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. Author manuscript; available in PMC: 2014 Aug 7.
Published in final edited form as: J Aging Health. 2013 May 15;25(4):701–717. doi: 10.1177/0898264313488165

Prevalence and correlates of disability in a late middle-aged population of women

Carrie A Karvonen-Gutierrez 1, Kelly R Ylitalo 1,2
PMCID: PMC4124609  NIHMSID: NIHMS598096  PMID: 23676712

Abstract

Objectives

This study estimates the prevalence of disability among late middle-aged women and identifies important correlates of disability among this population.

Methods

Disability was assessed among 376 participants of the Michigan Study of Women’s Health Across the Nation cohort at the 2011 follow-up using the World Health Organization Disability Assessment Scale. Demographic and health measures were related to disability status using logistic regression models (none or mild vs. moderate, severe or extreme disability).

Results

Nearly 25% of women reported moderate to extreme global disability. African-American race/ethnicity, economic strain, peripheral neuropathy and depressive symptomatology was associated with global disability. Obesity, knee osteoarthritis and hypertension were only associated with disability for the mobility domain (getting around).

Discussion

The prevalence of disability is relatively high among this population of late middle-aged women. Efforts to prevent or forestall disability should be extended to include mid-aged populations as they may be most amenable to intervention.

INTRODUCTION

The mid-life is an important lifestage with respect to onset of poor functioning. The National Health Interview Survey identified that 15% of persons aged 45-64 had some functional limitations or disability and of those, 50% reported that their functional limitations or disability developed between the ages of 40 and 55 years (Adams & Marano, 1995). Assessment of mid-life disablity has largely relied on report of functional limitations or difficulty preforming activities of daily living. In the Study of Women’s Health Across the Nation (SWAN), a longitdinal multi-site study of mid-life women, 29.6% of the cohort (aged 45-57 years) reported moderate functional limitations and 11.0% reported severe limitations (Tseng et al., 2012). Similarly, data from a British cohort of mid-aged adults reported 3-5% prevalence of uppper and lower body limitations at age 43 years; by age 53 years, the prevalence increased to 21-28% (Murray et al., 2011). Important correlates of mid-aged disability include obesity (Imai et al., 2008; Nosek et al., 2008), depression symptoms (Wolinsky et al., 2007), and chronic disease comorbidity (Melzer, Gardener, & Guralnik, 2005).

Physical functioning and functional limitations are an important part of the disablement process (Verbrugge & Jette, 1994; Nagi, 1976). While the disablement model (active pathology → impairment → functional limitations → disability) has served as the prevailing guide for disability research, and importantly considers transition to disability as a process, it has been critiqued as focusing only on medical pathologies as the initating factor in the cascade towards disablement. Recognition that functional limitations may be due to factors without a well-defined pathology, or that limitations may be more more social or situational in nature has prompted an international collaboration to develop a biopsychosocial model which includes personal, social and environmental factors in addition to health conditions as important determinants of disability.

The World Health Organization’s (WHO) International Classification of Functioning (ICF), which conceptualizes disability as a general construct not only defined by underlying pathology, includes 6 domains: (1) diseases/disorders; (2) body functions/structure; (3) activity; (4) participation; (5) environmental factors and (6) personal factors. This biopsychosocial model allows for examination of non-disease-related disability, which may be important among mid-aged populations who may not yet have manifested overt disease. To support assessment of ICF-conceptualized disability, the WHO developed the Disability Assessment Schedule (WHO-DAS). It is recognized and promoted as a universal and standardized measure of disablity, suitable for national and international comparisons of disability prevalence and determinants across populations and age groups (Ustün et al., 2010; Garin, Ayuso-Mateos, & Almansa, 2010).

While the WHO-DAS has examined disability and its correlates in several clinical popoulations including those with mental health conditions, migraine, Parkinson’s Disease, multiple sclerosis and traumatic brain injury, few studies have examined the prevalence of WHO-DAS assessed disability in the general population. Data from a Spanish population cohort study among individuals aged 75 years and older report that 10% of individuals had severe or extreme disablity and that this prevalence was slightly higher among women (Virues-Ortega et al., 2011b). In the same population, Alzheimers Disease and depression were highly predictive of severe/extreme disability (Virues-Ortega et al., 2011a).

Adoption of the ICF framework by United States (US) researchers has been met with tepid enthusiasm (Jette, 2009; Guralnik & Ferrucci, 2009) given the large body of work supported by the Nagi model (Nagi, 1976). However, recent work demonstrated that depression and obesity were associated with WHO-DAS assessed disbility among a sample of mid-aged women but that the association with disability differed by domain (Arterburn et al., 2012). While characterization of these domain-specific differences is the strength of the ICF framework, there are currently no other published studies reporting the prevalence of WHO-DAS assessed disability and its correlates among a community-dwelling US population.

Obtaining disability prevalence estimates and gaining a better understanding of processes that begin or become prominent in the mid-life is essential to plan effective clinical or public health interventions, particularly because the mid-life represents a time in which individuals may be more amenable and able to respond to interventions. This paper estimates the prevalence of WHO-DAS assessed disability among a cohort of mid-life women and aims to identify factors associated with disability in that population.

