Sociopolitical indicators of food insecurity: a study of 25 US states

粮食不安全状况的社会政治指标:一项针对美国25个州的研究

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Abstract

OBJECTIVE: Food insecurity (FI) prevalence has increased globally, including in the USA, and disproportionately affects certain subgroups (e.g. women). Both food-related and non-food-related sociopolitical indicators may impact FI rates; however, these associations are underexplored. This study assessed select state-level sociopolitical indicators among states with higher and lower FI rates compared to the national average. DESIGN: Cross-sectional. SETTING: US. PARTICIPANTS: We identified twenty-five states representing lower (n 18) and higher (n 7) FI prevalence compared to the 2021-2023 US average (12·2 %) and used national data sources to characterise sixteen sociopolitical indicators (selected via prior review) across three categories: (1) proximal to FI (related to food access/income/resources), (2) inequality (contributing to disparities) and (3) tobacco/alcohol/cannabis regulation (may exacerbate/perpetuate financial constraints). We described each indicator and explored their associations (using t tests or Fisher's tests) with state FI status (high v. low). RESULTS: For proximal indicators, low-FI (v. high-FI) states had greater food environment scores, nutrition assistance programme participation, minimum wage and insured individuals. For inequality indicators, low-FI (v. high-FI) states had narrower gender wage gaps, greater racial equity and more protective policies for sexual/gender minority populations and abortion rights. For substance-related indicators, low-FI (v. high-FI) states had higher cigarette taxes and were more likely to have comprehensive smoke-free laws, legalised non-medical cannabis and provisions for expunging/pardoning prior cannabis-related convictions. CONCLUSION: Low-FI states had more sociopolitical indicators aimed at improving food access, financial resources, equality and substance use-related regulations. Findings highlight the importance of adopting a holistic, sustainable, multilevel approach to effectively address the broader determinants of FI.

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