Abstract:
Alcohol use has been part of many cultures globally for many years. However,
alcoholism or alcohol use disorders was recognized in Kenya in 2014 as a disease as
classified by World Health Organization. Alcoholism is one of the highest causes of
global disease burden resulting from liver cirrhosis, road traffic accidents and several
types of cancers. In Kenya alcoholism is a persistent health problem with harmful
alcohol consumption, especially among young people (18-35 years), being on the rise
in spite of stringent laws governing alcohol use. Existing models consider transmission
of alcoholism through social interaction in addition prevalence and incidences of
alcohol use and alcoholism in Kenya have mainly been determined using surveys.
Models that address the progression stages of alcoholism, from susceptible through
social drinking to alcoholism are lacking. This study sought to analyse structural
relationship between risk factors and alcoholism and model alcoholism as a non communicable disease. The specific objectives were to: Analyse structural relationship
between risk factors and alcoholism; model incubation period of alcoholism; evaluate
parametric and non-parametric hazard of alcoholism and predict incidences of
alcoholism. Method: Secondary data was sourced from the Ministry of Health.
Structural Equation Modelling (SEM) was used to show structural relationship between
alcoholism and the latent variables; to model incubation period of alcoholism
Birnbaum-Saunders (B-S) distribution hinged on biological process of cumulative cell
damage caused by excessive alcohol consumption was used; hazard of becoming
alcoholic was determined non-parametrically using discrete-time hazard model and
incidences of alcoholism were found using logistic regression and back-projection.
Results: There was a significant relationship between alcoholism and the risk factors
(gender, peer influence, age at onset, social-cultural, economic status, environmental
settings, drinking habits and pattern, family and family attention and personality)
(RMSEA =0.06; CFI =0.80; SRMR=0.06); B-S distribution (𝛼 =0.77 [CI: 0.68, 0.85]
and 𝛽 = 6.13 [CI: 5.44, 6.83], R
2 =0.94, was appropriate for modelling incubation
period of alcoholism; the probability of becoming alcoholic increased from 0.31%
when drinking once per week to 57% when drinking seven sessions a week, in addition
the hazard of becoming alcoholic was higher for females than for males; The model
was used to predict incidence of alcoholism between 2014 and September 2019. The
predicted number of alcoholics (6632) do not differ significantly from the reported
cases alcoholics (6631). In conclusion the analyses of the relationship between risk
factors and alcoholism showed that risk of becoming alcoholic was affected differently
by different risk factors with gender having the largest impact. Biophysical process of
fatigue failure caused by cumulative cell damage yielded a model of alcoholism as a
non-communicable disease. Recommendation: The study recommends initiatives for
sensitization on impacts of alcohol use and early diagnosis of alcoholism to help initiate
prevention policies.