The associations between dairy product intake, fatigue status, and physical activity among postpartum women in Saudi Arabia: a cross-sectional study

Abstract

Background

Fatigue is a major issue that affects women during the postpartum period. A healthy dietary pattern and increased physical activity (PA) are commonly recommended lifestyle modifications to promote health during this time. However, little is known about the interrelationship between dairy product intake, PA level, and postpartum fatigue (PPF) among women. The aim of this study was to evaluate whether PPF is associated with dairy product intake in relation to PA level.

Methods

A total of 242 women were included in this cross-sectional study. Data related to dairy product intake and PA were collected using a food frequency questionnaire and the International Physical Activity Questionnaire—Short Form, respectively. PPF was assessed using the Fatigue Severity Scale. Logistic regression models were used to examine associations between the intake of dairy products and PPF among women engaged in low, moderate, and high levels of PA while controlling for potential confounders.

Results

Higher consumption rates of yogurt and total dairy predicted lower odds of PPF in women engaged in moderate levels of PA (aOR = 0.24 [95% CI = 0.07, 0.86] and 0.70 [95% CI = 0.53, 0.93], respectively). In women engaged in high levels of PA, lower odds of experiencing PPF were predicted by higher consumption rates of milk (aOR = 0.24 [95% CI = 0.07, 0.89]), yogurt (aOR = 0.21 [95% CI = 0.05, 0.83]), laban (aOR = 0.16 [95% CI = 0.03, 0.86]), and total dairy (aOR = 0.66 [95% CI = 0.47, 0.92]). However, no association was observed between dairy product intake and PPF in women with low levels of PA.

Conclusions

Higher consumption rates of dairy products were associated with lower odds for experiencing PPF, particularly for women engaged in moderate to high levels of PA. These findings support nutritional and PA promotion programs to moderate issues with PPF. However, the cross-sectional design of this study could limit the ability to infer causality between dairy intake, PA, and PPF. Further longitudinal studies are needed to establish causality and explore the mechanisms underlying these associations.

Background

Postpartum fatigue (PPF) is a major health issue characterized by a prolonged lack of physical and/or mental energy, a persistent feeling of exhaustion, and impaired concentration [1]. It occurs in women in the weeks after giving birth and is not easily relieved by rest or sleep [2–7]. PPF detrimentally affects women’s health and wellness and negatively impacts the development of the infant [4, 8]. In addition, PPF has been linked to the development of symptoms of anxiety [9] and depression [10] and lowers feelings of parental self-efficacy [11], which may lead to difficulties in caring for the infant and disrupt maternal–infant bonding [12–15].

Previous studies have estimated the incidence rate of PPF to be between 37% and 66%, depending on the postpartum period when fatigue was measured and the methodology used in these studies [16, 17]. Several studies have explored possible predisposing factors for fatigue in postpartum women [16, 18–20]. Such factors have been either psychological (i.e., symptoms of depression and anxiety), socio-demographical (i.e., maternal age and economic status), or related to sleep and breastfeeding [18, 19]. Factors related to the woman’s or child’s health status such as having chronic disease, thyroid abnormalities [21, 22], hormonal imbalances [23], or infant illnesses [24] were also shown to contribute to PPF.

Nutrition may also affect fatigue [25]. Previous research has confirmed the relationship between nutritional intake and fatigue in people with cancer [26–28]. It has been also stated that nutrition crucially facilitates positive lifestyle behaviors and therefore decreases the likelihood of developing cardiometabolic diseases [29]. However, factors related to specific nutrient intake or nutrition insufficiencies, such as dairy, have not been explored in depth in relation to fatigue among postpartum women. Research has shown that symptoms of fatigue decrease with the intake of a Mediterranean diet, Nordic diet, and leaky gut diet as types of anti-inflammatory diets that are high in fiber, omega-3 fatty acids, and polyphenols [30].

Certain nutrients such as fiber, omega-3 fatty acids, calcium, probiotics, and polyphenols have been shown to decrease the inflammatory load, which could further improve the symptoms of fatigue related to neurological or psychological diseases such as Alzheimer’s and depression [27, 31]. Other nutrients such as the vitamin B complex, vitamin C, magnesium, iron, and zinc have also been shown to promote well-being by alleviating both mental and physical fatigue [32]. Thus, good nutrition from foods is a non-pharmacological approach that should be among the first approaches to wellness prior to the introduction of any nutrient supplementation [33].

Whilst research on the beneficial effects of dairy products on PPF is greatly lacking in terms of depth and breadth, a handful of studies have focused on its effects on biomarkers of inflammation [34]. For example, Bordoni et al. reported that dairy products have anti-inflammatory effects in people with metabolic disorders [35]. According to Hess et al.‘s review, there is evidence suggesting that the consumption of dairy foods does not result in significant differences in the impact on biomarkers of inflammation compared to those who do not consume dairy foods [36]. The discrepancy between these findings could easily be misinterpreted as fatigue potentially being associated with pro-inflammatory reactions [37, 38]. However, these differences reveal that dairy products may be a logical option for reducing inflammatory load. This line of research has not been established by a series of studies and therefore requires further work, though a recent study has indicated that dairy foods are associated with lower symptoms of postpartum depression [39].

