Because much of diabetes management during pregnancy occurs at home, self-management factors such as self-efficacy, self-care activities, and care satisfaction may affect glycemia. Our objective was to explore trends in glycemic control during pregnancy in women with type 1 or type 2 diabetes; assess self-efficacy, self-care, and care satisfaction; and examine these factors as predictors of glycemic control.
We conducted a cohort study from April 2014 to November 2019 at a tertiary center in Ontario, Canada. Self-efficacy, self-care, care satisfaction, and A1C were measured three times during pregnancy (T1, T2, and T3). Linear mixed-effects modeling explored trends in A1C and examined self-efficacy, self-care, and care satisfaction as predictors of A1C.
We recruited 111 women (55 with type 1 diabetes and 56 with type 2 diabetes). Mean A1C significantly decreased by 1.09% (95% CI −1.38 to −0.79) from T1 to T2 and by 1.14% (95% CI −1.43 to −0.86) from T1 to T3. Self-efficacy significantly predicted glycemic control for women with type 2 diabetes and was associated with a mean change in A1C of −0.22% (95% CI −0.42 to −0.02) per unit increase in scale. The exercise subscore of self-care significantly predicted glycemic control for women with type 1 diabetes and was associated with a mean change in A1C of −0.11% (95% CI −0.22 to −0.01) per unit increase in scale.
Self-efficacy significantly predicted A1C during pregnancy in a cohort of women with preexisting diabetes in Ontario, Canada. Future research will continue to explore the self-management needs and challenges in women with preexisting diabetes in pregnancy.
Evidence indicates that the prevalence of diabetes is increasing nationally and globally, both in the general population and among pregnant women (1–4). The growing rate of diabetes in pregnancy is of particular concern because it is associated with a significant increase in adverse perinatal outcomes (5,6). Research indicates that maternal glycemic control during pregnancy is a significant predictor of pregnancy outcomes (7–14). Women who maintain optimal glycemic control during preconception and pregnancy have a lower risk of complications (7–14). Thus, recommended A1C targets are close to the normoglycemic range during the preconception and prenatal periods (15).
Glycemic control during pregnancy in women with preexisting type 1 or type 2 diabetes is affected by physiological variables, such as the degree of insulin resistance, as well as social determinants of health, such as education and income levels (16–19). Multiple clinical interventions aim to improve glycemic control during pregnancy, including preconception care, education and counseling, and the provision of medical care by a multidisciplinary health care team, among others (15). In addition, health care providers (HCPs) recommend various methods of glucose monitoring (e.g., fingerstick blood glucose monitoring or continuous glucose monitoring) and insulin delivery (e.g., multiple daily injections of insulin or insulin pump therapy) in an attempt to optimize glycemia during the prenatal period (15). However, the majority of diabetes self-management during pregnancy occurs at home between appointments with HCPs. Thus, self-management factors such as self-efficacy, defined as confidence in one’s ability to succeed in specific situations or accomplish specific tasks, may also affect glycemic control.
Similarly, diabetes self-care behaviors, which include healthy eating, being physically active, self-monitoring glucose levels, taking medications, using problem-solving and healthy coping skills, and engaging in risk-reduction behaviors, could be linked to prenatal glycemia (20).
Finally, patients’ satisfaction with support from their health care team may also contribute to their ability to attain glycemic targets.
Among nonpregnant adults, research has indicated that self-efficacy, self-care, and patients’ satisfaction with medical care are significant predictors of glycemic control (21–23). For example, diabetes self-care behaviors are moderately correlated with A1C (r = −0.37, P <0.05) among adults with type 2 diabetes aged 30–55 years (22). Thus, the specific clinical interventions implemented by HCPs may have less of an impact on prenatal glycemia than self-management factors, including women’s levels of self-efficacy and self-care and satisfaction with their medical care (24).
Research has explored the relationships between diabetes self-efficacy, self-care, and care satisfaction and diabetes management and glycemic control among women with gestational diabetes mellitus (GDM) (25,26). The evidence suggests that self-efficacy is a predictor of a healthy lifestyle among women with GDM, with higher self-efficacy associated with increased physical activity, a healthier diet, and a lower BMI (26). However, to our knowledge, no investigations have focused on these self-management factors as predictors of diabetes management and glycemic control in pregnancies complicated by type 1 or type 2 diabetes.
The objective of this study was to explore trends in glycemic control during pregnancy in women with type 1 or type 2 diabetes. We also aimed to assess self-management factors such as self-efficacy, self-care, and care satisfaction and examine these factors as potential predictors of glycemic control.
Research Design and Methods
Study Design and Participants
We conducted a cohort study from 17 April 2014 to 28 November 2019. Consecutive convenience sampling was used to recruit women from a high-risk pregnancy clinic at a tertiary center in Ontario, Canada. We recruited women who met the following eligibility criteria: a diagnosis of type 1 or type 2 diabetes and age ≥18 years. This study received ethics approval from our local Research Ethics Board (REB #14–222). The conduct and reporting of this study followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines (27).
Data Collection and Outcomes
Data collection occurred three times during pregnancy to align with the conventional trimesters: between 0 and 16 weeks (time point 1 [T1]), between 17 and 28 weeks (time point 2 [T2]), and between 29 and 40 weeks (time point 3 [T3]). Women completed a questionnaire at baseline to capture demographic and clinical characteristics such as age, ethnicity, diabetes type, and gravidity. Glycemic control was assessed through self-report of A1C at each time point and confirmed by an HCP at the clinic visit.
Self-efficacy was measured at each time point using the Self-Efficacy for Diabetes (SED) scale (28). The SED scale is an eight-item questionnaire that asks participants to rate their confidence in activities, such as choosing healthy foods to eat or knowing what to do when their blood glucose is higher or lower than the target. Responses are rated on a 10-item Likert scale ranging from 1 (not at all confident) to 10 (totally confident). The total score is calculated by determining the mean of the eight item responses, with a maximum score of 10. A higher score indicates higher self-efficacy in diabetes management (28). The literature indicates that the SED scale is reliable, with strong internal consistency (Cronbach α = 0.85) and test-retest reliability (intraclass correlation coefficient = 0.80), and has convergent validity, with item-scale correlations exceeding 0.50 (29).
Self-care was assessed at each time point using the Summary of Diabetes Self-Care Activities (SDSCA) scale, which includes 11 questions in five subscales to assess self-care behaviors (30). The subscales include general diet, specific diet, exercise, glucose self-monitoring, and foot care. Scores are determined by calculating the mean score for each subscale; the tool was not designed to yield a total score across subscales. A higher frequency of activities performed indicates better self-management and adherence to treatment (30). This scale has been widely used for more than 20 years and has demonstrated both reliability, with adequate internal consistency (Cronbach α >0.5) and test-retest reliability (intraclass correlation coefficient = 0.47), and strong construct validity (comparative fit index >0.90 and goodness of fit index >0.90) (31).
