Abstract

Several studies demonstrate gender and partisan differences among Americans in COVID-19 socioeconomic consequences, attitudes, and behaviors. The authors of this study use six waves of panel survey data to explore the intersection of gender and party across COVID-19 mitigation behaviors, concerns, and policy preferences. The authors observe small gender gaps on several measures; however, partisan differences are larger than gender differences when considering the interaction between gender and partisanship. Democratic women are more similar to Democratic men on these measures than to Republican women. On virtually all measures, Republican women report lower levels of mitigation behaviors, worries, and support for expansive government policies compared to Democratic women and men. Analyzing the interaction of gender and partisanship illuminates how individuals navigated the pandemic with respect to identity factors that often pull in different directions. These findings suggest that one's partisan identity is more consequential than gender when it comes to COVID behaviors, concerns, and policy preferences.

At the height of the COVID-19 pandemic, media profiles depicted harried and exhausted working mothers struggling to hold onto their jobs and sanity while protecting their children's health and supporting remote schooling. A New York Times piece featured a mother staring at two laptops on her dining table while listening to a work meeting in one ear and to her daughter's special education teacher in the other (Bennett 2021). Women met throughout the country for group scream sessions—outlets for the stress and unrelenting demands brought on by COVID-19 (Lukpat 2022). Education became a political battleground, with women often at the center of the debates. Conservative groups such as Moms for Liberty protested masking in schools (Kingkaid 2022). Meanwhile, female-dominated—and often left-leaning—teachers unions advocated for enhanced safety precautions as reopening plans took shape and case counts fluctuated (Genota 2022). These examples highlight not only the many ways in which COVID-19 was a gendered experience but also how gender and partisanship have intersected in complex ways in American society during the pandemic.

Beyond the anecdotes, the academic literature demonstrates the centrality of both gender and party identification in reactions to the COVID-19 pandemic. While men faced a greater health risk from the virus itself (Bwire 2020), women faced worse mental health consequences and were harder hit with the pandemic's secondary economic effects, such as job loss and work-family conflict (Collins, Landivar, et al. 2021; Collins, Ruppanner, et al. 2021; Croda and Grossbard 2021; Graham et al. 2021). Studies demonstrate substantial partisan differences in COVID-related beliefs, health behaviors, and policy preferences, and these differences persist even when controlling for multiple socioeconomic factors and the severity of the outbreak (Allcott et al. 2020; Clinton et al. 2020; Gadarian, Goodman, and Pepinsky 2022).

Existing research has not, however, fully examined the heterogeneous consequences of gender across political parties. Such heterogeneity may be particularly important for understanding the gendered consequences of the pandemic and implications for future health crises. We use six waves of panel survey data from March 2020 through March 2021 to explore the interactive relationship between gender and partisanship in shaping a variety of COVID-19–related behaviors and attitudes in the first year of the COVID-19 pandemic. While women were more likely than men to report a wide variety of COVID-related behaviors (e.g., mask-wearing) and attitudes (e.g., concern about the pandemic), we also demonstrate that partisan identity is more consequential than gender in explaining COVID behaviors, concerns, and policy preferences in the first year of the pandemic.

We use data from more than 1,600 respondents each interviewed six times across 18 different dependent variables to compare men and women across and within political parties in the United States. This analysis of gender-partisan subpopulations illuminates how individuals navigated the pandemic with respect to identity factors that often pull in opposite directions when making decisions about risk-mitigation behaviors and policy preferences.

We find that Democratic women were most worried about COVID and most likely to engage in mitigation behaviors, while Republican men expressed the least amount of concern and reported being the group least likely to engage in mitigation. Across almost all behaviors and attitudes, Democratic women are more similar to Democratic men than to Republican women. Despite women's unique pandemic-related economic challenges, increased care work, and greater engagement with the health care system, on virtually all measures women's level of mitigation behaviors, level of worry, and support for expansive government policies to combat the pandemic varied by political party. Democratic women and men were more like each other than they were like Republican women in attitudes and behaviors. The findings underscore the primacy of partisanship during the COVID-19 pandemic despite gender-related challenges that spanned political parties.