Physical activity (PA) is defined as any bodily movement caused by the contraction of skeletal muscles [40]. Regular engagement in PA has been shown to improve overall physical well-being; lower the risk of developing cardiovascular disease [41], diabetes mellitus [42], obesity [43], cancer [44], lipid profile abnormalities [45], and bone density disorders [46]; and lower the total mortality rate [47]. In addition, research has revealed positive findings for associations between PA patterns and levels of reported fatigue [48]. It has been shown that pregnant and postpartum women can also reap the benefits of regular PA [49]; the World Health Organization (WHO) recommends at least 150 min of moderate-intensity aerobic exercise each week during pregnancy and postpartum [5]. Despite the well-acknowledged advantages of regular PA, studies note that women tend not to engage in PA during postpartum [50, 51].

Previous research has investigated the positive impact of PA participation on PPF. Results of systematic reviews and meta-analyses revealed that exercise reduces symptoms PPF among mothers, which ultimately may improve maternal quality of life [52, 53]. In an attempt to understand the effectiveness of various types of exercise interventions on PPF, an interventional pilot randomized controlled trial demonstrated that moderate-intensity gymnastic exercise reduces stress, fatigue and improves sleep quality during postpartum [54]. Another study investigated the effect of Pilates home exercises on PPF. The findings showed that, when compared to control group, the interventional group had lower mean scores in the standard Multidimensional Fatigue Inventory, which suggests that physical exercise should be encouraged during postpartum to combat symptoms of PPF [55]. Moreover, a low-intensity exercise program, that incorporates Pilates, yoga movements and music has also shown to be effective in reducing PPF symptoms [56]. Collectively, those results signify the benefits of physical exercise for the overall maternal health and particularly PPF.

Literature has shown that a healthy dietary pattern and increased PA are commonly recommended as lifestyle modifications for managing many conditions including during postpartum [29, 39, 48]. While dairy products and PA have been independently associated with health-related outcomes for chronic diseases such as hypertension [57], other research has found that the combined effect of dairy intake and PA improved bone health and weight status as well as prevention of gestational diabetes [58–60]. Yet, there is limited information on the associations between dairy products intake and fatigue and on the combined effects of dairy products and PA on fatigue in postpartum.

Regular examinations of nutrition and PA can improve or prevent health-related complications. Much of the previous research in this regard has concerned adults in general rather than women during postpartum in particular; therefore, we sought to evaluate the association between dairy intake and fatigue status among women during postpartum. We further endeavored to examine these associations specifically among women engaged in low, moderate, and high levels of PA. These findings might be applied to develop appropriate rehabilitative management strategies that combine nutritional interventions and PA to improve fatigue status during postpartum, a critical phase for women, and, therefore, women’s overall quality of life.

Methods

Study design

A cross-sectional study was conducted between February 2021 and August 2021, targeting women who had recently given birth and residing in all regions of Saudi Arabia. The present study was conducted as part of a research project that focused on maternal health during postpartum. The study was conducted in accordance with the guidelines proposed in the Declaration of Helsinki and was reviewed and approved by the Unit of Biomedical Ethics Research Committee, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia (Registration Number: HA-02-J-008, Reference No 84 − 21).

Sample size calculation

While considering the total female population in Saudi Arabia, OpenEpi.com was employed to estimate the required sample size [61]. With the confidence level set at 95%, the margin of error at 5%, and the anticipated frequency at 50%, the estimated sample size required for this study was 385 participants.

Study participants and recruitment

Women during postpartum who were between 18 and 50 years old, living in Saudi Arabia, within the first two weeks and up to one year after childbirth, and had no history of mental illness, cardiovascular disease, and physical disability were included in the final analyses of the study.

A non-probability convenient sampling method was employed during the recruitment process. An online survey was created using SurveyMonkey^® platform. The link to the survey included the required questionnaire that was provided in Arabic language and was distributed via email and through various social media platforms (WhatsApp, Twitter). Participants were allowed to answer the questionnaire only once. The study protocol, procedures, and participants’ rights were explained at the beginning of the survey and digital informed consent was obtained from all participants prior to their participation. The consent statement presented in the survey was as follows:” By clicking ‘Proceed’ to begin the survey, you are indicating your voluntary participation in this study. You understand that your participation is entirely voluntary, and you have the right to withdraw at any time without penalty. Your responses will be kept confidential, and any identifiable information will be anonymized. Please note that by proceeding, you are giving your informed consent to participate in this study.” The approximate time required to fill out the online questionnaire did not exceed 10–15 min from start to finish.

Study instrument

Demographic data

All participants completed a self-administrated online survey that included the following: sociodemographic data on pregnancy and postpartum-related factors and health-related factors (smoking status, and body mass index). The survey also included the Food Frequency Questionnaire (FFQ), the Fatigue Severity Scale (FSS), the Edinburgh Postnatal Depression Scale (EPDS), and the short form of the International Physical Activity Questionnaire (IPAQ-SF).

