Use of dietetic services among pregnant women with gestational diabetes in the UAE: Prevalence,correlates,and patient experiences

Abstract

Background

Dietetic care plays a crucial role in the management of Gestational Diabetes Mellitus (GDM). Little is known about its utilization in the United Arab Emirates (UAE).

Objective

This study assessed the prevalence, correlates, and patient experiences of the use of dietetic services among pregnant women with GDM.

Design

A cross-sectional study was conducted in six hospitals (public and private) in the Emirates of Dubai, Sharjah, and Ajman, between May and November 2024.

Methods

A total of 223 pregnant women, aged 18–45 years, in their third trimester with a confirmed GDM diagnosis, were recruited. Data were collected using a multicomponent questionnaire and medical record reviews. The main outcome in this study was visiting a dietitian following GDM diagnosis (yes/no). Descriptive, bivariate, and multiple logistic regression analyses identified factors associated with dietitian visits.

Results

Of the 223 participants, 93 visited a dietitian (41.7%); of whom 92 (99%) were referred by a physician. Examining the sociodemographic, lifestyle and health related factors showed that daily breakfast consumption (aOR=3.3, p=0.009), initiating exercise post-diagnosis (aOR=3.9, p=0.012), sleeping ≥8 hours/night (aOR=3.2, p=0.004), previous history of GDM (aOR=2.7, p=0.039), and family history of GDM (aOR=3.2, p=0.009) were associated with higher odds of visiting the dietitian. Non-Emirati nationality (aOR=0.3, p=0.004), GDM medication use (aOR=0.3, p=0.007), and perceiving health as good/excellent (aOR=0.3, p=0.030) were inversely associated with visiting the dietitian. Among participants who visited the dietitian, the majority were either very satisfied (16.1%) or satisfied (63.4%), with only 3% reporting dissatisfaction with their visit to the dietitian.

Conclusion

A considerable proportion of women with GDM did not visit the dietitian, with physician referral being the most influential factor of dietitian visits. Dietitian consultations are associated with healthier behaviors and high satisfaction, emphasizing their critical role in GDM care. Promoting access to dietetic care, including strengthening referral systems, is needed to improve pregnancy outcomes and reduce future disease burden in mothers and children.

Plain language summary

Gestational diabetes mellitus (GDM) is a common condition during pregnancy that can affect both mothers and babies. Diet and lifestyle changes are the main treatment, and dietitians are key in providing this support. Yet, little is known about how often women in the United Arab Emirates (UAE) actually use dietitian services. In this study, we surveyed 223 pregnant women with GDM across six hospitals in Dubai, Sharjah, and Ajman. We examined not only how many women visited a dietitian but also what factors encouraged or discouraged these visits, and how women felt about the care they received. We found that fewer than half of the women (42%) saw a dietitian, and nearly all of them did so only when referred by a doctor. Women who had healthier daily habits or a history of GDM were more likely to visit, while non-Emirati women, those on GDM medication, and those who believed they were already in good health were less likely to go. Importantly, most women who did attend reported being satisfied or very satisfied with their dietitian visits. This is the first study in the UAE to explore both the use of dietitian services and women’s experiences of care in GDM. Our findings highlight the need for stronger referral systems and better access to dietetic care. By addressing these gaps, healthcare providers can improve pregnancy outcomes and reduce future health risks for mothers and children.

Keywords

gestational diabetes mellitus dietitian referral maternal nutrition pregnancy outcomes United Arab Emirates dietetic services utilization

Introduction

Gestational Diabetes Mellitus (GDM) is a common complication of pregnancy, characterized by glucose intolerance during gestation. According to the International Diabetes Federation, approximately 14.7% of pregnancies worldwide are affected by GDM, with the highest regional prevalence observed in the Middle East and North Africa at 27.6%.¹ Women with GDM face a heightened risk of metabolic syndrome, cardiovascular disease, and future Type 2 Diabetes Mellitus (T2DM), with an estimated 20% to 50% at risk of developing T2DM later in life.^2,3 Meanwhile, infants born to mothers with GDM are at increased risk of several adverse outcomes, including preterm birth, macrosomia, neonatal hypoglycemia, and long-term risks of obesity, T2DM, and cardiovascular diseases.^4–6

Although GDM poses significant risks to both maternal and infant health, it is a manageable condition, particularly when diagnosed early and treated with lifestyle modifications. Dietary intake modification is recognized as one of the most effective and modifiable strategies, with clinical practice guidelines universally endorsing it as the first-line treatment for GDM.^7,8 A substantial body of evidence supports the use of low glycemic index diets, demonstrating their efficacy in improving postprandial glycemic control and reducing the incidence of macrosomia without adverse maternal or fetal outcomes.^9–12 Based on this evidence, the WHO strongly recommends maternal nutrition counseling during antenatal and postnatal care for all women, regardless of their nutritional status.¹³ In addition to the WHO, professional organizations including the American Diabetes Association, the American College of Obstetricians and Gynecologists, and Diabetes Canada recommend individualized, carbohydrate-controlled meal plans that emphasize low-to-moderate glycemic index foods, adequate protein intake, moderate fat consumption, and sufficient dietary fiber.¹⁴

