- Email: [email protected]
Disparities in Obesity and Related Conditions Among Americans with Disabilities
Disparities in Obesity and Related Conditions Among Americans with Disabilities Katherine Froehlich-Grobe, PhD, Jaehoon Lee, PhD, Richard A. Washburn, PhD Background: Despite representing nearly 20% of the U.S. population, individuals with disabilities are invisible in obesity surveillance and intervention efforts. Purpose: The current study (1) compares obesity and extreme obesity prevalence between Americans with and without disabilities and (2) examines the association between BMI category and weight-related chronic disease risk factors in both groups. Methods: In 2012, six waves of data from the National Health and Nutrition Examination Survey (NHANES, 1999–2010) were pooled to compare the prevalence of obesity and extreme obesity between adults (aged ≥20 years, N¼31,990) with disabilities (n¼11,556) versus without disabilities (n¼ 20,434). Chronic disease risk factors (blood pressure, lipids, C-reactive protein [CRP], glucose) were compared across weight categories, by disability severity, and disability status. Results: Obesity (41.6%) and extreme obesity (9.3%) prevalence among those with disabilities were significantly higher than they were among those without disabilities (29.2% and 3.9%, respectively). Disability severity and disability status negatively affected nearly all chronic disease risk factors. Additionally, there was a disability-by-weight interaction: people with disabilities at all weight categories were significantly more likely to report being told they had hypertension, high cholesterol, or diabetes and to have been prescribed antihypertensive and lipid-lowering medications. Conclusions: The prevalence of obesity (41.6%) and extreme obesity (9.3%) found in individuals with disabilities is high. When compared to obese adults without disabilities, obese adults with disabilities are more likely to have diabetes, high cholesterol, hypertension, and higher CRP. Thus, the study provides convincing evidence of obesity-related health disparities between Americans with and without disabilities. (Am J Prev Med 2013;45(1):83–90) & 2013 American Journal of Preventive Medicine
Introduction
C
urrently, 54 million Americans (20% of the adult population) experience disability.1 Disability prevalence is expected to increase2 for several reasons, including (1) recent medical advances that have increased survival rates following traumatic injury, premature birth, and combat injuries incurred in Mideast conflicts (where those injured outnumber those killed3
From the University of Texas School of Public Health (Froehlich-Grobe), Dallas Regional Campus, Dallas, Texas, Center for Research Methods and Data Analysis (Lee), Center for Physical Activity and Weight Management (Washburn), Life Span Institute, University of Kansas, Lawrence, and Cardiovascular Research Institute, University of Kansas Medical Center, Kansas City, Kansas Address correspondence to: Katherine Froehlich-Grobe, PhD, UT School of Public Health, Dallas Regional Campus, 6011 Harry Hines Blvd., V8.112, Dallas TX 75390. E-mail: [email protected]. 0749-3797/$36.00 http://dx.doi.org/10.1016/j.amepre.2013.02.021
& 2013 American Journal of Preventive Medicine
by 7.5 to 1); (2) increased life expectancy for those born with disability or who acquire disability; and (3) aging of the “baby-boomer” generation. For all individuals, with or without disabilities, excess weight increases risk for chronic conditions such as type 2 diabetes, hypertension, hyperlipidemia, osteoarthritis, stroke, specific cancers, and metabolic syndrome; it also may limit physical function, independence, and productivity.4 However, individuals with disabilities are underserved by national efforts targeting surveillance, treatment, and prevention of obesity,5 even though this condition is thought to be more prevalent in those with disabilities compared to those without.6 Estimates from self-report data from the Behavioral Risk Factor Surveillance System7,8 (BRFSS, 1998–1999, 2001–2003) and the National Health Interview Survey6,9 (NHIS, 1994–1995, 2001–2005) reveal that the prevalence of obesity (BMI ≥30) is higher among individuals with disabilities (24.9%–31.6%) than without (15.1%–18.7%).
Published by Elsevier Inc.
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However, these data likely underestimate prevalence, as individuals with disabilities, like their nondisabled counterparts,10–13 tend to overestimate height and underestimate weight, resulting in lower BMI and obesity prevalence.14 Arguably, obesity prevalence estimates for people with disabilities should be based on measured height and weight data, such as those available from NHANES. Since 1999, NHANES has conducted annual crosssectional surveys of approximately 5000 individuals using a complex survey design to select participants representative of the non-institutionalized U.S. population. NHANES is the only ongoing national health survey that combines self-report interview data with physical examinations at a mobile examination center where anthropometric measures and laboratory data on disease risk factors are collected and includes questions to identify individuals with functional limitations. The purpose of the current study was to use NHANES data to compare obesity prevalence between individuals with disabilities and those without, and to assess the association between BMI category and weight-related chronic disease risk factors in both groups.
Methods Data analyses were performed in June 2012 by pooling six waves of publicly available NHANES data (1999–2000, 2001–2002, 2003– 2004, 2005–2006, 2007–2008, 2009–2010). Pooling data across years ensured an adequate sample size of adults (aged ≥20 years) with disabilities. Participants were classified as having mobility or nonmobility limitations based on self-report data using the schema of Rasch et al.15 Adults were identified as having a disability if they reported difficulty (some, much, or unable to do) with one or more of the following: (1) walking without special equipment use; (2) walking 0.25 miles; (3) walking ten steps without stopping; (4) stooping, crouching, or kneeling; (5) walking from one room to another on the same level; (6) standing up from an armless straight chair; or (7) standing or being on their feet for 2 hours. Individuals who reported difficulty (some, much, or unable to do) with one or more of the following activities were considered to have a nonmobility limitation: (1) being limited because of difficulty remembering or having periods of confusion; (2) being limited in any way in any activity because of a physical, mental, or emotional problem; (3) getting in and out of bed; (4) eating, such as holding a fork, cutting food, or drinking from a glass; (5) dressing, including tying shoes, working zippers, and doing buttons; (6) reaching up over their head; (7) using their fingers to grasp small objects; (8) lifting or carrying something as heavy as 10 pounds; (9) doing housework such as vacuuming, sweeping, dusting; (10) preparing their own meals; (11) managing money; or (12) responded affirmatively to a question about using special equipment due to a health problem. Respondents without mobility or nonmobility limitations were categorized as having no disability. Impairment severity was calculated by summing respondent reports of their level of difficulty in performing each assessed task. NHANES also collects information about the top three health conditions that limit function.
Anthropometric and laboratory data including weight, height, waist circumference, body composition by dual-energy x-ray absorptiometry (DXA); blood pressure; lipid profile (total cholesterol, high-density lipoprotein [HDL], low-density lipoprotein [LDL], triglycerides); C-reactive protein (CRP); and fasting glucose were assessed in a mobile examination center using standardized techniques and equipment.16 BMI was calculated by standard formula. Weight categories were based on BMI using National Heart, Lung, and Blood Institute (NHLBI) guidelines, as follows17: underweight/normal weight¼≤24.9; overweight¼25.0–29.9; obese¼≥30.0; and extreme obesity (Class III)¼ ≥40. Demographic data including age, gender, ethnicity, education, marital status, and information on physical functioning to determine disability status were obtained by in-person interview. Data on smoking status; physician-diagnosed high bold pressure, cholesterol, and diabetes; and prescribed medication use were obtained from the relevant self-report questionnaire sections. All variables selected for analysis were available for all study years, with the exception of percentage body fat, as NHANES has not released body fat data from DXA scans since 2004.
