The present study extends prior research by drawing on a large, recent national sample to provide estimates of the prevalence and composition of the older dating population in the U. Drawing on Bulcroft and Bulcroft , we anticipated that daters are younger and more likely to be men. Age and gender were expected to interact such that the gender gap in dating widens with age. Bulcroft and Bulcroft found no racial variation in dating; neither did dating vary by ever having divorced.
This latter nonsignificant association may reflect the rarity of divorce among older adults 25 years ago.
Economic resources, including education, employment, and assets, presumably make one more attractive in the dating market and are indicators of success. Economic factors may be more salient for men than women. Bulcroft and Bulcroft found that comparative health i.
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We examined overall comparative health and driving ability. Finally, social ties encompass both behavioral and subjective indicators of social connectedness and support. There are competing hypotheses about the relationship between social ties and dating Talbott, The complementarity hypothesis suggests that individuals with the most social connections are most likely to date because they are more interested in and adept at forming social ties.
In contrast, the compensatory hypothesis indicates that lower levels of social connectedness lead individuals to seek ties through intimate relationships, and thus social connectedness is negatively associated with dating.
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In contrast, the compensatory hypothesis is expected to characterize men, who want to date because they lack other forms of social ties Carr, Data came from the NSHAP, a nationally representative sample of 3, community-dwelling persons ages 57 to 85 i. Fielded by the National Opinion Research Center and the University of Chicago, the sample design was developed by the Health and Retirement Study, using their household screening process. The NSHAP included an in-person interview, a self-administered questionnaire, and a biomeasures collection. Topics covered by the NSHAP included demographic characteristics, sexual and union histories, social networks, physical and mental health, well-being and illness, and social and cultural activities.
A key advantage of the NSHAP is that it included a question about non-coresidential partners, allowing the measurement of dating among older adults. Missing data were minimal. Mean substitution was used to handle missing values. Several factors associated with older adult dating, including indicators of demographic characteristics, economic resources, health, and social ties, were included as covariates. Demographic characteristics included age, race, and marital status. Age was coded in years. Race was dummy coded as a Black, b Other, and c White reference group.
Marital status was captured by a series of dummies: Economic resources encompassed education, employment, and assets. College education differentiated those with a college degree coded 1 from others coded 0. Respondents were to confirm that the numeric value referred to their net worth. The measure was logged to adjust for skewness.
Health was gauged by two measures. Values on the social connectedness scale ranged from 0 to Thus, the scale ranged from 4 to 21, with higher values indicating greater perceived social support. First, we documented the prevalence of dating and how it differed among men and women as well as by age group. Second, we examined the characteristics of daters versus non-daters, both for all unmarried individuals and separately by gender. Third, we estimated logistic regression models predicting dating among unmarried individuals to evaluate the covariates of dating in a multivariate framework.
Because our objective was to describe the population of older adult daters, we were less concerned about causal order and acknowledge that some of the factors examined may be antecedents of dating, whereas others may be consequences of dating. Thus, all analyses were conducted in Stata using svy procedures to generate corrected standard errors that adjust for the complex sampling design. For both men and women, the prevalence of dating declined with age, as depicted in Figure 1.
A comparison of daters and non-daters, both for the total sample and separately by gender, is provided in Table 1. Daters and non-daters differ in terms of demographic characteristics, economic resources, health, and social ties. Daters were about 3 years younger 68 , on average, than non-daters The health indicators for daters also were more favorable.
Dating Relationships in Older Adulthood: A National Portrait
Relative to their similar-age peers, daters 4. Social connectedness among daters was greater, on average, than non-daters. The mean value for daters of 9. Daters and non-daters reported comparable levels of perceived social support. Another relevant comparison is that of daters versus non-daters within gender. Among men, a larger share of daters was divorced and a smaller share had never been married compared to non-daters. Dating men were also economically advantaged relative to non-dating men in that they were more likely to have a college degree and to be employed and held more assets.
They were also healthier in that they rated their comparative health more favorably and a larger proportion still drove. Dating men reported greater social connectedness than non-dating men.
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Among women, daters were younger and disproportionately likely to be divorced and unlikely to be widowed. The economic advantage was less pronounced among women, although daters were more likely to have a college degree. Dating and non-dating women did not differ in terms of health. Dating women reported greater social connectedness than non-dating women. Table 1 also includes boldface coefficients that indicate significant gender differences among either daters or non-daters. Among daters, the characteristics of men and women were overwhelmingly similar. In contrast, there were several notable gender differences among non-daters, perhaps because the larger sample size yielded greater statistical power.
Non-dating women were about 1 year older than non-dating men.
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Among non-daters, women reported more social connectedness and social support than men. The odds ratios from logistic regression models predicting dating among the entire sample, as well as men and women separately, are shown in Table 2. Blacks were more likely to be dating than Whites.
Relative to divorced individuals, never-married and widowed people were less likely to be dating. Economic resources were associated with dating: We expected that the role of economic resources might be more pronounced among men, but gender interactions with college degree and assets did not achieve significance results not shown. Comparative health was positively related to dating, indicating that those who are most robust compared with their peers are most likely to be dating. Social ties were linked to dating, with greater social connectedness positively associated with dating.
This pattern aligned with the complementarity hypothesis, according to which those with the most ties would be most likely to date. We estimated separate models for men and women to explore possible gender differences in how factors are related to dating. Although the gender interactions in the full model failed to achieve statistical significance at conventional levels, this may reflect a lack of statistical power associated with the modest number of daters. Among men, the odds of dating were 2. Never-married men were less likely to be dating than divorced men. The odds that college-educated men were dating were more than twice as high as those for men with less education.
Wealthier men were more likely to be dating than men with fewer assets. Also, men who reported being comfortable driving during the day had odds of dating roughly 2.