Measuring the Impact of Diabetes on Life Expectancy and Disability-Free Life Expectancy Among Older Adults in Mexico

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1 Andrade, F.C.D. (2009). Measuring the impact of diabetes on life expectancy and disability-free life expectancy among older adults in mexico. Journal of Gerontology: Social Sciences, /geronb/gbp119 Measuring the Impact of Diabetes on Life Expectancy and Disability-Free Life Expectancy Among Older Adults in Mexico Flávia C. D. Andrade Department of Kinesiology and Community Health, University of Illinois at Urbana Champaign. Objectives. The aim of the present study is to investigate differences in total life expectancy (TLE), disability-free life expectancy (DFLE), disabled life expectancy (DLE), and personal care assistance between individuals with and without diabetes in Mexico. Methods. The sample was drawn from the nationally representative Mexican Health and Aging Study. Disability was assessed through a basic Activities of Daily Living (ADL) measure, the Instrumental Activities of Daily Living (IADL) scale, and the Nagi physical performance measure. The Interpolation of Markov Chains method was used to estimate the impact of diabetes on TLE and DFLE. Results. Results indicate that diabetes reduces TLE at ages 50 and 80 by about 10 and 4 years, respectively. Diabetes is also associated with fewer years in good health. DFLE (based on ADL measures) at age 50 is 20.8 years (95% confidence interval [CI]: ) for those with diabetes, compared with 29.9 years (95% CI: ) for those without diabetes. Regardless of diabetes status, Mexican women live longer but face a higher disability burden than men. Conclusion. A mong older adults in Mexico, diabetes is associated with shorter TLE and DFLE. The negative effect of diabetes on the number of years lived, particularly in good health, creates significant economic, social, and individual costs for elderly Mexicans. Key Words: Aging Diabetes Disability Life expectancy Mexico. I N Mexico, life expectancy at birth increased from 51 years in 1950 to nearly 73 years in 2000; further increases are expected in the coming decades ( Centro Latinoamericano y Caribeño de Demografía [CELADE], 2004 ). Moreover, the elderly population is growing faster than younger age groups; consequently, the percentage of individuals aged 65 years and older is expected to increase from 5.2% currently to 9.3% in 2025 (CELADE). A primary concern is whether this increase in life expectancy is accompanied by better health for the large aging population. In addition to this demographic transition, an epidemiological transition is in progress ( Stevens et al., 2008 ). There is already solid evidence that the incidence of diabetes is rising, and further increases are expected in the upcoming decades due to a rise in the prevalence of obesity ( Rull et al., 2005 ). Of the population aged 60 years and older, 17% have diabetes ( Palloni, Pinto-Aguirre, & Pelaez, 2002 ). Ageadjusted diabetes mortality rates increased 47% between 1980 and 2000 ( Barquera, Tovar-Guzmán, Campos-Nonato, González-Villalpando, & Rivera-Dommarco, 2003 ); since the year 2000, diabetes has been the leading cause of death among women and the second leading cause of death among men (Rull et al., 2005). The average age of the Mexican population is increasing rapidly; because diabetes prevalence rises with age, the impact of diabetes on the disability rate is expected to increase as well. As a consequence, the economic costs associated with the disease (most of which are indirect costs arising from permanent or temporary disability and death) are expected to increase even further ( Arredondo & Zuniga, 2004 ). A large body of literature shows that diabetes and associated comorbidities cardiovascular disease, stroke, vision impairment, neuropathy, nephropathy, and peripheral vascular disease are strongly correlated with physical limitations and functional disability ( Graham et al., 2007 ; Otiniano, Du, Ottenbacher, & Markides, 2003 ). However, very few studies estimate the impact of diabetes on total life expectancy (TLE) and disability-free life expectancy (DFLE) and most of those that do use data from developed countries ( Franco, Steyerberg, Hu, Mackenbach, & Nusselder, 2007 ; Jagger, Goyder, Clarke, Brouard, & Arthur, 2003 ; Jagger et al., 2007 ; Laditka & Laditka, 2006 ). A small number of recent papers use data from the Hispanic Established Populations for Epidemiologic Study of the Elderly to study the effects of diabetes among Mexicans in the United States; their results show that diabetes greatly reduces physical functioning and quality of life among this population (Graham et al.; Otiniano et al.). Very few studies focus on health expectancies in Latin America and the Caribbean ( Alves, Leite Ida, & Machado, 2008 ; Camargos, Machado, & Rodrigues, 2008 ; Parahyba, Stevens, Henley, Lang, & Melzer, 2009 ; Reyes-Beaman The Author Published by Oxford University Press on behalf of The Gerontological Society of America. 1 All rights reserved. For permissions, please journals.permissions@oxfordjournals.org. Received August 18, 2009 ; Accepted August 25, 2009 Decision Editor: Kenneth F. Ferraro, PhD