Data Analysis The NHANES uses probability sampling and weighting methodology. Ignoring its complex design can lead to biased population estimates and overstated significance levels. Thus, the current study followed NHANES guidelines18 to account for the design features, including stratification, cluster sampling, and weighting. First, sample weights were rescaled by taking correct proportions of the original 4- and 2-year weights when combining 12 years (six waves) of NHANES data. For example, the 4-year weight provided for 1999–2002 was multiplied by 2/6; each 2-year weight for 2003–2004, 2005–2006, 2007–2008, and 2009–2010 was multiplied by 1/6, thereby yielding a new 12-year weight that is based on 2000 Decennial Census population estimates, as are the 4- and 2-year weights. A correct weight was selected among (new) weights for various survey components (e.g., demographics, examination, laboratory) in order to provide estimates appropriately adjusted for survey nonresponse (e.g., to analyze adults’ lipid profile from a laboratory exam conducted on only a subsample of the original NHANES sample); a fasting or nonfasting weight was used for laboratory data, along with the SAS SURVEY subpopulation procedure. Second, age standardization was used because age could confound comparisons of population subgroups having different age distributions, and age is closely related to the primary outcomes. Using the standard age proportions derived from 2000 Census counts,19 age-adjusted estimates and SEs were calculated (except for demographic variables). Third, NHANES uses multiple techniques to impute missing observations in DXA data. As recommended, each imputed data set was analyzed separately, and then the results were combined using Rubin’s rule20 implemented in the SAS MIANALYZE procedure. Finally, SAS SURVEY procedures that can handle properly the survey’s design features were used. Data were summarized for sample demographics, anthropometric measures, obesity prevalence, percentage of physiciandiagnosed high blood pressure, high cholesterol, and diabetes, and percentage of medication use. The data were initially analyzed across three groups: those with mobility limitations, those with nonmobility limitations, and those without disability limitations. www.ajpmonline.org
Froehlich-Grobe et al / Am J Prev Med 2013;45(1):83–90 There were no differences by weight categories between the mobility and nonmobility limitation groups; thus, these groups were collapsed to compare against those without any disability for the final analysis presented. Disability groups and nondisability groups were compared, as were three weight categories (under/normal weight, overweight, obese) within each group, on all measures except demographics. Differences were examined using the Rao-Scott chi-square test (for categoric variables) and a t-test with or without Bonferroni adjustment (for continuous variables). Additionally, potential interactions were assessed between disability status and weight category using the SAS SURVEYREG procedure. Finally, disability severity was evaluated for each of the study variables.
Results A total of 11,556 adults with disabilities and 20,434 adults with no disability were identified from six waves of NHANES data. Demographic characteristics of the study sample appear in Table 1. Adults with disabilities were older (59.4⫾0.3 years vs 41.3⫾0.2 years); more likely to be female (57.3% vs 50.0%); more likely to be white (75.8% vs 68.2%); had lower educational levels (27.6% vs 16.8% did not complete high school); had lower levels of annual household income (17.6% vs 35.2% earned ≥$75,000); and were less likely to have never married (10.4% vs 20.0%), but more likely to be widowed (16.4% vs 2.6%) or divorced (12.3% vs 8.8%). The most common health problems causing limitations (Table 2) were arthritis/rheumatism (22.5%), followed by back or neck problem (20.4%) and other impairment/problem (11.1%). The mean disability severity score was 6.7⫾0.1 (range: 0–45). Table 3 presents unadjusted and age-adjusted estimates and SEs of the anthropometric measures and obesity prevalence by disability status. These results also show whether there were differences by disability severity, presence of disability, or the interaction of disability by weight category. Obesity prevalence was significantly higher among both men (37.2%) and women (45.1%) with disabilities than among those without disabilities (men, 28.5%; women, 30.0%). Results were similar for extreme obesity (BMI ≥40) with significantly higher prevalence among those with disabilities for both men (6.3% vs 2.8%) and women (11.6% vs 5.0%). Individuals with disabilities had significantly greater waist circumference and higher percentage body fat (100.5 cm, 35.7% fat) than those without disabilities (95.8 cm, 33.4% fat). Additionally, there were significant interactions between disability status and weight category for waist circumference and percentage body fat in men and women, with the widest gap between those who were obese. Blood pressure, total cholesterol, HDL, LDL, triglycerides, and triglycerides to LDL ratio, CRP, and glucose values were compared across weight categories (under/normal weight, overweight, obese), by disability severity, between individuals with and without disability, July 2013
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and across weight categories by disability status (Appendix A, available online at www.ajpmonline.org).
Disability Status by Weight Category For those with and without disabilities, increased weight generally was associated with higher levels of chronic disease risk factors. However, total and LDL cholesterol did not follow this pattern, likely due to increased prescription of cholesterol-lowering medication and/or less cigarette smoking among overweight and obese individuals. Thus, values were significantly higher among those with and without disabilities who were overweight or obese than under/normal weight for systolic blood pressure, total cholesterol, HDL, LDL, triglycerides, triglyceride to HDL ratio, and glucose. Values were significantly higher by weight category for those without disabilities for diastolic blood pressure and CRP. Yet, these values were not significantly different for under/normal weight compared to overweight individuals with disabilities, although CRP values were significantly higher for obese compared to under/normal and overweight individuals. Additionally, among those with disabilities, overweight and obese individuals did not differ on systolic blood pressure, LDL cholesterol, triglycerides, or ratio of triglycerides to HDL cholesterol. Among those without disabilities, there were no differences between those who were overweight versus obese for total and LDL cholesterol.
Disability Severity by Weight Category Increasing disability severity was associated with increased chronic disease risk factors and obesity (values not shown). For example, obesity and extreme obesity, waist circumference, and percentage body fat were greater for those with more severe disability. The only exceptions observed were for total cholesterol and HDL cholesterol in men.
