The Social Vulnerability Index, Mortality and Disability in Mexican Middle-Aged and Older Adults
by
,
Natalia Sánchez-Garrido
1,*
,
Sara G. Aguilar-Navarro
1, 
José Alberto Ávila-Funes
1,2,
Olga Theou
3,4,
Melissa Andrew
4 and
Mario Ulises Pérez-Zepeda
4,5 1
Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Mexico City 14080, Mexico
2
Bordeaux Population Health Research Center, INSERM-University of Bordeaux, UMR 1219, F-33000 Bordeaux, France
3
School of Physiotherapy, Dalhousie University, Halifax, NS B3H 4R2, Canada
4
Geriatric Medicine, Department of Medicine, Dalhousie University, Halifax, NS B3H 4R2, Canada
5
Instituto Nacional de Geriatría, Mexico City 10200, Mexico
*
Author to whom correspondence should be addressed.
Geriatrics 2021, 6(1), 24; https://doi.org/10.3390/geriatrics6010024
Submission received: 16 January 2021
/
Revised: 19 February 2021
/
Accepted: 3 March 2021
/
Published: 8 March 2021
(This article belongs to the Section Healthy Aging)
Abstract
:The social vulnerability index (SVI) independently predicts mortality and others adverse outcomes across different populations. There is no evidence that the SVI can predict adverse outcomes in individuals living in countries with high social vulnerability such as Latin America. The aim of this study was to analyze the association of the SVI with mortality and disability in Mexican middle-aged and older adults. This is a longitudinal study with a follow-up of 47 months, the Mexican Health and Aging Study, including people over the age of 40 years. A SVI was calculated using 42 items stratified in three categories low (<0.36), medium (0.36–0.47), and high (>0.47) vulnerability. We examined the association of SVI with three-year mortality and incident disability. Cox and logistic regression models were fitted to test these associations. We included 14,217 participants (58.4% women) with a mean age of 63.9 years (±SD 10.1). The mean SVI was of 0.42 (±SD 0.12). Mortality rate at three years was 6% (n = 809) and incident disability was 13.2% (n = 1367). SVI was independently associated with mortality, with a HR of 1.4 (95% CI 1.1–1.8, p < 0.001) for the highest category of the SVI compared to the lowest. Regarding disability, the OR was 1.3 (95% CI 1.1–1.5, p = 0.026) when comparing the highest and the lowest levels of the SVI. The SVI was independently associated with mortality and disability. Our findings support previous evidence on the SVI and builds on how this association persists even in those individuals with underlying contextual social vulnerability.
1. Introduction
As the demographic transition takes place worldwide, novel factors associated with aging health contribute to adverse outcomes [1]. In particular, socio-economic determinants play a crucial role in older adults’ health [2,3]. Older adults have a greater frequency of chronic health conditions and higher mortality rates, as well as other adverse outcomes, and socio-economic determinants are part of the multicausality path that impacts older adults’ health [4]. From a syndemic angle, an adverse health outcome could potentially be caused by the synergic action of biologic and social factor [5].
A number of different aspects have been included in the study of social determinants framework [6]. These factors impact older adults’ health [7,8,9,10,11,12]. Moreover, socio-economic determinants mediate the relationship of frailty with chronic diseases in low- and middle-income countries [13].
An integrative approach to socio-economic determinants in older adults is depicted in the social vulnerability index (SVI). This index gathers a number of social factors (socio-economic status, social capital, isolation, mastery, a sense of control, etc.) into one score ranging from 0 to 1 with a higher score meaning higher social vulnerability, in a similar fashion to that of the frailty index (FI) [14,15]. In various populations worldwide, the SVI predicts mortality and other adverse outcomes such as cognitive decline and disability [16,17,18,19,20].
The link between social vulnerability and frailty has been established previously [14], and previous work by our group has shown a variable relationship between frailty and socio-economic determinants among different age groups, including middle-aged and older adults [21]. Furthermore, social vulnerability has been related to an increased mortality risk even in less frail individuals [18,19,20,21,22]. Inequalities may affect the relationship of SVI with health outcomes. Therefore, the aim of this study is to describe the association of the SVI with a short follow-up mortality and newly established disability in Mexican middle-aged and older adults.
