Correlational finding on Happiness and subject: Life-stress inventories

StudyKye & Park (2014): study KR 2009
TitleHealth-related determinants of Happiness in Korean Adults.
SourceInternational Journal of Public Health, 2014, Vol. 59, 731-738
DOIDOI: 10.1007/s00038-014-0588-0
Public30-69 aged, general population, South Korea 2009
SampleProbability multistage stratified area sample
Respondents N =1530

Author's labelStress
Page in Source 735
Our classificationLife-stress inventories
The psychosocial well/being index in short form was 
used to assess the participants level of psychosocial 
stress. It contain the items as; social performance, 
self-confidence, general well-being and vitality, 
sleeping disturbance and anxiety.
1: low (reference
2: moderate
3: high
Observed distributionLow: 8, Moderate: 75.5, High: 16.5
Error EstimatesCronbach Alpha: ..87
Jang (2000 ) PWI-SF, based on Goldberg & Hillier (1979) 
General Health Questionnaire

Observed Relation with Happiness
O-HL-g-sq-v-4-mD%=+ p < .001
Current stress  
             % happy %unhappy  %difference
- low            97.6    2.4     +95.2
- moderate       65.6    34.4    +31.2
- high           13.4    86.6    -73.2
O-HL-g-sq-v-4-mOR=0,05 p < .05
Moderate stress (vs low) CI95[0,01-0,16]
O-HL-g-sq-v-4-mOR=0.01 p < .05
High stress (vs low) CI95[0,00-0,01] 

OR's controled for:
- socio-demographic factors
  - age
  - marital status
  - income
  - education
- healthy behavior
  - smoking
  - regular exercise
  - healthy eating
- exercise environment
  - parks
  - fitness clubs
  - mountain trails

Appendix 1: Happiness measures used
CodeFull Text
O-HL-g-sq-v-4-mSelfreport on single question

In general, how would you describe your happiness?
4 very happy
3 mostly happy
2 a little bit happy
1 not happy at all

Appendix 2: Statistics used
Type: descriptive statistic only.
Measurement level: Correlate level: dichotomous, but nominal or ordinal theoretically possible as well. Happiness level: dichotomous
Range: [-100; +100]

Meaning: the difference of the percentages happy people at two correlate levels.
OROR: Odds ratio in binary logistic regression.

Happiness is a binary or dichotomous variable with Happy =1 and Unhappy=0.

OR < 1 indicates that the odds of being happy-to-being unhappy
decreases by a factor OR when

1) the corresponding metric correlate increases by one unit
2) the corresponding category of a categorical correlate is compared to the reference category.

OR > 1 indicates an increase by a factor OR for both the above cases.
Ruut Veenhoven, World Database of Happiness, Collection of Correlational Findings, Erasmus University Rotterdam.