Are Supplemental Nutrition Assistance Program Restrictions on Sugar-Sweetened Beverages Effective in Reducing Purchase or Consumption? A Systematic Review.

The participants in the Supplemental Nutrition Assistance Program (SNAP) consume greater amounts of sugar and sweetened beverages (SSBs) compared to non-eligible individuals, which could result in potential negative health outcomes. This can be attributed to the lack of restrictions on SSB purchases with SNAP benefits. In view of the increasing calls from advocates and policymakers to restrict the purchase of SSBs with SNAP benefits, we performed a systematic review to assess its impact towards SSB purchases and consumption. We searched articles from five databases-Cochrane, EBSCO, SCOPUS, Web of Science, and PubMed-and selected seven studies, four of which were randomized controlled trials (RCTs) and three were simulation modeling studies. All three simulation studies and one RCT reported outcomes in terms of consumption, while the other three RCTs reported outcomes in terms of purchases. All seven studies found that an SSB restriction led to a decrease in SSB consumption or purchases, with six studies reporting significant results. Nonetheless, limitations exist. These include limited studies on this subject, potential workarounds circumventing SSB restrictions, like making purchases using personal cash, potentially differed estimated effects when combined with incentives or other initiatives, and the limited geographical scope among the selected RCTs.

Effectively communicating with local policymakers: a randomized trial of policy brief dissemination to address obesity.

Introduction: Evidence-based policies are a powerful tool for impacting health and addressing obesity. Effectively communicating evidence to policymakers is critical to ensure evidence is incorporated into policies. While all public health is local, limited knowledge exists regarding effective approaches for improving local policymakers' uptake of evidence-based policies. Methods: Local policymakers were randomized to view one of four versions of a policy brief (usual care, narrative, risk-framing, and narrative/risk-framing combination). They then answered a brief survey including questions about their impressions of the brief, their likelihood of using it, and how they determine legislative priorities. Results: Responses from 331 participants indicated that a majority rated local data (92%), constituent needs/opinions (92%), and cost-effectiveness data (89%) as important or very important in determining what issues they work on. The majority of respondents agreed or strongly agreed that briefs were understandable (87%), believable (77%), and held their attention (74%) with no brief version rated significantly higher than the others. Across the four types of briefs, 42% indicated they were likely to use the brief. Logistic regression models showed that those indicating that local data were important in determining what they work on were over seven times more likely to use the policy brief than those indicating that local data were less important in determining what they work on (aOR = 7.39, 95% CI = 1.86,52.57). Discussion: Among local policymakers in this study there was no dominant format or type of policy brief; all brief types were rated similarly highly. This highlights the importance of carefully crafting clear, succinct, credible, and understandable policy briefs, using different formats depending on communication objectives. Participants indicated a strong preference for receiving materials incorporating local data. To ensure maximum effect, every effort should be made to include data relevant to a policymaker's local area in policy communications.

Leveraging artificial intelligence to advance implementation science: potential opportunities and cautions.

BACKGROUND: The field of implementation science was developed to address the significant time delay between establishing an evidence-based practice and its widespread use. Although implementation science has contributed much toward bridging this gap, the evidence-to-practice chasm remains a challenge. There are some key aspects of implementation science in which advances are needed, including speed and assessing causality and mechanisms. The increasing availability of artificial intelligence applications offers opportunities to help address specific issues faced by the field of implementation science and expand its methods. MAIN TEXT: This paper discusses the many ways artificial intelligence can address key challenges in applying implementation science methods while also considering potential pitfalls to the use of artificial intelligence. We answer the questions of "why" the field of implementation science should consider artificial intelligence, for "what" (the purpose and methods), and the "what" (consequences and challenges). We describe specific ways artificial intelligence can address implementation science challenges related to (1) speed, (2) sustainability, (3) equity, (4) generalizability, (5) assessing context and context-outcome relationships, and (6) assessing causality and mechanisms. Examples are provided from global health systems, public health, and precision health that illustrate both potential advantages and hazards of integrating artificial intelligence applications into implementation science methods. We conclude by providing recommendations and resources for implementation researchers and practitioners to leverage artificial intelligence in their work responsibly. CONCLUSIONS: Artificial intelligence holds promise to advance implementation science methods ("why") and accelerate its goals of closing the evidence-to-practice gap ("purpose"). However, evaluation of artificial intelligence's potential unintended consequences must be considered and proactively monitored. Given the technical nature of artificial intelligence applications as well as their potential impact on the field, transdisciplinary collaboration is needed and may suggest the need for a subset of implementation scientists cross-trained in both fields to ensure artificial intelligence is used optimally and ethically.

