Maternal metabolic conditions as predictors of breastfeeding outcomes: Insights from an Australian cohort study

Abstract

Introduction

Breastfeeding represents an important opportunity to optimize health outcomes for both mother and infant, particularly in the context of maternal metabolic conditions such as diabetes and polycystic ovary syndrome. However, evidence suggests that women affected by these conditions breastfeed at reduced rates and durations. Our aim was to use the large, prospective, community‐based Australian Longitudinal Study on Women's Health (ALSWH) to conduct an in‐depth exploratory analysis of breastfeeding outcomes in Australian women affected by key maternal metabolic conditions.

Material and Methods

Data from 12 920 pregnancies to 5605 women from the 1973–1978 birth cohort of the ALSWH were examined. Univariable and multivariable regression using generalized estimating equation models were applied to assess breastfeeding initiation and duration (outcome measures) in relation to key self‐reported maternal metabolic diagnoses (pre‐gestational type 1 and type 2 diabetes, gestational diabetes, and polycystic ovary syndrome; main explanatory variables). Key sociodemographic and clinical covariates were also considered.

Results

Results showed no significant association between specific maternal metabolic diagnoses (pre‐gestational or gestational diabetes, or polycystic ovary syndrome) and breastfeeding outcomes. However, maternal body mass index emerged as a key predictor of suboptimal breastfeeding outcomes. Pregnancies affected by maternal obesity were associated with a 2.1‐fold increase in the odds of not initiating breastfeeding, after adjusting for other key variables (95% CI 1.67 to 2.60, p < 0.01). Maternal overweight and obesity were, respectively, associated with an adjusted 1.4‐fold (95% CI 1.20 to 1.55, p < 0.01) and 1.8‐fold increase (95% CI 1.60 to 2.10, p < 0.01) in the odds of a breastfeeding duration less than 6 months.

Conclusions

Maternal obesity, rather than any specific maternal metabolic condition, appears to be a key predictor of breastfeeding outcomes in Australian women.

This study uses the large, prospective, community‐based Australian Longitudinal Study on Women's Health to conduct an in‐depth exploratory analysis of breastfeeding in Australian women affected by key maternal metabolic conditions (including diabetes mellitus and polycystic ovary syndrome). Findings suggest that maternal obesity, rather than specific maternal metabolic conditions, predicts suboptimal breastfeeding outcomes.

Abbreviations

ALSWH

Australian Longitudinal Study on Women's Health

GDM

gestational diabetes mellitus

NICU

neonatal intensive care unit

PCOS

polycystic ovary syndrome

SCN

special care nursery

T1DM

type 1 diabetes mellitus

T2DM

type 2 diabetes mellitus

Key message.

Data from a large, community‐based cohort of Australian women suggest that maternal obesity (rather than specific maternal metabolic conditions) predicts suboptimal breastfeeding outcomes among Australian women.

1. INTRODUCTION

Metabolic conditions are a significant public health concern among reproductive‐aged women globally. In Australia, 1.2% of women aged 15–44 years were affected by either type 1 or 2 diabetes mellitus (T1DM; T2DM) in 2020. ¹ Gestational diabetes mellitus (GDM) currently affects some 17% of Australian pregnancies, with a recent rise in prevalence related to altered diagnostic definitions as well as to rising rates of overweight and obesity and changing demography (rising maternal age and increasing ethnic diversity). ¹ Polycystic ovary syndrome (PCOS) has a prevalence of around 10% of reproductive‐aged women (with many remaining undiagnosed) and is often underpinned by insulin resistance and/or accompanied by obesity. ² , ³

Breastfeeding represents an important opportunity to optimize metabolic health outcomes for both mother and child. The Australian National Health and Medical Research Council (NHMRC) infant feeding guidelines recommend that infants be exclusively breastfed until around 6 months of age and that breastfeeding continues until 12 months of age and beyond, “for as long as the mother and child desire.” ⁴ Breastfed offspring have a reduced risk of developing childhood obesity, ⁵ as well as both T1DM ⁶ and T2DM. ⁷ Crucially, breastfeeding also modifies metabolic risk in the mother, promoting postpartum weight loss and improving glucose tolerance and insulin sensitivity. ⁸ Evidence suggests that breastfeeding reduces the risk of progression to T2DM among women with a history of GDM. ⁹ , ¹⁰ Breastfeeding may also reduce chronic disease burden in mothers in other ways, with studies suggesting reduced rates of metabolic syndrome and cardiovascular disease, more favorable adipokine profiles, and reduced lifetime risk of breast and ovarian cancer. ¹¹

Despite the clear metabolic benefits of breastfeeding for both mothers and infants, international observational evidence suggests that women with metabolic disorders such as diabetes and PCOS breastfeed at reduced rates and durations than childbearing women without metabolic disease. ¹² , ¹³ , ¹⁴ Suboptimal breastfeeding outcomes in these populations are likely multifactorial. Obstetric complications such as pre‐term delivery, instrumental delivery, and cesarean sections are disproportionately common among women affected by maternal diabetes and/or obesity; and infants born to mothers with diabetes also have increased rates of neonatal hypoglycemia and special care nursery (SCN) admission. These clinical factors may delay critical early breast contact and impair successful breastfeeding initiation. ¹⁵ Women with diabetes also commonly experience delayed onset of lactogenesis, ongoing reduced milk supply, and fluctuating maternal blood glucose levels; all of which present physiological barriers to sustained exclusive breastfeeding. ¹⁵ , ¹⁶ , ¹⁷ In women with PCOS, hyperandrogenism and insulin resistance may contribute to breastfeeding difficulties, ² and a link to insufficient mammary glandular tissue has been postulated. ¹⁸

To date, the limited available Australian data support the finding that women with metabolic diseases breastfeed at reduced rates and durations compared to those without these conditions. ² , ¹⁹ , ²⁰ However, studies are few in number, and large‐scale population data are lacking. A clearer picture of breastfeeding outcomes in maternal metabolic disease, and a more in‐depth understanding of the interactions with other key demographic and clinical factors, will help to inform future strategies to target those most at risk. This study aims to use the large, prospective, community‐based Australian Longitudinal Study on Women's Health (ALSWH) to conduct an in‐depth exploratory analysis of breastfeeding epidemiology in Australian women affected by key maternal metabolic conditions (T1DM, T2DM, GDM, and PCOS).

