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Sample size determination for open-ended questions or qualitative interviews relies primarily on custom and finding the point where little new information is obtained (thematic saturation). Here, we propose and test a refined definition of saturation as obtaining the most salient items in a set of qualitative interviews (where items can be material things or concepts, depending on the topic of study) rather than attempting to obtain all the items. Salient items have higher prevalence and are more culturally important. To do this, we explore saturation, salience, sample size, and domain size in 28 sets of interviews in which respondents were asked to list all the things they could think of in one of 18 topical domains. The domains-like kinds of fruits (highly bounded) and things that mothers do (unbounded)-varied greatly in size. The datasets comprise 20-99 interviews each (1,147 total interviews). When saturation was defined as the point where less than one new item per person would be expected, the median sample size for reaching saturation was 75 (range = 15-194). Thematic saturation was, as expected, related to domain size. It was also related to the amount of information contributed by each respondent but, unexpectedly, was reached more quickly when respondents contributed less information. In contrast, a greater amount of information per person increased the retrieval of salient items. Even small samples (n = 10) produced 95% of the most salient ideas with exhaustive listing, but only 53% of those items were captured with limited responses per person (three). For most domains, item salience appeared to be a more useful concept for thinking about sample size adequacy than finding the point of thematic saturation. Thus, we advance the concept of saturation in salience and emphasize probing to increase the amount of information collected per respondent to increase sample efficiency.

Deaths due to hypertension in the US are highest among African Americans, who have a higher prevalence of hypertension and more severe hypertensive symptoms. Research indicates that there are both genetic and sociocultural risk factors for hypertension. Racial disparities in hypertension also likely involve genetic and sociocultural factors, but the factors may interact and manifest differently across racial groups. Here we use a biocultural approach to integrate genetic and social network data to better understand variation in blood pressure. We assay genetic variation at the angiotensin I converting enzyme gene (ACE) and analyze social network composition and structure in African Americans living in Tallahassee, FL (n = 138). We demonstrate that models including both genetic and social network data explain significantly more variation in blood pressure and have better model diagnostics than do models including only one datatype. Specifically, optimal models for systolic and diastolic blood pressure explain a notable 35% and 21%, respectively, of blood pressure variation. Analysis of the social networks reveals that individuals whose networks are dominated by family connections and are more fragmented have higher blood pressure. Historically, family support has been associated with better mental and physical health, but our results suggest that those family connections can also take a toll on health. These findings raise compelling questions regarding the roles of genetics, family, and social environment in hypertension in the African American community and suggest that interactions among these factors may help explain racial disparities in hypertension more accurately than any of the factors alone.

Sequencing of the human genome and decades of genetic association and linkage studies have dramatically improved our understanding of the etiology of many diseases. However, the multiple causes of complex diseases are still not well understood, in part because genetic and sociocultural risk factors are not typically investigated concurrently. Hypertension is a leading risk factor for cardiovascular disease and afflicts more African Americans than any other racially defined group in the US. Few genetic loci for hypertension have been replicated across populations, which may reflect population-specific differences in genetic variants and/or inattention to relevant sociocultural factors. Discrimination is a salient sociocultural risk factor for poor health and has been associated with hypertension. Here we use a biocultural approach to study blood pressure (BP) variation in African Americans living in Tallahassee, Florida by genotyping over 30,000 single nucleotide polymorphisms (SNPs) and capturing experiences of discrimination using novel measures of unfair treatment of self and others (n = 157). We perform a joint admixture and genetic association analysis for BP that prioritizes regions of the genome with African ancestry. We only report significant SNPs that were confirmed through our simulation analyses, which were performed to determine the false positive rate. We identify eight significant SNPs in five genes that were previously associated with cardiovascular diseases. When we include measures of unfair treatment and test for interactions between SNPs and unfair treatment, we identify a new class of genes involved in multiple phenotypes including psychosocial distress and mood disorders. Our results suggest that inclusion of culturally relevant stress measures, like unfair treatment in African Americans, may reveal new genes and biological pathways relevant to the etiology of hypertension, and may also improve our understanding of the complexity of gene-environment interactions that underlie complex diseases.

The description and explanation of racial and ethnic health disparities are major initiatives of the public health research establishment. Black Americans suffer on nearly every measure of health in relation to white Americans. Five theoretical models have been proposed to explain these disparities: a racial-genetic model, a health-behavior model, a socioeconomic status model, a psychosocial stress model, and a structural-constructivist model. We psychosocial review literature on health disparities, emphasizing research on low birth weight and high blood pressure. The psychosocial stress model and the structural-constructivist model offer greatest promise to explain disparities. In future research, theoretical elaboration and operational specificity are needed to distinguish among three distinct factors: (a) genetic variants contributing to disease risk; (b) ethnoracial or folk racial categories masquerading as biology; and (c) ethnic group membership. Such elaboration is necessary to move beyond the conflation of these three distinct constructs that characterizes much of current research.

