There are a number of strengths to using federal survey data for research, such as the ability to generalize findings at a national level or across large populations. However, a number of limitations exist, such as the cross-sectional nature of the data, weaknesses with self-reported data, and selection bias. In general, problems stem from the size of these segments relative to the total population due to the small likelihood that an adequate number will be included in the sample to study. These segments may also be less likely to particulate in federal survey research or difficult to identify when they do.
To illustrate the challenges facing research on small populations, this report focuses on four case examples:
Asian-American subpopulations. Challenges exist in obtaining adequate sample sizes to conduct analysis on Asian Americans overall, and even more for subpopulations. However, instances where subpopulation analysis has been possible reveal major differences in health. There is also a lack of consistent race/ethnicity categories used in data collection.
Lesbian, gay, bisexual, and transgender population. Many of the health issues and research challenges facing this population are related to stigma, which has caused hesitation in collecting data on LGBT status and has prevented this population from identifying themselves. In addition, there is a lack of standard definitions by which to identify this population through surveys, as questions regarding behavior, attraction, and identity all result in different responses and each have important implications for health.
Adolescents with autism spectrum disorders. While much research has concentrated on diagnosis of these disorders during childhood, little is known about health and health care during the transition to adulthood for individuals with ASDs, a time period that is critical to their future well-being. The cross-sectional nature of most surveys and inconsistency in how disability is measured among children and in adults makes it impossible to follow this population over time in most existing survey data.
Rural populations. Geographic isolation and low population density has limited both economic opportunities and access to health care services for rural populations, who face the health care needs of an aging population as well as unique environmental health issues. Variations in how to define the boundaries of rural areas (which may not always align with county -boundaries—the smallest geographic unit used in most surveys) also complicate studying this population.