INTRODUCTION
Non-alcoholic fatty liver disease (NAFLD) is the most prevalent liver disease worldwide and includes non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH). Both conditions result from chronic fat accumulation in the liver, which can progress to fibrosis, cirrhosis, and hepatocellular carcinoma
1
,
2
.
In Europe and the United States, NAFLD represents one of the leading causes of chronic liver disease, with its prevalence increasing from 47% to 75% between 1988 and 2008, in association with metabolic risk factors such as obesity, type 2 diabetes mellitus (T2DM), and hypertension
3
.
In 2016, the global prevalence of NAFLD was 25.2%, with the highest rates in the Middle East (31.8%) and South America (30.5%), and the lowest in Africa (13.5%)
4
.
In Mexico, prevalences have been reported between 10.3% and 30.9%, although in populations with obesity or T2DM these range from 70% to 86%
5
–
8
.
This is related to the global increase in obesity and diabetes. According to the World Health Organization (WHO), in 2022, 43% of adults over 18 years old (2.5 billion) were overweight, and 16% (890 million) had obesity
9
.
The 2022 World Obesity Atlas, published by the World Obesity Federation, projects that by 2030, one billion people will live with obesity, equivalent to one in every five women and one in every seven men
10
.
Meanwhile, the 2021 Diabetes Atlas of the International Diabetes Federation (IDF) estimates that 537 million adults have diabetes (10.5%), a figure that will increase to 643 million in 2030 and 783 million in 2045, representing a 46% increase
11
.
These figures reflect the close association between NAFLD, obesity, and diabetes, and the need for preventive strategies and early diagnosis in vulnerable populations.
In Mexico, deaths due to cirrhosis secondary to NAFLD increased by 128% between 1991 and 2021, reaching 6.9 deaths per 100,000 inhabitants, with similar patterns in Morelos
12
, highlighting the need for more accurate and accessible diagnostic methods.
The treatment of NAFLD combines non-pharmacological interventions, such as diet and exercise, with pharmacological options. Exercise improves clinical and biochemical parameters depending on its type, intensity, and frequency
13
–
15
.
Low-carb diets
15
and the Mediterranean diet offer biochemical benefits, although without consistent clinical improvements
16
.
While adherence is key
17
, pharmacological treatment is also essential.
The main international guidelines — the European Association for the Study of the Liver, the European Association for the Study of Diabetes, the European Association for the Study of Obesity, the American Association for the Study of Liver Diseases, and the National Institute for Health and Care Excellence — recommend a range of drugs targeting pathophysiological mechanisms such as oxidative stress, insulin resistance, and inflammation.
These include vitamin E, polyphenols, glutathione, bile acids (ursodeoxycholic acid, obeticholic acid), oral antidiabetic drugs (pioglitazone, metformin, DPP-4 inhibitors, GLP-1 agonists), omega-3 fatty acids, berberine, statins, fibrates, pentoxifylline, microbiome modulators, and antifibrotic agents like pirfenidone
18
–
22
.
Pharmacotherapy should be individualized according to the patient, the stage of the disease, and comorbidities. Some medications, originally indicated for other diseases, have shown benefits in the management of NAFLD, reinforcing the need for a comprehensive approach. However, combining these treatments with sustained lifestyle changes remains essential for effective management. Therefore, the aim of this study was to determine the pharmacological treatment and other factors associated with fatty liver disease in patients with T2DM.
Methodology
Design and study area
A cross-sectional analytical study was conducted in the state of Morelos, Mexico. The research was carried out at the Family Medicine Unit No. 3 of the Mexican Social Security Institute (IMSS), specifically at the DiabetIMSS Module, where integrated services are provided to patients with T2DM. The study was designed to evaluate the association between pharmacological treatment and the presence of NAFLD in this population.
Population and sample
The study population consisted of patients with a confirmed diagnosis of T2DM, registered at the DiabetIMSS Module of the Family Medicine Unit No. 3 of IMSS. Adults aged 18 years or older, under pharmacological treatment for T2DM, who expressed their willingness to participate by signing the informed consent, were included. Patients with a history of hepatitis C, HIV infection, or documented chronic alcoholism in their electronic medical record were excluded. The sample consisted of 109 patients selected by simple random sampling; the sample size was calculated with an expected odds ratio (OR) of 3.72 based on a previous study
23
. with hypertriglyceridemia as the independent variable. The sample size was determined based on epidemiological criteria and operational feasibility within the medical unit.
Variables and instruments
Sociodemographic variables (age, sex, marital status, education level, occupation) were collected using a structured questionnaire. Clinical records were accessed through the Family Medicine Information System (SIMF) to obtain relevant clinical history. Somatometric measurements, such as weight, height, body mass index (BMI), and blood pressure, were taken by a trained field worker, under the direct supervision of the principal investigator.