2 2 ANDRADE et al., 2005 ; Seuc, Domínguez, & Díaz, 2003 ). The availability of data, and in particular longitudinal data pertaining to functional disability, on Latin America and the Caribbean is relatively recent ( Camargos et al., 2008 ); therefore, most studies use cross-sectional data and the Sullivan method to estimate healthy life expectancies. Based on data from the Mexican Institute of Social Security (IMSS), Reyes-Beaman and colleagues (2005) find that among older Mexicans, most of the life expectancy beyond age 60 years does not include any limitation of the basic activities of daily living, but higher body mass index and chronic diseases are positively associated with limitations. An even more limited number of studies have focused on the impact of diabetes on measures of health expectancy in Latin America and the Caribbean. There is evidence that the impact of diabetes on disability-adjusted life expectancy increased between 1990 and 2003 in Cuba ( Dominguez et al., 2006 ). Previous studies show that diabetes and associated risk factors are related to decreased physical functioning and quality of life among Mexicans. Recently, Stevens and colleagues (2008) ranked diabetes as the fourth leading cause of disease burden in Mexico. Though these studies are a good start, given the paucity of research on the effects of diabetes on TLE and DFLE on residents of developing countries, specifically in Latin America and the Caribbean, there is a need for more research on this topic. This paper expands the current literature by using nationally representative panel data from Mexico to provide estimates of TLE, DFLE, and disabled life expectancy (DLE) for individuals with and without diabetes. I use three distinct measures, Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), and Nagi functional limitations, to assess quality of life and functional limitations. The first two measures, ADL and IADL, incorporate the difficulties individuals face in basic and instrumental life activities, whereas Nagi gauges physical performance. These measures address aspects of functioning ability that impact the quality of life and well-being of individuals in three distinct ways. The use of these measures provides an opportunity to address the extent to which diabetes affects different aspects of individuals lives from moderate difficulties with physical activities (such as lifting or carrying heavy objects) to more severe and limiting conditions (such as the inability to eat independently). Because the duration of disability has an impact on the demand for personal care, I also analyze differences in the number of years that individuals with and without diabetes will require assistance to perform ADL and IADL. Finally, given the expected gender differences in TLE and DFLE, estimates will be disaggregated by sex. Methods Data The Mexican Health and Aging Study (MHAS) is a prospective two-wave panel study of a nationally representative cohort of Mexicans born prior to 1951 (50 years and older at the time of the baseline interview). Surviving spouses, regardless of their age, were also interviewed. Baseline interviews were conducted in 2001; the second wave of interviews was completed in Detailed information on the MHAS is presented elsewhere ( Palloni et al., 2002 ). In the first wave, a total of 15,144 complete interviews were obtained (a response rate of 94.2% at the household level). Of the initial respondents, 1,718 were less than 50 years old and were excluded from the analysis. Another 404 individuals who did not report diabetic status in the baseline interview were also excluded. This leaves 13,022 respondents in the correct age range who provided complete information on age, sex, and diabetic status. There were no age differences between those with complete information and those with missing information on diabetic status, but more men lacked this information than women. Data were collected on 12,273 of the original respondents in the second wave; 11,755 were alive, whereas 518 had died between waves. Data on those who died between waves was obtained from next-of-kin questionnaires. For the analysis of the ADL limitations, the final sample was restricted to 11,929 individuals with complete information on age, sex, and diabetic status in the first wave and ADL information in at least one wave. For analysis of IADL, 11,944 respondents were included; for Nagi limitations, 11,935 respondents were analyzed. Those with missing data on disability and mobility measures in the first wave were older ( p <.0001) and more likely to be men ( p =.0001). However, there were no differences by diabetic status. Statistical Methods Estimates of DFLE and DLE were obtained using the multistate life table method. Usually, four transitions are measured in multistate models: incidence (disability free to disabled), recovery (disabled to disability free), and two types of mortality (disability free to dead or disabled to dead) ( Laditka & Hayward, 2003 ). There are also two retention statuses, as respondents declare being disability free or disabled in both waves. I used the 0.98g version of the IMaCh (Interpolative Markov Chain) software developed by Brouard and Lièvre (2006) and cross-longitudinal data from MHAS to compute transition probabilities. Sample weights are used in the analysis. IMaCh generates estimates of total and statespecific life expectancies and their standard errors, based on the methodology introduced by Laditka and Wolf ( Lièvre, Brouard, & Heathcote, 2003 ). The embedded Markov chain introduced by Laditka and Wolf (1998) and incorporated in the IMaCh software applies the multistate life table model to shorter transition periods, which are embedded within the longer interval between surveys. For the current analysis, monthly transitions were computed.

