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Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

Objective:

To investigate the prevalence of overweight and obesity among white and American Indian children in a predominantly rural state.

Design and Methods:

Using a repeated, cross-sectional design of school children's height and weight, the study sample included 361,352 measures of children who were 5.0–19.9 years, attending school across 13 academic calendar years. Trained staff measured height, weight, and recorded gender, age, and race. Data were voluntarily reported to the State Department of Health.

Results:

American Indian children consistently had higher rates of overweight and obesity compared to white children. Across the years, 16.3% of white students were overweight, whereas 19.3% of American Indian students were overweight. In addition, 14.5% of white children were obese and 25.9% of American Indian children were obese. Examining by rural versus urban schools, prevalence of overweight had been increasing among white male and female students and American Indian female students living in rural areas. Obesity is also increasing among rural white females and male and female American Indian children.

Conclusions:

The findings here suggest that although American Indian children are at higher risk, in general, compared to white children, rural populations in general are experiencing increases in childhood overweight and obesity. Targeted rural interventions beginning at an early age are necessary to improve the health of rural children, especially in American Indian communities.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

The rates of childhood obesity continue to be a public health concern, in particular the rates among rural and minority populations in the United States. Data from the National Health and Nutrition Examination Survey 2003–2004 and 2005–2006 show that rural children had a significantly higher prevalence of obesity (21.8%) compared to urban children (16.9%) (1). American Indian children specifically have the highest prevalence of obesity in the United States with subsequent complications of insulin resistance risk, type 2 diabetes mellitus, and high blood pressure starting at young ages (2–4). By the age of 5 years, 47% of American Indian boys and 41% of American Indian girls in the northern plains region were overweight, and 35% were obese in 2003, and these rates increased as children grew older (5). The prevalence of overweight and obesity among these American Indian children exceeded in all US children across the ages (5).

School-based screening is an effective strategy to monitor the prevalence of overweight and obesity among school children over time, because it can support state government decisions to allocate resources and implement targeted programming and evaluation. This is useful in rural states to monitor a relatively small population dispersed over a large geographic area where obesity risk is known to be higher than in more densely populated areas. For example, 35% of children attending rural schools live in poverty (6) and a higher percentage of American Indian students in remote rural areas attend moderate-to-high poverty schools compared to large cities (6). We know American Indian children have high overweight and obesity risk and rates (4, 5, 7–10) and that poverty is a risk factor for obesity (11–13).

The South Dakota Department of Health (DOH) has been working in partnership with the South Dakota State Department of Education (DOE) to collect height and weight data on school children throughout South Dakota for over a decade. In the mid-1990s, the DOH identified the need to quantify obesity in the school-aged population in the state. At that time, state-specific data did exist for the preschool population who participated in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) and for the adult population via Behavioral Risk Factor Surveillance System (BRFSS), but not for school-aged children. As pediatric obesity increased nationally, many local stakeholders at that time did not believe that the problem was increasing in South Dakota. As a result, the DOH and its Maternal and Child Health Program observed the need to collect obesity surveillance data to determine the extent of the problem to take any prevention programming actions if needed.

The purpose of this manuscript is to present the prevalence of childhood overweight and obesity in school children attending schools in South Dakota, so that the association between rural geographies and obesity can be better understood to inform targeted prevention strategies. South Dakota is a rural state with one of the largest reservations in the Unites States, home to the Oglala Sioux, and encompassed the second poorest county in the United States according to the 2000 Census (14). There are nine reservations in South Dakota and the counties where some of the reservations reside have also some of the highest poverty rates in the nation. Obesity in rural America and in poor America is leading the obesity epidemic and the specific drivers for this part of the epidemic need to be better understood to undertake effective prevention strategies in rural areas. This analysis will provide important information to public health policy makers, practitioners, and researchers on the extent of obesity disparities that exist by race and rural environments. This information is needed to develop efficient and targeted interventions.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

Study population

The student measurement was taken by school staff at schools throughout South Dakota. Students present at the day of the measurement and at a school that shared their data were included in the study. South Dakota is a rural and frontier state, with two urban areas with populations >50,000 in Sioux Falls and Rapid City. Bussing from rural to urban communities does not occur in South Dakota, and hence the school is an accurate representation of urban and rural communities in the state.