2. Materials and Methods
2.1. Study Population
This is a secondary analysis of the 2012 and 2015 waves of the Mexican Health and Aging Study [23]. The main purpose of the Mexican Health and Aging Study is to analyze the health dynamics of Mexican older adults. It includes a population-based cohort of community-dwelling Mexican adults aged 50 years or older and their spouses regardless of age (n = 15,186). Data was collected in-person at the participant’s home by trained interviewers. Baseline assessments were done in 2001 and there were four additional waves (2003, 2012, 2015, and 2018) [24]. In 2012, a refreshment of the cohort was performed in order to increase the sample that is expected to be followed up until 2021. Each assessment contains information from different domains, including a thorough questionnaire on social determinants and health-related variables that allow the construction of the SVI and FI.
In order to take advantage of the Mexican Health and Aging Study design, all participants in the 2012 wave were included in this study; survivors of the baseline wave in 2012 and the cohort sample refreshment (n = 18,465). Information for 2742 and 1275 participants were collected through next-of-kin (spouse, child, person familiar to the surroundings of the deceased in the las months) interviews and proxy interviews, respectively (http://mhasweb.org/StudyDescription.aspx (accessed on 7 March 2021)). These participants as well as those younger than the age of 40 (N = 119) or with incomplete data (n = 112) were excluded. The final sample included in this study was 14,217. Among them, 924 individuals were lost to follow-up; therefore, 13,293 adults comprised the sample for the survival and disability analysis. (Figure 1)
2.2. Exposure Variable, Outcome Variables, and Covariables
Variables included in the SVI were selected according to previously published indexes [14,18,20,21] and included measures from various social domains such as communication, marital status, social support, locus of control, satisfaction with life, social engagement activities and economic status. Forty-two variables (42) were screened, and none had ≥5% of missing values. Each variable was coded into a 0 to 1 scale using two or more categories. For example, self-rated financial status was coded as zero if the response was ‘excellent’, 0.25 if it was ‘very good’, 0.5 if it was ‘good’, 0.75 if it was ‘regular’, and 1 if it was ‘bad’. Once every variable was coded, we counted the number of variables with missing values for each participant and excluded those participants with ≥20% of SVI variables missing (n = 48). Finally, to obtain the index, the sum score of all coded variables was divided by the total number of non-missing SVI variables. The higher the score, and the closest to one, the higher the social vulnerability of the individual. For purposes of interpretation, SVI was categorized in three groups (according to tertiles): <0.36, 0.36–0.47, and >0.47.
To construct the frailty index, we followed standard procedures: plotted the frequency of potential deficits with age, examined the deficit prevalence, and excluded variables missing more than 5% of the cases [25]. From the variables available in 2012, 67 were screened and we ended up with a 60-item FI. For the coding and scoring of each variable we followed similar steps with the SVI (see above). Deficits included in the FI, their prevalence and coding are shown in supplementary material (supplementary Table S2). For interpretation purposes, the FI was divided into four categories: <0.1, 0.1–0.2, 0.21–0.3, and >0.3.
Tobacco use was divided into ‘never’, ‘former user’, and ‘current user’. Alcohol drinking was categorized according to the Canadian Centre on Substance Abuse definition. High-risk alcohol drinking was defined as having ≥3 drinks per occasion or ≥15 a week for men, and as having ≥2 drinks per occasion or ≥10 a week for women [26]. Physical activity was measured with the question: “on average in the last two years, have you exercised or performed strenuous activities at least three times a week?” A positive response identified someone as physically active.
Disability was defined as difficulty in performing any of the following activities of daily living (ADL): dressing, walking in a room, bathing, eating, getting in/out of bed, and toileting. Only individuals without disability in 2012 were included in this analysis (n = 10,317) and incident disability was considered present if a participant reported difficulty in any ADL in the 2015 assessment.
2.3. Statistical Analysis
Descriptive statistics for each variable were done using mean and standard deviations for continuous variables, and relative and absolute frequencies for categorical variables. Kernel distribution plots were drawn stratified by sex for both the SVI and the FI. Four-way interactions were tested for the effect of SVI (independent variables), sex, age and FI, on mortality and disability (dependent variables). No significant interactions were found, and thus analyses were performed without stratification.
Survival was assessed in the 2015 wave. Reliable information on those who died between 2012 and 2015 was gathered from next-of-kin informants. Time in months from the baseline assessment (2012) to the interview in 2015 or death was used to construct the Kaplan–Meier curves and for the Cox regression analyses. The median of follow-up was 47 months.
