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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Hawaii Med J. Author manuscript; available in PMC 2008 November 21.
Published in final edited form as:
Hawaii Med J. 2008 September; 67(9): 233–236.
PMCID: PMC2586007
NIHMSID: NIHMS73022

Environmental Factors of Obesity in Communities with Native Hawaiians

Abstract

Objective

To compare the fast food outlets and exercise resources across 3 communities with varying percentages of Native Hawaiians (NH) and to correlate these findings with obesity prevalence.

Methods

Data on all food and exercise resources were collected from January through July 2006 within a 1-mile radius in 3 distinct communities (site A=higher %NH to site C=lower %NH). Comparisons between communities were analyzed in 2007 using Fisher’s Exact and ANOVA.

Results

Trends in obesity prevalence paralleled the percentage of NHs. After adjusting for population size, site B had a greater number of fast food outlets (p<0.001) than site A or C, and more exercise facilities compared to site A (p=0.05). Availability of fast food outlets was significantly greater at site A compared to site C (p=0.03). Usage of exercise facilities was not significantly different between sites although exercise resources were in ‘poorer’ condition at site A compared to site B or C (p≤0.05).

Discussion

Results confirm the increased frequency of obesogenic environmental factors and their correlation with obesity trends across 3 distinct NH communities. These results suggest that environmental factors may offer another means for reducing obesity disparities in minority communities.

Introduction

In the US, recent studies have highlighted the disproportionate rates of obesity in ethnic/racial minority populations including Native Hawaiians (NHs) with a prevalence of up to 70-80%.1-5 Although the multiple causes for obesity disparities among NHs and other racial minorities are not clearly understood, several studies have found that environmental factors, including the availability of healthy food options or exercise facilities, affect the development of excess weight.6-8 In addition, despite some mixed results9-11, the majority of studies suggest a higher prevalence of fast food outlets and lower prevalence of recreational facilities in minority communities compared to non-minority communities.12-15 To date little is known about access to food outlets or exercise resources in communities that are predominantly Native Hawaiian and/or other Pacific Islander even though they are known have increased obesity disparities.

The purpose of this study was to examine the quantity, usage, and quality of fast food outlets and exercise resources in 3 distinct communities distinguished by the proportion of NHs living in each community.

Methods

Assessments of food and exercise resources were collected using the study protocol of the PILI ‘Ohana Program – Community Assessment Study from January – July 2006. Three non-contiguous geographical areas on the island of Oahu were selected for assessment. Each site had varying percentage of NHs with Site A having the highest and Site C with the lowest (Table 1). Within each geographical area, a 1 mile radius was constructed around a centrally located public facility (i.e., community health center, elementary school, etc.). Due to the coastal geography of Site A, 2 semi-circles were constructed around 2 focal points to approximate a complete 1-mile radius.

Table 1
Description of Communities by Sites ; Oahu, Hawai’i (2005-2006)

Assessments were conducted on both weekdays and weekends at various time points by trained researchers using standardized forms. Food resources were categorized as follows: 1) supermarket (at least 5 aisles of household staple foods), 2) fast food (no wait staff, meal obtained in 10 minutes or less), 3) restaurant (patrons seated at tables and served by wait staff), or 4) specialty food (narrow range of non-meal food, e.g. smoothies, desserts). Exercise resources (excluding those located on private property) were divided into: 1) beaches, 2) swimming pools, 3) gym/exercise facilities, 4) walking/running trails, or 5) playgrounds/fields/courts. Each resource was evaluated visually for physical condition and utilization and assigned a score from 1 (poor condition or low utilization) to 3 (good condition or high utilization).

The distribution of resources was compared using Fisher‘s Exact test (categorical data) and analysis of variance (ANOVA, continuous data). All data analyses were carried out in 2007 using SAS 9.1 and p ≤ 0.05 was considered statistically significant. This study was approved by the University of Hawaii, Committee on Human Studies.

Results

The prevalence of obesity paralleled the trend in percentage of Native Hawaiians in each of the 3 sites (Table 1); however, the trend in percent below poverty level did not. Sites A and B had a similar number of fast food eateries (Site A = 29; Site B =31) although Site A had a slightly larger proportion of fast food establishments compared to other food resources (n=29 fast food resources; 22 other food resources). Assessment of exercise facilities at each site showed that Site B had the lowest number of exercise resources (n=14) compared to Site A (n=20) or C (n=32).

After adjusting for population density, Site C was found to have a significantly lower frequency of fast food resources or outlets than Site B (p<0.001) and Site B had a significantly higher frequency of fast food outlets compared to site A (p <0.001) (Table 2). Both Site B (p=0.05) and Site C (p=0.02) had significantly more exercise resources compared to Site A even after adjustment for population density.