Data collection varied year to year. In 2011, data were collected from 193 schools and 35.2% of the students registered in the state. Although American Indian students comprise 15.4% of the South Dakota enrollment population, they represent 13.6% of the observations in this analysis. The percentage of American Indians ranged from 11.7 to 23.4% over the 13 academic calendar years of measurement.

Data collection history and methods

When the DOH and DOE (then the Department of Education and Cultural Affairs) considered collecting height and weight data, it was noted that some schools routinely obtained these measurements and often reported them on report cards to parents to show physical growth. The DOH and DOE began to explore the feasibility of a state-wide surveillance effort to collect this data. Partnering with the South Dakota Association of Physical Education, Recreation, and Dance, the SD School Nurses Association, and the DOH Office of Health Statistics, the State Nutritionist developed and finalized a plan to collect height and weight data from students across the state.

Letters were sent from the DOH to all public, private, and Bureau of Indian Education schools, requesting schools to share with DOH the height and weight data they were collecting. Letters were first sent in March 1999 on Coordinated School Health Program letterhead to all school superintendents. A data collection form and instructions on how to measure children were included with the letter. Equipment was purchased from Perspective Enterprises, Inc (Portage, Michigan). The Easy-Glide Bearing Stadiometer with measurement range from 36 1/4″ to 83 3/4″ and Health O Meter 402 lb were used at the schools. Height and weight were to be measured by health and physical education teachers or school nurses although the exact person conducting the measurements was not documented. Copies of the letter were sent to the building principals, health and physical education teachers, and school nurses. Recently, letters have been sent directly to school nurses and health/physical education teachers with copies sent to superintendents and principals. Participation in the data collection effort was voluntary and no remuneration was provided.

An internal memorandum was sent to field DOH personnel, asking them to encourage participation by the schools. Community Health Nurses employed by DOH also serve under contract as school nurses in some communities. Although school contracts were not amended for this activity, support staffs in DOH field offices were requested to transfer the previously obtained data to the format needed for data analysis.

All data were originally submitted as hard copies and generally handwritten. In subsequent years, electronic spread sheets were promoted. Starting with the 2006–2007 school year, the DOE's statewide computer system that tracks data needed for No Child Left Behind was also utilized to collect height and weight data.

Schools entered their data into the system and then prepared an extract of the needed components for school height and weight analysis. This allowed more accurate and timely data entry and a link to data that already existed at the school level on date of birth, gender, and race/ethnicity. Each year, analyzed data are returned to the participating schools in summary form. The project continues to enjoy strong support from DOH and DOE and the collaborating schools. No attempt has been made to obtain a representative sample. Given the large sample size, although modest participation rates across the state and over the years, there is no expectation of systematic bias.

Measurement

Trained staff including school nurses and physical education or health teachers conducted height and weight measurements of all children present at school during the days of measurement. Height was measured to the nearest 0.1 cm using a wall-mounted measuring board and weight was measured to the nearest 0.1 pound using a balance scale. Weight in pounds was converted to kilograms. Height and weight were converted to age- and sex-specific z-scores and BMI percentiles as recommended by the US Centers for Disease Control and Prevention (15). Participants were categorized as overweight if age- and sex-specific BMI ≥85th and <95th percentiles, and categorized as obese if BMI ≥95th percentile.

Student's date of birth, sex, and race were extracted from the student records. Age was calculated by subtracting the student's date of birth from the date of measurement and converting age into months. Race was recoded to non-Hispanic white, American Indian, mixed race and other, which included Asian, African American, and Hispanic for a total sample size of n = 399,841. The “other” category was used, given the relatively small proportion of those racial/ethnic groups (4.6%). This analysis included only the students who reported being white or American Indian (n = 361,352). Variables were recoded to comply with the CDC SAS code provided for age and sex standardized BMI z-scores [SAS/STAT. SAS Institute Inc., Cary, NC] (15).