Impact of soda tax on beverage price, sale, purchase, and consumption in the US: a systematic review and meta-analysis of natural experiments.

Background: As a primary source of added sugars in the US diet, sugar-sweetened beverage (SSB) consumption is presumed to contribute to obesity prevalence and poor oral health. We systematically synthesized and quantified evidence from US-based natural experiments concerning the impact of SSB taxes on beverage prices, sales, purchases, and consumption. Methods: A keyword and reference search was performed in PubMed, Web of Science, Cochrane Library, Scopus, and EconLit from the inception of an electronic bibliographic database to Oct 31, 2022. Meta-analysis was conducted to estimate the pooled effect of soda taxes on SSB consumption, prices, passthrough rate, and purchases. Results: Twenty-six natural experiments, all adopting a difference-in-differences approach, were included. Studies assessed soda taxes in Berkeley, Oakland, and San Francisco in California, Philadelphia in Pennsylvania, Boulder in Colorado, Seattle in Washington, and Cook County in Illinois. Tax rates ranged from 1 to 2 ¢/oz. The imposition of the soda tax was associated with a 1.06 ¢/oz. (95% confidence interval [CI] = 0.90, 1.22) increase in SSB prices and a 27.3% (95% CI = 19.3, 35.4%) decrease in SSB purchases. The soda tax passthrough rate was 79.7% (95% CI = 65.8, 93.6%). A 1 ¢/oz. increase in soda tax rate was associated with increased prices of SSBs by 0.84 ¢/oz (95% CI = 0.33, 1.35). Conclusion: Soda taxes could be effective policy leverage to nudge people toward purchasing and consuming fewer SSBs. Future research should examine evidence-based classifications of SSBs, targeted use of revenues generated by taxes to reduce health and income disparities, and the feasibility of redesigning the soda tax to improve efficiency.

Assessing the longitudinal relationship between whole egg consumption and cognition in Chinese older adults.

BACKGROUND: Given China's fast-growing aging population, cognitive decline is a leading public health concern. Eggs are an affordable food rich in several shortfall nutrients that may benefit cognitive health. AIM: This study assessed the longitudinal relationship between whole egg consumption and cognition among older adults in China. METHODS: Individual-level data of 4737 Chinese adults 55+ years came from the China Health and Nutrition Survey (CHNS) 1997-2006 waves. Daily egg consumption was measured using 3-day 24-h dietary recalls. Cognitive functioning was assessed with immediate and delayed recall of a 10-word list, counting backward from 20, and serial 7 subtraction. Multivariate mixed-effects regressions were performed to estimate the longitudinal associations between daily whole egg consumption and cognitive functioning in older Chinese adults. RESULTS: Approximately 46% of CHNS participants were whole egg consumers, and their daily intake averaged 47.4 g. The overall cognitive functioning test scores, separate scores for cognitive functioning subdomains, and the prevalence of cognitive impairment at the baseline were modestly higher among whole egg consumers than nonconsumers. However, after adjusting for individual characteristics, multivariate mixed-effects regressions did not find daily whole egg consumption to be associated with cognitive functioning among CHNS participants. By contrast, several demographic and socioeconomic factors, such as age, education attainment, and health insurance coverage, were found to correlate with older Chinese adults' cognition. CONCLUSION: This study has measurement and design limitations. Future research should investigate the causal impact of habitual egg intake on different domains of cognition using experimental designs with an extended follow-up period.

