Factors linked to early adverse neonatal outcomes in diabetic pregnant women at selected Ugandan hospitals: A prospective cohort study

doi:10.21203/rs.3.rs-4720789/v1

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Factors linked to early adverse neonatal outcomes in diabetic pregnant women at selected Ugandan hospitals: A prospective cohort study

https://doi.org/10.21203/rs.3.rs-4720789/v1

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Background

Diabetes mellitus during pregnancy is associated with increased risks of adverse neonatal outcomes. Understanding the incidence and factors contributing to these outcomes is crucial for improving maternal and neonatal health in low-resource settings.

Methods

This prospective cohort study enrolled 150 pregnant women with diabetes mellitus delivering at Jinja, Hoima, and Lira Regional Referral Hospitals in Uganda. Data on socio-demographic characteristics, obstetric history, and neonatal outcomes were collected using standardized protocols. Logistic regression analyses were performed to assess associations between maternal characteristics and adverse neonatal outcomes.

Results

The incidence of adverse neonatal outcomes was 69.3%. Specific outcomes included macrosomia (45.3%), low APGAR scores (4–6: 28.0%, < 3: 7.3%), NICU admission (27.3%), hypoglycaemia (25.3%), respiratory distress (20.7%), early neonatal death (14.0%), birth injuries (7.3%). Significant factors associated with adverse outcomes included unemployment (aOR = 5.94, 95%CI = 1.70-20.67, p = 0.005), fewer than four antenatal care visits (aOR = 1.63, 95%CI = 1.24–16.49, p = 0.035), preterm delivery (aOR = 3.57, 95%CI = 1.06–12.03, p = 0.040), and not receiving treatment for maternal diabetes (aOR = 1.93, 95%CI = 1.05–4.36, p = 0.016). In contrast, a monthly income of ≥ 150,000 was protective against adverse outcomes (aOR = 0.18, 95%CI = 0.06–0.57, p = 0.004).

Conclusions

The study revealed a high incidence of adverse neonatal outcomes among mothers with diabetes, highlighting the urgent need for improved care. Key factors linked to these adverse outcomes included unemployment, fewer antenatal care visits, preterm delivery, and lack of maternal diabetes treatment, while higher monthly income was protective. Targeted interventions, such as enhanced antenatal care and effective diabetes management, are essential to reduce adverse neonatal outcomes. Future research should focus on evaluating specific interventions to mitigate these risks and improve maternal and neonatal health in similar low-resource settings.

Diabetes mellitus

Pregnancy

Neonatal outcomes

Antenatal care

Preterm delivery

Uganda

Diabetes mellitus (DM) in pregnancy, including pre-existing diabetes and gestational diabetes mellitus (GDM), poses significant health risks to both mothers and their neonates. Poorly controlled diabetes can lead to complications such as macrosomia, hypoglycemia, respiratory distress, preterm birth, and increased neonatal intensive care unit (NICU) admissions (1). These complications can result in long-term health issues for the child and increase healthcare costs. Understanding the impact of diabetes in pregnancy is vital for developing effective healthcare strategies to improve outcomes (2).

It affects approximately 5% of all pregnancies worldwide (3). In 2019, the International Diabetes Federation estimated that 15.5% of pregnancies were affected by diabetes, with GDM accounting for 12.8% and pre-existing diabetes for 2.7% (4). In Uganda, a study at Itojo General Hospital reported a 15.6% prevalence of diabetes among pregnant women (5). Additionally, a study at Mulago Hospital found that neonates born to mothers with GDM were more likely to experience adverse outcomes such as macrosomia, stillbirth, and shoulder dystocia compared to those born to non-diabetic mothers (6).

Proper diagnosis and management of diabetes in pregnancy can significantly improve maternal and neonatal outcomes, reducing rates of shoulder dystocia, fractures, nerve palsies, and neonatal hypoglycemia (7). However, many low- and middle-income countries (LMICs), where most cases of diabetes in pregnancy are reported, face significant challenges. These include limited resources, inadequate healthcare worker training, and low utilization of maternal health services (8, 9).