The Patient Assessment of Chronic Illness Care (PACIC) scale measures the degree to which patients perceive that their medical care is congruent with the Chronic Care Model (32). The Chronic Care Model seeks to optimize the following care components: health care organization, delivery system design, clinical information systems, decision support, self-management support, and community resources (32). This tool has 20 items that ask participants to quantify the care they received from their health care team during the past 6 months. Responses range from none of the time (1 point) to always (5 points). The PACIC has five subscales: patient activation, delivery system design/decision support, goal-setting, problem-solving/contextual counseling, and follow-up/coordination. Items in each subscale are averaged to calculate a subscale score. The overall score for the instrument is an average of the combined subscale scores, with a maximum score of 5. A higher score indicates that a patient is receiving care that is congruent with the Chronic Care Model, in other words, care that is planned, proactive, population-based, and patient-centered (32). This scale is reliable, with strong internal consistency (Cronbach α = 0.93) and adequate test-retest reliability (intraclass correlation coefficient = 0.58) and has moderate to strong convergent validity with existing measures of patient activation (r = 0.42–0.60) (32).
Statistical Analysis
Descriptive statistics were completed to understand the distribution of baseline characteristics and levels of diabetes self-efficacy, self-care, and care satisfaction. Descriptive statistics were reported as mean ± SD for continuous data and frequency and percentage for categorical data. Independent samples t tests, χ2 tests, and Fisher exact tests explored differences in baseline variable distribution stratified by diabetes type. Linear mixed-effects modeling was used to explore trends in glycemic control and examine self-efficacy, self-care, and care satisfaction as predictors of A1C. We reported model parameters and 95% CIs. To control for potential confounders of the relationship between self-management factors and glycemic control, we adjusted the model for participant age, diabetes duration, ethnicity, education level, household income, and insurance coverage. P values <0.05 were considered statistically significant. SPSS statistical software, v. 28 (IBM Corp., Armonk, NY), was used to perform all statistical analyses.
Results
Participant Characteristics
Of the 128 women approached to participate in the study, 111 women were recruited, including 55 with type 1 diabetes and 56 with type 2 diabetes. Of the 17 women who were approached but did not participate, 16 declined citing time as the most common reason for nonparticipation, and 1 was deemed too medically complex by the health care team to participate.
The mean age of participants was 30.23 ± 4.97 years, and the majority identified as European (n = 87 [81.3%] and were married (n = 72 [65.5%]). Almost half had a college/trade level of education (n = 51 [45.9%]), and nearly two-fifths had third-party insurance (n = 43 [39.8%]). Significantly more women with type 2 diabetes had a college/trade-level education compared with those with type 1 diabetes (n = 32 [57.1%] vs. n = 19 [34.5%], P = 0.02). Significantly more women with type 1 diabetes had a university-level education compared with those with type 2 diabetes (n = 22 [40.0%] vs. n = 10 [17.9%], P = 0.01). The current pregnancy was the first for 48 (43.2%) of the women and was a singleton pregnancy for nearly all women (n = 109 [98.2%]). Significantly more women with type 2 diabetes used assisted reproductive technology compared with those with type 1 diabetes (n = 8 [14.3%] vs. n = 1 [1.8%], P = 0.03). Diabetes duration was significantly longer among women with type 1 diabetes compared with those with type 2 diabetes (mean 15.3 ± 8.38 vs. 5.14 ± 5.39 years, P <0.0001). Significantly more women with type 2 diabetes than with type 1 diabetes used oral medications (n = 6 [10.7%] vs. n = 0 [0%], P = 0.03) and insulin injections (n = 49 [87.5%] vs. n = 28 [50.9%], P <0.001) to manage diabetes. Significantly more women with type 1 diabetes compared with those with type 2 diabetes used insulin pumps to manage diabetes (n = 27 [49.1%] vs. n = 0 [0%], P <0.001). Significantly more women with type 1 diabetes compared with those with type 2 diabetes had insurance coverage through the provincial Assistive Devices Program (ADP) (n = 25 [47.2%] vs. n = 2 [3.6%], P <0.001). In contrast, significantly more women with type 2 diabetes compared with those with type 1 diabetes had third-party insurance (n = 28 [50.9%] vs. n = 15 [28.3%], P = 0.02) or no insurance (n = 13 [23.6%] vs. n = 3 [5.7%], P = 0.01). There were no other statistically significant differences in baseline characteristics between women with type 1 diabetes and those with type 2 diabetes (Table 1).
Participant Baseline Characteristics, Stratified by Type of Diabetes
| . | Total (n = 111)* . | Type 1 Diabetes (n = 55) . | Type 2 Diabetes (n = 56) . | P . |
|---|---|---|---|---|
| Age, years | 30.23 ± 4.97 | 29.45 ± 4.69 | 30.98 ± 5.15 | 0.105 |
| Ethnicity African East Asian European Hispanic Middle Eastern South Asian Indigenous Unsure Other | 2 (1.9) 2 (1.9) 87 (81.3) 1 (0.9) 2 (1.9) 4 (3.7) 6 (5.6) 2 (1.9) 3 (2.8) | 2 (3.8) 1 (1.9) 47 (88.7) 0 (0) 1 (1.9) 0 (0) 1 (1.9) 1 (1.9) 1 (1.9) | 0 (0) 1 (1.9) 40 (74.1) 1 (1.9) 1 (1.9) 4 (7.4) 5 (9.3) 1 (1.9) 2 (3.7) | 0.243 1.000 0.053 1.000 1.000 0.118 0.205 1.000 1.000 |
| Marital status Single Supportive partner Married | 12 (10.9) 26 (23.6) 72 (65.5) | 5 (9.1) 14 (25.5) 36 (65.5) | 7 (12.7) 12 (21.8) 36 (65.5) | 0.784 |
| Education level Grade school High school College/trade University Other | 3 (2.7) 24 (21.6) 51 (45.9) 32 (28.8) 1 (0.9) | 0 (0) 13 (23.6) 19 (34.5) 22 (40.0) 1 (1.8) | 3 (5.4) 11 (19.6) 32 (57.1) 10 (17.9) 0 (0) | 0.243 0.609 0.017† 0.010† 0.495 |