Blood samples were taken at the institutional clinical laboratory to analyze the following biochemical parameters: glucose, total cholesterol, triglycerides, urea, creatinine, aspartate aminotransferase (AST), and alanine aminotransferase (ALT). The values were recorded according to the International System (SI) units. NAFLD was evaluated using hepatic ultrasound performed by a trained radiologist and interpreted initially by the same radiologist and later by two additional radiologists, independently, to determine interobserver agreement.
Procedures
After the signing of the informed consent, clear instructions were given to the participants to go to the clinical laboratory in a fasting state, where blood samples were taken. Subsequently, patients were referred to the imaging service, where a hepatic ultrasound was performed. The ultrasound findings were classified into three grades, based on the visualized characteristics: Grade I (mild), with a normal-sized liver, well-defined edges, and clear visualization of the portal vessels; Grade II (moderate), with mild liver enlargement, difficulty identifying the diaphragm and portal vessels, and increased echogenicity of the hepatic parenchyma; and Grade III (severe), with marked liver enlargement, limited visualization of the diaphragm, vascular pattern, and deep areas of the organ. All collected information was alphanumerically coded to ensure the confidentiality of the participants.
Statistical analysis
A descriptive statistical analysis was performed. For qualitative variables, absolute frequencies and percentages were calculated, while for quantitative variables, central tendency measures (mean and median) and dispersion measures (standard deviation and interquartile range) were determined, depending on the data distribution, assessed using the Kolmogorov-Smirnov test. Comparisons between groups were made using ANOVA or Kruskal-Wallis for quantitative variables, and the chi-square test or Fisher’s exact test for qualitative variables. Logistic regression and multilevel logistic regression analyses were conducted, both in crude and adjusted models, to identify factors associated with the presence and severity of NAFLD. Finally, a multiple model was constructed to adjust for potential confounding factors. A p-value <0.05 was considered statistically significant.
Results
The data from 109 patients with T2DM were analyzed. The average age was 56.6 ± 10.6 years. Female patients predominated, comprising 67.9%. Regarding marital status, 66.1% of the participants were married. The majority had secondary education level (34.9%), and 47.7% were dedicated to household tasks. Regarding habits, 65.1% did not consume alcohol, and 87.2% were non-smokers. The median duration of T2DM was six years, with a significant difference between the groups with and without hepatic steatosis (p-value = 0.003). The median energy consumption was 1,866 kcal (Table 1).
Sociodemographic characteristics of patients with Type 2 Diabetes Mellitus from the DiabetIMSS Module at the No. 3 Family Medicine Unit, Jiutepec, Morelos..
Variable |
Information |
Total (n=109) |
No Steatosis (n=16) |
Steatosis GI (n=58) |
Steatosis GII (n=35) |
p-value |
Age |
|
56,6 ± 10,6 |
59,1 ± 8,4 |
57,65 ± 10,11 |
53,85 ± 11,77 |
0,145* |
Sex |
Male Female |
35 (32,1%) 74 (67,9%) |
7 (43,8%) 9 (56,3%) |
18 (31,0%) 40 (69,0%) |
10 (28,6%) 25 (71,4%) |
0,542† |
Maritial status |
Single |
14 (12,8%) |
-- |
11 (19,0%) |
3 (8,6%) |
0,114£ |
Married |
72 (66,1%) |
10 (62,5%) |
37 (63,8%) |
25 (71,4%) |
Common-law partnership |
4 (3,7%) |
2 (12,5%) |
1 (1,7%) |
1 (2,9%) |
Divorced |
6 (5,5%) |
2 (12,5%) |
1 (1,7%) |
3 (8,6%) |
Widowed |
9 (8,3%) |
1 (6,3%) |
5 (8,6%) |
3 (8,6%) |
Separated |
4 (3,7%) |
1 (6,3%) |
3 (5,2%) |
-- |
Education |
Illiterate |
3 (2,8%) |
1 (6,3%) |
2 (3,5%) |
-- |
0,743£ |
Elementary |
23 (21,1%) |
5 (31,3%) |
13 (22,4%) |
5 (14,3%) |
Middle school |
38 (34,9%) |
3 (18,8%) |
21 (36,2%) |
14 (40,0%) |
High school |
38 (34,9%) |
4 (25,0%) |
11 (19,0%) |
9 (25,7%) |
Bachelor’s degree |
17 (15,6%) |
3 (18,8%) |
8 (13,8%) |
6 (17,2%) |
Postgraduate |
4 (3,7%) |
-- |
3 (5,2%) |
1 (2,9%) |
Ocupation |
Homemaker |
52 (47,7%) |
6 (37,5%) |
29 (50,0%) |
17 (48,6%) |
0,893£ |
Laborer |
4 (3,7%) |
-- |
3 (5,2%) |
1 (2,9%) |
Employee |
41 (37,6%) |
8 (50,0%) |
19 (32,8%) |
14 (40,0%) |
Self-employed |
12 (11,0%) |
2 (12,5%) |
7 (12,1%) |
3 (8,6%) |
Alcohol consumption |
No |
71 (65,1%) |
11 (68,8%) |
38 (65,5%) |
22 (62,9%) |
0,916† |
Yes |
38 (34,7%) |
5 (31,3%) |
20 (34,5%) |
13 (37,1%) |
Smoking |
No |
95 (87,2%) |
15 (93,8%) |
51 (87,9%) |
29 (82,9%) |
0,578£ |
Sí |
14 (12,8%) |
1 (6,3%) |
7 (12,1%) |
6 (17,1%) |
T2DM Duration (years) |
|
6 (2-15) |
15,5 (5-21) |
7 (2-16) |
3 (1-9) |
0,003¥ |
Energy Consumption |
|
1866 (1427–2539) |
1798 (1164–2233) |
1957 (1522–2573) |
1856 (1380–2594) |
0,452¥ |
*ANOVA, † Chi square, £Fisher’s exact, Kruskal-Wallis,
Grade I, GII: Grade II, T2DM: Type 2 Diabetes Mellitus.
