Abstract
Background
The burden of obesity and chronic disease is increasing in the older US Hispanic/Latino adult population. There is limited evidence on successful weight management strategies as perceived by this population. Assessing barriers and opportunities for weight management using mixed methods is a robust approach to collect in‐depth information that can be applied to the development of well‐tailored weight management interventions for this population.
Objective
The objective of this study was to assess perceived individual, interpersonal, and environmental factors that influence weight management in older Hispanic/Latino adults.
Methods
This community‐based cross‐sectional study included 23 Hispanic/Latino older (>50y) adults with obesity (BMI >30 kg/m2). Perceived barriers and opportunities for weight management were assessed through validated questionnaires and focus groups. Prospectively registered on ClinicalTrials.gov (NCT03978416) on 7 June 2019.
Results
In this demographically heterogeneous population, language acculturation was generally low, and the frequency of poor dietary behaviors was high. Participants linked financial strain to lower diet quality, as well as anxiety to uncontrolled eating and food cravings. Social support and trust in healthcare professionals were perceived as priorities for healthy eating. Structural and environmental barriers such as affordability and availability of culturally preferred foods were also identified as influences on food choices and eating behavior.
Conclusions
This study revealed opportunities for culturally tailored weight management interventions in older Hispanic/Latino adults with obesity.
Clinical Trial Registry Number
Keywords: Hispanic/Latino, language acculturation, obesity, older adults, weight management
1. INTRODUCTION
The Hispanic adult population in the United States (US) has a prevalence of obesity of 46% compared to 41% in non‐Hispanic whites, and nearly twice the prevalence of type 2 diabetes (T2D). 1 The burden of the obesity epidemic varies according to sociodemographic characteristics within the Hispanic population, with middle‐aged Hispanic adults (40–59 years) bearing the greatest burden of this disease (46%), which is higher than in non‐Hispanic whites (40%), according to NHANES 2013–2014. 2 The same report showed that older Hispanic adults (>60 years) have an obesity prevalence of 39%, which is comparable to the obesity prevalence in non‐Hispanic older white adults. Behaviors that modulate weight status are determined by individual characteristics such as cultural background, inter‐personal influences such as social support or stigma, and environmental influences such as food availability and policies that impact the food environment, as postulated in the Social Ecological Model (SEM) 3 ; however, little is known about the cultural and social influences on body weight in Hispanic/Latino adults.
Multi‐level interventions that integrate individual‐focused elements such as direct education with changes to policies, systems, and/or environments are increasingly recommended as they have been effective in reducing obesity‐related chronic disease risk, particularly in vulnerable populations. 4 Therefore, understanding how the social context, built environment and other social determinants of health are perceived by vulnerable populations is crucial to develop interventions that lead to high adherence and effectiveness in cardiometabolic improvement. 5 Such an approach has been used, for example, in a physical activity intervention in community‐dwelling older adults of Latino background. 6 However, the interplay between individual, interpersonal, and environmental factors influencing the development of obesity and chronic disease risk as perceived by older US Hispanic/Latino adults has not been studied in detail. These gaps in research have hindered the development of effective approaches to prevention and treatment.
In addition to the weight management intervention focus of lifestyle and behavior modification, 7 other considerations for US Hispanic/Latino populations are warranted. These include cultural and demographic heterogeneity, acculturation status, and psychosocial stress exposure, particularly among communities with greater financial strain. Even though a higher degree of acculturation in US Hispanics/Latinos has been associated with adoption of unhealthy eating behaviors and an increased risk for overweight/obesity and chronic conditions such as T2D, 8 , 9 , 10 , 11 , 12 , 13 it is important to recognize the heterogeneity in dietary patterns and preference not only between Hispanics and non‐Hispanic whites, but also within the Hispanic/Latino population. 14 , 15 , 16 Chronic psychosocial stress resulting from prolonged exposure to adverse financial and social circumstances may result in increased physiological burden, or allostatic load, 17 and may contribute to a higher chronic disease risk among racial and ethnic minorities. 18 , 19 Chronic stress may also exacerbate eating behaviors that negatively impact weight status. 20
Factors underlying weight status, as well as weight management targets, can be identified through quantitative methodologies using validated survey instruments, but greater depth of knowledge about attitudes and perceptions of intrinsic, social, and environmental factors influencing weight status may be attained through qualitative approaches. The purpose of the present study was to identify perceived barriers and opportunities for weight management in a group of older Hispanic/Latino adults in the greater Boston area (US) by collecting information through the completion of validated questionnaires on lifestyle and health behaviors, and through focus groups. The greater Boston area is largely urban and has a high degree of racial and ethnic diversity. Therefore, the challenges and opportunities investigated here could be applied to other regions of similar sociodemographic composition in the US. We hypothesized that malleable dietary and psychosocial targets for weight loss and weight loss maintenance could be identified through this approach, including factors such as food cravings, hunger, and disinhibited eating, which we have shown to be effective targets in other population groups. 21 , 22 , 23
2. METHODS
2.1. Participants and recruitment
This cross‐sectional, community‐based, mixed methods study included 23 older (>50y) adults who identified as Hispanic/Latino, and who had obesity (BMI >30 kg/m2) based on self‐reported weight and height. The study was advertised locally in community centers, health centers, and community events in the greater Boston area, specifically Roxbury, Chelsea, and Mission Hill. Study activities took place from October 2019 through February 2020 in the Roxbury YMCA, the Mission Hill Senior Legacy Project, and the adult daycare center Happy Days ADH Program in Chelsea.
