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A Data Guide for this study is available as a web page and for download. The National Longitudinal Study of Adolescent to Adult Health (Add Health), 1994-2008 [Public Use] is a longitudinal study of a nationally representative sample of U.S. adolescents in grades 7 through 12 during the 1994-1995 school year. The Add Health cohort was followed into young adulthood with four in-home interviews, the most recent conducted in 2008 when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents' social, economic, psychological, and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships. Add Health Wave I data collection took place between September 1994 and December 1995, and included both an in-school questionnaire and in-home interview. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12, and gathered information on social and demographic characteristics of adolescent respondents, education and occupation of parents, household structure, expectations for the future, self-esteem, health status, risk behaviors, friendships, and school-year extracurricular activities. All students listed on a sample school's roster were eligible for selection into the core in-home interview sample. In-home interviews included topics such as health status, health-facility utilization, nutrition, peer networks, decision-making processes, family composition and dynamics, educational aspirations and expectations, employment experience, romantic and sexual partnerships, substance use, and criminal activities. A parent, preferably the resident mother, of each adolescent respondent interviewed in Wave I was also asked to complete an interviewer-assisted questionnaire covering topics such as inheritable health conditions, marriages and marriage-like relationships, neighborhood characteristics, involvement in volunteer, civic, and school activities, health-affecting behaviors, education and employment, household income and economic assistance, parent-adolescent communication and interaction, parent's familiarity with the adolescent's friends and friends' parents. Add Health data collection recommenced for Wave II from April to August 1996, and included almost 15,000 follow-up in-home interviews with adolescents from Wave I. Interview questions were generally similar to Wave I, but also included questions about sun exposure and more detailed nutrition questions. Respondents were asked to report their height and weight during the course of the interview, and were also weighed and measured by the interviewer. From August 2001 to April 2002, Wave III data were collected through in-home interviews with 15,170 Wave I respondents (now 18 to 26 years old), as well as interviews with their partners. Respondents were administered survey questions designed to obtain information about family, relationships, sexual experiences, childbearing, and educational histories, labor force involvement, civic participation, religion and spirituality, mental health, health insurance, illness, delinquency and violence, gambling, substance abuse, and involvement with the criminal justice system. High School Transcript Release Forms were also collected at Wave III, and these data comprise the Education Data component of the Add Health study. Wave IV in-home interviews were conducted in 2008 and 2009 when the original Wave I respondents were 24 to 32 years old. Longitudinal survey data were collected on the social, economic, psychological, and health circumstances of respondents, as well as longitudinal geographic data. Survey questions were expanded on educational transitions, economic status and financial resources and strains, sleep patterns and sleep quality, eating habits and nutrition, illnesses and medications, physical activities, emotional content and quality of current or most recent romantic/cohabiting/marriage relationships, and maltreatment during childhood by caregivers. Dates and circumstances of key life events occurring in young adulthood were also recorded, including a complete marriage and cohabitation history, full pregnancy and fertility histories from both men and women, an educational history of dates of degrees and school attendance, contact with the criminal justice system, military service, and various employment events, including the date of first and current jobs, with respective information on occupation, industry, wages, hours, and benefits. Finally, physical measurements and biospecimens were also collected at Wave IV, and included anthropometric measures of weight, height and waist circumference, cardiovascular measures such as systolic blood pressure, diastolic