Regarding clinical characteristics, 51.4% of the patients were obese. The median BMI was 30.2 kg/m², with significant differences between the groups (p-value <0.001). Regarding dyslipidemia, 55.1% of participants had it, more frequently in those with Grade II hepatic steatosis (74.3%), followed by Grade I (53.5%), and absent in those with no steatosis (18.8%) (p-value <0.001). The median waist circumference was 98 cm. The median diastolic blood pressure was 70 mmHg, while the mean mean arterial pressure was 86.6 ± 8.4 mmHg, with significant differences between groups (p-value = 0.038) (Table 2).
With respect to the biochemical characteristics, The median triglycerides level was 145.2 mg/dL, with statistically significant differences (p-value <0.001). The total cholesterol median was 172.2 mg/dL (p-value = 0.047). Likewise, the very low-density lipoprotein (VLDL) cholesterol median was 31.5 mg/dL (p-value = 0.010). Regarding the hepatic profile, no significant differences were observed between groups in the concentrations of AST, ALT, bilirubin, urea, or creatinine (p-value >0.05). However, the glomerular filtration rate had a median of 102 mL/min/1.73 m², with significant differences between groups (p-value ≪0.001) (Table 2).
Table 2. Clinical and biochemical characteristics of patients with type 2 diabetes mellitus from the DiabetIMSS Module at Family Medicine Unit No. 3, Jiutepec, Morelos.
Variable |
Information |
Total (n=109) |
Without Steatosis (n=16) |
Steatosis GI (n=58) |
Steatosis GII (n=35) |
p-value |
Body Mass Index |
Normal |
9 (8.2%) |
4 (25.0%) |
3 (5.2%) |
2 (5.7%) |
<0.001* |
Overweight |
44 (40.4%) |
11 (68.75%) |
25 (43.1%) |
8 (22.8%) |
Obesity |
56 (51.4%) |
1 (6.25%) |
30 (51.7%) |
25 (71.5%) |
Systemic Arterial Hypertension |
No |
62 (56.9%) |
9 (56.2%) |
34 (58.6%) |
19 (54.3%) |
0.918† |
Yes |
47 (43.1%) |
7 (43.8%) |
24 (41.4%) |
16 (45.7%) |
Dyslipidemia |
No |
49 (45.0%) |
13 (81.3%) |
27 (46.6%) |
9 (25.7%) |
<0.001£ |
Yes |
60 (55.0%) |
3 (18.7%) |
31 (53.4%) |
26 (74.3%) |
Body Mass Index (kg/m²) |
|
30.18 (27.31-34.86) |
26.04 (25.09-27.87) |
30.34 (27.83-33.71) |
33.17 (29.53-36.85) |
<0.001‡ |
Waist Circumference (cm) |
|
98 (94-106) |
95 (87-98) |
98 (93-105) |
106 (95-113) |
<0.001‡ |
Systolic Blood Pressure (mmHg) |
|
118.22 ± 11.8 |
115.06 ± 13.39 |
117.5 ± 11.14 |
120.85 ± 11.97 |
0.213§ |
Diastolic Blood Pressure (mmHg) |
|
70 (60-80) |
69.5 (60-70) |
70 (60-80) |
75 (60-80) |
0.043¥ |
Mean Arterial Pressure (mmHg) |
|
86.62 ± 8.41 |
83.14 ± 8.17 |
86.01 ± 7.52 |
89.23 ± 9.32 |
0.038* |
Glucose (mg/dL) |
|
141 (112.6–182.8) |
175.4 (116.7–223.6) |
139.25 (109.1–169.16) |
