Hostname: page-component-8448b6f56d-qsmjn Total loading time: 0 Render date: 2024-04-20T00:43:58.778Z Has data issue: false hasContentIssue false

Late-life depression in sub-Saharan Africa: lessons from the Ibadan Study of Ageing

Part of: Editorials

Published online by Cambridge University Press:  20 July 2020

A. Ojagbemi*
Affiliation:
Department of Psychiatry, College of Medicine University of Ibadan, Ibadan, Nigeria
T. Bello
Affiliation:
Department of Psychiatry, College of Medicine University of Ibadan, Ibadan, Nigeria
O. Gureje
Affiliation:
Department of Psychiatry, College of Medicine University of Ibadan, Ibadan, Nigeria
*
Author for correspondence: Akin Ojagbemi, E-mail: drakinjagbemi@yahoo.com; aa.ojagbemi@ui.edu.ng
Rights & Permissions [Opens in a new window]

Abstract

The population surviving to old age in sub-Saharan Africa (SSA) is increasing rapidly in consonance with the rest of the world. Nevertheless, the sub-region offers unique challenges to survival across the lifespan. The determinants of health and ageing in SSA are thus likely different from those in higher income countries. The need to explore pressing epidemiological and health service challenges of older people living in SSA in the context of multiple social changes and rapid ageing of the population provided the rationale for the Ibadan Study of Ageing (ISA). This article appraises ISA findings in relation to late-life depression. It concludes that healthcare policies in SSA need to deliberately prioritise the treatment of depression and other mental health problems in late-life in order to stem the neglect of older people's mental health in the region.

Type
Editorial
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Introduction

The population surviving to old age is increasing rapidly in all regions of the world. The projection is that by 2050 approximately 80% of persons who will be ⩾60 years globally will be residents of low-/middle-income countries (LMICs), with approximately 212 million living in Africa (Dotchin et al., Reference Dotchin, Akinyemi, Gray and Walker2013). As with physical health, the burden of mental health conditions increases with age (World Health Organization, 2017).

Mental health conditions rank among the leading causes of years lived with disability (Eaton et al., Reference Eaton, Mccay, Semrau, Chatterjee, Baingana, Araya, Ntulo, Thornicroft and Saxena2011), and depression is the most common and disabling mental health condition after the age of 60 years (Whiteford et al., Reference Whiteford, Degenhardt, Rehm, Baxter, Ferrari, Erskine, Charlson, Norman, Flaxman, Johns, Burstein, Murray and Vos2013). Late-life depression is associated with complex comorbidities and chronic course of symptoms and disability (Haigh et al., Reference Haigh, Bogucki, Sigmon and Blazer2018; Ojagbemi et al., Reference Ojagbemi, Abiona, Luo and Gureje2018a). The disability-weight ascribed to late-life depression is set to increase in the coming few years (Whiteford et al., Reference Whiteford, Degenhardt, Rehm, Baxter, Ferrari, Erskine, Charlson, Norman, Flaxman, Johns, Burstein, Murray and Vos2013), with some observational studies (Gureje et al., Reference Gureje, Ogunniyi, Kola and Abiona2011) suggesting that compared with higher income countries (HICs), the disability-burden of late-life depression may be much higher in LMICs such as those in much of sub-Saharan Africa (SSA).

In contrast to reports from elsewhere (Savva et al., Reference Savva, Maty, Setti and Feeney2013; Darker et al., Reference Darker, Donnelly-Swift, Whiston, Moore and Barry2016), the social determinants of late-life depression in SSA may be different from those in HICs. In particular, the social, economic and health challenges faced by people living in SSA may present unique risks for the occurrence of depression among older people. For example, poverty, social deprivation, a high burden of infectious disease and a rapidly growing burden of non-communicable diseases in the sub-region (Cappuccio and Miller, Reference Cappuccio and Miller2016; Ojagbemi et al., Reference Ojagbemi, Bello, Luo and Gureje2017b) are potential risks for depression in old age. Major social changes in SSA, including those related to migration and urbanisation as well as the changing roles of women, are leading to the erosion of traditional multigenerational living arrangement. These factors, combined with the effects of globalisation, are changing the status of older people in the sub-region (United Nations, 2017; Ojagbemi and Gureje, Reference Ojagbemi and Gureje2019b) and stripping away traditional support systems. Older persons may be less equipped to cope with these challenges (Leigh-Hunt et al., Reference Leigh-Hunt, Bagguley, Bash, Turner, Turnbull, Valtorta and Caan2017; The Academy of Medical Sciences, 2018) and become increasingly exposed to social isolation and its effects (especially depression) (Ojagbemi and Gureje, Reference Ojagbemi and Gureje2019a; Ojagbemi and Gureje, Reference Ojagbemi and Gureje2019b). Furthermore, there are no formal social welfare packages for older people in many countries in SSA and access to healthcare is often limited and dictated by personal financial resources (Uwakwe et al., Reference Uwakwe, Ibeh, Modebe, Bo, Ezeama, Njelita, Ferri and Prince2009). The need to explore these pressing epidemiological, social and health challenges of older people living in SSA provided the rationale for the Ibadan Study of Ageing (ISA).

