Ghose Bishwajit
Household wealth status and overweight and obesity among adult women in Bangladesh and Nepal
University of Dhaka
obesity science practicevolume 3 issue 2 p 185192 original articleopen access household wealth status overweight obesity among adult women bangladesh nepal g bishwajit corresponding author g bishwajit brammaputramgmailcom institute nutrition food science university dhaka dhaka bangladeshaddress correspondence g bishwajit institute nutrition food science university dhaka ramna 1000 dhaka bangladesh email brammaputramgmailcomsearch papers author g bishwajit corresponding author g bishwajit brammaputramgmailcom institute nutrition food science university dhaka dhaka bangladeshaddress correspondence g bishwajit institute nutrition food science university dhaka ramna 1000 dhaka bangladesh email brammaputramgmailcomsearch papers author first published 11 march 2017 httpsdoiorg101002osp4103citations 56aboutsectionspdf toolsrequest permissionexport citationadd favoritestrack citation shareshare give accessshare full text accessshare fulltext accessplease review terms conditions use check box share fulltext version articlei read accept wiley online library terms conditions useshareable linkuse link share fulltext version article friends colleagues learn morecopy url share linkshare onfacebooktwitterlinkedinredditwechat summary background south asia women reported likely higher normal body weight however nationally representative evidence association socioeconomic status body weight terms regional cutoffs body mass index limited south asian women study aimed address gap investigating association household wealth status overweight obesity among adult women bangladesh nepal methodology crosssectional data 6144 nepalese 17683 bangladeshi women obtained recent demographic health surveys countries cutoffs overweight obesity defined per world health organization recommendation south asian population results mean age respondents respectively 2876 974 3101 921 nepal bangladesh prevalence obesity overweight respectively 135 14 nepal 153 242 bangladesh compared women living poorest households odds overweight respectively 344 212 146 119 times higher women living richest richer middle poorer wealth status households nepal bangladesh compared poorest households women richest richer middle poorer households respectively 98 60 32 22 higher odds overweight among bangladeshi women odds obese richest households 462 adjusted odds ratio 4572 95 confidence interval 38135484 times among nepalese women 854 adjusted odds ratio 8452 95 confidence interval 522813663 times higher compared poorest households conclusion higher household wealth associated increased likelihood overweight obese among adult women bangladesh nepal using regional cutoffs body mass index shows prevalence obesity among women first time exceeded overweight countries introduction estimates suggest 2025 threequarters entire obese population worldwide living nonindustrialized countries 1 2 number overweight adults obesity developing world increased fourfold 1980 2013 3 4 different subregions africa excluding northern africa combined prevalence overweight obesity found ranging 64 87 5 6 many countries prevalence overweightobesity already higher undernutrition 4 although disease structure developing countries usually marked higher burden undernutrition infectious diseases overweightobesity associated noncommunicable diseases ncds fast becoming important public health concerns significant health socioeconomic consequences 4 7 2010 worldwide 34 million deaths 39 years life lost 38 disabilityadjusted life years attributable overweightobesity 5 convincing consensus rapid emergence overweightobesity past decades developing countries resulted large extent recent economic technological progress fast urbanization growing global interconnectedness adoption western diet lifestyle 810 similar developing world regions south asian countries also undergoing changes along noticeable shift disease structure marked increasingly higher proportion ncdrelated morbidities 9 although currently lack concrete evidence overweightobesity significantly contributing higher ncdrelated mortalities however higher normal body weight remains serious concern higher susceptibility south asian population diabetes cardiovascular complications 11 bangladesh nepal impoverished asian nations epidemiological trend historically characterized higher burden macronutrient micronutrient deficiency disorders eg anaemia chronic energy deficiency communicable infectious diseases 9 however countries experienced steady economic progress past 2 decades accompanied certain demographic nutritional transition rising prevalence overweightobesity amid widespread undernutrition phenomenon known double burden malnutrition dbm 12 researchers found dbm commonly coincides nutrition transition involves moving usually driven economic development traditional home cooked food processed precooked food usually calorie rich nutrient poor 2 8 13 evidence