Abstract
Background
Little is known about infant feeding practices of Indian immigrant mothers in Australia; this study examined current practices and associated sociodemographic factors.
Methods
A cross-sectional online survey collected infant feeding practices and sociodemographic data from 365 mothers born in India, with a full-term child born in Australia aged 1.5-5 years. Exclusive breastfeeding duration was calculated based on the child’s earliest introduction to any non-breastmilk liquids or solids. Multivariable linear and logistic regression assessed the association between sociodemographic characteristics and infant feeding practices.
Results
Mean breastfeeding duration and age when exposed to formula was 15.0 and 2.9 months, respectively. Exclusive breastfeeding until 6 months was reported by 30.1% of the mothers; and at 6 months 72.1% of infants had been introduced to formula, and 73.3% of infants had been introduced to solids. The introduction to cow’s milk and sweet drinks before 12 months was 24% and 37%, respectively. Higher maternal BMI was associated with shorter breastfeeding duration (β: -0.33, 95%CI: -0.54, -0.13, p = 0.001), and higher odds of introducing sweet drinks before 12 months (OR:1.07, 95%CI: 1.01, 1.14, p = 0.01). Urban region before migration was associated with shorter breastfeeding duration (β: -2.92, 95%CI: -5.40, -0.44, p = 0.02) and lower odds of exclusively breastfeeding at 6 months (OR: 0.52, 95%CI: 0.29, 0.94, p = 0.03). Older mothers were less likely to introduce sweet drinks before 12 months (OR: 0.83, 95%CI: 0.75, 0.92, p = 0.001). Compared to mothers with a bachelor’s degree or lower (lower levels of education) mothers with postgraduate education (higher levels of education) had 88% higher odds of introducing their infants to sweet drinks before 12 months (95% CI:1.06, 3.33). Mothers who lived in Australia for ≥ 10 years had reduced odds of exclusive breastfeeding at 6 months (OR: 0.49, 95%CI: 0.28, 0.83, p = 0.01).
Conclusion
The findings of this study highlight the associations between infant feeding practices and maternal sociodemographic factors, however causality cannot be inferred. Opportunities exist to improve prevalence of exclusive breastfeeding at 6 months and to delay the introduction to sweet drinks. Culturally tailored support acknowledging regional contexts and length of stay, may help improve infant feeding practices.
Clinical trial number
Not applicable.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s13006-026-00882-1.
Keywords: Indian immigrant, Infant feeding, Religion, Region of residence, Obesity
Background
Indian immigrants are Australia’s second-largest immigrant population with numbers projected to rise to 1.4 million by 2031 [1]. Children of Indian immigrant mothers are 50–70% more likely to be living with overweight or obesity compared to children of Australian-born mothers, leading to a range of health risks later in life [2].
Suboptimal infant feeding in the first 2000 days (i.e. the period of time from conception to age 5) can increase the risk of chronic diseases like obesity, cardiovascular disease, and type 2 diabetes in later life [3–7]. The first 2000 days window is important for developing healthy behaviours (e.g. eating, active play and sleep) and is linked to later obesity risk [8]. The first 2000 days period also aligns with the broader developmental origins of health and disease hypothesis that focuses on family, social and economic factors extending beyond the first 1000 days [9].
The Australian Infant Feeding Guidelines [10] and the World Health Organization (WHO), Infant and Young Child Feeding Guidelines [11] recommend exclusive breastfeeding for the first 6 months, introduction of nutritionally adequate and safe complementary (solid) foods at 6 months with continued breastfeeding up to 2 years of age or beyond for optimal child growth [10, 11]. An analysis of 2010 Australian National Infant Feeding survey data [12] revealed Indian immigrant mothers introduced their infants to cow’s milk, fruit juice, water-based drinks and formula early and these practices did not align with the Australian Infant Feeding Guidelines [13]. These data are more than a decade old and infant feeding practices may have changed and the outdated data may no longer reflect the current sociodemographic profile of Indian immigrants in Australia [13].
Australian and US studies suggest that infant feeding practices among immigrant mothers in Western countries may be influenced by maternal sociodemographic factors including age, body mass index (BMI), gestational diabetes mellitus (GDM) status, mode of delivery, education, parity, employment status, religion, length of stay in the host country, and language spoken at home [14–22]. Younger immigrant mothers or those with lower educational qualifications have been reported to have shorter breastfeeding duration and a lower likelihood of exclusive breastfeeding [18, 23]. Furthermore, mothers living with overweight or obesity have been found to be more likely to exclusively formula feed [24].
Sociodemographic factors such as region of residence and religion may be associated with infant feeding practices [19, 25]. A lower proportion of mothers from rural Indian regions breastfed compared to mothers from urban regions (76% vs. 88%); and a higher proportion of mothers from rural Indian regions introduced their infants to solids before six months compared to those from urban regions (11.9% vs. 9.9%) [19]. Further, Ojha et al. revealed higher breastfeeding prevalence among Christian (78%) compared with Hindu (58%) and Muslim (75%) mothers and early weaning among Hindu (54%) compared with Christian (35%) and Muslim (33%) mothers [25]. Together, these findings highlight the influence of diverse social and cultural contexts on infant feeding practices within India. However, it remains unclear whether these patterns are maintained, modified, or attenuated following migration to a high-income country such as Australia, where social norms, healthcare systems, and infant feeding recommendations may differ substantially.
A qualitative study in Melbourne, Australia, revealed that Indian immigrant mothers initiated breastfeeding according to their cultural identity, social support, and cultural connectivity positively impacting breastfeeding duration [26]. Acculturation is a process of cultural and behavioral change when people from one culture adapt to or accommodate a second culture’s behaviour, thoughts, and norms post-migration [27]. Berry’s model of acculturation categorizes adaptation strategies onto two dimensions such as retention or rejections of one’s culture resulting in integration, assimilation, separation, and marginalization strategies used to adjust to the new culture [28]. In the context of infant feeding behaviours, these strategies can shape infant feeding practices by influencing the extent to which mothers retain traditional practices or adopt host-country recommendations, resulting in interplay between cultural norms and the host environment [29]. Overall lower acculturation among immigrant mothers in developed countries has shown lower likelihood of formula exposure and longer breastfeeding duration consistent with their home country practices [30, 31]. Lower acculturation among South Asian mothers in the UK was linked to stronger breastfeeding intentions, whereas higher acculturation was associated with formula feeding norms and earlier formula introduction [31].
