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... each regression, IQ and N were en- tered in Step 1, and Health Behaviors was entered in Step 2. Lastly, we incorporate state income levels and additional var- iables (i.e., the sub-domains of well-being reported by Pesta et al., 2010) to see where Health Behaviors and Chronic Dis- ease fit within the U.S. state well-being nexus. Table 1 shows rankings by U.S. state for IQ, N and the three BRFSS factor scores (Health Behaviors, Chronic Disease, and Metabolic Syndrome). Note for example that West Vir- ginia has the highest incidence of Chronic Disease. ...
Citations
... There is research evidence that higher neuroticism is associated with higher levels on the lifestyle health risk factors used in the present study singly or in combination. This has been demonstrated in individual-level studies (e.g., Krizan & Hisler, 2019) and in state-level studies (e.g., McCann, 2010McCann, , 2014McCann, , 2023aMcCann, , 2025Pesta et al., 2012). Studies with individuals as the analytic units also have demonstrated that higher neuroticism prospectively predicts lifestyle health risk factors such as smoking (e.g., Zvolensky et al., 2015) and physical inactivity (Caille et al., 2024). ...
... Past research also supports a positive relation between neuroticism and chronic conditions with individuals as the analytic units (e.g., Heid et al., 2021;Wright et al., 2022) and with states as the analytic units (e.g., McCann, 2014McCann, , 2020McCann, , 2021McCann, , 2023aMcCann, , b, 2024bPesta et al., 2012). Also, there is individual-level evidence that neuroticism may be a causal factor regarding chronic conditions. ...
... State-level research providing information regarding the relation between IQ and such health risk factors is quite limited. However, one state-level study by Pesta et al. (2012) has reported a positive relation of IQ to exercise and activity, and a negative relation to smoking. There also is evidence that such relations may be causal in nature. ...
This study is the first to examine the plausibility of a network of speculated direct and indirect causal paths between general population Neuroticism, general population IQ, senior (65 years and over) socioeconomic status (SES), senior lifestyle Health Risk Factors, and senior Chronic Conditions using structural equation modelling (SEM). Focused on 2018–2019 with the 48 contiguous American states as analytic units, the final model showed four significant direct paths: Neuroticism to Chronic Conditions (β = 0.39), IQ to Chronic Conditions (β = − 0.25), SES to Health Risk Factors (β = − 0.80), and Health Risk Factors to Chronic Conditions (β = 0.34). SES also showed a significant indirect path through Health Risk Factors to Chronic Conditions (β = − 0.27). As well, neither Neuroticism nor IQ had an indirect impact through Health Risk Factors on Chronic Conditions, and SES also had no direct impact on Chronic Conditions. This final model accounted for 64% of the variance in Health Risk Factors and 57% of the variance in Chronic Conditions. SEM statistics showed a high goodness of fit (e.g., RMSEA = 0.046; CFI = 0.998; Tucker-Lewis Index = 0.992; GFI = 0.974; SRMR = 0.037). Spatial lag adjustment for spatial autocorrelation revealed no substantive difference in the SEM results pattern. These results strongly suggest that neuroticism, IQ, and SES each should be treated as important sociodemographic variables within a multivariable framework in the prediction and explanation of lifestyle health risk factors and chronic conditions, and the relations of such health risk factors to chronic conditions.
... However, recent intelligence estimates for the general population of each state based on individual-level standardized test results have been produced by Pesta (2022). Using somewhat similar procedures and databases, these state IQ scores essentially update earlier estimates produced by McDaniel (2006) which have been used occasionally (e.g., McDaniel et al., 2015;Pesta et al., 2012;Pesta & McDaniel, 2014). ...
... Research shows that those facing the challenges of the added burden of living with chronic conditions are more likely to report mental distress (e.g., Massetti et al., 2017;Price et al., 2020). They also are more likely to manifest lower intelligence and higher neuroticism (e.g., Charles et al., 2008;Gottfredson & Deary, 2004;Pesta et al., 2012). The multiple chronic conditions variable in the present study pertains directly to adults over 65 having four or more chronic conditions. ...
... This somewhat unconventional final equation entry order was employed because it was assumed that dispositional intelligence and neuroticism are fundamental variables temporally and developmentally antecedent to poverty, educational attainment, and chronic conditions. As Pesta et al. (2012) pointed out, their dispositional variance accounting capacities consequently should take precedence over those of these other five potential contributors. ...
