Vulnerabilities to flood hazards among rural households in India

Flooding constitutes the most predominant natural disaster in India. The degree and causes of vulnerability to flood risk vary by society, geographical region and over time. The rural people of India are highly vulnerable to flood hazards due to high dependence on natural resources for livelihood and poor socio-economic situations. The information regarding the degree of vulnerability of these people is limited. In order to formulate improved adaption policies and effective programmes to reduce vulnerability, it is crucial to quantify the vulnerability of rural households affected by floods at a regional level. Our study provides insight into the vulnerability of rural households affected by floods in India. We use primary data of 220 flood-prone rural households of Odisha state in India for analysis. The vulnerability is analysed using the Livelihood Vulnerability Index and the Socio-economic Vulnerability Index. Our results show that these households are vulnerable to flood in more than one dimension. Sociodemographic characteristics such as a low literacy rate, a high dependency ratio and a weak housing structure increase these residents’ vulnerability. Access to social networks and social institutions plays a significant role in uplifting poor rural households. Our study concludes that the vulnerability of a household is governed by both non-climatic factors and the incidence of floods. The findings of our study may be considered in developing policies and programmes that will reduce the flood risk. The recommendations we suggested in this study can be applied in other south Asian counties with similar socio-economic profiles

Quantifying household vulnerability triggered by drought: evidence from rural India

Drought is a complex, slow-onset phenomenon that imposes serious challenges on human beings and ecosystems. The vulnerability associated with drought may vary at different social, geographical and temporal scales. These differences emphasize the need for regional-level vulnerability assessments, which in turn helps to formulate efficient adaptation policies and strategies that are suitable for the region to mitigate the drought risk. The objective of this paper is to quantify the livelihood and socio-economic vulnerability of rural households that are affected by drought in rural India. The Livelihood Vulnerability Index and Socioeconomic Vulnerability Index were applied to analyse the vulnerability of rural households. A sample size of 157 rural households from the state of Odisha in India was surveyed in 2015. Socio-demographic characteristics such as low literacy rates, high dependency ratios and weak housing structures make people more vulnerable, whereas access to social networks plays a significant role in supporting poor rural households. The research concludes that the impacts of drought make people who are already vulnerable due to poverty, inequality and marginalization even more vulnerable. The outcomes of this study may be considered in formulating effective coping strategies and policies that may help mitigate the drought risk. The findings and recommendations of this study will find applicability in other rural, natural resource-dependent countries with similar socio-economic profiles such as other south Asian countries

The My Active and Healthy Aging (My-AHA) ICT platform to detect and prevent frailty in older adults: Randomized control trial design and protocol