Currently there is a lack of contemporary Australian evidence on infant feeding practices and associated maternal sociodemographic factors including acculturation variables of Indian immigrant mothers in Australia. US and UK studies have explored infant feeding practices among South Asian or Arab mothers [32–34] but not Indian immigrant mothers specifically. This study examined infant feeding practices among Indian immigrant mothers in Australia and their associations with maternal sociodemographic factors including religion, Indian region before migration, BMI, parity, education, work status and acculturation proxy variables such as length of stay and language spoken at home. Findings may inform culturally tailored support strategies to improve infant feeding practices for the growing number of Indian immigrant mothers living in Australia.
Methods
Study design
A cross-sectional online survey was conducted between October 2023 and July 2024. A target sample size of 386 mothers was calculated using a previous study breastfeeding prevalence of 60% in Indian immigrant mothers in Australia [13] a 95% confidence level and a margin of error of 10%. No further adjustments for non-responding participants were made. The STROBE checklist was used to guide the reporting of this cross-sectional study (see Additional file 3).
Participants and recruitment
Eligible mothers (born in India, had at least one child born at ≥ 37 weeks in Australia, with infants aged 1.5-5 years old) completed the online survey (n = 365). Social media platforms (Facebook, Instagram, LinkedIn, and WhatsApp) were used for online recruitment and advertised flyers with a link to the online survey. Printed flyers were distributed via Indian grocery stores, childcare centres, dietitians (Australia-wide) and maternal child health nurses, community groups, temples, doctors’ surgeries, Diwali melas, and Indian markets in Melbourne. Mothers scanned a QR code on the printed flyers to access the survey. Eligible participants went in a draw to win one of 16 AUD 50 supermarket vouchers.
Survey design and administration
The survey was adapted from the validated Australian National Infant Feeding Survey developed by the Australian Bureau of Statistics and the Australian Institute of Health and Welfare in 2010 [12]. This survey was modified to include questions suitable for this study. Questions regarding mental health were removed, but the rest of the questions regarding maternal demographic characteristics and infant feeding practices were retained. Additionally, culturally specific demographic questions related to Indian immigrant mothers were added including maternal religion, language spoken at home, region before migration, and length of stay. The inclusion of these questions was informed by existing literature. As the core components of the questionnaire were derived from a validated Australian National Infant Feeding Survey, no formal validity testing was undertaken. However, the questionnaire was reviewed for clarity and cultural appropriateness prior to dissemination by the research team. Pilot testing for the questionnaire was carried out with 2 Indian immigrant mothers. Feedback was obtained regarding clarity, comprehension, and survey length and also how personal information was captured [35]. Minor revisions were made based on this feedback, including refinement of wording, improvement of question sequencing, and clarification of response options. For example, mothers were not comfortable with disclosing full date of birth, therefore month and year were captured and therefore birth date for all participants was set to ’01’ for calculating maternal age.
This survey was administered in English using Qualtrics (Qualtrics, Provo, UT) [36]. Mothers self-reported data on maternal and child sociodemographic characteristics and infant feeding practices. The survey was not anonymous, as participants provided email addresses for follow-up correspondence. However, these details were stored separately from survey responses and linked only through a unique identifier. Duplicate entries were assessed using IP addresses and cross-checked against maternal demographic and infant feeding data, with any confirmed duplicates removed prior to analysis.
Sample characteristics
Maternal sociodemographic variables such as education, parity, GDM, work status, religion, Indian self-identified region of residence before migration and acculturation variables such as length of stay and language spoken at home, were collected as categorical data, except for maternal date of birth (reported as month and year) and pre-pregnancy weight and height (reported as kilograms and centimetres). Maternal age was derived from reported month and year. Maternal anthropometry measurements were used to calculate pre-pregnancy BMI (kg/m2) and analysed as a continuous (kg/m2) and categorical variable according to the WHO cutoffs [37]. Maternal BMI was included as a continuous variable in regression analyses to estimate the association between each one unit increase in BMI and the outcome. Maternal BMI categorical variables were used to compare participant characteristics across established BMI categories.
For categorical variables with small sample sizes, data were collapsed with other relevant categories. Variables such as maternal BMI (underweight/healthy weight vs. overweight vs. obesity), maternal education (bachelor’s degree and below vs. postgraduate degree), parity (1 child vs ≥ 2 children), religion (Hindu vs Christian vs other), Indian region of residence before migration (remote vs urban), acculturation proxy variables such as length of stay (< 10 years vs ≥ 10 years), language spoken at home (English vs not English), maternal work status (working vs not working), GDM (yes vs no), mode of delivery (vaginal vs not vaginal) and child’s sex were assessed as correlates of infant feeding practices. For length of stay, a 10-year cut off was used as 10 years in the host country is often associated with more reliable changes in outcome measures [38, 39] and has been used previously [26, 32]. Child demographic characteristics were collected as categorical variables.
