Policies and politics of the US food supply

Relationship between Food Insecurity and Nutritional Risk among Older Adults in Poland-A Preliminary Study

Aging populations may be associated with increased nutritional risk, malnutrition, and food insecurity. This study aims to examine the relationship between food insecurity and nutritional risk, taking into account selected characteristics of the study group, and factors describing nutritional risk. It was conducted between May and July 2021, among 417 people aged 60 and older, in two regions of Poland. Questions from the SCREEN-14 questionnaire were used to assess nutritional risk. Selected questions from the HFSS questionnaire (U.S. Household Food Security Survey Module) concerning the elderly were used to assess food insecurity. A K-means cluster analysis was used to separate homogeneous clusters into food security indicators and nutritional risk factors. The Mann-Whitney U test and Kruskal-Wallis test were used to compare mean values between groups, and the Chi-square test was used to verify the differences. Two clusters were distinguished: I-"low food security and high nutritional risk" and II-"high food security and low nutritional risk". Cluster I included people aged 60-65, and over 75, living in urban areas, living alone or with family, with unfavorable economic situations and family relationships. Cluster II was composed of people aged 71-75, who were rural residents, living with a partner, with favorable economic situations and family relations. The vast majority of nutritional risk factors were found in Cluster I and among those at high nutritional risk. The largest number of people were affected by such nutritional risk factors such as difficulty in chewing or biting, loss in appetite, skipping meals, and perceiving one's weight as abnormal. Moreover, the group of people most significantly affected by high nutritional risk were in unfavorable economic situations, had poor family relationships, lived alone or with family, rated their health as worse than their peers, were overweight and obese, had metabolic disease, or impeding mobility. The results obtained can be applied to the planning of social and health policies for the elderly in Poland.

Food, health, and complexity: towards a conceptual understanding to guide collaborative public health action

BACKGROUND

What we eat simultaneously impacts our exposure to pathogens, allergens, and contaminants, our nutritional status and body composition, our risks for and the progression of chronic diseases, and other outcomes. Furthermore, what we eat is influenced by a complex web of drivers, including culture, politics, economics, and our built and natural environments. To date, public health initiatives aimed at improving food-related population health outcomes have primarily been developed within 'practice silos', and the potential for complex interactions among such initiatives is not well understood. Therefore, our objective was to develop a conceptual model depicting how infectious foodborne illness, food insecurity, dietary contaminants, obesity, and food allergy can be linked via shared drivers, to illustrate potential complex interactions and support future collaboration across public health practice silos.

METHODS

We developed the conceptual model by first conducting a systematic literature search to identify review articles containing schematics that depicted relationships between drivers and the issues of interest. Next, we synthesized drivers into a common model using a modified thematic synthesis approach that combined an inductive thematic analysis and mapping to synthesize findings.

RESULTS

The literature search yielded 83 relevant references containing 101 schematics. The conceptual model contained 49 shared drivers and 227 interconnections. Each of the five issues was connected to all others. Obesity and food insecurity shared the most drivers (n = 28). Obesity shared several drivers with food allergy (n = 11), infectious foodborne illness (n = 7), and dietary contamination (n = 6). Food insecurity shared several drivers with infectious foodborne illness (n = 9) and dietary contamination (n = 9). Infectious foodborne illness shared drivers with dietary contamination (n = 8). Fewer drivers were shared between food allergy and: food insecurity (n = 4); infectious foodborne illness (n = 2); and dietary contamination (n = 1).

CONCLUSIONS

Our model explicates potential interrelationships between five population health issues for which public health interventions have historically been siloed, suggesting that interventions targeted towards these issues have the potential to interact and produce unexpected consequences. Public health practitioners working in infectious foodborne illness, food insecurity, dietary contaminants, obesity, and food allergy should actively consider how their seemingly targeted public health actions may produce unintended positive or negative population health impacts.