Research in Gerontological Nursing

Empirical Research 

Prevalence of Moderate to Severe Obesity Among U.S. Nursing Home Residents, 2000–2010

Holly C. Felix, PhD, MPA; Christine Bradway, PhD, CRNP, FAAN; Latarsha Chisholm, PhD, MSW; Rohit Pradhan, PhD; Robert Weech-Maldonado, PhD

Abstract

Obesity rates are high among all age groups, including older adults. Obesity negatively affects health and functional ability, increasing the risk for nursing home (NH) admission. The current study examines trends over 11 years in moderate to severe obesity rates among NH residents. A generalized least squares regression model for panel data was used to test the effect of time (years) on the rates. A significant increase in rates and significant variation in rates were observed. Little research has focused on the issue of obesity in NHs. High and increasing rates and variation in rates raise questions on demand and access to NH care for obese older adults. Additional research is needed to consider factors other than time that may affect NHs’ ability to admit moderate to severely obese individuals. Understanding these trends will help NHs prepare for future demand, ensure equal access, quality care, and financing of services.

[Res Gerontol Nurs. 2015; 8(4):173–178.]

Dr. Felix is Associate Professor of Health Policy, and Dr. Pradhan is Assistant Professor of Health Policy, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas; Dr. Bradway is Associate Professor of Gerontological Nursing, School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania; Dr. Chisholm is Assistant Professor, Department of Health Management & Informatics, University of Central Florida, Orlando, Florida; and Dr. Weech-Maldonado is Professor and L.R. Jordan Chair of Health Administration, Department of Health Services Administration, University of Alabama at Birmingham, Birmingham, Alabama.

The authors have disclosed no potential conflicts of interest, financial or otherwise. The study used 11 years of nursing home–level datasets made publicly available through the National Institute on Aging–funded Shaping Long-Term Care in America Project, referred to as LTCFocus, of the Center for Gerontology and Healthcare Research at the Brown University. This line of research has grown out of Dr. Felix’s career development award focused on the impact of obesity on long-term care in the United States (KL2RR029883) awarded by the U.S. Translational Research Institute (UL1TR000039).

Address correspondence to Holly C. Felix, PhD, MPA, Associate Professor of Health Policy, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, 4301 West Markham Street, Slot 820, Little Rock, AR 72205; e-mail: felixholly@uams.edu.

Received: August 18, 2014
Accepted: November 24, 2014
Posted Online: March 10, 2015

Abstract

Obesity rates are high among all age groups, including older adults. Obesity negatively affects health and functional ability, increasing the risk for nursing home (NH) admission. The current study examines trends over 11 years in moderate to severe obesity rates among NH residents. A generalized least squares regression model for panel data was used to test the effect of time (years) on the rates. A significant increase in rates and significant variation in rates were observed. Little research has focused on the issue of obesity in NHs. High and increasing rates and variation in rates raise questions on demand and access to NH care for obese older adults. Additional research is needed to consider factors other than time that may affect NHs’ ability to admit moderate to severely obese individuals. Understanding these trends will help NHs prepare for future demand, ensure equal access, quality care, and financing of services.

[Res Gerontol Nurs. 2015; 8(4):173–178.]

Dr. Felix is Associate Professor of Health Policy, and Dr. Pradhan is Assistant Professor of Health Policy, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas; Dr. Bradway is Associate Professor of Gerontological Nursing, School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania; Dr. Chisholm is Assistant Professor, Department of Health Management & Informatics, University of Central Florida, Orlando, Florida; and Dr. Weech-Maldonado is Professor and L.R. Jordan Chair of Health Administration, Department of Health Services Administration, University of Alabama at Birmingham, Birmingham, Alabama.

The authors have disclosed no potential conflicts of interest, financial or otherwise. The study used 11 years of nursing home–level datasets made publicly available through the National Institute on Aging–funded Shaping Long-Term Care in America Project, referred to as LTCFocus, of the Center for Gerontology and Healthcare Research at the Brown University. This line of research has grown out of Dr. Felix’s career development award focused on the impact of obesity on long-term care in the United States (KL2RR029883) awarded by the U.S. Translational Research Institute (UL1TR000039).

Address correspondence to Holly C. Felix, PhD, MPA, Associate Professor of Health Policy, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, 4301 West Markham Street, Slot 820, Little Rock, AR 72205; e-mail: felixholly@uams.edu.

Received: August 18, 2014
Accepted: November 24, 2014
Posted Online: March 10, 2015

The obesity epidemic has affected all age groups in the United States; older adults have not been immune to the epidemic. More than one third of American adults are obese (body mass index [BMI] ≥30), as are those specifically in the older adult group (60 or older). Moderate to severe obesity (BMI ≥35) among this group is also high (14%) and comparable to the rate among adults ages 20 to 59 (13.6% to 15.7%). Although obesity rates have leveled off in recent years, obesity rates among older women have increased significantly from 2003 to 2012 (Flegal, Carroll, Kit, & Ogden, 2012; Ogden, Carroll, Kit, & Flegal, 2014).