Infant feeding practices
Mothers self-reported age at which breastfeeding stopped; whether they were currently breastfeeding at the time of survey completion (yes vs no) and whether the infant ever had formula (yes vs no). Mothers were also asked to report the age at which their infant was first introduced to formula. This enabled differentiation between exclusive breastfeeding and mixed feeding, including infants who received both breastmilk and formula from birth. According to WHO, exclusive breastfeeding is defined as the infant receiving only breastmilk, with no other food or drink, not even water, except breastmilk (including milk expressed or from a wet nurse) for the first 6 months of life, with the exception of rehydration solution, drops and syrups (vitamins, minerals and medicines), this includes formula or any formula products [11]. Exclusive breastfeeding duration was calculated based on the child’s earliest introduction of solids or any non-breastmilk liquids. Further, the age of introduction to cow’s milk, fruit juice, water, water-based drinks, and soft semisolid/solid foods was captured. Water included any sips of water on its own; however, water-based drinks included water combined with any other liquids such as cordial (a sweet non-alcoholic drink made from fruit juice). Soft semi-solid and solid foods include custards, mashed and foods diluted with water, milk and other fluids. Infant feeding practices such as timing of introduction to fruit juice and water-based drinks were combined into a ‘sweet drinks’ variable. This approach was adopted because of the small number of participants in each category, and the infant feeding recommendations [40] for both the beverages are similar as both drinks are not recommended before 12 months of age and have adverse health implications for infant health from early introduction [41, 42]. Infant feeding variables such as breastfeeding duration, age of formula introduction, and timing of introduction to soft semisolid/solid foods, cow’s milk and sweet drinks were categorised into relevant categories informed by Australian Infant Feeding Guidelines [10] and WHO Infant and Young Child Feeding Guidelines [11] for ease of interpretation. For example, exclusive breastfeeding and feeding soft semisolid/ solid foods were categorised as < 6 months vs ≥ 6 months, ever fed formula (yes vs no), sweet drinks and cow’s milk as < 12 months vs. ≥ 12 months. Since only one mother introduced soft semisolid or solid foods < 4 months, early exposure was not assessed.
Statistical analysis
Analyses were conducted using complete case analysis for each infant feeding outcome, therefore there were no missing data. Descriptive statistics (mean ± SD or proportion) were conducted to summarise sample characteristics and infant feeding practices. Univariable linear and logistic regressions models were used to examine the associations between individual maternal sociodemographic variables, acculturation proxy variables and child’s demographic variables, and continuous dependent variables (e.g. breastfeeding duration in months), and dichotomous dependent infant feeding variables (e.g. yes vs. no: exclusive breastfeeding at 6 months, ever fed formula etc.).No evidence of multicollinearity was identified among maternal independent variables using Pearson’s correlation coefficient matrices and a threshold of > 0.7. Multivariable linear and logistic regression models were then conducted with all maternal sociodemographic variables, acculturation proxy variables and child’s sex simultaneously, enabling assessment of the independent association of each variable on infant feeding outcome variables. All analyses were conducted using Stata version 18 (StataCorp LLC, TX, USA) and with significance level set at p < 0.05 (two-sided).
Results
A total of 1078 mothers accessed the survey, 791 mothers were eligible, and 365 mothers had complete data (Fig. 1). All were married and non-smokers, the average maternal age was 35.9 years, 47.1% were classified as living with overweight or obesity, 29.9% had GDM, 58.9% were Hindu and 21.4% were Christian. A higher proportion of mothers migrated from urban compared to remote Indian regions (79.7%), had postgraduate qualification (57.3%), worked after their child was born (79.7%), lived in Australia for less than 10 years (55.1%) and spoke a native Indian language at home (81.6%). Distribution of children’s sexes was similar, and the mean age of children was 3.0 ± 1.3 years (Table 1).
Fig. 1.
Flowchart of sampling of Indian immigrant mothers in Australia for the data collected between October 2023 – July 2024
Table 1.
Sociodemographic characteristics of Indian immigrant mothers and demographic characteristics of their children (n = 365)
| Maternal sociodemographic characteristics | n | Mean (SD) or % |
|---|---|---|
| Age (years) | 35.9 (3.0) | |
| Age in categories (years) | ||
| 25–29 | 13 | 3.7% |
| 30–35 | 101 | 27.7% |
| 35 + | 251 | 68.8% |
| Pre-pregnancy BMI (kg/m2)a | 25.6 (4.9) | |
| Pre-pregnancy BMI categories (kg/m2)b | ||
| Underweight/ healthy weight (< 18–24.9) | 193 | 52.9% |
| Overweight (25-29.9) | 112 | 30.7% |
| Obesity (≥ 30) | 60 | 16.4% |
| Parity | ||
| 1 child | 172 | 47.1% |
| ≥2 children | 193 | 52.9% |
| Mode of delivery | 365 | |
| Not vaginalc | 164 | 44.9% |
| Vaginal | 201 | 55.1% |
| GDMd | ||
| No | 256 | 70.1% |
| Yes | 109 | 29.9% |
| Work statuse | ||
| Not working | 75 | 20.3% |
| Working | 290 | 79.7% |
| Education | ||
| Bachelor’s degree or belowf | 155 | 42.5% |
| Postgraduate degree | 210 | 57.3% |
| Indian region of migration | ||
| Remote | 74 | 20.8% |
| Urban | 291 | 79.7% |
| Religion | ||
| Hindu | 215 | 58.9% |
| Christian | 78 | 21.4% |
| Otherg | 72 | 19.7% |
| Acculturation proxy variables | ||
| Length of stay in Australia | ||
| <10 years | 201 | 55.1% |
| ≥10 years | 164 | 44.9% |
| Language spoken at home | ||
| English | 67 | 18.4% |
| Not Englishh | 193 | 81.6% |
| Child’s demographic characteristics | ||
| Age (years) | 3.0 (1.3) | |
| Sex | ||
| Female | 188 | 51.5% |
| Male | 177 | 48.5% |
| Australian state of residence where infant was born | ||
| Australian Capital Territory | 14 | 3.8% |
| New South Wales | 104 | 28.5% |
| Victoria | 169 | 46.3% |
| Queensland | 40 | 11.0% |
| South Australia | 22 | 6.0% |
| Western Australia | 13 | 3.6% |
| Tasmania | 3 | 0.8% |
Mean (SD) OR %: mean, SD or proportion
aBMI: body mass index calculated using the formula: (weight in kg / [height in m] ²)
bMaternal pre-pregnancy BMI categories based on World Health Organization’s cut off [37]
cNot vaginal includes mothers who had c-section or emergency c-section
dGDM: gestational diabetes mellitus
eMaternal work status includes mothers who worked after the child was born
fBachelor’s degree/ below includes mothers with bachelor’s degree, certificate and diploma qualifications
gOther religions include mothers from Muslim, Jain, Sikh and Buddhist and atheist mothers
hNot English category includes languages such as Hindi, Marathi, Punjabi, Gujrati, Telugu and Malayalam
Infant feeding practices
Table 2 shows prevalence of infant feeding practices among Indian immigrant mothers living in Australia. The mean breastfeeding duration was 15.3 months, and median duration was 14 months. The average age of formula introduction was 3 months, and the median age was one month. One third of mothers exclusively breastfed at 6 months (30.1%), nearly three quarters of mothers had introduced their infants to formula at the time of survey collection (72.1%) and had introduced their infants to solids after 6 months (73%). The proportion of mothers who introduced their infants to sweet drinks and cow’s milk before 12 months was 37%, and 24%, respectively.