To establish the ability of the SVI to predict mortality and disability, Receiver operating curves (ROC) were calculated, and we estimated the area under the curve. Furthermore, Kaplan–Meier curves were drawn for the categorical SVI and FI in relation to survival; log-rank tests were conducted. Cox regression (mortality) and logistic regression (incident disability) models were conducted in three sequential steps: the first one was an unadjusted model, the second was a fully adjusted model (age, sex, FI, physically active, tobacco use, high-risk alcohol drinking) and the third included only the variables that remained after the stepwise regression. To test the assumption of proportionality, log–log curves were drawn for all the models. To assess the impact of lost individuals to follow-up, three additional models were conducted, imputing their values as if they were ‘dead’, ‘alive’, or a random outcome. Results were not significantly different (not shown, data available upon request). A p-value of 0.05 was considered significant and all the statistical analyses were done in STATA 14.2 (StataCorp LLC, College Station, TX, USA).
3. Results
The baseline sample included 14,217 middle-aged and older adults (n = 5959 men and n = 8379 women), with a mean age of 63.9 years (±SD 10.1). SVI and FI were higher in women compared to men (Table 1). The distribution of the SVI was normal but the FI had a right skewed distribution (Supplementary Figures S1 and S2).
The overall mortality rate was 5.9% (n = 785). According to the bivariate analyses, all variables were significantly associated with mortality (Table 2). The group in the highest SVI tertile had a higher rate of mortality compared to the lowest SVI groups (Figure S3). Finally, the AUC of the ROC for the ability of the SVI to predict mortality was 0.659 (Supplementary Figure S4).
A total of 1367 individuals, out of the 11,846 who had no disability in 2012, developed difficulty in at least one ADL in 2015. All variables were significantly different between those with and without disability (Table 3). The AUC of the ROC for the ability of the SVI to predict disability was of 0.603 (Supplementary Figure S5).
In the Cox regression unadjusted model, both the intermediate (2.1 (95% CI 1.6–2.7)) and the highest (4.5 (95% CI 3.4–5.8)) SVI tertiles were significantly associated with higher mortality compared to the lowest tertile. In the adjusted model, SVI remained statistically significant only when comparing the highest with the lowest tertiles (1.7 (95% CI 1.2–2.3)). Tobacco use and high-risk alcohol drinking were not significant predictors of mortality, both in the fully adjusted and in the stepwise models (Table 4). In addition, in this last model SVI score highest tertiles remained significant.
Both SVI tertiles were significantly associated with incident disability (unadjusted and adjusted models). In particular, the OR for the intermediate SVI tertile was 1.2 (95% CI 1.1–1.4, p = 0.024), and for the highest SVI tertile was 1.3 (95% CI 1.1–1.5, 0.026) when compared to the lowest tertile (Table 4). In the stepwise model, SVI remained significant, and tobacco use with high-risk alcohol drinking were not significantly associated with incident disability.
4. Discussion
Social vulnerability is a complex phenomenon, and items included in the SVI are from different psychosocial domains. This study showed the association of the SVI with mortality and incident disability in Mexican middle-aged and older adults; to our knowledge, this is the first study to address this relationship in Latin America. Previous work on SVI has been done in countries with more homogeneous social factors and low inequity (e.g., Canada, USA, and Europe) [14,18,20]. Mexico is a country with well-known high inequality levels, and even in a population with these characteristics, the SVI was associated with mortality and disability. Also, many of the prior studies on SVI did not address the potential impact of lifestyle factors—such as tobacco use, high-risk alcohol drinking, and physical activity—that have been shown to be associated with adverse health outcomes [14,18,19,20,21]. Though in this study, lifestyle factors need to be considered with caution since they are self-reported. In our work, when adjusting using these factors, the SVI’s associations with adverse outcomes persisted. Moreover, according to our results, three domains (apart from the well-known effects of age and sex) are clearly identified as independent risk factors for mortality and disability: frailty, social vulnerability, and physical activity.
Higher social vulnerability was present in our sample and the SVI distribution identified here for Mexico was similar to what Wallace et al. (2015) found in the Mediterranean sub-group of the SHARE study. Since the interactions with FI levels and sex were not significant, the effect of the SVI on mortality and disability was similar across levels of frailty. This is consistent with previous studies showing, a persistent impact of SVI even in the fittest group [18,19,20,21]. Moreover, as stated by Andrew et al. (2012), countries with adverse environmental and infrastructural conditions may have higher mortality rates and small number of very fit individuals. In fact, our sample had no individuals in the zero-state frailty; the lowest FI score was 0.01 (everyone had at least one SVI deficit).
