Skip to main content

Disability and severe depression among Peruvian older adults: analysis of the Peru Demographic and Family Health Survey, ENDES 2017



Depression is considered a mental health-related disability that affects approximately 350 million people worldwide. On the other hand, it is estimated that 15% of the world’s population lives with some form of disability, and this scenario is currently riddled with the global burden of mental disorders, non-communicable diseases and other age-related comorbidities.


To assess the association between disability and depression among Peruvian older adults.


We used data from the 2017 Peru Demographic and Familiar Health Survey, with a focus on adults aged 50 years and older. Whereas the presence of disability was assessed using different questions of the survey, depression was measured with the Patient Health Questionnaire-9 (PHQ-9). We calculated the adjusted prevalence ratios (aPR) using Poisson regression models with log link function, with their respective 95% confidence intervals (95% CI).


From the study population, 5% had a disability. In addition, 43.3% were screened positive for depression (13.2% for moderately severe/severe). After adjusting for confounding variables, disability was associated with moderate and severe depression (aPR: 1.06; 95% CI: 1.01–1.11, aPR: 1.10; 95% CI: 1.05–1.15).


Disability was positively associated with moderate and severe depression. Public health policies should address the early diagnosis and rehabilitation of patients with any of these problems. Likewise, coping strategies should be promoted among families of persons with disabilities.

Peer Review reports


Depression is considered a mental health-related disability that affects approximately 350 million people worldwide [1], causing high healthcare costs due to the recurrence and chronicity of depressive symptoms (DS) [2, 3]. Despite efforts for screening and early interventions, the etiology of depression is still not fully understood [4]. Furthermore, the negative impact of DS on the development and worsening of some non-communicable diseases (NCDs) [5,6,7] and substance use disorders [8, 9] makes even more difficult the understanding of the already complex pathophysiology.

On the other hand, it is estimated that 15% of the world’s population lives with some form of disability [10], and this scenario is currently riddled with the global burden of mental disorders [11], NCDs [12] and other age-related comorbidities [13]. In addition, people with disabilities usually have to face the loss of role within the family, unemployment, the social and self-stigma of disability and low-quality healthcare [14,15,16,17,18].

Current evidence suggests that there is a close relationship between disability and mental health, which includes an increased risk for depression [1, 19]. However, not only the linked pathophysiology and mechanisms are still not fully understood [4], but there are also several factors (e.g. sociodemographic and clinical) which might act as confounders in this relationship [20, 21].

In Peru, the probability of having a disability and the disability-Adjusted Life Year (DALYs) from depressive disorders increase from the age of 50 years onwards [22, 23]. In addition, whereas a previous study found an association between physical disability and depression in a population aged 60 years and over [24], other population-based studies only focused on mental health and its comorbidities in general [25, 26]. Thus, this study aimed to assess the association between disability and depression among Peruvian adults aged 50 years and older, using the Demographic and Family Health Survey (ENDES 2017).


Source of information

The data used in this research was collected during the 2017 Peru Demographic and Familiar Health Survey (ENDES) [27]. The ENDES is a nationally representative, stratified, cluster sample survey performed annually by the National Institute of Statistics and Informatics (INEI). It is composed of three questionnaires (household, reproductive-age women and health) and is performed with the aim to update knowledge about health indicators of the Peruvian population [28]. For this study, we used the health questionnaire data set, which was applied to one person per household aged 15 or above and selected by the last-birthday method [29]. Databases and additional information about the ENDES methodology are publicly available on the INEI web page.

Setting and population

During 2017, 36,595 households were surveyed in ENDES and 34,099 individuals participated in answering the health questionnaire. We restricted our analysis to 8298 adults aged 50 years and older [30, 31]. A total of 37 participants (< 0.1%) had missing data in our variables of interest; these were removed from analyses and we worked with a final sub-sample of 8261 individuals.

Exposure: disability

ENDES assessed disability by using six questions which asked if the responder had permanent limitation to move, talk, heard, see, understand or communicate/interact with other persons. Disability was defined as a positive answer to any of these limitations. Then, it was dichotomized in yes or no.