2.2. Quantitative data: Questionnaires
The following questionnaires were administered to collect information on cultural background, psychosocial characteristics and eating behaviors: the Short Acculturation Scale for Hispanics (SASH), 24 the Financial Wellbeing Questionnaire, 25 the Latino Diet Behavior Questionnaire (LDBQ), 26 the NHANES Dietary Screener Questionnaire (DSQ), 27 the Perceived stress scale 4 (PSS4), 28 and the Three Factor Eating Questionnaire (TFEQ 29 p18). A sociodemographic questionnaire was also administered. All study materials were available in English and Spanish.
Scoring and analysis were conducted using SAS 9.4 following the guidance provided by the questionnaire developers. The SASH questionnaire had four items, which were factored into a total language acculturation score (range = 1‐6, high = more acculturation). In addition, Likert‐scale responses to each item were converted to numeric values depicting language preference while reading and speaking, speaking at home, thinking, and speaking with friends. The financial wellbeing questionnaire contained three items, which were analyzed to generate a financial strain score (range = 1‐5, high = more financial strain), and a total economic problems score (range = 0–7, high = more economic problems). The LDBQ had 13 items that led to the calculation of a total LDBQ score representing the healthfulness of dietary behaviors (range = 0–47, low = poor diet behavior), and four sub‐scores where higher numbers indicate a greater frequency of that dietary behavior: Health dietary changes score (range = 0–19), artificial sweeteners in drinks score (range = 0–13), number of meals per day score (range = 0–6), and fat consumption score (range = 0–9). The NHANES DSQ contained 30 items and was analyzed by following the analytical pipeline and code published by developers to estimate intake of key food groups and nutrients. Finally, the analytical approach published by the developers of the short version of the TFEQ (18 items) was followed to calculate three constructs of eating behavior which have been associated with weight management in various populations, including US Hispanics: Cognitive restraint (range = 0–24, high = more CR), uncontrolled eating (range = 0–36, high = more UE), and emotional eating (range = 0–12, high = more EE). The questionnaires were completed by 21 of the 23 participants. Five of the 21 participants who completed the questionnaires chose not to answer some of the questions. No statistical tests were performed to compare questionnaire scores between men and women due to the small number of men recruited.
2.3. Qualitative data: Focus groups
Five focus groups with 2 to 7 participants were conducted in Spanish and a key informant interview was conducted in English by a bilingual moderator (MCD). These activities took place in private rooms at the community sites. The questions discussed during the focus groups addressed topics related to food habits, eating behaviors, individual and social determinants of health, health behaviors, willingness to make lifestyle changes for weight loss, food availability and environment, and the influence of celebratory or social occasions on food consumption. Discussions were recorded using voice recorders and lasted approximately 60 min, after which participants completed the aforementioned questionnaires.
The audio recordings from the focus groups and key informant interview were transcribed verbatim in their original language by a second bilingual team member (AMR). Transcripts were coded using NVivo 12 Plus (QSR International, Melbourne, Australia). Transcripts were analyzed for emerging themes and a codebook was developed and agreed upon by the study team. Specifically, a total of 40 codes were identified and organized into seven different categories (emotions related to eating; food preferences; eating and health; food habits in general; beverages; eating and weight control; and identity, culture and eating). A definition and examples of each code was developed by the team. The codes were combined into main topics and arranged according to the levels of influence of the SEM, intrinsic, interpersonal, and environmental factors related to diet behaviors. Representative quotes were selected for the manuscript and translated to English.
2.4. Ethical approval
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Tufts Health Science Institutional Review Board (22 May 2019/No. 13352). All subjects received an information form containing details about the study and a statement on voluntary participation. A $30 stipend was distributed upon completion of participation completion. This study has been registered on ClinicalTrials.gov (NCT03978416).
3. RESULTS
3.1. Population characteristics
The study participants were mostly women (78%) and had a mean (SD) age of 64.8 (8.3) years, with men being on average older (68.2 (10.7) years) than women (63.8 (7.6) years) (Table 1). Most participants resided in urban areas (n = 15) at the time of data collection, and there were 2.2 (1.3) people per household. Racial identities included white (n = 7), unknown (n = 3), or more than one race (n = 9).
TABLE 1.
