Statin use is not associated with inflammation among Chilean women of Mapuche and non-Mapuche ancestry with gallstones

Figures & data

Table 1. Demographic and medical characteristics of Mapuche and non-Mapuche Chilean women by statin use from the Chile BiLS cohort (N = 400).

Characteristic	Mapuche women			Non-Mapuche women
	Statin use (N = 99)	No statin use (N = 101)	P-value ^†	Statin use (N = 100)	No statin use (N = 100)	P-value^†
Age, years, mean (SD)	59.4 (6)	59.5 (6)	0.89 ^§	59.8 (6)	59.7 (6)	0.94^§
Education level¸ n (%)
– 0–8 years	73 (74)	76 (75)	0.3	44 (44)	52 (52)	0.4
– 9–12 years	23 (23)	19 (19)		46 (46)	42 (42)
– ≥13 years	2 (2)	6 (6)		10 (10)	6 (6)
– Missing	1 (1)	0 (0)		0 (0)	0 (0)
Monthly family income, n (%)
– ≤CLP $250,000	59 (60)	57 (56)	0.93	56 (56)	49 (49)	0.52
– >CLP $250,000	26 (26)	23 (23)		34 (34)	38 (38)
– Missing	14 (14)	21 (21)		10 (10)	13 (13)
Health coverage,^‡ n (%)
– FONASA Group A	54 (55)	61 (60)	0.63	43 (43)	38 (38)	0.64
– FONASA Group B	24 (24)	18 (18)		41 (41)	41 (41)
– FONASA Group C	1 (1)	2 (2)		5 (5)	5 (5)
– FONASA Group D	3 (3)	6 (6)		8 (8)	5 (5)
– Unknown/none	17 (17)	14 (14)		3 (3)	11 (11)
BMI in kg/m^2, mean (SD)	33.0 (5)	32.6 (6)	0.6 ^§	32.1 (6)	30.6 (7)	0.07 ^§
Obese (BMI ≥30 kg/m^2), n (%)	71 (72)	71 (70)	0.95	61 (61)	45 (45)	0.03
Waist circumference in cm, mean (SD)	103.9 (12)	102.5 (12)	0.42 ^§	99.5 (12)	96.9 (14)	0.14 ^§
Hip circumference in cm, mean (SD)	111.4 (10)	110.6 (11)	0.62 ^§	109.3 (11)	107.6 (12)	0.32 ^§
Diabetes diagnosis, n (%)	32 (32)	22 (22)	0.12	49 (49)	18 (18)	<0.001
Ever smoker, n (%)	3 (3)	7 (7)	0.36	18 (18)	21 (21)	0.72
Gallstones, n (%)
– 1 stone	28 (28)	43 (43)	0.10	43 (43)	39 (39)	0.37
– ≥2 stones	47 (47)	42 (42)		40 (40)	49 (49)
– Unknown	24 (24)	16 (16)		17 (17)	12 (12)
Recruitment method, n (%)
– Door-to-door contact in urban areas	7 (7)	6 (6)	0.20	22 (22)	16 (16)	0.41
– Local health/community centers, hospitals, media	68 (69)	81 (80)		67 (67)	67 (67)
– Ultrasonography, surgical consultation and cholecystectomy waiting lists	20 (20)	10 (10)		11 (11)	16 (16)
– Invitation by local health center	3 (3)	4 (4)		0 (0)	1 (1)
Diet, n (%)
– Consumption of fresh green chilis	56 (57)	55 (54)	0.75	40 (40)	41 (41)	0.95
– Consumption of fresh red chilis	41 (41)	37 (37)	0.51	24 (24)	21 (21)	0.73
– Consumption of dried red chilis	35 (35)	31 (31)	0.51	27 (27)	26 (26)	1.00
– Consumption of red chili paste	34 (34)	27 (27)	0.27	22 (22)	26 (26)	0.65
– Consumption of fried food	57 (58)	62 (61)	0.82	51 (51)	53 (53)	0.89
Regular use of Aspirin/NSAID	38 (38)	12 (12)	<0.001	44 (44)	15 (15)	<0.001

† p-value calculated using a chi-square test for the categorical variables except where noted.