| Household income, $ <20,000 20,001–40,000 40,001–60,000 60,001–80,000 80,001–100,000 >100,000 | 9 (8.3) 26 (24.1) 11 (10.2) 19 (17.6) 18 (16.7) 25 (23.1) | 4 (7.5) 9 (17.0) 7 (13.2) 10 (18.9) 10 (18.9) 13 (24.5) | 5 (9.1) 17 (30.9) 4 (7.3) 9 (16.4) 8 (14.5) 12 (21.8) | 0.606 |
| Employment Not working Casual/part-time Full-time Other | 30 (27.0) 24 (21.6) 55 (49.5) 1 (1.8) | 12 (21.8) 13 (23.6) 29 (52.7) 1 (1.8) | 18 (32.1) 11 (19.6) 26 (46.4) 1 (1.8) | 0.677 |
| Primiparous | 48 (43.2) | 25 (45.5) | 23 (41.1) | 0.641 |
| Singleton gestation | 109 (98.2) | 54 (98.2) | 55 (98.2) | 1.000 |
| Used assisted reproductive technology | 9 (8.1) | 1 (1.8) | 8 (14.3) | 0.032† |
| Previous GDM | 7 (6.3) | 7 (12.5) | ||
| Diabetes duration, years | 10.09 ± 8.61 | 15.13 ± 8.38 | 5.14 ± 5.39 | <0.000† |
| Diabetes treatment Diet/exercise Oral medications Insulin injections Insulin pump therapy | 1 (0.9) 6 (5.4) 77 (69.4) 27 (24.3) | 0 (0) 0 (0) 28 (50.9) 27 (49.1) | 1 (1.8) 6 (10.7) 49 (87.5) 0 (0) | 1.000 0.027† <0.001† <0.001† |
| Glucose monitoring at least four times daily | 61 (57.0) | 29 (54.7) | 32 (59.3) | 0.635 |
| Insurance coverage for diabetes supplies ADP Third-party Other None | 27 (25.0) 43 (39.8) 22 (20.4) 16 (14.8) | 25 (47.2) 15 (28.3) 10 (18.9) 3 (5.7) | 2 (3.6) 28 (50.9) 12 (21.8) 13 (23.6) | <0.001† 0.016† 0.704 0.009† |
| . | Total (n = 111)* . | Type 1 Diabetes (n = 55) . | Type 2 Diabetes (n = 56) . | P . |
|---|---|---|---|---|
| Age, years | 30.23 ± 4.97 | 29.45 ± 4.69 | 30.98 ± 5.15 | 0.105 |
| Ethnicity African East Asian European Hispanic Middle Eastern South Asian Indigenous Unsure Other | 2 (1.9) 2 (1.9) 87 (81.3) 1 (0.9) 2 (1.9) 4 (3.7) 6 (5.6) 2 (1.9) 3 (2.8) | 2 (3.8) 1 (1.9) 47 (88.7) 0 (0) 1 (1.9) 0 (0) 1 (1.9) 1 (1.9) 1 (1.9) | 0 (0) 1 (1.9) 40 (74.1) 1 (1.9) 1 (1.9) 4 (7.4) 5 (9.3) 1 (1.9) 2 (3.7) | 0.243 1.000 0.053 1.000 1.000 0.118 0.205 1.000 1.000 |
| Marital status Single Supportive partner Married | 12 (10.9) 26 (23.6) 72 (65.5) | 5 (9.1) 14 (25.5) 36 (65.5) | 7 (12.7) 12 (21.8) 36 (65.5) | 0.784 |
| Education level Grade school High school College/trade University Other | 3 (2.7) 24 (21.6) 51 (45.9) 32 (28.8) 1 (0.9) | 0 (0) 13 (23.6) 19 (34.5) 22 (40.0) 1 (1.8) | 3 (5.4) 11 (19.6) 32 (57.1) 10 (17.9) 0 (0) | 0.243 0.609 0.017† 0.010† 0.495 |
| Household income, $ <20,000 20,001–40,000 40,001–60,000 60,001–80,000 80,001–100,000 >100,000 | 9 (8.3) 26 (24.1) 11 (10.2) 19 (17.6) 18 (16.7) 25 (23.1) | 4 (7.5) 9 (17.0) 7 (13.2) 10 (18.9) 10 (18.9) 13 (24.5) | 5 (9.1) 17 (30.9) 4 (7.3) 9 (16.4) 8 (14.5) 12 (21.8) | 0.606 |
| Employment Not working Casual/part-time Full-time Other | 30 (27.0) 24 (21.6) 55 (49.5) 1 (1.8) | 12 (21.8) 13 (23.6) 29 (52.7) 1 (1.8) | 18 (32.1) 11 (19.6) 26 (46.4) 1 (1.8) | 0.677 |
| Primiparous | 48 (43.2) | 25 (45.5) | 23 (41.1) | 0.641 |
| Singleton gestation | 109 (98.2) | 54 (98.2) | 55 (98.2) | 1.000 |
| Used assisted reproductive technology | 9 (8.1) | 1 (1.8) | 8 (14.3) | 0.032† |
| Previous GDM | 7 (6.3) | 7 (12.5) | ||
| Diabetes duration, years | 10.09 ± 8.61 | 15.13 ± 8.38 | 5.14 ± 5.39 | <0.000† |
| Diabetes treatment Diet/exercise Oral medications Insulin injections Insulin pump therapy | 1 (0.9) 6 (5.4) 77 (69.4) 27 (24.3) | 0 (0) 0 (0) 28 (50.9) 27 (49.1) | 1 (1.8) 6 (10.7) 49 (87.5) 0 (0) | 1.000 0.027† <0.001† <0.001† |
| Glucose monitoring at least four times daily | 61 (57.0) | 29 (54.7) | 32 (59.3) | 0.635 |
| Insurance coverage for diabetes supplies ADP Third-party Other None | 27 (25.0) 43 (39.8) 22 (20.4) 16 (14.8) | 25 (47.2) 15 (28.3) 10 (18.9) 3 (5.7) | 2 (3.6) 28 (50.9) 12 (21.8) 13 (23.6) | <0.001† 0.016† 0.704 0.009† |
Data are n (%) or mean ± SD.
All totals do not equal 111 because of missing observations.
P value statistically significant at <0.05.
Glycemic Control
Overall, the cohort’s change in mean A1C was significant, at −1.09% (95% CI −1.38 to −0.79, P <0.001) from T1 to T2 and −1.14% (95% CI −1.43 to −0.86, P <0.001) from T1 to T3. The change from T2 to T3 was not significant (−0.51%, 95% CI −0.33 to 0.22, P = 0.71). Stratified by diabetes type, the change in mean A1C was significant for those with type 1 diabetes from T1 to T2 (−0.77%, 95% CI −1.13 to −0.39, P <0.001) and from T1 to T3 (−0.89%, 95% CI −1.25 to −5.21, P <0.001) and for those with type 2 diabetes from T1 to T2 (−1.45%, 95% CI −1.91 to −0.99, P <0.001) and from T1 to T3 (−1.49%, 95% CI −1.85 to −0.96, P <0.001). The change from T2 to T3 remained nonsignificant (Table 2).
Trends in A1C Across Time Points, Stratified by Type of Diabetes
| . | Total (n = 111) . | Type 1 Diabetes (n = 55) . | Type 2 Diabetes (n = 56) . | |||
|---|---|---|---|---|---|---|
| A1C, % T1 T2 T3 | 7.49 (7.23–7.77) 6.41 (6.15–6.67) 6.36 (6.11–6.60) | 7.49 (7.15–7.83) 6.72 (6.39–7.06) 6.60 (6.28–6.93) | 7.53 (7.11–7.95) 6.08 (5.68–6.48) 6.12 (5.78–6.49) | |||
| P | P | P | ||||
| Change in A1C, % T1 to T2 T2 to T3 T1 to T3 | −1.09 (−1.38 to −0.79) −0.05 (−0.33 to 0.22) −1.14 (−1.43 to −0.86) | <0.001* 0.713 <0.001* | −0.77 (−1.14 to −0.39) −0.12 (−0.47 to 0.24) −0.89 (−1.25 to −0.52) | <0.001* 0.509 <0.001* | −1.45 (−1.91 to −0.99) −0.04 (−0.46 to 0.38) −1.41 (−1.85 to −0.97) | <0.001* 0.848 <0.001* |
| . | Total (n = 111) . | Type 1 Diabetes (n = 55) . | Type 2 Diabetes (n = 56) . | |||
|---|---|---|---|---|---|---|
| A1C, % T1 T2 T3 | 7.49 (7.23–7.77) 6.41 (6.15–6.67) 6.36 (6.11–6.60) | 7.49 (7.15–7.83) 6.72 (6.39–7.06) 6.60 (6.28–6.93) | 7.53 (7.11–7.95) 6.08 (5.68–6.48) 6.12 (5.78–6.49) | |||
| P | P | P | ||||
| Change in A1C, % T1 to T2 T2 to T3 T1 to T3 | −1.09 (−1.38 to −0.79) −0.05 (−0.33 to 0.22) −1.14 (−1.43 to −0.86) | <0.001* 0.713 <0.001* | −0.77 (−1.14 to −0.39) −0.12 (−0.47 to 0.24) −0.89 (−1.25 to −0.52) | <0.001* 0.509 <0.001* | −1.45 (−1.91 to −0.99) −0.04 (−0.46 to 0.38) −1.41 (−1.85 to −0.97) | <0.001* 0.848 <0.001* |
Data are mean (95% CI).