This study has limitations such as, the sample being of a single country could preclude the generalization of our results and may generalize only in contexts similar to Mexico. Furthermore, 6.5% of the individuals were not included in the analyses for various reasons (incomplete data, lost to follow-up, etc.); additional analyses on those excluded did not show different results. Even though our approach in constructing the SVI was consistent with prior operationalizations, some elements are different from previous reports. However, since aging studies around the world include similar questionnaires, the vast majority of included items are similar to other studies. Other social vulnerability factors not included in the SVI that could be specific to a highly disadvantaged population, such as food insecurity or collective violence, could also impact the social vulnerability of the participants in our study; both phenomena have been shown to impact the health of Mexican older adults [27,28].
There is an ongoing discussion about how to measure frailty; however, the FI is a comprehensive measure that maximizes the number of potential deficits included; many of these FI items can also be found in other instruments. Our choice of cutoffs for both the SVI and the FI were only for informative purposes and were not intended to be strict cutoff points; this is typical for the SVI and FI. Initial analysis was done with 0.1 intervals for the SVI score, but due to low sample size for these categories, we decided to use tertiles.
There is an urgent need to focus resources on the improvement of the social aspects of older adults in countries such as Mexico, and to not focus on only the biological aspects. Proper allocation of resources and further research on this matter could shed light on different interventions that change the future of those fast-aging countries such as Mexico.
5. Conclusions
Individual-level social vulnerability as measured by the SVI is independently associated with mortality and incident disability in a country with high social vulnerability, such as Mexico.
Supplementary Materials
The following are available online at https://www.mdpi.com/2308-3417/6/1/24/s1, Table S1: The social vulnerability index; Table S2: The frailty index; Table S3: Cox and logistic regressions (mortality and incident disability respectively) fully adjusted with interaction terms between frailty index and social vulnerability index; Figure S1: Kernel density of the social vulnerability index stratified for sex; Figure S2. Kernel distribution of the frailty index according to sex; Figure S3: ROC curve for the social vulnerability index on mortality; Figure S4: ROC curve for the social vulnerability index on incident disability.
Author Contributions
The following statements should be used. Conceptualization: N.S.-G. and M.U.P.-Z.; Methodology: M.U.P.-Z. and O.T.; Writing—original draft preparation: N.S.-G. and M.U.P.-Z.; Writing—review and editing: J.A.Á.-F., S.G.A.-N., and M.A. All authors have read and agreed to the published version of the manuscript.
Funding
The study is a collaborative effort among researchers from the University of Texas Medical Branch (UTMB), the Instituto Nacional de Estadística y Geografía (INEGI, Mexico), the University of Wisconsin, the Instituto Nacional de Geriatría (INGER, Mexico), the Instituto Nacional de Salud Pública (INSP, Mexico), and University of California Los Angeles (UCLA). The MHAS is partly supported by the National Institutes of Health/National Institute on Aging (R01AG018016, R Wong, PI) and the INEGI in Mexico.
Institutional Review Board Statement
Institutional Review Boards of the University of Texas Medical Branch (Galveston, TX, USA) and the National Institute of Public Health in Mexico reviewed and approved MHAS. All subjects signed informed consent and all proceedings are according to the Helsinki declaration.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
Data available in a publicly accessible repository http://mhasweb.org/StudyDescription.aspx (accessed on 7 March 2021).
Conflicts of Interest
Authors declare no conflict of interest.