METHODS

Study population

The SWAN study is a multi-ethnic cohort study of the menopause transition and its associated health consequences. First established in 1996, the Michigan site is one of seven clinical sites for SWAN and includes a population-based sample of eligible women from two Detroit-area communities identified using a community census based on the electrical utility listings of the targeted communities. Households were contacted by telephone (if available) or in-person; the response rate for inclusion in the cohort was 58.9% among eligible women (Sowers et al., 2000).

At the study’s inception in 1996, a total of 543 eligible women were recruited into the Michigan SWAN cohort, including 325 African American and 218 Caucasian women. Eligiblity criterion at baseline included 42-52 years of age, having an intact uterus, having had at least one menstrual period in the previous 3 months, no use of reproductive hormones in the previous 3 months, and self-identification as either African American or Caucasian race/ethnicity. Data for this analysis were collected at the 2011 study visit in which 77% of the still-living Michigan SWAN women participated. The analytic sample represents 376 women with a 2011 study visit; of those, 326 had an in-person visit that included physical measurements for assessment of body size. The University of Michigan Institutional Review Board approved the study protocol and written informed consent was obtained from each participant.

Measures

Disability assessment

Disability was assessed at the 2011 follow-up visit using the WHO-DAS instrument, which includes 36 questions across six domains including (1) understanding and communicating (6 items); (2) getting around (5 items); (3) self care (4 itms); (4) getting along with people (5 items); (5) engaging in life activities (8 items); and (6) participation in society (8 items). Each item is scored using a 5-point Likert format which grades the difficulty on that task experienced by the respondent. Domain-specific scores and a summary index score were calculated for each participant and scaled to a 100-point scale whereby higher scores represent higher disability. Established cutpoints for ICF disability were used with scores as follows: no problem (0-4); mild problem (5-24); moderate problem (25-49); severe problem (50-95) and extreme problem (95-100) (Maierhofer, Almazan-Isla, Alcalde-Cabero, & de Pedro-Cuesta, 2011; Virues-Ortega et al., 2011b). Potential demographic and health status correlates of disability were assessed concurrently with the WHO-DAS at the 2011 follow-up visit unless noted otherwise below.

Explanatory variables

Potential correlates of disability including health status and conditions, demographic and environmental factors were considered to the extent that they were available.

Health status and conditions

Height (cm) and weight (kg) were measured using a stadiometer and calibrated balance-beam scale, and used to calculate body mass index (BMI) in (kg/m2). Participants were categorized as obese (BMI ≥ 30 kg/m2) or non-obese (BMI < 30 kg/m2). Menopausal status was defined as surgical menopause (hysterectomy) vs. natural postmenopause or unable to determine due to exogenous hormone use. Two participants were still having menses at the 2011 follow-up visit and were excluded from analyses in which menopause status was a covariate.

We measured the prevalence of 10 health conditions including diabetes, hypertension, knee osteoarthritis (OA), peripheral neuropathy (PN), depression, liver problems, peripheral vascular disease (PVD), cancer, heart attack and stroke. For this investigation, health conditions were retained for statistical analysis if the prevalence was >10% and it was determined a priori that they could be associated with disability. Diabetes status was based on a self-report of a health care provider diagnosis of diabetes or current use of diabetes medications. Hypertension was defined as self-reported a doctor’s diagnosis of hypertension, use of anti-hypertensive medications, or measured systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg. Knee OA was defined as a Kellgren-Lawrence score ≥ 2 in either knee (Kellgren & Lawrence, 1963) based on radiographs obtained at the 2010 follow-up visit (if available) or 2009 follow-up visit. PN was defined as ≥ 4 on the self-reported Michigan Neuropathy Screening Instrument (MNSI) symptom questionnaire (Herman et al., 2012) or ≥ 20% failure rate on monofilament testing (Nang et al., 2009). Depressive symptomatology was defined as a score ≥16 on the Center for Epidemiologic Studies Depression Scale (Radloff, 1977). Liver problems, PVD, cancer, heart attack and stroke were self-reported.

Demographic and environmental factors

Age was calculated as date of visit minus date of birth. Race/ethnicity was self-reported at baseline as African American or Caucasian. Level of economic strain was coded as none versus some or substantial economic strain based on participant response to the question “How difficult is it to pay for the very basics such as food, medical care, and housing?”. Level of education at baseline (less than high school, high school, some college, college, or more than college) and marital status (never married, formerly married, or married) were also reported.

Statistical Analysis

Frequencies and percents of the categorical WHO-DAS domain and summary scores were calculated to estimate disability prevalence and corresponding 95% confidence intervals (CI). Means and standard deviations (SD) or frequencies and percents of demographic and health status variables were examined overall and by disability severity. The statistical significance of differences by disability category were evaluated using analysis of variance for continuous variables and chi-square tests for categorical variables. For analytical purposes, overall and domain-specific disability was dicotomized as none or mild disability (referent) verus moderate, severe or extreme disability. A multi-nomial model with disability as none vs. mild vs. moderate-extreme was considered but, given the very low prevalence of ‘no disability’ among women with peripheral neuropathy or depressive symptoms, it did not produce reliable estimates. Prevalence odds ratios (OR) were calculated using multivariable logistic regression models. All demographic and environmental factors and all health status variables with > 10% prevalence were considered for inclusion in the multivariable models. Final model selection was based upon model fit (evaluated using Akaike’s Information Criterion) and statistical significance of each variable. Potential interactions between the health conditions and demographic/environmental factors were tested and all were found to be non-significant.

