| Literature DB >> 34911714 |
Charlotte Probst1,2,3, Jakob Manthey4,5,6, Carina Ferreira-Borges7, Maria Neufeld4,7, Ivo Rakovac7, Diana Andreasyan8, Lela Sturua9, Irina Novik10, Gahraman Hagverdiyev11, Galina Obreja12, Nurila Altymysheva13, Muhammet Ergeshov14, Shukhrat Shukrov15, Safar Saifuddinov16, Jürgen Rehm17,3,4,18,19,20,21.
Abstract
OBJECTIVES: As unrecorded alcohol use contributes to a substantial burden of disease, this study characterises this phenomenon in newly independent states (NIS) of the former Soviet Union with regard to the sources of unrecorded alcohol, and the proportion of unrecorded of total alcohol consumption. We also investigate associated sociodemographic characteristics and drinking patterns.Entities:
Keywords: epidemiology; health policy; public health; substance misuse
Mesh:
Substances:
Year: 2021 PMID: 34911714 PMCID: PMC8679101 DOI: 10.1136/bmjopen-2021-051874
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Overview of surveys included in this study: the country where the survey was conducted including the region, the World Bank income level,34 the proportion of Muslims in the general population,35 WHO estimates on litres of recorded alcohol per capita,2 recorded grams per day (GPD) among drinkers;2 the year of the survey, response rate, total sample (N), number of current drinkers (N (CD); past 7 days) as well as the number of current drinkers reporting use of unrecorded alcohol (N (unrec); past 7 days)
| Country | Region | Income level* | Muslim religion* | Recorded APC* | Recorded GPD among drinkers† | Survey year | Response rate | N | N (CD) | N (unrec) |
| Armenia | Transcaucasia | UMIC | 0.5% | 3.8 | 13.9 | 2016 | 42% | 2349 | 373 | 106 |
| Azerbaijan | Transcaucasia | UMIC | 97.2% | 0.4 | 2.8 | 2017‡ | 97% | 5602 | 478 | 42 |
| Belarus | Eastern Europe | UMIC | 0.5% | 10.1 | 30.1 | 2016/2017‡ | 87% | 5010 | 1348 | 157 |
| Georgia | Transcaucasia | LMIC | 11.2% | 7.4 | 26.6 | 2016 | 76% | 4204 | 801 | 488 |
| Kyrgyzstan | Central Asia | LMIC | 88.4% | 5.7 | 61.7 | 2013 | 100% | 2623 | 473 | 56 |
| Republic of Moldova | Eastern Europe | LMIC | 0.5% | 9.6 | 27.3 | 2013 | 84% | 4807 | 2020 | 1308 |
| Tajikistan | Central Asia | LMIC | 96.5% | 0.9 | 14.6 | 2016 | 99% | 2717 | 98 | 2 |
| Turkmenistan | Central Asia | UMIC | 93.0% | 3.9 | 33.8 | 2013 | 89% | 5113 | 311 | 21 |
| Uzbekistan | Central Asia | LMIC | 96.9% | 1.5 | 22.1 | 2014 | 89% | 3834 | 349 | 19 |
*Referring to the year of the survey
†Expressed as average consumption of pure alcohol in grams per day.
‡Referring to 2016.
APC, alcohol per capita; LMIC, lower-middle-income country; UMIC, upper-middle-income country.
Figure 1Prevalence of current alcohol use (past 7 days) and current use of unrecorded alcohol (past 7 days) in Armenia (ARM), Azerbaijan (AZE), Belarus (BLR), Georgia (GEO), Kyrgyzstan (KGZ), Republic of Moldova (MDA), Tajikistan (TJK), Turkmenistan (TKM) and Uzbekistan (UZB).
Figure 2Proportion of unrecorded alcohol of the total alcohol consumed (past 7 days) in Armenia (ARM), Azerbaijan (AZE), Belarus (BLR), Georgia (GEO), Kyrgyzstan (KGZ), Republic of Moldova (MDA), Turkmenistan (TKM), Uzbekistan (UZB) and all nine newly independent states included in this analysis.
Figure 3Sources of unrecorded alcohol (% of total unrecorded) in Armenia (ARM), Azerbaijan (AZE), Belarus (BLR), Georgia (GEO), Kyrgyzstan (KGZ), Republic of Moldova (MDA), and Uzbekistan (UZB). Note: results for Tajikistan were omitted due to low sample size (n=2).
