Since the mid-1990s, livelihoods-based approaches have increasingly come to dominate the analysis of poverty and food insecurity, and the design of anti-poverty and famine prevention interventions, especially at the local (community to district or ‘food economy zone’) level. There is a growing consensus on the usefulness of livelihoods approaches for assessing, monitoring and mapping food insecurity and vulnerability, and a number of analytical toolkits have been developed and adopted by development agencies that draw on the holistic nature of livelihoods-based approaches. Because of their integrated view of livelihood systems, methodologies such as the ‘Household Economy Approach’ are better placed to interpret information on ‘coping strategies’ and nutritional status. Also, because they generate information on disaggregated livelihood categories or ‘vulnerable groups’, livelihood approaches have the potential to generate more sensitive and appropriate interventions than is possible with generic policies and programmes that are not tailored to local circumstances.

The greatest strengths of livelihoods approaches – their holistic and disaggregated nature – are also the source of their major limitations. Any multi-dimensional analysis is difficult to incorporate within government Ministries and agency programmes that are organised sectorally, around agriculture, health, and so on. Like other participatory and qualitative methods, livelihoods approaches also face the challenge of scaling up local-level findings to national level at affordable cost. On paper, these limitations suggest that the relevance of livelihoods-based approaches is less apparent for national and global FIVIMS work than for sub-national monitoring and locally relevant interventions.

One solution to these challenges may be to develop stronger analytical linkages between a range of methodologies and sources of information that all have the potential to contribute to food insecurity assessment and vulnerability monitoring. One under-exploited source is household surveys – whether donor-funded, nationally-owned, or specialist topic surveys – which have been conducted in almost all developing countries. Conventional household budget surveys can provide a great deal of relevant data for food security analysts, but their sampling frames may not be large enough or suitable for disaggregation by livelihood category, recall and measurement errors are inevitably associated with expenditure and consumption variables, household-level data cannot be easily disaggregated to generate intra-household distribution data, and a single cross-sectional survey is not very informative about trends in food insecurity and vulnerability over time. On the positive side, several recent developments in household survey analysis, reviewed in this paper, could be of great interest to food security information systems. These include: (1) a methodology based on ‘net benefit ratios’ that assesses the ‘winners and losers’ from policy changes, or shifts in food prices; (2) innovative techniques in poverty and vulnerability mapping, involving geo-referenced data and GIS software; (3) using cross-sectional or panel data to estimate household vulnerability to poverty; (4) non-parametric techniques such as Receiver Operating Characteristics curves to assess proxies for poverty and food insecurity.

Another area with great potential for FIVIMS is to incorporate nutrition indicators monitoring into food security information systems. Much positive experience has been accumulated on the use of nutrition surveillance to monitor food security status and predict vulnerability to food crises. However, nutritional indicators in isolation have several limitations, including: (1) as an outcome indicator, anthropometry cannot explain the causes of food insecurity; (2) since an individual’s nutritional status is determined not only by food intake, but also by health status and caring practices, the risk of misdiagnosing a poor nutritional outcome is high; (3) declining nutritional status may be a late indicator of a livelihood crisis, especially if children are monitored but adults protect their children’s food consumption. These factors make a strong case for integrating nutritional data with livelihoods information. Indeed, a number of recent actual or averted food crises (in Afghanistan, Burundi, and Sudan) show the value of combining nutritional status data with contextual information on livelihoods – including livelihood activities, assets, coping strategies, and market prices. Taken together, a fuller picture can be derived of the severity of a situation as well as its causes and impacts than if the two types of information are collected and analysed separately.

The argument for combining different types of food security information applies not only to data collection and analysis, but also to the establishment and improvement of integrated food security and information systems. With this in mind, this paper proposes a ‘FIVIMS Integrated Livelihoods Security Information System’ (FILSIS), defined as: “an integrated, spatially detailed, national information and mapping system which follows basic FIVIMS ideas on inter-agency collaboration and which is able to address two types of related problems: (a) transitory lack of access to adequate food, and basic medical care, water, and sanitation services which, together, impact on the nutritional status of well-defined population groups; and (b) more chronic sources of risk to the security of livelihoods, as measured by the level and stability of household income and other relevant indicators”. This system is eclectic in terms of information needs and methodologies, and it supports a two-track approach to fighting both food insecurity (i.e. dealing with shocks) and underlying household income poverty (i.e. strengthening livelihoods). Prerequisites for successful implementation of a FILSIS – or even more effective national and global FIVIMS – include: (1) better inter-agency collaboration; (2) higher levels of donor resourcing; (3) effective use of innovative GIS, mapping and database software; (4) genuine commitment to building in-country capacity to collect, analyse and disseminate quality food security information. The institutional, technical and financial challenges are daunting, but the potential returns, in terms of effective information systems for fighting poverty and hunger, are enormous.

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