The Ibadan Study of Ageing

The ISA comprised two integrated components. An initial cross-sectional study that was conducted to determine the profile and availability of informal care for older persons in need of care was followed by a 5-year prospective observation of the same cohort to investigate key determinants of successful ageing in the population. The integration of both phases allowed for the examination of both cross-sectional and longitudinal relationships among social, psychological and physical health indices. The main hypothesis of the ISA was that factors reflecting social changes associated with the adoption of ‘modern’ lifestyles will be associated with ageing outcomes in Nigeria.

The ISA cohort comprised persons who were 65 years or older living in households within communities spread across the Yoruba-speaking south-west and north-central regions of Nigeria (or nearly a quarter of the Nigerian population at the time of the study). Notably, Nigeria is the African country with the largest population. Selection of respondents was done using a multistage cluster sampling of local government areas (LGAs), followed by enumeration areas (geographical units demarcated by the National Population Commission) within the LGAs, and households in the enumeration areas.

Households included in the ISA were randomly generated from a computer listing of all eligible households in the selected enumerated areas. When the household had more than one eligible person, the eligible respondent per household was selected using the Kish method (Kish, Reference Kish1949). In cases where the person so selected refused to participate, no replacement was chosen in the same household.

National representativeness of the ISA sample was achieved through the application of poststratification sampling weights in accordance with the stratified multistage sampling procedures (Bell et al., Reference Bell, Onwuegbuzie, Ferron, Jiao, Hibbard and Kromrey2012). Common sources of sampling bias (e.g., non-response and chance) were examined by comparing age and gender categories with those of the Nigerian national population while adjusting for differences between the sample and the total Nigerian population (Brick and Kalton, Reference Brick and Kalton1996). The ISA is thus the largest community-based prospective observation of the health and wellbeing of older persons in SSA.

The highly successful study has produced over 30 publications which have generated a wealth of information about the mental health of older people living in SSA. This article appraises ISA findings and lessons learnt in relation to late-life depression.

Late-life depression in the ISA

Major depressive disorder (MDD) was assessed with the fully structured World Health Organization (WHO) Composite International Diagnostic Interview (CIDI) (Kessler et al., Reference Kessler, Abelson, Demler, Escobar, Gibbon, Guyer, Howes, Jin, Vega, Walters, Wang, Zaslavsky and Zheng2004). The diagnosis was made on the basis of the criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) (American Psychiatric Association, 1994).

Additional quantitative assessment of depression symptoms was conducted using the 30-item Geriatric Depression Scale (GDS) (Yesavage et al., Reference Yesavage, Brink, Rose, Lum, Huang, Adey and Leirer1982). The GDS was developed specifically for use in older populations (Yesavage et al., Reference Yesavage, Brink, Rose, Lum, Huang, Adey and Leirer1982), and has been used extensively among Yoruba Nigerians where cut-off scores of ⩾11 had a κ agreement of 0.65 with psychiatrist diagnosed depression (Sokoya and Baiyewu, Reference Sokoya and Baiyewu2003).