The role of race in human genetics and biomedical research is among the most contested issues in science. Much debate centers on the relative importance of genetic versus sociocultural factors in explaining racial inequalities in health. However, few studies integrate genetic and sociocultural data to test competing explanations directly. We draw on ethnographic, epidemiologic, and genetic data collected in Southeastern Puerto Rico to isolate two distinct variables for which race is often used as a proxy: genetic ancestry versus social classification. We show that color, an aspect of social classification based on the culturally defined meaning of race in Puerto Rico, better predicts blood pressure than does a genetic-based estimate of continental ancestry. We also find that incorporating sociocultural variables reveals a new and significant association between a candidate gene polymorphism for hypertension (alpha(2C) adrenergic receptor deletion) and blood pressure. This study addresses the recognized need to measure both genetic and sociocultural factors in research on racial inequalities in health. Our preliminary results provide the most direct evidence to date that previously reported associations between genetic ancestry and health may be attributable to sociocultural factors related to race and racism, rather than to functional genetic differences between racially defined groups. Our results also imply that including sociocultural variables in future research may improve our ability to detect significant allele-phenotype associations. Thus, measuring sociocultural factors related to race may both empower future genetic association studies and help to clarify the biological consequences of social inequalities.

Objectives. Our understanding of the relationships between perceived discrimination and health was limited by the cross-sectional design of most previous studies. We examined the longitudinal association of self-reported everyday discrimination with depressive symptoms and self-rated general health. Methods. Data came from 2 waves (1996 and 2001) of the Eastside Village Health Worker Partnership survey, a community-based participatory survey of African American women living on Detroit’s east side (n=343). We use longitudinal models to test the hypothesis that a change in everyday discrimination over time is associated with a change in self-reported symptoms of depression (positive) and on self-reported general health status (negative). Results. We found that a change over time in discrimination was significantly associated with a change over time in depressive symptoms (positive) (b=0.125; P<.001) and self-rated general health (negative) (b=−0.163; P<.05) independent of age, education, or income. Conclusions. The results reported here are consistent with the hypothesis that everyday encounters with discrimination are causally associated with poor mental and physical health outcomes. In this sample of African American women, this association holds above and beyond the effects of income and education.

Forces such as the opening of trade, globalization, multinational corporate resource extraction, urbanization, acculturation, and colonization catalyze economic, ecological, and sociocultural change, which can threaten the well‐being and habitat of native Amazonians. Understanding these forces is of paramount importance to improve the well‐being of native Amazonians and to foster the conservation of biological diversity, yet most analyses of these forces rely on cross‐sectional data. Though adequate to describe the association between variables at one point in time, cross‐sectional data do not allow one to estimate changes in well‐being over time. We collected data annually during five consecutive years (2002–2006, inclusive) from a foraging and farming society of native Amazonians in Bolivia (Tsimane’) to estimate annual rates of change for seven indicators of adult well‐being. Indicators encompassed both objective and subjective measures of well‐being that included economic, health, psychological, and social dimensions that overlap well with Tsimane’ notions of well‐being. The annual rate of change in the inflation‐adjusted (hereafter real) value of food consumption (+6.35%), body mass index (+0.71%), and incidence of anger (−10.40%) show significant improvements over time, but the annual rate of change in the self‐reported number of recent ailments (+7.35%) shows a significant deterioration. Trends in other indicators of well‐being (smiles, real wealth, social relations) show positive but insignificant rates of change. Results did not vary by sex and were consistent when using other indicators of well‐being.

Objectives. We assessed the relative roles of education and genetic ancestry in predicting blood pressure (BP) within African Americans and explored the association between education and BP across racial groups. Methods. We used t tests and linear regressions to examine the associations of genetic ancestry, estimated from a genomewide set of autosomal markers, and education with BP variation among African Americans in the Family Blood Pressure Program. We also performed linear regressions in self-identified African Americans and Whites to explore the association of education with BP across racial groups. Results. Education, but not genetic ancestry, significantly predicted BP variation in the African American subsample (b = −0.51 mm Hg per year additional education; P = .001). Although education was inversely associated with BP in the total population, within-group analyses showed that education remained a significant predictor of BP only among the African Americans. We found a significant interaction (b = 3.20; P = .006) between education and self-identified race in predicting BP. Conclusions. Racial disparities in BP may be better explained by differences in education than by genetic ancestry. Future studies of ancestry and disease should include measures of the social environment.

The Handbook of Methods in Cultural Anthropology, now in its second edition, maintains a strong benchmark for understanding the scope of contemporary anthropological field methods.Avoiding divisive debates over science and humanism, the contributors draw upon both traditions to explore fieldwork in practice.

Objectives. We tested competing hypotheses for the skin color–blood pressure relationship by analyzing the association between blood pressure and 2 skin color variables: skin pigmentation and social classification. Methods. We measured skin pigmentation by reflectance spectrophotometry and social classification by linking respondents to ethnographic data on the cultural model of “color” in southeastern Puerto Rico. We used multiple regression analysis to test the associations between these variables and blood pressure in a community-based sample of Puerto Rican adults aged 25–55 years (n=100). Regression models included age, gender, body mass index (BMI), self-reported use of antihypertensive medication, and socioeconomic status (SES). Results. Social classification, but not skin pigmentation, is associated with systolic and diastolic blood pressure through a statistical interaction with SES, independent of age, gender, BMI, self-reported use of antihypertensive medication, and skin reflectance. Conclusion. Our findings suggest that sociocultural processes mediate the relationship between skin color and blood pressure. They also help to clarify the meaning and measurement of skin color and “race” as social variables in health research.