Research ArticleANTHROPOLOGY

Urbanization and market integration have strong, nonlinear effects on cardiometabolic health in the Turkana

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Science Advances  21 Oct 2020:
Vol. 6, no. 43, eabb1430
DOI: 10.1126/sciadv.abb1430
  • Fig. 1 Sampling and dataset overview.

    (A) Sampling locations throughout northern and central Kenya are marked with red dots; the county borders are marked with dashed lines. In both Laikipia and Turkana counties, the largest city (which is generally central within each county) is marked with a black dot. (B) Schematic describing the three lifestyle groups that were sampled as part of this study. (C) The proportion of people from each lifestyle group who reported that they consumed a particular item “regularly,” defined as “one to two times per week,” “more than two times per week,” or “every day.” People who reported that they consumed a particular item “rarely” or “never” were categorized as not consuming the item regularly. Animal products are a staple of the traditional pastoralist diet (85), while carbohydrates and added nutrients, which can only be obtained through trade, are indicative of market integration.

  • Fig. 2 Pastoralist and rural nonpastoralist Turkana have similar health profiles, while biomarkers of metabolic dysfunction are elevated in urban Turkana but not as extremely as in the U.S.

    (A) Effect sizes for contrasts between pastoralist, rural nonpastoralist, and urban nonpastoralist Turkana (from linear models controlling for age and sex; table S2A). Effect sizes are standardized, such that the x axis represents the difference in terms of SDs between groups. BP, blood pressure. (B) Standardized effect sizes for contrasts between rural Turkana (pastoralist and rural nonpastoralist grouped together), urban nonpastoralist Turkana, and the U.S. (from linear models controlling for age and sex; table S2B). In (A) and (B), lighter colored bars represent effect sizes that were not significant [false discovery rate (FDR) > 5%], and analyses of body fat and blood glucose focus on females only (see Supplementary Materials and Methods). Symbols correspond to FDR significance thresholds as follows: *FDR < 0.1%, °FDR < 1%, and +FDR < 5%. (C) Predicted values for a typical rural Turkana (pastoralist and rural nonpastoralist grouped together), urban Turkana, and U.S. individual are shown for a subset of significant biomarkers. Estimates and error bars were obtained using coefficients and their SEs from fitted models, for a female of average age (see Supplementary Materials and Methods).

  • Fig. 3 Urban-rural health differences are mediated by both dietary and other factors.

    (A) Key measures of urbanicity and market integration used in mediation analyses, with means and distributions shown for urban and rural Turkana. (B) Schematic of mediation analyses. Specifically, mediation analyses test the hypothesis that lifestyle effects on health are explained by an intermediate variable, such as consumption of particular food items (red arrows); alternatively, lifestyle effects on health may be direct (black arrow) or mediated by a variable that we did not measure. (C) Summary of mediation analysis results, where colored squares indicate a variable that was found to significantly explain urban-rural health differences in a given biomarker. Significant mediators are colored on the basis of how much the lifestyle effect (urban/rural) decreased when a given mediator was included in the model. MI, market integration. Full results and sample sizes for mediation analyses are presented in table S3.

  • Fig. 4 Early-life population density predicts biomarkers of adult health.

    The relationship between the population density of each individual’s birth location and (A) BMI, (B) our composite measure of health, (C) waist circumference, and (D) diastolic blood pressure are shown for individuals sampled in rural and urban locations, respectively. Notably, while the intercept for a linear fit between early-life population density and each biomarker differs between rural and urban sampling locations (indicating mean differences in biomarker values as a function of adult lifestyle), the slope of the line does not. In other words, we find no evidence that the relationship between early-life conditions and adult health is contingent on the adult environmnt (as predicted by PAR). Instead, being born in an urban location predicts poorer metabolic health regardless of the adult environment.

  • Table 1 Sample sizes by age, sex, and lifestyle, as well as summary statistics for select variables indicating market integration.

    NHANES, National Health and Nutrition Examination Survey; MI, market integration. M, Male; F, Female.

    PastoralistNonpastoralist, ruralNonpastoralist, urbanU.S. (NHANES)
    Age categoryMFMFMFMF
    Select variables indicating MI
    Proportion who frequently
    use cooking oil
    Proportion who frequently
    use salt
    Proportion who frequently
    use sugar
    Mean population density
    (persons per 5 km2)
    SD of population density
    (persons per 5 km2)
  • Table 2 Sample sizes for each biomarker of metabolic and cardiovascular health.

    BP, blood pressure.

    Waist circumference1204515689cm
    Body fat835367468Percentage
    Total cholesterol406201205mg/dl
    HDL cholesterol406201205mg/dl
    LDL cholesterol353171182mg/dl
    Blood glucose436213223mg/dl
    Systolic BP1196512684mmHg
    Diastolic BP1143476667mmHg

Supplementary Materials

  • Supplementary Materials

    Urbanization and market integration have strong, nonlinear effects on cardiometabolic health in the Turkana

    Amanda J. Lea, Dino Martins, Joseph Kamau, Michael Gurven, Julien F. Ayroles

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    The PDF file includes:

    • Supplementary Materials and Methods
    • Figs. S1 to S5
    • Legends for tables S1 to S4
    • References

    Other Supplementary Material for this manuscript includes the following:

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