Poorly controlled diabetes during pregnancy increases the risk of neonatal complications, including hypoglycemia, low birth weight, prematurity, respiratory distress, and higher neonatal mortality rates (10–12). The National Institute for Health and Care Excellence (NICE) recommends Continuous Glucose Monitoring (CGM) for all pregnant women with diabetes to improve neonatal outcomes (13).

In Uganda, the healthcare system faces challenges such as limited resources and low utilization of maternal health services (14). Studies have shown that neonates born to mothers with diabetes in Uganda are at higher risk for adverse outcomes. For instance, a study at Mulago Hospital found that infants born to mothers with GDM were more likely to be macrocosmic, stillborn, or experience shoulder dystocia (6). Despite these findings, Uganda continues to struggle with inadequate diabetes care, increasing the risk of neonatal complications (14).

Research into the effects of diabetes in pregnancy on neonatal outcomes is essential for improving both maternal and neonatal health. The increasing prevalence of diabetes among pregnant women, especially in LMICs like Uganda, emphasizes the need for effective management strategies. This study's findings will provide valuable insights into the incidence and factors associated with adverse neonatal outcomes, informing policies and clinical practices to better manage diabetes during pregnancy and mitigate its risks.

1.2 Study Objectives

This study aims to determine the incidence and factors associated with early adverse neonatal outcomes among mothers with diabetes delivering at Kampala International University (KIU) teaching hospitals. Identifying these factors will contribute to the development of evidence-based guidelines and interventions to improve neonatal outcomes in Uganda and similar settings.

2.1 Study design: A prospective cohort study.

2.2 Study site: This study was conducted at Jinja, Hoima, and Lira Regional Referral Hospitals in Uganda. These hospitals serve large and diverse patient populations across different regions of the country. They are equipped with significant obstetric and neonatal care facilities, including specialized units for managing high-risk pregnancies and neonatal complications. 2.3 Sample size calculation: The sample size for this study was determined using the Open Epi data calculator, considering macrosomia as a previous adverse outcome with an adjusted relative risk of 2.38 (22). The calculation was based on a two-sided significance level of 95% and a study power of 80%. The ratio of unexposed to exposed subjects was set at 1, with 8.1% of unexposed subjects expected to experience the outcome compared to 26% of exposed subjects. The odds ratio was 4.1, the risk/prevalence ratio was 3.3, and the risk/prevalence difference was 18. Using these parameters, the Kelsey formula indicated a required sample size of 136 participants (68 exposed and 68 unexposed). To account for potential loss to follow-up, an additional 10% was added, resulting in a final sample size of 150 participants. This approach ensures adequate power and precision to detect significant differences in neonatal outcomes related to maternal diabetes.
2.4 Inclusion and exclusion criteria
2.4.1 Inclusion criteria: Mothers with diabetes mellitus who delivered at Jinja Regional Referral Hospital (JRRH), Lira Regional Referral Hospital (LRRH), and Hoima Regional Referral Hospital (HRRH) during the study period were included in the study after obtaining informed consent.
2.4.2 Exclusion criteria: Mothers with diabetes mellitus who had co-existing medical conditions such as hypertension and cardiac diseases were excluded from the study.
2.5 Study procedure: The principal investigator and research assistants approached pregnant women in labor, provided education about the study, and identified those with diabetes mellitus from antenatal care (ANC) cards and medical history. Those not previously screened during pregnancy and admitted for delivery in the maternity wards of JRRH, HRRH, and LRRH were screened using history and random blood glucose levels. A random blood glucose level > 200 mg/dL, combined with classic symptoms such as polydipsia, polyuria, and unexplained weight loss, indicated overt diabetes mellitus, while gestational diabetes mellitus was indicated by a random blood glucose level between 140 mg/dL and 200 mg/dL.

Eligible pregnant women were assessed at the ward. The study's nature was explained to each eligible participant, and written informed consent was obtained. Participants were assured of confidentiality, privacy, and anonymity. An approved informed consent form from the Kampala International University Research Ethics Committee was used.

