Artículo de revista: Castro-Prieto, Paula A.; Spijker, Jeroen; Recaño, Joaquín (2023) “A quasi- cohort trend analysis of adult obesity in Colombia”. Journal of Biosocial Science (online, 26 June 2023): 1-27 (ISSN: 0021-9320). DOI: https://doi.org/10.1017/S002193202300010X Journal of Biosocial Science (2023), page 1 of 27 doi:10.1017/S002193202300010X RESEARCH ARTICLE A quasi-cohort trend analysis of adult obesity in Colombia Paula Andrea Castro-Prieto1,2 , Jeroen Spijker2 and Joaquín Recaño1,2 1 Universitat Autònoma de Barcelona, Barcelona, Spain and 2Centre d'Estudis Demogràfics (CED-CERCA), Bellaterra, Spain Corresponding author: Paula Andrea Castro-Prieto; Email: pcastro@ced.uab.es (Received 29 July 2022; revised 8 May 2023; accepted 18 May 2023) Abstract In Colombia, the prevalence of obesity has been increasing in recent years due to changes in dietary and nutritional patterns. While previous studies have focussed on describing obesity and its associated factors, they have mainly used a cross-sectional methodology. Accordingly, this study aims to conduct a descriptive quasi-cohort analysis to capture age-specific cohort trends in body mass index (BMI) according to sex and ethnicity (indigenous, Afro-Colombian, and the remaining population). The study utilised data from the National Survey of the Nutritional Situation in Colombia (ENSIN) conducted in 2005, 2010, and 2015 that included 214,136 individuals aged 20–64 years after screening. Data on ethnicity were only available from the 2010 and 2015 surveys. Overall, the prevalence of obesity increased by 6.1 percentage points (from 15.2% to 21.3%) between 2005 and 2015 (men from 10.4% to 15.7%; women from 18.2% to 25.7%). Among Afro-Colombians, obesity rose 6.6 percentage points (from 19.4% to 26.0%), again more so in women than in men (2015: 35.2% versus 17.8%). Among indigenous people, the proportion increased by 5.3 percentage points (from 13.5% to 18.8%), with women reporting highest rates (2015: 23.7% against 12.6% in men). Age- and cohort-specific results also indicate that recent adult cohorts are experiencing sharp increases in BMI, for example, while 25–29-year-old males born in 1975–1979 had a BMI of 24.2 kg/m2, among 40–44-year-olds of the same cohort, this equalled 26.8 kg/m2. In the case of women, these age differences in BMI among the same cohort are even greater (24.4 and 28.0 kg/m2). In summary, the results of this study indicate that Colombia is still in the early stages of the obesity transition, urging the need to monitor obesity trends in Colombia from both an age and cohort perspective. To achieve this, longitudinal surveys or repeated cross-sectional surveys like the ENSIN could be utilised. Keywords: Obesity; Demography; Population Health; Colombia Introduction Excessive body weight is a risk marker for cardiovascular disease and is associated with an increased prevalence of diabetes, hypertension, metabolic syndrome, and premature mortality (Bozkurt et al., 2016) and is also a potential mediator of female infertility and cancer (Iyengar et al., 2016; Broughton & Moley, 2017). In addition, the rising incidence and prevalence of obesity constitute an important issue in global public health in terms of economic burden (Tremmel et al., 2017). Although obesity trends differ greatly between and within countries, according to Jaacks et al. (2019) there are discernible patterns in broad changes in obesity prevalence over time. These patterns can be grouped into predictable stages of, what the authors call, the ‘obesity transition’. The first stage is characterised by an increase in obesity from very low initial levels, especially in © The Author(s), 2023. Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 2 Paula Andrea Castro-Prieto et al. women. The second stage corresponds to a more generalised increase in obesity in adults, and smaller increases in children, leading to a narrowing of the gender gap. According to Jaacks et al. (2019), many Latin American and Middle Eastern countries are presently at this stage, although, as our results show, in Colombia gender differences are not yet declining. The third stage is identified by the closing of the gender gap and an acceleration of obesity prevalence in the low socioeconomic status (SES) subpopulation that still had a low body mass index (BMI) during the previous stage to the point that they surpass the high SES population. The obesity prevalence in children also increases. The USA and all European countries that were analysed pertained to this stage in 2016 (Jaacks et al., 2019). Current evidence from Europe suggests a stabilisation of obesity prevalence. In the case of Austria, this has been shown for women since 2007 (Großschädl & Stronegger, 2021). In Scotland, while there was an increase in BMI between 1995 and 2008 among adults, it stayed level between 2008 and 2014 (Tod et al., 2017). In Spain, the evidence shows a stabilisation in the excess body weight in men since 2017 and in women since 1997 (García & Martín, 2022). However, recent studies in Latin America have observed an increase in the prevalence of overweight, particularly obesity, which has been unevenly distributed according to SES and gender. A study of 14 Latin American countries found that on average the highest prevalence of obesity was found in the fourth wealth quintile (26.1%), the third education quintile (27.1%), and urban areas (26.0%) (Jiwani et al., 2019). Furthermore, the ethnic dimension implies an additional issue in Latin America, due to its diverse socio-cultural and economic conditions and characteristics. Afro-descendants and indigenous people are an examples of this, as they have experienced situations of extreme poverty, lower levels of education, poorer nutrition and health, in addition to being victims of crime, violence, and forced displacement (CEPAL, 2014; Freire et al., 2018) Due to its social, ethnic, and geographical diversity, Colombia is therefore an interesting case for the study of obesity trends making it also a potential model for countries with similar characteristics. According to the Nutritional Situation Survey (ENSIN, by its acronym in Spanish), obesity in adults has been increasing in recent years. In 2005, 13.7% of the adult population (men: 8.8% and women: 16.6%) suffered from obesity (ICBF, 2006). In 2010, the figure rose to 16.5% (men: 11.5% and women: 20.1%) (Profamilia, 2011) and by 2015 it stood at 18.7% (men: 14.4% and women: 22.4%) (Ministerio de Salud y Protección Social de Colombia, 2019). The information available at the ethnic dimension indicates that the highest levels of obesity are found in the Afro-Colombian population and lowest in the indigenous population. In 2010, 18.2% of Afro-Colombians were found to suffer from obesity, while the figure for indigenous people was 15.1%, compared to 16.5% for Colombia as a whole (Profamilia, 2011). In 2015, obesity had increased to 22.9% in the case of Afro-Colombians and remained stable among indigenous people (14.9%) as well as for the entire population (18.7%) (Ministerio de Salud y Protección Social de Colombia, 2019). The ENSIN has been used in different studies for food and nutrition analysis in Colombia (Flórez Pregonero et al., 2012; Kasper et al., 2013; Herrán et al., 2016; Vecino-Ortiz & Arroyo-Ariza, 2018). However, descriptive quasi-cohort analyses have not been conducted, even though they have been used in demographic and other fields elsewhere when longitudinal data were not available (Preston & Wang, 2006; Cámara & Spijker, 2010; Suissa, 2015; Waite, 2015; Qian et al., 2017; Pensiero & Green, 2018; García & Martín, 2022). One important advantage of the quasi-cohort approach is that allows cohort trends and differences between age groups to be analysed simultaneously, while standard cross-sectional analyses may mask generation-specific life course experiences related to nutrition (Cámara & Spijker, 2010). The aim of our research is therefore to perform a descriptive quasi-cohort analysis to capture age and cohort trends in BMI for different social and ethnic segments of the population in Colombia. https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 3 Table 1. Sample size of the ENSIN according to subgroup and age group used in the analysis Individuals Households Segments Primary sampling units Survey year 0–64 20–64 0–64 0–64 0–64 2005 156076 89740 17740 1920 209 2010 202253 119677 50670 4987 258 2015 136138 81501 44000 4379 295 Source: ENSIN 2005–2015. Methods