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 Table of Contents  
Year : 2014  |  Volume : 3  |  Issue : 2  |  Page : 144-153

Prevalence and risk factors for psychological distress and functional disability in urban Pakistan

1 University of Manchester, United Kingdom of Great Britain and Northern Ireland
2 Dow University of Health Sciences, Karachi, Pakistan
3 Barnet, Enfield and Haringey Mental Health (NHS) Trust, London, United Kingdom of Great Britain and Northern Ireland

Date of Web Publication22-May-2017

Correspondence Address:
Nusrat Husain
Institute of Brain, Behaviour & Mental Health, The University of Manchester, University Place, The Scan Building, 3rd floor east, Oxford Road, Manchester M13 9WL, United Kingdom of Great Britain and Northern Ireland

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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2224-3151.206730

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Background: There is a close association between poor mental health status and both poor physical health and decreased productivity. An evidence base on the risk factors for psychological distress in low-income countries is lacking and is much needed to help develop appropriate interventions. We aimed to estimate the prevalence of psychological distress in urban Pakistan and identify associated risk factors and functional disability.
Methods: This was a population-based study of 18–75-year-olds in urban Pakistan. The Self-Reporting Questionnaire (SRQ) was offered to 1000 adults to measure psychological distress. The Life Events Checklist, Oslo-3 for Social Support and Brief Disability Questionnaires were used to establish social stressors, support and functional disability.
Results: Questionnaires were completed by 880 (94%) eligible participants, of whom 41% of women and 19% of men scored 9 or more on the SRQ (possible range 0–20). Low educational status was associated with high rates of psychological distress. Women had significantly higher levels of distress than men and were less likely to receive practical support.
Conclusions: The prevalence of psychological distress was lower in urban Karachi than that reported previously for rural Punjab province, Pakistan. However, in urban Karachi, as in rural Punjab, socioeconomic status seemed to have more of an impact on the mental health of women than that of men.

Keywords: Functional disability, low-income country, psychological stress, risk factors, south Asia

How to cite this article:
Husain N, Chaudhry N, Jafri F, Tomenson B, Surhand I, Mirza I, Chaudhry IB. Prevalence and risk factors for psychological distress and functional disability in urban Pakistan. WHO South-East Asia J Public Health 2014;3:144-53

How to cite this URL:
Husain N, Chaudhry N, Jafri F, Tomenson B, Surhand I, Mirza I, Chaudhry IB. Prevalence and risk factors for psychological distress and functional disability in urban Pakistan. WHO South-East Asia J Public Health [serial online] 2014 [cited 2023 Feb 5];3:144-53. Available from: http://www.who-seajph.org/text.asp?2014/3/2/144/206730

  Introduction Top

Depressive disorder is among the leading causes of disability worldwide and is projected to be second only to HIV/AIDS in its link to disability-adjusted life-years by 2030. It will be the third most common cause of disability in lower-income countries and the leading cause in higher-income country settings.[1] There is a wide treatment gap for mental disorders, which approaches astonishingly high rates of 90% in least-resourced countries.[2] Thus, there is an urgent need to collect systematic information on mental disorders – to inform the development of interventions in low-income settings.

The prevalence of anxiety and depressive disorders is high in Pakistan, at 66% in women and 25% in men in rural Pakistan, and is associated with social adversity.[3],[4],[5] These findings have been confirmed in a systematic review, which found that socioeconomic adversity and relationship problems were major risk factors for depression.[6] A study by Mumford et al. in 2000[7] reported the rate of depression in an urban slum in Punjab province, Pakistan, to be less than half of that of a nearby rural village.

Studies in high-income countries show that rates of mental illness are higher in urban than in rural populations.[8] In a European study (Outcome of Depression International network – ODIN), there were large urban/rural differences in the prevalence of depressive disorder in women in the United Kingdom of Great Britain and Northern Ireland (UK) and Ireland, with high rates of depression in women among urban areas, whereas in men this difference was insignificant.[9] The possible reasons suggested for this disparity were factors such as lack of a confidant having difficulties in getting practical help from neighbours.[10] In 2000, Paykel et al. analysed differences between urban, semi-rural and rural areas in mainland UK. They found that urban subjects had higher rates of mental illness than rural populations, which they attributed to adverse urban social environments.[11] Similar findings have been reported from a study in the United States of America (USA) exploring rural and urban disparities, where psychiatric disorders were more prevalent in urban settings.[12]

There have been few comparison studies of mental health in urban/rural populations in Asia. In the Republic of Korea, Lee et al. compared the prevalence of psychiatric disorders in men and women in the urban city of Seoul and rural areas, and found that the prevalence of psychiatric disorders, including alcohol dependence, was higher among women in rural areas.[13]

Psychological distress is defined as mental anguish or suffering;[14] it includes symptoms of anxiety and depression.