developing countries suggests households experiencing dbm likely urban among highest income levels compared underweight individuals 14 reflected research findings urbanization nutrition transition two remarkable features south asia context economic cultural globalization 9 although countries still predominantly rural urbanization occurring fast pace highest rate nepal followed bangladesh india 9 urbanization facilitates access laboursaving technologies rise various nonfarm sectors associated reduced need scope physical activities induce development overweight obesity 2 9 although bulk scientific literature considers overweightobesity result rising prosperity recent studies reported burden gradually shifting poor however result remains mixed therefore present study wanted investigate whether women wealthy households bear higher susceptibility overweightobesity bangladesh nepal two impoverished asian nations purpose data recent demographic health surveys dhss utilized provide reliable nationally representative population healthrelated information region methods surveys sampling data collection demographic health surveys operate developing countries across asia africa south america aim providing quality data wide range population health development indicators ultimate objective assist countries making informed policy decisions evidencebased planning monitoring evaluation outcomes health programmes survey themes commonly include maternal child nutrition anaemia birth outcomes family planning utilization maternal child health services knowledge hivaids among women age 1549 years surveys also include men ageing 15 59 years children ageing 5 years data present survey sourced latest dhs surveys bangladesh bangladesh demographic health survey bdhs 2014 nepal nepal demographic health survey 2011 2011 nepal demographic health survey fourth kind conducted country auspices ministry health population technical assistance international climate fund icf macro funding united states agency international development survey started 2 february 2011 completed 14 june 2011 nepal broadly divided three ecological regions namely mountain hill terai divided five development regions 15 ecological regions referred subregions domains 2011 nepal demographic health survey 13 selected survey stratified urban rural enumeration areas eas urban ea contained randomly selected 35 households rural ea 40 households total 11353 households selected sample 10826 finally interviewed household response rate 99 2014 bdhs conducted authority national institute population research training ministry health family welfare technical assistance icf macro funding united states agency international development survey started 21 may 2014 completed 17 august year bangladesh broadly divided seven administrative divisions barisal chittagong dhaka khulna rangpur rajshahi sylhet division subdivided smaller administrative regions divide country rural urban areas bdhs employs similar sampling strategy however ea contained average 30 households total 17989 households selected survey 17300 finally interviewed response rate 99 details regarding survey sampling methods described elsewhere 10 15 variables outcome variable study body mass index bmi according insights previous researchers asian population shares increased susceptibility cardiovascular diseases diabetes lower bmi cutoff points considered appropriate measures body weight 11 world health organization recommends lower cutoff point bmi follows less 185 kg m2 underweight 185229 kg m2 increased acceptable risk 23275 kg m2 increased risk 275 kg m2 higher risk 11 hence instead conventional cutoffs asian population specific cutoff points used present study 185 kg m2 underweight 185229 kg m2 normal weight 23275 kg m1 overweight 275 kg m2 obese 16 covariates basis insights literature search availability data sets following covariates included analysis age 15242534354444 years residency urbanrural education educationprimarysecondaryhigher employment noyes number childbirths 0122 frequency watching tv allless weekat least week wealth status richestrichermiddlepoorerpoorest data analysis data analysed using spss version 22 ibm armonk ny usa mac data sets checked missing values outliers weighted analysis baseline sociodemographic information presented descriptive statistics chisquared tests performed check association overweight obesity explanatory variables variables showed significance p 001 retained regression models multinomial logistic regression technique used examine association wealth status overweight obesity regression analyses performed separately country results bivariate multivariate analysis presented odds ratios 95 confidence intervals statistical tests two tailed p 005 considered statistically significant results basic characteristics total 6144 women nepal 17683 bangladesh ageing 15 49 years included study table 1 shows baseline sociodemographic characteristics study population mean age respondents respectively 2876 97 3101 921 nepal