Table 1: Predicting poor health with scenicness and greenspace.

From: Quantifying the Impact of Scenic Environments on Health

 All areasUrbanSuburbanRural
Scenicness−0.008***−0.007*−0.005**−0.012***
Greenspace−0.008−0.0010.020*0.004
Income Deprivation1.684***1.788***1.416***1.024***
Employment Deprivation3.200***3.114***3.310***4.027***
Education Deprivation0.003***0.003***0.003***0.006***
Housing Deprivation−0.001***0.000−0.001***−0.001**
Crime0.009***−0.0040.007*0.013***
Living Deprivation0.000***0.001***0.000*0.000
AIC−10938−1305−5038−5458
No of observations16907394477815182
  1. Regression coefficients for CAR models predicting standardized rates of reports of poor health using scenicness and greenspace. In these models, a range of socioeconomic deprivation variables are controlled for. Models are built for England as a whole, and for urban, suburban and rural areas separately. The analysis is carried out at the level of Lower Layer Super Output Areas, such that each data point relates to an area inhabited by roughly 1,600 people. Lower ratings of scenicness are significantly associated with reports of worse health across England as a whole, as well as across urban, suburban and rural areas. However, greenspace only bears a relationship to health in suburban areas, where more greenspace is in fact positively correlated with worse health. *p < 0.05, **p < 0.01, ***p < 0.001.