Part 1:
1. Choose a paper describing the development or validation of a measure of relevance in health disparities research (please give the full citation and/or upload the paper if that's possible).
Toffano R, et al. Validation of the Brazilian Healthy Eating Index-Revised Using Biomarkers in Children and Adolescents. Nutrients 2018;10(2).
http://www.mdpi.com/2072-6643/10/2/154/htm
2. What was the definition of the construct?
There is not a definition of the construct on the paper, but in the objective, the authors say that "The purpose of this study was to assess the Brazilian Healthy Eating Index (BHEI-R) as a measure of dietary status in children." However I think that the BHEI doesn't measure the nutritional status of children; it measures the quality of diet, the patterns, and interaction between single foods; which could influence the nutritional status in children.
The advantage of using a dietary index rather than a single food item, is that helps to capture the complexity of the diet, food preparation, interaction of nutrients and eating patterns. Twelve components compose the index regarding to the diet consumption, (total grains, whole grains, total vegetable and legumes, total fruits, whole fruits, meat eggs and legumes, milk and dairy, oils, saturated fat, sodium, and SoFAAS). Each component is evaluated and scored from a minimum of 0 to a maximum of 20. The maximum BHEI-R score is 100. The diet is then, defined as "poor diet" as a total index score < 65, and a "good diet" as a total index-R score >85, with scores of 65-74 and 75-84 in between.
3. How did the authors provide evidence on the validity of the measure? Could you think of additional approaches to validating the measure?
The authors did Correlation tests, agreement, and covariance analyses to associate BHEI components with biomarkers. Total BHEI scores were positively associated with intakes of omega-6, omega-3, fiber and vitamin C, and inversely associated with energy and saturated, fat intakes of individuals
4. How did the authors provide evidence on the reliability of the measure? Could you think of additional approaches to evaluating the reliability of the measure?
It is important to note that the index is based on a 24 hours recall questionnaire and that the variability of diet changes day by day, so the authors did repeated measures of the 24 h recall. questionnaire but at a different time point (week 0, 6 and 12). Therefore, the differences of the repeated measures could be influenced for the time, and it is not necessarily a way to evaluate reliability. It would be ideal to have repeated measures of 24 h questionnaire in a non-consecutive day of the same week to account for the day to day variability, as well as to evaluate the reliability of the instrument.
5. Describe the implications of a lack of measurement validity or reliability for future research applications.
The lack of measurement validity and reliability could affect the association of the instrument with some health outcome. If there is a random error on the reliability, it would be likely that the association will toward to the null while having a not valid instrument, that could systematically overestimate or underestimate the diet quality, could bias the results on unpredictable directions.
Part 2:
1. Find a paper describing a health disparity (please give the full citation or, even better, upload the paper so everyone else can look at it too)
Abouzeid M1, Philpot B, Janus ED, Coates MJ, Dunbar JA. Type 2 diabetes prevalence varies by socioeconomic status within and between migrant groups: analysis and implications for Australia. BMC Public Health 2013, 13:252
https://bmcpublichealth.biomedcentral.com/articles/10.1186/1471-2458-13-252
2. Summarize the construct and measurement of the dimension of disparity (e.g., racial inequalities?, SES inequalities?) and the outcome measured (e.g., self-rated health).
The objective of the study was to compare the prevalence of diabetes among SES and ethnicity in Australia.
The socioeconomic status was estimated with a through a Residential area socioeconomic deprivation that was obtained from the ABS Socio-Economic Indexes for Areas, using the Index of Relative Socio-Economic Disadvantage (IRSD) postal area scores, that includes 17 census items (proportion of people with low incomes, low education and unemployed). ABS assigns IRSD scores to collection districts, standardized. These collection districts are then combined to yield postal area scores that approximate to postcodes used in this study. Low scores represent relatively high levels of disadvantage and vice versa. Postal areas were additionally ranked into SES quintiles, representing IRSD scores 765-960, 961-993, 994-1025, 1026-1058, and 1059-1142.
The outcome was diabetes, obtained from the National Diabetes Services Scheme. To evaluate the place of birth, they used the Standard Australian Classification of Countries to categorize in regions based on geographic proximity. To examine Australian-born people separately, they recategorized this group into 'Australia' and 'Oceania' (the latter also including Antarctica). Also, given socio-cultural and developmental similarities between Australia and New Zealand and differences between New Zealand and other Oceanic countries, they generated two additional region-of-birth ( 'New Zealand' and 'Pacific Islands,') as a distinct category separate from the Pacific Islands in Oceania. The final categories of the region of birth were: Oceania, North-Wes Europe, Southern and Eastern Europe, North Africa and Middle East, South-East Asia, North-East Asia, Southern and Central Asia, Americas, Sub-saharan Africa and Australia, and the two extra categories: Pacific Islands and New Zealand.
3. What is the evidence for the validity and reliability of the measures?
The authors mention that the National Diabetes database is a valid way to obtain the diabetes information, the mention that it is the best available data to estimate the prevalence of diagnosed diabetes. However, they didn't do any analysis to evaluate the validity of the information. Besides, they don't account undiagnosed diabetes, which it is estimated in some countries that could 50% of people with diabetes could not have a diagnosis. Therefore, they could be underestimating the prevalence of diabetes, and this error could be differential among SES and place of birth.
Regarding to the evaluation of SES, they didn't mention any assessment of the validity of the index they used.
4. What is the reference category used for the disparity measure (i.e., who is the comparison group)? Why does this reference category make sense (or not) for this research question?
The reference category was Australia. It makes sense, given that they want to compare disparities among immigrants, the "default" should be the non-immigrants.
5. How is the disparity quantified or measured? Is this an absolute or relative measure or are both provided? Describe which type of measure you would prefer for this research area, or, if both, why.
They provided both. In an absolute measure, authors presented the prevalence of diabetes among birthplace and SES quintile. In a relative measure, they showed OR of diabetes by region of birth adjusted for age and SES.
Both measures give great information of the disparities. However, given that there are many comparison groups, and all of them have the same referent group, in order to evaluate the must unprivileged groups, I think it is easier to identify with OR. In contrast, to know, how big is this difference I would rather prefer the absolute numbers