RESULTS

Nearly 25% of women in this late middle-aged population reported moderate, severe, or extreme disability (Table 1). With the exception of the self-care domain, the prevalence of moderate, severe or extreme problems was approximately one in five for all domains, including understanding and communicating (19%), getting around (39%), getting along with people (19%), work related life activities (18%), and participation in society (30%).

Table 1. Prevalence of World Health Organization Disability Assessment Scale (WHO-DAS) Disability Summary and Domain-Specific Scores among 376 Michigan Study of Women’s Health Across the Nation Participants, 2011 Follow-up Visit.

Domains
Summary Score Understanding
&
Communicating
Getting Around Self-Care Getting Along
With People
Non-Work Life
Activities
Work Life
Activities
Participation in
Society
Percent
95% CI
Percent
95% CI
Percent
95% CI
Percent
95% CI
Percent
95% CI
Percent
95% CI
Percent
95% CI
Percent
95% CI
No Problem (Score 0-4) 32.98% (28.22,37.73) 43.88% (38.86, 48.90) 34.84% (30.02, 39.66) 76.86% (72.60, 81.12) 56.91% (51.90, 61.91) 29.86% (22.39, 37.33) 52.16% (45.73, 58.59) 31.65% (26.95, 36.35)
Mild Problem (Score 5-24) 42.82% (37.82, 47.82) 36.70% (31.82, 41.57) 26.33% (21.88, 30.78) 12.77% (9.40, 16.14) 23.94% (19.63, 28.25) 9.72% (4.88, 14.56) 30.17% (24.26, 36.08) 38.56% (33.67, 43.51)
Moderate Problem (Score 25-49) 19.15% (15.17, 23.13) 14.36% (10.82, 17.90) 19.41% (15.41, 23.41) 6.12% (3.70, 8.54) 13.03% (9.63, 16.43) 17.36% (11.17, 23.54) 9.05% (5.39, 12.74) 21.01% (16.89, 25.13)
Severe/Extreme Problem (Score 49-100) 5.05% (2.84, 7.26) 5.05% (2.84, 7.23) 19.41% (15.41, 23.41) 4.26% (2.22, 6.30) 6.12% (3.70, 8.54) 43.16% (35.07, 51.25) 8.62% (5.00, 12.23) 8.78% (3.92, 11.64)

The average age of this sample was 60.6 years (SD=2.8) (range 55.9-67.7 years). By design, 60% were African-American and 40% were Caucasian. Nearly half of women reported economic strain. The majority of women were obese (61%) and there was a high prevalence of health conditions including knee osteoarthritis (70%), and hypertension (61%). In the bivariate analyses (Table 2), economic strain, obesity, knee osteoarthritis, peripheral neuropathy and depressive symptoms were associated with global disability (P<0.001).

Table 2. Demographic and health characteristics among 376 Michigan Study of Women’s Health Across the Nation Participants, Overall and by WHO-DAS Disability Category.

Overall No Problem Mild Problem Moderate Problem Severe or Extreme Problem Test Statistic (DF)* P-value
N=376 N=124 N=161 N=72 N=19

Demographics

 Age, years (mean, SD) 60.6 (2.8) 60.9 (2.9) 60.5 (2.7) 60.7 (2.8) 59.8 (2.3) 1.73 (1) 0.19

Percent Percent Percent Percent Percent

 Race/ethnicity

  African-American 38.8 30.8 50.0 13.7 5.5 7.0 (3) 0.07

  Caucasian 61.2 34.4 38.3 22.6 4.8

 Economic Strain

  None 56.0 43.5 43.1 11.5 1.9 60.3 (6) <0.001

  Some 34.6 28.2 47.3 22.5 7.8

  Substantial 9.4 5.7 28.6 54.3 11.4

 Education

  High school or less 29.7 26.9 42.6 24.1 6.5 10.4 (6) 0.11

  Some college 45.6 34.9 39.2 19.9 6.0

  College or more 24.7 32.4 52.2 11.1 2.2

 Marital Status

  Single 17.0 33.3 33.3 25.4 7.9 8.8 (6) 0.19

  Married 46.2 30.8 49.4 16.9 2.9

  Formerly Married 36.8 35.0 39.4 19.0 6.6

Menopause Status

  Surgical Postmenopause 13.8 34.6 36.5 19.2 9.6 3.1 (3) 0.38

  Natural Postmenopause 86.2 32.7 43.8 19.1 4.3

Health Status

 Obesity (BMI≥30 kg/m2) 61.0 24.1 52.3 19.1 4.5 20.0 (3) <0.001

 Diabetes 30.1 24.8 44.3 25.7 5.3 7.0 (3) 0.07

 Knee osteoarthritis 70.1 26.0 48.4 21.1 4.5 19.0 (3) <0.001

 Peripheral neuropathy 21.3 2.5 42.5 41.3 13.8 69.8 (3) <0.001

 Depressive symptomatology 22.1 3.6 38.6 42.2 15.7 83.9 (3) <0.001

 Hypertension 61.1 30.4 41.3 22.2 6.1 5.6 (3) 0.14
*

Degrees of freedom (DF). Test statistics are from ANOVA global F-test for continuous variables (age) and from chi-square test for categorical variables (all others).

