Food purchase patterns: empirical identification and analysis of their association with diet quality, socio-economic factors, and attitudes

Sociodemographic and behavioural differences between frequent and non-frequent users of convenience food in Germany

Introduction

Convenience foods are a double-edged sword in that they provide quick and easy nutrition but may promote non-communicable diseases related to excess intakes of sugar, fat, and salt. To inform the German national reduction and innovation strategy for less sugar, fat, and salt in processed foods, the present study sought to analyse the consumption frequency of selected convenience foods and to determine sociodemographic and behavioural factors that characterise frequent users.

Methods

In a representative computer-assisted telephone interview survey in the adult German population (N = 3,997) conducted in 2018, consumption frequency of 21 convenience foods was assessed. To characterise frequent in contrast to non-frequent users, data on sociodemographics and behavioural aspects were compared. Statistical analyses comprised chi-square tests with Bonferroni correction as well as Spearman's rank correlation. Cramer's V was used to determine the strength of an association.

Results

Overall and among frequent users (7.7% of the sample) sweet convenience foods and savoury cooking aids were consumed most frequently. Around 75% of the participants indicated little-to-no consumption of 19 of the 21 convenience foods. Male gender (p < 0.001), younger age (p < 0.001), and not having a high level of education (p = 0.017) were identified as key characteristics of frequent users. Furthermore, frequent users were more likely than non-frequent users to live in a family household (p = 0.003) or without a partner (p < 0.001), and to work in shifts (p = 0.002). Additionally, they showed significantly lower cooking skills (p < 0.001).

Conclusion

Public health interventions to limit excess intakes of sugar, fat, and salt from convenience food in Germany should target people of male gender, younger age, and having a lower level of education. On the behavioural side, developing the skills to cook from scratch emerged as major point of focus. Simultaneously, reformulation of the food offer should continue in order to help transition to a more health-promoting food environment.

An Entropy-Based Approach to Measuring Diet Adherence

The aim of this study is to put forward an approach designed to calculate and sum up discrepancies between the actual food acquisition or intake and any standard or norm. Based on secondary analysis of cross-sectional data from the Mexican National Survey of Household Income and Expenditure, our proposed method to produce classes of entropy-based Diet Adherence Indices generates a Food Basket Adherence Index (FBAI) for Mexico City (2129 households). Findings suggest that it is possible to measure and decompose diet adherence using a cross entropy measure. Using food expenditure data and a normative food basket for Mexico City results, we show households' deviations from the suggested norm for different food groups. The average FBAI was 0.44, far above the minimum score of 0 which would indicate full adherence to the normative food basket. Our measure has a distribution wide enough to detect meaningful changes and distinguish between groups with known differences, providing important new insights on the linkages between home food environments and income distribution, and food insecurity and household distribution.

The healthful plant-based diet index as a tool for obesity prevention-The healthy lifestyle community program cohort 3 study

Background

World-wide the prevalence of obesity is high, and promoting a shift toward more healthful and more plant-based dietary patterns appears to be one promising strategy to address this issue. A dietary score to assess adherence to a healthy plant-based diet is the healthful plant-based diet index. While there is evidence from cohort studies that an increased healthful plant-based diet index is associated with improved risk markers, evidence from intervention studies is still lacking.

Methods

A lifestyle intervention was conducted with mostly middle-aged and elderly participants from the general population (n = 115). The intervention consisted of a 16-month lifestyle program focusing on a healthy plant-based diet, physical activity, stress management, and community support.

Results

After 10 weeks, significant improvements were seen in dietary quality, body weight, body mass index, waist circumference, total cholesterol, measured and calculated low-density lipoprotein (LDL) cholesterol, oxidized LDL particles, non-high-density lipoprotein cholesterol, remnant cholesterol, glucose, insulin, blood pressure, and pulse pressure. After 16 months, significant decreases were seen in body weight (-1.8 kg), body mass index (-0.6 kg/m2), and measured LDL cholesterol (-12 mg/dl). Increases in the healthful plant-based diet index were associated with risk marker improvements.

Conclusions

The recommendation of moving toward a plant-based diet appears acceptable and actionable and may improve body weight. The healthful plant-based diet index can be a useful parameter for intervention studies.