Study design and data source National Survey of the Nutritional Situation (ENSIN) The ENSIN survey has been conducted every five years since 2005 and currently the microdata of three editions are publicly available (2005, 2010, and 2015). The ENSIN survey contains a representative sample of the Colombian population aged 0–64 years. It collects data on food security, nutritional status by anthropometry and biochemical indicators, and information on the 24-hour dietary recall and food frequency questionnaires (Ministerio de Salud y Protección Social de Colombia, 2019); however, the last has not been widely disseminated or published. The sample constructed for this survey is probabilistic by multi-stage sampling. In the ENSIN 2005 and 2010, the rural population of Orinoquía and Amazonia, which corresponds to less than 1% of the country’s population, was not included. In turn, the ENSIN only started to include the variable of ethnicity since 2010. The sample sizes according to each sampling unit level are described in Table 1. For our analysis, we used the demographic information (age, sex) of the respondents aged 20– 64 years born between 1940–1944 and 1995–1999 as well as their anthropometric components height and weight to calculate BMI. This age threshold was previously applied by other national and international studies and surveys (Cámara & Spijker, 2010; Briceño et al., 2012; García & Martín, 2022). Specifically, our study covers the period 2005–2015 and includes 214,136 individuals after screening (see Table 2). The respondents were aggregated into one database and subsequently designated into quasi birth-cohorts by subtracting their age from the survey year. Cross-sectional and quasi-cohort approaches: In Colombia, the main data source for data on nutrition is the ENSIN, which is a cross-sectional rather than a panel survey, as it does not follow the same subjects over time. When longitudinal data are absent, one alternative is merge existing cross-sectional data as this enables cohort differences in age-related changes to be analysed (Thomas, 2018). Given the large sample size in each ENSIN survey, we were able to apply a quasi-cohort to study trends in the nutritional indicators weight, height, and BMI. A quasi-cohort approach provides a more nuanced understanding of the complex relationship between sex, age, and nutritional indicators not only over time but also across different birth-cohorts as they age, thereby aiding the construction of more precise evidence-based policy decisions aimed at reducing the prevalence of overweight and obesity and its associated health risks. Variables The anthropometric nutritional status indicator BMI was obtained by taking the ratio of weight in kilograms over height in metres squared. Before calculating the BMI of the respondents, the data https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 4 Paula Andrea Castro-Prieto et al. Table 2. Number of after-screening sample cases used in the analysis by sex, age, and quasi birth-cohort Age group Quasi birth-cohort 20–24 25–29 30–34 35–39 40–44 45–49 50–54 55–59 60–64 Males 1940–1944 1040 1945–1949 1388 1891 1950–1954 1788 2290 2021 1955–1959 2065 2760 2340 743 1960–1964 2409 3358 2939 887 1965–1969 2541 3717 3164 1050 1970–1974 2604 3774 3282 1078 1975–1979 2944 3977 3173 1105 1980–1984 3560 4494 3700 1111 1985–1989 5055 3891 1273 1990–1994 4421 1383 1995–1999 1489 Females 1940–1944 1517 1945–1949 2139 2395 1950–1954 2791 3051 2517 1955–1959 3735 4194 3074 947 1960–1964 3886 4728 3734 1228 1965–1969 4299 5146 4007 1393 1970–1974 4302 5181 4141 1335 1975–1979 4584 5293 4395 1366 1980–1984 5096 5773 4638 1557 1985–1989 6011 4743 1610 1990–1994 5189 1721 1995–1999 1715 Source: ENSIN 2005–2015. Own calculations. were screened on omitted values in height and/or weight (52,275 cases), errors, and unusual values (weight less than 30 kg (35 cases) and height less than 130 cm (116 cases)). This led to the removal of 52,426 cases (see also Appendix Table A1). Finally, additional 1054 cases were also removed because they were in an age-cohort category that contained too few cases to be analysed. In other words, a total of 53,480 cases were not included in the study (20.0% of all cases in the selected age and birth-cohort range). It is also important to note that 68.3% of the cases eliminated were men. This could be due to two reasons. Firstly, in Colombia men are more likely to be employed than women (DANE, 2023) and therefore not at home at the time of the survey. Secondly, taking into account that women are the main caregivers of children under 12 and the primary source of information about their https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 5 children’s nutrition, it was mandatory during the data collection phase to make initial contact with them rather than with men (ICBF, 2015). While BMI is perhaps the most commonly used indicator to assess the prevalence of obesity among the adult population, in part due to its precision, accuracy, and validity, one important criticism is the lack of information on body fat mass and fat location (Nuttall, 2015), characteristics that are known to differ between population groups due to its relation to body shape (Norgan, 1994). However, BMI is widely used by the World Health Organization (2021) and health ministries in different countries (Ministerio de Salud y Protección Social, 2016; Estado Plurinacional de Bolivia, 2017; INEGI, 2018), especially in lower–middle-income countries, because of its low cost, simple acquisition, and comparability. Hence, we analysed 20–64-year-olds according to 5-year age groups, 5-year birth-cohorts, sex (male and female), and for the 2010 and 2015 data, ethnicity, distinguishing between the indigenous, Afro-Colombian, and remaining population (labelled as others, the majority of whom are of mixed ethnicity). We analysed both the continuous values of BMI and the standard BMI categories underweight (levels below 18.5 kg/m2), normal weight (values between 18.5 kg/m2 and 24.9 kg/m2), overweight (levels between 25 and 29.9 kg/m2), and obesity (values above 30 kg/m2) (World Health Organization, 2021). Analysis This was a descriptive study, starting with an analysis of the weight by survey year, sex, and age group to understand its evolution in Colombia between 2005 and 2015. We then analysed weight gain by quasi birth-cohort and sex to discern the age-specific trend within reach quasi birth- cohort. We also analysed the trend in height of the 1940–1944 to 1995–1995 quasi birth-cohorts by ethnicity as weight increases may partly be explained by changes in height across the different generations. Finally, to control for changing height we conducted an analysis of BMI by age group, sex, and survey year, as well as by age group, quasi birth-cohort, and ethnicity. We also performed significance tests on mean weight by quasi birth-cohort and age group. The statistical program R was used to process and perform the descriptive analyses and for the construction of the graphs. The code is available upon request. Results Cross-sectional analysis of average weight by sex and age Between 2005 and 2015, the average weight of Colombian adult men aged 20–64 years increased from 69.7 kg to 73.2 kg (+3.5 kg, equal to an increase of 4.7%). In women, the increase was from 62.3 kg to 65.9 kg (i.e. +3.6 kg and +5.4%, respectively). As Figure 1 shows, for both men and women and all age groups analysed, similar increases were observed between 2005 and 2010 as between 2010 and 2015, whereby increases over the 10-year period were statistically significant at the 95% level, except for the 20–24-year age group in the case of men and the 45–49, 50–54, and 55–59-year age groups in the case of women (see also Appendix Table A2). The highest increases between the first and last survey were observed for the 35–39-year age group among men (+4.6 kg) and 45–49-year age group among women (+2.7 kg). Quasi birth-cohort analysis of average weight by age and sex Figure 2a and 2b shows the evolution in average body weight experienced by people belonging to quasi birth-cohorts at different ages. In men, in almost all age groups each quasi birth-cohort reported an average weight increase over the previous quasi-cohort. For example, in the 50–54- https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 6 Paula Andrea Castro-Prieto et al. year age group between the 1950–1969 quasi-cohorts, weight increased from 70.2 kg to 74.4 kg (+4.2 