‡ FONASA groups A-D are hierarchical classifications used to determine the proportion of healthcare costs covered by the government, based on taxable individual income. FONASA Group A has the lowest income level and receives the highest level of governmental coverage of healthcare costs.

§ p-value calculated using a t-test.

Chile BiLS: Chile biliary longitudinal study; CLP: Chilean pesos; cm: Centimeters; FONASA: Fondo Nacional de Salud (Chile's public health insurance system); kg: Kilogram; m: Meter; n: Number; SD: Standard deviation.

Table 2. Coefficients for association between inflammation marker and statin use by ancestry estimated from adjusted linear regression models except where noted.

Marker name	All women		Mapuche women		Non-Mapuche women		Interaction p-value
	Estimate	p-value	Estimate	p-value	Estimate	p-value
CCL20	-0.08	0.41	-0.08	0.56	-0.07	0.58	0.99
CXCL10	-0.04	0.64	-0.01	0.96	-0.05	0.65	0.43
IL-6	-0.14	0.07	-0.14	0.19	-0.13	0.29	0.97
IL-8	-0.08	0.27	0.04	0.70	-0.19	0.06	0.08
ADA	-0.01	0.78	0.03	0.59	-0.03	0.55	0.10
ARTN^†	-0.04	0.87	-0.12	0.72	0.00	1.00	0.95
AXIN1	0.00	0.50	0.02	0.04	-0.01	0.19	0.01
Beta-NGF	-0.05	0.04	-0.04	0.31	-0.06	0.09	0.35
CASP-8	-0.02	0.84	0.06	0.51	-0.08	0.49	0.19
CCL11	-0.02	0.72	0.03	0.61	-0.07	0.34	0.17
CCL19	0.04	0.75	0.11	0.48	-0.06	0.71	0.87
CCL23	0.05	0.30	0.05	0.35	0.04	0.59	0.67
CCL25	0.04	0.48	0.13	0.09	-0.05	0.52	0.05
CCL28	-0.07	0.11	-0.04	0.54	-0.12	0.08	0.34
CCL3	0.08	0.18	0.17	0.08	-0.01	0.84	0.07
CCL4	0.03	0.67	0.10	0.28	-0.04	0.64	0.15
CD244	-0.05	0.14	-0.04	0.45	-0.06	0.22	0.45
CD40	0.02	0.59	0.09	0.16	-0.05	0.41	0.04
CD5	-0.01	0.88	0.02	0.71	-0.03	0.51	0.17
CD6	0.02	0.64	0.06	0.37	-0.02	0.82	0.18
CD8A	0.02	0.79	-0.08	0.36	0.10	0.35	0.27
CDCP1	-0.11	0.05	-0.04	0.59	-0.17	0.04	0.21
CSF-1	-0.01	0.62	0.00	0.91	-0.02	0.62	0.56
CST5	-0.02	0.76	-0.01	0.89	-0.03	0.64	0.48
CX3CL1	-0.04	0.41	0.05	0.41	-0.12	0.04	0.01
CXCL1	0.02	0.77	0.04	0.72	0.06	0.60	0.82
CXCL11	-0.02	0.83	0.05	0.71	-0.06	0.64	0.39
CXCL5	-0.03	0.72	-0.09	0.43	0.07	0.56	0.43
CXCL6	0.02	0.81	0.02	0.89	0.06	0.62	0.87
CXCL9	-0.04	0.67	0.05	0.68	-0.09	0.47	0.12
DNER	-0.01	0.64	-0.01	0.70	-0.01	0.86	0.55
EN-RAGE	-0.07	0.50	0.13	0.34	-0.22	0.12	0.02
FGF-19	-0.07	0.44	0.03	0.83	-0.15	0.25	0.16
FGF-21	-0.03	0.74	0.14	0.35	-0.22	0.12	0.12
FGF-23^‡	0.33	0.09	0.44	0.11	0.23	0.44	0.42
FGF-5^†	0.18	0.41	0.09	0.78	0.27	0.40	0.70