[EN] Introduction Frailty increases the risk of poor health outcomes, disability, hospitalization, and death in older adults and affects 7%¿12% of the aging population. Secondary impacts of frailty on psychological health and socialization are significant negative contributors to poor outcomes for frail older adults. Method The My Active and Healthy Aging (My-AHA) consortium has developed an information and communications technology¿based platform to support active and healthy aging through early detection of prefrailty and provision of individually tailored interventions, targeting multidomain risks for frailty across physical activity, cognitive activity, diet and nutrition, sleep, and psychosocial activities. Six hundred adults aged 60 years and older will be recruited to participate in a multinational, multisite 18-month randomized controlled trial to test the efficacy of the My-AHA platform to detect prefrailty and the efficacy of individually tailored interventions to prevent development of clinical frailty in this cohort. A total of 10 centers from Italy, Germany, Austria, Spain, United Kingdom, Belgium, Sweden, Japan, South Korea, and Australia will participate in the randomized controlled trial. Results Pilot testing (Alpha Wave) of the My-AHA platform and all ancillary systems has been completed with a small group of older adults in Europe with the full randomized controlled trial scheduled to commence in 2018. Discussion The My-AHA study will expand the understanding of antecedent risk factors for clinical frailty so as to deliver targeted interventions to adults with prefrailty. Through the use of an information and communications technology platform that can connect with multiple devices within the older adult's own home, the My-AHA platform is designed to measure an individual's risk factors for frailty across multiple domains and then deliver personalized domain-specific interventions to the individual. The My-AHA platform is technology-agnostic, enabling the integration of new devices and sensor platforms as they emerge.This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 689582 and the Australian National Health and Medical Research Council (NHRMC) European Union grant scheme (1115818). M.J.S. reports personal fees from Eli Lilly (Australia) Pty Ltd and grants from Novotech Pty Ltd, outside the submitted work. All other authors report nothing to disclose.Summers, MJ.; Rainero, I.; Vercelli, AE.; Aumayr, GA.; De Rosario Martínez, H.; Mönter, M.; Kawashima, R. (2018). The My Active and Healthy Aging (My-AHA) ICT platform to detect and prevent frailty in older adults: Randomized control trial design and protocol. Alzheimer's and Dementia: Translational Research and Clinical Interventions. 4:252-262. https://doi.org/10.1016/j.trci.2018.06.004S2522624Blair, S. N. (1995). Changes in Physical Fitness and All-Cause Mortality. JAMA, 273(14), 1093. doi:10.1001/jama.1995.03520380029031Fried, L. P., Ferrucci, L., Darer, J., Williamson, J. D., & Anderson, G. (2004). Untangling the Concepts of Disability, Frailty, and Comorbidity: Implications for Improved Targeting and Care. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 59(3), M255-M263. doi:10.1093/gerona/59.3.m255Gillick, M. (2001). Guest Editorial: Pinning Down Frailty. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 56(3), M134-M135. doi:10.1093/gerona/56.3.m134Hamerman, D. (1999). Toward an Understanding of Frailty. Annals of Internal Medicine, 130(11), 945. doi:10.7326/0003-4819-130-11-199906010-00022Fried, L. P., Tangen, C. M., Walston, J., Newman, A. B., Hirsch, C., Gottdiener, J., … McBurnie, M. A. (2001). Frailty in Older Adults: Evidence for a Phenotype. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 56(3), M146-M157. doi:10.1093/gerona/56.3.m146Panza, F., Solfrizzi, V., Barulli, M. R., Santamato, A., Seripa, D., Pilotto, A., & Logroscino, G. (2015). Cognitive Frailty: A Systematic Review of Epidemiological and Neurobiological Evidence of an Age-Related Clinical Condition. Rejuvenation Research, 18(5), 389-412. doi:10.1089/rej.2014.1637Soong, J., Poots, A., Scott, S., Donald, K., Woodcock, T., Lovett, D., & Bell, D. (2015). Quantifying the prevalence of frailty in English hospitals. BMJ Open, 5(10), e008456. doi:10.1136/bmjopen-2015-008456Varadhan, R., Walston, J., Cappola, A. R., Carlson, M. C., Wand, G. S., & Fried, L. P. (2008). Higher Levels and Blunted Diurnal Variation of Cortisol in Frail Older Women. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 63(2), 190-195. doi:10.1093/gerona/63.2.190BROWN, I., RENWICK, R., & RAPHAEL, D. (1995). Frailty. International Journal of Rehabilitation Research, 18(2), 93-102. doi:10.1097/00004356-199506000-00001Buchner, D. M., & Wagner, E. H. (1992). Preventing Frail Health. Clinics in Geriatric Medicine, 8(1), 1-18. doi:10.1016/s0749-0690(18)30494-4Kojima, G., Iliffe, S., Jivraj, S., & Walters, K. (2016). Association between frailty and quality of life among community-dwelling older people: a systematic review and meta-analysis. Journal of Epidemiology and Community Health, 70(7), 716-721. doi:10.1136/jech-2015-206717Ory, M. G., Schechtman, K. B., Miller, J. P., Hadley, E. C., Fiatarone, M. A., … Province, M. A. (1993). Frailty and Injuries in Later Life: The FICSIT Trials. Journal of the American Geriatrics Society, 41(3), 283-296. doi:10.1111/j.1532-5415.1993.tb06707.xShamliyan, T., Talley, K. M. C., Ramakrishnan, R., & Kane, R. L. (2013). Association of frailty with survival: A systematic literature review. Ageing Research Reviews, 12(2), 719-736. doi:10.1016/j.arr.2012.03.001Woodhouse, K. W., & O’Mahony, M. S. (1997). Frailty and ageing. Age and Ageing, 26(4), 245-246. doi:10.1093/ageing/26.4.245CAMPBELL, A. J., & BUCHNER, D. M. (1997). Unstable disability and the fluctuations of frailty. Age and Ageing, 26(4), 315-318. doi:10.1093/ageing/26.4.315Drey, M., Pfeifer, K., Sieber, C. C., & Bauer, J. M. (2011). The Fried Frailty Criteria as Inclusion Criteria for a Randomized Controlled Trial: Personal Experience and Literature Review. Gerontology, 57(1), 11-18. doi:10.1159/000313433Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., … Phelps, C. H. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7(3), 270-279. doi:10.1016/j.jalz.2011.03.008Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999). Mild Cognitive Impairment. Archives of Neurology, 56(3), 303. doi:10.1001/archneur.56.3.303Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L.-O., … Petersen, R. C. (2004). Mild cognitive impairment - beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. Journal of Internal Medicine, 256(3), 240-246. doi:10.1111/j.1365-2796.2004.01380.xDubois, B., Hampel, H., Feldman, H. H., Scheltens, P., Aisen, P., … Andrieu, S. (2016). Preclinical Alzheimer’s disease: Definition, natural history, and diagnostic criteria. Alzheimer’s & Dementia, 12(3), 292-323. doi:10.1016/j.jalz.2016.02.002Moher, D., Hopewell, S., Schulz, K. F., Montori, V., Gotzsche, P. C., Devereaux, P. J., … Altman, D. G. (2010). CONSORT 2010 Explanation and Elaboration: updated guidelines for reporting parallel group randomised trials. BMJ, 340(mar23 1), c869-c869. doi:10.1136/bmj.c869Gray, L. C., Bernabei, R., Berg, K., Finne-Soveri, H., Fries, B. E., Hirdes, J. P., … Ariño-Blasco, S. (2008). Standardizing Assessment of Elderly People in Acute Care: The interRAI Acute Care Instrument. Journal of the American Geriatrics Society, 56(3), 536-541. doi:10.1111/j.1532-5415.2007.01590.xRadloff, L. S. (1977). The CES-D Scale. Applied Psychological Measurement, 1(3), 385-401. doi:10.1177/014662167700100306Guralnik, J. M., Simonsick, E. M., Ferrucci, L., Glynn, R. J., Berkman, L. F., Blazer, D. G., … Wallace, R. B. (1994). A Short Physical Performance Battery Assessing Lower Extremity Function: Association With Self-Reported Disability and Prediction of Mortality and Nursing Home Admission. Journal of Gerontology, 49(2), M85-M94. doi:10.1093/geronj/49.2.m85Powell, L. E., & Myers, A. M. (1995). The Activities-specific Balance Confidence (ABC) Scale. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 50A(1), M28-M34. doi:10.1093/gerona/50a.1.m28Kendzierski, D., & DeCarlo, K. J. (1991). Physical Activity Enjoyment Scale: Two Validation Studies. Journal of Sport and Exercise Psychology, 13(1), 50-64. doi:10.1123/jsep.13.1.50Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). «Mini-mental state». Journal of Psychiatric Research, 12(3), 189-198. doi:10.1016/0022-3956(75)90026-6Brandt, J. (1991). The hopkins verbal learning test: Development of a new memory test with six equivalent forms. Clinical Neuropsychologist, 5(2), 125-142. doi:10.1080/13854049108403297Lubben, J. E. (1988). Assessing social networks among elderly populations. Family & Community Health, 11(3), 42-52. doi:10.1097/00003727-198811000-00008Russell, D., Peplau, L. A., & Cutrona, C. E. (1980). The revised UCLA Loneliness Scale: Concurrent and discriminant validity evidence. Journal of Personality and Social Psychology, 39(3), 472-480. doi:10.1037/0022-3514.39.3.472De Vries, O. J., Peeters, G. M. E. E., Lips, P., & Deeg, D. J. H. (2013). Does frailty predict increased risk of falls and fractures? A prospective population-based study. Osteoporosis International, 24(9), 2397-2403. doi:10.1007/s00198-013-2303-zTheou, O., Stathokostas, L., Roland, K. P., Jakobi, J. M., Patterson, C., Vandervoort, A. A., & Jones, G. R. (2011). The Effectiveness of Exercise Interventions for the Management of Frailty: A Systematic Review. Journal of Aging Research, 2011, 1-19. doi:10.4061/2011/569194Cadore, E. (2014). Strength and Endurance Training Prescription in Healthy and Frail Elderly. Aging and Disease, 5(3), 183. doi:10.14336/ad.2014.0500183Cadore, E. L., Rodríguez-Mañas, L., Sinclair, A., & Izquierdo, M. (2013). Effects of Different Exercise Interventions on Risk of Falls, Gait Ability, and Balance in Physically Frail Older Adults: A Systematic Review. Rejuvenation Research, 16(2), 105-114. doi:10.1089/rej.2012.1397Gardner, M. M. (2001). Practical implementation of an exercise-based falls prevention programme. Age and Ageing, 30(1), 77-83. doi:10.1093/ageing/30.1.77Eng, J. J. (2010). Fitness and Mobility Exercise Program for Stroke. Topics in Geriatric Rehabilitation, 26(4), 310-323. doi:10.1097/tgr.0b013e3181fee736Wadlinger, H. A., & Isaacowitz, D. M. (2008). Looking happy: The experimental manipulation of a positive visual attention bias. Emotion, 8(1), 121-126. doi:10.1037/1528-3542.8.1.121MacLeod, C. (2012). Cognitive bias modification procedures in the management of mental disorders. Current Opinion in Psychiatry, 25(2), 114-120. doi:10.1097/yco.0b013e32834fda4aMensink, R. P., & Katan, M. B. (1989). Effect of a Diet Enriched with Monounsaturated or Polyunsaturated Fatty Acids on Levels of Low-Density and High-Density Lipoprotein Cholesterol in Healthy Women and Men. New England Journal of Medicine, 321(7), 436-441. doi:10.1056/nejm19890817321070