Main findings in relation to late-life MDD

High prevalence and incidence

Epidemiological studies of late-life depression in HICs (Thielke et al., Reference Thielke, Diehr and Unutzer2010) as well as in LMICs (Guerra et al., Reference Guerra, Prina, Ferri, Acosta, Gallardo, Huang, Jacob, Jimenez-Velazquez, Llibre Rodriguez, Liu, Salas, Sosa, Williams, Uwakwe and Prince2016) report widely varying prevalence estimates. Community-based studies using standardised criteria such as the ICD 10 and DSM IV for clinically significant depression report an average prevalence of 3% (Goncalves-Pereira et al., Reference Goncalves-Pereira, Prina, Cardoso, Da Silva, Prince and Xavier2019). Rates of late-life depressive episodes (Guerra et al., Reference Guerra, Prina, Ferri, Acosta, Gallardo, Huang, Jacob, Jimenez-Velazquez, Llibre Rodriguez, Liu, Salas, Sosa, Williams, Uwakwe and Prince2016) and MDD (Bromet et al., Reference Bromet, Andrade, Hwang, Sampson, Alonso, De Girolamo, De Graaf, Demyttenaere, Hu, Iwata, Karam, Kaur, Kostyuchenko, Lepine, Levinson, Matschinger, Mora, Browne, Posada-Villa, Viana, Williams and Kessler2011) are observed to be higher in LMICs than in HICs, and in nearly all cases, the prevalence of clinically significant late-life depression is higher for women than for men and in rural locations than urban centres (Bromet et al., Reference Bromet, Andrade, Hwang, Sampson, Alonso, De Girolamo, De Graaf, Demyttenaere, Hu, Iwata, Karam, Kaur, Kostyuchenko, Lepine, Levinson, Matschinger, Mora, Browne, Posada-Villa, Viana, Williams and Kessler2011; Guerra et al., Reference Guerra, Prina, Ferri, Acosta, Gallardo, Huang, Jacob, Jimenez-Velazquez, Llibre Rodriguez, Liu, Salas, Sosa, Williams, Uwakwe and Prince2016). By global standards, the ISA recorded high prevalence and incidence of late-life MDD. Lifetime and 12-month prevalence estimates were 26.2% [95% confidence interval (CI) 24.3–28.2] and 7⋅1% (95% CI 5.9–8.3), respectively (Gureje et al., Reference Gureje, Kola and Afolabi2007). Mean age at onset of MDD was 51 years for both men and women. The mean number of lifetime episodes was approximately two. When assessed in three follow-up waves over a period of 5 years (Ojagbemi et al., Reference Ojagbemi, Bello and Gureje2018b), the incidence rate of MDD of 120.9 per 1000 person years (95% CI 110.4–132.5) was found among 1394 persons who were free of lifetime MDD and dementia at baseline. Incidence rates were 94.7 (95% CI 82.5–108.7) and 153.8 (95% CI 136.3–173.6) per 1000 person years in men and women, respectively (Ojagbemi et al., Reference Ojagbemi, Bello and Gureje2018b).

Social nature of risk factors

Late-life MDD is consistently associated with economic, health and lifestyle factors in HICs (Goncalves-Pereira et al., Reference Goncalves-Pereira, Prina, Cardoso, Da Silva, Prince and Xavier2019). These factors have also been significantly linked with depression in older adults living in LMICs (Lotfaliany et al., Reference Lotfaliany, Hoare, Jacka, Kowal, Berk and Mohebbi2019). The risk factors for MDD in the ISA were mainly social in nature. For example, prevalent MDD was associated with poor social engagement (Ojagbemi and Gureje, Reference Ojagbemi and Gureje2019a), loneliness (Ojagbemi and Gureje, Reference Ojagbemi and Gureje2019a) and increasing level of urbanisation in the place of residence (Gureje et al., Reference Gureje, Kola and Afolabi2007) with odds ratios (OR) of 3.1, 2.3 and 1.4, respectively. Overall, poor social network was a key modifiable risk factor for incident MDD (Gureje et al., Reference Gureje, Ogunniyi, Kola and Abiona2011; Ojagbemi et al., Reference Ojagbemi, Bello and Gureje2018b). Specifically, living in a rural location and having no regular contact with family (both of which can be regarded as indicators of poor social network) at baseline were associated with subsequent onset of MDD (Gureje et al., Reference Gureje, Ogunniyi, Kola and Abiona2011; Ojagbemi et al., Reference Ojagbemi, Bello and Gureje2018b). One plausible interpretation of this finding is that the migration of younger family members to areas with better economic opportunities may be reducing the social network of elderly persons living in affected communities. Those who are unable to maintain regular contacts with migrated family members may be especially at risk of MDD.

