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This telephone-based survey included adults of Hispanic/Latino background residing in New Hampshire (NH). Information on food security and access, food environment, and health status and behaviors was collected through validated questionnaires. This project addresses the need for assessment of barriers to nutrition and health during COVID-19 in this population.
This telephone-based survey included a convenience sample of Hispanic/Latino adults (>18 years) with cultural origin in a Spanish-speaking country and residing in NH. A subgroup of the study population was assessed at baseline and 6-months following baseline. Validated questionnaires assessing the following outcomes were included:
Objective food access will be assessed through mapping and calculation of proximity of subjects' residential addresses to various food sources.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| NH Hispanic/Latino Adults | New Hampshire adults(at least 18 years of age) with cultural background in a Spanish-speaking Latin American country or territory surveyed between March 2021 - March 2022. |
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| Measure | Description | Time Frame |
|---|---|---|
| The correlation between weight status and indicators of physical and psychological wellbeing during the COVID-19 pandemic. | Physical activity will be assessed with the Global Physical Activity Questionnaire (GPAQ - possible scores for physical activity level at work, recreation, or transport: sedentary, moderate, or vigorous). Eating behavior will be examined with the Pennington Biomedical Research Center (PBRC) Impacts of COVID-19 on Dietary Intake survey. Results from linear regression analysis will reveal the relationship between weight status (BMI) and lifestyle (physical activity, eating behavior) and psychological characteristics during the COVID-19 pandemic. Linear regression models will be adjusted for age, gender, month of survey completion, and other demographic characteristics as needed. | March 2021 - September 2021 |
| Correlation between food insecurity, psychosocial factors, and weight status. | Severity of depressive, anxiety, and stress symptoms will be assessed with the 21-item Depression, Anxiety, Stress Scale (DASS-21 - possible scores for symptoms: normal, mild, moderate, severe, extremely severe). The USDA Household Food Sufficiency Questionnaire will be used to calculate food insecurity scores at both the household and the individual level (possible food security levels: high, marginal, low, and very low). The PBRC Impacts of COVID-19 on Sleep survey will assess sleeping behavior. Analysis will generate information on how food insecurity during the pandemic is associated with psychological wellbeing (stress, anxiety, depression), sleeping patterns, degree of acculturation, and weight status. Linear regression models will be used to ascertain the correlation between lifestyle and psychosocial factors with weight status. Models will be adjusted for age, gender, month of survey completion, and other demographic characteristics as appropriate. | March 2021 - September 2021 |
| Role of lifestyle and psychosocial factors in dietary fiber intake. | Intake of fiber-rich foods during the month prior to the data collection date will be assessed using the National Health and Nutrition Examination Survey (NHANES) Dietary Screener. The correlation between fiber intake, food access and insecurity, weight status, and gastrointestinal symptoms will be examined using linear regression models adjusted for age, gender, month of survey completion, and other demographic characteristics as appropriate. |
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Inclusion Criteria:
Exclusion Criteria:
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This study included a convenience sample in which participants were primarily recruited by past participants (without prompting by study staff). Unique participants (excluding participants who completed both surveys, N=139) were mostly female (81.3%). Of those who reported age (N=138), as well as weight and height information (N=132), the average age was 45.6 years (SD=14.9) and the average BMI was overweight (M=28.6, SD=5.2).
