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Prevalence and Socio Demographic Determinants of Malnutrition in Rural Communities of District Fatehgarh Sahib, Punjab

Poonam Khanna1, Rajbir Kaur1,Tejinder Singh3, Jill Miller4, Amandeep Kahlon Sandhu2 and Jyoti1

1School of Public Health, PGIMER, Chandigarh, India
2Mehar Baba Charitable Trust, Fatehgarh Sahib, India.
3University of Utah, Salt Lake City, UT
4Girl Rising, Salt Lake City, UT

DOI : http://dx.doi.org/10.12944/CRNFSJ.5.3.23

ABSTRACT:

Malnutrition is a global concern in developing countries. About one third of the world's malnourished children live in India.
To study the prevalence of malnutrition and its associations with socio demographic factors among under 5 children in rural areas.
A community based cross sectional study was conducted in district Fatehgarh Sahib. A census based technique was used with 573 under 5 children from nine villages of Fatehgarh Sahib District. Data was collected using structured questionnaire and anthropometric measurements.
573 children, ages 5 years and below, were enrolled for this study with 58.2% participants in upper middle and upper class, and 5.9% in lower and lower middle class. It was found that 14.14%, 15.71% and 18.85 % of the children were malnourished with respect to Weight for age (WHZ) and Height for age (HAZ) z-scores and disturbet body weight. Multivariate regression analyses of all indicators of malnutrition reflect parental education, socioeconomic status, an increase in number of children in household and children born in second or third order were some of the socio-demographic factors, which had an impact on the nutritional status of the under-five children. Significantly for stunting ( a marker of malnutrition of great concern), children from a lower caste had a 2.2 fold higher odds (OR 2.24), second or higher birth order was associated with 26% higher odds (OR 1.262), and children born to parents with lower literacy ( primary and below) had 52% and 33% higher odds for mother’s and father’s education respectively (OR 1.52 and 1.32).
The burden of under-nutrition among under-5 children has not changed significantly even after several intervention programs. Therefore, policy makers must focus on simultaneous socioeconomic development also. Additional qualitative research is needed on identifying and designing new programs or modifying existing programs with services which can be easily understood and afforded equitably by the intended beneficiaries

KEYWORDS:

Malnutrition; Under-five children; Anthropometric; Socio-economic

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Khanna P, Kaur R, Singh T, Miller J, Sandhu A. K, Jyoti. Prevalence and Socio Demographic Determinants of Malnutrition in Rural Communities of District Fatehgarh Sahib, Punjab. Curr Res Nutr Food Sci 2017;5(3). doi : http://dx.doi.org/10.12944/CRNFSJ.5.3.23


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Khanna P, Kaur R, Singh T, Miller J, Sandhu A. K, Jyoti. Prevalence and Socio Demographic Determinants of Malnutrition in Rural Communities of District Fatehgarh Sahib, Punjab. Curr Res Nutr Food Sci 2017;5(3). http://www.foodandnutritionjournal.org/?p=4561


Introduction

Malnutrition  is  a  global  concern  and  continues  to  be  one  of  the  leading  causes  of  morbidity  and  mortality, particularly  in  developing  countries  where  one  out  of  three preschool  children  is  affected1.  Malnutrition  also  prevents  children  from  reaching  their  full  physical  and  mental  potential,  which,  in  turn  hampers  progress  of  a  country  where  this malady  is  conspicuously  large  in  proportion.  Global  child  malnutrition  findings  estimate  that 156  million  children  under  5  around  the  world  are  stunted,  42  million  are  overweight  and 50  million  are  wasted2.

