Although the importance of fruit and vegetable consumption to health has been well established, few studies have focused on access to fruits and vegetables in rural areas; even fewer examined the relationship between food access and fruit and vegetable consumption among seniors.
To examine the spatial challenges to good nutrition faced by seniors who reside in rural areas and how spatial access influences fruit and vegetable intake.
A cross-sectional analysis using data from the 2006 Brazos Valley Health Assessment (mailsurvey) for 582 rural seniors (60-90 years), who were recruited by random digit dialing; food store data from the 2006-2007 Brazos Valley Food Environment Project that used ground-truthed methods to identify, geocode, and inventory fruit and vegetables in all food stores.
Few of the BVHA seniors consumed the recommended intakes of fruits or vegetables; women consumed more servings of fruit (1.49 ± 0.05 vs. 1.29 ± 0.07,
Findings suggest that interventions designed to increase fruit and vegetable consumption among rural seniors should consider strategies to ameliorate differential access to healthy food due to food store distance.
The percentage of older adults with nutrition-related health conditions, such as obesity, diabetes, cardiovascular disease, and some cancers has been increasing [
Personal and environmental characteristics result in differential access to health resources and serve as either barriers or enhancements to healthy eating, especially in rural areas [
Physical access is a major problem for people without cars, the elderly, people on low incomes, and residents in rural areas [
We used data from the 2006 Brazos Valley Health Assessment (BVHA), the 2006-2007 Brazos Valley Food Environment Project (BVFEP), and the decennial 2000 U.S. Census Summary File 3 (SF-3) for a 6-county rural area (see Figure
Fruit and vegetable intakes were separately measured by a validated, self-reported two-item screener [
BVFEP data included the on-site identification and geocoding of all supercenters, supermarkets, grocery stores, convenience stores, dollar stores, mass merchandisers, and pharmacies; and completion of an observational survey by trained researchers of the availability and variety of fresh and processed (canned, frozen, and juice) fruits and vegetables in the 185 food stores that marketed some form of fruit or vegetable [
Socioeconomic characteristics were extracted from the SF-3 for all 101 CBG in the rural study area to describe socioeconomic deprivation and population density [
Network distance was calculated with ESRI's Network Analysis extension in ArcInfo 9.2, which computed the distance along the road network to the geographic position measured in front of each food store. Separate network distances were calculated from the residential address of each BVHA senior respondent to the nearest corresponding supermarket, and food store (regardless of type) with a good selection of fresh fruit, fresh and processed fruit, fresh vegetables, or fresh and processed vegetables. The network distance to the nearest food store was calculated between paired point data (respondent address and nearest corresponding food store within the study area).
Release 11 of Stata Statistical Software was used for all statistical analyses;
Sample characteristics between the analytic sample of 582 seniors who completed all nutrition-related questions in the BVHA and the 663 rural seniors who returned surveys were not significantly different (data not shown). The mean age for the 582 BVHA respondents was almost 70 years; 68% were women; almost 65% were married; and 27% lived alone (Table
Characteristics of Rural Seniors in 2006 Brazos Valley Health Assessment (n = 582)
| % ( | Mean ± SD | |
|---|---|---|
| Age, y | 69.92 ± 6.91 | |
| Women | 68.2 (397) | |
| Race/ethnicity | ||
| Minority | 14.4 (84) | |
| Household income | ||
| ≤ 100% FPL | 17.0 (99) | |
| 101-199% FPL | 16.3 (95) | |
| Education | ||
| Low (< High school) | 13.1 (76) | |
| Marital status | ||
| Married | 64.8 (377) | |
| Household composition | ||
| Lives alone | 27.7 (161) | |
| Deprivation, % ( | ||
| Low | 29.6 (172) | |
| Medium | 46.2 (269) | |
| High | 24.2 (141) | |
| Population density (persons/mi2) | ||
| Low (<14) | 27.0 (157) | |
| Medium (14-127) | 46.6 (271) | |
| High (>127) | 26.5 (154) | |
| Fruit | 1.43 ± 0.98 | |
| Vegetables | 2.15 ± 0.91 | |
| Combined fruit and vegetables | 3.58 ± 1.60 |
SD = standard deviation
The rural food environment consisted of 186 food stores, including one supercenter, 11 supermarkets, 12 grocery stores, 141 convenience stores, 16 dollar stores, four mass merchandisers, and one pharmacy [