Obesity is problematic for any age group, but it can exacerbate many age-related chronic conditions (Villareal, Apovian, Kushner, & Klein, 2005), leading to increased health services utilization—average annual Medicare expenditures are twice as much for severely obese beneficiaries compared to normal beneficiaries (Daviglus et al., 2004)—and increased need for nursing home (NH) care (Elkins et al., 2006; Valiyeva, Russell, Miller, & Safford, 2006). This increased need may be due to obesity’s negative effect on general strength, lower body mobility, and ability to perform activities of daily living (ADLs) among older adults (Jenkins, 2004). The effect of obesity on physical function is exasperated with higher BMIs, as shown by a study of homebound older adults in North Carolina (Sharkey, Ory, & Branch, 2006). Older adults with BMI ≥35 (compared to those with BMIs 25 to 29.9 and BMIs 30 to 34.9) were seven times more likely to lose lower body physical function over 1 year (p < 0.001), after controlling demographic and comorbid conditions (Sharkey et al., 2006). Some scientists have even expressed concern that the obesity epidemic will undermine past reductions in disability rates among older adults (Sturm, Ringel, & Andreyeva, 2004).

A small but growing body of research has started to examine how obesity effects NH care (Bradway, DiResta, Fleshner, & Polomano, 2008; Bradway et al., 2009; Felix, 2008a,b; Lapane & Resnick, 2006). Using NH admission assessment data, Felix (2008b) found that older adults (i.e., age ≥60) who were obese at admission were significantly more likely to require assistance from two or more staff to perform basic ADLs (e.g., bathing, toileting, dressing) compared to those individuals who were not obese, resulting in greater use of NH staff time and higher labor costs (Felix et al., 2009). Interestingly, Felix (2008b) also found that among the studied older adults entering NHs, the average age of those who were obese (78.5 years) was significantly lower than those older adults who were not obese (82.5 years), raising questions about length of stay differences between obese and non-obese NH residents.

Despite this emerging evidence of the impact of obesity on NH care, only three studies could be identified that examined the prevalence of obesity within NHs (Felix, 2008b; Lapane & Resnick, 2005; Zhang, Li, & Temkin-Greener, 2013). Lapane and Resnik (2005) documented a 66.7% increase in prevalence of obesity among those newly admitted to NHs in five states (Kansas, Maine, Mississippi, New York, and South Dakota) from 1992 (∼15%) to 2002 (25%). They also found that 17.8% of newly admitted residents (all ages) in all U.S. NHs in 2002 were obese (Lapane & Resnick, 2005). Felix (2008b) documented a slightly lower prevalence rate of obesity (15%) among older residents (age ≥60) newly admitted to NHs in Arkansas in 1999–2004. In the most recent analysis, Zhang et al. (2013) documented that 21% of individuals newly admitted (all ages) to New York NHs from 2005–2007 were obese.

Although these studies help lay the ground work for understanding the extent of obesity among U.S. NH residents and the potential impact of obesity among NH residents, they are limited by the age of the data used, the geographic area examined, and variations in outcome. More importantly, these existing studies broadly describe obesity (i.e., BMI ≥30) and do not examine trends in higher classes of obesity (e.g., moderate [Class 2] to severe obesity [Class 3], BMI ≥35) (World Health Organization [WHO], 2000). This distinction is particularly important as those higher weights decrease physical function (Sharkey et al., 2006) and increase caregiver challenges for health care workers, as documented in acute care settings (Drake, Dutton, Engelke, McAuliffe, & Rose, 2005; Drake et al., 2008) that are likely to persist into NHs.

NHs have already been described as being ill-prepared (Lapane & Resnick, 2006) for the obesity epidemic. Understanding past trends in moderate to severe obesity rates in NHs will help predict future demand as well as help inform NH policy and practice necessary for the care of this subgroup. The current study aims to fill this gap by describing trends in moderate to severe obesity rates in federally certified U.S. NHs from 2000 to 2010.

Method

This retrospective, observational study used 11 years of NH-level datasets made publicly available through the National Institute on Aging (NIA)-funded Shaping Long-Term Care in America Project, referred to as LTCFocus, of the Center for Gerontology and Healthcare Research at Brown University. The annual datasets contain characteristics of federally certified U.S. NHs and all their residents (of all ages) as of the first Thursday in April for each year (in aggregate). This dataset also includes the percent of residents on that date who were moderately to severely obese. The BMI for moderate obesity, also referred to as Class 2 obesity, ranges from 35 to 39. Severe obesity, or Class 3 obesity, is classified as a BMI ≥40 (WHO, 2000). For any given year, resident characteristics for NHs with less than 4,500 NH days were not included in the datasets; therefore, analysis focuses on NHs with ≥4,500 NH days.

