Research Article: Distributional change of women’s adult height in low- and middle-income countries over the past half century: An observational study using cross-sectional survey data

Date Published: May 11, 2018

Publisher: Public Library of Science

Author(s): Jewel Gausman, Ivan Meija Guevara, S. V. Subramanian, Fahad Razak, Peter Byass

Abstract: BackgroundAdult height reflects childhood circumstances and is associated with health, longevity, and maternal–fetal outcomes. Mean height is an important population metric, and declines in height have occurred in several low- and middle-income countries, especially in Africa, over the last several decades. This study examines changes at the population level in the distribution of height over time across a broad range of low- and middle-income countries during the past half century.Methods and findingsThe study population comprised 1,122,845 women aged 25–49 years from 59 countries with women’s height measures available from four 10-year birth cohorts from 1950 to 1989 using data from the Demographic and Health Surveys (DHS) collected between 1993 and 2013. Multilevel regression models were used to examine the association between (1) mean height and standard deviation (SD) of height (a population-level measure of inequality) and (2) median height and the 5th and 95th percentiles of height. Mean-difference plots were used to conduct a graphical analysis of shifts in the distribution within countries over time. Overall, 26 countries experienced a significant increase, 26 experienced no significant change, and 7 experienced a significant decline in mean height between the first and last birth cohorts. Rwanda experienced the greatest loss in height (−1.4 cm, 95% CI: −1.84 cm, −0.96 cm) while Colombia experienced the greatest gain in height (2.6 cm, 95% CI: 2.36 cm, 2.84 cm). Between 1950 and 1989, 24 out of 59 countries experienced a significant change in the SD of women’s height, with increased SD in 7 countries—all of which are located in sub-Saharan Africa. The distribution of women’s height has not stayed constant across successive birth cohorts, and regression models suggest there is no evidence of a significant relationship between mean height and the SD of height (β = 0.015 cm, 95% CI: −0.032 cm, 0.061 cm), while there is evidence for a positive association between median height and the 5th percentile (β = 0.915 cm, 95% CI: 0.820 cm, 1.002 cm) and 95th percentile (β = 0.995 cm, 95% CI: 0.925 cm, 1.066 cm) of height. Benin experienced the largest relative expansion in the distribution of height. In Benin, the ratio of variance between the latest and earliest cohort is estimated as 1.5 (95% CI: 1.4, 1.6), while Lesotho and Uganda experienced the greatest relative contraction of the distribution, with the ratio of variance between the latest and earliest cohort estimated as 0.8 (95% CI: 0.7, 0.9) in both countries. Limitations of the study include the representativeness of DHS surveys over time, age-related height loss, and consistency in the measurement of height between surveys.ConclusionsThe findings of this study indicate that the population-level distribution of women’s height does not stay constant in relation to mean changes. Because using mean height as a summary population measure does not capture broader distributional changes, overreliance on the mean may lead investigators to underestimate disparities in the distribution of environmental and nutritional determinants of health.

Partial Text: An individual’s maximum height is both heritable and heavily influenced by childhood environmental exposures [1,2]. Genetics play a limited role in the marginal changes observed in the heights of populations over time, while environmental factors, such as illness and nutritional deprivation, are thought to be the primary determinants [3–8]. Adverse circumstances during periods of rapid growth, such as those occurring in utero [9,10] and during childhood and adolescence [11–15], have been associated with decreased adult height. Height is also associated with future health and well-being. Studies have found that increased height is negatively associated with mortality from a variety of noncommunicable diseases such as cardiac disease, stroke, and some types of cancer [16–21]; adiposity and type 2 diabetes [22]; suicide [23]; and all-cause mortality [24]. Additionally, health-related quality of life [25] and age-related declines in cognitive function [26] are associated with adult height. In India, shorter maternal height is associated with increased child mortality, stunting, and wasting [27]. Short maternal stature has also been associated with increased perinatal mortality [28–30], cesarean delivery [31], and maternal morbidity and mortality [32,33].

We include the prospective analysis plan used to guide our analysis as S1 Analysis Plan. This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (S1 STROBE Checklist) [50]. The study is based on an anonymous, publicly available dataset with no personally identifiable information. Ethical approval for the Demographic and Health Surveys (DHS) was provided centrally by the ORC Macro Institutional Review Board and by individual review boards within each participating country.

The final analytic sample comprised 857,053 women. Table 1 provides basic statistics on the population included in the study according to country and birth cohort, as well as change in mean height and SD of height for each country. While 26 countries exhibited statistically significant gains in mean height across birth cohorts, 7 countries experienced statistically significant declines, all of which are in SSA. Rwanda experienced the largest decline in mean height (−1.4 cm, 95% CI: −1.8, 1.0), from 158.0 cm among the cohort born in 1950–1959 to 156.6 cm among the cohort born in 1980–1989, while Colombia experienced the greatest gain in height (2.6 cm, 95% CI: 2.4, 2.8) from 143.8 cm among the cohort born in the years 1950–1959 to 143.6 cm among the cohort born in the years 1980–1989. Sierra Leone consistently had the largest spread in the height distribution, with a SD that ranged from 11.6 to 11.8 cm depending on the birth cohort. Benin experienced the largest relative expansion in the distribution of height, from a SD of 6.4 cm among the cohort born in the years 1950–1959 to 7.9 cm among the cohort born in the years 1980–1989; thus, the ratio of the SD among the latest versus the earliest birth cohorts was 1.52 (95% CI: 1.4, 1.6), while Uganda and Lesotho experienced the largest relative contraction in SD, with a ratio comparing the latest versus the earliest cohorts estimated to be 0.8 (95% CI: 0.7, 0.9) in both countries.

Our study has 3 salient findings. First, consistent with other studies, we find that less than half of the 59 LMICs included in our study have experienced gains in mean women’s height, while the majority have experienced no significant change, or even a decline, in mean height [34–36]. Second, we demonstrate that in many countries, the distribution of women’s height has not stayed constant across successive birth cohorts, and that variance does not have a consistent relationship with mean height changes. Multilevel models show that there is no evidence for an association between changes in mean height and SD in LMICs. Third, we find that a focus on the mean obscures distributional changes within countries.

Source:

http://doi.org/10.1371/journal.pmed.1002568

 

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