137.7 (118–182.5) |
0.285¥ |
Hb1Ac (%) |
|
7.8 (6.3–9.7) |
7.9 (7.1–10.5) |
7.4 (6.15–9.7) |
8.2 (7.1–9.3) |
0.390¥ |
Triglycerides (mg/dL) |
|
145.2 (104.3–219.9) |
104.4 (77.6–127.8) |
137.5 (109.4–198.9) |
210.8 (117.4–262.2) |
<0.001¥ |
Total Cholesterol (mg/dL) |
|
172.2 (143.5–201.3) |
146 (124.3–182.2) |
171.1 (148.2–197.5) |
185.7 (141.6–215.6) |
0.047¥ |
C-HDL (mg/dL) |
|
41.6 (35–48.5) |
43.8 (38.1–51.8) |
41.8 (36.6–49.8) |
38.1 (32–46.1) |
0.155¥ |
C-LDL (mg/dL) |
|
93.8 (72.5–118.6) |
76.2 (71.6–105.5) |
92.8 (73.6–118) |
105.3 (75–122) |
0.317¥ |
C-VLDL (mg/dL) |
|
31.5 (21.2–43.9) |
21.9 (16.4–29.9) |
30.9 (22.4–44.2) |
39.6 (22.6–47) |
0.010¥ |
AST (U/L) |
|
23.1 (18.7–32.2) |
19.7 (18.4–24) |
23.3 (17.7–32) |
25 (19.9–33.6) |
0.107¥ |
AST (U/L) |
|
23,1 (18,7–32,2) |
19,7 (18,4–24) |
23,3 (17,7–32) |
25 (19,9–33,6) |
0,107¥ |
ALT (U/L) |
|
27,2 (20–42,2) |
21,9 (19,4–27,4) |
28,25 (19,9–43,5) |
29,8 (21,2–51,5) |
0,215¥ |
Total Bilirubin (mg/dL) |
|
0,4 (0,3–0,5) |
0,4 (0,4–0,5) |
0,4 (0,3–0,5) |
0,4 (0,3–0,6) |
0,187¥ |
Direct Bilirubin (mg/dL) |
|
0,1 (0,1–0,2) |
0,1 (0,1–0,2) |
0,1 (0,1–0,2) |
0,1 (0,1–0,2) |
0,313¥ |
Indirect Bilirubin (mg/dL) |
|
0,3 (0,2–0,3) |
0,3 (0,3–0,3) |
0,3 (0,2–0,3) |
0,3 (0,2–0,4) |
0,313¥ |
Creatinine (mg/dL) |
|
0,7 (0,6–0,8) |
0,8 (0,65–0,85) |
0,7 (0,6–0,8) |
0,7 (0,6–0,81) |
0,482¥ |
Urea (mg/dL) |
|
28 (24,3–34) |
29,7 (24,8–39,4) |
27,7 (24,7–33,1) |
28,5 (18,5–36,6) |
0,724¥ |
Glomerular Filtration Rate |
|
102 (80–135) |
86 (80–99) |
104 (80–130) |
125 (79–159) |
<0,001¥ |
*Fisher’s Exact, † Chi square, ‡Kruskalwallis, §ANOVA
GI: Grade I, GII: Grade II, HbA1c: Glycated Hemoglobin, HDL: High-Density Lipoprotein, LDL: Low-Density Lipoprotein, VLDL: Very Low-Density Lipoprotein, AST: Aspartate Aminotransferase, ALT: Alanine Aminotransferase.
Pharmacological treatment data showed that the most prescribed oral antidiabetic drugs were: metformin (86.2%), sitagliptin (37.6%), glibenclamide (36.7%), acarbose (21.1%), and pioglitazone (3.7%). Among insulins, the most frequently used were NPH (22.0%), glargine insulin (6.4%), rapid insulin (5.5%), and insulin mixtures (3.7%). For dyslipidemia management, the most common drugs were bezafibrate (33.9%), pravastatin (24.8%), and atorvastatin (16.5%), with the overall use of statins at 37.6%. Statistically significant differences were found in the use of pioglitazone (p-value=0.004) and statins (p-value=0.042) between groups with and without hepatic steatosis (Table 3).
Pharmacotherapy of patients with Type 2 Diabetes Mellitus at the DiabetIMSS Module of the Family Medicine Unit No. 3, Jiutepec, Morelos.
