Study suggests that women may have greater cognitive reserve but faster cognitive decline than men, which could contribute to sex differences in late-life dementia

Sex Differences in Cognitive Decline Among US Adults. Deborah A. Levine et al. JAMA Netw Open. 2021;4(2):e210169. February 25, 2021, doi:10.1001/jamanetworkopen.2021.0169

h/t David Schmitt women have greater cognitive reserve but faster later-life cognitive decline than men. Evidence suggests that dementia incidence in Europe and the US has declined over the past 25 years, but declines were less in women than in men

Key Points

Question  Does the risk of cognitive decline among US adults vary by sex?

Findings  In this cohort study using pooled data from 26 088 participants, women, compared with men, had higher baseline performance in global cognition, executive function, and memory. Women, compared with men, had significantly faster declines in global cognition and executive function, but not memory.

Meaning  These findings suggest that women may have greater cognitive reserve but faster cognitive decline than men.

Abstract: Importance  Sex differences in dementia risk are unclear, but some studies have found greater risk for women.

Objective  To determine associations between sex and cognitive decline in order to better understand sex differences in dementia risk.

Design, Setting, and Participants  This cohort study used pooled analysis of individual participant data from 5 cohort studies for years 1971 to 2017: Atherosclerosis Risk in Communities Study, Coronary Artery Risk Development in Young Adults Study, Cardiovascular Health Study, Framingham Offspring Study, and Northern Manhattan Study. Linear mixed-effects models were used to estimate changes in each continuous cognitive outcome over time by sex. Data analysis was completed from March 2019 to October 2020.

Exposure  Sex.

Main Outcomes and Measures  The primary outcome was change in global cognition. Secondary outcomes were change in memory and executive function. Outcomes were standardized as t scores (mean [SD], 50 [10]); a 1-point difference represents a 0.1-SD difference in cognition.

Results  Among 34 349 participants, 26 088 who self-reported Black or White race, were free of stroke and dementia, and had covariate data at or before the first cognitive assessment were included for analysis. Median (interquartile range) follow-up was 7.9 (5.3-20.5) years. There were 11 775 (44.7%) men (median [interquartile range] age, 58 [51-66] years at first cognitive assessment; 2229 [18.9%] Black) and 14 313 women (median [interquartile range] age, 58 [51-67] years at first cognitive assessment; 3636 [25.4%] Black). Women had significantly higher baseline performance than men in global cognition (2.20 points higher; 95% CI, 2.04 to 2.35 points; P < .001), executive function (2.13 points higher; 95% CI, 1.98 to 2.29 points; P < .001), and memory (1.89 points higher; 95% CI, 1.72 to 2.06 points; P < .001). Compared with men, women had significantly faster declines in global cognition (−0.07 points/y faster; 95% CI, −0.08 to −0.05 points/y; P < .001) and executive function (−0.06 points/y faster; 95% CI, −0.07 to −0.05 points/y; P < .001). Men and women had similar declines in memory (−0.004 points/y faster; 95% CI, −0.023 to 0.014; P = .61).

Conclusions and Relevance  The results of this cohort study suggest that women may have greater cognitive reserve but faster cognitive decline than men, which could contribute to sex differences in late-life dementia.

Discussion

Among 26 088 individuals pooled from 5 prospective cohort studies, women had higher baseline performance than men in global cognition, executive function, and memory. Women, compared with men, had significantly faster declines in global cognition and executive function but not memory. These sex differences persisted after accounting for the influence of age, race, education, and cumulative mean BP.