3 THE IMPACT OF DIABETES ON LIFE EXPECTANCY 3 Measures Diagnosed diabetes was measured by self-report. Respondents were considered to have diabetes if they had previously been diagnosed as diabetic by a physician. Those who reported having diabetes in the first wave were assumed to have the condition in the second wave. In the second wave, individuals were asked whether a doctor had diagnosed them with diabetes in the last two years. Disability status was ascertained using three measures: ADL, IADL, and Nagi functional limitations ( Nagi, 1976 ). Individuals with ADL limitations face difficulties performing daily activities related to functional mobility and self-care. Six activities were included in this measure: dressing, bathing, eating, getting in and out of a bed, toileting, and moving across a room. The ADL questions (except dressing) were asked only of respondents with Nagi limitations. Those who did not report Nagi limitations were assumed not to have ADL limitations. The IADL measure asked about the respondent s ability to prepare a hot meal, manage money, shop, and take medication. Individuals with IADL limitations are not as severely affected as those with ADL limitations but nevertheless face difficulties that may limit their ability to live independently within a community. The Nagi physical performance measure included lifting or carrying objects weighing 5 kg or more; lifting a coin; pulling or pushing a large object, such as a living room chair; stooping, kneeling, or crouching; and reaching or extending arms above shoulder level. Each of the three disability measures was converted to binary form, in which respondents scored 0 if they did not indicate any limitations, and 1 if they reported having difficulty performing at least one activity in the scale. Finally, two additional measures captured the need for help with basic life activities. For both ADL and IADL limitations, respondents were asked whether a spouse or other person assisted them. This information was converted into two binary measures; for both ADL and IADL, respondents scored 0 if they indicated no need for assistance and 1 if they reported requiring assistance with at least one activity. MHAS does not provide similar information on Nagi limitations. Results The results illustrate that disability rates are higher for older respondents, women, and those with diabetes. Table 1 presents the prevalence rates of ADL, IADL, and Nagi limitations by age group, sex, and diabetic status. Weighted estimates indicate that in 2001, 15.2% of Mexicans aged 50 years and older had been diagnosed with diabetes. The prevalence was higher among women (17.2%) than among men (12.9%). These individuals face a higher burden of disability, particularly when measured by ADL and IADL limitations. The prevalence rate of ADL limitations among respondents with diabetes is 15.2%, compared with 8.3% among individuals without diabetes. The prevalence of IADL limitations is almost twice as high for individuals with diabetes compared with those without diabetes. The rate of Nagi limitations is 43.8% for those without diabetes and 56.5% for those with diabetes. Older respondents also face a higher likelihood of disability. The rate of ADL disability is 5.9% among individuals aged years and rises steeply with age, reaching a high of 27.2% among those aged 80 years and older. IADL and Nagi limitations follow a similar pattern. Women report higher levels of disability than men. For instance, 10.7% of women aged 50 years and older have difficulty performing Table 1. Prevalence of ADL, IADL, and Nagi Limitations by Sex and Age Groups, MHAS 2001 (weighted estimates) Men Women Total ADL IADL Nagi ADL IADL Nagi ADL IADL Nagi (years) and older Total (years) and older Total Total (years) and older Total Note : ADL = Activities of Daily Living; IADL = Instrumental Activities of Daily Living; MHAS = Mexican Health and Aging Study.

4 4 ANDRADE at least one ADL activity, compared with 7.7% of their male counterparts. The prevalence of IADL limitations is approximately twice as high for women as for men. Nagi limitations affect more than half of the women in the sample, compared with 36.3% of the men. Multistate Life Table Results: DFLE and DLE by Diabetic Status and Age Multistate life table results indicate that diabetes reduces all three aspects of life expectancy. For those with diabetes, TLE at age 50 years is decreased by about 10 years and DFLE by about 9 years (see Table 2 ). Length of life with limitations (DLE) is also shorter for those with diabetes. In the following paragraphs, I present results describing the relationship between diabetes and DFLE (and how this relationship changes with age) using the three measures described earlier (ADL, IADL, and Nagi limitations). First, I examine the relationship between diabetes and DFLE using ADL limitations. At age 50, individuals with and without diabetes can expect to live 21 and 29.9 years, respectively, without