blood pressure, and pulse, metabolic measures from dried blood spots assayed for lipids, glucose, and glycosylated hemoglobin (HbA1c), measures of inflammation and immune function, including High sensitivity C-reactive protein (hsCRP) and Epstein-Barr virus (EBV). Datasets: DS0: Study-Level Files DS1: Wave I: In-Home Questionnaire, Public Use Sample DS2: Wave I: Public Use Contextual Database DS3: Wave I: Network Variables DS4: Wave I: Public Use Grand Sample Weights DS5: Wave II: In-Home Questionnaire, Public Use Sample DS6: Wave II: Public Use Contextual Database DS7: Wave II: Public Use Grand Sample Weights DS8: Wave III: In-Home Questionnaire, Public Use Sample DS9: Wave III: In-Home Questionnaire, Public Use Sample (Section 17: Relationships) DS10: Wave III: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancies) DS11: Wave III: In-Home Questionnaire, Public Use Sample (Section 19: Relationships in Detail) DS12: Wave III: In-Home Questionnaire, Public Use Sample (Section 22: Completed Pregnancies) DS13: Wave III: In-Home Questionnaire, Public Use Sample (Section 23: Current Pregnancies) DS14: Wave III: In-Home Questionnaire, Public Use Sample (Section 24: Live Births) DS15: Wave III: In-Home Questionnaire, Public Use Sample (Section 25: Children and Parenting) DS16: Wave III: Public Use Education Data DS17: Wave III: Public Use Graduation Data DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS20: Wave III: Peabody Picture Vocabulary Test (PVT), Public Use DS21: Wave III: Public In-Home Weights DS22: Wave IV: In-Home Questionnaire, Public Use Sample DS23: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16B: Relationships) DS24: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16C: Relationships) DS25: Wave IV: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancy Table) DS26: Wave IV: In-Home Questionnaire, Public Use Sample (Section 19: Live Births) DS27: Wave IV: In-Home Questionnaire, Public Use Sample (Section 20A: Children and Parenting) DS28: Wave IV: Biomarkers, Measures of Inflammation and Immune Function DS29: Wave IV: Biomarkers, Measures of Glucose Homeostasis DS30: Wave IV: Biomarkers, Lipids DS31: Wave IV: Public Use Weights Wave I: The Stage 1 in-school sample was a stratified, random sample of all high schools in the United States. A school was eligible for the sample if it included an 11th grade and had a minimum enrollment of 30 students. A feeder school -- a school that sent graduates to the high school and that included a 7th grade -- was also recruited from the community. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12. The Stage 2 in-home sample of 27,000 adolescents consisted of a core sample from each community, plus selected special over samples. Eligibility for over samples was determined by an adolescent's responses on the in-school questionnaire. Adolescents could qualify for more than one sample.; Wave II: The Wave II in-home interview surveyed almost 15,000 of the same students one year after Wave I.; Wave III: The in-home Wave III sample consists of over 15,000 Wave I respondents who could be located and re-interviewed six years later.; Wave IV: All original Wave I in-home respondents were eligible for in-home interviews at Wave IV. At Wave IV, the Add Health sample was dispersed across the nation with respondents living in all 50 states. Administrators were able to locate 92.5% of the Wave IV sample and interviewed 80.3% of eligible sample members. ; For additional information on sampling, including detailed information on special oversamples, please see the Add Health Study Design page. Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health. Waves I and II focused on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants aged into adulthood, the scientific goals of the study expanded and evolved. Wave III explored adolescent experiences and behaviors related to decisions, behavior, and health outcomes in the transition to adulthood. Wave IV expanded to examine developmental and health trajectories across the life course of adolescence into young adulthood, using an integrative study design which combined social, behavioral, and biomedical measures data collection. Response Rates: Response rates for each wave were as follows: Wave I: 79 percent; Wave II: 88.6 percent; Wave III: 77.4 percent; Wave IV: 80.3 percent; Adolescents in grades 7 through 12 during the 1994-1995 school year. Respondents were geographically located in the United States. audio computer-assisted self interview (ACASI) computer-assisted personal interview (CAPI) computer-assisted self interview (CASI) paper and pencil interview (PAPI) face-to-face interview