A simple consecutive sampling approach was used to select participants, who were then given a pre-tested interviewer-administered questionnaire to obtain data. Baseline characteristics at enrollment were captured and followed through labor and delivery, where neonatal outcomes were recorded. Data regarding the bio-data of pregnant women and neonatal outcomes post-birth were collected using closed-ended questions.

2.6 Data collection procedure:

2.6.1 Training of Research Assistants

Data collection was conducted by the principal investigator under supervision with the help of research assistants. Training research assistants on the research protocol, standard operating procedures and data collection tools. Checking for accuracy and completeness in real time. Regular refresher meetings. All saved data copies were reviewed on a daily basis, checked for inconsistencies and re-saved.

Research assistants were trained on how to obtain informed consent, patient approach and proper data collection. Adherence to the inclusion and exclusion criteria and use of the standardized checklists and laboratory reports for all participants was ensured.

2.6.2 Data collecting tools

Data from this study was collected with the help of the structured investigator-administered pre-tested and pre-coded questionnaires with close-ended questions together with a checklist recording early adverse neonatal outcomes. The questionnaire was in English and interviews were made in local languages when deemed necessary. A detailed obstetric and gynecologic history including thorough medical and social factors and physical examination was done as appropriate to ensure the patient meets inclusion criteria.

2.6.3 Flow of Participants during Data Collection

Pregnant women admitted in labor at Jinja, Lira, and Hoima Regional Referral Hospitals were first sensitized and educated about the study. They were then assessed, with those having diabetes mellitus or who were unscreened being screened for the condition. Women not meeting the inclusion criteria or without diabetes continued with their normal routine care. Those who met the inclusion criteria provided informed consent and were included in the study. Participants were monitored for neonatal outcomes: those with adverse outcomes received appropriate management, while those without adverse outcomes followed the standard postnatal care routine. Follow-up for all participants continued until discharge or up to seven days, whichever came first.

2.7 Study variables: The study examined various independent variables affecting adverse neonatal outcomes, including maternal age, occupation, monthly income, residence, number of antenatal care (ANC) visits, gestational age at delivery, history of previous neonatal adverse outcomes, treatment status, and whether the mother engaged in exercise.

Physical assessments involved measuring weight with a digital scale (model PS-103, up to 180 kg) and height with a stadiometer (200 cm, wall-mounted) to calculate Body Mass Index (BMI). BMI was categorized as normal (18.5–24.9), overweight (25-29.9), or obese (≥ 30) per WHO standards. Gestational weight gain was determined by subtracting the initial visit weight from the current weight.

Glycemic levels were measured using finger prick blood samples for mothers and heel prick blood samples for neonates, with both procedures involving cleaning the site with 70% alcohol antiseptic. A random blood glucose level > 200 mg/dL plus symptoms like polydipsia, polyuria, and unexplained weight loss indicated overt diabetes mellitus, while levels between 140 mg/dL and 200 mg/dL indicated gestational diabetes mellitus. Neonates with blood glucose levels below 40 mg/dL were considered hypoglycemic.

Gestational age was assessed postnatally using the New Ballard Scoring system for mothers unsure of their last menstrual period, evaluating neurological and physical maturity. Birth weight was assessed using INTERGROWTH-21st standards, with growth charts specific to boys and girls corresponding to gestational age.

Adverse early neonatal outcomes were defined as any of the following conditions: a low Apgar score (less than 7 at 5 minutes) (25), early neonatal death (death within seven days of birth) (26), hypoglycemia (blood glucose levels less than 40 mg/dL) (27), macrosomia (birth weight at or above the 90th percentile or greater than 4,000 g) (1), neonatal respiratory distress (symptoms including tachypnea, nasal flaring, grunting, and chest wall retractions) (28), and NICU admission due to these complications (12).

2.8 Data quality control: To ensure the integrity and reliability of this study, rigorous quality control measures were implemented throughout the research process. Research assistants received comprehensive training on the study protocol, data collection tools, informed consent procedures, and patient interaction. Regular refresher meetings were conducted to maintain high standards of accuracy and consistency in data collection. Data collection tools, including structured, pre-tested questionnaires and checklists, were used to ensure uniformity and precision. Daily reviews of collected data were performed to identify and rectify any inconsistencies promptly. Pre-testing of data collection instruments was carried out at Kampala International University Teaching Hospital, and necessary adjustments were made based on the findings. Physical assessments, including anthropometric measurements and glycemic level evaluations, were conducted using calibrated equipment to ensure accuracy. Gestational age was assessed using the New Ballard Scoring system, and birth weights were measured according to INTERGROWTH-21st standards. These measures ensured that the data collected was accurate, reliable, and reflective of the study population, thereby enhancing the validity of the study's findings.