ADL limitations. At age 80, those without diabetes are expected to live about 8 years without Table 2. TLE, DFLE, and DLE by Age and Diabetes Status, MHAS Age ADL (n = 11,929) TLE 33.1 (0.584) 24.4 (0.555) 16.6 (0.524) 10.3 (0.481) DFLE 29.9 (0.534) 21.4 (0.510) 14.0 (0.487) 8.2 (0.448) DLE 3.3 (0.181) 3.1 (0.184) 2.7 (0.186) 2.1 (0.185) TLE 23.1 (0.901) 16.0 (0.718) 10.2 (0.596) 6.0 (0.480) DFLE 20.8 (0.792) 13.8 (0.620) 8.3 (0.497) 4.4 (0.382) DLE 2.3 (0.255) 2.2 (0.241) 1.9 (0.234) 1.5 (0.231) IADL (n = 11,944) TLE 32.7 (0.553) 24.0 (0.515) 16.2 (0.478) 9.8 (0.436) DFLE 29.2 (0.468) 20.6 (0.431) 13.0 (0.395) 7.0 (0.348) DLE 3.5 (0.198) 3.4 (0.201) 3.2 (0.207) 2.8 (0.217) TLE 23.2 (0.897) 16.2 (0.704) 10.3 (0.595) 6.0 (0.501) DFLE 20.7 (0.767) 13.7 (0.582) 8.0 (0.457) 3.9 (0.330) DLE 2.5 (0.279) 2.5 (0.276) 2.4 (0.285) 2.1 (0.304) Nagi (n = 11,935) TLE 33.0 (0.547) 24.1 (0.511) 16.2 (0.482) 9.8 (0.451) DFLE 18.9 (0.312) 12.0 (0.280) 6.7 (0.246) 3.2 (0.189) DLE 14.1 (0.398) 12.1 (0.383) 9.5 (0.371) 6.6 (0.358) TLE 23.3 (0.918) 16.3 (0.704) 10.4 (0.593) 5.9 (0.473) DFLE 11.3 (0.526) 6.4 (0.352) 3.1 (0.227) 1.3 (0.130) DLE 12.1 (0.702) 9.9 (0.566) 7.2 (0.487) 4.6 (0.409) Note : Author s calculations using MHAS 2001 and Standard errors in parentheses. MHAS = Mexican Health and Aging Study; ADL = Activities of Daily Living; TLE = total life expectancy; DFLE = disability-free life expectancy; DLE = disabled life expectancy; IADL = Instrumental Activities of Daily Living. any ADL limitation almost twice as long as their counterparts with diabetes. Notably, for younger respondents, the proportion of remaining years expected to be lived with some limitation is about 10% for those both with and without diabetes. However, at age 80, this pattern shifts and the proportion of remaining life with disability is higher among those with diabetes than among those without 25% and 20.4%, respectively ( Table 2 ). Results based on IADL limitations follow a similar pattern. At age 50, individuals with and without diabetes can expect to live about 21 and 29 years, respectively, without IADL limitations. As with ADL limitations, the proportions are comparable; for individuals both with and without diabetes, about 11% of their remaining lives will be lived with at least one IADL limitation. At age 80, the percentage of years with an IADL limitation is greater for those with diabetes: 28.6% of remaining life is expected to be lived with IADL limitations compared with 35% among those with diabetes ( Table 2 ). Given the overall higher prevalence of Nagi limitations, DFLE based on this measure is considerably lower than when measured by ADL and IADL measures ( Table 2 ). At age 50, DFLE based on Nagi limitations was about 18.9 years for those without diabetes but only 11.3 years for those with diabetes. Unlike results using the previous two measures, at age 50, the proportion of remaining years with Nagi limitations was higher among those with diabetes than among those without diabetes: 42.7% and 51.9%, respectively. This trend continues at age 80, with DFLE as measured by Nagi limitations representing only 22% of the remaining lives of those with diabetes but 32.7% of those without diabetes (Table 2 ). DFLE and DLE by Diabetic Status and Sex Given previously documented differences in TLE and DFLE between men and women ( Camargos, Machado, & Rodrigues, 2007 ; Laditka & Laditka, 2002 ; Reyes-Beaman et al., 2005 ), it is worthwhile to disaggregate these results by sex. Differences in TLE between those with and without diabetes are larger among men than among women. For example, for men and women at age 50, diabetes reduces TLE by 12 and 8.5 years, respectively (based on ADL sample). At age 80, the reduction is 4.9 years for men and 3.6 years for women. A similar pattern holds for DFLE: Significant reductions were observed for both men and women with diabetes but were larger among men than among women. These results indicate that diabetes has a stronger negative effect on the TLE and DFLE of men than of women in Mexico. Earlier work has shown that compared with men, women experience limitations for more years and for a greater proportion of their remaining lives. Results in Table 3 are consistent with these findings. DLE at age 50, as measured by the ADL scale, is 4.4 years (12.7% of remaining life) for