The well-known relationship between low economic position and late-life depression in HICs (Goncalves-Pereira et al., Reference Goncalves-Pereira, Prina, Cardoso, Da Silva, Prince and Xavier2019) was not replicated in the ISA with the use of asset-based measurement of economic status, a commonly used indicator of wealth in low-income settings (Ferguson et al., Reference Ferguson, Tandon, Gakidou, Murray and Evans2003). Nevertheless, incident MDD was associated with a lifetime of unskilled occupation in men (Ojagbemi et al., Reference Ojagbemi, Bello and Gureje2018b). Perhaps, this finding suggests that composite indices of economic position such as lifetime occupational attainment, which embraces education, longer term income, social status and potential for asset acquisition over-time, may be more stable and sensitive to capture longer term economic effect of late-life depression in SSA and other LMIC settings. For example, in many SSA locations with large subsistent farming populations, less stable measures of economic position may exhibit seasonal fluctuations. The health advantages of longer term and relatively stable economic status may accumulate over the life-course (Mensah and Hobcraft, Reference Mensah and Hobcraft2008) and lead to a significant protective effect against the onset of MDD in old age (Kim and Durden, Reference Kim and Durden2007; Lahelma et al., Reference Lahelma, Pietilainen, Chandola, Hyde, Rahkonen and Lallukka2019).

Outcomes of late-life MDD

Similar to reports from both HICs (Goncalves-Pereira et al., Reference Goncalves-Pereira, Prina, Cardoso, Da Silva, Prince and Xavier2019) and LMICs (Guerra et al., Reference Guerra, Prina, Ferri, Acosta, Gallardo, Huang, Jacob, Jimenez-Velazquez, Llibre Rodriguez, Liu, Salas, Sosa, Williams, Uwakwe and Prince2016), ISA participants with MDD had impaired quality of life and functioning in home, work and social roles. These outcomes worsened with increasing MDD symptoms severity (Gureje et al., Reference Gureje, Kola and Afolabi2007). Also, in pair-wise comparisons with arthritis, spinal pain, systemic hypertension, asthma and diabetes mellitus, late-life MDD in the ISA was associated with greater disability burden than the listed health conditions (Gureje et al., Reference Gureje, Ademola and Olley2008). Specifically, approximately 47.2% of ISA participants with late-life MDD were rated as having a severe disability (Gureje et al., Reference Gureje, Ademola and Olley2008). Conversely, severe disability among those with systemic hypertension, chronic spinal pain and arthritis was 25, 24.2 and 20.6%, respectively (Gureje et al., Reference Gureje, Ademola and Olley2008). Late-life MDD comorbidity with the listed conditions was also very high at 61.7% overall (Ojagbemi et al., Reference Ojagbemi, Bello, Luo and Gureje2017a), with angina (28.2%) and uncorrected vision impairment (24.7%) (Ojagbemi et al., Reference Ojagbemi, Bello, Luo and Gureje2017a) standing out as the most comorbid health conditions with late-life MDD.

Access to MDD treatment rates was low (Gureje et al., Reference Gureje, Kola and Afolabi2007), and only about 37% of ISA respondents with a lifetime history of MDD received any treatment (orthodox, traditional or religious). Low economic status and residence in a rural area were associated with lack of treatment. For those who received these treatments, there was a mean delay of 5 years from the onset of MDD to receipt of first treatment (Gureje et al., Reference Gureje, Kola and Afolabi2007).

Symptomatic recovery from late-life MDD was possible, but this was commonly associated with persisting and worsening course of functional disability (ADL). In mixed-effect linear regression models constructed across 5 years of observation and adjusted for the effect of age, gender and socioeconomic status, ADL worsened in both respondents who recovered symptomatically from MDD [coefficient (β) = 1.0, 95% CI 0.2–1.8] and those who failed to achieve symptoms recovery (β = 2.3, 95% CI 1.6–3.0) (Ojagbemi et al., Reference Ojagbemi, Abiona, Luo and Gureje2018a).