Table 2.
Prevalence of introduction and timing of infant feeding practices of Indian immigrant mothers in Australia
| Infant feeding practices | n 1 | Mean (SD) | Median (IQR) |
|---|---|---|---|
| Breastfeeding duration (months) | 365 | 15.3 (9.3) | 14.0 (9.0–21.0) |
| Age when introduced infant formula (months) | 352 | 2.9 (3.7) | 1.0 (0.0–6.0) |
| Age when first introduced semi-solid/solid foods (months) | 337 | 5.9 (1.3) | 6.0 (5.0–6.0) |
| Age of introduction to cow’s milk (months) | 304 | 12.1 (4.7) | 12.0 (12.0–13.0) |
| Age of introduction to sweet drinks (months) | 265 | 13.6 (7.4) | 12.0 (8.0–18.0) |
| Proportion % | |||
| Exclusive breastfeeding at 6 months (yes) | 365 | 30.1% | |
| Ever had formula (yes) | 352 | 72.2% | |
| Introduction to semi-solids/ solids before 6 months (yes) | 337 | 27.0% | |
| Introduction to cow’s milk before 12 months (yes) | 304 | 24.0% | |
| Introduction to sweet drinks before 12 months (yes) | 265 | 37.0% | |
*sweet drinks: fruit juice and water-based drinks; mixed feeding includes breastfeeding and formula feeding
an is different for feeding practices as some mothers had not exposed their infants to cow’s milk or sweet drinks or formula or data was missing (soft semi-solid foods) at the time of survey completion
Associations between infant feeding practices and maternal sociodemographic factors
Breastfeeding practices were examined. In both unadjusted and adjusted models, higher maternal BMI and migration from urban Indian regions were associated with reduced breastfeeding duration (Table 3). Each unit increase in BMI (kg/m2) resulted in 0.34 month reduction in breastfeeding duration (95% CI: -0.54, -0.13 months). Mothers migrating from urban Indian regions breastfed for approximately 3 months less than mothers from remote regions (95%CI: -5.40, -0.44 months) (Table 3). However other maternal sociodemographic factors were not associated with breastfeeding duration.
Table 3.
Associations between sociodemographic factors and breastfeeding duration (age in months) and exclusive breastfeeding (yes vs. no) amongst Indian immigrant mothers in Australia
| Sociodemographic factors | Breast feeding duration (months) (n = 365) |
Exclusive breastfeeding at 6 months (yes [n = 110] vs. no [n = 255]) (n = 365) |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Univariablea | Multivariableb | Univariablec | Multivariabled | |||||||||
| β | 95% CI | p-value | β | 95% CI | p-value | OR | 95% CI | p-value | OR | 95% CI | p-value | |
| Maternal characteristics | ||||||||||||
| Age (years) | 0.05 | (-0.25, 0.37) | 0.71 | 0.18 | (-0.16, 0.53) | 0.28 | 0.99 | (0.92, 1.07) | 0.89 | 1.04 | (0.92, 1.14) | 0.37 |
| BMI (kg/m2)e | -0.34 | (-0.53, -0.15) | < 0.001*** | -0.33 | (-0.54, -0.13) | < 0.001*** | 0.95 | (0.90, 1.00) | 0.08 | 0.95 | (0.90, 1.00) | 0.09 |
| Parity | ||||||||||||
| 1 child vs. ≥ 2 children | -0.99 | (-2.92, -0.93) | 0.31 | -1.75 | (-3.72,0.20) | 0.08 | 1.38 | (0.86, 2.20) | 0.17 | 1.50 | (0.90, 2.48) | 0.11 |
| Mode of delivery | ||||||||||||
| Vaginal vs. not vaginalf | -1.85 | (-3.77, 0.07) | 0.06 | -1.42 | (-3.36, 0.52) | 0.15 | 0.82 | (0.51, 1.32) | 0.43 | 1.02 | (0.62, 1.68) | 0.93 |
| GDMg | ||||||||||||
| No vs. yes | -1.19 | (-3.30, 0.90) | 0.26 | -0.65 | (-2.78,1.47) | 0.54 | 0.72 | (0.43, 1.23) | 0.23 | 0.72 | (0.41, 1.26) | 0.25 |
| Work statush | ||||||||||||
| No vs. yes | -1.10 | (-3.48, 1.28) | 0.36 | -1.69 | (-4.08, 0.69) | 0.16 | 0.99 | (0.56, 1.75) | 0.98 | 0.92 | (0.50,1.68) | 0.79 |
| Education | ||||||||||||
| Bachelor’s degree or belowi vs. postgraduate | -0.30 | (-2.25,1.64) | 0.75 | 0.05 | (-1.93, 2.03) | 0.96 | 1.06 | (0.66, 1.69) | 0.80 | 1.05 | (0.63, 1.74) | 0.83 |
| Indian region before migration | ||||||||||||
| Remote vs. urban | -2.89 | (-5.27, -0.52) | 0.01** | -2.92 | (-5.40, -0.44) | 0.02* | 0.59 | (0.35, 1.01) | 0.05 | 0.52 | (0.29, 0.94) | 0.03* |
| Religion | ||||||||||||
| Hindu vs. Christian | 2.36 | (-0.05, 4.78) | 0.05 | 2.22 | (-0.25, 4.72) | 0.79 | 1.19 | (0.67, 2.11) | 0.54 | 0.89 | (0.48, 1.68) | 0.74 |
| Hindu vs. otherj | -0.94 | (-3.44, 1.54) | 0.45 | -1.40 | (-3.91, 1.11) | 0.27 | 0.81 | (0.43, 1.51) | 0.51 | 0.70 | (0.36, 1.35) | 0.29 |
| Acculturation proxy variables | ||||||||||||
| Length of stay in Australia | ||||||||||||