Table 3 reports the results from the multivariable logistic regression model with global disabiltiy as the dependent variable and including the health status/condition measures, race/ethnicity, and economic strain as independent variables. African-American race/ethnicity and economic strain were statistically signficantly associated with greater global disability. In terms of health conditions, only peripheral neuropathy and depressive symptomatology were statistically signficiantly associated with greater global disability. Peripheral neuropathy was associated with 4.6 times greater odds of moderate-severe global disability (OR=4.55, 95% CI 2.21, 9.38) and depressive symptomatology was associated with more than 6 times greater odds of disability (OR=6.24, 95% CI 3.16, 12.34), independent of the impact of demographic and other health status/conditions.

Table 3. Multivariable logistic regression of demographic and health status correlates of global disability among Michigan Study of Women’s Health Across the Nation Participants.

Odds Ratio (95% CI)
African American Race/Ethnicity 2.04 (1.01, 4.12)
Economic Strain 2.20 (1.16, 4.18)
Obesity (BMI≥30 kg/m2) 0.82 (0.39, 1.74)
Diabetes 0.90 (0.43, 1.74)
Knee osteoarthritis 1.36 (0.62, 3.00)
Peripheral neuropathy 4.55 (2.21, 9.38)
Depressive symptomatology 6.24 (3.16, 12.34)
Hypertension 1.83 (0.87, 3.83)

Table 4 includes the results of 5 separate sets of multivariable logistic regression domain-specific models; each set of models included one health status/condition measure as the main independent variable of interest and was adjusted for race/ethnicity, economic strain and obesity status. Peripheral neuropathy was associated with the getting around, getting along with people, life activities and participation in society domains. Depressive symtpoms were significantly associated with all disability domains. The magnitude of these associations ranged from 3 times greater odds of moderate-severe disability among those with depressive symptoms for getting around (95% CI 3.17, 95% CI 1.72, 2.85) to more than 7 times greater odds for self care (95% CI 7.05, 2.90, 17.11). While obesity, knee osteoarthritis, and hypertension were not associated with global disability, each of these measures were associated with domain 2 (getting around). Obese women had nearly 3 times greater odds of Domain 2 disability (OR=2.89, 95% CI 1.72, 4.86) as compared to non-obese women. In these domain-specific models, economic strain was associated with moderate-severe disability for all domains whereas race/ethnicity was only associated with the understanding and communicating, life activities and participation in society domains.

Table 4. Multivariable analysis of health status correlates of domain-specific disability among Michigan Study of Women’s Health Across the Nation Participants.*.

Domain 1: Understanding & Communicating Domain 2: Getting Around Domain 3: Self Care Domain 4: Getting Along With People Domain 5: Life Activities Domain 6: Participation in Society
Odds Ratio
(95% CI)
Odds Ratio
(95% CI)
Odds Ratio
(95% CI)
Odds Ratio
(95% CI)
Odds Ratio
(95% CI)
Odds Ratio
(95% CI)
Model 1: Diabetes 0.94 (0.49, 1.80) 1.29 (0.76, 2.18) 1.37 (0.57, 3.28) 1.15 (0.60, 2.20) 1.44 (0.79, 2.62) 1.10 (0.62, 1.97)
Model 2: Knee OA 1.36 (0.67, 2.76) 2.81 (1.51, 5.23) 1.23 (0.43, 3.52) 1.15 (0.56, 2.33) 1.48 (0.75, 2.95) 1.49 (0.78, 2.83)
Model 3: Peripheral neuropathy 1.58 (0.81, 3.09) 6.61 (3.42, 12.77) 2.29 (0.96, 5.45) 2.40 (1.25, 4.62) 4.66 (2.49, 8.70) 3.70 (2.01, 6.84)
Model 4: Depressive symptomatology 6.56 (3.36, 12.84) 3.17 (1.72, 2.85) 7.05 (2.90, 17.11) 4.75 (2.48, 9.11) 6.52 (3.44, 12.38) 6.09 (3.23, 11.51)
Model 5: Hypertension 1.21 (0.63, 2.30) 1.89 (1.10, 3.26) 1.89 (0.69, 5.16) 1.25 (0.64, 2.41) 2.05 (1.07, 3.94) 1.59 (0.88, 2.88)
*

All models are adjusted for race/ethnicity, economic strain and obesity status

CONCLUSIONS

Evidence suggests that the development of functional limitations begins during the mid-life (Adams & Marano, 1995; Tseng et al., 2012) and the prevalence of late mid-life disability has been reported to range from 20-30% (Murray et al., 2011; CDC, 2009; Sowers et al., 2006). These prevalences are similar to the estimate of global disability prevalence we report using the WHO-DAS questionnaire (25%). Traditional measures of disability including functional limitations and difficulties in activities of daily living may under-estimate disability which is related to one’s personal, social and environmental factors. Notably, our study found that the prevalence of disability for the mobility domain (‘getting around’) was nearly 40% and the prevalence of disability for the non-work life activity domain was in excess of 60%. These findings suggest that the burden of disability in the mid-aged population may far exceed traditional estimates and that mid-aged women may experience substantial difficulty with mobility.

