Sex Differences in Physical Activity Among Individuals With Type 2 Diabetes Across the Life Span: A Systematic Review and Meta-analysis

Diabetes affects more than 537 million adults ages 20–79 years worldwide (1). More than 90% of adults with diabetes have type 2 diabetes mellitus (T2DM) (1), and the prevalence of T2DM has continued to increase since the 1990s (2). Sex differences exist in T2DM incidence. Females have higher rates of T2DM in youth and males have a higher incidence in midlife, although rates are equal between sexes in older age (3,4). While a diagnosis of T2DM alone carries significant disease burden, it is also associated with a greatly increased risk of cardiovascular disease (CVD) morbidity, and mortality (5). In addition, diagnosis with T2DM at a younger age (<40 years) further increases the risk of CVD and early mortality (6). Cardiorespiratory fitness is a prognostic factor for cardiovascular mortality, and adults and adolescents with T2DM have lower cardiorespiratory fitness compared with individuals without T2DM, even in the absence of clinically significant CVD (7). There are notable sex differences in CVD burden and cardiorespiratory fitness; females with T2DM have lower cardiorespiratory fitness than males with T2DM (7) and bear a disproportionate burden of CVD in the context of T2DM (3,8).

Physical activity (PA) is a cornerstone of treatment of T2DM. PA has positive effects on blood glucose control and prevention of diabetes complications (9), and meeting PA guidelines (10) has been associated with 40% risk reduction in CVD mortality (11). It has been suggested that the relationship between low PA and increased risk of coronary heart disease may be stronger in females than in males (12). Population studies consistently demonstrate that among adults, females are less active than males and females tend to engage in less moderate-to-vigorous PA (MVPA) (13). Whether these differences are also present among individuals with T2DM has received less attention.

The shift of the 2018 Physical Activity Guidelines for Americans (10) away from “bouts” to “all activity counts” highlights the need to understand not only participation in MVPA but also involvement in other types of PA (i.e., light PA [LPA]). Additionally, barriers to PA, which are likely influenced by both biology (sex) and psychological and/or sociocultural factors (gender), among other factors, may be different between men and women as well as individuals with and without T2DM (14). For the purposes of this paper, the terms “female” and “male” will be used in the context of sex differences in participation in PA, while the terms “girls/women” and “boys/men” will be used in describing barriers/facilitators to PA to acknowledge the potential role of psychological and/or sociocultural factors in these outcomes. No previous systematic review and meta-analysis has summarized evidence of participation in PA by sex (and associated barriers) among individuals with T2DM across the life span. Therefore, the aim of the present systematic review and meta-analysis was to summarize the evidence related to sex differences in participation in PA among individuals with T2DM across the life span, with additional subgroup analyses according to 1) type of PA assessment and 2) study quality. Additionally, we sought to examine the evidence related to gender differences in barriers and facilitators to PA among individuals with T2DM.

We followed the 2020 Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines (15), and the review and meta-analysis protocol was registered on PROSPERO (CRD42021254246). The inclusion/exclusion criteria, search strategy, process used to evaluate evidence quality, and meta-analysis methods are detailed below.

Studies of male and female individuals with T2DM of any age were included. We defined age categories using the mean age of the study sample (i.e., adolescents 10–17 years, adults 18–64 years, and older adults ≥65 years). Studies that included individuals with other conditions were included, provided the data for participants with T2DM were reported separately. Additionally, due to changes in the terminology used to describe T2DM (16), we also included articles where diabetes type was not specified, provided there was reasonable evidence to suggest that all, or a significant majority of the participants had T2DM (e.g., elevated BMI, waist-to-hip ratio, lipids, presence of comorbidities such as obesity, hypertension, coronary artery disease, insulin use). Studies that included only individuals with type 1 diabetes, prediabetes, or gestational diabetes mellitus, or studies that did not report the PA data for these groups separately, were excluded. Additionally, studies that focused on PA as a risk factor for the development of T2DM or baseline data from studies in which inactive or sedentary individuals were preferentially selected (e.g., baseline data from a randomized controlled trial designed specifically for inactive patients with T2DM) were also excluded.