P value statistically significant at <0.05.
Patient-Reported Outcomes
Self-Efficacy
For women with type 1 or type 2 diabetes, the overall mean self-efficacy score rose from 7.83 ± 1.31 in T1 to 7.96 ± 1.20 in T3. There were no statistically significant differences in self-efficacy scores in women with type 1 diabetes compared with those with type 2 diabetes across any time point (Table 3).
Results of Questionnaires Assessing Diabetes Self-Efficacy, Self-Care, and Care Satisfaction Across Time Points, Stratified by Type of Diabetes
| . | Total (n = 111) . | Type 1 Diabetes (n = 55) . | Type 2 Diabetes (n = 56) . | P . |
|---|---|---|---|---|
| SED scale T1 T2 T3 | 7.83 ± 1.31 7.76 ± 1.33 7.96 ± 1.20 | 8.06 ± 1.22 7.85 ± 1.33 8.12 ± 1.14 | 7.56 ± 1.38 7.66 ± 1.34 7.81 ± 1.26 | 0.098 0.521 0.219 |
| SDSCA scale T1 Diet, general Diet, specific Exercise Glucose monitoring Foot care T2 Diet, general Diet, specific Exercise Glucose monitoring Foot care T3 Diet, general Diet, specific Exercise Glucose monitoring Foot care | 4.89 ± 1.56 3.80 ± 1.47 2.92 ± 1.98 6.42 ± 1.03 2.56 ± 2.07 4.96 ± 1.38 3.88 ± 1.18 2.72 ± 1.75 6.32 ± 1.10 2.72 ± 2.05 4.84 ± 1.41 3.84 ± 1.13 2.92 ± 1.98 6.50 ± 0.89 2.99 ± 2.21 | 4.95 ± 1.63 3.99 ± 1.42 2.88 ± 1.96 6.68 ± 0.70 2.79 ± 2.26 4.98 ± 1.44 4.02 ± 1.09 2.62 ± 1.79 6.54 ± 0.78 2.76 ± 2.28 4.72 ± 1.58 4.08 ± 1.16 2.94 ± 1.86 6.68 ± 0.64 3.27 ± 2.32 | 4.84 ± 1.49 3.59 ± 1.51 2.97 ± 2.02 6.12 ± 1.26 2.29 ± 1.88 4.85 ± 1.32 3.72 ± 1.26 2.83 ± 1.73 6.09 ± 1.34 2.69 ± 1.79 4.95 ± 1.23 3.59 ± 1.06 2.89 ± 2.09 6.33 ± 1.06 2.71 ± 2.07 | 0.761 0.246 0.837 0.026* 0.310 0.929 0.246 0.586 0.072 0.858 0.436 0.032* 0.922 0.051 0.216 |
| PACIC scale T1 T2 T3 | 3.32 ± 0.88 3.42 ± 0.80 3.39 ± 0.81 | 3.48 ± 0.74 3.29 ± 0.69 3.26 ± 0.79 | 3.14 ± 1.00 3.57 ± 0.89 3.51 ± 0.82 | 0.111 0.116 0.124 |
| . | Total (n = 111) . | Type 1 Diabetes (n = 55) . | Type 2 Diabetes (n = 56) . | P . |
|---|---|---|---|---|
| SED scale T1 T2 T3 | 7.83 ± 1.31 7.76 ± 1.33 7.96 ± 1.20 | 8.06 ± 1.22 7.85 ± 1.33 8.12 ± 1.14 | 7.56 ± 1.38 7.66 ± 1.34 7.81 ± 1.26 | 0.098 0.521 0.219 |
| SDSCA scale T1 Diet, general Diet, specific Exercise Glucose monitoring Foot care T2 Diet, general Diet, specific Exercise Glucose monitoring Foot care T3 Diet, general Diet, specific Exercise Glucose monitoring Foot care | 4.89 ± 1.56 3.80 ± 1.47 2.92 ± 1.98 6.42 ± 1.03 2.56 ± 2.07 4.96 ± 1.38 3.88 ± 1.18 2.72 ± 1.75 6.32 ± 1.10 2.72 ± 2.05 4.84 ± 1.41 3.84 ± 1.13 2.92 ± 1.98 6.50 ± 0.89 2.99 ± 2.21 | 4.95 ± 1.63 3.99 ± 1.42 2.88 ± 1.96 6.68 ± 0.70 2.79 ± 2.26 4.98 ± 1.44 4.02 ± 1.09 2.62 ± 1.79 6.54 ± 0.78 2.76 ± 2.28 4.72 ± 1.58 4.08 ± 1.16 2.94 ± 1.86 6.68 ± 0.64 3.27 ± 2.32 | 4.84 ± 1.49 3.59 ± 1.51 2.97 ± 2.02 6.12 ± 1.26 2.29 ± 1.88 4.85 ± 1.32 3.72 ± 1.26 2.83 ± 1.73 6.09 ± 1.34 2.69 ± 1.79 4.95 ± 1.23 3.59 ± 1.06 2.89 ± 2.09 6.33 ± 1.06 2.71 ± 2.07 | 0.761 0.246 0.837 0.026* 0.310 0.929 0.246 0.586 0.072 0.858 0.436 0.032* 0.922 0.051 0.216 |
| PACIC scale T1 T2 T3 | 3.32 ± 0.88 3.42 ± 0.80 3.39 ± 0.81 | 3.48 ± 0.74 3.29 ± 0.69 3.26 ± 0.79 | 3.14 ± 1.00 3.57 ± 0.89 3.51 ± 0.82 | 0.111 0.116 0.124 |
Data are mean ± SD.
P value statistically significant at <0.05.
Self-Care
The mean subscale score for self-monitoring glucose in T1 was significantly higher among women with type 1 diabetes compared with those with type 2 diabetes (6.68 ± 0.70 vs. 6.12 ± 1.26, P = 0.03). The mean subscale score for diet in T3 was significantly higher among women with type 1 diabetes compared with those with type 2 diabetes (4.08 ± 1.16 vs. 3.59 ± 1.06, P = 0.03). There were no other statistically significant differences in self-care scores in women with type 1 diabetes compared with those with type 2 diabetes (Table 3).
Care Satisfaction
The mean care satisfaction score improved for the whole cohort from 3.32 ± 0.88 in T1 to 3.39 ± 0.81 in T3. There were no statistically significant differences in care satisfaction scores in women with type 1 compared with those with type 2 diabetes (Table 3).
Self-Management Predictors of Glycemic Control
We used linear mixed-effects modeling to examine self-efficacy, self-care, and care satisfaction (independent variables) as predictors of A1C (dependent variable). After adjustment for confounders, self-efficacy significantly predicted glycemic control for women with type 2 diabetes and was associated with a mean change in A1C of −0.22% (95% CI −0.42 to −0.02, P = 0.03) per unit increase in scale. The exercise subscore of self-care significantly predicted glycemic control for women with type 1 diabetes after adjustment for confounders and was associated with a mean change in A1C of −0.11% (95% CI −0.22 to −0.01, P = 0.04) per unit increase in scale. Other factors that significantly predicted A1C after adjustment for confounders were baseline characteristics, including ethnicity (P = 0.01–0.04) and education level (P <0.001) (Table 4).
Predictors of A1C, Stratified by Type of Diabetes
| . | Total (n = 111) . | Type 1 Diabetes (n = 55) . | Type 2 Diabetes (n = 56) . | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Unadjusted . | Adjusted† . | P . | Unadjusted . | Adjusted† . | P . | Unadjusted . | Adjusted† . | P . | |
| SED scale | −0.18* (−0.31 to −0.05) | −0.06 (−0.19 to 0.07) | 0.339 | −0.16 (−0.34 to 0.03) | 0.01 (−0.19 to 0.19) | 0.989 | −0.22* (−0.40 to −0.04) | −0.22* (−0.42 to −0.02) | 0.034 |
| SDSCA scale | |||||||||
| Diet, general | −0.19 (−0.31 to −0.08)* | −0.08 (−0.19 to 0.03) | 0.175 | −0.18 (−0.32 to −0.04)* | −0.11 (−0.24 to 0.03) | 0.111 | −0.21 (−0.39 to −0.03)* | −0.04 (−0.03 to 0.15) | 0.667 |
| Diet, specific | 0.09 (−0.22 to 0.03) | −0.05 (−0.17 to 0.07) | 0.414 | −0.11 (−0.23 to 0.48) | −0.09 (−0.25 to 0.08) | 0.306 | −0.11 (−0.29 to 0.07) | −0.05 (−0.22 to 0.12) | 0.579 |
| Exercise | −0.07 (−0.16 to 0.02) | −0.07 (−0.16 to 0.01) | 0.084 | −0.09 (−0.20 to 0.02) | −0.11 (−0.22 to −0.01)* | 0.037 | −0.04 (−0.18 to 0.09) | −0.06 (−0.19 to 0.08) | 0.431 |
| Glucose monitoring | −0.06 (−0.22 to 0.10) | 0.05 (−0.10 to 0.20) | 0.525 | −0.21 (−0.52 to 0.10) | −0.07 (−0.40 to 0.27) | 0.692 | −0.05 (−0.25 to 0.15) | 0.09 (−0.08 to 0.28) | 0.282 |
| Foot care | −0.02 (−0.09 to 0.05) | −0.03 (−0.10 to 0.04) | 0.422 | −0.07 (−0.17 to 0.02) | 0.08 (−0.17 to 0.01) | 0.08 | 0.04 (−0.09 to 0.16) | 0.06 (−0.05 to 0.18) | 0.283 |
| PACIC scale | −0.08 (−0.28 to 0.11) | −0.07 (−0.25 to 0.12) | 0.482 | 0.20 (−0.09 to 0.50) | 0.07 (−0.22 to 0.36) | 0.611 | −0.17 (−0.44 to 0.10) | −0.19 (−0.45 to 0.07) | 0.155 |
| Age, years | −0.07 (−0.11 to −0.04)** | −0.03 (−0.06 to 0.01) | 0.168 | −0.07 (−0.12 to −0.02)* | −0.02 (−0.07 to 0.04) | 0.585 | −0.07 (−0.13 to −0.01)* | 0.04 (−0.03 to 0.10) | 0.262 |
| Diabetes duration, years | −0.02 (−0.03 to 0.02) | 0.01 (−0.01 to 0.04) | 0.305 | −0.02 (−0.05 to 0.02) | −0.01 (−0.04 to 0.04) | 0.874 | −0.03 (−0.09 to 0.02) | −0.02 (−0.06 to 0.02) | 0.380 |
| Ethnicity | |||||||||
| European | Reference | Reference | Reference | Reference | Reference | Reference | |||
| African | −0.42 (−2.02 to 1.18) | −0.51 (−2.24 to 1.22) | 0.561 | −0.62 (−2.21 to 0.98) | −0.74 (−2.48 to 0.99) | 0.392 | — | — | |
| East Asian | 2.27 (0.68–3.87)* | 3.19 (1.00–5.39)* | 0.005 | 0.79 (−1.32 to 2.90) | —‡ | 4.18 (1.79–6.57)** | —‡ | ||
| Hispanic | 0.13 (−1.87 to 2.12) | −2.80 (−4.97 to −0.64)* | 0.012 | — | — | 0.38 (−1.54 to 2.29) | −2.64 (−0.04 to 3.04) | 0.055 | |
| Middle Eastern | 1.61 (0.01–3.21)* | 1.47 (0.09–2.85)* | 0.038 | 0.44 (−1.68 to 2.55) | —‡ | 3.28 (0.89–5.67)* | −2.64 (−4.95 to −0.34)* | 0.026 | |
| South Asian | −0.85 (−1.97 to 0.27) | −0.75 (−1.69 to 0.20) | 0.122 | — | — | −0.55 (−1.66 to 0.56) | −0.17 (−1.47 to 1.13) | 0.796 | |
| Indigenous | −0.59 (−1.63 to 0.46) | −1.27 (−2.17 to −0.36)* | 0.007 | — | — | −0.29 (−1.32 to 0.73) | 0.20 (−0.84 to 1.12) | 0.693 | |
| Unsure | 0.79 (−0.62 to 2.22) | 0.84 (−0.29 to 1.96) | 0.142 | −0.21 (−2.23 to 1.80) | 0.36 (−1.22 to 1.94) | 0.641 | 1.84 (−0.07 to 3.76) | 1.50 (−0.04 to 3.04) | 0.055 |
| Other | −0.49 (−1.77 to 0.79) | −0.52 (−1.59 to 0.56) | 0.342 | 0.19 (−1.93 to 2.29) | −1.64 (−3.50 to 0.22) | 0.082 | −0.64 (−2.20 to 0.93) | −0.43 (−1.75 to 0.88) | 0.509 |
| Education level | |||||||||
| Grade school | Reference | Reference | — | — | Reference | Reference | |||
| High school | −1.20 (−2.34 to −0.07)* | −2.30 (−3.64 to −0.97)** | <0.001 | 1.44 (0.87–2.01)** | 0.53 (−0.38 to 1.45) | 0.242 | −1.53 (−2.76 to −0.30)* | −3.63 (−5.09 to −2.18)** | <0.001 |
| College/trade | −2.03 (−3.12 to −0.93)** | −2.81 (−4.16 to −1.46)** | <0.001 | −2.25 (−3.38 to −1.12)** | 0.53 (−0.13 to 1.19) | 0.110 | −2.25 (−3.38 to −1.12)** | −3.90 (−5.37 to −2.44)** | <0.001 |
| University | −2.50 (−3.61 to −1.39)** | −3.36 (−4.79 to −1.93)** | <0.001 | Reference | Reference | −2.82 (−4.06 to −1.59)** | −4.39 (−6.00 to −2.78)** | <0.001 | |