bangladesh shown table countries majority women 25 34 years age onethird women rural origin countries 330 nepal 344 bangladesh rates literacy 765 vs 615 primary level education higher bangladesh however nepal higher rates secondary secondary qualification compared bangladesh 474 vs 433 rates female unemployment high countries onethird women nepal 359 twothirds 685 bangladesh reported employment onethird women nepal onetenth bangladesh children 367 414 two children quarter women nepal reported never watching tv 239 little less half 487 reported watching least week bangladesh hand twofifths 395 reported never watching tv half 518 watching least week table 1 basic sociodemographic characteristics study population nepal bangladesh n 6144 overweight 14 obese 135 n 17683 overweight 153 obese 242 age years 1524 406 296 154 290 230 160 2534 294 336 372 356 395 408 3544 218 291 335 253 284 313 44 82 76 138 101 91 118 p 00001 00001 residency urban 283 330 490 344 379 505 rural 717 670 510 656 621 495 p 00001 00001 education education 385 364 317 235 203 162 primary 170 162 184 292 274 248 secondary 363 377 394 338 404 433 higher 82 97 104 95 119 157 p 0001 0000 working 359 348 430 685 680 720 yes 641 652 570 315 320 280 p 00001 0010 parity 0 307 219 144 99 90 62 1 138 149 153 223 215 202 2 188 229 287 264 294 323 2 367 404 416 414 401 414 p 0031 00001 frequency watching tv 239 222 97 395 317 223 less week 274 236 189 87 85 72 least week 487 542 713 518 598 704 p 00001 0003 wealth status richest 244 339 524 215 252 423 richer 194 209 233 212 253 246 middle 187 172 113 203 207 162 poorer 183 145 80 188 165 101 poorest 192 135 50 182 123 69 p 00001 00001 table also shows percentage overweight obesity among participants prevalence obesity overweight respectively 135 14 nepal 153 242 bangladesh results chisquared tests association show likelihood overweight obese higher among women 25 34 years age rural origin secondary level education engaged outdoor employment women higher number childbirths watching tv least week living wealthier households also higher likelihood overweight obese association household wealth status body weight results regression models analysing association household wealth status overweight obese presented table 2 bivariate analysis table 3 table 3 contains results multivariable association adjusted covariates found significant association overweight obesity chisquared tests results bivariate multivariate analyses illustrate women living relatively wealthier households shared increased likelihood overweight obese countries compared women living poorest households odds overweight respectively 344 212 146 119 times higher women living richest richer middle poorer wealth status households nepal bangladesh compared poorest households women richest richer middle poorer households respectively 98 60 32 22 higher odds overweight among bangladeshi women odds obese richest households 46 adjusted odds ratio 4572 95 confidence interval 38135484 times among nepalese women 85 adjusted odds ratio 8452 95 confidence interval 522813663 times higher compared poorest households table 2 association unadjusted household wealth status overweight obese among women ageing 15 49 years nepal bangladesh nepal bangladesh overweight cor 95ci obese cor 95ci overweight cor 95ci obese cor 95ci wealth index poorest poorer 1159 08451590 1736 11382649 1324 11311550 1441 12241697 middle 1437 10541958 2557 17073830 1630 14001897 2286 19632664 richer 2009 14792728 6079 41518903 2160 18622506 3764 32494360 richest 3324 24814454 13976 967320194 3120 26793633 9383 811010855 indicates reference category cor crude odds ratios table 3 association adjusted household wealth status overweight obese among women ageing 15 49 years nepal bangladesh nepal bangladesh overweight aor 95ci obese aor 95ci overweight aor 95ci obese aor 95ci wealth index poorest poorer 1190 08601646 1620 10502501 1216 10361428 1282 10841515 middle 1458 10402045 1968 12723043 1318 11191552 1694 14381996 richer 2127 14753067 4385 28176825 1602 13511900 2419 20462859 richest 3442 22765205 8452 522813663 1975 16282396 4572 38135484 indicates reference category adjusted age residency employment status parity frequency watching tv aor adjusted odds ratio discussion conclusions researchers widely acknowledge rising prevalence overweightobesity serious public health challenge effective intervention issue developing countries great extent constrained dearth accurate quality data understand exact situation literature review south asian nations also reveals lack research evidence trends determinants vulnerable groups overall consequences population health moreover studies nationally representative majority classify body weight international standards instead recommended cutoffs asian population gives erroneous picture situation end present study tried address gaps analysing recent nationally representative data sets women bangladesh 2014 nepal 2011 adopting world health organization recommended cutoffs countries findings show