2. MATERIAL AND METHODS

The ALSWH is an ongoing, longitudinal, population‐based survey of more than 57 000 Australian women across four birth cohorts. Initial recruitment took place in 1996, with participants randomly selected from the National Health Insurance (Medicare) database, consisting of almost all Australian citizens and permanent residents. Women were recruited nationally, with deliberate oversampling from rural and remote areas. The study has ongoing ethical approval from the Human Research Ethics Committees of the Universities of Newcastle and Queensland, respectively (approval numbers: H‐076‐0795 and 2004000224, approval date July 26, 1995, expiration date December 31, 2030). Written informed consent was provided by participants. Full data on recruitment, participant retention, and methodology are available on the ALSWH website, https://alswh.org.au/.

Data for this study were obtained from the 1973 to 1978 birth cohort of the ALSWH database. Following their recruitment in 1996, when aged 18–23 years old (n = 14 247), women from this cohort were invited to participate in the first follow‐up survey in 2000 and then every 3 years thereafter. The questionnaires include questions on general health and well‐being, diabetes status, PCOS, reproductive health, birth outcomes, pregnancy and delivery complications, breastfeeding, anthropometric and sociodemographic factors, and health behavior. Early surveys were mailed paper questionnaires, but from 2013 onward, women have been given the option to complete an online or a paper questionnaire.

Sample selection for this analysis focused on the five most recent waves of survey data from the 1973 to 1978 cohort (2009, 2012, 2015, 2018, and 2021; earlier waves of survey data lacked sufficient detail on self‐reported metabolic diagnoses). Women were selected for this analysis if they had participated in Survey 5 in 2009 (aged 31–36 years), were still participating in Survey 9 in 2021 (aged 43–48 years), and had at any stage reported one or more live births with outcomes in the study's birth events data (n = 5605 women). The analysis was cross‐sectional, focusing on the latest (2021) survey data, including the birth events data. However, the iterative nature of the surveys enabled selected key variables to be validated across the four previous surveys, particularly those pertaining to self‐reported maternal metabolic diagnoses and maternal body mass index (BMI). This approach aimed to reduce the impact of recall bias on the reporting of key variables.

Each pregnancy that resulted in the birth of a live infant was considered a separate “pregnancy event,” so the number of pregnancy events (n = 12 920) exceeded the number of eligible survey participants (n = 5605).

2.1. Maternal metabolic predictors

Self‐reported diagnoses of T1DM, T2DM, or PCOS were examined across five surveys (2009, 2012, 2015, 2018, and 2021). These were based on each participant's response to the question “In the last 3 years, have you been diagnosed with or treated for: insulin dependent (type 1) diabetes/non‐insulin dependent (type 2) diabetes/polycystic ovary syndrome?”. While participants may not report health conditions consistently, these conditions are typically considered to be enduring. As such, if one of these conditions was reported by a participant on Survey 5 in 2009 (used as the baseline for the purposes of this variable), it was applied to all the participant's pregnancy events prior to that date, and all subsequent pregnancy events for that participant. If a condition was first reported by a participant on any of the subsequent surveys (Surveys 6–9), the same condition was applied only to pregnancy events occurring at/after the year of first report.

Examination of responses to questions around T1DM and T2DM over time revealed some inconsistencies in self‐reporting of diabetes type, especially as the conditions were defined in brackets in the surveys as “insulin dependent diabetes” and “non‐insulin dependent diabetes,” respectively. As such, participants who reported T1DM and T2DM interchangeably over the five surveys examined were deemed most likely to have T2DM and were excluded from the T1DM group.

Self‐reported diagnoses of GDM were reported per pregnancy and were captured from the pregnancy outcome dataset derived from the most recent (2021) survey.

2.2. Breastfeeding outcome measures

In each survey, women were asked to individually report the number of complete months they had breastfed each of their children. Breastfeeding duration data for each pregnancy event were captured cross‐sectionally from the pregnancy outcome dataset derived from the most recent (2021) survey. For the purposes of this analysis, breastfeeding for one or more complete months was considered “yes” for breastfeeding initiation for that pregnancy event (coded as a binary variable). Breastfeeding for six or more complete months was considered “yes” for breastfeeding to 6 months or more for that pregnancy event (coded as a separate binary variable). If women breastfed for 1–6 months, they were categorized as having initiated breastfeeding but not breastfeeding for more than 6 months. The number of months of breastfeeding was also captured as a continuous variable for each pregnancy event.

2.3. Selected covariates

Maternal BMI was calculated from self‐reported maternal height and weight. Acknowledging that the most recent BMI may not accurately reflect BMI at the time of the reported pregnancies, maternal BMI was captured across 2009, 2012, 2015, 2018, and 2021 surveys, and a mean BMI was derived. This was subsequently classified using World Health Organization criteria as: underweight BMI <18.5 kg/m², healthy weight BMI 18.5–24.9 kg/m², overweight BMI 25.0–29.9 kg/m², and obese BMI ≥30 kg/m². The applicable BMI category was applied to all pregnancy events for each participant. This methodology is consistent with previous comparable analyses in the ALSWH. ²

Other self‐reported sociodemographic variables such as maternal education, occupation, smoking status, and ability to manage current income were captured cross‐sectionally based on responses to the most recent (2021) survey. These were applied to all of a participant's pregnancy events.

Key pregnancy, obstetric, and postpartum variables were also self‐reported per pregnancy event, with responses captured from the pregnancy outcome dataset associated with the 2021 survey. Variables were chosen based on their potential to impact breastfeeding initiation and duration, consistent with prior analysis in the ALSWH. ² , ²¹ These included antenatal and/or postnatal depression, antenatal and/or postnatal anxiety, GDM, hypertension during pregnancy, premature birth (defined as <36 weeks gestation), cesarean section, instrumental delivery, low birthweight baby (<2.5 kg), and baby requiring SCN or neonatal intensive care unit (NICU) admission.

2.4. Statistical analyses

Continuous variables were summarized as means with standard deviation (if normally distributed) or as medians with range (where distribution was non‐parametric). Categorical outcomes were reported as counts and percentages. Differences in breastfeeding outcomes according to maternal metabolic diagnosis were assessed using t‐tests or Wilcoxon rank‐sum tests for normally or non‐normally distributed continuous variables, respectively, and chi‐squared tests were used for categorical variables.

