Dataset Information

Complexity in action: Untangling latent relationships between land quality, economic structures and socio-spatial patterns in Italy.

ABSTRACT: Land quality, a key economic capital supporting local development, is affected by biophysical and anthropogenic factors. Taken as a relevant attribute of economic systems, land quality has shaped the territorial organization of any given region influencing localization of agriculture, industry and settlements. In regions with long-established human-landscape interactions, such as the Mediterranean basin, land quality has determined social disparities and polarization in the use of land, reflecting the action of geographical gradients based on elevation and population density. The present study investigates latent relationships within a large set of indicators profiling local communities and land quality on a fine-grained resolution scale in Italy with the aim to assess the potential impact of land quality on the regional socioeconomic structure. The importance of land quality gradients in the socioeconomic configuration of urban and rural regions was verified analyzing the distribution of 149 socioeconomic and environmental indicators organized in 5 themes and 17 research dimensions. Agriculture, income, education and labour market variables discriminate areas with high land quality from areas with low land quality. While differential land quality in peri-urban areas may reflect conflicts between competing actors, moderate (or low) quality of land in rural districts is associated with depopulation, land abandonment, subsidence agriculture, unemployment and low educational levels. We conclude that the socioeconomic profile of local communities has been influenced by land quality in a different way along urban-rural gradients. Policies integrating environmental and socioeconomic measures are required to consider land quality as a pivotal target for sustainable development. Regional planning will benefit from an in-depth understanding of place-specific relationships between local communities and the environment.

SUBMITTER: Salvati L

PROVIDER: S-EPMC5456058 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Complexity in action: Untangling latent relationships between land quality, economic structures and socio-spatial patterns in Italy.

Salvati Luca L Tombolini Ilaria I Gemmiti Roberta R Carlucci Margherita M Bajocco Sofia S Perini Luigi L Ferrara Agostino A Colantoni Andrea A

PloS one 20170602 6

Land quality, a key economic capital supporting local development, is affected by biophysical and anthropogenic factors. Taken as a relevant attribute of economic systems, land quality has shaped the territorial organization of any given region influencing localization of agriculture, industry and settlements. In regions with long-established human-landscape interactions, such as the Mediterranean basin, land quality has determined social disparities and polarization in the use of land, reflecti ...[more]

PMID: 28574984

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Project description:Ecosystems degradation represents one of the major global challenges at the present time, threating people's livelihoods and well-being worldwide. Ecosystem restoration therefore seems no longer an option, but an imperative. Restoration challenges are such that a dialogue has begun on the need to re-shape restoration as a science. A critical aspect of that reshaping process is the acceptance that restoration science and practice needs to be coupled with socio-economic research and public engagement. This inescapably means conveying complex ecosystem's information in a way that is accessible to the wider public. In this paper we take up this challenge with the ultimate aim of contributing to making a step change in science's contribution to ecosystems restoration practice. Using peatlands as a paradigmatically complex ecosystem, we put in place a transdisciplinary process to articulate a description of the processes and outcomes of restoration that can be understood widely by the public. We provide evidence of the usefulness of the process and tools in addressing four key challenges relevant to restoration of any complex ecosystem: (1) how to represent restoration outcomes; (2) how to establish a restoration reference; (3) how to cope with varying restoration time-lags and (4) how to define spatial units for restoration. This evidence includes the way the process resulted in the creation of materials that are now being used by restoration practitioners for communication with the public and in other research contexts. Our main contribution is of an epistemological nature: while ecosystem services-based approaches have enhanced the integration of academic disciplines and non-specialist knowledge, this has so far only followed one direction (from the biophysical underpinning to the description of ecosystem services and their appreciation by the public). We propose that it is the mix of approaches and epistemological directions (including from the public to the biophysical parameters) what will make a definitive contribution to restoration practice.

Project description:BackgroundSince the use of medicines is strongly correlated to population health needs, higher drug consumption is expected in socio-economical deprived areas. However, no systematic study investigated the relationship between medications use in the treatment of chronic diseases and the socioeconomic position of patients. The purpose of the study is to provide a description, both at national level and with geographical detail, of the use of medicines, in terms of consumption, adherence and persistence, for the treatment of major chronic diseases in groups of population with different level of socioeconomic position. METHODS: A cross-sectional study design was used to define the "prevalent" users during 2018. A longitudinal cohort study design was performed for each chronic disease in new drug users, in 2018 and the following year. A retrospective population-based study, considering all adult Italian residents (i.e. around 50.7 million people aged ≥ 18 years). Different medications were used as a proxy for underlying chronic diseases: hypertension, dyslipidemia, osteoporosis, diabetes and chronic obstructive pulmonary disease. Only "chronic" patients who had at least 2 prescriptions within the same subgroup of drugs or specific medications during the year were selected for the analysis. A multidimensional measures of socio-economic position, declined in a national deprivation index at the municipality level, was used to identify and estimate the relationship with drug use indicators. The medicine consumption rate for each pharmacological category was estimated for prevalent users while adherence and persistence to pharmacologic therapy at 12 months were evaluated for new users.ResultsThe results highlighted how the socioeconomic deprivation is strongly correlated with the use of medicines: after adjustment by deprivation index, the drug consumption rates decreased, mainly in the most disadvantaged areas, where consumption levels are on average higher than in other areas. On the other hand, the adherence and persistence indicators did not show the same trend.ConclusionsThis study showed that drug consumption is influenced by the level of deprivation consistently with the distribution of diseases. For this reason, the main levers on which it is necessary to act to reduce disparities in health status are mainly related to prevention. Moreover, it is worth pointing out that the use of a municipal deprivation indicator necessarily generates an ecological bias, however, the experience of the present study, which for the first-time deals with the complex and delicate issue of equity in Italian pharmaceutical assistance, sets the stage for new insights that could overcome the limits.

Dataset Information

Complexity in action: Untangling latent relationships between land quality, economic structures and socio-spatial patterns in Italy.

Publications

Complexity in action: Untangling latent relationships between land quality, economic structures and socio-spatial patterns in Italy.

Similar Datasets

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