Despite  India’s  50% increase  in  Gross Domestic Product (GDP)  since 1991,  more  than  one  third  of  the  world’s malnourished  children  live  in  India.3,4  As  per  National  Family  Health  Survey  of  2015-16  nearly  one-third  of  children  were  found  too  short  for  their  age  whereas,  wasting  was  still  very  high  by  international  standards  in  all  of  the  States/Union  Territories1.  This  is believed  to  be  due  to  a  combination  of  socio-economic  and  societal  factors  including poverty,5- 9   food  insecurity,  gender  inequality,  disease  and  poor  access  to  health  and developmental  services.10  The  majority  of  studies  on  child  nutritional  status  have  described the  prevalence  of  malnutrition  among  under-5  children  and  analyzed  socioeconomic  and demographic  factors  associated  with  child  malnutrition.11, 12

The State of Punjab is an otherwise wealthy region and compared to the Empowered Action Group States of the country, it has overall better performance in relation to the socio-economic status and constituting socio-demographic variables. Despite the presence of factors like relatively improved food security and access to health care services, the nutritional status of under-five children doesn’t appear to be better. According to National Family Health Survey (2015-16)1, approximately 24.5% under five rural children of the State are affected by some degree of stunting, a relatively incurable state of malnutrition.

Although  poverty  is  an  important  factor  in  the  poor  nutrition  situation,  nutritional deficiencies  are  widespread  even  in  households  that  are  economically  well  off.17  To  recognize and  reveal  the possible impact of various socio-demographic  variables  in  rural communities  of relatively wealthy regions of country, an  attempt  has  been  made  to  investigate  the  prevalence  of  malnutrition  and  associated socio  demographic  variables among  under  5  children.

Methodology

Study design and area

A  community  based  cross  sectional  study  was  conducted  in  Fatehgarh  Sahib  District  of  the state  of  Punjab  in  the  northwestern  part  of  India.

Study population, sample size and sampling technique

In  this  study,  a  census based  sampling  technique  was  used to enrol 573  under -five   children  from  nine  villages  of  Fatehgarh  Sahib  District. The villages were selected using purposive sampling technique. Instead  of  statistical  computation,  an attempt  was  made  to  include  all  the  under-five children  in  the  study,  with  an  aim  to  analyze the  impact  of  various  demographic  variables  on  the  nutritional  status  of  these  children.

Data collection

Data was collected using structured questionnaire consisting of items to collect information on socio-demographics and anthropometric measurements.  The anthropometric  data  was  collected  using  the  procedure  stipulated  by  the  WHO  (2006)13  for taking  anthropometric  measurements.

Height/length  measurement:  Body  length  of  children  age  up  to  23  months  was  measured without  shoes  and  height  was  read  to  the  nearest  0.1cm  by  using  a  horizontal  wooden length  board  with  the  infant  in  recumbent  position.  However,  height  of  children  24  months and  above  was  measured  using  a  vertical  wooden  height  board  by  placing  the  child  on  the measuring  board,  and  child  standing  upright  in  the  middle  of  board,  with  the  child’s  head, shoulders,  buttocks,  knees  and  heels  touching  the  board.

Body weight was measured using electronic digital weighing scale with minimum/light clothing   and no shoes.  Calibration was done before making the measurement by setting it to zero. In  the  case  of  child’s  age  below  two  years,  an  automatic  mother-child adjustment  was  made  to  the  scale  that  eliminated  the  mother’s  weight  while  she  stood  on the  scale  with  her  baby.

Z-Scores  for  weight-for  height,  height-for-age  and  weight-for-age  were  calculated  using WHO  growth  standards  for  specific  age  groups. Malnutrition indicators including wasting,  stunting  and  underweight  were defined  as  z-score ≤ -2 SD  for  weight-for-height,  height-for-age  and  weight-for-age, respectively  (WHO, 2006)13. The  socio-demographic  data  were  obtained  in  an  interview  using  a structured  questionnaire developed  by  the  researchers including the Udai-Pareek Socio-Economic Measurement Scale for Rural Population.

Operational definitions

The term malnutrition is an umbrella term including indicators reflecting both decreasing and increasing anthropometric measurement; the results focused on indicators which reflect poor health due to under-nutrition.

The term Stunting included moderate to severe height retardation for age (low height for age) with z-scores of -2SD and less. Wasting included moderate to severe reduction in body weight for height (low weight for height) with z-scores of -2SD and less. Similarly, underweight included moderate to severe reduction in body weight for child’s age (low weight for age) with z-scores of -2SD and less.

