Abstract
Background and Purpose
Obesity and physical inactivity are independently associated with declines in physical and functional limitations in older adults. The current study examines the impact of physical activity on odds of physical and functional limitations in older adults with central and general obesity.
Methods
Data from 6,279 community dwelling adults aged ≥ 60 years from the Health and Retirement Study 2006 and 2008 waves were used to calculate prevalence and odds of physical and functional limitation among obese older adults with high waist circumference (WC) (WC ≥ 88cm in females and ≥ 102cm in males) who were physically active vs. inactive (engaging in moderate/vigorous activity less than once per week). Logistic regression models were adjusted for age, gender, race/ethnicity, education, smoking status, body mass index (BMI) and number of comorbidities.
Results
Physical activity was associated with lower odds of physical and functional limitations among older adults with high WC odds ratios (OR) and confidence intervals (CI) were OR 0.59 (CI: 0.52–0.68) for physical limitations, OR 0.52 (CI: .44–.62) for activities of daily living and OR 0.44 (CI: 0.39–0.50) for instrumental activities of daily living.
Conclusion
Physical activity is associated with significantly lower odds of physical and functional limitations in obese older adults regardless of how obesity is classified. Additional research is needed to determine whether physical activity moderates long-term physical and functional limitations.
Keywords: older adults, waist circumference, physical activity, functional limitations, prevalence, obesity
INTRODUCTION
Obesity is associated with a variety of poor health outcomes including cardiovascular disease, increased prevalence of medical comorbidities, and functional disability.1–3 Approximately 35.5% of adults in the U.S. are currently obese.4 This represents an almost three-fold increase from 1960 to present and continues to rise, even among older adults.5 Among those aged 60 and above, the combined prevalence of overweight and obesity, as assessed by body mass index (BMI) is estimated at over 70%6. Concurrently, the prevalence of abdominal adiposity is also rising in the U.S. across all age groups.7 This growing trend in central adiposity represents an important public health concern given that excess abdominal fat is independently associated with disability among older adults.8 Although general adiposity (as measured by body mass index) remains the most widely used marker of obesity in clinical settings and epidemiological studies, accumulating evidence suggests that abdominal adiposity may be a more sensitive predictor of obesity- related health problems and functional impairment than BMI.9,10 Thus, gaining a better understanding of the effects of both general and abdominal obesity on functional outcomes is important for preserving independence in older adults.
Physical activity can help maintain and improve individuals’ health by decreasing risk of disability and delaying the onset of functional impairment.11,12 At least 150 minutes of moderate physical activity and/or muscle strengthening activities per week is recommended for health maintenance13 yet only 24% of adults aged 65 and older report engaging in any regular physical activity.14 Population estimates employing more objective measures of activity suggest even lower rates of engagement in older adults.15 Both physical inactivity and obesity are independently associated with functional decline and disability in older adults. However, less is known regarding the association between central adiposity, physical activity and functional outcomes in older adults.16 Given the heightened risk of disability and potential loss of independence among older adults who are obese, there is an urgent need for effective lifestyle interventions which may aide in the prevention and management of obesity-related limitation and functional disability. The current study examined the impact of physical activity on physical and functional limitations among community dwelling older adults with central adiposity.
METHODS
Data Source
This is a secondary analysis of existing data. Data was obtained from the 2006 and 2008 waves of the Health and Retirement Study (HRS), enhanced face to face interview. HRS is a nationally representative panel survey of community-dwelling adults aged 50 and older being conducted by the University of Michigan with support from the National Institute of Aging. The initial HRS sample was drawn in 1992 from a multi-stage, clustered area probability design of households, targeted individuals born between 1931 and 1941. Follow-up interviews and new cohort additions have occurred at regular intervals and have resulted in a nationally representative sample of American adults over age 50. A random one-half of the larger HRS sample was pre-selected to complete an enhanced face-to-face interview in 2006, which included physical and biomarker measurements. The second half of the HRS sample received the enhanced face-to-face interview in 2008. Inclusion of both 2006 and 2008 waves ensures that all HRS respondents who were eligible for and consented to the enhanced face-to-face interviews are included in the analyses. Additional descriptions of sampling procedures and study design are available online at: (http://hrsonline.isr.umich.edu).