2.9 Data analysis: Results were expressed as percentages, showing the proportion of neonates with early adverse outcomes among those born to women with diabetes mellitus and presented graphically. The numerator was neonates with adverse outcomes, and the denominator was the total number of neonates born to diabetic mothers.

Factors associated with adverse neonatal outcomes were analyzed using bivariate and multivariate logistic regression, reported as Odds Ratios (OR). A binary variable for adverse outcomes served as the dependent variable, with socio-demographic, obstetric, gynecologic factors, and treatment as independent variables. Bivariate analysis compared independent variables with the dependent variable using Chi-square tests and logistic regression, reporting unadjusted ORs with 95% confidence intervals (CI). Variables with p-value < 0.2 proceeded to multivariate analysis to control for confounding. Multivariate analysis checked assumptions like multicollinearity and normality, reporting adjusted ORs (aOR) with 95% CIs. Variables were deemed significant if p-value < 0.05.

2.10 Ethical considerations: The study was approved by the Research and Ethics Committee of KIU (KIU REC Reference Number: KIU-2022-140), the administration of KIU teaching sites, and the department of obstetrics and gynecology. Participants' autonomy was ensured through informed consent, explained in both English and local languages, with no coercion involved, allowing participants to withdraw at any time without affecting their care. The study posed minimal risk, primarily slight pain from blood sample collection, mitigated by aseptic techniques to prevent infections. Participants received close monitoring and appropriate management, with study findings expected to guide policy formulation, benefiting the broader community and healthcare system. Data collected was anonymized using codes, and interviews were conducted privately to maintain confidentiality. A consecutive sampling method was used, adhering strictly to eligibility criteria without bias regarding tribe, race, or religion. Participants were not paid or compensated for their participation. The study procedures were respectful of local beliefs, traditions, and culture.

3.1 Flow of Study Participants: In Fig. 1 below, the flow of study participants is illustrated.

Figure 1 Data collection flow chart.

3.2 Descriptive characteristics of study participants

Table 1

Characteristics of the study participants (N = 150).
Variables		Frequency(n)	Percent
Age	≤ 20 years	12	8.0
	20–34 years	98	65.3
	> 34 years	40	26.7
Occupation	Unemployed	132	88.0
Occupation	Employed	18	12.0
Monthly Income	≥ 150000	56	37.3
Monthly Income	< 150000	94	62.7
Residence	Rural	81	54.0
Residence	Urban	69	46.0
ANC visits	< 4	34	22.7
ANC visits	≥ 4	116	77.3
Gestational age	< 37 weeks	33	22.0
Gestational age	≥ 37 weeks	117	78.0
History of previous neonatal adverse outcomes	Yes	29	19.3
History of previous neonatal adverse outcomes	No	121	80.7
Treatment	Not on treatment	72	52.0
Treatment	On treatment	78	48.0
Exercise	Yes	105	70.0
Exercise	No	45	30.0

The majority of participants were aged 20–34 years (65.3%) and unemployed (88.0%). Most had a monthly income of less than 150,000 UGX (62.7%) and resided in rural areas (54.0%). Almost all participants had four or more antenatal care visits (77.3%) and delivered at 37 weeks or more gestational age (78.0%). A significant portion did not have a history of previous neonatal adverse outcomes (80.7%). Participants were nearly evenly split between those on treatment (48.0%) and not on treatment (52.0%). Additionally, a large majority engaged in exercise (70.0%) (Table 1).

3.3 Incidence of early adverse neonatal outcomes among mothers with diabetes mellitus

The findings indicate that 69.3% of mothers with diabetes mellitus who delivered at Jinja, Hoima, and Lira Regional Referral Hospitals experienced adverse neonatal outcomes (Fig. 2).

