ABSTRACT
Maintaining cognitive function is a prerequisite of living independently, which is a highly valued component in older individuals’ well-being. In this article we assess the role of early-life and later-life nutritional status, education, and literacy on the cognitive functioning of older adults living in poverty in Peru. We exploit the baseline sample of the Peruvian noncontributory pension program Pension 65 and find that current nutritional status and literacy are strongly associated with cognitive functioning for poor older adults. In a context of rising popularity of noncontributory pension programs around the world, our study intends to contribute to the discussion of designing accompanying measures to the pension transfer, such as adult literacy programs and monitoring of adequate nutrition of older adults.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. In Latin America, about 17 countries and 19 million individuals (32% of the 60+ population) receive noncontributory pensions. This figure refers to the period 2012 to 2013 and is computed with data extracted on December 12, 2016, from http://www.pension-watch.net/ and the United Nations’ World Population Prospects 2015 revision.
2. The data were gathered in 12 departments (out of 24) where the Ministry of Development and Social Inclusion (MIDIS) had already completed the census of socioeconomic variables intended to update its household targeting score system (SISFOH) and where, according to administrative records, 70% of Pension 65 beneficiaries lived. Households in the sample were randomly drawn from the total number of households showing a SISFOH score located at ±0.3 standard deviations from the SISFOH cut-off for extreme poverty. Households with a score above and below this threshold were classified as “non-extreme poor” and “extreme poor,” respectively, and therefore were assigned into control and treatment groups for a posterior impact evaluation. The sampling selection was probabilistic, independent in each department, stratified in rural/urban areas, and carried out in two steps. In the first step, the primary sampling units (PSUs) were census units in urban areas and villages in rural areas with at least four households living in poverty and with elderly members. The selection of PSUs was made by probability proportional to size according to the total number of households. In the second step, four households were randomly drawn from each PSU for interview and two for replacements.