A major strength of this study is our utilization of the WHO-DAS, which allowed for examination of not only global disability but also domain-specific measures. Compared to previously used models, the WHO-DAS provides a unifying framework and language to characterize disability in the U.S. and international settings, emphasizing participation and the interaction of an individual and his or her environment (Jette, 2009). Our data suggest that there is great value in assessing domain-specific disability because it provides a more in-depth examination of the nature of one’s disability, as evidenced by the drastic difference in disability prevalence across domains. Similar to what has been observed in an elderly Spanish cohorts (de Pedro-Cuesta et al., 2011; Virues-Ortega et al., 2011b), getting around and non-work life activities were the most common domains in which we observed disability among this mid-aged cohort. However, in contrast, the prevalence of disability in this population was lowest for the self-care domain whereas in elderly populations the participation in society and getting along with people domains were the least affected (de Pedro-Cuesta et al., 2011).

Furthermore, our examination of multiple domains allowed us to understand which types of health conditions were associated with different aspects of disability. In a middle-aged population like ours, where disability may be predominantly associated with acute and specific physiology, a focus on prevention and an enabling environment may be more useful than for very old frail individuals (Guralnik & Ferrucci, 2009). As the ICF framework conceptualizes that one’s functional status is due to not only health conditions but also the interactions between one’s contextual factors, this multi-domain aspect of the WHO-DAS allows us to consider different support needs for different domains – an important detail that may be missed by examining only global disability. In our study, only peripheral neuropathy and depression were associated with the global disability measure but knee osteoarthritis and hypertension were also associated with at least one of the domain-specific measures.

While obesity has been reported to be an important risk factor for disability (Peytremann-Bridevaux & Santos-Eggimann, 2008; Sirtoriet al., 2012), our findings support this association only in the domain associated with mobility (domain 2). While obesity may be more broadly associated with all aspects of disability due to the reported psychological symptoms of anxiety and depression among obese individuals (Van Hout, Van Oudheusden, & Van Heck, 2004), our data suggest that in this mid-aged population, obesity is associated with mobility limitations, which have been well documented among obese women (Vincent, Vincent, & Lamb, 2010). Our findings support work by Raggi et al. (2009, 2010) that mobility domains were the most relevant measures among the comprehensive ICF core set of indicators for obesity.

Economic strain was one of the strongest and most consistent correlates of both global and domain-specific disability in this study. Although the cross-sectional nature of our study precludes us from being able to determine if the economic strain contributed to disability onset or was a consequence of being disabled, work from other studies suggests that economic hardship is an important predictor of disability. Among mid-aged African American adults, childhood financial strain was associated with physical disability in adulthood (Szanton, Thorpse, & Whitfield, 2010). Further, income inadequacy predicted age at disability onset among an elderly cohort of British individuals with the age of disability onset being 7 years earlier among those with income inadequacy as compared to those with adequate income report (Matthews, Smith, Hancock, Jagger, &Spiers, 2005). Thus, women with economic disadvantage may be especially vulnerable to disability. The association of economic strain and disability persisted after adjustment for health status, thereby suggesting that the impact of economic hardship likely goes beyond the greater burden of comorbid conditions. Intervention strategies should target not only improvement of health status but also economic security issues in an effort to prevent or forestall the onset of disability in economically vulnerable populations.

Several studies have reported an association between depression and disability and previous work suggests that depression is more likely to be a consequence of being disabled (Ormel, Rijsdijk, Sullivan, van Sonderen, &Kempen, 2002; Chen et al., 2012; Barry, Soulos, Murphy, Kasl, & Gill, 2012) than vice versa. While our work confirmed the importance of the depression-disability association, our cross-sectional design precludes us from exploring the timing of this relationship.

Peripheral neuropathy is a well-documented as a risk factor for poor lower-extremity function, including slower gait, poorer balance, and falls (Richardson & Hurvitz, 1995; Resnicket al., 2002; Strotmeyer et al., 2008; Ylitalo, Herman, & Harlow, 2012), consistent with the strong association we observed between peripheral neuropathy and the mobility disability domain (domain 2). However, neuropathy was also associated with getting along with people, life activities, and participation in society. These findings are consistent with the few studies that have evaluated the effect of neuropathy on reduced quality of life in diabetes patients (Venkataraman et al., 2012; Currie et al., 2006). While peripheral neuropathy is predictive of depression and psychosocial distress (Vileikyte et al., 2005), we found a relationship between neuropathy and disability independent of depressive symptoms. We hypothesize that the association between neuropathy and psychosocial disability domains may be mediated by the mobility domain, since decreased physical functioning may cause decreased emotional and social function as well (van Schie, 2008). Peripheral neuropathy is under-appreciated as a cause of disability, particularly for mid-life women with and without diabetes, and deserves further research attention.