Studies that reported the percentage or number of participants meeting PA guidelines (≥150 min of MVPA per week or its equivalent in MET min per week [i.e., ≥600 MET min per week] among adults and older adults [17], ≥60 min of MVPA per day among children and adolescents [17]) or assessment of PA or sedentary behaviors (SB) (waking behavior performed in a sitting or lying position with low energy expenditure) with any method (e.g., questionnaire, pedometer, accelerometer, observation, etc.) and reported or examined data by sex or gender were included. PA could be reported in any format, including time in activity (e.g., minutes, hours), percent time in activity, frequency of activity, proportion of people engaging in any activity, steps, number of flights of stairs, and MET min or MET h per week (amount of energy expended during PA). Additionally, studies that assessed barriers and/or facilitators to PA and reported those data by gender were also included.

A systematic search was conducted of MEDLINE (via Ovid MEDLINE and Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Daily and Versions, 1946 to present), Embase (via Elsevier, Embase.com, 1947 to present), Web of Science Core Collection (via Clarivate Analytics, including Science Citation Index Expanded and Social Sciences Citation Index, 1974 to present), Cumulative Index to Nursing and Allied Health Literature (CINAHL) (via EBSCOhost, 1981 to present), Allied and Complementary Medicine (AMED) (via Ovid, 1985 to present), SPORTDiscus (via EBSCOhost, 1800 to present), and APA PsychInfo (via Ovid, 1806 to present). The search strategy included a combination of subject heading and keyword searches for identification of articles with reported findings related to PA, sex differences, and T2DM. The search was optimized with the assistance of a research librarian from the University of Colorado Strauss Health Sciences Library. Additional limits (when available) were placed on the searches to restrict the output to articles in English and human subjects. No limits were placed on publication date; thus, the search included articles published from database inception to 11 November 2021. The search strategies used for each database are included in Supplementary Material. In addition to the database searches, the reference lists of the selected articles were also reviewed for additional eligible articles.

Review and selection of potential manuscripts were facilitated by the Web-based software platform Covidence (covidence.org; Melbourne, Australia). Identified records were imported into Covidence and duplicates were removed. Titles and abstract of all identified records were screened in duplicate by independent reviewers (M.O.W., A.J.P., L.A.A., or K.C.). Manuscripts deemed to be potentially relevant were retrieved for full-text review and screened in duplicate by independent reviewers (M.O.W., A.J.P., or L.A.A.). Discrepancies in inclusion or exclusion were resolved via discussion.

The following data were extracted from each individual manuscript: country, study aim and design, participant characteristics (target population, sample size, sex distribution, age, BMI, race distribution, diabetes duration, age at diagnosis, fasting glucose, glycated hemoglobin [HbA_1c], diabetes medications, and diabetes complications and other comorbidities), key components of outcome assessment (method, frequency, and duration of assessment, intensity, pattern and setting/context of each assessed behavior, and unit of measurement), outcomes related to PA level and/or barriers and facilitators to PA, primary findings for each outcome, and stated conclusions. Data were extracted by two independent reviewers (M.O.W., A.J.P., or L.A.A.), with discrepancies resolved via discussion.

Study quality and the risk of bias of the qualified cross-sectional studies were assessed with the Appraisal tool for Cross-Sectional Studies (AXIS) (18). AXIS is comprised of 20 questions covering quality of reporting (7 questions), study design quality (7 questions), and possible introduction of biases (6 questions). Each question was answered with “yes,” “no,” or “don’t know.” For this critical appraisal, responses indicating high quality were scored as “1,” while those indicating poor or unknown quality were scored as “0.” The publication score was considered to indicate high quality if ≥70% (≥14 of 20), fair quality if between 60 and 69.9% (12–13 of 20), and low quality if <60% (≤11 of 20) (19). Methodological quality and risk of bias assessments were independently conducted by two authors (M.O.W., A.J.P., or L.A.A.), with discrepancies resolved via discussion to achieve consensus.