eine prospektive Kohortenstudie

Objective: The Mental Adjustment to Cancer Scale (MAC scale) has evolved to a standard measure in the field of psycho-oncology. In this context an attitude called "fighting spirit" gained much attention as a coping style. Some reports suggest that coping efforts as measured by the MAC scale are predictive for survival of breast cancer patients. We explored the predictive power of the MAC scale by using a sample of patients with haematological malignancies undergoing allogenic hemopoietic stem cell transplantation (HSCT). Methods: Between 9/1999 and 12/2001 127 patients were administered the MAC scale prior to HSCT. Follow-up data of overall survival and event-free survival were obtained in December 2003 and analyzed using Cox-regression models. Results: At the time of the follow-up, 68 patients had died (overall survival), 75 patients had experienced a relapse or had died (event-free survival). We failed to find significant results for the MAC subscales with and without adjustment for prognostic factors. Conclusion: In the special situation of patients facing HSCT the MAC scale seems not to be of predictive value. In general, with respect to survival the empirical evidence is not very convincing.Zielsetzung: Die Mental Adjustment to Cancer Scale (MAC-Skala) hat sich im Feld der Psychoonkologie zu einem Standardmessinstrument entwickelt. In diesem Zusammenhang gewann ein als "fighting spirit" bezeichneter Bewältigungsstil breite Aufmerksamkeit. In manchen Studien wurde berichtet, dass mit der MAC-Skala erfasste Krankheitsverarbeitungsweisen mit späterer Überlebensdauer korreliert sind. Wir untersuchten die Vorhersagekraft der MAC-Skala in einer Stichprobe von Patienten mit hämatologischen Erkrankungen, die sich einer allogenen hämatopoietischen Stammzelltransplantation (HSZT) unterzogen. Methode: Zwischen 9/1999 und 12/2001 bearbeiteten 127 Patienten die MAC-Skala vor Durchführung der HSZT. Ein Follow-up im Hinblick auf Überlebenszeit erfolgte im Dezember 2003. Die Überlebenszeitdaten wurden mit Cox-Regressionsmodellen evaluiert. Ergebnisse: 68 Patienten waren verstorben, 75 Patienten waren verstorben oder erlitten Rezidiv. Es wurden mit und ohne Adjustierung bezüglich medizinischer Prognosefaktoren keine signifikanten Zusammenhänge einer der MAC-Subskalen mit der allgemeinen und der krankheitsfreien Überlebenszeit gefunden. Fazit: In der speziellen Situation vor HSZT scheint die MAC-Skala keinen Vorhersagewert für die Überlebenszeit zu haben. Jedoch gilt auch allgemein, dass die empirische Evidenz in dieser Hinsicht nicht überzeugend ist