Figure 2: Bar-chart showing the incidence of early adverse neonatal outcomes among mothers with diabetes mellitus.

Table 2

Description early adverse neonatal outcomes among mothers with diabetes mellitus (N = 150).
Adverse neonatal outcomes	Frequency	Percent
NICU admission
Yes	41	27.3
No	109	72.7
Early Neonatal Death
Yes	21	14.0
No	129	86.0
Hypoglycemia
Yes	38	25.3
No	112	74.7
APGAR
< 3	11	7.3
4–6	42	28.0
≥ 7	97	64.7
Respiratory Distress
Yes	31	20.7
No	119	79.3
Birth injuries
Yes	11	7.3
No	139	92.7
Birth weight
Macrosomia	68	45.3
Low birth weight	3	2.0
Normal	79	52.7

Among the neonates born to mothers with diabetes mellitus at Jinja, Hoima, and Lira Regional Referral Hospitals, 27.3% required NICU admission, and 14.0% experienced early neonatal death. Hypoglycemia occurred in 25.3% of the neonates. Regarding the Apgar scores, 7.3% had scores less than 3, 28.0% had scores between 4 and 6, and 64.7% had scores of 7 or higher. Respiratory distress was noted in 20.7% of the cases, while 7.3% suffered birth injuries. In terms of birth weight, 45.3% of the neonates were macrosomic, 2.0% had low birth weight, and 52.7% had normal birth weight (Table 2).

3.4 Factors associated with early adverse neonatal outcome among mothers with diabetes

Table 3

Analysis of factors associated with adverse neonatal outcome among mothers with diabetes (N = 150)
Variables		Early adverse neonatal outcome		cOR(95%CI)	P-value	aOR(95%CI)	P-value
Variables		Yes (104)	No (46)	cOR(95%CI)	P-value	aOR(95%CI)	P-value
Age	21–34 years	70	28	1.78(0.52–6.10)	0.355
	> 34 years	27	13	1.48(0.39–5.58)	0.560
	≤ 20 years	7	5	1.00
Occupation	Unemployed	96	36	3.33(1.22–9.11)	0.019*	5.94 (1.70-20.67)	0.005**
Occupation	Employed	8	10	1.00		1.00
Monthly Income	≥ 150000	55	39	0.20(0.08–0.49)	0.001*	0.18 (0.06–0.57)	0.004**
Monthly Income	< 150000	49	7	1.00		1.00
Residence	Rural	63	18	2.39(1.17–4.87)	0.016*	0.99 (0.38–2.57)	0.983
Residence	Urban	41	28	1.00		1.00
ANC visits	< 4	21	13	1.64(0.79–6.43)	0.078*	1.63 (1.24–16.49)	0.035*
ANC visits	≥ 4	83	33	1.00		1.00
Gestational age	< 37 weeks	28	5	3.021(1.08–8.42)	0.034*	3.57 (1.06–12.03)	0.040*
Gestational age	≥ 37 weeks	76	41	1.00		1.00
History of previous neonatal adverse outcomes	Yes	23	6	1.89(0.71–5.02)	0.200
History of previous neonatal adverse outcomes	No	81	40	1.00
Treatment	Not on treatment	62	16	2.77(1.34–5.69)	0.006	1.93(1.05–4.36)	0.016*
Treatment	On treatment	42	30	1.00		1.00
Exercise	Yes	25	20	2.43(1.16–5.08)	0.018*	1.68(0.72–3.94)	0.231
Exercise	No	79	26	1.00		1.00

cOR: Crude Odds Ratio, CI: Confidence Interval, P*: represents p values ≤ 0.2 before aOR P**: ≤0.05 aOR: adjusted Odds Ratio.