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| Name | Affiliation | Role |
|---|---|---|
| Maria C Dao, PhD | University of New Hampshire | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Dao Research Lab, University of New Hampshire | Durham | New Hampshire | 03824 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 29549476 | Background | Kamdar N, Rozmus CL, Grimes DE, Meininger JC. Ethnic/Racial Comparisons in Strategies Parents Use to Cope with Food Insecurity: A Systematic Review of Published Research. J Immigr Minor Health. 2019 Feb;21(1):175-188. doi: 10.1007/s10903-018-0720-y. | |
| 30732673 | Background | Mousa TY, Freeland-Graves JH. Food security of food recipients of a food pantry and soup kitchen. Public Health Nutr. 2019 Jun;22(8):1451-1460. doi: 10.1017/S1368980018003658. Epub 2019 Feb 8. |
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| ID | Term |
|---|---|
| D009765 | Obesity |
| D050177 | Overweight |
| D000086382 | COVID-19 |
| ID | Term |
|---|---|
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
| D001835 | Body Weight |
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| March 2021 - September 2021 |
| Updated New Hampshire (NH) food access database and characterization of barriers to healthy nutrition in NH Hispanics. | Perceived (Perceived Nutrition Environment Survey or NEMS-P) and objective food access (food sources) will be compared to characterize personal and geographical barriers to food access. NH food sources will be aggregated and geo-located using publicly available data from the State of NH (e.g., the USDA Economic Research Service (ERS) Food Access and Food Environment Research Atlases). ArcGIS software will be used to calculate measures of food access and to map sources in conjunction with participants' addresses to inspect for high-level spatial patterning in proximity gaps. For each participant, a count of the food sources can be tallied and constrained to a specified, geographically-dependent radius (e.g., within 1 mile of urban residents, 10 miles of rural residents), used for calculating a binary measure of access (e.g., access within zip code, yes/no), or used for measures of access for exploratory research. | October 2021 - March 2022 |
| Assessment of the physical and psychosocial burden of food insecurity. | A questionnaire assessing health history and sociodemographic characteristics will be administered as well as the Short Acculturation Scale for Hispanics (language acculturation score range=1-6, high=more acculturation). Other health-related constructs include psychological symptoms, sleep patterns, gastrointestinal symptoms, and food insecurity (possible food security levels: high, marginal, low, and very low). Changes in these constructs from baseline to follow-up will be assessed with a dependent t-test for paired samples, and their association with food insecurity through repeated measures ANOVA including only repeat subjects. The cross-sectional correlation between food insecurity and health behavior will be determined through bivariate linear regression models and chi square analyses. Covariate adjustment will include age and sex, and other relevant sociodemographic characteristics. | March 2021 - March 2022 |
| Characterization of the impact of the COVID-19 pandemic on health behaviors and their correlation with food insecurity and weight status. | Food insecurity will be assessed with the USDA Food Sufficiency Questionnaire (possible food security levels: high, marginal, low, and very low). Weighing behaviors will be evaluated with the Early Adult Reduction of weight through Lifestyle intervention (EARLY) Self-Weighing Questionnaire and a modified version of NHANES Weight History Questionnaire. Vaccine receipt will be assessed with questions from the Census Bureau's Household Pulse Survey. COVID-19 vaccination rate will be calculated, and attitudes to vaccination will be analyzed qualitatively through deductive coding. The predictive power of health behaviors on food insecurity and weight status will be assessed by logistic regression. Covariate adjustment will include age and sex. | October 2021 - March 2022 |
| 10064320 | Background | Carlson SJ, Andrews MS, Bickel GW. Measuring food insecurity and hunger in the United States: development of a national benchmark measure and prevalence estimates. J Nutr. 1999 Feb;129(2S Suppl):510S-516S. doi: 10.1093/jn/129.2.510S. |
| 28739148 | Background | Hernandez DC, Reesor LM, Murillo R. Food insecurity and adult overweight/obesity: Gender and race/ethnic disparities. Appetite. 2017 Oct 1;117:373-378. doi: 10.1016/j.appet.2017.07.010. Epub 2017 Jul 22. |
| 27568273 | Background | Alarcon RD, Parekh A, Wainberg ML, Duarte CS, Araya R, Oquendo MA. Hispanic immigrants in the USA: social and mental health perspectives. Lancet Psychiatry. 2016 Sep;3(9):860-70. doi: 10.1016/S2215-0366(16)30101-8. |
| 29267260 | Background | Ogden CL, Fakhouri TH, Carroll MD, Hales CM, Fryar CD, Li X, Freedman DS. Prevalence of Obesity Among Adults, by Household Income and Education - United States, 2011-2014. MMWR Morb Mortal Wkly Rep. 2017 Dec 22;66(50):1369-1373. doi: 10.15585/mmwr.mm6650a1. |
| 28820783 | Background | Forrest KYZ, Leeds MJ, Ufelle AC. Epidemiology of Obesity in the Hispanic Adult Population in the United States. Fam Community Health. 2017 Oct/Dec;40(4):291-297. doi: 10.1097/FCH.0000000000000160. |
| D012816 |
| Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
| D014777 | Virus Diseases |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |