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Assessing Prevalence and Trends in Obesity: Navigating the Evidence (2016)

Chapter: Appendix D: Presentation of Findings

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Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
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Appendix D

Presentation of Findings

This appendix contains tables summarizing the committee’s review of the evidence. From the collection of 137 recent published reports (the selection of reports is described in Appendix C), associated manuals, protocols, training materials, and other intructions for directly measuring height and weight were identified. Tables D-1, D-2, and D-3 outline the height, weight, and data collector procedures, respectively, across 32 different protocols. Next, Tables D-4, D-5, and D-6 outline the different ways race and ethnicity, socioeconomic status, and age have been categorized and presented in the collection of recent published reports. Table D-7 summarizes the statistical approaches taken in the published reports to arrive at an estimate of prevalence, change, or trend, or assess differences between groups or other reports. Table D-8 presents a simulation demonstrating that the current FitnessGram’s®1 “Needs Improvement-Health Risk” cut points correspond to the 95th percentile on the 2000 Centers for Disease Control and Prevention (CDC) sex-specific body mass index (BMI)-for-age growth charts. Finally, references for all eight tables can be found at the end of this appendix.

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1 The FitnessGram® was developed and is a registered trademark of The Cooper Institute®, Dallas, Texas.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

TABLE D-1 Examples of Protocols for Directly Measuring Height

Study or Data Sourcea Reference Stadiometer Type Precision of Recorded Height Number of Repetitions Number of Contact Pointsb Measured Without Shoes Special Instructions
Add Health >Entzel et al., 2009 Portablec 0.50 cm 4 X

No hat, hair ornament, or other accessories that would affect measurement

Measurement taken at the end of a normal exhalation

Bogalusa Heart Study BioLINCC, 2008 Wall-mountedd 0.10 cm 3 X

In socks

Flat hairstyles

California FitnessGram® FitnessGram, 2016 Wall-mounted 1.00 in
CARDIAC Lilly et al., 2014 Wall-mounted X
CAYPOS Kolbo et al., 2012 Wall-mounted 1.00 in X

No belts

No jackets

No heavy jewelry

Child Health Measures Study Brown et al., 2010 Wall-mounted 0.25 in X

No excess clothing

Cincinnati Children’s Hospital Crowley et al., 2011 Wall-mounted X
Medical Center Echocardiography Database
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Sourcea Reference Stadiometer Type Precision of Recorded Height Number of Repetitions Number of Contact Pointsb Measured Without Shoes Special Instructions
Community Alliance for Research and Engagement Kallem et al., 2013e Wall-mounted
Creating Healthy, Active and Nurturing Growing-up Environments Tovar et al., 2012e Portable 0.30 cm (1/8 in) 3
Early Childhood Longitudinal Survey-Birth Cohort Najarian et al., 2010 Portable 2 X

Light clothing

EAT-I, EAT-2010 Larson et al., 2013f Portable 0.10 cm
Fels Longitudinal Study Sun et al., 2012g Portable 0.10 cm 2
HEALTH-KIDS Wang et al., 2009 Portable 0.10 cm 2 X

Light clothing

Louisiana Health Control Participants Williamson et al., 2011 Portable X

Normal clothing

No socks

Mississippi Delta Study Gamble et al., 2012 1.00 cm
New York City FitnessGram® New York City Departmemt of Education, 2016 0.30 cm (1/8 in) X

No hats or hairpieces

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
NHANES CDC, 2013a Wall-mounted or Portable 4 X

No hair ornaments, jewelry, buns, or braids on top of head

Measurement taken on exhale

Head aligned in horizontal planeh

Ohio Schools Ohio Department of Health, 2010 Wall-mounted or Portable 0.30 cm (1/8 in) X

No hats

No bulky clothing

Looking straight ahead

Penn State Child Cohort Bixler et al., 2008; Rodríguez-Colón et al., 2011 Portable 0.10 cm X

Light clothing

Philadelphia Schools Pennsylvania Department of Health, 2011 Wall-mounted 0.25 in or 0.10 cm 4 if possible, minimum 2 X

No hats or hairpieces

No bulky clothing

Feet flat on the floor

Head aligned in horizontal planeh

Philadelphia Schools Lawman et al., 2015 Portable 0.10 cm 2i X

No bulky clothing

No items in pockets

Pine Ridge Reservation School-Based Assessment, 1998-2002 Hearst et al., 2011 Portable 0.10 cm
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Sourcea Reference Stadiometer Type Precision of Recorded Height Number of Repetitions Number of Contact Pointsb Measured Without Shoes Special Instructions
South Dakota School-Based BMI Assessment Hearst et al., 2013 Wall-mounted 0.10 cm
Special Olympics International Healthy Athletes Database Special Olympics International, 2007 Wall-mounted 0.01 cm 4 X

Feet flat on the floor

Looking straight aheadh,j

Texas SPAN Study Texas School Physical Activity and Nutrition (SPAN) Study, 2016 Portable 1.00 cm 2 X
Not Specified Acharya et al., 2011k Wall-mounted 0.10 cm
Not Specified Huh et al., 2012 Portable 0.10 cm 2 2 X

Head aligned in horizontal planeh

Not Specified Nafiu et al., 2014 Wall-mounted 0.10 cm X

Head aligned in horizontal planeh

Not Specified Rogozinski et al., 2007 Wall-mountedl
Not Specified Taylor et al., 2014 Wall-mounted 0.25 in
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

NOTE: This table presents only information available given in the source study’s methods. If a general anthropometric measurement manual was referenced, it is noted in the footnotes; cm, centimeter; in, inch; all study and dataset acronyms are listed in Appendix A.

a The manuals and measurement protocolsin this table are from the data sources included in the committee’s review of recent reports. If the publication did not specifically name the data source that was used, but provided details about data collection protocol, it is labeled as “Not Specified” in the table.

b Common contact points with stadiometer include back of head, shoulder blades, buttocks, and heels.

c Carpenter’s square and steel tape measure used for measurement.

d Used both manual and electronic measuring board.

e Measurement protocol based on Economos et al., 2007. A community intervention reduces BMI z-score in children: Shape up Somerville first year results. Obesity (Silver Spring) 15(5):1325-1336 and Lohman, 1993. Advances in body composition assessment. Current Issues in Exercise Science (Monograph No. 3) 5(2):200-201.

f Measurement protocol based on Gibson, 1990. Principles of nutritional assessment. New York: Oxford University Press.

g Measurement protocol is based on Lohman, et al., 1988. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Books.

h Standardized measurement technique where a horizontal line drawn from the ear canal to the lower border of the orbit of the eye is parallel to the floor and perpendicular to the vertical backboard; also called the Frankfort horizontal plane.

i Duplicate measures required to be within 0.10 cm of each other.

j For individuals who were not able to stand, arm span was used as a proxy for height.

k Measurement protocol is based on Lohman et al., 1991. Anthropometric standardization reference manual: Abridged edition. Champaign, IL: Human Kinetics Books.

l For children who had difficulty standing fully erect because of weakness or knee flexion contractures, recumbent height was measured with use of a flexible tape measure.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

TABLE D-2 Examples of Protocols for Directly Measuring Weight

Study or Data Sourcea Reference Scale Type Precision of Recorded Weight Number of Repetitions Clothing Status of Participant Special Instructions
Add Health >Entzel et al., 2009 Digitalb 0.10 kg

No shoes

No change, wallets, keys in pockets

Bogalusa Heart Study BioLINCC, 2008 Digital 2

Short sleeve hospital gown

Underpants Socks

No shoes

CARDIAC Project Lilly et al., 2014 Digital No shoes
CAYPOS Kolbo et al., 2012 Digitalc 1.00 lb

No belts

No heavy jewelry

No jackets

No shoes

Child Health Measures Study Brown et al., 2010 Digitald 0.10 lb

No shoes

No excess clothing

Cincinnati Children’s Hospital Medical Center Echocardiography Database Crowley et al, 2011 Not specifiedd

Light street clothing

No shoes

Community Alliance for Research and Engagement Kallem et al., 2013 Digital 0.10 kge
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Creating Healthy, Active and Nurturing Growing-up Environments Tovar et al., 2012f Digital 0.50 lb 3

Light clothing

No shoes

EAT-I, EAT-2010 Larson et al., 2013g Beam or Electronicd 0.10 kg
ECLS-B Najarian et al. 2010 Digital 2

Light clothing

No shoes

Fels Longitudinal Study Sun et al., 2012h Beam 0.10 kg 2
HEALTH-KIDS Wang et al., 2009 Electronic 0.10 kg 2

Light clothing

No shoes

Louisiana Health Control Participants Williamson et al., 2011 Digital

Normal school clothing

No shoes

No socks

Mississippi Delta Study Gamble et al., 2012 Portable
New York City FitnessGram® New York City Department of Education, 2016 Digital Beam

No shoes

No heavy jackets

NHANES CDC, 2013a Digital, Portablei

Standard examination gown, including slippers

No shoes

Small children Casts or prosthesis

Wearing street clothes

Exceeding scale’s capacity

Ohio Schools Ohio Department of Health, 2010 Digital 0.20 lb 2

No shoes

No bulky clothing

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Sourcea Reference Scale Type Precision of Recorded Weight Number of Repetitions Clothing Status of Participant Special Instructions
Penn State Child Cohort Bixler et al., 2008; Rodríguez-Colón et al., 2011 Digitalj 0.01 lb

Light clothing

No shoes

Philadelphia Schools Robbins et al., 2012 Digital, Beam, Diald 0.25 lb

Light clothing

No shoes

No jackets

Empty pockets

Note special devices worn (e.g., prosthesis)

Philadelphia Schools Lawman et al., 2015 Digital 0.20 kg 2k

No shoes

No excess clothing

Empty pockets

Pine Ridge Reservation School-Based Assessment Hearst et al., 2011 Balance 0.10 lb
South Dakota School-Based BMI Assessment Hearst et al., 2013 Beam 0.10 lb
Special Olympics International Healthy Athletes Database Special Olympics International, 2007 Digital, Beamd 0.10 kg

No shoes

No sports packs

No jackets or other bulky items

Weighing individuals in wheelchairs

Texas SPAN Study SPAN Study, 2016 Digitald 0.25 lb 2

No shoes

No jacket

No heavy clothing

Empty pockets

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Not Specified Acharya et al., 2011l Electronic 0.10 kg
Not Specified Huh et al., 2012 Digital 0.10 kg 2

Light clothing

No shoes

No coat

Not Specified Nafiu et al, 2014 Electronicd 0.10 kg

Hospital gowns

Not Specified Rogozinski et al., 2007 Beam, force platform
Not Specified Taylor et al., 2014 Beam 0.25 lb

NOTE: This table presents only information available given in the source study’s methods. If a general anthropometric measurement manual was referenced, it is noted in the footnotes; kg, kilogram; lb, pound; all study and dataset acronyms are listed in Appendix A.

a The manuals and measurement protocols in this table are from the data sources included in the committee’s review of recent reports. If the publication did not specifically name the data source that was used, but provided details about data collection protocol, it is labeled as “Not Specified” in the table.

b Calibrated weekly.

c Calibrated after every 10th measurement.

d “Calibrated.”

e Measurement protocol based on World Health Organization, 2008. STEPS surveillance manual. Geneva: World Health Organization.

f Measurement protocol based on Economos et al., 2007. A community intervention reduces BMI z-score in children: Shape up Somerville first year results. Obesity (Silver Spring) 15(5):1325-1336 and Lohman, 1993. Advances in body composition assessment. Current Issues in Exercise Science (Monograph No. 3) 5(2):200-201.

g Measurement protocol based on Gibson, 1990. Principles of nutritional assessment. New York: Oxford University Press.

h Measurement protocol is based on Lohman, et al., 1988. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Books.

i Portable scales were used in cases of power outage, malfunction of primary scale, or individuals over 440 pounds maximum weight. In the case of individuals over 440 pounds, two scales were used to determine weight.

j Calibrated daily.

k Duplicate measurements must be within 0.2 kg of each other.

l Measurement protocol is based on Lohman, et al., 1991. Anthropometric standardization reference manual: Abridged edition. Champaign, IL: Human Kinetics Books.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

TABLE D-3 Examples of Protocols for Data Collectors

Study or Data Source Namea Reference Position of the Data Collector Data Collector Received Training Data Entry Method
Add Health, Wave IV >Entzel et al., 2009 Interviewer Hand-written values on Post-it note; later entered into a computer
Anchorage and Matanuska-Susitna Borough School Districts, Alaska CDC, 2013b School nurse
California FitnessGram® Madsen et al., 2010 Physical Fitness Test coordinators, teachers, and other local educational agency staff Xb
CAYPOS Kolbo et al., 2012 School nurse Direct entry to a secure website
Chicago school-based, environmental obesity prevention program in low-income African American adolescents Wang et al., 2009 Research staff X
Child Health Measures Study Brown et al., 2010 Staff X
Community Alliance for Research and Engagement Kallem et al., 2013 Research assistants X
Control Group from the MOVE Projectc Carlson et al., 2012 Staff X
Creating Healthy, Active and Nurturing Growing-up Environments Tovar et al., 2012 Staff X
ECLS-B Najarian et al. 2010 Interviewer X Hand-written in Child Assessment Booklet and entered into computer-based system
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Position of the Data Collector Data Collector Received Training Data Entry Method
Fels Longitudinal Study Sun et al., 2012 Researchers
Head Start Simmons et al., 2012 Teachers and assistants X
Health e-Tools for Schools, Pennsylvania Lohrmann, 2014; YoussefAgha et al., 2013 School nurse
New York City FitnessGram® Rundle et al., 2012 Physical education teachers Xd Hand-written; later entry into a Web-based systeme
NHANES CDC, 2013a Examiner and recorder Direct entry into ISISf
Ohio Schools Ohio Department of Health, 2010 Volunteer health care professionals X
Penn State Child Cohort Rodríguez-Colón et al., 2011 Research staff
Philadelphia Schools Lawman et al., 2015 Research assistants X
Philadelphia Schools Pennsylvania Department of Health, 2011 School nurse Direct entry to a secure school district database
Pine Ridge Reservation School-Based Assessment Hearst et al., 2011 Research staff Xg
South Dakota School-Based BMI Assessment Hearst et al., 2013 Staff including school nurses and physical education or health teachers X
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Position of the Data Collector Data Collector Received Training Data Entry Method
Special Olympics International Healthy Athletes Database Special Olympics International, 2007 Trained Special Olympics volunteer clinicians (e.g., nurses, doctors, dieticians) X Hand-written on athlete’s individual sheet
Texas SPAN Study Ezendam, 2011 Study staff or state or county personnel Hand-written directly on student’s questionnaire form
The Tucson Children’s Assessment of Sleep Apnea Study Goodwin et al., 2001 Research staff (two-person team)
Not Specified Acharya et al., 2011 Interviewer
Not Specified Huh et al., 2012 Research assistants
Not Specified Nafiu et al., 2014 Research assistants X
Not Specified Taylor et al., 2014 Nursing students enrolled in community health course X

NOTE: All study and dataset acronyms are listed in Appendix A.

a The manuals and measurement protocols in this table are from the data sources included in the committee’s review of recent reports. If the publication did not specifically name the data source that was used, but provided details about data collection protocol, it is labeled as “Not Specified” in the table.

b Schools have the option of participating in training and purchasing equipment for the FitnessGram®; however, documentation of school participation in training is not available.

c The MOVE Project is a 12-month childhood obesity prevention program with a 24-month follow-up.

d Training received through an NYC DOE-sponsored workshop, with additional reference material posted online.

e System has built-in validation features that alert the teacher to possible data entry errors.

f Integrated Survey Information System.

g Staff were trained by a public health nurse and Indian Health Service physician.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

TABLE D-4 Race and Ethnicity Categories, as Presented in a Collection of Recent Published Reports

Race and Ethnicity Categories Reference
One Category
African American Chen and Wang, 2012; Reed et al., 2013
American Indian Arcan et al., 2012
American Indian (% Indian Heritage) Hearst et al., 2011
Caucasian Johnson et al., 2012, 2013; Sun et al., 2012; von Hippel and Nahhas, 2013
Mexican American Warner et al., 2013
Two Categories
African American/Black; White Broyles et al., 2010; Freedman et al., 2012; Halloran et al., 2012; Kolbo et al., 2012; Molaison et al., 2010; Staiano et al., 2013; Williamson et al., 2011; Zhang et al., 2014
Native American; Other (not specified) Brown et al., 2010
American Indian; Non-Hispanic White Hearst et al., 2013
White/Caucasian; Non-White Adams et al., 2008; Kolbo et al., 2008; Rodríguez-Colón et al., 2011
Non-Hispanic White; Non-White Nader et al., 2014
White/Non-Whitea Bailey-Davis et al., 2012
Three Categories
American Indian/Alaskan Native; Non-Hispanic White; All Other CDC, 2013b
Mexicans; Mexican immigrants; Mexican Americans Hernandez-Valero et al., 2012
Mexican American (U.S. born); Non-Hispanic Black; Non-Hispanic White Robinson et al., 2013b
Mexican American; Non-Hispanic Black; Non-Hispanic White Din-Dzietham et al., 2007b; Freedman et al., 2006b; Ogden et al., 2006b; Okosun et al., 2010b; ver Ploeg et al., 2008b
Black; Hispanic; White Acharya et al., 2011
Black; White; Other Hsu et al., 2007
Four Categories
(Non-Hispanic) Blackc; (Non-Hispanic) Whitec; Mexican-Americand; Otherd Lee et al., 2010b
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Race and Ethnicity Categories Reference
African American; Latino; White; Other Huang et al., 2013
African American; Latino; Non-Hispanic White; Other Kim, 2012
African American/Black; Hispanic; White; Other Benson et al., 2009, 2011; Skinner et al., 2015b; Tovar et al., 2012
Asian-American (Chinese, Filipino, Other Asian); Hispanic (Cuban, Puerto Rican, Central/South American, Mexican, Other Hispanic); Non-Hispanic Black; Non-Hispanic White Gordon-Larsen et al., 2010
Mexican American; Non-Hispanic Black; Non-Hispanic White; Other Skelton et al., 2009b; Wang and Zhang, 2006b; Wang et al., 2012b
Mexican American; Non-Hispanic Black; Non-Hispanic White; Otherd Rossen and Schoendorf, 2012b
Mexican Americand; Non-Hispanic Black; Non-Hispanic White; Other Hispanicd Murasko, 2011b
Hispanic (includes Mexican American); Mexican American; Non-Hispanic Black; Non-Hispanic White Ogden et al., 2012b
Hispanicd; Non-Hispanic Black; Non-Hispanic White; Otherd Lee et al., 2011
Hispanic/Mexican Americane; Non-Hispanic Black; Non-Hispanic White; Other Skinner and Skelton, 2014b
Hispanic; Non-Hispanic Black; Non-Hispanic White; Non-Hispanic Other Oza-Frank et al., 2013; Taber et al., 2012
Hispanic; Non-Hispanic Black; Non-Hispanic White; Other Sekhobo et al., 2010f
Five Categories
African American; Asian; Caucasian; Hispanic; Unknownd Shustak et al., 2012
African American; Black Caribbean; Black Hispanic; Hispanic White; White Saab et al., 2011
African American; Asian; Hispanic; Non-Hispanic White; Other Lawman et al., 2015; Robbins et al., 2012
American Indian/Alaska Native; Asian/Pacific Islander; Hispanic; Non-Hispanic Black; Non-Hispanic White CDC, 2009f; Hinkle et al., 2012; Pan et al., 2012f
Asian; Black; Hispanic; White; Other Rundle et al., 2012; Wen et al., 2012
Asian/Pacific Islander; Black; Hispanic; White; Other/Unknownd Lo et al., 2014
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Race and Ethnicity Categories Reference
Asian/Pacific Islander; Hispanic; Non-Hispanic Black; Non-Hispanic White; Other (including multiple races) Day et al., 2014
Hispanic; Black; White; Other (includes American Indian, Alaska Native, Asian, Native Hawaiian or other Pacific Islander, or Mixed); Missing Eaton et al., 2008,g 2010,g 2012g; Kann et al., 2014g
Hispanic-Mexican American; Hispanic-Other; Non-Hispanic Black; Non-Hispanic White; Other Khoury et al., 2013b; Trasande et al., 2012b
Hispanic; Native American; Non-Hispanic Asian; Non-Hispanic Black; Non-Hispanic White Harris et al., 2006
Hispanic; Non-Hispanic Asian; Non-Hispanic Black; Non-Hispanic White; Non-Hispanic Other/Multipled Ogden et al., 2014b
Six or More Categories
African American; American Indian; Asian; Latino; White; Mixed Races or Other Babey et al., 2010
African American; Asian/Pacific Islander; European American; Latinah; Native American; Other/Mixedd Huh et al., 2012
African American; American Indian/Alaska Native; Asian; Filipino; Hispanic/Latino; Pacific Islander/Native Hawaiian; White; Two or More Races Jin and Jones-Smith, 2015
African American; American Indian/Alaskan Native; Asiani; Filipinoi; Hispanic/Latino; Pacific Islanderi; Non-Hispanic White Madsen et al., 2010
African American; American Indian/Alaskan Native; Asiand; Hispanic; Multiraciald; Native Hawaiian/Pacific Islanderd; White Weedn et al., 2014
African/African American; American Native/Alaska Native; Asian/Asian American; Filipino/Filipino American; Hispanic; Pacific Islander; White Aryana et al., 2012
African-American; Asian; Latino; Dominican; Mexican; Puerto Rican; Other Latino; White; Other Stingone et al., 2011
American Indian/Native Alaskan; Asian/Pacific Islander; Hispanic; Non-Hispanic Black; Non-Hispanic White; Other/Unknown Hruby et al., 2015
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Race and Ethnicity Categories Reference
Asian; Black; Hispanic/Latino; White; Other; Unknown Gee et al., 2013
Asian; Black; Hispanic; Native American; White; Other/Mixed (includes those who identified as Hawaiian or Pacific Islander) Neumark-Sztainer et al., 2012b
Asian/Pacific Islander; Black; Non-Hispanic White; White Hispanic; Other or Multiple; Unknownd Christensen et al., 2013
Asian/Part Asian; Filipino; Hawaiian/Part Hawaiian; Pacific Islander; White; Other (Hispanic, Black, other) Stark et al., 2011

NOTE: Table does not include reports where race/ethnicity was only presented as demographics table or adjusted for in statistical models. Reports listed in the table are individual reports. There is repetition of datasets.

a Estimates were generated for school districts with a population above and below the median for percent non-white.

b Primary dataset was NHANES.

c Dichotomized as “White” and “Black” in NHANES 1971-1975, 1976-1980.

d Presented in aggregate estimates, but did not have estimate separate from other racial/ethnic groups.

e Claims to have categorized “Mexican American” and “other Hispanics” in separate groups in the methods section, but results are presented as “Hispanic.”

f Primary dataset was PedNSS.

g Primary dataset was YRBS; the number of participating states and cities varies with each YRBS cycle.

h Study only included females.

i To protect the confidentiality of students, those responding “Pacific Islander” or “Filipino” were collapsed into the “Asian” category.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

TABLE D-5 Individual and Community Level Socioeconomic Status (SES) Categories, as Presented in a Collection of Recent Published Reports

Measure of SES Categories Presented in the Report Reference
Measure of Individual SES Status
Household Income, Gross Cutoffs <$15,000, $15,000-$34,999, $35,000+ Arcan et al., 2012
<$25,000, $25,000-$74,999, $75,000+ Okosun et al., 2010
<$15,999, $16,000-$23,999, $24,000-$31,999, $32,000+ Adams et al., 2008
<$9,999, $10,000-$29,999, $30,000-$49,999, $50,000+, Missing Reed et al., 2013a
<$20,000, $20,000-$39,999, $40,000-$74,999, $75,000+ Stingone et al., 2011
Household Income, Percent of Federal Poverty Level (FPL) 0-99%,100-199%, 200-399%, 400%+ Kim et al., 2011; Rossen and Schoendorf, 2012a,b
0-199%, 200%+ Holtby et al., 2015; Kim, 2012
0-100%, 100-300%, 300%+ Babey et al., 2010; Wang et al., 2012
0-130%, 130-350%, 350%+ Fakhouri et al., 2013
0-130%, 130-300%, 300%+ Ver Ploeg et al., 2008c
0-185%, 185-300%, 300%+ Ver Ploeg et al., 2008c
Household Income, Poverty-to-Income Ratio (PIR) Study sample divided into tertiles based on PIR distribution Wang and Zhang, 2006a
Study sample divided into quartiles based on PIR distribution Trasande et al., 2012a
PIR <1, PIR >1 Lalwani et al., 2013
PIR <1, PIR >4 Murasko, 2011
PIR <1, 1 to 3, >3 Skelton et al., 2009a
PIR <1 to <2, 2 to <4, >4 Li et al., 2012
PIR calculated, no further grouping Sekhobo et al., 2014
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Measure of SES Categories Presented in the Report Reference
Highest Education Level Attained by Either Parent/Caregiver Less than high school, High school, Greater than high school Kim, 2012a
Less than high school, High school graduate, Greater than high school, College or greater Suglia et al., 2014
Less than high school, Some high school, High school graduate or GED, Some college, College graduate or greater Trasande et al., 2012d
Grade school graduate, Some high school, High school graduate, Some college, Advanced degree Huh et al., 2012
Maternal Education Level Less than high school graduate, High school graduate or greater Kim et al., 2011
Less than high school, Some high school, High school graduate Lemay et al., 2008
Less than high school, High school graduate, Some college, College/graduate school Tovar et al., 2012a
Categorized as high, average, or low based on expected years of education at reported age Halloran et al., 2012
Parent or Caregiver’s Education Level (not specified further) No college degree, College degree or more Carlson et al., 2012
Less than high school, High school diploma/GED, Some college, College degree Stingone et al., 2011
Eligibility for Free or Reduced-Price Lunch Eligible for free or reduced lunch (yes/no) Day et al., 2014; Jin and Jones-Smith, 2015a; Kallem et al., 2013; Robbins et al., 2012; Rundle et al., 2012
Insurance Type Medicaid/public, non-Medicaid/private Black et al., 2012e; Christensen et al., 2013e; Demment et al., 2014a,f; Halloran et al., 2012; Lemay et al., 2008; Stark et al., 2011a; Wen et al., 2012
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Measure of SES Categories Presented in the Report Reference
Participitation in an Assistance Program Head Start enrollment Acharya et al., 2011g
Head Start enrollment and SNAP participation Simmons et al., 2012g
WIC participation CDC, 2009g; Davis et al., 2014g; Hinkle et al., 2012g; Sekhobo et al., 2010,g 2014g; Weedn et al., 2014g
WIC or SNAP enrollment Ver Ploeg et al., 2008
Participation in any assistance program CDC, 2013cg; Murasko, 2011g
Eligibility for any assistance program Reed et al., 2013; Tovar et al., 2012
Perception of Neighborhood as Safe Neighborhood perceived as safe (yes/no) Kim et al., 2011
Measure of Community-Level SES Status
Eligibility for Free or Reduced-Price School Meals Percentage of students eligible for free or reduced-price school meals Sanchez-Vaznaugh et al., 2015
Percentage of students receiving free or reduced-price lunch CDC, 2013ba,h, Oza-Frank et al., 2013a; Rundle et al., 2012
Racial/Ethnic Population Greater or less than 70% black, greater or less than 70% Hispanic students in schools Rundle et al., 2012
Percentage black and percentage white in county Gamble et al., 2012
Percentage of non-white population in school district Bailey-Davis et al., 2012a
Mean Neighborhood Income, Gross Cutoffs <$15,000, $15,000-$34,999, $35,000-$49,999, $50,000-$74,999, $75,000-$99,999, $100,000-$149,999, $150,000+ Black et al., 2012
Mean Neighborhood Income, Percent of FPL Percent of households living below federal poverty line Day et al., 2014i, Gamble et al., 2012; Taylor et al., 2014; Warner et al., 2013
Median Neighborhood Income Study sample grouped into income tertiles based on annual median income in the census tract Sanchez-Vaznaugh et al., 2015a
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Measure of SES Categories Presented in the Report Reference
Neighborhood Education Level Percentage of adults 25 years and older with 16 or more years of education Sanchez-Vaznaugh et al., 2015a
Percentage of adults 25 years and older with less than high school education Taylor et al., 2014
Less than high school, High school graduate, Some college or associated degree, Bachelor’s degree or higher Black et al., 2012; Langer-Gould et al., 2013
Less than high school, High school graduate, Some college or associated degree, Bachelor’s degree, Graduate or professional degree Christensen et al., 2013
Other SES Assessmentsj Participant residence in low-risk areas (those with Dept. of Public Health Office) versus high-risk areas (those without Dept. Public Health Office) Sekhobo et al., 2014
Participant residence in a socioeconomically distressed neighborhood Spilsbury et al., 2015
Participant residence classified by a neighborhood deprivation index Hearst et al., 2011a
School district distress index Bailey-Davis et al., 2012a
Percentage of economically disadvantaged students in school (based on eligibility for free/reduced lunch, income below FPL, or other assistance program) Ezendam et al., 2011

NOTE: Individual studies identified in literature search are represented in the table. Datasets are repeated across presented published reports. Reports often use multiple variables, SES or otherwise, in combination with each other.

a Obesity prevalence or trend estimate was reported for these subgroup, rather than only being a demographic characteristic.

b Actual cutoffs for this study were 0-100% FPL, 101-200% FPL, 201-400% FPL, >400% FPL.

c Percent of FPL was used only in cases where study participants were income eligible but non-participants in assistance programs.

d In the analysis, this variable was dichotomized to “some college and more” versus “no college.”

e Used Medi-Cal in addition to Medicaid.

f Used Child Health Plus in addition to Medicaid.

g Study population only included those participating in the specificed assistance program.

h Schools subdivided further into 2 groups: less than 50% of students receiving free/reduced lunch and more than 50% of students receiving free/reduced lunch.

i Study population groupings were <10%, 10% to <20%, 20% to <30%, ≥30%.

j Refers to a standardized assessment, usually based on a combination of factors, used to better capture unique populations and fit study goals.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

TABLE D-6 Variables and Categories Related to Age, as Presented in a Collection of Recent Published Reports

Measure of Age Categories Presented in the Report Reference
Age (years)

0.75 (9 months), 2, 4, 5-6

Castetbon and Andreyeva, 2012a

2, 3, 4

CDC, 2013c; Pan et al., 2012b

3, 4, 5

Lo et al., 2014b

7

Warner et al., 2013

10, 11, 12

Sanchez-Vaznaugh et al., 2015

12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26

Lee et al., 2011b

<14, 15, 16, 17+

Nickelson et al, 2012

14, 15, 16, 17, 18, 19

Adams et al., 2008b

18

Hsu et al., 2007b

Age Groups (years) 0-5

Holtby et al., 2015

0-<0.5, 0.5-<1, 1-<2, 2-<3, 3-<6

Wen et al., 2012

1-16

Saland et al., 2010

1-18, 19+

Song et al., 2012b

2-4

CDC, 2009; Davis et al., 2014; Weedn et al., 2014

2-4, 5-9, 10-14, 15-19

Robinson et al., 2013b,c

2-4, 5-19

Ver Ploeg et al., 2008

2 to <5

Sekhobo et al., 2010

2-5

Simmons et al., 2012

2-5, 6-11, 12-17, 18+

Eilerman et al., 2014b

2-5, 6-11, 12-17

Freedman et al., 2006

2-5, 6-11, 12-18

Skelton et al., 2009b; Skinner and Skelton, 2014

2-5, 6-11, 12-19

Gee et al., 2013; Ogden et al., 2006, 2012,b 2014; Shustak et al., 2012; Wang et al., 2012b

2-9, 10-18

Wang and Zhang, 2006b

2-9, 10-19, 20-29, 30-39, 40-49, 50-59, 60-69, 70-79

Lee et al., 2010b

2-10 (2-3, 4-5, 6-10)

Stark et al., 2011b

2-11, 12-19

Murasko, 2011

2-15

Demment et al., 2014

2-17, 18+

Arterburn et al., 2010

2-18

Benson et al., 2009, 2011; Johnson et al., 2012; Nader et al., 2014; Rossen and Schoendorf, 2012

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Measure of Age Categories Presented in the Report Reference
9-15

Kallem et al., 2013

10-12

Reed et al., 2013b

10-14

Chen and Wang, 2012

11-17

Halloran et al., 2012; Kim, 2012b

12-13, 14-15, 16-17, 18-19

May et al., 2012

12-14, 15-17

Babey et al., 2010b

12-15, 16-17, 18-21

Gordon-Larsen et al., 2010b,e

12-15, 16-19

Lalwani et al., 2013

12-17

Okosun et al., 2010

12-19

Harris et al., 2006b,f

13-14, 15-16, 17-18

Blank et al., 2015

13-19

Huh et al., 2012

14-19

Lemay et al., 2008b

<15, 16-17, 18-19, 20-24

Salihu et al., 2010b

15-19

Christensen et al., 2013

15-34, 35-44

George et al., 2011

<18, 18-24, 25-34, 35-44, 45-54, 55-59, 60-64, 65-67, 70+

Crawford et al., 2010g

18-20, 21-23, 24-28, 29-54

Hinkle et al., 2012

<20, 20-<30, 30-<40, 40+

Hruby et al., 2015

<20, 20-39, 40-59, 60+

Crawford et al., 2010h

<20 and >20

Ng et al., 2014

Mean Age of Study Sample (years) 5.8

Arcan et al., 2012

8.8

Taylor et al., 2014

10.0

Choumenkovitch et al., 2013

12.2

Wilson et al., 2011

13

Jin and Jones-Smith, 2015

15.6

Saab et al., 2011

16 (adolescents), 20 (young adults)

Suglia et al., 2014

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Measure of Age Categories Presented in the Report Reference
Birth Cohort Year

1928-1953; 1954-1972; 1973-1999

Johnson et al., 2012

1958-1970; 1971-1983; 1984-1995i

Johnson et al., 2013

1971-1975; 1976-1980; 1981-1985; 1986-1990; 1991-1995; 1996-2000; 2001-2005; 2006-2010

Robinson et al., 2013b

1988-1994; 1999-2000; 2001-2002; 2003-2004; 2005-2006; 2007-2008

Rosner et al., 2013

1995 (June)-1997 (July)

Demment et al., 2014

Grade in School

K, 1 and 3, 5 and 7

CDC, 2013b

1, 2, 3, 4, 5, 6

Lawman et al., 2015

3

Oza-Frank et al., 2013

4

Ezendam et al., 2011

4, 5, 6

Williamson et al., 2011

5

Lilly et al., 2014

5, 7, 8

Kallem et al., 2013

5, 7, 9

Jin and Jones-Smith, 2015

5, 8, 12

Lohrmann et al., 2014

6, 7, 9

Aryana et al., 2012

8, 10, 12

Kern et al., 2014; Slater et al., 2013

9, 10, 11, 12

Eaton et al., 2008, 2010, 2012; Kann et al., 2014

10

Saab et al., 2011

Grade Range K-5

Rodríguez-Colón et al., 2011; Stingone et al., 2011

K-5, 6-8, 9-12

Kolbo et al., 2008, 2012; Molaison et al., 2010; Robbins et al., 2012; Rundle et al., 2012; YoussefAgha et al., 2013; Zhang et al., 2014

K-6

Taylor et al., 2014

3-6

Choumenkovitch et al., 2013

6-10

Iannotti and Wang, 2013

9-12

Taber et al., 2012

School Level

Middle school, high school

Ritzman and Elmore, 2006

NOTES: Each reference corresponds to a published report. There is repetition of datasets (e.g., National Health and Nutrition Examination Survey); K, Kindergarten.

a Assessed the same child at each age given.

b Estimate of obesity prevalence or trend reported by age groupings given.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

c Ages based on cohort birth year.

d This age categorization is clinical and not data based; it was used because the Tanner index of sexual maturation was not measured at all periods.

e Age at last birthday.

f Ages at onset of study, assessed again at additional time interval.

g Groupings used in bivariate analysis.

h Groupings used in multivariate analysis.

i Aged 8-<18 years at assessment.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

TABLE D-7 Summary of Statistical Approaches Taken in a Collection of Recent Published Reports

Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
Add Health Gordon-Larsen et al., 2010 1996, 2001-2002, 2007-2009 Percent (95 percent CI)
Add Health Harris et al., 2006 1994-1995, 1996, 2001-2002 Proportion (95 percent CI)
Add Health Suglia et al., 2014 1994-2001 Percent (standard error)
Anchorage and Matanuska-Susitna Borough School Districts, Alaska CDC, 2013b 2003-2004 through 2010-2011 Weighted percentages; unadjusted obesity prevalence; 95 percent confidence interval
Bogalusa Heart Study Broyles et al., 2010 1973-2008b Percent
Bright Start Study Acran et al., 2012 2005-2006 Number of participants
California FitnessGram® Madsen et al., 2010 2001-2008 Percent (standard error; most considered negligible)
California FitnessGram® Sanchez-Vaznaugh et al., 2015 2001-2010 Percent
California FitnessGram® Aryana et al., 2012 2003-2008 Percentc
California FitnessGram® Jin and Jones-Smith, 2015 2010-2012 Percent
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
Stratified by sex and race, ethnicity categories F-statistic and t-test used to compare groups NR Stratified prevalence estimates plotted on chart
Stratified by sex, race and ethnicity categories Marginal (or “population-average”) longitudinal regression model Presented absolute change and 95 percent confidence interval (CI) NR
Regression models (difference between sexes) NR NR
Pearson Chi-square test Stratified by socioeconomic status, gender, race and ethnicity, grade grouping Relative percent change Multivariate logistic regression model; linear term for time, Unadjusted weighted prevalence (95 percent CIs) plotted
Stratified analyses (by age groups) Plotted results on same graph as NHANES prevalence Estimated secular trends were presented per 10 years Generalized estimating equations; accounted for demographic shift
Linear (additive) model; group-by-time interaction effect included in the models
NR NR NR
Stratified analyses Logistic regression Adjusted odds ratios between first year and peak year compared Logistic regression
Stratified percentages Cross-product terms added to trend models Trend line slope Multilevel logistic regression Multilevel logistic regression with spline terms
General linear model for analysis of variance for subgroup comparisons over time NR Cochran-Armitage trend test Multivariable logistic regression
Percent, stratified by income status Log-binomial regression; relative risk of obesity NR NR
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
CARDIAC Project Lilly et al., 2014 2002-2012 Average BMI percentile with standard error
The Caring Initiative Adams et al., 2008 1996-2005 n (%)
CAYPOS Kolbo et al., 2008 2005-2007 Weighted estimates and standard errors
CAYPOS Molaison et al., 2010 2005-2009 Weighted estimates and standard errors
CAYPOS Kolbo et al., 2012 2005-2011 Weighted estimates and standard errors
CAYPOS Zhang et al., 2014 2005-2013 Weighted estimates and standard errors
CENTURY Study Wen et al., 2012 1999-2008 Percent Percent (standard error)
CHAMACOS Study Warner et al., 2013 1999-2008 Number of participants (%)
Child Health Measures Study Brown et al., 2010 2007-2008 n (%)
Children of NLSY79 Participants Huang et al., 2013 1986-2008 NR
Chronic Kidney Disease in Children Study Wilson et al., 2011 2005-2009 n (%)
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
NR NR Generalized estimating equation model
NR NR Graphed the prevalence for each year; approach not described
Proc Crosstab Considered non-overlapping 95 percent CI significant NR NR
Proc Crosstab Considered non-overlapping 95 percent CI significant NR Compared values across the 3 years
Proc Crosstab Considered non-overlapping 95 percent CI significant NR Logistic regression used to assess linearity of longitudinal trends; linear coefficients and quadratic coefficients
Proc Crosstab Considered non-overlapping 95 percent CI significant NR Logistic regression used to assess linearity of longitudinal trends; linear coefficients and quadratic coefficients were assigned
Stratified analyses Compared to NHANES, PedNSS Relative change Absolute change Adjusted obesity risk per year Multivariable logistic regression models during two 5-year periods separately
Logistic regression NR Generalized estimating equation model
NR NR NR
Chi-square analyses Multivariate analyses NR Trajectory modeling
NR NR NR
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
Chronic Kidney Disease in Children Study Saland et al., 2010 As of May 2009 n (%)
Cleveland Children’s Sleep and Health Study Spilsbury et al., 2015 n (%)
Community Alliance for Research and Engagement – Baseline Kallem et al., 2013 NR n (%)
Creating Healthy, Active and Nurturing Growing-up Environments Tovar et al., 2012 NR Number of participants
Creating Healthy, Active and Nurturing Growing-up Environments Choumenkovitch et al., 2013 2008 Percent
ECLS-B Castetbon and Andreyeva, 2012 2005-2006, 2006-2007 Percent
Fels Longitudinal Study Johnson et al., 2012 1930-2008d Mean (standard deviation) BMI, BMI z-score;
Percent (number of participants)e
Fels Longitudinal Study Sun et al., 2012 1960-1999d NR
Fels Longitudinal Study (born 1958-1995) Johnson et al., 2013 1958-1995d NR
GE Centricity EMR Crawford et al., 2010 NR n (%)
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
NR NR NR
Presented by age groups NR NR
Multiple linear regression analyses NR NR
Present characteristics by weight category (e.g., n [%])
Logistic regression (unadjusted and adjusted)
NR NR
Generalize linear model Multiple logistic regression NR NR
Stratified by sex, presented by age groups (4, 5-6 years) NR NR
Presented by birth cohort NR Mixed effects growth modesl
Presented by birth cohort NR Sex-specific mixed-effect repeated measure analysis of variance model (BMI not percentile)
Stratified by sex*birth cohort
Two-degrees-of-freedom chi-square test comparing each subsequent birth cohort to the first
Generalized estimating equations (GEEs) specifying an autoregressive correlation structure
Stratified by comorbidity (*race, ethnicity groups; *sex), age group NR NR
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
Hawaiian HMO Stark et al., 2011 2003 n (%)
Health Behavior in School-aged Children Quadrennial Surveys Iannotti and Wang, 2013 2001-2002, 2005-2006, 2009-2010 Percent (SE)
Health eTools for Schools, Pennsylvania YoussefAgha et al., 2013 2005-2009 n (%)
Health eTools for Schools, Pennsylvania Lohrmann et al., 2014 2007-2011 Percentage
HMO Network Arterburn et al., 2010 2005-2006 Percent
Kaiser Permanente Northern California Gee et al., 2013 2003-2005, 2009-2010 Mean (95 percent CI)
Kaiser Permanente Northern California Lo et al., 2014 2007-2010 Percentage
KPSC Children’s Health Study Christensen et al., 2013 2007-2009 n (%)
KPSC Children’s Health Study Black et al., 2012 2007-2009 Percentage
n (%)
KPSC pediatric acquired demyelinating diseases Cohort, KPSC Children’s Health Study Langer-Gould et al., 2013 2004-2010, 2007-2009 n (%)
MetroHealth System, EpicCare – Northeast Ohio Benson et al., 2009 1999-2007 Number of participants
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
Wald Chi-square analysis Logistic regression NR NR
Multinomial logistic regression analysis Multinomial logistic regression analysis Multinomial logistic regression analysis
Presented by school level for each year
Compared prevalence by HS grades to YRBS (just percent, no CI)
Least-squares method, a simple linear regression formula
Pearson chi-square NR Least-squares method, a simple linear regression formula
Stratified by site NR NR
Stratified logistic regression models, combination of age and race categories
Compared to NHANES, California FitnessGram®
Absolute and relative change presented Logistic regression NR
Chi-square test
Cochrane-Armitage test
NR NR
Chi-square test
Multiple logistic regression models
NR NR
Presented by asthma status chi-square NR NR
Chi-square NR NR
Logistic regression Performed; presumably through the generalized estimating equation Generalized estimating equations for logistic regression with autoregressive correlation structure
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
MetroHealth System, EpicCare – Northeast Ohio Benson et al., 2011 1999-2008 Number of participants
Miami-Dade County Schools Health Screenings Saab et al., 2011 1999-2005 Percent
Military Health System Eilerman et al., 2014 2009-2012 Crude and age-adjusted prevalence
Entire population; no standard error or CIs presented
Monitoring the Future Slater et al., 2013 2010 Percent
MOVE Projectf Carlson et al., 2012 2007-2010 n (%)
Multiple datasetsg Lee et al., 2011 1959-2002 Plotted on a graph
Multiple datasetsh Ng et al., 2014 1984-2012 Age-standardized prevalence rates
Multiple datasetsj Hernández-Valero et al., 2012 2001-2007 Percent
Multiple datasetsk Lasserre et al., 2007 Varied by dataset Percent
National Comorbidity Survey – Adolescent Supplement Blank et al., 2015 2001-2002 Number of participants
National Hospital Discharge Survey Koebnick et al., 2009 1986-2006 Calculated per 100,000 population for 3-year periods
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
NR NR NR
Presented by school year Analyses stratified, by sex NR Logistic regression analyses
Stratified by sex, active duty status
Compared calculated prevalence to NHANES 95 percent confidence interval
NR Presented prevalence for each year
Multivariable logistic regression NR NR
NR Absolute change in BMI z-score (standard deviation); paired t-test NR
Presented by dataset used Stratified by sex, race, and sex*age Linear regression coefficients for time periods Plotted on a graph Linear regression analysis Growth curve models (longitudinal)
Stratified by sex and age (<20 and >20 years) NR Spatiotemporal regression model and Gaussian process regression with smoothing function smoothing functioni
Stratified by origin and resident status Chi-square
Univariate and multivariate multinomial logistic regression models
NR NR
Compared three different countries NR Plotted on graph and discussed
Percent ± standard error Logistic regression adjusted for age, sex, and race NR NR
Chi-square NR Plotted on a graph
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
Nationwide Inpatient Sample George et al., 2011 1995-2008 Percent (standard error)
New York City FitnessGram® Day et al., 2014 2006-2007 through 2010-2011 Percent
New York City FitnessGram® Rundle et al., 2012 2007-2008 Percent
New York City PedNSS Sekhobo et al., 2014 2004-2006 versus 2008-2010 n (%)
New York State PedNSS Sekhobo et al., 2010 2002-2007 Percent
NHANES Din-Dzietham et al., 2007 1963-2002 Prevalence with Taylor series linearization for variance estimation Unadjusted weighted prevalence (standard error)
NHANES Freedman et al., 2006 1971-1974, 1976-1980, 1988-1994, 1999-2002 Percent (standard error)
NHANES Murasko, 2011 1971-1980 versus 1999-2008 NR
NHANES Song et al., 2012 1971-1994 Prevalence with Taylor series linearization for variance estimation
NHANES Wang and Zhang, 2006 1971-2002 Percent ± standard error
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
Stratified by sex, age groups NR Linear regression; orthogonal polynomial contrasts across time periods
Wald statistic Relative change presented Multivariable logistic models
Presented by gender* race* school-level groups Multivariable generalized estimating equations with a logit link NR NR
Stratified by high-risk and low-risk neighborhoods, and by borough Chi-square tests Absolute change presented Ecologic, time-trend analysis
Present percent by sex and sex*race/ethnicity NR Prevalence presented for each year; plotted on a graph
Present unadjusted prevalence (standard error) by race and NHANES cycles NR Present unadjusted weighted prevalence and mean (SE) of participants’ selected characteristics by race/ ethnicity over time
Presented by race/ethnicity groups (*sex; *age groups) Present absolute change Logistic regression models
Stratified by age groups, income level Absolute difference (BMI z-score) Bayesian penalized-spline technique for structured additive models
NR NR NR
Chi-square NR Pooled data; logistic and linear regression analysis; included survey periods in models
Logistic regression; odds of obesity by socioeconomic status and race/ethnicity
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
NHANES Lee et al., 2010 1971-2006 Prevalence with Taylor series linearization for variance estimation
NHANES Robinson et al., 2013 1971-2008 Contingency table of prevalence, percent
NHANES Wang et al., 2012 1971-2008 NR
NHANES Skelton et al., 2009 1976-1980, 1988-1994, 1999-2000, 2001-2002, 2003-2004 n (%), 95 percent CI Standard errors were estimated using Taylor series linearization Extrapolated estimates to entire U.S. population
NHANES Ver Ploeg et al., 2008 1976-2002 NR
NHANES Zachariah et al., 2014 1976-2008 Percent
NHANES Rosner et al., 2013 1988-2008 Mean ± standard error BMI
NHANES Ogden et al., 2006 1999-2000, 2001-2002, 2003-2004 Weighted prevalence estimates (95 percent CI); Taylor series linearization for variance estimation
NHANES May et al., 2012 1999-2008 Weighted prevalence, n (%) % (standard error)
NHANES Khoury et al., 2013 1999-2008 Present mean ± standard deviation of BMI
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
No statistical comparisons; discussed absolute differences Absolute increases in obesity prevalence were calculated for the age trend by birth cohort analyses Age-period-birth cohort analysis
Age-period-cohort analysis (median polish technique) NR Age-period-cohort analysis (median polish technique)
Models presented by age groups and race/ethnicity Average annual changes estimated by regression models
Logistic regression models also fitted
Average annual changes estimated by regression models
Logistic regression models Differences in the slope of trends tested (per/post 1999)
Chi-square tests Bonferroni correction for multiple comparisons NR Cochran-Armitage trend test
Multiple regression analysis Logit models Multiple regression analysis Logit models Multiple regression analysis Logit models
NR NR Present percent by NHANES cycle
Stratified by NHANES cycle, sex NR NR
Sex-specific multiple logistic regression models T-tests NR Sex-specific logistic regression; survey years was used as a ordinal variable
Chi-square tests Bonferroni correction for multiple comparisons NR Presented prevalence (standard error) by NHANES cycle
NR NR NR
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
NHANES Ogden et al., 2012 1999-2010 Weighted prevalence estimates (95 percent CI); Taylor series linearization for variance estimation
NHANES Skinner et al., 2015 1999-2012 n, weighted percentl
NHANES Skinner and Skelton, 2014 1999-2012 Prevalence estimates for each obesity definition by 2-year NHANES cycles
NHANES Rossen and Schoendorf, 2012 2001-2002, 2009-2010 Multivariable logistic regression generated adjusted probabilities (prevalence); Taylor series linearization for variance estimation
NHANES Okosun et al., 2010 2003-2004 Number of participants
NHANES Ogden et al., 2014 2003-2004, 2005-2006, 2007-2008, 2009-2010, 2011-2012 Weighted prevalence estimates (95 percent CI); Taylor series linearization for variance estimation
NHANES Trasande et al., 2012 2003-2008 Number of participants Percent ± standard error
NHANES Lalwani et al., 2013 2005-2006 Number of participants
NHANES Li et al., 2012 2005-2008 Percent ± standard error
NHANES Fakhouri et al., 2013 2009-2010 Number of participants
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
Sex-specific multiple logistic regression models T-tests (difference by sex overall, between race/ethnicity groups) “Regression models using survey period as a discrete variable with appropriate contrast matrices” Sex-specific multiple logistic regression models; linear trends tested with survey cycle as discrete and continuous variable
Stratified by age category NR NR
Adjusted Wald tests of differences by demographics Adjusted Wald test Logistic regression; regressed NHANES years as an ordinal variable on the binary outcome; coefficient and standard errors represent a test for a linear trend
Presented by race, ethnicity groups, and socioeconomic status by cycle year Presented estimates by cycle year NR
One-way ANOVA Pearson chi-square tests NR NR
T-tests (sex difference) ANOVA (difference between race/ethnicity categories); T-tests Adjustments not made for multiple comparisons Absolute change Unadjusted prevalence trends tested with t statistics and orthogonal contrast matrices
Sex- and age-specific logistic regression models
Multivariable logistic regression NR NR
Cochrane-Armitage trend test (across various levels of hearing loss groups) Independent t-test NR NR
Stratified by age groups NR NR
NR NR NR
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
NSCH Kim, 2012 2002-2003, 2006-2007 Percent
NSCH Kim et al., 2011 2003 Percent
Ohio Schools – Third Grade Dataset Oza-Frank et al., 2013 2004-2005 through 2009-2010 Percent (95 percent CI) Adjusted prevalence estimates; predictive margins
Oklahoma WIC Datam Weedn et al., 2014 2005-2010 n (%)
PedNSS CDC, 2009 1998, 2003, 2008 n (%)
PedNSS Pan et al., 2012 1998-2010 Percent (95 percent CI)
PedNSS CDC, 2013c 2008-2011 n (%)
Penn State Child Cohort Rodríguez-Colón et al., 2011 2002-2006 n (%)
Penn State Child Cohort Calhoun et al., 2011 NR Average BMI percentile presented
Pennsylvania Public School BMI Surveillance Bailey-Davis et al., 2012 2006-2007, 2007-2008, 2008-2009 Proportion Presented by school years and as 3-year mean
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
Logistic regression; odds of obesity by school physical education requirements NR NR
Stratified by sex Regression analyses used to assess adjusted odd ratios by ADHD and medication status NR NR
Presented prevalence by age, sex, race/ethnicity, National School Lunch Program participation, county type NR Logistic regression; survey year included as ordinal variable
Sex-stratified multivariable logistic regression with interaction terms NR Sex-specific regression models; year included as continuous variable
Presented by state for three different years
Figure present prevalence over time by race/ethnicity categories
Chi-square tests for difference in proportions Graphed the prevalence for the entire sample over the 3-year period
Average absolute change
T-tests with Bonferroni adjustments NR Joinpoint regression Piecewise logistic regression
Logistic regression Absolute change presented Logistic regression models Crude and adjusted odds ratios are presented
NR NR NR
Average BMI percentile presented by groups NR NR
Bivariate comparisons; ANOVA
Multivariate models with adjusted pairwise comparisons
NR Box-plots presented by school year
Linear models used and F test and model coefficients
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
Philadelphia Schools Robbins et al., 2012 2006-2007 through 2009-2010 Percent
Philadelphia Schools Lawman et al., 2015 2011-2012 Percent
Pine Ridge Reservation School-Based Assessment Hearst et al., 2011 1998-2002 Percent (number of participants)
PNSS Hinkle et al., 2012 1999, 2004, 2008 n (%)
South Dakota School-Based BMI Assessment Hearst et al., 2013 1998-2010 n (%)
Special Olympics International Healthy Athletes Database Foley et al., 2014 2005-2010 Percent (95 percent CI)
Texas SPAN Study Ezendam et al., 2011 2000-2002 to 2004-2005 Percent
Total Army Injury and Health Outcomes Database Hruby et al., 2015 1989-2012 Percent
Truven Health Analytics MarketScan Database Joyce et al., 2015 2004-2010 n (%)
The Tucson Children’s Assessment of Sleep Apnea Study Archbold et al., 2012 1999-2004 n (%)
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
Prevalence presented by grade groups, sex, sex*race/ethnicity group, by eligibility for free/reduced-priced lunch Relative percent change presented Testing a linear variable for school year in multivariable models
P-value for trend was calculated using Wald Chi-square test
Stratified by sex, race, and grade Present absolute change Ordinal regression mixed model
Multinomial logistic regressions Chi-square
Presented by age groups, sex, percent Indian heritage Wald Chi-square test NR NR
Presented by participating locations, by demographic characteristics by year Average annual percentage point changes Cochran-Armitage test for trend
1 degree of freedom Wald chi-square test 1 degree of freedom Wald chi-square test
Chi-squared tests comparing results to NHANES NR Chi-squared tests Presented percent (95 percent CI)
Logistic regression used to assess effect of age and gender on overall prevalence (2005-2010) Plotted prevalence for each year on a graph
Chi-square test Cross-sectional mediation analysis Present percent at both time points NR
Multivariate logistic regression Present prevalence by each year Multivariate logistic regression with time interval as a predictor
Multivariate regression NR NR
NR Student paired t-test and the 2-sample test of proportions NR
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
Washington State Healthy Youth Survey Kern et al., 2014 2004-2012 Percent ± 95 percent CI
YRBS (national, state, large urban school districts) Eaton et al., 2012 1999-2011 Percent (95 percent CI)
YRBS (national, state, large urban school districts) Kann et al., 2014 1999-2013 Percent (95 percent CI)
YRBS (national, state, local) Eaton et al., 2008 1999-2007 Percent (95 percent CI)
YRBS (national, state, local) Eaton et al., 2010 1999-2009 Percent (95 percent CI)
YRBS, Florida Nickelson et al., 2012 2006 n (%)
YRBS, North Carolina Ritzman and Elmore, 2006 2001, 2005 Percent
YRBSS Taber et al., 2012 2001-2007 Percent
Not Specified Acharya et al., 2011 2004-2005 Percent
Not Specified Chen and Weng, 2012 2004 Percent
Not Specified Crowley et al., 2011 1986-1989, 2008 n (%)
Not Specified Gamble et al., 2012 2009-2010 Percent
Not Specified Halloran et al., 2012 1993-2006 n (%)
Not Specified Huh et al., 2012 NR Percent
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
Stratified analyses Interaction terms in logistic regression (group*year) Logistic regression analysis; change in odds (2010 versus 2012) Logistic regression analysis (2004-2012); adjusted for potential confounders
T-test T-test Logistic regression analyses; simultaneously assessed linear and quadratic time effects
T-test T-test Logistic regression analyses; simultaneously assessed linear and quadratic time effects Joinpoint analysis
T-test T-test Logistic regression analyses; simultaneously assessed linear and quadratic time effects
T-test T-test Logistic regression analyses; simultaneously assessed linear and quadratic time effects
NR NR NR
Present by school level Simply report apercentage for each year NR
Linear mixed models (between state comparisons) NR Sex-stratified linear model and included a quadratic term for time
Chi-square, by race, ethnicity NR NR
Logistic regression adjusting for covariates NR NR
Stratified by “era” (1986-1989, 2008) Likelihood ratio chi-square test NR
One-way ANOVA; Tukey’s post-hoc tests NR NR
Chi-square test Plotted graphs by race NR Cochran-Armitage test of trend
Plotted prevalence for each year on a graph, by race
Models regressed on age; age and ethnicity; and age*ethnicity interaction NR Longitudinal regression analyses using generalized estimating equation
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Study or Data Source Namea Reference Data Collection Years Statistical Approach
Prevalence
Not Specified Lemay et al., 2008 2001-2005 Percent
Not Specified Nader et al., 2014 2003, 2006, 2009 n (%)
Not Specified Nafiu et al., 2014 NR Number of participants
Not Specified Reed et al., 2013 2010 n (%)
Not Specified Rogozinski et al., 2007 1994-2004 Percent Percent (N)
Not Specified Salihu et al., 2010 2004-2007 Percent
Not Specified Simmons et al., 2012 2008-2010 Percent
Not Specified Staiano et al., 2013 NR Mean ± standard deviation; BMI and BMI z-score
Not Specified Stingone et al., 2011 NR n (%)
Not Specified Taylor et al., 2014 NR Percent (mean, median, standard deviation, min, max)
Not Specified Williamson et al., 2011 2006-2008 n (%)

NOTES: CI, confidence interval; NR, not reported in published report; * indicates interactions in analysis; all study and dataset acronyms are listed in Appendix A.

a Study or data source name provided in text of the publication. If the publication did not specifically name the data source that was used, but provided details about data collection protocol, it is labeled as “Not Specified” in the table.

b The 2008-2009 data came from routine measurements of students from the middle school (grades 6-8) and high school (grades 9-12), which enrolls ~81% of students in the community.

c Percent in the body composition “Healthy Fitness Zone.”

d Birth cohort years; end year of data collection not specified in the published report.

e Presented as overweight and obese at age 10 years.

f The MOVE project is a 12-month childhood obesity prevention program with a 24-month follow-up.

g Includes NHANES (1959-1962, 1966-1970, 1971-1975, 1976-1980, 1988-1994, 1999-2000, 2001-2002); Add Health (Wave 1: 1994-1995; Wave 2: 1996; Wave 3: 2001-2002); NHIS (1980, 1990, 2000-2003); NLSY79 (1981-1982, 1985); NLSY97 (1997, 2001).

h Includes National Longitudinal Survey of Youth (1997-2011); National Survey of Family Growth (2006, 2007, 2008, 2009); National Longitudinal Survey of Adolescent Health (1994); International Social Survey Programme (ISSP) (2012); National Health Measurement

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
Comparisons Between Groups, Datasets Changes (2 points in time) Trends (≥3 points in time)
Chi-square tests Reported the percent at each time point NR
Univariate and multivariate logistic regression models Chi-square test Cochran–Armitage test for trend
NR NR NR
ANOVA Chi-square NR NR
Compared estimates to NHANES (graph) NR Chi-square test for trend Multiple logistic regression analysis
Chi-square for trend NR NR
Chi-square test Wilcoxon signed-rank test NR
NR NR NR
NRn NR NR
Pearson product-moment correlation coefficients (partial correlations) NR NR
NR n (%) at both time points presented NR

Survey (2006); National Survey on Drug Abuse (1995); NHANES (1988, 1999, 2001, 2003, 2005, 2007, 2009, 2011); BRFSS (1984-2012); National Longitudinal Survey - Child/Young Adult (1986, 1988, 1990, 1992, 1992, 1996, 1998, 200, 2002, 2004, 2006, 2008, 2010); Health Behavior in School-Aged Children (2001, 2005, 2009); National Health Interview Survey (NHIS) (1980-2012); PedNSS (1980-2012).

i U.S. data included in the “developed” country age-birth cohort trend.

j Includes Cohort of Mexican School Age Children and Adolescents (2004-2006); Mano a Mano Cohort (2001-2003); and From Mother to Child Project (2004-2007).

k Includes previously published NHANES data; published aggregate data from Switzerland (Zurich [1960/1965; 1980/1990]; national data [2002]); and raw data from Seychelles (1998-2004).

l Only assessed children at or above the 85th percentile on the 2000 Centers for Disease Control and Prevention BMI-for-age growth charts; prevalence presented by gradation of obesity categories.

m Oklahoma did not report to national PedNSS during this time.

n Obesity prevalence is presented in the text, but the figures and tables describe overweight rather than obesity.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

TABLE D-8 2000 CDC Body Mass Index-for-Age Percentiles Corresponding to the 2015 FitnessGram’s®/sup> Needs Improvement-Health Risk (NI-HR) Cut Points, by Age and Sex

Hypothetical Information Used to Calculate a BMI Corresponding to the NI-HR BMI Cut Point
Age, years Sex Date of Birth Date of Measurement Height, inchesa Weight, poundsb NI-HR BMI Cut Pointc Corresponding BMI-forAge Percentiled
5.0 F 01/01/1999 01/01/2004 48 60.6 18.5 95.8
5.5 F 01/01/1999 07/01/2004 48 60.6 18.5 95.0
6.0 F 01/01/1999 01/01/2005 48 62.9 19.2 96.0
6.5 F 01/01/1999 07/01/2005 48 62.9 19.2 95.0
7.0 F 01/01/1999 01/01/2006 48 66.2 20.2 96.1
7.5 F 01/01/1999 07/01/2006 48 66.2 20.2 95.1
8.0 F 01/01/1999 01/01/2007 48 69.5 21.2 96.0
8.5 F 01/01/1999 07/01/2007 48 69.5 21.2 95.0
9.0 F 01/01/1999 01/01/2008 48 73.4 22.4 96.0
9.5 F 01/01/1999 07/01/2008 48 73.4 22.4 95.0
10.0 F 01/01/1999 01/01/2009 48 77.3 23.6 95.9
10.5 F 01/01/1999 07/01/2009 48 77.3 23.6 95.1
11.0 F 01/01/1999 01/01/2010 48 81.0 24.7 95.8
11.5 F 01/01/1999 07/01/2010 48 81.0 24.7 95.0
12.0 F 01/01/1999 01/01/2011 48 84.6 25.8 95.7
12.5 F 01/01/1999 07/01/2011 48 84.6 25.8 95.0
13.0 F 01/01/1999 01/01/2012 48 87.8 26.8 95.6
13.5 F 01/01/1999 07/01/2012 48 87.8 26.8 95.0
14.0 F 01/01/1999 01/01/2013 48 90.8 27.7 95.5
14.5 F 01/01/1999 07/01/2013 48 90.8 27.7 95.0
15.0 F 01/01/1999 01/01/2014 48 93.4 28.5 95.4
15.5 F 01/01/1999 07/01/2014 48 93.4 28.5 95.0
16.0 F 01/01/1999 01/01/2015 48 96.0 29.3 95.4
16.5 F 01/01/1999 07/01/2015 48 96.0 29.3 95.0
17.0 F 01/01/1999 01/01/2016 48 98.3 30.0 95.4
Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×
17.5 F 01/01/1999 07/01/2016 48 98.3 30.0 95.0
5.0 M 01/01/1999 01/01/2004 48 59.3 18.1 95.8
5.5 M 01/01/1999 07/01/2004 48 59.3 18.1 94.9
6.0 M 01/01/1999 01/01/2005 48 61.6 18.8 96.3
6.5 M 01/01/1999 07/01/2005 48 61.6 18.8 95.2
7.0 M 01/01/1999 01/01/2006 48 64.2 19.6 96.2
7.5 M 01/01/1999 07/01/2006 48 64.2 19.6 95.1
8.0 M 01/01/1999 01/01/2007 48 67.5 20.6 96.1
8.5 M 01/01/1999 07/01/2007 48 67.5 20.6 95.1
9.0 M 01/01/1999 01/01/2008 48 70.8 21.6 95.9
9.5 M 01/01/1999 07/01/2008 48 70.8 21.6 95.0
10.0 M 01/01/1999 01/01/2009 48 74.4 22.7 95.9
10.5 M 01/01/1999 07/01/2009 48 74.4 22.7 95.1
11.0 M 01/01/1999 01/01/2010 48 77.7 23.7 95.7
11.5 M 01/01/1999 07/01/2010 48 77.7 23.7 95.0
12.0 M 01/01/1999 01/01/2011 48 81.0 24.7 95.7
12.5 M 01/01/1999 07/01/2011 48 81.0 24.7 95.0
13.0 M 01/01/1999 01/01/2012 48 83.9 25.6 95.6
13.5 M 01/01/1999 07/01/2012 48 83.9 25.6 95.0
14.0 M 01/01/1999 01/01/2013 48 86.9 26.5 95.6
14.5 M 01/01/1999 07/01/2013 48 86.9 26.5 95.1
15.0 M 01/01/1999 01/01/2014 48 89.1 27.2 95.5
15.5 M 01/01/1999 07/01/2014 48 89.1 27.2 95.0
16.0 M 01/01/1999 01/01/2015 48 91.4 27.9 95.5
16.5 M 01/01/1999 07/01/2015 48 91.4 27.9 95.0
17.0 M 01/01/1999 01/01/2016 48 93.7 28.6 95.5
17.5 M 01/01/1999 07/01/2016 48 93.7 28.6 95.0

NOTE: NI-HR, Needs Improvement-Health Risk.

a For ease of calculation of the BMI corresponding to the 2015 FitnessGram’s® NI-HR cut points, all heights were set to 48 inches.

b Values are weights in pounds that correspond to the NI-HR BMI cut point, based on a height of 48 inches.

c BMI cut points correspond to the values used in the 2015-2016 California Physical Fitness Test (California Department of Education, 2015).

d Percentiles correspond to the 2000 CDC sex-specific BMI-for-age growth charts. BMI-for-age percentile calculated using the CDC Children’s BMI Tool for Schools spreadsheet (CDC, 2015).

