Analyzing Personal Happiness from Global Survey and Weather Data: A Geospatial Approach.

Ta-Chien Chan,Dongmei Li,Yi-Fan Peng,Yang-Chih Fu,Jia-Hong Tang,I-Chun Fan,Maw-Kae Hor

doi:10.1371/journal.pone.0153638

Abstract

Past studies have shown that personal subjective happiness is associated with various macro- and micro-level background factors, including environmental conditions, such as weather and the economic situation, and personal health behaviors, such as smoking and exercise. We contribute to this literature of happiness studies by using a geospatial approach to examine both macro and micro links to personal happiness. Our geospatial approach incorporates two major global datasets: representative national survey data from the International Social Survey Program (ISSP) and corresponding world weather data from the National Oceanic and Atmospheric Administration (NOAA). After processing and filtering 55,081 records of ISSP 2011 survey data from 32 countries, we extracted 5,420 records from China and 25,441 records from 28 other countries. Sensitivity analyses of different intervals for average weather variables showed that macro-level conditions, including temperature, wind speed, elevation, and GDP, are positively correlated with happiness. To distinguish the effects of weather conditions on happiness in different seasons, we also adopted climate zone and seasonal variables. The micro-level analysis indicated that better health status and eating more vegetables or fruits are highly associated with happiness. Never engaging in physical activity appears to make people less happy. The findings suggest that weather conditions, economic situations, and personal health behaviors are all correlated with levels of happiness.

Highlights

Happiness is one of the most important human emotions and a key predictor of many important life outcomes
The research findings based on the geospatial approach shed new light on the substantive research subject
The ordinal logistic analyses indicated that people living under the conditions of higher temperature, higher visibility, a little wind, lower dew point, and an improving economic situation felt happier

Summary

Introduction

Happiness is one of the most important human emotions and a key predictor of many important life outcomes. Several studies have examined how factors in the external environment and human behaviors affect happiness [1, 2]. Those factors can be roughly divided into either. A Geospatial Approach to Analyzing Personal Happiness macro or micro effects The former include weather effects, such as temperature [3], sunlight [4, 5], seasonal climate change [6], and the societal socio-economic environment [7], while the latter include individuals’ demographic factors such as gender [8], age [4], and personal health behaviors like smoking [9], exercise [10], and eating more fruits and vegetables [11]. The spatiotemporal resolution of the weather data, might have deeply affected this inference

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