kg). In women, the results indicate a similar trend to that of men. For example, in the same age and quasi-cohort group, the weight increased from 65.2 to 68.0 kg, indicating an increase of 2.8 kg, that is, 1.4 kg less. The results also clearly show that the slope of average weight changes between two five-year age groups in the same quasi-cohort is steeper in the younger quasi-cohorts. Quasi-cohort analysis of average height by quasi birth-cohort and sex Figure 3 presents the evolution of the average height experienced by people belonging to each quasi birth-cohorts by sex. Successive male and female birth-cohorts saw their average height increase. For instance, between the five-year cohorts 1940–1944 and 1995–1999, the increase in men was 5.6 cm and in women 5.8 cm. It should be noted that the above reflects the national average height of the Colombian population. However, when calculating the average height in Afro-Colombian and indigenous communities, the figure changes considerably. While only aggregated data on ethnicity were available for the 2010 and 2015 surveys, Afro-Colombian men born in 1995–1999 were, on average, 3.5 cm taller than those born in 1945–1949 (171.6 cm vs. 168.1 cm). In the case of women, height increased by 5.2 cm (154.7–159.5 cm). On average, indigenous men born in 1995–1999 were 3.7 cm taller than the 1945–1949 cohort (162.6 cm vs. 158.9 cm). In the case of women, it increased by 4.7 cm (147.3–152.0 cm). Lastly, for the remainder of the Colombian population, men born in 1995–1999 were 5.4 cm taller on average than those born in 1945–1949 (169.8 cm vs. 164.4 cm). In the case of women, height increased by 5.8 cm (157.1–151.3 cm). Table 3 shows the evolution of height by ethnicity by age group for the aggregated samples (2010 and 2015). The results indicate the younger the taller, with Afro-Colombians being the tallest on average whereas indigenous people are the shortest. The remaining group has an average height that is in-between the two ethnic groups. Cross-sectional analysis of BMI by sex and age The average BMI in both males and females also increased between the studied periods (Figure 4a and 4b). In men, this was most evident in the 35–39-year age group (from 25.3 kg/m2 in 2005 to 26.7 kg/m2 in 2015), but all age groups observed notable rises in BMI. Among women, the highest increase was observed in the 55–59-year age group (from 27.8 kg/m2 in 2005 to 28.4 kg/m2 in 2015). When analysing the BMI categories, the proportion of the population with normal weight decreased by 9.9 percentage points between 2005 (47.7%) and 2015 (37.8%), with similar decreases occurring among both sexes. In men, the decrease was 10.7 percentage points (from 53.0% to 42.3%) and in women 10.1 (from 44.3% to 34.2%). In men, the decline was concentrated among ages 35–59 years and in women among 20–44-year-olds (Figure 5) (see also Appendix Table A3). Regarding the proportion of the overweight population, between 2005 and 2015 it increased from 33.8% to 38.9% (i.e. 5.1 percentage points). In men, this was 6.3 percentage points (from 33.6% to 39.9%) and in women 4.2 (from 33.9% to 38.1%). In terms of obesity, between 2005 and 2015 it increased by 6.1 percentage points (from 15.2% to 21.3%). In contrast to overweight, the proportion of obese men was lower compared to women. By 2005, 10.4% of men suffered from obesity, in 2010 12.9%, and in 2015 15.7%. The respective figures for women were 18.2% in 2005, 22% in 2010, and 25.7% in 2015, which translates to an increase of 7.5 percentage points. Similar to men, obesity was highest in the 55–59-year age group, which in this case exceeded 30%. At the ethnic level, information was only available from the ENSIN 2010 and 2015. In Afro- Colombians, normal weight decreased from 44.3% to 36.5%, while overweight increased from 33.1% to 35.8%, and obesity from 19.4% to 26.0%. Overweight and obesity were more prevalent in https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 7 Figure 1. Weight by age group and survey year. Source: ENSIN 2005–2015. Own calculations. Figure 2. Weight by sex, age group, and quasi-cohort. Source: ENSIN 2005–2015. Own calculations. https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 8 Paula Andrea Castro-Prieto et al. Figure 3. Evolution of height according to quasi-cohort. Source: ENSIN 2005–2015. Own calculations. https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 9 Table 3. Mean height by ethnicity and age group Age group Sex Afro-Colombian Indigenous Others Total 20–24 Men 171.5 162.8 169.3 167.9 25–29 170.8 162.9 169.1 167.6 30–34 170.9 162.9 168.7 167.5 35–39 170.4 162.2 168.0 166.9 40–44 170.0 162.8 167.6 166.8 45–49 169.6 161.2 167.0 165.9 50–54 168.8 161.0 166.3 165.4 55–59 168.3 161.5 165.5 165.1 60–64 167.9 160.2 164.2 164.1 Total 169.8 161.9 167.3 166.3 20–24 Women 159.1 151.7 156.8 155.9 25–29 158.6 151.2 156.4 155.4 30–34 158.7 151.2 155.9 155.3 35–39 158.2 150.7 155.5 154.8 40–44 157.9 150.4 155.0 154.4 45–49 157.4 150.4 154.5 154.1 50–54 156.7 149.6 153.7 153.3 55–59 156.6 148.8 152.8 152.7 60–64 155.2 147.8 151.9 151.6 Total 157.6 150.2 154.7 154.2 Source: ENSIN 2010–2015. Own calculations women than in men in 2010: 34.3% of women vs. 31.6% of men were overweight and for obesity it was, respectively, 24.9% and 12.5%. In 2015, however, overweight increased only slightly among women (to 35.3%) but more so among men (36.2%), although sex differences in obesity increased (35.2% vs. 17.8%). Proportions were especially high in the 45–49-year age group (see also Appendix Figure A1). Results for indigenous people indicated a decrease in normal weight by 9.6% from 49.3% to 39.7%, an increase in overweight from 35.7% to 40.2%, and in obesity from 13.5% to 18.8%. Similar to Afro-Colombians, women reported the highest figures for overweight. In 2010, the proportion overweight was 36.9% vs. 34.2% for men, while 18.1% of women and 8.3% of men were obese. In 2015, the proportion overweight increased to 39.6%, while the increase was even greater among men, as they surpassed women in overweight (41.1%). Obesity was still close to twice as prevalent among women (23.7% vs. 12.6%). Regarding age, the highest proportion of obese men in 2015 was found among 60–64-year-olds, while among women it is the group aged 40–44 years (see also Appendix Figure A2). Concerning subjects with another ethnicity (mainly of mixed ancestry), the decrease in normal weight was five percentage points (from 42.8% to 37.8%), while overweight and obesity both increased close to three percentage points (respectively, from 36.4% to 39.1% and from 18.5% to 21.0%). Being overweight was more common in males than in females, but both sexes observed https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 10 Paula Andrea Castro-Prieto et al. Figure 4. BMI by sex, age, and survey year. Source: ENSIN 2005–2015. Own calculations. small increases between the two surveys. In 2010, the proportions were 36.9% vs. 35.9%, respectively, while in 2015 it was 40.2% for men against 38.2% for women. In the case of obesity, it was higher in women than in men (22.1% vs. 13.6% in 2010) and increased slightly during the 5- year period (25.1% vs. 15.8% in 2015). The ages most affected by obesity in 2015 were 55–59-year- olds (both sexes) (see also Appendix Table A4 and Figure 3). https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 11 Figure 5. Nutritional status by sex, age group, and survey year. Source: ENSIN 2005–2015. Own calculations. https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 12 Paula Andrea Castro-Prieto et al. Figure 6. BMI trends by sex, quasi birth-cohort, and age. Source: ENSIN 2005–2015. Own calculations. BMI trends by quasi birth-cohort, age, and sex The increasing height of successive birth-cohorts can only explain part of the increasing weight of the Colombian population between 2005 and 2015 as within the same quasi-cohort the average BMI increased as individuals became older, except for the 1950–1954 and 1945–1949 cohorts. As Figure 6 and Table 4 show, especially the most recent adult cohorts are experiencing sharp increases in BMI. For instance, while 25–29-year-old males born in 1975–1979 had a BMI of 24.2 kg/m2, among 40–44-year-olds of same cohort this equalled 26.8 kg/m2. In the case of women, these age differences in BMI among the same cohort are even greater (24.4 kg/m2 and 28.0 kg/m2). But even the 1955–1959 cohort has seen its BMI increase over age by about 1 kg/m2. Interestingly, if