For dietary interventions to be effective, they must be practical, clearly communicated, and tailored to the needs of the target population. Dietitians play a critical role in this process, given their specialized training in delivering individualized nutritional counseling and facilitating sustainable dietary behavior change.¹⁵ Evidence from the Academy of Nutrition and Dietetics supports the effectiveness of dietary interventions delivered by dietitians in improving clinical outcomes in several cardiometabolic conditions, including diabetes, dyslipidemia, and hypertension.^16–18 In the context of GDM, dietetic interventions have been associated with improved outcomes for both mothers and neonates. For instance, a randomized clinical trial involving 25 sites demonstrated that dietitians’ implementation of nutrition practice guidelines correlated with decreased insulin requirements and improved glycated hemoglobin levels in women with GDM.¹⁹ Moreover, a large retrospective cohort study of 1,185 women with GDM found that those receiving dietitian consultations exhibited significantly lower odds of neonatal intensive care unit admissions, underscoring the beneficial impact of dietetic care on neonatal health outcomes.²⁰

In the United Arab Emirates (UAE), GDM represents a significant public health challenge where the reported prevalence rates range from 19.1% to 27.1 %,^21,22 considerably higher than the globally reported prevalence of 14.7%.¹ Although dietary intervention constitutes a fundamental component of GDM management, the extent to which dietitians are integrated within routine antenatal care in the UAE remains unclear. Therefore, the primary aim of this study is to examine the prevalence of dietetic consultation among women with GDM in the UAE. In addition, the study seeks to identify various sociodemographic, lifestyle, and health-related characteristics associated with utilization of dietetic services, and to explore women’s experiences and perceived barriers to accessing dietetic care in the country.

Methodology

Study design and settings

A cross-sectional survey of pregnant women with GDM was conducted over six months, from May to November 2024. A two-stage stratified cluster sampling design was employed for subjects’ recruitment. In the first stage, stratification was based on the Emirate (Sharjah, Ajman, and Dubai). In the second stage, clusters (hospitals) within each Emirate were further stratified by hospital sector (public vs. private). From each Emirate, one governmental hospital and one private hospital were randomly selected, resulting in a total of six participating hospitals. In the hospital, pregnant women with GDM were recruited from the antenatal outpatient clinics during their routine follow-up visits. The reporting of this cross-sectional study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement.²³

Study population

The study included a sample of pregnant women aged 18 to 45 years, in their third trimester, with a confirmed diagnosis of GDM. Screening for GDM in the hospitals is routinely carried out in the hospitals during 24–28 weeks of gestation using the National Institute for Health and Care Excellence (NICE) Diabetes in Pregnancy criteria.²⁴ Pregnant women from all pre pregnancy BMI categories were included in the study. Women with multiple pregnancies and other gestational complications, and women with pre-existing T2DM or any other chronic diseases, were excluded from the study.

Sample size

For this study, the minimum required sample size was estimated at 225 participants, based on an assumed prevalence of dietitian visits of 82% among pregnant women with GDM, a 5% margin of error, and a 95% confidence level.²⁵ The prevalence estimate used in the sample size calculations was chosen as the midpoint of previously reported rates, which ranged from 78% to 85.9%.^26,27

Study protocol

Data were collected through face-to-face interviews conducted by trained research assistants (RAs). Pregnant women with GDM were identified by hospital administrative staff during routine prenatal visits. The RAs approached these women and screened them for eligibility, explained the study objectives and procedures in detail, and invited them to participate. All interviews were conducted in a private setting to ensure confidentiality. The study was approved by the Research Ethics Committees at the University of Sharjah (Reference No. REC-22-01-03-02), the Ministry of Health and Prevention (Reference No. MOHAP/DXB-REC/JFF/No.10/2022), and the Dubai Health Authority (Reference No. DSREC-08/2022_10). Written informed consents were obtained from all participants prior to data collection, following a clear explanation of the study objectives and protocol. The RAs underwent comprehensive training to ensure standardized and consistent data collection procedures.

Data collection

Two data sources were used in this study: a multi-component structured questionnaire and participants’ medical records. Data were collected using a multi-component questionnaire, developed based on existing literature and tailored to the UAE context. While no formal quantitative psychometric testing of the developed questionnaire was conducted, several alternative forms of validity were addressed during instrument development. Specifically, content validity was addressed through review by a multidisciplinary expert panel comprising nutritionists, gynecologists, and educators with extensive experience in maternal health in the UAE. The panel evaluated item relevance, comprehensiveness, clarity, and contextual appropriateness. Revisions were incorporated based on structured feedback. In addition, face validity was established during both expert review and pilot testing, ensuring that items were understandable, culturally appropriate, and appeared to measure the intended constructs. Parallel form and translation validity (linguistic and cross-cultural validity) was ensured through forward translation (English to Arabic) followed by back-translation to confirm conceptual equivalence and linguistic accuracy between versions. The practical validity and clarity testing were further supported through the pilot study involving 20 women with GDM. Participants provided feedback regarding clarity, comprehension, and cultural suitability. Minor wording refinements were made accordingly. The pilot participants were not included in the final analysis.