| Other | −1.51 (−3.65 to 0.63) | −2.48 (−4.69 to −0.27)* | 0.028 | 0.91 (−0.79 to 2.59) | —‡ | — | — | ||
| Household income, $ | |||||||||
| <20,000 | Reference | Reference | Reference | Reference | Reference | Reference | |||
| 20,001–40,000 | 0.09 (−0.69 to 0.89) | 0.15 (−0.61 to 0.92) | 0.690 | 0.20 (−0.85 to 1.25) | 0.39 (−0.69 to 1.46) | 0.471 | 0.15 (−0.99 to 1.29) | 0.67 (−0.37 to 1.70) | 0.195 |
| 40,001–60,000 | −0.49 (−1.41 to 0.42) | −0.09 (−0.98 to 0.79) | 0.835 | −0.91 (−1.98 to 0.17) | −0.31 (−1.43 to 0.82) | 0.577 | −0.39 (−1.90 to 1.12) | 0.40 (−1.07 to 1.87) | 0.581 |
| 60,001–80,000 | −0.25 (−1.08 to 0.59) | 0.02 (−0.82 to 0.86) | 0.975 | −0.85 (−1.88 to 0.18) | −0.07 (−1.15 to 0.99) | 0.885 | 0.23 (−1.05 to 1.49) | 0.69 (−0.51 to 1.91) | 0.249 |
| 80,001–100,000 | −0.77 (−1.59 to 0.06) | −0.15 (−1.02 to 0.72) | 0.734 | −1.15 (−2.16 to −0.13)* | −0.04 (−1.18 to 1.11) | 0.946 | −0.54 (−1.81 to 0.73) | 0.27 (−1.08 to 1.62) | 0.681 |
| >100,000 | −0.84 (−1.64 to −0.05)* | 0.01 (−0.87 to 0.88) | 0.989 | −1.19 (−2.19 to −0.21)* | −0.09 (−1.29 to 1.09) | 0.872 | −0.63 (−1.82 to 0.57) | 0.38 (−0.88 to 1.64) | 0.543 |
| Insurance coverage | |||||||||
| None | Reference | Reference | Reference | Reference | Reference | Reference | |||
| ADP | −0.31 (−0.95 to 0.33) | 0.18 (−0.49 to 0.84) | 0.599 | −0.41 (−1.32 to 0.50) | −0.24 (−1.36 to 0.88) | 0.661 | −1.06 (−2.84 to 0.72) | −0.17 (−1.90 to 1.56) | 0.841 |
| Third party | −0.31 (−0.91 to 0.29) | 0.09 (−0.48 to 0.66) | 0.758 | −0.33 (−1.27 to 0.61) | −0.25 (−1.34 to 0.84) | 0.642 | −0.37 (−1.12 to 0.39) | 0.14 (−0.67 to 0.96) | 0.739 |
| Other | 0.52 (−0.16 to 1.19) | 0.76 (0.16–1.36)* | 0.013 | 1.19 (0.19–2.19)* | 1.34 (−0.19 to 2.66) | 0.087 | −0.21 (−1.13 to 0.72) | −0.40 (−1.25 to 0.45) | 0.344 |
| . | Total (n = 111) . | Type 1 Diabetes (n = 55) . | Type 2 Diabetes (n = 56) . | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Unadjusted . | Adjusted† . | P . | Unadjusted . | Adjusted† . | P . | Unadjusted . | Adjusted† . | P . | |
| SED scale | −0.18* (−0.31 to −0.05) | −0.06 (−0.19 to 0.07) | 0.339 | −0.16 (−0.34 to 0.03) | 0.01 (−0.19 to 0.19) | 0.989 | −0.22* (−0.40 to −0.04) | −0.22* (−0.42 to −0.02) | 0.034 |
| SDSCA scale | |||||||||
| Diet, general | −0.19 (−0.31 to −0.08)* | −0.08 (−0.19 to 0.03) | 0.175 | −0.18 (−0.32 to −0.04)* | −0.11 (−0.24 to 0.03) | 0.111 | −0.21 (−0.39 to −0.03)* | −0.04 (−0.03 to 0.15) | 0.667 |
| Diet, specific | 0.09 (−0.22 to 0.03) | −0.05 (−0.17 to 0.07) | 0.414 | −0.11 (−0.23 to 0.48) | −0.09 (−0.25 to 0.08) | 0.306 | −0.11 (−0.29 to 0.07) | −0.05 (−0.22 to 0.12) | 0.579 |
| Exercise | −0.07 (−0.16 to 0.02) | −0.07 (−0.16 to 0.01) | 0.084 | −0.09 (−0.20 to 0.02) | −0.11 (−0.22 to −0.01)* | 0.037 | −0.04 (−0.18 to 0.09) | −0.06 (−0.19 to 0.08) | 0.431 |
| Glucose monitoring | −0.06 (−0.22 to 0.10) | 0.05 (−0.10 to 0.20) | 0.525 | −0.21 (−0.52 to 0.10) | −0.07 (−0.40 to 0.27) | 0.692 | −0.05 (−0.25 to 0.15) | 0.09 (−0.08 to 0.28) | 0.282 |
| Foot care | −0.02 (−0.09 to 0.05) | −0.03 (−0.10 to 0.04) | 0.422 | −0.07 (−0.17 to 0.02) | 0.08 (−0.17 to 0.01) | 0.08 | 0.04 (−0.09 to 0.16) | 0.06 (−0.05 to 0.18) | 0.283 |
| PACIC scale | −0.08 (−0.28 to 0.11) | −0.07 (−0.25 to 0.12) | 0.482 | 0.20 (−0.09 to 0.50) | 0.07 (−0.22 to 0.36) | 0.611 | −0.17 (−0.44 to 0.10) | −0.19 (−0.45 to 0.07) | 0.155 |
| Age, years | −0.07 (−0.11 to −0.04)** | −0.03 (−0.06 to 0.01) | 0.168 | −0.07 (−0.12 to −0.02)* | −0.02 (−0.07 to 0.04) | 0.585 | −0.07 (−0.13 to −0.01)* | 0.04 (−0.03 to 0.10) | 0.262 |
| Diabetes duration, years | −0.02 (−0.03 to 0.02) | 0.01 (−0.01 to 0.04) | 0.305 | −0.02 (−0.05 to 0.02) | −0.01 (−0.04 to 0.04) | 0.874 | −0.03 (−0.09 to 0.02) | −0.02 (−0.06 to 0.02) | 0.380 |
| Ethnicity | |||||||||
| European | Reference | Reference | Reference | Reference | Reference | Reference | |||
| African | −0.42 (−2.02 to 1.18) | −0.51 (−2.24 to 1.22) | 0.561 | −0.62 (−2.21 to 0.98) | −0.74 (−2.48 to 0.99) | 0.392 | — | — | |
| East Asian | 2.27 (0.68–3.87)* | 3.19 (1.00–5.39)* | 0.005 | 0.79 (−1.32 to 2.90) | —‡ | 4.18 (1.79–6.57)** | —‡ | ||
| Hispanic | 0.13 (−1.87 to 2.12) | −2.80 (−4.97 to −0.64)* | 0.012 | — | — | 0.38 (−1.54 to 2.29) | −2.64 (−0.04 to 3.04) | 0.055 | |
| Middle Eastern | 1.61 (0.01–3.21)* | 1.47 (0.09–2.85)* | 0.038 | 0.44 (−1.68 to 2.55) | —‡ | 3.28 (0.89–5.67)* | −2.64 (−4.95 to −0.34)* | 0.026 | |
| South Asian | −0.85 (−1.97 to 0.27) | −0.75 (−1.69 to 0.20) | 0.122 | — | — | −0.55 (−1.66 to 0.56) | −0.17 (−1.47 to 1.13) | 0.796 | |
| Indigenous | −0.59 (−1.63 to 0.46) | −1.27 (−2.17 to −0.36)* | 0.007 | — | — | −0.29 (−1.32 to 0.73) | 0.20 (−0.84 to 1.12) | 0.693 | |