Population characteristics
| n | All mean or % | SD | n | Men mean or % | SD | n | Women mean or % | SD | |
|---|---|---|---|---|---|---|---|---|---|
| Age (y) | 23 | 64.8 | 8.3 | 5 | 68.2 | 10.7 | 18 | 63.8 | 7.6 |
| BMI (kg/m2) | 23 | 37.0 | 5.3 | 5 | 34.9 | 3.8 | 18 | 37.6 | 5.6 |
| Sex (n) | 23 | 100% | 5 | 22% | 18 | 78% | |||
| Self‐reported weight status | |||||||||
| Underweight | 0 | 0% | 0 | 0% | 0 | 0% | |||
| Normal weight | 1 | 5% | 1 | 20% | 0 | 0% | |||
| Overweight | 17 | 85% | 4 | 80% | 13 | 87% | |||
| Obese | 2 | 10% | 0 | 0% | 2 | 13% | |||
| Self‐reported health status | |||||||||
| Unhealthy | 5 | 26% | 1 | 20% | 4 | 29% | |||
| Moderately unhealthy | 6 | 32% | 2 | 40% | 4 | 29% | |||
| Moderately healthy | 6 | 32% | 2 | 40% | 4 | 29% | |||
| Healthy | 2 | 11% | 0 | 0% | 2 | 14% | |||
| Place of birth | |||||||||
| Colombia | 1 | 5% | 1 | 20% | 0 | 0% | |||
| Cuba | 1 | 5% | 0 | 0% | 1 | 6% | |||
| Dominican Republic | 3 | 14% | 2 | 40% | 1 | 6% | |||
| El Salvador | 3 | 14% | 0 | 0% | 3 | 19% | |||
| Guatemala | 1 | 5% | 0 | 0% | 1 | 6% | |||
| Puerto Rico | 10 | 48% | 2 | 40% | 8 | 50% | |||
| United States | 2 | 10% | 0 | 0% | 2 | 13% | |||
| Time in the United States (y) | 17 | 31 | 16 | 4 | 24 | 15 | 13 | 33 | 16 |
| Race | |||||||||
| More than one race | 9 | 47% | 5 | 83% | 5 | 36% | |||
| Unknown | 3 | 16% | 1 | 17% | 2 | 14% | |||
| White | 7 | 37% | 0 | 0% | 7 | 50% | |||
| Current living area | |||||||||
| Rural | 1 | 5% | 0 | 0% | 1 | 7% | |||
| Suburbs | 3 | 16% | 1 | 20% | 2 | 14% | |||
| Urban | 15 | 79% | 4 | 80% | 11 | 79% | |||
| Marital status | |||||||||
| Divorced | 6 | 29% | 1 | 20% | 5 | 31% | |||
| Married | 6 | 29% | 2 | 40% | 4 | 25% | |||
| Living with partner | 1 | 5% | 0 | 0% | 1 | 6% | |||
| Separated | 1 | 5% | 0 | 0% | 1 | 6% | |||
| Single, never married | 2 | 10% | 1 | 20% | 1 | 6% | |||
| Widowed | 5 | 24% | 1 | 20% | 4 | 25% | |||
| Education | |||||||||
| College degree(s) | 3 | 14% | 1 | 20% | 2 | 13% | |||
| Some college/Associates | 3 | 14% | 1 | 20% | 2 | 13% | |||
| High‐school degree or equiv. | 4 | 19% | 1 | 20% | 3 | 19% | |||
| Some high‐school | 4 | 19% | 0 | 0% | 4 | 25% | |||
| Some elementary school | 7 | 33% | 2 | 40% | 5 | 31% | |||
| Employment | |||||||||
| Employed full time | 3 | 14% | 1 | 20% | 2 | 13% | |||
| Retired | 11 | 52% | 2 | 40% | 9 | 56% | |||
| Unable to work | 5 | 24% | 1 | 20% | 4 | 25% | |||
| Unemployed | 2 | 10% | 1 | 20% | 1 | 6% | |||
| Household income | |||||||||
| $0‐$19,999 | 13 | 68% | 3 | 75% | 10 | 67% | |||
| $20,000‐$39,999 | 2 | 11% | 0 | 0% | 2 | 13% | |||
| $40,000‐$59,999 | 1 | 5% | 0 | 0% | 1 | 7% | |||
| $80,000‐$99,999 | 1 | 5% | 0 | 0% | 1 | 7% | |||
| Greater than $100,000 | 2 | 11% | 1 | 25% | 1 | 7% | |||
| Number of people in household | 20 | 2.2 | 1.3 | 4 | 1.5 | 0.9 | 16 | 2.4 | 1.3 |
| Have children | |||||||||
| No | 2 | 10% | 1 | 20% | 1 | 6% | |||
| Yes | 19 | 90% | 4 | 80% | 15 | 94% | |||
| Childhood obesity | |||||||||
| No | 18 | 90% | 5 | 100% | 13 | 87% | |||
| Yes | 2 | 10% | 0 | 0% | 2 | 13% | |||
| History of eating disorder | |||||||||
| No | 17 | 85% | 4 | 80% | 13 | 87% | |||
| Yes | 3 | 15% | 1 | 20% | 2 | 13% | |||
| Hours of sleep each night | |||||||||
| <3 h | 1 | 5% | 0 | 0% | 1 | 6% | |||
| 3–5 h | 12 | 57% | 2 | 40% | 10 | 63% | |||
| 6–8 h | 8 | 38% | 3 | 60% | 5 | 31% | |||
| Exercise how often | |||||||||
| I do not exercise | 5 | 24% | 2 | 40% | 3 | 19% | |||
| Once per week | 5 | 24% | 2 | 40% | 3 | 19% | |||
| 2–3 times per week | 5 | 24% | 1 | 20% | 4 | 25% | |||
| More than 4 times per week | 6 | 29% | 0 | 0% | 6 | 38% | |||
Education level varied, and 11 participants did not have a high school or equivalent degree while three of the participants had a college degree. Household annual income was below $20,000 for 68% (n = 13) of the participants (Table 1). This coincided with a financial strain score (range of 1–5, where higher scores indicate greater stress) that was greater than the midpoint particularly for women, who scored 3.2 (1.1), versus men, who scored 2.9 (1.4) (Table 2).
TABLE 2.