The questionnaire consisted of four sections: the first section included sociodemographic characteristics and pregnancy-related information, such as age, nationality, education (whether it was health-related, medical, or health sciences specialties), employment status, household income, and number of children. The second section included current lifestyle and behavioral factors, focusing on changes since the GDM diagnosis, particularly frequency of breakfast consumption, and whether participants’ eating patterns (meal frequency, timing, and composition) have changed after the diagnosis. Participants were asked if they were current smokers or not (yes, no). Physical activity was evaluated by asking participants whether they exercised regularly (defined as 3–5 times per week), whether they had been exercising before pregnancy or started after GDM diagnosis. For ‘Sleep’, both the number of hours (duration) and the quality were assessed using the following two questions: ‘On average, how may hours of sleep do you get per day (including naps)’ (open ended); ‘Overall, how do you rate the quality of your sleep’: ‘Good’, ‘Moderate’ and ‘Poor’. The number of hours was later categorized as ‘seven hours or less’ and ‘8 hours or more’. The third section covered health and medical history, including self-perceived health status, current medication use, personal and family history of diabetes and GDM, participants’ awareness of GDM health risks, daily blood glucose monitoring post-GDM diagnosis, and perceived best treatment for GDM. The “Perceived general health” was assessed using the following question: “Overall how do you rate your own health”. The possible answers to this question were poor, fair, good, or excellent. Participants were asked whether they were aware that GDM is associated with any health risks and the answers were either yes or no. For ‘the perceived best treatment for GDM’, the question was ‘in your opinion which of the following is considered the best treatment for GDM’, with ‘diet only’, exercise only’, ‘both diet and exercise’, ‘medication/insulin’, as possible answers. The fourth section addressed the use of dietetic services. The main outcome of the study (visiting a dietitian) was evaluated by the following question: Since your diagnosis with GDM, have you visited a dietitian? (Yes/No). In addition, participants were asked whether they had been referred by a physician for dietetic counseling, the time between referral and the first appointment, the mode of service delivery, and the dietitian’s recommendations. Adherence to the recommendations was measured using the following question: “To what extent did you follow the dietitian’s advice regarding dietary and lifestyle modifications?” with three possible answers “Rarely, not at all”, “Partially/sometimes”, and “Most of the time/completely”. Moreover, participants were asked to report the barriers to adherence and overall satisfaction with the dietetic care received. At the end of the interview, RAs retrieved the anthropometric data from the medical records, including height, pre-pregnancy weight, and current body weight. The full questionnaire is provided as Supplementary Material.

Maternal prepregnancy BMI was calculated and categorized according to the WHO classification into: ‘underweight’ (BMI < 18.5 kg/m²), normal weight (BMI: 18.5–24.9 kg/m²), overweight (BMI: 25.0–29.9 kg/m²), and obese (BMI: ≥30.0 kg/m²).^28,29

Gestational Weight Gain Rate (GWGR) was used as an indicator of the adequacy of weight accretion during pregnancy. As per the IOM criteria, GWGR is the rate of weight gain per week after the 12th week of gestation. In this study, women were assumed to have gained an average of 1 kg during the first trimester. This assumption is based on the IOM weight gain recommendation of 0.5– 2 kg over the first trimester.³⁰

The following formula was used to calculate the GWGR:

G W G R = \frac{(Weight taken during the interview - prepregnancy weight) - 1}{gestational age - 12}

The GWGR was then categorized as insufficient, adequate or excessive, as per the IOM recommendations and taking into account the prepregnancy weight.³⁰

Statistical analysis

All analyses were conducted using Stata Version 17. Descriptive statistics were computed to summarize participant characteristics. Categorical variables were reported as frequencies and percentages. The primary outcome was whether the participant visited a dietitian (Yes/No). Bivariate analyses were performed using chi-square tests and simple logistic regressions to examine the association of dietitian visit status with sociodemographic and health-related characteristics, lifestyle and behavioral factors, and medical history variables. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were reported. In addition to ‘age’, the variables with a p-value <0.20 in bivariate analyses were entered into the multiple logistic regression to identify independent factors associated with visiting a dietitian. The final adjusted model included age, nationality, education level, household income, parity (number of children), frequency of breakfast consumption, eating pattern changes after diagnosis, exercise initiation after diagnosis, sleep duration, previous history of GDM, family history of diabetes, family history of GDM, GDM medication use, perceived general health status, knowledge about GDM risks, and perceived best treatment for GDM. Adjusted odds ratios (aORs) with 95% CIs were reported. The final multiple regression model excluded “referral to a dietitian” due to perfect prediction and separation issues, which would distort the estimates of other predictors. Statistical significance was set at p < 0.05.

Results

A total of 275 women diagnosed with GDM were approached. Of these, 229 agreed to participate, response rate 82%. The main reasons for refusing to participate in the study were lack of interest and lack of time. Five women did not meet the inclusion criteria. One participant who consented to take part in the study did not complete the questionnaire and withdrew. As a result, the number of complete questionnaires included in the study was 223 (Figure 1). Figure 2 presents the distribution of ‘referral to the dietitian’ and ‘visit the dietitian’ among study participants. A total of 101 women (45.3%) reported being referred to a dietitian, of whom 92 (91.1%) visited the dietitian. On the other hand, 122 women were not referred to the dietitian with only one of those women visiting the dietitian. (Figure 2). As such ‘referral to a dietitian’ was found to be a strong predictor of use of dietetic services with an OR of 1,237 (95% CI: 154-9937; p < 0.001).

Figure 1.

Participants’ recruitment in the study.

Figure 2.

Dietitian’s referrals and visits among the study sample (n= 223). ^* The odds of visiting a dietitian were significantly higher among those referred compared to those not referred (OR = 1237, 95% CI: 154–9937, p < 0.001).