References
- Bessa, B.; Ribeiro, O.; Coelho, T. Assessing the social dimension of frailty in old age: A systematic review. Arch. Gerontol. Geriatr. 2018, 78, 101–113. [Google Scholar] [CrossRef] [PubMed]
- Northwood, M.; Ploeg, J.; Markle-Reid, M.; Sherifali, D. Integrative review of the social determinants of health in older adults with multimorbidity. J. Adv. Nurs. 2017, 74, 45–60. [Google Scholar] [CrossRef]
- Commission on Social Determinants of Health; World Health Organization; Marmot, M.G. Closing the Gap in a Generation: Health Equity Through Action on the Social Determinants of Health; WHO: Geneva, Switzerland, 2008. [Google Scholar]
- Cesari, M.; Prince, M.; Thiyagarajan, J.A.; De Carvalho, I.A.; Bernabei, R.; Chan, P.; Gutierrez-Robledo, L.M.; Michel, J.-P.; Morley, J.E.; Ong, P.; et al. Frailty: An emerging public health priority. J. Am. Med. Dir. Assoc. 2016, 17, 188–192. [Google Scholar] [CrossRef] [PubMed]
- Singer, M.; Bulled, N.; Ostrach, B.; Mendenhall, E. Syndemics and the biosocial conception of health. Lancet 2017, 389, 941–950. [Google Scholar] [CrossRef]
- Andrew, M.K.; Keefe, J.M. Social vulnerability from a social ecology perspective: A cohort study of older adults from the National Population Health Survey of Canada. BMC Geriatr. 2014, 14, 90. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hoogendijk, E.O.; van Hout, H.P.; Heymans, M.W.; van der Horst, H.E.; Frijters, D.H.; van Groenou, M.I.B.; Deeg, D.J.; Huisman, M. Explaining the association between educational level and frailty in older adults: Results from a 13-year longitudinal study in the Netherlands. Ann. Epidemiol. 2014, 24, 538–544.e2. [Google Scholar] [CrossRef] [PubMed]
- Grundy, E.M.; Tomassini, C. Marital history, health and mortality among older men and women in England and Wales. BMC Public Health 2010, 10, 554. [Google Scholar] [CrossRef] [Green Version]
- Ng, T.P.; Jin, A.; Feng, L.; Nyunt, M.S.Z.; Chow, K.Y.; Feng, L.; Fong, N.P. Mortality of older persons living alone: Singapore Longitudinal Ageing Studies. BMC Geriatr. 2015, 15, 126. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Luanaigh, C.O.; Lawlor, B.A. Loneliness and the health of older people. Int. J. Geriatr. Psychiatry 2008, 23, 1213–1221. [Google Scholar] [CrossRef]
- Holt-Lunstad, J.; Smith, T.B.; Layton, J.B. Social relationships and mortality risk: A meta-analytic review. PLoS Med. 2010, 7, e1000316. [Google Scholar] [CrossRef]
- Hill, T.D.; Saenz, J.; Rote, S.M. Religious participation and mortality risk in Mexico. J. Gerontol. B Psychol. Sci. Soc. Sci. 2018. [CrossRef]
- Hoogendijk, E.O.; Rijnhart, J.J.; Kowal, P.; Pérez-Zepeda, M.U.; Cesari, M.; Abizanda, P.; Ruano, T.F.; Schop-Etman, A.; Huisman, M.; Dent, E. Socioeconomic inequalities in frailty among older adults in six low- and middle-income countries: Results from the WHO Study on global AGEing and adult health (SAGE). Maturitas 2018, 115, 56–63. [Google Scholar] [CrossRef]
- Andrew, M.K.; Mitnitski, A.B.; Rockwood, K. Social vulnerability, frailty and mortality in elderly people. PLoS ONE 2008, 3, e2232. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mitnitski, A.B.; E Graham, J.; Mogilner, A.J.; Rockwood, K. Frailty, fitness and late-life mortality in relation to chronological and biological age. BMC Geriatr. 2002, 2, 1. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Andrew, M.K.; Dupuis-Blanchard, S.; Maxwell, C.; Giguere, A.; Keefe, J.; Rockwood, K.; John, P.S. Social and societal implications of frailty, including impact on Canadian healthcare systems. J. Frailty Aging 2018, 7, 217–223. [Google Scholar]