Variable |
Category |
Total(n=109) |
No steatosis (n=16) |
Steatosis GI (n=58) |
Steatosis GII (n=35) (n=35) |
p-value |
Metformin |
No |
15 (13,76%) |
2 (12,50%) |
7 (12,07%) |
6 (17,14%) |
0,861* |
Yes |
94 (86,24%) |
14 (87,50%) |
51 (87,93%) |
29 (82,86%) |
Glibenclamide |
No |
69 (63,30%) |
7 (43,75%) |
39 (67,24%) |
23 (65,71%) |
0,211† |
Yes |
40 (36,70%) |
9 (56,25%) |
19 (32,76%) |
12 (34,29%) |
Acarbose |
No |
86 (78,90%) |
11 (68,75%) |
46 (79,31%) |
29 (82,86%) |
0,516† |
Yes |
23 (21,10%) |
5 (31,25%) |
12 (20,69%) |
6 (17,14%) |
Pioglitazone |
No |
105 (96,33%) |
13 (81,25%) |
58 (100%) |
34 (97,14%) |
0,004* |
Yes |
4 (3,67%) |
3 (18,75%) |
-- |
1 (2,86%) |
Sitagliptin |
No |
68 (62,39%) |
6 (37,50%) |
40 (68,97%) |
22 (62,86%) |
0,085† |
Yes |
41 (37,61%) |
10 (62,50%) |
18 (31,03%) |
13 (37,14%) |
Rapid insulin |
No |
103 (94,50%) |
14 (87,50%) |
56 (96,55%) |
33 (94,29%) |
0,285* |
Yes |
6 (5,50%) |
2 (12,50%) |
2 (3,45%) |
2 (5,71%) |
NPH insulin |
No |
85 (77,98%) |
10 (62,50%) |
48 (82,76%) |
27 (77,14%) |
0,221† |
Yes |
24 (22,02%) |
6 (37,50%) |
10 (17,24%) |
8 (22,86%) |
Glargine insulin |
No |
102 (93,58%) |
14 (87,50%) |
55 (94,83%) |
33 (94,29%) |
0,559* |
Yes |
7 (6,42%) |
2 (12,50%) |
3 (5,17%) |
2 (5,71%) |
Insulin lispro protamine Mix |
No |
105 (96,33%) |
15 (93,75%) |
56 (96,55%) |
34 (97,14%) |
0,629* |
Yes |
4 (3,67%) |
1 (6,25%) |
2 (3,45%) |
1 (2,86%) |
Bezafibrate |
No |
72 (66,06%) |
12 (75,00%) |
41 (70,69%) |
19 (54,29%) |
0,204* |
Yes |
37 (33,94%) |
4 (25,00%) |
17 (29,31%) |
16 (45,71%) |
Atorvastatin |
No |
91 (83,49%) |
12 (75,00%) |
48 (82,76%) |
31 (88,57%) |
0,429* |
Yes |
18 (16,51%) |
4 (25,00%) |
10 (17,24%) |
4 (11,43%) |
Pravastatin |
No |
82 (75,23%) |
10 (62,50%) |
44 (75,86%) |
28 (80,00%) |
0,400* |
Yes |
27 (24,77%) |
6 (37,50%) |
14 (24,14%) |
7 (20,00%) |
Statins |
No |
68 (62,39%) |
6 (37,50%) |
36 (62,07%) |
26 (74,29%) |
0,042* |
Yes |
41 (37,61%) |
10 (62,50%) |
22 (37,93%) |
9 (25,71%) |
*Fisher’s Exact Test, † Chi-squared
GI: Grade I, GII: Grade II.
Logistic regression analysis identified, in the multivariate analysis, three variables significantly associated with the presence of hepatic steatosis. An increase of 1 mg/dL in cholesterol levels was associated with a 5% increase in the probability of presenting steatosis (OR=1.05; 95% CI: 1.00–1.10; p-value=0.038). The use of statins was associated with a 99% reduction in this probability (OR=0.01; 95% CI: 0.00–0.18; p-value=0.003). Additionally, although borderline, BMI showed a positive association with the presence of steatosis, with a 1.65-fold increase in probability for each additional kg/m² (OR=1.65; 95% CI: 0.99–2.72; p-value=0.051), but did not reach statistical significance (Table 4).