Sentiment Analysis of Tweets on Soda Taxes.

CONTEXT: As a primary source of added sugars, sugar-sweetened beverage (SSB) consumption may contribute to the obesity epidemic. A soda tax is an excise tax charged on selling SSBs to reduce consumption. Currently, 8 cities/counties in the United States have imposed soda taxes. OBJECTIVE: This study assessed people's sentiments toward soda taxes in the United States based on social media posts on Twitter. DESIGN: We designed a search algorithm to systematically identify and collect soda tax-related tweets posted on Twitter. We built deep neural network models to classify tweets by sentiments. SETTING: Computer modeling. PARTICIPANTS: Approximately 370 000 soda tax-related tweets posted on Twitter from January 1, 2015, to April 16, 2022. MAIN OUTCOME MEASURE: Sentiment associated with a tweet. RESULTS: Public attention paid to soda taxes, indicated by the number of tweets posted annually, peaked in 2016, but has declined considerably ever since. The decreasing prevalence of tweets quoting soda tax-related news without revealing sentiments coincided with the rapid increase in tweets expressing a neutral sentiment toward soda taxes. The prevalence of tweets expressing a negative sentiment rose steadily from 2015 to 2019 and then slightly leveled off, whereas that of tweets expressing a positive sentiment remained unchanged. Excluding news-quoting tweets, tweets with neutral, negative, and positive sentiments occupied roughly 56%, 29%, and 15%, respectively, during 2015-2022. The authors' total number of tweets posted, followers, and retweets predicted tweet sentiment. The finalized neural network model achieved an accuracy of 88% and an F1 score of 0.87 in predicting tweet sentiments in the test set. CONCLUSIONS: Despite its potential to shape public opinion and catalyze social changes, social media remains an underutilized source of information to inform government decision making. Social media sentiment analysis may inform the design, implementation, and modification of soda tax policies to gain social support while minimizing confusion and misinterpretation.

Using Mobile Phone Data to Assess Socio-Economic Disparities in Unhealthy Food Reliance during the COVID-19 Pandemic.

Background: Although COVID-19 has disproportionately affected socio-economically vulnerable populations, research on its impact on socio-economic disparities in unhealthy food reliance remains scarce. Methods: This study uses mobile phone data to evaluate the impact of COVID-19 on socio-economic disparities in reliance on convenience stores and fast food. Reliance is defined in terms of the proportion of visits to convenience stores out of the total visits to both convenience and grocery stores, and the proportion of visits to fast food restaurants out of the total visits to both fast food and full-service restaurants. Visits to each type of food outlet at the county level were traced and aggregated using mobile phone data before being analyzed with socio-economic demographics and COVID-19 incidence data. Results: Our findings suggest that a new COVID-19 case per 1,000 population decreased a county's odds of relying on convenience stores by 3.41% and increased its odds of fast food reliance by 0.72%. As a county's COVID-19 incidence rate rises by an additional case per 1,000 population, the odds of relying on convenience stores increased by 0.01%, 0.02%, and 0.06% for each additional percentage of Hispanics, college-educated residents, and every additional year in median age, respectively. For fast food reliance, as a county's COVID-19 incidence rate increases by one case per 1,000 population, the odds decreased by 0.003% for every additional percentage of Hispanics but increased by 0.02% for every additional year in the county's median age. Conclusion: These results complement existing literature to promote equitable food environments.

The Impact of Sugar-Sweetened Beverage Taxes by Household Income: A Multi-City Comparison of Nielsen Purchasing Data.