Statistical analysis

The  data  obtained  were  cleaned,  validated  manually  and analyzed  using  computer  software  (STATA version 14.1).  Prevalence of malnutrition in under-five children was measured separately for wasting, stunting and underweight. Influence of various socio-demographic factors on under-nutrition was measured using bivariate analysis, whereas binomial logistic regression analysis was done to measure impact of a particular socio-demographic factor by controlling for other variables. Results were considered significant when p-value was < 0.05. Measures of under-nutrition including wasting, stunting and underweight were outcome variables. The socio-demographic factors including age, parental education, socio-economic status, family size, birth order etc. constituted the independent variables in the study.

Ethical considerations

A  written  consent  was  taken  from  the  mother  or  legal  caregiver  to  collect  data.

This study was approved by Ethics Committee of Post Graduate Institute of Medical Education and Research, Chandigarh.

Results

Data was collected for 573 under five children located in nine villages of the district. The study population included 48.69% (n=279) female and 51.31% (n=294) male children. The majority of children (23.6%, n=135) belonged to 12-24 month age group. Nearly 58.2% (n=334) study participants belonged to upper middle and upper socio-economic class; 5.9% (n=34) were in lower middle and lower class. There were a total of two or less number of children in a household among 71.75% (n=409) study participants, followed by 22.98% (n=131) study participants’ homes with 3 to 4 children. Sixty one percent participants were being raised in joint families (n=351) (Table 1).

Table 1: Socio-demographic characteristics of the under-five children in nine villages of district Fatehgarh Sahib

Variable Females (n=279) Males (n= 294) Total (n=573)
Age in months      
0-6 months 16 (2.8%) 15 (2.6%) 31 (5.4%)
6-12 months 28 (4.9%) 25 (4.4%) 53 (9.2%)
12-24 months 71 (12.4%) 64 (11.2%) 135 (23.6%)
24-36 months 54 (9.4%) 63 (11.0%) 117 (20.4%)
36-48 months 50 (8.7%) 66 (11.5%) 116 (20.2%)
48-60 months 60 (10.5%) 61 (10.6%) 121 (21.1%)
Socio-Economic Status class      
Lower class middle and lower class 18 (3.1%) 16 (2.7%) 34 (5.9%)
Middle class 97 (16.9%) 108 (18.8%) 205 (35.7%)
Upper middle and upper class 164 (28.6%) 170 (29.6%) 334 (58.2%)
Type of family      
Single 61 (10.6%) 56 (9.8%) 117 (20.4%)
Joint 172 (30.0%) 179 (31.2%) 351 (61.3%)
Extended 46 (8.0%) 59 (10.3%) 105 (18.3%)
Type of house      
No house 2 (0.3%) 3 (0.5%) 5 (0.9%)
Kutcha 17 (3.0%) 16 (2.8%) 33 (5.8%)
Mixed 39 (6.8%) 58 (10.1%) 97 (16.9%)
Pucca 221 (38.6%) 217 (37.9%) 438 (76.4%)

 

The prevalence of under-nutrition was determined based on different parameters of moderate to severe degree of under-nutrition represented by z-score of -2 standard deviations and less; with 14.14% (n=81) study participants having low weight for height (wasting), 15.71% (n=90) having low height for age (stunting) and 18.85% (n=108) study participants having low weight for age (underweight) (Table 2).

Table 2: Prevalence of under-nutrition among under five children in nine villages of district Fatehgarh Sahib

Indicator of undernutrition* Females (n=279) Males(n= 294) Total(n=573)
Moderate to severe wasting 45 16.13% 36 12.24% 81 14.14%
Moderate to severe stunting 45 16.13% 45 15.31% 90 15.71%
Moderate to severe underweight 60 21.51% 48 16.33% 108 18.85%

 

The bivariate analysis highlighted that not all the factors were associated with occurrence of all the forms of under-nutrition considered in the study. The occurrence of low weight for height (wasting) was statistically significantly associated (p value<0.05) with socioeconomic status of the under-five rural children. More number of socio-demographic characteristics of the child and family were statistically significantly associated with occurrence of low weight for age and height for age among under-five rural children, including birth order of the child with more likelihood of being stunted or underweight with advancing birth order, the socio-economic class, type of family and parental education. The occurrence of low weight for height, low height for age and low weight for age was not statistically significantly associated with sex of the under-five child. (Table 3)