Figure 3 illustrates the distribution of referrals to ‘Other healthcare practitioners’, among participants who were not referred to the dietitian. A total of 27.9% were referred to a diabetes educator, 13.9% to an internal medicine specialist, 13.1% to a gynecologist, 8.2% to an endocrinologist, and 15.6% provided miscellaneous responses, while 21.3% reported not being referred to any healthcare specialist (Figure 3). The reasons for not visiting the dietitian are illustrated in Figure 4. The most commonly reported reason was that they were already following up with a diabetes educator or another specialist (74.6%). Other reasons included perceiving no need for a dietitian visit (12.3%), difficulty to adhere to diet restrictions (4.6%), scheduling difficulties (3.9%), lack of insurance coverage (1.5%), and other unspecified reasons (3.1%) (Figure 4).

Figure 3.

Referral to other healthcare specialties (n=122) ^*. ^*In this figure, the sample analyzed was that of participants who were referred to ‘other healthcare practitioners’ (n=122), other than the dietician. In this study, the number of participants who were referred to the dietician was 101. These participants (n=101) were not included in the figure

Figure 4.

Reasons for ‘not visiting the dietitian’ in the study sample (n=130).

Table 1 summarizes the sociodemographic and health-related characteristics of participants in association with visiting the dietitian. Nationality showed a strong association, with non-Emirati women being less likely to visit a dietitian compared to Emiratis (OR=0.3, 95% CI: 0.2–0.5). Participants with a university degree were less likely to visit a dietitian compared to those with diploma-level education or below (OR=0.4, 95% CI: 0.2–0.8). Women with higher household income (>15,000 AED) had lower odds of visiting a dietitian (OR=0.6, 95% CI: 0.3–1.0). Parity showed a significant relationship with dietitian visits; those with four or more children were significantly more likely to visit a dietitian compared to primiparous women (OR=3.1, 95% CI: 1.5–6.2). No significant differences were found regarding age, health-related major, employment status, pre-pregnancy BMI, and GWGR with dietitian visits.

Table 1.

Sociodemographic and Health-Related Characteristics of the study population (n=223).

	Dietitian visit
	Total	No	Yes	OR	p-value	95% CI
	n (%)	n (%)	n (%)	OR	p-value	95% CI
Age
18–29	48 (21.52)	27 (20.77)	21 (22.58)	1.0
30–39	130 (58.3)	85 (65.38)	45 (48.39)	0.7	0.264	0.4	1.3
40–49	45 (20.18)	18 (13.85)	27 (29.03)	1.9	0.119	0.9	4.4
Nationality
Emirati	105 (47.1)	45 (34.6)	60 (64.5)	1.0
Other	118 (52.9)	85 (65.4)	33 (35.5)	0.3	<0.001	0.2	0.5
Education
Diploma and below	80 (35.9)	36 (27.7)	44 (47.3)	1.0
University degree	143 (64.1)	94 (72.3)	49 (52.7)	0.4	0.003	0.2	0.8
Health Related Major
No	193 (86.5)	112 (86.2)	81 (87.1)	1.0
Yes	30 (13.5)	18 (13.8)	12 (12.9)	0.9	0.839	0.4	2.0
Employment
Housewife	122 (54.7)	73 (56.2)	49 (52.7)	1.0
Employed	101 (45.3)	57 (43.8)	44 (47.3)	1.2	0.608	0.7	2.0
Income
≤ 15,000 AED	93 (41.7)	47 (36.2)	46 (49.5)	1.0
> 15,000 AED	130 (58.3)	83 (63.8)	47 (50.5)	0.6	0.048	0.3	1.0
Number of Children
Primi	65 (29.1)	42 (32.3)	23 (24.7)	1.0
1-3 children	91 (40.8)	63 (48.5)	28 (30.1)	0.8	0.545	0.4	1.6
4 children and more	67 (30)	25 (19.2)	42 (45.2)	3.1	0.002	1.5	6.2
Pre-pregnancy BMI
Normal/Underweighta	62 (27.8)	35 (26.9)	27 (29)	1.0
Overweight	83 (37.2)	52 (40)	31 (33.3)	0.8	0.451	0.4	1.5
Obese	78 (35)	43 (33.1)	35 (37.6)	1.1	0.986	0.5	2.1
GWGR
Adequate	45 (20.2)	22 (16.9)	23 (24.7)	1.0
Insufficient	56 (25.1)	35 (26.9)	21 (22.6)	0.6	0.172	0.3	1.3
Excessive	122 (54.7)	73 (56.2)	49 (52.7)	0.6	0.207	0.3	1.3

OR = Odds Ratio; CI = Confidence Interval; as derived from simple logistic regression; GWG = Gestational Weight Gain; BMI = Body Mass Index. Odds ratios represent the likelihood of having visited a dietitian (Yes vs. No). A p-value < 0.05 is considered statistically significant.

^aUnderweight (n=4) and Normal weight (N=58).

Table 2 shows lifestyle and behavioral characteristics of the study participants, stratified by dietitian visit. Women who reported modifying their eating patterns following a GDM diagnosis had over three times the odds of visiting a dietitian compared to those who reported making no changes (OR=3.2, 95% CI: 1.2–8.9). After diagnosis, daily breakfast consumption was strongly associated with dietitian visits; women who ate breakfast every day had more than five times the odds of visiting the dietitian compared to those who did not eat breakfast every day (OR=5.1, 95% CI: 2.8–9.4). Initiating exercise after the diagnosis was also linked to a greater likelihood of visiting a dietitian (OR=2.6, 95% CI: 1.2–5.4). In addition, sleeping eight hours or more per night was associated with higher odds of visiting a dietitian compared to sleeping seven hours or less (OR=2.3, 95% CI: 1.3–4.0).