Due to the role that sugar-sweetened beverages (SSBs) play in the obesity epidemic, SSB taxes have been enacted in the United States in the California cities of Albany, Berkeley, Oakland, and San Francisco, as well as in Boulder, Philadelphia, and Seattle. We pooled five years of Nielsen Consumer Panel and Retail Scanner Data (2014-18) to examine purchasing behaviors in and around these cities that have instituted SSB taxes. We included households that were either subject to the tax during the study period or were in surrounding areas within the same state. The goal was to test for the differential impact of SSB taxes by income level and type of tax. Multivariate analyses of beverage purchases found that (1) there is a dose-response relationship with the size of the SSB tax; (2) the Philadelphia tax, which is the only one that includes low-calorie beverages, is associated with greater reductions in SSB purchases and an increase in bottled water purchase; and (3) approximately 72% of the tax is passed through to consumers, but this does not vary by income level of the household. Few income-related effects were detected. Overall, our findings suggest that the Philadelphia model may be the most effective at encouraging healthy habits in beverage choice.

Projecting the Influence of Sugar-Sweetened Beverage Warning Labels and Restaurant Menu Labeling Regulations on Energy Intake, Weight Status, and Health Care Expenditures in US Adults: A Microsimulation.

BACKGROUND: Accurate, readily accessible, and easy-to-understand nutrition labeling is a promising policy strategy to address poor diet quality and prevent obesity. OBJECTIVE: This study projected the influence of nationwide implementation of sugar-sweetened beverage (SSB) warning labels and restaurant menu labeling regulations. DESIGN: A stochastic microsimulation model was built to estimate the influences of SSB warning labels and menu labeling regulations on daily energy intake, body weight, body mass index, and health care expenditures among US adults. PARTICIPANTS/SETTING: The model used individual-level data from the National Health and Nutrition Examination Survey, Medical Expenditure Panel Survey, and other validated sources. STATISTICAL ANALYSES PERFORMED: The model was simulated using the bootstrapped samples, and the means and associated 95% CIs of the policy effects were estimated. RESULTS: SSB warning labels and restaurant menu labeling regulations were estimated to reduce daily energy intake by 19.13 kcal (95% CI 18.83 to 19.43 kcal) and 33.09 kcal (95% CI 32.39 to 33.80 kcal), body weight by 0.92 kg (95% CI 0.90 to 0.93 kg) and 1.57 kg (95% CI 1.54 to 1.60 kg), body mass index by 0.32 (95% CI 0.31 to 0.33) and 0.55 (95% CI =0.54 to 0.56), and per-capita health care expenditures by $26.97 (95% CI $26.56 to $27.38) and $45.47 (95% CI $44.54 to $46.40) over 10 years, respectively. The reduced per-capita health care expenditures translated into an annual total medical cost saving of $0.69 billion for SSB warning labels and $1.16 billion for menu labeling regulations. No discernable policy effect on all-cause mortality was identified. The policy effects could be heterogeneous across population subgroups, with larger effects in men, non-Hispanic Black adults, and younger adults. CONCLUSIONS: SSB warning labels and menu labeling regulations could be effective policy leverage to prevent weight gains and reduce medical expenses attributable to adiposity.

A scoping review on economic globalization in relation to the obesity epidemic.

This study reviewed evidence linking economic globalization to the obesity epidemic. Keyword/reference search was performed in PubMed, Web of Science, Cochrane Library, Scopus, EconLit, Google Scholar, and BMC Globalization and Health. A total of 16 studies were identified, in which six adopted a cross-sectional study design, nine adopted a longitudinal study design, and the remaining one adopted a case-control study design. Thirteen studies assessed the relationship between economic globalization and obesity at the country level, whereas the remaining three analyzed individual-level data. Fourteen studies found at least one aspect and/or measure of economic globalization to be positively associated with overweight/obesity, one found an inverse association, and the remaining one reported a null finding. Through market deregulation, tariff reduction, and investment liberalization, economic globalization tends to accelerate the market entry of modern food manufacturers, supermarket chains, and fast-food restaurants, resulting in substantially increased supply of high-sugar/fat energy-dense foods with enhanced variety and accessibility and reduced price. The potential impact of economic globalization on obesity through the adoption of modern workplace and domestic technologies and motorized transportation and through changes in social norms and culture were hypothesized in the literature but not empirically examined, which warrants future data-driven research.

Trade openness and the obesity epidemic: a cross-national study of 175 countries during 1975-2016.