Food frequency questionnaire

An Arabic version of the FFQ was adapted from the Saudi Food and Drug Administration’s FFQ [62]. The questionnaire included 133 food-related items that were assessed using a close-ended approach. For each close-ended question, the following nine answer options were provided regarding consumption frequency: never or less than once a month, 1–3 times per month, once a week, 2–4 times per week, 5–6 times per week, once a day, 2–3 times per day, 4–5 times per day, or 6 + times per day.

An additional set of questions regarding other food items that were not listed were included as open-ended questions at the end of the FFQ to gather specific information on nutritional intake. In this study, we utilized FFQ to assess both the frequency and the quantity of dairy product consumption. We examined the consumption as a collective food group and analyzed its components. These components included total dairy intake (measured in servings per day) as well as the specific intake of milk (servings per day), cheese (servings per day), yogurt (servings per day), and laban (servings per day). Servings were used to align with common dietary guidelines and to make the results more relatable to the general public.

Fatigue severity scale

The level of fatigue for each participant was assessed using the FSS. This questionnaire consists of nine items and was first developed by Krupp et al. [63]. Each item is rated from 1 (completely disagree) to 7 (completely agree). The translation of the FSS into Arabic was performed according to international standards, and the resulting tool is valid for use by Arabic-speaking populations [64]. The questionnaire is brief, easy to administer, and demonstrates reliability and internal consistency. Participants with an average score of 4.05 or higher were considered to be experiencing significant fatigue [64]. Responses to the questionnaire items showed good internal consistency among the present sample (α = 0.79).

Edinburgh postnatal depression scale

The EPDS is a ten-item scale developed by Cox et al. to screen for PPD risk to perform additional assessments and treatment recommendations [65]. Each item on the EPDS is scored on a 4-point scale between 0 and 3 based on the severity of the symptoms with total potential scores ranging from 0 to 30. The EPDS is the most widely used PPD screening tool in both the pre- and postnatal periods [66]. The EPDS has been translated into and validated in 18 languages, including Arabic [67]. The Arabic version of the EPDS has a Cronbach’s alpha coefficient of 0.84, which indicates good internal consistency. A cutoff value of ≥ 12 indicates good specificity for postpartum depressive symptoms among Arabic-speaking populations [68].

International physical activity questionnaire—short form

The IPAQ-SF [69] is a self-reporting 7-day recall of PA designed to provide information about the duration and frequency of engagement in different patterns of PA in the previous seven days. The IPAQ-SF categorizes physical activities into four generic groups: vigorous, moderate, walking, and sitting. Participants are sorted into one of the following three PA categories: active (vigorous-intensity activities for at least three days per week totaling at least 1,500 metabolic equivalent of task (MET)-min/week or seven days of any combination of walking, moderate-intensity, or vigorous-intensity activities equivalent to at least 3,000 MET-min/week), minimally active (vigorous activity for at least 20 min per day for three or more days, five or more days of moderate-intensity activities or walking for at least 30 min per day, or five or more days of any combination of walking, moderate-intensity, or vigorous-intensity activities totaling at least 600 MET-min/week), or inactive to insufficiently active (neither minimally active nor highly active). The concurrent validity of the IPAQ-SF shows reasonable agreement with the long-form questionnaire, and its criteria validity reveals fair to moderate agreement with the Computer Science Application, Inc. Accelerometer [70].

Statistical analysis

All data were analyzed using the Statistical Package for Social Sciences (SPSS; version 24.0; Armonk, NY, USA). The distribution of the sociodemographic and general health characteristics and the PPF status were expressed as frequency (percentage). Bivariate analyses were conducted to examine differences in characteristics between the fatigued and non-fatigued groups using the χ² test. The effect size of the χ² test was assessed using Cramér’s V. The magnitudes of the associations were determined as follows: a weak association if Cramér’s V was between 0.10 and < 0.20, a moderate association if Cramér’s V was between 0.20 and < 0.40, a relatively strong if Cramér’s V was between 0.40 and < 0.60, and a strong association if Cramér’s V was ≥ 0.60 [71].

The normality assumption for the dairy intake variables was tested using the Shapiro–Wilk test of normality; the results indicated non-normal distribution of dairy intake data (p < 0.05). Descriptive statistics for the dairy intake variables were illustrated using median (M) [interquartile range (IQR)]. The non-parametric Mann–Whitney U test was used to investigate differences in dairy intake between the fatigued and non-fatigued groups, wherein the effect size was evaluated using the effect size estimator r. The strength of the effect size was determined based on Cohen (1992) [72]; small effect size if the r estimate was between 0.10 and < 0.30; medium effect size if the r estimate was between 0.30 and < 0.50; large effect size if the r estimate was ≥ 0.50 [73].

To examine the association between the intake of milk, cheese, yogurt, laban, and total dairy products (servings per day), logistic regression analyses were conducted with the dichotomous PPF status variables (fatigued vs. not fatigued) as the dependent variable. First, simple logistic regression models (Model 1) were examined for each independent variable (milk, cheese, yogurt, laban, and total dairy intake [servings per day]) to estimate the odds ratios (ORs) and associated 95% confidence intervals (CI). Then, multiple regression models (Model 2) were tested, adjusting for the empirical confounders (based on significant bivariate analyses), including employment status, monthly income, postpartum phase, PPD risk, and PA, wherein the adjusted ORs (aORs) and associated 95% CI were reported.