Disability Status and Disability-by-Weight Interactions Values across all chronic disease measures, except for systolic blood pressure, were significantly different between those with and without disabilities. Additionally, prevalence of diagnoses for high blood pressure, high cholesterol, or diabetes were significantly higher among those with disabilities (49.7%, 51.6%, and 16.5%, respectively) than those without disabilities (20.2%, 34.2%, and 4.2%, respectively). This difference also was found for the prevalence of being prescribed medication for blood pressure (44.6% vs 14.8%) or high cholesterol (26.1% vs 15.8%). Further, interactions between disability status and weight category were observed for diastolic blood pressure; HDL cholesterol in women; CRP; and the percentage diagnosed with high blood pressure, high cholesterol,
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Table 1. Demographic characteristics of adult population subgroups Disability Variable
n
%
No disability %a
n
%
%a
o0.001
Gender Men
5280
42.7
12.2
9,980
50.0
35.7
Women
6276
57.3
16.4
10,454
50.0
35.7 o0.001
Ethnicity Mexican American
1855
4.7
1.3
4,626
9.1
6.5
649
3.9
1.1
1,469
5.5
3.9
Non-Hispanic white
6464
75.8
21.6
9,286
68.2
48.7
Non-Hispanic black
2172
10.8
3.1
4,113
11.3
8.0
416
4.7
1.3
940
5.9
4.2
Other Hispanic
Multi-racial/other
Grade school
2374
11.3
3.2
2,220
5.1
3.7
Some high school
2129
16.3
4.7
3,187
11.7
8.4
High school graduate
2831
28.1
8.0
4,756
24.0
17.2
Some college
2614
26.8
7.6
5,729
30.8
22.0
College graduate or above
1549
17.5
5.0
4,513
28.4
20.3 o0.001
Annual household income ($) 0–4,999
243
2.1
0.6
337
1.3
0.9
5,000–9,999
977
7.4
2.1
575
2.2
1.5
10,000–14,999
1367
10.4
2.9
1,101
4.0
2.9
15,000–19,999
1136
8.8
2.5
1,208
4.8
3.4
20,000–24,999
1055
9.2
2.6
1,442
5.9
4.2
25,000–34,999
1465
13.7
3.9
2,457
10.9
7.9
35,000–44,999
1034
10.7
3.0
1,967
9.9
7.1
45,000–54,999
808
9.4
2.6
1,803
10.2
7.3
55,000–64,999
463
5.8
1.6
1,418
8.3
6.0
65,000–74,999
365
4.8
1.4
1,123
7.2
5.2
1287
17.6
5.0
4,972
35.2
25.3 o0.001
Marital status Married
5679
53.7
15.4
11,269
58.7
41.9
Widowed
2457
16.4
4.7
771
2.6
1.8
Divorced
1361
12.3
3.5
1,695
8.8
6.2
365
2.7
0.8
653
2.5
1.8
1078
10.4
3.0
4,044
20.0
14.3
437
4.6
1.3
1,615
7.5
5.3
Separated Never married Living with partner/ other a
Discussion o0.001
Education level
≥75,000
p-value
Percentage of overall adult population
or diabetes; and prescribed medication use for both high blood pressure and high cholesterol. Across all weight categories, individuals with disabilities had higher prevalence for these outcomes than those without disabilities, with the greatest discrepancy between those with and without disability for chronic disease risk factors observed in the obese category.
These results confirm earlier findings that obesity is significantly more prevalent among individuals with disabilities than in the general population.6,7,9 The study also substantiated previous contentions that obesity prevalence among those with disabilities would likely be higher based on estimates derived from direct measures of height and weight rather than self-report.5,21 Obesity (41.5%) and extreme obesity (9.3%) prevalence among individuals with disability from NHANES data were higher than previously observed in other national surveys based on self-report (obesity range=24.9%–31.6%, extreme obesity of 4.2%).6,7,9 Correspondingly, individuals with disabilities had a higher percent body fat and larger waist circumference than individuals without disabilities, both of which are associated with increased risk for cardiovascular disease and total mortality.17 Similar to findings for those without disabilities22,23 increased weight among those with disabilities was associated with higher blood pressure, total cholesterol, CRP, glucose, and lower HDL cholesterol. Additionally, disability severity negatively affected nearly all www.ajpmonline.org
Froehlich-Grobe et al / Am J Prev Med 2013;45(1):83–90
Table 2. Health problems of adult population subgroups with disability Disability
n
%
Arthritis/rheumatism
4581
22.5
Back or neck problem
3663
20.5
85
0.6
251
1.2
1103
6.4
63
0.4
Diabetes
1009
3.8
Fractures, bone/joint injury
1679
9.3
Hearing problem
568
2.4
Heart problem
850
3.7
Hypertension/high blood pressure
936
3.8
Lung/breathing problem
741
4.0
68
0.4
Other injury
351
2.1
Senility
124
0.4
Stroke problem
350
1.4
Vision/problem seeing
605
2.4
Weight problem
569
3.5
2162
11.2
Variable Health problemsa
Birth defect Cancer Depression/anxiety/emotional problem Other developmental problem
Mental retardation
Other impairment/problem a
Multiple responses up to three different health problems
chronic disease risk factors. Notably, although others have shown that those with disabilities have a higher prevalence of chronic diseases such as hypertension and diabetes,15 to our knowledge, this study presents the first published evidence from a national sample that included physiologic measures of blood pressure, cholesterol, glucose, body fat, waist circumference, and CRP, adding to the data from self-reports of being diagnosed with chronic conditions for those with disabilities. Individuals with disabilities were more likely to report physician-diagnosed obesity-related chronic conditions including hypertension, high cholesterol, and diabetes, which are all risk factors for cardiovascular disease. Notably, weight-by-disability interactions occurred for all physician-diagnosed chronic conditions, with a wider gap observed between those considered obese. Although diabetes may lead to disability, some types of disability (e.g., spinal cord injury) also may increase the risk for impaired glucose tolerance and diabetes.24 July 2013
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Additionally, there was a weight-by-disability interaction for being prescribed medication for blood pressure and cholesterol, again with the greatest discrepancies observed among those classified as obese. Twice as many with disabilities reported being prescribed medication for hypertension (40% vs 20%) and cholesterol-lowering medication (55% vs 24%). Although doctors actively prescribe pharmacologic agents to control blood pressure and cholesterol for obese patients with disabilities, the question remains of whether providers also recommend lifestyle changes for their patients with disabilities. Weil et al.9 found that those with mobility impairments were less likely to report receiving exercise counseling from their physician than those without a disability. Obesity is often neglected among those with disabilities,5,21 yet the current study provides compelling evidence that greater efforts should be made to address weight-related health disparities observed among individuals with disabilities. The study shows that the risk conferred by obesity to individuals with disabilities for chronic conditions such as diabetes, high cholesterol, hypertension, and higher CRP is greater than that for obese adults without disabilities. Obesity also likely exacerbates disability-related limitations (e.g., mobility) and health problems (e.g., chronic pain). The nation spends nearly $400 billion on disabilityassociated healthcare costs,25 70% of which is borne by the public sector (i.e., Medicare and Medicaid). Efforts are therefore urgently needed to improve the health of this group, and a logical step would be targeting weight management, which may yield substantial improvements in health. Activities could include designing and evaluating weight management strategies specific to individuals with disabilities who are less physically active than those without disabilities26 because of functional and environmental barriers27–29 and who typically have limited financial resources1 to purchase the fruits, vegetables, and unprocessed foods associated with a healthy diet.