Our results provide evidence suggesting that women have greater cognitive reserve but faster cognitive decline than men, independent of sex differences in cardiovascular risk factors and educational years. Previous studies³¹ have shown that women have higher initial scores on most types of cognitive tests except those measuring visuospatial ability. Few studies have examined sex differences in cognitive trajectories in population-based cohorts of cognitively normal Black and White individuals. A 2016 study³¹ of older adults in Baltimore (mean ages 64-70 years) found that men had steeper rates of decline on 4 of 12 cognitive tests (mental status [Mini Mental State Examination], perceptuomotor speed and integration, visual memory, and visuospatial ability) but no sex differences in declines on 8 of 12 cognitive tests (verbal learning and memory, object recognition and semantic retrieval, fluent language production, attention, working memory and set-shifting, perceptuomotor speed, and executive function). Similarly, we found no sex differences in verbal learning and memory; but, in contrast, we found that women had faster cognitive decline in global cognitive performance and executive function than men. These latter results might differ because we included young and middle-aged adults (mean age 58 years). Our findings are consistent with studies showing that women with mild cognitive impairment or AD have faster decline in global cognition than men.^32,33

Our results of sex differences in cognitive decline were consistent across most cohorts. The potential reasons for the finding of slower cognitive decline in women in the Framingham Offspring Study are unclear and might be due to socioeconomic, life stress, geographic, and environmental factors as well as cohort differences in sampling strategies, eligibility criteria, and cognitive tests. Although our finding that declines in memory do not differ by sex are consistent with other studies,³¹ the finding is surprising because memory decline is the clinical hallmark of AD, a common cause of dementia,¹ and some studies suggest that women have higher incidence of AD.^4-6 One explanation is that women manifest verbal memory declines at more advanced stages of neurodegenerative disease than men owing to women having greater initial verbal memory scores and cognitive reserve.^34,35 However, evidence against this explanation is that women in our study had faster declines in global cognition and executive function despite having higher initial levels of these measures. Another explanation is that the memory measure was less sensitive than the global cognition and executive function measures to detect sex differences in cognitive decline.

If the observed sex differences in declines in global cognition and executive function are causal, then they would be clinically significant, equivalent to 5 to 6 years of cognitive aging. The faster declines in mean cognitive scores associated with female sex can be related to approximate equivalent changes in years of brain or cognitive aging by calculating the ratio of slope coefficients for female sex and baseline age on cognition. Experts have defined clinically meaningful cognitive decline as a decline in cognitive function of 0.5 or more SDs from baseline cognitive scores.^36-38 Women will reach the threshold of a 0.5-SD decrease from the baseline score 4.72 years faster than men for global cognition, 1.97 years faster for executive function, and 0.24 years faster for memory (eTable 7 in the Supplement). Based on this approach, sex differences in cognitive declines are clinically meaningful. Declines in global cognition and executive function markedly raise the risk of death, dementia, and functional disability.^39-41 Diagnosis of the clinical syndrome of dementia/neurocognitive disorder requires cognitive decline by history and objective measurement.⁴² Our findings that women have faster declines in global cognition and executive function mean women would have greater risk than men for being diagnosed with dementia based on objectively measured cognitive decline. Our findings that women had higher initial cognitive scores suggest informants and clinicians might not observe significant cognitive decline in women until substantial loss and impairment has occurred.

Studies have consistently found evidence of sex differences in baseline cognitive functioning with women demonstrating stronger verbal cognitive skills than men, but men demonstrating stronger visuospatial skills than women (eg, mental rotations).^31,43 Reasons for these sex differences are complex and likely influenced by biological (eg, sex hormones), genetic (eg, APOE), and social and cultural factors.⁴³ While sex differences in cognitive reserve might also be associated with differences in life course risk factors such as vascular risk,⁴⁴ education, and health behaviors such as smoking and exercise,⁴⁵ our findings of sex differences in baseline cognitive performance independent of these factors suggest that additional contributors and biological pathways play a role.

