Predictors of depression and malnutrition among older persons attending primary healthcare centres in South Western Nigeria

Babatunde Akodu; Samuel Akinwunmi; Temitope Ladi-Akinyemi; Ibukunoluwa Baiyeroju; Adebayo Onajole

doi:10.4103/jcls.jcls_24_22

ORIGINAL RESEARCH REPORT

Year : 2023 | Volume : 20 | Issue : 1 | Page : 22-29

Predictors of depression and malnutrition among older persons attending primary healthcare centres in South Western Nigeria

Babatunde Akodu¹, Samuel Akinwunmi², Temitope Ladi-Akinyemi², Ibukunoluwa Baiyeroju³, Adebayo Onajole²
¹ Department of Community Health and Primary Care, Faculty of Clinical Sciences, College of Medicine, University of Lagos and Lagos University Teaching Hospital; Department of Family Medicine, Lagos University Teaching Hospital, Idi-Araba, Lagos, Nigeria
² Department of Community Health and Primary Care, Faculty of Clinical Sciences, College of Medicine, University of Lagos and Lagos University Teaching Hospital, Idi-Araba, Lagos, Nigeria
³ Department of Family Medicine, Lagos University Teaching Hospital, Idi-Araba, Lagos, Nigeria

Date of Submission	04-Mar-2022
Date of Acceptance	01-Mar-2023
Date of Web Publication	29-Mar-2023

Correspondence Address:
Dr. Babatunde Akodu
Department of Community Health and Primary Care, Faculty of Clinical Sciences, College of Medicine, University of Lagos and Lagos University Teaching Hospital, Idi-Araba, Lagos
Nigeria

Source of Support: None, Conflict of Interest: None

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DOI: 10.4103/jcls.jcls_24_22

Abstract

Background: Malnutrition and depression have been found to be prevalent in the older persons and often lead to preventable adverse complications. Depression has been shown to be associated with malnutrition. This study was aimed at determining the predictors of depression and malnutrition among older persons attending selected primary health-care centers (PHC) in Kosofe local government area in Lagos, Nigeria. Methods: This was a descriptive cross-sectional study carried out among older persons attending PHC in Kosofe local government, Lagos. A multi-stage random technique was used to select the 219 participants from the PHC centers. Data were collected using a structured interviewer-administered questionnaire and analyzed using Epi Info 7.1. Chi-square was used to test the association between Socio-demographic characteristics and nutritional status, body mass index and depression, and one-way ANOVA was used to test for the association between anthropometric parameters and malnutrition. Associations were statistically significant if P < 0.05. Results: It was found that 57.9% were malnourished or at risk of malnutrition. The study showed that 47.1% of the participants were depressed. There was a significant association (<0.001) between the malnutrition and the level of depression. There was a statistically significant association between family support (P ≤ 0.001), malnutrition (P ≤ 0.001), and depression. There was statistically significant association between the height (P = 0.009), weight (P = 0.001), waist–hip ratio (P = 0.036), and the malnutrition. Remarkably, there was statistically significant association between the waist (P = 0.023) and hip circumference (P = 0.047) and their level of depression. Conclusion: The results from this study revealed a high prevalence of malnutrition and depression among older persons. Therefore, health providers working in PHC centers should have a high index of suspicion for depression among older persons with malnutrition.

Keywords: Anthropometry, depression, malnutrition, nutritional status, older persons, primary healthcare

How to cite this article:
Akodu B, Akinwunmi S, Ladi-Akinyemi T, Baiyeroju I, Onajole A. Predictors of depression and malnutrition among older persons attending primary healthcare centres in South Western Nigeria. J Clin Sci 2023;20:22-9

How to cite this URL:
Akodu B, Akinwunmi S, Ladi-Akinyemi T, Baiyeroju I, Onajole A. Predictors of depression and malnutrition among older persons attending primary healthcare centres in South Western Nigeria. J Clin Sci [serial online] 2023 [cited 2023 Jun 2];20:22-9. Available from: https://www.jcsjournal.org/text.asp?2023/20/1/22/372687

Introduction

Depression is defined by the WHO as “a common mental disorder, characterized by sadness, loss of interest or pleasure, feeling of guilt or low self-worth, disturbed sleep or appetite, feeling of tiredness and poor concentration.”^[1] The overall prevalence of malnutrition in older persons in the developed world is about 22.6%, with the National Institute of Mental Health estimating that about 16.2 million adults have one major depression episode in the united states with about 4.8% in people 50 and above.^[2] About 38% of the malnourished or at risk of being malnourished in older persons dwell in the community.

