This study therefore aimed to (1) document changes in adiposity measures that occurred among Tsimane’ adults in the first decade of the 21st century (2002‐2010); (2) estimate shifts in household consumption of refined grains and sugars, cooking oil, domesticated animal products, homegrown crops, and hunted or fished animal products; and (3) assess how household availability of market‐ and subsistence‐based foods relate to different measures of body fat across time. Given previous research on nutrition transitions among urban and rural populations ( 1 , 2 , 4 ), we predicted that adiposity measures would be positively associated with consumption of market‐based refined grains and sugars, cooking oils, and domesticated animal products but that greater consumption of homegrown crop foods and hunted or fished animal products would be protective against weight gain.

Tsimane’ forager‐horticulturalists in Amazonian Bolivia still live a primarily subsistence‐based lifestyle ( 15 ), and their limited and variable access to commercial markets across households and communities creates a unique circumstance for exploring the role of distinct market foods in the promotion of weight gain and adiposity. Tsimane’ consume a relatively high‐carbohydrate, high‐fiber, high‐protein, low‐fat diet consisting predominantly of cultivated starchy crops (e.g., plantain, rice, manioc, maize) supplemented with lean game, freshwater fish, and occasional fruit and honey ( 13 , 15 , 16 ). However, recent population growth, encroachment on land, reductions in game and fish, loss of traditional ecological knowledge, and growing opportunities for wage labor may provide impetus and means for greater reliance on market‐purchased refined grain products (e.g., flour, bread, pasta), sugar, cooking oil, and domesticated meat and eggs to supplement their traditionally labor‐intensive diets ( 13 , 17 - 21 ). A recent study reported that Tsimane’ intake of total calories, carbohydrates, sugar, and cooking oil rose significantly between 2010 and 2015 ( 13 ). This analysis did not, however, explore the degree to which increases in BMI, body fat percentage, or risk of overweight or obesity depended on specific dietary characteristics or changes. A cross‐sectional study found that higher household expenditures on market‐based foods (e.g., oils, market meats, refined carbohydrates, sweets) were positively associated with BMI and body fat percentage, at least among Tsimane’ men ( 19 ). However, an assessment of the relationship between consumption of different market foods and increases in adiposity has not yet been conducted longitudinally.

The global rise in obesity among both urban and rural populations is often attributed to a composite of dietary and lifestyle changes that promote positive energy balance, including increased consumption of calorically dense refined grains and sugars, edible oils, and domesticated animal products ( 1 - 4 ). This theme has also become pervasive across studies of small‐scale, subsistence‐based societies undergoing rapid economic transitions ( 5 - 12 ). Yet as shifts from traditional subsistence‐ to modern market‐based diets often co‐occur with reductions in physical activity, separating the effect of diet versus other lifestyle factors on weight gain is difficult. Few studies have quantified dietary changes among small‐scale subsistence‐oriented societies across time ( 11 , 13 ) or examined which market‐based foods are most strongly associated with increased adiposity during economic and nutrition transitions. However, prospective research among small‐scale societies with variable consumption of market‐based foods provides a valuable addition to the mostly ecological and cross‐sectional studies among more economically developed populations that fuel unresolved debates about the role of fat versus sugar in the development of obesity ( 14 ).

LMMs with random intercepts for individual, household, and community were used to estimate within‐individual shifts in BMI, body fat percentage, or WC (natural log‐transformed) in relation to the measure of total calories (natural log‐transformed) or servings of different food groups per 2,500 kcal, controlling for Model 1 and Model 2 covariates from the previous adiposity models as well as year (continuous), household AMEs, and (for the food models) total calories. Sensitivity analyses re‐estimated LMMs with all three market‐based food groups added to the model simultaneously. Finally, GLMMs were used to test how total calories (natural log‐transformed) or servings per 2,500 kcal of each of the five food groups related to the odds of BMI ≥ 25.

GLMMs were used to test annual shifts in odds of households reporting consumption of food groups, along with linear, quadratic, and cubic trends, controlling for total household AMEs and total number of household observations. To estimate the change in household consumption patterns between 2002 and 2010, LMMs with random intercepts for household and community were used to regress total calories (log‐transformed) or the density of each food group (expressed as grams per 2,500 kcal or milliliters per 2,500 kcal) on year (ordinal), controlling first for total household AMEs and total number of household observations and then adjusting for the following household‐ and community‐level market integration variables: household income, wealth, and distance from the nearest market center. Marginal standardization was used to estimate the overall mean change in consumption of calories and different foods from 2002 to 2010. In recognition that excess zeros in all food groups (with the exception of crop‐based foods) could bias our estimates, we ran sensitivity analyses using two‐part models for semicontinuous data ( 38 ).

