Identification of Salty Dietary Patterns of the Japanese Macroregion

Table 5

Loading scores of cities in dietary patterns (Factors 1 to 3) identified using partial least squares regression analysis.

No.	Name of a city	Factor 1 2015	Factor 1 2018	Factor 2 2013	Factor 2 2018	Factor 3 2013	Factor 3 2018
1	Sapporo-shi	3.62	1.14	−3.29	−4.46	−2.96	−4.29
2	Aomori-shi	11.36	11.78	−0.84	4.55	−3.83	−1.16
3	Morioka-shi	6.67	8.49	1.32	−0.50	2.61	0.08
4	Sendai-shi	4.59	3.05	−1.66	−2.63	2.12	0.11
5	Akita-shi	9.33	7.90	1.12	−1.89	−1.36	−4.79
6	Yamagata-shi	7.70	4.57	5.39	2.06	6.88	1.40
7	Fukushima-shi	4.45	1.60	1.61	−1.14	1.18	−2.49
8	Mito-shi	−0.55	2.24	−3.57	−0.66	−1.51	0.20
9	Utsunomiya-shi	−0.06	0.23	−2.18	−1.73	−1.30	1.30
10	Maebashi-shi	−1.49	1.20	−2.42	−0.35	0.22	2.00
11	Saitama-shi	−0.99	1.02	−4.53	−3.74	1.73	2.15
12	Chiba-shi	1.64	1.44	−5.23	−4.89	0.03	0.76
13	Ku-areas of Tokyo	−2.03	−1.60	−6.13	−5.15	0.61	1.32
14	Yokohama-shi	−0.64	−0.58	−7.02	−4.00	1.40	2.17
15	Niigata-shi	8.94	7.92	−1.62	−1.25	−1.07	−0.47
16	Toyama-shi	2.84	3.96	−0.16	−0.15	−0.37	−1.34
17	Kanazawa-shi	−0.28	1.05	0.20	1.89	−0.20	1.12
18	Fukui-shi	−1.26	−1.93	3.21	−0.63	−0.04	−2.91
19	Kofu-shi	1.01	−0.49	−3.31	0.61	0.40	3.98
20	Nagano-shi	2.39	5.35	0.29	5.73	2.51	7.45
21	Gifu-shi	−2.55	−1.66	0.39	−1.79	−1.18	−0.58
22	Shizuoka-shi	−0.16	−0.64	−4.25	−2.77	0.11	2.43
23	Nagoya-shi	−2.29	−1.61	−2.37	−1.97	−0.50	1.14
24	Tsu-shi	−2.40	−0.86	1.87	−0.44	0.75	−1.56
25	Otsu-shi	−4.52	1.31	−0.33	−1.13	1.51	0.57
26	Kyoto-shi	−1.80	−0.66	−0.88	−2.48	3.53	0.42
27	Osaka-shi	−4.26	−1.47	−0.71	−0.80	0.61	−0.74
28	Kobe-shi	−4.72	−4.75	0.11	−1.67	0.92	0.39
29	Nara-shi	−1.43	−0.24	0.54	−1.87	1.18	−0.17
30	Wakayama-shi	−3.76	−2.03	0.93	2.59	−1.32	0.42
31	Tottori-shi	2.29	2.43	3.26	4.22	−4.92	−3.03
32	Matsue-shi	2.55	0.94	4.62	−0.05	−0.08	−2.51
33	Okayama-shi	−4.19	−2.41	1.09	3.45	−1.38	3.09
34	Hiroshima-shi	−1.55	−1.08	−0.05	2.29	−1.41	0.10
35	Yamaguchi-shi	−1.55	−0.47	3.70	3.20	−1.81	−1.96
36	Tokushima-shi	−1.68	−4.09	1.75	1.76	0.35	−0.75
37	Takamatsu-shi	−3.18	−1.46	2.54	3.01	0.05	0.49
38	Matsuyama-shi	−3.64	−3.31	3.11	3.71	−1.13	−0.20
39	Kochi-shi	−1.22	−3.09	6.63	2.30	2.60	−0.75
40	Fukuoka-shi	−3.06	−3.77	0.16	−0.94	0.46	−0.48
41	Saga-shi	2.00	−0.63	2.54	1.77	−2.88	−1.48
42	Nagasaki-shi	−1.81	−2.07	1.32	1.26	−2.26	−1.19
43	Kumamoto-shi	−1.99	−4.39	2.78	3.41	−1.26	−1.43
44	Oita-shi	0.09	−1.22	5.65	3.57	1.62	−0.99
45	Miyazaki-shi	−3.01	−3.60	3.47	4.66	−0.87	0.05
46	Kagoshima-shi	−2.39	−3.68	1.84	3.77	−2.06	0.06
47	Naha-shi	−6.05	−8.74	0.10	−3.18	0.80	−1.15
48	Kawasaki-shi	−0.42	−0.41	−6.40	−4.47	1.45	2.40
49	Sagamihara-shi	1.09	2.02	−3.83	−3.84	1.07	1.60
50	Hamamatsu-shi	−1.62	−1.80	−1.77	−0.37	−1.61	1.44
51	Sakai-shi	−0.24	−2.77	0.16	−0.67	2.72	−0.19
52	Kitakyushu-shi	0.45	−1.92	1.53	1.76	−2.06	−2.60
Spearman’s correlation coefficient between 2013 and 2018		0.77		0.71		0.38

Family Income and Expenditure Survey in 2013/2018. ; . Numbers 1 to 47 are prefectural capitals and 48 to 52 are ordinance-designated cities. The numbers correspond to those in Supporting Figure S1 (distribution map of prefectures in Japan).