Summary statistics (e.g., mean) were used to describe the data from individual NHs, by U.S. region, and by NH profit status. A generalized least squares regression model for panel data was used to test the effect of time (years) on moderate to severe obesity rates in U.S. NHs. The unbalanced panel dataset contained 96,254 observations across 13,691 NHs, with an average of seven observations per nursing home (range = 1 to 11 observations).

The University of Arkansas for Medical Sciences Institutional Review Board determined that this study using publicly available, deidentified data was not human subjects research.

Results

The number of federally certified NHs with ≥4,500 NH days per year has steadily increased over the past 11 years, from 6,009 NHs in 2000 to 10,538 NHs in 2010. Over the 11 years, moderate to severe obesity rates in these NHs increased from 14.7% in 2000 to 23.9% in 2010 (Table). Results of the regression model indicate the annual increase was statistically significant (p < 0.0001). Specifically, for each additional year a 9.06% increase occurred in the moderate to severe obesity rates. Figure 1 illustrates the overall trend of increasing moderate to severe obesity rates in U.S. NHs with ≥4,500 NH days.

Moderate to Severe Obesity Rates in U.S. Nursing Homes, 2000–2010

Table:

Moderate to Severe Obesity Rates in U.S. Nursing Homes, 2000–2010

Annual moderate to severe obesity rates in U.S. nursing homes (black circle) and mean U.S. rate (line with white diamond), by year, 2000–2010.Data source: LTCFocus facility-level data files, 2000–2010; authors’ calculations.

Figure 1.

Annual moderate to severe obesity rates in U.S. nursing homes (black circle) and mean U.S. rate (line with white diamond), by year, 2000–2010.

Data source: LTCFocus facility-level data files, 2000–2010; authors’ calculations.

Substantial variation in moderate to severe obesity rates in any given year was observed. Rates ranged from zero to as high as 75%. However, the proportion of NHs with no moderately to severely obese residents declined from 4.7% of all NHs with ≥4,500 NH days in 2000 to <1% in 2010 (Figure 1).

Figure 2 shows the trends in moderate to severe obesity rates in NHs in the four U.S. Census Regions: Midwest, Northeast, South, and West. Midwest NHs had the highest rate of moderate to severe obesity among their residents compared to the other three regions in each of the 11 years observed. Across the same time frame, the NHs in the West maintained a lower prevalence rate among their residents.

Trends in moderate to severe obesity rates among residents of federally certified U.S. nursing homes, by U.S. Census region, 2000–2010. Date source: LTCFocus facility-level data files, 2000–2010.Note. Midwest = IA, IL, IN, KS, MI, MN, MO, ND, NE, OH, SD, and WI; Northeast = CT, MA, ME, NH, NJ, NY, PA, RI, and VT; South = AL, AR, DE, FL, GA, KY, LA, MD, MS, NC, OK, SC, TN, TX, VA, and WV; and West = AZ, CA, CO, ID, MT, NM, NV, OR, UT, WA, and WY.

Figure 2.

Trends in moderate to severe obesity rates among residents of federally certified U.S. nursing homes, by U.S. Census region, 2000–2010. Date source: LTCFocus facility-level data files, 2000–2010.

Note. Midwest = IA, IL, IN, KS, MI, MN, MO, ND, NE, OH, SD, and WI; Northeast = CT, MA, ME, NH, NJ, NY, PA, RI, and VT; South = AL, AR, DE, FL, GA, KY, LA, MD, MS, NC, OK, SC, TN, TX, VA, and WV; and West = AZ, CA, CO, ID, MT, NM, NV, OR, UT, WA, and WY.

Trends in moderate to severe obesity by NH profit status were also examined. Over the 11 years, moderate to severe obesity rates increased at a steady pace. However, a higher prevalence of moderately to severely obese residents was noted in for-profit NHs compared to non-profit NHs. On average, for-profit NHs had 1.4 percentage points more moderately to severely obese residents than non-profit NHs.

Discussion

Obesity is a significant public health issue, affecting all segments of the population, including those needing institutional care. However, trends in and effects of obesity in NHs have not been well studied. The current analysis shows an overall significant annual increase in the prevalence of moderate to severe obesity among NH residents from 2000 to 2010.