Outcome: depression

Depression was assessed using the Patient Health Questionnaire-9 (PHQ-9), which has been previously validated in Peruvian population [32]. The PHQ-9 requires a respondent to report “over the last 2 weeks, how many days have you felt any of the following problems”. Nine items were assessed: (i) “Little interest or pleasure in doing things”; (ii) “Feeling down, depressed, or hopeless”; (iii) “Trouble falling or staying asleep, or sleeping too much”; (iv) “Feeling tired or having little energy”; (v) “Poor appetite or overeating”; (vi) “Trouble concentrating on things”; (vii) “Moving or speaking so slowly that other people could have noticed, or the opposite, being so fidgety or restless that you have been moving around a lot more than usual”; (viii) “Thoughts that you would be better off dead or of hurting yourself in some way”, (ix) “Feeling bad about yourself or that you are a failure or have let yourself or your family down”. The answers of the questions were recoded using a standardized protocol, 0 to 1 day was recoded as ‘0’; 2 to 6 days was recoded as ‘1’; 7 to 11 days was recorded as ‘2’; and 12 to 14 days was recoded as ‘3’.

The total score was divided into the following categories of increasing severity: 1–4 for no significant depression; 5–9 for mild depression, 10–14 for moderate depression; and ≥ 15 for moderately severe/severe depression. These categories were chosen based on the Kroenke et al. research that validated the PHQ-9 for depression severity assessment [33].

Other variables

Based on previous literature we included as confounder variables: Sociodemographic characteristics (sex, age, education, income level, geographical region), lifestyle habits (daily smoking, harmful alcohol consumption, body mass index) and two comorbidities (diabetes and hypertension).

Statistical analysis

ENDES data sets were downloaded and imported to R v3.5.2. Using the survey package, we specified the complex design using the primary and secondary sample units, weights and strata for each observation. Categorical variables were described using absolute frequencies, and weighted proportions with 95% confidence intervals (95% CI). For assessing the associations between categories of depressive symptom severity (dependent variable) and the presence of disability (explanatory variable), we used a Poisson regression model with log link function and calculated the adjusted prevalence ratios (aPR) with their respective 95% CI. We performed three separate models for each category of depression severity, using the category “no significant depressive symptoms” as reference.


General characteristics of the study population

Table 1 shows the characteristics of the sample of 8261 adults aged 50 and older. Nearly 5% of respondents had a disability and 27% were screened positive for depression. Other important variables were hypertension (21.4%), diabetes (8.4%), daily smoking (2.2%), harmful alcohol consumption (0.4%), overweight (41.3%) and obesity (26.8%).

Table 1 General characteristics, disability and depression levels of a sub-sample of Peruvian adults, ENDES 2017 (n = 8261)

Depression severity in adults with disabilities

Among people with disabilities, 43.3% had depression (weighted %): 19.4, 10.7 and 13.2% were screened positive for mild, moderate and moderately severe/severe depression, respectively).

Prevalence of depressive symptom severity by characteristics of the study population

Severe depression was significantly more frequent among women (p < 0.001) and respondents from the highlands (p < 0.001), considered poor or very poor by their wealth index (p < 0.001), with hypertension (p < 0.001), with a harmful alcohol consumption (p = 0.010), and with a disability (p < 0.001). The age group (p < 0.001), education level (p < 0.001), geographical region (p < 0.001) and body mass index (BMI) (p < 0.001) were also related to depressive symptom severity (Table 2).

Table 2 Depressive symptom severity by characteristics of the study population, ENDES 2017

Association between disability and depressive symptom severity

Table 3 shows the prevalence ratios after adjusting for sex, age, education, income, BMI, smoking, harmful alcohol consumption, diabetes and hypertension. We found that disability was positively associated with moderate and severe depression (aPR: 1.06; 95% CI: 1.01–1.11 and aPR: 1.10; 95% CI: 1.05–1.15, respectively).

Table 3 Adjusted prevalence ratios (aPR) for depressive symptom severity, according to disability, ENDES 2017


Main findings

We conducted a secondary analysis using data from the 2017 Peru Demographic and Family Health Survey. The overall prevalence of severe depression in the population was 4.2% and among people with disabilities was 13.2%.

Depression and disability

Some mechanisms could explain the reciprocal relationship between disability and depression. First, depression itself is a disabling illness [34]. Second, disability is an independent determinant of the severity of depressive symptoms in different health conditions [34, 35]. Third, depression is usually associated with other important comorbidities such as hypertension and diabetes [36], which could result in a complex disabling condition. Fourth, disability could play the role of chronic stressful condition which increases the risk of developing depression [19]. Fifth, disability and depression might share hormonal and metabolic pathways: Depression has been linked with high levels of cortisol [37] but it has been hypothesized that physical exercise could modulate these levels possibly due to an upregulation of the glucocorticoid receptor [38]. Since physical inactivity is particularly prevalent among adults with disabilities [39], depression could be a reflection and a consequence of this scenario. Sixth, the complex social and family context of disability can increase the severity of depression [40,41,42].

