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1 Department of Preventive Medicine, Hanyang University, College of Medicine, Seoul, 133-791, Korea and 2 Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC 29208
* To whom correspondence should be addressed. E-mail: efrongil{at}gwm.sc.edu.
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ABSTRACT |
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Introduction |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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A common model for the experience of stress depicts that the presence of certain resources as conditioning variables modifies the relation between a stressor and poor outcomes (23,24). Given that food insecurity can be considered a stressor, social resources such as participation in food assistance programs (FAP)3 could alleviate at least part of the effect of food insecurity on poor outcomes such as overweight and depression. Prior findings on the effect of participation in FAP on overweight are inconsistent (12,25–28), however, probably due partly to study limitations.
This study examined the effect of participation in FAP on overweight and depression among elders, paying specific attention to overcoming some of the limitations of previous studies. The main hypotheses were that food insecurity causes greater weight and depression among elders, and that elders' participation in FAP modifies this effect.
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Methods |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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70 and their spouses regardless of age. Both HRS and AHEAD used multistage complex sampling with 4 distinct selection stages and the intentional oversampling of blacks, Hispanics, and Florida residents. The primary stage involved probability proportionate to size selection of U.S. counties. The 2nd stage selected area segments within sampled primary stage units. The 3rd sampling stage was a systematic selection of housing units from an enumeration of the selected area segments. The 4th stage was the selection of an age-eligible person within a sampled housing unit. HRS and AHEAD were poststratified to known 1990 census household totals and, at the individual level, to the 1990 Public Use Microdata Sample file. This study used data from 4 follow-up surveys (i.e., waves) beginning with 1995–1996 (1996, 1998, 2000, and 2002 for HRS and 1995, 1998, 2000, and 2002 for AHEAD), because food insecurity was measured starting in 1995. The age-eligible study sample numbered 9481 for HRS and 6354 for AHEAD (people who were >54 y of age for HRS and >71 y of age for AHEAD in 1996 and 1995, respectively). The mean age of respondents was 60.8 ± 4.2 for HRS and 79.6 ± 5.8 for AHEAD. The prevalence of food insecurity (modified measure, see below) was 8.4% for HRS and 6.7% for AHEAD, showing higher rate for HRS and similar for AHEAD compared with 6.5% from national survey data for the years 1995–2004 (31). HRS and AHEAD estimated individual prevalence, whereas the national survey data estimated household prevalence. In the national survey data, households with elders had lower prevalence than households without elders (Table 1). Because personal identifiers were not used, this study was exempted from human subjects review.
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25 kg/m2, they were classified into the overweight group; the others were classified into the nonoverweight group. Depression was assessed by an 8-item version of the Center for Epidemiologic Studies-Depression (CES-D) scale. It included dichotomous questions about depression, happiness, loneliness, sadness, enjoyment of life, effort to do things, restless sleep, and ability to "get going" during the past week. The total CES-D score ranged from 0 to 8. A cut-off of >4 was used to identify those with depression (33). Independent variables. Modified food insecurity questions based on the U.S. Household Food Security Survey Module (HFSSM) were used to measure food insecurity status in elders over the past 2 y: whether they always had enough money to buy the food they need and whether they had skipped meals or eaten less than they felt they should because there was not enough food in the house. A respondent was classified as food insecure if he or she reported a negative response to the 1st question or an affirmative response to the 2nd question. A single-item of the HFSSM has shown validity in discriminating energy intake differences (34). This has been especially true in elders: the mean energy intake of food-insecure elders was 58% of their recommended daily allowance. Elders' food insecurity status might be underestimated, however, because only 2 items were used (35–38).
Control variables included age, gender, ethnicity (white and nonwhite; only 2% of HRS and 1% of AHEAD respondents were Hispanic), marital status (married and living together, never married, and divorced/widowed), education (no formal education, less than high school, graduated from high school, some college, college degree, and postcollege degree), smoking status (current smoker or nonsmoker), income, physical functioning, health conditions, and social interaction. Income was defined as the sum of all income for all household members, including money earned from working, investments, and transfers. Income was positively skewed, so a log-transformed variable was used in the regression models.