Women might have faster cognitive decline than men because of differences in sex hormones, structural brain development, genetics, psychosocial factors, lifestyle factors, functional connectivity, and tau pathology.^45-47 Women might have greater burden of small vessel disease, including white matter hyperintensity volume, and less axonal structural integrity that in turn leads to faster cognitive decline particularly in executive function and processing speed.^48,49 Women also appear to have lower gray matter volume,⁵⁰ so they might be more vulnerable to both the accelerated gray volume loss that occurs with aging and the differential volume loss in specific brain regions that occurs with neurodegenerative diseases.⁵¹ Recent studies suggest that women develop greater neurofibrillary degeneration, brain parenchymal loss, and cognitive decline.^52-54 Our results suggest that women’s greater cognitive reserve might enable them to withstand greater AD-pathology than men.

Strengths and Limitations

Our study has several strengths. By pooling 5 large, high-quality cohorts, we had longitudinal cognitive assessments and vascular risk factor measurements in a large number of Black and White individuals who were young, middle-aged, and older-aged to estimate cognitive trajectories in men and women. We had repeated cognitive measures during up to 21 years of follow-up. The cohort studies included in our study systematically measured major cognitive domains important for daily, occupational, and social functioning: global cognition, executive function, and memory. Our findings were consistent across cohorts.

This study also has several limitations. While we adjusted for educational years, we could not adjust for educational quality, literacy, other socioeconomic factors,¹⁰ or depressive symptoms, because not all cohorts had these data at or before the first cognitive assessment. However, studies suggest that socioeconomic factors tend to influence initial cognitive scores (ie, intercepts) rather than the change in cognitive scores over time (slopes).^55,56 Selective attrition of cognitively impaired participants could underestimate the rate of cognitive decline⁵⁷ or not.⁵⁸ Estimating the potential clinical impact of sex differences in cognitive decline by correlating it with decline due to aging is a common approach, but it does not directly measure clinical impact, and a clinically meaningful change might vary by an individual’s age, educational quality, race, and baseline cognition.⁵⁹ There were no sex differences in participants excluded because of stroke or dementia before first cognitive assessment, so this would not influence sex differences in cognitive decline (eTable 8 in the Supplement).

We did not study incident dementia because some cohort studies lacked this information. By design, we did not adjust for baseline cognition. We also did not study any particular age interval associated with greatest risk of sex-related cognitive decline. Heterogeneity of the association of sex with cognitive decline between cohorts might have affected the statistical validity of the summary estimate of the effect in the pooled cohort. Smaller sample size and fewer cognitive assessments might have reduced precision of estimates of cognitive decline in executive function and memory (ie, the secondary outcomes). We did not have information on participants’ instrumental activities of daily living, family history of dementia, and hormone replacement therapy use. While the assumption that participants’ postmortem cognitive data are missing at random might lead to immortal cohort bias and underestimate memory declines,⁶⁰ it is valid to answer the research question quantifying sex differences in cognitive trajectories through study follow-up. Women might have had a greater likelihood of regressing to a lower value than men at follow-up because they had higher baseline cognitive function than men. Using a fixed effect for cohorts might have produced conservative estimates of sex effects on cognitive slopes.

Cross‐sex shifts in two brain imaging phenotypes and their relation to polygenic scores for same‐sex sexual behavior: A study of 18,645 individuals from the UK Biobank

Cross‐sex shifts in two brain imaging phenotypes and their relation to polygenic scores for same‐sex sexual behavior: A study of 18,645 individuals from the UK Biobank. Christoph Abé  Alexander Lebedev  Ruyue Zhang  Lina Jonsson  Sarah E. Bergen  Martin Ingvar  Mikael Landén  Qazi Rahman. Human Brain Mapping, February 26 2021. https://doi.org/10.1002/hbm.25370

