| Literature DB >> 31704967 |
Nalinee Jakkaew1, Kanokporn Pinyopornpanish1, Wichuda Jiraporncharoen1, Anawat Wisetborisut1, Surin Jiraniramai1, Ahmar Hashmi1, Chaisiri Angkurawaranon2.
Abstract
While there is an abundance of literature examining the relation between quantity of alcohol consumption and risk factors for non-communicable diseases (NCD), there is less evidence on whether the risk of harm from alcohol use would have a similar relationship with NCD risk factors. The study aims to determine the association between level of harm from alcohol use and NCD risk factors. A cross-sectional survey was conducted among health care workers in Thailand in 2013. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) was used to assessed risk of harm from alcohol use. The results suggest that higher risk of harm from alcohol use was associated with two of the eight NCD risk factors among women (higher blood pressure and higher triglyceride level) and five of the eight NCD risk factors among men (smoking, physical inactivity, higher blood pressure, higher blood glucose and higher triglyceride level). For men, assessing risk of harm could be incorporated as part of NCD programs as practitioners do not have to worry about the accuracy of the alcohol quantification and conversion to standard drinks. However, among women, quantifying volume may still be needed.Entities:
Mesh:
Year: 2019 PMID: 31704967 PMCID: PMC6842002 DOI: 10.1038/s41598-019-52754-w
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Risk of Harm from alcohol use.
| Female (2,472) | Male (732) | p-value* | |||||
|---|---|---|---|---|---|---|---|
| Abstainer (1,296) | Low risk (1,091) | Moderate/High risk (85) | Abstainer (98) | low risk (370) | Moderate/High risk (264) | ||
| Mean age (sd) | 42.6 (10.7) | 37.4 (10.5) | 34.7 (9.7) | 44.6 (10.4) | 41.3 (10.0) | 38.2 (9.0) | 0.32** |
| Highest education (col %) | <0.001# | ||||||
| Below bachelor’s degree | 34.5 | 21.5 | 47.0 | 55.1 | 48.4 | 68.2 | |
| Bachelor’s degree | 51.1 | 66.5 | 51.8 | 33.7 | 40.0 | 29.2 | |
| Higher than bachelor’s degree | 14.4 | 12.0 | 1.2 | 11.2 | 11.6 | 2.6 | |
| Income per month (col %) | <0.01# | ||||||
| <20,000 | 30.7 | 30.5 | 54.1 | 56.1 | 47.6 | 71.2 | |
| 20,000–40,000 | 28.9 | 33.1 | 35.3 | 23.5 | 24.9 | 17.4 | |
| 40,000–60,000 | 19.8 | 18.3 | 4.7 | 9.2 | 10.0 | 6.1 | |
| >60,000 | 20.6 | 18.1 | 5.9 | 11.2 | 17.6 | 5.3 | |
| Job (col %) | <0.01# | ||||||
| Doctors/nurses | 46.5 | 56.4 | 22.3 | 19.4 | 23.2 | 4.6 | |
| Other health professionals | 24.4 | 19.3 | 24.7 | 16.3 | 17.3 | 12.1 | |
| Administrators | 10.9 | 9.5 | 16.5 | 18.4 | 13.2 | 11.4 | |
| Workers | 18.2 | 14.8 | 36.5 | 45.9 | 46.2 | 72.0 | |
*p-value comparing demographic status between men and women; **T-test; #Chi-square.
Risk of Harm from alcohol use and patterns of alcohol use.
| Female (2,472) | Male (732) | p-value* | |||||
|---|---|---|---|---|---|---|---|
| Risk of Harm from alcohol use | Risk of harm from alcohol use | ||||||
| Abstainer (1,296) | Low risk (1,091) | Moderate/High risk (85) | Abstainer (98) | low risk (370) | Moderate/High risk (264) | ||
| Alcohol consumption | |||||||
Mean number of standard drink per day in last 30 days (sd) | 0 (0) | 1.03 (1.93) | 3.56 (4.07) | 0 (0) | 2.98 (3.59) | 7.05 (5.5) | <0.01** |
Median number of standard drink per day in past 30 days (IQR) | 0 (0–0) | 0 (0–1) | 2.5 (1–5) | 0 (0–0) | 2 (0–5) | 6 (3–10) | <0.01## |
| Pattern of alcohol consumption (col %) | <0.01# | ||||||
| Abstainer | 100 | 0 | 0 | 100 | 0 | 0 | |
| Non-binge drinking | 0 | 90.4 | 55.3 | 0 | 65.1 | 17.4 | |
| Binge drinking | 0 | 9.6 | 44.7 | 0 | 34.9 | 82.6 | |
| Biological marker | |||||||
| Mean AST (sd) | 22.5 (8.2) | 22.3 (8.2) | 21.7 (5.1) | 26.1 (6.5) | 29.8 (15.8) | 39.0 (28.7) | <0.01** |
| Mean ALT (sd) | 19.2 (12.9) | 18.5 (12.3) | 18.3 (8.8) | 27.6 (13.3) | 34.1 (26.0) | 46.1 (41.0) | <0.01** |
*p-value comparing alcohol consumption and patterns of alcohol consumption between men and women; **T-test; #Chi-square; ##Wilcoxon rank-sum test.
Figure 1Heavy alcohol use, risk of harm from alcohol use and behavioral risk factors for NCDs among women (N = 2,472). p-value obtained from overall likelihood ratio test between exposure of interests (alcohol consumption or risk of harm) and NCD risk factor using linear or logistic regression. Error bars represent 95% Confidence intervals.
Figure 2Heavy alcohol use, risk of harm from alcohol use and behavioral risk factors for NCDs among men (N = 732) p-value obtained from overall likelihood ratio test between exposure of interests (alcohol consumption or risk of harm) and NCD risk factor using linear or logistic regression. Error bars represent 95% Confidence intervals.
Figure 3Heavy alcohol use, risk of harm from alcohol use and physiological risk factors for NCDs among women (N = 2,472). p-value obtained from overall likelihood ratio test between exposure of interests (alcohol consumption or risk of harm) and NCD risk factor using linear or logistic regression. Error bars represent 95% Confidence intervals.
Figure 4Heavy alcohol use, risk of harm from alcohol use and physiological risk factors for NCDs among men (N = 732). p-value obtained from overall likelihood ratio test between exposure of interests (alcohol consumption or risk of harm) and NCD risk factor using linear or logistic regression. Error bars represent 95% Confidence intervals.