High social status is often associated with greater mating opportunities and fertility for men, but do women also obtain fitness benefits of high status? Greater resource access and child survivorship may be principal pathways through which social status increases women’s fitness. Here we examine whether peer-rankings of women’s social status (indicated by political influence, project leadership and respect) positively covaries with child nutritional status and health in a community of Amazonian horticulturalists. We find that maternal political influence, but not fathers’,  is associated with improved child health outcomes in models adjusting for maternal age, parental height and weight, level of schooling, household income, family size, and number of co-resident kin in the community. Children of politically influential women have higher weight-for-age (B=0.33; 95% CI= 0.12 – 0.54), height-for-age (B=0.32; 95%CI=0.10 – 0.54), and weight-for-height (B= 0.24; 95% CI=0.04 – 0.44), and they are less likely to be diagnosed with common illnesses (OR= 0.48; 95% CI= 0.31 – 0.76). These results are consistent with women leveraging their social status to enhance reproductive success through improvements in child health. We discuss these results in light of parental investment theory and the implications for the evolution of female social status in humans.

Social status. All resident adults in the village of study were rated by peers on three dimensions of social status: political influence, project leadership and respect. Six women and six men from the village were randomly selected as raters and were asked to evaluate photographs of community members, for each of the following questions: 1) “Whose voice carries the most weight during community debates?” (“political influence”); 2) “Who knows how to manage community projects?” (“project leadership”); and 3) “Who receives more respect in the village?” (“respect”). Men and women’s photographs were included in the same array and evaluated together by each rater.  

Child health. From 2012 to 2016, as part of the Tsimane Health and Life History Project’s (THLHP) focus on health, growth and development, team physicians collected anthropometric measurements and diagnosed children’s illnesses during annual or biannual medical exams. Of the men and women whose social status measures were collected in 2014, 47 women and men had children aged 0 to 16 years who had been evaluated by the THLHP between 2012 and 2016, and who were included in our dataset resulting in 342 observations. Children’s standing and sitting height were measured without shoes to the nearest millimeter with a portable Seca 213 stadiometer. Weight was measured with a Tanita BF-572 scale in light clothing without shoes. Anthropometric measurements were used to assess population-specific z-scores (sensu [35]; localgrowth R package: https://github.com/adblackwell/localgrowth) for 1) weight-for-age (indicator of low weight), 2) height-for-age (indicator of stunting), and 3) weight-for-height (indicator of wasting). Using bilingual (Spanish-Tsimane) research assistants, physicians also diagnosed children’s illnesses using the International Classification of Diseases (ICD-10). Clinical diagnoses were binary (disease present or absent) and grouped into three categories reflecting common illnesses: gastrointestinal diseases , respiratory infections and anemia.

Socio-demographics. Demographic data used to determine kinship, age and live births per woman at the time of the child’s medical visit come from reproductive histories collected from 2003-2005 and updated annually thereafter. In interviews conducted by lead authors in 2014, parents also reported their years of schooling and income over the past year. 

Child's age, maternal age, and all parental attributes were standardized in our analysis. Household income was logged then standardized.

Given that the dataset contains over three measures that can be potentially used to indirectly identify study participants, we have z-scored all variables in our published dataset.

19 missing values for mothers'height and weight, and # livebirths at time of medical visit

8 missing values for fathers'weight

45 missing values for child clinical diagnoses