Hierarchical logistic regression analyses on using unrecorded alcohol in the past 7 days among people who used any alcohol in the past 7 days (N=6339)
| Type of unrecorded (N) | Category (reference) | Crude model* | Full model | |||||
| OR | P value | 95% CI | OR | P value | 95% CI | |||
| All unrecorded (2199) | ||||||||
| Sex (female) | Male | 1.10 | 0.527 | 0.78 to 1.56 | 1.11 | 0.568 | 0.74 to 1.66 | |
| Age (25–44) | 18–24 | 0.49 | <0.001 | 0.42 to 0.58 | 0.45 | <0.001 | 0.38 to 0.54 | |
| 45–69 | 1.48 | 0.028 | 1.06 to 2.07 | 1.47 | 0.026 | 1.06 to 2.05 | ||
| Employment (employed) | Unemployed | 1.50 | <0.001 | 1.28 to 1.75 | 1.64 | 0.001 | 1.32 to 2.04 | |
| Other | 1.20 | 0.010 | 1.06 to 1.36 | 1.35 | 0.029 | 1.04 to 1.76 | ||
| Education (high) | Low | 1.03 | 0.862 | 0.74 to 1.43 | 0.98 | 0.920 | 0.65 to 1.48 | |
| Medium | 1.04 | 0.812 | 0.70 to 1.55 | 1.00 | 0.996 | 0.63 to 1.57 | ||
| Home-made spirits (586) | ||||||||
| Sex (female) | Male | 1.88 | 0.005 | 1.29 to 2.73 | 1.79 | 0.005 | 1.26 to 2.55 | |
| Age (25–44) | 18–24 | 0.50 | 0.007 | 0.32 to 0.78 | 0.54 | 0.004 | 0.38 to 0.76 | |
| 45–69 | 1.58 | 0.021 | 1.09 to 2.27 | 1.68 | 0.008 | 1.19 to 2.36 | ||
| Employment (employed) | Unemployed | 1.08 | 0.545 | 0.82 to 1.42 | 1.08 | 0.530 | 0.82 to 1.43 | |
| Other | 0.81 | 0.432 | 0.46 to 2.04 | 0.92 | 0.707 | 0.55 to 1.53 | ||
| Education (high) | Low | 1.41 | 0.061 | 0.98 to 2.04 | 1.49 | 0.008 | 1.14 to 1.93 | |
| Medium | 1.22 | 0.199 | 0.88 to 1.69 | 1.25 | 0.220 | 0.85 to 1.85 | ||
| Home-made beer/wine (1636) | ||||||||
| Sex (female) | Male | 1.24 | 0.221 | 0.85 to 1.80 | 1.28 | 0.189 | 0.86 to 1.92 | |
| Age (25–44) | 18–24 | 0.59 | <0.001 | 0.50 to 0.70 | 0.52 | <0.001 | 0.41 to 0.67 | |
| 45–69 | 1.47 | 0.014 | 1.11 to 1.94 | 1.45 | 0.018 | 1.09 to 1.94 | ||
| Employment (employed) | Unemployed | 1.44 | 0.009 | 1.13 to 1.84 | 1.51 | 0.015 | 1.11 to 2.06 | |
| Other | 1.25 | 0.095 | 0.95 to 1.64 | 1.43 | 0.004 | 1.17 to 1.76 | ||
| Education (high) | Low | 1.21 | 0.218 | 0.87 to 1.69 | 1.18 | 0.367 | 0.79 to 1.74 | |
| Medium | 1.20 | 0.316 | 0.81 to1.79 | 1.17 | 0.465 | 0.73 to 1.86 | ||
| Cross-border (148) | ||||||||
| Sex (female) | Male | 0.68 | 0.456 | 0.22 to 2.10 | 0.59 | 0.289 | 0.20 to 1.72 | |
| Age (25–44) | 18–24 | 0.66 | 0.285 | 0.28 to 1.53 | 0.78 | 0.539 | 0.32 to 1.92 | |
| 45–69 | 0.66 | 0.054 | 0.43 to 1.01 | 0.73 | 0.054 | 0.53 to 1.01 | ||
| Employment (employed) | Unemployed | 1.28 | 0.125 | 0.92 to 1.78 | 1.46 | 0.034 | 1.04 to 2.06 | |
| Other | 0.44 | 0.009 | 0.25 to 0.76 | 0.45 | 0.008 | 0.27 to 0.76 | ||
| Education (high) | Low | 0.41 | 0.045 | 0.17 to 0.97 | 0.43 | 0.022 | 0.21 to 0.85 | |
| Medium | 0.77 | 0.423 | 0.38 to 1.56 | 0.81 | 0.493 | 0.41 to 1.59 | ||
| Surrogate alcohol (19) | ||||||||
| Sex (female) | Male | 1.09 | 0.849 | 0.42 to 2.83 | 1.19 | 0.730 | 0.39 to 3.61 | |
| Age (25–44) | 18–24 | n/a | n/a | |||||
| 45–69 | 1.45 | 0.239 | 0.74 to 2.85 | 1.25 | 0.448 | 0.66 to 2.39 | ||
| Employment (employed) | Unemployed | 1.76 | 0.130 | 0.81 to 3.81 | 2.07 | 0.145 | 0.73 to 5.87 | |
| Other | 1.93 | 0.243 | 0.58 to 6.44 | 2.03 | 0.090 | 0.87 to 4.75 | ||
| Education (high) | Low | 0.59 | 0.529 | 0.09 to 3.78 | 0.55 | 0.492 | 0.08 to 3.70 | |
| Medium | 1.68 | 0.665 | 0.12 to 24.37 | 1.52 | 0.712 | 0.12 to 18.94 | ||
*Crude model on the bivariate association between dependent variable and one covariate.
†Multivariate model adjusting for all covariates simultaneously.
n/a, not available.