To examine whether the association between dairy product intake and PPF status was moderated by PA levels, interaction terms for milk, cheese, yogurt, laban, and total dairy intake with PA were included in fully adjusted models. The interaction terms were statistically significant (p < 0.001), which suggested that the association between the intake of all dairy product variables and PPF status may vary by PA level. Thus, separate logistic regression analyses were conducted to examine the association between dairy product intake (independent variable) and fatigue status (dependent variable) among women engaged in low, moderate, and high PA, adjusted for employment status, monthly income, postpartum phase, and PPD risk (empirical confounders).

Results

A total of 1855 participants responded to the survey. Of these respondents, 59 (3.2%) did not agree to participate, and 1073 (57.85%) did not complete the entire questionnaire. 723 (38.9%) participants completed the entire questionnaire. Of the 723, a total of 481 (66.5%) participants were then excluded, as their data in the food frequency questionnaire were either hyper-inflated or deflated or did not fulfill the eligibility criteria (i.e., exceeded the maximum age (50) for study participation). The remaining 242 participants’ responses were included in the final analysis for the study.

As number of participants included in the analysis was lower than the priori estimated sample size, the power of the study was calculated according to the current sample size of 242, effect size of 0.3 and significant level of 0.05. The power calculation ≈ 99%; indicating that there is a high likelihood of detecting an effect with the current sample size. The flowchart of study’s participant selection (Fig. 1) represents the sequence of steps followed for participant eligibility in the study.

Fig. 1.

Flowchart of study’s participant selection

Characteristics of the sample and differences by fatigue status

Approximately half of the postpartum women were experiencing fatigue (n = 109; 45.0%); see Table 1. The majority of the postpartum women were Saudis (n = 224; 92.6%), non-smokers (n = 225; 93.0%), and held a college degree or higher (n = 194; 80.2%). Over two-thirds of the sample were at risk of PPD (n = 167; 69.0%). Proportions of women experiencing PPF were statistically significantly different for employment status (p = 0.003) with a weak effect size (Cramér’s V = 0.19), monthly income (p < 0.001) with a moderate effect size (Cramér’s V = 0.34), postpartum phase (p = 0.001) with a moderate effect size (Cramér’s V = 0.26), PPD risk (p = 0.004) with a weak effect size (Cramér’s V = 0.13), and PA (p < 0.001) groups, with a moderate effect size (Cramér’s V = 0.35).

Table 1.

Characteristics of the sample and differences between fatigued and non-fatigued postpartum women

Variables		Total sample (n = 242)	Fatigued (≥ 4.05) n = 109 (45.0%)	Non-fatigued (< 4.05) n = 133 (55.0%)	p-value
Age in years, n (%)	18–19	4 (1.70)	1 (0.90)	3 (2.30)	0.049
	20–29	151 (62.4)	59 (54.1)	92 (69.2)
	30–39	82 (33.9)	47 (43.1)	35 (26.3)
	40–49	5 (2.10)	2 (1.80)	3 (2.30)
Nationality	Saudi	224 (92.6)	102 (93.6)	122 (91.7)	0.586
	Non-Saudi	18 (7.40)	7 (6.40)	11 (8.30)
Education	< college degree	48 (19.8)	23 (21.1)	25 (18.8)	0.655
	≥ college degree	194 (80.2)	86 (78.9)	108 (81.2)
Employment status	Unemployed	95 (39.3)	54 (49.5)	41 (30.8)	0.003*
	Employed	147 (60.7)	55 (50.5)	92 (69.2)
Monthly income in SAR	≤ 10,000	138 (57.0)	42 (38.5)	96 (72.2)	< 0.001*
	> 10,000	104 (43.0)	67 (61.5)	37 (27.8)
Weight status	Underweight	3 (1.20)	2 (1.80)	1 (0.80)	0.222
	Normal weight	88 (36.4)	35 (32.1)	53 (39.8)
	Overweight	113 (46.7)	58 (53.2)	55 (41.4)
	Obese	38 (15.7)	14 (12.8)	24 (18.0)
Postpartum phase	≤ 1 month	39 (16.1)	15 (13.8)	24 (18.0)	0.001*
	2–3 months	53 (21.9)	15 (13.8)	38 (28.6)
	4–6 months	56 (23.1)	22 (20.2)	34 (25.6)
	7–12 months	94 (38.8)	57 (52.3)	37 (27.8)
PPD risk	PPD risk	167 (69.0)	68 (62.4)	99 (74.4)	0.044*
	Non-PPD risk	75 (31.0)	41 (37.6)	34 (25.6)
Smoking status	Smoker	17 (7.00)	11 (10.1)	6 (4.50)	0.091
	Non-smoker	225 (93.0)	98 (89.9)	127 (95.5)
PA level	Low	106 (43.8)	68 (62.4)	38 (28.6)	< 0.001*
	Moderate	82 (33.9)	28 (25.7)	54 (40.6)
	High	54 (22.3)	13 (11.9)	41 (30.8)