Limitations Several limitations should be noted. First, this study pooled NHANES data collected across 12 years to increase the sample size of individuals with disability. Thus, no assessment could be made of changes in obesity prevalence that may have occurred over this time frame. This concern may be tempered partially by a recent publication by Flegal et al.,30 who reported only slight increases in the prevalence of obesity over the past 12 years in nondisabled individuals, particularly among men, non-Hispanic black women, and Mexican American women. Second, NHANES data may underestimate obesity prevalence for those with disabilities for two reasons:
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Table 3. Obesity prevalence, anthropometric measures, and obesity-related chronic disease diagnoses Disability a
a
No disability b
b
Mb
SEb
p-value**
35.5
0.5
34.8
0.5
o0.001
2,797
30.0
0.7
29.1
0.7
0.905
o0.001
3,499
41.1
0.7
40.6
0.7
o0.001
0.8
o0.001
6,899
34.7
0.5
35.9
0.5
o0.001
33.9
1.3
o0.001
3,897
41.3
0.6
42.4
0.6
o0.001
0.9
25.3
1.0
0.001
3,002
28.0
0.6
29.4
0.7
o0.001
40.7
0.6
41.6
0.9
o0.001
6,069
29.8
0.6
29.2
0.6
o0.001
1663
38.0
1.0
37.2
1.4
o0.001
2,699
28.7
0.8
28.5
0.8
o0.001
2492
42.7
0.7
45.1
1.1
o0.001
3,370
30.9
0.7
30.0
0.7
o0.001
796
8.1
0.4
9.3
0.5
o0.001
916
4.4
0.2
3.9
0.2
o0.001
Men
226
5.5
0.5
6.3
0.6
o0.001
304
3.1
0.2
2.8
0.2
o0.001
Women
570
10.0
0.6
11.6
0.8
o0.001
612
5.7
0.3
5.0
0.3
o0.001
9871
101.8
0.2
100.5
0.4
o0.001
18,752
95.3
0.2
95.8
0.2
o0.001
o0.001
Men
4574
105.3
0.4
103.1
0.5
o0.001
9,146
98.6
0.2
99.3
0.2
o0.001
o0.001
Women
5297
99.2
0.3
98.4
0.4
o0.001
9,606
92.0
0.2
92.2
0.3
o0.001
o0.001
4789
36.9
0.2
35.7
0.3
o0.001
8,150
33.0
0.1
33.4
0.1
o0.001
0.001
Men
2189
30.1
0.2
29.1
0.3
o0.001
4,278
27.4
0.1
27.9
0.1
0.001
o0.001
Women
2600
41.9
0.2
41.0
0.3
o0.001
3,872
39.0
0.2
39.3
0.2
o0.001
0.007
M
SE
M
SE
p-value
n
M
2684
27.1
0.6
29.3
0.9
o0.001
6,296
Men
1275
25.6
0.9
28.9
1.4
0.821
Women
1409
28.3
0.8
29.5
1.1
Overweight
3431
32.2
0.6
29.1
Men
1784
36.4
1.0
Women
1647
29.0
Obese
4155
Men Women
Variable Under/normal weight
Extremely obese
Waist circumference (cm)
Body fat %, including BMC
www.ajpmonline.org
Note: Ms are given as %, unless otherwise noted. a Unadjusted Ms and SEs b Ms and SEs adjusted by the standard age proportions derived from 2000 Census data n p testing disability severity; nnp comparing disability vs no disability; nnn p testing disability-by-weight category interaction BMC, bone mineral content
a
p-value***
Froehlich-Grobe et al / Am J Prev Med 2013;45(1):83–90
SEa
n
*
Froehlich-Grobe et al / Am J Prev Med 2013;45(1):83–90
(1) Individuals with the most severe impairments may not come to the mobile exam unit because of physical limitations or difficulties with transportation or arranging assistance; and (2) no data on height and weight are available for individuals who are unable to stand unassisted. Thus, of the 1286 individuals with disabilities who were missing BMI data, some may have been unable to perform the tests. Notably, NHIS data published by Weil et al.9 found that obesity was more prevalent among those with mobility impairments than those with sensory, mental health, or other physical impairments. A final limitation derives from the cross-sectional design of the NHANES survey. Thus, the directionality of the relationship between disability and obesity cannot be determined (i.e., whether obesity causes disability or disability causes obesity).
Conclusion The prevalence estimates of obesity (41.5%) and extreme obesity (9.3%) based on NHANES data for individuals with disabilities are substantially higher than previous prevalence estimates based on self-reported height and weight.6,7,9 The data also indicate that the average waist circumference among Americans with disabilities exceeds the current guidelines17 and that their average percentage body fat is indicative of obesity. Further, values observed for blood pressure, cholesterol, CRP, and glucose increased with increasing body weight. These findings are consistent with results from this study and others15 showing that people with disabilities experience a greater burden of obesity-related chronic diseases such as hypertension, high cholesterol, and diabetes than those without disabilities. Continuing efforts to address and reverse the obesity epidemic cannot afford to neglect the 54 million Americans living with disabilities. Individuals with disabilities should be included in studies designed to examine factors contributing to weight gain and test innovative weight loss and maintenance strategies. Additionally, healthcare providers should be encouraged to include individuals with disabilities in their clinical weight management efforts. Specifically, primary care providers should be reminded and encouraged to follow the U.S. Preventive Services Task Force31 and Healthy People 202032 recommendations to screen all individuals for obesity and refer those obese individuals, including those with disabilities, to intensive multicomponent weight management programs. The potential effects of addressing obesity among individuals with disabilities are great and include improved general health and quality of life and reduced secondary conditions and financial expenditures for treating obesity-related chronic conditions. No financial disclosures were reported by the authors of this paper.