The annual change in body composition was assessed by regressing the natural logarithm of BMI, BF‐BIA, and WC on year (continuous) using multilevel linear mixed‐effects models (LMM) that were estimated separately for females and males and included random intercepts for (clustered on) community, household, and individual. Model 1 primarily focused on time trends and controlled only for fixed effects of mean‐centered age, age squared, self‐reported days spent in bed the previous week, number of total observations between 2002 and 2010 (mean‐centered), and lactation status (for females). Model 2 added fixed effects for market integration variables: education, Spanish proficiency, natural log‐transformed wealth, natural log‐transformed ( n + 1) income, and distance from the nearest market town (mean‐centered). As a robustness analysis, we re‐estimated these LMM models with natural log‐transformed SUM4 and FFM. Additionally, because a previous TAPS analysis examined changes in body composition between 2002 and 2006 ( 36 ), we re‐estimated Model 1 and Model 2 for changes in BMI, BF‐BIA, and WC between 2006 and 2010 to explore whether adiposity gains are accelerating. Generalized LMMs (GLMMs) were used to test the annual shift in odds of overweight and obesity, high body fat, and high WC among females and males, controlling for Model 1 covariates. Marginal standardization was used to illustrate the predicted outcomes from these models with year as an ordinal variable adjusted for the distribution of covariates ( 37 ). Marginal standardization of BMI models with community as a fixed (rather than random) effect were used to plot average male and female BMI across communities ranked by their distance to the nearest market town.

All analyses were run using Stata software, version 14.2 (StataCorp LLC). For descriptive purposes, we examined the proportion of males and females in the underweight, overweight, and obesity categories across years. χ 2 tests with a subsample of 136 males and 124 females with BMI measurements in both 2002 and 2010 compared the change in overweight and obesity prevalence.

Educational attainment, Spanish proficiency, household income, household wealth, and distance from a market center were used as proxies for market integration. Educational attainment was based on self‐reported years of formal schooling. Spanish proficiency was self‐reported as none, some, or fluent. Household income was calculated as the monetary sum of income from wages and sale of goods within the previous 2 weeks. Household wealth was calculated as the sum of the inflation‐adjusted value of 22 physical assets, including 5 locally made materials (e.g., canoes, arrows), 13 market‐based materials (e.g., cooking pots, guns), and 4 domesticated animals ( 24 ). Finally, distance from a market center was based on distance (kilometers) along known travel routes to the closest commercial town (San Borja or Yucumo).

The weekly household caloric intake of each food was divided by 7 to estimate average daily food availability and then divided by a measure of household adult male equivalents (AMEs) to account for varying household size and composition ( 32 , 33 ). Household AMEs were estimated using data on total energy expenditure and physical activity among Tsimane’ adults ( 15 , 16 ) and Food and Agriculture Organization‐recommended energy requirements for children and adolescents ( 32 ) (Supporting Information Table S1 ). Each food group was truncated at 4,500/AME/day to account for over‐reporting. Values for all 21 foods were summed to estimate total household calories. Unrealistically high (> 6,000 kcal/AME/day) total energy intake was common due to over‐reporting crop‐based foods, potentially because of unaccounted food sharing or reporting what was harvested rather than what was consumed. We thus avoided use of absolute measures of any food ( 34 , 35 ) and instead used percent of total calories from any given food or the edible grams or milliliters of a given food group per 2,500 kcal.

Dietary intake was estimated through 1‐week retrospective reports by the female household head on the 21 most common foods in Tsimane’ diets; these data were collected annually during the dry season ( 24 ). We grouped foods most representative of “traditional” or “modern/market” foods in global nutrition transitions ( 1 , 2 , 4 , 30 ). Traditional foods included homegrown crops (plantains, manioc, rice, maize, and pigeon peas) and hunted or fished animal products (game and wild caught fish). Modern/market foods included domesticated animal products (fresh beef, dried beef, cow heads, pork, chicken, duck, and eggs), market grain products and sugar (flour, bread, pasta, and white sugar), and cooking oil. Canned sardines and lard were excluded because they do not fit in either group and are a minimal part of Tsimane’ diets ( 13 ). Foods were reported by weight (kilograms) or in units (e.g., liter of oil, cob of corn), which were converted into weights. Food weights were multiplied by the average edible proportion and caloric value of the respective food based on Latin American composition tables ( 31 ).