This study determined (1) whether state resident levels of intelligence and neuroticism in the general populations of the 50 states of the USA are independently related to state frequent mental distress (FMD) prevalence among older adults, and (2) whether such state intelligence and neuroticism levels account for any relations found between FMD prevalence and older adult poverty, educational attainment, chronic conditions, health behavior, and clinical care quality. Using 2019 data, Pearson correlations and multiple regression determined relations between FMD for persons 65 years and over and each of the seven potential predictors. FMD correlated significantly with intelligence (-.62), neuroticism (.38), poverty (.58), chronic conditions (.50), health behavior (-.47), and clinical care quality (-.45). Multiple regression showed that intelligence and neuroticism were independent predictors of FMD, and that older adult poverty level was the only independent predictor of FMD from a pool consisting of educational attainment, chronic conditions, health behavior, and clinical care quality variables as other potentially independent predictors. However, with intelligence and neuroticism statistically controlled in a sequential multiple regression equation, none of these five other variables was retained as a significant predictor of FMD. It is cautiously speculated that the resulting state-level relations largely mirror and are based on the accumulation of individual-level relations, that the foundational dispositions of intelligence and neuroticism may foster the development of FMD among older adults, and that older adult poverty, educational attainment, chronic conditions, health behavior, and clinical care quality also stem in part from state resident levels of intelligence and neuroticism.
... Elleman et al. (2018) showed that these Big Five state scores had consistent relations at least through until 2015, the last year examined in their research. As well, researchers have successfully used the scores in many studies since they were developed (e.g., McCann, 2019a, 2019b, Gerhart et al., 2020, McCann, 2014, 2019a, 2019b, Pesta et al., 2012, Renfrow et al., 2013. Furthermore, the temporal robustness of the state personality scores is evident in the relations found in the current research. ...
Two studies using the 48 contiguous American states tested the general hypothesis that the percent of the total number of movers leaving an origin state that migrates to a particular destination state is related to the degree of similarity in Big Five personality between the residents of the origin state and the destination state. Datasets for 2005-2006 and 2016-2017 were analyzed. The hypothesis was tested using Pearson correlation and multiple regression strategies without and with consideration of the following state-level statistical controls: socioeconomic status based on two economic and two educational variables, unemployment rate, White population percent, urban population percent, conservatism, and road distance between state capitals for the 48 states. A consistent pattern of support for the hypothesis was found for each of the Big Five personality dimensions—openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism—for both datasets without and with statistical controls. Results without statistical controls demonstrated that movers from states with residents higher on a Big Five personality dimension indeed are more likely to migrate to states with residents higher on that personality dimension, and that movers from states with residents lower on a personality dimension are more likely to migrate to states with residents lower on that personality dimension. Similar results were obtained with statistical controls but the relations for conscientiousness were in the supportive direction but not statistically significant. It is speculated that these state-level relations are grounded in parallel individual-level relations suggested by the theories of selective migration, homophily, similarity-attraction, and person-environment fit.
... Pesta et al. (2010) first reported this effect for aggregate-level data, though Belasen and Hafer (2013) reported the same using individual-level data. Thus, there appears to be a consistent, positive correlation between IQ and alcohol consumption, and even alcohol consumption and various chronic health conditions (Pesta et al. 2012). Consider the correlations between alcohol consumption and the variables I used here to measure state health. ...
At the level of the 50 U.S. states, an interconnected nexus of well-being variables exists. These variables strongly correlate with estimates of state IQ in interesting ways. However, the state IQ estimates are now more than 16 years old, and the state well-being estimates are over 12 years old. Updated state IQ and well-being estimates are therefore needed. Thus, I first created new state IQ estimates by analyzing scores from both the Program for the International Assessment of Adult Competency (for adults), and the National Assessment of Educational Progress (for fourth and eighth grade children) exams. I also created new global well-being scores by analyzing state variables from the following four well-being subdomains: crime, income, health, and education. When validating the nexus, several interesting correlations existed among the variables. For example, state IQ most strongly predicted FICO credit scores, alcohol consumption (directly), income inequality, and state temperature. Interestingly, state IQ derived here also correlated 0.58 with state IQ estimates from over 100 years ago. Global well-being likewise correlated with many old and new variables in the nexus, including a correlation of 0.80 with IQ. In sum, at the level of the U.S. state, a nexus of important, strongly correlated variables exists. These variables comprise well-being, and state IQ is a central node in this network.