PURPOSE: This study assessed the longitudinal relationship between trade openness and obesity rate across 175 countries during 1975-2016. METHODS: Two-way (country and year) fixed-effects regressions were performed to examine the openness index (i.e., sum of export and import over gross domestic product) in relation to country obesity rate, using data from World Health Organization and World Bank. RESULTS: The openness index was found to be positively associated with country obesity prevalence-a 10% increase in the openness index was associated with an increase in obesity rate by 0.80% (95% confidence interval, 0.67%-0.94%). Across continents, the positive relationship between the openness index and obesity prevalence was strongest among Asian countries, followed by countries in North America and Africa. Across income levels, the positive relationship between the openness index and obesity prevalence was strongest among lower middle-income countries, followed by upper middle-income countries and low-income countries. In contrast, no relationship between the two was identified among high-income countries. CONCLUSIONS: Trade openness was positively associated with country obesity prevalence, and its influence concentrated among developing nations. Policy makers should closely monitor the evolution in obesity rate during trade liberalization and nutrition transition to minimize its negative impact on weight-related population health.

Use of Survival Analysis to Predict Attrition Among Women Participating in Longitudinal Community-Based Nutrition Research.

OBJECTIVE: To identify participant characteristics and study methodology that influenced the completion of a 15-month community-based longitudinal study evaluating the impact of the Supplemental Nutrition Assistance Program Education and Expanded Food and Nutrition Education Program. DESIGN: Observational longitudinal 15-month study across 12 data collection timepoints. Sociodemographic characteristics were collected with a paper-based survey at baseline. SETTING: Five counties across central and southern Illinois. PARTICIPANTS: Women, aged 18 to 65 years (n = 297), recruited at sites likely to serve families eligible for the Supplemental Nutrition Assistance Program Education and Expanded Food and Nutrition Education Program (housing departments, child care centers, etc). MAIN OUTCOME MEASURES: Predictors of participant attrition during the study duration. ANALYSIS: Cox proportional hazard models. RESULTS: Ninety-seven participants were retained across the full study. In unadjusted models, greater income and education levels were significantly related to lower attrition; however, this relationship did not persist in a multivariate model. When adjusted for other characteristics, larger household size was the only measured variable significantly related to greater odds of attrition (odds ratio = 1.09; 95% confidence interval = 1.02, 1.17). CONCLUSIONS AND IMPLICATIONS: Several characteristics predicting attrition in other settings were not significant in this study. Future attrition analyses that evaluate social support, transportation capacity, and type of phone in longitudinal nutrition education studies are warranted.

Impact of State Laws Governing Physical Education on Attendance Among US High School Students, 2003 to 2017.

PURPOSE: This study assessed the influence of state laws governing physical education (PE) on weekly PE class attendance among US high school students. DESIGN: Cross-sectional. SETTING: 2003 to 2017 US national Youth Risk Behavior Survey (YRBS). PARTICIPANTS: A total of 533 468 high school students. MEASURES: Data on state laws governing PE came from National Cancer Institute's Classification of Laws Associated with School Students (CLASS). Eight distinct state PE policies were scored, with higher scores denoting stronger laws. ANALYSIS: Individual-level YRBS data were merged with CLASS data based on students' residential state and survey year. State fixed-effect negative binomial regressions were performed, adjusting for individual-level characteristics and YRBS survey design. RESULTS: A 1-score increase in state laws governing PE class time, staffing for PE, joint use agreement for physical activity, assessment of health-related fitness, and PE curriculum was associated with an increase in weekly PE attendance by 0.30, 0.28, 0.22, 0.20, and 0.13 days (P < .001), respectively. In contrast, a 1-score increase in state laws governing moderate-to-vigorous-intensity physical activity time in PE, PE proficiency, and recess time was associated with a reduction in weekly PE attendance by 0.25, 0.15, and 0.09 days (P < .001), respectively. The effects of most state PE policies on PE class attendance were larger among girls than boys. CONCLUSION: State PE policies differentially impacted US high school students' PE class attendance, with larger effects on female students.