BMI, body fat percentage as measured by bioelectric impedance (BF‐BIA), and waist circumference (WC) were our primary measures of adiposity. Weight (nearest 0.1 kg) and BF‐BIA were measured using a Tanita BF‐522W bioelectric impedance scale. Standing height (nearest 0.1 cm) was measured using a portable Seca stadiometer. To reduce noise from measurement error and isolate the effects of weight change, we used each individual’s median adult height to calculate BMI (weight in kilograms divided by height in meters squared). To obtain estimates of underweight, overweight, and obesity prevalence that could be compared with other studies of Tsimane’ and small‐scale societies, we used standard cutoffs for underweight (BMI < 18.5), overweight (BMI ≥ 25 to < 30), and obesity (BMI ≥ 30) ( 25 ). High BF‐BIA was defined as ≥ 35% and ≥ 23% for 20‐ to 39‐year‐old females and males, respectively, and as ≥ 36% and ≥ 24% for 40‐year‐old or older females and males, respectively ( 26 , 27 ). WC (nearest 0.1 cm) was measured using a Gulick fiberglass tape measure. WC measures > 80 cm and > 90 cm were considered high for females and males, respectively, using the recommended cutoffs for South American populations ( 28 , 29 ). As secondary measures of adiposity and body composition, we used fat‐free mass (FFM) estimated as weight − (weight × BF‐BIA) and caliper‐measured (nearest 0.1 cm) sum of the following four skinfold measurements (SUM4): triceps, biceps, subscapular, and suprailiac skinfolds.

This study used 9 years of data collected annually among 13 Tsimane’ communities between 2002 and 2010 by the Tsimane’ Amazonian Panel Study (TAPS), designed to investigate the effects of increasing modernization and market exposure on the well‐being of Tsimane’ ( 24 ). Participants had an average of five observations across the 9‐year period; 8.8% ( n = 198) of those with data in one of the years between 2002 and 2009 were lost to follow‐up in subsequent years. We restricted our sample to the 365 males and 339 nonpregnant females ≥ 20 years old with ≥ 2 BMI and household dietary measurements. TAPS was approved by Northwestern University’s Institutional Review Board and the Grand Tsimane’ Council. All participants provided informed oral consent.

During the study period, travel to a commercial town could take between 2 hours and several days by foot or dugout canoe, but increased travel of traders along nearby thoroughfares provided some access to market goods without commuting to commercial centers. In recent decades, missionary‐formed schools allowed Tsimane’ to receive limited formal education and Spanish language instruction ( 18 , 23 ). Opportunities for wage labor increased as loggers, ranchers, and farmers moved into the area, and data have suggested that monetary income increased by ~ 5.3% per year between 2002 and 2006 ( 18 ). Nevertheless, participation in market economies continued to vary substantially across Tsimane’ households and communities.

Tsimane’ are among the most isolated of 36 indigenous groups living in Bolivia, residing in communities ranging from 50 to 500 individuals in the Bolivian lowlands; however, the rate of Tsimane’ population growth between 1990 and 2012 was estimated to be more than 3.5% ( 21 ). Despite aid from nongovernmental organizations and missionaries, Tsimane’ still have limited access to modern amenities, such as running water, electricity, sanitation, and biomedicine ( 16 , 21 ). Infectious diseases, particularly gastrointestinal and respiratory infections, continue to be the main cause of morbidity and mortality among Tsimane’ ( 16 , 21 , 22 ). Their high pathogen load, along with relatively high levels of physical activity sustained across adulthood ( 15 ), contributes to elevated resting metabolic rates relative to industrialized populations ( 16 ).

Among males, each 10% increase in household calories was associated with a 0.19% ± 0.07% ( P = 0.01) increase in BF‐BIA (Table 5 ). A 25 g/2,500 kcal increase in household refined grains and sugar was associated with a 0.16% ± 0.08% ( P = 0.04) higher BF‐BIA (Table 5 ) but a 0.05 ± 0.02% ( P = 0.005) lower FFM (Supporting Information Table S7 ). Each 100 g/2,500 kcal increase in household availability of domesticated animal products was associated with a 0.25% ± 0.10% ( P = 0.008) increase in male WC, and this estimate remained robust when adding cooking oil and refined grains and sugars to the model (Supporting Information Table S8 ). Higher household servings of crop‐based foods were associated with an 8% (95% CI: 1.02‐1.14; P = 0.007) higher odds of BMI ≥ 25 among males, but no other foods predicted males’ odds of overweight or obesity.