COVID, Partisanship, and Gender—Theory and Hypotheses

Women and men experienced the health and economic effects of the COVID-19 pandemic differently. Generally, women use more health care services than men and make the majority of health care decisions for families (DOL 2005), including decisions on vaccination (Callaghan et al. 2021). During the COVID-19 pandemic, women faced some unique health risks: pregnancy increased the risk of severe disease in women (Ellington et al. 2020), women were underrepresented in drug trials (Connor et al. 2020; Nowogrodzki 2017), and women experienced poorer mental health (Frederiksen et al. 2020). Although women expressed more hesitancy about COVID vaccines early on in the pandemic before vaccines were available (Troiano and Nardi 2021), they were more likely to report masking (Cassino and Besen-Cassino 2020) and actually became vaccinated at higher rates than men when vaccines became available (CDC 2022). Men were at higher risk for both morbidity and mortality from COVID-19 than women (Bwire 2020), and men were also less likely to report following public health recommendations. On the economic front, women experienced more job loss (Bluedorn et al. 2021) and reduced work hours in the pandemic, partly as a result of disproportionate increases in caregiving and remote-school support responsibilities (Collins, Ruppanner, et al. 2021; Dunatchik et al. 2021; Yavorsky, Qian, and Sargent 2021; Zamarro and Prados 2021). These negative effects were felt more acutely among women of color (Laster Pirtle and Wright 2021).

These gendered health dynamics of the pandemic lead us to expect that, on average, women would be more likely to change their health behaviors, express more concern, and support more expansive government policies to stem the pandemic and its secondary effects. In addition, the pandemic's negative economic impacts may suggest that women, on average, might be more concerned about personal adverse consequences than men are, and that they are thus more likely to engage in risk-mitigation behaviors such as adhering to public health recommendations and mandates. For example, if working mothers are more likely to miss work because of day care closures, then they may be even more vigilant about taking precautions to avoid virus exposures. If women's health and economic experiences shape their response to the pandemic, then we expect:

  • H1: Women are more likely than men to report risk-mitigation behaviors, express higher levels of worry, and support government policies to stem the pandemic.

Partisanship is also a potent force shaping attitudinal and behavioral reactions to the pandemic in the United States. Whether the result of cues that the Trump administration sent downplaying the seriousness of the pandemic while Democratic leaders emphasized the threat (Gadarian, Goodman, and Pepinsky 2021), the more skeptical view of the virus in conservative media (Faris et al. 2020), or the slower and less aggressive mitigation policies in states led by Republican governors (Adolph et al. 2020; Adolph, Amano, Bang-Jensen, Fullman, and Wilkerson 2021; Wright et al. 2020), partisanship divided mass responses to the pandemic. Democrats were more likely to see the coronavirus as a serious threat early on and to engage in health-related behavior change such as masking and social distancing, whereas Republicans were less likely to hold such beliefs or change their behavior. Partisan differences in several health behaviors such as social distancing, masking, and later, vaccination and COVID-related policy preferences are substantial, and these differences persist even when controlling for multiple socioeconomic factors and the severity of the outbreak (Allcott et al. 2020; Barrios and Hochberg 2021; Baxter-King et al. 2022; Clinton et al. 2020; Ye 2021). The common conclusion is that partisan identity is one of the main determinants of individuals’ adherence to public health guidelines and beliefs about COVID-19 (Gadarian, Goodman, and Pepinsky 2022). We therefore expect:

  • H2: Democrats are more likely than Republicans to report mitigation behaviors, express higher levels of worry, and support government intervention.

While our expectations about the independent effects of gender and partisanship are straightforward, disentangling the combined effect of gender and partisanship is more complicated because both identity factors drive COVID-related beliefs and actions. The task is further complicated by the longstanding partisan gender gap in which American women have identified with the Democratic Party and voted for Democrats at higher rates than men because of a conservative shift of men (Box-Steffensmeier, De Boef, and Lin 2004) and women's greater support for more generous social safety net policies (Kaufmann and Petrocik 1999). Since women are more likely to identify as Democrats compared to men, this would lead to the expectation that more women are engaging in these risk-mitigation behaviors because of their party identification.