To assess the relationship between maternal metabolic diagnosis and key breastfeeding outcomes (likelihood of not initiating breastfeeding and likelihood of breastfeeding duration <6 months), univariable and multivariable logistic regression analyses were performed for each maternal metabolic condition. Generalized estimating equation models with an exchangeable correlation structure were used to account for clustering of pregnancy events under individual participants. ²² Multivariable regression models accounted for key potential confounding covariates including maternal age, parity, pregnancy/obstetric/postpartum factors, and sociodemographic factors as described above. Included covariates were selected based on known or suspected prognostic importance for the outcome of interest, with reference to previous similar analyses ² , ²¹ and to relevant clinical and epidemiological literature; as well as to the results of univariable analysis. As the original ALSWH recruitment methodology involved deliberate oversampling from rural and remote areas, logistic regression estimates were also adjusted by area of residence.

All statistical analyses were performed using STATA software version 17.0 (StataCorp LLC, College Station, Texas, USA).

3. RESULTS

Study participation, as described in the Methods section, is depicted in Figure 1. From n = 5605 eligible participants, there were a total of n = 12 920 reported pregnancies.

FIGURE 1.

Participant selection and eligibility for this study of maternal metabolic conditions and breastfeeding outcomes among the 1973–1978 birth cohort of the ALSWH. ALSWH, Australian Longitudinal Study on Women's Health.

3.1. Maternal metabolic and other conditions

T1DM and T2DM were self‐reported in 0.16% and 0.88% of pregnancies, whereas 5.4% and 4.7% were affected by GDM and PCOS, respectively. Maternal age at pregnancy was higher in GDM‐ and PCOS‐affected pregnancies than in pregnancies unaffected by these conditions (Table 1). Maternal BMI was also higher in T2DM, GDM, and PCOS pregnancies than in unaffected control pregnancies (Table 1). In the cohort overall, 24.3% of pregnancies occurred in participants classified as “obese” by WHO criteria. For T2DM, GDM, and PCOS pregnancies, the prevalence of maternal obesity was 49.1%, 38.7%, and 38.7%, respectively (Table 1).

TABLE 1.

Participant characteristics according to metabolic diagnosis among pregnancies in the 1973–1978 ALSWH birth cohort (n = 12 920).

Characteristics	All pregnancy events (n = 12  920)	T1DM pregnancies (n = 21)	Non‐T1DM pregnancies (n = 12 899)	p	T2DM pregnancies (n = 114)	Non‐T2DM pregnancies (n = 12 806)	p	GDM pregnancies (n = 697)	Non‐GDM pregnancies (n = 12 160)	p	PCOS pregnancies (n = 601)	Non‐PCOS pregnancies (n = 12 319)	p
Age (years) at pregnancy	31.4 ± 5.2	32.7 ± 5.7	31.4 ± 5.2	0.26	32.1 ± 6.1	31.4 ± 5.2	0.18	34.3 ± 5.5	31.3 ± 5.2	<0.01	33.0 ± 5.3	31.3 ± 5.2	<0.01
Mean BMI	26.9 ± 5.8	28.6 ± 6.4	26.9 ± 5.8	0.17	31.7 ± 9.7	26.8 ± 5.8	<0.01	29.2 ± 6.9	26.7 ± 5.7	<0.01	28.9 ± 6.5	26.8 ± 5.8	<0.01
BMI category
Underweight	132 (1.0)	0	132 (1.0)		0	132 (1.0)		3 (0.4)	129 (1.1)		6 (1.0)	126 (1.0)
Healthy weight	5668 (44.3)	10 (47.6)	5658 (44.3)	0.60	37 (32.5)	5631 (44.4)	<0.01	199 (29.0)	5451 (45.2)	<0.01	190 (31.8)	5478 (44.9)	<0.01
Overweight	3887 (30.4)	4 (19.1)	3883 (30.4)		21 (18.4)	3866 (30.5)		219 (31.9)	3658 (30.4)		170 (28.5)	3717 (30.5)
Obese	3105 (24.3)	7 (33.3)	3098 (24.3)		56 (49.1)	3049 (24.1)		266 (38.7)	2811 (23.3)		231 (38.7)	2874 (23.6)
Parity prior to index pregnancy
0	5558 (43.0)	7 (33.3)	5551 (43.0)		50 (43.9)	5508 (43.0)		327 (46.9)	5201 (42.8)		262 (43.6)	5296 (43.0)
1	4715 (36.5)	9 (42.9)	4706 (36.5)	0.75	42 (36.8)	4673 (36.5)	0.36	216 (31.0)	4476 (36.8)	<0.01	229 (38.1)	4486 (36.4)	0.50
2	1904 (14.7)	3 (14.3)	1901 (14.7)		12 (10.5)	1892 (14.8)		93 (13.3)	1804 (14.8)		76 (12.7)	1828 (14.8)
3+	743 (5.8)	2 (9.5)	741 (5.7)		10 (8.8)	733 (5.7)		61 (8.8)	679 (5.6)		34 (5.7)	709 (5.8)
Maternal education
Year 12 or less	1621 (13.4)	9 (50)	1612 (13.4)		32 (31.1)	1589 (13.3)		83 (12.7)	1531 (13.5)		70 (12.5)	1551 (13.5)
Trade/certificate	3505 (29.0)	3 (16.7)	3502 (29.0)	<0.01	33 (32.0)	3472 (29.0)	<0.01	207 (31.8)	3278 (28.8)	0.27	165 (29.6)	3340 (29.0)	0.82
University/higher degree	6958 (57.6)	6 (33.3)	6952 (57.6)		38 (36.9)	6920 (57.8)		362 (55.5)	6575 (57.8)		323 (57.9)	6635 (57.6)
Maternal occupation
No paid job	1321 (10.8)	5 (23.8)	1316 (10.8)		11 (10.7)	1310 (10.8)		73 (11.1)	1243 (10.8)		74 (13.1)	1247 (10.7)
Clerical/sales/service/production/transport worker/laborer	695 (5.7)	3 (14.3)	692 (5.7)		10 (9.7)	685 (5.7)		34 (5.2)	656 (5.7)		17 (3.0)	678 (5.8)
Associate professional/trades/service worker	3630 (29.7)	9 (42.9)	3621 (29.7)	<0.01	21 (20.4)	3609 (29.8)	0.09	210 (31.9)	3402 (29.6)	0.58	175 (30.9)	3455 (29.7)	0.01
Professional/manager/administrator	6564 (53.8)	4 (19.1)	6560 (53.8)		61 (59.2)	6503 (53.7)		342 (51.9)	6203 (53.9)		300 (53.0)	6264 (53.8)
Maternal income (ability to manage available income)
Significant difficulty	1257 (10.2)	3 (14.3)	1254 (10.2)		5 (4.9)	1252 (10.3)		78 (11.8)	1171 (10.1)		70 (12.3)	1187 (10.1)
Moderate/neutral	8149 (66.3)	15 (71.4)	8134 (66.3)	0.56	80 (77.7)	8069 (66.2)	0.04	458 (69.1)	7657 (66.1)	0.02	355 (62.5)	7794 (66.5)	0.10
No concerns	2884 (23.5)	3 (14.3)	2881 (23.5)		18 (17.5)	2866 (23.5)		127 (19.2)	2752 (23.8)		143 (25.2)	2741 (23.4)
Maternal smoking status
Current %	1091 (8.6)	3 (14.3)	1088 (8.6)		15 (14.4)	1076 (8.6)		49 (7.2)	1027 (8.6)		41 (7.0)	1050 (8.7)
Ex‐smoker %	3641 (28.7)	8 (38.1)	3633 (28.7)	0.34	29 (27.9)	3612 (28.8)	0.10	234 (34.4)	3391 (28.4)	<0.01	161 (27.4)	3480 (28.8)	0.21
Never smoker %	7936 (62.7)	10 (47.6)	7926 (62.7)		60 (57.7)	7876 (62.7)		398 (58.4)	7510 (63.0)		385 (65.6)	7551 (62.5)
Area of residence (Australia)
Major cities	6685 (56.2)	14 (66.7)	6671 (56.2)		53 (51.5)	6632 (56.2)		380 (59.3)	6288 (56.1)		320 (59.2)	6365 (56.0)
Inner regional	3463 (29.1)	5 (23.8)	3458 (29.1)		34 (33.0)	3429 (29.1)		172 (26.8)	3271 (29.2)		143 (26.4)	3320 (29.2)
Outer regional	1564 (13.1)	2 (9.5)	1562 (13.2)	0.89	16 (15.5)	1548 (13.1)	0.55	80 (12.5)	1474 (13.2)	0.58	69 (12.8)	1495 (13.2)	0.61
Remote	140 (1.2)	0	140 (1.2)		0	140 (1.2)		6 (0.9)	134 (1.2)		6 (1.1)	134 (1.2)
Very remote	48 (0.4)	0	48 (0.4)		0	48 (0.4)		3 (0.5)	45 (0.4)		3 (0.6)	45 (0.4)
Pregnancy and postpartum variables
AN and/or PN anxiety	876 (6.8)	1 (4.8)	875 (6.8)	0.71	9 (7.9)	867 (6.8)	0.63	86 (12.3)	786 (6.5)	<0.01	60 (10.0)	816 (6.6)	<0.01
AN and/or PN depression	1274 (9.9)	0	1274 (9.9)	0.13	23 (20.2)	1251 (9.8)	<0.01	105 (15.1)	1165 (9.6)	<0.01	86 (14.3)	1188 (9.6)	<0.01
GDM	697 (5.4)	—	—	—	—	—	—	—	—	—	80 (13.3)	617 (5.0)	<0.01
HTN during pregnancy	930 (7.2)	5 (23.8)	925 (7.2)	<0.01	21 (18.4)	909 (7.1)	<0.01	99 (14.2)	828 (6.8)	<0.01	67 (11.2)	863 (7.0)	<0.01
Delivery variables
Prem birth (<36 weeks)	948 (7.4)	4 (19.1)	944 (7.4)	0.04	13 (11.4)	935 (7.3)	0.10	74 (10.7)	868 (7.2)	<0.01	84 (14.0)	864 (7.1)	<0.01
Cesarean section	3557 (27.5)	10 (47.6)	3547 (27.5)	0.04	45 (39.5)	3512 (27.4)	<0.01	287 (41.2)	3255 (26.8)	<0.01	219 (36.4)	3338 (27.1)	<0.01
Instrumental delivery	1682 (13.1)	1 (4.8)	1681 (13.1)	0.26	14 (12.3)	1668 (13.1)	0.80	91 (13.2)	1587 (13.1)	0.97	78 (13.0)	1604 (13.1)	0.94
Low birthweight (<2.5 kg)	643 (5.0)	3 (14.3)	640 (5.0)	0.05	9 (7.9)	634 (5.0)	0.15	54 (7.8)	585 (4.8)	<0.01	44 (7.3)	599 (4.9)	<0.01
SCN/NICU admission	1483 (11.6)	6 (28.6)	1477 (11.6)	0.02	29 (25.7)	1454 (11.5)	<0.01	150 (21.7)	1328 (11.0)	<0.01	101 (16.8)	1382 (11.3)	<0.01