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

REFERENCES

Acharya, K., M. Feese, F. Franklin, and E. K. Kabagambe. 2011. Body mass index and dietary intake among Head Start children and caregivers. Journal of the American Dietetic Association 111(9):1314-1321.

Adams, M. H., T. M. Carter, C. A. Lammon, A. H. Judd, J. Leeper, and J. R. Wheat. 2008. Obesity and blood pressure trends in rural adolescents over a decade. Pediatric Nursing 34(5):381-386, 394.

Arcan, C., P. J. Hannan, J. H. Himes, J. A. Fulkerson, B. Holy, M. Smyth, and M. Story. 2012. American Indian parents’ assessment of and concern about their kindergarten child’s weight status, South Dakota, 2005-2006. Preventing Chronic Disease 9:E56.

Archbold, K. H., M. M. Vasquez, J. L. Goodwin, and S. F. Quan. 2012. Effects of sleep patterns and obesity on increases in blood pressure in a 5-year period: Report from the Tucson children’s assessment of sleep apnea study. Journal of Pediatrics 161(1):26-30.

Arterburn, D. E., G. L. Alexander, J. Calvi, L. A. Coleman, M. W. Gillman, R. Novotny, V. P. Quinn, M. Rukstalis, V. J. Stevens, E. M. Taveras, and N. E. Sherwood. 2010. Body mass index measurement and obesity prevalence in ten U.S. health plans. Clinical Medicine and Research 8(3-4):126-130.

Aryana, M., Z. Li, and W. J. Bommer. 2012. Obesity and physical fitness in California school children. American Heart Journal 163(2):302-312.

Babey, S. H., T. A. Hastert, J. Wolstein, and A. L. Diamant. 2010. Income disparities in obesity trends among California adolescents. American Journal of Public Health 100(11):2149-2155.

Bailey-Davis, L., M. Horst, M. M. Hillemeier, and A. Lauter. 2012. Obesity disparities among elementary-aged children: Data from school-based BMI surveillance. Pediatrics 130(6):1102-1109.

Benson, L., H. J. Baer, and D. C. Kaelber. 2009. Trends in the diagnosis of overweight and obesity in children and adolescents: 1999-2007. Pediatrics 123(1):e153-e158.

Benson, L. J., H. J. Baer, and D. C. Kaelber. 2011. Screening for obesity-related complications among obese children and adolescents: 1999-2008. Obesity (Silver Spring) 19(5):1077-1082.

BioLINCC. 2008. Bogalusa heart study. In Biospecimen and Data Resources: National Heart, Lung, and Blood Institute. https://biolincc.nhlbi.nih.gov/studies/bhs (accessed June 9, 2016).

Bixler, E. O., A. N. Vgontzas, H.-M. Lin, D. Liao, S. Calhoun, F. Fedok, V. Vlasic, and G. Graff. 2008. Blood pressure associated with sleep-disordered breathing in a population sample of children. Hypertension 52(5):841-846.

Black, M. H., N. Smith, A. H. Porter, S. J. Jacobsen, and C. Koebnick. 2012. Higher prevalence of obesity among children with asthma. Obesity (Silver Spring) 20(5):1041-1047.

Blank, M., J. Zhang, F. Lamers, A. D. Taylor, I. B. Hickie, and K. R. Merikangas. 2015. Health correlates of insomnia symptoms and comorbid mental disorders in a nationally representative sample of US adolescents. Sleep 38(2):197-204.

Brown, B., C. Noonan, B. Bentley, K. Conway, M. Corcoran, K. FourStar, S. Gress, and S. Wagner. 2010. Acanthosis nigricans among Northern Plains American Indian children. Journal of School Nursing 26(6):450-460.

Broyles, S., P. T. Katzmarzyk, S. R. Srinivasan, W. Chen, C. Bouchard, D. S. Freedman, and G. S. Berenson. 2010. The pediatric obesity epidemic continues unabated in Bogalusa, Louisiana. Pediatrics 125(5):900-905.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

Calhoun, S. L., A. N. Vgontzas, J. Fernandez-Mendoza, S. D. Mayes, M. Tsaoussoglou, M. Basta, and E. O. Bixler. 2011. Prevalence and risk factors of excessive daytime sleepiness in a community sample of young children: The role of obesity, asthma, anxiety/depression, and sleep. Sleep 34(4):503-507.

California Department of Education. 2015. FitnessGram performance standards: Females. http://www.cde.ca.gov/ta/tg/pf/documents/pft15hfzstd.pdf (accessed March 22, 2016).

Carlson, J. A., N. C. Crespo, J. F. Sallis, R. E. Patterson, and J. P. Elder. 2012. Dietary-related and physical activity-related predictors of obesity in children: A 2-year prospective study. Childhood Obesity 8(2):110-115.

Castetbon, K., and T. Andreyeva. 2012. Obesity and motor skills among 4 to 6-year-old children in the United States: Nationally-representative surveys. BMC Pediatrics 12:28.

CDC (Centers for Disease Control and Prevention). 2009. Obesity prevalence among low-income, preschool-aged children—United States, 1998-2008. Morbidity and Mortality Weekly Report 58(28):769-773.

CDC. 2013a. National Health and Nutrition Examination Survey (NHANES) anthropometry procedures manual. http://www.cdc.gov/nchs/data/nhanes/nhanes_13_14/2013_Anthropometry.pdf (accessed March 11, 2016).

CDC. 2013b. Obesity in K-7 students—Anchorage, Alaska, 2003-04 to 2010-11 school years. Morbidity and Mortality Weekly Report 62(21):426-430.

CDC. 2013c. Vital signs: Obesity among low-income, preschool-aged children—United States, 2008-2011. Morbidity and Mortality Weekly Report 62(31):629-634.

CDC. 2015. Children’s BMI tool for schools. http://www.cdc.gov/healthyweight/assessing/bmi/childrens_BMI/tool_for_schools.html (accessed March 10, 2016).

Chen, X., and Y. Wang. 2012. Is ideal body image related to obesity and lifestyle behaviours in African American adolescents? Child: Care, Health, and Development 38(2):219-228.

Choumenkovitch, S. F., N. M. McKeown, A. Tovar, R. R. Hyatt, V. I. Kraak, A. V. Hastings, J. B. Herzog, and C. D. Economos. 2013. Whole grain consumption is inversely associated with BMI z-score in rural school-aged children. Public Health Nutrition 16(2):212-218.

Christensen, S. B., M. H. Black, N. Smith, M. M. Martinez, S. J. Jacobsen, A. H. Porter, and C. Koebnick. 2013. Prevalence of polycystic ovary syndrome in adolescents. Fertility and Sterility 100(2):470-477.

Crawford, A. G., C. Cote, J. Couto, M. Daskiran, C. Gunnarsson, K. Haas, S. Haas, S. C. Nigam, and R. Schuette. 2010. Prevalence of obesity, type II diabetes mellitus, hyperlipidemia, and hypertension in the United States: Findings from the GE Centricity Electronic Medical Record database. Population Health Management 13(3):151-161.

Crowley, D. I., P. R. Khoury, E. M. Urbina, H. M. Ippisch, and T. R. Kimball. 2011. Cardiovascular impact of the pediatric obesity epidemic: Higher left ventricular mass is related to higher body mass index. Journal of Pediatrics 158(5):709-714.

Davis, J. N., M. Koleilat, G. E. Shearrer, and S. E. Whaley. 2014. Association of infant feeding and dietary intake on obesity prevalence in low-income toddlers. Obesity (Silver Spring) 22(4):1103-1111.

Day, S. E., K. J. Konty, M. Leventer-Roberts, C. Nonas, and T. G. Harris. 2014. Severe obesity among children in New York City public elementary and middle schools, school years 2006-07 through 2010-11. Preventing Chronic Disease 11:E118.

Demment, M. M., J. D. Haas, and C. M. Olson. 2014. Changes in family income status and the development of overweight and obesity from 2 to 15 years: A longitudinal study. BMC Public Health 14:417.

Din-Dzietham, R., Y. Liu, M. V. Bielo, and F. Shamsa. 2007. High blood pressure trends in children and adolescents in national surveys, 1963 to 2002. Circulation 116(13):1488-1496.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
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Eaton, D. K., L. Kann, S. Kinchen, S. Shanklin, J. Ross, J. Hawkins, W. A. Harris, R. Lowry, T. McManus, D. Chyen, C. Lim, N. D. Brener, and H. Wechsler. 2008. Youth Risk Behavior Surveillance—United States, 2007. MMWR Surveillance Summaries 57(4):1-131.

Eaton, D. K., L. Kann, S. Kinchen, S. Shanklin, J. Ross, J. Hawkins, W. A. Harris, R. Lowry, T. McManus, D. Chyen, C. Lim, L. Whittle, N. D. Brener, and H. Wechsler. 2010. Youth Risk Behavior Surveillance—United States, 2009. MMWR Surveillance Summaries 59(5):1-142.

Eaton, D. K., L. Kann, S. Kinchen, S. Shanklin, K. H. Flint, J. Hawkins, W. A. Harris, R. Lowry, T. McManus, D. Chyen, L. Whittle, C. Lim, and H. Wechsler. 2012. Youth Risk Behavior Surveillance—United States, 2011. MMWR Surveillance Summaries 61(4):1-162.

Economos, C. D., R. R. Hyatt, J. P. Goldberg, A. Must, E. N. Naumova, J. J. Collins, and M. E. Nelson. 2007. A community intervention reduces BMI z-score in children: Shape Up Somerville first year results. Obesity (Silver Spring) 15(5):1325-1336.

Eilerman, P. A., C. M. Herzog, B. K. Luce, S. Y. Chao, S. M. Walker, L. A. Zarzabal, and D. H. Carnahan. 2014. A comparison of obesity prevalence: Military health system and United States populations, 2009-2012. Military Medicine 179(5):462-470.

Entzel, P., E. A. Whitsel, A. Richardson, J. Tabor, S. Hallquist, J. Hussey, C. T. Halpern, and K. M. Harris. 2009. Cardiovascular and anthropometric measures. Carolina Population Center. Add Health Wave IV Documentation.

Ezendam, N. P., A. E. Springer, J. Brug, A. Oenema, and D. H. Hoelscher. 2011. Do trends in physical activity, sedentary, and dietary behaviors support trends in obesity prevalence in 2 border regions in Texas? Journal of Nutrition Education and Behavior 43(4):210-218.

Fakhouri, T. H., J. P. Hughes, D. J. Brody, B. K. Kit, and C. L. Ogden. 2013. Physical activity and screen-time viewing among elementary school-aged children in the United States from 2009 to 2010. JAMA Pediatrics 167(3):223-229.

FitnessGram. 2016. California physical fitness test: Body mass index. Sacramento, CA: California Department of Education.

Foley, J. T., M. Lloyd, D. Vogl, and V. A. Temple. 2014. Obesity trends of 8-18 year old Special Olympians: 2005-2010. Research in Developmental Disabilities 35(3):705-710.

Freedman, D. S., L. K. Khan, M. K. Serdula, C. L. Ogden, and W. H. Dietz. 2006. Racial and ethnic differences in secular trends for childhood BMI, weight, and height. Obesity (Silver Spring) 14(2):301-308.

Freedman, D. S., A. Goodman, O. A. Contreras, P. DasMahapatra, S. R. Srinivasan, and G. S. Berenson. 2012. Secular trends in BMI and blood pressure among children and adolescents: The Bogalusa heart study. Pediatrics 130(1):e159-e166.

Gamble, A., D. Waddell, M. A. Ford, J. P. Bentley, C. D. Woodyard, and J. S. Hallam. 2012. Obesity and health risk of children in the Mississippi delta. Journal of School Health 82(10):478-483.

Gee, S., D. Chin, L. Ackerson, D. Woo, and A. Howell. 2013. Prevalence of childhood and adolescent overweight and obesity from 2003 to 2010 in an integrated health care delivery system. Journal of Obesity 2013:417907.

George, M. G., X. Tong, E. V. Kuklina, and D. R. Labarthe. 2011. Trends in stroke hospitalizations and associated risk factors among children and young adults, 1995-2008. Annals of Neurology 70(5):713-721.

Gibson, R. S. 1990. Principles of nutritional assessment. New York: Oxford University Press.

Goodwin, J. L., P. L. Enright, K. L. Kaemingk, G. M. Rosen, W. J. Morgan, R. F. Fregosi, and S. F. Quan. 2001. Feasibility of using unattended polysomnography in children for research—Report of the Tucson Children’s Assessment of Sleep Apnea Study (TuCASA). Sleep 24(8):937-944.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

Gordon-Larsen, P., N. S. The, and L. S. Adair. 2010. Longitudinal trends in obesity in the United States from adolescence to the third decade of life. Obesity (Silver Spring) 18(9):1801-1804.

Halloran, D. R., N. E. Marshall, R. M. Kunovich, and A. B. Caughey. 2012. Obesity trends and perinatal outcomes in black and white teenagers. American Journal of Obstettrics and Gynecology 207(6):492.e1-492.e7.