The authors predicted that the rates of psychological distress in Karachi would be lower than those found in their earlier studies in rural areas of Pakistan, in both men and women, and that these would be associated with similar risk factors.[15],[16]

The aim of this study was to establish the prevalence of psychological distress in an urban Pakistani population, and to identify social stressors and functional disability associated with this distress.

  Methods Top

Study design and setting

The study was conducted in Karachi, the largest city of Pakistan, with an estimated inner-city population of 15.5 million compared with 18 million in the metropolitan city.[17] There is wide variation in socioeconomic status, with some areas being highly affluent while others lack the basic amenities such as piped water, sewerage, gas and electricity.

The study was a population-based house-to-house survey in Arafat Town, a typical densely populated inner-city area that was not an officially planned residential area, but 20 years ago received official status. Since then, water, gas, electricity and drainage systems have been developed, but even today, a number of households are without the basic amenities.

Data collection

A random sample of 1000 adults (500 men and 500 women) was obtained from the electoral register, using a table of random numbers. This sample size was considered to be adequate, considering the number of variables that were examined in this study. All 18–75-year-old individuals, residing at the stated address and not suffering from serious physical illness at that time – were invited to participate in the study by the research team through house-to-house visits in person.

Ethics committee approval was obtained from Karachi Medical College and the Pakistan Institute of Learning and Living. The study was described to each potential participant, with a witness present. After a complete description of the study, informed consent was obtained. Literate participants then signed the consent form but, if the participant could not write their name, they placed a thumbprint on the consent form, which was countersigned by the witness. The Self-Reporting Questionnaire (SRQ,) Brief Disability Questionnaire (BDQ), Oslo-3 for Social Support, and Life Events Checklist are self-administered questionnaires but, to maintain consistency, research assistants read out the questions to all participants, Some degree of privacy was attempted while administering the questionnaires. Male participants were interviewed by male research assistants and female participants by the female research assistant. Members of the research team visited many houses on more than one occasion (up to six visits) to complete the questionnaires. Details of the methodology are described in a previous paper.[18]

Basic demographic details, including sex, age, number of family members, marital status, education, employment, family system and income group, were recorded.

Medical history data

Participants were also asked whether or not they had been hospitalized and whether they had had any diagnostic tests or procedures in the past 12 months.

Psychiatric symptoms

Psychiatric symptoms were recorded using the Self-Reporting Questionnaire (SRQ-20).[19] This standardized instrument has been in use in low- and middle-income countries for more than 20 years. It has been validated on a Pakistani population, and found to have good psychometric properties.[15] Each of 20 symptoms are rated “yes” or “no”, according to whether the patient has experienced them in the past 30 days. The total SRQ score is the total number of symptoms experienced out of 20, so the range of score is from 0 to 20. An SRQ score of 9 or more was used, as high scores are indicative of greater psychological distress and this correlates more with a diagnosis of depressive disorder.[15]

Social support

The Oslo-3 scale was used to measure social support. This consists of three questions to address relationships with family, friends and neighbourhood. These questions explore how easy is it to get help from neighbours if required, how many people can the person rely on and how much concern they show.[20] It has been used to study inequalities in the health of Pakistanis living in Norway.[21] Each item is scored from 1 to 5, and a total of the three scores ranges from 3 to 15, with high scores indicating greater social support.

Life events

Life events were determined using a list of 15 questions, including categories based on the Quebec Health Survey, identified in studies of physical illness and depression.[16] Participants were asked about life events experienced during the previous 12 months. A response format of yes/no was used and a total score (number of events experienced) is quoted in the results. This scale has been used in the authors’ earlier studies.[16]


The cross-culturally validated BDQ was used to assess disability. This includes six items from the Short-Form (SF-36) questionnaire, which asks respondents whether they have been limited in any everyday activities in the past month and four questions addressing daily functioning.[22],[23] Two additional items were included – inability to carry out usual activities fully and staying in bed because of illness or injury. Each item is scored on a three-point scale (0 = no/not at all, 1 = yes/ sometimes and 2 = yes/moderately or definitely). The total score of the 10 items, which ranges from 0 to 20, was used, with higher scores indicating greater disability.

