Iron is an essential micronutrient for human health, and is involved in DNA and enzyme synthesis, oxygen transportation, erythropoiesis, metabolism, and immune function [1
]. Low iron status may result in iron deficiency anaemia (IDA) and is associated with poor physical, cognitive, and immune development and function [3
]. Additionally, iron deficiency (ID) without IDA has also been associated with negative effects in adults, including lethargy, difficulty concentrating, and poor immune function [1
Dietary iron is present in two forms, haem iron (HI) and non-haem iron (NHI), with HI being absorbed from the gut with greater efficiency [1
]. The greater efficiency of absorption is due to specific haem transporters which enable HI to pass directly across cell membranes and into the bloodstream [2
], whereas NHI is unable to utilise these transporters, requiring reduction of ferric iron to ferrous iron to occur prior to absorption [2
]. Animal products, such as meat, poultry, and fish, are major dietary contributors of HI, comprising approximately 55–70% of the total iron content of these products [7
]. The remainder of the iron in these food items, and iron present in non-animal products, such as legumes, breads, and cereals, including the elemental iron present in supplements and for food fortification, is NHI [1
]. As a result, although HI typically makes up 10–15% of dietary iron intake in an omnivorous diet, it contributes 40% or more to the total iron absorbed by the body due to its higher absorptive capacity [9
]. As such, the type of dietary iron (HI or NHI) may be a more important determinant of iron status than total dietary iron intake [10
Young women of child bearing age (<50 years) are one of the most at-risk group for ID with a prevalence in Australia estimated to be 20% [11
]. Young women are also at increased risk of IDA with 6.4% of Australian women compared to only 2.5% of young men reported to have IDA [12
]. Women’s higher risk of ID can be attributed to menstrual losses, which can contribute significantly to ongoing iron depletion during the reproductive years [13
]. Women also often have lower overall dietary intake and, in turn, iron intake when compared to men [14
]. This is particularly important during pregnancy as during the third trimester iron requirements increase substantially to support the growth of the foetus [16
]. Young women, in particular, are at risk of low iron intake due to the high proportion engaging in dieting behaviours, such as energy or food group restriction, and disordered eating [17
] which may increase an individual’s risk of nutrient deficiencies [18
]. Dietary restraint often involves reduced intake of red meat, and should be explored for when studying the relationship between diet and risk of ID/IDA.
Other factors may affect iron status in young women. The oral contraceptive pill, commonly used in this age group, protects against ID through reduced menstrual losses [20
]. Inflammation secondary to a range of conditions, including obesity, is known to alter iron metabolism and is often associated with ID [22
]. Inflammation can complicate diagnosis of iron status as serum ferritin (SF) (a key indicator of ID) is an acute phase reactant and may be falsely elevated in the presence of inflammation, potentially leading to missed diagnosis of ID [23
]. As young women are one of the groups within the population who are at an increased risk of obesity [24
], it is of clinical importance that obesity be accounted for when examining iron status studies.
Few studies have assessed intakes of both HI and NHI in conjunction with dieting habits and weight status. A recent study examined the contribution of HI intake to iron status in a large cohort of Australian women [25
], however, in that study iron status was self-reported rather than measured haematologically. Furthermore, we sought to understand how HI and NHI intakes independently contributed towards iron status in young women. Therefore, this study aimed to explore the associations between intakes of both HI and NHI and the iron status of young women while taking into account dietary restraint, inflammation, and other confounders.
This cross-sectional study recruited 299 healthy young (18–35 years) women. The prevalence of ID and IDA within the group was 26.3% (n
= 71) and 5.9% (n
= 16), respectively, with 67.5% of the group being IR (n
= 183). Participants with ID and IDA were pooled (n
= 87) and compared to IR, and their characteristics summarised in Table 1
Participants were of varying education levels, with 56.3% having completed a tertiary degree (n = 152). The mean weight of participants was 77.9 ± 23.8 kg with a mean BMI of 28.5 ± 8.6 kg/m2. Age, ethnicity, location (urban/rural), total activity (METmin/week), anthropometric measurements, and dietary restraint were not significantly different between the IR and ID/IDA groups.