Adjusting for market integration, females’ BMI increased by 0.43% ± 0.20% ( P = 0.03) for each 100 g/2,500 kcal of household consumption of domesticated animal products and by 0.54% ± 0.21% ( P = 0.01) in relation to each 30 mL/2,500 kcal (~ 2 Tbsp) of cooking oil (Table 5 ). Each available household serving of domesticated animal products was associated with a 57% (95% CI: 1.16‐2.12; P = 0.003) increase in females’ odds of BMI ≥ 25, while each serving of hunted or fished animal products was associated with a 16% (OR, 0.84; 95% CI: 0.73‐0.96; P = 0.01) lower odds. In contrast, each 100 g/2,500 kcal of household crop‐based foods was associated with 0.44% ± 0.19% ( P = 0.02) lower female BF‐BIA (Table 5 ) and, relatedly, a 0.11% ± 0.05% ( P = 0.03) higher FFM (Table S7 ). Sensitivity analyses that simultaneously included all market foods in the LMM models suggested that domesticated animal products and cooking oil were independently associated with female BMI (Supporting Information Table S8 ).

Household income was positively associated with household availability of calories, domesticated animal products, cooking oil, and refined grains and sugar but negatively associated with intake of crop‐based foods. However, the effect sizes were miniscule (Table 4 , Model 2). Likewise, the negative effect of market distance on availability of domesticated meat and refined grains and sugar and positive effect on intake of crop‐based foods was small.

The odds of reported sugar intake increased annually by 13% (95% CI: 1.08‐1.19; P < 0.001). Yet, refined grains and sugars, analyzed together (Table 4 ) or separately (Supporting Information Table S6 ), did not contribute a greater proportion of calories across time, suggesting that total calories may have risen proportionally to calories from refined grains and sugars.

The odds of cooking oil use increased by 24% (95% CI: 1.19‐1.29; P < 0.001) each year, though there was evidence of both a linear ( P < 0.001) and cubic ( P = 0.03) trend in the odds of reporting oil intake (data not shown). By 2010, the number of households using cooking oil doubled from 14.5% to 30.2%. Both LMM and two‐part semicontinuous models predicted an approximate 8.8 mL/2,500 kcal increase in household cooking oil use from 2002 to 2010 ( P < 0.001) (Table 4 , Model 1; Supporting Information Table S6 ). This translated into household calories from oil increasing from 2.3% to 5.2% of calories (Table 2 ; Figure 3 C).

Reported household calories did not increase to a statistically significant degree between 2002 and 2010 (Table 4 ). Homegrown crops consistently comprised the bulk (≥ 61%) of household calories (Table 2 ; Figure 3 A). However, the proportion of crop‐based foods declined by approximately 233 ± 39 g/2,500 kcal ( P < 0.001) (Table 4 , Model 1). Reports of household consumption of hunted or fished animal products and domesticated animal products did not change and supplied roughly 8% to 11% and 7% to 9% of household calories, respectively (Table 2 ; Figure 3 B).

WC measures were inconsistent across time for both sexes (Figure 1 E‐1F). The direction of the coefficients for annual change in WC differed depending on whether the analyses included all nine survey years or were restricted to 2006 to 2010 (Supporting Information Table S3 ).

Among the subsample with BMI measurements in both 2002 and 2010 (Supporting Information Table S4 ), the prevalence of overweight increased from 22.6% to 28.2% in females ( P = 0.3) and from 16.2% to 25.0% in males ( P = 0.05). The prevalence of obesity rose from 2.4% to 8.9% in females ( P = 0.03) but only from 0.8% to 1.5% ( P = 0.6) in males.