Implication, recommendations and future directions

The ISA findings in relation to late-life MDD have important implications especially in the context of on-going social transitions in Nigeria and SSA. For example, changes that lead to attenuation of traditional supportive networks may be stripping older people in the setting of the ISA of protective buffers against depression. Previously, traditional gender roles were fairly well defined in the Nigerian contexts. Men are known to work outside the home and women to take up the role of ‘home making’ and provide emotional support to vulnerable family members (Adeleye et al., Reference Adeleye, Aldoory and Parakoyi2011). Changes that encourage women, who are the most common caregivers, to find jobs outside the home have the unintended consequence of exposing older persons in these settings to social isolation and its effects (especially depression) (Ojagbemi and Gureje, Reference Ojagbemi and Gureje2019a; Ojagbemi and Gureje, Reference Ojagbemi and Gureje2019b).

Results suggesting high prevalence and incidence, as well as poor access to late-life depression treatments in Nigeria, a situation that is likely to be applicable to other countries in SSA, highlight the public health challenge posed by MDD in the sub-region. Health systems in SSA are highly focused on physical health conditions, especially conditions with acute presentations, and less likely attuned to provide chronic care. In these circumstances, older people with mental health conditions are particularly disadvantaged in the competition for the scarce healthcare resources. Given the projected rapid increase in the population of older people in SSA, the common focus on acute physical health conditions, to the neglect of mental health, may become even more pronounced as greater demands are placed on the weak healthcare systems as a result of rapidly growing populations. To stem the neglect of older people's mental health in SSA, it is important for healthcare policies to specifically pay attention to the detection and treatment of depression and other mental health problems in late-life in primary health care settings.

The findings of the ISA suggesting that the disability associated with late-life depression persists despite symptomatic recovery also have implications for policy as well as for needed guidelines for the management of both depression and disability in older people. For example, future guidelines for the treatment of late-life MDD could consider a programme of rehabilitation for any resulting functional disability.

Conclusion

The ISA provides ground-breaking information about late-life depression in SSA. Many of the findings are currently the basis for the design of clinical trials of tailored interventions for late-life MDD in SSA. The ISA opens up opportunities for further explorations of the data, leads for future research and avenues for collaborations that offer the prospect of advancing our knowledge of factors that shape the lived experience of depression in later life.

Acknowledgement

The Ibadan Study of Ageing team.

Financial support

The Ibadan Study of Ageing was supported by the Wellcome Trust (grant no: WT079662MF).

Conflict of interest

None.