Note: Continuous variables are presented as mean ± SD, and categorical variables as n (%). Bold p values are statistically significant (p ≤ 0.05). The χ ² test for categorical variables and t‐test for continuous variables were used to test for differences between the two groups.

Abbreviations: AN, antenatal; BMI, body mass index; GDM, gestational diabetes mellitus; HTN, hypertension; NICU, neonatal intensive care unit; PCOS, polycystic ovary syndrome; PN, postnatal; SCN, special care nursery; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus.

Antenatal and/or postnatal mood disorders were significantly more prevalent in pregnancies affected by T2DM, GDM, and PCOS (but not T1DM) when compared with pregnancies unaffected by these conditions (Table 1). GDM was significantly more common in PCOS than non‐PCOS pregnancies (13.3% vs 5.0%, p < 0.01). All four metabolic conditions were associated with an increased prevalence of hypertension during pregnancy, p < 0.01 (Table 1).

Obstetric and delivery complications were more likely to occur in pregnancies affected by maternal metabolic disease. All four metabolic conditions were associated with an increased reported prevalence of cesarean sections and SCN/NICU admissions when compared with unaffected pregnancies (Table 1). Premature delivery and low birthweight were more prevalent among T1DM, GDM, and PCOS (but not T2DM) pregnancies compared with their respective controls.

3.2. Breastfeeding practices and metabolic conditions

The prevalence of breastfeeding initiation was significantly lower for T1DM pregnancies than for those without T1DM (81.0% vs 92.6%, p = 0.04). Breastfeeding for six complete months or more was significantly less common following T2DM pregnancy (57.4% vs 67.4%, p = 0.03) and GDM pregnancy (62.6% vs 67.6%, p < 0.01), than in women without these conditions (Table 2). Median reported breastfeeding durations (months) following pregnancies affected by all four maternal metabolic disease states were shorter than for unaffected pregnancies: this difference achieved statistical significance for T2DM (6 months vs 9 months, p < 0.01) and PCOS (7 months vs 9 months, p < 0.01) (Table 2), but not for T1DM or GDM.

TABLE 2.

Breastfeeding durations according to metabolic diagnosis following pregnancies in the 1973–1978 ALSWH birth cohort (n = 12 576).

