title: Health-promoting and health-risk behaviors: theory-driven analyses of multiple health behavior change in three international samples.
abstract: BACKGROUND
  Co-occurrence of different behaviors was investigated using the theoretical underpinnings of the Transtheoretical Model, the Theory of Triadic Influence and the concept of Transfer.
  
  
  OBJECTIVE
  To investigate relationships between different health behaviors' stages of change, how behaviors group, and whether study participants cluster in terms of their behaviors.
  
  
  METHODS
  Relationships across stages for different behaviors were assessed in three studies with N = 3,519, 965, and 310 individuals from the USA and Germany by telephone and internet surveys using correlational analyses, factor analyses, and cluster analyses.
  
  
  RESULTS
  Consistently stronger correlations were found between nutrition and physical activity (r = 0.16-0.26, p < 0.01) than between non-smoking and nutrition (r = 0.08-0.16, p < 0.03), or non-smoking and physical activity (r = 0.01-0.21). Principal component analyses of investigated behaviors indicated two factors: a "health-promoting" factor and a "health-risk" factor. Three distinct behavioral patterns were found in the cluster analyses.
  
  
  CONCLUSIONS
  Our results support the assumption that individuals who are in a higher stage for one behavior are more likely to be in a higher stage for another behavior as well. If the aim is to improve a healthy lifestyle, success in one behavior can be used to facilitate changes in other behaviors--especially if the two behaviors are both health-promoting or health-risky. Moreover, interventions should be targeted towards the different behavioral patterns rather than to single behaviors. This might be achieved by addressing transfer between behaviors.
authors.affiliation: Health Psychology/ Health Promotion, Freie Universität Berlin & Maastricht University, Habelschwerdter Allee 45, 14195, Berlin, Germany. s.lippke@fu-berlin.de
authors.forename: Sonia
authors.initials: S
authors.lastname: Lippke
authors.forename: Claudio R
authors.initials: CR
authors.lastname: Nigg
authors.forename: Jason E
authors.initials: JE
authors.lastname: Maddock
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016000:Cluster Analysis; D003920:Diabetes Mellitus / Q000453:epidemiology*; D005260:Female; D005858:Germany / Q000453:epidemiology; D015438:Health Behavior; D006801:Humans; D020407:Internet; D008297:Male; D008875:Middle Aged; D012307:Risk Factors; D012907:Smoking / Q000453:epidemiology*; D014163:Transfer, Psychology / Q000502:physiology*; D014481:United States / Q000453:epidemiology; D055815:Young Adult