DOI: 10.5061/dryad.37pvmcvth
title: Subjective well-being across the life course among non-industrialized populations

description: Subjective well-being (SWB) is often described as being U-shaped over
 adulthood, declining to a midlife slump and then improving thereafter.
 Improved SWB in later adulthood has been considered a paradox given
 age-related declines in health and social losses. While SWB has mostly
 been studied in high-income countries, it remains largely unexplored in
 rural subsistence populations lacking formal institutions that reliably
 promote social welfare. Here, we evaluate the age profile of SWB among
 three small-scale subsistence societies (n=468; Study 1), forest users
 from 23 low-income countries (n=6,987; Study 2), and Tsimane’
 horticulturalists (n=1,872; Study 3). Across multiple specifications, we
 find variability in SWB age profiles. In some cases, we find no
 age-related differences in SWB or even inverted-U shapes. Adjusting for
 confounders reduces observed age effects. Our findings highlight
 variability in average well-being trajectories over the life course.
 Ensuring successful aging will require a greater focus on cultural and
 socioecological determinants of individual trajectories.
description: Due to IRB arrangements with the Tsimane tribe, the datasets for
 Study 3 can't be shared openly. However, users can request access by
 following the instructions in the associate manuscript's Data Sharing
 Statement. <strong><em>Study 1: Baka,
 Punan, and Tsimane </em></strong>As part of a cross-cultural
 project on the adaptive value of local ecological knowledge, subjective
 well-being was studied among two foraging populations, the Baka of the
 Congo Basin and the Punan of Borneo, and Tsimane’ horticulturalists,
 between 2012-2013. Subjective well-being was queried by: “Taking
 everything into consideration, would you say your life is 0=very bad,
 1=not good, 2=fair, 3=good, 4=very good”, followed by verbal explanations
 for their answers. Overall, roughly half of the people in each of the
 three groups said life was “good”, and with more reports of “very good”
 than “very bad”. Individuals were sampled every three months, up to four
 times. In total, 474 individuals were sampled 1,174 times: Baka (n=223
 inds/460 ob, mean age=36.4 ± 15.0 y), Punan (n=110/309, mean age=36.6 ±
 14.5y) and Tsimane’ (n=135/405, mean age=36.3 ± 18.1 y). Half (49.5%) of
 participants showed consistency across quarters, and a quarter (25.1%)
 differed by one level. The few with larger differences stemmed from life
 events like widowhood or birth. Poor health was given as the main reason
 for low well-being, especially among Tsimane’ and Punan. Additional
 variables available include the highest level of schooling, household
 size, household wealth, total annual income, and the maximum number of
 days unable to work due to sickness in the past two weeks.
 <strong><em>Study 2: Rural forest users in 23
 countries</em> (PEN)<em> </em></strong>The CIFOR
 Poverty Environment Network (PEN) collected individual and household-level
 data from rural-living people in 23 low-income countries in Asia, Africa,
 and Latin America between 2005-2010. Roughly 8,000 households were
 randomly sampled from village censuses; villages were selected based on
 stratification criteria according to land tenure regime, market
 involvement, vegetation type, and ethnicity. The first household head that
 was available was selected to be interviewed. The PEN study therefore had
 a strong female bias in sampling due to male absenteeism, with men
 constituting 75% of the total sample (see Table S4). Subjective well-being
 was measured on a five-point scale in response to the question: “All
 things considered together, how satisfied are you with your life over the
 past 12 months?” Interviewer ratings of positive affect were assigned
 based on observations of smiling and laughter, on a four-point scale
 (1=minimal,…,4=pervasive). Control variables include household size,
 marital status, education level and income (absolute and relative), and
 recent household shocks, like job loss, income loss, and death in the
 household. The final sample of SWB with covariates is 6,970
 households.
description: # Subjective well-being across the life course among non-industrialized
 populations
 [https://doi.org/10.5061/dryad.37pvmcvth](https://doi.org/10.5061/dryad.37pvmcvth) Data are available for Study 1 and Study 2. Due to IRB arrangements with the Tsimane tribe, the datasets for Study 3 can't be shared openly. However, users can request access to this data by following the instructions in the associated manuscript's Data Sharing Statement ## Description of the data and file structure Study 1: As part of a cross-cultural project on the adaptive value of local ecological knowledge, subjective well-being was studied among two foraging populations, the Baka of the Congo Basin and the Punan of Borneo, and Tsimane’s horticulturalists. Study 2: The CIFOR Poverty Environment Network (PEN) collected individual and household-level data from rural-living people in 23 low-income countries in Asia, Africa, and Latin America. Note: To meet Dryad specifications about de-identification (e.g., maximum three indirect identifiers), several variables in each dataset were binned into a small number of categories (e.g. household size, number of children, wealth, and income variables). A couple of minor variables (controls in Study 2) were also removed. The vital information about population/ethnicity, age, sex, and subjective well-being measures are unaltered. For further information or questions, please contact the corresponding author, Dr. Michael Gurven ([gurven@anth.ucsb.edu](mailto:gurven@anth.ucsb.edu)).  ## Sharing/Access information Original source information is available from the following papers: **Study 1:** V. Reyes-García, S. Gallois, A. Pyhälä, I. Díaz-Reviriego, Á. Fernández-Llamazares, E. Galbraith, S. Miñarro, L. Napitupulu, Happy just because. A cross-cultural study on subjective wellbeing in three Indigenous societies. *PloS one* **16**, e0251551 (2021). **Study 2:** V. Reyes-García, R. Babigumira, A. Pyhälä, S. Wunder, F. Zorondo-Rodríguez, A. Angelsen, Subjective wellbeing and income: Empirical patterns in the rural developing world. *Journal of happiness studies* **17**, 773-791 (2016). A. Angelsen, H. O. Larsen, J. F. Lund, C. Smith-Hall, S. Wunder, *Measuring livelihoods and environmental dependence: Methods for research and fieldwork*.  (Earthscan, London, 2011). ## **DATA-SPECIFIC INFORMATION FOR:** **LEK dataset for Study 1.csv** * *16 variables* * *1180 rows* * *Variable List: * | **Variable** | **Description** | | :---------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | society | Ethnic group (Baka, Punan, Tsimane) | | NewID | a new ID number for participant unique to this public dataset | | female | sex of participant | | imind | Taking everything into consideration, would you say your life is?  Translation into Baka: *A sia e kope, mu a doto pe*? Translation into Bahasa Indonesia: \*Secara umum, apakah kamu.... (bahagia). \*Translation into Tsimane’: *Juñi buty tyi mi?  very bad; not good; fair; good; very good]* | | swb | Converts imind into three-level subjective well-being: If imind = 'very bad' or 'not good' then swb='negative'; if imind='good' or 'very good' then swb='positive'; else swb='neutral' | | age | Age of participant (in years) | | ihcedu | Maximum level of formal schooling attained | | hhsize | Number of people living in the household, binned one-two, three-five, 6+ | | isicknotwork | Number of days too sick to work in the past month | | wagetotal\_ppp | Total wages entering the household, in purchasing power parity (PPP) $US,  binned as zero, 0-10, ten-fifty, 50+ | | WealthHh\_ppp | Household wealth, in PPP $US, binned as &lt;100, 100-500, 500+ | | score | converts imind into five level score variable (1=very bad,…, 5=very good) | | agegp | Age groups (1="&lt;30" 2="30-44" 3="45-59" 4="60+") | | bad | Converts swb into binary variable (1=negative; 0=neutral or positive) | | good | Converts swb into binary variable (1=positive; 0=neutral or negative) | | **PEN data 23 countries for Study 2.csv** | | * *59 variables* * *6987 rows* * *Variable List: * | **Variable** | **Description** | | | :------------ | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :- | | country | Country (23 participating countries in PEN study) | | | gvillcode | ID code for village within country | | | swb | Subjective well-being (How satisfied are you with your life over the past 12 months?) (1=very unsatisfied to 5=very satisfied) | | | wpsc\_trust | In general do you trust people in the village (community)? \[recoded as 1=(3, usually), 0=(1,rarely; 2, sometimes)] | | | wpsc\_help | ‘‘Can you get help from other people in the village if you are in need, for example, if you need extra money because someone in your family is sick?’’ \[recoded as 1=(3, usually), 0=(1,rarely; 2, sometimes)] | | | smile | Did the respondent smile or laugh | | | hhc\_sex | Sex of participant | | | hhc\_educ | Number of years of formal schooling completed | | | age | Age of participant (in years) | | | hhsize | Number of people living in the household, binned one-two, three-five, 6+ | | | ppp\_inc | Cash income, purchasing power parity (PPP),  binned &lt;500, 500-1000, 1000+ | | | shilldeath | whether any illness or death experienced by household members in the last year | | | shloss | whether the household suffered any major loss of crops or livestock | | | shock | Has the household faced any major crisis or unexpectedly large expenditures | | | edu | level of schooling | | | numchild | number of children in levels: 0-1, two-four, 5+ | | | totalinc | Total cash income,  binned &lt;1000, 1000-5000, 5000+ | | | totalinc\_cen | ppp\_inc (standardized) (unidentifiable to original) | | | swb2 | converting swb from 5-level to 3-level subjective well-being (1=unsatisfied, 3=satisfied) | | | bad | 1=unsatisfied, 0=otherwise | | | good | 1=satisfied, 0=otherwise | | | continent | Latin America, Asia or Africa | | | ecuador | country dummy code | | | peru | country dummy code | | | bolivia | country dummy code | | | guatema | country dummy code | | | brazil | country dummy code | | | ethiopia | country dummy code | | | nigeria | country dummy code | | | uganda | country dummy code | | | burkina | country dummy code | | | zambia | country dummy code | | | cameroon | country dummy code | | | ghana | country dummy code | | | senegal | country dummy code | | | malawi | country dummy code | | | drc | country dummy code | | | mozambi | country dummy code | | | china | country dummy code | | | cambodia | country dummy code | | | nepal | country dummy code | | | vietnam | country dummy code | | | india | country dummy code | | | indonesia | country dummy code | | | banglad | country dummy code | | | ageb | recode to categorize age into 5-year intervals (assigning age at mid-interval) | | | edu\_bin | binary education variable (1=any education; 0=none) | | ## Code/Software The SAS (version 9.4) scripts to reproduce the figures and tables from the associated manuscript can be found in the scripts.txt file and the scripts.sas files ([https://doi.org/10.5281/zenodo.13830502)](https://doi.org/10.5281/zenodo.13830502 "Go to software"). Please note that the data for Study 3 is not available on Dryad. However, we have included all the code necessary to generate the figures and analyses for Study 3. For complete information on how to access the data for Study 3, please refer to the Data Sharing Statement in the manuscript. ## Change log **26 Feb 2025:** The previous version uploaded had messed-up IDs: in assigning newIDs from the original, the algorithm was flawed and so unique people ended up getting the same newID. This version is corrected.