Characteristics	All pregnancy events (n = 12 576)	T1DM pregnancies (n = 21)	Non‐T1DM pregnancies (n = 12 555)	p	T2DM pregnancies (n = 108)	Non‐T2DM pregnancies (n = 12 486)	p	GDM pregnancies (n = 669)	Non‐GDM pregnancies (n = 11 886)	p	PCOS pregnancies (n = 591)	Non‐PCOS pregnancies (n = 11 985)	p
Median (range) BF duration, months	9 (0–84)	7 (0–24)	9 (0–84)	0.34	6 (0–24)	9 (0–84)	<0.01	8 (0–78)	9 (0–84)	0.77	7 (0–60)	9 (0–84)	<0.01
BF to one complete month or more (= “initiation”), n (%)	11 646 (92.6)	17 (81.0)	11 629 (92.6)	0.04	95 (88.0)	11 551 (92.7)	0.06	616 (92.1)	11 009 (92.6)	0.60	538 (91.0)	11 108 (92.7)	0.13
BF to six complete months or more, n (%)	8468 (67.3)	11 (52.4)	8457 (67.4)	0.14	62 (57.4)	8406 (67.4)	0.03	419 (62.6)	8035 (67.6)	<0.01	378 (64.0)	8090 (67.5)	0.07

Note: Breastfeeding duration (months) was non‐parametrically distributed, so reported values are median (range). The two‐sample Wilcoxon rank‐sum test was used to test for differences between the two groups. Categorical variables are reported as n (%), with the χ ² test used to test for differences between groups. Bold p values are statistically significant (p < 0.05).

Abbreviations: BF, breastfeeding; GDM, gestational diabetes mellitus; PCOS, polycystic ovary syndrome; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus.

3.3. Factors associated with breastfeeding initiation and durations

Results of univariable and multivariable logistic regression analyses did not suggest that T1DM, T2DM, GDM, or PCOS was associated with either no initiation of breastfeeding (Table 3) or with a breastfeeding duration of less than 6 months (Table 4). However, maternal obesity showed a significant association with both outcomes. Pregnancies affected by maternal obesity were associated with a 2.1‐fold increase in the odds of not initiating breastfeeding, after adjusting for other key variables (Table 3). Maternal overweight and obesity were associated with a 1.4‐fold and 1.8‐fold increases (respectively) in the odds of a breastfeeding duration of less than 6 months, after adjustment for other variables (Table 4).

TABLE 3.

Association (OR) of T1DM, T2DM, GDM, PCOS, BMI, demographic data, and pregnancy complications with no initiation of breastfeeding (breastfeeding to 1 complete month or less) among pregnancies in the 1973–1978 ALSWH birth cohort (n = 12 576).

	Univariable results			Multivariable results
	OR	95% CI	p	OR	95% CI	p
Maternal metabolic diagnosis
T1DM	2.88	0.83–10.0	0.10	2.63	0.73–9.51	0.14
T2DM	1.40	0.65–3.01	0.39	1.06	0.48–2.34	0.88
GDM	1.08	0.84–1.38	0.56	0.94	0.72–1.24	0.66
PCOS	1.26	0.88–1.79	0.21	1.14	0.78–1.67	0.49
BMI
Underweight	0.56	0.16–2.02	0.38	0.76	0.22–2.60	0.66
Healthy weight (ref)	1	—	—	1	—	—
Overweight	1.30	1.04–1.62	0.02	1.19	0.95–1.51	0.13
Obese	2.51	2.05–3.09	<0.01	2.08	1.67–2.60	<0.01
Parity prior to index pregnancy
0 (ref)	1	—	—	1	—	—
1	1.10	0.99–1.22	0.07	1.15	1.02–1.30	0.02
2	1.10	0.95–1.27	0.21	1.14	0.97–1.35	0.12
3+	1.04	0.82–1.32	0.74	1.07	0.82–1.39	0.63
Maternal educational level
Year 12 or less (ref)	1	—	—	1	—	—
Trade/certificate	0.82	0.64–1.04	0.11	0.85	0.65–1.09	0.20
University/higher degree	0.39	0.31–0.50	<0.01	0.52	0.39–0.70	<0.01
Maternal occupation category
No paid job (ref)	1	—	—	1	—	—
Clerical/sales/service/production/transport worker/laborer	1.36	0.92–2.01	0.12	1.18	0.78–1.79	0.42
Associate professional/trades/service worker	1.04	0.78–1.38	0.81	0.99	0.73–1.35	0.96
Professional/manager/administrator	0.57	0.43–0.76	<0.01	0.79	0.58–1.09	0.15
Maternal income category (ability to manage available income)
Significant difficulty (ref)	1	—	—	1	—	—
Moderate/neutral	0.73	0.56–0.96	0.02	0.91	0.69–1.20	0.49
No concerns	0.53	0.39–0.73	<0.01	0.82	0.59–1.15	0.25
Maternal smoking status
Current %	1.53	1.16–2.03	<0.01	1.24	0.92–1.67	0.15
Ex‐smoker %	1.05	0.87–1.28	0.61	0.95	0.77–1.17	0.63
Never smoker % (ref)	1	—	—	1	—	—
Area of residence (Australia)
Major cities (ref)	1	—	—	1	—	—
Inner regional	1.01	0.83–1.24	0.92	0.82	0.67–1.02	0.07
Outer regional	1.07	0.82–1.40	0.63	0.85	0.64–1.13	0.26
Remote	0.71	0.27–1.85	0.48	0.39	0.13–1.19	0.10
Very remote	1.95	0.64–5.94	0.24	1.47	0.46–4.63	0.52
Pregnancy and postpartum variables
AN and/or PN anxiety	0.92	0.72–1.17	0.48	0.81	0.60–1.08	0.15
AN and/or PN depression	1.14	0.94–1.37	0.18	1.08	0.87–1.34	0.49
HTN during pregnancy	1.12	0.90–1.39	0.30	1.01	0.80–1.27	0.94
Delivery variables
Premature birth (<36 weeks)	1.58	1.30–1.91	<0.01	1.25	0.96–1.61	0.10
Cesarean section	1.25	1.09–1.44	<0.01	1.23	1.05–1.44	0.01
Instrumental delivery	0.92	0.78–1.09	0.35	1.09	0.90–1.32	0.40
Low birthweight (<2.5 kg)	1.68	1.35–2.09	<0.01	1.33	0.99–1.79	0.06
SCN/NICU admission	1.31	1.12–1.53	<0.01	1.06	0.88–1.29	0.52

Note: Data presented as odds ratios with 95% confidence intervals based on logistic regression analyses with the dependent outcome: no initiation of breastfeeding (breastfeeding for one complete month or less). Generalized estimating equation methodology was used to account for clustering of pregnancies under individual participants. In multivariable model, each variable is adjusted for all other variables. Ref denotes reference category. Bold p values are statistically significant (p < 0.05).