| <10 years vs. ≥ 10years | 0.47 | (-1.46, 2.40) | 0.63 | 0.75 | (-1.31, 2.82) | 0.47 | 0.57 | (0.36, 0.90) | 0.02 | 0.49 | (0.28, 0.83) | 0.01** |
| Language spoken at home | ||||||||||||
| English vs. not Englishk | 0.97 | (-1.51, 3.46) | 0.44 | 0.82 | (-1.70, 3.34) | 0.52 | 1.02 | (0.56, 1.84) | 0.94 | 0.80 | (0.42,1.54) | 0.52 |
| Child characteristics | ||||||||||||
| Child’s sex | ||||||||||||
| Male vs. female | -0.16 | (-2.08, 1.76) | 0.87 | -0.12 | (-2.02, 1.77) | 0.89 | 1.16 | (0.73, 1.85) | 0.51 | 1.27 | (0.78,2.06) | 0.33 |
aUnivariable model: Univariable model (linear regression) was used to examine associations between breastfeeding duration in months and maternal sociodemographic factors (age, BMI, parity, mode of delivery, gestational diabetes mellitus, work status, education, Indian region before migration, religion, length of stay, language spoken at home) and child’s characteristics such as child’s sex
bMultivariable model: A multivariable model (linear regression) was used to examine associations between breastfeeding duration in months and maternal sociodemographic factors (age, BMI, parity, mode of delivery, gestational diabetes mellitus, work status, education, Indian region before migration, religion, length of stay, language spoken at home) and child’s characteristics such as child’s sex, allowing for adjustment of multiple variables simultaneously
cUnivariable model: Univariable model (linear regression) was used to examine associations between breastfeeding duration in months and maternal sociodemographic factors (age, BMI, parity, mode of delivery, gestational diabetes mellitus, work status, education, Indian region before migration, religion, length of stay, language spoken at home) and child’s characteristics such as child’s sex
dMultivariable model: Multivariable model (linear regression) was used to examine associations between breastfeeding duration in months and maternal sociodemographic factors (age, BMI, parity, mode of delivery, gestational diabetes mellitus, work status, education, Indian region before migration, religion, length of stay, language spoken at home) and child’s characteristics such as child’s sex, allowing for adjustment of multiple variables simultaneously
eBMI: body mass index calculated using the formula: (weight in kg / [height in m] ²)
fNot vaginal includes mothers who had c-section or emergency c-section
gGDM: gestational diabetes mellitus
hMaternal work status includes mothers who worked after the child was born
iMothers with diploma or certificate qualifications were grouped under ‘Bachelor’s degree or below’ due to small sample size
jOther religion’ category includes Jain, Muslim, and atheist mothers due to small sample sizes
kNot English category includes languages such as Hindi, Marathi, Punjabi, Gujrati, Telugu and Malayalam
* p < 0.05, ** p < 0.01, *** p < 0.001
Mothers migrating from urban regions in India had 46% reduced odds of exclusively breastfeeding at 6 months compared to those from remote regions (95%CI: 0.26, 0.87). Similarly, mothers who had lived in Australia for 10 years or more had 48% reduced odds to exclusively breastfeed at 6 months than those who had lived in Australia for less than 10 years (95% CI: 0.28, 0.83) (Table 3). Other maternal sociodemographic factors were not associated with and exclusively breastfeeding at 6 months.
In both unadjusted and adjusted models, lower maternal age, increasing BMI and higher levels of education were associated with increased odds of introduction to sweet drinks before 12 months (Table 4). For example, one year increase in age was associated with 17% reduced odds (95%CI: 0.75, 0.92), and each unit increase in BMI was associated with 7% increased odds (95%CI: 1.01, 1.14) of introducing infants to sweet drinks before 12 months. In the unadjusted model there was no association between maternal education and introduction of sweet drinks before 12 months. However, in the adjusted model this association was significant. Compared to mothers with a bachelor’s degree or lower (lower levels of education) mothers with postgraduate education (higher levels of education) had 88% higher odds of introducing their infants to sweet drinks before 12 months (95% CI:1.06, 3.33).
Table 4.