A systematic review of food pantry-based interventions in the USA.

OBJECTIVE: Food pantries play a critical role in combating food insecurity. The objective of the present work was to systematically review and synthesize scientific evidence regarding the effectiveness of food pantry-based interventions in the USA. DESIGN: Keyword/reference search was conducted in PubMed, Web of Science, Scopus, Cochrane Library and CINAHL for peer-reviewed articles published until May 2018 that met the following criteria. SETTING: food pantry and/or food bank in the USA; study design: randomized controlled trial (RCT) or pre-post study; outcomes: diet-related outcomes (e.g. nutrition knowledge, food choice, food security, diet quality); study subjects: food pantry/bank clients. RESULTS: Fourteen articles evaluating twelve distinct interventions identified from the keyword/reference search met the eligibility criteria and were included in the review. Five were RCT and the remaining seven were pre-post studies. All studies found that food pantry-based interventions were effective in improving participants' diet-related outcomes. In particular, the nutrition education interventions and the client-choice intervention enhanced participants' nutrition knowledge, cooking skills, food security status and fresh produce intake. The food display intervention helped pantry clients select healthier food items. The diabetes management intervention reduced participants' glycaemic level. CONCLUSIONS: Food pantry-based interventions were found to be effective in improving participants' diet-related outcomes. Interventions were modest in scale and usually short in follow-up duration. Future studies are warranted to address the challenges of conducting interventions in food pantries, such as shortage in personnel and resources, to ensure intervention sustainability and long-term effectiveness.

Recreational marijuana legalization and prescription opioids received by Medicaid enrollees.

OBJECTIVES: Medical marijuana use may substitute prescription opioid use, whereas nonmedical marijuana use may be a risk factor of prescription opioid misuse. This study examined the associations between recreational marijuana legalization and prescription opioids received by Medicaid enrollees. METHODS: State-level quarterly prescription drug utilization records for Medicaid enrollees during 2010-2017 were obtained from Medicaid State Drug Utilization Data. The primary outcome, opioid prescriptions received, was measured in three population-adjusted variables: number of opioid prescriptions, total doses of opioid prescriptions in morphine milligram equivalents, and related Medicaid spending, per quarter per 100 enrollees. Two difference-in-difference models were used to test the associations: eight states and DC that legalized recreational marijuana during the study period were first compared among themselves, then compared to six states with medical marijuana legalized before the study period. Schedule II and III opioids were analyzed separately. RESULTS: In models comparing eight states and DC, legalization was not associated with Schedule II opioid outcomes; having recreational marijuana legalization effective in 2015 was associated with reductions in number of prescriptions, total doses, and spending of Schedule III opioids by 32% (95% CI: (-49%, -15%), p = 0.003), 30% ((-55%, -4.4%), p = 0.027), and 31% ((-59%, -3.6%), p = 0.031), respectively. In models comparing eight states and DC to six states with medical marijuana legalization, recreational marijuana legalization was not associated with any opioid outcome. CONCLUSIONS: No evidence suggested that recreational marijuana legalization increased prescription opioids received by Medicaid enrollees. There was some evidence in some states for reduced Schedule III opioids following the legalization.

Trends in Life Expectancy and Its Association with Economic Factors in the Belt and Road Countries-Evidence from 2000⁻2014.

In 2013, China launched the Belt and Road (B&R) Initiative in an effort to promote trade and economic collaboration. This study examined the change in life expectancy (LE) among countries along B&R and studied the impact of economic development on LE. Data from 65 B&R countries from 2000 to 2014 were compiled and analyzed. Trend of LE was examined by sex and country. Linear quantile mixed model was used to study the associations between LE and economic factors. In 2014, the average LE in all B&R countries was 69.7 years for men and 73.7 years for women. Across countries in 2014, LE for men ranged from 58.6 years in Afghanistan to 80.2 years in Israel. LE for women ranged from 61.3 years in Afghanistan to 85.9 in Singapore. GDP per capita was positively associated with longevity across B&R countries. The unemployment rate was positively associated with LE only for countries in the top LE quantiles. GDP growth rate and Inflation were negatively associated with LE for the countries in the bottom LE quantiles for men, not for women. LE increased substantially among B&R countries during 2000⁻2014. The influence of macroeconomic factors on LE was related to the distribution of LE.

