A prospective study of trends in consumption of cigarettes and alcohol among adults in a rural Ugandan population cohort, 1994–2011

Abstract

Abstractobjectives To characterise trends over time in smoking and alcohol consumption in a rural Ugandan population between 1994 and 2011.methods We used self-reported data from a long-standing population cohort -the General Population Cohort. From 1989 to 1999, the study population comprised about 10 000 residents of 15 adjacent villages. results The reported prevalence of smoking among men was 17% in 1994/1995, 14% in 2008/ 2009 and 16% in 2010/2011; equivalent figures for women were 1.5%, 1% and 2%. In the most recent time period, for both sexes combined, prevalence of smoking increased from 1.5% in those aged <29 years, to 18% in those 50+ years (P < 0.001); prevalence was 14.8% in the lowest tertile of socio-economic status, decreasing to 3.7% in the highest (P < 0.001). For alcohol consumption, current drinking was reported by 39% in 1996/1997, 35% in 2000/2001 and 28% in 2010/2011; men were more likely to drink than women (32.9% vs. 23.5% in 2010/2011) and consumption increased with age (P < 0.001); and was associated with low socio-economic status, riskier sexual behaviour and being HIV positive (P < 0.001).conclusions In this rural Ugandan population, consumption of cigarettes and alcohol is higher among men than women, increases with age and is more frequent among those with low socioeconomic status. We find no evidence of increases in either exposure over time.

Gender and age disparities in adult undernutrition in northern Uganda: high‐risk groups not targeted by food aid programmes

“…Our finding that men who smoked daily were twice as likely to be underweight as non‐smokers was therefore unsurprising. The prevalence of daily smokers was high (31.6%) and almost twice as high than the prevalence in south‐west Uganda .…”

Acceptability and Predictors of Uptake of Anti-retroviral Pre-exposure Prophylaxis (PrEP) Among Fishing Communities in Uganda: A Cross-Sectional Discrete Choice Experiment Survey

“…The sampling fractions differed between strata to allow oversampling of HIV-uninfected respondents. The sampling fractions were chosen based on the HIV prevalence in previous literature (7). Respondents who were absent after three visits over a three-month period were replaced at random by respondents from the same fishing community, matched for age group, gender and HIVnegative status.…”

“…Fishing communities constitute about 10% of Uganda's population and are one of the key populations at high risk of HIV-infection in Uganda (2)(3)(4)(5). HIV prevalence among fishing communities is estimated to be five times the national average, with women disproportionately affected (2)(3)(4)(6)(7)(8). HIV incidence among fishing communities is estimated to be between 3.3 to 6.7 cases/100 person-years, compared to <1 cases/100 person years at national level (3,4,9).…”

Consumo de bebida alcoólica entre fumicultores: prevalência e fatores associados

“…Alcohol was mainly consumed on the weekend 12 during reproduction moments, when the worker seeks relaxation 3 , recreational activities, and festivities 4,28 . In the literature, the association between age and high-risk consumption or heavy drinking are inconsistent 3,7,9,13,19,21,22,28,31 . In this study, a higher frequency of high-risk consumption was found among young men and women 19,28 , which reflects the cultural values and social norm that considers the practice acceptable and even incentives drinking in parties and gatherings in the communities 4,28 .…”

“…Working longer hours in the field, driving a motor vehicle or tractor, and using agricultural equipment were associated with consumption over the previous 30 days 29 . Being retired and having some type of social support 22 were protection factors against highrisk consumption while practicing some religion was negatively associated with alcohol-related disorders 30 and high-risk consumption 19,31 . Inconsistent findings were reported regarding the association of age 9,18,21,22,31 , income 8,9,18,22 , marital status 5,9,18,22,31, schooling 6,7,10,12,19,21,31 , and hours of work in agriculture 32 with different consumption patterns.…”