BACKGROUND: Current tools assessing affordability of nutritious diets are incomplete. "Food poverty" uses expenditure data to identify households unable to acquire a diet adequate in energy but does not consider other nutrients. The "minimum cost of a nutritious diet" method provides a threshold for purchasing a nutritious diet but must rely on other data to identify "nutrient-poor" households. OBJECTIVE: Integrating both methods into a single framework using a common data source, we sought to jointly estimate the proportions of a population that are food and nutrient poor. METHODS: Household expenditure data from the 2010/11 Nepal Living Standards Survey were used, focusing on representative samples of households from the mountain region (n = 401) and Kathmandu (n = 857). Food poverty thresholds were set at the cost for a low-income household to purchase a basket of foods providing adequate energy following the Cost of Basic Need method. Linear optimization was used to calculate a "nutrient poverty" threshold. Household expenditures were used to determine food and nutrient poverty rates. RESULTS: The food and nutrient poverty thresholds were 13,294 and 18,628 rupees/person/year, respectively, in the mountain region and 14,610 and 22,945 rupees/ person/year, respectively, in Kathmandu. In the mountain region, 34% of households were both food and nutrient poor and 24% were just nutrient poor. In Kathmandu the percentages were 7% and 14%, respectively. CONCLUSIONS: This approach, integrating two commonly used tools, provides a more nuanced interpretation of economic access to a nutritious diet and an opportunity to improve the design and targeting of nutrition and food security interventions.
BACKGROUND: Current tools assessing affordability of nutritious diets are incomplete. "Food poverty" uses expenditure data to identify households unable to acquire a diet adequate in energy but does not consider other nutrients. The "minimum cost of a nutritious diet" method provides a threshold for purchasing a nutritious diet but must rely on other data to identify "nutrient-poor" households. OBJECTIVE: Integrating both methods into a single framework using a common data source, we sought to jointly estimate the proportions of a population that are food and nutrient poor. METHODS: Household expenditure data from the 2010/11 Nepal Living Standards Survey were used, focusing on representative samples of households from the mountain region (n = 401) and Kathmandu (n = 857). Food poverty thresholds were set at the cost for a low-income household to purchase a basket of foods providing adequate energy following the Cost of Basic Need method. Linear optimization was used to calculate a "nutrient poverty" threshold. Household expenditures were used to determine food and nutrient poverty rates. RESULTS: The food and nutrient poverty thresholds were 13,294 and 18,628 rupees/person/year, respectively, in the mountain region and 14,610 and 22,945 rupees/ person/year, respectively, in Kathmandu. In the mountain region, 34% of households were both food and nutrient poor and 24% were just nutrient poor. In Kathmandu the percentages were 7% and 14%, respectively. CONCLUSIONS: This approach, integrating two commonly used tools, provides a more nuanced interpretation of economic access to a nutritious diet and an opportunity to improve the design and targeting of nutrition and food security interventions.
Authors: Nasima Akhter; Naomi Saville; Bhim Shrestha; Dharma S Manandhar; David Osrin; Anthony Costello; Andrew Seal Journal: Food Secur Date: 2018-05-12 Impact factor: 3.304
Authors: Amy Deptford; Tommy Allieri; Rachel Childs; Claudia Damu; Elaine Ferguson; Jennie Hilton; Paul Parham; Abigail Perry; Alex Rees; James Seddon; Andrew Hall Journal: BMC Nutr Date: 2017-03-14