Physical functioning was assessed with 6 items of Activities of Daily Living (ADL) (i.e., walking across the room, dressing, bathing, eating, getting in and out of bed, and using the toilet) and 5 items of Instrumental Activities of Daily Living (IADL) (i.e., preparing meals, shopping for groceries, making telephone calls, taking medications, and managing money). Health conditions were measured with the number of chronic diseases ever diagnosed by a physician (39). The diseases included hypertension (or high blood pressure), diabetes (or high blood sugar), cancer (or a malignant tumor, excluding minor skin cancers), heart conditions (heart attack, coronary, heart disease, angina, congestive heart failure, or other heart problems), chronic lung disease (chronic bronchitis or emphysema), stroke, and arthritis (or rheumatism). Social interaction was categorized into 2 groups. If respondents had any good friends in the neighborhood (or near the facility), or if they got together with people nearby for a chat or a social visit, they were classified in the high social interaction group. Respondents were categorized into the physical activity group if they had engaged in vigorous physical activity or exercise such as sports, heavy housework, or a job that involves physical labor 3 times a week. Participation in FAP was defined as whether a respondent received food stamps at any time in the past 2 y or home-delivered meals currently.
Data analysis. Prevalence of overweight and depression over time were estimated using sampling weights to adjust for unequal selection probabilities and differences in response rates (40,41). The HRS and AHEAD includes poststratification weights that calibrate the estimate to the demographic characteristics of the U.S. elderly population. Weights from each wave were highly correlated, so the weight variable for 1998 was used. The relations among food insecurity, participation in FAP, and outcomes were assessed by a weighted multilevel linear regression analysis using 3 different models that account for variation within an individual: 1) current, 2) lagged, and 3) difference. These models have various advantages and disadvantages.
The effect of current food insecurity (FIS) and the effect of its interaction with participation in FAP on current outcomes were examined using the current model:
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The current model captures the effect of food insecurity on outcomes in a timely manner, but the direction of causality is questionable; the outcomes may influence contemporaneous food insecurity.
For the lagged and the difference model, 4 waves were combined to make 3 intervals of 2 successive time points, so we used observations for waves 1, 2, and 3 as explanatory variables, and waves 2, 3, and 4, respectively, as dependent variables. The lagged model assessed whether previous food insecurity was related to subsequent change of outcomes, and whether there was an interaction effect of previous food insecurity and previous participation in programs on subsequent change of outcomes.
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The lagged model better establishes the direction of effect than the current model, and distinguishes it from reverse causality by substituting lagged (i.e., earlier) food insecurity (41). This model may not capture the effect of food insecurity accurately if the 2-y period is the wrong period of time in which to see the effect. In addition, the lagged model cannot control for unobserved variables that affect outcomes and are also correlated with food insecurity. Thus, the effect of food insecurity on outcomes could be biased by unobserved factors.
The difference model examined whether the change in food insecurity was related to the change of outcomes, and whether the effect of the change in food insecurity on the change of outcomes was modified by the change of participation in programs.
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The difference model can eliminate the effects of unobserved factors using differences within the same person but cannot establish the direction of causality (42).
Dropout and death rates were examined to assess any potential selection bias. The dropout rate was <3% at each wave for HRS and <4% at each wave for AHEAD. Death rate was <3% in HRS and 13% in AHEAD, and there was no association between food insecurity and death in AHEAD. Because dropout and death rates were low and not related to food insecurity, sampling attrition was considered ignorable (43). All analyses were conducted in SAS software (version 8.0, SAS Institute) with P < 0.5 as a reference P-value. As noted in the equations above, interactions between FIS and FAP were modeled as product terms, with FAP representing the dichotomy of participants vs. nonparticipants.
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Results |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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For AHEAD, current food-insecure elders had higher BMI than current food-secure elders by 0.19 unit of BMI (P < 0.033) (Table 2). In the lagged model, previous food-insecure elders had a greater change in BMI than previous food-secure elders by 0.16 (P < 0.1) for AHEAD. As elders became food insecure after being food secure, their BMI increased by a mean of 0.3 for AHEAD (P < 0.025). For HRS, food insecurity was not related to BMI (Table 2). When the HRS respondents were categorized into 2 groups based on BMI level (<25 kg/m2 and 25 kg/m2), those with food insecurity increased BMI for the higher BMI group (ß = 0.35, P < 0.004) in the lagged model but did not for the lower BMI group (ß = 0.06, P < 0.564).
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For HRS, interactions between food insecurity and participation in FAP on BMI were not significant (Table 3). For AHEAD, food insecurity was positively related to BMI among nonparticipants in the Food Stamp Program for the current and lagged models, but was not related to BMI among participants.