Psychosocial characteristics, language acculturation, and eating behavior
| All | Men | Women | |||||||
|---|---|---|---|---|---|---|---|---|---|
| n | Mean | SD | n | Mean | SD | n | Mean | SD | |
| SASH score (1–6, high = more acculturation) | 21 | 1.9 | 1.1 | 5 | 2.2 | 1.4 | 16 | 1.8 | 1.0 |
| Read and speak English (high = more) | 21 | 2.0 | 1.1 | 5 | 2.4 | 1.5 | 16 | 1.9 | 1.0 |
| English spoken at home (high = more) | 21 | 1.8 | 1.2 | 5 | 2.0 | 1.4 | 16 | 1.8 | 1.1 |
| English used to think (high = more) | 21 | 1.9 | 1.3 | 5 | 2.0 | 1.4 | 16 | 1.8 | 1.3 |
| English spoken with friends (high = more) | 21 | 1.9 | 1.1 | 5 | 2.2 | 1.3 | 16 | 1.8 | 1.0 |
| Financial strain (1–5, high = more) | 19 | 3.1 | 1.1 | 5 | 2.9 | 1.4 | 14 | 3.2 | 1.1 |
| Total economic problems (0–7, high = more) | 19 | 0.8 | 0.6 | 5 | 0.6 | 0.5 | 14 | 0.9 | 0.7 |
| PSS score (0–16, high = more stressed) | 20 | 6.3 | 3.3 | 5 | 5.2 | 1.9 | 15 | 6.6 | 3.6 |
| PSS1: Unable to control important things | 21 | 1.9 | 1.1 | 5 | 1.6 | 0.5 | 16 | 2.0 | 1.1 |
| PSS2: Confident to handle personal problems | 20 | 1.5 | 1.1 | 5 | 1.2 | 0.8 | 15 | 1.6 | 1.2 |
| PSS3: Things going your way | 20 | 1.2 | 1.0 | 5 | 0.8 | 0.4 | 15 | 1.3 | 1.1 |
| PSS4: Could not overcome difficulties | 20 | 1.7 | 1.1 | 5 | 1.6 | 0.9 | 15 | 1.7 | 1.2 |
| Total LDBQ score (0–47, low = poorer diet behavior) | 16 | 24.3 | 5.0 | 3 | 24.3 | 8.1 | 13 | 24.3 | 4.5 |
| Health dietary changes score (0–19) | 16 | 10.0 | 3.5 | 3 | 10.0 | 3.0 | 13 | 10.2 | 3.7 |
| Artificial sweeteners in drinks score (0–13) | 18 | 8.4 | 2.7 | 5 | 8.2 | 3.0 | 13 | 8.5 | 2.7 |
| Number of meals per day score (0–6) | 16 | 3.1 | 1.6 | 3 | 2.7 | 2.1 | 13 | 3.2 | 1.6 |
| Fat consumption score (0–9) | 16 | 2.8 | 2.8 | 3 | 3.7 | 4.7 | 13 | 2.5 | 2.4 |
| Cognitive restraint (0–24, high = more CR) | 18 | 15.9 | 3.0 | 5 | 14.4 | 1.8 | 13 | 16.5 | 3.2 |
| Uncontrolled eating (0–36, high = more UE) | 18 | 20.1 | 5.7 | 5 | 22.4 | 5.4 | 13 | 19.2 | 5.7 |
| Emotional eating (0–12, high = more EE) | 18 | 7.3 | 2.3 | 5 | 8.4 | 1.8 | 13 | 6.8 | 2.4 |
The mea5n (SD) self‐reported BMI for all participants was 37.0 (5.3) kg/m2, and ranged from 30.5 to 49.7 kg/m2. BMI was higher for women (37.6 (5.6) kg/m2, ranging from 30.5 to 49.7 kg/m2) than for men (34.9 (3.8) kg/m2, ranging from 30.8 to 40.4 kg/m2). Even though the BMI of all participants was in the obese range, their perception of their own weight status was predominantly in the overweight category (n = 17), and their perception of their own health status was evenly distributed across unhealthy (n = 5), moderately unhealthy (n = 6), and moderately healthy (n = 6) categories, with two participants considering themselves as healthy. Reports of childhood obesity (n = 2 women) or eating disorders (n = 1 men and 2 women) were not prevalent. Self‐reported exercise frequency ranged from no exercise (n = 2 men and 3 women) to exercising more than 4 times per week (n = 6 women) (Table 1).
3.2. Psychosocial characteristics and language acculturation
Two participants were born in the continental US, 10 in Puerto Rico, and the remaining participants were from Caribbean, and Central and South American countries (Table 1). On average, participants who relocated to the US had spent 31 16 years there; 24 15 years for men and 33 16 years for women. However, the level of language acculturation calculated from the SASH scale was low. Out of a range from 1 to 6, where high scores indicate a higher degree of language acculturation, the average SASH score in this group was 1.9 (1.1), having a slightly higher value for men than women: 2.2 (1.4) and 1.8 (1.0), respectively (Table 2). Perceived stress was lower than the scale midpoint (which ranges from 0 to 16), 6.3 (3.3), but higher for women, 6.6 (3.6), than for men, 5.2 (1.9).
3.3. Dietary patterns
Dietary intake was assessed with the DSQ and intakes of several food groups were estimated using a scoring algorithm created by the DSQ developers. Estimated average daily intakes of fruits and vegetables were lower than daily recommended amounts, which are 2 cups/day for fruits and 2.5 cups/day for vegetables. Estimated daily fruit consumption was 1.1 (0.7) cup equivalents/day, and estimated vegetable consumption, including legumes and excluding French fries, was 1.6 (0.5) cup equivalents/day (Table 3). Intakes were similar between men and women. Estimated average daily fiber intake, 15.1 (2.3) g/day, was also lower on average than recommended levels (25–30 g/day). The estimated average whole grain intake was 0.6 (0.2) ounce equivalents/day. Estimated daily dairy consumption was half of recommended amounts (i.e., 3 cups/day), with a higher estimate for men (1.8 (0.6) cup equivalents/day), than women (1.4 (0.4) cup equivalents/day). Added sugar consumption was high in this group, with an estimated daily average intake of 14.5 (6.3) tsp equivalents/day. This number was twice as high in men, who reported consuming 23.1 (9.1) tsp equivalents/day, whereas women reported consuming 12.1 (1.8) tsp equivalents/day (Table 3).
TABLE 3.