It was estimated that in 2015 the proportion of the world’s population with depression was 4.4%. Prevalence rates vary by age and peak in most adulthood (above 7.5% in women aged 55–74 and above 5.5% in men) [1]. Depression contributes to functional disability in patients with chronic medical conditions and leads to impairment in self-maintenance and instrumental activities of daily living [43]. Unfortunately, the diagnosis can be particularly tricky because of the clinical overlap of several symptoms that may confound the complex clinical picture of this disorder [44], especially among people with disabilities [45, 46].

In Peru, one study that assessed the relationship between depression and disability was conducted by Martina M et al. [24]. The research team described that people with disabilities and some level of depression represented 12.7% of the surveyed population. However, several confounding variables were not assessed, and the study population was restricted to people ≥60 years, which limited the extrapolation of the results. A study conducted in Italy by Solaro C et al. (2016) [47] reported that 19% of the adult population with multiple sclerosis (considered in this context as a disability) had severe depression. The authors attributed this finding to the correlation between brain damage and the frequency of depressive symptoms, more critical than disability per se. Hughes R et al. (2007) found that 75.4% of US rural women with a physical disability had severe depression [48], a much higher proportion than in our study. However, both of them used the Beck Depression Inventory-II instead of the PHQ-9. Although in our study mild depression was the most prevalent, it is necessary to consider that disability (primarily physical) in adults is often long and permanent. Thus, depression might reach higher levels if psychological and psychosocial interventions are not taken [1].

Public health relevance

Depression is considered the leading cause of disability worldwide [49]. In Peru, the implementation of mental health care is still an unmet challenge. It is not available in several regions, and private health insurance is not required by law to cover such care [50]. In addition, the absence of a community-based care and rehabilitation system forces patients with disability and depression to live and stay all day at their homes. This often results in family issues, attrition of the primary caregiver, and social discrimination for both the individuals and their families [40,41,42, 50, 51].

In Peru, the Mental Health Law (N° 30,947) was recently promulgated on April 2019, establishing the legal framework to guarantee access to services, promotion, prevention, treatment and rehabilitation in mental health, as conditions for the full exercise of the right to health and well-being of the individual, the family and the community [52]. This is certainly an important beginning in the process of addressing the burden of mental illness in the country, especially because it includes the adoption of measures to eliminate barriers to access to mental health care in people with disabilities. However, it is necessary to assess the impact and usefulness of this law, and our results could serve as a baseline for future studies.

Strengths and limitations

This was a population-based study with a representative and multi-stage sampling. In addition, since ENDES is based on DHS methodology, our results could be compared with other surveys either in Peru or other countries. However, some limitations should be highlighted. First, we cannot infer causality in the interpretation of results due to the cross-sectional design of the study. Moreover, in the interpretation of the results reverse causality can not be ruled out. Second, the World Health Organization defines disability as a continuous phenomenon; however, this variable is dichotomized in the ENDES 2017 (yes/no). Third, since this was a secondary analysis we could not include some potential confounding variables such as the family history of depression or other comorbidities different from hypertension and diabetes. Fourth, PHQ-9 is a screening and not a diagnostic tool for depression, which could produce false-positive results; however, we used validated cut-off points for depressive symptoms severity, which should reduce the risk of misclassification.


This study found that disability was associated with moderate and severe depression. It is essential to prioritize public health policies that address the early diagnosis and rehabilitation of patients with any of these problems. Likewise, coping strategies should be promoted among families of persons with disabilities.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available in the Peruvian National Institute of Statistics and Informatics repository:



Encuesta Demográfica y de Salud Familiar (Demographic and Family Health Survey)


Instituto Nacional de Estadística e Informática (National Institute of Statistics and Informatics)


Patient Health Questionnaire-9


Body mass index


Prevalence ratio

95% CI:

95% confidence intervals


Non-communicable diseases


Depressive symptoms


Disability-Adjusted Life Year


Demographic and Health Survey


  1. 1.

    World Health Organization. Depression and other common mental disorders: Global Health estimates. Geneva: WHO; 2017.

