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dc.contributor.authorAdams, H
dc.contributor.authorAdger, WN
dc.contributor.authorAhmad, S
dc.contributor.authorAhmed, A
dc.contributor.authorBegum, D
dc.contributor.authorLázár, AN
dc.contributor.authorMatthews, Z
dc.contributor.authorRahman, MM
dc.contributor.authorStreatfield, PK
dc.date.accessioned2016-11-23T09:57:21Z
dc.date.issued2016-11-08
dc.description.abstractPopulations in resource dependent economies gain well-being from the natural environment, in highly spatially and temporally variable patterns. To collect information on this, we designed and implemented a 1586-household quantitative survey in the southwest coastal zone of Bangladesh. Data were collected on material, subjective and health dimensions of well-being in the context of natural resource use, particularly agriculture, aquaculture, mangroves and fisheries. The questionnaire included questions on factors that mediate poverty outcomes: mobility and remittances; loans and micro-credit; environmental perceptions; shocks; and women's empowerment. The data are stratified by social-ecological system to take into account spatial dynamics and the survey was repeated with the same respondents three times within a year to incorporate seasonal dynamics. The dataset includes blood pressure measurements and height and weight of men, women and children. In addition, the household listing includes basic data on livelihoods and income for approximately 10,000 households. The dataset facilitates interdisciplinary research on spatial and temporal dynamics of well-being in the context of natural resource dependence in low income countries.en_GB
dc.description.sponsorshipThe authors gratefully acknowledge the residents of Khulna and Barisal who gave up many hours of their time to be interviewed on multiple occasions. We are indebted to their generosity and patience. In addition we would like to acknowledge the important contribution of Tauhida Nasrin and colleagues at Associates for Community and Population Research and the team of enumerators who ensured the smooth implementation of the survey; Masfiqus Salehin and Rezaur Rahman at Bangladesh University of Engineering and Technology, Munir Ahmed at Technological Assistance for Rural Advancement and Hamidul Huq at University of Liberal Arts Bangladesh for their assistance in defining the social-ecological systems; Mahin Al Nahian for his assistance in implementing the survey; Rakin Muhtadee Shihab for completing the final translation of the questionnaire to Bengali; Munir Ahmed, Abir Ahammad Talukdar and Ali Mohammad Rezaie for assistance with qualitative fieldwork and pretesting; Abul Kashem Mohammad Hasan at the Center for Environmental and Geographic Information Services and Muhammad Zahirul Haq at icddr,b for the GIS work. The survey was part of the project Assessing Health, Livelihoods, Ecosystem Services And Poverty Alleviation In Populous Deltas (Espa Deltas; Grant No. NE/J000892/1), part of the Ecosystem Services for Poverty Alleviation (ESPA) programme. The ESPA programme is funded by the Department for International Development, the Economic and Social Research Council and the Natural Environment Research Council. Helen Adams had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.en_GB
dc.identifier.citationVol. 3, pp. 160094 -en_GB
dc.identifier.doi10.1038/sdata.2016.94
dc.identifier.othersdata201694
dc.identifier.urihttp://hdl.handle.net/10871/24556
dc.language.isoenen_GB
dc.publisherNature Publishing Groupen_GB
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pubmed/27824340en_GB
dc.rightsThis is the final version of the article. Available from Nature Publishing Group via the DOI in this record.en_GB
dc.titleSpatial and temporal dynamics of multidimensional well-being, livelihoods and ecosystem services in coastal Bangladesh.en_GB
dc.typeArticleen_GB
dc.date.available2016-11-23T09:57:21Z
exeter.place-of-publicationEnglanden_GB
dc.descriptionPublished onlineen_GB
dc.descriptionJournal Articleen_GB
dc.identifier.eissn2052-4463
dc.identifier.journalScientific Dataen_GB


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