Potential spatial access (in miles) from rural senior's residence to the nearest supermarket and good selection of fruit and vegetables (
| Mean (SD)a | Median | IQRb | ||
|---|---|---|---|---|
| Supermarket | 9.9 (9.2) | 8.7 | 1.06 - 14.46 | |
| Fresh | ||||
| Fruit | 6.1 (5.3) | 5.5 | 0.87 - 9.65 | |
| Vegetables | 6.7 (5.7) | 6.4 | 0.97- 10.47 | |
| Fresh and processedc | ||||
| Fruit | 4.4 (4.1) | 3.4 | 0.58 - 7.62 | |
| Vegetables | 4.2 (4.0) | 3.2 | 0.65 - 6.89 | |
a SD = standard deviation
bIQR = interquartile range (first to third quartiles)
cProcessed = canned, frozen, and 100% juice
Individual evaluations of community food resources, stores where most of the groceries are purchased, and household food resources are presented in Table
Perceptions of Rural Seniors on Adequacy of Community and Household Food Resources (
| % ( | |
|---|---|
| Little variety of foods that can be purchased | 32.0 (186) |
| Few grocery stores or supermarkets | 59.6 (347) |
| Food prices are high | 79.5 (463) |
| Variety of fruits and vegetables is fair/poor | 10.0 (58) |
| Freshness of fruits and vegetables is fair/poor | 13.1 (76) |
| Price of fruits and vegetables is fair/poor | 45.5 (265) |
| Food bought last month didn't last and we didn't have enough money to buy more | 13.9 (81) |
| In the last month, we couldn't afford to eat balanced meals | 13.1 (76) |
| In the past 12 months, we had to cut size of our meals or skip meals because there wasn't enough money to buy food | 8.3 (48) |
Bivariate correlations with fruit and vegetable intake indicated poverty status, population density, and neighborhood deprivation were not significantly correlated with individual or combined fruit and vegetable intake (lowest
Association of sample characteristics, community and household food resources, and network distance to food stores with fruit intake among 582 rural seniors, using multivariable linear regression models
| Model: Supermarket | Model 2: Fresh Fruit | Model 3: Fresh and Processed Fruit | ||||
|---|---|---|---|---|---|---|
| Live alone | -0.171 (0.087) | 0.050 | -0.158 (0.087) | 0.070 | -0.170 (0.087) | 0.051 |
| Female | 0.288 (0.084) | 0.001 | 0.301 (0.084) | 0.000 | 0.285 (0.084) | 0.001 |
| Age, y | 0.028 (0.006) | 0.000 | 0.028 (0.006) | 0.000 | 0.029 (0.006) | 0.000 |
| Food not last | -0.473 (0.108) | 0.000 | -0.464 (0.109) | 0.000 | -0.460 (0.108) | 0.000 |
| Few grocery stores | -0.073 (0.082) | 0.371 | -0.093 (0.081) | 0.253 | -0.098 (0.081) | 0.227 |
| Fruit/vegetable variety | -0.270 (0.112) | 0.016 | -0.281 (0.112) | 0.012 | -0.276 (0.110) | 0.012 |
| Supermarketb | -0.012 (0.004) | 0.003 | ||||
| Fresh fruitc | -0.013 (0.007) | 0.067 | ||||
| Fresh and processed fruitd | -0.027 (0.009) | 0.003 | ||||
| R2 | 0.111 | 0.105 | 0.112 | |||
| <0.0001 | <0.0001 | <0.0001 | ||||
a SE = White-corrected standard errors
b Network distance in miles from participant's residence to nearest supermarket
c Network distance in miles from participant's residence to nearest food store with a good selection of fresh fruit
d Network distance in miles from participant's residence to nearest food store with a good selection of fresh and processed (canned, frozen, and 100% juice) fruit
Association of sample characteristics, community and household food resources, and network distance to food stores with vegetable intake among 582 rural seniors, using multivariable linear regression models
| Model 1: Supermarket | Model 2: Fresh Vegetables | Model 3: Fresh and Processed Vegetables | ||||
|---|---|---|---|---|---|---|
| Live alone | -0.373 (0.086) | 0.000 | -0.362 (0.086) | 0.000 | -0.370 (0.086) | 0.000 |
| Female | 0.206 (0.082) | 0.013 | 0.217 (0.082) | 0.008 | 0.210 (0.082) | 0.011 |
| Age, y | 0.017 (0.005) | 0.003 | 0.016 (0.005) | 0.003 | 0.017 (0.005) | 0.002 |
| Food not last | -0.495 (0.112) | 0.000) | -0.486 (0.113) | 0.000 | -0.485 (0.113) | 0.000 |
| Few grocery stores | -0.226 (0.077) | 0.004 | -0.242 (0.077) | 0.002 | -0.240 (0.077) | 0.002 |
| Fruit/vegetable variety | 0.128 (0.119) | 0.281 | -0.134 (0.119) | 0.261 | 0.133 (0.119) | 0.262 |
| Supermarketb | -0.008 (0.004) | 0.033 | ||||
| Fresh vegetablesc | -0.007 (0.006) | 0.267 | ||||
| Fresh and processed vegetablesd | -0.015 (0.009) | 0.116 | ||||
| R2 | 0.125 | 0.119 | 0.121 | |||
| <0.0001 | <0.0001 | <0.0001 | ||||
a SE = White-corrected standard errors
b Network distance in miles from participant's residence to nearest supermarket
c Network distance in miles from participant's residence to nearest food store with a good selection of fresh vegetables
d Network distance in miles from participant's residence to nearest food store with a good selection of fresh and processed (canned, frozen, and 100% juice) vegetables