The multivariate analysis revealed several significant factors that increased the likelihood of early adverse neonatal outcomes among mothers with diabetes mellitus. Unemployed mothers were nearly six times more likely to experience adverse outcomes compared to employed mothers. Mothers with a monthly income of ≥ 150,000 UGX were about five times less likely to have adverse outcomes than those earning less. Mothers with fewer than four antenatal care (ANC) visits were over one and a half times more likely to experience adverse outcomes compared to those with four or more visits. Preterm deliveries (before 37 weeks) increased the likelihood of adverse outcomes by over three and a half times compared to full-term deliveries. Lastly, mothers not receiving treatment were almost twice as likely to have adverse outcomes compared to those receiving treatment. (Table 3).

4.1 Incidence of early adverse neonatal outcomes among mothers with diabetes mellitus

The overall incidence of early adverse neonatal outcomes among neonates born to mothers with diabetes mellitus at Jinja, Hoima, and Lira Regional Referral Hospitals was found to be 69.3%. This high incidence can be attributed to the increased risk of morbidity and mortality associated with diabetes mellitus during pregnancy. For instance, Joewono and Sulistyono (2020) suggest that diabetes in pregnancy significantly heightens the risk of adverse neonatal outcomes. Moreover, Feig et al. (2014) reported that overt diabetes and gestational diabetes increase the risks of unfavorable neonatal outcomes by factors of 1.86 and 1.26, respectively (1, 2).

The 69.3% incidence observed in this study is significantly higher than the 5.3% pooled incidence of adverse birth outcomes reported in a systematic review and meta-analysis involving studies from Addis Ababa, Amhara, and Oromia regions of Ethiopia (20). It also surpasses the 10.66% incidence found in a study of 75 women with diabetes mellitus in Dharan, Nepal (21), and the 30.3% composite incidence from a prospective cohort study in Ethiopia (22). These discrepancies can be attributed to variations in geographic locations, study designs, and the number of studies included.

The study also noted a higher incidence of adverse neonatal outcomes among mothers with overt diabetes (76.3%) compared to those with gestational diabetes (66.3%). This contrasts with findings from Muche et al. (2020) in Ethiopia, which indicated a higher proportion of composite adverse neonatal outcomes among mothers with gestational diabetes (51.7%) compared to those with overt diabetes (25.8%) (22). These differences may be due to geographical variations, differences in study design, and sample sizes.

Additional literature supports these findings, highlighting the significant impact of diabetes on neonatal outcomes. For example, a study on maternal and neonatal outcomes in Qatar found higher rates of adverse outcomes such as NICU admission, hypoglycemia, and low Apgar scores among infants born to mothers with diabetes (23). Furthermore, research indicates that gestational diabetes significantly increases the risk of preterm birth, macrosomia, and neonatal intensive care unit (NICU) admissions (24).

Overall, these findings underscore the critical need for targeted interventions and effective management strategies to mitigate the risks associated with diabetes in pregnancy and improve neonatal outcomes.

4.2 Description early adverse outcomes among neonates born to mothers with diabetes

In this study, the most common early adverse neonatal outcome among mothers with diabetes was macrosomia, with an incidence of 45.3%. This was followed by NICU admission (27.3%), hypoglycemia (25.3%), respiratory distress (20.7%), early neonatal death (14.0%), low Apgar scores (7.3%), birth injuries (7.3%), and low birth weight (2.0%). Similar outcomes were observed in studies by El-Dairi & House (2019) and Anjum & H. T. (2018) (2, 4).

Macrosomia was the most common adverse outcome, occurring in 45.3% of cases. This is consistent with findings from a prospective study at the Centre Hospitalier Universitaire Vaudois in Lausanne, Switzerland, which linked gestational weight gain (GWG) and HbA1c at the end of pregnancy to large for gestational age (LGA) outcomes (5). A population-based cohort study in Pomerania, Germany, also reported that gestational diabetes increased the odds of macrosomia by 2.43 times (6). However, the incidence in this study was higher compared to 15% in a hospital-based study in India (4) and 16% in a study at the Pakistan Institute of Medical Sciences (8). The increased risk of macrosomia is due to insulin resistance and increased glucose exposure in utero (9–11).

The incidence of NICU admission was 27.3%, comparable to 29% in GDM pregnancies reported in a New Zealand study (12). However, it was lower than the 40% incidence in type 2 DM pregnancies reported in the same study. Neonates born to diabetic mothers often have higher NICU admission rates due to low Apgar scores, respiratory distress, and hypoglycemia.

