Univariate logistic regression

Socio-demographic factors

In the unadjusted models, several socio-demographic characteristics were significantly associated with dysgeusia at the prespecified level of significance (p<0.25). This included age, which demonstrated a positive association, with each one-year increase at screening yielding a 2 % increase in the odds of taste dysfunction (OR=1.020, 95 % CI: 1.004–1.036; p=0.019). Race was also significantly associated with taste problems (p=0.008), driven primarily by elevated odds among Non-Hispanic Black (OR=2.660, 95 % CI: 1.400–5.070) and Non-Hispanic White (OR=2.230, 95 % CI: 1.060–4.690) sub-populations relative to the Non-Hispanic Asian group that served as the reference category.

Other demographic factors that were associated with taste problems included the level of educational attainment (p=0.039) and the annual household income (p=0.025). Notably, individuals with a low income (<$20,000) exhibited nearly twice the odds of taste dysfunction compared to those in the high-income bracket (OR=1.910, 95 % CI: 1.050–3.480). Furthermore, being born inside the United States significantly increased the unadjusted odds of reporting taste dysfunction by 53 % (OR=1.530, 95 % CI: 1.080–2.160; p=0.019).

Metabolic serum biomarkers

Univariate screening identified multiple metabolic, liver, and renal biomarkers associated with taste dysfunction. Serum albumin levels demonstrated an inverse relationship (OR=0.310, 95 % CI: 0.130–0.730; p=0.010) while ALT (OR=1.004, p=0.021), AST (OR=1.006, p=0.032), creatinine (OR=1.340, p=0.011), serum glucose (OR=1.010, p=0.034), and LDH (OR=1.010, p=0.016) showed a positive association with taste problems.

Serum potassium (OR=1.460, p=0.170) and bicarbonate (OR=1.060, p=0.210) were positively associated, while sodium (OR=0.950, p=0.150) and chloride (OR=0.930, p=0.008) levels were negatively associated with taste dysfunction.

Several other biochemical factors were significant at the preset level of significance (p<0.25) and are summarized in Table 2.