Associations between sociodemographic factors for introduction to sweet drinks before 12 months (yes vs. no) and introduction to cow’s milk before 12 months (yes vs. no) amongst Indian immigrant mothers in Australia
| Sociodemographic factors | Introduction to sweet drinks < 12 months (yes [n = 98] vs. no [167]) (n = 265) |
Introduction to cow’s milk < 12 months (yes [n = 73] vs. no [n = 231]) (n = 304) |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Univariablea | Multivariableb | Univariablec | Multivariabled | |||||||||
| OR | 95% CI | p-value | OR | 95% CI | p-value | OR | 95% CI | p-value | OR | 95% CI | p-value | |
| Maternal characteristics | ||||||||||||
| Age (years) | 0.98 | (0.78, 0.94) | < 0.001*** | 0.83 | (0.75, 0.92) | < 0.001*** | 0.97 | (0.89, 1.06) | 0.64 | 0.97 | (0.87, 1.07) | 0.57 |
| BMI (kg/m2)e | 1.05 | (0.99, 1.06) | 0.06 | 1.07 | (1.01, 1.14) | 0.01 | 1.03 | (0.97, 1.08) | 0.25 | 1.02 | (0.97, 1.08) | 0.35 |
| Parity | ||||||||||||
| 1 child vs. ≥ 2 children | 0.96 | (0.58, 1.58) | 0.87 | 1.03 | (0.58, 1.82) | 0.91 | 0.59 | (0.35, 1.01) | 0.05 | 0.62 | (0.35, 1.10) | 0.10 |
| Mode of deliveryf | ||||||||||||
| Vaginal vs. not vaginalg | 0.69 | (0.41, 1.16) | 0.17 | 0.58 | 0.32, 1.05) | 0.07 | 0.96 | (0.57, 1.64) | 0.91 | 0.95 | (0.54, 1.67) | 0.85 |
| GDMh | ||||||||||||
| No vs. yes | 1.07 | (0.61, 1.85) | 0.80 | 0.84 | 0.45, 1.56) | 0.58 | 0.41 | (0.80, 2.49) | 0.22 | 1.37 | (0.74, 2.50) | 0.30 |
| Work statusi | ||||||||||||
| No vs. yes | 0.67 | (0.36, 1.23) | 0.24 | 0.63 | (0.32, 1.25) | 0.19 | 1.17 | (0.59,2.32) | 0.63 | 1.17 | (0.57, 2.39) | 0.66 |
| Education | ||||||||||||
| Bachelor’s degree or belowj vs. postgraduate | 1.18 | (0.71, 1.96) | 0.50 | 1.88 | (1.06, 3.33) | 0.02* | 1.22 | (0.71, 2.08) | 0.46 | 1.26 | (0.71, 2.22) | 0.41 |
| Indian region before migration | ||||||||||||
| Remote vs. urban | 0.64 | (0.35, 1.19) | 0.16 | 0.66 | (0.33, 1.33) | 0.25 | 0.81 | (0.42, 1.55) | 0.53 | 0.66 | (0.32, 1.32) | 0.24 |
| Religion | ||||||||||||
| Hindu vs. Christian | 1.02 | (0.54, 1.94) | 0.93 | 0.74 | (0.35, 1.55) | 0.42 | 0.61 | (0.30, 1.24) | 0.17 | 0.65 | (0.30, 1.39) | 0.26 |
| Hindu vs. otherk | 0.74 | (0.38, 1.43) | 0.37 | 0.55 | (0.26, 1.17) | 0.12 | 0.72 | (0.35, 1.48) | 0.36 | 0.71 | (0.33, 1.52) | 0.39 |
| Acculturation proxy variables | ||||||||||||
| Length of stay in Australia | ||||||||||||
| < 10 years vs. ≥ 10 years | 0.74 | (0.45, 1.23) | 0.25 | 1.21 | (0.67, 2.18) | 0.51 | 0.88 | (0.52, 1.50) | 0.65 | 0.97 | (0.54, 1.76) | 0.93 |
| Language spoken at home | ||||||||||||
| English vs. not Englishl | 2.40 | (1.19, 4.83) | 0.01 | 2.11 | (0.99, 4.48) | 0.05* | 0.86 | (0.45, 1.63) | 0.65 | 0.76 | (0.38, 1.53) | 0.45 |
| Child characteristics | ||||||||||||
| Child’s sex | ||||||||||||
| Male vs. female | 1.05 | (0.63, 1.73) | 0.84 | 1.02 | (0.59, 1.75) | 0.94 | 1.32 | (0.77, 2.24) | 0.3 | 1.33 | (0.77, 2.31) | 0.29 |
aUnivariable model: Univariable model (logistic regression) was used to examine associations between introduction to sweet drinks < 12 months (y/n) and maternal sociodemographic factors (age, BMI, parity, mode of delivery, gestational diabetes mellitus, work status, education, Indian region before migration, religion, length of stay, language spoken at home) and child’s characteristics such as child’s sex
bMultivariable model: A multivariable model (logistic regression) was used to examine associations between introduction to sweet drinks before 12 months (y/n) and maternal sociodemographic factors (age, BMI, parity, mode of delivery, gestational diabetes mellitus, work status, education, Indian region before migration, religion, length of stay, language spoken at home) and child’s characteristics such as child’s sex, allowing for adjustment of multiple variables simultaneously
cUnivariable model: Univariable model (logistic regression) was used to examine associations between introduction to cow’s milk < 12 months (y/n) and maternal sociodemographic factors (age, BMI, parity, mode of delivery, gestational diabetes mellitus, work status, education, Indian region before migration, religion, length of stay, language spoken at home) and child’s characteristics such as child’s sex
dMultivariable model: Multivariable model (logistic regression) was used to examine associations between introduction to cow’s milk < 12 months (y/n) and maternal sociodemographic factors (age, BMI, parity, mode of delivery, gestational diabetes mellitus, work status, education, Indian region before migration, religion, length of stay, language spoken at home) and child’s characteristics such as child’s sex, allowing for adjustment of multiple variables simultaneously
eBMI: body mass index calculated using the formula: (weight in kg / [height in m] ²)
fNot vaginal includes mothers who had c-section or emergency c-section
gGDM: gestational diabetes mellitus
hMaternal work status includes mothers who worked after the child was born
iMothers with diploma or certificate qualifications were grouped under ‘Bachelor’s degree or below’ due to small sample size
jOther religion’ category includes Jain, Muslim, and atheist mothers due to small sample sizes
kNot English category includes languages such as Hindi, Marathi, Punjabi, Gujrati, Telugu and Malayalam
* p < 0.05, ** p < 0.01, *** p < 0.001
In the unadjusted model, language spoken at home was significantly associated with introduction to sweet drinks before 12 months. Mothers who spoke native language at home had 2.88 times increased odds of introducing sweet drinks before 12 months (95%CI: 1.19, 4.83). However, in the adjusted model, this association was attenuated. Parity, mode of delivery, GDM, work status, Indian region before migration and religion were not associated with introduction to sweet drinks before 12 months. No associations were found between maternal characteristics and infants who received formula (Additional file 2) or being introduced to solids before 6 months (Additional file 2).