Analysis

Data by year were appended into one file and all data management and final analyses were conducted using Stata v. 11 [Stata Corp., College Station, TX]. Data were transferred using Stat Transfer [Stat/Transfer version 11, Circle Systems, Seattle, WA] between SAS v9.1 for Windows [SAS/STAT. SAS Institute Inc., Cary, NC] and Stata. Annual data files were imported into Stata individually, variable names were standardized across years, and files were appended. Using the SAS code provided, age and sex z-scores were calculated. Following CDC protocol, biologically improbable values were deleted (n = 3136) as well as defined outliers for BMI z-scores and weight-for-age z-scores (n = 588), resulting in a sample size of 399,841. Finally, keeping only American Indian and white children resulted in an analytic sample size of 361,352. Bivariate baseline sample frequencies were calculated by white and American Indian children and weight status classification by gender, age category, and year. A chi-square test was used to assess difference in prevalence of overweight or obesity by race. A 1 degree of freedom (df) Wald chi-square test was used to assess the linear trend by year for race. Further subanalysis was conducted by sex and urbanicity within race categories using the same procedures.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

The final sample included 361,352 white and American Indian children who were 5.0–19.9 years of which 312,121 (86.4%) were white and 49,231 (13.6%) were American Indian. Table 1 summarizes sample characteristics by weight status and race. Averaged across all the years of data, the prevalence of overweight among white children was 16.3% and among American Indian children was 19.3% (chi-square = 265.9, P < 0.001). The prevalence of obesity among American Indian children was nearly double that of white children, again pooling the data across all years available (25.9 vs. 14.5%, chi-square = 4.1 + 03, P < 0.001). American Indian children had higher prevalence of both overweight and obesity compared to whites, regardless of gender, age categories and whether they attended urban or rural schools. In fact, prevalence of overweight and obesity was both higher among American Indian children compared to white children each year of data collection, with the exception of 2000–2001, 2001–2002, and 2002–2003 for overweight. Using a 1 df chi-square test, the prevalence of overweight did not increase over time among white children; however, prevalence of overweight did significantly increase among American Indian children (P = 0.01) although the prevalence estimates fluctuate over the measurement period. Obesity prevalence among white children significantly trended lower over the years of the surveillance (1998–1999: 13.9%; 2010–2011: 13.2%; P = 0.02) and increased among American Indian children during that same time period (1998–1999: 21.1; 2010–2011: 27.0; P < 0.001). Other than the substantial increase in obesity among American Indian children, all other changes were minimal and fluctuated over the time period. A combined weight status category of all children whose BMI percentile was >85th percentile highlighted similar patterns.

Table 1. Sample characteristics of White and American Indian school children weight status, South Dakota, 1998–2011
N = 361,352 OverweightObeseOverweight and obese
VariableValueWhite % (n)American Indian % (n)Chi-squareP-valueWhite % (n)American Indian % (n)Chi-squareP-valueWhite %American Indian %Chi-squareP-value
  1. Note: Overweight category includes only those 85 ≤ BMI percentile < 95. Obese category includes only those BMI percentile ≥ 95.