To estimate sex differences in meeting PA guidelines (primary outcome) among individuals with T2DM across age-groups, we calculated odds ratios (ORs) and 95% CIs using the number of events (individuals meeting PA guidelines) and the total number of observations for each sex. To estimate sex differences in participation in SB, LPA, and MVPA (secondary outcomes), we calculated standardized mean differences (SMD) (Cohen d effect size) and 95% CIs using the sample size, mean, and SD for each sex. We calculated pooled effect estimates for each outcome and age-group (adolescents, adults, and older adults) using the inverse variance method and a random effects model, due to the small number of studies included in some analyses and the methodological diversity of included studies, with between-study variance estimated through a restricted maximum likelihood (REML) model. An OR >1 indicated that males were more likely than females to meet PA guidelines, and a positive SMD indicated that males had higher participation in SB, LPA, or MVPA. Subsequently, a subgroup analysis was performed to investigate the potential influence of 1) type of PA level assessment (subjective and objective methods) and 2) study quality as assessed with AXIS (low, fair, and high quality).

We carried out a sensitivity analysis to identify the presence of highly influential studies by removing one study at a time (leave-one-out sensitivity analysis) and then examining the resulting effect on sex differences in participation in PA. The most benefit and least benefit were reported, and studies were considered influential if their removal resulted in a change of the OR and SMD significance or magnitude. Publication bias was evaluated through visual inspection of the Begg funnel plot when at least 10 trials were included in the meta-analysis, as with fewer studies the power of the tests is too low to distinguish chance from real asymmetry (20). Heterogeneity was measured with Higgin I² test and interpreted with the following thresholds: 0–40%, might not be important; 30–60%, may represent moderate heterogeneity; 50–90%, may represent substantial heterogeneity; and 75–100%, represents considerable heterogeneity.

Significance was set at P < 0.050 (two tailed). Data are presented as OR or SMD (95% CI). All statistical analyses were performed with the R meta package (21) in RStudio (RStudio, Boston, MA, U.S.) for Windows, version 1.4.1717.

A total of 9,591 articles were identified from the included databases and an additional 14 articles were identified via other sources. Of these, 1,984 were duplicate records. Among the 7,621 articles screened, 7,527 were excluded as irrelevant based on abstract review and 1 could not be retrieved. The remaining 80 articles were assessed for eligibility, and 53 articles (22–74) representing 48 unique studies met criteria for inclusion in this review. Of these included articles, 50 reported subjective and objective PA (46 unique studies) and 3 (22,45,60) only included discussion of barriers/facilitators to PA. Seven articles reported both PA and barriers/facilitators to PA (22,25,33,40,44,48,71). All articles except for one had a cross-sectional design (58). The PRISMA flowchart is provided in Supplementary Fig. 1.

Table 1 summarizes the characteristics of the included articles with assessment of PA. Studies included a total of 65,344 individuals age ≥9 years from 22 countries. Seven articles focused exclusively on adolescents (39,41,53,55,62,68,69). Four articles did not include sex distribution (27,47,54,74); however, of 45,157 individuals with reported sex, 49.3% were female. Eleven articles did not explicitly define the type of diabetes of the sample (23,27,28,36,56,59,67,71–74). Thirty-eight articles reported subjective measures only (all questionnaires) (23–25,27–31,33–42,44,46–48,50–52,54,58,59,61,63–65,67,69,71–74), five reported objective measures only (two with pedometers [49,70], three with accelerometers [32,56,57]), and seven included both subjective (six with questionnaires [43,53,55,62,66,68], one with pictograms [26]) and objective measures (five with accelerometers [26,43,53,66,68], two with pedometers [55,62]). The most commonly used questionnaire was the International Physical Activity Questionnaire (IPAQ) (n = 9) (28,34,36,38,42,50–52,67). Figure 1A represents the age and population distribution by sex of studies (n = 21) with measurement of meeting PA guidelines (by either subjective or objective measures). Supplementary Table 1 presents detailed characteristics of the included articles with assessment of PA.

Of the included articles, nine evaluated barriers and facilitators to PA by gender (22,25,33,40,44,45,48,60,71) (Table 2 and Supplementary Table 2). Three articles did not explicitly define the type of diabetes of the sample (22,45,71). Seven articles assessed barriers and facilitators via questionnaire (22,33,40,44,45,48,71); two articles used semistructured interviews or focus groups (25,60). Barriers and facilitators data were only available among adults, with a mean sample age ranging from 48 years among males and 52 years among females (71) to 67 years among both sexes (40). Among women, lack of social support, motivation, and embarrassment were the most frequently reported barriers (22,25,33). Conversely, lack of time was more frequently reported among men (22,25,33,45,48). Only three studies included assessment of facilitators, but there were no differences reported by gender (25,45,60).

