Home » Topics » Biomarkers » BMI of males (how to find the height and weight data of males?)
Re: BMI of males [message #29024 is a reply to message #29011] |
Thu, 11 April 2024 03:51 |
archanapkar
Messages: 7 Registered: April 2024
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Thank you for your response!
I understand that there may be survey errors in men's heights across NFHS rounds. Are you saying that these errors in heights are causing the haz for men to be off by an order of magnitude across the rounds?
I tried to generate the haz for adult men using zanthro and the same assumptions as DHS and they look a lot more meaningful (they are not off by a lot across the years). However, women's haz values using zanthro do not match their IPUMS/DHS values. As explained in other posts this might be due to how DHS flags cases and/or treats missing values.
What should be my approach to hb5/heights now if I want the closest correct value of haz for adult men?
Code and output here:
/* haz scores for men 18+ using the same assumption as IPUMS */
gen men_age_haz = 17.9167 if (hhage > 18 & !mi(hhage) & sex == 1 & hhage<95)
gen men_height = (hwmheight/10) if hwmheight < 9000
egen men_haz_zanthro = zanthro(men_height, ha ,WHO) if !mi(men_age_haz) & sex != 3, ageunit(year) xvar(men_age_haz) gender(ind_female) gencode(male=0, female=1) nocutoff
replace men_haz_zanthro = . if men_haz > 600
/* haz scores for women 18+ using the same assumption as IPUMS */
gen women_age_haz = 17.9167 if (hhage > 18 & !mi(hhage) & sex == 2 & hhage<95)
gen women_height = (hwfheight/10) if hwfheight < 9000
egen women_haz_zanthro = zanthro(women_height, ha ,WHO) if !mi(women_age_haz) & sex != 3, ageunit(year) xvar(women_age_haz) gender(ind_female) gencode(male=0, female=1) nocutoff
replace women_haz_zanthro = . if women_haz > 600
------------------------------------------------------------ ------------------------------------------------------------ --------
Ouput:
. tabstat men_haz_zanthro [aw=sample_weight_denorm],by(year)
tabstat men_haz_zanthro [aw=sample_weight_denorm],by(year)
Summary for variables: men_haz_zanthro
by categories of: year (Year of sample)
year | mean
-------+----------
2005 | -1.523549
2015 | -1.639422
2020 | -1.73249
-------+----------
Total | -1.640272
------------------
. tabstat women_haz_ipums [aw=sample_weight_denorm],by(year)
tabstat women_haz_ipums [aw=sample_weight_denorm],by(year)
Summary for variables: women_haz_ipums
by categories of: year (Year of sample)
year | mean
-------+----------
2005 | -1.943618
2015 | -1.937207
2020 | -1.930234
-------+----------
Total | -1.936554
------------------
. tabstat women_haz_zanthro [aw=sample_weight_denorm],by(year)
tabstat women_haz_zanthro [aw=sample_weight_denorm],by(year)
Summary for variables: women_haz_zanthro
by categories of: year (Year of sample)
year | mean
-------+----------
2005 | -1.683147
2015 | -1.667163
2020 | -1.658341
-------+----------
Total | -1.668515
------------------
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