Estimated mean intakes of food groups, sugar, and fiber, assessed with the Dietary Screener Questionnaire (DSQ)
| All | Men | Women | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n | Mean | SD | Min | Max | n | Mean | SD | Min | Max | n | Mean | SD | Min | Max | |
| Fruits (cup equivalents) per day (recommended: 2 cups/d) | 21 | 1.05 | 0.65 | 0.50 | 3.31 | 5 | 1.04 | 0.27 | 0.74 | 1.42 | 16 | 1.06 | 0.73 | 0.50 | 3.31 |
| Vegetables including legumes and French fries (cup equivalents) per day (recommended: 2.5 cups/d) | 20 | 1.64 | 0.43 | 1.11 | 2.84 | 4 | 1.62 | 0.18 | 1.43 | 1.82 | 16 | 1.65 | 0.47 | 1.11 | 2.84 |
| Vegetables including legumes and excluding French fries (cup equivalents) per day (recommended: 2.5 cups/d) | 20 | 1.55 | 0.46 | 0.98 | 2.81 | 4 | 1.47 | 0.21 | 1.26 | 1.71 | 16 | 1.57 | 0.51 | 0.98 | 2.81 |
| Dairy (cup equivalents) per day (recommended: 3 cups/d) | 20 | 1.51 | 0.49 | 0.99 | 2.74 | 5 | 1.84 | 0.57 | 1.32 | 2.74 | 15 | 1.40 | 0.42 | 0.99 | 2.25 |
| Added sugars (tsp equivalents) per day | 18 | 14.54 | 6.29 | 10.29 | 32.25 | 4 | 23.14 | 9.13 | 12.98 | 32.25 | 14 | 12.08 | 1.81 | 10.29 | 17.31 |
| Added sugars from sugar‐sweetened beverages (tsp equivalents) per day | 20 | 8.75 | 11.33 | 3.70 | 51.62 | 5 | 12.21 | 8.23 | 5.65 | 23.53 | 15 | 7.60 | 12.21 | 3.70 | 51.62 |
| Whole grains (ounce equivalents) per day | 19 | 0.62 | 0.22 | 0.31 | 1.18 | 4 | 0.56 | 0.22 | 0.36 | 0.86 | 15 | 0.64 | 0.22 | 0.31 | 1.18 |
| Fiber (gm) per day (25–50 g/d) | 18 | 15.13 | 2.28 | 10.62 | 19.76 | 4 | 17.00 | 2.20 | 14.68 | 19.76 | 14 | 14.60 | 2.07 | 10.62 | 19.22 |
Scores were generated from the LDBQ to assess dietary behaviors such as fat consumption, where low scores are indicative of poorer diet behaviors. The average score for this group was 24.3 (5.0) out of 47, with similar values for men and women (Table 2). Eating behaviors assessed through the TFEQ‐R18 revealed a higher cognitive restraint (CR) score for women (16.5 (3.2) out of 24) than men (14.4 (1.8)). Conversely, the uncontrolled eating (UE) score was lower for women than for men (19.2 (5.7) and 22.4 (5.4), respectively), as was the emotional eating (EE) score (6.8 (2.4) and 8.4 (1.8), respectively).
3.4. Emerging themes from qualitative data: Intrinsic factors related to diet behaviors
3.4.1. Anxiety and emotions around food
Emotions were consistently identified as important influencers of eating behaviors during the focus groups and interviews. Anxiety was mentioned by most participants as a very significant driver of impulsive eating, more so than other emotions such as stress, guilt, or frustration. Nonetheless, some participants identified strategies that help them overcome this situation, such as limiting food purchases and availability at home. Quotes in both Spanish and English are presented in Table 4.
TABLE 4.
Key emerging themes from focus groups
| Topic | Description | Quote | Translation |
|---|---|---|---|
| Intrinsic factors related to diet behaviors | |||
| Anxiety and emotions around food | Refers to the role that emotions play as drivers or restraints of dietary behaviors. The topic encompasses attachment to certain foods. | ‘Salí de mi casa porque tenía hambre, porque tenía mucha ansiedad […] tenía yo como mucha preocupación’. | ‘I left my house because I was hungry, because I was very anxious. […] I had a lot of worries’. |
| ‘Ansiedad, ansiedad, ansiedad, de comer y comer y comer. De que todo lo que miro, todo lo quiero comer.’ | ‘Anxiety, anxiety, anxiety, from eating and eating and eating. That everything I look at, I want to eat everything’. | ||
| Relationship between food and health | Refers to how participants perceive and explain the positive and negative influence that food has on health status. This includes knowledge, attitudes and beliefs related to pathways by which certain foods, preparation methods or nutrients affect health and quality of life. This influence is bi‐directional; hence some illnesses or conditions can also affect how people eat. | ‘Desde que me dio ese dolor, yo aprendí a cuidarme y no como mucho. Como menos. Trato de no comer muchas grasas ni sal’. | ‘Since I experienced that pain, I learned to take care of myself and do not eat much. I eat less. I try not to eat a lot of fat or salt’. |
| ‘Yo misma dejé la soda, dije ‘espérate, tengo que cuidar la soda, tengo que cuidar la carne, tengo que dejar la sal’ y ahora yo cocino con menos sal’. | “I stopped drinking soda myself. I said 'wait, I have to watch my intake of soda, I watch my intake of meat, I have to give up salt.' And now I cook with less salt’. | ||
| ‘…yo no les voy a traer veneno a la casa’. | ‘… I'm not going to bring poison home’. | ||
| Personal history surrounding food and weight | Alludes to one's own life experiences in relation to food and lifestyle behaviors, and how these change through the life course. This incorporates weight, exercise habits and health changes, as well as changes in knowledge or attitudes towards those issues. The topic also includes food and beverages consumption, as well as behaviors in general. | ‘He aprendido mucho, estoy comiendo por alimentarme o estoy comiendo porque me tengo que llenar. Entonces, eso, por ejemplo, pienso ‘¿qué bien le va a hacer esto a mi cuerpo o me va a hacer?’ | ‘I have learned a lot, I am eating to feed myself or I am eating because I have to fill up. So, for example, I think 'what good is this going to do to my body or is it going to do to me?’ |
| Hunger, cravings, and internal cues that affect intake | States how hunger and satiety signals are perceived and the impact hey have on dietary behavior, as well as common strategies to deal with them. Furthermore, it also refers to food properties that affect consumption (i.e., appealing display), impulse control and enjoyment of foods. | ‘Y si tengo hambre, ¿tú ves? Dos o tres galleticas de esas, porque esas tienen mucha fibra. Y me cojo una botella de agua, y ya con eso, sostengo el estómago’. | ‘And if I'm hungry, do you see? Two or three of those crackers, because those have a lot of fiber. And I take a bottle of water, and with that, I sustain my stomach’. |