FLT3L	0.05	0.19	0.09	0.09	-0.01	0.94	0.30
GDNF	-0.05	0.22	-0.03	0.64	-0.08	0.12	0.36
HGF	-0.04	0.37	0.05	0.38	-0.12	0.07	0.05
IL-2RB^†	0.12	0.62	0.20	0.57	0.00	0.99	0.27
IL-5^‡	-0.08	0.68	0.17	0.53	-0.45	0.12	0.12
IL-7	0.03	0.62	0.04	0.63	0.05	0.51	0.62
IL-10	0.00	0.94	0.08	0.19	-0.07	0.35	0.10
IL-10RA^‡	-0.13	0.52	-0.36	0.19	0.08	0.78	0.31
IL-10RB	-0.02	0.58	0.02	0.59	-0.06	0.19	0.09
IL-12B	0.03	0.67	0.08	0.35	-0.03	0.73	0.34
IL-15RA	-0.02	0.54	0.01	0.78	-0.04	0.19	0.07
IL-17A^‡	-0.05	0.80	0.05	0.85	-0.16	0.57	0.71
IL-17C^‡	0.09	0.64	0.11	0.68	0.13	0.64	0.97
IL18	-0.03	0.64	0.13	0.11	-0.22	0.02	0.01
IL-18R1	-0.04	0.33	0.04	0.46	-0.12	0.08	0.03
IL-20RA^‡	-0.12	0.56	0.12	0.66	-0.42	0.15	0.15
IL-24^†	-0.22	0.46	-0.22	0.62	-0.29	0.49	0.79
LAP-TGF-beta-1	0.02	0.72	0.02	0.81	0.02	0.79	0.93
LIF-R	-0.05	0.06	-0.02	0.55	-0.08	0.03	0.15
MCP-1	0.04	0.44	0.08	0.25	0.02	0.75	0.54
MCP-2	-0.05	0.60	0.05	0.73	-0.11	0.39	0.39
MCP-3	-0.05	0.46	-0.04	0.71	-0.04	0.63	0.73
MCP-4	0.04	0.58	0.11	0.31	0.01	0.95	0.44
MMP-1	-0.09	0.42	-0.06	0.65	-0.13	0.44	0.62
MMP-10	-0.03	0.64	0.00	0.96	-0.03	0.73	0.66
NRTN^†	-0.03	0.90	0.41	0.20	-0.65	0.09	0.04
NT-3	-0.05	0.19	-0.02	0.60	-0.08	0.16	0.45
OPG	-0.02	0.51	0.06	0.18	-0.10	0.07	0.01
OSM	-0.13	0.23	0.10	0.48	-0.31	0.05	0.02
PD-L1	-0.04	0.41	0.03	0.73	-0.12	0.09	0.13
SCF	0.11	0.01	0.06	0.24	0.13	0.03	0.42
SIRT2	-0.03	0.82	0.02	0.90	-0.07	0.69	0.54
SLAMF1	-0.13	0.003	-0.10	0.12	-0.15	0.02	0.20
ST1A1	0.01	0.95	0.29	0.04	-0.28	0.10	0.01
STAMBP	0.02	0.79	0.07	0.54	-0.02	0.89	0.40
TGF-alpha	-0.04	0.52	0.08	0.29	-0.15	0.09	0.01
TNFB	-0.01	0.78	-0.05	0.44	0.03	0.58	0.32
TNFRSF9	0.03	0.54	0.10	0.21	-0.04	0.54	0.11
TNFSF14	-0.06	0.48	0.12	0.35	-0.24	0.07	0.02
TRAIL	-0.01	0.66	-0.01	0.83	-0.03	0.40	0.73
TRANCE	-0.10	0.10	-0.13	0.13	-0.10	0.25	0.49
TWEAK	0.04	0.25	0.06	0.13	0.01	0.81	0.30
UPA	-0.05	0.15	-0.02	0.62	-0.07	0.17	0.32
VEGFA	-0.07	0.25	-0.03	0.74	-0.11	0.25	0.51
4E-BP1	0.02	0.88	-0.03	0.87	0.05	0.79	0.87

All models are adjusted for age group (50–54, 55–59, 60–64, 65–69, or 70–74 years), waist circumference (continuous), diabetes (yes or no), smoking status (ever or never), education level (0–8, 9–12, or ≥13 years of schooling), health insurance category (FONASA group A, B, C, D, or unknown/none), fresh red chili and fried food consumption.

† Coefficients were estimated with logistic regression.

‡ Coefficients were estimated with ordinal regression.