Statistical analysis

The data were analysed using SPSS for Windows version 15.[24] Men and women were compared with respect to demographic and medical history data, and all questionnaire items and totals were analysed, using the t test for continuous measures, and the chi-squared test for categorical measures.

Bivariate analyses were carried out for men and women separately, with total SRQ score as the dependent variable, using t tests for dichotomous variables, one-way analysis of variance followed by Bonferroni corrected pair-wise group comparisons for other categorical variables, and Pearson correlation for continuous variables. Correlation coefficients between 0 and 0.3 are considered to be very weak and not indicative of a linear correlation; between 0.29 and 0.45 they are considered to be moderate; and correlation coefficients above 0.45 are considered to be strong.

In order to determine significant independent correlates of higher SRQ scores, a multiple regression analysis was carried out with total SRQ as the dependent variable, and independent variables all those that were significant at P<0.05 on bivariate analysis with total SRQ score. These were age, sex, unmarried, education level primary or less, employment as a labourer, monthly income below Rs 5000 (Pakistani rupees), whether the subject had been in hospital or had any diagnostic tests, four or more children aged under 14 years, six or fewer people in the household, access to clean drinking water, whether waste was kept outside, house construction of both concrete and local materials, and total scores for Oslo, life events and disability. The multiple regression analysis was repeated for men and women separately. Variance inflation factors were calculated for all variables in all the multiple regression analyses, to ensure that multicollinearity was not a problem. Analysis of covariance compared the SRQ scores of men and women, after accounting for differences in age, education, income, house construction, hospitalization, disability, life events and social support.

  Results Top

Of the 1000 people selected from the electoral register, 50 were not living at the chosen address and 12 were excluded because they had serious physical illness. Of the 938 eligible participants, 49 (15 women and 34 men) refused to participate and the data were incomplete for a further 9, so data for 880 participants were analysed.

Characteristics of the sample

The sample included 411 men and 469 women, of whom 712 (80.9%) were married, 237 (26.9%) were illiterate, 539 (61.3%) were unemployed, housewives or retired, and 321 (36.5%) had a monthly family income of less than Rs 5000 (see [Table 1]). The men were significantly older than the women. Women were significantly more likely to be illiterate and less likely to have received education beyond 10 years of schooling. They were also significantly more likely to live in a joint family than the men and to be in a lower income group.
Table 1: Characteristics of the sample

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Psychological distress

The mean SRQ score was significantly higher for women than for men (see [Table 2]). Seventy-eight (19.0%) men and 194 (41.4%) women had nine or more of the SRQ symptoms (χ2 p<0.001). Eighty-eight women (18.8%) and 29 men (7.1%) reported suicidal ideation (χ2 p<0.001). The proportion of women who had experienced each symptom on the SRQ was significantly greater than that for the men, with the exception of poor appetite and poor digestion, which had similar proportions for two sexes.
Table 2: Questionnaire scores

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Life events

The mean number of life events for the whole sample was 4.2 (see [Table 2]), which represents just over 4 of the 15 different types of life events experienced” The most common life event experienced was problems relating to employment (N = 476, 54.1%), followed by illness or hospitalization of patient or a relative (N = 424, 48.2%), pregnancy or birth in the family (N= 410,46.6%) and financial worries (N=367,41.7%). There was no significant difference between men and women for the total number of life events, and men and women reported similar proportions of all types of life events. The only type of event for which they differed significantly was difficulties at work or school, which were experienced by 132 (28.1%) of the women and 88 (21.4%) of the men, P= 0.024.


The mean BDQ score was 6.8 for the whole sample, which represents either 7 symptoms with a little disability, or 3–4 symptoms with moderate disability (see [Table 2]). There was a trend towards a significant difference between men and women with respect to the BDQ scores, but women were significantly more likely than men to be limited with respect to motivation for work, efficiency and daily activities, and were more likely to have spent one or more days in bed because of illness or injury. Men were significantly more likely than women to have health problems that limited vigorous activity (data not shown).

Social support

The mean Oslo score was 8.1, which represents either three items scoring 2–3 on the scale from 1 to 5, or two out of the three items showing good support and scoring 4. The Oslo total score was significantly higher for men than women (see [Table 2]). Ease of getting practical help from neighbours was the only individual item to show a significant difference (data not shown).