Predictive margins for changes in body fat measures for Tsimane’ adults from 2002 to 2010. Controlling for age, age squared, number of bedridden days in the previous week, and (among females) lactation status as fixed effects, including random effects for community, household, and individual. Female,= 339; male,= 365; BF‐BIA models exclude two males and two females with < 2 BF‐BIA measures; WC models exclude one male with < 2 WC measures.High BF‐BIA defined as ≥ 23 and ≥ 35 for males and females, respectively, between 20 and 39 years old and ≥ 24 and ≥ 36 for males and females, respectively, at 40 years or older. Because of discontinuous regions when running the BF‐BIA GLMM model with males, this model included random intercepts for community and individual only.Definitions of “high” WC are based on recommended cutoffs for South American populations

The average annual increase in BMI was 0.60% ± 0.12% ( P < 0.001) among women and 0.22% ± 0.09% ( P = 0.009) among men (Table 3 ). This translated into a predicted increase in BMI between 2002 and 2010 of 1.21 kg/m 2 among women and 0.46 kg/m 2 among men (Figure 1 A). The rate of change in BMI was not more rapid from 2006 to 2010 (Supporting Information Table S3 ) compared with estimates from 2002 to 2006 ( 36 ). Average BMI was higher in 2010 compared with 2002 in all communities (Figure 2 ), although no statistically significant linear trend between market distance and BMI was apparent. Other measures of market integration likewise had a limited effect on adiposity measures.

All measures of adiposity were strongly correlated (Supporting Information Table S2 ). The prevalence of underweight remained low among females (< 3%) and males (< 2%). The odds of developing overweight and obesity increased by 14% (95% CI: 1.03‐1.26; P = 0.01) and 37% (95% CI: 1.13‐1.66; P = 0.001) per year, respectively, among women (Table 2 ). There was a statistically significant linear (but not quadratic) trend in the marginal predictions for the proportion of women in overweight ( P = 0.02) and obesity ( P = 0.01) categories (data not shown). There was no evidence of statistically significant linear or quadratic trends in overweight or obesity among men (data not shown). The annual change in males’ odds of overweight was only marginally statistically significant (OR, 1.13; 95% CI: 0.99‐1.27; P = 0.05), and there was no increase in their odds of obesity.

Between 2002 and 2010, the mean age of participants in our sample remained between 40 and 42 years old (range: 20‐90 years) (Table 1 ). Males completed approximately 1.7 years more schooling and reported higher Spanish proficiency than females, but educational attainment increased over time for both sexes. Estimated household wealth and reported household income likewise gradually increased across time.

Discussion

This study aimed to assess how changes in household availability of market‐ and subsistence‐based foods between 2002 and 2010 related to concurrent changes in adiposity among Tsimane’ forager‐horticulturalists. The estimated annual increase in BMI of 0.60% and 0.22% among women and men, respectively, align with previous findings (36) and indicate that weight gain among Tsimane’ adults remained gradual and was not accelerating across the first decade of the 21st century.

We found that household use of cooking oil was positively associated with female BMI, reinforcing the idea that consuming more energy‐dense foods promotes weight gain (39, 40). When available, Tsimane’ will use oil to cook plantains, rice, dried meat, and fish in order to enhance their flavor and texture. Thus, oil does not displace but rather supplements other sources of calories, potentially contributing to positive energy balances. The relative energy density of fattier meat may similarly explain the associations observed between consumption of domesticated animal products (but not hunted or fished animal products) and higher female BMI and male WC.

Notwithstanding, the approximate 0.53% increase in female FFM combined with only moderate changes in SUM4 suggest that observed weight gain among females was not entirely due to increased adiposity. This finding, along with observations that household availability of crop‐based foods was inversely associated with female BF‐BIA but positively associated with female FFM, suggests that physical activity may help blunt adiposity‐promoting effects of small increases in market‐based foods. Women are highly involved with the labor‐intensive production of household crops, and these foods still comprise the bulk of Tsimane’ diets. The physical labor involved in crop production could also help explain the unexpected positive association between household availability of crops and males’ odds of BMI ≥ 25 kg/m2; the higher BMI may in fact be due to higher FFM because the two measures were correlated.

Therefore, while gradual shifts in BMI were enough to increase females’ odds of reaching thresholds typically considered to increase risk of cardiometabolic diseases (41), these numbers may not be as troubling among a physically active and immunologically stressed population (15, 16). In fact, the increase in fat consumption and dietary energy density may be beneficial for some Tsimane’. Though caloric shortfalls are relatively infrequent among Tsimane’, a recent analysis suggested that, between 2010 and 2015, approximately 5% of a large sample of Tsimane’ adults consumed under 1,000 calories and < 25 g/day of protein, and approximately 33% consumed < 25 g/day of fat (13). Males were more likely than females to consume less than their estimated energy needs and report low fat intake, which may be one reason we did not observe strong relationships between oil consumption and adiposity measures in men.