- Armstrong, J.J.; Godin, J.; Launer, L.J.; White, L.R.; Mitnitski, A.; Rockwood, K.; Andrew, M.K. Changes in frailty predict changes in cognition in older men: The Honolulu-Asia Aging Study. J. Alzheimers Dis. 2016, 53, 1003–1013. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Armstrong, J.J.; Andrew, M.K.; Mitnitski, A.; Launer, L.J.; White, L.R.; Rockwood, K. Social vulnerability and survival across levels of frailty in the Honolulu-Asia Aging Study. Age Ageing 2015, 44, 709–712. [Google Scholar] [CrossRef] [Green Version]
- Ouvrard, C.; Avila-Funes, J.A.; Dartigues, J.; Amieva, H.; Tabue-Teguo, M. The social vulnerability index: Assessing replicability in predicting mortality over 27 years. J. Am. Geriatr. Soc. 2019, 67, 1305–1306. [Google Scholar] [CrossRef]
- Wallace, L.M.K.; Theou, O.; Pena, F.; Rockwood, K.; Andrew, M.K. Social vulnerability as a predictor of mortality and disability: Cross-country differences in the survey of health, aging, and retirement in Europe (SHARE). Aging Clin. Exp. Res. 2015, 27, 365–372. [Google Scholar] [CrossRef]
- Andrew, M.K.; Mitnitski, A.; Kirkland, S.A.; Rockwood, K. The impact of social vulnerability on the survival of the fittest older adults. Age Ageing 2012, 41, 161–165. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Perez-Zepeda, M.U.; Avila-Funes, J.A.; Gutierrez-Robledo, L.M. Frailty across age groups. J. Frailty Aging 2016, 5, 15–19. [Google Scholar]
- Wong, R.; Michaels-Obregon, A.; Palloni, A. Cohort profile: The Mexican Health and Aging Study (MHAS). Int. J. Epidemiol. 2017, 46, e2. [Google Scholar] [CrossRef] [PubMed]
- Wong, R.; Palloni, A.; Gutierrez-Robledo, L.M. MHAS Mexican Health and Aging Study 2012. In Data Files and Documentation (PUBLIC use): Mexican Health and Aging Study, (Methodological Document); Branch, U.T.M., Ed.; MHAS: Galveston, TX, USA, 2014; Available online: www.MHASweb.org (accessed on 7 March 2021).
- Searle, S.D.; Mitnitski, A.; Gahbauer, E.A.; Gill, T.M.; Rockwood, K. A standard procedure for creating a frailty index. BMC Geriatr. 2008, 8, 24. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Butt, P.; Beirness, D.; Gliksman, L. Alcohol and Health in Canada: A Summary of Evidence and Guidelines for Low Risk Drinking. Canadian Centre on Substance Abuse. 2011. Available online: www.ccsa.ca/2011%20CCSA%20Documents/2011-Summary-of-Evidence-and-Guidelines-for-Low-Risk%20Drinking-en.pdf (accessed on 7 March 2021).
- Pérez-Zepeda, M.U.; Castrejón-Pérez, R.C.; Wynne-Bannister, E.; García-Peña, C. Frailty and food insecurity in older adults. Public Health Nutr. 2016, 19, 2844–2849. [Google Scholar] [CrossRef] [Green Version]
- Pérez-Zepeda, M.U.; García-Peña, C.; Sánchez-Garrido, N.; Wynne-Bannister, E.G.; Moreno-Peniche, B. Collective violence and the health of the elderly: A cross-sectional analysis of a population-based national survey in Mexico. Rev. Panam. Salud Pública 2017, 41, e29. [Google Scholar] [CrossRef] [PubMed]
Figure 1.
Sample flowchart.
Table 1.
Baseline characteristics of participants stratified by sex.
| Total (n = 14,217) | Men (n = 5959) | Women (n = 8379) | |
|---|---|---|---|
| Age, mean (SD) | 63.9 (10.1) | 65.2 (9.6) | 63 (10.2) |
| Physically active, n (%) | 5603 (39.4) | 2843 (48.1) | 2760 (33.2) |
| Tobacco use, n (%) | |||
| Never | 8931 (62.8) | 2352 (39.8) | 6579 (79.2) |
| Former user | 3553 (24.9) | 2427 (41) | 1126 (13.5) |
| Current user | 1733 (12.1) | 1134 (19.1) | 599 (7.2) |
| High-risk alcohol drinking, n (%) | 1330 (9.3) | 1019 (17.2) | 311 (3.7) |
| Social vulnerability index, mean (SD) | 0.42 (0.12) | 0.39 (0.11) | 0.43 (0.12) |
| Frailty index, mean (SD) | 0.23 (0.11) | 0.2 (0.1) | 0.25 (0.1) |
Table 2.