Nutrition has also been linked with depression, diet lacking in foods such as carbohydrate, proteins (amino acids), omega-3 fatty acid, B-complex vitamins, Vitamin B12, folate, calcium, chromium, iodine, iron, lithium, selenium, and zinc.^[3],[4] Food rich in omega-3 that has antidepressant effect and its absence or low intake is linked with dementia. A decrease dietary folate has been linked with depression.^[3] A study in KwaZulu-Natal,^[5] South Africa using mini-nutritional assessment (MNA) tool discovered that the prevalence of malnutrition was 54 (5.5%) and the risk was 427 (43.4%). It was a cross-sectional study done at 3 areas in KwaZulu-Natal using the community, interviewer administered, it was done on 984 of which the men were 224 people and the women were 760 in number, with about 978 (99.4%) being Africans. The mean age of the study was 68.9 ± 7.4. The study showed that men were more malnourished or at risk of being malnourished with about 58% affected by one form of food insecurity or the other. It was also discovered that does that spent a lot of time indoors were malnourished or at risk of malnutrition.

The general outpatient department of university college hospital Ibadan,^[6] carried out a cross-sectional study on 500 consecutively presenting participants using the MNA tool and body mass index (BMI). It was discovered that 61.9% had nutritional problems with about 7.8% malnourished, associations were found with marital status, occupation, rectal bleeding, oral problems, age, sex, and BMI.

In Uyo, Nigeria, a cross-sectional study was carried out to screen for the presence of depression in older persons at the University of Uyo Teaching Hospital, using 310 participants using the geriatric depression scale (GDS), 177 (57.1%) of the participants were females.^[7] A proportion of 42.9% was depressed. A comparative study in India demonstrated that there was a significant association between nutritional status and height, weight, waist and hip circumference.^[8]

The aim of this study was to determine the predictors of depression and malnutrition among the older persons attending primary health-care centers (PHCs) in Kosofe Local Government, Lagos Nigeria.

Methods

The study was carried out at PHC in Kosofe Local Government, Lagos. Kosofe local government consists of two local council development areas (LCDAs) following its division in 2003 by the Lagos state government. The two LCDAs are Agboyi-Ketu LCDA and Ikoso-Isheri LCDA. The study was done in 2 of the 12 PHC in Kosofe local government. The study was carried out using a cross-sectional descriptive design to assess the nutritional status, anthropometric parameters, and depression among older persons aged 60 years and above attending PHC in Kosofe.

The study was carried out among the older persons (60 and above). Older persons with dementia or a known mental disorder were excluded.

Sample size determination

The minimum sample size was estimated using Cochran's formula as stated below:

Where n denotes sample size when the population is more than 10,000, z refers to standard normal deviate at 95% confidence interval (CI) which is equivalent to 1.96, P stands for the prevalence of depression attribute which is 0.63.^[10] Extrapolation of q from (1 − P) gave 0.37. The acceptable margin of sampling error, d, (0.5%) was 0.05. Therefore, employing the variables in the formula, the sample size was n = (1.96² × 0.63 × 0.37) ÷ 0.05² = 358

Since n < 10,000, then the formula used to perform finite correction for sample size was

Where n_f denotes desired sample size (when target population is < 10,000). Data retrieved from PHC attendance register showed that about 500 patients aged 60 and above visit from both PHCs in 2 months. Therefore, using the formula, n_f = 358 ÷ (1 + 358/500) to calculate minimum sample size, a total of 208 was arrived at as the minimum sample size (n) for study. However, a total of 219 participants were selected for the study.

Sampling technique

Data were collected using a multi-stage sampling technique.

Stage 1: Selection of local government area (LGA)

Stage 2: Selection of LCDA

Stage 3: Selection of PHCs

Stage 4: Selection of participants.