Association of sample characteristics, community and household food resources, and network distance to fruit with combined fruit and vegetable intake among 582 rural seniors, using multivariable linear regression models
| Model 1: Supermarket | Model 2: Fresh Fruit | Model 3: Fresh and Processed Fruit | ||||
|---|---|---|---|---|---|---|
| Live alone | -0.544 (0.150) | 0.000 | -0.517 (0.149) | 0.001 | -0.539 (0.149) | 0.000 |
| Female | 0.494 (0.138) | 0.000 | 0.521 (0.138) | 0.000 | 0.491 (0.138) | 0.000 |
| Age, y | 0.045 (0.009) | 0.000 | 0.045 (0.009) | 0.000 | 0.045 (0.009) | 0.000 |
| Food not last | -0.968 (0.182) | 0.000 | -0.947 (0.184) | 0.000 | -0.945 (0.182) | 0.000 |
| Few grocery stores | -0.299 (0.132) | 0.024 | -0.332 (0.132) | 0.012 | -0.341 (0.131) | 0.010 |
| Fruit/vegetable variety | -0.399 (0.197) | 0.043 | -0.412 (0.196) | 0.036 | -0.407 (0.193) | 0.036 |
| Supermarketb | -0.020 (0.006) | 0.002 | ||||
| Fresh fruitc | -0.017 (0.012) | 0.153 | ||||
| Fresh and processed fruitd | -0.043 (0.015) | 0.005 | ||||
| R2 | 0.152 | 0.142 | 0.151 | |||
| <0.0001 | <0.0001 | <0.0001 | ||||
a SE = White-corrected standard errors
b Network distance in miles from participant's residence to nearest supermarket
c Network distance in miles from participant's residence to nearest food store with a good selection of fresh fruit
d Network distance in miles from participant's residence to nearest food store with a good selection of fresh and processed (canned, frozen, and 100% juice) fruit
Association of sample characteristics, community and household food resources, and network distance to vegetables with combined fruit and vegetable intake among 582 rural seniors, using multivariable linear regression models
| Model 1: Supermarket | Model 2: Fresh Vegetables | Model 3: Fresh and Processed Vegetables | ||||
|---|---|---|---|---|---|---|
| Live alone | -0.544 (0.150) | 0.000 | -0.521 (0.149) | 0.000 | -0.549 (0.149) | 0.000 |
| Female | 0.494 (0.138) | 0.000 | 0.518 (0.138) | 0.000 | 0.494 (0.138) | 0.000 |
| Age, y | 0.045 (0.009) | 0.000 | 0.044 (0.009) | 0.000 | 0.043 (0.009) | 0.000 |
| Food not last | -0.968 (0.182) | 0.000 | -0.950 (0.184) | 0.000 | -0.947 (0.183) | 0.000 |
| Few grocery stores | -0.299 (0.132) | 0.024 | -0.340 (0.131) | 0.010 | -0.335 (0.132) | 0.011 |
| Fruit/vegetable variety | -0.399 (0.197) | 0.043 | -0.416 (0.197) | 0.035 | -0.415 (0.194) | 0.033 |
| Supermarketb | -0.020 (0.006) | 0.002 | ||||
| Fresh vegetablec | -0.021 (0.011) | 0.054 | ||||
| Fresh and processed vegetabled | -0.046 (0.016) | 0.004 | ||||
| R2 | 0.152 | 0.148 | 0.152 | |||
| <0.0001 | <0.0001 | <0.0001 | ||||
a SE = White-corrected standard errors
b Network distance in miles from participant's residence to nearest supermarket
c Network distance in miles from participant's residence to nearest food store with a good selection of fresh vegetables
d Network distance in miles from participant's residence to nearest food store with a good selection of fresh and processed (canned, frozen, and 100% juice) vegetables
Lower fruit intake (Table
Lower vegetable intake (Table
The importance of fruit and vegetable consumption to health has been well established [
Although the food environment experienced by rural seniors is different from the food environment experienced by seniors in high-population-density urban and suburban areas [
Several additional findings warrant further mention: 1) the distance to the nearest food store with a good selection of fruit or vegetables decreased when fruit or vegetables included canned, frozen, and 100% juice types in addition to fresh; 2) perception of fair or poor variety of fruit and vegetables in the store where most of the groceries were purchased was associated with decreased daily fruit intake (greater than one-quarter serving), but not vegetable intake; 3) perceptions there were few grocery stores or supermarkets in their community was associated with decreased intake of vegetables and not fruit; 4) neighborhood socioeconomic deprivation and population density were not associated with fruit and vegetable intake; 5) negative perceptions of community food resources were consistently associated with decreased intake of combined fruit and vegetables; and 6) the magnitude of association with decreased intake of fruit, vegetables, and combined fruit and vegetables was largest for limited household food resources; that is, food purchased in the past month not lasting and no money available to purchase more food. Generally, studies have shown that neighborhood access to a supermarket influences individual fruit and vegetable consumption [