Discussion
This study offers contemporary insights into the infant feeding practices of Indian immigrant mothers living in Australia. Breastfeeding for ≥ 12 months, introduction of solid foods around 6 months, and delayed introduction of cow’s milk ≥ 12 months, aligned with the Australian Infant Feeding Guidelines [10]. However, early introduction to formula, low prevalence of exclusive breastfeeding at six months, and a high proportion of mothers introducing sweet drinks < 12 months were suboptimal. In this study, BMI was associated with breastfeeding duration, acculturation with exclusive breastfeeding, and region of residence in India was associated with breastfeeding duration and exclusivity. The introduction of sweet drinks before 12 months was associated with BMI, age and education levels of the mother.
Prolonged breastfeeding is common amongst mothers in India and Indian immigrant mothers in western countries largely due to cultural beliefs [13, 33, 43, 44]. The present study findings revealed that mothers breastfed longer than the Australian cohort of Indian immigrant mothers in 2010 (15.3 months vs. 6.1 months) [13]. This difference may reflect the demographic variation between the two cohorts with the current study having older, more educated mothers. In the current study, 96.1% of mothers had tertiary qualifications and 96.5% were aged ≥ 30 years; compared with 80% and 65.8%, respectively, in the 2010 cohort [45, 46]. The higher proportion of mothers over 30 years of age in this cohort likely reflects a broader demographic shift consistent with national data where the mean maternal age was 31.3 years in 2023 [47]. Note that almost 70% of Indian immigrants migrating are tertiary educated [1]. While the sample reflects current Indian migrant cohort characteristics, mothers with lower educational attainment were underrepresented, likely due to convenience sampling. Additionally, use of self-reported data may introduce selection bias and limit generalisability for mothers with lower education. Therefore, these findings should be interpreted with caution.
A lower prevalence of exclusive breastfeeding has been observed among immigrant mothers in Western countries including Australia, Italy, the US, and Denmark compared with non-immigrant White mothers [44]. Consistent with these findings, the prevalence of exclusive breastfeeding at 6 months in this study was below the Australian average (30.1% vs 37.5%) as well as the WHO estimates of global prevalence of exclusive breastfeeding (48%) [48]. The UNICEF Global Breastfeeding Scorecard suggests an increase in global exclusive breastfeeding prevalence in the last 10 years [49]. Therefore, it is concerning that exclusive breastfeeding prevalence within this immigrant group are falling behind the national and global averages. Previous studies have shown acculturation, perceived low milk supply and mental health challenges influence breastfeeding practices [44]. However, the present study revealed an association with maternal pre-pregnancy BMI and Indian region before migration. Mothers migrating from Indian urban regions had shorter breastfeeding duration and reduced likelihood of exclusive breastfeeding at 6 months. Indian evidence shows that urbanisation has increased mothers’ reliance on ready-made, convenient weaning foods, such as formula [50]. This shift in perceptions of infant formula may have adversely affected breastfeeding among mothers in this study, migrating from urban Indian regions. Understanding the reasons for a shift in perceptions of infant formula is important as emerging evidence suggests formula marketing is pervasive, persuasive and sophisticated across traditional and digital media environments [51, 52].
In this study, although the prevalence of any breastfeeding was optimal, the median age of introduction to formula was one month; and high prevalence of formula feeding (72.2%) misaligns with WHO and Australian Infant Feeding Guidelines [10, 11]. As noted above, the high prevalence of formula feeding may be associated with aggressive formula marketing and with maternal acculturation experience [52]. Qualitative findings from a subsample of mothers from this study cohort has also revealed that formula use may be influenced by health practitioners’ concerns about low birth weight and limited awareness of normal growth differences between migrant and Western infants [43]. Evidence suggests that infants born to Indian parents were significantly lighter compared to infants born to European parents (2.9 kg vs 3.5 kg) [53]. Future studies should examine if exposure to commercial infant formula marketing, acculturation and healthcare professional interactions influence infant feeding decisions among immigrant mothers and the use of infant formula.
Despite recommendations to avoid sweet drinks before 12 months [10, 11] due to their association with early exposure and development of sweet taste preferences [54], excess energy with no nutritional benefit [55] and increased risk of childhood overweight and obesity [56]; 37% of mothers in this study introduced them early. This non-adherence to the Australian Infant Feeding Guidelines [10] may be attributable to high maternal pre-pregnancy BMI and younger age of mothers in this cohort [57]. Mothers with high BMI tend to consume and introduce sugar‑sweetened beverages earlier to their infants, shaping early dietary patterns and health outcomes [58] whereas older mothers may delay introduction to sweet drinks due to better understanding of infant feeding guidelines [59]. In the present study a high proportion of mothers introduced solids after 6 months, sweet drinks and cow’s milk after 12 months compared with mothers from 2010 cohort [13]. However, these findings contrast previous literature where immigrant mothers from India, Pakistan and Bangladesh introduced solids before 6 months [60]. These findings suggest improved adherence to the Australian Infant Feeding Guidelines and also the WHO recommendations for complementary feeding [40] may be attributed to a higher proportion of mothers with tertiary education in the current cohort compared with the 2010 cohort (96% vs. 80%) [10]. Higher educational attainment has previously been associated with greater awareness and uptake of health recommendations [61].
Acculturation is a complex process, and its measurement varies across studies [31, 62]. A UK study used length of stay to measure acculturation, where higher acculturation amongst South Asian immigrant mothers was associated with formula feeding preference [31], while a Canadian study used language use and social media engagement to show that Western‑oriented mothers introduced sweet and fast foods earlier [62]. Consistent with the UK findings, present study showed that living in Australia for more than 10 years reduced the likelihood of exclusive breastfeeding at 6 months. However, speaking a native language at home was protective against early sweet drink introduction, highlighting the complex nature of acculturation. The present study used length of stay and language spoken at home as proxy variables for acculturation; therefore associations with one variable may not be indicative of the complete influence of acculturation which is a multidimensional process [63]. A deeper understanding of these processes is crucial for designing targeted, culturally sensitive interventions that support optimal feeding practices.