| ‘…mientras estoy haciendo algo en la casa, o estoy afuera caminando, no me pasa, pero si estoy viendo el televisor, creo que no tengo hambre, pero como que la mente ‘Wow, tengo que hacer…’, voy a la cocina a buscar algo, como que tengo que comer algo.’ | ‘… While I'm doing something at home, or I'm walking outside, it doesn't happen to me, but if I'm watching TV, I don't think I'm hungry, but my mind goes 'Wow, I have to make…', I go to the kitchen to get something, like I have to eat something’. | ||
| Interpersonal factors related to diet behaviors | |||
| Eating habits during weekends and special occasions | Denotes how food and beverage behaviors change during weekends, family reunions, traditions and other special occasions, which includes mention of unusual dishes. Reference to how cultural norms in such occasions affect an individual's actions in relation to eating. | Originally in English: ‘Whatever they're serving because if not it would be rude’. | ‘Whatever they're serving because otherwise it would be rude’ |
| ‘Pero voy a una fiesta y entonces digo ‘esto hay que aprovechar’ porque quien sabe hasta cuándo’. | ‘I go to a party and then I say, 'I have to take advantage of this' because who knows until when [I will have this opportunity]’. | ||
| ‘Yo cuando voy a un sitio así que voy a comer, que yo sé, no como en el día entero para que pueda comer esta noche’. | ‘When I go to a place to eat, that I know, I don't eat all day so I can eat that night’. | ||
| Family and social networks | Represents how family members, friends, colleagues and acquaintances influence any aspects related to eating and health, either directly (i.e., preparing food and choosing menu) or indirectly (i.e., opinions about an issue, motivation to change a behavior). | ‘Mi hija también tiene problemas de peso, entonces yo estoy tratando de ayudarla a ella. Y como ella come lo que yo cocino, entonces por medio de eso estoy tratando de eliminar o cambiar muchas cosas’. | ‘My daughter also has weight problems, so I am trying to help her. And since she eats what I cook, then through that I am trying to eliminate or change a lot of things’. |
| ‘A mí a veces mi hija me cocina. Cuando ella cocina, lo más que le gusta hacer son sopas, arroz con habichuelas’. | ‘Sometimes my daughter cooks for me. When she cooks, what she likes to make the most are soups, rice and beans’. | ||
| ‘Nosotros cocinamos de más por si alguien llegó’. | ‘We cook extra in case someone else arrives’. | ||
| ‘Pero los fines de semana si mi hija me llama, que me va a invitar a comer en algún lugar, yo como me dicen y como’. | ‘But on the weekends if my daughter calls me, to invite me to eat somewhere, I do as they say and I eat’. | ||
| Sources of information about nutrition and health | Refers to perceived credible sources of nutrition and health information, as well as characteristics of health professionals that are valued when receiving medical/nutrition advice. | ‘Es tremendo cerebro […] ella está con toda la familia. Y entonces ella me busca y ahí me lo hace. Toma. Coge esta dieta, por un mes’. | ‘She is very smart […] she will be with the whole family and she looks for me and there she says it. Here, go on this diet, for a month’ |
| ‘No me hable de esa nutricionista, porque ella dice 'vamos a hacer un plan'. Pero yo digo ‘mira si lo que tú me estás hablando es lo mismo que yo estoy haciendo’. | ‘Don't talk to me about that nutritionist, because she says, 'let's make a plan.' But I say, ‘look, what you are telling me is the same as I am doing’. | ||
| ‘Una amiga mía, ella es, casi veganas de esas, y ella me dijo ‘mira, tienes que aprender a beberte estos jugos, en la mañana y en la noche, cuando si te da hambre’. Y ella me ayudó mucho’. | ‘A friend of mine, she is, one of those almost vegans, and she told me 'look, you have to learn to drink these juices, in the morning and at night, when you feel hungry.' And she helped me a lot’. | ||
| Environmental factors related to diet behaviors | |||
| Environmental influences on dietary behaviors | Includes elements from both the micro (i.e., kitchen) and macroenvironment (i.e. neighborhood) that affect positively or negatively dietary and lifestyle behaviors. | ‘Yo cuando voy a hacer compras siempre hay una pizzería ahí. Siempre yo me paro, y por lo menos un slice’. | ‘When I go shopping there is always a pizzeria there. I always stop and eat at least one slice’. |
| ‘La cosa es que no hay tiempo en comer. Yo no tengo tiempo para ablandar las habichuelas’. | ‘The thing is, there is no time to eat. I don't have time to soak the beans’. | ||
| ‘Yo quisiera comer siempre fruta, vegetales, pero a veces uno no tiene el presupuesto’. | ‘I would like to always eat fruit, vegetables, but sometimes you don't have the budget’. | ||
| ‘Yo sigo viendo televisión y cuando veo ya me lo he comido todo’. | ‘I keep watching television and suddenly I realize I have already eaten everything’. | ||
| Food as a cultural identity | Denotes the role that culture, country of origin and ethnicity play on identity, and how it shapes past and present dietary preferences and behaviors. | ‘Nosotros los hispanos nos gusta todo. Nosotros, el dominicano, que comemos esto, que comemos lo otro, que pa’ allí, que pa’ aquí’. | ‘We Hispanics like everything. We, the Dominicans, who eat this, who eat that, here and there’. |
| ‘Mi comida preferida siempre es arroz con gandules y pernil asado. Y también las verduras. verduras con bacalao’. | ‘My favorite food is always rice with pigeon peas and roast pork. And also vegetables. Vegetables with cod’. | ||
3.4.2. Relationship between food and health
When asked about the connection between food and health, participants showed a profound awareness of the many ways in which diet impacts their quality of life. They frequently mentioned personal experiences with diseases or health conditions which have influenced their lifestyle habits, such as gastrointestinal conditions or medications that led to dietary modifications, and changes in dietary habits, such as reducing portion sizes, which led to desired outcomes such as intentional weight loss. It is noteworthy that for some participants, the process of identifying appropriate eating practices considered beneficial for their own health was done without guidance from a health professional (Table 4). Most participants seemed mindful about the negative effect that some foods have on health. The word ‘poison’, as part of the composition of certain foods, was frequently mentioned and could be identified as a motivation to modify intake or purchase of certain items.