The IBM 3D models and derivative products were generated via a typical Image-based modeling pipeline. The aerial photos were collected by the UC Merced team using a DJI Phantom 3 Pro multi-rotor drone. The geospatial control data was collected by California State Parks licensed surveyor David Gutierrez using a Trimble differential GPS and Trimble robotic total station. The TLS LiDAR data were collected by the UC Merced team using a FARO Focus 3D S120 range finder and processed in FARO Scene and CloudCompare. The CAD drawings were created by Arianna Campiani using orthographic views of the buildings' terrestrial laser scanning point clouds produced by Scott McAvoy in the Potree Viewer. Dataset includes all the natively digital geospatial and 3D data collected in our topographic and 3D survey of the iconic Dechambeau Hotel & IOOF Hall buildings located at the entrance of town on Main St.

Eosinophil results by foragingData necessary to run analysis on the influence of foraging on eosinophil concentrations. Given small population sizes all data have been randomised to protect individuals identity.eosfarm.csvEosinophil results by settlementData necessary to run analysis on the influence of settlement on eosinophil concentrations. Given small population sizes all data have been randomised to protect individuals identity.eosset.csvFertility by foragingData necessary to run analysis on the influence of foraging on fertility. Given small population sizes all data have been randomised to protect individuals identity.fertfarm.csvFertility by settlementData required for analysis of fertility and mobility.fertset.csvLymphocytosis by foragingData necessary to run analysis on the influence of foraging on Lymphocytosis. Given small population sizes all data have been randomised to protect individuals identity.lymfarm.csvLymphocytosis by settlementData necessary to run analysis on the influence of settlement on Lymphocytosis. Given small population sizes all data have been randomised to protect individuals identity.lymset.csvMortality by foragingData necessary to run analysis on the influence of foraging on mortality. Given small population sizes all data have been randomised to protect individuals identity.mortfarm.csvMortality by settlementData necessary to run analysis on the influence of settlement on mortality. Given small population sizes all data have been randomised to protect individuals identity.mortset.csvNeutrophilia by foragingData necessary to run analysis on the influence of foraging on Neutrophilia. Given small population sizes all data have been randomised to protect individuals identity.neufarm.csvNeutrophilia by settlementData necessary to run analysis on the influence of settlement on Neutrophilia. Given small population sizes all data have been randomised to protect individuals identity.neuset.csvParasite loadData necessary to run analysis on the influence of settlement on parasite burdenparaload.csvReproductive success and foragingData necessary to run analysis on the influence of foraging on RS. Given small population sizes all data have been randomised to protect individuals identity.rsfarm.csvReproductive success and settlementData necessary to run analysis on the influence of settlement on RS. Given small population sizes all data have been randomised to protect individuals identity.rsset.csv The Neolithic demographic transition remains a paradox, because it is associated with both higher rates of population growth and increased morbidity and mortality rates. Here we reconcile the conflicting evidence by proposing that the spread of agriculture involved a life history quality–quantity trade-off whereby mothers traded offspring survival for increased fertility, achieving greater reproductive success despite deteriorating health. We test this hypothesis by investigating fertility, mortality, health, and overall reproductive success in Agta hunter-gatherers whose camps exhibit variable levels of sedentarization, mobility, and involvement in agricultural activities. We conducted blood composition tests in 345 Agta and found that viral and helminthic infections as well as child mortality rates were significantly increased with sedentarization. Nonetheless, both age-controlled fertility and overall reproductive success were positively affected by sedentarization and participation in cultivation. Thus, we provide the first empirical evidence, to our knowledge, of an adaptive mechanism in foragers that reconciles the decline in health and child survival with the observed demographic expansion during the Neolithic.

The Canary Islands were settled in the first millennium AD by colonizers likely originating from North Africa. The settlers developed a farming economy with barley as the main crop. Archaeological evidence suggests the islands then remained isolated until European sea-travellers discovered and colonized them during the 14th and 15th centuries. Here we report a population study of ancient DNA from twenty-one archaeobotanical barley grains from Gran Canaria dating from 1050 to 1440 cal AD. The material showed exceptional DNA preservation and genotyping was carried out for 99 single nucleotide markers. In addition 101 extant landrace accessions from the Canary Islands and the western Mediterranean were genotyped. The archaeological material showed high genetic similarity to extant landraces from the Canary Islands. In contrast, accessions from the Canary Islands were highly differentiated from both Iberian and North African mainland barley. Within the Canary Islands, landraces from the easternmost islands were genetically differentiated from landraces from the western islands, corroborating the presence of pre-Hispanic barley cultivation on Lanzarote. The results demonstrate the potential of population genetic analyses of ancient DNA. They support the hypothesis of an original colonization, possibly from present day Morocco, and subsequent isolation of the islands and reveal a farmer fidelity to the local barley that has lasted for centuries. Barley SNP genotypesGenotyping results of archaeological and extant barley from the Canary Islands and extant barley from North Africa and the Mediterranean.CanaryBarley.csv

δ13C values of broomcorn millet leaves and reference taxa displayed in Fig. 3, including corrections used to account for Suess effect for modern samples and trophic level enrichment between dietary sources and tissues

δ13Ccol and δ15Ncol values and radiocarbon dates of humans from the IAMC and wider steppe region

δ13Ccol and δ15Ncol values from samples of bone collagen from domesticated and wild herbivores and humans, including modern steppe tortoise

3D models and derivative products were generated via a typical Image-based modeling pipeline. The 2015 aerial photos were collected by contractor Monarch Inc. using a custom-made multi-rotor drone. The 2020 aerials photos were collected by Denise Jaffke using a DJI Phantom 4 Pro quadcopter drone. All of the IBM 3D models and derivative data were processed in Agisoft Metashape Pro. The geospatial control data was collected by California State Parks licensed surveyor David Gutierrez using a Trimble differential GPS and Trimble robotic total station. Dataset includes all the natively digital geospatial and 3D data collected in our topographic and 3D survey of the Roseklip Mill Complex, a cyanid gold ore processing facility that remained active until the 1940s. The site is located in an area of the park closed to the public and includes a biohazard area that was fenced by the U.S. Environmental Protection Agency.