References

Adeleye, OA, Aldoory, L and Parakoyi, DB (2011) Using local culture and gender roles to improve male involvement in maternal health in southern Nigeria. Journal of Health Communication 16, 11221135.CrossRefGoogle ScholarPubMed
American Psychiatric Association (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th Edn.Washington, DC: American Psychiatric Association.Google Scholar
Bell, BA, Onwuegbuzie, AJ, Ferron, JM, Jiao, QG, Hibbard, ST and Kromrey, JD (2012) Use of design effects and sample weights in complex health survey data: a review of published articles using data from 3 commonly used adolescent health surveys. American Journal of Public Health 102, 13991405.CrossRefGoogle ScholarPubMed
Brick, JM and Kalton, G (1996) Handling missing data in survey research. Statistical Methods in Medical Research 5, 215238.CrossRefGoogle ScholarPubMed
Bromet, E, Andrade, LH, Hwang, I, Sampson, NA, Alonso, J, De Girolamo, G, De Graaf, R, Demyttenaere, K, Hu, C, Iwata, N, Karam, AN, Kaur, J, Kostyuchenko, S, Lepine, JP, Levinson, D, Matschinger, H, Mora, ME, Browne, MO, Posada-Villa, J, Viana, MC, Williams, DR and Kessler, RC (2011) Cross-national epidemiology of DSM-IV major depressive episode. BMC Medicine 9, 90.CrossRefGoogle ScholarPubMed
Cappuccio, FP and Miller, MA (2016) Cardiovascular disease and hypertension in sub-Saharan Africa: burden, risk and interventions. Internal and Emergency Medicine 11, 299305.CrossRefGoogle ScholarPubMed
Darker, CD, Donnelly-Swift, E, Whiston, L, Moore, F and Barry, JM (2016) Determinants of self-rated health in an Irish deprived suburban population – a cross sectional face-to-face household survey. BMC Public Health 16, 767.CrossRefGoogle Scholar
Dotchin, CL, Akinyemi, RO, Gray, WK and Walker, RW (2013) Geriatric medicine: services and training in Africa. Age Ageing 42, 124128.CrossRefGoogle ScholarPubMed
Eaton, J, Mccay, L, Semrau, M, Chatterjee, S, Baingana, F, Araya, R, Ntulo, C, Thornicroft, G and Saxena, S (2011) Scale up of services for mental health in low-income and middle-income countries. The Lancet 378, 15921603.CrossRefGoogle ScholarPubMed
Ferguson, B, Tandon, A and Gakidou, E (2003) Estimating permanent income using indicator variables. In Murray, C and Evans, D (eds), Health Systems Performance Assessment: Diabetes, Methods and Empiricism. Geneva: World Health Organisation, pp. 747760.Google Scholar
The Academy of Medical Sciences (2018) Challenges and Priorities of Global Mental Health in the Sustainable Development Goals (SDG) Era (Workshop Report). In Global Mental Health (ed.), London, United Kingdom: The Academy of Medical Sciences.Google Scholar
Goncalves-Pereira, M, Prina, AM, Cardoso, AM, Da Silva, JA, Prince, M, Xavier, M and WORKGROUP IN, P (2019) The prevalence of late-life depression in a Portuguese community sample: a 10/66 Dementia Research Group study. Journal of Affective Disorders 246, 674681.CrossRefGoogle Scholar
Guerra, M, Prina, AM, Ferri, CP, Acosta, D, Gallardo, S, Huang, Y, Jacob, KS, Jimenez-Velazquez, IZ, Llibre Rodriguez, JJ, Liu, Z, Salas, A, Sosa, AL, Williams, JD, Uwakwe, R and Prince, M (2016) A comparative cross-cultural study of the prevalence of late life depression in low and middle income countries. Journal of Affective Disorders 190, 362368.CrossRefGoogle ScholarPubMed
Gureje, O, Kola, L and Afolabi, E (2007) Epidemiology of major depressive disorder in elderly Nigerians in the Ibadan Study of Ageing: a community-based survey. The Lancet 370, 957964.CrossRefGoogle ScholarPubMed
Gureje, O, Ademola, A and Olley, BO (2008) Depression and disability: comparisons with common physical conditions in the Ibadan study of aging. Journal of the American Geriatric Society 56, 20332038.CrossRefGoogle ScholarPubMed
Gureje, O, Ogunniyi, A, Kola, L and Abiona, T (2011) Incidence of and risk factors for dementia in the Ibadan study of aging. Journal of the American Geriatric Society 59, 869874.CrossRefGoogle ScholarPubMed
Haigh, EAP, Bogucki, OE, Sigmon, ST and Blazer, DG (2018) Depression among older adults: a 20-year update on five common myths and misconceptions. American Journal of Geriatric Psychiatry 26, 107122.CrossRefGoogle ScholarPubMed
Kessler, RC, Abelson, J, Demler, O, Escobar, JI, Gibbon, M, Guyer, ME, Howes, MJ, Jin, R, Vega, WA, Walters, EE, Wang, P, Zaslavsky, A and Zheng, H (2004) Clinical calibration of DSM-IV diagnoses in the World Mental Health (WMH) version of the World Health Organization (WHO) Composite International Diagnostic Interview (WMHCIDI). International Journal of Methods Psychiatric Research 13, 122139.CrossRefGoogle Scholar