we consider the oldest age of each cohort analysed (which would translate to the most recent period studied), we observe very few age differences in BMI between ages 35 and 64 in the case of men and ages 45 and 59 in the case of women. This is in part because the younger cohorts experienced very large increases in BMI during the 10-year period studied. As this occurred among all but the oldest cohorts, Figure 6 also clearly shows the cohort differences in BMI at each age group. For instance, the average BMI of a male aged 35–39 born in 1965–1969 was 25.3 kg/m2, compared to 26.9 kg/m2 for those of the same age but born in 1980–1984. In the case of women of the same age, cohort differences are less but still substantial (respectively 26.2 kg/m2 and 27.3 kg/m2). BMI trends at the ethnicity level (based on the 2010 and 2015 surveys) indicate that Afro- Colombian men reported an increase of up 1.2 kg/m2 in the 40–44-year age group between the quasi birth-cohorts 1965–1969 and 1975–1979. In Afro-Colombian women, the highest values were found in the 45–49-year age group between the 1960–1964 and 1970–1974 quasi birth- cohorts (+1.3 kg/m2). In indigenous men, the average BMI of 55–59-year-olds born in 1960–1964 was 1.3 kg/m2 higher than in the 1960–1964 quasi birth-cohort. In indigenous women, the largest increase was observed among the 40–44-year age group between the 1965–1969 and 1970–1974 cohorts (+1.2 kg/m2). In other ethnicities (mainly of mixed ethnicity), in men the highest increase in average BMI was found in the 35–39-year age group between the 1970–1974 and 1980–1984 quasi birth-cohorts (+0.8 kg/m2). In women, this was among 60–64-year-olds, where the average BMI of the 1955–1959 cohort was 0.5 kg/m2 higher than that of the 1945–1949 cohort (see Figure 7). https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Table 4. 95% confidence intervals of BMI by sex, age group, and quasi birth-cohort Age group Quasi birth-cohort 20–24 25–29 30–34 35–39 40–44 45–49 50–54 55–59 60–64 Males 1940–1944 25.29–25.74 1945–1949 25.44–25.89 25.49–25.85 1950–1954 25.44–25.83 25.82–26.17 25.85–26.22 1955–1959 25.6–25.95 25.85–26.16 26.12–26.46 26.37–27.01 1960–1964 25.38–25.70 25.98–26.27 26.35–26.66 26.51–27.05 1965–1969 25.19–25.50 26.03–26.29 26.42–26.72 26.46–26.99 1970–1974 24.87–25.18 25.72–25.97 26.34–26.62 26.59–27.10 1975–1979 24.06–24.34 25.48–25.74 26.38–26.68 26.52–27.04 1980–1984 22.92–23.16 24.75–24.99 25.86–26.13 26.67–27.18 1985–1989 23.28–23.48 24.99–25.25 25.52–25.99 1990–1994 23.58–23.81 24.65–25.10 1995–1999 22.83–23.17 Females 1940–1944 27.12–27.65 1945–1949 27.62–28.06 27.79–28.22 Journal of Biosocial Science 1950–1954 27.61–27.98 27.97–28.33 27.84–28.24 1955–1959 27.39–27.70 28.01–28.32 28.3–28.66 28.41–29.06 1960–1964 26.59–26.89 27.63–27.91 28.03–28.35 28.12–28.70 1965–1969 26.07–26.35 27.18–27.45 27.96–28.27 28.14–28.70 1970–1974 25.36–25.63 26.61–26.87 27.68–27.99 28.08–28.62 1975–1979 24.25–24.51 26.06–26.32 27.33–27.63 27.72–28.28 1980–1984 23.08–23.30 24.95–25.19 26.62–26.90 27.05–27.58 1985–1989 23.65–23.86 25.65–25.93 26.53–27.03 1990–1994 24.33–24.59 25.38–25.83 1995–1999 23.86–24.30 13 Source: ENSIN 2005–2015. Own calculations. 14 Paula Andrea Castro-Prieto et al. Discussion Based on data from the National Survey of the Nutritional Situation (ENSIN) from 2005, 2010, and 2015, we were able to observe an increase in height, weight, and BMI across successive generations of working age and born between 1945 and 1999. Specifically, regarding BMI, 38.9% of Colombians aged 20–64 years were overweight in 2015, up from 33.8% in 2005. Regarding obesity, 21.3% of Colombians were obese in 2015 compared to 15.2% in 2005, that is, an increase of more than 40%. Increases were found among adults of successive cohorts at each 5-year age category that was analysed. In the case of men, the largest increase across successive generations occurred at age 35– 39 (+1.6 kg/m2 between the 1965–1969 and 1980–1984 quasi birth-cohorts). In the case of women, the largest increase across successive generations occurred at age 60–64 (1.4 kg/m2 between the 1940–44 and 1955–1959 quasi birth-cohorts). In general, the 20–24-year age group born between 1980–1984 and 1995–1999 observed the lowest levels of BMI, whereby the youngest cohort of men even observed a lower average BMI (−0.4 kg/m2), while for women the average level was still increasing among younger quasi birth-cohorts (+0.8 kg/m2). The evidence provided here goes in line with increases observed in other Colombian studies. For instance, Herrán et al. (2016) noted that overweight changed from 36.4% in 2005 to 37.6% in 2010, and Kasper et al. (2013) indicated that the prevalence of obesity increased from 13.9% in 2005 to 16.4% in 2010. Our study also found that obesity is more prevalent in women than in men and increases with age, but whereby sex differences were still not converging, which is consistent with the literature and places Colombia towards the end of stage one of the obesity transition (Jaacks et al., 2019). In addition to analyzing a more recent period (2015), our study incorporated an ethnic component, which distinguishes it from previous research on overweight and obesity in Colombia. Increases in BMI occurred among all three ethnic groups, although results also indicated that the prevalence of obesity was higher in people of Afro-Colombian communities. This insinuates parallels to black races in other countries such as the USA (Hales et al., 2017; McTigue et al., 2002). Potential factors involved In terms of age-specific increases in (over)weight, the weight of Colombian men stabilises after age 35–39. For instance, 35–39-year-olds have a similar average BMI as 40–44-year-olds and 60–64- year-olds when we consider the most recent cohort. On the other hand, in the case of women, our results showed that among all but the oldest cohorts, average BMI kept increasing with age. This sex difference can, at least partly, be explained by genetic and physiology factors. Within genetics, a meta-analysis of waist-to-hip ratio developed by genome-wide associations studies found that, when adjusted for total fat in more than 200,000 individuals, 20 of 49 loci identified showed sex- specific effects, and 19 of these had stronger effects in women (Zore et al., 2018). Physiologically, women have a higher percentage of body fat and a lower percentage of fat-free mass than men (Fu, 2019) as well as a low prevalence of exclusive breastfeeding (Victora et al., 2016) which is associated with postpartum weight loss (da Silva et al., 2015). In addition, after menopause, women accumulate fat in subcutaneous area facilitated due to a decrease oestrogen, which makes them more prone to central obesity than men (Fu, 2019). Moreover, there are also other potential factors involved in the increase of overweight and obesity in Colombian adults, in particular dietary, nutritional, historical, social, and political factors. Among the dietary factors is calorie intake, which has increased from an average of 1950 calories in 1960 (Bourges et al., 2000) to 2117 calories in 2015 (Herrán et al., 2021). Similarly, ultra-processed foods, especially junk food (chatarra), increasingly form part of the diet of Colombians (Bejarano-Roncancio et al., 2015; García & Contreras, 2022). https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 15 Figure 7 BMI trends by sex, quasi birth-cohort, age, and ethnicity. Source: ENSIN 2005–2015. Own calculations. Research indicates that in some indigenous communities the diet is based on carbohydrates due to food scarcity (Hernández et al., 2014). For example, the Guambiana community located in the southwest of Colombia bases its diet on preparations based on corn, ullucos (type of tubercle), and beans (Molano & Molano, 2018). A study that determined traditional foods in indigenous and Afro-Colombian communities in ten Colombian departments found that of the 92 foods reported, 39 came from plants and only 18 were classified as meat (Rivas et al., 2010). Some approaches have quantified the level of some macronutrients and micronutrients in the diet, reporting low levels of protein and vitamin A adequacy, such as the indigenous Tules in Antioquia (Carmona et al., 2005). In other cases, qualitative research has described how indigenous people have been immersed in the promotion of industrialised foods through the media, which affects their food consumption (Farfán et al., 2019). Regarding nutritional factors, the