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    • We examined the average height among adult men

    2018-11-01

    We examined the average height among adult men and women as recorded in the 2011 Bangladesh Demographic and Health Survey (BDHS) [5]. We noted that adult heights were not substantially different for 20-year-old men and women than for 50-year-old men and women, indicating that the heights of adult men and women have not changed substantially over the period between 1980 and 2010. Because heights did not vary over this period, we used the mean height of men and women to calculate an ideal weight using the 2009 WHO growth reference curves for BMI-for-age for 19-year-olds by sex. This weight was used to estimate average po1 requirements among adults using the appropriate formulas. For adolescents, we scaled the 2007 WHO height-for-age growth reference curve to the observed average adult height in Bangladesh and calculated the ideal weight for this height using the 2007 WHO growth reference curves for BMI-for-age. In line with FAO recommendations, the energy requirements for adolescents were increased by 15% for a high level of activity, and decreased by 15% for a low level of activity [6]. The energy requirements for adults were calculated with a physical activity level (PAL) of 1.85 for a moderate level of activity, a PAL of 2.15 for a high level of activity, and a PAL of 1.55 for a low level of activity. These values are within the ranges recommended by the FAO guidelines [6]. We calculated the additional energy need of lactating women, considering that the energy requirements for infants and young children are recorded separately in household consumption surveys. To avoid double counting of both the energy expended by the lactating mother and received by the breastfeeding child, additional energy need for lactating women is limited to the energy required by the mother to convert her consumption to breastmilk. In the FAO manual this conversion loss rate for breastfeeding is estimated at 20% of energy given to the child as breastmilk. For completeness, we also included the energy costs and AME for pregnancy by trimester, though pregnancy status is often not included in HCES surveys. The calculated energy requirements for all sex and age groups were converted to AME using the energy requirement of an adult male 30 to 50 years of age, as recommended by the FAO [6].
    Acknowledgements This analysis was undertaken as part of two projects: 1) “Aquaculture and the Poor: improving fish production, consumption and nutrition linkages,” in partnership with the WorldFish Center and with financial support of the German Federal Ministry for Economic Cooperation and Development (81170271) and 2) Food and Agricultural Approaches to Reducing Malnutrition (FAARM), led by Heidelberg University and funded by the German Federal Ministry of Education and Research (FKZ 01ER1201). We also acknowledge the financial support of the Deutsche Forschungsgemeinschaft and Ruprecht-Karls-Universität Heidelberg within the funding programme Open Access Publishing.
    Data
    Experimental design, materials and methods According to the local government, there are nine sites in the city where street vendors conduct their economic activity (see Fig. 1 – marked in red). The study took place in two sites: Centro and Santa Helena, the most populated areas in the city in terms of street vendors and formal commerce. Street vending in downtown (centro) covers an important array of cheap merchandise from footwear to cell phone accessories. Santa Helena is a food market. Two types of data were collected: observational and survey data (Figs 2 and 3 present the details). The former was collected using a standardized observational format which collected information on: types of stalls (fixed or mobile), type of products offered, number of people working at a stall, and an indicator of the physical condition of the stall (physical condition was defined as good, fair and poor and its classification was based on the condition of each stall as perceived by the observer). This information allowed to count total number of street vendors and proxy to the occupation in public space. Second type of data was survey information. Respondents answered questions concerning socioeconomic status, family composition, income (including sales and profits), education, life satisfaction and access to government welfare. This information is used to construct variables about business operation and profitability and socioeconomic conditions of street vendors Analysis using Fingerprint of DNA information has been published (Martinez et al., 2017).