Data analysis

Data were collected in November and December 2018 and analyzed using Epi Info software Version 7.1 created by the Centre for Disease Control, Atlanta, Georgia. Proportions, means, and frequencies were calculated and presented with charts and tables. Chi-square was used to test the association between Socio-demographic characteristics and malnutrition, BMI, and depression and one-way ANOVA was used to test for the association between Anthropometric parameters and Malnutrition. Associations were statistically significant if P < (0.05).

Sociodemographic characteristics and anthropometry

Descriptive statistics were used to describe the sociodemographic characteristics of the respondents. Appropriate charts were used to illustrate categorical variables. The anthropometric parameters measured included height, weight, BMI, waist circumference, hip circumference, and waist–hip ratio. BMI values were calculated as weight (kg) ÷ height² (m²). BMI values of lower than 18.4 were regarded as underweight, 18.5–24.9 were considered normal, 25.0–29.9 as overweight, 30–39.9 as obese, 40 and above as morbidly obese.^[11] Waist–hip ratio was calculated by dividing the waist by hip circumference. Values above 0.90 for male or 0.85 for female was indicative of abdominal obesity.^[12]

Nutritional status was assessed using an adapted MNA questionnaire. Each question was scored using 0, 1, 2, 3 depending on the question with a total score of 13. Any summation of scores between 11 and 13 was assumed to be normal nutrition, 7–10 was at risk of malnutrition and 0–6 is malnourished.^[13],[14] Depression was assessed using the GDS. One point was given for every “YES” apart from the number 1, 5, 7, and 11. This made a total of 15 points, a score of 1–5 was considered normal, 6–9 was mildly depressed and a score of 10–15 was seen as very depressed.^[14]

Nutritional assessment

MNA Short Form (MNA-SF) has a sensitivity of 89% and a specificity of 83%, a strong positive predictive ability (Youden index = 0.70) and some studies that have been done and show an internal consistency and inter-observer reliability to range from 0.51 to 0.89.^[15] This tool was used by an Iranian and German researchers.^{[16],[17],[18]}

Geriatric depression assessment

GDS-SF is made up of 15 questions. The correlation of GDS-30 (Pearson) with GDS-15 was r = 0.966 (P < 0.001), the analysis performed considering Diagnostic and Statistical Manual of Mental Disorders 5^th Edition criteria revealed that the sensitivity, specificity, positive predictive value, and negative predictive value of GDS-15 in determining depression were 92%, 91%, 76%, and 97%, respectively.^[7] The area under the receiver operating characteristics curve (95% CI) was 0.97 (95% CI = 0.947–0.996) for GDS-15 (P < 0.001). This tool was used by some researchers.^{[10],[16],[18]}

Ethical consideration

Ethical consideration was gotten from the health research and ethics committee of Lagos university teaching hospital with assigned number ADM/DCST/HREC/APP/282. Participants were informed of the purpose of the study and informed verbal consent was obtained from each of the participants before administering the questionnaires.

Results

A total of 219 elderly participated in the study, majority of them (68.35%) were within the ages of 60 and 69 years with a mean age of 68 and the standard deviation (SD) of 7.3. in this study, 77.63% of them were females, majority (80.37%) were Yoruba, 63.47% were married, 61.19% were Christians and 46.12% had attended secondary school [Table 1].

Table 1: Sociodemographic characteristics of participants

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This study found that 42.0% had normal nutrition, 58.0% had poor nutrition, which was further sub-classified into the group at risk of malnutrition (49.8%) and those malnourished (8.2%).

The proportion of the elderly that were severely depressed, mildly depressed, and not depressed were 11.0%, 36.0%, and 53%, respectively.

Majority were females (58.3%) and within the ages 60–69 years (58.3%); and female sex was found to be associated with malnutrition (P = 0.048). There was statistically significant association between female sex (P = 0.027), secondary school educational qualification (P = 0.049) of participants, and BMI [Table 2].

Table 2: Association between sociodemographic characteristics and malnutrition

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For family support, participants with children and grandchildren constituted 61.9% and an association was found between having children and grandchildren and being overweight and obese. A significant proportion of the participants who were obese (22.5%) and overweight (25.) were self-employed. There was statistically significant association between the BMI and being self-employed (P = 0.003). As well as between the BMI and family support from children and grandchildren (P = 0.002) [Table 3].

