Multiple sclerosis (MS) is a chronic and progressively disabling inflammatory autoimmune disorder of the central nervous system. MS has a multifactorial etiology and is triggered by environmental factors in individuals with complex genetic risk profiles. The epidemiology of MS changes with the spatial and temporal distribution of these genetic and nongenetic risk factors. This population-based matched case-control study aimed to determine the risk factors for MS in Kuwait. From May 2 to 9, 2010, we enrolled 101 confirmed MS cases using the list frame maintained by the Multiple Sclerosis Association of Kuwait. For each case, two population controls individually matched for age (±2 years), gender and nationality were selected. Data on demographic, socioeconomic variables, potential genetic and environmental factors were collected using a structured questionnaire. For a case, the questions were directed to the period that preceded the recognition of the disease, while for each of the two matched controls, a date of ‘pseudodiagnosis’ of MS was established, i.e. the date on which the control subject was of the same age as his/her matched case was at MS diagnosis and accordingly questions were directed to the preceding period. The multivariable conditional logistic regression model showed that compared with controls, the cases were significantly more likely to have a family history of MS [matched odds ratio (OR)_adj = 6.7; 95% confidence interval (95% CI): 2.5–18.0; p < 0.001] or have suffered from a head trauma in the past before MS diagnosis (matched OR_adj = 2.6; 95% CI: 1.2–5.5; p = 0.014). Furthermore, compared with controls, cases were significantly more likely to have stayed in Kuwait during the Iraqi invasion of 1990 (matched OR_adj = 1.8; 95% CI: 1.1–3.5; p = 0.022). This study showed that a family history of MS, a history of head injury, and presence in Kuwait at the time of the Iraqi invasion of 1990 were associated with a significantly increased MS risk. Future retrospective cohort studies by using existing biological and epidemiological databases may provide a clue to MS etiology.