Nutrition Environment Food Pantry Assessment Tool (NEFPAT): Development and Evaluation.

OBJECTIVE: To develop and evaluate a nutrition environment assessment tool to assess the consumer nutrition environment and use of recommended practices in food pantries. METHODS: The Nutrition Environment Food Pantry Assessment Tool (NEFPAT) was developed based on a literature review and guidance from professionals working with food pantries. The tool was pilot-tested at 9 food pantries, an expert panel assessed content validity, and interrater reliability was evaluated by pairs in 3 pantries. After revisions, the NEFPAT was used in 27 pantries. RESULTS: Pilot tests indicated positive appraisal for the NEFPAT and recommendations were addressed. The NEFPAT's 6 objectives and the overall tool were rated as content valid by experts, with an average section rating of 3.85 ± 0.10. Intraclass correlation coefficients for interrater reliability were >0.90. CONCLUSIONS AND IMPLICATIONS: The NEFPAT is content valid with high interrater reliability. It provides baseline data that could be valuable for interventions within the nutrition environment of food pantries.

Depression and Unmet Needs for Assistance With Daily Activities Among Community-Dwelling Older Adults.

Background and Objectives: This study aims to investigate the impact of depressive symptoms on adverse consequences of unmet needs for assistance with daily activities among community-dwelling older adults. Research Design and Methods: Data came from round 1 to 5 of the National Health and Aging Trends Study. Study sample consisted of 3,400 Medicare beneficiaries needing assistance with activities of daily living (ADL), instrumental activities of daily living (IADL), or mobility for any two consecutive years between 2011 and 2015. Study outcome was the number of self-reported adverse consequences of unmet needs for assistance with daily activities (e.g., went without eating, wet or soiled clothes). Mixed-effects negative binomial regression was used to estimate the association of lagged depressive symptoms and covariates in period t-1 and the number of adverse consequences of unmet needs in period t. Results: The prevalence rates of adverse consequences of unmet needs were twice as high among older adults with elevated depressive symptoms as those without depression. After adjusting for covariates, prior wave depressive symptoms were associated with 1.24 times the rate of adverse consequences of unmet needs for assistance with ADL (Incidence Rate Ratio [IRR] = 1.24, 95% confidence interval [CI] = 1.09-1.41, p < .01) and IADL (IRR = 1.24, 95% CI = 1.06-1.44, p < .01), and 1.14 times the rate of adverse consequences of unmet needs for assistance with mobility (IRR = 1.14, 95% CI = 1.03-1.27, p < .05). Discussion and Implications: Caring for older adults with mental health and long-term care needs calls for an integrated social and health services system.

Obesity Prevalence and Voting Behaviors in the 2016 US Presidential Election.

Objective We assessed the relationship between county-level prevalence of adult obesity and voting behaviors in the 2016 US presidential election. Methods Spatial autoregressive regression was performed to examine county-level obesity rate in relation to the vote margin for the Republican Party presidential candidate, defined as the percentage difference in votes received by the Republican presidential candidate and those received by the Democratic presidential candidate, adjusting for county sociodemographics and state fixed effects. Results A quadratic association was found between county-level obesity rate and the vote margin for the Republican Party presidential candidate-the margin increased when obesity rate increased from 11.8% to 34.1%, but after reaching its peak of 36.1%, it started to decrease when obesity rate further increased to 47.9%. Conclusion Typically, health disparity has been considered as a political outcome, whereas its impact on political behavior is rarely examined. Our findings indicate obesity disparities may not only be influenced by political decisions but also affect political behavior. Future studies should elucidate the pathway linking obesity to voting behavior and track the long-term trend of this relationship.