Socioeconomic inequalities in food purchasing practices and expenditure patterns: Results from a cross-sectional household survey in western Kenya

Introduction

Socioeconomic inequalities contribute to poor health. Inequitable access to diverse and healthy foods can be a risk factor for non-communicable diseases, especially in individuals of low socioeconomic status. We examined the extent of socioeconomic inequalities in food purchasing practices, expenditure, and consumption in a resource-poor setting in Kenya.

Methods

We conducted a secondary analysis of baseline cross-sectional data from a natural experimental study with a sample size of 512 individuals from 376 households in western Kenya. Data were collected on household food sources, expenditure and food consumption. Household socioeconomic status (SES) was assessed using the multiple correspondence analysis (MCA) model. Concentration indices (Ci) and multivariable linear regression models were used to establish socioeconomic inequalities.

Results

About half (47.9%) of individuals achieved a minimum level of dietary diversity with the majority coming from wealthier households. The two most consumed food groups were grains and roots (97.5%, n = 499) and dark green leafy vegetables (73.8%, n = 378), but these did not vary by SES. The consumption of dark green leafy vegetables was similar across wealth quantiles (Ci = 0.014, p = 0.314). Overall, the wealthier households spent significantly more money on food purchases with a median of USD 50 (IQR = 60) in a month compared to the poorest who spent a median of USD 40 (IQR = 40). Of all the sources of food, the highest amount was spent at open-air markets median of USD 20 (IQR = 30) and the expenditure did not vary significantly by SES (Ci = 0.4, p = 0.684). The higher the socioeconomic status the higher the total amount spent on food purchases. In multivariable regression analysis, household SES was a significant determinant of food expenditure [Adjusted coefficient = 6.09 (95%confidence interval CI = 2.19, 9.99)].

Conclusion

Wealthier households spent more money on food compared to the poorest households, especially on buying food at supermarkets. Individuals from the poorest households were dominant in eating grains and roots and less likely to consume a variety of food groups, including pulses, dairy, eggs and fruits, and vegetables. Individuals from the poorest households were also less likely to achieve adequate dietary diversity. Deliberate policies on diet and nutrition are required to address socioeconomic inequalities in food purchasing practices.

Food purchase behaviour in a Finnish population: patterns, carbon footprints and expenditures

OBJECTIVE

To identify food purchase patterns and to assess their carbon footprint and expenditure.

DESIGN

Cross-sectional.

SETTING

Purchase patterns were identified by factor analysis from the annual purchases of 3435 product groups. The associations between purchase patterns and the total purchases' carbon footprints (based on life-cycle assessment) and expenditure were analysed using linear regression and adjusted for nutritional energy content of the purchases.

PARTICIPANTS

Loyalty card holders (n 22 860) of the largest food retailer in Finland.

RESULTS

Eight patterns explained 55 % of the variation in food purchases. The Animal-based pattern made the greatest contribution to the annual carbon footprint, followed by the Easy-cooking, and Ready-to-eat patterns. High-energy, Traditional and Plant-based patterns made the smallest contribution to the carbon footprint of the purchases. Animal-based, Ready-to-eat, Plant-based and High-energy patterns made the greatest contribution, whereas the Traditional and Easy-cooking patterns made the smallest contribution to food expenditure. Carbon footprint per euros spent increased with stronger adherence to the Traditional, Animal-based and Easy-cooking patterns.

CONCLUSIONS

The Animal-based, Ready-to-eat and High-energy patterns were associated with relatively high expenditure on food, suggesting no economic barrier to a potential shift towards a plant-based diet for consumers adherent to those patterns. Strong adherence to the Traditional pattern resulted in a low energy-adjusted carbon footprint but high carbon footprint per euro. This suggests a preference for cheap nutritional energy rather than environment-conscious purchase behaviour. Whether a shift towards a plant-based pattern would be affordable for those with more traditional and cheaper purchase patterns requires more research.

Algorithm-based mapping of products in a branded Canadian food and beverage database to their equivalents in Health Canada's Canadian Nutrient File

Introduction

There is increasing recognition of the value of linking food sales databases to national food composition tables for population nutrition research.