Table 3: Association between sociodemographic characteristics and body mass index

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Sixty-four participants whose ages were between 60 and 69 years were more at risk of mild and severe depression (P = 0.001), 86 female participants were shown to be depressed, while 55 participants who were widows had depression. Participants without income and those with low income were depressed. Majority (73.7%), who lived with their spouse and those who had family support from self and spouse had no depression. A significant proportion of the participants with risk of malnutrition (54.3%) had mild and severe depression. Statistically significant associations exist between participants within ages 60 and 69 years (P < 0.001), female sex (P = 0.024), being a widow (P < 0.001), without formal educational, and depression as depicted in [Table 4]. Statistically significant associations were also found between participants with no income and low-income monthly income (P ≤ 0.001), those living with their spouses (P = 0.002) and depression. Also depicted in the table was a statistically significant association between Depression and family support (P ≤ 0.001); as well as depression and malnutrition (P ≤ 0.001).

Table 4: Association between sociodemographic characteristics, malnutrition, and depression

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The mean waist circumference and SD were 79.8 ± 14.1 and 92.3 ± 17.2 for participants who were malnourished and at risk of malnutrition, respectively. The mean hip circumference and SD were 96.1 ± 15.1 and 109.4 ± 19.5 for participants who were malnourished and at risk of malnutrition respectively while for the waist-hip ratio, the mean and SD for the participants who were malnourished and at risk of malnutrition were 0.82 ± 0.081 and 0.84 ± 0.065, respectively. Statistically significant association was found between the height (P = 0.009), weight (P = 0.001), waist circumference (P < 0.001), hip circumference (P = 0.003), waist–hip ratio (P = 0.036), and malnutritional. Furthermore, there was a statistically significant difference between the waist (P = 0.024) and hip circumference (P = 0.048) and their level of depression [Table 5].

Table 5: Comparison of anthropometric parameters and malnutrition

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Discussion

This study assessed depression level and malnutrition among older persons in PHC in Kosofe LGA of Lagos State and their relationship with one another based on the MNA and GDS. A total of 219 questionnaires were administered and analyzed. The mean age (±SD) was 67.7 (±6.8), which was similar to the study done in Nigeria.^[7] Majority of the participants were women (77.63%) which was similar to the study by Keshavarzi et al.,^[19] in which there were about 72.1%. Majority of the participants were Yoruba (80.37%) in contrast to the study in Uyo where most of the participants were Ibibio.^[7] This is probably due to difference in the tribes of the inhabitants. In this study, 63.47% of the participants were married, 61.19% were Christians which contrasted with the study in Uyo which had about 51.9% of them married, 46.12% had secondary school education while in Uyo, 7.1% went to secondary school.^[7] it was found that 79% were self-employed, 53.88% earned between 1 and 20,000 naira, 61.64% lived with their children, 69.41% were from nuclear families, 53.88% were supported by their children, 56.16% were the interacting stage of the Stevenson's family model. The differences in these studies could be due to the geographical area.

Assessment of depression level

In this study, 36.07% were mildly depressed and 10.96% were severely depressed according to the GDS scoring. This is similar to the study where the level of severe depression was 9.5%.^[20] It, however, contrasted with the study done in Egypt,^[10] where the prevalence severe depression of 18.5% and in India,^[21] and the study done in Pakistan,^[22] where the level of severe depression was 16.5%, this could be attributable to the absence of social support.

A significant proportion of female participants was shown to be depressed There was a statistically significant association between sex and level of depression. This was consistent with the findings other studies that were done in Greece, Pakistan, and India^{[20],[21],[22]} this might be due to lower sex hormonal levels associated with the both genders. It however contrasted with findings from another study^[10] the reason for this could be because the study made use of a large study group of people.

Sixty-four participants whose ages were between 60 and 69 years were more at risk of mild and severe depression (P = 0.001). There was a statistically significant association between age and level of depression. This was seen in the study by some other studies^[10],[22] in their study on older persons. This could be attributable to the decreased levels of serotonin in the brain. This contrasted with the study done in Indian^[21] this might be related to the standard of living in the place.