Table 3: Factors affecting the status of nutrition among under-five children in nine villages of district Fatehgarh Sahib

Parameter of measurement of malnutrition
Wasted (n=81) Stunted (n=90) Underweight (n=108)
Variable N, % p-value N, % p-value N, % p-value
Sex
Females (n=279) 45 (7.9) 0.182 45 (7.9) 0.787 60 (10.5) 0.113
Males (n=293) 36 (6.3) 45 (7.9) 48 (8.4)
Birth order of child
1 (n=294) 46 (8.0) 0.519 27 (4.7) 0.000 47 (8.2) 0.000
2 (n=215) 28 (4.9) 42 (7.3) 37 (6.5)
3 and above (n=64) 7 (1.2) 21 (3.7) 24 (4.2)
Age
0 to 6 months (n=31) 6 (1.0) 0.705 3 (0.5) 0.07 6 (1.0) 0.202
6 to 12 months (n=53) 8 (1.4) 3 (0.5) 6 (1.0)
12 to 24 months (n=135) 15 (2.6) 16 (2.8) 19 (3.3)
24 to 36 months (n=117) 15 (2.6) 21 (3.7) 25 (4.4)
36 to 48 months (n=116) 16 (2.8) 24 (4.7) 22 (3.8)
48 to 60 months (n=121) 21 (3.7) 23 (4) 30 (5.2)
Caste
General  (n= 237) 21 (3.7) 0.001 17 (3.0) 0.000 16 (2.8) 0.000
Others (n= 336) 60 (10.5) 73 (12.7) 92 (16.1)
Socio-Economic Status (SES) class
Lower (middle, lower middle and lower) 46 (8.0) 0.002 62 (10.8) 0.000 77 (13.4) 0.000
Upper (upper middle and upper) 35 (6.1) 28 (4.9) 31(5.4)
Number of children in family
2 or less (n= 409) 59(10.4) 0.436 50 (8.8) 0.000 65 (11.4) 0.011
3-4 (n=131) 15(2.6) 28 (4.9) 34 (6)
5 or more (n=33) 6(1.1) 12 (2.1) 9 (1.6)
Type of family
Single (n=117) 18 (3.1) 0.891 32 (5.6) 0.000 37 (6.5) 0.00
Joint (n=351) 49 (8.6) 40 (7.0) 54 (9.4)
Extended (n=105) 14 (2.4) 18 (3.1) 17 (3.0)
Mother’s education
Illiterate 6 (1.0) 0.211 12(2.1) 0.000 11 (1.9) 0.000
Below or up to primary 14 (2.4) 18 (3.1) 22 (3.8)
Below or up to high 34 (5.9) 45 (7.9) 49 (8.6)
Secondary and above 27 (4.7) 15 (2.6) 26 (4.5)
Father’s education
Illiterate 8 (1.4) 0.067 10 (1.7) 0.000 14 (2.4) 0.000
Below or up to primary 6 (1.0) 16 (2.8) 12 (2.1)
Below or up to high 46 (8.0) 44 (7.7) 57 (9.9)
Secondary and above 21 (3.7) 20 (3.5) 25 (4.4)

 

The binomial logistic regression was performed to see the independent effect of various socio-demographic factors of the child which appeared to be statistically significantly associated with the outcome variables in the bivariate analysis. After adjusting for the statistically significantly associated factors of bivariate analysis, binomial logistic regression modeling showed a statistically significant association of socio-economic status of child’s family with occurrence of low height for age and low weight for age. The adjusted odds ratio signified that poor socio-economic status due to lower rank in ascribed social hierarchy (caste) tended to have an impact on occurrence of acute form of under-nutrition (i.e. underweight). It also signified that the occurrence of chronic form of under-nutrition (i.e. stunting) among under-5 rural children living in families of lower socio-economic status was due to increased number of children in the household. (Table 4 a).