The distribution of participants across education groups was significantly different (p = 0.014). It was found that participants with secondary education as their highest qualification were twice as likely (odds ratio 2.1) to be ID/IDA than those with higher education (χ2(2) = 8.365, p = 0.015).
Participants with high dietary restraint had significantly lower reported energy intakes than those with low or moderate restraint. Mean energy intake for high restrainers was 6622 kJ, compared to 7556 kJ and 8148 kJ for moderate and low restrainers, respectively (p = 0.001). Dietary restraint was compared between OB and NW participants, which showed no significant weight-related differences.
There were significantly more low-energy reporters in the ID/IDA group (p = 0.005), with 70.1% compared to 51.9% for IR. Low-energy reporting was also significantly higher in the OB versus the NW groups (χ2(1) = 18.046, p < 0.0005), with 71.4% of OB participants reporting low energy intakes compared with 45.8% of NW participants (data not shown). There were also significantly more low energy reporters in the high dietary restraint group when compared to the low and moderate restraint groups (p = 0.029, n = 49(31.4%)).
The oral contraceptive pill was used by 32.3% of the cohort and was not found to be significantly different between the two iron status groups (p = 0.863). Although there were missing data for oral contraceptive pill use (n = 35), the proportion of missing data from both groups was not significant.
IR participants had higher average reported energy intakes than ID/IDA participants (Table 2
). When comparing food and nutrient intakes that were unadjusted for energy, intakes of all nutrients (with the exception of calcium and vitamin C), meat, red meat, and grains and cereals, were significantly higher for IR participants (Table A1
). When comparing unadjusted food groups intakes of meat, red meat and alcohol were significantly higher in IR participants than those with ID/IDA (Table A1
After adjusting for energy (Table 2
), IR participants were found to consume higher amounts of HI than ID/IDA participants, with mean intakes of 2.1 ± 1.0 mg and 1.8 ± 0.8 mg per day respectively (p
= 0.043). Additionally, intakes of iron (p
= 0.012) and zinc (p
= 0.008) were significantly higher in the IR group compared to the ID/IDA group. Overall, when looking at food group data, there was a trend for higher consumption of meat in IR compared to ID/IDA participants (p
Intakes of HI and NHI, and higher levels of education were positively associated with SF (Table 3
). HI had a stronger association with SF (β
= 0.128) than NHI (β
= 0.037). The overall model explained 5.8% of the variance in SF. The addition of energy intake into the model did not substantially affect the regression coefficients for HI and NHI intake.
The main findings of this study were the significant, positive association between energy-adjusted HI and NHI intake and SF and total energy intake and SF on iron status in healthy young women. Energy-adjusted HI had a stronger association than NHI, indicating that iron bioavailability is an important consideration for maintaining normal iron status in young women during reproductive years. The negative effect of restricting energy intake on iron status also reinforces the importance of adequate energy consumption to healthy iron status. The proportion of women with ID and IDA within the sample was 25.6% and 5.6%, respectively, or approximately one third of participants having a sub-optimal iron status. This high prevalence of sub-optimal iron status, when compared to current estimates of 20% within the Australian population [11
], confirms the relevance of examining this nutrient deficiency in young women. No associations were found between SF and BMI, OCP use, or level of physical activity; however, women with the lowest level of education (high school completion only) had lower SF than those with the highest level of education (tertiary degree completion). The overall model including energy adjusted HI and NHI and level of education only explained 5.8% of the variance in SF. Therefore, other factors, such as iron loss via menstruation and the presence of absorption enhancers and inhibitors for NHI [44
], would be expected to contribute to the variance in SF levels.