Table 4. Crude and adjusted model of factors associated with hepatic steatosis in patients with Type 2 Diabetes Mellitus at the DiabetIMSS Module of the Family Medicine Unit No. 3, Jiutepec, Morelos
Variable |
Crude model |
Adjusted model* |
OR |
p-value |
IC 95% |
OR |
p-value |
95% IC |
Age(years) |
0.97 |
0.310 |
0.92-1.02 |
0.99 |
0.973 |
0.88-1.13 |
Female sex |
1.80 |
0.285 |
0.61-5.33 |
23.1 |
0.059 |
0.88-604 |
Alcoholism |
1.21 |
0.743 |
0.38-3.78 |
0.50 |
0.584 |
0.04-5.92 |
Smoking |
2.43 |
0.407 |
0.29-20 |
52.9 |
0.180 |
0.15-1757 |
Time with T2DM |
0.92 |
0.012 |
0.87-0.98 |
0.97 |
0.687 |
0.85-1.10 |
Systemic hypertension |
0.97 |
0.956 |
0.33-2.82 |
0.88 |
0.920 |
0.08-9.27 |
Body mass index (kg/m²) |
1.47 |
0.001 |
1.18-1.84 |
1.65 |
0.051 |
0.99-2.72 |
Waist circumference (cm) |
1.06 |
0.006 |
1.01-1.12 |
0.96 |
0.520 |
0.85-1.08 |
Mean arterial pressure (mmHg)
|
1.06 |
0.077 |
0.99-1.13 |
1.14 | 0.079 |
0.98-1.32 |
Glucose (mg/dL) |
0.99 |
0.177 |
0.98-1.00 |
0.98 |
0.113 |
0.96-1.00 |
Triglycerides (mg/dL) |
1.01 |
0.024 |
1.00-1.02 |
1.00 |
0.322 |
0.99-1.02 |
Cholesterol (mg/dL) |
1.02 | 0.028 |
1.00-1.03 |
1.05 |
0.038 |
1.00-1.10 |
Metformin |
0.87 |
0.874 |
0.17-4.32 |
7.13 |
0.316 |
0.15-332 |
Bezafibrate |
1.65 |
0.417 |
0.49-5.52 |
0.26 |
0.471 |
0.00-9.57 |
Statins |
0.30 |
0.032 |
0.09-0.90 |
0.01 |
0.003 |
0.00-0.18 |
Energy consumption (Kcal) |
1.00 |
0.196 |
0.99-1.00 |
1.00 |
0.112 |
0.99-1.00 |
*Adjusted multiple model for age, sex, alcohol consumption, cigarette consumption, time with T2DM, systemic hypertension, body mass index, waist circumference, mean arterial pressure, glucose levels, triglycerides, cholesterol, use of metformin, bezafibrate and statins, and energy consumption.
.
OR: Odds Ratio. 95% CI: 95% Confidence Interval. T2DM: Type 2 Diabetes Mellitus2.
In the multinomial adjusted model for Grade I steatosis, an increase of 1 mg/dL in cholesterol levels was associated with a 5% increase in the probability of presenting this grade of steatosis (OR=1.05; 95% CI: 1.00–1.10; p-value=0.040). Additionally, the use of statins was associated with a 99% reduction in this probability (OR=0.01; 95% CI: 0.00–0.25; p-value=0.005). For Grade II hepatic steatosis, female sex was associated with a 91-fold increase in the probability of developing this grade of steatosis (OR=91.2; 95% CI: 2.54–328; p-value=0.014). Furthermore, for each additional mmHg in mean arterial pressure, the probability increased by 19% (OR=1.19; 95% CI: 1.01–1.40; p-value=0.032), while the use of statins reduced the probability of presenting Grade II steatosis by 99% (OR=0.01; 95% CI: 0.00–0.02; p-value<0.001) (Table 5).
Table 5. Multilevel analysis of the crude and adjusted models of factors associated with the degree of hepatic steatosis in patients with Type 2 Diabetes Mellitus at the DiabetIMSS Module of the Family Medicine Unit No. 3, Jiutepec, Morelos.
|
Crude model |
Adjusted model* |
Variable |
OR |
P |
95% CI |
OR |
P |
95% CI |
Without hepatic steatosis (Reference) |
- |
Grade I Steatosis |
- |
Age(years) |
0,98 |
0,607 |
0,93-1,04 |
0,99 |
0,984 |
0,88-1,13 |
Female sex |
1,72 |
0,344 |
0,55-5,36 |
22,0 |
0,065 |
0,82-591 |
Alcoholism |
1,15 |
0,809 |
0,35-3,79 |
0,52 |
0,604 |
0,04-6,07 |
Smoking |
2,05 |
0,515 |
0,23-18 |
48,7 |
0,183 |
0,16-149 |
Time with T2DM |
0,94 |
0,072 |
0,88-1,00 |
0,98 |
0,788 |
0,86-1,11 |
Systemic hypertension |
0,90 |
0,865 |
0,29-2,77 |
0,91 |
0,936 |
0,08-9,50 |
Body mass index (kg/m²) |
1,43 |
0,002 |
1,14-1,79 |
1,64 |
0,055 |
0,99-2,71 |
Waist circumference (cm) |
1,05 |
0,040 |
1,00-1,10 |
0,96 |
0,499 |
0,84-1,08 |
Mean arterial pressure (mmHg) |
1,04 |
0,218 |
0,97-1,12 |
1,13 |
0,091 |
0,98-1,32 |
Glucose (mg/dL) |
0,99 |
0,241 |
0,98-1,00 |
0,98 |
0,122 |
0,96-1,00 |
Triglycerides (mg/dL) |
1,01 |
0,090 |
0,99-1,02 |
1,00 |
0,411 |
0,99-1,02 |