Table 4a: Binomial Logistic Regression Model for factors affecting stunting and underweight in under five rural children in nine villages of district Fatehgarh Sahib (for statistically significant associations in bivariate analysis)

Variable in question Stunting Under weight
  Unadjusted Adjusted Unadjusted Adjusted
  OR p-value OR p-value OR p-value OR p-value
Socio-demographic factors of child
Birth order of child   0.000   .087   0.000   .503
First child 0.207 0.000 .665 .405 0.317 0.000 .745 .517
Second child 0.497 0.027 1.262 .601 0.346 0.001 .628 .276
Socio economic factors of the family
Socio-economic Status class (lower) 3.82 0.000 2.24 0.03 4.64 0.000 2.52 0.006
Caste (general) 0.278 0.000 0.75 0.48 0.192 0.000 0.42 0.02
Number of children in household   0.000   .037   0.012   .407
1-2 children 0.209 0.000 .226 .014 0.441 0.052 .470 .201
3-4 children 0.408 0.037 .300 .018 0.818 0.652 .666 .430
Type of family   0.000   .421   0.001   .449
Single 1.841 0.066 1.260 .629 2.421 0.008 1.590 .309
Joint 0.631 0.135 .837 .669 0.955 0.880 1.126 .763
Parental Education
Mother’s Education   0.000   .111   0.000   .957
Illiterate or unknown 9.929 0.000 3.570 .025 4.701 0.000 1.169 .771
Below or up to primary 5.167 0.000 1.523 .375 3761 0.000 1.205 .653
Below or up to high 3.073 0.000 1.843 .087 1.866 0.017 1.006 .985
 Father’s Education   0.001   .894   0.001   .512
Illiterate or unknown 4.065 0.002 .988 .983 5.364 0.000 1.421 .499
Below or up to primary 3.937 0.000 1.328 .550 2.080 0.061 .665 .381
Below or up to high 1.751 0.05 .980 .952 1.869 0.016 1.072 .814

 

Table 4b: Binomial Logistic Regression Model for factors affecting wasting in under five rural children in nine villages of district Fatehgarh Sahib (for statistically significant associations in bivariate analysis)

Variable in question Unadjusted Adjusted
  OR p-value OR p-value
SES class (lower) 2.04 0.003 1.44 0.24
Caste (general) 0.44 0.003 0.57 0.11

 

Discussion

Prevalence of  wasting,  stunting  and  underweight  among  children  was  14.14%,  15.71%  and  18.85%  respectively is closer  to  the  National  average  in  India  (16.1 %,  24.5 %  and 21.1 %)  established by  NFHS-4  (2015-16)  for  rural  Punjab. The percentage of kids affected by moderate degree of wasting has increased dramatically from 9.2 per cent in 2005 to 15.6 per cent in 2015 in both urban and rural areas.26

Prevalence of under-nutrition is relatively higher among females in this study, however, without having any significant association.

Children older than two years of age reported to have higher prevalence of one or the other form of under-nutrition. Though it had no statistically significant association with occurrence of under-nutrition, it does points out towards the importance of first 1000 days of pregnancy and post-partum. The strikingly increased proportion of undernourished children in the age band of 24 months and above may signifies that the health of child not only depends upon the type of nutrition she or he is being provided routinely, but health of woman during the gestational period also has an effect on the nutritional status of under five children. The age group of 24 months and above may be representing the group of under-five children whose mothers’ health could have suffered from  lack of adherence to the right protocol to be followed during pregnancy including full antenatal check-up, nutritious diet; and a healthy life-style and care of child after birth to reduce the risk of acquiring diseases or infections. National Family Health Survey of 2015-16 has also revealed that only 27.9% females from rural Punjab availed full ante-natal services.27 Poor gestational development pushes children towards morbidity and increased the risk of death, poor school performance and poor socio-economic growth. A report by Save the Children organization reveals that globally, 14.5% of under-five child deaths happen among the stunted children.28

