23 research outputs found
Behavioural activation therapy for depression in adults with non-communicable diseases
No full textBACKGROUND: Depression is common in people with non-communicable diseases (NCDs) such as cardiovascular disease, diabetes, cancer, and chronic respiratory conditions. The co-existence of depression and NCDs may affect health behaviours, compliance with treatment, physiological factors, and quality of life. This in turn is associated with worse outcomes for both conditions. Behavioural activation is not currently indicated for the treatment of depression in this population in the UK, but is increasingly being used to treat depression in adults. OBJECTIVES: To examine the effects of behavioural activation compared with any control group for the treatment of depression in adults with NCDs. To examine the effects of behavioural activation compared with each control group separately (no treatment, waiting list, other psychological therapy, pharmacological treatment, or any other type of treatment as usual) for the treatment of depression in adults with NCDs. SEARCH METHODS: We searched CCMD-CTR, CENTRAL, Ovid MEDLINE, Embase, four other databases, and two trial registers on 4 October 2019 to identify randomised controlled trials (RCTs) of behavioural activation for depression in participants with NCDs, together with grey literature and reference checking. We applied no restrictions on date, language, or publication status to the searches. SELECTION CRITERIA: We included RCTs of behavioural activation for the treatment of depression in adults with one of four NCDs: cardiovascular disease, diabetes, cancer, and chronic respiratory conditions. Only participants with a formal diagnosis of both depression and an NCD were eligible. Studies were included if behavioural activation was the main component of the intervention. We included studies with any comparator that was not behavioural activation, and regardless of reported outcomes. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane, including independent screening of titles/abstracts and full-text manuscripts, data extraction, and risk of bias assessments in duplicate. Where necessary, we contacted study authors for more information. MAIN RESULTS: We included two studies, contributing data from 181 participants to the analyses. Both studies recruited participants from US hospital clinics; one included people who were recovering from a stroke and the other women with breast cancer. For both studies, the intervention consisted of eight weeks of face-to-face behavioural therapy, with one study comparing to poststroke treatment as usual and the other comparing to problem-solving therapy. Both studies were at risk of performance bias and potential conflict of interest arising from author involvement in the development of the intervention. For one study, risks of selection bias and reporting bias were unclear and the study was judged at high risk of attrition bias. Treatment efficacy (remission) was greater for behavioural activation than for comparators in the short term (risk ratio (RR) 1.53, 95% confidence interval (CI) 0.98 to 2.38; low-certainty evidence) and medium term (RR 1.76, 95% CI 1.01 to 3.08; moderate-certainty evidence), but these estimates lacked precision and effects were reduced in the long term (RR 1.42, 95% CI 0.91 to 2.23; moderate-certainty evidence). We found no evidence of a difference in treatment acceptability in the short term (RR 1.81, 95% CI 0.68 to 4.82) and medium term (RR 0.88, 95% CI 0.25 to 3.10) (low-certainty evidence). There was no evidence of a difference in depression symptoms between behavioural activation and comparators (short term: MD -1.15, 95% CI -2.71 to 0.41; low-certainty evidence). One study found no difference for quality of life (short term: MD 0.40, 95% CI -0.16 to 0.96; low-certainty evidence), functioning (short term: MD 2.70, 95% CI -6.99 to 12.39; low-certainty evidence), and anxiety symptoms (short term: MD -1.70, 95% CI -4.50 to 1.10; low-certainty evidence). Neither study reported data on adverse effects. AUTHORS' CONCLUSIONS: Evidence from this review was not sufficient to draw conclusions on the efficacy and acceptability of behavioural activation for the treatment of depression in adults with NCDs. A future review may wish to include, or focus on, studies of people with subthreshold depression or depression symptoms without a formal diagnosis, as this may inform whether behavioural activation could be used to treat mild or undiagnosed (or both) depressive symptoms in people with NCDs. Evidence from low-resource settings including low- and middle-income countries, for which behavioural activation may offer a feasible alternative to other treatments for depression, would be of interest
Climate Change Innovation Programme (CCIP) Scoping Studies on State Action Plan on Climate Change (SAPCC), 2014, Commissioned Study Report sponsored by DFID, Govt of UK and coordinated by EPCO, Madhya Pradesh
No full textMultiple shocks, coping and welfare consequences: natural disasters and health shocks in the Indian Sundarbans.
No full textBACKGROUND: Based on a household survey in Indian Sundarbans hit by tropical cyclone Aila in May 2009, this study tests for evidence and argues that health and climatic shocks are essentially linked forming a continuum and with exposure to a marginal one, coping mechanisms and welfare outcomes triggered in the response is significantly affected. DATA & METHODS: The data for this study is based on a cross-sectional household survey carried out during June 2010. The survey was aimed to assess the impact of cyclone Aila on households and consequent coping mechanisms in three of the worst-affected blocks (a sub-district administrative unit), viz. Hingalganj, Gosaba and Patharpratima. The survey covered 809 individuals from 179 households, cross cutting age and gender. A separate module on health-seeking behaviour serves as the information source of health shocks defined as illness episodes (ambulatory or hospitalized) experienced by household members. KEY FINDINGS: Finding reveals that over half of the households (54%) consider that Aila has dealt a high, damaging impact on their household assets. Result further shows deterioration of health status in the period following the incidence of Aila. Finding suggests having suffered multiple shocks increases the number of adverse welfare outcomes by 55%. Whereas, suffering either from the climatic shock (33%) or the health shock (25%) alone increases such risks by a much lesser extent. The multiple-shock households face a significantly higher degree of difficulty to finance expenses arising out of health shocks, as opposed to their counterparts facing only the health shock. Further, these households are more likely to finance the expenses through informal loans and credit from acquaintances or moneylenders. CONCLUSION: This paper presented empirical evidence on how natural and health shocks mutually reinforce their resultant impact, making coping increasingly difficult and present significant risks of welfare loss, having short as well as long-run development manifestations
Nutritional status of children in India: household socio-economic condition as the contextual determinant
No full textAbstract
Background
Despite recent achievement in economic progress in India, the fruit of development has failed to secure a better nutritional status among all children of the country. Growing evidence suggest there exists a socio-economic gradient of childhood malnutrition in India. The present paper is an attempt to measure the extent of socio-economic inequality in chronic childhood malnutrition across major states of India and to realize the role of household socio-economic status (SES) as the contextual determinant of nutritional status of children.