5 THE IMPACT OF DIABETES ON LIFE EXPECTANCY 5 Table 3. TLE, DFLE, and DLE by Sex and Diabetic Status, MHAS, Age 50 Age 60 Age 70 Age 80 Men Women Men Women Men Women Men Women ADL (n = 11,929) TLE 31.6 (0.766) 34.7 (0.759) 23.3 (0.704) 25.7 (0.727) 15.9 (0.646) 17.5 (0.683) 10.0 (0.563) 10.7 (0.614) DFLE 29.3 (0.712) 30.3 (0.672) 21.1 (0.650) 21.6 (0.645) 14.0 (0.594) 13.9 (0.605) 8.4 (0.519) 7.9 (0.533) DLE 2.3 (0.186) 4.4 (0.288) 2.2 (0.185) 4.1 (0.287) 2.0 (0.182) 3.6 (0.283) 1.6 (0.176) 2.8 (0.274) TLE 19.6 (1.159) 26.2 (1.110) 13.5 (0.832) 18.6 (0.949) 8.6 (0.625) 12.1 (0.798) 5.1 (0.478) 7.1 (0.629) DFLE 18.3 (1.051) 22.8 (0.942) 12.2 (0.742) 15.4 (0.788) 7.4 (0.547) 9.3 (0.635) 4.1 (0.412) 5.0 (0.468) DLE 1.3 (0.191) 3.4 (0.380) 1.3 (0.179) 3.2 (0.367) 1.2 (0.173) 2.8 (0.354) 1.0 (0.174) 2.2 (0.337) IADL (n = 11,944) TLE 30.8 (0.739) 34.5 (0.729) 22.6 (0.659) 25.3 (0.701) 15.3 (0.594) 17.0 (0.657) 9.3 (0.508) 10.1 (0.592) DFLE 28.5 (0.658) 29.6 (0.576) 20.4 (0.576) 20.6 (0.544) 13.2 (0.508) 12.7 (0.495) 7.4 (0.417) 6.5 (0.412) DLE 2.3 (0.194) 4.9 (0.327) 2.3 (0.198) 4.7 (0.328) 2.2 (0.203) 4.3 (0.329) 1.9 (0.209) 3.6 (0.331) TLE 19.1 (1.160) 26.7 (1.086) 13.2 (0.819) 18.9 (0.947) 8.5 (0.605) 12.1 (0.830) 5.1 (0.452) 7.0 (0.698) DFLE 17.9 (1.050) 22.8 (0.866) 12.0 (0.721) 15.1 (0.722) 7.2 (0.514) 8.7 (0.577) 3.8 (0.359) 4.1 (0.403) DLE 1.2 (0.185) 3.9 (0.441) 1.3 (0.185) 3.8 (0.441) 1.3 (0.193) 3.5 (0.446) 1.2 (0.210) 2.9 (0.449) Nagi (n = 11,935) TLE 31.2 (0.690) 35.1 (0.817) 22.6 (0.610) 26.0 (0.800) 14.9 (0.540) 17.8 (0.767) 8.8 (0.459) 11.1 (0.701) DFLE 20.6 (0.449) 17.2 (0.375) 13.3 (0.375) 10.6 (0.330) 7.5 (0.305) 5.7 (0.271) 3.6 (0.221) 2.6 (0.191) DLE 10.6 (0.426) 17.9 (0.669) 9.3 (0.397) 15.4 (0.656) 7.5 (0.368) 12.2 (0.639) 5.2 (0.333) 8.5 (0.601) TLE 19.9 (1.294) 26.1 (1.103) 13.8 (0.782) 18.5 (0.914) 8.7 (0.585) 11.9 (0.772) 4.9 (0.438) 7.0 (0.624) DFLE 11.9 (0.769) 10.7 (0.555) 7.0 (0.435) 5.9 (0.373) 3.5 (0.271) 2.8 (0.227) 1.5 (0.156) 1.1 (0.122) DLE 8.0 (0.711) 15.4 (0.646) 6.8 (0.519) 12.6 (0.763) 5.2 (0.431) 9.1 (0.666) 3.4 (0.355) 5.9 (0.560) Note : Author s calculations using MHAS 2001 and Standard errors in parentheses. MHAS = Mexican Health and Aging Study; ADL = Activities of Daily Living; TLE = total life expectancy; DFLE = disability-free life expectancy; DLE = disabled life expectancy; IADL = Instrumental Activities of Daily Living. women without diabetes and 2.3 years (7.3% of remaining life) for men without diabetes. In comparison, among those with diabetes at age 50, women are expected to live 3.4 years (12.8% of remaining life) with at least one ADL limitation; their male counterparts will spend only 1.3 years (6.7% of remaining life) in the disabled status. For both men and women, diabetes reduces DLE at age 50 by 1 year. Results indicate a similar pattern at older ages women can expect to live more years, and a greater proportion of remaining years, with ADL limitations compared with men, regardless of diabetes status. This pattern is repeated again in results based on IADL and Nagi limitations. Examining the relationship among diabetes, sex, and DFLE adds a further component to the understanding of the diabetes impact. Diabetes greatly reduces DFLE among men. Results show that at age 50, men with and without diabetes are expected to live, on average, 18.3 and 29.3 years, respectively, without any ADL problems. DFLE decreases considerably with age. By age 80, DFLE among those without diabetes declines to 8.4 years, in contrast to 4.1 years among those with diabetes. Results are similar if IADL is used instead of ADL. Nagi limitations are much more prevalent than ADL and IADL limitations; however, the general trends are similar. For women aged 50 years, those with and without diabetes are expected to live, on average, 22.8 and 30.3 years, respectively, without any ADL limitations. At age 80, women without diabetes are expected to live an additional 7.9 years without any ADL limitations, whereas their counterparts with diabetes will experience only 5 more years without disability. Therefore, at both ages 50 and 80 years, diabetes is related to a greater decrease in DFLE for men than for women. Results based on IADL limitations are similar using ADL. By age 50, women without and with diabetes are expected to live, on average, 17.2 and 10.7 years, respectively, without any Nagi limitations. At age 80, DFLE measured by Nagi reaches 2.6 and 1.1 among women without and with diabetes. Assistance With Daily Activities The results outlined in the previous sections emphasize that diabetes imposes a large burden on individuals by reducing TLE and DFLE. A large percentage of older adults, and an even greater proportion of those with diabetes, face difficulties performing activities related to self-care and independent living. As a result, these individuals may require personal assistance in order to perform daily activities. Results indicate that at age 50, respondents without diabetes will require 1.7 years of help to perform ADL and 3.2 years of help to perform IADL, compared with 1.3 and 2.5 years for those with diabetes. Although the absolute number