Sample
A total of 14,724 eligible HRS respondents consented to physical assessments in 2006 and 2008. Of these 10,419 were ≥60 years of age. After eliminating respondents with missing waist circumference (WC), body mass index (BMI), out of range values and duplicate observations there were 6,279 subjects remaining for analyses. Subjects of all races/ethnicity were included in the sample. The study was exempt from Institutional Review Board approval at all respective institutions due to the de-identified nature of the data used.
Measures
Adiposity
Waist circumference was used as a proxy for abdominal adiposity.17 Waist circumference was assessed in person, using a non-elastic tape measure over a thin layer of clothing at the level of the respondents’ navel while standing. The respondent was instructed to inhale and slowly exhale, holding their breath at the end of the exhale. Waist circumference was measured and recorded while holding the exhale. Individuals were categorized as having high abdominal adiposity in accordance with waist circumference (WC) cut points established by National Institutes of Health.18 Women with WC ≥ 88cm and men with WC ≥ 102cm were classified as having high abdominal adiposity; individuals with values below cut points were categorized as having low abdominal adiposity. Body Mass Index (BMI) was also calculated where available for all respondents who consented to physical measures. In HRS, weight was measured using a Healthometer 830KL (Medstock, Australia) scale and rounded to the nearest half pound. Weight for individuals over 300lbs was not recorded in HRS as this was beyond the capacity of the measurement device. Height was measured by having the respondent stand barefoot with their heels and shoulders touching the wall. Individuals with BMI between 18.5 to 24.9 kg/m2 were classified as normal weight, 24.9–29.9 kg/m2 as overweight and ≥ 30kg/m2 as obese.18 Individuals who were underweight (n=61) were excluded from the analyses as this population is known to be at higher risk of frailty and disability.19
Physical Activity
Physical activity (PA) was assessed using a self-report physical health questionnaire as part of the HRS interview. Respondents were asked: “ How often do you take part in sports or activities that are vigorous, such as running or jogging, swimming, cycling, aerobics or gym, workout, tennis, or digging with a spade or shovel: more than once a week, once a week, one to three times a month, or hardly ever or never?” and “ And how often do you take part in sports or activities that are moderately energetic such as, gardening, cleaning the car, walking at a moderate pace, dancing, floor or stretching exercises … ?” Frequency of engagement in HRS was reported as: more than once a week, once a week, one to three times a month, or hardly ever or never?” For purposes of analyses respondents reporting that they engaged in moderate or vigorous PA “once per week”, or “more than once per week” were classified as active; those reporting activity less than once per week were classified as inactive (ref=0).
Outcome Measures
Physical Limitations (PL) in HRS was assessed using self-report. Respondents were asked to report whether ‘they had difficulties (yes, no) in performing the following tasks because of a health or physical problem’: walking several blocks, walking 1 block, sitting 2 hours, getting up from chair, climbing one flight of stairs, stooping, reaching arms, pulling/pushing large objects, lifting weights and picking up a dime. All yes responses were compiled into a summary score in the HRS database ranging from 0–10. Univariate analyses revealed that 67% of our sample reported at least 1 limitation. Thus we chose a conservative cut point. For purposes of these analyses, respondents who reporting difficulty with performing two or more of the above tasks were classified as having physical limitations (0= limitation,1=limitation).