Abbreviations: AN, antenatal; BMI, body mass index; CI, confidence interval; GDM, gestational diabetes mellitus; HTN, hypertension; NICU, neonatal intensive care unit; OR, odds ratio; PCOS, polycystic ovary syndrome; PN, postnatal; SCN, special care nursery; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus.

TABLE 4.

Association (OR) of T1DM, T2DM, GDM, PCOS, BMI, demographic data, and pregnancy complications with breastfeeding duration of less than 6 months, among pregnancies in the 1973–1978 ALSWH birth cohort (n = 12 576).

	Univariable results			Multivariable results
	OR	95% CI	p	OR	95% CI	p
Maternal metabolic diagnosis
T1DM	1.86	0.69–5.00	0.22	2.04	0.69–6.03	0.20
T2DM	1.53	0.95–2.46	0.08	1.16	0.69–1.96	0.57
GDM	1.13	0.98–1.30	0.10	1.03	0.88–1.22	0.69
PCOS	1.09	0.88–1.36	0.42	0.91	0.71–1.15	0.42
BMI
Underweight %	0.79	0.46–1.37	0.40	0.96	0.53–1.71	0.88
Healthy weight % (ref)	1	—	—	1	—	—
Overweight %	1.48	1.32–1.67	<0.01	1.36	1.20–1.55	<0.01
Obese %	2.29	2.03–2.59	<0.01	1.83	1.60–2.10	<0.01
Parity prior to index pregnancy
0 (ref)	1	—	—	1	—	—
1	0.92	0.87–0.98	<0.01	0.97	0.90–1.04	0.34
2	0.78	0.72–0.85	<0.01	0.80	0.73–0.89	<0.01
3+	0.71	0.62–0.82	<0.01	0.72	0.61–0.84	<0.01
Maternal educational level
Year 12 or less (ref)	1	—	—	1	—	—
Trade/certificate	0.72	0.62–0.85	<0.01	0.74	0.62–0.87	<0.01
University/higher degree	0.35	0.30–0.41	<0.01	0.45	0.37–0.53	<0.01
Maternal occupation category
No paid job (ref)	1	—	—	1	—	—
Clerical/sales/service/production/transport worker/laborer	1.21	0.94–1.56	0.14	0.97	0.74–1.28	0.84
Associate professional/trades/service worker	1.07	0.90–1.27	0.46	1.07	0.88–1.30	0.50
Professional/manager/administrator	0.60	0.51–0.71	<0.01	0.89	0.74–1.08	0.25
Maternal income category (ability to manage available income)
Significant difficulty (ref)	1	—	—	1	—	—
Moderate/neutral	0.62	0.53–0.73	<0.01	0.81	0.68–0.96	0.02
No concerns	0.48	0.40–0.57	<0.01	0.78	0.63–0.95	0.01
Maternal smoking status
Current %	2.22	1.87–2.63	<0.01	1.62	1.34–1.95	<0.01
Ex‐smoker %	1.29	1.15–1.44	<0.01	1.10	0.97–1.23	0.13
Never smoker % (ref)	1	—	—	1	—	—
Area of residence (Australia)
Major cities (ref)	1	—	—	1	—	—
Inner regional	1.14	1.02–1.28	0.02	0.97	0.86–1.10	0.64
Outer regional	1.22	1.04–1.42	0.01	0.99	0.84–1.17	0.90
Remote	1.23	0.77–1.95	0.38	0.95	0.59–1.54	0.84
Very remote	1.63	0.74–3.56	0.22	1.41	0.63–3.17	0.40
Pregnancy and postpartum variables
AN and/or PN anxiety	1.31	1.15–1.49	<0.01	1.16	0.99–1.36	0.07
AN and/or PN depression	1.37	1.23–1.53	<0.01	1.24	1.09–1.41	<0.01
HTN during pregnancy	1.17	1.04–1.33	0.01	0.94	0.81–1.08	0.38
Delivery variables
Premature birth (<36 weeks)	1.57	1.39–1.77	<0.01	1.51	1.28–1.77	<0.01
Cesarean section	1.27	1.17–1.38	<0.01	1.20	1.10–1.32	<0.01
Instrumental delivery	1.02	0.93–1.12	0.65	1.01	0.91–1.13	0.82
Low birthweight (<2.5 kg)	1.36	1.18–1.58	<0.01	1.01	0.84–1.23	0.89
SCN/NICU admission	1.28	1.16–1.40	<0.01	1.10	0.98–0.24	0.10

Note: Data presented as odds ratios with 95% confidence intervals based on logistic regression analyses with the dependent outcome: breastfeeding duration of less than 6 months. Generalized estimating equation methodology was used to account for clustering of pregnancies under individual participants. In multivariable model, each variable is adjusted for all other variables. Ref denotes reference category. Bold p values are statistically significant (p < 0.05).

Abbreviations: AN, antenatal; BMI, body mass index; CI, confidence interval; GDM, gestational diabetes mellitus; HTN, hypertension; ICU, intensive care unit; OR, odds ratio; PCOS, polycystic ovary syndrome; PN, postnatal; SCN, special care nursery; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus.

Broader sociodemographic variables also emerged as significant. Tertiary‐level maternal education was independently associated with lower odds of not initiating breastfeeding (OR 0.52, 95% CI 0.39 to 0.70, p < 0.01) and cesarean delivery with higher odds of not initiating breastfeeding (OR 1.23, 95% CI 1.05 to 1.44, p = 0.01) (Table 3). Higher parity, higher maternal educational attainment, and higher self‐reported financial security were all independently associated with lower odds of breastfeeding for less than 6 months (ORs ranging between 0.45 and 0.81; Table 4). Pregnancies affected by current smoking, antenatal and/or postnatal depression, premature delivery, and cesarean delivery were all independently associated with higher odds of breastfeeding duration of less than 6 months (ORs ranging between 1.20 and 1.62; Table 4).