Methods
Using National Family Health Survey-3 data, an attempt is made to estimate socio-economic inequality in childhood stunting at the state level through Concentration Index (CI). Multi-level models; random-coefficient and random-slope are employed to study the impact of SES on long-term nutritional status among children, keeping in view the hierarchical nature of data.
Main findings
Across the states, a disproportionate burden of stunting is observed among the children from poor SES, more so in urban areas. The state having lower prevalence of chronic childhood malnutrition shows much higher burden among the poor. Though a negative correlation (r = -0.603, p < .001) is established between Net State Domestic Product (NSDP) and CI values for stunting; the development indicator is not always linearly correlated with intra-state inequality in malnutrition prevalence. Results from multi-level models however show children from highest SES quintile posses 50 percent better nutritional status than those from the poorest quintile.
Conclusion
In spite of the declining trend of chronic childhood malnutrition in India, the concerns remain for its disproportionate burden on the poor. The socio-economic gradient of long-term nutritional status among children needs special focus, more so in the states where chronic malnutrition among children apparently demonstrates a lower prevalence. The paper calls for state specific policies which are designed and implemented on a priority basis, keeping in view the nature of inequality in childhood malnutrition in the country and its differential characteristics across the states.
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Socioeconomic inequality in life expectancy in India
No full textIntroduction Concern for health inequalities is an important driver of health policy in India; however, much of the empirical evidence regarding health inequalities in the country is piecemeal focusing only on specific diseases or on access to particular treatments. This study estimates inequalities in health across the whole life course for the entire Indian population. These estimates are used to calculate the socioeconomic disparities in life expectancy at birth in the population.Methods Population mortality data from the Indian Sample Registration System were combined with data on mortality rates by wealth quintile from the National Family Health Survey to calculate wealth quintile specific mortality rates. Results were calculated separately for males and females as well as for urban and rural populations. Life tables were constructed for each subpopulation and used to calculate distributions of life expectancy at birth by wealth quintile. Absolute gap and relative gap indices of inequality were used to quantify the health disparity in terms of life expectancy at birth between the richest and poorest fifths of households.Results Life expectancy at birth was 65.1 years for the poorest fifth of households in India as compared with 72.7 years for the richest fifth of households. This constituted an absolute gap of 7.6 years and a relative gap of 11.7 %. Women had both higher life expectancy at birth and narrower wealth-related disparities in life expectancy than men. Life expectancy at birth was higher across the wealth distribution in urban households as compared with rural households with inequalities in life expectancy widest for men living in urban areas and narrowest for women living in urban areas.Conclusion As India progresses towards Universal Health Coverage, the baseline social distributions of health estimated in this study will allow policy makers to target and monitor the health equity impacts of health policies introduced
Study site: A mark on map (not on scale) depict the actual local of the study area, Sundarbans, West Bengal, India.
No full text<p>Study site: A mark on map (not on scale) depict the actual local of the study area, Sundarbans, West Bengal, India.</p
Joint effect of climate and health shocks on coping strategies against expenditure following health shock, Sundarbans, West Bengal, India.
No full text<p>Note: <sup>#</sup>Expenditure items include direct costs of treatment, expenses on drugs and medicines, transport, and related expense such as those incurred on food or lodging for patients and accompanying person(s).</p><p>@ denotes that the testing of hypotheses for difference of means (results in column B-F) was carried out only for the households reporting an incidence of health shock (n = 94).</p>∧<p>The coefficients in column G are odds-ratios on the ‘multiple-shock’ variable – households experiencing both the health shock as well as high-impact due to climatic shock – from logit regressions with the dependent variable in the corresponding row of the first column. Health shock variable is for illness of household head and/or spouse. The comparison group for column G coefficients is households with health shock alone (with a less-impact of Climatic shock). Models additionally control for (log) total health expenses, <i>pre-shock</i> vulnerabilities (see text) and village-level fixed effects. Coping models (items B and C, in column A) also controls for the self-assessed ‘difficulty in financing’ variable.</p><p>Figures in parentheses are t-statistics testing for the hypothesis that the variable is not different from zero.</p><p>* *p<0.05, *** p<0.01.</p><p>Joint effect of climate and health shocks on coping strategies against expenditure following health shock, Sundarbans, West Bengal, India.</p
Proportion of households incurring sacrifices of different items according to self-assessed intensity of climatic shock, Sundarbans, West Bengal, India.
No full text#<p>building embankments, dwelling repairs etc.</p><p>*p<0.1,</p><p>** p<0.05,</p><p>*** p<0.001.</p><p>Proportion of households incurring sacrifices of different items according to self-assessed intensity of climatic shock, Sundarbans, West Bengal, India.</p
Significance of Multiple Shocks on Individual Items of Welfare, Sundarbans, West Bengal, India.
No full text<p>Significance of Multiple Shocks on Individual Items of Welfare, Sundarbans, West Bengal, India.</p