Functional Limitations
Activities of daily living (ADL’s) and instrumental activities of daily living (IADLs) were used to assess functional limitations20. Respondents were classified as having ADL limitations if they reported difficulty or inability with one or more of the following: bathing, dressing, eating, toileting or getting out of bed. Respondents were classified as having IADL limitations if they reported difficulty with at least one of the following IADL’s: preparing meals, managing money or needing help with house or yard work, using the phone or taking medications All limitations reported in this manuscript were measured in HRS using self-report. Respondents were instructed to exclude any difficulties that were expected to last less than three months. For all outcomes, responses were dichotomized (0=no limitation vs. 1=limitation).
Covariates
Race/ethnicity (white, black, other) were entered as a categorical variable into the model. Age at time of physical assessment, years of education completed and number of medical comorbidities were entered as continuous variables in the model. The comorbidity index ranged from 0 to 8 to reflect the number of diagnosed health conditions that the respondent self-reports. Conditions include diabetes, hypertension, lung disease, stroke, any cancer, arthritis, myocardial infarction and chronic heart failure coded (0=no history, 1=positive history). Gender (male=0, female=1) and current smoking status were entered as dichotomous variables into the model.
Analyses
The prevalence and odds of physical and functional limitations were examined within each waist circumference (WC) category using chi-square and multivariate logistic regression. Unadjusted models were used to examine the impact of physical activity on functional limitations within each WC category as well as within each BMI category. Adjusted, multivariable models were adjusted for age, years of education, ethnicity, gender, smoking status, BMI, and number of medical comorbidities. Waist circumference was used as a covariate in models stratified by BMI. All data was examined using SAS software version 9.3 (SAS Institute Cary, NC) and weighted using the HRS respondent-level weights for physical measures which includes adjustments for sample selection probability and non-response. Detailed documentation regarding HRS sample weight calculations is available at (http://hrsonline.isr.umich.edu/sitedocs/wghtdoc.pdf). Statistical tests were two-sided with p-values less than or equal to 0.05. Confidence intervals excluding 1.0 were considered statistically significant.
RESULTS
Respondent demographics are presented in Table 1 by WC category. Over half of the sample was classified as having high abdominal adiposity (as measured by WC). Those in the high WC category were less educated, slightly younger, less active and had a higher number of medical comorbidities than those in the low circumference category and were predominately female. Prevalence of physical and IADL limitations was notably higher among those with high WC as compared to those with low WC but there were no significant differences in the prevalence of ADL limitation between low and high WC groups. Prevalence of physical, ADL and IADL limitations are reported in Table 2 by WC. We also report prevalence by BMI for purposes of comparison.
Table 1.
Differences in Sample Characteristics by Waist Circumference Category
| Characteristic | Total Sample | Low WC | High WC | P Valuea |
|---|---|---|---|---|
| N | 6,279 | 2,353 | 3,926 | |
| M(SD) | M(SD) | M(SD) | ||
| Age years | 68.9 (6.09) | 69.2 (6.17) | 68.7 (6.03) | .0004 |
| Education years | 12.3 (3.30) | 12.4 (3.39) | 12.2 (3.26) | .0022 |
| Comorbidities | 2.7 (1.22) | 2.6 (1.23) | 2.8 (1.21) | .0001 |
| Waist Circumference (cm) | 100.1 (14.69) | 87.3 (8.88) | 107.8 (11.86) | .0001 |
| Sex N(%) | <.0001 | |||
| Male | 2875 (45.8) | 1666 (70.8) | 1209 (30.8) | |
| Female | 3404 (54.2) | 687 (29.2) | 2717 (69.2) | |
| Race N(%)b | .05 | |||
| White | 5106 (81.3) | 1947 (82.7) | 3159 (80.5) | |
| Black | 1015 (16.2) | 352 (15.0) | 663 (16.9) | |
| Other | 158 (2.5) | 54 (2.3) | 104 (2.7) | |
| Current Smoker N(%) | 1517 (24.2) | 615 (26.1) | 902 (23.0) | .006 |
| Active N(%) | 3429 (54.6) | 1392 (59.2) | 2037 (51.9) | <.0001 |
| Body Mass Index N(%)b | <.0001 | |||
| Normal | 1523 (24.5) | 1156 (50.4) | 367 (9.4) | |
| Overweight | 2310 (37.2) | 910 (39.7) | 1400 (35.7) | |
| Obese | 2385 (38.4) | 229 (10.0) | 2156 (55.0) |
Abbreviations: WC=waist circumference; M=mean; SD=standard deviation
Chi-square for categorical variables and t-test for continuous variables used to determine P values.