Kim, J and Durden, E (2007) Socioeconomic status and age trajectories of health. Social Science and Medicine 65, 24892502.CrossRefGoogle ScholarPubMed
Kish, L (1949) A procedure for objective respondent selection within the household. Journal of the American Statistical Association 247, 380387.CrossRefGoogle Scholar
Lahelma, E, Pietilainen, O, Chandola, T, Hyde, M, Rahkonen, O and Lallukka, T (2019) Occupational social class trajectories in physical functioning among employed women from midlife to retirement. BMC Public Health 19, 1525.CrossRefGoogle Scholar
Leigh-Hunt, N, Bagguley, D, Bash, K, Turner, V, Turnbull, S, Valtorta, N and Caan, W (2017) An overview of systematic reviews on the public health consequences of social isolation and loneliness. Public Health 152, 157171.CrossRefGoogle ScholarPubMed
Lotfaliany, M, Hoare, E, Jacka, FN, Kowal, P, Berk, M and Mohebbi, M (2019) Variation in the prevalence of depression and patterns of association, sociodemographic and lifestyle factors in community-dwelling older adults in six low- and middle-income countries. Journal of Affective Disorders 251, 218226.CrossRefGoogle ScholarPubMed
Mensah, FK and Hobcraft, J (2008) Childhood deprivation, health and development: associations with adult health in the 1958 and 1970 British prospective birth cohort studies. Journal of Epidemiology and Community Health 62, 599606.CrossRefGoogle ScholarPubMed
Ojagbemi, A and Gureje, O (2019 a) Social relationships and the association of loneliness with major depressive disorder in the Ibadan study of aging. World Social Psychiatry 1, 8288.Google Scholar
Ojagbemi, A and Gureje, O (2019 b) Typology of social network structures and late-life depression in low- and middle-income countries. Clinical Practice and Epidemiology in Mental health 15, 134142.CrossRefGoogle ScholarPubMed
Ojagbemi, A, Bello, T, Luo, Z and Gureje, O (2017 a) Chronic conditions, new onset, and persistent disability in the Ibadan study of aging. The Journals of Gerontology Series A Biological Sciences and Medical Sciences 72, 9971005.CrossRefGoogle ScholarPubMed
Ojagbemi, A, Bello, T, Luo, Z and Gureje, O (2017 b) Living conditions, low socioeconomic position, and mortality in the Ibadan study of aging. The Journals Gerontology Series B Psychological Sciences and Social Sciences 72, 646655.Google ScholarPubMed
Ojagbemi, A, Abiona, T, Luo, Z and Gureje, O (2018 a) Symptomatic and functional recovery from major depressive disorder in the Ibadan study of ageing. American Journal of Geriatric Psychiatry 26, 657666.CrossRefGoogle ScholarPubMed
Ojagbemi, A, Bello, T and Gureje, O (2018 b) Gender differential in social and economic predictors of incident major depressive disorder in the Ibadan Study of Ageing. Social Psychiatry and Psychiatric Epidemiology 53, 351361.CrossRefGoogle ScholarPubMed
Savva, GM, Maty, SC, Setti, A and Feeney, J (2013) Cognitive and physical health of the older populations of England, the United States, and Ireland: international comparability of the Irish Longitudinal Study on Ageing. Journal of the American Geriatric Society 61(suppl. 2), S291S298.CrossRefGoogle ScholarPubMed
Sokoya, OO and Baiyewu, O (2003) Geriatric depression in Nigerian primary care attendees. International Journal of Geriatric Psychiatry 18, 506510.CrossRefGoogle ScholarPubMed
Thielke, SM, Diehr, P and Unutzer, J (2010) Prevalence, incidence, and persistence of major depressive symptoms in the Cardiovascular Health Study. Aging and Mental Health 14, 168176.CrossRefGoogle ScholarPubMed
United Nations (2017) The International Migration Report 2017. Geneva: United Nations.Google Scholar
Uwakwe, R, Ibeh, CC, Modebe, AI, Bo, E, Ezeama, N, Njelita, I, Ferri, CP and Prince, MJ (2009) The epidemiology of dependence in older people in Nigeria: prevalence, determinants, informal care, and health service utilization. A 10/66 dementia research group cross-sectional survey. Journal of the American Geriatrics Society 57, 16201627.CrossRefGoogle ScholarPubMed
Whiteford, HA, Degenhardt, L, Rehm, J, Baxter, AJ, Ferrari, AJ, Erskine, HE, Charlson, FJ, Norman, RE, Flaxman, AD, Johns, N, Burstein, R, Murray, CJ and Vos, T (2013) Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet 382, 15751586.CrossRefGoogle ScholarPubMed
World Health Organization (2017) Mental health of older adults. Fact Sheets. Geneva: World Health Organization.Google Scholar
Yesavage, JA, Brink, TL, Rose, TL, Lum, O, Huang, V, Adey, M and Leirer, VO (1982) Development and validation of a geriatric depression screening scale: a preliminary report. Journal of Psychiatric Research 17, 3749.CrossRefGoogle ScholarPubMed