This study linked two contemporaneous datasets (BVFEP and BVHA) with the 2000 U.S. Census. The BVFEP food store data in this study were originally collected using ground-truthed methods that involved direct observation of all food stores and food service places in all six rural counties, on-site collection of locational points using mobile Global Positioning System, and on-site collection of presence of fresh, canned, frozen, and 100% juice fruit and vegetables. The ground-truthed method provided more accurate information than utilization of publicly available food stores lists [
This study has several limitations. Daily consumption of fruit and vegetables was estimated through a self-reported, self-administered two-item survey, which is subject to measurement error. Unlike the Brooklyn study, the identification of participant's primary grocery destination was not available [
Despite these limitations, the data presented suggest that distance to the nearest supermarket or food store, regardless of type, with a good selection of fresh and processed fruit or vegetables was associated with daily consumption of fruit, vegetables, and combined fruit and vegetables. For rural seniors, increased distance to food stores was associated with decreased fruit and vegetable intake. Further, inadequate household food resources and perceptions of fair or poor community food resources were also associated with lower intake of fruit and vegetables among rural seniors. This is particularly important, given that there has been limited attention to environmental factors that may influence food choice and dietary intake among rural seniors. As important as easy access to community food sources are to a healthy diet, rural seniors are particularly disadvantaged. For rural seniors, many of whom have to watch their fixed income, the changing grocery store environment translates into a lack of choice in food store destination where they shop, limited selection, and higher prices [
Rural areas have reported disadvantages when it comes to availability, accessibility, and adequacy of health and social services and healthy foods, which particularly affects seniors [
Thus, greater attention must be directed toward the availability and utilization of food resources in rural areas. To foster creative and effective community-based approaches to meeting dietary needs, prospective research needs to be conducted, which identifies the household, neighborhood, and community barriers and facilitators to healthful food choices. Additional research is needed to better understand older consumers and how characteristics of the home and community food environment in rural areas serve as barriers and facilitators for healthful eating. Interventions targeting the prevention and management of nutrition-related health conditions, especially for rural seniors, should understand the context in which rural seniors live and shop, and recognize the influence of access and availability to healthy food on an individual's ability to initiate and maintain a healthy nutritional lifestyle. Educational interventions need to emphasize the availability of healthy foods in non-conventional locations such as convenience and dollar stores. Furthermore, considering the importance of all vegetables and all fruits in this study, they should also focus on the beneficial nutritional characteristics of frozen and canned fruits and vegetables.
It is difficult to initiate or maintain healthful eating habits without access to healthful foods. Large numbers of an increasingly diverse older population are living in rural areas; many of whom face the burden of disease, increased economic constraints, and greater spatial inequality for access to healthful food. Indeed, the preparation for policy change to strengthen food assistance programs or program delivery activities, or interventions to improve nutritional health of this growing population should include an understanding of the community - where people live and where they shop for food [
The authors declare that they have no competing interests.
JRS developed the original idea for the study. JRS wrote the first draft of the paper. JRS, CMJ, and WRD read and approved the final manuscript.
The pre-publication history for this paper can be accessed here:
The analysis and drafting of the manuscript was supported by USDA RIDGE Program; National Center on Minority Health and Health Disparities grant #5P20MD002295; and Centers for Disease Control and Prevention, Prevention Research Centers Program, through the Center for Community Health Development cooperative agreement #1U48DP001924-01. The views are ours and do not represent those of the funders.