Totals may not add up to 100% due to rounding.
Table 2.
Prevalence of Physical and Functional Limitations in Physically Active, Community Dwelling Older Adults by WC and BMI
| Obesity Category | Physical Limitations | ADL | IADL |
|---|---|---|---|
| N(%)a | N(%)a | N(%)a | |
| Waist Circumference | |||
| Low WC | 1,1091 (46.4) | 595 (49.8) | 1,011 (43.9) |
| High WC | 2,163 (55.1) | 1,144 (50.0) | 1,823 (47.3) |
| Body Mass Index | |||
| Normal | 721 (47.3) | 417 (53.1) | 702 (46.8) |
| Overweight | 1137 (49.2) | 592 (47.0) | 997 (44.1) |
| Obese | 1,356 (56.9) | 710 (50.5) | 1,100 (47.0) |
Abbreviations: ADL=activities of daily living; IADL=instrumental activities of daily living; WC=waist circumference; BMI=body mass index.
Totals may not add up to 100% due to rounding.
Odds ratios and confidence intervals for functional limitations among physically active older adults as compared to older adults who report low or no activity are presented in Table 3. A total of n =1,503 of the sample had non-positive weights and were automatically excluded from the analyses (they did not contribute statistically to the analyses). Both un-weighted (n = 6,279) and weighted (n = 4,776) adjusted models are reported in Table 3. However, a comparison of weighted and un-weighted models revealed no meaningful differences in the results. Results discussed in text are un-weighted. In the high WC group, physical activity was associated with significantly lower odds of physical, ADL and IADL limitations. The association remained after adjusting for age, gender, race/ethnicity, education, smoking status, BMI and number of comorbidities. Physical activity was also associated with lower odds of physical and functional limitation among those with low WC. Consistent with existing literature,2 having a higher number of comorbidities was associated with higher odds of limitation in all functional domains among older adults with high and low WC. Similar results were obtained using BMI categories (see Table 4). Gender and ethnicity were also found to be differentially associated with odds of physical and functional impairment among older adults with low WC. Non-white status was marginally associated with lower odds of physical limitation OR .82 (.67–1.00), but not ADL or IADL limitation; and being female was associated with higher odds of ADL limitation OR 1.52 (1.16–1.99).
Table 3.
Odds of Physical and Functional Limitation for Physically Active, Community Dwelling Older Adults
| Obesity Category | Physical Limitations | ADL | IADL | ||||||
|---|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | OR (95% CI) | OR (95% CI) | |||||||
| Waist Circumference | Unadjusted | Adjusted | Adjusted Wt. | Unadjusted | Adjusted | Adjusted Wt. | Unadjusted | Adjusted | Adjusted Wt. |
| Low WC | .48 (.41–.57)a | .56 (.47–.66)a | .56 (.45–.71)a | .49 (.39–.62)a | .51 (.40–.64)a | .58 (.42–.79)b | .35 (.29–.41)a | .39 (.32–.46)a | .34 (.27–.44)a |
| High WC | .52 (.44–.59)a | .59 (.52–.68)a | .66 (.56–.68)a | .50 (.42–.59)a | .52 (.44–.62)a | .45 (.36–.57)a | .40 (.35–.45)a | .44 (.39–.50)a | .48 (.40–.58)a |
| BMI | |||||||||
| Normal | .47 (.38–.58)a | .54 (.44–.67)a | .48 (.36–.64)a | .49 (.37–.65)a | .51 (.38–.69)a | .60 (.41–.88)d | .37 (.30–.45)a | .41 (.33–.51)a | .43 (.32–.57)a |
| Overweight | .48 (.41–.57)a | .56 (.47–.67)a | .62 (.49–.79)a | .52 (.42–.65)a | .55 (.44–.69)a | .49 (.36–.66)a | .36 (.30–.43)a | .41 (.34–.48)a | .39 (.30–.49)a |
| Obese | .56 (.48–.66)a | .64 (.54–.76)a | .74 (.59–.93)c | .48 (.39–.60)a | .51 (.39–.60)a | .44 (.33–.59)a | .41 (.35–.49)a | .47 (.39–.55)a | .50 (.39–.63)a |
Abbreviations: ADL=activities of daily living; IADL=instrumental activities of daily living; OR=odds ratios; CI=confidence intervals.