    Google Scholar 

  2. 2.

    Marcus M, Yasamy M, van Ommeren O, Chisholm D, Saxena S. Depression: a global public health concern. Geneva: World Health Organization; 2012.

    Google Scholar 

  3. 3.

    Welch CA, Czerwinski D, Ghimire B, Bertsimas D. Depression and costs of health care. Psychosomatics. 2009;50(4):392–401.

    PubMed  Article  Google Scholar 

  4. 4.

    Patten SB. Medical models and metaphors for depression. Epidemiol Psychiatr Sci. 2015;24(4):303–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. 5.

    Li Z, Li Y, Chen L, Chen P, Hu Y. Prevalence of depression in patients with hypertension: a systematic review and meta-analysis. Medicine (Baltimore). 2015;94(31):e1317.

    CAS  Article  Google Scholar 

  6. 6.

    Jia Z, Li X, Yuan X, Zhang B, Liu Y, Zhao J, et al. Depression is associated with diabetes status of family members: NHANES (1999-2016). J Affect Disord. 2019;249:121–6.

    PubMed  Article  Google Scholar 

  7. 7.

    World Health Organization. Addressing comorbidity between mental disorders and major noncommunicable diseases. Copenhagen: WHO Regional Office for Europe; 2017.

    Google Scholar 

  8. 8.

    Dierker L, Selya A, Lanza S, Li R, Rose J. Depression and marijuana use disorder symptoms among current marijuana users. Addict Behav. 2018;76:161–8.

    PubMed  Article  Google Scholar 

  9. 9.

    Quello SB, Brady KT, Sonne SC. Mood disorders and substance use disorder: a complex comorbidity. Sci Pract Perspect. 2005;3(1):13–21.

    PubMed  PubMed Central  Article  Google Scholar 

  10. 10.

    World Health Organization. World report on disability 2011. Geneva: WHO; 2011.

    Google Scholar 

  11. 11.

    Vigo D, Thornicroft G, Atun R. Estimating the true global burden of mental illness. Lancet Psychiatry. 2016;3(2):171–8.

    PubMed  Article  Google Scholar 

  12. 12.

    Habib SH, Saha S. Burden of non-communicable disease: global overview. Diabetes Metab Syndr Clin Res Rev. 2010;4(1):41–7.

    Article  Google Scholar 

  13. 13.

    Torres JL, Lima-Costa MF, Marmot M, de Oliveira C. Wealth and disability in later life: the English longitudinal study of ageing (ELSA). PLoS One. 2016;11(11):e0166825.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  14. 14.

    Lépine J-P, Briley M. The increasing burden of depression. Neuropsychiatr Dis Treat. 2011;7(Suppl 1):3–7.

    PubMed  PubMed Central  Google Scholar 

  15. 15.

    Shen S-C, Huang K-H, Kung P-T, Chiu L-T, Tsai W-C. Incidence, risk, and associated factors of depression in adults with physical and sensory disabilities: a nationwide population-based study. PLoS One. 2017;12(3):e0175141.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  16. 16.

    Ali A, Hassiotis A, Strydom A, King M. Self stigma in people with intellectual disabilities and courtesy stigma in family carers: a systematic review. Res Dev Disabil. 2012;33(6):2122–40.

    PubMed  Article  Google Scholar 

  17. 17.

    Buljevac M, Majdak M, Leutar Z. The stigma of disability: Croatian experiences. Disabil Rehabil. 2012;34(9):725–32.

    PubMed  Article  Google Scholar 

  18. 18.

    Nurmela K, Mattila A, Heikkinen V, Uitti J, Ylinen A, Virtanen P. Identification of depression and screening for work disabilities among long-term unemployed people. Int J Environ Res Public Health. 2018;15(5):909.

    PubMed Central  Article  Google Scholar 

  19. 19.

    Noh J-W, Kwon YD, Park J, Oh I-H, Kim J. Relationship between physical disability and depression by gender: a panel regression model. PLoS One. 2016;11(11):e0166238.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  20. 20.

    Penninx BW, Leveille S, Ferrucci L, van Eijk JT, Guralnik JM. Exploring the effect of depression on physical disability: longitudinal evidence from the established populations for epidemiologic studies of the elderly. Am J Public Health. 1999;89(9):1346–52.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Feroz-Nainar C. Confounding factors for depression in adults with mild learning disability. Br J Psychiatry J Ment Sci. 2005;187:89.