Bivariate analysis of mortality.
| Alive (n = 12,508) | Dead (n = 785) | p-Value * | |
|---|---|---|---|
| Age Categories, n (%) | |||
| 40–49 | 621 (4.9) | 4 (0.5) | <0.001 |
| 50–59 | 3987 (31.8) | 57 (7.2) | |
| 60–69 | 4616 (36.9) | 226 (28.8) | |
| 70–79 | 2488 (19.9) | 262 (33.4) | |
| ≥80 | 796 (6.4) | 236 (30.1) | |
| Sex, n (%) | |||
| Women | 7390 (59.1) | 388 (49.4) | <0.001 |
| Men | 5118 (40.9) | 397 (50.6) | |
| Physically active, n (%) | 5027 (40.2) | 177 (22.6) | <0.001 |
| Tobacco use, n (%) | |||
| Never | 7911 (63.2) | 474 (60.3) | 0.008 |
| Former user | 3076 (24.6) | 230 (29.3) | |
| Current user | 1521 (12.1) | 81 (10.3) | |
| High-risk alcohol drinking, n (%) | 1193 (9.5) | 39 (4.9) | <0.001 |
| Social vulnerability index, mean (SD) | 0.41 (0.12) | 0.48 (0.12) | <0.001 |
| Frailty index, mean (SD) | 0.22 (0.1) | 0.31 (0.13) | <0.001 |
| Social vulnerability index score tertiles, n (%) | |||
| <0.36 | 4233 (33.8) | 126 (16) | <0.001 |
| 0.36–0.47 | 4241 (33.9) | 233 (29.7) | |
| >0.47 | 4034 (32.2) | 426 (54.2) | |
| Frailty index categories, n (%) | |||
| <0.1 | 1079 (8.6) | 21 (2.7) | <0.001 |
| 0.11–0.2 | 4921 (39.3) | 168 (21.4) | |
| 0.21–0.3 | 3525 (28.2) | 196 (25) | |
| >0.3 | 2983 (23.9) | 400 (50.9) | |
* p-values were obtained from log-rank test; with the exception of the continuous SVI and FI variables in which case a t-test was used * p-values were obtained from log-rank test; with the exception of the continuous SVI and FI variables in which case a t-test was used to estimate p-value. * Only those without difficulty in 2012 for any of six activities of daily living (dressing, walking in a room, bathing, eating, going in and out of bed and using the toilet) were included.
Table 3.
Bivariate analysis for incident disability *.
| No Disability (n = 8950) | Disability (n = 1367) | p-Value * | |
|---|---|---|---|
| Age Categories, n (%) | |||
| 40–49 | 517 (5.8) | 34 (2.5) | <0.001 |
| 50–59 | 3310 (36.9) | 290 (21.2) | |
| 60–69 | 3306 (37) | 521 (38.1) | |
| 70–79 | 1485 (16.6) | 371 (27.1) | |
| ≥80 | 332 (3.7) | 151 (11.1) | |
| Sex, n (%) | |||
| Women | 5069 (56.6) | 828 (60.6) | 0.006 |
| Men | 3881 (43.4) | 539 (39.4) | |
| Physically active, n (%) | 3924 (43.8) | 455 (33.2) | <0.001 |
| Tobacco use, n (%) | |||
| Never | 5603 (62.6) | 902 (66) | 0.013 |
| Former user | 2178 (24.3) | 322 (23.6) | |
| Current user | 1169 (13.1) | 143 (10.4) | |
| High-risk alcohol drinking, n (%) | 962 (10.7) | 116 (8.5) | 0.011 |
| Social vulnerability index, mean (SD) | 0.2 (0.12) | 0.44 (0.12) | <0.001 |
| Frailty index, mean (SD) | 0.21 (0.09) | 0.28 (0.11) | <0.001 |
| Social vulnerability index score tertiles, n (%) | |||
| <0.36 | 3442 (38.4) | 340 (24.8) | <0.001 |
| 0.36–0.47 | 3033 (33.8) | 474 (34.6) | |
| >0.47 | 2475 (27.6) | 553 (40.4) | |
| Frailty index levels, n (%) | |||
| <0.1 | 681 (7.6) | 23 (1.7) | <0.001 |
| 0.11–0.2 | 3924 (43.9) | 299 (21.9) | |
| 0.21–0.3 | 2688 (30) | 462 (33.8) | |
| >0.31 | 1657 (18.5) | 583 (42.6) | |
* Only those without difficulty in 2012 for any of six activities of daily living (dressing, walking in a room, bathing, eating, going in and out of bed, and using the toilet) were included.
Table 4.