4. DISCUSSION

This study uses survey data from a large, prospective, community‐based cohort of Australian women to examine key breastfeeding outcomes across pregnancies affected by four common metabolic conditions (T1DM, T2DM, GDM, and PCOS). Our data suggest that none of the named conditions are significantly independently associated with breastfeeding initiation or duration. However, maternal overweight and obesity—which overlap significantly with GDM, T2DM, and PCOS—emerged as significant independent predictors of adverse breastfeeding outcomes (both no initiation of breastfeeding and breastfeeding duration of 6 months or less).

Our study relied on self‐reported maternal diagnoses for all four metabolic conditions, although in each case, participant responses were examined across five consecutive survey waves to increase accuracy. The percentage of pregnancies affected by pre‐gestational T1DM or T2DM were 0.16% and 0.88%, respectively, in our study, which is comparable to current population estimates (2010 data suggest that 0.6% of Australian pregnancies were affected by maternal pre‐gestational diabetes). ²³ For GDM, the reported 5.4% prevalence in our cohort is lower than would be expected based on the current population prevalence (which estimates that 17% of pregnancies are affected), ¹ but is consistent with prevalence estimates from the time the index pregnancies were occurring, mostly in the early 2000s. Rising rates in more recent years relate to increasing maternal age, higher rates of maternal overweight and obesity, and a growing proportion of higher‐risk ethnic groups in the population. ¹ The national endorsement of more stringent diagnostic criteria between 2011 and 2013 may also have contributed. ¹ , ²⁴ Similar principles apply for PCOS: the 4.7% prevalence in our cohort is lower than current population estimates (which suggest a prevalence of approximately 10%), ³ but is broadly consistent with estimates from the time of the index pregnancies. The increasing prevalence of PCOS in Australia since the early 2000s reflects rising rates of obesity among women of reproductive age, more clearly defined diagnostic criteria, and greater awareness among healthcare professionals and the general public after a major international initiative including guidelines and dissemination of information about PCOS. ³ Breastfeeding recommendations from major national and international organizations such as the NHMRC ⁴ and World Health Organization (WHO) ²⁵ have remained broadly consistent over the duration of the captured surveys; emphasizing the importance of immediate skin‐to‐skin contact after birth, and recommending exclusive breastfeeding to 6 months of age, with extended breastfeeding thereafter (alongside suitable complementary foods).

Results of our univariable and multivariable regression analyses provided no evidence to suggest that maternal T1DM, T2DM, GDM, or PCOS were independently associated with breastfeeding initiation. Most existing literature examining breastfeeding initiation in women affected by T1DM or T2DM supports lower initiation rates compared with unaffected women or women with GDM, ³ , ¹² , ²⁰ , ²⁶ , ²⁷ , ²⁸ but methodology in these studies tended to capture data close to the birth hospitalization. The lack of association in our cohort may relate to the small sample sizes for T1DM and T2DM (n = 21 and 114, respectively), and to the definition of “initiation” used in our study, whereby lack of initiation was defined as a breastfeeding duration of less than 1 month (self‐reported, retrospective). The absence of an association between maternal GDM and PCOS and reduced odds of breastfeeding initiation in our study were more consistent with the existing literature, much of which suggests that these conditions are less likely than pre‐gestational diabetes to adversely impact breastfeeding initiation. ² , ¹³ , ²⁰ , ²⁷ , ²⁹

We also found no evidence to suggest that a maternal diagnosis of T1DM, T2DM, GDM, or PCOS was associated with increased odds of a breastfeeding duration of 6 months or less. Existing literature in this regard is heterogeneous due to variable outcome definitions (“any,” “predominant,” and “exclusive” breastfeeding), but the lack of association in our study was consistent with previous studies in small cohorts of Australian women with GDM and T2DM ²⁰ and one prior analysis of women with PCOS in the ALSWH. ² In T1DM, several existing studies are suggestive of reduced breastfeeding durations, ³⁰ , ³¹ but the relationship is often attenuated after adjustment for key sociodemographic variables. ³⁰ , ³² , ³³

Our analysis demonstrates a clear association between maternal BMI and breastfeeding outcomes (both initiation and duration), with overweight/obesity emerging as a significant independent predictor of suboptimal breastfeeding outcomes among Australian women. This is consistent with previous findings in Australian cohorts at community, ³⁴ state, ³⁵ and national ³⁶ levels. It is also in keeping with the body of existing international evidence, including the results of previous systematic reviews ³⁷ , ³⁸ and umbrella reviews. ³⁹ Indeed, mothers with obesity were highlighted as a “priority population” in the 2019 Australian National Breastfeeding Strategy. ⁴⁰

Breastfeeding difficulties in women affected by overweight and obesity are likely to be multifactorial, with potential physiological, clinical, and psychosocial explanations.

Physiologically, delayed onset of lactogenesis II (the onset of a copious milk supply) is common in women with obesity. ⁴¹ While the exact biological mechanisms remain unclear, weaker insulin‐to‐glucose responses and lower serum adiponectin have been associated with lactogenesis delay in one study of primiparas with a high prevalence of obesity. Given that insulin has a key role in regulating milk synthesis in other mammalian species, poor insulin availability at the level of the lactocyte in women with insulin resistance may limit upregulation of lactose synthesis, resulting in lactogenesis delay. ⁴² Others have demonstrated blunted early prolactin responses to infant suckling in women with obesity. ⁴³ A further theory postulates that—given that steroid hormones are produced and stored in adipose tissue—higher progesterone levels in women with obesity may disrupt the usual sudden drop in progesterone post delivery that initiates lactogenesis. ³⁷

Clinically, maternal obesity is associated with an increased risk of pregnancy and neonatal complications such as hypertensive disorders of pregnancy, pre‐term delivery, cesarean section, SCN/NICU admission, prematurity, birth defects, hypoglycemia, and jaundice. ⁴⁴ Such complications may delay critical early breast contact, prevent rooming‐in, and mandate supplemental feeding, all potentially interfering with maternal milk production. However, our data suggest that the relationship between obesity and suboptimal breastfeeding outcomes persists even after correction for obstetric complications and delivery method; a finding consistent with recent systematic review evidence. ³⁸ Physical barriers associated with obesity, including larger breasts, larger areolas, and additional body tissue, may make infant handling and breastfeeding positions more difficult. ⁴⁵ In a case–control study among a French cohort, Mok et al. ⁴⁶ reported that mothers with obesity (in comparison to reference weight peers) had higher rates of early nipple shield use and reported more practical breastfeeding difficulties such as cracked nipples, fatigue, or inadequate supply. Mothers with obesity were also less likely to report perceived sufficient milk supply at 1 month and 3 months postpartum than those with normal BMI. ⁴⁶