Harris, K. M., P. Gordon-Larsen, K. Chantala, and J. R. Udry. 2006. Longitudinal trends in race/ethnic disparities in leading health indicators from adolescence to young adulthood. Archices of Pediatrics and Adolescent Medince 160(1):74-81.

Hearst, M. O., M. N. Laska, J. H. Himes, M. Butterbrodt, A. Sinaiko, R. Iron Cloud, M. Tobacco, and M. Story. 2011. The co-occurrence of obesity, elevated blood pressure, and acanthosis nigricans among American Indian school children: Identifying individual heritage and environment-level correlates. American Journal of Human Biology 23(3):346-352.

Hearst, M. O., K. Biskeborn, M. Christensen, and C. Cushing. 2013. Trends of overweight and obesity among white and American Indian school children in South Dakota, 1998-2010. Obesity (Silver Spring) 21(1):E26-E32.

Hernandez-Valero, M. A., L. P. Bustamante-Montes, M. Hernandez, E. Halley-Castillo, A. V. Wilkinson, M. L. Bondy, and N. Olvera. 2012. Higher risk for obesity among Mexican-American and Mexican immigrant children and adolescents than among peers in Mexico. Journal of Immigrant and Minority Health 14(4):517-522.

Hinkle, S. N., A. J. Sharma, S. Y. Kim, S. Park, K. Dalenius, P. L. Brindley, and L. M. Grummer-Strawn. 2012. Prepregnancy obesity trends among low-income women, United States, 1999-2008. Maternal and Child Health Journal 16(7):1339-1348.

Holtby, S., E. Zahnd, and D. Grant. 2015. Ten-year trends in the health of young children in California: 2003 to 2011-2012. Policy Brief (UCLA Center for Health Policy Research) (PB2015-2):1-10.

Hruby, A., O. T. Hill, L. Bulathsinhala, C. J. McKinnon, S. J. Montain, A. J. Young, and T. J. Smith. 2015. Trends in overweight and obesity in soldiers entering the US Army, 1989-2012. Obesity (Silver Spring) 23(3):662-670.

Hsu, L. L., R. L. Nevin, S. K. Tobler, and M. V. Rubertone. 2007. Trends in overweight and obesity among 18-year-old applicants to the United States military, 1993-2006. Journal of Adolescent Health 41(6):610-612.

Huang, D. Y., H. I. Lanza, K. Wright-Volel, and M. D. Anglin. 2013. Developmental trajectories of childhood obesity and risk behaviors in adolescence. Journal of Adolescence 36(1):139-148.

Huh, D., E. Stice, H. Shaw, and K. Boutelle. 2012. Female overweight and obesity in adolescence: Developmental trends and ethnic differences in prevalence, incidence, and remission. Journal of Youth and Adolescence 41(1):76-85.

Iannotti, R. J., and J. Wang. 2013. Trends in physical activity, sedentary behavior, diet, and BMI among US adolescents, 2001-2009. Pediatrics 132(4):606-614.

Jin, Y., and J. C. Jones-Smith. 2015. Associations between family income and children’s physical fitness and obesity in California, 2010-2012. Preventing Chronic Disease 12:E17.

Johnson, W., L. E. Soloway, D. Erickson, A. C. Choh, M. Lee, W. C. Chumlea, R. M. Siervogel, S. A. Czerwinski, B. Towne, and E. W. Demerath. 2012. A changing pattern of childhood BMI growth during the 20th century: 70 y of data from the Fels Longitudinal Study. American Journal of Clinical Nutrition 95(5):1136-1143.

Johnson, W., W. C. Chumlea, S. A. Czerwinski, and E. W. Demerath. 2013. Secular trends in the fat and fat-free components of body mass index in children aged 8-18 years born 1958-1995. Annal of Human Biology 40(1):107-110.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

Joyce, N., G. A. Wellenius, D. D. Dore, J. W. Newburger, and J. P. Zachariah. 2015. Patterns of lipid lowering therapy among children ages 8-20 years. Journal of Pediatrics 167(1):113-119.

Kallem, S., A. Carroll-Scott, L. Rosenthal, E. Chen, S. M. Peters, C. McCaslin, and J. R. Ickovics. 2013. Shift-and-persist: A protective factor for elevated BMI among low-socioeconomic-status children. Obesity (Silver Spring) 21(9):1759-1763.

Kann, L., S. Kinchen, S. L. Shanklin, K. H. Flint, J. Kawkins, W. A. Harris, R. Lowry, E. O. Olsen, T. McManus, D. Chyen, L. Whittle, E. Taylor, Z. Demissie, N. Brener, J. Thornton, J. Moore, and S. Zaza. 2014. Youth Risk Behavior Surveillance—United States, 2013. MMWR Surveillance Summaries 63(Suppl 4):1-168.

Kern, E., N. L. Chan, D. W. Fleming, and J. W. Krieger. 2014. Declines in student obesity prevalence associated with a prevention initiative—King County, Washington, 2012. Morbidity and Mortality Weekly Report 63(7):155-157.

Khoury, M., C. Manlhiot, and B. W. McCrindle. 2013. Role of the waist/height ratio in the cardiometabolic risk assessment of children classified by body mass index. Journal of the American College of Cardiology 62(8):742-751.

Kim, J. 2012. Are physical education-related state policies and schools’ physical education requirement related to children’s physical activity and obesity? Journal of School Health 82(6):268-276.

Kim, J., B. Mutyala, S. Agiovlasitis, and B. Fernhall. 2011. Health behaviors and obesity among US children with attention deficit hyperactivity disorder by gender and medication use. Preventive Medicine 52(3-4):218-222.

Koebnick, C., D. Getahun, K. Reynolds, K. J. Coleman, A. H. Porter, J. M. Lawrence, M. Punyanitya, V. P. Quinn, and S. J. Jacobsen. 2009. Trends in nonalcoholic fatty liver disease-related hospitalizations in US children, adolescents, and young adults. Journal of Pediatric Gastroenterology and Nutrition 48(5):597-603.

Kolbo, J. R., M. G. Armstrong, L. C. Blom, W. Bounds, H. Dickerson, B. Harbaugh, E. F. Molaison, and L. Zhang. 2008. Prevalence of obesity and overweight among children and youth in Mississippi: Current trends in weight status. Journal of the Mississippi State Medical Association 49(8):231-237.

Kolbo, J. R., L. Zhang, E. F. Molaison, B. L. Harbaugh, G. M. Hudson, M. G. Armstrong, and N. Werle. 2012. Prevalence and trends in overweight and obesity among Mississippi public school students, 2005-2011. Journal of the Mississippi State Medical Association 53(5):140-146.

Lalwani, A. K., K. Katz, Y. H. Liu, S. Kim, and M. Weitzman. 2013. Obesity is associated with sensorineural hearing loss in adolescents. Laryngoscope 123(12):3178-3184.

Langer-Gould, A., S. M. Brara, B. E. Beaber, and C. Koebnick. 2013. Childhood obesity and risk of pediatric multiple sclerosis and clinically isolated syndrome. Neurology 80(6):548-552.

Larson, N. I., M. M. Wall, M. T. Story, and D. R. Neumark-Sztainer. 2013. Home/family, peer, school, and neighborhood correlates of obesity in adolescents. Obesity (Silver Spring) 21(9):1858-1869.

Lasserre, A. M., A. Chiolero, F. Paccaud, and P. Bovet. 2007. Worldwide trends in childhood obesity. Swiss Medical Weekly 137(9-10):157-158.

Lawman, H. G., G. Mallya, S. V. Veur, T. McCoy, L. Colby, T. Sanders, J. Wylie-Rosett, and G. D. Foster. 2015. Trends in relative weight over 1 year in low-income urban youth. Obesity (Silver Spring) 23(2):436-442.

Lee, H., D. Lee, G. Guo, and K. M. Harris. 2011. Trends in body mass index in adolescence and young adulthood in the United States: 1959-2002. Journal of Adolescent Health 49(6):601-608.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

Lee, J. M., S. Pilli, A. Gebremariam, C. C. Keirns, M. M. Davis, S. Vijan, G. L. Freed, W. H. Herman, and J. G. Gurney. 2010. Getting heavier, younger: Trajectories of obesity over the life course. International Journal of Obesity (London) 34(4):614-623.

Lemay, C. A., D. S. Elfenbein, S. B. Cashman, and M. E. Felice. 2008. The body mass index of teen mothers and their toddler children. Maternal and Child Health Journal 12(1):112-118.

Li, Y., S. Raychowdhury, S. H. Tedders, R. Lyn, A. Lopez-De Fede, and J. Zhang. 2012. Association between increased BMI and severe school absenteeism among US children and adolescents: Findings from a national survey, 2005-2008. International Journal of Obesity (London) 36(4):517-523.

Lilly, C. L., Y. D. Gebremariam, L. Cottrell, C. John, and W. Neal. 2014. Trends in serum lipids among 5th grade CARDIAC participants, 2002-2012. Journal of Epidemiology and Community Health 68(3):218-223.

Lo, J. C., B. Maring, M. Chandra, S. R. Daniels, A. Sinaiko, M. F. Daley, N. E. Sherwood, E. O. Kharbanda, E. D. Parker, K. F. Adams, R. J. Prineas, D. J. Magid, P. J. O’Connor, and L. C. Greenspan. 2014. Prevalence of obesity and extreme obesity in children aged 3-5 years. Pediatric Obesity 9(3):167-175.

Lohman, T. G. 1993. Advances in body composition assessment. Current Issues in Exercise Science (Monograph No. 3) 5(2):200-201.

Lohman, T. G., A. F. Roche, and R. Martorell. 1988. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Books.

Lohman, T. G., A. F. Roche, and R. Martorell. 1991. Anthropometric standardization reference manual: Abridged edition. Champaign, IL: Human Kinetics Books.

Lohrmann, D., A. YoussefAgha, and W. Jayawardene. 2014. Trends in body mass index and prevalence of extreme high obesity among Pennsylvania children and adolescents, 2007-2011: Promising but cautionary. American Journal of Public Health 104(4):e62-e68.

Madsen, K. A., A. E. Weedn, and P. B. Crawford. 2010. Disparities in peaks, plateaus, and declines in prevalence of high BMI among adolescents. Pediatrics 126(3):434-442.

May, A. L., E. V. Kuklina, and P. W. Yoon. 2012. Prevalence of cardiovascular disease risk factors among US adolescents, 1999-2008. Pediatrics 129(6):1035-1041.

Molaison, E. F., J. R. Kolbo, L. Zhang, B. Harbaugh, M. G. Armstrong, K. Rushing, L. C. Blom, and A. Green. 2010. Prevalence and trends in obesity among Mississippi public school students, 2005-2009. Journal of the Mississippi State Medical Association 51(3):67-72.

Murasko, J. E. 2011. Trends in the associations between family income, height and body mass index in US children and adolescents: 1971-1980 and 1999-2008. Annals of Human Biology 38(3):290-306.

Nader, N., V. Singhal, A. Javed, A. Weaver, and S. Kumar. 2014. Temporal trends in the diagnosis and management of childhood obesity/overweight in primary care. Journal of Primary Care and Community Health 5(1):44-49.

Nafiu, O. O., A. Zepeda, C. Curcio, and Y. Prasad. 2014. Association of neck circumference and obesity status with elevated blood pressure in children. Journal of Human Hypertension 28(4):263-268.

Najarian, M., K. Snow, J. Lennon, and S. Kinsey. 2010. Early Childhood Longitudinal Study, Birth Cohort (ECLS-B), preschool–kindergarten 2007 psychometric report. Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. (NCES 2010-009).

Neumark-Sztainer, D., M. M. Wall, N. Larson, M. Story, J. A. Fulkerson, M. E. Eisenberg, and P. J. Hannan. 2012. Secular trends in weight status and weight-related attitudes and behaviors in adolescents from 1999 to 2010. Preventive Medicine 54(1):77-81.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

New York City Department of Education. 2016. NYC FITNESSGRAM. http://schools.nyc.gov/teachers/resources/classroom/fitnesshealth/videos/fitnessassessmentvideo.htm (accessed March 21, 2016).

Ng, M., T. Fleming, M. Robinson, et al. 2014. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: A systematic analysis for the global burden of disease study 2013. Lancet 384(9945):766-781.

Nickelson, J., C. A. Bryant, R. J. McDermott, E. R. Buhi, and R. D. Debate. 2012. A modified obesity proneness model predicts adolescent weight concerns and inability to self-regulate eating. Journal of School Health 82(12):560-571.

Ogden, C. L., M. D. Carroll, L. R. Curtin, M. A. McDowell, C. J. Tabak, and K. M. Flegal. 2006. Prevalence of overweight and obesity in the United States, 1999-2004. Journal of the American Medical Association 295(13):1549-1555.

Ogden, C. L., M. D. Carroll, B. K. Kit, and K. M. Flegal. 2012. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999-2010. Journal of the American Medical Association 307(5):483-490.

Ogden, C. L., M. D. Carroll, B. K. Kit, and K. M. Flegal. 2014. Prevalence of childhood and adult obesity in the United States, 2011-2012. Journal of the American Medical Association 311(8):806-814.

Ohio Department of Health. 2010. Guidelines for measuring heights and weights and calculation of body mass index-for-age in Ohio’s schools. https://www.odh.ohio.gov/~/media/ODH/ASSETS/Files/chss/school%20nursing/bmiscreeningguidelines.pdf (accessed March 15, 2016).

Okosun, I. S., J. M. Boltri, R. Lyn, and M. Davis-Smith. 2010. Continuous metabolic syndrome risk score, body mass index percentile, and leisure time physical activity in American children. Journal of Clinincal Hypertension (Greenwich) 12(8):636-644.

