Bivariate analysis between factors and antibiotic use behaviors among Thai population using simple logistic regression
Bivariate analysis between factors and antibiotic use behaviors among the Thai population using simple logistic regression is a statistical method used to understand the relationships between two variables, one independent (predictor) variable and one dependent (outcome) variable, where the dependent variable is binary. factors associated with antibiotic use among the Thai population based on data from the National Survey 2023. It includes an analysis of demographic characteristics, health status and behaviors, and healthcare utilization patterns to understand their relationship with antibiotic use.
Among the demographic characteristics, females were slightly more likely to use antibiotics (60.30%) than males were (39.70%), with a crude odds ratio (OR) of 1.10 (95% CI: 1.00-1.20, p = 0.033). Age was significantly associated with increasing antibiotic use. The highest usage was observed in individuals aged 60 years and above (9.02%), with an OR of 1.70 (95% CI: 1.04–2.79, p < 0.001). There was no significant trend in antibiotic use across different education levels (p = 0.155). Marital status also showed significant associations, with divorced individuals having the highest percentage of antibiotic use (10.84%) and an OR of 1.58 (95% CI: 1.22–2.04, p < 0.001).
Health status and behavioral factors demonstrated strong associations with antibiotic use. Individuals who experienced illness or discomfort in the past month had a significantly greater rate of antibiotic use (28.51%) than did those who did not (4.55%), with an OR of 8.35 (95% CI: 7.61–9.17, p < 0.001). Those who had injuries from accidents in the past month were more likely to use antibiotics (22.51%) than those who did not (8.03%), with an OR of 3.32 (95% CI: 2.66–4.16, p < 0.001). Patients with chronic or congenital diseases were also more likely to use antibiotics (11.05%) than were those without such diseases (7.11%), with an OR of 1.62 (95% CI: 1.48–1.77, p < 0.001). The likelihood of antibiotic use was lower among individuals with high knowledge of antibiotic use (4.92%) than among those with moderate (8.66%) or low (9.07%) knowledge. The ORs were 1.83 (95% CI: 1.56–2.15) for moderate knowledge and 1.92 (95% CI: 1.64–2.25) for low knowledge (p < 0.001).
In terms of healthcare utilization, those who received information about antimicrobial resistance (AMR) were more likely to use antibiotics (18.44%) than those who did not receive such information (3.60%), with an OR of 6.04 (95% CI: 5.49–6.65, p < 0.001). Individuals who received dental services in the past year had a greater rate of antibiotic use (13.14%) than did those who did not receive such services (7.77%), with an OR of 1.79 (95% CI: 1.58–2.03, p < 0.001). Those with oral health issues who did not utilize services had a greater rate of antibiotic use (18.25%) than did those who did not have such issues (8.18%), with an OR of 2.50 (95% CI: 1.83–3.41, p < 0.001). Individuals who experienced illness without hospital admission had a greater rate of antibiotic use (20.88%) than did those who did not (8.02%), with an OR of 3.02 (95% CI: 2.43–3.75, p < 0.001). Those who were advised to be admitted to the hospital but were not admitted had the highest antibiotic use rate (42.03%) compared to those who did not receive such advice (8.19%), with an OR of 8.12 (95% CI: 5.02–13.13, p < 0.001). (Details are shown in Table 3.)