Relationship between total SRQ score and age, number of family members, life events, disability and social support

The SRQ total score was moderately positively associated (r>0.3) with both the total number of life events and the BDQ score for each sex, and moderately negatively correlated with the Oslo total score for women. The remaining correlations (between total SRQ score and both age and number of family members) were weak (r<0.21), as was the correlation between Oslo score and SRQ score for men (r = –0.10).

For men, significant correlates of higher SRQ scores were being married, having a poor education, being a labourer, having had a diagnostic test or investigation in the past year, and living in a house constructed of both local materials and concrete (see [Table 3]). For women, significant risk factors were poor education, being a labourer, being in the low income group, having been in hospital in the past year, not having clean drinking water, being in a smaller household, having fewer children aged under 14 years, and living in a house constructed of both local materials and concrete.
Table 3: Association between categorical measures and total SRQ score, for men and women separatelya

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Multiple regressions for SRQ scores

Age, female sex, poor education, low income, having been in hospital, having three or fewer children, and having a house constructed of both concrete and local materials, and all the questionnaire scores were all significantly associated with a raised SRQ score (see [Table 4]). Having had some diagnostic procedures or tests was significantly associated with lower SRQ scores. The adjusted R2 value was 38.5%. This means that 38.5% of the variance of total SRQ is explained by the variables in the analysis. Multicollinearity of variables was not a problem, as the maximum variance inflation factor was 1.85. The regression coefficient for female sex indicates that women had SRQ total scores that were 1.77 higher than those of men, on average, after adjusting for the other variables in the analysis. Similarly, poorly educated people had scores 1.11 higher than those who were better educated; people with a low income had scores 0.75 less than those with a higher income; and those who had been in hospital had scores 1.33 higher than those of people who had not, on average. People with higher levels of support had lower SRQ scores by 0.29 per point increase in support scores, those with higher life events scores scored 0.63 higher on the SRQ score per life event, and those with higher levels of disability scored higher on the SRQ by 0.17 per point on the disability scale.
Table 4: Linear regression analyses with SRQ total score as the dependent variable

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Multiple regression analyses for men and women separately

For men, age, poor education, house construction and the questionnaire scores (disability, life events and social support) were the only factors that were significantly associated with higher SRQ scores (see [Table 5]). The adjusted R2 value of 32.3% was slightly lower than for the group as a whole.
Table 5: Linear regression analyses with SRQ total score as the dependent variable: men only

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For women, the results were very similar to the group as a whole, although being unmarried was significant, and low education was not (see [Table 6]). The adjusted R2 value of 37.8% was similar to that for the whole group.
Table 6: Linear regression analyses with SRQ total score as the dependent variable: women only

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Analysis of covariance comparing the total SRQ scores of men and women, after accounting for differences in age, education, income, house construction, hospitalization, disability, life events and social support, showed that, although the other factors accounted for some of the differences in SRQ scores between men and women, women still had significantly higher scores than men, after accounting for these factors. Unadjusted means for men and women were 5.1 and 7.7, respectively, while adjusted means were 5.5 and 7.4, respectively (standard error = 0.2).

  Discussion Top

This is one of the very few population-based studies of an urban area of Pakistan. Previous studies are primarily from rural populations.[4],[5],[15],[16] The one other community-based study of an urban population using a robust methodology was done in Punjab province, Pakistan where the authors reported lower rates of psychiatric morbidity in the urban slum compared with the rural areas.[7] Similar to Mumford’s findings, the results of our study also show that the rate of psychological distress was less than in our previous study in rural Pakistan using the same methodology.[9],[10] This finding was applicable to both men and women, although the prevalence of psychological distress was 2.6 points higher, on average, in women compared with men, which reduced to 1.77 points higher after adjusting for other covariates. This has been a consistent finding in previous studies). In 2007, Gadit and Mugford reported variability in prevalence rates between the cities of Pakistan in a telephone study.[25] They found that the city of Lahore had the highest prevalence (53.4%), as compared with Quetta (43.9%) and Karachi (35.7%). The prevalence finding for the city of Karachi in the present study is consistent with their report.

Urban/rural differences

This study and Mumford’s earlier study in urban Punjab province, Pakistan, has shown lower rates of psychological distress in urban areas, which is contrary to the higher rates reported in urban areas in high-income countries. The reasons for this could be positive selection, in that individuals in Pakistan who are more psychologically robust migrate to the cities, where life is better socially and socioeconomically. There are improved basic amenities such as water, electricity, gas and transport, and better employment, leisure and health facilities. There is also a social support system in the form of family and clan loyalties, which tends to mitigate the effect of factors such as lack of a confidant, and inability to get practical support.