^{* p < 0.05 is significant}

^{Data presented as n (%)}

^{PPD: Postpartum depression}

^{PA: Physical Activity}

Differences in dairy intake by fatigue status

Bivariate analyses were conducted to evaluate differences in the intake of dairy products (servings per day) between fatigued and non-fatigued postpartum women (Table 2). Compared to non-fatigued women, women experiencing fatigue reported significantly lower intakes of milk (M = 1.00 [0.12–2.00] vs. 0.43 [0.09–1.00] servings/day, p = 0.011), cheese (M = 1.00 [0.49–2.46] vs. 0.55 [0.20–1.03] servings/day, p < 0.001), yogurt (M = 0.57 [0.00–1.52] vs. 0.14 [0.00–0.80] servings/day, p = 0.007), laban (M = 0.43 [0.00–1.14] vs. 0.12 [0.00–0.62] servings/day, p = 0.011), and total dairy food products (M = 5.00 [2.00–7.49] vs. 2.00 [1.26–3.48] servings/day, p < 0.001). The effect sizes for milk intake (r = 0.16), yogurt intake (r = 0.17), and laban intake (r = 0.16) suggest weak associations with the fatigue status. However, moderate effect sizes were observed for the associations of cheese intake (r = 0.26) and total dairy intake (r = 0.30) with the fatigue status in postpartum women.

Table 2.

Dairy intake and differences in fatigue status among postpartum women

Intake of dairy product (servings/day)		Total sample (n = 242)	Fatigued (≥ 4.05) n = 109 (45.0%)	Non-fatigued (< 4.05) n = 133 (55.0%)	p-value
Milk intake	Median (IQR)	1.00 [0.12–1.00]	0.43 [0.09–1.00]	1.00 [0.12–2.00]	0.011*
Cheese intake	Median (IQR)	0.92 [0.26–2.00]	0.55 [0.20–1.03]	1.00 [0.49–2.46]	< 0.001*
Yogurt intake	Median (IQR)	0.42 [0.00–1.00]	0.14 [0.00–0.80]	0.57 [0.00–1.52]	0.007*
Laban intake	Median (IQR)	0.14 [0.00–1.00]	0.12 [0.00–0.62]	0.43 [0.00–1.14]	0.011*
Total dairy intake	Median (IQR)	2.91 [1.38–6.33]	2.00 [1.26–3.48]	5.00 [2.00–7.49]	< 0.001*

^{* p < 0.05 is significant}

^{IQR: interquartile range; SD: standard deviation}

Associations between the intake of dairy products and fatigue status

The associations between dairy intake (servings/day) and PPF status were tested in logistic regression models (Table 3). Lower odds of experiencing PPF were predicted by a higher intake of milk (OR = 0.74 [95% CI = 0.57, 0.95]), cheese (OR = 0.64 [95% CI = 0.51, 0.80], yogurt (OR = 0.59 [95% CI = 0.43, 0.81]), laban (OR = 0.68 [95% CI = 0.51, 0.91]), and total dairy (OR = 0.83 [95% CI = 0.76, 0.91]). However, the associations of milk, yogurt, and laban intake with PPF status disappeared when the models were adjusted for the empirical confounders, including employment status, monthly income, postpartum phase, PPD risk, and PA (Separate analyses indicated the effect is attributed to adding all confounders to the model). Nonetheless, the associations between PPF status and the intake of cheese (aOR = 0.72 [95% CI = 0.56, 0.93]) and dairy products (aOR = 0.90 [95% CI = 0.82, 0.99]) remained significant.

Table 3.

Logistic regression analysis of dairy intake on fatigue status (n = 242)

Intake of dairy product	Model 1		Model 2
	OR [95% CI]	p-value	aOR [95% CI]	p-value
Milk intake (servings/day)	0.74 [0.57, 0.95]*	0.017	0.80 [0.60, 1.06]	0.114
Cheese intake (servings/day)	0.64 [0.51, 0.80]**	< 0.001	0.72 [0.56, 0.93]*	0.012
Yogurt intake (servings/day)	0.59 [0.43, 0.81]**	0.001	0.75 [0.54, 1.04]	0.084
Laban intake (servings/day)	0.68 [0.51, 0.91]*	0.009	0.87 [0.64, 1.17]	0.347
Total dairy intake (servings/day)	0.83 [0.76, 0.91]**	< 0.001	0.90 [0.82, 0.99]*	0.022

^{aOR: adjusted odds ratio; CI: confidence interval}

^{Model 1: unadjusted models; Model 2: adjusted for employment status, monthly income, postpartum phase, postpartum depression (PPD) risk, and physical activity (PA)}

^{* p < 0.05; ** p < 0.01}

Adjusted associations between the intake of dairy products and fatigue status according to PA levels