| Unsure | 0.79 (−0.62 to 2.22) | 0.84 (−0.29 to 1.96) | 0.142 | −0.21 (−2.23 to 1.80) | 0.36 (−1.22 to 1.94) | 0.641 | 1.84 (−0.07 to 3.76) | 1.50 (−0.04 to 3.04) | 0.055 |
| Other | −0.49 (−1.77 to 0.79) | −0.52 (−1.59 to 0.56) | 0.342 | 0.19 (−1.93 to 2.29) | −1.64 (−3.50 to 0.22) | 0.082 | −0.64 (−2.20 to 0.93) | −0.43 (−1.75 to 0.88) | 0.509 |
| Education level | |||||||||
| Grade school | Reference | Reference | — | — | Reference | Reference | |||
| High school | −1.20 (−2.34 to −0.07)* | −2.30 (−3.64 to −0.97)** | <0.001 | 1.44 (0.87–2.01)** | 0.53 (−0.38 to 1.45) | 0.242 | −1.53 (−2.76 to −0.30)* | −3.63 (−5.09 to −2.18)** | <0.001 |
| College/trade | −2.03 (−3.12 to −0.93)** | −2.81 (−4.16 to −1.46)** | <0.001 | −2.25 (−3.38 to −1.12)** | 0.53 (−0.13 to 1.19) | 0.110 | −2.25 (−3.38 to −1.12)** | −3.90 (−5.37 to −2.44)** | <0.001 |
| University | −2.50 (−3.61 to −1.39)** | −3.36 (−4.79 to −1.93)** | <0.001 | Reference | Reference | −2.82 (−4.06 to −1.59)** | −4.39 (−6.00 to −2.78)** | <0.001 | |
| Other | −1.51 (−3.65 to 0.63) | −2.48 (−4.69 to −0.27)* | 0.028 | 0.91 (−0.79 to 2.59) | —‡ | — | — | ||
| Household income, $ | |||||||||
| <20,000 | Reference | Reference | Reference | Reference | Reference | Reference | |||
| 20,001–40,000 | 0.09 (−0.69 to 0.89) | 0.15 (−0.61 to 0.92) | 0.690 | 0.20 (−0.85 to 1.25) | 0.39 (−0.69 to 1.46) | 0.471 | 0.15 (−0.99 to 1.29) | 0.67 (−0.37 to 1.70) | 0.195 |
| 40,001–60,000 | −0.49 (−1.41 to 0.42) | −0.09 (−0.98 to 0.79) | 0.835 | −0.91 (−1.98 to 0.17) | −0.31 (−1.43 to 0.82) | 0.577 | −0.39 (−1.90 to 1.12) | 0.40 (−1.07 to 1.87) | 0.581 |
| 60,001–80,000 | −0.25 (−1.08 to 0.59) | 0.02 (−0.82 to 0.86) | 0.975 | −0.85 (−1.88 to 0.18) | −0.07 (−1.15 to 0.99) | 0.885 | 0.23 (−1.05 to 1.49) | 0.69 (−0.51 to 1.91) | 0.249 |
| 80,001–100,000 | −0.77 (−1.59 to 0.06) | −0.15 (−1.02 to 0.72) | 0.734 | −1.15 (−2.16 to −0.13)* | −0.04 (−1.18 to 1.11) | 0.946 | −0.54 (−1.81 to 0.73) | 0.27 (−1.08 to 1.62) | 0.681 |
| >100,000 | −0.84 (−1.64 to −0.05)* | 0.01 (−0.87 to 0.88) | 0.989 | −1.19 (−2.19 to −0.21)* | −0.09 (−1.29 to 1.09) | 0.872 | −0.63 (−1.82 to 0.57) | 0.38 (−0.88 to 1.64) | 0.543 |
| Insurance coverage | |||||||||
| None | Reference | Reference | Reference | Reference | Reference | Reference | |||
| ADP | −0.31 (−0.95 to 0.33) | 0.18 (−0.49 to 0.84) | 0.599 | −0.41 (−1.32 to 0.50) | −0.24 (−1.36 to 0.88) | 0.661 | −1.06 (−2.84 to 0.72) | −0.17 (−1.90 to 1.56) | 0.841 |
| Third party | −0.31 (−0.91 to 0.29) | 0.09 (−0.48 to 0.66) | 0.758 | −0.33 (−1.27 to 0.61) | −0.25 (−1.34 to 0.84) | 0.642 | −0.37 (−1.12 to 0.39) | 0.14 (−0.67 to 0.96) | 0.739 |
| Other | 0.52 (−0.16 to 1.19) | 0.76 (0.16–1.36)* | 0.013 | 1.19 (0.19–2.19)* | 1.34 (−0.19 to 2.66) | 0.087 | −0.21 (−1.13 to 0.72) | −0.40 (−1.25 to 0.45) | 0.344 |
Data are mean change (95% CI).
Statistically significant at P <0.05.
Statistically significant at P <0.001.
Adjusted for participant age, diabetes duration, ethnicity, education level, household income, and insurance coverage.
Only one participant; no adjusted value reported.
Discussion
This study explored trends in glycemic control during pregnancy; assessed self-efficacy, self-care, and care satisfaction; and examined these factors as predictors of glycemic control among a cohort of women with type 1 or type 2 diabetes receiving obstetrical care at a tertiary center in Ontario, Canada. We found that the overall cohort achieved an A1C of ≤6.5% by T2 and maintained this target in T3. In both T2 and T3, women with type 1 diabetes had a higher mean A1C than did women with type 2 diabetes (mean A1C at T2 6.72% and at T3 6.60% for type 1 diabetes vs. mean A1C at T2 6.08% and at T3 6.12% for type 2 diabetes). The difference may be clinically significant, as a 0.5% reduction in A1C has been deemed clinically meaningful (33).
A previous population-based cohort study in Ontario reported on-target A1C by midpregnancy (mean A1C 6.4 ± 1.1%) among women with preexisting diabetes in pregnancy (34). However, the authors did not stratify A1C by diabetes type. Thus, we do not know whether there was a difference in glycemic control between those with type 1 versus type 2 diabetes. Diabetes duration may contribute to insulin resistance (35). The longer duration of diabetes and insulin resistance among women with type 1 versus type 2 diabetes may have contributed to their higher mean A1C.
Furthermore, the goal for women with type 1 diabetes is to target A1C as low as is safely possible while also avoiding frequent and severe hypoglycemia (15). Therefore, avoidance of hypoglycemia may have contributed to the higher mean A1C among women with type 1 versus type 2 diabetes. However, we did not collect data on the occurrence of hypoglycemia within this cohort.
Maternal self-efficacy improved from T1 to T3. There was some variation in maternal self-care from T1 to T3. For example, the score for the foot care subscale increased for the entire cohort from 2.56 in T1 to 2.72 in T2 and to 2.99 in T3. However, the score for the general diet subscale increased from 4.89 to 4.96 from T1 to T2 but then decreased to 4.84 in T3. Maternal care satisfaction improved from T1 to T3 in the entire cohort and among women with type 2 diabetes. However, care satisfaction decreased from T1 to T3 among women with type 1 diabetes. None of the self-management variable scores have a cutoff value. Thus, we cannot comment on whether women reached a target score. However, all of the mean questionnaire scores among our cohort appear to have been relatively high. With maximum possible scores of 10 and 5 for self-efficacy and care satisfaction, respectively (28,32), the overall mean scores in our cohort by T3 were 7.96 ± 1.20 and 3.39 ± 0.81, respectively. For self-care, the subscale scores for glucose monitoring and diet were significantly higher at T1 and T3, respectively, for women with type 1 diabetes compared with those with type 2 diabetes. Given their clinical heterogeneity, a significantly higher percentage of women with type 2 diabetes used oral medications to manage diabetes compared with women with type 1 diabetes, who exclusively used insulin injections or insulin pump therapy. Insulin has a higher risk for hypoglycemia than do oral medications; that higher risk may have contributed to the higher frequency of glucose monitoring in the group with greater insulin use.
After adjustment for confounders, increased self-efficacy was significantly associated with improved glycemic control for women with type 2 diabetes, and the exercise subscore of self-care was significantly associated with improved glycemic control for women with type 1 diabetes. Transitioning to parenthood, in general, is associated with intentions to make positive lifestyle changes such as increasing healthy eating (36). Thus, women may be motivated during pregnancy to optimize glycemia for the well-being of their infant. Participant interviews could explore this finding and further examine the impact of impending parenthood on diabetes self-management and glycemic control during pregnancy (37).
Several baseline factors, including level of education, income, insurance status, and ethnicity, significantly predicted glycemic control. Having a household income between $81,000 and $100,000 was associated with a mean change in A1C of −1.15% (95% CI −2.16 to −0.13%) among women with type 1 diabetes. Having a household income >$100,000 was associated with a mean change in A1C of −0.84% (95% CI −1.64 to −0.05%) for the entire cohort and a mean change in A1C of −1.19% (95% CI −2.19 to −0.21%) for women with type 1 diabetes. Having insurance other than ADP or a third-party payer was associated with a mean change in A1C of 0.76% (95% CI 0.16–1.36%) for the entire cohort and a mean change in A1C of 1.19% (95% CI 0.19–2.19%) for women with type 1 diabetes. Being of East Asian ethnicity was associated with a mean change in A1C of 3.19% (95% CI 1.00–5.39%) for the entire cohort and a mean change in A1C of 4.18% (95% CI 1.79–6.57%) for women with type 2 diabetes. Hispanic ethnicity was associated with a mean change in A1C of −2.80% (95% CI −4.97 to −0.64%) for the entire cohort. Having a Middle Eastern background was associated with a mean change in A1C of 0.47% (95% CI 0.09–2.85%) for the entire cohort and a mean change in A1C of −2.64% (95% CI −4.95 to −0.34%) for women with type 2 diabetes. Being of Indigenous ethnicity was associated with a mean change in A1C of −1.27% (95% CI −2.17 to −0.36%) for the entire cohort. These findings correlate with existing literature that demonstrates a negative association between social determinants of health and glycemic control (18,19).
Strengths and Limitations
Our study had a number of strengths. First, women with preexisting type 1 or type 2 diabetes make up only about one-fifth of those with diabetes in pregnancy. Although this is a small population, we amassed a comparatively large data set by recruiting women over 5 years. In addition, the tertiary center from which we recruited is the regional center for all women with type 1 or type 2 diabetes in pregnancy, encompassing two regional health networks.
Our study also has several limitations. First, we observed a higher mean A1C in T1 than is recommended in the preconception period (<7% and ideally <6.5%) (15). We also noted that mean A1C in T1 was lower among women with type 1 diabetes than among those with type 2 diabetes. Lower A1C may have occurred if more women with type 1 diabetes received preconception care and counseling, as this is more commonly provided for those with type 1 versus type 2 diabetes (38). However, we did not inquire about preconception care, which is a significant limitation of our study. Furthermore, we did not collect data on baseline diabetes complications, BMI, pre-pregnancy A1C, hypoglycemia, or the number of missed medications, which are further limitations. The lack of data on pregnancy outcomes is another limitation, as the recommended glycemic targets in pregnancy have been established to improve perinatal outcomes (15). Although it is well established that achieving target A1C reduces the occurrence of perinatal morbidity and mortality (15), it would have been valuable to link our data on self-management behaviors and perinatal maternal glycemia to pregnancy outcomes. Finally, the study relied on self-reported data, which may be affected by social desirability and recall bias. To address recall bias, we attempted to make the recall period short (≤6 months) and the duration of the overall study relatively short (over the 9 months of pregnancy), thus addressing factors that are known to be related to impact recall bias (39).
Conclusion
In this cohort of expectant mothers with type 1 or type 2 diabetes, we demonstrated that glycemic control improved and reached target as pregnancy progressed. Self-efficacy, self-care, and care satisfaction also improved, remaining relatively high from T1 to T3. Furthermore, the self-management variables self-efficacy and self-care were significant predictors of A1C. Specifically, self-efficacy was associated with a mean change in A1C of −0.22% (95% CI −0.42 to −0.02) per unit increase in scale among women with type 2 diabetes.
The data from this cohort provide valuable insight for future studies; therefore, we have several forthcoming projects that will build on the results reported here. First, we plan to continue recruitment to expand the cohort. However, we foresee augmenting our methods to incorporate the collection of data on preconception care and hypoglycemia. Furthermore, as continuous glucose monitoring is now widely used, particularly among women with type 1 diabetes, we plan to collect data from these devices, when available, to provide additional glycemic control outcomes. We also plan to link collected perinatal data with pregnancy outcomes, including fetal outcomes. Finally, we aim to conduct a qualitative study to further explore findings from the current study as well as to examine the experience of managing diabetes during pregnancy and identify diabetes self-management education and support needs among expectant mothers with type 1 or type 2 diabetes.
Article Information
Acknowledgments
The authors acknowledge the contributions of Marilynne Oskamp and Dr. Barbara Brennan of McMaster University in Hamilton, Ontario, Canada, and the participants of the study.
Funding
This study received funding from Hamilton Health Sciences through Research Early Career Support, the Registered Nurses Foundation of Ontario, the Canadian Nurses Foundation, and, for D.S., the Heather M. Arthur Population Health Research Institute/Hamilton Health Sciences Chair in Interprofessional Health Research.
Duality of Interest
No potential conflicts of interest relevant to this article were reported.
Author Contributions
K.S., H.T.M., and D.S. conceptualized the study and developed the methodology. K.S. and H.T.M. curated the data. K.S. wrote the manuscript, and all authors reviewed and edited the manuscript and approved it for submission. K.S. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