n 50,7899462  45,25312,727  96,04222,189  
Overall 16.319.3265.9<0.00114.525.94.1 e +03<0.00130.845.14.0 e +03<0.001
GenderMale16.2 (26,173)18.5 (4576)79.5<0.00115.9 (25,536)27.3 (6738)1.9 + 03<0.00132.145.81.8 e +03<0.001
 Female16.3 (24,616)19.9 (4886)199.4<0.00113.1 (19,717)24.4 (5989)2.2 + 03<0.00129.444.42.2 e +03<0.001
Age (years)5–8.915.5 (16,400)18.9 (3531)134.9<0.00112.5 (13,170)22.6 (4218)1.4 + 03<0.00128.041.51.4 e +03<0.001
 9–11.916.6 (16,375)19.5 (2971)79.7<0.00115.8 (15,565)28.6 (4366)1.5 + 03<0.00132.348.11.5 e +03<0.001
 12–14.916.9 (13,649)19.8 (2145)55.8<0.00115.5 (12,470)28.0 (3031)1.1 + 03<0.00147.932.41.0 e +03<0.001
 15–19.916.1 (4365)18.1 (815)11.60.00114.9 (4048)24.8 (1112)271.3<0.00131.142.9245.3<0.001
UrbanUrban15.5 (14,324)19.1 (1338)63.1<0.00112.6 (11,613)24.8 (1733)828.1.0<0.00128.143.9781.4<0.001
 Rural16.6 (36,465)19.2 (8124)176.8<0.00115.3 (33,640)26.0 (10,994)2.9 + 03<0.00131.945.32.8 e +03<0.001
Year1998–199916.1 (2132)20.3 (473)25.6<0.00113.9 (1840)21.1 (491)81.1<0.00129.941.4120.2<0.001
 1999–200016.4 (1901)19.8 (480)17.2<0.00113.6 (1575)21.3 (515)94.4<0.00129.941.1115.9<0.001
 2000–200115.7 (1522)16.9 (345)1.70.1915.6 (1512)29.0 (593)205.9<0.00131.345.8159.9<0.001
 2001–200216.1 (1639)17.5 (545)3.60.0615.2 (1553)24.2 (752)132.8<0.00131.341.7114.7<0.001
 2002–200316.2 (2310)17.7 (504)3.70.0614.7 (2094)23.8 (678)144.1<0.00130.941.4119.9<0.001
 2003–200415.7 (3385)18.2 (619)12.9<0.00114.3 (3076)26.1 (891)308.7<0.00130.044.3275.9<0.001
 2004–200516.4 (4600)18.8 (828)15.2<0.00114.9 (4164)26.6 (1174)383.1<0.00131.345.4342.3<0.001
 2005–200616.7 (5867)19.5 (1248)29.1<0.00115.0 (5277)27.3 (1<750)580.6<0.00131.746.7545.2<0.001
 2006–200716.4 (5471)20.1 (889)38.9<0.00114.5 (4839)26.7 (1179)433.4<0.00130.946.8449.6<0.001
 2007–200816.4 (5052)20.7 (884)50.7<0.00114.9 (4591)26.1 (1116)351.2<0.00131.246.9414.2<0.001
 2008–200916.9 (5357)19.3 (875)16.8<0.00115.0 (4751)26.4 (1194)376.8<0.00131.845.7342.0<0.001
 2009–201016.4 (5491)19.9 (827)33.1<0.00114.5 (4843)26.0 (1078)369.9<0.00130.845.9381.8<0.001
 2010–201115.6 (6062)19.4 (945)46.3<0.00113.2 (5138)27.0 (1316)654.0<0.00128.846.4628.0<0.001
P-Test for trend(1 df Chi-square)0.740.01  0.02<0.001  0.13<0.001  

To better understand the patterns of greatest need, prevalence estimates were calculated by attendance at an urban school versus rural school, and by gender. Table 2 summarizes the prevalence estimates of children who were overweight. Table 3 lists the prevalence estimates of children classified obese and Table 4 lists the prevalence estimates of children overweight and obese (>85th BMI percentile). The number of children by urbanicity, race, and sex varied by year. In the 1998–1999 data collection, there were 5964 rural white males, 6279 rural white females, 1146 rural American Indian males, and 1158 rural American Indian females. The urban distribution was as follows: 499 white males, 527 white females, 14 American Indian males, and 11 American Indian males. The numbers in all four categories steadily increased over time. In the 2010–2011 data collection, there were 10,692 rural white males, 10,297 rural white females, 1595 rural American Indian males, and 1692 rural American Indian females. The urban distribution was as follows: 9513 white males, 8342 white females, 794 American Indian males, and 790 American Indian males. Given the small sample size, particularly of American Indian children in 1998–1999 that year was excluded in trend analyses although including it did not change the test for trend results.