... In addition to mapping the geographical distribution of the Big Five, several studies have investigated the ways in which regional personality differences relate to important political, economic, social, and health (PESH) outcomes. For example, studies have revealed evidence that state-level Big Five scores are related to health and morbidity (McCann, 2010a(McCann, , 2010bPesta et al., 2012;Voracek, 2009), psychological well-being (McCann, 2011;Pesta et al., 2010;Rentfrow, Mellander, & Florida, 2009), social capital (Rentfrow, 2010), creative capital (Florida, 2008), income inequality (De Vries et al., 2011), entrepreneurship rates (Obschonka et al., 2013), innovation (Lee, 2017), political values (Rentfrow, Jost, et al., 2009), regional stereotypes (Rogers & Wood, 2010), and economic behavior (Ebert et al., 2020;Matz & Gladstone, 2018). ...
... These studies have focused on just a single level of spatial analysis, such as large multistate regions, U.S. states, cities, or neighborhoods (Bleidorn et al., 2016;Jokela et al., 2015;Rentfrow et al., 2008Rentfrow et al., , 2015. Furthermore, the results from this research suggest that regional differences in the Big Five are associated with a number of important PESH outcomes (e.g., votes in political elections, economic innovations, violent crimes, disease death rates; Lee, 2017;McCann, 2010aMcCann, , 2010bMcCann, , 2011Obschonka et al., 2013Obschonka et al., , 2015Obschonka et al., , 2018Pesta et al., 2012;Rentfrow et al., 2008Rentfrow et al., , 2015. However, it is unclear whether the correlates of regional personality differences generalize across multiple spatial levels, and only very few studies have controlled for spatial dependencies in the data. ...
... With respect to research on regional personality differences, some of the observed results from different studies show patterns of associations that are consistent between individual and aggregate levels of analysis, and some do not. For example, the patterns of results for emotional stability and openness reveal a remarkable consistency across different spatial units and countries (McCann, 2011;Pesta et al., 2012;Rentfrow et al., 2008Rentfrow et al., , 2015, which is consistent with results observed at the individual level (Ozer & Benet-Martınez, 2006;Roberts et al., 2007). However, the patterns of associations observed for extraversion, agreeableness, and conscientiousness appear less stable and fluctuate depending on the country and level of aggregation. ...
There is growing evidence that psychological characteristics are spatially clustered across geographic regions and that regionally aggregated psychological characteristics are related to important outcomes. However, much of the evidence comes from research that relied on methods that are theoretically ill-suited for working with spatial data. The validity and generalizability of this work are thus unclear. Here we address two main challenges of working with spatial data (i.e., modifiable areal unit problem and spatial dependencies) and evaluate data-analysis techniques designed to tackle those challenges. To illustrate these issues, we investigate the robustness of regional Big Five personality differences and their correlates within the United States (Study 1; N = 3,387,303) and Germany (Study 2; N = 110,029). First, we display regional personality differences using a spatial smoothing approach. Second, we account for the modifiable areal unit problem by examining the correlates of regional personality scores across multiple spatial levels. Third, we account for spatial dependencies using spatial regression models. Our results suggest that regional psychological differences are robust and can reliably be studied across countries and spatial levels. The results also show that ignoring the methodological challenges of spatial data can have serious consequences for research concerned with regional psychological differences.
... That is, a resident of a region typically has a more similar personality to fellow residents than non-residents. Additionally, the aggregated personalities of regions are associated with important region-level demographics, such as rates of chronic disease (Pesta et al., 2012) and crime (Rentfrow et al., 2008). These results have been found for regions of varying sizes: countries (McCrae & Terracciano, 2008), large regions within a country (e.g., New England and the Midwest; Rentfrow et al., 2013), smaller regions within a country (e.g., U.S. states; Rentfrow et al., 2008), cities (Park & Peterson, 2010), and even neighborhoods within a city (Jokela et al., 2015). ...