Limitations of our analysis included the cross-sectional nature of the design and consequent focus on prevalent disability. It has been well documented that disability is often a dynamic and heterogeneous process, including both acute and chronic episodes in individuals (Hardy, Dubin, Holfort, & Gill, 2005). Longitudinal studies are needed to be able to better describe the dynamic process of disability and to discern whether our observed associations of demographic and health status measures are predictive of disability onset or a consequence of being disabled. Our analysis was also limited to a relatively small sample of mid-aged women living in one geographic area of the United States; thus, our results may not be generalizable to other populations.

In conclusion, we report a relatively high prevalence of global and domain-specific disability among late middle-age women. Health conditions including knee osteoarthritis, peripheral neuropathy and hypertension were most strongly associated with the mobility domain (getting around, domain 2) whereas depressive symptoms and economic strain were more strongly associated with domains reflecting interactions of individuals with their environment (life activities, participation in society). Notably, obesity was not associated with the global disability and was only associated with the mobility domain. Future programs to prevent disability should include consideration of mental health and equity issues as important targets for intervention.

References

  1. Adams PF, Marano MA. Current estimates from the National Health Interview Survey, 1994. National Center for Health Statistics. Vital Health Statistics 10. 1995;193(Pt 1):1–260. [PubMed] [Google Scholar]
  2. Arterburn D, Westbrook EO, Ludman EJ, Operskalski B, Linde JA, Rohde P, Simon GE, et al. Relationship between obesity, depression, and disability in middle-aged women. Obesity Research and Clinical Practice. 2012;6:e197–206. doi: 10.1016/j.orcp.2012.02.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Barry LC, Soulos PR, Murphy TE, Kasl SV, Gill TM. Association between indicators of disability burden and subsequent depression among older persons. Journals of Gerontology, Series A:Biological Sciences and Medical Sciences. 2012;68:286–92. doi: 10.1093/gerona/gls179. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Centers for Disease Control and Prevention (CDC) Prevalence and most common causes of disability among adults—United States, 2005. Morbidity and Mortality Weekly Report. 2009;58:421–6. [PubMed] [Google Scholar]
  5. Chen CM, Mullan J, Su YY, Griffiths D, Kreis IA, Chiu HC. The longitudinal relationship between depressive symptoms and disability for older adults: a population-based study. Journals of Gerontology, Series A: Biological Sciences and Medical Sciences. 2012;67:1059–67. doi: 10.1093/gerona/gls074. [DOI] [PubMed] [Google Scholar]
  6. Currie CJ, Poole CD, Woehl A, Morgan CL, Cawley S, Rousculp MD, Peters JR, et al. The health-related utility and health-related quality of life of hospital-treated subjects with type 1 or type 2 diabetes with particular reference to differing severity of peripheral neuropathy. Diabetologia. 2006;49:2272–80. doi: 10.1007/s00125-006-0380-7. [DOI] [PubMed] [Google Scholar]
  7. de Pedro-Cuesta J, Alberquilla A, Virues-Ortega J, Carmona M, Alcalde-Cabero E, Bosca G, Monteagudo JL, et al. ICF disability measured by WHO-DAS II in three community diagnostic groups in Madrid, Spain. Gaceta Saintaria. 2011;25(Suppl 2):21–8. doi: 10.1016/j.gaceta.2011.08.005. [DOI] [PubMed] [Google Scholar]
  8. Garin O, Ayuso-Mateos JL, Almansa J. Validation of the World Health Organization Disability Assessment Schedule, WHODAS-2 in patients with chronic diseases. Health and Quality of Life Outcomes. 2010;8:51. doi: 10.1186/1477-7525-8-51. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Guralnik JM, Ferrucci L. The challenge of understanding the disablement process in older persons: commentary responding to Jette AM. Toward a common language of disablement. Journals of Gerontology, Series A: Biological Sciences and Medical Sciences. 2009;64:1169–71. doi: 10.1093/gerona/glp094. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Hardy SE, Dubin JA, Holfort TR, Gill TM. Transitions between states of disability and independence among older persons. American Journal of Epidemiology. 2005;161:575–84. doi: 10.1093/aje/kwi083. [DOI] [PubMed] [Google Scholar]
  11. Herman WH, Pop-Busui R, Braffett BH, Martin CL, Cleary PA, Albers JW, Feldman EL DCCT/EDIC Research Group. Use of the Michigan Neuropathy Screening Instrument as a Measure of Distal Symmetrical Peripheral Neuropathy in Type 1 Diabetes: Results from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications. Diabetic Medicine. 2012;29:937–44. doi: 10.1111/j.1464-5491.2012.03644.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Imai K, Gregg EW, Chen YJ, Zhang P, de Rekeneire N, Williamson DF. The association of BMI with functional status and self-rated health in US adults. Obesity. 2008;16:402–8. doi: 10.1038/oby.2007.70. [DOI] [PubMed] [Google Scholar]