Hypoglycemia occurred in 25.3% of neonates, aligning with the 28% incidence reported in a study at the Pakistan Institute of Medical Sciences (8). However, it was lower than the 43% incidence in a study in Bangalore, India (4). Hypoglycemia is a common metabolic disorder in neonates born to diabetic mothers due to failure to maintain glucose homeostasis (13). Domanski et al. (2018) noted that diabetes mellitus in mothers increased the odds of neonatal hypoglycemia by 11.71 times. The condition is linked to the hyperglycemic intrauterine environment, causing increased fetal insulin output and subsequent hypoglycemia (14, 15).

Respiratory distress affected 20.7% of neonates, similar to the 20% reported by Mortier et al. (2017) (16). Studies have long established a strong link between maternal diabetes and neonatal respiratory distress syndrome (17). The major cause is impaired surfactant production due to difficulties in glycemic management during pregnancy (18). Li et al. (2019) reported pooled odds ratios of 1.57 for gestational diabetes and 2.66 for pre-gestational diabetes (19).

The incidence of early neonatal death was 14.0%, supported by findings from Opara et al. (2010), who noted a fivefold increase in neonatal death rates among infants born to diabetic mothers (26). A case-control study in Tehran also reported a 1.63 times higher risk of neonatal mortality among diabetic mothers (27). In Uganda, a study at Mulago Hospital found that infants born to mothers with gestational diabetes were more likely to die shortly after birth (28).

Low Apgar scores (< 7) were observed in 7.3% of neonates, lower than the 11.33% reported in Nepal (21). The Apgar score assesses heart rate, reflexes, color, muscle tone, and respiratory effort to determine the need for resuscitation (9). Infants born to diabetic mothers are more likely to have low Apgar scores (13).

Birth injuries occurred in 7.3% of cases, higher than the 0.5% reported in Finland (29) but lower than the 13% observed in Pakistan (8). Diabetes increases the risk of delivery complications, including preeclampsia and macrosomic deliveries, which heighten the risk of birth injuries (30).

These findings underscore the significant risks associated with maternal diabetes and highlight the need for improved management and preventive strategies to reduce adverse neonatal outcomes.

4.3 Factors associated with early adverse neonatal outcome among others with diabetes mellitus.

In this study, both occupation and monthly income level were significantly associated with early adverse neonatal outcomes. Neonates born to unemployed women were 5.94 times more likely to experience adverse outcomes (p = 0.005), while those born to women earning ≥ 150,000 UGX monthly were 0.18 times less likely to develop such outcomes (p = 0.004). This finding aligns with research by Kim et al. (2018), which indicates that low socioeconomic status increases the risk of adverse pregnancy outcomes due to inadequate prenatal care (17). A study by Hwang and Shon (2014) found that lower income individuals are more likely to have diabetes due to factors like obesity and unhealthy lifestyles (18). Agardh et al. (2011) also noted that socioeconomic position impacts diabetes development through access to healthcare and healthy lifestyle options (2).

Gestational age was significantly associated with early adverse neonatal outcomes, with neonates born before 37 weeks being 3.57 times more likely to experience such outcomes (p = 0.040). This is supported by a meta-analysis showing that the odds of adverse neonatal outcomes were 9.76 times higher among women with diabetes delivering before 37 weeks (19). Preterm birth is a well-documented risk factor for adverse neonatal outcomes, exacerbated by maternal diabetes (20).

The number of antenatal care (ANC) visits was also significant, with neonates born to women who attended fewer than four ANC visits being 1.63 times more likely to develop early adverse outcomes (p = 0.035). This is consistent with findings from a systematic review indicating that inadequate ANC is associated with a higher risk of adverse neonatal outcomes (21).

Neonates born to women receiving treatment for diabetes were 1.93 times more likely to experience adverse outcomes (p = 0.016). This could be linked to the use of insulin, which is associated with higher risks of adverse outcomes such as macrosomia and hypoglycemia (10, 11). A meta-analysis by Castillo (2015) found that medical therapy, especially insulin and glyburide, increased NICU admissions, respiratory distress, and neonatal hypoglycemia (22). Furthermore, studies have shown that combined treatment with insulin and metformin can result in higher rates of large-for-gestational-age infants and neonatal complications (23, 24).