Cholesterol (mg/dL) |
1,02 |
0,050 |
0,99-1,03 |
1,05 |
0,040 |
1,00-1,10 |
Metformin |
1,04 |
0,963 |
0,19-5,57 |
7,90 |
0,296 |
0,16-381 |
Bezafibrate |
1,24 |
0,735 |
0,35-4,40 |
0,25 |
0,454 |
0,00-9,03 |
Statins |
0,36 |
0,085 |
0,11-1,14 |
0,01 |
0,005 |
0,00-0,25 |
Energy consumption (Kcal) |
1,00 |
0,197 |
0,99-1,00 |
1,00 |
0,107 |
0,99-1,00 |
Steatosis grade II |
- |
Age (years) | 0.95 | 0.105 | 0.89-1.01 | 1.01 | 0.883 | 0.88-1.16 |
Female sex | 1.94 | 0.289 | 0.56-6.65 | 91.2 | 0.014 | 2.54-328 |
Alcoholism | 1.3 | 0.683 | 0.36-4.58 | 0.64 | 0.753 | 0.04-10.3 |
Smoking | 3.10 | 0.315 | 0.34-28.2 | 122 | 0.116 | 0.30-4941 |
Duration of having T2DM | 0.87 | 0.001 | 0.80-0.94 | 0.86 | 0.084 | 0.74-1.02 |
Systemic arterial hypertension | 1.08 | 0.896 | 0.32-3.56 | 0.97 | 0.986 | 0.07-13.1 |
Body mass index (kg/m²) | 1.60 | <0.001 | 1.26-2.02 | 1.55 | 0.110 | 0.90-2.67 |
Waist circumference (cm) | 1.12 | <0.001 | 1.05-1.19 | 1.05 | 0.542 | 0.89-1.23 |
Mean arterial pressure (mmHg) | 1.09 | 0.019 | 1.01-1.18 | 1.19 | 0.032 | 1.01-1.40 |
Glucose (mg/dL) | 0.99 | 0.185 | 0.98-1.00 | 0.97 | 0.075 | 0.95-1.00 |
Triglycerides (mg/dL) | 1.01 | 0.003 | 1.00-1.02 | 1.01 | 0.077 | 0.99-1.03 |
Cholesterol (mg/dL) | 1.02 | 0.016 | 1.00-1.04 | 1.05 | 0.029 | 1.00-1.10 |
Metformin | 0.69 | 0.673 | 0.12-3.86 | 3.70 | 0.531 | 0.06-221 |
Bezafibrate | 2.52 | 0.166 | 0.67-9.38 | 0.62 | 0.807 | 0.01-27.3 |
Statins | 0.20 | 0.015 | 0.06-0.73 | 0.01 | <0.001 | 0.00-0.02 |
Energy consumption (Kcal) | 1.00 | 0.262 | 0.99-1.00 | 1.00 | 0.317 | 0.99-1.00 |
*Multiple model adjusted for age, sex, alcohol consumption, smoking, duration of T2DM, systemic arterial hypertension, body mass index, waist circumference, mean arterial pressure, glucose levels, triglycerides, cholesterol, metformin use, bezafibrate and statins use, and energy consumption.
OR: Odds ratio. CI 95%: 95% confidence interval. T2DM: Type 2 diabetes mellitus.
DISCUSSION
The results identified elevated BMI, high triglyceride and cholesterol levels as significant associated risk factors for NAFLD, consistent with previous findings, such as those reported by van den Berg EH et al., who noted a direct relationship between these metabolic parameters and the associated cardiovascular risk
24
.
Our study highlighted that statins seem to have a protective role by reducing the frequency of NAFLD, a finding that aligns with research such as that of Sfikas G et al., where statins like atorvastatin and rosuvastatin may limit the development of NAFLD and liver fibrosis markers
25
.
This highlights the role of statins, not only in lipid control but also as a potential tool for the comprehensive management of NAFLD in patients with T2DM. This approach complements the care provided at the Diabetes Care Centers of IMSS (CADIMSS), formerly known as DiabetIMSS modules, which aim to provide comprehensive management to patients diagnosed with diabetes, improving metabolic control and delaying the onset of chronic complications.
Of course, further studies are required to confirm the role of statins in managing the population with T2DM and potential NAFLD profile.
Statins confer cardiovascular protection primarily through the inhibition of the HMG-CoA reductase enzyme, which reduces hepatic cholesterol synthesis and favors greater low-density lipoprotein (LDL) uptake by the liver, thus lowering its plasma concentrations. Additionally, they have beneficial pleiotropic effects, including improving endothelial function, reducing systemic inflammation — evidenced by a decrease in C-reactive protein levels — stabilizing atherosclerotic plaques, as well as having antioxidant and antithrombotic properties. Together, these effects contribute to a significant reduction in the risk of cardiovascular events, even in individuals with normal cholesterol levels, as demonstrated in the JUPITER study
26
.