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References 1. Brault M. Americans with disabilities: 2005. Current Population Reports, P70–117. Washington DC: US Census Bureau, 2008. 2. IOM. The future of disability in America. Washington DC: National Academies Press, 2007. 3. Department of Defense. U.S. Casualty Status of Operation Iraqi Freedom (OIF), Operation Enduring Freedom (OEF), and Operation New Dawn (OND). 2012. www.defense.gov/news/casualty.pdf. 4. IOM. Secondary conditions and aging with disability. In: Field MJ, Jette AM, eds The future of disability in America. Washington DC: National Academies Press, 2007. 5. Froehlich-Grobe K, Lollar D. Obesity and disability: time to act. Am J Prev Med 2011;41(5):541–5. 6. Weil E, Wachterman M, McCarthy EP, et al. Obesity among adults with disabling conditions. JAMA 2002;288(10):1265–8. 7. Campbell VA, Crews JE, Sinclair L. State-specific prevalence of obesity among adults with disabilities—eight states and the District of Columbia, 1998-1999. MMWR Morb Mortal Wkly Rep 2002;51: 805–8. 8. CDC. Disability and health state chartbook, 2006: profiles of health for adults with disabilities. Atlanta GA: CDC, 2006. 9. Altman BM, Bernstein A. Disability and health in the U.S., 2001-2005. Hyattsville MD: National Center for Health Statistics, DHHS, 2008. 10. John U, Hanke M, Grothues J, Thyrian J. Validity of overweight and obesity in a nation based on self-report versus measurement device data. Eur J Clin Nutr 2006;60(3):372–7. 11. Gorber SC, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self-report measures for assessing height, weight, and body mass index: a systematic review. Obes Rev 2007;8:307–26. 12. Nawaz H, Chan W, Abdulrahman M, Larson D, Katz DL. Self-reported weight and hegiht: implications for obesity research. Am J Prev Med 2001;20(4):294–8. 13. Kuczmarski MA, Kuczmarski RJ, Najjar M. Effects of age on validity of self-reported height, weight, and body mass index: findings from the third National Health and Nutrition Examination Survey, 1988-1994. J Am Dietetic Assoc 2001;101:28–34. 14. Froehlich-Grobe K, Nary DE, VanSciver A, Washburn RA, Aaronson LS. Truth be told: evidence of wheelchair users accuracy in reporting their height and weight. Arch Phys Med Rehabil 2012;93(11):2055–61. 15. Rasch EK, Hochberg MC, Magder L, Magaziner J, Altman BM. Health of community-dwelling adults with mobility limitations in the U.S.: prevalent health conditions. Part I. Arch Phys Med Rehabil 2008;89: 210–8. 16. CDC. National Health and Nutrition Examination Survey. Survey Questionnaires, Examination Components and Laboratory Components 1999-2000. 2012. www.cdc.gov/nchs/nhanes/nhanes1999-2000/ questexam99_00.htm. 17. National Heart, Lung, and Blood Institute. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults—the evidence report. Obes Res 1998;6(S2):51S–209S. 18. National Center for Health Statistics (NCHS). Analytic and reporting guidelines: The National Health and Nutrition Examination Survey (NHANES). Hyattsville MD: National Center for Health Statistics, 2005. www.cdc.gov/nchs/data/nhanes/nhanes_03_04/nhanes_analytic_guideli nes_dec_2005.pdf. 19. Klein RJ, Schoenborn CA. Age adjustment using the 2000 projected U.S. population. Healthy People Statistical Notes. Hyattsville MD: National Center for Health Statistics, 2001. 20. Rubin DB. Multiple imputation for nonresponse in surveys. New York: Wiley, 1987. 21. Liou T, Pi-Sunyer FX, Laferrere B. Physical disability and obesity. Nutr Rev 2005;63(10):321–31. 22. Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA 1999;282(16):1523–9.
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23. Joshi AV, Day D, Lubowski TJ, Ambegaonkar A. Relationshiop between obesity and cardiovascular risk factors: findings from a multi-state screening project in the U.S. Curr Med Res Opin 2005;21(11): 1755–61. 24. Bauman WA, Spungen AM. Carbohydrate and lipid metabolism in chronic spinal cord injury. J Spinal Cord Med 2001;24(4):266–77. 25. Anderson B, Armour BS, Finkelstein EA, Wiener JM. Estimates of state-level health-care expenditures associated with disability. Public Health Rep 2010;125:44–51. 26. CDC. Physical activity among adults with a disability—U.S., 2005. MMWR Morb Mortal Wkly Rep 2007;56(39):1021–4. 27. Rimmer JH, Rubin SS, Braddock D. Barriers to exercise in African American women with physical disabilities. Arch Phys Med Rehabil 2000;81(2):182–8. 28. Froehlich AK, Nary DE, White GW. Identifying barriers to participation in physical activity for women with disabilities. SCI Psychosoc Process 2002;15:21–8. 29. Nary DE, Froehlich AK, White GW. Accessibility of fitness facilities for persons with physical disabilities using wheelchairs. Topics Spinal Cord Inj Rehabil 2000;6(1):87–98.
30. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among U.S. adults, 19992010. JAMA 2012;307(5):491–7. 31. U.S. Preventive Services Task Force. Screening for and management of obesity in adults. 2012. www.uspreventiveservicestaskforce.org/ uspstf11/obeseadult/obesesum.htm. 32. 2020 Healthy People. Nutrition and weight status objectives. 2012. www.healthypeople.gov/2020/topicsobjectives2020/objectiveslist.aspx? topicId=29.
Appendix Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.amepre.2013.02.021.
www.ajpmonline.org
Introduction
C
urrently, 54 million Americans (20% of the adult population) experience disability.1 Disability prevalence is expected to increase2 for several reasons, including (1) recent medical advances that have increased survival rates following traumatic injury, premature birth, and combat injuries incurred in Mideast conflicts (where those injured outnumber those killed3
From the University of Texas School of Public Health (Froehlich-Grobe), Dallas Regional Campus, Dallas, Texas, Center for Research Methods and Data Analysis (Lee), Center for Physical Activity and Weight Management (Washburn), Life Span Institute, University of Kansas, Lawrence, and Cardiovascular Research Institute, University of Kansas Medical Center, Kansas City, Kansas Address correspondence to: Katherine Froehlich-Grobe, PhD, UT School of Public Health, Dallas Regional Campus, 6011 Harry Hines Blvd., V8.112, Dallas TX 75390. E-mail: [email protected]. 0749-3797/$36.00 http://dx.doi.org/10.1016/j.amepre.2013.02.021
& 2013 American Journal of Preventive Medicine
by 7.5 to 1); (2) increased life expectancy for those born with disability or who acquire disability; and (3) aging of the “baby-boomer” generation. For all individuals, with or without disabilities, excess weight increases risk for chronic conditions such as type 2 diabetes, hypertension, hyperlipidemia, osteoarthritis, stroke, specific cancers, and metabolic syndrome; it also may limit physical function, independence, and productivity.4 However, individuals with disabilities are underserved by national efforts targeting surveillance, treatment, and prevention of obesity,5 even though this condition is thought to be more prevalent in those with disabilities compared to those without.6 Estimates from self-report data from the Behavioral Risk Factor Surveillance System7,8 (BRFSS, 1998–1999, 2001–2003) and the National Health Interview Survey6,9 (NHIS, 1994–1995, 2001–2005) reveal that the prevalence of obesity (BMI ≥30) is higher among individuals with disabilities (24.9%–31.6%) than without (15.1%–18.7%).
Published by Elsevier Inc.
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However, these data likely underestimate prevalence, as individuals with disabilities, like their nondisabled counterparts,10–13 tend to overestimate height and underestimate weight, resulting in lower BMI and obesity prevalence.14 Arguably, obesity prevalence estimates for people with disabilities should be based on measured height and weight data, such as those available from NHANES. Since 1999, NHANES has conducted annual crosssectional surveys of approximately 5000 individuals using a complex survey design to select participants representative of the non-institutionalized U.S. population. NHANES is the only ongoing national health survey that combines self-report interview data with physical examinations at a mobile examination center where anthropometric measures and laboratory data on disease risk factors are collected and includes questions to identify individuals with functional limitations. The purpose of the current study was to use NHANES data to compare obesity prevalence between individuals with disabilities and those without, and to assess the association between BMI category and weight-related chronic disease risk factors in both groups.