All forms of under-nutrition were found increasingly in underprivileged caste sections. Similar scenario of under-nutrition was observed in relation to the socio-economic status class. Since stunting is chronic form of under-nutrition, its occurrence tends to link to the poor status of the female health during pregnancy, which may be due to poverty in the house. This is supported by a multinational cohort study published in the year 2010.29

Stunting and underweight were also statistically significantly associated with number of children in a household; supported by a study representing global scenario.23 However, this may not be a significant causal association. There will be difference in impact on nutritional status with respect to number of children in a household by virtue of a joint or extended family versus that of the total number of children born to a female. The difference could not be clearly explained based on the available data. But, the adjusted odds ratio of stunting among households having less vs. more number of total children obtained in this study favors that the lesser the number of children in a household, the better is the nutritional status of under-five children. A south-Ethiopian study favors this in relation to underweight under-five children.30

Further analysis involving the age gap among all children in a household may favor the importance of keeping a three-year gap between two pregnancies for better nutritional outcomes of children.

Other than the above findings, parental education was found to be statistically significantly associated with stunting and underweight among under-five children; however it became statistically non-significant association when adjusted for other socio-demographic factors in the regression modeling. Study conducted by Jyothi Lakshmi et al18 also mentioned  that  presence  of  wasting  among  preschool  children  were  not  significantly  associated  with  mother’s  literacy  status. These findings are in contrast with many other studies.4-8, 24, 25 However, one cannot rule out the fact that a relatively better educational status of parents has a positive impact on understanding the importance of factors determining good health, even when the earning parent is not able to earn enough to feed the family.20-22, 28

Overall, this study illustrated that the socio-economic status of a family impacts the prevalence of under-nutrition among under-five rural children.14-16, 19 The  resultant  inequality  is  much  more  pronounced  for chronic conditions like  stunting  than  for  wasting. Similar findings were observed by Poel et al.  Many other studies  have  identified  poverty  as  the  chief  determinant  of  malnutrition  in  developing  countries  that  enables intergenerational  shift  of  poor  nutritional  status  among  children.3, 10

From  the  results  it  can be concluded  that  the  prevalence  of  under-nutrition  is lesser  but  comparable  to  the  national  averages  for  the  state  of  Punjab  in  India. Other associated  variables  need  to  be  studied  including  hygiene  and  sanitation practices followed in the family,  breast  feeding and weaning practices,  parents’  nutritional  knowledge  and  practices.

In India, various interventions programs are in operation but the impact of these operations is such that under-nutrition still prevails among children below 5 years of age.  In  addition,  changes  in  dietary and life-style related practices are  also  negatively  impacting  the  nutritional  status  of  children below 5 years,  resulting  in  an  increased  prevalence  of  non  communicable  diseases  including cardiovascular and musculoskeletal disorders. The existing programs need to be implemented and streamlined in a way so that they can actually help controlling the  progression  of  malnutrition  from  mild  to  moderate  and  to  severe at the earliest. The policy makers must focus on simultaneous socioeconomic development also. Additional qualitative research is needed on identifying and designing new programs or modifying existing programs with services which can be easily understood and afforded equitably by the intended beneficiaries.28

It is recommended to ensure the effective service delivery under various existing programs at the grass root level. Qualitative research may be carried out to have an insight on the beneficiaries’ knowledge and attitude related barriers to effective service utilization targeting maternal and child health. Information on the morbidity status in previous month can help identify most common cause of acute forms of under-nutrition. Periodic surveys may be conducted to identify seasonal variations affecting nutritional status of under-five rural children.

Acknowledgements

We are thankful to Mehar Baba Charitable Trust (MBCT), a non-government organization for their kind support. We acknowledge Rotary Club Chandigarh, Rotary Club Salt Lake City, USA and The Good Works Institute, USA for financial assistance.

Conflict of interests

This study is a baseline information collected under Village Child Health and Nutrition Project in District Fatehgarh Sahib and there is no conflicts of interests.

Funding sources

The Village Child Health and Nutrition project was supported by Rotary Club Chandigarh, Rotary Club Salt Lake City, USA and The

Good Works Institute, USA

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