IV.3 VARIABLES DEL ESTUDIO

The EXPLORE study Māori (9761 KJ) and Pacific women (11484 KJ) reported a higher average EI than those in the NZANS and DHHS (Table 5.2) (MOH, 2012a). This may partly be due to the analysis of butter, margarine, oils and fats (BMOF), which have the highest energy density (fats) of all the macronutrients. EXPLORE’s FFQ enquired the type, amount and frequency of BMOF (Appendix 1). In comparison, the NZANS coupled BMOF with the foods to which they were added, rather than in a separate ‘BMOF’ group (MOH, 2011a). This may have under- estimated the amount of BMOF consumed by participants in the NZANS. The EXPLORE FFQ also utilised cross-checking, through different questions on SSE of BMOF, in separate sections of the FFQ. For instance, the number of SSE used per dish and per week in food preparation/ cooking, and the frequency of using dressings and sauces, including BMOF. Therefore, cross- checking questions are a useful way to validate answers (Gibson, 2005) and helped to minimise the chance of under-reporting EI in this study.

Table 5.2 compares daily EI from Māori and/ or Pacific women in the women’s EXPLORE study, NZANS (2008/09) and DHHS (2008).

Table 5.2 Energy intake among Māori and Pacific women in comparable New Zealand studies

Daily energy intake EXPLORE, 2015/16 NZANS, 2008/09 DHHS, 2008 Māori (n=79) Pacific (n=75) Māori (n=588) Pacific (n=343) Māori (n=562) Pacific (n=508) Energy Intake (KJ) 9761 11484 7632 7970 9600 10300

BMI = Body mass index; EXPLORE = Examining the Predictors Linking Obesity Related Elements; NZANS = New Zealand Adult Nutrition Survey; NZHS = New Zealand Health Survey

General under-reporting could have contributed towards disparity in EI between the current study and NZANS. Gemming et al. (2014) found that under-reporting was highest in Māori (31.8%) and Pacific (34.3%) women from the NZANS, especially if they were overweight or obese. These findings were consistent in multiple studies (Black, 2000a; Gnardellis, Boulou, & Trichopoulou, 1998; Houston, 2014; Livingstone & Black, 2003; Rush et al., 2004; Subar et al., 2003) because it is likely that obese people are more ambivalent of dietary (energy) intake (Vandenbroeck et al., 2007). Furthermore, social desirability bias can cause under-reporting of foods that are perceived to be unhealthy, such as biscuits, fats, cakes and desserts. Social desirability bias encompasses the propensity of participants to provide what they believe would be the most socially acceptable answers but does not necessarily reflect their true eating behaviours (Fisher, 1993; Klesges, Baranowski, Beech, Cullen, Murray, Rochon, & Pratt, 2004; Nederhof, 1985).

There also may have been under-reporting of EI in the DHHS because participants did not specify whether they were trying to lose/ gain weight, or were free from chronic disease and illness, whereas participants in the current study did. These factors could have affected the usual relationship between EI and EE/ storage. For instance, if participants were trying to lose weight, they are likely to have a lower EI than the EER for their current body weight/ height. However, compared to NZANS participants, Māori (9600 KJ) and Pacific women (10300 KJ) from the DHHS had similar EI to those in the current study.

Similarity in EI between the current study and DHHS may partly be due to their method of dietary assessment, using a FFQ. The current study used a 220-item, self-administered, semi- quantitative FFQ, while the DHHS had a 142-item FFQ, which was validated and reproducible in Māori and Pacific participants (Metcalf et al., 2008). Cade, Thompson, Burley, & Warm (2002) reviewed the development, validation and utilisation of FFQs. They found FFQs over-estimated dietary intake under certain circumstances, such as when participants were presented with a long list of FAVs, with numerous food items, and with options for consuming the food item multiple times a day (Cade, Thompson, Burley, & Warm, 2002). More specifically, Metcalf et al. (1997) tested the reproducibility and validity of a FFQ in Polynesian NZers and found Pacific participants were more likely to over-estimate their total EI (Metcalf et al., 1997). Instead of a FFQ, the NZANS used multiple-pass 24-hour dietary recalls to overcome this. Although 24-hour dietary recalls have demonstrated more precision than FFQs, they are time-consuming and require skilled assessors (Livingstone & Black, 2003).

112 The EER of Māori and Pacific women (8800 KJ) in the current study was calculated from a formula based on women aged 31-50 years, with an average height of 1.6 metres, and a PAL of ~1.6 (Schofield, 1985; Black et al., 1996; German Nutrition Society, 2002; Trumbo et al., 2002; NHMRC, 2006). These variables took into account the age-range, height and probable PAL of most of the Māori and Pacific women in the current study. The percentage of Māori women who exceeded their 8800 KJ guideline was 58.2%, which is similar to the percentage (51.9%) of women found in the in the obese BF group (BF ≥35%). Similarly, 62.7% of Pacific women exceeded their EER (8800 KJ), which is identical to the percentage (62.7%) of women found in the obese BF group. This suggests a link between excess EI with excess BF percentage, which has been well documented in the literature (Peters, Wyatt, Donahoo, & Hill, 2002; Rodriguez et al., 2015; Vadiveloo et al., 2015).

Women in this study were less likely to be obese than those in the NZANS, even though they reported higher average EIs (↑ 27.9%-44.1%) (Table 5.2) (MOH, 2012a). Average EI may have been higher because of under-reporting found among Māori (31.8%) and Pacific (34.3%) women from the NZANS (Gemming et al., 2014). Similarly, Pacific BMI (31.9 kg/m2) was 11.6% lower than women in the DHHS (35.6 kg/m2), despite women in the current study having an 11.5% higher EI (Metcalf et al., 2008). However, it is expected for women in an older age bracket (35-74 years in the DHHS) to have a higher BMI than those in a younger age bracket (16-45 years in the current study), reaching a peak around 50-59 years (Villareal, Apovian, Kushner, & Klein, 2005).

Depending on their activity levels, EE could have made a huge difference to the estimation of energy requirements and relation to BF percentage. For instance, it was expected for

participants with a greater EE to have a greater EI (National Research Council, 1989), rather than an increase in body weight. However, more recent studies found that increases in EE did not necessarily increase hunger or EI (Blundell & King, 1998). Instead, EI would increase with EE when participants misjudged the rate at which they could expend energy or rewarded themselves with inappropriate foods, such as those which are energy-dense and nutrient-poor (Blundell & King, 1998). Despite all these findings on EI, the most up-to-date research

recommends avoiding use of self-reported EI as a true measure of EI (Subar et al., 2015). Instead, Subar et al. (2015) suggested using both short-term (e.g. food recalls) and long-term (e.g. FFQ) approaches to assessing dietary intake of study populations because it would help maximise the strengths of each method. Although this would take more time, the data would be more reliable.