notes:**
Eligibility for the free and reduced price meal program is an indicator of economic status. Among 3rd graders whose parents reported they were eligible for FRPM, 22.3% were overweight and 17.9% were at risk of overweight. Among 3rd graders whose parents reported they were not eligible, 17.8 were overweight and 15.5% were at risk of overweight. This difference was highly statistically significantly. 

	FRPM Eligible 40.2	, Not Eligible		33.3	

## Overweight among Ohio 3rd Graders by County Type, 2004-5

*****

*** Different from rural non-App and suburban by ****χ****2****, p< 0.05**

**Notes:**
In Ohio we routinely look at our counties by how urban or rural they are. Additionally, because the southeaster, or Appalachian, area of our state is unique, we split our rural counties into those that are in the Appalachian. We found that there seemed to be a gradient of prevalence of overweight with children living in increasingly rural areas being increasingly more likely to be overweight. Children attending school in the rural Appalachian counties had a significantly greater prevalence of overweight or at risk of overweight than children attending school suburban or metropolitan counties. They had a greater prevalence of being overweight than children living in rural non-Appalachian counties.

	Rural App'n 41.3 , Rural Non-App'n	38.4, Suburban 37.4, Metropolitan 36.5	

## Slide 23

**Notes:**
Ohio has 88 counties...
Red 50 – 55
Green 40 to 49.9
Blur 30 – 39.9
Tan 25-29.9

## Limitations

**School participation **
**Low response rate (returned consent)**
**PPS sampling was based on the total number of students in the school**

**Notes:**
These findings will be subject to at least 3 limitations. First, not all schools randomly chosen were willing to participate and the health profiles of students in schools not willing to participate may differ from the profiles of students in participating schools. 
Second, the response rate was low, primarily due to non-return of consent forms. Consent was very high among those with returned forms, but it is not known if non-return of consent forms was due to non-consent, or simply failure to return the forms. Either way, those returning forms may differ from those not returning forms and may produce bias. 
Finally, the PPS sampling was based on the total number of students in the school, not the total number of third graders. This may have led to a bias favoring selection of schools with more grades.

## Conclusions

**Over 1/3 of Ohio 3****rd**** graders are overweight or at risk of overweight**
**Rural Appalachian counties have the highest overweight prevalences**
**Lower SES children have higher overweight prevalences**
**State prevalence comparable to national**

## Now What?

**Call to Action**
**Families**
**Schools**
**Communities**
**Health Care Providers**
**Local Governments**
**Data used to target resources**
**ODH state plan to address childhood overweight **
**Continued data collection**
**The report:**** **_[www.healthyohioans.org/schools/schools.aspx](http://www.healthyohioans.org/schools/schools.aspx)_

## THANK YOU!

**Contact Information**
**Elizabeth Conrey **
**    ****614-728-0994**
_**e**__[l](mailto:lizabethj.conrey@odh.ohio.gov)__[izabethj.conrey@odh.ohio.gov](mailto:lizabethj.conrey@odh.ohio.gov)_** **
**Angela Norton  **
**     ****614-466-6039**
_**a**__[ngela.norton@odh.ohio.gov](mailto:Angela.norton@odh.ohio.gov)_** **

## Ohio Children – 2004 PedNSS

**Notes:**
Before this survey, we did know a little about Ohio’s children. 

We knew that among low-income 2-5 year olds who participated in Ohio’s WIC Program, 12.0% were overweight and 15.0% were at risk for overweight in 2004. That’s more than one in 10 of Ohio’s low income children!
(source: Ohio Pediatric Nutrition Surveillance System (PedNSS)).

## Ohio Children – 2005 YRBS

**Notes:**
We also knew that among Ohio high school students in 2003, 12.7% were overweight and 14.7% were at risk of becoming overweight. This information is based on self-reported heights and weights and so probably is an underestimate of the true burden of overweight among our high school student. (source: 2003 Youth Risk Factor Behavior Surveillance System (YRBSS)).