  13. Jette AM. Toward a common language of disablement. Journals of Gerontology, Series A: Biological Sciences and Social Sciences. 2009;64A:1165–68. doi: 10.1093/gerona/glp093. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Kellgren JH, Lawrence JS. The epidemiology of chronic rheumatism: Atlas of standard radiographs of arthritis. II. Philadelphia: FA Davis; 1963. [Google Scholar]
  15. Maierhofer S, Almazan-Isla J, Alcalde-Cabero E, de Pedro-Cuesta J. Prevalence and features of ICF-disability in Spain as captured by the 2008 National Disability Survey. BMC Public Health. 2011;11:897. doi: 10.1186/1471-2458-11-897. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Matthews RJ, Smith LK, Hancock RM, Jagger C, Spiers NA. Socioeconomic factors associated with the onset of disability in older age: a longitudinal study of people aged 75 years and over. Social Science and Medicine. 2005;61:1567–75. doi: 10.1016/j.socscimed.2005.02.007. [DOI] [PubMed] [Google Scholar]
  17. Melzer D, Gardener E, Guralnik JM. Mobility disability in the middle-aged: cross-sectional associations in the English Longitudinal Study of Ageing. Age and Ageing. 2005;34:594–602. doi: 10.1093/ageing/afi188. [DOI] [PubMed] [Google Scholar]
  18. Murray ET, Hardy R, Strand BH, Cooper R, Guralnik JM, Kuh D. Gender and life course occupational social class differences in trajectories of functional limitations in midlife: findings from the 1946 British birth cohort. Journals of Gerontology, Series A: Biological Sciences and Medical Sciences. 2011;66:1350–9. doi: 10.1093/gerona/glr139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Nagi SZ. An epidemiology of disability among adults in the United States. Milbank Memorial Fund Quarterly: Health and Society. 1976;54:439–67. [PubMed] [Google Scholar]
  20. Nang EE, Khoo CM, Tai ES, Lim SC, Tavintharan S, Wong TY, Lee J, et al. Is there a clear threshold for fasting plasma glucose that differentiates between those with and without neuropathy and chronic kidney disease? American Journal of Epidemiology. 2009;169:1454–62. doi: 10.1093/aje/kwp076. [DOI] [PubMed] [Google Scholar]
  21. Nosek MA, Robinson-Whelen S, Hughes RB, Petersen NJ, Taylor HB, Bryne MM, Morgan R. Overweight and obesity in women with physical disabilities: associations with demographic disability characteristics and secondary conditions. Disability and Health Journal. 2009;1:89–98. doi: 10.1016/j.dhjo.2008.01.003. [DOI] [PubMed] [Google Scholar]
  22. Ormel J, Rijsdijk FV, Sullivan M, van Sonderen E, Kempen GI. Temporal and reciprocal relationship between IADL/ADL disability and depressive symptoms in late life. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences. 2002;57:P338–347. doi: 10.1093/geronb/57.4.p338. [DOI] [PubMed] [Google Scholar]
  23. Peytremann-Bridevaux I, Santos-Eggimann B. Health correlates of overweight and obesity in adults aged 50 years and older: results from the Survey of Health, Ageing and Retirement in Europe (SHARE) Swiss Medical Weekly. 2008;138:261–6. doi: 10.4414/smw.2008.12067. [DOI] [PubMed] [Google Scholar]
  24. Radloff LS. The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement. 1977;1:385–401. [Google Scholar]
  25. Raggi A, Sirtori A, Brunani A, Liuzzi A, Leonardi M. Use of the ICF to describe functioning and disability in obese patients. Disability and Rehabilitation. 2009;31(Supp1):S153–8. doi: 10.3109/09638280903317724. [DOI] [PubMed] [Google Scholar]
  26. Raggi A, Brunani A, Sirtori A, Liuzzi A, Berselli ME, Villa V, Leonardi M, et al. ICF-Obesity Group. Obesity-related disability: key factors identified by the International Classification of Functioning, Disability and Health (ICF) Disability and Rehabilitation. 2010;32:2028–34. doi: 10.3109/09638281003797372. [DOI] [PubMed] [Google Scholar]
  27. Resnick HE, Stansberry KB, Harris TB, Tirivedi M, Smith K, Morgan P, Vinik AI. Diabetes, peripheral neuropathy, and old age disability. Muscle Nerve. 2002;25:43–50. doi: 10.1002/mus.1217. [DOI] [PubMed] [Google Scholar]
  28. Richardson JK, Hurvitz EA. Peripheral neuropathy: a true risk factor for falls. Journals of Gerontology, Series A: Biological Sciences and Medical Sciences. 1995;50:M211–5. doi: 10.1093/gerona/50a.4.m211. [DOI] [PubMed] [Google Scholar]