Note. Adjusted Wt. models are reported for n = 4,776 of the sample.
p = .0001;
p <.0006
p =.01
p =.008
Table 4.
Independent Impact of Increasing Comorbidities on Physical and Functional Limitations in Physically Active, Community Dwelling Older Adults.
| Obesity Category | Physical Limitations | ADL | IADL | |||
|---|---|---|---|---|---|---|
| OR (95% CI) | OR (95% CI) | OR (95% CI) | ||||
| Waist Circumference | ||||||
| Low WC | 1.48 (1.37– 1.59)a | 1.46 (1.32– 1.61)a | 1.13 (1.02– 1.25)a | 1.21 (1.05– 1.39)a | 1.54 (1.43– 1.67)a | 1.67 (1.50–1.86)a |
| High WC | 1.48 (1.40– 1.6)a | 1.54 (1.42– 1.67)a | 1.23 (1.15– 1.33)a | 1.21 (1.09– 1.34)a | 1.00 (0.85–1.17)a | 1.65 (1.52–1.79)a |
| Body Mass Index | ||||||
| Normal | 1.45 (1.32– 1.58)a | 1.41 (1.25– 1.58)a | 1.09 (0.96– 1.24) | 1.09 (0.92–1.29) | 1.55 (1.41–1.71)a | 1.73 (1.52–1.97)a |
| Overweight | 1.50 (1.39–1.62)a | 1.54 (1.38– 1.71)a | 1.21 (1.10–1.34)a | 1.22 (1.07– 1.38)b | 1.52 (1.41–1.65)a | 1.56 (1.40– 1.73)a |
| Obese | 1.45 (1.34– 1.57)a | 1.53 (1.37–1.70)a | 1.25 (1.14–1.38)a | 1.28 (1.11– 1.46)c | 1.63 (1.50–1.77)a | 1.72 (1.55– 1.91)a |
Abbreviations: ADL=activities of daily living; IADL=instrumental activities of daily living; OR=odds ratios; CI=confidence intervals.
Note. Adjusted for n = 4,776 of the sample.
p = .0001;
p <.003
p =.0004
DISCUSSION
The current study examined the impact of physical activity on prevalence and odds of physical and functional limitations in obese older adults. Obesity was categorized using both waist circumference and body mass index criteria. Our results indicate that regardless of the obesity criteria used (WC or BMI), physical activity is significantly associated with lower odds of physical and functional limitations in older adults who are obese. Obese older adults in the current sample who reported engaging in moderate/vigorous physical activity at least once per week were significantly less likely to report physical and functional limitations than those who reported low /no physical activity. Finding suggests that the benefits of physical activity are not limited to normal weight older adults, but may moderate the negative impact of carrying excess weight on physical and functional limitations among those who are obese. Our results are also encouraging in that the deleterious effects of increasing comorbidities did not negate the positive impact of PA on physical and functional limitations in the current study. This is a particularly important consideration among obese elders whom are more likely to present with multiple health conditions and suggests that even minimal engagement in moderate/vigorous PA is associated with reduced odds of impairment in spite of multiple health conditions.