Oza-Frank, R., E. M. Hade, A. Norton, H. Scarpitti, and E. J. Conrey. 2013. Trends in body mass index among Ohio’s third-grade children: 2004-2005 to 2009-2010. Journal of the Academy of Nutrition and Dietetics 113(3):440-446.

Pan, L., H. M. Blanck, B. Sherry, K. Dalenius, and L. M. Grummer-Strawn. 2012. Trends in the prevalence of extreme obesity among US preschool-aged children living in low-income families, 1998-2010. Journal of the American Medical Association 308(24):2563-2565.

Pennsylvania Department of Health. 2011. Procedures for the growth screening program for Pennsylvania’s school-age population. http://www.chadphila.org/files/CHADassets/pdf/health/d1.pdf (accessed March 21, 2016).

Reed, M., B. Dancy, K. Holm, J. Wilbur, and L. Fogg. 2013. Eating behaviors among early adolescent African American girls and their mothers. Journal of School Nursing 29(6):452-463.

Ritzman, R., and L. Elmore. 2006. Obesity and overweight in North Carolina: Prevalence, trends, and risk factors. North Carolina Medical Journal 67(4):329-330.

Robbins, J. M., G. Mallya, M. Polansky, and D. F. Schwarz. 2012. Prevalence, disparities, and trends in obesity and severe obesity among students in the Philadelphia, Pennsylvania, school district, 2006-2010. Preventing Chronic Disease 9:E145.

Robinson, W. R., K. M. Keyes, R. L. Utz, C. L. Martin, and Y. Yang. 2013. Birth cohort effects among US-born adults born in the 1980s: Foreshadowing future trends in US obesity prevalence. International Journal of Obesity (London) 37(3):448-454.

Rodríguez-Colón, S. M., E. O. Bixler, X. Li, A. N. Vgontzas, and D. Liao. 2011. Obesity is associated with impaired cardiac autonomic modulation in children. International Journal of Pediatric Obesity 6(2):128-134.

Rogozinski, B. M., J. R. Davids, R. B. Davis, L. M. Christopher, J. P. Anderson, G. G. Jameson, and D. W. Blackhurst. 2007. Prevalence of obesity in ambulatory children with cerebral palsy. Journal of Bone and Joint Surgery. American Volume 89(11):2421-2426.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

Rosner, B., N. R. Cook, S. Daniels, and B. Falkner. 2013. Childhood blood pressure trends and risk factors for high blood pressure: The NHANES experience 1988-2008. Hypertension 62(2):247-254.

Rossen, L. M., and K. C. Schoendorf. 2012. Measuring health disparities: Trends in racial-ethnic and socioeconomic disparities in obesity among 2- to 18-year old youth in the United States, 2001-2010. Annals of Epidemiology 22(10):698-704.

Rundle, A., C. Richards, M. D. Bader, O. Schwartz-Soicher, K. K. Lee, J. Quinn, G. S. Lovasi, C. Weiss, and K. Neckerman. 2012. Individual- and school-level sociodemographic predictors of obesity among New York City public school children. American Journal of Epidemiology 176(11):986-994.

Saab, P. G., S. Fitzpatrick, B. Lai, and J. R. McCalla. 2011. Elevated body mass index and obesity among ethnically diverse adolescents. Ethnicity and Disease 21(2):176-182.

Saland, J. M., C. B. Pierce, M. M. Mitsnefes, J. T. Flynn, J. Goebel, J. C. Kupferman, B. A. Warady, and S. L. Furth. 2010. Dyslipidemia in children with chronic kidney disease. Kidney International 78(11):1154-1163.

Salihu, H. M., S. Luke, A. P. Alio, A. Deutsch, and P. J. Marty. 2010. The impact of obesity on spontaneous and medically indicated preterm birth among adolescent mothers. Archives of Gynecology and Obstetrics 282(2):127-134.

Sanchez-Vaznaugh, E. V., B. N. Sanchez, P. B. Crawford, and S. Egerter. 2015. Association between competitive food and beverage policies in elementary schools and childhood overweight/obesity trends: Differences by neighborhood socioeconomic resources. JAMA Pediatrics 169(5):e150781.

Sekhobo, J. P., L. S. Edmunds, D. K. Reynolds, K. Dalenius, and A. Sharma. 2010. Trends in prevalence of obesity and overweight among children enrolled in the New York State WIC program, 2002-2007. Public Health Reports 125(2):218-224.

Sekhobo, J. P., L. S. Edmunds, K. Dalenius, J. Jernigan, C. F. Davis, M. Giddings, C. Lesesne, and L. Kettel Khan. 2014. Neighborhood disparities in prevalence of childhood obesity among low-income children before and after implementation of New York City child care regulations. Preventing Chronic Disease 11:E181.

Shustak, R. J., S. B. McGuire, T. W. October, C. K. Phoon, and A. J. Chun. 2012. Prevalence of obesity among patients with congenital and acquired heart disease. Pediatric Cardiology 33(1):8-14.

Simmons, S., J. L. Alexander, H. Ewing, and S. Whetzel. 2012. SNAP participation in preschool-aged children and prevalence of overweight and obesity. Journal of School Health 82(12):548-552.

Skelton, J. A., S. R. Cook, P. Auinger, J. D. Klein, and S. E. Barlow. 2009. Prevalence and trends of severe obesity among US children and adolescents. Academic Pediatrics 9(5):322-329.

Skinner, A. C., and J. A. Skelton. 2014. Prevalence and trends in obesity and severe obesity among children in the United States, 1999-2012. JAMA Pediatrics 168(6):561-566.

Skinner, A. C., E. M. Perrin, L. A. Moss, and J. A. Skelton. 2015. Cardiometabolic risks and severity of obesity in children and young adults. New England Journal of Medicine 373(14):1307-1317.

Slater, S. J., L. Nicholson, J. Chriqui, D. C. Barker, F. J. Chaloupka, and L. D. Johnston. 2013. Walkable communities and adolescent weight. American Journal of Preventive Medicine 44(2):164-168.

Song, W. O., Y. Wang, C. E. Chung, B. Song, W. Lee, and O. K. Chun. 2012. Is obesity development associated with dietary sugar intake in the U.S.? Nutrition 28(11-12):1137-1141.

Special Olympics International. 2007. Healthy choices, healthy athletes: Health promotion guide for clinical directors: Special Olympics International.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
×

Spilsbury, J. C., A. Storfer-Isser, C. L. Rosen, and S. Redline. 2015. Remission and incidence of obstructive sleep apnea from middle childhood to late adolescence. Sleep 38(1):23-29.

Staiano, A. E., S. T. Broyles, A. K. Gupta, and P. T. Katzmarzyk. 2013. Ethnic and sex differences in visceral, subcutaneous, and total body fat in children and adolescents. Obesity (Silver Spring) 21(6):1251-1255.

Stark, M. J., V. P. Niederhauser, J. M. Camacho, and L. Shirai. 2011. The prevalence of overweight and obesity in children at a Health Maintenance Organization in Hawai’i. Hawaii Medical Journal 70(7 Supplement 1):27-31.

Stingone, J. A., O. F. Ramirez, K. Svensson, and L. Claudio. 2011. Prevalence, demographics, and health outcomes of comorbid asthma and overweight in urban children. Journal of Asthma 48(9):876-885.

Suglia, S. F., S. Kara, and W. R. Robinson. 2014. Sleep duration and obesity among adolescents transitioning to adulthood: Do results differ by sex? Journal of Pediatrics 165(4):750-754.

Sun, S. S., X. Deng, R. Sabo, R. Carrico, C. M. Schubert, W. Wan, and C. Sabo. 2012. Secular trends in body composition for children and young adults: The Fels Longitudinal Study. American Journal of Human Biology 24(4):506-514.

Taber, D. R., J. Stevens, C. Poole, M. L. Maciejewski, K. R. Evenson, and D. S. Ward. 2012. State disparities in time trends of adolescent body mass index percentile and weight-related behaviors in the United States. Journal of Community Health 37(1):242-252.

Taylor, W. C., S. L. Upchurch, C. A. Brosnan, B. J. Selwyn, T. Q. Nguyen, E. T. Villagomez, and J. C. Meininger. 2014. Features of the built environment related to physical activity friendliness and children’s obesity and other risk factors. Public Health Nursing 31(6):545-555.

Texas School Physical Activity and Nutrition (SPAN). 2016. Training on measuring heights and weights. https://www.youtube.com/watch?v=hoio5ySq04w&feature=youtu.be (accessed March 21, 2016).

Tovar, A., K. Chui, R. R. Hyatt, J. Kuder, V. I. Kraak, S. F. Choumenkovitch, A. Hastings, J. Bloom, and C. D. Economos. 2012. Healthy-lifestyle behaviors associated with overweight and obesity in US rural children. BMC Pediatrics 12:102.

Trasande, L., T. M. Attina, and J. Blustein. 2012. Association between urinary bisphenol A concentration and obesity prevalence in children and adolescents. Journal of the American Medical Association 308(11):1113-1121.

Ver Ploeg, M., L. Mancino, B. H. Lin, and J. Guthrie. 2008. US food assistance programs and trends in children’s weight. International Journal of Pediatric Obesity 3(1):22-30.

von Hippel, P. T., and R. W. Nahhas. 2013. Extending the history of child obesity in the United States: The Fels Longitudinal Study, birth years 1930-1993. Obesity (Silver Spring) 21(10):2153-2156.

Wang, Y., and Q. Zhang. 2006. Are American children and adolescents of low socioeconomic status at increased risk of obesity? Changes in the association between overweight and family income between 1971 and 2002. American Journal of Clinical Nutrition 84(4):707-716.

Wang, Y., H. Liang, and X. Chen. 2009. Measured body mass index, body weight perception, dissatisfaction and control practices in urban, low-income African American adolescents. BMC Public Health 9(1):1-12

Wang, Y. C., C. T. Orleans, and S. L. Gortmaker. 2012. Reaching the healthy people goals for reducing childhood obesity: Closing the energy gap. American Journal of Preventive Medicine 42(5):437-444.

Warner, M., R. Aguilar Schall, K. G. Harley, A. Bradman, D. Barr, and B. Eskenazi. 2013. In utero DDT and DDE exposure and obesity status of 7-year-old Mexican-American children in the CHAMACOS cohort. Environmental Health Perspectives 121(5):631-636.

Suggested Citation:"Appendix D: Presentation of Findings." National Academies of Sciences, Engineering, and Medicine. 2016. Assessing Prevalence and Trends in Obesity: Navigating the Evidence. Washington, DC: The National Academies Press. doi: 10.17226/23505.
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Weedn, A. E., J. J. Hale, D. M. Thompson, and P. M. Darden. 2014. Trends in obesity prevalence and disparities among low-income children in Oklahoma, 2005-2010. Childhood Obesity 10(4):318-325.

Wen, X., M. W. Gillman, S. L. Rifas-Shiman, B. Sherry, K. Kleinman, and E. M. Taveras. 2012. Decreasing prevalence of obesity among young children in Massachusetts from 2004 to 2008. Pediatrics 129(5):823-831.

Williamson, D. A., H. Han, W. D. Johnson, T. M. Stewart, and D. W. Harsha. 2011. Longitudinal study of body weight changes in children: Who is gaining and who is losing weight. Obesity (Silver Spring) 19(3):667-670.

Wilson, A. C., M. F. Schneider, C. Cox, L. A. Greenbaum, J. Saland, C. T. White, S. Furth, B. A. Warady, and M. M. Mitsnefes. 2011. Prevalence and correlates of multiple cardiovascular risk factors in children with chronic kidney disease. Clinical Journal of the American Society of Nephrology 6(12):2759-2765.

WHO (World Health Organization). 2008. STEPS surveillance manual. Geneva: World Health Organization.

YoussefAgha, A. H., D. K. Lohrmann, and W. P. Jayawardene. 2013. Use of data mining to reveal body mass index (BMI): Patterns among Pennsylvania schoolchildren, pre-k to grade 12. Journal of School Health 83(2):85-92.

Zachariah, J. P., D. A. Graham, S. D. de Ferranti, R. S. Vasan, J. W. Newburger, and G. F. Mitchell. 2014. Temporal trends in pulse pressure and mean arterial pressure during the rise of pediatric obesity in US children. Journal of the American Heart Association 3(3):e000725.

Zhang, L., J. R. Kolbo, M. Kirkup, E. F. Molaison, B. L. Harbaugh, N. Werle, and E. Walker. 2014. Prevalence and trends in overweight and obesity among Mississippi public school students, 2005-2013. Journal of the Mississippi State Medical Association 55(3):80-87.

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Obesity has come to the forefront of the American public health agenda. The increased attention has led to a growing interest in quantifying obesity prevalence and determining how the prevalence has changed over time. Estimates of obesity prevalence and trends are fundamental to understanding and describing the scope of issue. Policy makers, program planners, and other stakeholders at the national, state, and local levels are among those who search for estimates relevant to their population(s) of interest to inform their decision-making. The differences in the collection, analysis, and interpretation of data have given rise to a body of evidence that is inconsistent and has created barriers to interpreting and applying published reports. As such, there is a need to provide guidance to those who seek to better understand and use estimates of obesity prevalence and trends.

Assessing Prevalence and Trends in Obesity examines the approaches to data collection, analysis, and interpretation that have been used in recent reports on obesity prevalence and trends at the national, state, and local level, particularly among U.S. children, adolescents, and young adults. This report offers a framework for assessing studies on trends in obesity, principally among children and young adults, for policy making and program planning purposes, and recommends ways decision makers and others can move forward in assessing and interpreting reports on obesity trends.

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