Table 2.

Lifestyle and Behavioral Factors in the study population (n=223).

	Dietitian visit
	Total	No	Yes	OR	p-value	95% CI
	n (%)	n (%)	n (%)	OR	p-value	95% CI
Eating pattern change after the diagnosis
No	25 (11.2)	20 (15.4)	5 (5.4)	1.0
Yes	198 (88.8)	110 (84.6)	88 (94.6)	3.2	0.025	1.2	8.9
Breakfast consumption (since GDM diagnosis)
Not everyday	99 (44.4)	78 (60)	21 (22.6)	1.0
Everyday	124 (55.6)	52 (40)	72 (77.4)	5.1	<0.001	2.8	9.4
Exercise
No	144 (64.6)	92 (70.8)	52 (55.9)	1.0
Yes, I started before GDM	42 (18.8)	23 (17.7)	19 (20.4)	1.5	0.285	0.7	2.9
Yes, I started after GDM	37 (16.6)	15 (11.5)	22 (23.7)	2.6	0.011	1.2	5.4
Sleeping hours
7 hrs. Or less	136 (61)	90 (69.2)	46 (49.5)	1.0
8 hrs. And more	87 (39)	40 (30.8)	47 (50.5)	2.3	0.003	1.3	4.0
Sleep quality
Good	63 (28.3)	35 (26.9)	28 (30.1)	1.0
Moderate	119 (53.4)	67 (51.5)	52 (55.9)	1.0	0.923	0.5	1.8
Poor	41 (18.4)	28 (21.5)	13 (14)	0.6	0.196	0.3	1.3
Smoking
No	220 (98.7)	129 (99.2)	91 (97.8)	1.0
Yes	3 (1.3)	1 (0.8)	2 (2.2)	2.8	0.398	0.3	31.7

OR = Odds Ratio; CI = Confidence Interval as derived from simple logistic regression; GDM = Gestational Diabetes Mellitus. Odds ratios represent the likelihood of having visited a dietitian (Yes vs. No). A p-value < 0.05 is considered statistically significant.

Table 3 presents the health and medical history characteristics of study participants by dietitian visit. Women who had GDM in a previous pregnancy had more than twice the odds of visiting a dietitian compared to those who did not (OR = 2.2, 95% CI: 1.2–4.1). Having close family members with diabetes was also associated with higher odds of a dietitian visit (OR=1.8, 95% CI: 1.0–3.3), as was having close family members with GDM (OR=2.1, 95% CI: 1.2–3.8, p=0.011). Women taking medications for GDM were less likely to visit a dietitian compared to those not on medication (OR=0.5, 95% CI: 0.3–0.9). Moreover, participants who rated their health as good or excellent had significantly lower odds of visiting a dietitian than those reporting poor or fair health (OR=0.4, 95% CI: 0.2–0.8). Participants’ knowledge about the risks and complications of GDM was strongly associated with an increase in the odds of visiting a dietitian (OR=3.1, 95% CI: 1.6–5.9). Participants who perceived either diet or exercise alone as the best treatment for GDM were significantly less likely to visit a dietitian compared to those who considered both diet and exercise as the best treatment (OR=0.4, 95% CI: 0.2–0.8).

Table 3.

Health and medical history in the study population (n=223).

	Dietitian visit
	Total	No	Yes	OR	p-value	95% CI
	n (%)	n (%)	n (%)	OR	p-value	95% CI
Taking medications for any health conditions
No	181 (81.2)	107 (82.3)	74 (79.6)	1.0
Yes	42 (18.8)	23 (17.7)	19 (20.4)	1.2	0.606	0.6	2.4
Had gestational diabetes in a previous pregnancy
No	68 (30.5)	46 (35.4)	22 (23.7)	1.0
Yes	129 (57.8)	63 (48.5)	66 (71)	2.2	0.012	1.2	4.1
First pregnancy	26 (11.7)	21 (16.2)	5 (5.4)	0.5	0.214	0.2	1.5
Have close family members with diabetes
No	72 (32.3)	49 (37.7)	23 (24.7)	1.0
Yes	151 (67.7)	81 (62.3)	70 (75.3)	1.8	0.042	1.0	3.3
Have close family members with GDM
No	153 (68.6)	98 (75.4)	55 (59.1)	1.0
Yes	70 (31.4)	32 (24.6)	38 (40.9)	2.1	0.011	1.2	3.8
Check blood glucose daily upon current diagnosis of GDM
No	24 (10.8)	16 (12.3)	8 (8.6)	1.0
Yes	199 (89.2)	114 (87.7)	85 (91.4)	1.5	0.381	0.6	3.7
Taking any medications for gestational diabetes
No	98 (43.9)	49 (37.7)	49 (52.7)	1.0
Yes	125 (56.1)	81 (62.3)	44 (47.3)	0.5	0.027	0.3	0.9
Perceived general health
Poor/Fair	34 (15.2)	13 (10)	21 (22.6)	1.0
Good/Excellent	189 (84.8)	117 (90)	72 (77.4)	0.4	0.012	0.2	0.8
Awareness about the risks and complications of GDM
No	67 (30)	51 (39.2)	16 (17.2)	1.0
Yes	156 (70)	79 (60.8)	77 (82.8)	3.1	0.001	1.6	5.9
Perceived best GDM treatment
Diet or Exercise	35 (15.7)	26 (20)	9 (9.7)	0.4	0.014	0.2	0.8
Diet & Exercise	123 (55.2)	62 (47.7)	61 (65.6)	1.0
Treatment Including Medication/Insulin	65 (29.1)	42 (32.3)	23 (24.7)	0.6	0.064	0.3	1.0