Examining the association between dairy intake and PPF status while stratifying by PA and controlling for covariates (employment status, monthly income, postpartum phase, and PPD risk) revealed that higher consumption rates of yogurt and total dairy predicted lower odds of experiencing fatigue among postpartum women who were engaged in moderate PA (aOR = 0.24 [95% CI = 0.07, 0.86] and 0.70 [95% CI = 0.53, 0.93], respectively); see Table 4. In postpartum women engaged in high levels of PA, lower odds of experiencing fatigue were predicted by the higher consumption of milk (aOR = 0.24 [95% CI = 0.07, 0.89]), yogurt (aOR = 0.21 [95% CI = 0.05, 0.83]), laban (aOR = 0.16 [95% CI = 0.03, 0.86]), and total dairy (aOR = 0.66 [95% CI = 0.47, 0.92]). In contrast, no associations were found between the intake of all dairy products and PPF status for women who reported low PA levels.

Table 4.

Adjusted associations between dairy product intake and fatigue status stratified by PA level1

Intake of dairy product	PA level (n = 242)
	Low PA (n = 106, 43.8%)		Moderate PA (n = 82, 33.9%)		High PA (n = 54, 22.3%)
	aOR [95% CI]	p-value	aOR [95% CI]	p-value	aOR [95% CI]	p-value
Milk intake (servings/day)	0.95 [0.65, 1.39]	0.778	0.81 [0.45, 1.45]	0.472	0.24 [0.07, 0.89]*	0.032
Cheese intake (servings/day)	0.90 [0.61, 1.34]	0.615	0.60 [0.34, 1.04]	0.068	0.50 [0.25, 0.99]	0.047
Yogurt intake (servings/day)	1.72 [0.85, 3.47]	0.132	0.24 [0.07, 0.86]*	0.028	0.21 [0.05, 0.83]*	0.026
Laban intake (servings/day)	1.63 [0.87, 3.03]	0.125	0.41 [0.15, 1.15]	0.090	0.16 [0.03, 0.86]*	0.032
Total dairy intake (servings/day)	1.06 [0.92, 1.22]	0.435	0.70 [0.53, 0.93]*	0.015	0.66 [0.47, 0.92]*	0.015

^{aOR: adjusted odds ratio; CI: confidence interval}

^{1 Adjusted for employment status and monthly income, postpartum phase, and postpartum depression status (PPD)}

^{* p < 0.05}

^{PA: Physical Activity}

Discussion

This study aimed to evaluate the associations between the intake of dairy products and fatigue status among postpartum women and to examine these associations in postpartum women engaged in low, moderate, and high PA levels. Nearly half of participants reported experiencing PPF. This is consistent with previous research, which has found that 18–66% of postpartum women experienced fatigue [16, 17].

The bivariate analysis indicated statistically significant differences in the proportions of women experiencing PPF based on employment status (p = 0.003, Cramér’s V = 0.19), monthly income (p < 0.001, Cramér’s V = 0.34), postpartum phase (p = 0.001, Cramér’s V = 0.26), PPD risk (p = 0.004, Cramér’s V = 0.13), and PA levels (p < 0.001, Cramér’s V = 0.35); yet, the associations of PPF with monthly income and PA level appeared more meaningful (moderate effect sizes) than the other demographic and health-related variables (moderate effect sizes). The observed associations emphasize potential targets for interventions aimed at mitigating PPF in women, particularly those with lower income or less PA. which aligns with previous research [19, 20, 48].

The bivariate analysis of the association between dairy intake and PPF were statistically significant but weak for the intake of milk (p = 0.011, r = 0.16), yogurt (p = 0.007, r = 0.17), and laban (p = 0.011, r = 0.16), indicating that the variations in milk, yogurt, and laban consumption are minimally associated with PPF. However, more pronounced moderate effect sizes were observed for the associations of cheese intake (p < 0.001, r = 0.26) and total dairy intake (p < 0.001, r = 0.30) with fatigue status. Similarly, while the unadjusted associations between PPF and dairy products were significant for each of the dairy products, adjusting the associations by confounders (employment status, monthly income, postpartum phase, PPD risk, and PA) eliminated the statistical significance for milk, yogurt, and laban. These findings suggest that higher consumption of cheese and overall dairy intake may have a more substantial impact on PPF compared to milk, yogurt, or laban. As such, the results emphasize the importance of considering different dairy sources when exploring dietary factors associated with PPF.

The associations observed between dairy products and PPF contribute to the growing body of research on dietary factors that affect maternal health during postpartum. There are several possible explanations for these findings based on the nutritional content of dairy products and existing research in this area. For instance, dairy products contain tryptophan, which is involved in the production of serotonin and melatonin, neurotransmitters that regulate mood and sleep as well as suppress the action of the inhibitory neurotransmitter gamma-aminobutyric acid, which can promote sleep [74]. Indeed, several studies have suggested that consuming dairy products may positively affect sleep quality, which could indirectly influence the severity of fatigue [74].

Furthermore, probiotics derived from dairy products (i.e., yogurt, laban, and cheese) may foster a healthier gut microbiota. Indeed, a well-balanced gut microbiota has been implicated in various aspects of well-being, including fatigue management [30], potentially through its regulatory effects on inflammatory pathways. For example, probiotics in yogurt can modulate the gut microbiota and reduce inflammation by downregulating the production of pro-inflammatory cytokines [75].