so-called double nutritional burden, defined as the manifestation of undernutrition and overweight simultaneously (Popkin et al., 2020), can occur at different levels: population, household, and even on an individual level (Shrimpton & Rokx, 2012). In a Colombian study conducted in 2010, it was found that this double burden occurred in 4.6% of households, that is, the coexistence of chronic malnutrition in a child under five years of age and an overweight mother. The prevalence increased to 4.9% in indigenous communities (Rueda, 2019). In 2015, in rural Colombia, 7.8% of households were double burdened (Sansón-Rosas et al., 2021). https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 16 Paula Andrea Castro-Prieto et al. Previous studies have also linked physical inactivity and sedentary lifestyles to obesity in Colombia, primarily related to watching television (Lear et al., 2014) and the use of private motor vehicles, especially motorcycles, where time spent riding a motorcycle per week could exceed 150 minutes (Parra et al., 2009; Flórez Pregonero et al., 2012). Regarding the latter, one study suggested that the increased use of motorcycles is due to vehicle restrictions known as ‘pico y placa’ and congested traffic (Niño-Muñoz & Morera-Ubaque, 2018). In addition, one of the best explanations for motorbikes and cars was per capita income, car prices (Mercado Díaz, 2015), and the lack of safety in public transport systems (Kash, 2019). In the case of Colombia, there are also historical, social, and geographical factors to consider. This includes forced displacement, which caused obstacles for families to obtain food, a longing for some foods and preparations usually consumed (Ruiz Pascua, 2015), as well as an increase in the consumption of calorie-dense foods such as flour, panela water (type of sugar), tubers, soups, and sausages (Puentes & Bejarano, 2020). In Girón, Santander, a study reported that the forcibly displaced families ate twice as much corn flour and a third additional of rice and panela (Prada Gómez et al., 2008). These difficulties are exacerbated in ethnic minority populations because the geographical location of many indigenous communities coincides with areas where the armed conflict takes place (Centro Nacional de Memoria Histórica, 2018). As dietary patterns vary greatly across regions, reflecting local food traditions and availability and the influence of globalisation, future research should look at regional BMI patterns. Economic and political factors also play a role in the nutritional status of the Colombian population. In economic terms, the number of informally employed people, that is, those who do not have social security and no employment relationship with the employer, was 57.9% between November 2022 and January 2023, being higher in men than in women (60.1% vs 54.6%) (DANE, 2023), that could have an impact on the food and nutrition sphere. On political factors, while most packaged foods available in Bogotá are eligible for front-of-package warning labels, this has not yet been done (Mora-Plazas et al., 2019). Regarding the type of labelling, one study showed that respondents liked and trusted those of an octagonal shape the most (Taillie et al., 2020). Evidence also suggests that there has only been a minimal reduction in caloric density and sugar in food and beverages in Colombia (Lowery et al., 2020). The implementation of regulation defined in 2022 therefore needs to be accelerated (Ministerio de Salud y Protección Social, 2022). It is also worth mentioning that the Colombia government had made continuous efforts to prevent obesity, for instance through their 10-year public health plan (2012–2021). This plan contains a food and nutrition security dimension that includes a series of actions to reduce overweight and obesity (Ministerio de Salud y Protección Social, 2012). This policy is currently being evaluated and the plan for the next period is under construction. In 2009, a law on obesity was also passed, defining this disease as a public health priority and indicating that the state through the Ministries of health, culture, education, transport, environment, agriculture, and rural development will promote policies related to food and nutritional security and physical activity that promote safe environments for the development of the same (Ministerio de Educación Nacional, 2009). Similarly, the Colombian Institute for Family Welfare (Instituto Colombiano de Bienestar Familiar (ICBF) in Spanish) has developed food guides for pregnant and breastfeeding mothers, infants, children under 2 years of age, and the general population. These guides contain a rigorous study of energy and nutrient needs and are based on regional tastes, knowledge, and food culture. They also contain technical and community outreach material that facilitates the process (ICBF, 2018b, 2018a). Despite these advances, in Colombia there are still problems concerning the unification of criteria on nutrition among professionals and effective mechanisms for the dissemination of information. Moreover, free trade agreements still promote the entry of foodstuffs into Colombia that are high in sugars, saturated fats, and sodium (Bejarano-Roncancio et al., 2015) what restricts compliance with the country’s food sovereignty policy that promotes ‘the right of peoples to nutritious and culturally appropriate, accessible, sustainable and ecologically https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 17 produced food, and their right to decide their food and production system’ (Clacso, 2006). At the same time, the problem of seed hoarding and commodification, through genetic engineering and intellectual property rights by biotechnology transnationals (Gutiérrez, 2015), has affected the food and nutritional sphere in Colombia. Strengths and limitations of the study and ideas for future research One important strength of this study is that the ENSIN survey uses an interdisciplinary team of nutritionists, nurses, and bacteriologists during data collection. This minimises biases and errors, particularly in the taking of anthropometric measurements of weight and height required for the calculation of BMI. Due to the technical rigor applied by the survey, there is no issue of social desirability bias (i.e., underestimation of weight and overestimation of height) that is common in BMI studies that rely on self-reported measures (Gorber et al., 2007). While our research provides insights into the basic demographic characteristics of changes in average BMI levels in the Colombian population between 2005 and 2015, there are some limitations in the use of anthropometrics for the study of trends based on cross-sectional survey data. One such limitation is the fact that BMI is only an approximate indicator of obesity, as (age, sex, and race specific) fat level, skinfold thickness, or body shape are not controlled for, although BMI is known to be highly associated with fatness (Norgan, 1994; Tsai et al., 2014). Another limitation is selection as the proportion of a cohort who already died from either underweight or obesity is unknown (Cámara & Spijker, 2010). Finally, the results suggest the need to continue carrying out synthetic cohort studies based on cross-sectional surveys such as the ENSIN in Colombia until there are longitudinal studies with repeated measurements that allow the weight of the same individuals to be analysed over time. Especially in the context of the COVID-19 pandemic, since during confinement an increased intake of cereals, eggs, fats, sugars, and sugar cane was observed (Pertuz-Cruz et al., 2021), suggesting a possible increase in the rates of overweight and obesity in Colombia. Acknowledgements. The results presented in this paper are part of the ongoing Doctoral Dissertation of Paula Andrea Castro-Prieto to obtain the degree of Doctor in Demography from the Universitat Autònoma de Barcelona (UAB), Centre d’Estudis Demogràfics (CED-CERCA). The study supported with funding from the DEMOS_2021 contract through the R&D project “Salud de las personas de edad avanzada el análisis de la comorbilidad las múltiples causas de muerte y las desigualdades de género y socioeconómicas en la salud” (COMORHEALTHSES PID2020-113934RB-I00) financed by the Spanish Ministry of Science and Innovation (PI Jeroen Spijker) and also by the European Research Council (ERC-2019-COG agreement No 864616, HEALIN). Competing interests. The authors declare no conflicts of