The personality of individuals is clustered by geographic regions; a resident of a region is more similar to another resident than to a random non-resident. Research in geographical psychology often has focused on this clustering effect in broad regions, such as countries and states, using broad domains of personality, such as the Big Five. We examined the extent to which (a) a narrower geographic unit, the U.S. ZIP Code, accounted for more variance explained in aggregating personality than a broader region, the U.S. state; and (b) progressively narrower personality traits (domains, facets, and nuances, respectively) provided more specificity in describing personality-demographic relationships. Results from this study (nparticipants = 39,886, nzipcodes = 2,074) indicated that the variance explained by aggregating personality was multiple times as large for U.S. ZIP Codes than for states (median = 4.4). At the level of personality domains, ZIP Code population density and income disparity were positively correlated with Openness and negatively correlated with Conscientiousness and Agreeableness. Facets within each domain were differentially correlated with each demographic, which demonstrated that facets added specificity to the personality-demographic relationships beyond that of domains. Item-level analysis revealed the most specific finding: higher population density and income disparity were associated with politically liberal attitudes and beliefs of self-exceptionalism, while lower density and income disparity were associated with authoritarian attitudes and concern for abiding by rules and laws. Findings suggest that future studies in geographical and personality psychology could benefit from using the narrowest feasible unit of analysis.
... That is, a resident of a region typically has a more similar personality to fellow residents than non-residents. Additionally, the aggregated personalities of regions are associated with important region-level demographics, such as rates of chronic disease (Pesta, Bertsch, McDaniel, Mahoney, and Poznanski, 2012) and crime (Rentfrow, Gosling, and Potter, 2008). These results have been found for regions of varying sizes: countries (McCrae and Terracciano, 2008), large regions within a country (e.g., New England and the Midwest; Rentfrow, Gosling, Jokela, and Stillwell, 2013), smaller regions within a country (e.g., U.S. states; Rentfrow et al., 2008), cities (Park and Peterson, 2010), and even neighborhoods within a city (Jokela, Bleidorn, Lamb, Gosling, and Rentfrow, 2015). ...
The personality of individuals is clustered by geographic regions; a resident of a region is more similar to another resident than to a random non-resident. Research in geographical psychology often has focused on this clustering effect in broad regions, such as countries and states, using broad domains of personality, such as the Big Five. We examined the extent to which (a) a narrower geographic unit, the U.S. ZIP Code, accounted for more variance explained in aggregating personality than a broader region, the U.S. state; and (b) progressively narrower personality traits (domains, facets, and nuances, respectively) provided more specificity in describing personality-demographic relationships. Results from this study (n_participants = 39, 886, n_zipcodes = 2, 074) indicated that the variance explained by aggregating personality was multiple times as large for U.S. ZIP Codes than for states (median = 4.4). At the level of personality domains, ZIP Code population density and income disparity were positively correlated with Openness and negatively correlated with Conscientiousness and Agreeableness. Facets within each domain were differentially correlated with each demographic, which demonstrated that facets added specificity to the personality-demographic relationships beyond that of domains. Item-level analysis revealed the most specific finding: higher population density and income disparity were associated with politically liberal attitudes and beliefs of self-exceptionalism, while lower density and income disparity were associated with authoritarian attitudes and concern for abiding by rules and laws. Findings suggest that future studies in geographical and personality psychology could benefit from using the narrowest feasible unit of analysis.
... These results remained even after controlling for factors such as income and gender. Finally, regional personality differences have been shown to have significant correlations with mortality rates (Rentfrow et al., 2008, chronic disease rates (Pesta et al., 2012), suicide rates (McCann, 2010), and other public health indicators. For example, Pesta et al. (2012) found that neuroticism has positive associations with variables measured at the state-level such as diabetes, high blood pressure, coronary heart disease, and other chronic diseases. ...
... Finally, regional personality differences have been shown to have significant correlations with mortality rates (Rentfrow et al., 2008, chronic disease rates (Pesta et al., 2012), suicide rates (McCann, 2010), and other public health indicators. For example, Pesta et al. (2012) found that neuroticism has positive associations with variables measured at the state-level such as diabetes, high blood pressure, coronary heart disease, and other chronic diseases. The findings remained robust when controlling for income, education, and crime rate across states. ...