6 6 ANDRADE of years requiring assistance is lower, individuals with diabetes will require assistance to perform ADL and IADL activities for a greater proportion of remaining life, compared with those without diabetes (Table 4 ). As in the previous sections, it is helpful to disaggregate the results by sex. Results shown in Table 5 emphasize that women will require more years of personal assistance than men, regardless of diabetes status. For instance, at age 50, women and men without diabetes are expected to require, on average, 2.2 and 1.2 years, respectively, of personal care assistance for ADL. In comparison, the need for assistance at age 50 among women and men with diabetes is 1.9 and 0.7 years, respectively. For both men and women, as age increases, the average number of years one can expect to live without personal care assistance decreases. The average number of years in which men and women require help performing IADL activities is higher than for ADL activities; however, the results follow the same general pattern. Discussion There is a growing interest in the determination of health expectancies in Latin America and the Caribbean ( Alves et al., 2008 ; Camargos et al., 2008 ; Reyes-Beaman et al., 2005 ; Seuc et al., 2003 ). Although there are many studies that examine the impact of diabetes on TLE and DFLE among older adults in developed countries, relatively few studies focus on Latin America and the Caribbean. The few studies that have been done in this area show that diabetes is associated with an increase in disability and physical limitations and shorter healthy life expectancy in Latin America ( Dominguez et al., 2006 ; Seuc et al.; Stevens et al., 2008 ) and among Mexicans residing in the United States ( Graham et al., 2007 ; Otiniano et al., 2003 ). However, most of these studies use cross-sectional data and Sullivan method to estimate healthy life expectancies. The Sullivan method provides estimates of health expectancy based on few data requirements age-specific prevalence of the health state (usually obtained in cross-sectional surveys) and age-specific mortality from a life table. This paper builds on and expands the current literature by using a multistate life table model, which requires longitudinal data, to estimate the impact of diabetes on TLE, DFLE, and the duration of personal care assistance in Mexico. The main advantage of this method is that it explicitly takes into account incidence and recovery, which is a more realistic approach than the Sullivan method. In addition, this study uses nationally representative data and three alternative measures of disability in order to address the various levels of difficulty individuals face in daily life. Estimates of dependent and independent life expectancy demonstrate the extent to which individuals will require personal care support in their daily lives. These estimates are particularly important for assessing the future need for personal care assistance for the aging Mexican population. The results support previous findings in the literature which show that diabetes is related to a loss of autonomy and reduces TLE and DFLE ( Belanger, Martel, Berthelot, & Table 4. TLE, Independent Life Expectancy, and Dependent Life Expectancy by Diabetic Status Based on Measures of Assistance With Daily Activities, MHAS ADL assistance (n = 11,929) Life expectancy 32.9 (0.582) 24.2 (0.553) 16.4 (0.525) 10.2(0.485) Without help 31.2 (0.556) 22.6 (0.528) 14.9 (0.505) 8.9 (0.471) With help 1.7 (0.126) 1.6 (0.130) 1.5 (0.135) 1.3 (0.142) % of years requiring assistance Life expectancy 23.4 (0.873) 16.1 (0.703) 10.1 (0.569) 5.8 (0.444) Without help 22.1 (0.813) 14.8 (0.651) 8.9 (0.520) 4.8 (0.398) With help 1.3 (0.178) 1.3 (0.175) 1.2 (0.176) 1.0 (0.184) % of years requiring assistance IADL assistance ( n = 11,944) Life expectancy 32.5 (0.550) 23.8 (0.512) 16.0 (0.475) 9.7 (0.433) Without help 29.3 (0.470) 20.7 (0.432) 13.1 (0.396) 7.1 (0.349) With help 3.2 (0.187) 3.1 (0.191) 2.9 (0.197) 2.6 (0.208) % of years requiring assistance Life expectancy 23.2 (0.872) 16.0 (0.689) 10.1 (0.576) 5.8 (0.475) Without help 20.7 (0.754) 13.6 (0.579) 7.8 (0.450) 3.8 (0.319) With help 2.5 (0.276) 2.4 (0.272) 2.3 (0.280) 2.0 (0.299) % of years requiring assistance Note : Author s calculations using MHAS 2001 and Standard errors in parentheses. MHAS = Mexican Health and Aging Study; ADL = Activities of Daily Living; IADL = Instrumental Activities of Daily Living. Age

7 THE IMPACT OF DIABETES ON LIFE EXPECTANCY 7 Table 5. TLE, Independent Life Expectancy, and Dependent Life Expectancy by Diabetic Status Based on Measures of Assistance With Daily Activities, MHAS Age 50 Age 60 Age 70 Age 80 Men Women Men Women Men Women Men Women ADL assistance (n = 11,929) Life expectancy 31.2 (0.769) 34.5 (0.770) 22.9 (0.702) 25.4 (0.737) 15.7 (0.649) 17.2 (0.689) 9.8 (0.572) 10.6 (0.623) Without help 30.0 (0.730) 32.2 (0.739) 21.8 (0.663) 23.3 (0.710) 14.6 (0.609) 15.3 (0.669) 8.8 (0.537) 8.9 (0.609) With help 1.2 (0.132) 2.2 (0.191) 1.2 (0.136) 2.2 (0.192) 1.1 (0.141) 2.0 (0.192) 1.0 (0.147) 1.7 (0.191) % of years requiring assistance Life expectancy 19.9 (1.132) 26.4 (1.047) 13.5 (0.859) 18.5 (0.926) 8.5 (0.637) 11.8 (0.778) 5.0 (0.475) 6.8 (0.605) Without help 19.2 (1.064) 24.5 (0.965) 12.8 (0.798) 16.6 (0.849) 7.8 (0.584) 10.1 (0.703) 4.3 (0.429) 5.4 (0.537) With help 0.7 (0.129) 1.9 (0.266) 0.7 (0.129) 1.9 (0.265) 0.7 (0.133) 1.7 (0.265) 0.7 (0.143) 1.4 (0.264) % of years requiring assistance IADL assistance ( n = 11,944) Life expectancy 30.7 (0.732) 34.2 (0.728) 22.5 (0.653) 25.1 (0.701) 15.2 (0.588) 16.8 (0.657) 9.2 (0.499) 9.9 (0.588) Without help 28.7 (0.657) 29.7 (0.583) 20.5 (0.575) 20.8 (0.552) 13.2 (0.507) 12.8 (0.503) 7.4 (0.416) 6.5 (0.419) With help 2.1 (0.178) 4.5 (0.311) 2.0 (0.182) 4.3 (0.313) 2.0 (0.188) 4.0 (0.315) 1.8 (0.194) 3.4 (0.319) % of years requiring assistance Life expectancy 19.2 (1.161) 26.3(1.064) 13.2 (0.812) 18.5 (0.931) 8.5 (0.593) 11.8 (0.809) 5.0 (0.439) 6.7 (0.669) Without help 18.0 (1.055) 22.6 (0.861) 12.0 (0.720) 14.8 (0.721) 7.2 (0.509) 8.4 (0.570) 3.8 (0.355) 4.0 (0.391) With help 1.2 (0.183) 3.7 (0.436) 1.2 (0.182) 3.6 (0.436) 1.3 (0.189) 3.3 (0.442) 1.2 (0.208) 2.8 (0.447) % of years requiring assistance Note : Author s calculations using MHAS 2001 and Standard errors in parentheses. MHAS = Mexican Health and Aging Study; ADL = Activities of Daily Living; IADL = Instrumental Activities of Daily Living. Wilkins, 2002 ; Dominguez et al., 2006 ; Franco et al., 2007 ; Jagger et al., 2003, 2007 ; Laditka & Laditka, 2006 ; Stevens et al., 2008 ). Results show that individuals with diabetes have a higher prevalence of disability than those without diabetes; in addition, they face a higher incidence of disability at any age and a lower probability of recovering from functional limitations (results not shown). As a result, individuals with diabetes at age 50 have a TLE that is about 10 years shorter than individuals without diabetes. At age 80, TLE is shortened by about 4 years for individuals with diabetes. DFLE is also shorter for those with diabetes DFLE (measured by ADL and IADL limitations) at age 50 is reduced by about 9 years. Results in the current study differ somewhat depending on the measure of disability used; individuals with diabetes experience increased limitations using all three disability measures but to a greater degree with Nagi functioning measures than ADL and IADL measures. This indicates that diabetes has a strong effect on limiting upper and lower extremity functioning (Nagi) even at young adult ages, whereas its impact on measures of independent living and self-care needs (ADL and IADL) are more marked at older ages. Results presented in this paper show that in Mexican men aged 60 years are expected to live 90.7% of their remaining lives without any ADL limitation. This estimate is very similar to the estimate for Mexican men aged 60 years using data from IMSS 92.3% ( Reyes-Beaman et al., 2005 ). Among women in Mexico, those aged 60 years are expected to live, on average, 83.9% of their remaining lives without any ADL limitations; this estimate is smaller than a previous estimate based on IMSS data 89.7% (Reyes-Beaman et al.). The findings from this study go beyond those from Reyes-Beaman and colleagues (2005) by providing TLE and DFLE that incorporate health transitions (e.g., disability incidence and recovery), instead of using only crosssectional data to estimate health expectancies. In addition, this study provides evidence on the impact of diabetes on TLE and DFLE. It is well established in the literature that women live longer lives but face a higher disability burden than men, particularly in terms of the number and proportion of years to be lived with disability ( Camargos et al., 2007 ; Laditka & Laditka, 2002 ; Reyes-Beaman et al., 2005 ). This pattern occurs in Mexico as well (Reyes-Beaman et al.) and is reflected in my results. Women, regardless of their diabetic status, are expected to live more years with some sort of limitation on their daily lives. The results show that women are more likely to have IADL and Nagi limitations than men, even after controlling for demographic, socioeconomic, and other health conditions (results not shown). This study has some limitations, including a few possible sources of bias. First, the effects may be somewhat biased because diabetes is self-reported. Previous studies conducted in the United States, Canada, and England ( Belanger et al., 2002 ; Jagger et al., 2003, 2007 ; Laditka & Laditka, 2006 ) face the same limitation. The only exception is work by Franco and colleagues (2007), in which diabetes status was ascertained by blood glucose level. Previous studies