Sustained physical activity levels and persistent reliance on low‐fat, less calorically dense, subsistence‐based foods (15, 16) may help explain why Tsimane’ prevalence of obesity remained below those reported for other indigenous populations in lowland South America around the same time period, including Toba women and men (~ 45%) of Argentina in 2010 (42), Wichí women and men (~ 15%) of Argentina in 2005 (7), Mbyá women and men (~ 15%) of Argentina in 2003 (43), and Suruí women (~ 25%) and men (~ 12%) of Brazil in 2005 (6). A shift from reliance on slash‐and‐burn agriculture, hunting, fishing, and foraging to more market‐purchased foods, such as refined flour, pasta, oil, and fatty meats, have been noted in studies of other South American indigenous populations (5-11). However, few of these studies have quantified dietary changes longitudinally (11) or empirically demonstrated positive (5) or inconsistent (9) relationships between market‐based foods and adiposity (5, 9). The ownership of televisions (11) and descriptions of market foods playing a central role in daily meals (6) suggests that some of these other populations already became more sedentary and market integrated and had experienced greater nutrition transitions by 2010 compared with Tsimane’. In fact, the limited degree of market integration among Tsimane’ may explain why the effect sizes of education, Spanish language, household income and wealth, and market distance on measures of diet and adiposity were relatively minute, even when statistically significant. Additionally, the custom of food sharing among Tsimane’ family members has remained common in spite of increased market integration (44, 45) and may attenuate the effects of income and wealth on shifts in diet and adiposity and help explain heterogeneity across communities. Nevertheless, with population growth (21) and loss of traditional ecological knowledge (20), the push toward greater reliance on market‐based foods may soon become more apparent.

Our findings corroborate another report of gradual increases in adiposity among Tsimane’, particularly among women (13). The latter study did not examine distinct dietary changes as predictors of increasing adiposity, but it reported that between 2010 and 2015, household intake of sugar and cooking oil increased by 15.8 g/day and 4.9 mL/day. By 2015, 73.8% and 40.9% of households were reporting consumption of sugar and oil, respectively, in the previous month. These numbers suggest that the frequency and amount of sugar and oil may have continued to rise among Tsimane’ beyond the 2010 levels observed in the current study. Considering that an accumulated 3,850 caloric excess can result in a 0.5‐kg gain in body weight (46), even these seemingly small increases in sugar and oil consumption could contribute to rising adiposity levels in the coming years.

This study is subject to several limitations. First, shorter stature (47) and greater muscle mass can lead to higher BMI values; therefore, the reported BMI measures may represent different levels of adiposity and health risk than they would among industrialized populations (48). Nonetheless, BMI provides a useful measure of longitudinal weight gain within individuals, and use of standard overweight and obesity cutoffs allows us to make comparisons between Tsimane’ and other similarly short‐statured populations for which overweight and obesity have been documented using the same cutoffs (6, 7, 42, 43).

Second, though data from 24‐hour recalls recently reaffirmed that just 23 different food items account for 90% of calories in the Tsimane’ diet (13), week‐long household‐level dietary recalls of only 21 foods are limited in their ability to measure total calories and nutrient densities, especially in a population that engages in food sharing across households (44, 45). These recalls may not adequately capture the average intake of foods consumed episodically, such as oil, sugar, and refined grain products. Consequently, zero‐inflated variables may have biased the estimates of dietary change obtained from LMMs, though comparisons with the two‐part models for semicontinuous data suggested that the LMMs provided more conservative estimates. These measurement issues and the lack of information on individual consumption patterns may have reduced the statistical power to detect associations between diet and adiposity measures.

In conclusion, this study offers a unique perspective on how shifts in different subsistence‐ and market‐based foods influence body composition among an otherwise relatively active, self‐subsistent population. It suggests that household availability of cooking oil, domesticated meat, and refined grains and sugar were not uniformly associated with all measures of adiposity, and associations differed across females and males, potentially because of divisions of labor and/or different degrees of caloric or nutrient deficits. Sustained moderate physical activity levels and immunological stressors experienced by Tsimane’, along with their overall low‐fat, high‐fiber diets, may help blunt the adiposity‐promoting effects of gradual increases in market‐based foods. Nevertheless, this study demonstrates how even small additions of energy‐dense foods to the diet can gradually push weight into what are generally considered suboptimal ranges.