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BMJ 2005;330:1190 (21 May), doi:10.1136/bmj.38442.636181.E0 (published 3 May 2005)
Vikram Patel, reader in international mental health1, Betty R Kirkwood, professor of epidemiology and international health1, Helen Weiss, senior lecturer in epidemiology and statistics1, Sulochana Pednekar, research coordinator2, Janice Fernandes, researcher2, Bernadette Pereira, researcher2, Medha Upadhye, researcher2, David Mabey, professor of communicable diseases1
1 London School of Hygiene and Tropical Medicine, London WC1E 7HT, 2 Sangath, 831/1 Porvorim, Goa, India
Correspondence to: V Patel Vikram.patel{at}lshtm.ac.uk
Design Community survey.
Setting Primary health centre catchment area in Goa, India.
Participants 3000 randomly sampled women aged 18 to 50 years.
Main outcome measures Data on the primary outcome (reporting of fatigue for at least six months) and psychosocial exposures elicited by structured interview; presence of anaemia determined from a blood sample.
Results 2494 (83%) women consented to participate; 12.1% (95% confidence interval 10.8 to 13.4%) complained of chronic fatigue. In multivariate analyses, older women (P = 0.03) and those experiencing socioeconomic deprivationless education (P < 0.001), families in debt (P = 0.09), hunger in the past three months (P = 0.03)were more likely to report chronic fatigue. After adjustment for these factors, factors indicating gender disadvantage (notably sexual violence by the husband; P < 0.001) and poor mental health (P < 0.001) were strongly associated with chronic fatigue. Although women with a high body mass index had a reduced risk, suggesting an influence of poor nutrition, no association was found between chronic fatigue and haemoglobin concentrations.
Conclusions Chronic fatigue was commonly reported by women in this community study from India. The strongest associations with chronic fatigue were for psychosocial factors indicative of poor mental health and gender disadvantage.
Little research has been done on the associations of fatigue with psychological factors in developing countries, particularly in the context of the high prevalence of anaemia and poor nutrition. We hypothesised that the principal association of fatigue was with psychosocial risk factors, similar to patterns seen in developed countries,3 and with factors reflecting gender disadvantage that are important determinants of women's health.4 5
Data collection
We used a semistructured interview to elicit data on personal history and health history. Items were derived from existing interviews used in other studies.6-8 We estimated haemoglobin concentration from a finger prick sample of blood. A gynaecologist did a general medical examination for participants who consented. We organised the data as follows.
Socioeconomic risk factorsWe collected information on age, education, religion, and marital status from all participants, including those who refused to participate. We measured economic status through type of housing, access to water and a toilet, household composition and income, employment status, indebtedness, and experience of hunger in the previous three months.
Psychological factorsWe used two measures of psychological factors. The scale for somatic symptoms measures somatic symptoms that are features of somatoform disorders and has been used previously in India.9 The scale elicits experience of four categories of somatic symptoms in the previous two weeks. We summed the scores on the pain related symptoms and sensory symptom scales to generate a somatoform disorder symptom score. The second measure was the revised clinical interview schedule, a structured interview for the measurement of common mental disorders in community settings. A version of the schedule used in the study had been previously used in Goa.10 The sum of the section scores, excluding the fatigue item scores, generated a total score which we used as a measure of non-psychotic psychiatric morbidity.
Gender disadvantage and social supportQuestions on gender disadvantage and social support covered four domains. The first domain was the lifetime experience of verbal, physical, and sexual violence by the spouse and concerns about the spouse's extramarital relationships and substance use habits. Questions in the second domain were summed to generate an autonomy score. Questions in the third domain were summed to generate a social integration score. Finally we summed the questions in the last domain to generate a family support score (see bmj.com).
Physical health and anaemiaWe asked all participants about any pregnancies and asked participants who were sexually active in the past year about any difficulty in conception and their use of contraceptives. We evaluated anaemia as a categorical variable. We measured weight, height, and blood pressure. We measured disability by using the World Health Organization 12 item disability assessment schedule. This generates a total score and a measure of the number of days in the previous 30 days that the participant had to cut back her usual activities.
OutcomeWe defined the outcome on the basis of the responses to the fatigue section of the revised clinical interview schedule. This section has two optional questions on fatigue. Participants who answer positively to either of these are asked a series of four questions about the severity of the problem. We defined the outcome of chronic fatigue when participants had experienced fatigue in the past month and had scored at least 1 on the severity questions, and had experienced fatigue for a minimum duration of the past six months.
Analysis
We used logistic regression for all analyses, with chronic fatigue coded as a binary outcome (present or absent). We formed a composite multivariate model covering all domains. This consisted of the subset of socioeconomic factors in the first multivariate model; any mental health, gender disadvantage, and physical health factors for which the P value adjusted for the socioeconomic factors was
0.1; and haemoglobin concentrations on an a priori basis. We reached the final multivariate logistic regression model by dropping factors one at a time until all remaining factors were significant at the P
0.1 level (see bmj.com).
Fatigue was reported by 423 (17.0%) participants, of whom 301 (12.1%, 95% confidence interval 10.8% to 13.4%) had experienced it for at least six months. Participants who were experiencing chronic fatigue had significantly poorer WHO disability assessment schedule scores (mean score 14.1 (SD 2.5) v 12.4 (1.3); t = -19.03, P < 0.0001); they reported having to cut back on their daily activities on an average of 3.0 (2.2 to 3.9) days in the previous month compared with an average of 0.5 (0.3 to 0.6) days for participants who had not experienced chronic fatigue (P < 0.001).