8 8 ANDRADE suggest that the percentage of undiagnosed diabetes is high in Mexico. Rull and colleagues (2005) show that the prevalence of diabetes was 8.9%, but the prevalence of previously diagnosed diabetes was only 4.9%. In a national survey conducted in urban areas in the early 1990s, only 74% of adults aged 40 years and older identified as having diabetes were aware of their diabetic status ( Aguilar-Salinas et al., 2002 ). This study is not able to take into account the increased mortality of individuals with undiagnosed diabetes or those with pre-diabetes (impaired glucose tolerance and impaired fasting glucose); therefore, the estimates presented here are conservative in regard to the real burden faced by this population. However, undiagnosed rates tend to decrease with age, which reduces the bias in this study of older adults. Another limitation arises from the fact that the first wave of the MHAS focuses on the civilian population not residing in institutions. As a result, estimates may be biased if one expects that the institutionalized population, particularly those residing in nursing homes, is likely to have a higher prevalence of diabetes than the noninstitutionalized population. However, the institutionalized population in Mexico is relatively small, and therefore, this bias is likely to be small. Differential missing data may also affect the results. Missing data were more common among men than women. However, gender differences persisted even after imputation procedures were used (results available upon request). Other limitations of the paper originate from the empirical application of multistate methods (for a detailed discussion of the drawbacks of this method, see Laditka & Hayward, 2003 ). For instance, one should be aware that the estimation of DFLE is subject to more error and variance than traditional estimates of life expectancies because DFLE estimates are based on survey data rather than vital statistics. In other words, because sample sizes are smaller, the variance is larger ( Laditka & Hayward, 2003 ). The use of IMaCh also has drawbacks. For instance, an IMaCh computation assumes that the complex structure of panel data is taken into account when using the survey sample weights. However, this strategy has been shown to overestimate variances ( Lohr, 1999 ). Despite these limitations, the results of this study have important implications for Mexico s future, specifically in the areas of public health and economic consequences. Economic development has expanded the availability of foods rich in saturated fat and refined carbohydrates but low in complex carbohydrates and fiber, and reduced the consumption of beans, fruits, and legumes; these changes have been associated with increases in obesity and metabolic syndrome ( Kabagambe, Baylin, Ruiz-Narvarez, Siles, & Campos, 2005 ). Diabetes-related mortality rates have also been increasing in recent years ( Barquera et al., 2003 ; Rull et al., 2005 ). Findings from this study suggest that diabetes reduces both TLE and DFLE. have their lives shortened, particularly the number of years in good health. As the prevalence of diabetes in Mexico increases, economic, social, and individual costs related to diabetes are expected to increase in the upcoming decades. A relatively high prevalence of diabetes imposes a considerable economic burden. In Mexico, the average annual cost of treating a patient with diabetes is approximately US$708 ( Villarreal-Ríos et al., 2000 ); the annual cost related to treating all individuals with diabetes in Mexico has been estimated at US$2,618,000. This represents 0.79% of the Mexican gross domestic product. Moreover, the majority (52%) of the expenditures related to diabetes treatment in Mexico are paid out-of-pocket by individuals and families, whereas public spending covers less than half (45%) of the total costs ( Arredondo & Barceló, 2007 ). Data from MHAS confirm that personal assistance in Mexico is provided primarily by family members. As the prevalence of diabetes (and associated conditions) increases, the burden of care for Mexican families will also increase. The rise in the prevalence of obesity and diabetes in Mexico has motivated the development of public campaigns that emphasize changes in health behaviors and lifestyle. In particular, national campaigns have been organized to both fight obesity, such as the national Vamos Por Un Million de Kilos (Let s Lose a Million Kilos) campaign, and promote physical activity, such as the Por un México Activo (For an Active Mexico) campaign organized by the Comisión Nacional de Cultura Física y Deporte (National Sports Commission). However, in order to better target and address the rise in obesity and diabetes, national public campaigns need to be more thoroughly integrated. In addition, better access to health insurance can also improve health outcomes by promoting a greater sense of personal control over individuals health in Mexico ( Angel, Angel, & Hill, 2009 ). F unding CAPES, Brazil/Fogarty, National Institutes of Health (5D43TW001586) and University of Illinois at Urbana-Champaign (09070). Acknowledgments Th e author would like to thank the editor and the anonymous reviewers for their insightful comments. The author wants to thank the following individuals for comments on a previous version of the manuscript: Alberto Palloni, Michel Guillot, Patrick Remington, Lydia Buki, Pamela Hadley, and Heitor Almeida. The author received the 2006 BSS Student Research Award for an earlier version of this paper. Correspondence Address correspondence to Flavia C. D. 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