Methods Data analyses were performed in June 2012 by pooling six waves of publicly available NHANES data (1999–2000, 2001–2002, 2003– 2004, 2005–2006, 2007–2008, 2009–2010). Pooling data across years ensured an adequate sample size of adults (aged ≥20 years) with disabilities. Participants were classified as having mobility or nonmobility limitations based on self-report data using the schema of Rasch et al.15 Adults were identified as having a disability if they reported difficulty (some, much, or unable to do) with one or more of the following: (1) walking without special equipment use; (2) walking 0.25 miles; (3) walking ten steps without stopping; (4) stooping, crouching, or kneeling; (5) walking from one room to another on the same level; (6) standing up from an armless straight chair; or (7) standing or being on their feet for 2 hours. Individuals who reported difficulty (some, much, or unable to do) with one or more of the following activities were considered to have a nonmobility limitation: (1) being limited because of difficulty remembering or having periods of confusion; (2) being limited in any way in any activity because of a physical, mental, or emotional problem; (3) getting in and out of bed; (4) eating, such as holding a fork, cutting food, or drinking from a glass; (5) dressing, including tying shoes, working zippers, and doing buttons; (6) reaching up over their head; (7) using their fingers to grasp small objects; (8) lifting or carrying something as heavy as 10 pounds; (9) doing housework such as vacuuming, sweeping, dusting; (10) preparing their own meals; (11) managing money; or (12) responded affirmatively to a question about using special equipment due to a health problem. Respondents without mobility or nonmobility limitations were categorized as having no disability. Impairment severity was calculated by summing respondent reports of their level of difficulty in performing each assessed task. NHANES also collects information about the top three health conditions that limit function.
Anthropometric and laboratory data including weight, height, waist circumference, body composition by dual-energy x-ray absorptiometry (DXA); blood pressure; lipid profile (total cholesterol, high-density lipoprotein [HDL], low-density lipoprotein [LDL], triglycerides); C-reactive protein (CRP); and fasting glucose were assessed in a mobile examination center using standardized techniques and equipment.16 BMI was calculated by standard formula. Weight categories were based on BMI using National Heart, Lung, and Blood Institute (NHLBI) guidelines, as follows17: underweight/normal weight¼≤24.9; overweight¼25.0–29.9; obese¼≥30.0; and extreme obesity (Class III)¼ ≥40. Demographic data including age, gender, ethnicity, education, marital status, and information on physical functioning to determine disability status were obtained by in-person interview. Data on smoking status; physician-diagnosed high bold pressure, cholesterol, and diabetes; and prescribed medication use were obtained from the relevant self-report questionnaire sections. All variables selected for analysis were available for all study years, with the exception of percentage body fat, as NHANES has not released body fat data from DXA scans since 2004.
Data Analysis The NHANES uses probability sampling and weighting methodology. Ignoring its complex design can lead to biased population estimates and overstated significance levels. Thus, the current study followed NHANES guidelines18 to account for the design features, including stratification, cluster sampling, and weighting. First, sample weights were rescaled by taking correct proportions of the original 4- and 2-year weights when combining 12 years (six waves) of NHANES data. For example, the 4-year weight provided for 1999–2002 was multiplied by 2/6; each 2-year weight for 2003–2004, 2005–2006, 2007–2008, and 2009–2010 was multiplied by 1/6, thereby yielding a new 12-year weight that is based on 2000 Decennial Census population estimates, as are the 4- and 2-year weights. A correct weight was selected among (new) weights for various survey components (e.g., demographics, examination, laboratory) in order to provide estimates appropriately adjusted for survey nonresponse (e.g., to analyze adults’ lipid profile from a laboratory exam conducted on only a subsample of the original NHANES sample); a fasting or nonfasting weight was used for laboratory data, along with the SAS SURVEY subpopulation procedure. Second, age standardization was used because age could confound comparisons of population subgroups having different age distributions, and age is closely related to the primary outcomes. Using the standard age proportions derived from 2000 Census counts,19 age-adjusted estimates and SEs were calculated (except for demographic variables). Third, NHANES uses multiple techniques to impute missing observations in DXA data. As recommended, each imputed data set was analyzed separately, and then the results were combined using Rubin’s rule20 implemented in the SAS MIANALYZE procedure. Finally, SAS SURVEY procedures that can handle properly the survey’s design features were used. Data were summarized for sample demographics, anthropometric measures, obesity prevalence, percentage of physiciandiagnosed high blood pressure, high cholesterol, and diabetes, and percentage of medication use. The data were initially analyzed across three groups: those with mobility limitations, those with nonmobility limitations, and those without disability limitations. www.ajpmonline.org
Froehlich-Grobe et al / Am J Prev Med 2013;45(1):83–90 There were no differences by weight categories between the mobility and nonmobility limitation groups; thus, these groups were collapsed to compare against those without any disability for the final analysis presented. Disability groups and nondisability groups were compared, as were three weight categories (under/normal weight, overweight, obese) within each group, on all measures except demographics. Differences were examined using the Rao-Scott chi-square test (for categoric variables) and a t-test with or without Bonferroni adjustment (for continuous variables). Additionally, potential interactions were assessed between disability status and weight category using the SAS SURVEYREG procedure. Finally, disability severity was evaluated for each of the study variables.
Results A total of 11,556 adults with disabilities and 20,434 adults with no disability were identified from six waves of NHANES data. Demographic characteristics of the study sample appear in Table 1. Adults with disabilities were older (59.4⫾0.3 years vs 41.3⫾0.2 years); more likely to be female (57.3% vs 50.0%); more likely to be white (75.8% vs 68.2%); had lower educational levels (27.6% vs 16.8% did not complete high school); had lower levels of annual household income (17.6% vs 35.2% earned ≥$75,000); and were less likely to have never married (10.4% vs 20.0%), but more likely to be widowed (16.4% vs 2.6%) or divorced (12.3% vs 8.8%). The most common health problems causing limitations (Table 2) were arthritis/rheumatism (22.5%), followed by back or neck problem (20.4%) and other impairment/problem (11.1%). The mean disability severity score was 6.7⫾0.1 (range: 0–45). Table 3 presents unadjusted and age-adjusted estimates and SEs of the anthropometric measures and obesity prevalence by disability status. These results also show whether there were differences by disability severity, presence of disability, or the interaction of disability by weight category. Obesity prevalence was significantly higher among both men (37.2%) and women (45.1%) with disabilities than among those without disabilities (men, 28.5%; women, 30.0%). Results were similar for extreme obesity (BMI ≥40) with significantly higher prevalence among those with disabilities for both men (6.3% vs 2.8%) and women (11.6% vs 5.0%). Individuals with disabilities had significantly greater waist circumference and higher percentage body fat (100.5 cm, 35.7% fat) than those without disabilities (95.8 cm, 33.4% fat). Additionally, there were significant interactions between disability status and weight category for waist circumference and percentage body fat in men and women, with the widest gap between those who were obese. Blood pressure, total cholesterol, HDL, LDL, triglycerides, and triglycerides to LDL ratio, CRP, and glucose values were compared across weight categories (under/normal weight, overweight, obese), by disability severity, between individuals with and without disability, July 2013
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and across weight categories by disability status (Appendix A, available online at www.ajpmonline.org).