Although we hypothesize that women in general took COVID more seriously than men, for some gender-party subgroups these identities may pull in different directions when considering COVID-related decisions. Given the practical challenges that many women face with reduced employment and increased work-family conflict, regardless of party, we might expect Republican women to behave more like Democratic women than their male copartisans. On the other hand, partisanship is such a strong determinant that it may shape GOP women's behavior and preferences despite potential negative socioeconomic and health experiences. And while norms of masculinity lead men to display greater resistance to mask wearing, partisanship could hold distinct sway that overrides conformity to gender norms (Cassino and Besen-Cassino 2020; Palmer and Peterson 2020).

With these concerns in mind, we assess the interaction between gender and partisanship, which allows for a comparison of four gender-party subgroups of interest: Democratic women, Democratic men, Republican women, and Republican men. Hypotheses 3 and 4 outline our expectations about whether gender conditions the relationship between partisanship and COVID-19–related attitudes and behaviors.

  • H3: Democratic women are most likely of gender-party subgroups to engage in mitigation behaviors, express high levels of worry, and support government intervention to stem the pandemic.

  • H4: Republican men are least likely of gender-party subgroups to engage in mitigation behaviors, express high levels of worry, and support government intervention.

Hypothesis 5 outlines our expectation for the subpopulations of Democratic men and Republican women, whose identity factors may pull in conflicting directions. If the effects of partisanship outweigh those of gender, then we expect:

  • H5: Democratic men are more likely than Republican women to engage in mitigation behaviors, express high levels of worry, and support government intervention.

By comparing Republican women with Democratic men, hypothesis 5 can be interpreted as a test of whether the effect of partisanship outweighs that of gender in explaining COVID-related behaviors and attitudes.

Data and Methods

In March 2020, we partnered with YouGov to conduct a panel survey with a representative sample of Americans. Between March 2020 and March–April 2021 we interviewed the panel respondents six times to explore a broad range of pandemic-related attitudes and behaviors. We surveyed ordinary Americans six times (see table 1 for details on each wave). By interviewing the same respondents over the course of a year, we can follow participant attitudes and behaviors as the political and health situations changed. The survey measured health behaviors, partisanship, ideology, worries, and policy attitudes at each wave. Additional details about the sample demographics are included in the appendix.

We have three categories of dependent variables: (1) COVID-related concerns, (2) health behaviors, and (3) policy preferences. Each of these variables is assessed on each of the six survey waves (see results in table 2). For the six concerns variables, respondents were asked on a 4-point scale how worried, if at all, they were about a variety of issues. The eight health behavior variables are binary indicators for whether a respondent engaged in the following behaviors to lower their risk from the virus. For the four policy preferences variables, respondents were asked to what extent they agreed with the following policies, using a 5-point Likert scale of support or opposition.

To test the impact of gender and partisanship on these outcomes, we model the relationships among partisan identification, gender, and their interaction across subsequent waves. With the health behavior outcomes, we use logit regression for each of the six waves of the panel to test the effect of gender and partisanship and their interaction. We use ordinary least squares (OLS) regression for the worry and policy dependent variables. The independent variables of interest are gender, party identification, and the three-way interaction between gender, party, and survey wave. We interact gender and party with each survey wave to assess whether the effects of these variables change over time. As a robustness check, we run these models using mixed effects logit regressions for the health behavior variables and mixed effects ordered logit for the worry and policy dependent variables; these models include random effects by respondent to account for the fact that the same respondents are participating in multiple waves (see models in the appendix). The results between the two sets of models are consistent.1

