| Literature DB >> 35356027 |
Heather T Essigmann1, David A Aguilar2, William B Perkison3, Katherine G Bay3, Magdalena R Deaton3, Sharon A Brown4, Craig L Hanis3, Eric L Brown1.
Abstract
Background: The U.S.-Mexico Border is an area of opportunity for improved health care access; however, gaps remain as to how and where U.S. border residents, particularly those who are underinsured, obtain care. Antibiotics are one of the most common reported drivers of cross-border healthcare access and a medication of particular concern since indiscriminate or inappropriate use is associated with antimicrobial resistance. In addition, many studies assessing preferences for Mexican pharmaceuticals and healthcare in U.S. border residents were done prior to 2010 when many prescription medications, including antibiotics, were available over the counter in Mexico.Entities:
Keywords: U.S.-Mexico border; acculturation; antibiotics; border health; health care; insurance; socioeconomic status
Mesh:
Substances:
Year: 2022 PMID: 35356027 PMCID: PMC8960039 DOI: 10.3389/fpubh.2022.832266
Source DB: PubMed Journal: Front Public Health ISSN: 2296-2565
Descriptive statistics of the baseline cohort stratified by any antibiotic use in the past 12 months.
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| Age at baseline (years) | 50.01 (8.08) | 50.27 (7.95) | 49.69 (8.23) | 0.35 |
| Gender |
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| Male | 177 (28.73) | 118 (34.50) | 59 (21.53) | |
| Female | 439 (71.27) | 224 (65.50) | 215 (78.47) | |
| Fasting glucose at baseline (mg/dL) | 105.05 (24.51) | 106.61 (27.81) | 103.11 (19.50) | 0.06 |
| BMI at baseline (kg/m2) | 0.80 | |||
| 18.5–24.99 | 64 (10.39) | 28 (8.19) | 36 (13.14) | |
| 25–29.9 | 183 (29.71) | 109 (31.87) | 74 (27.01) | |
| 30–39.99 | 302 (49.03) | 173 (50.58) | 129 (47.08) | |
| >40.0 | 67 (10.88) | 32 (9.36) | 35 (12.77) | |
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| Number of years of education completed | 10.01 (3.59) | 9.74 (3.71) | 10.36 (3.41) |
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| Household income in past 12 months | 0.80 | |||
| ≤ $20,000 | 252 (41.52) | 147 (42.98) | 105 (38.32) | |
| $20,001–30,000 | 139 (22.90) | 74 (21.64) | 65 (23.72) | |
| $30,001–40,000 | 58 (9.56) | 31 (9.06) | 27 (9.85) | |
| $40,001–50,000 | 58 (9.56) | 28 (8.19) | 30 (10.95) | |
| $50,001–75,000 | 56 (9.23) | 30 (8.77) | 26 (9.49) | |
| >$75,000 | 44 (7.25) | 27 (7.89) | 17 (6.20) | |
| Insurance status | 0.90 | |||
| Insured | 282 (45.78) | 155 (45.32) | 127 (46.35) | |
| Not insured | 324 (52.60) | 182 (53.22) | 142 (51.82) | |
| Employment status | 0.99 | |||
| Full time | 276 (44.81) | 155 (45.32) | 121 (44.16) | |
| Part time | 123 (19.97) | 69 (20.18) | 54 (19.71) | |
| Unemployed | 148 (24.03) | 81 (23.68) | 67 (24.45) | |
| Retired/leave/disabled | 60 (9.74) | 32 (9.36) | 28 (10.22) | |
| Marital status | 0.45 | |||
| Married | 431 (69.97) | 244 (71.35) | 187 (68.25) | |
| Never married | 65 (10.55) | 31 (9.06) | 34 (12.41) | |
| Divorced or separated | 92 (14.94) | 52 (15.20) | 40 (14.60) | |
| Widowed | 27 (4.38) | 14 (4.09) | 13 (4.74) | |
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| Generation score | 2.41 (3.81) | 2.44 (3.89) | 2.39 (3.72) | 0.86 |
| Total acculturation score | 18.65 (7.19) | 18.35 (7.33) | 19.01 (7.00) | 0.08 |
| Language acculturation score | 8.69 (4.84) | 8.50 (4.86) | 8.91 (4.82) | 0.10 |
| Social acculturation score | 7.68 (2.28) | 7.64 (2.40) | 7.73 (2.14) | 0.41 |
| Media acculturation score | 2.28 (1.49) | 2.21 (1.46) | 2.37 (1.52) | 0.18 |
| Food preference | 0.44 | |||
| Mainly Latino foods | 92 (14.94) | 58 (16.96) | 34 (12.41) | |
| Mostly Latino/Some American foods | 106 (17.21) | 56 (16.37) | 50 (18.25) | |
| Equal Latino and American foods | 408 (66.23) | 222 (64.91) | 186 (67.88) | |
| Mostly American foods | 10 (1.62) | 6 (1.75) | 4 (1.46) | |
| Age moved to Starr County (years) | 17.63 (13.00) | 18.56 (13.43) | 16.48 (12.32) | 0.09 |
| Years lived in Starr County | 32.35 (12.40) | 31.68 (12.59) | 33.20 (12.14) | 0.23 |
| % of life lived in Starr county | 0.22 | |||
| 0–25% | 31 (5.03) | 22 (6.43) | 9 (3.28) | |
| 25–50% | 149 (24.19) | 87 (25.44) | 62 (22.63) | |
| 50–75% | 217 (35.23) | 114 (33.33) | 103 (37.59) | |
| 75–100% | 219 (35.55) | 119 (34.80) | 100 (36.50) | |
Chi-squared test for categorical variables; Mann-Whitney U-test for continuous variables.
Some values do not sum to 100% due to missingness.