    CAS  Article  Google Scholar 

  22. 22.

    Ministerio de Salud. Análisis de la Situación de la Discapacidad en el Perú 2007. Lima: MINSA; 2007.

    Google Scholar 

  23. 23.

    Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2017 (GBD 2017) Results. Seattle: Institute for Health Metrics and Evaluation (IHME); 2018.

    Google Scholar 

  24. 24.

    Martina M, Ara MA, Gutiérrez C, Nolberto V, Piscoya J. Depresión y factores asociados en la población peruana adulta mayor según la ENDES 2014-2015. An Fac Med. 2017;78(4):393–7.

    Article  Google Scholar 

  25. 25.

    Instituto Especializado de Salud Mental “Honorio Delgado - Hideyo Noguchi”. Estudio Epidemiológico Metropolitano de Salud Mental 2002, Informe general. Lima: IESM HD-HN; 2002.

    Google Scholar 

  26. 26.

    Instituto Especializado de Salud Mental “Honorio Delgado - Hideyo Noguchi”. Estudio Epidemiológico de Salud Mental en Lima Metropolitana y Callao Replicación 2012, Informe general. Lima: IESM HD-HN; 2013.

    Google Scholar 

  27. 27.

    Instituto Nacional de Estadística e Informática. Perú: Encuesta Demográfica y de Salud Familiar 2017. Lima: INEI; 2017.

    Google Scholar 

  28. 28.

    Instituto Nacional de Estadística e Informática Perú. Ficha técnica: Encuesta demográfica y de salud familiar 2017. Lima: INEI; 2017.

    Google Scholar 

  29. 29.

    Lavrakas PJ. Encyclopedia of survey research methods. Thousand Oaks: SAGE Publications, Inc; 2008.

    Google Scholar 

  30. 30.

    Gerst-Emerson K, Wong R, Michaels-Obregon A, Palloni A. Cross-National differences in disability among elders: transitions in disability in Mexico and the United States. J Gerontol B Psychol Sci Soc Sci. 2015;70(5):759–68.

    PubMed  PubMed Central  Article  Google Scholar 

  31. 31.

    Limburg H, Espinoza R, Lansingh VC, Silva JC. Functional low vision in adults from Latin America: findings from population-based surveys in 15 countries. Rev Panam Salud Publica. 2015;37(6):371–8.

    PubMed  Google Scholar 

  32. 32.

    Calderón M, Gálvez-Buccollini JA, Cueva G, Ordoñez C, Bromley C, Fiestas F. Validación de la versión peruana del PHQ-9 para el diagnóstico de depresión. Rev Peru Med Exp Salud Pública. 2012;29:578–9.

    PubMed  Article  Google Scholar 

  33. 33.

    Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606–13.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. 34.

    Friedman B, Lyness JM, Delavan RL, null CL, WH B. Major depression and disability in older primary care patients with heart failure. J Geriatr Psychiatry Neurol. 2008;21(2):111–22.

    PubMed  Article  Google Scholar 

  35. 35.

    Gesztelyi G, Bereczki D. Disability is the major determinant of the severity of depressive symptoms in primary headaches but not in low back pain. Cephalalgia Int J Headache. 2005;25(8):598–604.

    CAS  Article  Google Scholar 

  36. 36.

    Valladares-Garrido MJ, Soriano-Moreno AN, Rodrigo-Gallardo PK, Moncada-Mapelli E, Pacheco-Mendoza J, Toro-Huamanchumo CJ. Depression among Peruvian adults with hypertension and diabetes: analysis of a national survey. Diabetes Metab Syndr. 2020;14(2):141–6.

    PubMed  Article  Google Scholar 

  37. 37.

    Dienes KA, Hazel NA, Hammen CL. Cortisol secretion in depressed, and at-risk adults. Psychoneuroendocrinology. 2013;38(6):927–40.

    CAS  PubMed  Article  Google Scholar 

  38. 38.

    Beserra AHN, Kameda P, Deslandes AC, Schuch FB, Laks J, de Moraes HS. Can physical exercise modulate cortisol level in subjects with depression? A systematic review and meta-analysis. Trends Psychiatry Psychother. 2018;40(4):360–8.

    PubMed  Article  Google Scholar 

  39. 39.