Fatigue is a common condition among individuals with inflammatory diseases, such as inflammatory bowel diseases, rheumatologic diseases, cancers, and systemic autoimmune diseases. Although the etiologies of fatigue symptoms are complex and varied, inflammation has been suggested as a potential link between these symptoms [38]. For instance, a connection between the genes responsible for the expression of inflammatory cytokine and fatigue has been reported, regardless of chronic illness, which suggests that inflammation may play a significant role in fatigue [76]. Moreover, studies have found a correlation between fatigue and increased levels of inflammatory cytokines, such as TNF, IL-6, and IL-1. These cytokines may interact with the central nervous system and trigger fatigue [77]. As such, a comprehensive examination of the potential anti-inflammatory attributes of dairy products is critical to better understand their role in mitigating fatigue [35].

Hess et al. (2021) reviewed the existing evidence regarding the inflammatory properties of dairy products and their components, such as proteins, fats, probiotics, and bioactive peptides [36]. They also evaluated the impact of dairy consumption on inflammatory markers and the risk of chronic diseases. Although the evidence is not sufficient to conclusively establish an anti-inflammatory effect of dairy products, the study suggests that a high intake of dairy foods does not increase concentrations of biomarkers associated with chronic systemic inflammation. In light of these findings, low dairy consumption may contribute to PPF, due to the anti-inflammatory properties of dairy products. Furthermore, the association may differ according to the types of dairy products consumed, with fermented dairy products (e.g., yogurt) showing stronger inverse associations compared to non-fermented ones (e.g., milk) [35].

Additionally, nutrients in milk, such as calcium, have been shown to affect the production of inflammatory cytokines, while normal vitamin D status has been linked to reduced levels of inflammation [78, 79]. Vitamin D is playing a crucial role in modulating inflammation, particularly through its influence on the NF-κB pathway. This pathway is overactivated in people with chronic fatigue syndrome. The active form of vitamin D, known as calcitriol, can suppress NF-κB activation and its promotion of inflammatory responses. Additionally, vitamin D supports proper immune system function and improves the body’s defenses against microbial infection by acting on skin and mucosal barriers. Overall, vitamin D plays a key role in controlling inflammation and supporting immune responses, which may be relevant in addressing fatigue-related conditions like chronic fatigue syndrome [30].

Scrutinizing the associations between dairy product consumption and fatigue in postpartum women while accounting for PA levels along with other covariates indicated that a higher intake of yogurt and overall dairy was linked to a reduced likelihood of fatigue in women participating in moderate PA. In addition, for those engaged in high PA, a decreased likelihood of fatigue was associated with increased intake of milk, yogurt, laban, and total dairy products. However, this relationship was not observed in women with low PA. These findings underscore the potential role of PA in shaping the observed association between dairy intake and fatigue status among postpartum women.

Our results suggest that the beneficial effects of dairy consumption on PPF might be more pronounced in women who engage in moderate to high PA. This finding highlights the importance of promoting a balanced diet, one that potentially includes dairy products and engaging in regular PA as part of an integrated approach to managing PPF and enhancing maternal well-being. Indeed, PA has been recognized as a crucial intervention in alleviating PPF. Various studies have demonstrated the positive effects of regular PA on maternal women’s well-being, including the reduction of PPF symptoms. For instance, Qian et al. (2021) conducted a systematic review and meta-analysis and concluded that engaging in regular PA during the postpartum period can lead to reduced symptoms of PPF [52]. To further highlight the widespread benefits of PA, regular exercise promotes better health-related outcomes and physical fitness [80]. As per WHO guideline of recommended intensity [81], exercise increases cardiovascular health and fitness and enhances the body oxygen circulation, consumption and uptake [82–84]. In addition, regular participation in PA benefits muscle strength, endurance as well as to muscle contractile function [85, 86], in which a switch toward more slow-twitch type 1 fibers (fatigue resistance) may occur [87–89]. Thus, regular exercise may improve energy production, leading to less fatigue experience.

Dairy products, as previously mentioned, are a good source of high-quality proteins and calcium, vital nutrients for bones and muscle mass maintenance. It is well known that sufficient dairy consumption and the absorption of protein and vitamin D are essential for boosting muscle strength. It has been also found that gut microbiota are important for muscular size, strength, and function [90, 91]. Translating this into the context of postpartum mothers, proper dairy intake while being physically active may have a combined effect in mitigating PPF via improving muscle health, which may better enhance the ability to do routine and everyday tasks easier and be less fatigable [53, 91]. The combined effects on muscle mass, strength and functions could possible explanations on how the association between dairy intake and fatigue might vary based on PA level. Considering our findings, our study emphasizes the importance of promoting PA as a key intervention to address PPF in combination with consuming a balanced diet that includes dairy products. Public health initiatives targeting postpartum women’s nutrition should promote the dual benefits of PA and sufficient dairy consumption for combating fatigue. Given the positive impacts observed, our results could inform the development of nutritional guidelines tailored to manage postpartum fatigue more effectively. However, further research should investigate this in more depth and provide clear cellular and physiological interpretations of the underlying mechanisms.