From a psychosocial perspective, negative perceived body image is more common among those with overweight and obesity compared with their lean counterparts, and body dissatisfaction may mediate the relationship between maternal obesity and breastfeeding duration. ⁴⁵ Mok et al. reported that women with obesity most commonly cited “decency” as a reason not to initiate breastfeeding, and were more likely to feel uncomfortable breastfeeding in public at 3 months postpartum than their reference weight peers. ⁴⁶ Obesity stigma is also common in the maternity healthcare setting, and is associated with decreased health‐related quality of life, reduced utilization of healthcare, and increased stress among women with overweight and obesity. In a large US study (n = 19 145) in which 19% of mothers were classified as obese, those with obesity were less likely to receive breastfeeding information, assistance, or a telephone number for breastfeeding help, compared with normal‐weight individuals. They were also less likely to breastfeed in the first‐hour postdelivery or be encouraged to breastfeed on demand. These findings remained significant following adjustment for mode of delivery and key sociodemographic factors. ⁴⁷

Aside from maternal BMI, the other sociodemographic variables to emerge as significant predictors of breastfeeding outcomes in our analysis included higher maternal educational attainment, financial security, and parity (all associated with an increased likelihood of reaching breastfeeding targets), and cesarean delivery, antenatal/postnatal depression, premature delivery, and smoking (all associated with a reduced likelihood of meeting breastfeeding targets). These associations are all well described within the existing national ⁴⁸ and international ⁴⁹ breastfeeding literature, have also been explored in previously published analyses of ALSWH breastfeeding data, ²¹ and are reflected in the choice of “priority populations” within the 2019 Australian National Breastfeeding Strategy. ⁴⁰

Unique strengths of our analysis include the large, unselected community‐based ALSWH cohort. The cohort has previously been demonstrated to be generally representative of the population of Australian women of similar age (based on comparison to contemporaneous census data). ⁵⁰ While a small number of previous observational studies have examined breastfeeding outcomes in Australian women with maternal metabolic disease, most have used much smaller clinical cohorts selected on the basis of the diagnosis in question, and have also examined breastfeeding outcomes much closer to birth hospitalization. ¹⁹ , ²⁰ The longitudinal, iterative nature of the ASLWH surveys allowed for key variables (such as maternal BMI) to be collected over multiple survey waves for the purposes of our analysis, and enabled self‐reported maternal metabolic diagnoses to be examined for consistency over time for each participant. It also allowed complete breastfeeding durations (up to 84 months) to be captured for each pregnancy event, a follow‐up duration that is uncommon among breastfeeding studies.

Limitations of the analysis include the cross‐sectional nature of sociodemographic characteristics captured at Survey 9 in 2021. These may not accurately reflect participant status at the time of the index pregnancies (many of which occurred in the early 2000s). Similarly, maternal BMI category was derived from the mean BMI over five surveys, as opposed to the BMI at the time of each index pregnancy (the latter was not available in the pregnancy outcome dataset). Attrition from initial recruitment (Figure 1) is acknowledged, although the impact of attrition on associations between variables in the ALSWH was previously found to be minimal. ⁵¹ Maternal conditions (including weight) were self‐reported without objective verification, although repeated measures may reduce self‐report bias to some extent. Breastfeeding durations refer to “any” breastfeeding, with no measures of breastfeeding exclusivity or supplemental feeding captured in the surveys. The definition of breastfeeding “initiation” as any breastfeeding to 1 or more months was somewhat arbitrary (surveys asked women to report the “number of complete months” they breastfed each child, with no more granular detail around breastfeeding initiation). Finally, small participant numbers for T1DM and T2DM are noted, reflecting the unselected community nature of the cohort and the low population prevalence of these conditions. The small sample sizes for T1DM and T2DM in our analysis may explain the lack of statistically significant associations for these conditions with respect to breastfeeding initiation and duration.

5. CONCLUSION

Overall, the results of our study suggest that maternal obesity (rather than any specific maternal metabolic condition) is a key predictor of breastfeeding outcomes in Australian women. Given the increasing prevalence of obesity among women of reproductive age and the significant benefits of breastfeeding for both mother and infant, optimizing lactation support for women with obesity emerges as a public health priority. Future research efforts should aim to elucidate the physiological mechanisms linking obesity to breastfeeding difficulties, acknowledging the overlap with insulin resistance and with other conditions such as maternal diabetes and PCOS, and identifying opportunities for pharmacological and/or lifestyle interventions. In a clinical context, more intensive, additional, or specialized lactation support for birthing mothers with obesity may need to be prioritized; particularly in the setting of obstetric or delivery complications. Future endeavors should also explore psychosocial barriers to successful breastfeeding in mothers with obesity, and identify opportunities for broader systemic and social intervention.

AUTHOR CONTRIBUTIONS

Kate Rassie, Aya Mousa, Helena Teede, and Anju E. Joham conceptualized and planned the study. Kate Rassie executed the analysis with statistical support from Raja Ram Dhungana. Kate Rassie drafted the manuscript, which was reviewed and approved by Raja Ram Dhungana, Aya Mousa, Helena Teede, and Anju E. Joham. All authors have contributed to this manuscript in line with the ICMJE criteria for authorship and have read and approved the manuscript for publication.

FUNDING INFORMATION

This work received no specific funding from any agency in the public, commercial, or not‐for‐profit sectors. KR is supported by a National Health and Medical Research Council (NHMRC) Scholarship. AM and HT are supported by fellowships provided by the NHMRC.

CONFLICT OF INTEREST STATEMENT

All authors declare no conflicts of interest.

ETHICS STATEMENT

ALSWH survey data are owned by the Australian Government Department of Health and Aged Care, and due to the personal nature of the data collected, release by ALSWH is subject to strict contractual and ethical restrictions. The study has ongoing ethical approval from the Human Research Ethics Committees of the Universities of Newcastle and Queensland, respectively (approval numbers: H‐076‐0795 and 2004000224, approval date July 26, 1995, expiration date December 31, 2030). Written informed consent was provided by all participants.

Rassie K, Dhungana RR, Mousa A, Teede H, Joham A. Maternal metabolic conditions as predictors of breastfeeding outcomes: Insights from an Australian cohort study. Acta Obstet Gynecol Scand. 2024;103:1570‐1583. doi: 10.1111/aogs.14868

DATA AVAILABILITY STATEMENT

De‐identified data are available to collaborating researchers where a formal request to use the material has been approved by the ALSWH Data Access Committee. The committee is receptive to requests for datasets required to replicate results. Information on applying for ALSWH data is available from https://alswh.org.au/for‐data‐users/applying‐for‐data/.