A relevant finding was the inverse relationship between the duration of diabetes and the risk of NAFLD. This result suggests that patients with longer duration of T2DM may develop better self-care practices and metabolic control, or they may be receiving statins as a protective therapy due to the increased cardiovascular risk associated with diabetes, which could explain the lower incidence of NAFLD.
This aspect, though rarely explored in the literature, highlights the importance of long-term educational and preventive strategies, such as CADIMSS, in the management of T2DM patients, supporting the control of metabolic comorbidities.
Regarding pharmacological treatment, although the use of statins appeared to show a clear benefit in the studied population, the evaluation of the impact of other medications such as metformin, sodium-glucose cotransporter-2 inhibitors (SGLT2), glucagon-like peptide-1 receptor agonists (GLP-1RA), and pioglitazone revealed areas of controversy in the literature. In our study, no clear benefits were observed associated with the use of metformin in the presence of NAFLD. However, studies such as those by Huang Y et al. and Zachou M et al. have reported improvements in hepatic steatosis and transaminase levels, but with inconsistent results, such as a potential worsening of hepatic fibrosis
27
–
29
. These discrepancies have led international guidelines to not recommend metformin as a specific treatment for NAFLD, highlighting the need for studies with stronger scientific evidence and methodological quality.
However, with the adverse effect of weight gain, this finding suggests that its use should be carefully considered, prioritizing patients with specific characteristics such as significant fibrosis or active inflammation, as well as monitoring for the development of primarily metabolic adverse reactions.
29
,
30
. This finding suggests that its use should be carefully considered, prioritizing patients with specific characteristics, such as significant fibrosis or active inflammation, as well as monitoring for the development of primarily metabolic adverse reactions.
SGLT2 inhibitors and GLP-1RA have emerged as promising options for treating NAFLD. Although not evaluated in this study, as they were not yet part of the essential diabetes medication regimen, they have recently been included in IMSS, opening the possibility for future studies with these drugs. According to Jang H et al., SGLT2 inhibitors not only improve hepatic steatosis and metabolic parameters but also reduce long-term hepatic complications. GLP-1RAs, on the other hand, have demonstrated benefits in weight reduction, transaminase levels, and hepatic steatosis, although their effects on fibrosis remain inconsistent. Both agents represent innovative therapeutic alternatives for complementing the management of NAFLD in patients with T2DM
31
.
Regarding the impact of fenofibrate, reviews such as those by Mahmoudi A et al. highlight its antioxidant, anti-inflammatory, and antifibrotic potential in NAFLD. Although its use in our population was limited, previous studies suggest it may be useful for patients with altered lipid profiles and early hepatic damage
32
.
Finally, our study contributes to the literature by emphasizing the importance of comprehensive control of metabolic factors and the protective role of statins in patients with T2DM and NAFLD. However, the reviewed evidence suggests that the management of NAFLD should be personalized, integrating pharmacological options based on metabolic characteristics, the degree of liver damage, and the individual needs of patients. While statins, SGLT2 inhibitors, GLP-1RAs, and pioglitazone offer specific benefits, further large-scale and long-term studies are required to directly compare their efficacy and safety, especially in specific subgroups such as those with advanced fibrosis or insulin resistance.
The study has several important limitations that must be considered when interpreting its results. The sample was relatively small and limited to a single medical unit, which reduces the representativeness of the findings and their applicability to other populations. Additionally, the cross-sectional design prevents establishing cause-and-effect relationships between the studied factors and NAFLD. The diagnosis based on ultrasound, while practical, has limitations in detecting mild grades of steatosis and does not adequately assess liver fibrosis.
On the other hand, the study presents relevant biases that could affect its conclusions. There is a selection bias, as the participants come from a single location, excluding patients from other regions with different characteristics. Pharmacotherapy data were obtained from clinical records, which may lead to incomplete or inaccurate information. Finally, the lack of geographic and cultural diversity limits the applicability of the findings to populations other than the Mexican one studied. These aspects underline the need for broader, longitudinal, and multicenter future studies.
CONCLUSION
The findings of this study show that in patients with T2DM, elevated cholesterol and high mean arterial pressure are significantly associated with the presence and severity of NAFLD. Additionally, the use of statins robustly decreased the frequency of development and progression of NAFLD, both in the overall and stratified analyses by degree of steatosis. Female sex and an increase in mean arterial pressure were associated with a higher frequency of developing grade II hepatic steatosis. These results highlight the importance of a comprehensive clinical approach in the T2DM population, considering strict control of metabolic factors and the rational use of statins as a potential strategy for the prevention or management of NAFLD.
Longitudinal and multicenter studies are required to confirm these associations and explore the efficacy of other emerging therapeutic options, such as SGLT2 inhibitors and GLP-1RA agonists, in diverse clinical contexts.