OR = Odds Ratio; CI = Confidence Interval; as derived from simple logistic regression; GDM = Gestational Diabetes Mellitus. Odds ratios represent the likelihood of having visited a dietitian (Yes vs. No). A p-value < 0.05 is considered statistically significant.

Table 4 depicts the results of the multiple logistic regression analyses exploring adjusted associations with dietitian visits among study participants. In this analysis, physicians’ referrals to a dietitian were excluded due to their perfect prediction of dietitian visits, which led to estimation instability. Accordingly, women of non-Emirati nationality are significantly less likely to visit a dietitian (aOR=0.3; 95% CI: 0.1-0.6). Behavioral and lifestyle factors such as eating breakfast every day after diagnosis (aOR=3.3, 95%CI:1.4-8.0), starting exercise after GDM diagnosis (aOR=3.9, 95% CI: 1.3-11.1), and sleeping eight or more hours per night (aOR=3.2, 95% CI: 1.5-6.9) were all significantly associated with higher odds of visiting a dietitian. Similarly, a history of GDM in a previous pregnancy (aOR=2.7, 95% CI: 1.1-50.5) and having a close family member with GDM (aOR=3.2, 95% CI: 1.4-7.8) were strong predictors. Conversely, taking medications for GDM and women perceiving their health as good or excellent were significantly associated with lower odds of visiting a dietitian (aOR=0.3, 95% CI: 0.1-0.7 and aOR=0.3,95% CI: 0.1-0.9; respectively).

Table 4.

Multiple regression for the associations of various factors with dietitian visit in the study population (n=223).

	aOR	p-value	95% CI
Age
18–29	1.0
30–39	1.3	0.592	0.5	3.5
40–49	2.5	0.162	0.7	8.8
Nationality
Emirati	1.0
Other	0.3	0.004	0.1	0.6
Education
Diploma and below	1.0
University degree	0.8	0.513	0.4	1.7
Income
≤ 15,000 AED	1.0
> 15,000 AED	0.5	0.231	0.2	1.5
Number of Children
Primi	1.0
1-3 children	1.0	0.990	0.3	3.0
4 children and more	3.3	0.057	1.0	11.5
Breakfast (since your GDM diagnosis)
Not everyday	1.0
Everyday	3.3	0.009	1.4	8.0
Eating pattern change after the diagnosis
No	1.0
Yes	2.3	0.231	0.6	8.7
Exercise
No	1.0
Yes, I started before GDM	1.7	0.297	0.6	4.8
Yes, I started after GDM	3.9	0.012	1.3	11.1
Sleeping hours
7 hrs. Or less	1.0
8 hrs. And more	3.2	0.004	1.5	6.9
Had gestational diabetes in a previous pregnancy
No	1.0
Yes	2.7	0.039	1.1	6.7
Have close family member with diabetes
No	1.0
Yes	1.2	0.710	0.5	2.7
Have close family member with GDM
No	1.0
Yes	3.2	0.009	1.4	7.8
Taking any medications for gestational diabetes
No	1.0
Yes	0.3	0.007	0.1	0.7
Perceived general health
Poor/Fair	1.0
Good/Excellent	0.3	0.030	0.1	0.9
Awareness about the risks and complications of GDM
No	1.0
Yes	1.9	0.150	0.8	4.5
Perceived best GDM treatment
Diet or Exercise	0.4	0.132	0.1	1.3
Diet & Exercise	1.0
Medication/Insulin/All of the above	2.2	0.111	0.8	5.6

aOR: Adjusted Odds Ratio. CI: Confidence Interval. AED: United Arab Emirates Dirham. GDM: Gestational Diabetes Mellitus.

The adjusted odds ratios (aORs) were derived from a multivariable logistic regression model controlling for all variables with p < 0.20 in the bivariate analyses, and that all variables presented in the table were entered simultaneously in the adjusted model. Referral to a dietitian was found to be a near-perfect predictor of dietitian visits (crude OR = 1236.9; 95% CI: 153.95–9937.30; p < 0.001), explaining over 76% of the variance in the outcome (R² = 0.76). Due to perfect separation, inclusion of this variable in the multivariable model caused estimation issues and instability in other predictors. Therefore, the adjusted model presented here excludes referral to isolate other factors associated with visiting a dietitian.