Fifty-five participants who were widows had depression. In this study, there was a statistically significant association between widows and depression. This was also seen in the study in Greece, Pakistan, and India.^{[20],[21],[22]} This could be linked to the fact that marriage provides a partner's social support. It however contrasted an Egyptian study,^[10] this might be a consequence of higher life expectancy of the people.

A significant proportion of participants without formal education was found to be depressed. There was a statistically significant association between the educational qualification and the level of depression. This was similar to the findings by India and Pakistan researchers.^[21],[22] It contrasted findings from an Egyptian study.^[10] This could be accounted for by the fact that Egypt has a higher number of well-read individuals.

A significant proportion of participants with no income as well as those with low income was found to be depressed. There was a statistically significant association between monthly income and the level of depression. This was consistent with findings from some studies.^{[20],[21],[22]} This could be attributable to the inability to afford food which is a known cause depression. It contrasted findings from another study.^[10] This might be related to the better financial independently working elders.

Majority (73.7%), who lived with their spouse and those who had family support from self and spouse had no depression. There was a statistically significant association between living arrangement and level of depression. This was in line with the studies in India.^[21] This might have been because both countries have populations that have traditionally share feelings together in the family. There was a statistically significant association between family support and level of depression. This association was also recorded by an Indian study.^[21] This might have been because family support is one of the treatment remedies for depression.

Assessment of malnutrition

In this study, the prevalence of malnutrition and risk of malnutrition were 8.22% and 49.77% respectively according to the MNA scoring, this is similar to findings in Iran, South Africa and Ibadan^[5],[6],[18] where malnutrition levels of 6%, 5.5% and 7.8% respectively. This could be attributed to their geographical area.

However, it contrasted with the studies conducted in Germany and Iran,^[16],[17] which found malnutrition levels of 22.8% and 11.5% respectively which showed that there was a higher prevalence of malnutrition in older persons, this could be a consequence of depression and loss of motivation to eat.

In trying to study the relationship between the different variables with malnutrition, 99 female participants had malnutrition. There was a statistically significant association between female sex and malnutrition. This was similar to findings by Iran,^[16] this might be due to the inability to cook food to suit taste or desire. It however contrasted with study in Ibadan,^[6] this could have been because it was done in the general outpatient department of a large hospital.

A statistically significant association was found between weight circumference, hip circumference, and nutritional status. This was similar to findings from another researcher.^[8] This might have been because both countries have similarly large population size.

The average height, weight, waist circumference, hip circumference, waist–hip ratio was 164, 69, 93, 109, and 0.85, respectively. There was statistically significance association between the height, weight, waist circumference, hip circumference and waist-hip ratio, and the nutritional status.

There was statistically significant association between female sex and BMI. This was similar to findings from researchers in Ibadan,^[6] this might be because women have larger fat stores than men. It was found that there was a statistically significant association (P = 0.049) between educational qualification and BMI. It was also revealed that there was a statistically significant association (<0.001) between occupation and BMI. It was found that there was a statistically significant association (0.002) between family support and BMI.

Assessment of association between malnutrition and depression

A significant proportion of the participants with risk of malnutrition (54.3%) had mild and severe depression. There was a statistically significant association between malnutrition and depression. This was also discovered from the studies done in Germany and Iran;^[16],[17] this might be because there was already a scientifically established link between malnutrition and depression.

Conclusion

In this study, the overall prevalence of malnutrition was found to be 8.8%, with an overwhelming fact that the proportion of older persons at risk of malnutrition was relatively very high (49.8%). It was also found that a relationship existed between malnutrition and sex, ethnicity, religion, occupation, BMI.

Depression was found to be associated with female sex, age, widows, lack of formal education educational, occupation, low and lack of monthly income, living with spouse, and self and spouse family support. There was also an association between malnutrition and depression. There was a significant association between the height, weight, waist circumference, hip circumference and waist-hip ratio and the malnutrition.

Recommendations

There is a need to institute strategies to reduce the high prevalence of older persons at risk of malnutrition. While appropriate strategies should be targeted on the living arrangement and family support to limit depression among the older persons.