interest. Funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Ethical approval. The study complies with the definition in the Declaration of Helsinki regarding the development of research that involves human beings. For this research, only a secondary analysis of information from data systems was carried out; therefore, the risk of the research was minimal. References Bejarano JJ, Gamboa EM, Aya DH and Parra DC (2015) Los alimentos y bebidas ultra-procesados que ingresan a Colombia por el tratado de libre comercio: ¿influirán en el peso de los colombianos? Revista Chilena de Nutrición 42(4), 409–413. doi: 10.4067/S0717-75182015000400014 Bourges H, Bengoa JM and O’Donell AM (2000) Historia de la Nutrición en América Latina. óéhttps://www.slan.org.ve/ libros/HistoriasdelaNutriciónenAméricaLatina.pdf (accessed 16 February 2023). Bozkurt B, Aguilar D, Deswal A, Dunbar SB, Francis GS, et al. (2016) Contributory risk and management of comorbidities of hypertension, obesity, diabetes mellitus, hyperlipidemia, and metabolic syndrome in chronic heart failure: a scientific statement from the American Heart Association. Circulation 134(23), e535–e578. doi: 10.1161/CIR.0000000000000450 Briceño G, Durán P, Colón E, Line D, Merker A, et al. (2012) Protocolo del estudio para establecer estándares normativos de crecimiento de niños colombianos sanos. Pediatría 45(4), 235–242. doi: 10.1016/s0120-4912(15)30021-5 https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 18 Paula Andrea Castro-Prieto et al. Broughton DE and Moley KH (2017) Obesity and female infertility: potential mediators of obesity’s impact. Fertility and Sterility 107(4), 840–847. doi: 10.1016/J.FERTNSTERT.2017.01.017 Cámara AD and Spijker JJ (2010) Super size Spain? A cross-sectional and quasi-cohort trend analysis of adult overweight and obesity in an accelerated transition country. Journal of Biosocial Science 42(3), 377–393. doi: 10.1017/S0021932009990629 Carmona J, Correa A and Alcaraz G (2005) Población, alimentación y estado nutricional entre los tules (kunas) del resguardo Caimán Nuevo (Turbo y Necoclí; Antioquia, Colombia), 2003-2004*. Iatrea 18(3), 259–278. Centro Nacional de Memoria Histórica (2018) Regiones y conflicto armado (CNMH). https://centrodememoriahistorica.gov. co/regiones-y-conflicto-armado-balance-de-la-contribucion-del-cnmh-al-esclarecimiento-historico/ (accessed 16 February 2023). CEPAL (2014) Los pueblos índigenas en America Latina. Avances en el último decenio y retos pendientes para la garantía de sus derechos. In Naciones unidas (Vol. 1). https://bit.ly/2QbS1DN (accessed 16 February 2023). Clacso (2006) Declaración de Nyéléni Foro Mundial por la Soberanía Alimentaria Nyéléni, Selingue, Malí, 23 al 27 de febrero de 2007. http://biblioteca.clacso.edu.ar/ar/libros/osal/osal21/Nyeleni.pdf (accessed 16 February 2023). da Silva MC, Oliveira AM, Pinheiro SM, de Oliveira LP and da Cruz TR (2015) Breastfeeding and maternal weight changes during 24 months post-partum: a cohort study. Maternal and Child Nutrition 11(4). doi: 10.1111/mcn.12071 DANE (2023) Gran Encuesta Integrada de Hogares. Mercado laboral según sexo. https://www.dane.gov.co/index.php/ estadisticas-por-tema/mercado-laboral/segun-sexo (accessed 16 February 2023). DANE (2023) Ocupación informal. https://www.dane.gov.co/files/investigaciones/boletines/ech/ech/Nueva_medicion_ informalidad.pdf (accessed 21 March 2023). Estado Plurinacional de Bolivia (2017) Manual Integral de Antropometria Serie: Documentos Técnico Normativos. www. minsalud.gob.bo (accessed 16 February 2023). Farfán JC, Torres DA, Gómez MN and Tamayo MP (2019) Condiciones de seguridad alimentaria en una comunidad indígena de Colombia. Physis: Revista de Saúde Coletiva 28(4), 1–16. doi: 10.1590/S0103-73312018280405 Flórez PA, Gómez LF, Parra DC, Cohen DD, Arango PC, et al. (2012) Time spent traveling in motor vehicles and its association with overweight and abdominal obesity in Colombian adults who do not own a car. Preventive Medicine 54(6), 402–404. doi: 10.1016/j.ypmed.2012.04.002 Freire G, Bonilla DC, Schwartz OS, Soler LJ and Carbonari F (2018) Afrodescendientes en Latinoamérica. http://hdl.handle. net/10986/30201 (accessed 16 February 2023). Fu Q (2019) Sex differences in sympathetic activity in obesity and its related hypertension. Annals of the New York Academy of Sciences 1454(1), 1–11. doi: 10.1111/nyas.14095 García GJ and Martín CE (2022) A reversal in the obesity epidemic? A quasi-cohort and gender-oriented analysis in Spain. Demographic Research 46, 273–290. doi: 10.4054/DEMRES.2022.46.10 García LM and Contreras A (2022) A call for implementation of the law against processed foods during the pandemic times in Colombia. Biomedica 42(2), 14–18. doi: 10.7705/biomedica.6303 Gorber SC, Tremblay M, Moher D and Gorber B (2007) A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review. Obesity Reviews 8(4), 307–326. doi: 10.1111/J.1467-789X.2007.00347.X Großschädl F and Stronegger WJ (2021) Regional and social disparities for obesity among Austrian adults: representative long-term trends from 1973–2014 Regionale und soziale Ungleichheiten zu Adipositas bei Erwachsenen in Österreich: repräsentative Langzeittrends data source and sample. Gesundheitswesen 83(1), 59–65. doi: 10.1055/a-0965-6840 Gutiérrez L (2015) Soberanía alimentaria. La Red de Semillas Libres de Colombia. Contextos 4(13). https://scholar.google.es/ scholar?q=Guti%C3%A9rrez+L+(2015)+Soberan%C3%ADa+alimentaria.+La+Red+de+Semillas+Libres+de+Colombia.+ Contextos,+4(13).&hl=es&as_sdt=0&as_vis=1&oi=scholart Hales CM, Carroll MD, Fryar CD and Ogden CL (2017) Prevalence of Obesity and Severe Obesity among Adults: United States, 2017–2018 Key findings Data from the National Health and Nutrition Examination Survey. https://www.cdc.gov/ nchs/products/index.htm (accessed 16 February 2023). Hernández A, Velasco C, Oviedo M.P, Mantilla B and Flórez N (2014) Prácticas de alimentación de la población indígena del departamento de Chocó. Revista Ustasalud 13(2), 106–111. Herrán OF, Gamboa DE and Zea MDP (2021) Energy and protein intake in the Colombian population: results of the 2015 ENSIN population survey. Journal of Nutritional Science 10(e11), 1–10. doi: 10.1017/JNS.2021.2 Herrán OF, Patiño GA and Del Castillo SE (2016) La transición alimentaria y el exceso de peso en adultos evaluados con base en la encuesta de la situación nutricional en Colombia, 2010. Biomedica 36(1), 109–120. doi: 10.7705/biomedica.v36i1.2579 INEGI, Instituto Nacional de Salud Pública, & Secretaría de Salud (2018) Encuesta Nacional de Salud y Nutrición 2018 Presentación de resultados. https://ensanut.insp.mx/encuestas/ensanut2018/doctos/informes/ensanut_2018_presentacion_ resultados.pdf (accesed 16 February 2023). Instituto Colombiano de Bienestar Familiar (2006) Encuesta Nacional de la Situación Nutricional. https://www.icbf.gov.co/ sites/default/files/libro_2005.pdf (accessed 16 February 2023). Instituto Colombiano de Bienestar Familiar (2018a) Guías Alimentarias Basadas en Alimentos para la Población Colombiana Mayor de 2 Años | Portal ICBF – Instituto Colombiano de Bienestar Familiar ICBF. https://www.icbf.gov.co/ guias-alimentarias-basadas-en-alimentos-para-la-poblacion-colombiana-mayor-de-2-anos-0 (accessed 16 February 2023). https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 19 Instituto Colombiano de Bienestar Familiar (2018b) Guías Alimentarias basadas en Alimentos para mujeres gestantes, madres en período de lactancia y niños y niñas menores de 2 años para Colombia | Portal ICBF – Instituto Colombiano de Bienestar Familiar ICBF. https://www.icbf.gov.co/guias-alimentarias-basadas-en-alimentos-para-mujeres-gestantes- madres-en-periodo-de-lactancia-y-2 (accessed 16 February 2023). Instituto Colombiano de Bienestar Familiar, Ministerio de Salud y Protección Social, Instituto Nacional de Salud and Departamento de Prosperidad Social (2015) Encuesta Nacional de la Situación Nutricional – ENSIN 2015. Documento metodológico. https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VS/ED/GCFI/documento- metodologico-ensin-2015.pdf (accessed 16 February 2023). Instituto Nacional de Estadística y Geografía, Instituto Nacional de Salud Pública, Secretaría de Salud (2023) Encuesta Nacional de Salud y Nutrición 2018 Presentación de resultados. https://ensanut.insp.mx/encuestas/ensanut2018/doctos/ informes/ensanut_2018_presentacion_resultados.pdf (accessed 16 February 2023). Iyengar NM, Gucalp A, Dannenberg AJ and Hudis CA (2016) Obesity and cancer mechanisms: tumor microenvironment and inflammation. Journal of Clinical Oncology 34(35), 4270–4276. doi: 10.1200/JCO.2016.67.4283 Jaacks LM, Vandevijvere S, Pan A, McGowan CJ, Wallace C, et al. (2019) The obesity transition: stages of the global epidemic. The Lancet Diabetes & Endocrinology 7(3), 231–240. doi: 10.1016/S2213-8587(19)30026-9 Jiwani SS, Carrillo LR, Hernández VA, Barrientos GT, Basto AA, et al. (2019) The shift of obesity burden by socioeconomic status between 1998 and 2017 in Latin America and the Caribbean: a cross-sectional series study. The Lancet Global Health 7(12), e1644–e1654. doi: 10.1016/S2214-109X(19)30421-8 Kash G (2019) Always on the defensive: the effects of transit sexual assault on travel behavior and experience in Colombia and Bolivia. Journal of Transport and Health 13, 234–246. doi: 10.1016/j.jth.2019.04.004 Kasper NM, Herrán OF and Villamor E (2013) Obesity prevalence in Colombian adults is increasing fastest in lower socio- economic status groups and urban residents: results from two nationally representative surveys. Public Health Nutrition 17(11), 2398–2406. doi: 10.1017/S1368980013003418 Lear SA, Teo K, Gasevic D, Zhang X, Poirier PP, et al. (2014). The association between ownership of common household devices and obesity and diabetes in high, middle and low income countries. Canadian Medical Association Journal 186(4), 258–266. doi: 10.1503/cmaj.131090 Lowery CM, Mora-Plazas M, Gómez LF, Popkin B and Taillie LS (2020) Reformulation of packaged foods and beverages in the Colombian food supply. Nutrients 12(11), 3260. doi: 10.3390/nu12113260 McTigue KM, Garrett JM and Popkin B (2002) The natural history of the development of obesity in a cohort of young U.S. adults between 1981 and 1998. Annals of Internal Medicine 136(12), 857–864. doi: 10.7326/0003-4819-136-12-200206180- 00006 Mercado DM (2015) Modelos alternativos para la estimación de la tasa de motorización en Colombia. https://manglar. uninorte.edu.co/handle/10584/9213 (accessed 21th March 2023). Ministerio de Educación Nacional (2009) Ley 1355 de octubre 14 de 2009. https://www.mineducacion.gov.co/portal/ normativa/Leyes/381525:Ley-1355-de-octubre-14-de-2009 (accessed 16 February 2023). Ministerio de Salud y Protección Social (2012) Plan Decenal de Salud Pública. https://www.minsalud.gov.co/PlanDecenal/ Paginas/home2013.aspx (accessed 16 February 2023). Ministerio de Salud y Protección Social (2016) Resolución 2465 de 2016. https://www.icbf.gov.co/sites/default/files/ resolucion_no._2465_del_14_de_junio_de_2016.pdf (accessed 16 February 2023). Ministerio de Salud y Protección Social (2022) MinSalud expide Resolución 2492_2022 sobre etiquetado nutricional y frontal. https://www.minsalud.gov.co/Paginas/MinSalud-expide-Resolucion-2492-2022-sobre-etiquetado-nutricional-y-frontal. aspx (accessed 16 February 2023). Ministerio de Salud y Protección Social de Colombia, Instituto Colombiano de Bienestar Familiar, Instituto Nacional de Salud (2019) Encuesta Nacional de la Situación Nutricional-ENSIN, 2015. Documento metodológico. https://www.minsalud. gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VS/ED/GCFI/documento-metodologico-ensin-2015.pdf (accessed 16 February 2023). Molano TN and Molano TD (2018) Cosmovisión de salud y alimentación en la cultura Guambiana. Worldview of Health and Food in the Guambiana Culture 20(1), 16–25. doi: 10.22267/rus.182001.105 Mora-Plazas M, Gómez LF, Miles DR, Parra DC and Taillie LS (2019) Nutrition quality of packaged foods in Bogotá, Colombia: a comparison of two nutrient profile models. Nutrients 11(5), 1011. doi: 10.3390/nu11051011 Niño MD and Morera UN (2018) Percepción de la pobreza en Colombia en los años 2003 y 2016. Clío América 12(23), 25–38. doi: 10.21676/23897848.2614 Norgan NG (1994) Population differences in body composition in relation to the body mass index. European Journal of Clinical Nutrition 48(3), S10–S25. Nuttall FQ (2015) Body mass index: obesity, BMI, and health: a critical review. Nutrition Today 50(3), 117–128. doi: 10.1097/ NT.0000000000000092 Parra DC, Lobelo F, Gómez LF, Rutt C, Schmid T, et al. (2009) Household motor vehicle use and weight status among Colombian adults: are we driving our way towards obesity? Preventive Medicine 49(2–3), 179–183. doi: 10.1016/j.ypmed. 2009.07.010 https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 20 Paula Andrea Castro-Prieto et al. Pensiero N and Green A (2018) The effects of post-compulsory education and training systems on literacy and numeracy skills: a comparative analysis using PISA 2000 and the 2011 survey of adult skills. European Journal of Education 53(2), 238–253. doi: 10.1111/EJED.12268 Pertuz CS, Molina ME, Rodríguez PC, Guerra HE, Cobos de Rangel OP, et al. (2021) Exploring dietary behavior changes due to the COVID-19 confinement in Colombia: a national and regional survey study. Frontiers in Nutrition 8(644800), 1–16. doi: 10.3389/fnut.2021.644800 Popkin B, Corvalan C and Grummer SL (2020) Dynamics of the double burden of malnutrition and the changing nutrition reality. The Lancet 395(10217), 65–74. doi: 10.1016/S0140-6736(19)32497-3 Prada GG, Herrán FO and Cárdenas RO (2008) Patrón alimentario y acceso a los alimentos en familias desplazadas en el municipio de Girón, Santander, Colombia. Revista Panamericana de Salud Publica/Pan American Journal of Public Health 23(4), 257–263. doi: 10.1590/S1020-49892008000400005 Preston SH and Wang H (2006) Sex mortality differences in the United States: the role of cohort smoking patterns. Demography 43(4), 631–646. doi: 10.1353/dem.2006.0037 Profamilia, Instituto Nacional de Salud, Instituto Colombiano de Bienestar Familiar and Ministerio de la Protección Social (2011) Encuesta Nacional de la Situación Nutricional en Colombia 2010. https://www.icbf.gov.co/sites/default/files/ resumenfi.pdf (accessed 16 February 2023). Puentes M and Bejarano A (2020) Prácticas de consumo alimentario de familias desplazadas por el conflicto armado, asentadas en Bosa, Bogotá – Dialnet. Diversitas: Perspectivas En Psicología 16(1), 143–155. Qian CJ, Coulombe J, Suissa S and Ernst P (2017) Pneumonia risk in asthma patients using inhaled corticosteroids: a quasi- cohort study. British Journal of Clinical Pharmacology 83(9), 2077–2086. doi: 10.1111/bcp.13295 Rivas X, Pazos S, Castillo S and Pachón H (2010) Alimentos autóctonos de las comunidades indígenas y afrodescendientes de Colombia. Archivos Latinomericanos de Nutrición 60(3). https://www.alanrevista.org/ediciones/2010/3/art-1/ (accesed 5 June 2023). Rueda YP (2019) Aproximación a los determinantes de la doble carga nutricional en hogares. https://repositorio.uniandes. edu.co/handle/1992/34121 (accessed 16 February 2023). Ruiz PM (2015) Alimentando la vida frente al desplazamiento forzado: memoria y cocina como propuestas de paz* Nurturing life to face forced displacement: memories and kitchen as peace proposals. Eleuthera 12, 112–130. doi: 10.17151/eleu.2015. 12.6 Sansón RA, Bernal RJ, Kubow S, Suarez MA and Melgar QH (2021) Food insecurity and the double burden of malnutrition in Colombian rural households. Public Health Nutrition 24(14), 4417–4429. doi: 10.1017/S1368980021002895 Shrimpton R and Rokx C (2012) The Double Burden of Malnutrition: A Review of Global Evidence. https://openknowledge. worldbank.org/handle/10986/27417 (accessed 16 February 2023). Suissa S (2015) The quasi-cohort approach in pharmacoepidemiology: upgrading the nested case-control. Epidemiology 26(2), 242–246. doi: 10.1097/EDE.0000000000000221 Taillie LS, Hall MG, Gómez LF, Higgins I, Bercholz M, et al. (2020) Designing an effective front-of-package warning label for food and drinks high in added sugar, sodium, or saturated fat in Colombia: an online experiment. Nutrients 12(10), 3124. doi: 10.3390/nu12103124 Thomas RK (2018). Concepts, Methods and Practical Applications in Applied Demography. https://link.springer.com/book/10. 1007/978-3-319-65439-3 (accessed 16 February 2023). Tod E, Bromley C, Millard AD, Boyd A, Mackie P and McCartney G (2017) Obesity in Scotland: a persistent inequality. International Journal for Equity in Health 16(1), 1–13. doi: 10.1186/s12939-017-0599-6 Tremmel M, Gerdtham UG, Nilsson PM and Saha S (2017) Economic burden of obesity: a systematic literature review. International Journal of Environmental Research and Public Health 14(4), 1–18. doi: 10.3390/ijerph14040435 Tsai EW, Perng W, Mora-Plazas M, Marín C, Baylin A, et al. (2014) Accuracy of self-reported weight and height in women from Bogotá, Colombia. Annals of Human Biology 41(5), 473–476. doi: 10.3109/03014460.2013.856939 Vecino O and Arroyo A (2018) A tax on sugar sweetened beverages in Colombia: estimating the impact on overweight and obesity prevalence across socio economic levels. Social Science and Medicine 209(40), 111–116. doi: 10.1016/j.socscimed. 