Economic development and gender inequality in cognition: A comparison of China and India, and of SAGE and the HRS sister studies

Abstract

This paper examines cognition measures by age and gender from two types of studies in China and India. It finds that despite some notable differences in samples and measures, a general strong association of cognition in older ages with education emerges as a potential explanation for gender gaps and cohort differences. Female disadvantage in cognition is greater in India, both before and after controlling for education. The process of rural-urban migration draws more cognitively able women to cities in China but not in India. The advent of modern longitudinal studies of aging in these developing countries holds great promise for future work.

Patterns of cognitive function in middle-aged and elderly Chinese adults—findings from the EMCOA study

“…Furthermore, a 10-year cohort study found that women outperformed men not only on verbal memory, but also on verbal recognition and semantic fluency tasks [ 39 ], suggesting that the female advantage for verbal memory tasks is possibly because women are inclined to use semantic clustering in recall. Contrary to verbal memory, men tended to score higher than women for attention/processing speed/executive function, which is an important cognitive capacity to attend to or to “stay on” a task [ 40 ] to complete a task quickly and accurately under the cognitive control of behavior. However, the results only showed the male advantage in the 50–54 and 65–70 years age groups, consistent with previous reports that age-related associations for processing speed were stronger than other domains [ 41 ].…”

“…With respect to verbal memory, we may presume that education could strengthen the semantic clustering in recall. For attention/processing speed/executive function, the Chinese have a larger male advantage in this domain than Americans, with a potential reason being the relatively equivalent access to formal education in developed countries [ 40 ]. In former low-income environments, such as traditional rural China, families may favor sons and large gender gaps in schooling exist in low-income settings.…”

Cognition, Health, and Well-Being in a Rural Sub-Saharan African Population

“…Additional income is very often used to improve housing in Malawi, so a change in roof material from non-metal to metal acts as a strong proxy for a rise in household wealth (for example, in a 2012 survey of MLSFH interviewers—who are drawn from the rural regions represented in the study—70% of interviewers (20 of 29) reported using their previous MLSFH-related earnings on repairing or adding to their homes). In addition to roofing material, individuals’ height is also an often-used proxy for childhood nutrition status, and is thus a reliable marker of childhood SES (Maurer, 2010; Weir et al, 2014). The MLSFH collected height measurements in 2012 and 2013, and we test the association between height (measured in centimeters) and ICA score to gain insight into the relationship between early-life conditions and later-life cognitive health in the MLSFH sample.…”

A Cross-National Study of the Gender Gap in Health Among Older Adults in India and China: Similarities and Disparities

“…Comparisons of developed countries have consistently found a female disadvantage in levels of physical disability, depression, and physical performance; while gender differences in morbidity levels have been shown to vary depending on the chronic condition (Crimmins, Kim, & Solé-Auró, 2011;Oksuzyan et al, 2010;Van de Velde, Bracke, & Levecque, 2010). Research findings from low-and middle-income countries have suggested that relative to men, women have worse general health (Ng et al, 2010), lower physical functioning levels (Yount & Agree, 2005), a substantial disadvantage in physical performance levels (Zunzunegui, Alvarado, Béland, & Vissandjee, 2009), and lower scores on various cognition measures (Weir, Lay, & Langa, 2014).…”

“…Since the results of a descriptive analysis suggest that the agerelated decline in grip strength may differ by gender, Model 3 also includes the interaction between age and gender. In response to previous findings showing that health and mortality patterns differed by place of residence in India and in China Weir et al, 2014), we conducted additional analyses of gender differences in health for urban and rural subsamples separately. The model specifications were similar to those used in the analyses of the total country-specific samples.…”