Independent predictor variable | Odds ratio (95 % CI) | p-Value
Socio-demographic characteristics |  | 
Age (per 1-year increase at screening) | 1.020 (1.004–1.036) | 0.019
Race/Hispanic origin | – | 0.008
Mexican American | 2.020 (0.910–4.470) | 
Other Hispanic | 1.690 (0.810–3.530) | 
Non-Hispanic White | 2.230 (1.060–4.690) | 
Non-Hispanic Black | 2.660 (1.400–5.070) | 
Non-Hispanic Asian/other | 1.000 (reference) | 
Educational attainment (adults 20+) | – | 0.039
Less than 9th grade | 1.350 (0.520–3.550) | 
9th–11th grade (no HS diploma) | 1.230 (0.410–3.670) | 
High school graduate/GED | 0.540 (0.150–1.920) | 
Some college/associate degree | 0.710 (0.260–1.890) | 
College graduate or above | 1.000 (reference) | 
Annual household income | – | 0.025
Low income (<$20,000) | 1.910 (1.050–3.480) | 
Lower-middle ($20,000–$44,999) | 1.740 (0.900–3.370) | 
Middle ($45,000–$74,999) | 0.760 (0.380–1.530) | 
High income (≥$75,000) | 1.000 (reference) | 
Country of birth | – | 0.019
Born inside United States | 1.530 (1.080–2.160) | 
Born outside United States/other | 1.000 (reference) | 
Metabolic serum biomarkers |  | 
Albumin, g/dL | 0.310 (0.130–0.730) | 0.010
Alanine aminotransferase ALT, IU/L | 1.004 (1.001–1.007) | 0.021
Aspartate aminotransferase AST, IU/L | 1.006 (1.001–1.011) | 0.032
Alkaline phosphatase, IU/L | 1.006 (0.990–1.013) | 0.080
Bicarbonate, mmol/L | 1.060 (0.970–1.160) | 0.210
Creatinine, mg/dL | 1.340 (1.080–1.670) | 0.011
Serum glucose, mg/dL | 1.010 (1.000–1.010) | 0.034
Lactate dehydrogenase LDH, IU/L | 1.010 (1.002–1.014) | 0.016
Sodium, mmol/L | 0.950 (0.890–1.020) | 0.150
Potassium, mmol/L | 1.460 (0.840–2.550) | 0.170
Chloride, mmol/L | 0.930 (0.890–0.980) | 0.008
Environmental heavy metals & lipids |  | 
Blood mercury, total, µg/L | 0.950 (0.860–1.040) | 0.220
Blood selenium, µg/L | 1.010 (1.001–1.010) | 0.010
Serum copper, µg/dL | 1.010 (1.001–1.020) | 0.025
Iron, refrigerated, µg/dL | 0.990 (0.980–1.001) | 0.080
Direct HDL-cholesterol, mg/dL | 0.980 (0.970–1.004) | 0.120
Triglycerides, mg/dL | 1.001 (1.000–1.002) | 0.250
Total cholesterol, mg/dL | 0.990 (0.980–1.003) | 0.190
Hematologic & micronutrient indices |  | 
White blood cell count (103 cells/µL) | 1.060 (0.980–1.140) | 0.130
Monocyte number (103 cells/µL) | 1.410 (0.930–2.120) | 0.090
RBC folate, ng/mL | 1.001 (1.000–1.002) | 0.006
5-methyl-tetrahydrofolate, nmol/L | 1.005 (0.990–1.012) | 0.170
5-formyl-tetrahydrofolate, nmol/L | 0.840 (0.620–1.140) | 0.240
Serum fatty acid profiles |  | 
Myristic acid (14:0), µmol/L | 1.001 (0.990–1.003) | 0.170
Pentadecanoic acid (C15:0), µmol/L | 1.020 (1.001–1.040) | 0.040
Palmitic acid (16:0), µmol/L | 1.000 (1.000–1.000) | 0.140
Margaric acid (C17:0), µmol/L | 1.020 (0.990–1.040) | 0.100
Docosanoic acid (22:0), µmol/L | 0.980 (0.960–1.000) | 0.048
Lignoceric acid (24:0), µmol/L | 0.970 (0.950–0.990) | 0.029
Myristoleic acid (14:1n-5), µmol/L | 1.010 (0.990–1.030) | 0.190
Palmitoleic acid (16:1n-7), µmol/L | 1.000 (1.000–1.002) | 0.160
cis-vaccenic acid (18:1n-7), µmol/L | 1.002 (0.990–1.010) | 0.160
Oleic acid (18:1n-9), µmol/L | 1.000 (1.000–1.000) | 0.090
alpha-linolenic acid (18:3n-3), µmol/L | 1.002 (0.990–1.010) | 0.130
gamma-linolenic acid (18:3n-6), µmol/L | 1.010 (0.990–1.020) | 0.240
Eicosatrienoic acid (C20:3n-9), µmol/L | 1.020 (0.990–1.050) | 0.170
Eicosapentaenoic acid (20:5n-3), µmol/L | 1.003 (1.000–1.005) | 0.038
Docosatetraenoic acid (22:4n-6), µmol/L | 1.020 (0.990–1.040) | 0.090
Docosapentaenoic acid (22:5n-3), µmol/L | 1.010 (1.000–1.030) | 0.050
Docosapentaenoic acid (22:5n-6), µmol/L | 1.030 (0.990–1.050) | 0.070

Environmental heavy metals, lipids, and hematologic indices

Among trace minerals and heavy metals, serum selenium (OR=1.010, p=0.010) and serum copper (OR=1.010, p=0.025) were positively associated with taste dysfunction, while mercury (OR=0.950, p=0.220) and iron (OR=0.990, p=0.080) showed inverse associations with dysgeusia.

With respect to lipid profiles, direct HDL-cholesterol (OR=0.980, p=0.120), total cholesterol (OR=0.990, p=0.190), and triglycerides (OR=1.001, p=0.250) showed an inverse relationship with taste problems. Among hematologic and micronutrient indices, white blood cell counts (OR=1.060, p=0.130), monocyte numbers (OR=1.410, p=0.090), 5-methyl-tetrahydrofolate levels (OR=1.005, p=0.170) and RBC folate levels (OR=1.001, 95 % CI: 1.000–1.002; p=0.006) showed a positive association with dysgeusia.

Serum fatty acid profiles

Numerous serum fatty acid species met the univariate threshold (p<0.25) for inclusion in further modeling. Within the saturated fatty acids, pentadecanoic acid (C15:0) (OR=1.020, p=0.040), and margaric acid (C17:0) (OR=1.020, p=0.100) showed a positive association while very-long-chain saturated fatty acids like docosanoic acid (22:0; OR=0.980, p=0.048) and lignoceric acid (24:0; OR=0.970, p=0.029) showed a negative association.

Among unsaturated fatty acid profiles, significant positive associations were found for several including eicosapentaenoic acid (20:5n-3; OR=1.003, p=0.038) docosatetraenoic (22:4n-6; p=0.090) and docosapentaenoic acid (22:5n-3; OR=1.010, p=0.050), oleic acid (18:1n-9; p=0.090), myristoleic (p=0.190), palmitoleic (p=0.160), cis-vaccenic (p=0.160), alpha-linolenic (p=0.130), and eicosatrienoic (p=0.170) acids.