Dataset Information

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

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.

SUBMITTER: Peng YF

PROVIDER: S-EPMC4831775 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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

Peng Yi-Fan YF Tang Jia-Hong JH Fu Yang-chih YC Fan I-chun IC Hor Maw-Kae MK Chan Ta-Chien TC

PloS one 20160414 4

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 natio ...[more]

PMID: 27078263

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Project description:ObjectivesThe objective of the present study was to identify the factors that influence the happiness index of community residents, by considering personal and regional aspects, and to use as evidence of efforts for improvement of the happiness index.MethodsThe study was conducted based on information from 16,270 participants who met the data requirement among those who participated in the 2011 South Gyeongsang Community Health Survey. Of the factors that can influence the happiness index, socioeconomic characteristics, health behavior, morbidity, and healthcare use, social contact, and participation in social activities were classified as personal factors; for regional factors, data from the 2010 census were used to extrapolate the regional deprivation indices at the submunicipal-level (eup, myeon, and dong) in South Gyeongsang Province. The happiness index for each characteristic was compared to that for others via t-test and ANOVA, and multilevel analysis was performed, using four models: a basic model for identification of only random effects, model 1 for identification of personal factors, model 2 for identification of regional factors, and model 3 for simultaneous consideration of both personal and regional factors.ResultsThe mean happiness index was 63.2 points (64.6 points in males and 62.0 points in females), while the mean deprivation index was -1.58 points. In the multilevel analysis, the regional-level variance ratio of the basic model was 10.8%, confirming interregional differences. At the personal level, higher happiness indices were seen in groups consisting of males with high educational level, high income, high degree of physical activity, sufficient sleep, active social contact, and participation in social activities; whereas lower happiness indices were seen in people who frequently skipped breakfast, had unmet healthcare needs, and had accompanying diseases, as well as those with higher deprivation index.ConclusionsThe study confirmed that the happiness index of community residents was influenced by not only personal aspects but also various regional characteristics. To increase the happiness index, interests at both personal and regional levels, as well as community emphasis on creating social rapport and engaging in selective efforts, are needed in vulnerable regions with relatively high deprivation index.

Dataset Information

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

Publications

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

Similar Datasets

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