It is important to analyze sex and gender (see Analyzing Sex; Analyzing Gender), but examining how other factors intersect with sex and gender is also necessary (Hankivsky et al., 2008). These factors or variables can be biological, socio-cultural, or psychological aspects of users, customers, experimental subjects, or cells. These factors include but are not limited to:

• ●Genetics
  ●Age
  ●Sex Hormones
  ●Reproductive Status
  ●Body Composition
  ●Comorbidities
  ●Body Size
  ●Disabilities
  ●Ethnicity
  ●Nationality
  ●Geographic Location
  ●Socioeconomic Status
  ●Educational Background
  ●Sexual Orientation
  ●Religion
  ●Lifestyle
  ●Language
  ●Family Configuration
  ●Environment
  

Researchers can investigate how sex and/or gender intersect with other significant factors by:

• 1. Identifying relevant factors or variables. Before beginning a study, researchers should hypothesize relevant factors. Sex and gender intersect with other biological and social variables to produce between- or within-group differences (Whittle et al., 2001). Those factors may reveal sub-group differences among women and among men that would have been obscured by using only gender or sex as a variable (see Case Study: Nutrigenomics). Accounting for differences in socioeconomic status, for example, may reveal unexpected differences between women and men that cannot be explained by gender or socioeconomic status alone, such as women of high socioeconomic status having similar health outcomes similar to those of men of low socioeconomic status (Sen et al., 2010). 
  
• 2. Defining factors or variables. Researchers need to define factors explicitly in order to be able to account for potential users (see Case Study: Public Transportation), explain health disparities, reduce publication bias, and conduct reliable meta-analyses (Schulz et al., 2006; Rommes et al., 2000). 
  
• 3. Identifying intersections between factors or variables. Understanding how factors interrelate with sex or gender is important in explaining or predicting differences in health outcomes and determining user needs (Weber et al., 2007; Faulkner, 2004). For example, sex, socioeconomics, gendered divisions of labor, and language have all been found to interact in determining how agricultural workers are exposed to endocrine disruptors (see Case Study:Environmental Chemicals), and sex, geography, and gender relations interact to determine the technological needs of women and men (see Case Study: HIV Microbicides).