Acknowledgment

The authors would like to thank everyone who voluntarily participated in the study.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

References

1.	World Health Organization. Depression: Definition; 2012. Available from: https://wwww.euro.who.int/en/health-topics/noncommunicable-diseases/pages/news/news/2012/10/depression-in-europe/depression-definition. [Last accessed on 2018 Apr 24].
2.	National Institute of Mental Health. Major Depression. Available from: https://www.nimh.nih.gov/health/statistics/major-depression.shtml#part_155033. [Last accessed on 2018 May 19].
3.	Rao TS, Asha MR, Ramesh BN, Rao KS. Understanding nutrition, depression and mental illnesses. Indian J Psychiatry 2008;50:77-82.
4.	Popa TA, Ladea M. Nutrition and depression at the forefront of progress. J Med Life 2012;5:414-9.
5.	Naidoo I, Charlton KE, Esterhuizen TM, Cassim B. High risk of malnutrition associated with depressive symptoms in older South Africans living in KwaZulu-Natal, South Africa: A cross-sectional survey. J Health Popul Nutr 2015;33:19.
6.	Adebusoye LA, Ajayi IO, Dairo MD, Ogunniyi AO. Nutritional status of older persons presenting in a primary care clinic in Nigeria. J Nutr Gerontol Geriatr 2012;31:71-85.
7.	Morgan UM, Etukumana EA, Abasi-Ubong F. Screening for depression in the elderly: Outcome of a hospital based study in Uyo, Nigeria. IOSR J Dent Med Sci 2017;16:20-4.
8.	Pai MA. Comparative study of nutritional status of elderly population living in the home for aged versus those living in the community. Biomed Res 2011;22:120-6.
9.	Singh AJ, Masuku MB. Sampling techniques and determination of sample size in applied statistics research: An overview. IJECM 2014;2:1-21.
10.	Aly HY, Hamed AF, Mohammed NA. Depression among the elderly population in Sohag governorate. Saudi Med J 2018;39:185-90.
11.	Sturm R. Increases in morbid obesity in the USA: 2000-2005. Public Health 2007;121:492-6.
12.	UK Biobank. Anthropometry: Version 1.0; 2014. Available from: https://biobank.ctsu.ox.ac.uk/crystal/docs/Anthropometry.pdf. [Last accessed on 2018 Aug 18].
13.	Agarwalla R, Saikia AM, Baruah R. Assessment of the nutritional status of the elderly and its correlates. J Family Community Med 2015;22:39-43.
14.	Sözeri-Varma G. Depression in the elderly: Clinical features and risk factors. Aging Dis 2012;3:465-71.
15.	DiMaria-Ghalil RA, Amella EJ. Assessing nutrition in older adults. Try this: General assessment series. Journal of New York University College of Nursing. 2012; 9:1-2.
16.	Mokhber N, Majdi M, Ali-Abadi M, Shakeri M, Kimiagar M, Salek R, et al. Association between malnutrition and depression in elderly people in Razavi Khorasan: A population based-study in Iran. Iran J Public Health 2011;40:67-74.
17.	Smoliner C, Norman K, Wagner KH, Hartig W, Lochs H, Pirlich M. Malnutrition and depression in the institutionalised elderly. Br J Nutr 2009;102:1663-7.
18.	Payahoo L, Khaje-Bishak Y, Pourghassem Gargari B, Kabir-Alavi MB, Asgharijafarabadi M. Assessment of nutritional and depression status in free-living El-derly in Tabriz, Northwest Iran. Health Promot Perspect 2013;3:288-93.
19.	Keshavarzi S, Ahmadi SM, Lankarani KB. The impact of depression and malnutrition on health-related quality of life among the elderly Iranians. Glob J Health Sci 2014;7:161-70.
20.	Argyropoulos K, Bartsokas C, Argyropoulou A, Gourzis P, Jelastopulu E. Depressive symptoms in late life in urban and semi-urban areas of South-West Greece: An undetected disorder? Indian J Psychiatry 2015;57:295-300. [PUBMED] [Full text]
21.	Goyal A, Kajal KS. Prevalence of depression in elderly population in the Southern part of Punjab. J Family Med Prim Care 2014;3:359-61. [PUBMED] [Full text]
22.	Mubeen SM, Henry D, Nazimuddin Qureshi S. Prevalence of depression among community dwelling elderly in Karachi, Pakistan. Iran J Psychiatry Behav Sci 2012;6:84-90.