The AXIS quality score for each study is reported in Supplementary Table 3. Overall study quality was fair (mean [SD] 62.7% [12.2], range 25–90). Fourteen studies were considered low quality, 19 were considered fair quality, and 20 were considered high quality. The AXIS criteria related to the quality of reporting and study design were most frequently met (5.0 [1.5] of 7, range 1–7, and 4.9 [0.9] of 7, range 2–6, respectively). In contrast, questions related to the risk of bias were poorly rated (2.6 [1.1] of 6, range 1–5).

Of the 53 articles included in the narrative synthesis, only 21 reported the necessary data for inclusion in the quantitative synthesis (Supplementary Fig. 1). Among these, 15 articles were included in the meta-analysis on sex differences in meeting PA guidelines among individuals with T2DM across the life span (23,25,28,30,32–34,36,38,52,55,56,64,65,69). Five, three, and thirteen articles, respectively, were included in the meta-analysis on the sex differences in participation in SB (23,32,34,53,57), LPA (32,53,56), and MVPA (25,32,34,39,43,52,53,55–58,66,69). Reasons for exclusion from this quantitative synthesis were 1) incorrect criteria to define one as active (41,42,47,49,51,54,59,61,63,73), 2) insufficient data completeness (27,67), 3) use of data from exact same population as that of another included study (68), 4) assessment of PA but no report on meeting guidelines for SB, LPA, or MVPA (24,26,29,31,35,37,40,44,46,48,50,62,70–72,74), and 5) only reported data on barriers and facilitators to PA (22,45,60).

There were no sex differences in meeting PA guidelines among adolescents (OR 0.70 [95% CI 0.31, 1.59], P = 0.399) (Fig. 1B), and adolescent males performed more MVPA than adolescent females (SMD 0.42 [95% CI 0.20, 0.64], P < 0.001). In contrast, males performed less LPA than females (−0.21 [−0.35, −0.07], P = 0.003). No sex differences were observed in time spent in SB among adolescents (0.08 [−0.07, 0.22], P = 0.292) (Table 3).

Among adults, males were more likely than females to meet PA guidelines (OR 1.65 [95% CI 1.36, 2.01], P < 0.001) (Fig. 1B) and performed more MVPA than females (SMD 0.29 [95% CI 0.17, 0.42], P < 0.001). No sex differences were observed in time spent in SB (0.06 [−0.30, 0.42], P = 0.751) and LPA (−0.13 [−0.59, 0.32], P = 0.653) (Table 3).

Males were more likely than females to meet PA guidelines (OR 1.63 [95% CI 1.27, 2.09], P < 0.001) (Fig. 1B) and performed more MVPA than females (SMD 0.23 [95% CI 0.12, 0.33], P < 0.001) among older adults (Table 3). Meta-analyses were not performed for SB and LPA due to the lack of studies with assessment of these outcomes.

Subgroup analysis by type of PA assessment is presented in Supplementary Fig. 2. Males are significantly more likely than females to meet PA guidelines based on both objective (OR 1.94 [95% CI 1.22, 3.11], P < 0.001) and subjective (1.55 [1.32, 1.81], P < 0.001) methods to assess PA (test for subgroup differences: P = 0.370). No sex differences in time spent in objectively (SMD 0.05 [95% CI −0.14, 0.24], P = 0.606) and subjectively (0.06 [−0.26, 0.38], P = 0.719) measured SB were observed (test for subgroup differences: P = 0.960). When participation in LPA was subjectively (−0.24 [−0.40, −0.07], P = 0.006), but not objectively (−0.12 [−0.33, 0.10], P = 0.279) measured, males tended to perform less LPA than females (test for subgroup differences: P = 0.387). Males had a significantly higher engagement in MVPA than females based on both objective (0.38 [0.23, 0.53], P < 0.001) and subjective (0.25 [0.15, 0.35], P < 0.001) methods of assessment (test for subgroup differences: P = 0.144).