Table 5 reports the experiences and perceptions of the participants regarding their dietitian consultations. Among the 92 women who had seen a dietitian, 39.1% (n=36) were seen on the same day, another 39.1% (n=36) within a week, and 21.7% (n=20) had their appointment after more than one week. Follow-up modes were nearly equally divided, with 52.7% (n=49) of women seen in person and 47.3% (n=44) using telemedicine. In terms of dietitians’ recommendations, the majority of the participants (78.5%, n=73) were advised on both dietary modifications and physical activity, while 21.5%(n=20) of the women received advice only on dietary changes. Adherence to the dietitian’s advice was high, with 93.5% (n=87) of women reporting that they followed the recommendations, and 77.4% (n=72) reported no barriers to adherence. Among those who experienced barriers, the most common were difficulty in changing behavior (16.1%, n=15) and dietary restrictions conflicting with cultural preferences (9.7%, n=9). Overall, satisfaction with the dietitian consultation was high, with 79.5% (n=74) of participants being either satisfied or very satisfied with the experience.

Table 5.

Experiences and perceptions of dietitian consultations (n=93).

	n	%
What was the time between referral and first dietitian visit (n=92)?
The same day	36	39.1
within a week	36	39.1
After one week	20	21.7
How was the mode of follow up with the dietitian?
In-person	49	52.7
Telemedicine	44	47.3
What did the dietitian recommend?
Dietary modifications	20	21.5
Both dietary modifications and physical activity	73	78.5
Did you follow the dietitian’s advice regarding dietary and lifestyle modifications?^a
“Rarely, not at all” & “Partially, sometimes”	6	6.5
Most of the time/completely	87	93.5
What was/were the barrier/s to adherence (multiple selection)?
None	72	77.4
Too difficult to change one’s behavior	15	16.1
The food choices contradict my cultural preferences	9	9.7
Inability to engage in physical activity	2	2.2
I prefer medication	1	1.1
How satisfied were you with the dietitian consultation?
Very satisfied	15	16.1
Satisfied	59	63.4
Neutral	16	17.2
Dissatisfied	3	3.2
Very dissatisfied	0	0

^aGiven that only 1 participant answered “Rarely, not at all”, this category was merged with the “Partially/sometimes”, yielding two categories for this question (‘No, not at all & Partially/sometimes’ versus ‘Most of the time/completely’).

Discussion

This study examined the prevalence and correlates of the use of dietetic services among women with GDM in the UAE, a region characterized by diverse cultures and healthcare systems and already experiencing high rates of T2DM. The observed prevalence of dietitian visits of the participants was markedly low at 41.7%. This finding is concerning given the critical role that dietitians and dietary interventions play in the management of GDM and in mitigating its associated adverse outcomes. In this study, referral by the physician emerged as the most influential determinant of visiting a dietitian; with nearly all the referred women attending/visiting a dietitian. Such a finding confirms earlier reports indicating that referral acts as a critical gatekeeper.³¹ In this study, half (55%) of the participants were not referred by their physicians to dietetic services. A possible interpretation for this finding is that physicians were either unaware of or undervalued the benefits of structured nutrition counseling in GDM.³² As such, more awareness is needed, among healthcare professionals in general and physicians in specific, of the benefits of adding dietetic services within the multidisciplinary patient care team for effective GDM management.

The findings of this study showed that referrals were often inconsistent; participants were referred to different healthcare specialists for follow-up, including diabetes educators. Hanks et al. (2022) discussed that the overlap between dietitians’ and diabetes educators’ roles leads to fragmentation of care and may reduce the effectiveness of dietitian-led management.^33,34 Moreover, Yee et al. (2020) identified that physicians’ referral patterns significantly influence whether patients receive dietitian services or rely solely on general advice from diabetes educators.³²

In this study, nationality emerged as a significant predictor of dietitian visits, with Emirati women more likely to attend dietitian consultations than their non-Emirati counterparts. This finding could be due to differences in health insurance coverage. Existing evidence suggests that patients with certain medical service coverage plans are more likely to seek and attend these services.³⁵ In the UAE, Emiratis have insurance coverage for paramedical services including dietitian’s visit, while non-Emiratis either pay out-of-pocket or be covered through individually purchased health insurance plans.^33,36

The findings of this study highlighted that women who visited a dietitian demonstrated greater adoption of healthy lifestyle behaviors post-GDM diagnosis, including daily breakfast consumption, initiation of physical activity, and sleeping more than 8 hours. This aligns with existing evidence indicating that dietitian consultation not only provides individualized dietary recommendations but also promotes broader lifestyle modifications.^37,38 Such multidimensional support highlights the unique value of dietitian involvement in GDM care, complementing medical management.

A previous GDM diagnosis, family history of GDM, and awareness of GDM risk all increased the likelihood of visiting a dietitian among women in this study. This is consistent with earlier studies. For instance, Liu et al. (2024) reported that 85.9% of women diagnosed with GDM and with prior glycemic risk factors in New Zealand visited the dietitian.³⁹ Similarly, in an Australian mixed-methods study, Lang et al. (2023) demonstrated that high-risk antenatal women, including those with a family history of GDM or diabetes, were more motivated to seek dietitian guidance because they were highly concerned about their pregnancy outcomes.⁴⁰ Such findings underscore the critical role of clinical history and risk perception, as women who are more aware of their elevated risk tend to be more motivated to utilize dietetic services during pregnancy.

Women using pharmacologic therapy for GDM in this study were less likely to visit a dietitian. A possible explanation is that both patients and physicians may perceive pharmacological therapy as a more immediate or effective solution, thereby underestimating the importance of diet and lifestyle intervention,^8,27,41 while in fact existing studies showed that 70-85% of pregnant women diagnosed with GDM obtained and maintained glycemic targets only with MNT.⁴² Current recommendations advise that pharmacological treatments, such as insulin or other agents, be introduced when glycemic targets are not met through diet and lifestyle modifications alone.⁴³ These considerations underscore that pharmacological therapy should complement rather than replace the dietitian’s involvement.