Comparison of prevalence rates with other studies


We compared our findings with those of our previous studies in Mandra, a town near Rawalpindi and our tribal study in the village of Thooth Dhand, which is one of the seven tribal agencies of Pakistan.[15],[16] In this study in Karachi, 19.0% of the men scored 9 or more on the SRQ, which is very similar to the Mandra study with 18%, and much lower than the 45% reported in the tribal study. Corresponding results for women were 41% in this study, 44% in Mandra and 60% in the tribal study. In the present study, 16% of men and 36.1% of women scored 10 or more on the SRQ, compared with 12% of men and 45% of women in a study in rural Punjab province, Pakistan,.[5] Similar to the present findings, the prevalence of depression was quite high in women in a large population-based study in urban south India,[26] and was associated with increasing age in men and women, low socioeconomic status and physical health comorbidities.

Sex differences

Women are twice as likely as men to report depression. This difference increases in low-income countries. Patel and Kleinman argue that, other than biological factors, different stressors faced by women in developing countries, such as poverty, less opportunity for education, physical abuse by husbands, forced marriages, sexual trafficking and limited job opportunities, may explain this difference.[27] A cross-sectional study of a semi-urban community of Karachi reported a prevalence rate of depression of 30% in women.[28] The factors associated with depression were older age, lack of education and verbal abuse in relationships.

High rates of depression in women compared with men were also found in upper and upper–middle class women compared with men in a high socioeconomic area of urban Karachi.[29] The rate of depression in women was twice that in men and was mainly related to marital problems and role conflicts in domestic spheres of life. The present results also show that social problems were strongly correlated with depression. In urban Karachi, as in rural Punjab, socioeconomic status seems to have more impact on the mental health of women than that of men.

Other psychosocial correlates of depression

This study found that women found it significantly harder than men to obtain practical help from neighbours, and there was also a trend towards women having higher disability scores than men. Social support has long been thought to protect against depression. A meta-analysis by Henderson in 1992 included 35 studies relating to depression and social support.[30] The author reports two consistent findings: that there was an inverse association between social support and affective symptoms, whereby a lack of social support increases the risk of developing depression, and that social support acted as a buffer in the face of severe stressors.

In previous studies, lack of education and poverty have shown a strong association with depression.[27] This study found that poor education was associated with high rates of distress and it is likely that lack of education leads to limited understanding of health services and consequently less likelihood of engaging in health-seeking behaviours. A study using health survey data from 22 developing countries showed that educated mothers were more likely to engage in health-seeking behaviours.[31] Another study of postpartum women found that low literacy was a risk factor for depression.[32]

Although Karachi has a large migrant population, with estimates of 90% coming from different ethnic backgrounds, this study was conducted in Arafat Town in Karachi, which is typical of urban development in big cities. Most people living there are migrants from rural Punjab. The authors recognize that the results of this study may not be representative of the whole of Pakistan, particularly Baluchistan Province and the North-West Frontier Province.

Further prospective studies including studies in other cities of Pakistan may provide a better understanding of mental health and environmental factors, and the effects of internal migration to big cities of Pakistan.

The findings of this study have important public health and policy implications. Individuals with a low income are caught in a trap, as the symptoms of depression and anxiety make it less likely for them to find the resources and be able to work their way out of financial poverty and thus they are more likely to continue to be depressed and anxious. These individuals need to be identified and appropriately treated early. The increased risk of depression in women, especially considering the adverse effects of poor maternal mental health on the whole family, makes a strong case for developing targeted screening programmes for this high-risk population.

  Strengths and Weaknesses of the Study Top

The strengths of the study are a high response rate of 93.8%, which reflects the high acceptance rate for the study in the local population. The use of validated scales in the study, such as the SRQ, which has been validated in Urdu in previous studies in Pakistan, is a further strength.[15]

One of the limitations of the study is that the disability and social support measure used was subjective, which could have led to bias in the responses of participants with depression. Other limitations are the reliance on the use of self-reported questionnaires and the cross-sectional design, which meant that it was not possible to confirm the direction of the association between social distress and significant correlates.

  Acknowledgements Top

We thank all the participants of the study.

Source of Support: Nil.

Conflict of Interest: None declared.

Contributorship: The study in Pakistan was supervised by F J and IS. The first draft was prepared by IM. ВТ helped with the statistical analysis. All authors were involved in the interpretation and analysis of results and writing of the final draft. NH had overall responsibility for the project.

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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]

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