  29. Sirtori A, Brunani A, Villa V, Berselli ME, Croci M, Leonardi M, Raggi A. Obesity is a marker of reduction in QoL and disability. Scientific World Journal. 2012;2012:167520. doi: 10.1100/2012/167520. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Sowers MF, Crawford SL, Sternfeld B, Morganstein D, Gold EB, Evans D, Kelsey J, et al. SWAN: A multicenter, multiethnic, community-based cohort study of women and the menopausal transition. In: Lobo RA, Kelsey J, Marcus R, editors. Menopause: Biology and Pathobiology. San Diego: Academic Press; 2000. pp. 175–188. [Google Scholar]
  31. Sowers M, Jannausch ML, Gross M, Karvonen-Gutierrez CA, Palmieri RM, Crutchfield M, Richards-McCullough K. Performance-based physical functioning in African-American and Caucasian women at midlife: considering body composition, quadriceps strength, and knee osteoarthritis. American Journal of Epidemiology. 2006;163:950–8. doi: 10.1093/aje/kwj109. [DOI] [PubMed] [Google Scholar]
  32. Strotmeyer ES, de Rekeneire N, Schwartz AV, Faulkner KA, Resnick HE, Goodpaster BH, Newman AB, et al. The relationship of reduced peripheral nerve function and diabetes with physical performance in older white and black adults: the Health, Aging, and Body Composition (Health ABC) study. Diabetes Care. 2008;31:1767–72. doi: 10.2337/dc08-0433. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Szanton SL, Thorpe RJ, Whitfield K. Life-course financial strain and health in African-Americans. Social Science and Medicine. 2010;71:259–65. doi: 10.1016/j.socscimed.2010.04.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Tseng LA, El Khoudary SR, Young EA, Farhat GN, Sowers M, Sutton-Tyrrell K, Newman AB. The association of menopause status with physical function: the Study of Women’s Health Across the Nation. Menopause. 2012;19:1186–92. doi: 10.1097/gme.0b013e3182565740. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Ustün TB, Chatterji S, Kostanjsek N, Rehm J, Kennedy C, Epping-Jordan J, Pull C WHO/NIH Joint Project. Developing the world health organization disability assessment schedule 2.0. Bulletin of the World Health Organization. 2010;88:815–23. doi: 10.2471/BLT.09.067231. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Van Hout GCM, Van Oudheusden I, Van Heck GL. Psychological profile of the morbidly obese. Obesity Surgery. 2004;14:579–88. doi: 10.1381/096089204323093336. [DOI] [PubMed] [Google Scholar]
  37. van Schie CH. Neuropathy: mobility and quality of life. Diabetes Metabolism Research and Reviews. 2008;24(Supp 1):S45–51. doi: 10.1002/dmrr.856. [DOI] [PubMed] [Google Scholar]
  38. Venkataraman K, Wee HL, Leow MK, Tai ES, Lee J, Lim SC, Thumboo J, et al. Associations between complications and Health Related Quality of Life in individuals with diabetes. Clinical Endocrinology. 2012 doi: 10.1111/j.1365-2265.2012.04480.x. In Press. [DOI] [PubMed] [Google Scholar]
  39. Verbrugge LM, Jette AM. The disablement process. Social Science and Medicine. 1994;38:1–14. doi: 10.1016/0277-9536(94)90294-1. [DOI] [PubMed] [Google Scholar]
  40. Vileikyte L, Leventhal H, Gonzalez JS, Peyrot M, Rubin RR, Ulbrecht JS, Boulton AJ, et al. Diabetic peripheral neuropathy and depressive symptoms: the association revisited. Diabetes Care. 2005;28:2378–83. doi: 10.2337/diacare.28.10.2378. [DOI] [PubMed] [Google Scholar]
  41. Vincent KH, Vincent KR, Lamb KM. Obesity and mobility disability in the older adult. Obesity Reviews. 2010;11:568–79. doi: 10.1111/j.1467-789X.2009.00703.x. [DOI] [PubMed] [Google Scholar]
  42. Virues-Ortega J, de Pedro-Cuesta J, del Barrio JL, Almazan-Isla J, Bergareche A, Bermejo-Parajea F, et al. Spanish Epidemiological Study Group on Aging. Medical, environmental and personal factors of disability in the elderly in Spain: a screening survey based on the International Classification of Functioning. Gaceta Saintaria. 2011a;25(Suppl 2):29–38. doi: 10.1016/j.gaceta.2011.07.021. [DOI] [PubMed] [Google Scholar]
  43. Virués-Ortega J, de Pedro-Cuesta J, Seijo-Martínez M, Saz P, Sánchez-Sánchez F, Rojo-Pérez F, del Barrio JL, et al. Prevalence of disability in a composite >75 year-old population in Spain: A screening survey based on the International Classification of Functioning. BMC Public Health. 2011b;11:176. doi: 10.1186/1471-2458-11-176. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Wolinsky FD, Miller TR, Malmstrom TK, Miller JP, Schootman M, Andresen EM, Miller DK. Four-year lower extremity disability trajectories among African American men and women. Journals of Gerontology, Series A: Biological Sciences and Medical Sciences. 2007;62:525–30. doi: 10.1093/gerona/62.5.525. [DOI] [PubMed] [Google Scholar]
  45. Ylitalo KR, Herman WH, Harlow SD. Performance-based physical functioning and peripheral neuropathy in a population-based cohort of mid-life women. American Journal of Epidemiology. n.d doi: 10.1093/aje/kws327. In press. [DOI] [PMC free article] [PubMed] [Google Scholar]

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