Subgroup analysis by study quality is presented in Supplementary Fig. 3. Males were significantly more likely than females to meet PA guidelines irrespective of study quality (OR for low 1.37 [95% CI 1.21, 1.56], P < 0.001; fair 1.36 [1.02, 1.82], P = 0.039; and high 1.74 [1.40, 2.16], P < 0.001) (test for subgroup differences: P = 0.163). No sex differences were observed in time spent in SB in studies of fair quality (SMD 0.16 [95% CI −0.02, 0.34], P = 0.075) and high quality (−0.06 [−0.74, 0.63], P = 0.876) (test for subgroup differences: P = 0.548). For LPA, males significantly performed less LPA than females in studies of fair quality (−0.21 [−0.35, −0.07], P = 0.003) but not those of high quality (−0.13 [−0.59, 0.32], P = 0.653) (test for subgroup differences: P = 0.754). Males engaged in significantly more MVPA than females irrespective of study quality (low 0.36 [0.12, 0.60], P = 0.003; fair 0.31 [0.18, 0.44], P < 0.001; and high 0.32 [0.16, 0.48], P < 0.001) (test for subgroup differences: P = 0.933).

Results of leave-one-out sensitivity analysis indicated that none of the included studies unduly influenced the results for meeting PA guidelines in adults (OR for most benefit 1.72 [95% CI 1.43, 2.05] omitting the study by Falconer et al. [34] and least benefit 1.54 [1.31, 1.83] omitting Alghafri et al. [23]) and older adults (most benefit 1.74 [1.26, 2.41] omitting Plotnikoff et al. [65] [age 60–69 years] and least benefit 1.57 [1.16, 2.12] omitting Plotnikoff et al. [65] [age >70 years]). Sensitivity analysis was not performed for adolescents, as only two studies were included in the meta-analysis. Similarly, none of the included studies unduly affected the results for participation in SB, LPA, and MVPA (Table 3).

Visual inspection of the funnel plot for sex differences in meeting PA guidelines across all age-groups (A), in meeting PA guidelines among adults (B), and in participation in MVPA across all age-groups (C) revealed asymmetry (Supplementary Fig. 4). Funnel plots were not used for other population groups and outcomes due to the small number of studies (all <10 studies).

Heterogeneity was not important for sex differences in meeting PA guidelines among adolescents and older adults or for participation in SB and LPA among adolescents or MVPA among older adults (Fig. 1B and Table 2). However, substantial heterogeneity was observed for sex differences in participation in MVPA among adolescents (Table 2) and for meeting PA guidelines and participation in LPA and MVPA among adults (Fig. 1B and Table 2). Finally, there was considerable heterogeneity for sex differences in participation in SB among adults (Table 2). The high heterogeneity is probably due to the small number of included studies and sample and methodological heterogeneity. Sources of sample and methodological heterogeneity may include, but are not limited to, participant characteristics (city/country of residency, culture, clinical parameters, etc.), methods used to assess PA level, and the use of different cut points, thresholds, and units of measurement to report PA outcomes.

Sex differences were not observed in meeting PA guidelines among adolescents with T2DM, but males had significantly greater odds of meeting PA guidelines than females among adults and older adults with T2DM. Despite the inconsistent sex differences in meeting PA guidelines across the life span, females with T2DM consistently engaged in less MVPA than males among adolescents, adults, and older adults—thus demonstrating important sex differences across the life span in MVPA. The lack of agreement in these outcomes may be due, in part, to a lack of data on meeting PA guidelines among children and adolescents with T2DM. The scarcity of studies including LPA and SB as outcomes limit our conclusions for those measures.

Globally, one in four adults do not meet PA guidelines (75) based on self-reported data, and previous research suggests that individuals with T2DM are, on average, less active than the general population (27). Our results are consistent with those of previous studies (74), as only 36.2% (31.5% females and 40.9% males) of individuals with T2DM across all age-groups in the included articles met PA guidelines. These findings highlight the need for PA promotion for individuals with T2DM across the life span irrespective of sex (9,10,17,76). In this context, assessing participation in PA, and identifying facilitators and overcoming barriers to PA, may support the development of personalized, optimal PA prescriptions and increase engagement in PA among individuals with T2DM.