Objectives

Expanding upon automated and manual database mapping approaches in the literature, our aim was to match 1,179 food products in the Canadian data subset of Euromonitor International's Passport Nutrition to their closest respective equivalents in Health Canada's Canadian Nutrient File (CNF).

Methods

Matching took place in two major steps. First, an algorithm based on thresholds of maximal nutrient difference (between Euromonitor and CNF foods) and fuzzy matching was executed to offer match options. If a nutritionally appropriate match was available among the algorithm suggestions, it was selected. When the suggested set contained no nutritionally sound matches, the Euromonitor product was instead manually matched to a CNF food or deemed unmatchable, with the unique addition of expert validation to maximize meticulousness in matching. Both steps were independently performed by at least two team members with dietetics expertise.

Results

Of 1,111 Euromonitor products run through the algorithm, an accurate CNF match was offered for 65% of them; missing or zero-calorie data precluded 68 products from being run in the algorithm. Products with 2 or more algorithm-suggested CNF matches had higher match accuracy than those with one (71 vs. 50%, respectively). Overall, inter-rater agreement (reliability) rates were robust for matches chosen among algorithm options (51%) and even higher regarding whether manual selection would be required (71%); among manually selected CNF matches, reliability was 33%. Ultimately, 1,152 (98%) Euromonitor products were matched to a CNF equivalent.

Conclusion

Our reported matching process successfully bridged a food sales database's products to their respective CNF matches for use in future nutritional epidemiological studies of branded foods sold in Canada. Our team's novel utilization of dietetics expertise aided in match validation at both steps, ensuring rigor and quality of resulting match selections.

Spatial Association of Food Sales in Supermarkets with the Mean BMI of Young Men: An Ecological Study

Supermarket food sales data might serve as a simple indicator of population-level dietary habits that influence the prevalence of excess weight in local environments. To test this possibility, we investigated how variation in store-level food sales composition across Switzerland is associated with the mean Body Mass Index (BMI) of young men (Swiss Army conscripts) living near the stores. We obtained data on annual food sales (2011) for 553 stores from the largest supermarket chain in Switzerland, identified foods commonly regarded as “healthy” or “unhealthy” based on nutrient content, and determined their contribution to each store’s total sales (Swiss francs). We found that the sales percentages of both “healthy” and “unhealthy” food types varied by 2- to 3-fold among stores. Their balance ranged from −15.3% to 18.0% of total sales; it was positively associated with area-based socioeconomic position (r = 0.63) and negatively associated with the mean BMI of young men in the area (r = −0.42). Thus, even though we compared supermarkets from a single chain, different shopping behaviors of customers caused stores in privileged areas to sell relatively more healthy food. Knowledge about such patterns could help in designing in-store interventions for healthier nutrition and monitoring their effects over time.

What are the potential preventive population-health effects of a tax on processed meat? A quantitative health impact assessment for Germany

The International Agency for Research on Cancer considers processed meat to be carcinogenic. Further, processed meat is associated with diabetes, ischemic heart disease (IHD) and all-cause mortality. We aimed to assess health gains of four processed meat taxation scenarios in comparison to the reference and a minimum-risk-exposure-scenario. To estimate the shift in processed meat intake following respective taxes, we calculated price elasticities for processed meat. DYNAMO-HIA was used to dynamically project policy-attributable differences in the prevalence of diseases and deaths. In projection year 10, an extra 9300 males and 4500 females would be alive under the lowest tax scenario (4% tax), compared to the reference scenario. Prevalent IHD, diabetes and colorectal cancer cases in males would be 8400, 9500 and 500 lower, respectively, and there would be 4600, 7800 and 300 less cases in females. Of the respective death and disease reduction that would be achieved under the minimum-risk-exposure-scenario, the lowest tax reaches 2.84% (colorectal cancer in males) to 6.02% (diabetes in females). Under the highest tax scenario (33.3% tax), an extra 76,700 males and 37,100 females would be alive, compared to the reference scenario. Prevalent IHD, diabetes and colorectal cancer cases would be 70,800, 77,900 and 4900 lower in males and 29,900, 48,900 and 2300 lower in females, which represents 27.84% (colorectal cancer in males) to 37.76% (diabetes in females) of the maximal preventable death and disease burden. Further research needs to examine to what extent these health benefits are outweighed by a simultaneous tax-induced decrease in fish intake.