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Could nature help children rise out of poverty? Green space and future earnings from a cohort in ten U.S. cities

Author:
Browning, Matthew H.E.M., Rigolon, Alessandro
Source:
Environmental research 2019 pp. 108449
ISSN:
0013-9351
Subject:
Landsat, academic achievement, acreage, autocorrelation, children, cities, green infrastructure, income, models, normalized difference vegetation index, parks, population density, poverty, public lands, temperature, United States
Abstract:
Growing up in poverty is associated with poor health, and the American Dream of upward mobility is becoming an illusion for many low-income children. But nearby green space can support academic achievement, creativity, and emotional regulation, and these traits might help children rise out of poverty.To examine the relationship between recent incomes of children born into poverty in the ten largest U.S. cities and densities of residential green space during childhood.We calculate park proximity, park acreage, new park development, and NDVI greenness for 1980–1990 from Landsat and Trust for Public Land data. We obtain the 2014 income for children born between 1978 and 1982 into families in poverty from The Opportunity Atlas cohort, aggregated at the tract level (n = 5849).Conditional autoregressive (CAR) models of tracts show statistically significant associations between income rank and above-average levels of greenness but not between income rank and park measures, adjusting for individual and neighborhood confounders and spatial autocorrelation. We estimate that, over a 30-year career, children growing up in tracts with the most vegetative cover will earn cumulatively $28,000 more than children growing up in tracts with the least cover, on average. Tracts with lower than average levels of precipitation, higher disadvantage, higher population density, or higher annual temperatures do not show beneficial effects of green space.Greenness may be weakly associated with children rising out of poverty in wetter, cooler, less-dense, more advantaged census tracts.
Agid:
6440792