Strengths and limitations

The study sample consisted of respondents from a national dataset from a wide range of sociodemographic backgrounds in terms of age, level of education, employment status, income, weight, postpartum period, PPD risk, smoking status, and level of PA. The assessment of the relationships between these factors and the outcome of interest addresses fatigue in interventions to improve maternal health and well-being.

Regarding the limitations of our study, it should be noted that we focused only on examining dairy products, such as cheese, yogurt, laban, and milk, as whole food items without specifically measuring their individual nutrient components, such as probiotics and calcium. This approach may have limited our ability to elucidate the mechanisms underlying their associations and establish a direct link between these specific nutrients and fatigue. Future investigations should consider analyzing the effects of specific dairy components to gain a deeper understanding of their potential associations with fatigue. Additionally, data pertaining average daily dietary intake were not collected, which might influence the association between dairy product intake and PPF status. Future studies may consider evaluating dietary intake data, including macro- and micronutrient intake, to determine whether an individual dietary component may influence the associations between dairy product intake and PPF status. Moreover, other food items containing antioxidants or anti-inflammatory properties should also be taken into consideration in future research.

It is also important to note that the design of this was a cross-sectional survey design which may limit the ability to infer causality between dairy intake, PA, and PPF. Further longitudinal studies are needed to establish causality and explore the mechanisms underlying these associations. Furthermore, our assessments and estimations of dairy intake, PA, and fatigue severity measurements relied on self-reporting data collection methods rather than objective measures such as food intake records, journals, or other in-clinic physiological measurements. Thus, future investigations should incorporate a variety of measures to explore the intricacies of postpartum and better understand the underlying mechanisms of these associations as well as investigate the potential synergistic effects of dairy intake and PA on PPF and other maternal health outcomes. It should also be noted that the self-reporting data collection methods through electronic means may have led to reporting bias and potentially overestimated or underestimated results. An example of such issue in our study that we had to exclude those who exceeded the age criterion of the study (50 years old), as mothers’ year of birth might be typed incorrectly or they might be unaware of the exact year of their age, which may have led to such error and therefore an exclusion from the study. Future studies should adopt a rigorous method that affirm the age of mothers provided to prevent such limitations.

Additionally, our data is considered preliminary and only involved mothers who lived in Saudi Arabia during the postpartum period, which may have led to a selection bias and therefore hindered the generalizability of our findings to all mothers. Thus, it would be essential to assess the applicability and generalizability of these findings across diverse populations and cultural contexts.

Although our results identified significant relationships in the data, it is also important to note that after the data cleaning process, our study had sample size that was smaller than the power estimation, which may impact the validity of the study. Future replication of the study, perhaps with using multi-center approach, to include larger sample size is recommended in order to yield better representation, to provide more precise results and to draw valid conclusions.

An additional limitation in this specific study is that we did not collect information about sleep patterns and quality or influence of breastfeeding practices for mothers and infants. Such factors could directly or indirectly influence the level of PA, fatigue, as well as the nutritional intake. Further studies concerning postpartum maternal health should take the sleep and breastfeeding components into consideration.

Conclusions

The findings of the present study highlight that consuming lower amounts of dairy products was significantly associated with higher levels of fatigue in women during postpartum. In addition, higher consumption rates of dairy products were associated with a decreased likelihood of experiencing PPF in women who were engaged higher levels of PA. Together, our findings suggest that the consumption of dairy products and participation in PA are vital lifestyle components for managing fatigue during postpartum. Future studies should consider multimodal rehabilitation techniques, including promoting and implementing nutritional and PA strategies, to manage or prevent PPF.

Abbreviations

PPF

Postpartum fatigue

PPD

Postpartum Depression

FSS

Fatigue Severity Scale

IPAQ-SF

International Physical Activity Questionnaire- Short Form

NCDs

Non-communicable diseases

PA

Physical Activity

WHO

World Health Organization

Author contributions

All the authors contributed substantially to this manuscript. ASA, SA, HSZ, HAK, MDA and BAB contributed to the study conception and design. ASA, SA, HSZ and BAB contributed to data collection. ASA, SA, HSZ, HAK, MDA and BAB contributed to data analysis and interpretation of the analyzed data. ASA, SA, HSZ, HAK, MDA and BAB wrote the original manuscript. All authors have reviewed the manuscript for important intellectual content. All authors read, revised, and approved the final draft of the manuscript.

Funding

This study received no external funding.

Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to preparation of other potential manuscripts but are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with the guidelines proposed in the Declaration of Helsinki and was reviewed and approved by the Unit of Biomedical Ethics Research Committee, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia (Registration Number: HA-02-J-008, Reference No 84 − 21). The study protocol, procedures, and participants’ rights were explained at the beginning of the survey and digital informed consent was obtained from all participants prior to their participation. Participants were informed that they were free to leave the survey at any point and no personal information would be identified.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.