The study revealed a high incidence (69.3%) of early adverse neonatal outcomes among mothers with diabetes. Macrosomia, NICU admission, and hypoglycemia were the most common adverse outcomes. Key factors associated with these outcomes included socioeconomic status, gestational age, ANC visits, and diabetes treatment, highlighting the need for comprehensive care and support for diabetic mothers during pregnancy.

Public Health Authorities: Implement systematic screening protocols for glycemic control and prenatal care among pregnant women with diabetes to reduce adverse neonatal outcomes. Conduct research to identify regional factors contributing to higher incidences.

Healthcare Providers: Strengthen monitoring and management protocols to prevent macrosomia, NICU admissions, and hypoglycemia. Encourage regular prenatal check-ups, early gestational diabetes screening, and provide nutritional counseling for effective management.

Community Health Education: Address socioeconomic disparities by providing financial and social support to pregnant women. Promote at least four ANC visits, encourage lifestyle changes, and continuous glucose monitoring to improve diabetes management during pregnancy.

Investigate the genetic diversity and antimicrobial resistance mechanisms of Listeria monocytogenes strains isolated from women with spontaneous abortion in Uganda. This research could provide insights into strain virulence and resistance profiles, informing targeted treatment strategies and public health interventions.

Abbreviation	Meaning
DM	Diabetes Mellitus
GDM	Gestational Diabetes Mellitus
NICU	Neonatal Intensive Care Unit
ANC	Antenatal Care
aOR	Adjusted Odds Ratio
cOR	Crude Odds Ratio
CI	Confidence Interval
GWG	Gestational Weight Gain
HbA1c	Hemoglobin A1c
LGA	Large for Gestational Age
UGX	Uganda Shillings
LMICs	Low- and Middle-Income Countries
REC	Research Ethics Committee
KIU	Kampala International University
JRRH	Jinja Regional Referral Hospital
LRRH	Lira Regional Referral Hospital
HRRH	Hoima Regional Referral Hospital
NICE	National Institute for Health and Care Excellence
CGM	Continuous Glucose Monitoring

8.1 Consent for publications: Not applicable to this study.

8.2 Availability of data and material: The datasets utilized in this study can be obtained from the corresponding author upon request. Please contact Sharifah Namutebi via email at [email protected].

8.3 Conflict of interest: There are no conflicts of interest related to this study.

8.4 Funding: This study did not receive any grants or funding.

8.5 Author contributions: SN served as the principal investigator, contributing to the study design, data collection, analysis, and initial manuscript drafting. MK, SB, PO and AD contributed to the discussion and interpretation of study findings. IB, and AB supervised the study.

8.6 Acknowledgment: We extend our gratitude to all the patients who participated in this study.

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Competing interest reported. There are no conflicts of interest related to this study.

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Factors linked to early adverse neonatal outcomes in diabetic pregnant women at selected Ugandan hospitals: A prospective cohort study

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Abstract

Background

Methods

Results

Conclusions

Figures

1. Introduction

1.2 Study Objectives

2. Materials and Methods

2.6 Data collection procedure:

2.6.1 Training of Research Assistants

2.6.2 Data collecting tools

2.6.3 Flow of Participants during Data Collection

3. Results

3.1 Flow of Study Participants: In Fig. 1 below, the flow of study participants is illustrated.

3.2 Descriptive characteristics of study participants

3.3 Incidence of early adverse neonatal outcomes among mothers with diabetes mellitus

3.4 Factors associated with early adverse neonatal outcome among mothers with diabetes

4. Discussion

4.1 Incidence of early adverse neonatal outcomes among mothers with diabetes mellitus

4.2 Description early adverse outcomes among neonates born to mothers with diabetes

4.3 Factors associated with early adverse neonatal outcome among others with diabetes mellitus.

5. Conclusions

6. Recommendations

7. Further area of study

Abbreviations

Declarations

References

Additional Declarations

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Version 1