Table 3
Bivariate analysis between factors and antibiotic use behaviors among the Thai population using simple logistic regression
Factors | Number | Percentage of Antibiotic Use | Crude OR. | 95%CI | p value |
Demographic characteristics | | | | | |
1. Gender | | | | | 0.033 |
Male | 10,380 | 39.70 | 1 | 1 | |
Female | 15,763 | 60.30 | 1.10 | 1.00-1.20 | |
2. Age | | | | | < 0.001 |
Under 18 years | 310 | 5.48 | 1 | 1 | |
18–25 years | 1,134 | 6.44 | 1.18 | 0.68–2.04 | |
25–45 years | 6,524 | 7.45 | 1.38 | 0.84–2.28 | |
45–60 years | 8,991 | 8.46 | 1.59 | 0.97–2.61 | |
60 years and above | 9,184 | 9.02 | 1.70 | 1.04–2.79 | |
3. Education Level | | | | | 0.155 |
No formal education and other | 931 | 8.38 | 1 | 1 | |
Preprimary education | 2,378 | 8.24 | 0.98 | 0.74–1.29 | |
Primary education | 10,661 | 8.69 | 1.04 | 0.81–1.32 | |
Lower secondary education | 3,588 | 8.75 | 1.04 | 0.80–1.35 | |
Upper secondary education | 4,193 | 7.89 | 0.93 | 0.72–1.21 | |
Associate degree | 1,079 | 6.86 | 0.80 | 0.57–1.12 | |
Bachelor’s degree | 2,981 | 7.48 | 0.88 | 0.67–1.15 | |
Postgraduate degree | 332 | 6.93 | 0.81 | 0.50–1.31 | |
4. Marital status | | | | | |
Single | 4,435 | 7.13 | 1 | 1 | < 0.001 |
Married | 16,235 | 8.15 | 1.15 | 1.01–1.31 | |
Widowed | 3,704 | 9.88 | 1.42 | 1.22–1.67 | |
Divorced | 766 | 10.84 | 1.58 | 1.22–2.04 | |
Separated | 1,003 | 7.68 | 1.08 | 0.83–1.40 | |
Health Status and Behavior | | | | | |
1. Illness or Discomfort in the Past Month such as cold/cough/runny nose/diarrhea/food poisoning/skin diseases | | | | | |
Never | 22,074 | 4.55 | 1 | 1 | < 0.001 |
Ever | 4,069 | 28.51 | 8.35 | 7.61–9.17 | |
2. Injuries from Accidents in the Past Month | | | | | < 0.001 |
Never | 25,681 | 8.03 | 1 | 1 | |
Ever | 462 | 22.51 | 3.32 | 2.66–4.16 | |
3. Chronic or Congenital Diseases | | | | | < 0.001 |
Do not have | 18,363 | 7.11 | 1 | 1 | |
Have | 7,780 | 11.05 | 1.62 | 1.48–1.77 | |
4. Knowledge of Antibiotic Use | | | | | < 0.001 |
High | 3,945 | 4.92 | 1 | 1 | |
Moderate | 10,332 | 8.66 | 1.83 | 1.56–2.15 | |
Low | 11,866 | 9.07 | 1.92 | 1.64–2.25 | |
5. Concern about Antibiotic Use | | | | | 0.060 |
High | 16,390 | 8.01 | 1 | 1 | |
Moderate | 9,750 | 8.73 | 1.09 | 1.00–1.20 | |
Low | 3 | 33.33 | 5.74 | 0.52–63.36 | |
6. Received Information on Antimicrobial Resistance from Antibiotic Use | | | | | < 0.001 |
Not received | 8,244 | 3.60 | 1 | 1 | |
Received | 17,899 | 18.44 | 6.04 | 5.49–6.65 | |
Healthcare Utilization | | | | | |
1. Received Dental Services in the Past Year | | | | | < 0.001 |
Never | 23,662 | 7.77 | 1 | 1 | |
Ever | 2,481 | 13.14 | 1.79 | 1.58–2.03 | |
2. Oral Health Issues without Service Utilization in the Past Year | | | | | < 0.001 |
Never | 25,869 | 8.18 | 1 | 1 | |
Ever | 274 | 18.25 | 2.50 | 1.83–3.41 | |
3. Illness without Hospital Admission | | | | | < 0.001 |
Never | 25,621 | 8.02 | 1 | 1 | |
Ever | 522 | 20.88 | 3.02 | 2.43–3.75 | |
4. Illness with Doctor’s Advice for Hospital Admission but Not Admitted in the Past Year | | | | | < 0.001 |
Never | 26,074 | 8.19 | 1 | 1 | |
Ever | 69 | 42.03 | 8.12 | 5.02–13.13 | |
Multivariable analysis was conducted to examine the relationships between factors and antibiotic utilization behaviors among the Thai population using multilevel logistic regression. Random cluster effect intercepts were incorporated to address the variability observed at the region and province levels.