3.4.3. Personal history surrounding food and weight
Similarly, participants displayed awareness of changes in their lifestyle as age progresses, mentioning the role that aging and loss of mobility or functionality has played in their weight management and wellbeing (Table 4). They shared past experiences with weight management programs or strategies and described aspects of the programs or habits that have been either effective or ineffective for weight loss and maintenance. These experiences were identified as contributing factors to a greater degree of reflection about effect that lifestyle choices have on weight status.
3.4.4. Hunger, cravings, and internal cues that affect intake
Finally, other relevant intrapersonal factors that greatly affected dietary behaviors were hunger and food properties that prompt consumption of certain foods. Some participants referred to specific places or dates where they were prone to experiencing cravings, but this was not consistent across participants (Table 4). Additionally, some participants mentioned flavor and the desire to enjoy food as something that influences their habits. However, several participants stated that food is only the sustenance of our bodies and viewed it more as nourishment rather than enjoyment.
3.5. Emerging themes from qualitative data: Interpersonal factors related to diet behaviors
3.5.1. Family and social networks
As for interpersonal factors, mention of social relations emerged constantly throughout the focus groups and key informant interview. Most commonly, participants mentioned the role that some family members play in preparing foods or planning special eating occasions away from home (Table 4). Additionally, most participants mentioned specific places or situations that proved how often they ate in company of others. Social relations and a sense of community were significantly valued by participants. Participants who lived by themselves expressed less motivation to engage in cooking experiences. Furthermore, a few participants expressed their desire for some family members to improve their eating patterns. Leading and helping their families to make healthier choices were strong motivators for participants to seek healthful dietary choices. Finally, even though participants did not describe having different behaviors when eating in the company of others than when eating alone, dietary behaviors did change during celebrations and festivities (Table 4).
3.5.2. Sources of information about nutrition and health
There was some variety in the sources of health and nutrition information trusted by participants. Most participants mentioned medical physicians, nutritionists, and other health professionals as a trusted provider of health advice. However, they expressed different degrees of satisfaction with the information and attention received. Some participants mentioned that health providers did not adequately attend to their needs, while others mentioned that they valued their close relationship (Table 4). Family members and friends were also mentioned as influencing opinions on diet behaviors, but not as frequently.
3.6. Emerging themes from qualitative data: Environmental factors related to diet behaviors
3.6.1. Environmental influences on dietary behaviors
When discussing environmental factors, most participants identified some barriers to healthy eating in their environment at home or in their communities (i.e., price when shopping for some items) (Table 4). Some of the most common factors that were mentioned include limited time in daily lives to prepare foods, availability, and price of certain foods in the neighborhood or workspace, and within their home environment, cues that encourage consumption of certain food items.
3.6.2. Food as a cultural identity
Finally, another important factor that greatly influenced dietary behaviors was cultural identity. Most participants mentioned that their favorite foods were from their country of origin (Table 4). Furthermore, some participants mentioned that they had been disincentivized in the past when a weight loss program failed to acknowledge their food preferences. Nonetheless, when asked about willingness to try different versions of typical dishes to make them healthier, all participants expressed interest in trying new foods and cooking techniques that would allow them to enjoy some of their traditional foods and maintain a healthy diet.