With respect to sex differences in participation in PA, there were no differences in meeting PA guidelines between males and females among adolescents with T2DM, which is contrary to findings among apparently healthy adolescents (77). This unexpected finding may be driven by the relative paucity of data regarding meeting PA guidelines among adolescents in comparison with other age-groups. Nonetheless, our findings suggest that adolescent females with T2DM engaged in less MVPA than males and this difference persisted across the life span. Importantly, sex differences in meeting PA guidelines become evident among adults and older adults with T2DM, which corroborates evidence from the general population demonstrating that adult females are less likely to meet PA guidelines than adult males (13). Given that females with T2DM more often have lower cardiorespiratory fitness than males with T2DM (7) and bear a disproportionate burden of CVD in the context of T2DM (3,8), promoting participation in PA for females with T2DM across the life span is instrumental in enhancement of health, improvement of glycemic control, and reduction of CVD burden.

Only nine of the identified articles included assessment of barriers to PA, of which only three also included facilitators to PA. We observed some gender differences in barriers to PA, with lack of social support, motivation, and embarrassment more frequently reported by women and lack of time more frequently reported by men. These barriers are consistent with existing data on barriers to PA among adults with obesity (78). Of note, none of the studies included in the present review included assessment of barriers to PA among children and adolescents with T2DM. As differences in barriers to PA have been noted among healthy boys and girls (79), work is needed to understand barriers and facilitators to PA among children and adolescents with T2DM and to optimize the design of PA interventions for this population.

This is the first systematic review and meta-analysis to characterize participation in PA by sex and barriers/facilitators to PA by gender among individuals with T2DM across the life span. It is notable that many studies limited their evaluation of PA to MVPA rather than also including assessment of LPA and SB. Increased understanding of the impact of LPA on health outcomes is important because increasing LPA is frequently targeted as part of interventions designed to reduce SB (replace/interrupt SB with LPA). This focus is particularly notable in the context of the updated PA guidelines (10), where recommendations have shifted away from the requirement that PA occur in “bouts” of ≥10 min to be meaningful to an “all activity counts” approach. This shift highlights the need for an understanding of not only participation in MVPA but also involvement in other types of PA as important for health. For example, research has demonstrated that time spent in LPA is beneficially associated with 2-h blood glucose, with the opposite true for SB, independent of participation in MVPA (80). Additionally, breaking up prolonged SB with brief activity bouts also shows promise in improving blood glucose control among individuals with and without T2DM (81–83) Additional research is needed to understand the role of targeting increasing LPA and reducing SB in combination with other lifestyle interventions in the long-term management of T2DM.

Although the risk of T2DM increases with age (84), T2DM is becoming a major concern for children and young adults, with an estimated prevalence of 0.67 per 1,000 youths aged 10–19 years (85). Despite this increasing prevalence, only six of the eligible articles included individuals with T2DM <18 years old (39,41,53,55,68,69). As the population of children and young adults with T2DM increases, studies that include this younger age-group are needed for an understanding of PA levels in this population, particularly because individuals diagnosed at a young age are more likely to experience T2DM complications and have increased risk of CVD morbidity and mortality (86). Additionally, T2DM in children and adolescents presents a distinct challenge, as the development of complications is accelerated among children and adolescents and there are fewer approved treatment options available (87). Understanding the unique pathophysiology of T2DM in children and adolescents, including the role of PA in delaying the onset of complications, is essential.

In addition to the lack of data available in younger age-groups, the variability of methods used to classify participants as active/inactive is a limitation. In more than 20% (n = 10) (41,42,47,49,51,54,59,61,63,73) of the studies where investigators sought to classify activity levels, they did so using methods that were inconsistent with national or international guidelines for PA. In some cases, this is the product of relatively low levels of PA among individuals with T2DM, with any regular PA being considered “active.” Using published guidelines (e.g., of the American Diabetes Association [9], American College of Sports Medicine [17], the Physical Activity Guidelines for Americans [10], or World Health Organization guidelines on PA and SB [76]) to guide these classifications is critical to enable comparisons across populations.