Disability Status by Weight Category For those with and without disabilities, increased weight generally was associated with higher levels of chronic disease risk factors. However, total and LDL cholesterol did not follow this pattern, likely due to increased prescription of cholesterol-lowering medication and/or less cigarette smoking among overweight and obese individuals. Thus, values were significantly higher among those with and without disabilities who were overweight or obese than under/normal weight for systolic blood pressure, total cholesterol, HDL, LDL, triglycerides, triglyceride to HDL ratio, and glucose. Values were significantly higher by weight category for those without disabilities for diastolic blood pressure and CRP. Yet, these values were not significantly different for under/normal weight compared to overweight individuals with disabilities, although CRP values were significantly higher for obese compared to under/normal and overweight individuals. Additionally, among those with disabilities, overweight and obese individuals did not differ on systolic blood pressure, LDL cholesterol, triglycerides, or ratio of triglycerides to HDL cholesterol. Among those without disabilities, there were no differences between those who were overweight versus obese for total and LDL cholesterol.
Disability Severity by Weight Category Increasing disability severity was associated with increased chronic disease risk factors and obesity (values not shown). For example, obesity and extreme obesity, waist circumference, and percentage body fat were greater for those with more severe disability. The only exceptions observed were for total cholesterol and HDL cholesterol in men.
Disability Status and Disability-by-Weight Interactions Values across all chronic disease measures, except for systolic blood pressure, were significantly different between those with and without disabilities. Additionally, prevalence of diagnoses for high blood pressure, high cholesterol, or diabetes were significantly higher among those with disabilities (49.7%, 51.6%, and 16.5%, respectively) than those without disabilities (20.2%, 34.2%, and 4.2%, respectively). This difference also was found for the prevalence of being prescribed medication for blood pressure (44.6% vs 14.8%) or high cholesterol (26.1% vs 15.8%). Further, interactions between disability status and weight category were observed for diastolic blood pressure; HDL cholesterol in women; CRP; and the percentage diagnosed with high blood pressure, high cholesterol,
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Table 1. Demographic characteristics of adult population subgroups Disability Variable
n
%
No disability %a
n
%
%a
o0.001
Gender Men
5280
42.7
12.2
9,980
50.0
35.7
Women
6276
57.3
16.4
10,454
50.0
35.7 o0.001
Ethnicity Mexican American
1855
4.7
1.3
4,626
9.1
6.5
649
3.9
1.1
1,469
5.5
3.9
Non-Hispanic white
6464
75.8
21.6
9,286
68.2
48.7
Non-Hispanic black
2172
10.8
3.1
4,113
11.3
8.0
416
4.7
1.3
940
5.9
4.2
Other Hispanic
Multi-racial/other
Grade school
2374
11.3
3.2
2,220
5.1
3.7
Some high school
2129
16.3
4.7
3,187
11.7
8.4
High school graduate
2831
28.1
8.0
4,756
24.0
17.2
Some college
2614
26.8
7.6
5,729
30.8
22.0
College graduate or above
1549
17.5
5.0
4,513
28.4
20.3 o0.001
Annual household income ($) 0–4,999
243
2.1
0.6
337
1.3
0.9
5,000–9,999
977
7.4
2.1
575
2.2
1.5
10,000–14,999
1367
10.4
2.9
1,101
4.0
2.9
15,000–19,999
1136
8.8
2.5
1,208
4.8
3.4
20,000–24,999
1055
9.2
2.6
1,442
5.9
4.2
25,000–34,999
1465
13.7
3.9
2,457
10.9
7.9
35,000–44,999
1034
10.7
3.0
1,967
9.9
7.1
45,000–54,999
808
9.4
2.6
1,803
10.2
7.3
55,000–64,999
463
5.8
1.6
1,418
8.3
6.0
65,000–74,999
365
4.8
1.4
1,123
7.2
5.2
1287
17.6
5.0
4,972
35.2
25.3 o0.001
Marital status Married
5679
53.7
15.4
11,269
58.7
41.9
Widowed
2457
16.4
4.7
771
2.6
1.8
Divorced
1361
12.3
3.5
1,695
8.8
6.2
365
2.7
0.8
653
2.5
1.8
1078
10.4
3.0
4,044
20.0
14.3
437
4.6
1.3
1,615
7.5
5.3
Separated Never married Living with partner/ other a
Discussion o0.001
Education level
≥75,000
p-value
Percentage of overall adult population
or diabetes; and prescribed medication use for both high blood pressure and high cholesterol. Across all weight categories, individuals with disabilities had higher prevalence for these outcomes than those without disabilities, with the greatest discrepancy between those with and without disability for chronic disease risk factors observed in the obese category.
These results confirm earlier findings that obesity is significantly more prevalent among individuals with disabilities than in the general population.6,7,9 The study also substantiated previous contentions that obesity prevalence among those with disabilities would likely be higher based on estimates derived from direct measures of height and weight rather than self-report.5,21 Obesity (41.5%) and extreme obesity (9.3%) prevalence among individuals with disability from NHANES data were higher than previously observed in other national surveys based on self-report (obesity range=24.9%–31.6%, extreme obesity of 4.2%).6,7,9 Correspondingly, individuals with disabilities had a higher percent body fat and larger waist circumference than individuals without disabilities, both of which are associated with increased risk for cardiovascular disease and total mortality.17 Similar to findings for those without disabilities22,23 increased weight among those with disabilities was associated with higher blood pressure, total cholesterol, CRP, glucose, and lower HDL cholesterol. Additionally, disability severity negatively affected nearly all www.ajpmonline.org
Froehlich-Grobe et al / Am J Prev Med 2013;45(1):83–90
Table 2. Health problems of adult population subgroups with disability Disability
n
%
Arthritis/rheumatism
4581
22.5
Back or neck problem
3663
20.5
85
0.6
251
1.2
1103
6.4
63
0.4
Diabetes
1009
3.8
Fractures, bone/joint injury
1679
9.3
Hearing problem
568
2.4
Heart problem
850
3.7
Hypertension/high blood pressure
936
3.8
Lung/breathing problem
741
4.0
68
0.4
Other injury
351
2.1
Senility
124
0.4
Stroke problem
350
1.4
Vision/problem seeing
605
2.4
Weight problem
569
3.5
2162
11.2
Variable Health problemsa
Birth defect Cancer Depression/anxiety/emotional problem Other developmental problem
Mental retardation
Other impairment/problem a
Multiple responses up to three different health problems
chronic disease risk factors. Notably, although others have shown that those with disabilities have a higher prevalence of chronic diseases such as hypertension and diabetes,15 to our knowledge, this study presents the first published evidence from a national sample that included physiologic measures of blood pressure, cholesterol, glucose, body fat, waist circumference, and CRP, adding to the data from self-reports of being diagnosed with chronic conditions for those with disabilities. Individuals with disabilities were more likely to report physician-diagnosed obesity-related chronic conditions including hypertension, high cholesterol, and diabetes, which are all risk factors for cardiovascular disease. Notably, weight-by-disability interactions occurred for all physician-diagnosed chronic conditions, with a wider gap observed between those considered obese. Although diabetes may lead to disability, some types of disability (e.g., spinal cord injury) also may increase the risk for impaired glucose tolerance and diabetes.24 July 2013
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Additionally, there was a weight-by-disability interaction for being prescribed medication for blood pressure and cholesterol, again with the greatest discrepancies observed among those classified as obese. Twice as many with disabilities reported being prescribed medication for hypertension (40% vs 20%) and cholesterol-lowering medication (55% vs 24%). Although doctors actively prescribe pharmacologic agents to control blood pressure and cholesterol for obese patients with disabilities, the question remains of whether providers also recommend lifestyle changes for their patients with disabilities. Weil et al.9 found that those with mobility impairments were less likely to report receiving exercise counseling from their physician than those without a disability. Obesity is often neglected among those with disabilities,5,21 yet the current study provides compelling evidence that greater efforts should be made to address weight-related health disparities observed among individuals with disabilities. The study shows that the risk conferred by obesity to individuals with disabilities for chronic conditions such as diabetes, high cholesterol, hypertension, and higher CRP is greater than that for obese adults without disabilities. Obesity also likely exacerbates disability-related limitations (e.g., mobility) and health problems (e.g., chronic pain). The nation spends nearly $400 billion on disabilityassociated healthcare costs,25 70% of which is borne by the public sector (i.e., Medicare and Medicaid). Efforts are therefore urgently needed to improve the health of this group, and a logical step would be targeting weight management, which may yield substantial improvements in health. Activities could include designing and evaluating weight management strategies specific to individuals with disabilities who are less physically active than those without disabilities26 because of functional and environmental barriers27–29 and who typically have limited financial resources1 to purchase the fruits, vegetables, and unprocessed foods associated with a healthy diet.