Significant variation in prevalence of moderate to severe obesity rates among U.S. NHs was also observed. These wide ranges in prevalence raise questions about access to NH care by moderately to severely obese individuals, which are similar to those raised about access to NH care by individuals from minority racial and ethnic groups. Studies have shown that NHs are segregated, with African Americans concentrated in lower quality NHs (Mor, Zinn, Angelelli, Teno, & Miller, 2004; Smith, Feng, Fennel, Zinn, & Mor, 2007). This may be the case for moderately to severely obese individuals as well. In a single state study, Zhang et al. (2013) found that lower quality of NH care (indicated by higher numbers of quality of care deficiencies) was significantly associated with higher obesity rates in NHs. This study only considered one NH characteristic—profit status—that may account for variance in NH obesity rates (Zhang et al., 2013). It will be important to continue to examine variation patterns in a U.S. sample of NHs to determine if the disparity persists across the country and to identify characteristics and policies that may mitigate this disparity.

In each year reviewed, NHs in the Midwest region of the United States had the highest average rates of moderate to severe obesity among NH residents. The current study was not able to consider state or regional factors (e.g., Medicaid NH payment rates), which could account for the observed variations. Community obesity rates may affect the demand for long-term care and, consequently, the prevalence of obesity among NH residents. If community obesity rates were the only contributor, the NHs in the Southern region, which has the highest obesity rates in the nation, would have the highest prevalence of obesity among its NH residents. However, this was not the case, suggesting factors other than community demographics may be influencing NH obesity rates and/or that access to NH care by obese individuals is problematic in the South. Other factors that may play a role in NHs decisions to admit obese individuals include facility characteristics (e.g., size, funding mix, occupancy rates) and market characteristics (e.g., other NHs or NH alternatives, cultural difference in preferences for types of care, state payment policies). Indeed, the current analysis found a difference (although not statistically significant) in the prevalence of moderate to severe obesity by NH profit status. Non-profit NHs had fewer moderately to severely obese residents than for-profit NHs. It was beyond the scope of the current preliminary analysis to fully examine the effect of these and other potentially important characteristics (individually and collectively) on NH moderate to severe obesity rates. Therefore, future research is needed to fully explore characteristics that act as barriers or facilitators to NH access by moderately to severely obese individuals.

Limitations

The current analysis used the LTCFocus dataset. Although this dataset is publically available and serves as a significant source of information on characteristics of U.S. NHs and NH residents, it represents an aggregate picture of all NH residents within each federally certified NH on one particular day, not just older adult residents. Older adult NH residents who are obese may have different care needs than younger NH residents who are obese. Nevertheless, 85% of U.S. NH residents are 65 or older (Centers for Medicare & Medicaid Services, 2013), and the average age of NH residents in the LTCFocus dataset was ≥79 (analysis not shown). Although the results reported herein cannot be used to specifically address moderate to severe obesity among older adults, they represent the overall trend of moderate to severe obesity in NHs and may be representative of the trends among older NH residents.

Previous research profiling NHs has considered and identified structural and market characteristics that account for variations in NH resident characteristics (e.g., percent of residents by race) (Brannon, Zinn, Mor, & Davis, 2002; Mor et al., 2004; Smith et al., 2007). Therefore, NH profit status was included in the current analysis but other characteristics that may account for differences in the prevalence of moderate to severe obesity among NH residents were not considered. Future analysis should consider these as well as resident characteristics to control for the differences between NHs and to help identify potential intervention points.

Conclusion

Moderate to severe obesity rates in U.S. NHs are high and increasing. It is important to understand these trends to prepare for likely demand and specific care needs. Factors other than time that may predict the change in moderate to severe obesity rates within specific NHs (e.g., NH and community characteristics) were not considered in the current analysis on overall trends. However, future analyses in this area should consider the effect of these characteristics to identify predictors of rates and assess admissions disparities by weight status.

References

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Moderate to Severe Obesity Rates in U.S. Nursing Homes, 2000–2010

YearNHs (N)Included NHsa (n, %)Mean MSOR (%) (SD)Median MSOR (%)(Range)
200016,9196,009 (35.52)14.7 (5.98)14.29 (0 to 48.78)
200116,7346,843 (40.89)15.9 (6.11)15.31 (0 to 71.43)
200216,5107,568 (45.84)17.22 (6.11)16.67 (0 to 49.4)
200316,3228,160 (49.99)18.29 (6.37)17.59 (0 to 60)
200416,1368,691 (53.86)19.47 (6.51)18.75 (0 to 58.82)
200516,0009,092 (56.83)20.4 (6.67)19.77 (0 to 51.61)
200615,8949,422 (59.28)21.2 (6.84)20.51 (0 to 55)
200715,8299,735 (61.5)21.9 (7.01)21.18 (0 to 65.31)
200815,7529,914 (62.94)22.61 (7.16)21.90 (0 to 68.75)
200915,70110,282 (65.49)23.24 (7.26)22.55 (0 to 72.5)
201015,67810,538 (67.22)23.94 (7.37)23.21 (0 to 75)

10.3928/19404921-20150223-01

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