HI was found to be an independent predictor of SF in healthy young women. This indicates that intake of HI containing products such as meat (beef, veal, lamb, poultry, and fish) makes a useful contribution to maintaining adequate SF levels. This is supported by the analysis of food groups, which showed a non-significant trend for greater energy-adjusted meat consumption (p
= 0.058) in IR participants. While this association has been suggested previously [10
], few studies have combined the use of biochemical markers to diagnose iron deficiency, or specifically identify both HI and NHI intakes. Although NHI was a significant predictor of SF in this study, it was more weakly associated with SF (β
= 0.037) when compared to HI (β
= 0.128). This is likely due to its lower absorptive capacity when compared to HI [5
]. Despite this, the contribution of NHI is important to consider, especially for vegetarians and vegans who rely solely on NHI. In this case, the bioavailability of NHI can be increased by the concurrent intake of enhancers, such as ascorbic acid [45
] or, conversely, inhibited by intake of phytates found in fibrous foods which bind to NHI in the gut, limiting its absorption [46
]. The concurrent intake of both copper and zinc in specific mole ratios with iron can also cause decreases in iron absorption as the metals compete for transport across the gut [47
]. The dual significance of both HI and NHI has also been reported in the French population [48
], whilst the significance of NHI in the presence of absorption enhancers has also been noted in women from Central Mexico [49
] and China [50
Although biochemical evidence of zinc status was not reported in this study, zinc intake, although well above the RDI for women of this age group (8 mg/day), was found to be significantly different between the ID/IDA and IR groups, with IR participants consuming a significantly higher amount. This is consistent with previous research reporting that zinc intake increases with iron intake [51
] and is likely due to both zinc and iron being found in similar foods, such as meat products and some fortified foods [52
Another important finding from this study was the significant difference in reported energy intake between ID/IDA and IR groups. This is supported by other research which has found that increased total energy intake was associated with increased total iron intake [53
]. The additional energy consumed by the IR group was not from any one particular food group, and any differences in energy-adjusted food group intake did not reach statistical significance. However, the main differences in consumption appeared to be in the meat group, especially red meat, with a non-significantly greater number of servings in the IR group, supporting the stronger association that HI had with SF (p
High dietary restraint was found to be associated with lower energy intakes, suggesting that this is a risk factor for maintaining iron status in young women. Numerous studies have reported on the link between dieting and risk for micronutrient deficiency and also the tendency for iron containing foods such as meats, especially red meats, being more heavily restricted than other food groups when dieting occurs in young women [17
]. This is further supported by Cheng et al. (2013) who found that overweight and obese participants on energy restricted diets were unable to meet the recommended intake of iron, despite meal plan manipulation and dietary modelling [54
]. Interestingly, no significant difference was found between OB and NW weight groups for dietary restraint. This suggests that high restraint resulting in decreased energy intake could have negative impacts on iron status regardless of body weight or BMI.
Tertiary education was also significantly associated with higher SF which may be a result of participants being more aware of their health, including the risk of iron deficiency during reproductive years, leading individuals to follow better quality diets [55
]. It has been shown that socioeconomic status (SES) also including income and occupation have an impact on diet quality and iron status [55
Strengths of this study included the use of biochemical markers to adjust for inflammation and for the diagnosis of iron status. The collection of biochemical data is important for ID/IDA diagnosis as women may not always be aware of their iron status [57
], and this is a limitation for studies where iron status is self-reported [25
]. Dietary restraint was also measured and accounted for, and participants were otherwise healthy, reducing confounding from medical conditions which compromise iron status. The FFQ used in the current study was specifically validated for use within the study population and for measuring iron intake [28
]. HI and NHI content was calculated for each individual food item which allowed for both forms of iron to be analysed concurrently, enabling comparisons to be made about their respective and combined associations, analysis which has been identified as important in the future [25
A limitation of the study was the use of an FFQ which is prone to both over and under-reporting of total energy intake [58
]. The FFQ does not include information about the timing of food consumption and combinations of foods. This would have been useful to analyse the possible inhibitors and enhancers of iron absorption and their effect on iron status. Although the calculation of BMR was adjusted for current reported physical activity levels, the calculation was not adjusted for other factors that may affect energy metabolism, such as fat-free mass, cardiorespiratory fitness, or ethnicity. Furthermore, while CRP was used with α1GP to correct ferritin levels for inflammation [23
], as CRP is an acute phase reactant, the measurement of hsCRP would have strengthened the ability of this study to assess the true level of inflammation in individuals with chronic inflammation, such as in obesity. The need to calculate the HI and NHI content of foods was primarily due to a lack of recent Australia specific food data including HI and NHI [10
]. This was a limitation of the study as it resulted in reliance on data from 1997 [8
] which fails to account for recent agricultural developments or changes to practices which may alter HI content of meats [36