Abstract: Genetic and hormonal factors have been suggested to influence human sexual orientation. Previous studied proposed brain differences related to sexual orientation and that these follow cross‐sex shifted patterns. However, the neurobiological correlates of sexual orientation and how genetic factors relate to brain structural variation remains largely unexplored. Using the largest neuroimaging‐genetics dataset available on same‐sex sexual behavior (SSB) (n = 18,645), we employed a data‐driven multivariate classification algorithm (PLS) on magnetic resonance imaging data from two imaging modalities to extract brain covariance patterns related to sex. Through analyses of latent variables, we tested for SSB‐related cross‐sex shifts in such patterns. Using genotype data, polygenic scores reflecting the genetic predisposition for SSB were computed and tested for associations with neuroimaging outcomes. Patterns important for classifying between males and females were less pronounced in non‐heterosexuals. Predominantly in non‐heterosexual females, multivariate brain patterns as represented by latent variables were shifted toward the opposite sex. Complementary univariate analyses revealed region specific SSB‐related differences in both males and females. Polygenic scores for SSB were associated with volume of lateral occipital and temporo‐occipital cortices. The present large‐scale study demonstrates multivariate neuroanatomical correlates of SSB, and tentatively suggests that genetic factors related to SSB may contribute to structural variation in certain brain structures. These findings support a neurobiological basis to the differences in human sexuality.

4 DISCUSSION

In this large‐scale study on SSB, we used brain imaging phenotypes from two imaging modalities and a multivariate classification algorithm to extract independent brain covariance patterns related to sex. We then tested for SSB related cross‐sex shifts in such patterns. For the first time, we also examined whether polygenic scores for SSB relate to brain imaging phenotypes.

Our results showed that the PLS classifier was effective in classifying males and females, and that patterns important for classification were less pronounced in non‐heterosexual individuals, indicative of a cross‐sex shift. The analysis of LVs demonstrated that one (LV1) displayed a sex‐by‐SSB interaction. This interaction remained following adjustment for potential confounding variables, including psychiatric diagnoses and victimization experiences, and was driven by the fact that nHeF showed larger LV1 scores than HeF. Since males showed the largest LV scores, this indicates an SSB‐related cross‐sex shift in multivariate brain patterns predominantly in females. This shift in LV1 was not observed in males, which could potentially arise because SSB‐related differences in males might have less of a covarying nature, regionally differ, be more focal, or less pronounced (smaller effect size) compared to females, as indicated by secondary univariate analyses (Figure 6). However, these differences could also be explained by the fact that the SSB measure does not capture all aspects of sexual orientation. While SSB correlates highly with other components of sexual orientation, nHeF and nHeM in our sample may differ in other components such as sexual attractions, sexual identity labels, or romantic attractions (J. M. Bailey et al., 2016). Hence, we cannot exclude the presence of sub‐groups among non‐heterosexual individuals. In line with that notion, in an explorative analysis excluding individuals with one or two reported lifetime same‐sex partners (see Supporting Information), the peak of the LV1 distribution in nHeM was shifted toward smaller values (the mean of females), indicating that a sub‐group of nHeM (e.g., those with more same‐sex partners) may show a more female‐like multivariate brain pattern. However, this effect requires further investigation. Nevertheless, our findings suggest sexuality‐related variation in multivariate brain data, supporting the utility of data‐driven classification and that multivariate pattern analyses are effective at identifying such associations on group level, at least in females.

Our neuroanatomical findings support a number of previous small‐scale reports of sexual orientation‐related differences (Abé et al., 2014; Abé et al., 2018; Manzouri & Savic, 2018a, 2018b; Ponseti et al., 2007; Savic & Lindström, 2008) in that they indicate SSB‐related cross‐sex shifts in brain imaging phenotypes. Intriguingly, the calcarine sulcus (part of the visual cortex) appears to be the most consistently reported structure showing sexual orientation‐related differences (Abé et al., 2014; Abé et al., 2018; Manzouri & Savic, 2018b), which is consistent with results from our secondary univariate analyses (ROI approach: Figure 6, and whole brain analysis: Data S2). We did not replicate sexual orientation differences in the anterior cingulate cortex (Manzouri & Savic, 2018a, 2018b) and hippocampus (Abé et al., 2014) in males. Cross‐sex shifts in brain data are also consistent with a large body of empirical findings demonstrating cross‐sex shifted patterns of gender‐related behavior, cognitive ability (in tasks that typically differ between the sexes), and certain personality traits (Allen & Robson, 2020; Bailey et al., 2016; Li et al., 2017; Rieger et al., 2008; Xu et al., 2017). However, there is considerable overlap in the distribution of LV‐scores between the groups, and the magnitude of the effects for SSB‐related brain differences seem smaller than those reported for the aforementioned behavioral traits. Notably, effect sizes for SSB‐related differences in cortical volumes were also smaller than those of sex differences (Table S3, Data S2).

