Study | Warner et al. (2017): study US New England 2013 |

Title | Fruit and Vegetable Intake Predicts Positive Affect |

Source | Journal of Happiness Studies,2017, Vol.18, 809 - 826 |

URL | https://link.springer.com/article/10.1007/s10902-016-9749-6 |

DOI | DOI: 10.1007/s10902-016-9749-6 |

Public | Students, New England, United States of America, 2013 |

Sample | Sampling not reported |

Non-Response | |

Respondents N = | 1263 |

Correlate | |

Author's label | Fruit and Vergetable Intake (FVI) |

Page in Source | 819 |

Our classification | Healthy eating |

Operationalization | Self report on questions on typical daily servings of fruits and vegetables in the last month (FVI) Rated 0 to 8+ |

Observed distribution | M: 2,02, SD: 2,38 |

Observed Relation with Happiness | ||

Happiness Measure | Statistics | Elaboration/Remarks |

A-BW-?-mq-v-5-a | AoC=+ p < .014 | Positive Affect only. Negative affect ns Unaffected by gender Linear relationship |

Appendix 1: Happiness measures used

Code | Full Text |

A-BW-?-mq-v-5-a | Selfreport on 20 questions: Lead item not reported. A nervous B distressed C afraid D jittery E irritable F upset G scared H excited I ashamed J guilty K hostile L active M determined N inspired O enthusiastic P alert Q attentive R proud S strong T interested Rated: 1: slightly/not at all . . 5 extremely Negative affect score (NAS): A to K Positive affect score (PAS): L to T Affect Balance Score (ABS): PAS - NAS Name: Watson's PANAS version not reported |

Appendix 2: Statistics used

Symbol | Explanation |

AoC | ANALYSIS of COVARIANCE (ANCOVA) Type: statistical procedure Measurement level: Correlates: at least one nominal and at least one metric, Happiness: metric. Just as in an ANOVA, in an ANCOVA the total happiness variability, expressed as the sum of squares, is partitioned into several parts, each of which is assigned to a source of variability. At least two of those sources are the variability of the correlates, in case there is one for each correlate, and always one other is the residual variability, which includes all unspecified influences on the happiness variable. Each sum of squares has its own number of degrees of freedom (df), which sum up to Ne -1 for the total variability. If a sum of squares (SS) is divided by its own number of df, a mean square (MS) is obtained. The ratio of two correctly selected mean squares has an F-distribution under the hypothesis that the corresponding association has a zero-value. In an Analysis of Covariance, the treatment means for all levels of the nominal correlate are 'adjusted' for differences in the mean values of the metric correlate. |

Ruut Veenhoven, World Database of Happiness, Collection of Correlational Findings, Erasmus University Rotterdam.

https://worlddatabaseofhappiness.eur.nl