Background: The link between unhealthy lifestyle factors and non-communicable diseases is evident from a range of studies. Policy makers in high income settings have access to information identifying segments of the population where unhealthy lifestyles are most prevalent. However, this same information for low and middle income countries (LMICs)remains scarce, making it difficult to inform and target effective interventions. This study aims to quantify the prevalence and socioeconomic inequalities in unhealthy lifestyle factors in LMICs and to identify policy priority areas on the path towards the Sustainable Development Goal of reducing deaths from non-communicable diseases by one third in 2030. Methods: Self-reported data from 1,278,624 adults derived from the Demographics & Health Surveys in 22 LMICs between 2013 and 2018 were used to estimate crude prevalence rates and socioeconomic inequalities in BMI, tobacco use, alcohol use and harmful alcohol use. The variation in lifestyle factors across socioeconomic status is measured by means of the Erreygers concentration index. We identify whether countries that invest more in population health are less likely to exhibit large socioeconomic inequalities in unhealthy lifestyles by correlating the percentage of GDP spent on health with the Erreygers concentration index. We use a four quadrant model to identify countries that should be prioritized because of a “double disadvantage” i.e. both a skewed distribution of unhealthy lifestyles towards the poor and low spending on health nationwide. Results: Tobacco and alcohol use is largely concentrated among the poor, while overweight is heavily concentrated among the better-off in LMICs. Clustering of alcohol and tobacco use in individuals as shown for high income countries, is not found for LMICs. Conclusions: This study emphasized that unhealthy lifestyles play an important role in LMICs, and that different unhealthy lifestyle factors vary in their socioeconomic distribution. The targeting of interventions to reduce the burden from unhealthy lifestyles in LMICs should not be simply copied from high income countries but be tailored towards high-risk populations in LMICs. We identified Congo, Tanzania and Zambia as the most disadvantaged countries in our sample, implying that priority should be given to these populations, allowing for the largest health improvements.