The imaging variables that loaded most strongly on LV1 (displaying the sex‐by‐SSB interaction) were measures of regional volumes in prefrontal, parietal, and occipital (including visual) cortices. In the context of SSB, the visual cortex is involved in visual perception and processing of sexual stimuli (Georgiadis & Kringelbach, 2012). Prefrontal areas are involved in the integration of sensory information and reward‐value representation of sexual stimuli (Georgiadis & Kringelbach, 2012). Together with the precuneus, involved in self‐referential processes (Cavanna & Trimble, 2006), these areas are also recruited during visuo‐spatial processing and selective visual attention (Cavanna & Trimble, 2006; Georgiadis & Kringelbach, 2012; Paneri & Gregoriou, 2017; Posner & Gilbert, 1999). However, this study does not allow conclusions about causality or the brain regions' functional involvement. It requires further testing how differences in brain structure relate to SSB. Note that although volumes of those brain regions that tended to successfully predict group membership largely overlap with those previously reported in other studies, in contrast to direct group comparisons in univariate analyses, PLS results should not necessarily be interpreted as evidence of structural differences between the groups, but rather as generalized covariance patterns in the brain data that discriminate between them. Another important finding is that while LV1 appeared to capture the hypothesized cross‐sex shift, LV2 appeared to capture a main effect of SSB. This may indicate that SSB‐related multivariate brain patterns may exist that do not follow a cross‐sex shift and are similar in both nHeM and nHeF (regardless of sex). It is also noteworthy that cortical volumetric measures showed the highest loadings, whereas those of subcortical structures and DTI‐based FA values were close to zero, indicating that sex‐related brain phenotype variation may be more pronounced in gray matter than white matter or subcortical measures.

The causes of sexual orientation‐related differences in brain structure are as yet unknown. Both genetic and non‐genetic factors have been proposed to play a role, with the most prominent hypothesis involving prenatal androgen influences (Bailey et al., 2016; Kevin, Khytam, & David, 2018). Genetic influences are modest based on existing twin models and molecular genetic studies (Bailey et al., 2000; Bailey et al., 2016; Ganna & Verweij, 2019; Langstrom et al., 2010) and are almost certainly polygenic in nature (Ganna & Verweij, 2019). Here, we investigated genetic influences on brain phenotypes by testing the associations between polygenic scores for SSB (PS‐SSB) and brain imaging phenotypes. Whereas PS‐SSB did not seem to predict multivariate brain patterns (LVs), we found that PS‐SSB was associated with cortical volumes in individual brain regions. These associations were observed mainly in lateral occipital and temporo‐occipital cortex. In lateral occipital cortex, higher PS‐SSB was associated with lower volumes in both males and females. In temporo‐occipital cortex, higher PS‐SSB was associated with lower cortical volumes in nHeM and larger volumes nHeF. These findings tentatively indicate that genetic factors related to SSB are associated with variation in some cortical structures and that a higher genetic predisposition to SSB has the opposite effect on cortical volume in males and females who reported SSB. These associations were small and PS‐SSB explained little of the variance in brain structure. Notably, we did not find significant genetic correlations in complementary analyses linking previously published SSB and brain phenotype GWASs (Elliott et al., 2018; Ganna & Verweij, 2019). Therefore, these genetic associations should be treated with caution, and additional factors are likely to explain brain variation associated with human sexuality. Mechanisms responsible for how genetic factors influence brain structure, function, and in turn behavior are complex and multi‐factorial. Given the general limitations of the applied methodology (see below), these cannot be derived from this study. We also want to note that, given the wide and overlapping range of LVs and PS‐SSB, as well as the weak classification performance when solely predicting SSB (AUC = 0.57), the present results cannot be used to predict an individual's sexual orientation based on genetic or neuroimaging data.

Understanding the appeal of libertarianism: Gender and race differences in the endorsement of libertarian principles

Understanding the appeal of libertarianism: Gender and race differences in the endorsement of libertarian principles. Mary‐Kate Lizotte  Thomas Warren. Analyses of Social Issues and Public Policy, February 26 2021. https://doi.org/10.1111/asap.12237

Abstract: There is a stereotype of libertarians being young, college educated, white men and that the Libertarian Party lacks appeal among women and individuals of color. There is a great deal of research investigating gender differences in public opinion on a number of issues including the provision of government resources and government spending (Barnes and Cassese; Howell and Day). Nevertheless, there is no work specifically investigating why women and nonwhites do not find libertarianism appealing. We test several hypotheses using 2016 American National Election Study data and 2013 PRRI data. We find a sizeable and significant gender gap and race gap in support for libertarian principles. We investigate several explanations for these gaps finding moderate support for self‐interest, racial attitudes, and egalitarianism as reasons for women and African Americans being less supportive of Libertarian Principles. We believe that the modest success of and media attention garnered by Ron Paul and Rand Paul in recent years along with the success of the Libertarian Party presidential ticket in 2016 highlights the need to understand who is drawn to libertarianism and why.

Males were the most eager to view sexually arousing images of the opposite sex, whereas females were more strongly motivated to view less sexual images of couples

Sex Differences in the Motivation for Viewing Sexually Arousing Images. Maiko Kobayashi, Koyo Nakamura & Katsumi Watanabe. Evolutionary Psychological Science, Feb 27 2021. https://rd.springer.com/article/10.1007/s40806-021-00276-y

Abstract: Sexual motivation strongly influences mate choice and dating behavior and can be triggered by merely viewing sexually arousing visual images, such as erotic pictures and movies. Previous studies suggested that men, more than women, tend to search for sexual cues that signal promiscuity in short-term mates. However, it remains to be tested whether sex differences in the motivation to view sexual cues can be observed by using robust and well-controlled behavioral measures. To this end, we employed a pay-per-view key-pressing task. Japanese self-identified heterosexual male and female participants viewed images of men, women, or couples with two levels of sexual arousal (sexual vs. less sexual). Participants could alter the viewing time of a presented image according to their willingness to keep viewing it. Male participants were the most eager to view sexually arousing images of the opposite sex, whereas female participants were more strongly motivated to view less sexual images of couples. Such sex differences may reflect differentiated reproductive strategies between men and women in terms of men’s motivation toward promiscuity and women’s motivation toward long-term relationships.

Discussion

The purpose of this study was to examine whether there are differences between men and women in terms of their motivation to view sexual images. Drawing on SST (Buss & Schmitt, 1993), we hypothesized that our self-identified heterosexual male and female participants would view the opposite-sex images longer than the same-sex images because opposite-sex images can evoke sexual arousal (Chivers & Bailey, 2005; Hahn et al., 2013), and that men would be more eager than women to view the highly sexual images because sexually explicit opposite-sex images suggest sexual accessibility (Buss & Schmitt, 1993). Our results indicate that the motivational salience of sexual images differed between male and female participants. Here, we summarize the main findings and interpret such differences in light of the SST (Buss & Schmitt, 1993).