countries prevalence overweightobesity far exceeds 10 combined individual prevalence higher among bangladeshi women compared nepalese women although shown analysis worthy noting using lower cutoffs gives marked difference contrast internationally comparable one countries regional vs internal cutoff overweight 112 vs 135 obesity 22 vs 14 nepal overweight 194 vs 153 obesity 44 vs 242 bangladesh one remarkable unusuality regarding use lower cutoffs bmi prevalence obesity exceeded overweight first time among nepalese bangladeshi women recent study conducted rural population bangladesh found similar scenario prevalence obesity bmi 25 kg m2 262 considerably higher overweight bmi 23249 kg m2 177 17 gives clear indication fact current situation overweightobesity could far graver considered terms local contexts rather international ones therefore difference taken consideration making nationally comparable estimates designing intervention programmes finding national economic outlooks suggests two countries enjoyed steady gross domestic product growth since last 2 decades average annual growth rate 62 bangladesh 42 nepal since 2002 moderate reduction poverty extreme poverty rates reduction child maternal undernutrition rising share urban population nepal percentage underweight bmi 185 women ageing 15 49 years decreased 267 2001 182 2011 10 18 bangladesh rate dropped half since 2004 38 2004 vs 186 2014 15 19 surprisingly changes coincided considerable rise overweightobesity rates time course last 10 15 years prevalence overweightobesity exceeded 10 first time countries compared 2004 estimates combined prevalence overweight obesity bmi 25 among women ageing 15 49 years bangladesh increased twice 2014 9 2004 vs 24 2014 similar trend observed using lower cutoff point overweightobesity bmi 23 considered 17 2004 vs 395 2014 15 nepal hand combined prevalence doubled 65 2001 134 2011 bmi 25 299 55 vs 112 bmi 30 1 vs 22 10 18 line findings previous researches results show women households higher wealth status significantly likely overweight obese compared less wealthy households significantly higher rates general central obesity reported among men women higher socioeconomic status ses bangladesh south asian nations 17 20 one study based bdhs 2011 found compared richest women poorest households 275 times likely underweight least likely overweight 21 india significantly positive correlation observed overweightobese higher ses among women rural urban areas 4 22 similar results reported nigeria women richest group substantially higher odds 345 overweightobese 23 interestingly contrary findings developing countries overweightobesity found prevalent among population lower ses developed countries eg usa 2426 among adult men women pakistan compared lowest quintile upper wealth quintiles significantly greater odds preoverweight overweight obesity 27 underlying mechanism inequitable access affordability healthy food among lower ses neighbourhoods 25 association poverty obesity proposed mediated comparatively lower cost energydense nutrientpoor food serves cheaper yet palatable sources calorie poor consumers 28 29 however whether situation exists context south asian countries remains subject investigation first largest study explore association wealth status overweightobesity among adult women south asia one particular strength present study used two large nationally representative data sets measured overweightobesity per regional cutoffs however certain limitations considered interpreting findings data crosssectional causal relationship inferred wealth status overweightobesity outcomes control selection variables also limited data sets secondary several relevant factors dietary habit level physical activity type occupation presence disease conditions adjusted could altered prevalence rates moreover household wealth status may represent individual financial solvency among women gender disparities familial wealth distribution across south asia conclusion study reports gradual rise prevalence overweight obesity bangladesh nepal women living household higher wealth status significantly likely overweight obese compared living poorer households using regional cutoffs bmi also first nationally representative study report population obese women first time outnumbered overweight women countries abbreviations bdhs bangladesh demographic health survey ncds noncommunicable diseases dbm double burden malnutrition ses socioeconomic status conflict interest statement none declare acknowledgements author wishes acknowledge support dhs programme providing data sets time patience women participated survey funding funding available study consent publication applicable ethics approval dhss reviewed approved icf international institutional review board data sets available public domain anonymized form therefore additional approval required references 1ziraba ak fotso jc ochako r overweight obesity urban africa problem rich poor bmc public 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