4. DISCUSSION
Using a mixed methods design that included focus groups and validated questionnaires, we identified a series of perceived barriers and potential targets for weight management for older Hispanic/Latino adults with obesity. Specifically, participants identified emotions such as anxiety to have a profound link with decisions around eating and expressed a need for strategies to make informed decisions around healthy eating and manage cravings and disinhibited eating. Further, social support and trust in health care professionals delivering interventions was perceived as a priority for the maintenance of healthy eating behaviors, as well as structural and environmental barriers such as availability of culturally preferred foods and the affordability of healthy foods. While sociodemographic background and country/region of origin of this population were heterogeneous, the level of acculturation was low, the experienced financial strain was moderately high, and diet behaviors tended toward the unhealthy end of the LDBQ scale with some participants noting the causal role of financial strain on limited consumption of healthy foods. It was also noteworthy that the level of health literacy about the negative effects of unhealthy nutrition was high, but nevertheless food consumption patterns indicated widespread unhealthy eating influenced at least in part by emotional, financial, and familial impacts on dietary intake. Language acculturation, as measured with SASH, and length of residency in the US are two different dimensions of acculturation that have been shown to not always be equally associated with measures of lifestyle factors and health in Hispanic/Latino populations. A systematic review by Ayala et al reported that the association between acculturation and diet varied depending on the measure used. 30 Further, measures of acculturation have also been shown to have differing relationships with obesity in the HCHS/SOL cohort, where the strongest predictor of obesity was length of residency in the US, but not SASH language or SASH social relations subscales. 31
The identification of intrapersonal key emerging themes revealed that programs that aim to promote healthy dietary behaviors in Hispanic/Latino populations should use strategies that not only encourage the recognition of hunger and satiety signals, but also consider the connection between food intake and emotions, particularly anxiety, which was a recurring burden expressed by participants, consistent with the high prevalence of anxiety among community‐dwelling older adults in the US. 32 Perceived stress was on average moderately low according to the PSS scores. There is underutilization, limited access, and low perceived need of mental health resources among Hispanics in the US including older adults, 33 , 34 , 35 and interventions that address both cardiometabolic and mental health have shown promising results in Hispanic communities. 36 , 37 Further research is needed to conceptualize stress and anxiety among older Hispanic/Latino populations and to identify the psychological and social factors that contribute to stress and anxiety.
Effective design of weight loss programs design should also incorporate recommendations that are aligned with the participants' nutrition knowledge. Interpersonal key emerging themes suggested that behavioral interventions for this population should include a group setting, since social support is highly valued and a significant source of motivation. Engagement of family members and peers could improve effectiveness of weight loss programs for Hispanics/Latinos, and recommendations for navigating through social situations and celebrations should be included. 38 , 39 , 40 Furthermore, fostering authentic connections based on trust between the health professionals and participants of such interventions should also be a priority, recognizing the importance that relatedness plays in this population. Healthcare professionals treat obesity‐associated diseases and are generally trusted by patients for delivery of health information (although trust is not uniform across racial and ethnic backgrounds in the US). This presents an opportunity for healthcare professionals to provide weight management, diet, and physical activity advice. 41 Consistent with our findings, other studies have also reported trust in healthcare professionals and a desire for weight management, dietary, and physical activity advice among Hispanic patients. 42 , 43 However, the frequency of this type of advice is limited for patients with obesity in general, and Hispanic/Latino patients specifically, particularly when Spanish was their preferred language. 44 , 45 If weight management advice were to be routinely incorporated into clinical practice, cultural tailoring should be prioritized. Systematic reviews assessing the effectiveness of culturally competent interventions found that culturally adapted diabetes prevention programs improved patient outcomes related to glycemic health, 40 and that providing cultural competence training for healthcare providers increased trust and satisfaction of patients from ethnic and racial minorities. 46
The qualitative data also showed perceived environmental barriers and opportunities for healthy eating and weight management. Some of these barriers, such as affordability and access to healthy food options, are consistent with those previously identified in a qualitative assessment of a Hispanic adult population (ages 22–55 years). 47 Interventions that promote healthy dietary behaviors in Hispanic/Latino adults should adapt their recommendations to make them culturally relevant to the target population, and if possible, include strategies that increase participant's food resource management skills such as cooking, food shopping, and budget management.
Lak of effective tailoring to population characteristics in previous lifestyle interventions for racial/ethnic minorities with low socioeconomic status likely explains why they have achieved only half or less of the intervention effects achieved in non‐Hispanic white groups, and why drop‐out rates are often high. 38 , 48 Systematic reviews have indicated that current approaches to weight management are low to moderately effective in Hispanic adults. 38 , 39 To our knowledge no weight management (or weight loss) interventions have specifically targeted Hispanic older populations in the US, and the findings of this study identify important areas to address in future interventions. A limitation of this study is that the data were self‐reported or collected by a nutrition professional, which may have introduced recall or social desirability bias. The study population was culturally heterogeneous, and so it is not possible to determine whether responses would vary by Latin American origin. Further, certain demographic characteristics, such as living area, which was predominantly urban in this population, limit the generalizability of these findings.
Sustainable weight loss may prevent the progression of chronic disease, such as transitioning from prediabetes to T2D. 49 Thus, improving scalable lifestyle interventions to reduce obesity is recognized as a major research goal. 50 Further research is therefore required to develop interventions that are culturally tailored and effectively adapted to population‐specific constraints for healthy weight management. 51 , 52 In conclusion, new interventions that target different levels of influence of eating behaviors, and that address the cultural and sociodemographic diversity of US Hispanics/Latinos are urgently needed. The development of these interventions in older Hispanic/Latinos populations will have significant health, social and economic benefits.
AUTHOR CONTRIBUTIONS
Study conception and design was led by Maria Carlota Dao, Susan B. Roberts, Adolfo G. Cuevas, and Christina D. Economos. Data collection and analysis were performed by Maria Carlota Dao, Zihan Yu, Ana Maafs‐Rodríguez, and Brandy Moser. The first draft of the manuscript was written by Maria Carlota Dao and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
CONFLICT OF INTEREST
The authors declare no other conflict of interest.
ACKNOWLEDGMENTS
The authors would like to thank the study participants, and the staff and community partners at the Roxbury YMCA, especially Mr. Adam Marks, the Mission Hill Senior Legacy Project, especially Mrs. Carmen Pola, and the adult daycare center Happy Days ADH Program, especially Ms. Leda Perez, and the participants for their valuable contribution to this research. The project described was supported by the National Center for Advancing Translational Sciences, National Institutes of Health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Dao MC, Yu Z, Maafs‐Rodríguez A, et al. Perceived intrinsic, social, and environmental barriers for weight management in older Hispanic/Latino adults with obesity. Obes Sci Pract. 2023;9(2):145‐157. 10.1002/osp4.631
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