First, as predicted, our male participants viewed the opposite sex images and couple images longer than the same sex images, irrespective of the sexual arousal of the images. These results confirm that heterosexual males are strongly motivated to view opposite sex images (Baumeister et al., 2001; Hamann et al., 2004). Furthermore, the number of key-presses by the male participants for the opposite sex images in the sexual condition was higher compared to that for the other image. Such prioritized motivational responses to the opposite sex images were also evident in likability and sexual arousal ratings. In the less sexual condition of the opposite-sex images, there were no significant differences in the pay-per-view key pressing, but there were significant differences in subjective likeability and arousal ratings. This result was not reflected in the behavior of opposite sex images with less sexual condition, even though male participants reported higher levels of subjective sexual arousal and preference than female participants. This suggests that the pay-per-view responses reflect sexual motivation to view the images, not merely the subjective evaluations of them (Aharon et al., 2001). These observations of the male participants’ behavior are consistent with the behavioral predictions provided by the SST (i.e., prediction 6: cues to immediately available sex will be valued by men in short-term mates more than in long-term mates because they provide cues to sexual accessibility). Previous studies also suggest that men are likely to prefer visual sexual cues than women, and are thus eager to view nude images of women (Baumeister et al., 2001; Regnerus et al., 2016). Also, recent studies reveal that heterosexual men prefer to view opposite-sex images in both erotic and non-erotic contexts more than heterosexual women do (Lykins et al., 2006; Lykins et al., 2008; Rupp & Wallen, 2007). Taken together, these findings suggest that men tend to value cues to immediately available sex (e.g., promiscuity) in short-term mates (Buss & Schmitt, 1993), possibly leading to men’s greater attraction to sexually arousing visual images (Symons, 1979). Our results support these previous findings by using a behavioral measurement that reflects sexual motivation.

In contrast to the male participants, the female participants displayed different patterns of pay-per-view responses depending on the sexual arousal of the images. From the standpoint of mate choice, the female participants would have also viewed the male images longer than the female images (Chivers & Bailey, 2005; Hahn et al., 2013). However, the female participants in this experiment viewed the couple images longer than the other images, while they decreased the viewing time for all types of images in the sexual condition. Female participants in this study were less responsive than male participants to opposite sex images in all pay-per view key-pressing, subjective likeability and arousal. Previous studies indicate that women react to men’s physical attractiveness as strongly as men react to women’s physical attractiveness (Hahn et al., 2013; Hamann et al., 2004; Wiederman & Dubois, 1998). This indicates that men and women are equally able to identify sexual cues from the opposite sex (Kowalski, 1993). It is noteworthy that many previous findings were based on participants from Western cultures; so, the inconsistency between previous findings and our results may be partially derived from cultural and social differences in sexual attitudes (Thomas et al., 2015). Our results that women decreased viewing time for both sexual and less sexual same sex images ostensibly seem to be inconsistent with some previous findings (e.g., Women react to men’s physical attractiveness as strongly as men react to women’s physical attractiveness (Hahn et al., 2013; Hamann et al., 2004; Wiederman & Dubois, 1998). One possible explanation for the inconsistent results can be provided by cultural differences in expression and social expectations of female sexuality. Indeed, Western women tend to explicitly report higher sexual desire, arousal, and pleasure when experiencing orgasm compared to East Asian women (Brotto et al., 2005; Cain et al., 2003). Also, East Asian women are likely to have automatic thoughts related to sexual guilt (e.g., “I am an immoral person for wanting sex,” or “It is wrong for a woman to initiate sexual activity?”), which may originate from implicit social expectations of female sexuality and thereby motivate them to avoid sexual scenarios they believe immoral (Woo et al., 2011). Although such cultural differences are also found in men, they are reflected in women more strongly (Abramson & Imai-Marquez, 1982). It would be interesting to address this question by conducting a cross-cultural study with East-Asian and Western populations.