Associations with socioeconomic risk factors
Older participants, participants living in households with more than three children under the age of 18, and those facing socioeconomic difficulties were significantly more likely to be experiencing chronic fatigue (see bmj.com). However, we found no association with household income. Compared with married participants, single participants had a lower risk, whereas divorced or widowed participants had a higher risk. In multivariate analyses, the following factors were significantly associated with chronic fatigue: lower education (school completers v no education; odds ratio = 0.57, 0.4 to 0.8); families in debt (1.27, 1.0 to 1.6); hunger in the previous three months (1.61, 1.1 to 2.6); and older age (age 40-50 v 18-24 years, odds ratio = 2.0, 1.3 to 3.1).
Associations with gender disadvantage and mental health factors
Participants who lived in unhappy marriages, indicated by spousal violence and concerns about the husband's extramarital relationships and substance use habits (mainly alcohol), were significantly more likely to experience chronic fatigue (table). Participants whose lives were marked by restrictions on personal freedoms and decision making and those who had low support from their families were significantly more likely to complain of chronic fatigue. The associations with the two mental health risk factors (common mental disorders and somatoform disorder symptom scores) were strong. All pain and sensory symptoms were between two and 10 times more commonly reported by participants with chronic fatigue.
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Associations with physical health factors
The only significant associations with physical health factors were a reduced risk with high body mass index and having had a pregnancy in the previous year (see bmj.com). We found no association between haemoglobin concentrations and chronic fatigue. Haemoglobin concentrations were also not associated with chronic fatigue in participants who had no symptoms of common mental disorders or somatoform disorders. We found no interaction (P = 0.5) between anaemia (haemoglobin < 11 g/dl) and common mental disorders.
In the final multivariate model, the following variables were independently associated with chronic fatigue: having experienced spousal sexual violence (odds ratio = 1.96, 1.0 to 3.7); high revised clinical interview schedule scores (highest fifth v lowest fifth; 24.3, 14.3 to 41.3); high somatoform symptom scores (highest quarter v lowest quarter; 11.6, 4.5 to 30.1); low body mass index (
25 v < 17; 0.49, 0.3 to 0.9); and older age (40-50 v 18-24 years; 2.1, 1.2 to 3.7).
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Strengths of our study include the use of a population sample, the use of standardised and validated measures of risk factors and outcome, and the evaluation of both psychosocial and physical health risk factors. Our definition of chronic fatigue was based on responses by participants to the fatigue section of the revised clinical interview schedule. One limitation is the possibility of a selection bias, given the differences between refusers and participants in the study and the relatively high proportion of participants who were recruited through replacement. We did not, however, find an association of replacement status with chronic fatigue. Some of the morbidity could have been attributable to infectious diseases that we were unable to diagnose in this study.
The rates of chronic fatigue lasting for at least six months that we report are similar to or higher than those reported in community studies from developed countries. For example, the UK population study that used similar criteria reported a point prevalence rate of chronic fatigue of 9%; the rates were higher in women.11 The socioeconomic risk factors independently associated with chronic fatigue were older age and indicators reflecting socioeconomic deprivation. Compared with married women, being single was a protective factor, whereas being widowed or separated increased the risk. Although studies in developed countries have shown some of these associations (for example, with older age), the association with economic difficulties is less consistent.
Gender disadvantage is a major social determinant of health in developing countries.5 12 Our study shows a strong association between gender disadvantage and chronic fatigue. Chronic fatigue may be the result of heavy physical work, which might be experienced by women in such circumstances. Excess physical work and gender disadvantages in access to food are perhaps the most likely explanation for the association of fatigue with low body mass index.
Mental health factors, notably the comorbidity with other physical problems, and symptoms of depression and anxiety, had the strongest associations with chronic fatigue. Common mental disorders and medically unexplained symptoms are among the most common causes of morbidity in developing countries. However, less than a third of clinically significant morbidity is detected,13 and fatigue may be a key problem in these disorders.
In conclusion, our main finding is that the strongest association of chronic fatigue in developing countries is with mental illness. Chronic fatigue is often comorbid with other medically unexplained physical symptoms, suggesting that such symptoms are part of a medically unexplained somatic syndrome.3 Practitioners in developing countries should investigate the psychological and social determinants of chronic fatigue before assuming that it is the result of anaemia or a nutritional deficiency. The growing evidence for effective treatments should provide the basis for guidelines for management of such symptoms.14 15
This is the abridged version of an article that was posted on bmj.com on 3 May 2005: http://bmj.com/cgi/doi/10.1136/bmj.38442.636181.E0 We thank the Directorate of Health Services, Government of Goa, which has collaborated with the project from its inception. We also thank Suhas Lavanis, Chandrakant Mhambrey, and Arvind Salelkar for their support for the study; Sheela Gupte and Prasad Nevrekar for gynaecological supervision; Tamara Hurst and Fiona Marquet in London and Anil Pandey in India for their administrative support to the project. Finally, we acknowledge the contribution of the research team of the Stree Arogya Shodh Project.
Funding: This study was funded by a Wellcome Trust career development fellowship in clinical tropical medicine to VP.
Competing interests: None declared.
Ethical approval: The study received ethical approval from the ethics board of the London School of Hygiene and Tropical Medicine and the Independent Ethics Commission, Mumbai.
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