Multivariate analysis of mortality and incident disability.
| Mortality | Incident Disability | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 1 | Model 2 | |||||||||
| HR | 95% CI | p-Value | HR | 95% CI | p-Value | OR | 95% CI | p-Value | OR | 95% CI | p-Value | |
| Social vulnerability index tertiles | ||||||||||||
| <0.36 | Reference | |||||||||||
| 0.36–0.47 | 1.8 | 1.4–2.2 | <0.001 | 1.2 | 0.9–1.5 | 0.054 | 1.5 | 1.3–1.8 | <0.001 | 1.2 | 1.1–1.4 | 0.024 |
| >0.47 | 3.4 | 2.8–4.1 | <0.001 | 1.4 | 1.1–1.8 | <0.001 | 2.2 | 2.6 | <0.001 | 1.3 | 1.1–1.5 | 0.026 |
| Age categories | ||||||||||||
| 40–49 | Reference | |||||||||||
| 50–59 | 1.9 | 0.7–5.3 | 0.21 | 1.3 | 0.9–1.9 | 0.17 | ||||||
| 60–69 | 5.4 | 2–14.5 | 0.001 | 2.2 | 1.5–3.1 | <0.001 | ||||||
| 70–79 | 9.2 | 3.4–24.9 | <0.001 | 2.9 | 2–4.3 | <0.001 | ||||||
| ≥80 | 19.1 | 7.1–51.7 | <0.001 | 4.8 | 3.2–7.3 | <0.001 | ||||||
| Sex | ||||||||||||
| Women | Reference | |||||||||||
| Men | 1.7 | 1.5–2 | <0.001 | 1 | 0.8–1.1 | 0.7 | ||||||
| Physically active | 0.6 | 0.5–0.7 | <0.001 | 0.8 | 0.7–0.9 | <0.001 | ||||||
| Tobacco use | ||||||||||||
| Never | Reference | |||||||||||
| Former user | 0.99 | 0.83–1.18 | 0.84 | 0.9 | 0.8–1.1 | 0.42 | ||||||
| Current user | 1.04 | 0.81–1.3 | 0.81 | 0.9 | 0.7–1.1 | 0.29 | ||||||
| High-risk alcohol drinking | 0.7 | 0.5–1 | 0.11 | 1.1 | 0.9–1.4 | 0.27 | ||||||
| Frailty index levels | ||||||||||||
| <0.1 | Reference | |||||||||||
| 0.11–0.2 | 1.2 | 0.7–1.9 | 0.05 | 1.9 | 1.2–2.9 | <0.001 | ||||||
| 0.21–0.3 | 1.5 | 0.9–2.3 | 0.092 | 3.7 | 2.4–5.7 | <0.001 | ||||||
| >0.31 | 2.7 | 1.7–4.2 | <0.001 | 7.2 | 4.7–11.1 | <0.001 | ||||||
HR = hazard ratios, CI = confidence intervals. Model 1: unadjusted. Model 2: adjusted for physical activity, tobacco use and alcohol.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Sánchez-Garrido, N.; Aguilar-Navarro, S.G.; Ávila-Funes, J.A.; Theou, O.; Andrew, M.; Pérez-Zepeda, M.U. The Social Vulnerability Index, Mortality and Disability in Mexican Middle-Aged and Older Adults. Geriatrics 2021, 6, 24. https://doi.org/10.3390/geriatrics6010024
AMA Style
Sánchez-Garrido N, Aguilar-Navarro SG, Ávila-Funes JA, Theou O, Andrew M, Pérez-Zepeda MU. The Social Vulnerability Index, Mortality and Disability in Mexican Middle-Aged and Older Adults. Geriatrics. 2021; 6(1):24. https://doi.org/10.3390/geriatrics6010024
Chicago/Turabian StyleSánchez-Garrido, Natalia, Sara G. Aguilar-Navarro, José Alberto Ávila-Funes, Olga Theou, Melissa Andrew, and Mario Ulises Pérez-Zepeda. 2021. "The Social Vulnerability Index, Mortality and Disability in Mexican Middle-Aged and Older Adults" Geriatrics 6, no. 1: 24. https://doi.org/10.3390/geriatrics6010024
APA StyleSánchez-Garrido, N., Aguilar-Navarro, S. G., Ávila-Funes, J. A., Theou, O., Andrew, M., & Pérez-Zepeda, M. U. (2021). The Social Vulnerability Index, Mortality and Disability in Mexican Middle-Aged and Older Adults. Geriatrics, 6(1), 24. https://doi.org/10.3390/geriatrics6010024