Our findings also suggest that there are important gender and ethnic differences in the association between weight and physical and functional outcomes. Consistent with observations from studies of obese older persons and recently published trends4, there was a higher proportion of women classified as obese than men. This was particularly true when using WC guidelines and confirms recent reports that abdominal weight gain among women is occurring at a much greater rate than men.7 However, normal and overweight women in this sample tended to be at higher odds of ADL limitation than men, but the odds of ADL limitation did not differ between men and women among the obese as might be expected. This may in part be due to biological differences in body composition between men and women.21 We also found that non-white status was associated with lower odds of physical limitations in higher weight categories in spite of reports consistently placing minorities at higher ends of the weight spectrum. These findings suggests that the relationship between excess weight and functional outcomes in both minorities/non-whites and older women is complex and merits further investigation.22 Current research is underway by our group to further examine the nature of these ethnic and gender differences.
Primary strengths of the current study include analyses of data based in a large, well characterized, nationally representative community dwelling sample, and the availability of two objective measures of adiposity. Although the current results are based on a nationally representative population, the results are limited in generalizability in that they are cross-sectional in nature. Examination of longitudinal data is needed in order to understand the differential impact of changes in physical activity and changes in weight on physical and functional limitations over time particularly in women and minorities. Additional limitations include that there were no objective measures of physical activity used in the survey and the simple count measure of comorbidity used for analyses does not take disease severity into account.23 Imprecise measurements of physical activity may have affected study results including prevalence estimates reported here.
CONCLUSION
Engagement in moderate/vigorous intensity exercise at least once per week is associated with lower odds of physical and functional impairment in obese older adults. Encouraging physical activity in normal weight and obese older adults may help to lower the odds of physical and functional impairment. Additional research is needed to examine the long-term benefits of physical activity in older adults who remain obese.
ACKNOWLEDGEMENTS
We acknowledge James A. Blumenthal, Gerda Fillenbaum and Celia Hybels for their reviews of previous versions this manuscript. Cassandra M. Germain, PhD. is supported by NHLBI IRS Diversity Supplement #3R01HL109219 - 02S1. Elizabeth Vasquez, Dr. PH has no financial disclosures. John A. Batsis, MD is partially supported by UB4HP19206-01-00 as a Medical Educator from the Health Resources and Services Administration, the Dartmouth Centers for Health and Aging, and has received support from the Department of Medicine, Dartmouth-Hitchcock Medical Center. He has served as a consultant to the legal firm Dinse, Knapp, McAndrew LLC for a clinical case review in 2012.
This project was initiated and analyzed solely by the investigators.
Appendix
Table 5.
Demographic Characteristics of Subsample Missing BMI
| N | 6,486 | 207 | |
|---|---|---|---|
| M(SD) | M(SD) | ||
| Age years | 68.9 (6.08) | 69.2 (6.13) | .531 |
| Education years | 12.3 (3.30) | 12.4 (3.04) | .667 |
| Comorbidities | 2.7 (1.22) | 3.0 (1.21) | .0005 |
| Waist Circumference (cm) | 100.7 (15.44) | 118.17 (24.8) | .0001 |
| Sex N(%) | .573 | ||
| Male | 2967 (45.7) | 90 (43.48) | |
| Female | 3524 (54.3) | 117 (56.52) | |
| Race N(%)b | .134 | ||
| White | 5267 (81.1) | 159 (76.81) | |
| Black | 1061 (16.4) | 43 (20.77) | |
| Other | 163 (2.5) | 5 (2.42) | |
| Current Smoker N(%) | 1562 (24.1) | 45 (21.74) | .487 |
| Active N(%) | 3520 (54.3) | 91 (43.96) | .004 |
| Body Mass Index N(%)b | |||
| Normal | 1524 (24.5) | ||
| Overweight | 2311 (37.1) | ||
| Obese | 2388 (38.4) |
Footnotes
Conflicts of Interest
There are no additional financial disclosures to report.
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