Of particular interest is that our female participants viewed the couple images longer than the male and female images in the less sexual condition. Such patterns were also observed in the subjective likeability rating task but not in the subjective arousal task. These results are consistent with previous findings that women are highly motivated to view couple images depicting relationship contexts and emotional bonds (Laan et al., 1994; Carvalgho,  2013). According to the behavioral prediction of the sexual strategies theory, women place more emphasis on romantic relationships than men’s physical attractiveness (Rupp & Wallen, 2007). Indeed, Dewitte (2015) showed that women feel greater sexual desire when primed with visual cues conjuring up romantic relationships. Correspondingly, women experience more intense sexual arousal when viewing pornography with romantic elements (e.g., glancing at each other, kissing, or marriage) than pornography with actual sexual intercourse (Laan et al., 1994). In our study, the female participants displayed prolonged viewing of less sexual couple images compared to the highly sexual couple images. The less sexual couple images often include romantic elements as described above. The female preference for romantic or relational elements likely derives from psychological adaptations for long-term relationship and pair-bonding signals (Buss & Schmitt, 1993; Chivers & Timmers, 2012). Long-term relationships are more advantageous for women than for men (Trivers, 1972), because women tend to be the more heavily investing sex (e.g., fertilization, gestation, placentation, and maternal care). Thus, women’s strong preference for long-term mating cues might reflect the motivation to secure the quantity and quality of external resources for themselves and their offspring from men (Buss & Schmitt, 1993). At the same time, our female participants made key-press responses to reduce the viewing time for images with high sexual arousal (sexual condition), regardless of the image category. This response pattern may be related to an adaptive behavior such as preventing the initiation of sexual intercourse after only brief intervals of time (Buss & Schmitt, 1993) and/or women’s sexual attitudes are influenced by societal norms that place them in a dilemma regarding sexuality, such that female sexuality has historically been suppressed and deemed as immoral (Lemer et al., 2013).

The present study has been based on the sexual strategies theory and has discussed considerations related to reproductive success, such as opposite-sex and couple images, but it is necessary to discuss the results for same-sex sexual images, which are not thought to contribute to reproduction according to the sexual strategies theories. Our female participants were more motivated, more preferred, and more aroused by the same sex images with less sexual condition than male participants. This result may be due to a greater intra-individual variation in female preferences, behavior, attitudes, and responsiveness to cultural influences drives. Greater flexibility in female sexual preferences may also be reflected in a less specific pattern of sexual arousal (Baumeister et al., 2001; Chivers et al., 2004). These response characteristics to same-sex sexual stimuli are important in examining various genders, including LGBT, and can provide valuable insights for discussions that go beyond sexual strategies theory.

Limitations and Directions for Future Research

While the findings of the current study are novel, there exist several limitations to be considered. As mentioned in the introduction, sexual arousal is a multifaceted concept that includes physical, subjective, emotional, and behavioral aspects (Bancroft et al., 2009). Among them, this study focused on the motivation to view sexual images in an experimental setting as indexed by the pay-per-view key-pressing responses. It is important to keep in mind that the pay-per-view responses are not the direct measures of actual sexual behaviors and physiological arousal. Sex differences in psychological reactions to sexual cues await further validation with physiological and subjective measurements. In addition, the visual stimuli we used were limited to images from Western models, while the participants in this study were Japanese. Some studies demonstrate that people are susceptible to recognition errors or biased emotional evaluation when target images are from an unfamiliar group rather than their own group (e.g., other-race-effect; Feng et al., 2012; Herrmann et al., 2007; Hugenberg et al., 2010). Although we confirmed in the preliminary experiment that Japanese viewers were able to evaluate sexual arousal consistently, it may be more appropriate to use sexually arousing images from the same cultural group. However, to the best of our knowledge, the image database including a Japanese erotic category is not publicly available yet. Our findings await validation from future studies by using images from the same and different groups. Lastly, we could not rule out the possibility that unidentified factors other than sexual arousal and the image categories of our image stimuli affected the viewing time in the pay-per-view task because of the lack of experimental control for the components constituting each image, such as the presence of faces, the number of persons, and so on. More detailed analysis is needed for a deeper understanding of what triggers the sex differences in the motivation to view sexual images.