The bold values are those that have asterisks or are highlighting those values that are of statistical significance.
Number of respective antibiotic classes used in the 12 months prior to baseline by source country.
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| Penicillin | 236 (51.87) | 187 (79.24) | 49 (20.76) |
| Cephalosporin | 40 (8.79) | 13 (32.50) | 27 (67.50) |
| Quinolone | 35 (7.69) | 12 (34.29) | 23 (65.71) |
| Macrolide | 30 (6.59) | 8 (26.67) | 22 (73.33) |
| Folate synthesis inhibitor | 13 (2.86) | 7 (53.85) | 6 (46.15) |
| Nitrofuran | 6 (1.32) | 3 (50.00) | 3 (50.00) |
| Tetracycline | 5 (1.10) | 1 (20.00) | 4 (80.00) |
| Nitroimidazole | 3 (0.66) | 0 (0.00) | 3 (100.00) |
| Ophthalmic ointment | 1 (0.22) | 1 (100.00) | 0 (0.00) |
| Unknown | 86 (18.90) | 43 (50.00) | 43 (50.00) |
Univariable logistic regression: odds of preferentially sourcing antibiotics from Mexico.
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| Age at baseline (years) | 49.82 (8.43) | 49.61 (8.13) | 1.0 (0.97–1.03) |
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| Male | 24 (24.00) | 35 (20.11) |
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| Female | 76 (76.00) | 139 (79.89) | 1.25 (0.70–2.26) |
| Fasting glucose at baseline (mg/dL) | 105.38 (24.11) | 101.80 (16.21) | 0.99 (0.98–1.00) |
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| 18.5–24.99 | 14 (14.00) | 22 (12.64) |
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| 25–29.9 | 27 (27.00) | 47 (27.01) | 1.11 (0.49–2.52) |
| 30–39.99 | 45 (45.00) | 84 (48.28) | 1.19 (0.55–2.54) |
| >40.0 | 14 (14.00) | 21 (12.07) | 0.95 (0.37–2.47) |
| Rounds of antibiotics (1–4+) | 1.87 (1.47) | 1.54 (0.89) | 0.80 (0.61–1.04) |
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| 0–8 years | 26 (26.00) | 50 (28.74) |
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| 9–12 years | 44 (44.00) | 90 (51.72) | 1.06 (0.59–1.93) |
| 13 or more years | 28 (28.00) | 30 (17.24) | 0.56 (0.28–1.12) |
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| ≤ $20,000 | 38 (38.00) | 67 (38.51) |
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| $20,001–30,000 | 26 (26.00) | 39 (22.41) | 0.85 (0.45–1.61) |
| $30,001–40,000 | 16 (16.00) | 41 (23.56) | 1.98 (0.74–5.35) |
| $40,001–50,000 | 10 (10.00) | 20 (11.49) | 1.13 (0.48–2.67) |
| $50,001–75,000 | 9 (9.00) | 17 (9.77) | 1.107 (0.44–2.64) |
| >$75,000 | 9 (9.00) | 25 (14.37) | 0.50 (0.18–1.42) |
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| Insured | 64 (64.00) | 63 (36.21) |
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| Not Insured | 33 (33.00) | 109 (62.64) |
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| Full time | 47 (47.00) | 74 (42.53) |
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| Part time | 14 (14.00) | 40 (22.99) | 1.81 (0.89–3.69) |
| Unemployed | 18 (18.00) | 49 (28.16) | 1.72 (0.90–3.31) |
| Retired/leave/disabled | 19 (19.00) | 9 (5.17) |
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| Married | 13 (13.00) | 21 (12.07) |
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| Never married | 63 (63.00) | 124 (71.26) | 0.82 (0.39–1.75) |
| Divorced or separated | 19 (19.00) | 21 (12.07) | 0.56 (0.28–1.12) |
| Widowed | 5 (5.00) | 8 (4.60) | 0.81 (0.26–2.59) |
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| Generation score | 3.66 (4.42) | 1.66 (3.03) |
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| Total acculturation score | 21.12 (7.30) | 17.80 (6.54) |
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| Language acculturation subscore | 10.13 (5.08) | 8.21 (4.54) |
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| Social acculturation subscore | 8.22 (2.28) | 7.45 (2.01) |
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| Media acculturation subscore | 2.77 (1.59) | 2.14 (1.43) |
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| Mainly Latino Foods | 8 (8.00) | 26 (14.94) |
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| Mostly Latino/Some American Foods | 19 (19.00) | 31 (17.82) | 0.50 (0.19–1.33) |
| Equal Amounts or Mostly American Foods | 73 (73.00) | 117 (67.24) | 0.49 (0.21–1.14) |
| Age moved to Starr County (years) | 13.97 (12.64) | 17.93 (11.94) |
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| Years lived in Starr County | 35.85 (12.16) | 31.68 (11.93) |
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| 0–50% | 19 (19.00) | 52 (29.89) |
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| 50–75% | 34 (34.00) | 69 (39.66) | 0.74 (0.38–1.44) |
| 75–100% | 47 (47.00) | 53 (30.46) |
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Wald p-value ≤ 0.05;
≤ 0.01;
≤ 0.001.
Categories collapsed to avoid small cells.
Some values do not sum to 100% due to missingness.
OR interpreted as a 5-year increase.
The bold values are those that have asterisks or are highlighting those values that are of statistical significance.
Multivariable logistic regression: odds of preferentially sourcing antibiotics from Mexico.
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| Generation score |
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| Rounds of antibiotics used (1 to 4+ rounds) | 0.76 (0.57–1.02) |
| Insurance status | |
| Insured |
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| Not Insured |
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Wald p-value ≤ 0.001.
The bold values are those that have asterisks or are highlighting those values that are of statistical significance.