Table 2. Prevalence of overweight by urban and rural status, race, and sex, South Dakota, 1998–2011
  UrbanRural
  WhiteAmerican IndianWhiteAmerican Indian
  MaleFemaleMaleFemaleMaleFemaleMaleFemale
Year1998–199917.413.921.40.016.415.821.519.3
 1999–200016.015.916.120.516.516.420.219.5
 2000–200115.915.09.114.315.316.116.517.4
 2001–200216.714.921.115.916.216.117.517.4
 2002–200315.916.412.712.116.416.116.419.4
 2003–200416.315.212.312.815.915.617.919.5
 2004–200515.915.413.423.416.816.417.720.0
 2005–200616.016.318.920.416.417.518.919.9
 2006–200715.615.121.021.416.417.418.221.7
 2007–200815.216.619.921.916.117.020.620.8
 2008–200916.416.919.118.617.316.817.521.5
 2009–201015.915.419.520.317.016.618.521.4
 2010–201114.113.919.918.517.116.818.120.9
P-Test for trend 0.004NS0.06NS0.010.004NS<0.001
Table 3. Prevalence of obesity by urban and rural status, race, and sex, South Dakota, 1998–2011
  UrbanRural
  WhiteAmerican IndianWhiteAmerican Indian
  MaleFemaleMaleFemaleMaleFemaleMaleFemale
Year1998–199912.810.428.627.315.812.423.618.5
 1999–200012.710.932.312.815.312.822.020.6
 2000–200112.710.940.919.017.814.230.227.6
 2001–200214.09.918.420.517.214.725.823.0
 2002–200314.110.234.525.816.813.824.622.5
 2003–200414.310.921.025.516.213.327.625.2
 2004–200514.49.933.622.216.814.328.524.5
 2005–200613.911.827.621.017.714.228.526.8
 2006–200714.010.824.621.417.113.728.526.0
 2007–200815.311.329.320.017.113.627.025.9
 2008–200915.512.926.623.316.014.628.125.7
 2009–201014.211.328.322.616.614.227.225.0
 2010–201112.610.125.223.415.514.029.827.0
P-Test for trend NSNSNSNSNS0.004<0.001<0.001
Table 4. Prevalence of overweight and obesity by urban and rural status, race, and sex, South Dakota, 1998–2011
  UrbanRural
  WhiteAmerican IndianWhiteAmerican Indian
  MaleFemaleMaleFemaleMaleFemaleMaleFemale
Year1998–199931.324.350.027.332.228.245.037.8
 1999–200028.726.748.433.331.829.242.240.1
 2000–200128.626.050.033.333.230.446.745.0
 2001–200230.724.839.536.433.330.843.340.4
 2002–200329.926.647.337.933.229.841.041.8
 2003–200430.626.133.338.332.028.945.544.6
 2004–200530.225.447.045.633.630.846.244.4
 2005–200629.828.146.541.434.231.847.446.7
 2006–200729.625.845.642.833.431.046.747.7
 2007–200830.527.949.141.933.130.747.646.6
 2008–200931.929.845.841.933.331.445.647.2
 2009–201030.126.747.842.933.630.845.646.4
 2010–201126.724.045.141.932.630.847.847.8
P-Test for trend 0.01NSNSNSNS<0.0010.001<0.001

There were several significant findings. First, among urban children, the prevalence of overweight was stable over time for white and American Indian females. White male children showed a decreasing prevalence of overweight and obesity and American Indian male children also trended in that direction for overweight prevalence. However, among rural children, overweight trended upward among white female children and female American Indian children.

Prevalence of obesity (Table 3) increased over time among rural white females and American Indian males and females. Children living in urban environments had stable rates of obesity over time. Despite this stability of obesity among urban children, the prevalence of obesity was two to three times as high in American Indian compared to white children. Among rural children, the highest annual prevalence of obesity among white females was still lower than the lowest annual prevalence of obesity among American Indian females. Table 4 confirms that the proportion of white, urban males who are overweight or obese are decreasing. It also highlights that the proportion of rural children who are overweight and obese is rising for American Indians and white females, likely driven by the rising prevalence of obesity in particular.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

The levels of overweight and obesity among American Indian children are dangerously high and signify serious health risks distributed across a much larger proportion of the American Indian child population compared to the white child population (10). The overall estimates of 19% prevalence of overweight and 26% obesity are a little lower than a recent study of overweight and obesity among Northern Plains American Indian Children, (5) a study conducted with a similar population, but exclusively on the Pine Ridge Indian reservation (4). This likely is reflective of the rural-only population in the Hearst et al.'s study. If we compare only the prevalence of overweight and obese American Indian children attending rural schools, the estimates are much closer and therefore provide two independent estimates corroborating population obesity prevalence among rural American Indians in the northern plains.