Limitations Several limitations should be noted. First, this study pooled NHANES data collected across 12 years to increase the sample size of individuals with disability. Thus, no assessment could be made of changes in obesity prevalence that may have occurred over this time frame. This concern may be tempered partially by a recent publication by Flegal et al.,30 who reported only slight increases in the prevalence of obesity over the past 12 years in nondisabled individuals, particularly among men, non-Hispanic black women, and Mexican American women. Second, NHANES data may underestimate obesity prevalence for those with disabilities for two reasons:
88
Table 3. Obesity prevalence, anthropometric measures, and obesity-related chronic disease diagnoses Disability a
a
No disability b
b
Mb
SEb
p-value**
35.5
0.5
34.8
0.5
o0.001
2,797
30.0
0.7
29.1
0.7
0.905
o0.001
3,499
41.1
0.7
40.6
0.7
o0.001
0.8
o0.001
6,899
34.7
0.5
35.9
0.5
o0.001
33.9
1.3
o0.001
3,897
41.3
0.6
42.4
0.6
o0.001
0.9
25.3
1.0
0.001
3,002
28.0
0.6
29.4
0.7
o0.001
40.7
0.6
41.6
0.9
o0.001
6,069
29.8
0.6
29.2
0.6
o0.001
1663
38.0
1.0
37.2
1.4
o0.001
2,699
28.7
0.8
28.5
0.8
o0.001
2492
42.7
0.7
45.1
1.1
o0.001
3,370
30.9
0.7
30.0
0.7
o0.001
796
8.1
0.4
9.3
0.5
o0.001
916
4.4
0.2
3.9
0.2
o0.001
Men
226
5.5
0.5
6.3
0.6
o0.001
304
3.1
0.2
2.8
0.2
o0.001
Women
570
10.0
0.6
11.6
0.8
o0.001
612
5.7
0.3
5.0
0.3
o0.001
9871
101.8
0.2
100.5
0.4
o0.001
18,752
95.3
0.2
95.8
0.2
o0.001
o0.001
Men
4574
105.3
0.4
103.1
0.5
o0.001
9,146
98.6
0.2
99.3
0.2
o0.001
o0.001
Women
5297
99.2
0.3
98.4
0.4
o0.001
9,606
92.0
0.2
92.2
0.3
o0.001
o0.001
4789
36.9
0.2
35.7
0.3
o0.001
8,150
33.0
0.1
33.4
0.1
o0.001
0.001
Men
2189
30.1
0.2
29.1
0.3
o0.001
4,278
27.4
0.1
27.9
0.1
0.001
o0.001
Women
2600
41.9
0.2
41.0
0.3
o0.001
3,872
39.0
0.2
39.3
0.2
o0.001
0.007
M
SE
M
SE
p-value
n
M
2684
27.1
0.6
29.3
0.9
o0.001
6,296
Men
1275
25.6
0.9
28.9
1.4
0.821
Women
1409
28.3
0.8
29.5
1.1
Overweight
3431
32.2
0.6
29.1
Men
1784
36.4
1.0
Women
1647
29.0
Obese
4155
Men Women
Variable Under/normal weight
Extremely obese
Waist circumference (cm)
Body fat %, including BMC
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Note: Ms are given as %, unless otherwise noted. a Unadjusted Ms and SEs b Ms and SEs adjusted by the standard age proportions derived from 2000 Census data n p testing disability severity; nnp comparing disability vs no disability; nnn p testing disability-by-weight category interaction BMC, bone mineral content
a
p-value***
Froehlich-Grobe et al / Am J Prev Med 2013;45(1):83–90
SEa
n
*
Froehlich-Grobe et al / Am J Prev Med 2013;45(1):83–90
(1) Individuals with the most severe impairments may not come to the mobile exam unit because of physical limitations or difficulties with transportation or arranging assistance; and (2) no data on height and weight are available for individuals who are unable to stand unassisted. Thus, of the 1286 individuals with disabilities who were missing BMI data, some may have been unable to perform the tests. Notably, NHIS data published by Weil et al.9 found that obesity was more prevalent among those with mobility impairments than those with sensory, mental health, or other physical impairments. A final limitation derives from the cross-sectional design of the NHANES survey. Thus, the directionality of the relationship between disability and obesity cannot be determined (i.e., whether obesity causes disability or disability causes obesity).
Conclusion The prevalence estimates of obesity (41.5%) and extreme obesity (9.3%) based on NHANES data for individuals with disabilities are substantially higher than previous prevalence estimates based on self-reported height and weight.6,7,9 The data also indicate that the average waist circumference among Americans with disabilities exceeds the current guidelines17 and that their average percentage body fat is indicative of obesity. Further, values observed for blood pressure, cholesterol, CRP, and glucose increased with increasing body weight. These findings are consistent with results from this study and others15 showing that people with disabilities experience a greater burden of obesity-related chronic diseases such as hypertension, high cholesterol, and diabetes than those without disabilities. Continuing efforts to address and reverse the obesity epidemic cannot afford to neglect the 54 million Americans living with disabilities. Individuals with disabilities should be included in studies designed to examine factors contributing to weight gain and test innovative weight loss and maintenance strategies. Additionally, healthcare providers should be encouraged to include individuals with disabilities in their clinical weight management efforts. Specifically, primary care providers should be reminded and encouraged to follow the U.S. Preventive Services Task Force31 and Healthy People 202032 recommendations to screen all individuals for obesity and refer those obese individuals, including those with disabilities, to intensive multicomponent weight management programs. The potential effects of addressing obesity among individuals with disabilities are great and include improved general health and quality of life and reduced secondary conditions and financial expenditures for treating obesity-related chronic conditions. No financial disclosures were reported by the authors of this paper.
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Appendix Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.amepre.2013.02.021.
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