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. 2021 Nov 24;10(12):2907. doi: 10.3390/foods10122907

Table 4.

Cluster description: sociodemographic, lifestyle and food consumption patterns across clusters.

Cluster A
n = 205
(29.41%)
Cluster B
n = 172
(24.68%)
Cluster C
n = 206
(29.56%)
Cluster D
n = 114
(16.36%)
Pearson Chi-Quadrat Asymp. Sig. (Bilateral)
Sociodemographic characteristics
Age Ø in years 1 47.28 48.34 56.85 43.1 300.059 0.000
Share of woman (%) 1 42.9 ** 56.4 53.4 54.4 8.335 0.040
Place of living (%) 1,2 53.439 0.182
North 16.0 16.9 22.3 21.1
East 28.3 ** 16.2 17.1 13.3
West 33.7 33.7 34.9 42.1
South 22.0 33.1 25.7 23.5
Household income after taxes (%) 1,3 20.877 0.286
Under €900 8.8 8.7 6.7 4.0
€900 to €1499 13.5 9.9 11.8 13.9
€1500 to €1999 13.0 13.0 8.7 15.7
€2000 to €2499 15.0 12.4 16.9 21.8
€2500 to €2999 9.8 14.9 19.0 14.9
€3000 to €3499 14.5 11.2 13.8 8.9
€3500 and more 25.4 29.8 23.1 20.8
Education (%) 1,4 29.831 0.095
Brief education 17.1 19.8 16.4 21
Middle education 40.0 33.1 39.9 28
Higher education 42.9 47.1 43.7 50.9
Occupation (%) 1 90.418 0.000
Student/Trainee 5.8 14.0 5.8 17.5 *
Employee 54.1 *** 34.8 26.7 *** 47.4
Self-employed 3.9 4.7 10.2 *** 0.0
Public service 13.7 15.1 14.1 10.6
Housewife/men 1.0 8.7 *** 3.4 3.5
Retired 21.5 22.7 39.8 21.0
Healthy lifestyle (%)
Smoke 17.1 17.4 20.9 22.8 2.266 0.519
Exercise regularly 47.3 *** 69.8 *** 49.5 * 70.2 ** 32.656 0.000
Consume alcohol regularly 32.2 27.9 37.4 36.0 4.273 0.233
Food consumption patterns
Familiarity with blueberry characteristics (%) 5 14.7 *** 41.9 47.5 ** 64.00 *** 115.174 0.000
Dietary preference (%) 1
Vegan 1.5 8.7 *** 0.5 * 4.4 37.869 0.000
Vegetarian 3.8 7.6 12.6 * 8.8
Meat eater 85.9 72.1 * 81.1 76.3
Other 8.8 11.6 5.8 10.5
Blueberry consumption (%) 1 15.743 0.610
Daily 0.9 0.00 1.9 3.5
Multiple times per week 14.2 12.2 11.2 14.9
Once per week 13.2 16.3 12.1 15.8
Repeatedly within one month (but not every week) 18.5 19.2 17.9 18.4
Approximately once a month 12.7 13.4 9,7 7.0
Less than once a moth 33.7 31.9 39.3 30.7
Never 6.8 6.9 7.7 9.7
Fruit consumption (%) 1
Daily 36.6 45.4 38.4 36.8 9.066 0.170
Multiple times per week (but not daily) 49.3 44.8 49.0 57.0
Once per week 14.2 9.9 12.6 6.1
Repeatedly within one month (but not every week) 0.00 0.00 0.00 0.00
Approximately once a month 0.00 0.00 0.00 0.00
Less than once a moth 0.00 0.00 0.00 0.00
Fruit purchase frequency (%) 1 18.935 0.396
Daily 3.4 1.7 1.9 6.1
Multiple times per week 40.9 40.7 34.5 45.6
Once per week 43.9 47.1 53.8 40.4
Repeatedly within one month (but not every week) 7.3 6.9 7.8 5.3
Approximately once a month 1.9 2.3 1.9 1.8
Less than once a moth 2.5 0.0 0.0 0.9
Place of fruit purchase (%) 1 40.513 0.046
Discounter 38.0 23.8 25.7 23.7
Supermarket/convenience store 52.7 52.3 58.7 57.9
Farmers market/Sustainable production focused stores 8.8 22.7 15.1 18.5
Internet 0.0 0.6 0.5 0.0
Other 0.5 0.6 0.0 0.0

Level of significance: * = p ≤ 0.1, ** = p ≤ 0.05, and *** = p ≤ 0.01 indicate a significant difference between clusters between the expected and observed quantity. For all items, the Bonferroni adjustment has been applied to prevent type I errors. 1 Only one answer was possible regarding the represented question. 2 North: Schleswig-Holstein, Hamburg, Bremen, Lower Saxony, Mecklenburg-Vorpommern; East: Berlin, Brandenburg, Saxony-Anhalt, Saxony, Thuringia; South: Bavaria, Baden-Wuertemberg; West: North Rhine-Westphalia, Hessen, Rhineland-Palatinate, Saarland. 3 Independent of the marital status and resulting possible adjustments of the household income structure. 4 Brief education: no school leaving certificate/lower secondary school/primary school; Middle education: secondary school, polytechnic school, master school; Higher education: grammar school, university (the highest achieved level of education had to be indicated). 5 Question “I’m very familiar with the characteristics of fresh blueberries” queried on a 5-point Likert scale (from +2 = fully agree to −2 = fully disagree). Characteristics 2 = fully agree and 1 = agree were aggregated and are displayed here. Source: Authors’ calculation. Bold is to distinguishing categories from subcategories.