    Centers for Disease Control and Prevention (CDC). Physical activity among adults with a disability--United States, 2005. MMWR Morb Mortal Wkly Rep. 2007;56(39):1021–4.

    Google Scholar 

  40. 40.

    Seltzer MM, Floyd F, Song J, Greenberg J, Hong J. Midlife and aging parents of adults with intellectual and developmental disabilities: impacts of lifelong parenting. Am J Intellect Dev Disabil. 2011;116(6):479–99.

    PubMed  PubMed Central  Article  Google Scholar 

  41. 41.

    Lu N, Liu J, Wang F, Lou VWQ. Caring for disabled older adults with musculoskeletal conditions: a transactional model of caregiver burden, coping strategies, and depressive symptoms. Arch Gerontol Geriatr. 2017;69:1–7.

    PubMed  Article  Google Scholar 

  42. 42.

    Grey JM, Totsika V, Hastings RP. Physical and psychological health of family carers co-residing with an adult relative with an intellectual disability. J Appl Res Intellect Disabil. 2018;31(Suppl 2):191–202.

    PubMed  Article  Google Scholar 

  43. 43.

    Kiosses DN, Klimstra S, Murphy C, Alexopoulos GS. Executive dysfunction and disability in elderly patients with major depression. Am J Geriatr Psychiatry. 2001;9(3):269–74.

    CAS  PubMed  Article  Google Scholar 

  44. 44.

    Formánek T, Kagström A, Cermakova P, Csémy L, Mladá K, Winkler P. Prevalence of mental disorders and associated disability: results from the cross-sectional CZEch mental health study (CZEMS). Eur Psychiatry J. 2019;60:1–6.

    Article  Google Scholar 

  45. 45.

    Maïano C, Coutu S, Tracey D, Bouchard S, Lepage G, Morin AJS, et al. Prevalence of anxiety and depressive disorders among youth with intellectual disabilities: a systematic review and meta-analysis. J Affect Disord. 2018;236:230–42.

    PubMed  Article  Google Scholar 

  46. 46.

    Bruce ML. Depression and disability in late life: directions for future research. Am J Geriatr Psychiatry. 2001;9(2):102–12.

    CAS  PubMed  Article  Google Scholar 

  47. 47.

    Solaro C, Trabucco E, Signori A, Martinelli V, Radaelli M, Centonze D, et al. Depressive symptoms correlate with disability and disease course in multiple sclerosis patients: an Italian multi-center study using the Beck depression inventory. PLoS One. 2016;11(9):e0160261.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  48. 48.

    Hughes RB, Nosek MA, Robinson-Whelen S. Correlates of depression in rural women with physical disabilities. J Obstet Gynecol Neonatal Nurs. 2007;36(1):105–14.

    PubMed  Article  Google Scholar 

  49. 49.

    Friedrich MJ. Depression is the leading cause of disability around the world. JAMA. 2017;317(15):1517.

    PubMed  Google Scholar 

  50. 50.

    Rondón MB. Salud mental: un problema de salud pública en el Perú. Rev Peru Med Exp Salud Publica. 2006;23(4):237–8.

    Google Scholar 

  51. 51.

    Guerra M, Ferri CP, Sosa AL, Salas A, Gaona C, Gonzales V, et al. Late-life depression in Peru, Mexico and Venezuela: the 10/66 population-based study. Br J Psychiatry. 2009;195(6):510–5.

    PubMed  PubMed Central  Article  Google Scholar 

  52. 52.

    Perú, Congreso de la Republica. Ley 30947: Ley de Salud Mental. Lima: El Peruano; 2019.

Download references


Not applicable.


This study was self-funded.

Author information




JJBM, ANSM, ACL, JPM and CJTH conceived the idea and conceptualized the study and design. ANSM and CJTH performed and reviewed the statistical analyses, respectively. All authors drafted the manuscript and approved the final version.

Corresponding author

Correspondence to Carlos J. Toro-Huamanchumo.

Ethics declarations

Ethics approval and consent to participate

Not applicable since this study involved the use of a previously published secondary database that is publicly available.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Barboza, J.J., Soriano-Moreno, A.N., Copez-Lonzoy, A. et al. Disability and severe depression among Peruvian older adults: analysis of the Peru Demographic and Family Health Survey, ENDES 2017. BMC Psychiatry 20, 253 (2020).

Download citation


  • Disabled persons
  • Depression
  • Mental health
  • Surveys and questionnaires
  • Peru