The multivariate analysis conducted in the study examined the relationships between various factors and antibiotic utilization behaviors among the Thai population using multilevel logistic regression. Random cluster effect intercepts were incorporated to address the variability observed at the region and province levels.
The results indicate significant associations between health status, behaviors, and antibiotic use. For example, individuals who experienced illness or discomfort in the past month were significantly more likely to use antibiotics than were those who did not, with an adjusted odds ratio (OR) of 7.71 (95% CI: 6.94–8.57, p value < 0.001). Similarly, those who had injuries from accidents in the past month had a greater likelihood of antibiotic use, with an adjusted OR of 3.25 (95% CI: 2.48–4.26, p value < 0.001).
Knowledge of antibiotic use also plays a critical role. Individuals with lower knowledge had significantly greater odds of using antibiotics. Specifically, those with low knowledge had an adjusted OR of 2.73 (95% CI: 2.27–3.27, p value < 0.001), and those with moderate knowledge had an adjusted OR of 2.05 (95% CI: 1.71–2.46, p value < 0.001) compared to individuals with high knowledge. Furthermore, receiving information on antimicrobial resistance significantly increased the likelihood of antibiotic use, with an adjusted OR of 6.36 (95% CI: 5.70–7.10, p value < 0.001).
Healthcare utilization behaviors were also linked to antibiotic use. For instance, individuals who received dental services in the past year had a slightly greater likelihood of using antibiotics, with an adjusted OR of 1.29 (95% CI: 1.11–1.51, p value = 0.001). Those who had an illness without hospital admission were more likely to use antibiotics, with an adjusted OR of 1.50 (95% CI: 1.13–1.99, p value = 0.004). Notably, individuals who had an illness with a doctor’s advice for hospital admission but were not admitted had significantly greater odds of antibiotic use, with an adjusted OR of 3.25 (95% CI: 1.70–6.19, p value < 0.001).
Table 4
Multivariate analysis was conducted to examine the relationships between factors and antibiotic utilization behaviors among the Thai population using multilevel logistic regression
Factors | Number | Percentage of Antibiotic Use | Crude OR | Adjust OR | 95%CI | p value |
Health Status and Behavior | | | | | | |
1. Illness or Discomfort in the Past Month such as cold/cough/runny nose/diarrhea/food poisoning/skin diseases | | | | | | |
Never | 22,074 | 4.55 | 1 | 1 | 1 | < 0.001 |
Ever | 4,069 | 28.51 | 8.35 | 7.71 | 6.94–8.57 | |
2. Injuries from Accidents in the Past Month | | | | | | < 0.001 |
Never | 25,681 | 8.03 | 1 | 1 | 1 | |
Ever | 462 | 22.51 | 3.32 | 3.25 | 2.48–4.26 | |
3. Knowledge of Antibiotic Use | | | | | | < 0.001 |
High | 3,945 | 4.92 | 1 | | 1 | |
Moderate | 10,332 | 8.66 | 1.83 | 2.05 | 1.71–2.46 | |
Low | 11,866 | 9.07 | 1.92 | 2.73 | 2.27–3.27 | |
4. Received Information on Antimicrobial Resistance from Antibiotic Use | | | | | | < 0.001 |
Not received | 8,244 | 3.60 | 1 | 1 | 1 | |
Received | 17,899 | 18.44 | 6.04 | 6.36 | 5.70–7.10 | |
Healthcare Utilization | | | | | | |
5. Received Dental Services in the Past Year | | | | | | 0.001 |
Never | 23,662 | 7.77 | 1 | 1 | 1 | |
Ever | 2,481 | 13.14 | 1.79 | 1.29 | 1.11–1.51 | |
6 Illness without Hospital Admission | | | | | | 0.004 |
Never | 25,621 | 8.02 | 1 | 1 | 1 | |
Ever | 522 | 20.88 | 3.02 | 1.50 | 1.13–1.99 | |
7. Illness with Doctor’s Advice for Hospital Admission but Not Admitted in the Past Year | | | | | | < 0.001 |
Never | 26,074 | 8.19 | 1 | 1 | 1 | |
Ever | 69 | 42.03 | 8.12 | 3.25 | 1.70–6.19 | |