Table 2
Comparison of Fast Food and Exercise Resources Between Communities

Site A had the highest usage of fast food outlets (usage score 2.8 of 3.0) compared to all other community sites (all p <0.05) (Table 2). Site B had the lowest usage (usage score 1.9 of 3.0) of fast food outlets despite the higher absolute number of fast food establishments in Site B. The relative proportion of fast food resources per total food resources in a community site, an estimate of the availability of fast food in a community, was only significant for Site A which had a significantly higher proportion of fast food outlets per total food resources compared to Site C (p= 0.03). By contrast, mean usage of exercise resources was similar in all 3 community sites (all p >0.05). However, the exercise resources at Site A was found to be in ‘poorer’ condition when compared to either Site B or Site C. (both p ≤ 0.05).

Discussion

Communities with a higher proportion of NHs had a greater proportion of fast food outlets and the least number of exercise facilities per 10,000 population. Our results are consistent with previous literature which suggests that minority communities have a higher availability of fast foods and a lower number and quality of exercise resources.8, 15-21 Similarly, we found that the proportion of NHs in a community is directly correlated to the estimated obesity in the community. Our study also found that all 3 sites utilized existing exercise resources in their communities at near maximum. This suggests that even communities with a high proportion of NHs (Site A) are frequent users of exercise resources despite increased obesity prevalence and could probably benefit from increased access to exercise resources of sufficient quality. These results are consistent with prior studies that have shown that public access to exercise resources, i.e. parks, sidewalks, etc., are associated with a greater likelihood of being more physically active.8, 22, 23

One unexpected finding was the high number of fast food eateries with a low number of exercise resources in Site B. This increased availability of fast food eateries may increase the risk for the future development of obesity in Site B. As Site B is an emerging community that is likely to attract younger families, creating more exercise resources may be one means for reducing the risk for obesity in this community as few exercise resources were initially identified in this study.

Limitations of this study include restricting assessments to a 1-mile radius, using obesity estimates derived from self-reported data, and not examining socioeconomic status (SES) and its relationship with environmental factors of obesity. The cross-sectional nature of the study also does not allow for causal inferences. In future studies, multiple assessments should be made of the communities at different time points to gain a better representation of the resources and their utilization.

Despite these limitations, our study is the first to provide confirmatory evidence that increased obesogenic environmental factors are more frequent in communities with a higher proportion of Native Hawaiians and that there is a trend of increasing environmental factors associated with increasing obesity prevalence. In emerging communities, the increased number of fast food outlets and few exercise resources, such as in Site B, poses a potential risk for future obesity trends, especially among young families. The results of this study may help to identify communities at high risk for obesity, and also to inform the development of health policies to encourage built environments that promote and support healthier lifestyle practices.

Figure 1
Map of Study Sites

Acknowledgments

We gratefully acknowledge the ongoing community support for this study especially from

  • 1
    Ke Ola Mamo (The Native Hawaiian Health Care System on Oahu island),
  • 2
    Hawai’i Maoli, (The organization of the Association of Hawaiian Civic Clubs),
  • 3
    All the community and academic organizations from the PILI ‘Ohana Program (Kula No Na Po’e, Kokua Kalihi Valley Community Health Center, Kalihi-Palama Health Center) and
  • 4
    The Deparment of Native Hawaiian Health at the J.A. Burns School of Medicine.

We are especially grateful for the strong leadership support of this study from the individuals of the PILI Ohana Program Steering Committee:

  • 5
    Charles Rose,
  • 6
    Keawe’aimoku Kaholokula,
  • 7
    Donna Palikiko,
  • 8
    B. Puni Kekauoha,
  • 9
    Adrienne Dillard,
  • 10
    Henry Gomes,
  • 11
    Alohanani Jamaias,
  • 12
    Keali’i Lum,
  • 13
    Sheryl Raneses Yoshimura,
  • 14
    Dr. Anne Leake.

We gratefully acknowledge the research contributions of the following:

  • 15
    Dr. Larry Kolonel at the Hawaii Cancer Research Center,
  • 16
    Sean Mosier for assisting with data collection,
  • 17
    Dr. Robert Hirokawa at the State of Hawaii Department of Health,
  • 18
    Chieko Kimata for data programming assistance.

This study received funding support from

  • 19
    The Student National Medical Association Satcher Fellowship (KW),
  • 20
    PILI Ohana Project - R24 MD 1660 (MM, JE, MW, ES),
  • 21
    The Hawai’i EXPORT Center - P20 MD 000173 (MM, MW, JE, ES),
  • 22
    Research Centers in Minority Institution - RCMI 2G12RR003061-21 (JE),
  • 23
    The Myron Pinky Thompson Endowed Chair (MM),
  • 24
    Division of Specialized Information Services, National Library of Medicine to support Kurt Menke, Bird’s Eye View GIS and
  • 25
    The Department of Native Hawaiian Health, John A. Burns School of Medicine, University of Hawai’i.

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