An interesting finding in this study was that women who rated their general health as good or excellent were less likely to seek dietetic services. This finding is in agreement with previous reports that showed that individuals who perceive themselves as healthy may underestimate their need for dietary counseling, particularly in the absence of overt symptoms.^44,45 Nevertheless, the need persists for physicians to communicate the importance of diet and lifestyle management in GDM, regardless of women’s subjective health perceptions.

Consistent with prior reports, this study identified several common barriers to utilizing dietetic services, including simultaneous follow-up with other specialists, a perceived lack of need, scheduling difficulties, and cultural dietary preferences that conflicted with recommended dietary modifications.^33,46,47 Such barriers underscore the importance of culturally tailored counseling and development of integrated care pathways in which dietetic consultations are embedded into routine antenatal care rather than being treated as optional or additional.

Interestingly, this study revealed high satisfaction rates with dietetic services. Studies from antenatal and diabetes care settings confirm that women who receive structured nutrition counseling report higher levels of satisfaction with care, and better confidence in managing their diet, and stronger adherence to recommendations.^48,49 Among the dietitian consultation modes reported in this study, telemedicine accounted for nearly half of follow-up encounters, reflecting global trends in digital maternal care delivery and the potential to enhance accessibility and convenience.^46,50,51

Limitations

A key strength of this study lies in its novelty in the UAE context. This is one of the first studies investigating the correlates of the use of dietetic services for pregnant women with GDM and highlighting important factors that influence the management of GDM. Nonetheless, several limitations should be acknowledged. The cross-sectional design precludes causal inferences. In addition, reliance on self-reported measures for lifestyle changes, adherence, and satisfaction introduces the possibility of recall and social desirability bias. The fact that participants were recruited participants from selected healthcare facilities may limit the generalizability of the findings to all women with GDM in the UAE. Lastly, it is important to note that, although expert review, cross-cultural adaptation, and pilot testing were performed to enhance content, face, and translation validity forms, formal psychometric indices were not calculated. Future studies in this field may consider adding to the study tool further questions related to lifestyle such as the use of supplement and complementary and alternative medicine therapies.

Conclusion

This study highlights a rather low prevalence of visiting a dietitian among women with GDM in the UAE, with referral by healthcare providers as the most influential factor in the use of dietetic services. Dietitian consultation was linked to healthier lifestyle behaviors and high patient satisfaction, reinforcing its role as an essential component of GDM management. These findings are particularly significant in the UAE, where rates of GDM and T2DM continue to rise. Strengthening dietitian referral systems, integrating culturally tailored nutrition counseling into antenatal and postnatal care, and implementing automatic referral protocols could optimize pregnancy outcomes while serving as a strategic intervention to reduce long-term metabolic risks. In addition, addressing cultural and systemic barriers among healthcare providers, enhancing multidisciplinary coordination, and expanding telemedicine-based dietetic services may further improve access, adherence, and long-term maternal–child health outcomes. Future research is needed to further investigate the effects of visiting a dietitian on the fetal and long-term maternal outcomes among women with GDM.

Supplemental material

Supplemental material - Use of dietetic services among pregnant women with gestational diabetes in the UAE: Prevalence, correlates, and patient experiences

Supplemental material for Use of dietetic services among pregnant women with gestational diabetes in the UAE: Prevalence, correlates, and patient experiences by Hadia Radwan, Roba Saqan, Dana N. Abdelrahim, Nada Abbas, Mona Hashim, Salma Abu-Qiyas, Noha Mousa, Ghada Mohammed3, Wegdan Bani Issa, Manal Awad, Randa Fakhry, Latefa Rashid, Shameema Asif Muhammed and Farah Naja in Women's Health.

Footnotes

Acknowledgements

The authors express their sincere gratitude to the mothers who participated in this study.

ORCID iDs

Hadia Radwan

Roba Saqan

Dana N. Abdelrahim

Mona Hashim

Noha Mousa

Ghada Mohammed

Wegdan Bani Issa

Manal Awad

Farah Naja

Ethical considerations

The study was approved by the Research Ethics Committees at the University of Sharjah (Reference No. REC-22-01-03-02), the Ministry of Health and Prevention (Reference No. MOHAP/DXB-REC/JFF/No.10/2022), and the Dubai Health Authority (Reference No. DSREC-08/2022_10).

Consent to participate

Written informed consent was obtained from all participants prior to participation.

Author contributions

Conceptualization: HR, FN, RS, MH. Methodology: FN, DNA, MH, RS. Software: NA, DNA. Validation: HR. Formal analysis: NA. Investigation: FN, MH, GM, NM, SAM. Resources: MH, GM, NM, SAM. Data curation: NA, DNA. Writing – Original Draft: FN, MH, SAQ, RS, DNA. Writing – Review & Editing: HR, FN, DNA, GM, NM, WBI, MA, RF, LR, SAM. Visualization: NA, DNA. Supervision: HR, FN. Project administration: HR, FN. Funding acquisition: HR, FN, RS.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research study has received funding from the Vice-Chancellor of the Research and Graduate Studies Office/ University of Sharjah, Competitive Research Project grant No. (2201050779).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.*

Supplemental material

Supplemental material for this article is available online.

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