Public health implications
These findings have broader public health implications for multicultural populations in high-income countries, where infant feeding practices may be shaped by the intersection of maternal sociodemographic factors and migration. The findings and recommendations from this study align with Australian migrant and maternal-child health policy priorities and highlight the importance of culturally responsive service delivery that incorporates migration-related experiences and co-design principles. The coexistence of guideline-aligned infant feeding practices alongside suboptimal practices suggests that universal infant feeding recommendations in non-native living environments may not be engaging immigrant populations as optimally as they could be. Public health messaging around infant feeding guidelines requires more adaptive, culturally responsive strategies that are sensitive to a diverse range of maternal sociodemographic characteristics, traditions and beliefs. Co-designing strategies to optimise infant feeding practices with immigrant mothers (i.e. with lived experience) and health professionals may be a promising approach to ensure information and interventions are culturally relevant, acceptable, and responsive to real-world barriers, thereby improving infant feeding practices. Whilst this study had limited representation of mothers with limited English proficiency; it is hypothesised that resource translation into commonly spoken Indian languages such as Hindi and Punjabi, will also further enhance accessibility, equity, and inclusivity. Providing culturally appropriate training for healthcare professionals working with immigrant families (e.g. maternal child health nurses, paediatric health care providers) can help better understand the migration process and influence of cultural beliefs, traditions and acculturation impact on infant feeding practices. Community-based peer support interventions may also be an effective strategy to improve infant feeding practices among immigrant mothers by providing culturally relevant and guideline consistent information, social support, and shared lived experience.
Strengths and limitations
The data in this study were collected largely using questions from the already validated Australian National Infant Feeding Survey [12]. Piloting enabled survey refinement. Anonymity and minimal personal data collection improved participation and reduced bias. User friendly Qualtrics survey design enabled access from laptops and mobile devices, which facilitated participation from remote areas [64].
Despite these strengths, several limitations need to be acknowledged. Convenience sampling and recruiting through social media, community groups, and cultural events together with voluntary participation, may have introduced selection bias due to systematic differences between participants and non-participants; and may have different sociodemographic factors and different infant feeding practices [65]. We hypothesise that the online recruitment strategy and survey may have encouraged participation of highly educated mothers with greater digital literacy and potentially more health awareness as higher levels of education and exposure to digital media have been associated with breastfeeding duration and better health outcomes [66]. Consequently, the findings may not be generalisable to Indian immigrant mothers living in Australia with lower educational attainment or limited digital access. Future studies should employ broader recruitment strategies to improve representation from these groups.
Additionally, the modified survey instrument was not formally validated, and this may have introduced measurement error or affected the reliability of some responses [67]. The survey responses may have been subject to social desirability bias (self-reported survey) whereby participants may have reported practices that they perceived as more socially desirable, and recall bias as mothers were eligible to participate and recall infant feeding practices if they had a child up to five years old. Future studies could consider focusing on mothers of infants up to 18 months to reduce the possibility of recall bias but still allow sufficient time to capture adherence to recommendations for continued breastfeeding to 12 months and beyond. Proxy indicators of acculturation may also be a limitation; however, these measures are typically used in understanding infant feeding practices in immigrant populations [63]. Birth weight was excluded from analysis due to missing data (69.6%); future research should examine its influence on infant feeding practices in this population [68]. The cross-sectional study design limits causal inferences and residual confounding is possible as some measures which might influence infant feeding practices (e.g. breastfeeding support, family structure) were not measured.
Conclusion
The study contributes to understanding of contemporary infant feeding practices of Indian immigrant mothers living in Australia and their association with maternal sociodemographic factors. Prolonged breastfeeding duration, timely introduction to solids, and delayed introduction to cow’s milk were consistent with Australian Infant Feeding guidelines. Opportunities exist to improve prevalence of exclusive breastfeeding at 6 months, and to delay the very early introduction of formula and the premature introduction to sweet drinks, by implementing culturally responsive health promotion and service support.
This study identified several maternal sociodemographic factors associated with infant feeding practices, including pre-pregnancy BMI, acculturation, region of residence prior to migration, maternal age, and education. These findings highlight the multifactorial nature of infant feeding behaviours and identify potential targets for future intervention. Future studies should involve prospective studies to understand causal pathways and feeding transitions among Indian immigrant mothers with infants up to 18 months and examine the influence of acculturation to improve understanding of the complex nature of behaviour change after migration, along with the influence of infant formula marketing. Regional contexts, and variables related to acculturation should be considered when creating and delivering health promotion programs aimed at promoting long term health outcomes for children in this immigrant group.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We sincerely thank all the participants who generously donated their time for this study.
Abbreviations
- BMI
Body Mass Index
- GDM
Gestational Diabetes Mellitus
- WHO
World Health Organization
Author contributions
CT, MZ and KAB conceptualised the study. CT, MZ, KAB and EAS-G contributed to methodology, data analysis, and interpretation. CT contributed to data collection, data curation, data analysis, drafting manuscript, review and editing and project administration. KAB, MZ and EAS-G contributed to writing, review and supervision.
Funding
The School of Exercise and Nutrition Sciences, Deakin University, Australia, provided funding for participant reimbursement. CT is the recipient of the Australian Government’s Research Training Program Scholarship.
Data availability
All data supporting the findings of this study are available within the paper and its Supplementary Information.
Declarations
Ethics approval and consent to participate
Ethics approval was obtained from the Human Ethics Advisory Group Health from Deakin University (approval number: HEAG_H 100_2023), and written consent was obtained before mothers completed the online survey. The current study was carried out in accordance with relevant guidelines and recommendations (Australian Code for the Responsible Conduct of Research 2018, and National Statement on Ethical Conduct in Human Research 2018). Written informed consent was obtained from all participants.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Data Availability Statement
All data supporting the findings of this study are available within the paper and its Supplementary Information.