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Discussion |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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In general, food insecurity was positively related to depression in HRS and to both BMI and depression in AHEAD. Other studies of women and children showed a similar association between food insecurity and overweight (11,12,14,18). Several explanations have been suggested for the relation of food insecurity and overweight. Episodic food shortages could cause individuals to overeat when there is enough food and adapt to increased body fat. Limited economic resources might also encourage food-insecure persons to purchase cheap and high energy-dense foods that would result in weight gains (14,46–48). Because food insecurity is a stressor, food-insecure persons may cope with stress by eating uninhibitedly or excessively and thus experience higher body weight (27,49). Future research should aim to understand the experiences and behaviors of food-insecure people that result in this link between food insecurity and overweight.
The positive association of food insecurity with depression can be explained by the relation between stressors and depression. Environmental adversity, disadvantage, and stressful events, especially those associated with low socio-economic status, are known to contribute to the onset of depression symptoms (50,51). Therefore, it is plausible that being food insecure can cause depression. Other studies have also found that the stress of food deprivation caused depression (52,53). Depression is associated with disability, which is highly prevalent in elders (54–57). Food insecurity is a risk factor for disability (58), which could occur in part through depression.
Participation in FAP modified the relation between food insecurity and BMI and depression. The positive effect of previous food insecurity on subsequent change of BMI did not occur when food-insecure elders participated in the Food Stamp Program in AHEAD. Similarly, depression score decreased slightly for elders who became food insecure after being food secure among home-delivered meal participants in HRS.
Previous studies on the effect of participation in FAP on overweight reported various findings. Participation in FAP was associated with a high risk of overweight in Townsend et al. (12) and in Gibson's studies (25,28), and with a low risk of overweight in a study by Jones et al. (26). Townsend et al. (12) and Jones et al. (26) used cross-sectional data so that they could not verify the direction of causality in their findings. Gibson's studies (25,28) could not include food insecurity in the analysis model, which likely biased the estimates of the relation between participation in FAP and overweight, because food insecurity probably influences both participation in FAP and being overweight.
A positive effect of government programs on depression was also shown by Rodriguez et al. (59). They found that receipt of government entitlement benefits was associated with a long-term reduction in depression symptoms among unemployed women.
This study found plausible evidence that food insecurity is related to increased weight and depression in elders. We used 2 longitudinal data sets and accounted for possible confounding factors in the regression models. In addition, we analyzed the data with various statistical approaches for longitudinal data because each model has both strengths and limitations. This study also found some evidence that the effect of food insecurity on weight and depression was modified by participation in FAP, although the results were not consistent across models and data sets. The samples were representative of the U.S. elderly population, strengthening the generalization of the findings. Using different-aged populations in the analyses allowed us to test consistency of findings.
The use of BMI calculated by self-reported measures of height and weight could have created measurement error. Elders could have reported a weight that they maintained for most of their adult life rather than an accurate current weight. Furthermore, BMI may not accurately represent the component of body fat, as it is assumed to do in younger adults. Several factors, such as skeletal muscle mass or bone loss due to aging, the presence of disease processes, or a reduction in height due to vertebral fractures caused by osteoporosis may have influenced the accuracy of using BMI as an assessment of body fat in elders (60,61). Thus, we compared the distribution of BMI and prevalence of overweight in this study with NHANES IIII and NHANES 1999–2000 data (44,45) to confirm the accuracy of BMI. There were no important differences among these data. Using BMI in the elderly population is, however, less sensitive than in adults to assess effects of relative weight on morbidity or mortality (62).
In conclusion, food insecurity was generally related to a greater relative weight in the oldest group of elders and greater depression among both groups of elders in this study. The relation of food insecurity with BMI and depression was modified by participation in FAP in some analyses. When food-insecure elders participated in FAP, in general, food insecurity did not appear to increase weight and depression. These findings imply that food insecurity and food assistance programs can have both nutritional and non-nutritional impacts. The positive impact of participation in FAP for reducing or preventing the risk of poor outcomes resulting from food insecurity will improve elders' quality of life and save on their healthcare expenditures in addition to meeting their nutritional needs. These findings on the multiple impacts of participation in FAP support further development of these programs for elders.
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FOOTNOTES |
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Manuscript received 24 February 2006. Initial review completed 11 April 2006. Revision accepted 25 January 2007.
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LITERATURE CITED |
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