The models take this general form:

yit=βPartyParty IDi,t × Wavet + βGenderGenderi,t=1×Wavet+βGenderPIDPartyID×Genderi,t=1×Wavet+βWaveWavet+γXi,t=1+δZit+εit

yit captures dependent variables for individual i in wave t. Party IDi,t measures party identification in the each wave of the survey using indicator variables for Democrat, Republican, and other; Genderi,t=1 measures respondents’ gender identity as male or female measured in wave 1 of the survey; PID × Genderi,t=1 measures the interaction of partisanship and gender during each survey wave; and Wavet is a set of six indicator variables capturing each of the survey waves. The elements of Xi,t=1 include indicators for other demographic and geographical variables that do not vary over waves in the survey. These include race, income bracket, education status, marital status, and state of residence. Zit measures variables that vary over survey waves. These include unemployment status, self-reported prayer frequency, news interest, county-level COVID-19 growth in total cases, and growth in total deaths relative to the 14 days before the first day of each survey wave. Time-varying measures of COVID-19 capture local pandemic conditions that might be correlated both with partisanship and with health behaviors. εit is an error term. A table with summary statistics for all the dependent and independent variables is included in the appendix. We do not exclude any respondents from our analysis, nor do we drop any respondents for missing-data purposes. We employ sampling weights from our wave 5 round of data collection to account for the sampling design.2

Results

We test hypothesis 1 by assessing the relationship between gender and each of our 18 dependent variables. In these models, gender is interacted with wave to assess whether this relationship varies across the survey waves, partisanship is included as a control, and the three-way interaction of gender, partisanship, and wave is not included (see table S.2 in the appendix). As expected, women tend to report more behavior change, express more worry, and support more interventionist policies. In other words, there is a small residual gender effect even after controlling for party identification, although the differences are not always statistically significant.

Figure 1 shows the predicted health behaviors of men and women from a logit model, with predictions that average over the observed distribution of all control variables. The predicted differences between women and men are not statistically significant for half of the variables: washed hands, bought sanitizer, avoided gatherings, and changed travel plans. For the other four variables, the gender gap between point estimates is about 10 percentage points or less. For example, in wave 1 (March 2020), the models estimate that about 60% of women would report seeking information about COVID, compared to roughly 50% of men. In wave 2 (April 2020), about 70% of women reported having worn a mask compared to about 60% of men.

Across worries and the policy attitudes, we see similar patterns (see figures A.1 and A.2 in the appendix). Women were more worried about themselves or their families and friends getting sick, but gender gaps are not evident in the other worry variables. Across all the dependent variables, the largest gender gaps are in “paid leave” and the sentiment that we should “cancel everything,” which may suggest that either work-family conflict issues are driving women's greater support for public policy solutions or that women's more general support of government solutions to social problems is more apparent in these areas. In sum, our evidence provides some support for hypothesis 1, but the results are somewhat mixed.

We use the same models to test H2, which evaluates the relationship between partisanship and our outcome variables (see table S2 in the appendix). The results present a different story compared to the test of H1. As expected, the indicator for whether a respondent is a Democrat is positive and statistically significant, and it exerts a substantive effect across virtually all dependent variables and model specifications. As an example, compared to Republicans, Democrats are significantly more likely to support policies ranging from free COVID testing to canceling everything, with the magnitude of the effect ranging from 10% of the scale to 25% of the scale.3 Democrats are also significantly more worried than Republicans across all six worries questions (i.e., whether they would get sick, whether there would be negative effects on the economy), with logit coefficients ranging from .19 (SE = .03) for worries about the economy to .81 (SE = .03) for worries about a friend getting sick (see full tables in appendix). This is consistent with previous work tracing the strong effects of partisanship across a range of attitudes and behaviors in first year of the pandemic.

Next, we test hypotheses 3 through 5. To compare the four gender-party subpopulations, we turn to the three-way interaction models (interactions of survey wave, gender and partisanship), illustrated in figures 2–4 (see tables S3, S5, and S9 in the appendix for full models). These models and predicted values average over the observed distribution of all covariates. Figure 2 shows the probability of a respondent saying that they did the behavior by the survey wave and gender-party combination. Figure 3 shows the average level of worry by partisan and gender groups at each survey wave. Figure 4 shows COVID-related health policy attitudes at each survey wave. There are two main takeaways: the groups reporting the highest and lowest levels of worry, mitigation behaviors, and support for interventionist policies are Democratic women and Republican men, respectively. For these subgroups, gender and partisan effects run in the same direction, so these results are expected.