We also identified other limitations with respect to the scientific rigor of the included articles and available evidence in the literature. First, most of the included articles did not report PA data by age-group. Consequently, our meta-analysis was based on mean age provided by the authors and participation in PA in younger participants might have not been summarized well in most of the studies that were conducted in an adult population. There were inconsistencies in the use of terms for sex/gender, which precluded analysis of both sex and gender differences in participation in PA. There were also inconsistencies in the reporting of data on diabetes status (e.g., self-report vs. diagnosed diabetes, lack of laboratory data to confirm status, lack of ruling out type 1 diabetes). There was high variability in outcome reporting for the same measure (e.g., IPAQ data were summarized as meeting PA guidelines, time spent in each intensity with/without time spent in SB, total MET min, MET min in each intensity, etc.), which precluded the inclusion of some articles in our analysis. Reporting all possible outcomes from PA assessment would facilitate future meta-analysis. Finally, it is important to note that “sex differences” is a relatively unused subject heading. We used a complex search strategy that we optimized with the help of a research librarian but may have missed some relevant articles.

Articles included in this review provided initial evidence about sex differences in participation in PA among individuals with T2DM. However, the literature on the topic is still incipient and extensive further research needs to be conducted in this area. There is limited evidence on sex/gender differences in engagement in SB and LPA. Additionally, researchers should focus on stratification of data by sex/gender among individuals with T2DM, with specific attention to the appropriate use of the terms sex and gender, as well as assessment of diabetes status. It is also critical to disaggregate data by age (i.e., analyze data in smaller age groupings, such as 5-year increments) to facilitate understanding of age-related differences. Researchers should also consider the inclusion of racially and ethnically diverse samples. There is a need to understand unique barriers and facilitators to PA among women and men, as well as how they act as moderators of participation in PA. These data will support the development of personalized PA prescriptions and health promotion strategies across the life span, address decreases in PA that often occur with increasing age, and promote the delivery of optimal health interventions.

In summary, sex differences in meeting PA guidelines were not observed among adolescents with T2DM but were apparent among adults and older adults with T2DM. Despite these inconsistencies in sex differences of meeting PA guidelines across the life span, females with T2DM consistently engaged in less MVPA than males across the life span. Additional studies that include evaluation of sex differences in PA guidelines for SB, LPA, and MVPA across all age-groups of people with T2DM are needed, as well as studies on the role of gender and its sociocultural implications. Progress in the field needs to occur to attain a greater understanding of how differences in sex and gender influence participation in PA. This will potentially lead to an improved ability to increase PA in females, as well as an enhanced capability to develop individualized PA interventions for both sexes.

Acknowledgments. The authors acknowledge Christi Piper, Strauss Health Sciences Library, for her valuable help in optimizing the search strategy.

Funding. This study was supported by the National Institutes of Health (T32AG000279 to M.O.W., L30NR019425 to M.O.W., R01DK123334 to A.B., P50CA244688 to A.G.H., P30DK048520 to K.S.M., P30DK116073 to J.E.B.R., UL1TR001082 to J.E.B.R., R01AG066562 to J.E.B.R., R01DK124344 to J.E.B.R. and J.G.R., and K12HD057022 to J.G.R.), the Ludeman Family Center for Women’s Health Research (M.O.W., A.J.P., A.G.H., K.J.N., R.L.S., J.E.B.R., and J.G.R.), the American Diabetes Association (1-21-CMF-003 to L.A.A.), and the Department of Veterans Affairs (BX004533 to R.L.S., BX002046 to J.E.B.R., and CX001532 to J.E.B.R.).

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. M.O.W. and J.G.R. conceived of the idea. M.O.W., A.J.P., L.A.A., A.B., A.G.H., K.S.M., J.E.B.R., and J.G.R. refined the topic to be studied. M.O.W. performed the literature searches. M.O.W., A.J.P., L.A.A., and K.C. screened articles for eligibility. M.O.W., A.J.P., and L.A.A. extracted relevant data. A.J.P. performed the analysis. M.O.W., A.J.P., and L.A.A. drafted the manuscript. All authors discussed the results, critically revised the manuscript, and approved the final version to be published.