A second important finding revealed that although the prevalence of overweight and obesity was high among American Indian children, the prevalence among American Indian children attending urban schools did not increase over time, and was trending downward among males. This highlights the importance of the rural environment, where overweight and obesity were rising among rural white females too. Although, compared to American Indian females, the prevalence of overweight and obesity was both significantly lower among white rural females, rural white males showed either a stable profile (overweight) or an increasing prevalence (obesity), whereas urban white males had decreasing prevalence of overweight over time.

These findings suggest that while ongoing focused intervention and programming need to be directed at American Indian youth across the state, special emphasis must be directed at all rural children too. Rural environments are known to have fewer food outlets that sell quality, affordable, and nutritious foods (16). Through focus groups, recent research discerned that cost, travel distance, and food quality were important barriers to healthy eating in rural communities (16). Physical activity and sedentary behavior comprise the other side of the energy balance equation. Children in rural communities are engaging more in sedentary lifestyles and the contextual elements to support physical activity for children may not be present (17). Contextual elements relevant in rural settings include built environments, issues of isolation, school policy, available funding for physical activity programs, as well as macroenvironmental features such as transportation infrastructure (17). Overcoming both real and perceived barriers to healthy eating and physical activity resources is one important aspect of intervention opportunity in rural communities.

Individual behavior patterns are also important. A recent study found few behavioral differences between urban and rural children that would explain the difference in weight status. In fact, the two groups (urban and rural) of children had similar levels of activity, sedentary behavior, and consumption of sugar sweetened beverages, which is contradictory to other research (17) although the authors do agree that reporting bias may be at play (1). Although difficult to implement in low-resource environments, providing children and parents with appropriate information about activity and dietary decisions should be incorporated into any intervention program that includes a multifaceted or multilevel approach to obesity prevention (10).

Rural American Indian children face more difficult barriers to healthy eating and activity patterns than other rural children, particularly for those living on reservations and interventions are urgently needed (10). For interventions to be most effective and sustainable, the interventions must be developed in partnership with the American Indian community, and address the social, physical, and educational threats that high poverty communities are not able to overcome by themselves (9). Story, a leading expert in obesity research and policy, says that interventions should not solely address individual and family behavior, but also the social and physical factors in the environment that enhance or support those behaviors (10). Social and environmental factors include the need to focus on supply and demand, policy level interventions, and identification of institutions that can help sustain programming (18). Environmental change is needed in concert with individual, family, and school level change so that children can safely follow established dietary and physical activity recommendations. (10).

School-based interventions, as with school-based surveillance shows promise for childhood obesity prevention. A recent review suggests that school-based interventions were more effective when aimed at reducing sedentary behavior, including a physical activity component and engaging parents. The intervention effectiveness was moderated by a nutrition component, meaning the interventions were more successful when nutrition was also included. (19). However, schools are facing more demands that are outside of their primary mission (to educate students), including obesity prevention efforts. As resources (financial and time) continue to be stretched, access to school settings may also become more challenging. A balance needs to be reached such that improving the health and well-being of our children, particularly those who are most vulnerable or hardest to reach, is done in cooperation between state agencies, including researchers, community partners, and schools as partners to address challenges and improve outcomes (20).

This study should be viewed in light of its limitations. First, the children participating are not a random sample of students, but instead the measurements of students who were present at school the days the measurements took place. It is possible that those with higher weight status chose to not attend school on those days. The number of children who were measured decreased in later grades. This may be owing to older students dropping out of school, students with outside employment, or they do not participate in physical education classes and were thus not measured. In addition, schools voluntarily shared their data with the State Department of Health. Therefore, different schools were present during each year of measurement. Given the large sample size, the distribution of schools and districts from across the state and comparable population distribution of white compared to American Indian participants, we do not expect any systematic bias and therefore feel the data adequately represent the population of students in South Dakota.

Conclusions

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

Intervention research must focus resources on the growing overweight and obesity prevalence of rural children. Working in partnership with school district administrators and state agencies provides an effective venue for reaching children throughout the state, even in the most rural communities. Interventions should include individual behavior change for children and parents, but also concentrate on factors in the social and physical environment that enhance or inhibit healthy lifestyle opportunities and work in partnership with local communities.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References

The authors especially thank all of the schools and school districts who supported this data collection, including all the staff and students.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
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