2018.05.043 Victora CG, Bahl R, Barros AJ, França GV, Horton S, et al. (2016) Breastfeeding in the 21st century: epidemiology, mechanisms, and lifelong effect. The Lancet 387 (10017), 475–490. doi: 10.1016/S0140-6736(15)01024-7 Waite S (2015) Does it get better? A quasi-cohort analysis of sexual minority wage gaps. Social Science Research 54, 113–130. doi: 10.1016/J.SSRESEARCH.2015.06.024 World Health Organization (2021) Obesity and Overweight. https://www.who.int/news-room/fact-sheets/detail/obesity-and- overweight (accessed 16 February 2023). Zore T, Palafox M and Reue K (2018) Sex differences in obesity, lipid metabolism, and inflammation—a role for the sex chromosomes? Molecular Metabolism 15, 35–44. doi: 10.1016/j.molmet.2018.04.003 https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 21 Appendix A Figure A1. Nutritional status by sex, age group, and survey year of Afro-Colombians. Source: ENSIN 2010–2015. Own calculations. Figure A2. Nutritional status by sex, age group, and survey year of indigenous people. Source: ENSIN 2010–2015. Own calculations. https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 22 Paula Andrea Castro-Prieto et al. Figure A3. Nutritional status by sex, age group, and survey year of others ethnicities. Source: ENSIN 2010–2015. Own calculations. https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 23 Table A1. Missing values Missing values Missing val- Weight less Height less in weight ues in height than 30 kg than 130 cm Total Survey year Total cases Age group Men Women Men Women Men Women Men Women missing 2005 80006 Total population 20–24 2645 1040 1 0 1 3 5 2 3697 25–29 2302 866 4 5 0 4 0 6 3187 30–34 2031 694 6 3 0 4 2 5 2745 35–39 1873 682 4 9 0 3 2 3 2576 40–44 1670 666 6 6 0 0 1 0 2349 45–49 1368 649 7 7 0 1 1 2 2035 50–54 1168 515 4 4 0 1 0 4 1696 55–59 788 403 0 7 0 1 0 2 1201 60–64 783 556 1 6 0 0 1 2 1349 Total 14628 6071 33 47 1 17 12 26 20835 2010 106125 Afro-Colombians 20–24 178 122 0 0 0 0 0 1 301 25–29 192 92 0 0 0 0 0 0 284 30–34 140 64 0 0 0 0 1 0 205 35–39 136 61 0 0 0 0 0 1 198 40–44 155 59 1 0 0 0 0 1 216 45–49 122 45 0 1 1 0 0 1 170 50–54 80 47 0 0 0 0 0 0 127 55–59 74 45 0 0 0 0 0 1 120 60–64 51 29 0 0 0 0 0 0 80 Total 1128 564 1 1 1 0 1 5 1701 Indigenous 20–24 176 96 0 0 0 0 0 0 272 25–29 187 78 0 0 0 0 1 0 266 30–34 159 47 0 0 0 1 1 1 209 35–39 95 50 0 0 0 0 1 0 146 40–44 108 40 0 1 0 0 0 0 149 45–49 106 46 0 0 0 0 0 0 152 50–54 81 44 0 0 0 0 0 1 126 55–59 38 33 0 0 0 0 0 0 71 60–64 40 31 0 0 0 0 0 0 71 Total 990 465 0 1 0 1 3 2 1462 (Continued) https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 24 Paula Andrea Castro-Prieto et al. Table A1. (Continued ) Missing values Missing val- Weight less Height less in weight ues in height than 30 kg than 130 cm Total Survey year Total cases Age group Men Women Men Women Men Women Men Women missing Others 20–24 1842 1054 3 0 1 0 1 0 2901 25–29 1862 879 1 1 1 1 2 0 2747 30–34 1645 755 0 1 0 2 0 3 2406 35–39 1456 636 2 4 0 0 3 1 2102 40–44 1450 608 2 2 0 1 0 2 2065 45–49 1326 582 0 1 0 1 2 1 1913 50–54 1067 572 2 2 0 0 0 1 1644 55–59 826 462 1 2 0 0 1 2 1294 60–64 572 389 1 2 0 0 0 3 967 Total 12046 5937 12 15 2 5 9 13 18039 2015 81485 Afro-Colombians 20–24 100 33 1 0 0 0 0 1 135 25–29 77 37 1 0 0 0 0 1 116 30–34 73 25 1 0 0 0 0 1 100 35–39 63 34 1 0 0 0 0 0 98 40–44 54 31 0 0 0 0 0 0 85 45–49 47 24 1 2 0 0 0 0 74 50–54 41 25 0 0 0 0 0 0 66 55–59 44 21 0 0 0 0 1 0 66 60–64 21 21 0 0 0 0 0 0 42 Total 520 251 5 2 0 0 1 3 782 Indigenous 20–24 79 26 1 0 0 0 0 0 106 25–29 61 22 0 1 0 0 0 0 84 30–34 50 24 0 0 0 0 0 0 74 35–39 57 17 0 0 0 0 1 0 75 40–44 47 16 0 0 0 0 0 0 63 45–49 37 21 0 0 0 0 0 1 59 50–54 22 20 0 0 0 0 0 0 42 55–59 27 13 0 0 0 0 0 0 40 60–64 15 8 0 1 0 0 0 0 24 Total 395 167 1 2 0 0 1 1 567 (Continued) https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Journal of Biosocial Science 25 Table A1. (Continued ) Missing values Missing val- Weight less Height less in weight ues in height than 30 kg than 130 cm Total Survey year Total cases Age group Men Women Men Women Men Women Men Women missing Others 20–24 916 434 12 1 0 2 3 4 1372 25–29 943 404 6 3 0 0 1 2 1359 30–34 792 319 2 1 1 3 2 5 1125 35–39 735 285 0 2 1 0 2 2 1027 40–44 687 276 1 2 0 0 1 0 967 45–49 591 311 13 3 0 0 6 2 926 50–54 604 289 2 5 0 0 1 2 903 55–59 499 282 3 2 0 0 0 2 788 60–64 337 227 2 2 0 1 1 3 573 Total 6104 2827 41 21 2 6 17 22 9040 Total 267616 52426 https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press 26 Paula Andrea Castro-Prieto et al. Table A2. Cross-sectional analysis of average weight by sex and age Sex and Age group survey year 20–24 25–29 30–34 35–39 40–44 45–49 50–54 55–59 60–64 Men 2005 65.18– 68.06– 70.13– 70.74– 70.93– 70.79– 69.86– 69.39– 67.80– 65.90 68.90 71.06 71.70 71.90 71.87 70.99 70.68 69.26 Men 2010 66.34– 70.20– 72.22– 72.45– 73.04– 72.39– 71.32– 70.51– 68.94– 66.95 70.93 73.00 73.24 73.81 73.21 72.24 71.53 70.00 Men 2015 67.53– 71.99– 73.98– 75.40– 74.61– 74.32– 73.53– 72.68– 71.06– 68.24 72.82 74.87 76.30 75.50 75.27 74.45 73.69 72.15 Women 56.04– 58.75– 61.12– 62.67– 63.43– 64.78– 64.79– 64.11– 61.91– 2005 56.58 59.37 61.81 63.37 64.19 65.55 65.68 65.16 63.12 Women 57.86– 60.92– 63.09– 64.15– 65.23– 65.83– 65.96– 65.38– 63.85– 2010 58.39 61.50 63.72 64.80 65.88 66.51 66.70 66.24 64.84 Women 60.38– 63.33– 65.58– 66.64– 67.38– 67.55– 67.02– 66.52– 65.50– 2015 61.03 64.04 66.32 67.40 68.19 68.33 67.82 67.39 66.42 Source: ENSIN 2005–2015. Own calculations. Table A3. Nutritional status (%) by sex and, survey year Men Women Total Survey year Nutritional status n % n % n % 2005 Underweight 642 2.85 1219 3.43 1861 3.20 Normal weight 11945 53.07 15771 44.33 27716 47.72 Overweight 7579 33.68 12082 33.96 19661 33.85 Obese 2340 10.40 6502 18.28 8842 15.22 Total 22506 100.00 35574 100.00 58080 100.00 2010 Underweight 688 1.87 1242 2.58 1930 2.27 Normal weight 18009 49.05 19035 39.49 37044 43.62 Overweight 13271 36.15 17309 35.91 30580 36.01 Obese 4747 12.93 10621 22.03 15368 18.10 Total 36715 100.00 48207 100.00 82922 100.00 2015 Underweight 612 1.94 773 1.95 1385 1.95 Normal weight 13334 42.35 13561 34.20 26895 37.81 Overweight 12572 39.93 15108 38.10 27680 38.91 Obese 4966 15.77 10208 25.75 15174 21.33 Total 31484 100.00 39650 100.00 71134 100.00 Total 90705 42.36 123431 57.64 214136 100.00 Source: ENSIN 2005–2015. Own calculations. https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press https://doi.org/10.1017/S002193202300010X Published online by Cambridge University Press Table A4. Nutritional status (%) by sex, ethnicity, and survey year Afro-Colombians Indigenous Others Men Women Total Men Women Total Men Women Total Survey year Nutritional status n % n % n % n % n % n % n % n % n % 2010 Underweight 96 2.53 169 3.50 265 3.07 38 1.00 77 1.80 115 1.42 554 1.90 996 2.55 1550 2.27 Normal weight 2027 53.36 1803 37.29 3830 44.36 2153 56.45 1840 43.07 3993 49.38 13829 47.52 15392 39.37 29221 42.84 Overweight 1201 31.61 1660 34.33 2861 33.14 1308 34.29 1579 36.96 2887 35.70 10762 36.98 14070 35.98 24832 36.41 Obese 475 12.50 1203 24.88 1678 19.43 315 8.26 776 18.16 1091 13.49 3957 13.60 8642 22.10 12599 18.47 Total 3799 100 4835 100 8634 100 3814 100 4272 100 8086 100 29102 100 39100 100 68202 100 2015 Underweight 49 1.68 69 1.89 118 1.79 28 1.16 34 1.11 62 1.13 535 2.05 670 2.03 1205 2.04 Normal weight 1294 44.28 1105 30.20 2399 36.45 1093 45.09 1091 35.60 2184 39.79 10947 41.88 11365 34.52 22312 37.78 Overweight 1058 36.21 1295 35.39 2353 35.75 997 41.13 1213 39.58 2210 40.26 10517 40.24 12600 38.27 23117 39.14 Obese 521 17.83 1190 35.52 1711 26.00 306 12.62 727 23.72 1033 18.82 4139 15.84 8291 25.18 12430 21.04 Total 2922 100 3659 100 6581 100 2424 100 3065 100 5489 100 26138 100 32926 100 59064 100 Total 6721 44.17 8494 55.83 15215 100 6238 45.95 7337 54.05 13575 100 55240 43.41 72026 56.59 127266 100 Source: ENSIN 2010–2015. Own calculations. Journal of Biosocial Science Cite this article: Castro-Prieto PA, Spijker J, and Recaño J. A quasi-cohort trend analysis of adult obesity in Colombia. Journal of Biosocial Science. https://doi.org/10.1017/ S002193202300010X 27