The subgroups that allow for a better comparison of the competing effects of gender and party are Democratic men and Republican women, and we find some interesting results for these groups. In waves 1 and 2, surveyed in March and April–May 2020, Republican women tend to be most like Democratic men across several measures. For example, consider the worry variables in figure 3. In wave 1, Republican women and Democratic men are the most like each other among the subgroups with regard to worrying about themselves or friends getting sick, and about obtaining necessities. More specifically, the predicted value for these two groups on the worry variables is a little more than 2.5 (on a 5-point scale, where higher values indicate more worry) when assessing level of worry about themselves or friends getting sick, compared to 3 for Democratic women and 2 for Republican men. For the behavior variables, all four groups are clustered closer together in wave 1, as partisan messaging had not yet exerted influence. Over time these subgroups begin to divide along partisan lines, but within-party gender gaps are not evident. At this early point in the pandemic, all four subgroups are closer to one another than later in the pandemic across the three categories of dependent variables. Partisan messaging in these early months was less consistent, and the shared experiences of lockdowns across the country and the uncertainty of this novel virus created more similarity in the groups than existed later in the pandemic.

Overall, there is evidence of the offsetting nature of gender and partisanship in the early waves of the surveys (March–April 2020): the positions of Democratic men and Republican women relative to each other and their copartisans do seem to provide evidence of the conflicting influence of their gender and partisan identities. By wave 3 in August 2020, however, differences between Republican women and men had nearly disappeared, as the persistent effect of partisanship becomes more evident.

Further underscoring the primacy of partisanship, we do not observe statistically significant gender gaps within the parties across most variables. However, there are two notable exceptions in the public policy arena: we observe a gap between GOP women and men in the “paid leave” and “cancel everything” policy variables. Unlike most of the other variables, in which men and women converge toward their copartisans over time, the Republican gender gap in these two variables emerges and persists through the later survey waves. GOP women express higher levels of support than Republican men do for paid-leave policies and for policies that would limit public gatherings; however, this support is still much lower than that demonstrated by all Democrats. Still, the Republican gender gap underscores women's ongoing need for work-family reconciliation policies to counteract the pandemic's secondary economic effects that were experienced most acutely by women.

Discussion

We have tested the interactive relationship between gender, partisanship, and COVID-related attitudes and behaviors in the United States. Our findings are consistent with existing research that has identified gendered effects of COVID-19, and we provide a partial explanation for those differences as a function of gendered differences in partisan affiliation. Adopting a statistical framework that allows for heterogeneous effects of partisanship on COVID-19, we find strong evidence that across a range of behaviors and attitudes, partisan differences account for most of the gender differences that we identify. There are important exceptions to this pattern, however, showing that the different experiences of men and women do indeed shape COVID-related policy preferences regarding important things such as paid sick leave.

These findings for gender contrast with another important sociodemographic factor that influenced reactions to the pandemic: age. Age was a significant risk factor for COVID-19 illness and death, and it served as an important mediator for COVID-19–related behaviors, including vaccination. For example, in spring 2022, the COVID States Project ran a survey of 22,234 individuals across all 50 states to estimate that 87% of people aged 65 and older had had at least one COVID vaccination shot (Lazer et al. 2022). Data from the Centers for Disease Control and Prevention estimated in October 2022 that 93% of Americans older than the age of 65 were vaccinated compared to 74% of those between 18 and 64 (CDC 2022).

There were differences in vaccine uptake by partisanship as well as age. The Kaiser Family Foundation COVID-19 Vaccine Monitor found Republicans were significantly more hesitant to be vaccinated than either Democrats or Independents (Hamel et al. 2021). COVID States Project estimates that in people age 65 and older, 5% of Democrats remained unvaccinated compared to 21% of Republicans, but those differences across party were smaller than in younger age cohorts, where there were lower levels of vaccination (Lazer et al. 2022). We suspect that the independent effect of age on attitudes and vaccination despite partisanship is the result of a combination of several factors. Age was a significant and clear risk factor for illness and death that was communicated clearly and was likely more salient in decision-making than the less proximate risks related to gender (e.g., caretaking, pregnancy, etc.) (Ho et al. 2020). Older Americans are also more closely tied to the medical system and trust physicians more than younger people, which may make them more open to and accepting of the recommendation to mitigate their risk through nonpharmaceutical interventions and vaccination (Maurer and Harris 2011).