Geographical psychology aims to study the spatial distribution of psychological phenomenon at different levels of geographical analysis and their relations to macro-level important societal outcomes. The geographical perspective provides a new way of understanding interactions between humankind psychological processes and distal macro-environments. Studies have identified the spatial organizations of a wide range of psychological constructs, including (but not limited among) personality, individualism/collectivism, cultural tightness-looseness, and well-being; these variations have been plotted over a range of geographical units (e.g., neighborhoods, cities, states, and countries) and have been linked to a broad array of political, economic, social, public health, and other social consequences. Future research should employ multi-level analysis, taking advantage of more deliberated causality test methods and big data techniques, to further examine the emerging and evolving mechanisms of geographical differences in psychological phenomena.
... speaking, Binferential^statistics logically are unnecessary here (e.g., see McCann 2017a; Simonton 1984, Appendix A). As well, past smallsample studies have successfully used similar multiple regression strategies when the units of analysis have been states (e.g., McCann 2008McCann , 2014bPesta et al. 2012) and individuals (e.g., McCann 1992McCann , 1997Simonton 1986). ...
The present research was conducted to determine state-level relations of resident neuroticism to age-adjusted cancer incidence, overall health status, the prevalence of four other major illnesses, the incidence of 25 invasive cancer sites, all-cause mortality, and 10 main cause-of-death categories. Responses of 619,397 residents to the Big Five Inventory between 1999 and 2005 produced state neuroticism scores for each of the 50 states. State socioeconomic status, White population percent, urban population percent, heavy drinking, smoking, obesity, exercise, and consumption of fruits and vegetables served as control variables. For each of the 44 criteria, statistical control was attained in sequential multiple regression equations by entering the eight variables first as block, and then first stepwise, followed by the forced entry of neuroticism. For the 2000–2010 period, Study 1 established that state resident neuroticism accounted for an additional 11.2 to 31.7% of the variance in total, male, and female cancer incidence. With the same analytic procedures, Study 2 provided evidence for convergent and discriminant validity. Neuroticism accounted for significant variance in the incidence of a majority of the top 25 invasive cancer sites between 2000 and 2010, and cancer as a cause of death in 2011. In contrast, neuroticism was not a significant positive predictor of overall health in 2011, all-cause mortality in 2011, the prevalence of diabetes, COPD, and kidney disease in 2011, or, death in 2011 from digestive, nervous system, endocrine, nutritional, and metabolic diseases, as well as from mental and behavioral disorders and certain infectious and parasitic diseases.
... However, although thought to be strictly unnecessary, probability values have been included for potential benchmark comparison purposes. Nevertheless, such multiple regression strategies have been successful in past small-sample studies in which the units of analysis have been states (e.g., McCann, 2008McCann, , 2014aPesta, Bertsch, McDaniel, Mahoney, & Poznanski, 2012;Varnum, 2014) and individuals (e.g., McCann, 1992McCann, , 1997Simonton, 1986). ...
McCann (2015) showed that American states with lower mean levels of resident neuroticism have higher rates of residential mobility. The present research tested the hypothesis that state resident neuroticism correlates negatively with state entry order. The hypothesis was derived from McCann’s residential mobility theory and based on restricted gene pools producing lower resident neuroticism as successive areas gained statehood. Spearman correlation confirmed that state resident neuroticism levels correlated highly (−.72) with state entry order. With state entry order transformed to a standard normal distribution, sequential multiple regression showed that the relation could not be accounted for by recent state differences in socioeconomic status, urban population percent, White population percent, Black population percent, Hispanic population percent, sex ratio, median age, or pathogen prevalence level. Supplementary analyses replicated the results with an alternate neuroticism measure and found that the other Big Five personality variables did not play a part in this context. The results are consistent with an evolutionary perspective. One common adaptive problem humans have faced repeatedly is residential relocation and migration. As with other adaptive problems central to important recurring situations, psychological mechanisms referred to as adaptations have evolved. From this perspective, personality differences are adaptations that reflect ways in which individuals characteristically deal with adaptive problems. They also determine which adaptive problems to confront or avoid. Therefore, in different environmental contexts, personality traits have different fitness consequences. Higher and lower neuroticism indeed appear to function as alternative strategies for solving the recurrent adaptive problem of residential relocation or migration.