Given women's unique pandemic-related economic challenges and greater level of care work, these particularly gendered experiences could have been strong enough to align women's attitudes across partisanship. Instead, though, our data show that although Republican women begin the pandemic somewhat closer to Democrats on some issues, they quickly align themselves with their male Republican counterparts in subsequent survey waves. One notable exception is the Republican gender gap in support for paid leave as the pandemic wore on, which may result from the work-family conflict that has disproportionately affected women. Still, on virtually all measures, Democratic men engage in higher levels of mitigation behaviors, express higher levels of worry, and support more expansive government policies to combat the pandemic compared to both Republican women and Republican men.

Studies of time use during the earliest days of the pandemic showed increases in stress and multitasking work and parenting that particularly exacerbated inequalities across genders within American households (Augustine and Prickett 2022; Lyttelton, Zang, and Musick 2022). One question raised by this work is whether the very clear salience of gender in the early days of school shutdowns and lockdowns served to blunt the reception of some of the partisan messaging also emerging at that time (Motta, Stecula, and Farhart 2020).

Future research can build on our findings by exploring the earliest months of the pandemic, when partisan differences were smaller but gender differences were larger. This was the key moment in our analysis, and future research can identify how partisan messaging began to override demographic factors in shaping Americans’ views about the pandemic. Future research may examine the role the media played in highlighting the more skeptical messaging from President Trump about the severity of the crisis and disagreements with other policy makers and health leaders (Motta and Stecula 2023) or the role of state-level policy in easing some pandemic burdens (Adolph, Amano, Bang-Jensen, Fullman, Magistro, et al. 2021).

One clear area for future research is to examine the interaction of partisanship and gender in the decision to vaccinate oneself and one's child (if a parent). The data in this study only extend through the early part of the vaccination period; looking further into when vaccines were widely available will likely reveal additional evidence of gendered partisanship that our data cannot capture. There is evidence of partisan gaps in COVID-19 vaccine uptake (Cowan, Mark, and Reich 2021) that only grew as vaccination mandates were rolled back by many institutions such as universities and workplaces. Data from the Kaiser Family Foundation in 2022–2023 shows counties won by Joe Biden in the 2020 presidential election continued to have higher vaccination rates than Trump counties, and the gap between these places has grown over time (Kates, Tolbert, and Rouw 2022).

Gender continues to matter for COVID-19 responses; for example, women are more likely to report suffering from long COVID symptoms and more likely to be vaccinated than men (Kates, Tolbert, and Rouw 2022; Perlis et al. 2022). Yet, unless those experiences of long COVID are expressly connected to gender, we expect that gender would continue to matter less than partisanship in COVID mitigation behaviors even into 2024, when fewer people overall are taking precautions. We cannot test this directly because our panel ended in 2021, but data from other sources demonstrates how party affects COVID experiences long after 2021. Women make a majority of decisions regarding vaccination within families (Reich 2014), and the early days of the pandemic suggest that health communicators may be able to draw from those experiences of gender solidarity to tamp down on partisan messaging on COVID vaccines going forward.

Notes

1.

We use the figures from the logit (fig. 1) and OLS models (figs. 2–3) because of the computational intensity of calculating the standard errors of predicted values in the mixed-effects regression models necessary to produce the graphs.

2.

Wave 5 of the survey is only panelists from the original sample of 3,000 recruited in March 2020. Wave 6 of the survey included an additional fresh cross-sample of respondents with an oversample of African Americans, Latinos, and Asian Americans. Therefore, we use the sample weights from wave 5 in all analysis.

3.

See appendix for full models. These magnitudes come from indicator variables for whether a respondent identifies as a Democratic, Republican, or independent. The coefficients range from .58 (SE = .03) for support of free testing to 1.08 (SE = .04) for “cancel everything.” The OLS models include measures of gender, survey wave, the interaction of gender and survey wave, employment status, political information, race, income, education, marital status, state of residence, COVID case growth, and deaths growth between survey waves as covariates.

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Supplementary data